Miracle-dz/UniFAR-FTUs huggingface dataset:
On Maser Rate Equations and Transient Oscillations

Masers exhibit interesting transient behavior that cannot be completely understood on the basis of the rate equations. The use of the rate equations in most transient analyses is usually justified on a more or less intuitive basis and the implied assumptions are not always clear. In this paper, the macroscopic maser rate equations are derived systematically from the Boltzmann equation for the density matrix of the atomic systems and Maxwell's equations for the radiation fields. When the coherence linewidth (T2−1) of the atomic systems is much larger than the cavity linewidth and the natural linewidth (T1−1) of the atomic emission, and with a WKB approximation, in the lowest order of approximation one obtains the two widely used, coupled first‐order nonlinear rate equations of Statz and deMars. On the other hand, if the cavity linewidth is much larger than the atomic linewidths (T1−1 and T2−1), one can use the so‐called ``reaction‐field principle'' of Anderson and obtain, again, two coupled first‐order rat.
On high-frequency oscillatory viscous flows

The equations governing high-frequency oscillatory viscous flows are investigated through the separation of the steady and the unsteady parts. All Reynolds number ranges are studied and the orders of magnitude of the steady streaming produced by the Reynolds stresses are established. The oscillating circular cylinder at low Reynolds numbers is studied through the method of inner and outer expansions. Steady recirculating cells exist near the cylinder. The results compare very well with experiments. Analytic expressions for the streamfunction and the drag coefficient are obtained. The oscillating flow towards an infinite plate is investigated in detail. The steady streaming is caused by the steady component of the Reynolds stress. The pressure gradient always causes reverse flow near the solid boundary.
FairLight: Fairness-Aware Autonomous Traffic Signal Control With Hierarchical Action Space

Although reinforcement learning (RL) approaches are promising in autonomous traffic signal control (TSC), they often suffer from the unfairness problem that causes extremely long waiting time at intersections for partial vehicles. This is mainly because the traditional RL methods focus on optimizing the overall traffic performance, while the fairness of individual vehicles is neglected. To address this problem, we propose a novel RL-based method named FairLight for the fair and efficient control of traffic with variable phase duration. Inspired by the concept of user satisfaction index (USI) proposed in the transportation field, we introduce a fairness index in the design of key RL elements, which specially considers the travel quality (e.g., fairness). Based on our proposed hierarchical action space method, FairLight can accurately allocate the duration of traffic lights for selected phases. Experimental results obtained from various well-known traffic benchmarks show that, compared with the state-of-the-art RL-based TSC methods, FairLight can not only achieve better fairness performance but also improve the control quality from the perspectives of the average travel time of vehicles and RL convergence speed.
Compressibility Effect in Vortex Identification

F LOW problems of aircraft, missile dynamics, high-speed transportation, compressible slenderand bluff-body wakes, wingtip vortices, aerodynamics of rotors, propellers and blades, environmental flows, and local meteorology are some examples of aerodynamic problems frequently dominated by vortical structures. Understanding of vortices and vortex dynamics in such flows is of primary interest. Flow modeling is steadily forced to improve the analysis of the given aerodynamic problems and the accuracy of compressible-flow prediction. A considerable number of vortexidentification methods, vortex definitions, and vortex-core visualization techniques have been proposed during the last 25 years [1– 21]. The recent study of Kolař [21] has pointed out a variety of general requirements for vortex identification, just one of which is the validity of vortex-identification schemes for compressible flows. In this respect, the region-type definitions of a vortex should be distinguished from the line-type definitions of a vortex core [16]. It should be noted, however, that these methods may be generally combined [22]. It is shown subsequently that from the most popular region-type vortex-identification schemes (Q, , 2, and ci), only the criterion and the closely associated ci criterion are directly extendable to compressible flows.
Machine Learning-Based Reliability Improvement of Ambient Mode Extraction for Smart Grid Utilizing Isolation Forest

