Miracle-dz/UniFAR-FTUs huggingface dataset:
Event-triggered reliable dissipative filtering for the delay nonlinear system under networked systems with the sensor fault

ABSTRACT This paper investigates the problem of fuzzy filter design for a class of delayed nonlinear system under random sensor faults with an event-triggered (ET) mechanism. (1) To estimate the dynamics of nonlinear plant, a T–S fuzzy model is manipulated. Random variables are disclosed to express the sensor fault. (2) To take some advantages over existing one, a variable ET mechanism is offered in networked systems (NSs). Under the ET mechanism, sensor data are released only when the plant's measurement (sampled) violate specific threshold of the event condition. (3) Another purpose of this article is to design filters involving system state delays. Then, by using a novel fuzzy Lyapunov–Krasovskii function approach with free weighting matrix technique, dissipative filter design of ET delay networked control systems is proposed. We consider both the sensor fault and ET scheme simultaneously. The simulation example is given to demonstrate the effectiveness of design method.
Evaluation of the quality of automatic tree detection using photogrammetric canopy height models and orthomosaic

Работа выполнена в малонарушенном ельнике липняковом заповедника «Кологривский лес» (Костромская обл.) на основе данных аэрофотосъемки квадрокоптером. Алгоритмы автоматического детектирования позволили выделить большинство деревьев в пологе леса. Детектирование деревьев по ортофотоплану с использованием нейросетевого алгоритма Deep Forest оказалось более качественным, чем детектирование по модели высот при помощи алгоритма, основанного на методе скользящего окна. Как правило, оба метода демонстрировали более качественные результаты для хвойных деревьев по сравнению с лиственными. Сравнение средних высот деревьев, оцененных по дистанционным данным и измеренных наземными методами, не выявило значимых различий. Показана необходимость дополнительных наземных обследований для оценки качества детектирования подроста. The work was performed in the old-growth linden-spruce forest of the Kologrivsky Forest Nature Reserve (Kostroma Oblast, Russia) based on aerial photography with a quadcopter. Automatic detection algorithms made it possible to detect most of the trees in the forest canopy. Tree detection by orthomosaic using neural network algorithm ‘DeepForest’ turned out to be of better quality than detection based on the canopy height model using an algorithm based on the sliding window method. As a rule, both methods showed better results for conifers compared to deciduous trees. Comparison of the average heights of trees estimated from remote data and measured by ground survey did not reveal significant differences. Additional ground surveys to assess the quality of undergrowth detection are needed.
Pancreatic adenocarcinoma and aging: understanding the menace for better management

Pancreatic ductal adenocarcinoma (PDAC) is the leading cause of cancer-related death worldwide. As PDAC is more common in older adults and the population is aging, the incidence of pancreatic adenocarcinoma is expected to increase in the coming years. As a result, the mechanism and clinical management of PDAC in the elderly population is receiving more attention. This review will discuss age-related morphological and pathological changes, clinical management, surgery and adjuvant therapies, and molecular changes in elderly PDAC patients. More research is needed to clarify molecular mechanisms and develop new prevention and treatment strategies for PDAC in elderly patients.
Investigation of Flow Dynamics Over Turrets with Different Spanwise Aspect Ratios Using PSP

Unsteady pressure fields on and around turrets with the same streamwise curvature, but different spanwise extents were measured using a fast-response pressure sensitive paint and multiple high-speed cameras. Data were collected over a range of incoming Mach numbers between 0.4 and 0.68. POD and DMD techniques were used to analyze the dynamics and the topology of the wakes for different turret geometries and incoming speeds. The spectrum of the first POD mode, which is associated with the wake shifting mode, was found to scale with the spanwise extent of the turret. The spectra of the second and the third POD mode, associated with the wake breathing mode, scaled with the streamwise radius of curvature. The presence of an unsteady shock on top of both turret geometries at high transonic speeds was found to have an organizing effect on the separated flow, evidenced by the increased correlations between the convecting structures in the wake and the shockinduced separation and appearance of spectral peaks for dominant POD modes.
Geology of Good Sight Mountain and Uvas Valley, southwest New Mexico

