Miracle-dz/UniFAR-FTUs huggingface dataset:
Migration velocity analysis using residual diffraction moveout in the poststack depth domain

ABSTRACTDiffraction events contain more direct information on the medium velocity than reflection events. We have developed a method for migration velocity improvement and diffraction localization based on a moveout analysis of over- or undermigrated diffraction events in the depth domain. The method uses an initial velocity model as input. It provides an update to the velocity model and diffraction locations in the depth domain as a result. The algorithm is based on the focusing of remigration trajectories from incorrectly migrated diffraction curves. These trajectories are constructed by applying a ray-tracing-like approach to the image-wave equation for velocity continuation. The starting points of the trajectories are obtained from fitting an ellipse or hyperbola to the picked uncollapsed diffraction events in the depth-migrated domain. Focusing of the remigration trajectories points out the approximate location of the associated diffractor, as well as local velocity attributes. Apart from the migrati.
IMAGE SYSTEMS FOR A STOKESLET INSIDE A RIGID SPHERICAL CONTAINER

This Brief Communication derives a more compact form of the fundamental solution to the Stokes equations for a point force (Stokeslet) in a fluid domain bounded by a rigid spherical container. Although equivalent to Oseen’s (1927) solution, the present form is more useful in subsequent applications in boundary integral equation methods.
Evaluation of the Association between FGFR2 Gene Polymorphisms and Breast Cancer Risk in the Bangladeshi Population

Breast cancer is considered the most frequent cause of mortality from malignancy among females. Fibroblast growth factor receptor 2 (FGFR2) gene polymorphisms are highly related to the risk of breast cancer. However, no investigation has been carried out to determine the association of FGFR2 gene polymorphisms in the Bangladeshi population. Based on polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP), this study was performed to evaluate the association of FGFR2 (rs1219648, rs2420946, and rs2981582) variants in 446 Bangladeshi women (226 cases and 220 controls). A significant association of the FGFR2 rs1219648 variant with breast malignancy was reported in additive model 1 (aOR = 2.87, p < 0.0001), additive model 2 (aOR = 5.62, p < 0.0001), the dominant model (aOR = 2.87, p < 0.0001), the recessive model (aOR = 4.04, p < 0.0001), and the allelic model (OR = 2.16, p < 0.0001). This investigation also explored the significant association of the rs2981582 variant with the risk of breast cancer in additive model 2 (aOR = 2. 60, p = 0.010), the recessive model (aOR = 2.47, p = 0.006), and the allelic model (OR = 1.39, p = 0.016). However, the FGFR2 rs2420946 polymorphism showed no association with breast cancer except in the overdominant model (aOR = 0.62, p = 0.048). Furthermore, GTT (p < 0.0001) haplotypes showed a correlation with breast cancer risk, and all variants showed strong linkage disequilibrium. Moreover, in silico gene expression analysis showed that the FGFR2 level was upregulated in BC tissues compared to healthy tissues. This study confirms the association of FGFR2 polymorphisms with breast cancer risk.
The development and validation of a circulating tumor cells-based integrated model for improving the indeterminate lung solid nodules diagnosis

Background There is a risk of over investigation and delayed treatment in the work up of solid nodules. Thus, the aim of our study was to develop and validate an integrated model that estimates the malignant risk for indeterminate pulmonary solid nodules (IPSNs). Methods Patients included in this study with IPSNs who was diagnosed malignant or benign by histopathology. Univariate and multivariate logistic regression were used to build integrated model based on clinical, circulating tumor cells (CTCs) and radiomics features. The performance of the integrated model was estimated by applying receiver operating characteristic (ROC) analysis, and tested in different nodules size and intermediate risk IPSNs. Net reclassification index (NRI) was applied to quantify the additional benefit derived from the integrated model. Results The integrated model yielded areas under the ROC curves (AUCs) of 0.83 and 0.76 in internal and external set, respectively, outperforming CTCs (0.70, P=0.001; 0.68, P=0.128), the Mayo clinical model (0.68, P<0.001; 0.55, P=0.007), the and radiomics model (0.72, P=0.002; 0.67, P=0.050) in both validation sets. Robust performance with high sensitivity up to 98% was also maintained in IPSNs with different solid size and intermediate risk probability. The performance of the integrated model was comparable with positron emission tomography/computed tomography (PET-CT) examination (P=0.308) among the participants with established PET-CT records. NRI demonstrated that the integrated model provided net reclassification of at least 10% on the external validation set compared with single CTCs test. Conclusions The integrated model could complement conventional risk models to improve the diagnosis of IPSNs, which is not inferior to PET-CT and could help to guide clinician’s decision-making on clinically specific population.
Modeling Brittle and Ductile Behavior of Solids from First-Principles Calculations

