Miracle-dz/UniFAR-FTUs huggingface dataset:
High-sensitivity ITS real-time PCR assays for detection of Ceratocystis lukuohia and Ceratocystis huliohia in soil and air samples

Rapid Ohia Death (ROD) is caused by two pathogens, Ceratocystis lukuohia and Ceratocystis huliohia. The established species-specific real-time PCR assays targeting the single-copy cerato-platanin gene require DNA between 2 and 16 spores per reaction for consistent detection, which is suitable for analysis of infected plant tissue but not sensitive enough to consistently detect low spore-loads in environmental samples. Here we present two redesigned qPCR assays targeting the first Internal Transcribed Spacer (ITS) region of the multi-copy ribosomal DNA operon from the respective species, both capable of consistent detection of the pathogen at concentrations as low as 1 fg per reaction, less than the size of the haploid genome. Due to this increased sensitivity, these ITS qPCR assays are superior for analysis of DNA extracted from material collected in airborne particle samplers and from soil. Here, we demonstrate the utility of these qPCR assays for the characterization of windblown and soilborne dispersal of the pathogens, which is critical for the development of management practices that mitigate disease spread.
Interpretation of Reflection and Colorimetry Characteristics of Indium-Particle Films by Means of Ellipsometric Modeling

It is of great technological importance in the field of plasmonic color generation to establish and understand the relationship between optical responses and the reflectance of metallic nanoparticles. Previously, a series of indium nanoparticle ensembles were fabricated using electron beam evaporation and inspected using spectroscopic ellipsometry (SE). The multi-oscillator Lorentz–Drude model demonstrated the optical responses of indium nanoparticles with different sizes and size distributions. The reflectance spectra and colorimetry characteristics of indium nanoparticles with unimodal and bimodal size distributions were interpreted based on the SE analysis. The trends of reflectance spectra were explained by the transfer matrix method. The effects of optical constants n and k of indium on the reflectance were demonstrated by mapping the reflectance contour lines on the n-k plane. Using oscillator decomposition, the influence of different electron behaviors in various indium structures on the reflectance spectra was revealed intuitively. The contribution of each oscillator on the colorimetry characteristics, including hue, lightness and saturation, were determined and discussed from the reflectance spectral analysis.
The Exact Distribution of The Ratio of Two Independent Hypoexponential Random Variables

The distribution of ratio of two random variables are of interest in many areas of the sciences. The study of the ratio of same family and finding their exact density expression was examined by many authors for decades. Some are solved and others gave approximations, but many still unsolved. In this paper, we consider the ratio of two independent Hypoexponential distributions. We find the exact expressions for the probability density function, the cumulative distribution function, moment generating function, the reliability function and hazard function, which was proved to be a linear combination of the Generalized-F distribution.
MATHEMATICAL ANALYSIS OF NONLINEAR BONDED JOINT MODELS

Within the framework of nonlinear elasticity, we consider the problem of two adherents joined along their common surface by a thin soft adhesive. Two stored energy functions are considered: the stored energy function of Saint Venant–Kirchhoff and the stored energy function of Ciarlet–Geymonat. Using the asymptotic expansion method, the limit energy associated to each of these stored energy functions is obtained. The aim of this paper is to give a rigorous mathematical analysis of the formally derived limit problem. We show that the limit problem associated to the Saint Venant–Kirchhoff case admits at least one solution and the limit problem associated to the Ciarlet–Geymonat case admits exactly one solution. An analytical comparison in the one-dimensional case and a three-dimensional numerical application are also presented.
Smart spatial light modulators using liquid crystals on silicon

Smart pixels are discussed in terms of the following neurally inspired functions: memory, sensors, intrapixel circuitry, interpixel communication, and optical outputs. The types of liquid crystals and electronic circuits used in VLSI/liquid crystal arrays, and their electrooptic properties are reviewed. Examples of electrically addressed and optically addressed liquid crystal smart pixels, and results from a 128*128 VLSI/FLC SLM are presented. This device has a response time of 150 mu s, a contrast ratio of 8:1 measured on a row containing more than 50 pixels, and a frame rate of 4.7 kHz. Improvements of these devices are discussed in terms of what the silicon technology can yield in the future. A few examples in which the liquid crystal on silicon technology has been applied are presented. >
Survey of Deep Learning for Autonomous Surface Vehicles in Marine Environments

