Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of debris-mitigation tool for HVM DPP source

Debris-mitigation tools (DMTs) have been used in DPP sources and the performance has been well proven in alpha sources. In beta and HVM sources, requirement to the DMT is increasing to fulfill the power and lifetime requirements simultaneously. In order to bring DPP technology into HVM level, a high-performance DMT has been developed. It has high mitigation performance for both neutral and ionic debris, large collection angle of the collector having high optical transmission, and withstand large thermal input from the discharge source head. Experiments were carried out using mirror samples and proved sufficient performance with which no sputtering and deposition were observed.
Virus detection using nanoelectromechanical devices

We have used a resonating mechanical cantilever to detect immunospecific binding of viruses, captured from liquid. As a model virus, we used a nonpathogenic insect baculovirus to test the ability to specifically bind and detect small numbers of virus particles. Arrays of surface micromachined, antibody-coated polycrystalline silicon nanomechanical cantilever beams were used to detect binding from various concentrations of baculoviruses in a buffer solution. Because of their small mass, the 0. 5μm×6μm cantilevers have mass sensitivities on the order of 10−19g∕Hz, enabling the detection of an immobilized AcV1 antibody monolayer corresponding to a mass of about 3×10−15g. With these devices, we can detect the mass of single-virus particles bound to the cantilever. Resonant frequency shift resulting from the adsorbed mass of the virus particles distinguished solutions of virus concentrations varying between 105 and 107pfu∕ml. Control experiments using buffer solutions without baculovirus showed small amounts (<.
Treatment in Patients with Psoriatic Disease and Rheumatoid Arthritis: Seven Case Reports

The incidence of psoriasis, an intractable long-lasting inflammatory skin disease, is increasing and has many complications and comorbidities. Approximately 14% of patients have psoriatic arthritis (PsA). Rheumatoid arthritis (RA) is not a rare disease worldwide, and some patients may have both PsA and RA. In the present study, we encountered seven patients with concurrent diagnoses of RA and psoriatic disease and reported the details of clinical data, treatment efficacy, and X-ray findings. The diagnosis may require not only classification criteria but also a comprehensive judgment in collaboration with rheumatology over time. In addition to methotrexate as an anchor drug, anti-tumor necrosis factor-α agents are the first choice of biological agents for treatment, and interleukin (IL)-17 inhibitors may be effective, as IL-17 is also involved in the pathogenesis of RA. When treating patients with both PsA and RA, it may be essential to consider the treatment strategy, depending on which disease is more active.
Inverse Design of Spoof Surface Plasmon Polaritons Based on Artificial Neural Network

In this paper, an inverse design method based on artificial neural network (ANN) is used to deal with the design problem of spoof surface plasmon polaritons (SSPP). Compared with the conventional design method based on parameters sweeping, the proposed method can efficiently determine its geometrical parameters from the required dispersion characteristics. In this method, the upper cut-off frequency is used to feature the dispersion characteristics, which is set as the input of ANN. The well-trained ANN can directly generate the expected geometrical parameter to match the required dispersion characteristics. A U-shaped SSPP is set as an example to verify the accuracy and efficiency of the ANN-based inverse design approach, which indicates that the approach has the error about 0.028% and it can save 75% time than conventional design method.
Mechanical Performance, Microstructure, and Porosity Evolution of Fly Ash Geopolymer after Ten Years of Curing Age

This paper elucidates the mechanical performance, microstructure, and porosity evolution of fly ash geopolymer after 10 years of curing age. Given their wide range of applications, understanding the microstructure of geopolymers is critical for their long-term use. The outcome of fly ash geopolymer on mechanical performance and microstructural characteristics was compared between 28 days of curing (FA28D) and after 10 years of curing age (FA10Y) at similar mixing designs. The results of this work reveal that the FA10Y has a beneficial effect on strength development and denser microstructure compared to FA28D. The total porosity of FA10Y was also lower than FA28D due to the anorthite formation resulting in the compacted matrix. After 10 years of curing age, the 3D pore distribution showed a considerable decrease in the range of 5–30 µm with the formation of isolated and intergranular holes.
Antibacterial Activity of Combined Nanodiamonds and Snail Fractions with Biocompounds with MW below 10 kDa and above 30 kDa

