Miracle-dz/UniFAR-FTUs huggingface dataset:
Working mode recognition of the typical radiation source based on one-dimensional time-frequency features

By identifying the working mode of the communication radiation source, its behavioral intent can be comprehended. Tactical data link is a kind of classic communication radiation source with a variety of working modes. Aiming at the typical data link TADIL A, a method for extracting one-dimensional time-frequency features of signals using short-time Fourier transform (STFT) is proposed. Then, one-dimensional Convolutional Neural Network (CNN) DenseNet-1D is used for training and testing to complete the task of identifying different working modes. The experimental results illustrate that the working mode recognition based on the physical layer signal is feasible.
UAV micro-Doppler recognition comparison of HeRM lines versus blade flash phenomenology

The radar signatures of UAVs can be analyzed with micro-Doppler signal processing to produce features that may allow classification based on size or type as well as recognition of actions. This paper explores different micro-Doppler processing approaches to create more consistent UAV micro-Doppler signatures and improve the separability of relevant UAV features. The techniques are demonstrated through theory and simulation of UAV rotor blades. The feature extraction from a blade flash phenomenology is adapted to use with HeRM line phenomenology and found to be feasible but less accurate. HeRM lines are shown to capture the radar brightness structures shown in the blade flash, and HeRM lines do allow recognition of a change in the motion.
A Hierarchical Stereo Line Matching Method Based on a Triangle Constraint

A hierarchical stereo line matching method based on a triangle constraint is proposed to enhance the line matching reliability.The method includes three steps where thefirst step is to match seed points based on SURF algorithm.The seed points are then used toconstrain the nearby line matching.The second step is to triangulate the seed points to reduce the search range of the remaining line matching.A line-line matching process is thenperformed.The third step is a line-area matching process under the constraint of the triangles.To reduce the ambiguity of line matching,a shiftable self-adaptive line cross correlationmethod is proposed for discontinuous surfaces and with poor textural information.Experimental studies are carried out with typical close-range stereo images and aerial stereo images,and the results reveal that the proposed method is reliable for line matching.
Characterisation of local properties and prediction in chaotic dynamical systems

This work identifies regions in state space of conservative and dissipative chaotic systems that allow statements about future states or the predictability. This is done using two kinds of local exponents as well as ensemble studies. In conservative systems with trapping, the distribution of finite-time Lyapunov exponents (FTLE) has multiple maxima. These can be attributed to pieces of the trajectory that stay in the vicinity of islands of different orders. It is shown that in the vicinity of homoclinic tangencies regions of enhanced predictability exist, as measured by FTLE. Growth of finite errors is calculated using ensembles. For small errors it is the same as that calculated with maximum-growth exponents. The worst-case error grows exponentially for small, according to a power law for large prediction times. The influence of ensemble size on the accuracy of results is largest for the worst case, its error growth is the easiest to determine with a small ensemble.
Stability of an efficient Navier-Stokes solver with Navier boundary condition

In this paper, we study the stability of an efficient numerical scheme based on pressure separation for the Navier-Stokes equations with Navier slip boundary condition in a bounded domain with smooth boundary. The method was introduced in [7, 8] for the Navier-Stokes equation with no-slip boundary condition which decouples the updates of pressure and velocity through explicit time stepping for pressure. The scheme was shown to be very efficient and unconditionally stable. In this paper, we extend this pressure separation method to the problem with Navier slip boundary condition and prove the unconditional stability of the resulting numerical scheme under certain condition on the curvature of the boundary.
Selective HDAC6 inhibitor TubA offers neuroprotection after intracerebral hemorrhage via inhibiting neuronal apoptosis