Reliable and accurate extraction of ambient modes is an essential means of assessing the safety and stability of smart grids. While previous works have mainly concentrated on the introduction of novel identification tools. In this paper, the isolation forest (iForest) was presented to build an intelligent ambient mode extraction scheme with high reliability, which aims at detecting and eliminating abnormal ambient modes from extracted results. As the core technology of the proposed intelligent scheme, iForest exploits the concept of isolation and intends to combine the features of the outliers, which are ‘few’ and ‘different’, with the technique of ensemble learning to isolate them precisely. And the abnormal modes can be eliminated according to their anomaly scores in the proposed intelligent ambient mode extraction scheme. The evaluation of the proposed scheme is carried out through the database constructed by an IEEE 16-generator system and a real power system, the results of which indicate that the proposed scheme is intelligent enough to deal with a large amount of data with high accuracy and improve the reliability of existing identification tools.
Studies on the Requirement of Transthyretin Protein (BxTTR-52) for the Suppression of Host Innate Immunity in Bursaphelenchus xylophilus

The pinewood nematode, Bursaphelenchus xylophilus, has been determined as one of the world’s top ten plant-parasitic nematodes. It causes pine wilt, a progressive disease that affects the economy and ecologically sustainable development in East Asia. B. xylophilus secretes pathogenic proteins into host plant tissues to promote infection. However, little is known about the interaction between B. xylophilus and pines. Previous studies reported transthyretin proteins in some species and their strong correlation with immune evasion, which has also been poorly studied in B. xylophilus. In this study, we cloned and functionally validated the B. xylophilus pathogenic protein BxTTR-52, containing a transthyretin domain. An in situ hybridization assay demonstrated that BxTTR-52 was expressed mainly in the esophageal glands of B. xylophilus. Confocal microscopy revealed that BxTTR-52-RFP localized to the nucleus, cytoplasm, and plasma membrane. BxTTR-52 recombinant proteins produced by Escherichia coli could be suppressed by hydrogen peroxide and antioxidant enzymes in pines. Moreover, silencing BxTTR-52 significantly attenuated the morbidity of Pinus thunbergii infected with B. xylophilus. It also suppressed the expression of pathogenesis-related genes in P. thunbergii. These results suggest that BxTTR-52 suppresses the plant immune response in the host pines and might contribute to the pathogenicity of B. xylophilus in the early infection stages.
Type 2 Diabetes Mellitus and Alzheimer’s Disease: Shared Molecular Mechanisms and Potential Common Therapeutic Targets

The global prevalence of diabetes mellitus and Alzheimer’s disease is increasing alarmingly with the aging of the population. Numerous epidemiological data suggest that there is a strong association between type 2 diabetes and an increased risk of dementia. These diseases are both degenerative and progressive and share common risk factors. The amyloid cascade plays a key role in the pathophysiology of Alzheimer’s disease. The accumulation of amyloid beta peptides gradually leads to the hyperphosphorylation of tau proteins, which then form neurofibrillary tangles, resulting in neurodegeneration and cerebral atrophy. In Alzheimer’s disease, apart from these processes, the alteration of glucose metabolism and insulin signaling in the brain seems to induce early neuronal loss and the impairment of synaptic plasticity, years before the clinical manifestation of the disease. The large amount of evidence on the existence of insulin resistance in the brain during Alzheimer’s disease has led to the description of this disease as “type 3 diabetes”. Available animal models have been valuable in the understanding of the relationships between type 2 diabetes and Alzheimer’s disease, but to date, the mechanistical links are poorly understood. In this non-exhaustive review, we describe the main molecular mechanisms that may link these two diseases, with an emphasis on impaired insulin and IGF-1 signaling. We also focus on GSK3β and DYRK1A, markers of Alzheimer’s disease, which are also closely associated with pancreatic β-cell dysfunction and type 2 diabetes, and thus may represent common therapeutic targets for both diseases.
Root Cause Analysis And Improvement In Windows System Based On Windows Performance Toolkit WPT