The use of nanomaterials for enhancement of the antibacterial activity of different compounds is a new approach contributing to the efforts of overcoming the emerging antibiotics resistance. This study explores the combined antibacterial activity of nanodiamonds and snail peptides against Brevibacillus laterosporus BT271. Two peptide/protein fractions from Cornu aspersum mucus were used – with molecular weight (MW) below 10 kDa and with MW above 30 kDa. Four types of nanodiamonds (ND) were tested (positively charged, single digit and two types of detonation ND). Peptide fractions were characterized by using MALDI-TOF. The fraction with MW below 10 kDa consisted of many different peptides, while the fraction with proteins above 30 kDa showed proteins at m/z 26879.2 Da, 33903.11 Da, 43583.81 Da, 53986.81 Da, 79091.82 Da, 100650.42 Da, and 141 550.82 Da. When mixture peptides+ND was applied directly on the bacterial culture, the nanodiamonds showed enhanced antibacterial effect from 8% up to 42%. The combination of nanodiamonds and the mucus fraction with MW above 30 kDa had strongest bactericidal effect (1593.04 mm2/mgP*μL). The results demonstrated that ND have potential to enhance the antibacterial activity of the snail peptides but also highlighted that their effects should be carefully studied.
Millimeter-Wave $\pm 45^{\circ}$ Dual Slant Polarization Wide-Beam Antenna

In this paper, a $\pm \mathbf{45}^{\circ}$ dual slant polarization angle-fed patch antenna for 5G millimeter-wave (mm-Wave) base stations is proposed. The proposed antenna exhibits broadband characteristics that entirely cover the 5G n258 bands, by adopting double-layer patch technology. The port isolation is improved by up to 34 dB, which is caused by placing the $+ \mathbf{45}^{\circ}$ slant polarization and -45° slant polarization feeders on the upper and lower sides of the ground plane. Furthermore, adding metal pillars on the ground and loading four small rectangular patches on the dielectric substrate can increase the half-power beamwidth (HPBW) in both polarization in the H-planes. The HPBW is greater than 125° in the H-plane of +45° slant polarization, and the HPBW is greater than 133° in the H-plane of -45° slant polarization. The array can be formed later to realize the wide-angle scanning of the beam.
A Single Strain of Lactobacillus (CGMCC 21661) Exhibits Stable Glucose- and Lipid-Lowering Effects by Regulating Gut Microbiota

Type 2 diabetes (T2D) is usually accompanied by obesity and nonalcoholic fatty-liver-related insulin resistance. The link between T2D and dysbiosis has been receiving increasing attention. Probiotics can improve insulin sensitivity by regulating imbalances in microbiota, but efficacy varies based on the probiotic used. This study screened the main strain in the feces of healthy adult mice and found it to be a new Lactobacillus (abbreviated as Lb., named as CGMCC No. 21661) after genetic testing. We designed the most common Bifidobacterium longum subsp. longum (CGMCC1.2186, abbreviated as B. longum. subsp.), fecal microbiota transplantation (FMT), and Lb. CGMCC No. 21661 protocols to explore the best way for modulating dysbiosis to improve T2D. After 6 weeks of gavage in T2D mice, it was found that all three protocols had a therapeutic alleviating effect. Among them, compared with the B. longum. subsp. and FMT, the Lb. CGMCC No. 21661 showed a 1- to 2-fold decrease in blood glucose (11.84 ± 1.29 mmol/L, p < 0.05), the lowest HOMA-IR (p < 0.05), a 1 fold increase in serum glucagon-like peptide-1 (5.84 ± 1.1 pmol/L, p < 0.05), and lowest blood lipids (total cholesterol, 2.21 ± 0.68 mmol/L, p < 0.01; triglycerides, 0.4 ± 0.15 mmol/L, p < 0.01; Low-density lipoprotein cholesterol, 0.53 ± 0.16 mmol/L, p < 0.01). In addition, tissue staining in the Lb. CGMCC No. 21661 showed a 2- to 3-fold reduction in T2D-induced fatty liver (p < 0.0001), a 1- to 2-fold decrease in pancreatic apoptotic cells (p < 0.05), and a significant increase in colonic mucus layer thickness (p < 0.05) compared with the B. longum. subsp. and FMT. The glucose and lipid lowering effects of this Lb. CGMCC No. 21661 indicate that it may provide new ideas for the treatment of diabetes.
Systematic Literature Review of Information Extraction From Textual Data: Recent Methods, Applications, Trends, and Challenges