The 435-sq-mi area described by this report includes the Good Sight Mountains and the Uvas Valley in Luna, Dona Ana, and Sierra Counties, New Mexico; the geologic map covers the western part of the Good Sight-Cedar Hills volcano-tectonic depression of Oligocene age. The Sierra de las Uvas on the east and the Good Sight Mountains on the west border the north-plunging Uvas Valley syncline, near the western side of the depression. Rock units exposed in the area range fr om Eocene to Holocene. The Good Sight Mountains are composed chiefly of Rubio Peak Formation rocks, which include latite and andesite tuffs, breccias, flows, dikes, plugs, and stocks with minor interbedded conglomerate and volcaniclastic beds. The source o f these rocks was the Good Sight Mountains vent zone, which trends north for about 30 mi and is 4 mi wide. The Rubio Peak is correlative, in part, with the Palm Park Formation to the east, but may include some younger units. The Rubio Peak is unconformably overlain by tuff 6 and the upper sedimentary member of the Bell Top Formation on the eastern slopes of the Good Sight Mountains. Tuff 4, tuff 5, and the middle sedimentary member pinch out under the eastern part of the Uvas Valley. North of Nutt Mountain, Rubio Peak is overlain by Kneeling Nun Tuff or Tenaga Canyon (new name) andesites and latites, which intrude and overlie the Kneeling Nun. Uvas Basaltic Andesite flows are interbedded and overlie the upper sedimentary member of the Bell Top Formation on the west flank of the Sierra de las Uvas, under the Uvas Valley, and on the eastern flank of the Good Sight Mountains. Tenaga Canyon rocks are intruded and overlain locally by Uvas Basaltic Andesite. Nutt Mountain is a flow-banded rhyolite plug that intruded rocks as young as Tenaga Canyon formation. Quaternary clastic deposits, locally more than 300 ft thick, fill the Uvas Valley and extreme western part of the map area (eastern edge of the Mimbres Basin). Numerous water wells have penetrated these deposits and many of these wells bottom in the underlying Uvas and upper Bell Top Formation strata. Outcrops of the lower aquifers in the Sierra de las Uvas probably provide some recharge to the NuttHockett Underground Water Basin.
Amorphous plasma sprayed coating

The plasma spraying method has wide application in many industries, including the automotive industry, due to its diversity and efficiency. The interest in this technology is increasing as it is possible to replace expensive materials with iron-based alloys and use air instead of inert gas to activate plasma. There are a number of works that have emphasized the importance of properly selected spray parameters, but they used the plasma generation gas, which is an expensive inert gas such as argon, heli, or their gas mixture with a different ratio. The objective of this paper is to study the influence of the most specific parameters that affect the quality of the wear-resistant spray layer using Fe-based powder sprayed onto the steel substrate material. The experiment design with the ANOVA analysis helped to find out the nature of the elevation of the wear resistance under the influence of the particle velocity and the related technological parameters in the process. The research results provide an experimental formula that combines the main spray parameters with the evaluation of wear resistance in relation to the traditional material group.
Synthesize This: Meta-Analysis as a Dissertation Tool

ABSTRACT Meta-analyses are used to synthesize a body of literature to produce a single summary estimate as well as to explain differences among studies. The field of political science has slowly gained an appreciation for their use in recent years; however, using meta-analyses in dissertations remains rare. This is puzzling, given the tool’s ability to map a topic, to highlight potential gaps for future research to address, and its long-lasting utility for researchers in future projects. We argue that for these and several other reasons, graduate students should consider including a meta-analysis in their dissertation. This article discusses these advantages in detail and offers advice on how to conduct a meta-analysis based on several interviews and applied examples. We also address potential challenges when using this research design in a dissertation.
Strong and weak convergence rates of finite element method for stochastic partial differential equation with non-globally Lipschitz coefficients

Strong and weak approximation errors of a spatial finite element method are analyzed for the stochastic partial differential equations(SPDEs) with non-globally Lipschitz coefficients, including the stochastic Allen--Cahn equation, driven by additive noise. In order to give the strong convergence rate of the finite element method, we present an appropriate decomposition and some a priori estimates of the discrete stochastic convolution. To investigate the weak error, we first regularize the original equation by the splitting technique and obtain the regularity of the corresponding regularized Kolmogorov equation. Meanwhile, we present the refined estimates and the regularity in Malliavin sense of the finite element methods. Combining with the regularity of regularized Kolmogorov equation and Malliavin integration by parts, we give the weak convergence rate of the finite element method.
Randomly incorporated genomic N6‐methyldeoxyadenosine delays zygotic transcription initiation in a cnidarian

N6‐methyldeoxyadenosine (6mA) is a chemical alteration of DNA, observed across all realms of life. Although the functions of 6mA are well understood in bacteria and protists, its roles in animal genomes have been controversial. We show that 6mA randomly accumulates in early embryos of the cnidarian Hydractinia symbiolongicarpus, with a peak at the 16‐cell stage followed by clearance to background levels two cell cycles later, at the 64‐cell stage—the embryonic stage at which zygotic genome activation occurs in this animal. Knocking down Alkbh1, a putative initiator of animal 6mA clearance, resulted in higher levels of 6mA at the 64‐cell stage and a delay in the initiation of zygotic transcription. Our data are consistent with 6mA originating from recycled nucleotides of degraded m6A‐marked maternal RNA postfertilization. Therefore, while 6mA does not function as an epigenetic mark in Hydractinia, its random incorporation into the early embryonic genome inhibits transcription. In turn, Alkbh1 functions as a genomic 6mA “cleaner,” facilitating timely zygotic genome activation. Given the random nature of genomic 6mA accumulation and its ability to interfere with gene expression, defects in 6mA clearance may represent a hitherto unknown cause of various pathologies.
Manipulating Opinions in Social Networks With Community Structure