Performance issues could be appearing from anywhere in a computer system, finding the root cause of those issues is a troublesome issue due to the complexity of the modern systems and applications. Microsoft builds multiple mechanisms to make their engineers understand what is happening inside All Windows versions including Windows 10 Home and the behavior of any application working on it whether Microsoft services or even third-party applications, one of those mechanisms is the Event Tracing for Windows (ETW) which is the core of logging and tracing in Windows operating system to trace the internal events of the system and its applications. This study goes deep into internal process activities to investigate root cause analysis on Windows 10 Home 20H2, core i5 processor with 4 cores and 8GB of RAM. After simulating workload to get a performance issue, that makes the system and application get unresponsive, then using Windows Performance Toolkit WPT to trace and analyze the event log for root cause investigation. Our results demonstrate analysis works using WPT for decision making such as the reasons of underutilization on CPU and disk, labeling the highlighted patterns, the unbalanced use of system calls in memory, and deciding that the usage preview is the best way to get an idea about applications behavior inside Windows systems resources. Overall improving resources utilization usage and identifying the cause of slowing memory allocation, inefficient disk usage, and throughput.
Microwave photoconductivity in two-dimensional electron systems due to photon-assisted interaction of electrons with leaky interface phonons

We calculate the contribution of the photon-assisted interaction of electrons with leaky interface phonons to the dissipative dc photoconductivity of a two-dimensional electron system in a magnetic field. The calculated photoconductivity as a function of the frequency of microwave radiation and the magnetic field exhibits pronounced oscillations. The obtained oscillation structure is different from that in the case of photon-assisted interaction with impurities. We demonstrate that at a sufficiently strong microwave radiation in certain ranges of its frequency (or in certain ranges of the magnetic field) this mechanism can result in absolute negative conductivity.
Coarse-to-Fine Semantic Road Segmentation Using Super-Pixel Data Model and Semi-Supervised Modified CycleGAN

— Real time road scene understanding is a crucial challenge for vision-based Advanced Driver Assistance Systems (ADAS). In our previous work, we proposed a method to utilize the advantages of enhancement-based segmentation method to improve the road segmentation result at reasonable computational effort. However, the performance is suffered from the poor efficiency and generalizability of Conditional Random Field (CRF) models. To overcome these drawbacks, we propose a novel semi-supervised refinement strategy based on a modified Cycle Generative Adversarial Network (Cycle-GAN). Our contributions are the following: first, our method learns a mapping between unpaired 4 channel images and a label domain. Second, a new pair-wise metric learning for a subset of images is added to improve the robustness of learning procedure. Third, we proposed a generative network with fewer parameters than the original Cycle-GAN. Forth, adversarial learning procedure is limited to the already predicted road boundary obtained from our recent work, that all together boost the segmentation performance. Experiments on KITTI benchmark show the effectiveness of the 4-7% of improvement compares to our previous work based on the super pixel and Convolutional Neural Network (CNN) and achieves comparable performance among the top-performing algorithms of recent un/semi-supervised semantic segmentation tasks.
Diagnosis and Treatment of a Recurrent Bleeding Dieulafoy’s Lesion: A Case Report

Dieulafoy's lesions are uncommon causes of upper gastrointestinal bleeding (UGIB) that pose a life-threatening risk if not diagnosed promptly and treated appropriately. These lesions are composed of enlarged submucosal blood vessels that bleed despite any gross abnormality. Early intervention with esophagogastroduodenoscopy (EGD) is necessary to avoid more invasive treatment with angiogram embolization or surgical removal. This paper aims to discuss a case regarding a patient with difficult-to-control recurrent bleeding from a Dieulafoy's lesion located in the gastric fundus of a previously healthy 60-year-old female. This case highlights the need for dual therapy and special considerations regarding antiplatelet medications and supplements when treating patients with Dieulafoy's lesions.
Privacy-Preserving Authentication Scheme With Revocability for Multi-WSN in Industrial IoT