Information extraction (IE) is a challenging task, particularly when dealing with highly heterogeneous data. State-of-the-art data mining technologies struggle to process information from textual data. Therefore, various IE techniques have been developed to enable the use of IE for textual data. However, each technique differs from one another because it is designed for different data types and has different target information to be extracted. This study investigated and described the most contemporary methods for extracting information from textual data, emphasizing their benefits and shortcomings. To provide a holistic view of the domain, this comprehensive systematic literature review employed a systematic mapping process to summarize studies published in the last six years (from 2017 to 2022). It covers fundamental concepts, recent approaches, applications, and trends, in addition to challenges and future research prospects in this domain area. Based on an analysis of 161 selected studies, we found that the state-of-the-art models employ deep learning to extract information from textual data. Finally, this study aimed to guide novice and experienced researchers in future research and serve as a foundation for this research area.
Accretion tori and cones of ionizing radiation in Seyfert galaxies

Des regions tres etendues de gaz fortement ionise ont ete observees dans plusieurs classes de galaxies actives. Le mecanisme d'excitation le plus probable semble etre la photoionisation par le noyau actif. La possibilite que la photoionisation par un disque d'accretion geometriquement epais puisse reproduire les spectres des raies d'emission est exploree. Un modele simple pour un disque d'accretion epais autour d'un trou noir supermassif et un code de photoionisation sont utilises pour effectuer des predictions theoriques sur les rapports des raies. Les resultats sont compares avec des donnees observationnelles afin de contraindre les parametres du disque et les proprietes des nuages a raies d'emission.
Distance-only Measurements Based Distributed Shape Formation for Multi-Agent System

In the multi-agent system, the uniqueness of the formation shape is a difficult point in research. This paper proposes a distributed algorithm of the multi-agent system to shape predefined formation without using global information. In the proposed algorithm, each node holds a local coordinate system without a common orientation, and has only distance measurement information between its neighbors. Because no global coordinate system is needed, the restriction on the configuration of the agent is reduced. By using the barycentric coordinates of each node with respect to its neighbors, the proposed algorithm can achieve the desired shape. Simulation results have also been provided to verify the effectiveness of the algorithm.
HLA-G and Recurrent Pregnancy Loss

Placentation is an immunological compromise where maternal immune system cells and trophoblastic cells interact to reach an equilibrium condition. Although the cross talk between the two systems is complex and not completely understood, Human Leukocyte Antigen G (HLA-G), expressed on trophoblastic cell surfaces, seems to be one of the main molecules involved in the modulation of both local and systemic maternal immune response. The prevalence of recurrent pregnancy loss (RPL), probably underestimated, is 5% of all women who achieve pregnancy, and about 40–60% percent of RPL cases are unexplained. There is an immunological analogy between allograft rejection and miscarriage, and the purpose of this review is to describe how the HLA-G pathway alterations are involved in disrupting the immunologic balance and in increasing the risk of recurrent pregnancy loss.
Placental Galectins in Cancer: Why We Should Pay More Attention