A broad classification of solids in terms of their mechanical behavior would characterize them as brittle or ductile. While there is no doubt that ultimately this behavior is due to processes at the atomistic level, the link between these processes and their macroscopic manifestation is difficult to establish. Phenomenological theories that try to address this link must rely on microscopic parameters, the values of which are beyond their scope. Here we review recent efforts to employ first-principles electronic structure calculations in order to determine important physical quantities which, in conjunction with phenomenological theories, can provide insight into brittle versus ductile behavior. We apply this approach to cases of intrinsic interest, such as silicon, the prototypical brittle solid, as well as in cases of practical interest, such as the improvement of ductility in molybdenum disilicide, a material of potential usefulness in improved turbine blades. Current indications are that this combination of techniques can serve as powerful qualitative predictive tool for the dependence of mechanical behavior on the microscopic structure and chemical composition of a solid.
Induction Therapy With a Combination of Weekly Adalimumab Plus Intensive Granulocyte and Monocyte Adsorptive Apheresis in Patients With Ulcerative Colitis and Failure of Conventional Agents, Biologics and Janus Kinase Inhibitor

Every-week (ew) adalimumab (ADA) maintenance following induction therapy with a standard induction regimen has recently been approved for use in Japan. The efficacy and safety of combination therapy with ew-ADA maintenance following standard induction regimen plus intensive granulocyte and monocyte adsorptive apheresis (GMA) (two sessions/week) for the treatment of refractory ulcerative colitis (UC) displaying failure of conventional, biologics and Janus kinase inhibitor have not been evaluated previously. The present retrospective study evaluated the 10-week efficacy of this combination therapy among refractory UC patients. Six patients were given initial ADA combination therapy (ADA at 160 mg in week 0, ADA 80 mg in week 2, and 40 mg in week 4, followed by ew-ADA at 40 mg/week) plus intensive GMA. One patient (16.6%) achieved clinical remission and two patients (33.3%) achieved endoscopic improvement by week 10. After excluding two patients who discontinued treatment, mean full Mayo score (P = 0.14), endoscopic subscore (P = 0.18) and C-reactive protein level (P = 0.27) at 10 weeks were numerically decreased compared with baseline in the remaining four cases, although the differences were not significant. Use of ew-ADA maintenance following standard induction regimen plus intensive GMA appears unlikely to achieve satisfactory induction of clinical remission in UC patients for whom conventional agents, biologics and Janus kinase inhibitors have failed.
A transfer learning based artificial neural network in geometrical design of textured surfaces for tribological applications

This study aims at introducing the potential to utilise transfer learning methods in the training of artificial neural networks for tribological applications. Artificially enhanced surfaces through surface texturing, as an example, are investigated under hydrodynamic regime of lubrication. The performance of these surface features is assessed in terms of load carrying capacity and friction. A large performance dataset including bearing load carrying capacity and friction is initially obtained for a specific category of textures with rectangular cross-sectional profile through analytical methods. The produced bearing performance are used to train a neural network. This neural network was then trained further by a minimal set of performance measure data from an intended category of textures with triangular cross-sectional profiles. It is shown that the resulting neural network performs with acceptable level of confidence for those intended texture profiles when trained with such relatively low number of performance data points. The results indicate that fast analytical methods can potentially produce a large volume of training datasets, which effectively allows for use of relatively lower number of training data sets from the intended category, where creating data for trainings can be more complex or time consuming. Use of transfer learning method in tribological applications and use of bearing performance parameters, as opposed to bearing design parameters, for training the neural networks are the major novel contributions of this study, which has not hitherto been reported elsewhere.
Interaction of Flows with the Crystal-Melt Interface

