Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Fuzzy Prescribed Performance Control for Nonlinear Switched Time-Delay Systems With Unmodeled Dynamics

This paper considers the adaptive fuzzy output feedback tracking control problem for a class of uncertain nonlinear switched systems with time delay and unmodeled dynamics. Based on a kind of switched K-filters, a prescribed performance control scheme is proposed to guarantee the tracking performance and restrain the fluctuation caused by switches between submodes as well. In addition, fuzzy logic systems (FLSs) are use to approximate unknown nonlinear functions and dynamic surface control (DSC) method is employed to eliminate the explosion of complexity problem inherent in traditional backstepping method. The proposed controllers of corresponding subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time (ADT). A numerical simulation is performed to illustrate the effectiveness of the proposed approach.
Recommending Items Using Collectively Trained Models

Linear models with nonlinear attribute modeling are popularly selected for massive regression and categorization tasks with sparse inputs. Memorization of attribute interactions through a broad batch of cross-product attribute conversion is compelling and explainable, while generalization needs extra feature engineering exercise. With limited effort, deep neural networks (DNN) can be generalized exceptionally to undiscovered feature sequences. However, DNN can over-generalize and recommend lesser suited items. In this paper, we propose an ensemble of various collectively trained linear models and DNNs to blend the advantage of memorization and generalization for a recommender system (RS). We evaluated the system on MovieLens 100K Dataset, a stable benchmark dataset with 100,000 ratings on 1682 movies from 943 users. Our experiment results show that ensembling of wide & deep models significantly increased recommendation accuracy and decreased mean absolute error (MAE) and root mean square error (RMSE) in comparison with collaborative filtering techniques, deep-only and wide-only models.
Adaptive Fuzzy Fault-Tolerant Control of Nontriangular Structure Nonlinear Systems With Error Constraint

In this paper, an adaptive fuzzy fault-tolerant control approach is proposed for a class of nontriangular structure nonlinear systems, which contain immeasurable states and unknown actuator faults (actuator loss-of-effectiveness and bias fault). It should be noted that if the existing approaches are employed for nontriangular structure nonlinear systems, the algebraic loop problem may occur. In this study, fuzzy logic systems are employed to approximate unknown nonlinear functions, and a fuzzy state observer is designed to estimate immeasurable states. Then, based on the property of performance function and simple barrier Lyapunov function design method, the prescribed output tracking error dynamic performance and the corresponding stability are guaranteed. By using the parameter estimation technique, a new fault compensation strategy is developed to relax the requirement that the efficiency indicator must be known. The stability of the closed-loop system is proved by using the Lyapunov function stability theory. Finally, a simulation example is given to validate the effectiveness of the proposed control strategy.
Combined gemfibrozil (peroxisome proliferator-activated receptor alpha agonist) with reduced steroid dose gives a similar management picture as the full steroid dose in a rat adjuvant-induced arthritis model

Abstract Objectives: The study aimed to evaluate the efficacy of combined gemfibrozil with prednisolone in the management of adjuvant-induced arthritis (AIA) rat model. Methods: Seventy two adult male Wistar albino rats were divided equally into 1-control group, three diseased groups: 2- Adjuvant induced arthritis (AIA), 3- high fat diet (HF), and 4- combined AIA-HF, and treated groups: 5- gemfibrozil 30 mg/kg treated AIA group (AIA-G) and the combined AIA-HF treated groups: 6- prednisolone equivalent to human 10 mg (AIA-HF-P10), 7- prednisolone equivalent to human 5 mg (AIA-HF-P5) 8- gemfibrozil (HF-AIA-G) and 9- combined treatment (HF-AIA-G-P5) Results: HF diet represents a precipitating factor for knee arthritis. Gemfibrozil improved the inflammatory findings in both AIA and AIA-HF groups. Combined administration of gemfibrozil with reduced steroid dose gave a similar therapeutic effect to the full steroid dose. Fortunately, we reported more reduction in the nuclear factor kappa-B (NF-κB) and high mobility group box 1 (HMGB1) in the HF-AIA-G-P5 compared with the HF-AIA-P10 group. The improvement was proved by the histological findings. Conclusion: Combined reduced prednisolone dose with gemfibrozil potentiates its anti-inflammatory activity. This could be a target in the management of rheumatoid arthritis.
Online Robot Teaching With Natural Human–Robot Interaction

With the development of Industry 4.0, robots tend to be intelligent and collaborative. For one, robots can interact naturally with humans. For another, robots can work collaboratively with humans in a common area. The traditional teaching method is no longer suitable for the production mode with human–robot collaboration. Since the traditional teaching processes are complicated, they need highly skilled staffs. This paper focuses on the natural way of online teaching, which can be applied to the tasks such as welding, painting, and stamping. This paper presents an online teaching method with the fusion of speech and gesture. A depth camera (Kinect) and an inertial measurement unit are used to capture the speech and gesture of the human. Interval Kalman filter and improved particle filter are employed to estimate the gesture. To integrate speech and gesture information more deeply, a novel method of audio-visual fusion based on text is proposed, which can extract the most useful information from the speech and gestures by transforming them into text. Finally, a maximum entropy algorithm is employed to deal with the fusion text into the corresponding robot instructions. The practicality and effectiveness of the proposed approach were validated by five subjects without robot teaching skills. The results indicate that the online robot teaching system can successfully teach robot manipulators.
A Polysome-Based microRNA Screen Identifies miR-24-3p as a Novel Promigratory miRNA in Mesothelioma.