A large body of evidence has demonstrated that neuronal apoptosis is involved in the pathological process of secondary brain injury following intracerebral hemorrhage (ICH). Additionally, our previous studies determined that the inhibition of HDAC6 activity by tubacin or specific shRNA can attenuate neuronal apoptosis in an oxygen-glucose deprivation reperfusion model. However, whether the pharmacological inhibition of HDAC6-attenuated neuronal apoptosis in ICH remains unclear. In this study, we used hemin-induced SH-SY5Y cells to simulate a hemorrhage state in vitro and adopted a collagenase-induced ICH rat model in vivo to assess the effect of the HDAC6 inhibition. We found a significant increase in HDAC6 during the early stages of ICH. As expected, the acetylated α-tubulin significantly decreased in correlation with the expression of HDAC6. Medium and high doses (25, 40 mg/kg) of TubA, a selective inhibitor of HDAC6, both reduced neurological impairments, histological impairments, and ipsilateral brain edema in vivo. TubA or HDAC6 siRNA both alleviated neuronal apoptosis in vivo and in vitro. Finally, HDAC6 inhibition increased the level of acetylated α-tubulin and Bcl-2 and lowered the expression of Bax and cleaved caspase-3 post-ICH. In general, these results suggested that the pharmacological inhibition of HDAC6 may act as a novel and promising therapeutic target for ICH therapy by up-regulating acetylated α-tubulin and reducing neuronal apoptosis.
Association between change in body weight during early lactation and milk production in automatic milking system herds

Graphical Abstract Summary: Dairy cows mobilize adipose and muscle tissues as a response mechanism to the increased unmet nutrient demands in early lactation. We wanted to know whether this change in body weight (BW) was associated with milk production. The percent BW change from initial average BW of d 2 to 4 after calving (referred to in the graph as initial BW) to the average of 20 to 22 DIM (referred to in the graph as 21-d BW) was calculated for each cow (n = 4,695). We found that cows that lost approximately 5% (multiparous) or 7.5% (primiparous) of BW over the first ∼21 DIM were more productive than cows that gained weight or lost more weight.
Perspectives of patients, caregivers, and healthcare professionals in Indian context: A qualitative study on Medically Unexplained Physical Symptoms (MUPS)

BACKGROUND: Approximately one-fourth of individuals who seek treatment in outpatient medical settings have Medically Unexplained Physical Symptoms (MUPS), a prevalent medical ailment. Patients with MUPS have a considerable functional impairment, and a lower quality of life, and may also have co-occurring psychiatric conditions. MATERIALS AND METHODS: Eleven Focus Group Discussions (FGDs) (four virtual and seven face-to-face) were conducted with patients, caregivers, and healthcare professionals in 2021 in a tertiary care hospital in New Delhi. Thematic analysis was carried out using QSR Nvivo software. RESULTS: A total of 36 participants were recruited in the study, including patients with MUPS (n = 12), caregivers (n = 10), and healthcare professionals (n = 14) dealing with the patients of MUPS. Three themes were identified: burden of MUPS, symptom profile of patients with MUPS, and psychological profile of patients with MUPS. These were further categorized into eight sub-themes: prevalence, symptoms, course of illness, improvement with treatment, duration of symptoms, attribution of symptoms, psychological impact, and coping strategies. CONCLUSION: The study helped us to gain insight into the characteristics and experiences of patients, caregivers, and healthcare professionals dealing with MUPS in an Indian setup. Greater awareness of MUPS and training of care providers about the occurrence, management, and referral of MUPS can be beneficial.
Scaling intelligent agent combat behaviors through hierarchical reinforcement learning

Remaining competitive in future conflicts with technologically-advanced competitors requires us to continue to invest in developing robust artificial intelligence (AI) for wargaming. Although deep reinforcement learning (RL) continues to show promising results in intelligent agent behavior development, it has yet to perform at or above the human level in the long-horizon, complex tasks typically found in combat modeling and simulation. Capitalizing on the proven potential of RL and recent successes of hierarchical reinforcement learning (HRL), our research aims to extend the use of HRL to create intelligent agents capable of performing effectively in these large and complex simulation environments. We plan to do so by developing a scalable HRL agent architecture and training framework, developing a dimension-invariant dynamic abstraction engine, and demonstrating scalability by incorporating our approach into a high-fidelity combat simulation.
Gastro-Esophageal Reflux Disease and Paroxysmal Atrial Fibrillation Ablation