The coupling between a crystal-melt interface and fluid flow is investigated. The solidification boundary conditions at the crystal-melt interface are described. The influences of morphological and double-diffusive instabilities during directional solidification on the interface are studied. The experiments by Glicksman and Mickalonis (1982) and Fang et al. (1985) which examine the relationship between the hydrodynamic state of the phase melt and phase-change interface are analyzed. The Rayleigh-Benard problem, and the effect of crystal-melt interaction on the Rayleigh number are examined. Various applications for melt-flow interactions with solid-liquid interface to engineering and welding are discussed.
Fluorescence image deconvolution microscopy via generative adversarial learning (FluoGAN)

We propose FluoGAN, an unsupervised hybrid approach combining the physical modelling of fluorescence microscopy timelapse acquisitions with a generative adversarial learning procedure for the problem of image deconvolution. Differently from standard approaches combining a least-square data term based on one (long-time exposure) image with sparsity-promoting regularisation terms, FluoGAN relies on a data term being the distributional distance between the fluctuating observed timelapse (short-time exposure images) and the generative model. Such distance is computed by adversarial training of two competing architectures: a physics-inspired generator simulating the fluctuating behaviour as a Poisson process of the observed images combined with blur and undersampling, and a standard convolutional discriminator network. FluoGAN is a fully unsupervised approach requiring only a fluctuating sequence of blurred, undersampled and noisy images of the sample of interest as input. It can be complemented with prior knowledge on the desired solution such as sparsity, non-negativity etc. After having described the main ideas behind FluoGAN, we formulate the corresponding optimisation problem and report several results on simulated and real phantoms used by microscopy engineers to quantitatively assess spatial resolution. The comparison of FluoGAN with state-of-the-art methodologies shows improved resolution, allowing for high-precision reconstructions of fine structures in challenging real Ostreopsis cf Ovata data. The FluoGAN code is available at: https://github.com/cmayeul/FluoGAN.
Genome Characterization and Infectivity Potential of Vibriophage-ϕLV6 with Lytic Activity against Luminescent Vibrios of Penaeus vannamei Shrimp Aquaculture

Shrimp aquaculture, especially during the hatchery phase, is prone to economic losses due to infections caused by luminescent vibrios. In the wake of antimicrobial resistance (AMR) in bacteria and the food safety requirements of farmed shrimp, aqua culturists are seeking alternatives to antibiotics for shrimp health management, and bacteriophages are fast emerging as natural and bacteria-specific antimicrobial agents. This study analyzed the whole genome of vibriophage-ϕLV6 that showed lytic activity against six luminescent vibrios isolated from the larval tanks of P. vannamei shrimp hatcheries. The Vibriophage-ϕLV6 genome was 79,862 bp long with 48% G+C content and 107 ORFs that coded for 31 predicted protein functions, 75 hypothetical proteins, and a tRNA. Pertinently, the vibriophage-ϕLV6 genome harbored neither AMR determinants nor virulence genes, indicating its suitability for phage therapy. There is a paucity of whole genome-based information on vibriophages that lyse luminescent vibrios, and this study adds pertinent data to the database of V. harveyi infecting phage genomes and, to our knowledge, is the first vibriophage genome report from India. Transmission electron microscopy (TEM) of vibriophage-ϕLV6 revealed an icosahedral head (~73 nm) and a long, flexible tail (~191 nm) suggesting siphovirus morphology. The vibriophage-ϕLV6 phage at a multiplicity of infection (MOI) of 80 inhibited the growth of luminescent V. harveyi at 0.25%, 0.5%, 1%, 1.5%, 2%, 2.5%, and 3% salt gradients. In vivo experiments conducted with post-larvae of shrimp showed that vibriophage-ϕLV6 reduced luminescent vibrio counts and post-larval mortalities in the phage-treated tank compared to the bacteria-challenged tank, suggesting the potentiality of vibriophage-ϕLV6 as a promising candidate in treating luminescent vibriosis in shrimp aquaculture. The vibriophage-ϕLV6 survived for 30 days in salt (NaCl) concentrations ranging from 5 ppt to 50 ppt and was stable at 4 °C for 12 months.
Pulse Industry in India: Status and Way Forward –A Review