The expression of miRNAs in cancer has been widely studied and has allowed the definition of oncomirs and oncosuppressors. We note that it is often underestimated that many mRNAs are expressed, but translationally silent. In spite of this, systematic identification of miRNAs in equilibrium with their target mRNAs on polysomes has not been widely exploited. To identify biologically active oncomirs, we performed a screen for miRNAs acting on the polysomes of malignant mesothelioma (MPM) cells. Only a small percentage of expressed miRNAs physically associated with polysomes. On polysomes, we identified miRNAs already characterized in MPM, as well as novel ones like miR-24-3p, which acted as a promigratory miRNA in all cancer cells tested. miR-24-3p positively regulated Rho-GTP activity, and inhibition of miR-24-3p reduced growth in MPM cells. Analysis of miR-24-3p common targets, in two mesothelioma cell lines, identified a common subset of downregulated genes. These same genes were downregulated during the progression of multiple cancer types. Among the specific targets of miR-24-3p was cingulin, a tight junction protein that inhibits Rho-GTP activity. Overexpression of miR-24-3p only partially abrogated cingulin mRNA, but completely abrogated cingulin protein, confirming its action via translational repression. We suggest that miR-24-3p is an oncomir and speculate that identification of polysome-associated miRNAs efficiently sorts out biologically active miRNAs from inactive ones.Significance: Subcellular localization of miRNAs may predict their role in cancer and identify novel oncogenic miRNAs involved in cancer progression.Graphical Abstract: http://cancerres.aacrjournals. org/content/canres/78/20/5741/F1.large. jpg Cancer Res; 78(20); 5741-53. ©2018 AACR.
RNA editing in bacteria: occurrence, regulation and significance

ABSTRACT DNA harbors the blueprint for life. However, the instructions stored in the DNA could be altered at the RNA level before they are executed. One of these processes is RNA editing, which was shown to modify RNA sequences in many organisms. The most abundant modification is the deamination of adenosine (A) into inosine (I). In turn, inosine can be identified as a guanosine (G) by the ribosome and other cellular machineries such as reverse transcriptase. In multicellular organisms, enzymes from the ADAR (adenosine deaminase acting on RNA) family mediate RNA editing in mRNA, whereas enzymes from the ADAT family mediate A-to-I editing on tRNAs. In bacteria however, until recently, only one editing site was described, in tRNAArg, but never in mRNA. The tRNA site was shown to be modified by tadA (tRNA specific adenosine deaminase) which is believed to be the ancestral enzyme for the RNA editing family of enzymes. In our recent work, we have shown for the first time, editing on multiple sites in bacterial mRNAs and identified tadA as the enzyme responsible for this editing activity. Focusing on one of the identified targets – the self-killing toxin hokB, we found that editing is physiologically regulated and that it increases protein activity. Here we discuss possible modes of regulation on hokB editing, potential roles of RNA editing in bacteria, possible implications, and future research directions.
Brain region-dependent gene networks associated with selective breeding for increased voluntary wheel-running behavior

Mouse lines selectively bred for high voluntary wheel-running behavior are helpful models for uncovering gene networks associated with increased motivation for physical activity and other reward-dependent behaviors. The fact that multiple brain regions are hypothesized to contribute to distinct behavior components necessitates the simultaneous study of these regions. The goals of this study were to identify brain-region dependent and independent gene expression patterns, regulators, and networks associated with increased voluntary wheel-running behavior. The cerebellum and striatum from a high voluntary running line and a non-selected control line were compared. Neuropeptide genes annotated to reward-dependent processes including neuropeptide S receptor 1 (Npsr1), neuropeptide Y (Npy), and proprotein convertase subtilisin/kexin type 9 (Pcsk9), and genes implicated in motor coordination including vitamin D receptor (Vdr) and keratin, type I cytoskeletal 25 (Krt25) were among the genes exhibiting activity line-by-region interaction effects. Genes annotated to the Parkinson pathway presented consistent line patterns, albeit at different orders of magnitude between brain regions, suggesting some parallel events in response to selection for high voluntary activity. The comparison of gene networks between brain regions highlighted genes including transcription factor AP-2-delta (Tfap2d), distal-less homeobox 5 gene (Dlx5) and sine oculis homeobox homolog 3 (Six3) that exhibited line differential expression in one brain region and are associated with reward-dependent behaviors. Transcription factors including En2, Stat6 and Eomes predominated among regulators of genes that differed in expression between lines. Results from the simultaneous study of striatum and cerebellum confirm the necessity to study molecular mechanisms associated with voluntary activity and reward-dependent behaviors in consideration of brain region dependencies.
Interpretability Constraints for Fuzzy Modeling Implemented by Constrained Particle Swarm Optimization