Online social media have been one of the greatest drivers of societal change of the past two decades, but are now being recognized as one of the major causes of opinion radicalization and one of the most effective tools for opinion manipulation. Starting from a class of stochastic models of opinion dynamics, and considering different structures of social networks with increasingly realistic features (including a snapshot of the Facebook friendship network), we develop a mathematical model of different forms of opinion manipulation. We then explore how network properties, and in particular degree distribution and community structure, interact with the attack to amplify or reduce its effect on the population, both globally and on specific subsets. We find, in particular, that degree heterogeneity is key to making online social media susceptible to very effective attacks, even with relatively little effort. Communities instead play a more complex role, acting both as barriers to the spread of manipulated opinions through the whole population and as amplifiers of manipulated opinions when the target of the attack is a community of the online social medium. The results of our study can help design effective strategies to prevent the manipulation of opinions through online social media.
Dynamical Systems Approach for Predator-Prey Robot Behavior Control via Symbolic Dynamics Based Communication

The study of complex systems (Badii & Politi, 1997; Macau & Grebogi, 1999) has created a lot of research interests especially due to its diverse applications in science, engineering, management and biological systems. These exhibit emergent behavior that is neither completely ordered and predictable, nor completely random and unpredictable. It produces patterns and hierarchy of structures which emerge due to its attractor dynamics (Grassberger, 1991; Poon & Grebogi, 1995). Artificial intelligence, adaptive networks, collective intelligence, and chaos fall under this category. Out of these, chaotic system is the area under investigation in this work. Chaotic systems can be controlled through the technique of chaos synchronization (Pecora & Carroll, 1990). It involves the coupling of two chaotic systems so that both achieve identical dynamics asymptotically with time. Such non-linear systems have been effectively used in a plethora of engineering and scientific applications (Maoyin, 2008; Fallahi & Leung, 2010; Mukhopadhyay et al., 2010; Fan et al., 2010; Banerjee et al., 2012). An emergent area of robotics is based upon the paradigm of behavior-based robotics and it deals with an entirely different information flow structure than that of the classical artificial intelligent systems. This work presents an application of a nonlinear biological system in the area of chaos navigation with mobile robots and accomplishment of its control. The objective is to extend the phase synchronization of identical unidirectional coupled chaotic food webs (Blasius & Stone, 2000; Stone & He, 2007) in a robot foraging task. Chaotic synchronization promotes cooperative task achievement. Collaborative mobile robot exploration is achieved through noise aided synchronization of a two–wheeled mobile robot that follows the predator – prey dynamics. Thus, a bio-inspired mobile robotic design is proposed for the task of coverage of a workspace that is completed when a specified portion of the workspace is explored.
Using a blended distance pedagogy in teacher education to address challenges in teacher recruitment

Recruiting high-quality teachers is critical in supporting the delivery of an effective education experience for learners in schools. This paper examines how a new flexible two-year postgraduate teaching qualification is contributing to addressing the challenges of teacher recruitment in Wales. There is a shortage of teachers able to teach mathematics and science. It is also challenging to recruit Welsh-medium teachers, teachers from minority ethnic backgrounds and to fill vacancies in rural schools. To widen access to teacher education and diversify the teaching workforce, individuals with an appropriate undergraduate degree are offered the opportunity to train to teach via a flexible blended distance learning route, which is either part time or salaried. Early indications show that the flexibility of the programme has attracted career changers, who bring important transferable skills to their teaching practice. Although this is a relatively small-scale case study, it is apparent that offering a more flexible opportunity to those wishing to train to teach is of benefit to individuals, schools and the wider education system.
Daily Oral Memantine Attenuated the Severity of Borderline Personality Disorder Symptoms: A Double-Blind Placebo-Controlled, Randomized Clinical Trial