Wireless sensor network (WSN), as one of the core technology in the Industrial Internet of Things (IIoT) system, plays a critical role in collecting data for the monitoring areas. Security and privacy are essential to ensure the trustworthy completeness of data access and transmission for the WSN-based IIoT system. Recently, a series of excellent privacy-preserving authentication schemes for the WSN-based IIoT system have been proposed. There is, however, strong demand for further improvements in multiple registrations, user revocation, and forward secrecy. Targeted by these security issues, we propose an efficient privacy-preserving authentication scheme with revocability for multi-WSNs in the IIoT environment. In the proposed scheme, the user can access multiple different WSNs with the same identity and password through a single registration. Our scheme is provable secure under the random oracle model, and security analysis via practical circumstances shows that it is able to provide a variety of security requirements, such as user revocation, forward secrecy, etc. In addition, the comparison with related schemes indicates that the proposed one has fewer sensor nodes-based computations and overall communication overheads. It is, therefore, more suitable for the resource-constrained IIoT environment than existing approaches.
Objective function for minimizing optical pathlength difference in design of flat-field holographic concave gratings

An objective function that closely represents the maximum optical pathlength difference on the entire grating surface for designing a flat-field holographic concave grating is proposed. Compared to design methods that minimize certain aberration coefficients of the optical pathlength function, the present objective function has a clearer physical meaning of optical pathlength difference and guarantees a smaller spot size. Compared to design methods that minimize the spot size based on ray tracing, the present method requires less computing time, but is equally effective in minimizing spot size, and it even provides a better image quality in the sagittal direction.
Representing Points in Many Dimensions by Trees and Castles

Abstract A number of points in k dimensions are displayed by associating with each point a symbol: a drawing of a tree or a castle. All symbols have the same structure derived from a hierarchical clustering algorithm applied to the k variables (dimensions) over all points, but their parts are coded according to the coordinates of each individual point. Trees and castles show general size effects, the change of whole clusters of variables from point to point, trends, and outliers. They are especially appropriate for evaluating the clustering of variables and for observing clusters of points. Their major advantage over earlier attempts to represent multivariate observations (such as profiles, stars, faces, boxes, and Andrews's curves) lies in their matching of relationships between variables to relationships between features of the representing symbol. Several examples are given, including one with 48 variables.
Preparation, Characterization and Antibacterial Property Analysis of Cellulose Nanocrystals (CNC) and Chitosan Nanoparticles Fine-Tuned Starch Film

To improve the mechanical and antibacterial properties of traditional starch-based film, herein, cellulose nanocrystals (CNCs) and chitosan nanoparticles (CS NPs) were introduced to potato starch (PS, film-forming matrix) for the preparation of nanocomposite film without incorporation of additional antibacterial agents. CNCs with varied concentrations were added to PS and CS NPs composite system to evaluate the optimal film performance. The results showed that tensile strength (TS) of nanocomposite film with 0, 0.01, 0.05, and 0.1% (w/w) CNCs incorporation were 41, 46, 47 and 41 MPa, respectively. The elongation at break (EAB) reached 12.5, 10.2, 7.1 and 13.3%, respectively. Due to the reinforcing effect of CNCs, surface morphology and structural properties of nanocomposite film were altered. TGA analysis confirmed the existence of hydrogen bondings and electrostatic attractions between components in the film-forming matrix. The prepared nanocomposite films showed good antibacterial properties against both E. coli and S. aureus. The nanocomposite film, consist of three most abundant biodegradable polymers, could potentially serve as antibacterial packaging films with strong mechanical properties for food and allied industries.
The polarization electric field and its effects in an anisotropic rotating magnetospheric plasma