In this paper certain interpretability criteria are taken into account in order to extract a set of linear inequality constraints for enhancing the fuzzy model interpretability. Among others, the criteria of model distinguishability, completeness, compactness, and fuzzy set sharing between rules are considered. To support distinguishability, the distances between fuzzy set centers are lower bounded and the widths are manipulated as to control the overlap between fuzzy sets. Sufficient conditions are given to satisfy the completeness criterion, whereas the compactness requirement is addressed by comparing models with different number of rules. Finally, fuzzy set sharing between rules is achieved through a model optimization procedure that involves fuzzy set merging. It turns out that the feasible region is a compact and convex set. The tradeoff between interpretability and accuracy is established by minimizing the model's square error over the feasible region through constrained particle swarm optimization. The method is tested using a number of high-dimensional datasets and conducting two kinds of experiments. The first focuses on interpretability. The second studies the accuracy by comparing the method to other algorithms that perform unconstrained optimization, using nonparametric statistics.
A Singly Fed Wideband Circularly Polarized Dielectric Resonator Antenna

A singly fed wideband circularly polarized (CP) dielectric resonator (DR) antenna (DRA) with four sequentially rotated metallic plates is investigated. The square DRA is excited by a microstrip-coupled cross-slot to generate CP fields. By introducing four vertical metallic plates around the DR, three adjacent axial-ratio (AR) passbands are generated due to the cross-slot-fed DRA, the rotated metallic plates, and the interaction between the DR and metallic plates, leading to a very wide AR bandwidth. A prototype has been fabricated and measured to validate the design. Measured results show that the proposed CP DRA has a −10 dB impedance bandwidth of 46.9%, a 3 dB AR bandwidth of 49.5%, and an average gain of 4.7 dBic within the passband.
Design of Fractal Antenna for Wireless Multimedia Communication

With the increase in demand of multimedia communication based on next-generation wireless technology, antenna requires to be performed well and protected from electromagnetic environment. This includes reducing the electromagnetic interference (EMI) and ensuring compatibility for multimedia communication systems. In this work, the design of fractal carpet antenna has been proposed. Focusing on multimedia communication and EMI an attempt has been taken to design the antenna using compatible materials with complex permittivity and permeability. As the return loss and radiation pattern are most common ways to analyze the result of antenna, the result shows its performance in the frequency range of 6.4GHz for multiband communication lies in 1 to 10 GHz. The comparative results among two antennas and its far-field radiation pattern satisfies the less interference as well as stable energy distribution.
Design of Artificial Matching Layers With Arbitrary Permittivity Using a Metasurface

Metasurfaces have been used to design various new devices in microwaves and optics, and this letter presents a novel application of metasurfaces, which is to design an artificial matching layer (AML) with arbitrary permittivity. In contrast to a conventional matching layer that requires a certain permittivity and λ/4 thickness, a substrate with an available permittivity can be designed as an effective matching layer with the usage of a proper metasurface. The general design approach is described in this letter, and several design examples are presented. Full-wave simulation results agree well with the theoretical derivations, which validates the feasibility of the proposed AML design approach.
Organization of Neural Population Code in Mouse Visual System

Abstract The mammalian visual system consists of several anatomically distinct areas, layers, and cell types. To understand the role of these subpopulations in visual information processing, we analyzed neural signals recorded from excitatory neurons from various anatomical and functional structures. For each of 186 mice, one of six genetically tagged cell types and one of six visual areas were targeted while the mouse was passively viewing various visual stimuli. We trained linear classifiers to decode one of six visual stimulus categories with distinct spatiotemporal structures from the population neural activity. We found that neurons in both the primary visual cortex and secondary visual areas show varying degrees of stimulus-specific decodability, and neurons in superficial layers tend to be more informative about the stimulus categories. Additional decoding analyses of directional motion were consistent with these findings. We observed synergy in the population code of direction in several visual areas suggesting area-specific organization of information representation across neurons. These differences in decoding capacities shed light on the specialized organization of neural information processing across anatomically distinct subpopulations, and further establish the mouse as a model for understanding visual perception.
A Low-Profile Differentially Fed Microstrip Patch Antenna With Broad Impedance Bandwidth Under Triple-Mode Resonance