The first studies suggesting that abnormal expression of galectins is associated with cancer were published more than 30 years ago. Today, the role of galectins in cancer is relatively well established. We know that galectins play an active role in many types of cancer by regulating cell growth, conferring cell death resistance, or inducing local and systemic immunosuppression, allowing tumor cells to escape the host immune response. However, most of these studies have focused on very few galectins, most notably galectin-1 and galectin-3, and more recently, galectin-7 and galectin-9. Whether other galectins play a role in cancer remains unclear. This is particularly true for placental galectins, a subgroup that includes galectin-13, -14, and -16. The role of these galectins in placental development has been well described, and excellent reviews on their role during pregnancy have been published. At first sight, it was considered unlikely that placental galectins were involved in cancer. Yet, placentation and cancer progression share several cellular and molecular features, including cell invasion, immune tolerance and vascular remodeling. The development of new research tools and the concomitant increase in database repositories for high throughput gene expression data of normal and cancer tissues provide a new opportunity to examine the potential involvement of placental galectins in cancer. In this review, we discuss the possible roles of placental galectins in cancer progression and why they should be considered in cancer studies. We also address challenges associated with developing novel research tools to investigate their protumorigenic functions and design highly specific therapeutic drugs.
Two-dimensional growth of SrTiO3 thin films on (001) MgO substrates using pulsed laser deposition and reflection high energy electron diffraction

Two-dimensional epitaxial growth of SrTiO3 is achieved on MgO, a substrate presenting a large lattice mismatch of 7.9%. In situ reflection high energy electron diffraction (RHEED) is used to monitor and control the growth. An interval deposition technique is implemented to force the two-dimensional growth. It is necessary to deposit a single atomic layer of TiO2 before SrTiO3 to prevent the formation of high energy SrO/MgO interfaces and so allow the film to completely wet the substrate surface. Defect formation is inhibited. The resulting film exhibits a similar surface to the substrate and shows a streaky RHEED pattern.
Improved methodology for surface and atmospheric soundings, error estimates, and quality control procedures: the atmospheric infrared sounder science team version-6 retrieval algorithm

Abstract The atmospheric infrared sounder (AIRS) science team version-6 AIRS/advanced microwave sounding unit (AMSU) retrieval algorithm is now operational at the Goddard Data and Information Services Center (DISC). AIRS version-6 level-2 products are generated near real time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. Some of the significant improvements in retrieval methodology contained in the version-6 retrieval algorithm compared to that previously used in version-5 are described. In particular, the AIRS science team made major improvements with regard to the algorithms used to (1) derive surface skin temperature and surface spectral emissivity; (2) generate the initial state used to start the cloud clearing and retrieval procedures; and (3) derive error estimates and use them for quality control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, version-6 also operates in an AIRS only (AO) mode, which produces results almost as good as those of the full AIRS/AMSU mode. The improvements of some AIRS version-6 and version-6 AO products compared to those obtained using version-5 are also demonstrated.
Mechanotransduction for Muscle Protein Synthesis via Mechanically Activated Ion Channels

Cell mechanotransduction, the ability to detect physical forces and convert them into a series of biochemical events, is important for a wide range of physiological processes. Cells express an array of mechanosensors transducing physical forces into intracellular signaling cascades, including ion channels. Ion channels that can be directly activated by mechanical cues are known as mechanically activated (MA), or stretch-activated (SA), channels. In response to repeated exposures to mechanical stimulation in the form of resistance training, enhanced protein synthesis and fiber hypertrophy are elicited in skeletal muscle, whereas a lack of mechanical stimuli due to inactivity/mechanical unloading leads to reduced muscle protein synthesis and fiber atrophy. To date, the role of MA channels in the transduction of mechanical load to intracellular signaling pathways regulating muscle protein synthesis is poorly described. This review article will discuss MA channels in striated muscle, their regulation, and putative roles in the anabolic processes in muscle cells/fibers in response to mechanical stimuli.
Polygenic Risk of Prediabetes, Undiagnosed Diabetes, and Incident Type 2 Diabetes Stratified by Diabetes Risk Factors