Patients undergoing ablation for atrial fibrillation may be at increased risk of developing gastroesophageal reflux disease. We prospectively studied the presence of symptomatic gastroesophageal reflux disease in naïve patients who underwent atrial fibrillation ablation. Methods: The presence of typical symptoms suggestive of gastroesophageal reflux disease was clinically assessed by the gastroenterologist at baseline and at 3 months after ablation. In addition to that, all patients underwent upper gastrointestinal endoscopy. Results: Seventy-five patients were included in two groups: 46 patients who underwent atrial fibrillation ablation (study group) and 29 patients without ablation (control group). Patients with atrial fibrillation ablation were younger (57.76 ± 7.66 years versus 67.81 ± 8.52 years; p = 0.001), predominantly male (62.2% versus 33.3%; p = 0.030) and with higher body mass index (28.96 ± 3.12 kg/m2 versus 26.81 ± 5.19 kg/m2; p = 0.046). At three months after the ablation, in the study and control groups, there were 88.9% and 57.1% patients in sinus rhythm, respectively, (p = 0.009). Symptomatic gastroesophageal reflux disease was not more frequent in the study group (42.2% versus 61.9%; p = 0.220). There was no difference in terms of sinus rhythm prevalence in patients with versus without symptomatic gastroesophageal reflux disease (89.5% versus 88.5%; p = 0.709). Conclusion: In this small prospective study, typical symptoms suggestive of gastroesophageal reflux disease were not more frequent three months following atrial fibrillation ablation.
Novel Salinity-Tolerant Third-Generation Hybrid Rice Developed via CRISPR/Cas9-Mediated Gene Editing

Climate change has caused high salinity in many fields, particularly in the mud flats in coastal regions. The resulting salinity has become one of the most significant abiotic stresses affecting the world’s rice crop productivity. Developing elite cultivars with novel salinity-tolerance traits is regarded as the most cost-effective and environmentally friendly approach for utilizing saline-alkali land. To develop a highly efficient green strategy and create novel rice germplasms for salt-tolerant rice breeding, this study aimed to improve rice salinity tolerance by combining targeted CRISPR/Cas9-mediated editing of the OsRR22 gene with heterosis utilization. The novel alleles of the genic male-sterility (GMS) and elite restorer line (733Srr22-T1447-1 and HZrr22-T1349-3) produced 110 and 1 bp deletions at the third exon of OsRR22 and conferred a high level of salinity tolerance. Homozygous transgene-free progeny were identified via segregation in the T2 generation, with osrr22 showing similar agronomic performance to wild-type (733S and HZ). Furthermore, these two osrr22 lines were used to develop a new promising third-generation hybrid rice line with novel salinity tolerance. Overall, the results demonstrate that combining CRISPR/Cas9 targeted gene editing with the “third-generation hybrid rice system” approach allows for the efficient development of novel hybrid rice varieties that exhibit a high level of salinity tolerance, thereby ensuring improved cultivar stability and enhanced rice productivity.
En–DeNet Based Segmentation and Gradational Modular Network Classification for Liver Cancer Diagnosis

Liver cancer ranks as the sixth most prevalent cancer among all cancers globally. Computed tomography (CT) scanning is a non-invasive analytic imaging sensory system that provides greater insight into human structures than traditional X-rays, which are typically used to make the diagnosis. Often, the final product of a CT scan is a three-dimensional image constructed from a series of interlaced two-dimensional slices. Remember that not all slices deliver useful information for tumor detection. Recently, CT scan images of the liver and its tumors have been segmented using deep learning techniques. The primary goal of this study is to develop a deep learning-based system for automatically segmenting the liver and its tumors from CT scan pictures, and also reduce the amount of time and labor required by speeding up the process of diagnosing liver cancer. At its core, an Encoder–Decoder Network (En–DeNet) uses a deep neural network built on UNet to serve as an encoder, and a pre-trained EfficientNet to serve as a decoder. In order to improve liver segmentation, we developed specialized preprocessing techniques, such as the production of multichannel pictures, de-noising, contrast enhancement, ensemble, and the union of model predictions. Then, we proposed the Gradational modular network (GraMNet), which is a unique and estimated efficient deep learning technique. In GraMNet, smaller networks called SubNets are used to construct larger and more robust networks using a variety of alternative configurations. Only one new SubNet modules is updated for learning at each level. This helps in the optimization of the network and minimizes the amount of computational resources needed for training. The segmentation and classification performance of this study is compared to the Liver Tumor Segmentation Benchmark (LiTS) and 3D Image Rebuilding for Comparison of Algorithms Database (3DIRCADb01). By breaking down the components of deep learning, a state-of-the-art level of performance can be attained in the scenarios used in the evaluation. In comparison to more conventional deep learning architectures, the GraMNets generated here have a low computational difficulty. When associated with the benchmark study methods, the straight forward GraMNet is trained faster, consumes less memory, and processes images more rapidly.
Novel estimation algorithm for direction of arrival based on principal component analysis