India is the largest producer and consumer of pulses in the world accounting for about 25 per cent of global production, 27 per cent of global consumption and about 33 per cent of the world's area under pulses. However, compared to cereals like wheat and paddy, the growth rate of area and production of pulses is negligible and there exists wide variability in their yield in different states of country. Ironically, the country's pulse production has been hovering around 14–15 million tons, coming from a near-stagnated area of 22– 23 million ha, since 1990–91. For meeting the demand of the growing population, the country is importing pulses to the tune of 2.5–3.5 million tonns every year. Strong upward trend in the import of pulses is a cause of concern, since an increase in demand from India has shown to have cascading effect on international prices, thus draining the precious foreign exchange. By 2050, the domestic requirements would be 26.50 million tonns, necessitating stepping up production by 81.50 per cent, i.e. 11.9 million tonns additional produce at 1.86 per cent annual growth rate.
The Method of Decision-making based on FAHP and its Application

The fuzzy analytic hierarchy process method is more advantage than other methods in optimal selection of multi-object decision-making method. In this paper,presents a brief introduction of the basic theory of FAHP and build a mathematical model of fuzzy analytic hierarchy process,then give the building method of fuzzy complementary judgment matrix,the formula of weight and consistency check.The application in the use of the choice in certain V/STOL aircraft proved the validity of this method.
Genetic evaluation of lifetime performance of Phule Triveni cows by univariate and multivariate methods

Data pertaining to 509 Phule Triveni cows sired by 102 bulls maintained at Research-Cum Development Projecton Cattle, Mahatma Phule Krishi Vidyapeeth, Rahuri District Ahmadnagar (Maharashtra) were analysed to studythe performance of Phule Triveni cows for lifetime traits. Least-squares means and genetic parameters were estimated for different lifetime traits. The observed least squares means for actual life time milk yield (ALTMY), herd life (HL), productive life (PL) and breeding efficiency (BE) were 12767 ± 207 kg, 2863 ± 29 days, 1875 ± 28 days and77.00 ± 0.71%, respectively. The estimates of heritability (h2) for all these lifetime traits under univariate methods(LSML and REML) were 0.15 ± 0.11 and 0.22 ± 0.08 for ALTMY, 0.10 ± 0.12 and 0.19 ± 0.06 for HL, 0.10 ± 0.11 and 0.16 ± 0.05 for PL and 0.01 ± 0.11 and 0.10 ± 0.07 for BE, respectively. The h2 estimates obtained by REML method were higher as compared to LSML. The h2 estimates for ALTMY under two traits models were 0.27 ± 0.08, 0.20 ± 0.08 and 0.20 ± 0.06 for ALTMY + PL, ALTMY + HL and ALTMY + BE traits combinations, respectively. The observed estimates of h2 for ALTMY in combination with PL were higher than the estimates obtained under univariate model by REML method. The estimates of h2 for ALTMY were 0.54 ± 0.03, 0.54 ± 0.06 and 0.49 ± 0.02 for ALTMY + PL + HL, ALTMY + PL + BE and ALTMY + HL + BE traits combinations, respectively. The h2 estimates of ALTMY under three trait models were quite high, positive and significant compared to two trait and unitrait models by REML method. The lifetime trait combinations of ALTMY, HL, PL and BE could be used for genetic evaluation and selection of cows in the herd at any point of time. The genetic and phenotypic correlations among the lifetime traits in the present study were 0.90 ± 0.10 and 0.92 ± 0.11, 0.88 ± 0.17 and 0.98 ± 0.11 and 0.17 ± 0.08 and 0.06 ± 0.26 within ALTMY and PL, ALTMY and HL and ALTMY and BE, respectively. The high genetic and phenotypic correlations between ALTMY, HL and PL revealed that selection can be based on any one of these lifetime traits to bring improvement in other lifetime traits.
Transcriptional Profile Changes after Noise-Induced Tinnitus in Rats