Abstract Context Early diagnosis of type 2 diabetes is crucial to reduce severe comorbidities and complications. Current screening recommendations for type 2 diabetes include traditional risk factors, primarily body mass index (BMI) and family history, however genetics also plays a key role in type 2 diabetes risk. It is important to understand whether genetic predisposition to type 2 diabetes modifies the effect of these traditional factors on type 2 diabetes risk. Objective This work aimed to investigate whether genetic risk of type 2 diabetes modifies associations between BMI and first-degree family history of diabetes with 1) prevalent prediabetes or undiagnosed diabetes; and 2) incident confirmed type 2 diabetes. Methods We included 431 658 individuals aged 40 to 69 years at baseline of multiethnic ancestry from the UK Biobank. We used a multiethnic polygenic risk score for type 2 diabetes (PRST2D) developed by Genomics PLC. Prediabetes or undiagnosed diabetes was defined as baseline glycated hemoglobin greater than or equal to 42 mmol/mol (6.0%), and incident type 2 diabetes was derived from medical records. Results At baseline, 43 472 participants had prediabetes or undiagnosed diabetes, and 17 259 developed type 2 diabetes over 15 years follow-up. Dose-response associations were observed for PRST2D with each outcome in each category of BMI or first-degree family history of diabetes. Those in the highest quintile of PRST2D with a normal BMI were at a similar risk as those in the middle quintile who were overweight. Participants who were in the highest quintile of PRST2D and did not have a first-degree family history of diabetes were at a similar risk as those with a family history who were in the middle category of PRST2D. Conclusion Genetic risk of type 2 diabetes remains strongly associated with risk of prediabetes, undiagnosed diabetes, and future type 2 diabetes within categories of nongenetic risk factors. This could have important implications for identifying individuals at risk of type 2 diabetes for prevention and early diagnosis programs.
Subject Separation Network for Reducing Calibration Time of MI-Based BCI

Motor imagery brain–computer interface (MI-based BCIs) have demonstrated great potential in various applications. However, to well generalize classifiers to new subjects, a time-consuming calibration process is necessary due to high inter-subject variabilities of EEG signals. This process is costly and tedious, hindering the further expansion of MI-based BCIs outside of the laboratory. To reduce the calibration time of MI-based BCIs, we propose a novel domain adaptation framework that adapts multiple source subjects’ labeled data to the unseen trials of target subjects. Firstly, we train one Subject Separation Network(SSN) for each of the source subjects in the dataset. Based on adversarial domain adaptation, a shared encoder is constructed to learn similar representations for both domains. Secondly, to model the factors that cause subject variabilities and eliminate the correlated noise existing in common feature space, private feature spaces orthogonal to the shared counterpart are learned for each subject. We use a shared decoder to validate that the model is actually learning from task-relevant neurophysiological information. At last, an ensemble classifier is built by the integration of the SSNs using the information extracted from each subject’s task-relevant characteristics. To quantify the efficacy of the framework, we analyze the accuracy–calibration cost trade-off in MI-based BCIs, and theoretically guarantee a generalization bound on the target error. Visualizations of the transformed features illustrate the effectiveness of domain adaptation. The experimental results on the BCI Competition IV-IIa dataset prove the effectiveness of the proposed framework compared with multiple classification methods. We infer from our results that users could learn to control MI-based BCIs without a heavy calibration process. Our study further shows how to design and train Neural Networks to decode task-related information from different subjects and highlights the potential of deep learning methods for inter-subject EEG decoding.
Sepsis-Induced Coagulopathy: An Update on Pathophysiology, Biomarkers, and Current Guidelines

Significant cross talk occurs between inflammation and coagulation. Thus, coagulopathy is common in sepsis, potentially aggravating the prognosis. Initially, septic patients tend to exhibit a prothrombotic state through extrinsic pathway activation, cytokine-induced coagulation amplification, anticoagulant pathways suppression, and fibrinolysis impairment. In late sepsis stages, with the establishment of disseminated intravascular coagulation (DIC), hypocoagulability ensues. Traditional laboratory findings of sepsis, including thrombocytopenia, increased prothrombin time (PT) and fibrin degradation products (FDPs), and decreased fibrinogen, only present late in the course of sepsis. A recently introduced definition of sepsis-induced coagulopathy (SIC) aims to identify patients at an earlier stage when changes to coagulation status are still reversible. Nonconventional assays, such as the measurement of anticoagulant proteins and nuclear material levels, and viscoelastic studies, have shown promising sensitivity and specificity in detecting patients at risk for DIC, allowing for timely therapeutic interventions. This review outlines current insights into the pathophysiological mechanisms and diagnostic options of SIC.