Background: Borderline personality disorder (BPD) has been considered a psychiatric disorder, the effective pharmacological treatments for which have not been well established. Objectives: This study aimed to assess the efficacy of memantine (10 mg/day) in reducing BPD severity and cognitive impairment. Methods: The BPD patients diagnosed by psychologists were included and divided into the placebo (n = 19) and memantine (n = 20) groups. Included participants were randomized, double-blinded, and stabilized on the medication and psychotherapy for at least four weeks. The patients in the memantine group received oral memantine (10 mg/day) for four weeks. The severity of BPD was assessed by a self-reported questionnaire named Borderline Evaluation of Severity Over Time (BEST). Moreover, the Wisconsin test was carried out to assess executive function. Results: The mean score of the BEST test significantly decreased in week eight post-treatment in the memantine group. In addition, a significant decrease in this score was indicated in the memantine group compared to the placebo group in week eight. The mean total score of the BEST test was not significantly different before and after the placebo administration. There was no significant difference in the Wisconsin subscales, including the number of wrong answers and categories achieved after memantine or placebo administration. Perseverative errors rose after the administration of memantine. Adverse side effects did not occur in any of the participants. Conclusions: Our findings suggested the potential therapeutic effects of memantine for BPD. Furthermore, we found that a low dose of meantime might be preferable to prevent the side effects.
Comprehensive evaluation of target spectra for selecting bidirectional ground motions in nonlinear response history analysis of frame buildings at far‐field sites

An ensemble of bidirectional ground motions (GMs) is required as input for nonlinear response history analysis (RHA) of complex 3D structures. In building codes, an ensemble of GMs is often developed from a given design spectrum, or target spectrum. In the research literature, several target spectra have been proposed for such intensity‐based assessments. The present study aims to comprehensively evaluate different options for developing target spectra to select bidirectional GMs as inputs to nonlinear RHAs of 3D structural systems. To achieve this goal, we conducted both intensity‐based and risk‐based assessments of 49 multistory buildings with varying dynamic characteristics, heights, and plan shapes. The results from performing 11,074 bidirectional nonlinear RHAs and deriving the seismic demand hazard suggest that the Conditional Mean Spectrum‐Uniform Hazard Spectrum (CMS‐UHS) Composite Spectrum appears to be the most promising alternative. With less computational effort than use of multiple CMS, the Composite Spectrum tends to accurately estimate story drift ratios (average overestimation of 4%) and floor accelerations (average overestimation of 3%). Moreover, the relative ranking between the various target spectra options remains largely independent of the building type, height, and plan shape. However, the precision in estimates of demand tends to decrease for buildings with increasing complexity (e.g., more realistic, or taller, or more asymmetrical in plan).
Constructing Temporal Dynamic Knowledge Graphs from Interactive Text-based Games

In natural language processing, interactive text-based games serve as a test bed for interactive AI systems. Prior work has proposed to play text-based games by acting based on discrete knowledge graphs constructed by the Discrete Graph Updater (DGU) to represent the game state from the natural language description. While DGU has shown promising results with high interpretability, it suffers from lower knowledge graph accuracy due to its lack of temporality and limited generalizability to complex environments with objects with the same label. In order to address DGU's weaknesses while preserving its high interpretability, we propose the Temporal Discrete Graph Updater (TDGU), a novel neural network model that represents dynamic knowledge graphs as a sequence of timestamped graph events and models them using a temporal point based graph neural network. Through experiments on the dataset collected from a text-based game TextWorld, we show that TDGU outperforms the baseline DGU. We further show the importance of temporal information for TDGU's performance through an ablation study and demonstrate that TDGU has the ability to generalize to more complex environments with objects with the same label. All the relevant code can be found at \url{https://github.com/yukw777/temporal-discrete-graph-updater}.
Fluctuation of probe beam in thermolens schematics as potential indicator of cell metabolism, apoptosis, necrosis and laser impact

Recently we discovered that in developed integrated flow cytometry using combination high resolution transmission and two beam (pump-probe) of photothermal microscopy with flow module the temporal fluctuation of probe beam even without pump laser pulse are very sensitive to functional states of single cells (e.g. with 2-3 differences in average fluctuation amplitude for live and dead cells). In this paper we are focusing on theoretical and experimental studies of these new phenomena using thermolens schematics with highly stabilized continuous-wave He-Ne laser and photodiode/photomultiplier with pinhole. This scheme allows to study both random and laser-induced thermolens effects in passive and active mode including short and long term monitoring of scattered light fluctuation in trans-illumination mode at single cellular and even sub-cellular levels in vitro, and in vivo. We demonstrate these schematics has some potential to monitor intracellular dynamics including change in cell metabolism, and necrosis, especially, under pump laser impacts in vitro in stationary condition. Besides, we present some relevant data obtained with other similar schematics, including evaluation of bacterial motility by dynamic light scattering. We discuss further potential developing this approach for flow cytometry with fast speed photodetector and digital camera and the multi- wavelength statistical and correlation analysis of speckle-related signals in applications to analysis of complex motions and functional properties of cells in bioflows including the evaluation of the rotational and translational components of the motion of individual live and dead cells.