Spatial variations of density and temperature along a magnetic field line are evaluated for a plasma undergoing adiabatic motion in a rotating magnetosphere. The effects of centrifugal and gravitational forces are accounted for, as is anisotropy in the pitch angle distribution functions of individual species. A polarization electric field is invoked to eliminate the net electric charge density resulting from the aforementioned mass dependent forces and different anisotropies. The position of maximum density in a two-component, electron-ion plasma is determined both in the absence and in the presence of the polarization effect and compared. A scale height, generalized to include anisotropies, is derived for the density fall-off. The polarization electric field is also included in the parallel guiding center equation; equilibrium points are determined and compared in both individual and average senses with the position of density maximum. Finally a transverse (to magnetic field lines) electric component is deduced as a consequence of dissimilar charge neutralization on adjacent field lines. The E × B velocity resultant from such a “fringing” electric field is calculated and compared with the magnitude of other drifts.
A review on the effect on phytochemical compounds relevant to human health by broccoli processing technologies

Broccoli has been consumed around the world in various ways; either raw, blanched, frozen, dehydrated or fermented; however, functional foods and nutraceuticals are currently being designed and marketed from broccoli, through the extraction of compounds such as sulforaphane, which according to several studies and depending on its bioavailability has a protective effect on some types of cancer. Likewise, several food technologies are reported to seek to offer innovative foods to increasingly careful and critical consumers, ensuring that they retain their nutritional and sensory attributes even after processing and that they are also safe. In this sense, studies on the effect of processing on compounds of interest to health are of great relevance. Therefore, this article presents an overview on the study of traditionally consumed broccoli and the design of new products from the use of agro-industrial residues that, due to their high content of ﬁber and ﬁtochemical compounds, can beneﬁt the quality of life of the human population.
Agricultural Droughts Monitoring of Aceh Besar Regency Rice Production Center, Aceh, Indonesia – Application Vegetation Conditions Index Using Sentinel-2 Image Data

Monitoring the agricultural drought of paddy rice fields is a crucial aspect of preparing for proper action in main - taining food security in Indonesia. The Aceh Province is one of Indonesia’s national rice production centers, especially Aceh Besar Regency; it includes three central districts; Indrapuri, Kuta Cot Glie, and Seulimeum. Sat-ellite-Sentinel 2A data have been tested to monitor the drought levels of around 2,803 Ha in the three districts in this study. This study aimed to determine the drought level in Indrapuri, Kuta Cot Glie, and Seulimeum districts, Aceh Besar Regency’s paddy rice fields using Sentinel-2A data imagery. The vegetation conditions index (VCI) of Sentinel-2 data was utilized to identify a vegetative drought level in the area for the 2018, 2019, 2020, 2021, and 2022 growing seasons. The vegetation inertia index is derived from the Normalized Difference Vegetation Index (NDVI). The results show that the VCI looked volatile, but the trendline increased by four percent, from 92.56 in July 2019 to 96.08 in July 2021. Most areas on the dates investigated found that the no drought category was still dominant. The designated data analyzed found that the June 2022 data tend to be distributed to the drought in extreme, severe, moderate, and mild increases compared to the previous data investigated. This figure shows an increasing drought in the study area, and the average drought index is in the category of mild drought. In addition, there has been a trendline decline in the value of NDVI in recent years, causing agricultural land for paddy rice fields to be slightly vulnerable to drought.
A correction method for unfunctional cell distortion using orthogonal polynomials

In paper, we present a new correction algorithm for the unfunctional cell distortions in conventional CT imaging, based on the Chebyshev orthogonal polynomials series expressions. This algorithm first reevaluates the projection sinograms by the least mean square algorithm, and then the filtered backprojection (FBP) algorithm are executed for the reconstruction of CT image. Through the simulation experiment, the feasibility of this method is validated.
All-dielectric three-dimensional broadband Eaton lens with large refractive index range

We proposed a method to realize three-dimensional (3D) gradient index (GRIN) devices requiring large refractive index (RI) range with broadband performance. By combining non-resonant GRIN woodpile photonic crystals structure in the metamaterial regime with a compound liquid medium, a wide RI range (1–6.32) was fulfilled flexibly. As a proof-of-principle for the low-loss and non-dispersive method, a 3D Eaton lens was designed and fabricated based on 3D printing process. Full-wave simulation and experiment validated its omnidirectional wave bending effects in a broad bandwidth covering Ku band (12 GHz–18 GHz).