Many high resolution algorithms based on subspace technology like MUSIC and ESPRIT estimate the direction of arrival of plane wave impinging on an array of sensors via eigendecomposition in array signal processing. However high computational burden for eigendecomposition makes them unsuitable for real time processing. An iterative algorithm for signal subspace estimation based on principal component analysis is proposed. The algorithm contains only relatively simple operations and has self organizing properties. Simulations show that the proposed algorithm has an analogy performance with MUSIC algorithm.
Magnetic helicity ejections and coronal activity

Abstract Magnetic helicity quantifies the degree of linkage and/or twistedness in the magnetic field. It is probably the only physical quantity which is approximately conserved even in resistive MHD. This makes it an ideal tool for the exploration of the physics of solar eruptions. In this article, I discuss the sources of magnetic helicity injected into active regions and I point out that coronal mass ejections (CMEs) are probably necessary to remove at least part of the excess helicity produced in the Sun. I also discuss the importance of magnetic helicity in the overall coronal evolution that may lead to eruptions.
Cosine Similarity-based m-class Classifier and Algorithm

Multi-classification problem is a key research in the field of machine learning.How to solve the problem of classification is a hot research spot in recent years.In this paper,the cosine similarity is used to characterize the similarity of samples and cosine similarity is introduced into 2-class classifier.M-class classifier is constructed based on cosine similarity(CSMC). The experimental analysis on the UCI datasets shows,CSMC reaches with the existing multi-class classifier equivalent classification performance.CSMC is of good research and application value.
Nkx2-5 Loss of Function in the His-Purkinje System Hampers Its Maturation and Leads to Mechanical Dysfunction

The ventricular conduction or His-Purkinje system (VCS) mediates the rapid propagation and precise delivery of electrical activity essential for the synchronization of heartbeats. Mutations in the transcription factor Nkx2-5 have been implicated in a high prevalence of developing ventricular conduction defects or arrhythmias with age. Nkx2-5 heterozygous mutant mice reproduce human phenotypes associated with a hypoplastic His-Purkinje system resulting from defective patterning of the Purkinje fiber network during development. Here, we investigated the role of Nkx2-5 in the mature VCS and the consequences of its loss on cardiac function. Neonatal deletion of Nkx2-5 in the VCS using a Cx40-CreERT2 mouse line provoked apical hypoplasia and maturation defects of the Purkinje fiber network. Genetic tracing analysis demonstrated that neonatal Cx40-positive cells fail to maintain a conductive phenotype after Nkx2-5 deletion. Moreover, we observed a progressive loss of expression of fast-conduction markers in persistent Purkinje fibers. Consequently, Nkx2-5-deleted mice developed conduction defects with progressively reduced QRS amplitude and RSR’ complex associated with higher duration. Cardiac function recorded by MRI revealed a reduction in the ejection fraction in the absence of morphological changes. With age, these mice develop a ventricular diastolic dysfunction associated with dyssynchrony and wall-motion abnormalities without indication of fibrosis. These results highlight the requirement of postnatal expression of Nkx2-5 in the maturation and maintenance of a functional Purkinje fiber network to preserve contraction synchrony and cardiac function.
A confidence interval for Pr(X Y) estimated from simple cluster samples.