A low-profile differentially fed microstrip patch antenna with broad impedance bandwidth is proposed by incorporating a resonant mode of the slot into TM<sub>10</sub> and TM<sub>12</sub> modes of the patch resonator. Initially, the shorting pins are symmetrically placed underneath the patch so as to push up the resonant frequency of TM<sub>10</sub> mode in proximity to that of TM<sub>12</sub> mode (<italic>f</italic><sub>12</sub>). After that, the central slot could be employed to excite an additional mode resonating closely to the <italic>f</italic><sub>12</sub> by increasing the slot length. Additionally, a pair of small circular disks is introduced below the radiating patch for good impedance matching. Finally, the wideband antenna is fabricated and measured to validate the predicted performance. The results illustrate that the antenna has gained a broad impedance bandwidth of about 55% (1.62–2.85 GHz) with three in-band attenuation poles while maintaining the normal radiation pattern. In particular, a low-profile property with the height of about 0.06 free-space wavelength is achieved.
In vitro assays and techniques utilized in anticancer drug discovery

Development of a cancer is a multistep process and six major hallmarks of cancer that are known to control malignant transformation have been described. Anticancer drug development is a tedious process, requiring a number of in vitro, in vivo and clinical studies. In vitro assays provide an initial platform for cancer drug discovery approaches. A wide range of in vitro assays/techniques have been developed to evaluate each hallmark feature of cancer and selection of a particular in vitro assay or technique mainly depends on the specific research question (s) to be examined. In the present review, we have described some commonly utilized in vitro assays and techniques used to examine cell viability/proliferation, apoptosis, cellular senescence, invasion and migration, oxidative stress and antioxidant effects, gene and protein expression, angiogenesis and genomic alterations in cancer drug discovery. Additionally, uses of modern techniques such as high throughput screening, high content screening and reporter gene assays in cancer drug discovery have also been described.
Diosgenin Glucoside Protects against Spinal Cord Injury by Regulating Autophagy and Alleviating Apoptosis

Spinal cord injury (SCI) is a severe traumatic lesion of central nervous system (CNS) with only a limited number of restorative therapeutic options. Diosgenin glucoside (DG), a major bioactive ingredient of Trillium tschonoskii Max., possesses neuroprotective effects through its antioxidant and anti-apoptotic functions. In this study, we investigated the therapeutic benefit and underlying mechanisms of DG treatment in SCI. We found that in Sprague-Dawley rats with traumatic SCI, the expressions of autophagy marker Light Chain 3 (LC3) and Beclin1 were decreased with concomitant accumulation of autophagy substrate protein p62 and ubiquitinated proteins, indicating an impaired autophagic activity. DG treatment, however, significantly attenuated p62 expression and upregulated the Rheb/mTOR signaling pathway (evidenced as Ras homolog enriched in brain) due to the downregulation of miR-155-3p. We also observed significantly less tissue injury and edema in the DG-treated group, leading to appreciable functional recovery compared to that of the control group. Overall, the observed neuroprotection afforded by DG treatment warrants further investigation on its therapeutic potential in SCI.
Biosynthesis of Silver Nanoparticles from Oropharyngeal Candida glabrata Isolates and Their Antimicrobial Activity against Clinical Strains of Bacteria and Fungi

The objective of the present study was one step extracellular biosynthesis of silver nanoparticles (AgNPs) using supernatant of Candida glabrata isolated from oropharyngeal mucosa of human immunodeficiency virus (HIV) patients and evaluation of their antibacterial and antifungal potential against human pathogenic bacteria and fungi. The mycosynthesized AgNPs were characterized by color visualization, ultraviolet-visible (UV) spectroscopy, fourier transform infrared spectroscopy (FTIR), and transmission electron microscopy (TEM). The FTIR spectra revealed the binding and stabilization of nanoparticles with protein. The TEM analysis showed that nanoparticles were well dispersed and predominantly spherical in shape within the size range of 2–15 nm. The antibacterial and antifungal potential of AgNPs were characterized by determining minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC)/ minimum fungicidal concentration (MFC), and well diffusion methods. The MBC and MFC were found in the range of 62.5–250 μg/mL and 125–500 μg/mL, which revealed that bacterial strains were more susceptible to AgNPs than fungal strains. These differences in bactericidal and fungicidal concentrations of the AgNPs were due to the differences in the cell structure and organization of bacteria and yeast cells. The interaction of AgNPs with C. albicans analyzed by TEM showed the penetration of nanoparticles inside the Candida cells, which led the formation of “pits” and “pores” that result from the rupturing of the cell wall and membrane. Further, TEM analysis showed that Candida cells treated with AgNPs were highly deformed and the cells had shrunken to a greater extent because of their interaction with the fungal cell wall and membrane, which disrupted the structure of the cell membrane and inhibited the normal budding process due to the destruction and loss of membrane integrity and formation of pores that may led to the cell death.