Tinnitus is an unpleasant symptom characterized by detective hearing without the actual sound input. Despite numerous studies elucidating a variety of pathomechanisms inducing tinnitus, the pathophysiology of tinnitus is not fully understood. The genes that are closely associated with this subtype of the auditory hallucination that could be utilized as potential treatment targets are still unknown. In this study, we explored the transcriptional profile changes of the auditory cortex after noise-induced tinnitus in rats using high throughput sequencing and verification of the detected genes using quantitative PCR (qPCR). Tinnitus models were established by analyzing startle behaviors through gap pre-pulse inhibition (PPI) of the acoustic startle. Two hundred and fifty-nine differential genes were identified, of which 162 genes were up-regulated and 97 genes were down-regulated. Analysis of the pathway enrichment indicated that the tinnitus group exhibited increased gene expression related to neurodegenerative disorders such as Huntington’s disease and Amyotrophic lateral sclerosis. Based on the identified genes, networks of protein–protein interaction were established and five hub genes were identified through degree rank, including Fos, Nr4a1, Nr4a3, Egr2, and Egr3. Therein, the Fos gene ranked first with the highest degree after noise exposure, and may be a potential target for the modulation of noise-induced tinnitus.
SDV-LOAM: Semi-Direct Visual–LiDAR Odometry and Mapping

Visual-LiDAR odometry and mapping (V-LOAM), which fuses complementary information of a camera and a LiDAR, is an attractive solution for accurate and robust pose estimation and mapping. However, existing systems could suffer nontrivial tracking errors arising from 1) association between 3D LiDAR points and sparse 2D features (i.e., 3D-2D depth association) and 2) obvious drifts in the vertical direction in the 6-degree of freedom (DOF) sweep-to-map optimization. In this paper, we present SDV-LOAM which incorporates a semi-direct visual odometry and an adaptive sweep-to-map LiDAR odometry to effectively avoid the above-mentioned errors and in turn achieve high tracking accuracy. The visual module of our SDV-LOAM directly extracts high-gradient pixels where 3D LiDAR points project on for tracking. To avoid the problem of large scale difference between matching frames in the VO, we design a novel point matching with propagation method to propagate points of a host frame to an intermediate keyframe which is closer to the current frame to reduce scale differences. To reduce the pose estimation drifts in the vertical direction, our LiDAR module employs an adaptive sweep-to-map optimization method which automatically choose to optimize 3 horizontal DOF or 6 full DOF pose according to the richness of geometric constraints in the vertical direction. In addition, we propose a novel sweep reconstruction method which can increase the input frequency of LiDAR point clouds to the same frequency as the camera images, and in turn yield a high frequency output of the LiDAR odometry in theory. Experimental results demonstrate that our SDV-LOAM ranks 8th on the KITTI odometry benchmark which outperforms most LiDAR/visual-LiDAR odometry systems. In addition, our visual module outperforms state-of-the-art visual odometry and our adaptive sweep-to-map optimization can improve the performance of several existing open-sourced LiDAR odometry systems. Moreover, we demonstrate our SDV-LOAM on a custom-built hardware platform in large-scale environments which achieves both a high accuracy and output frequency. We have released the source code of our SDV-LOAM for the development of the community.
A Scheme for Representing Aromatic Secondary Organic Aerosols in Chemical Transport Models: Application to Source Attribution of Organic Aerosols Over South Korea During the KORUS‐AQ Campaign

We present a new volatility basis set (VBS) representation of aromatic secondary organic aerosol (SOA) for atmospheric chemistry models by fitting a statistical oxidation model with aerosol microphysics (SOM‐TOMAS) to results from laboratory chamber experiments. The resulting SOM‐VBS scheme also including previous work on SOA formation from semi‐ and intermediate volatile organic compounds (S/IVOCs) is implemented in the GEOS‐Chem chemical transport model and applied to simulation of observations from the Korea‐United States Air Quality Study (KORUS‐AQ) field campaign over South Korea in May–June 2016. Our SOM‐VBS scheme can simulate the KORUS‐AQ organic aerosol (OA) observations from aircraft and surface sites better than the default schemes used in GEOS‐Chem including for vertical profiles, diurnal cycle, and partitioning between hydrocarbon‐like OA and oxidized OA. Our results confirm the important contributions of oxidized primary OA and aromatic SOA found in previous analyses of the KORUS‐AQ data and further show a large contribution from S/IVOCs. Model source attribution of OA in surface air over South Korea indicates one third from domestic anthropogenic emissions, with a large contribution from toluene and xylenes, one third from external anthropogenic emissions, and one third from natural emissions.