: Distribution-free confidence intervals based on Somers' d (a simple function of the Mann-Whitney U statistic) are developed for Pr(X Y), where X and Y are the ranks of any two observations from two independent populations. The approach accommodates a complex sampling design, and explicit formulas are given for simple cluster sampling. The method also accommodates simple progressive left- and right-censoring. The accuracy of the interval is shown to improve when the tanh-1 transform is used. A bootstrap solution was tried and did not perform as well as the proposed solution.
The effect of fruit position and bagging treatment on Gamboge disorder in mangosteen (Garcinia mangostana L.)

Gamboge disorder has a detrimental effect on mangosteen. The leakage of the gamboge may result from water availability. Thus, modifying the transpiration of the fruit by bagging might minimize the inappropriate leak of the gamboge produced by the fruit. The study’s objective was to understand the relationship between different fruit positions and bagging treatment on the gamboge disorder in mangosteen. The experiment was conducted on 10-years old trees by tagging young fruits, five replicates with two fruit positions (inside and outside), and bagging treatment (no bagging, transparent and black plastic bagging). The result showed that bagging the fruits inside the canopy does not affect fruit mass. However, bagging with transparent and black plastic of the fruits inside the canopy decreases fruit size. The fruit quality improves by black bagging on the inside canopy fruits. These findings demonstrate that bagging fruits outside the canopy lowers their quality. Black bags used to package fruits inside the canopy improve fruit quality. However, the treatment also causes more fruit to fall from the tree and decreases the nutrient content.
The Production and Distribution of Knowledge in the United States.

The Production and Distribution of Knowledge in the United States marked the beginning of the study of our postindustrial information society. Austrian-born economist Fritz Machlup had focused his research on the patent system, but he came to realize that patents were simply one part of a much bigger "knowledge economy. " He then expanded the scope of his work to evaluate everything from stationery and typewriters to advertising to presidential addresses--anything that involved the activity of telling anyone anything. The Production and Distribution of Knowledge in the United States then revealed the new and startling shape of the U.S. economy. Machlup's cool appraisal of the data showed that the knowledge industry accounted for nearly 29 percent of the U.S. gross national product, and that 43 percent of the civilian labor force consisted of knowledge transmitters or full-time knowledge receivers. Indeed, the proportion of the labor force involved in the knowledge economy increased from 11 to 32 percent between 1900 and 1959--a monumental shift. Beyond documenting this revolution, Machlup founded the wholly new field of information economics. The transformation to a knowledge economy has resonated throughout the rest of the century, especially with the rise of the Internet. As two recent observers noted, "Information goods--from movies and music to software code and stock quotes--have supplanted industrial goods as the key drivers of world markets. " Continued study of this change and its effects is testament to Fritz Machlup's pioneering work.
Addition of Spirulina to Craft Beer: Evaluation of the Effects on Volatile Flavor Profile and Cytoprotective Properties

SPME-GC-MS and PTR-ToF-MS techniques were applied to describe the content of volatile flavor compounds in a craft beer before and after adding spirulina. The obtained results showed that the volatile profile of the two beer samples differed. Furthermore, to chemically characterize biomass spirulina, a derivatization reaction followed by GC-MS analysis was performed, highlighting a high content of molecules belonging to different chemical classes, such as sugars, fatty acids and carboxylic acids. A spectrophotometric analysis of total polyphenols and tannins, investigation into the scavenging activity towards DPPH and ABTS radicals and confocal microscopy of brewer’s yeast cells were carried out. Moreover, the cytoprotective and antioxidant properties towards the oxidative damage induced by tert-butyl hydroperoxide (tBOOH) in human H69 cholangiocytes were investigated. Finally, the modulation of Nrf2 signaling under oxidative stress conditions was also evaluated. Both samples of beer were shown to contain similar levels of total polyphenols and tannins, with slightly increased levels in that containing spirulina 0.25% w/v. Moreover, the beers were found to be endowed with radical scavenging properties towards both DPPH and ABTS radicals, albeit with a weak contribution of spirulina; however, a higher riboflavin content was detected in spirulina-treated yeast cells. Conversely, the addition of spirulina (0.25% w/v) appeared to improve the cytoprotective properties of beer towards tBOOH-induced oxidative damage in H69 cells and reduce intracellular oxidative stress. Accordingly, the cytosolic Nrf2 expression was found to be increased.