Within the next several years, there will be a high level of autonomous technology that will be available for widespread use, which will reduce labor costs, increase safety, save energy, enable difficult unmanned tasks in harsh environments, and eliminate human error. Compared to software development for other autonomous vehicles, maritime software development, especially in aging but still functional fleets, is described as being in a very early and emerging phase. This presents great challenges and opportunities for researchers and engineers to develop maritime autonomous systems. Recent progress in sensor and communication technology has introduced the use of autonomous surface vehicles (ASVs) in applications such as coastline surveillance, oceanographic observation, multi-vehicle cooperation, and search and rescue missions. Advanced artificial intelligence technology, especially deep learning (DL) methods that conduct nonlinear mapping with self-learning representations, has brought the concept of full autonomy one step closer to reality. This article reviews existing work on the implementation of DL methods in fields related to ASV. First, the scope of this work is described after reviewing surveys on ASV developments and technologies, which draws attention to the research gap between DL and maritime operations. Then, DL-based navigation, guidance, control (NGC) systems and cooperative operations are presented. Finally, this survey is completed by highlighting current challenges and future research directions.
UAV assisted communication for ground users using machine learning and optimization

Aim: Among a large number of products that support communication, there is one called space air ground integrated networks (SAGIN's), which is the most commonly used to support users in rural and emergency situations. Typicaly in emergency situations SAGIN's use unmanned aerial vehicles (UAVs) in their air layer to temporarily support the ground users. Although the cost of UAVs is lower than that of traditional base stations, and their actions are more flexible, but their battery life problems lead to frequent charging of drones, resulting in many resource losses and unable to provide communication support. In order to mitigate the issues, novel optimization algorithms need to be developed to support the ground users. Methods: In this work, we develop a grid-based deep learning method using the LSTM model to estimate the number of ground users as vehicles in each area, and developed an optimization algorithm to minimize the number of UAVs needed to the user's and meanwhile to satisfy quality of service (QoS) requirements. For optimization, we mainly use the Linear Optimization Tools and an objective function has been developed using density predicted and SINR data to achieve acceptable QoS. Results: The simulation results shows that this approach has improved the quality of the communication by 50%. Conclusion: Using unique grid technique and the LSTM machine learning model, the user densities on each partitioned grid is determined. Finally, a linear optimization algorithm is developed based on the user density to determine the lowest number of UAVs to support the users in each grid while maintaining the QoS.
Deep Learning Based Predictive Beamforming Design

This paper investigates deep learning techniques to predict transmit beamforming based on only historical channel data without current channel information in the multiuser multiple-input-single-output downlink. This will significantly reduce the channel estimation overhead and improve the spectrum efficiency especially in high-mobility vehicular communications. Specifically, we propose a joint learning framework that incorporates channel prediction and power optimization, and produces prediction for transmit beamforming directly. In addition, we propose to use the attention mechanism in the Long Short-Term Memory Recurrent Neural Networks to improve the accuracy of channel prediction. Simulation results using both a simple autoregressive process model and the more realistic 3GPP spatial channel model verify that our proposed predictive beamforming scheme can significantly improve the effective spectrum efficiency compared to traditional channel estimation and the method that separately predicts channel and then optimizes beamforming.
Primary School Students with Reading Comprehension Difficulties and Students with Learning Disabilities: Exploring Their Goal Orientations, Classroom Goal Structures, and Self-Regulated Learning Strategies

The aim of the present study was to investigate goal orientations and classroom goal structures and their relationship with strategies of self-regulated learning (SRL) in students with and without learning disabilities (LD) and reading comprehension difficulties (RCD). The sample consisted of 537 students attending the two last grades of primary school, fifth and sixth grade (Mage = 11.28 years, SD = ±0.59). Of these, 58 students were diagnosed with LD, and 70 students, after individually administered assessments in reading accuracy and reading comprehension, were assigned to the RCD group. Self-reported questionnaires were administered, assessing students’ personal goal orientations, classroom goal structures, and strategies of SRL. The results showed that students with LD and students with RCD scored lower in mastery orientation and higher in performance avoidance compared to their peers without difficulties (ND). LD students reported lower scores of adaptive strategies than their peers. In addition, the results confirmed the adaptive character of mastery-approach goals and mastery goal structures and the negative effects of performance-avoidance goals and performance goal structures on the adaptive strategies of SRL. Performance-approach goals predicted adaptive behaviors for all students, confirming the argument of an adaptive type of motivation. The findings of the current study highlight the importance of goal orientations and classroom goal structures for students’ SRL. Implications of the findings for enhancing motivation for students with LD and students with RCD are discussed.
Synchrony of Neural Activity in Electric Responses Evoked by Transient Acoustic Stimuli

Electric responses evoked by transient acoustic stimuli were recorded by gross electrodes from the periphery and cortex of the cat. The responses to clicks and to the rapid onset of bursts of noise or tones are characterized by a sharp N1 peak in the peripheral response and by a broader cortical response. When the rise time of the onset of bursts of noise (or tones) is lengthened, or when a burst of sudden onset is presented in a noise background, it is possible to obtain cortical responses under conditions for which the N1 component of the peripheral response is undetectable. These results and associated findings are interpreted by considering the degree of synchronization of the discharge and the wave forms of the activity of units that contribute to responses recorded by gross electrodes. A simple statistical interpretation is presented.
A cell assembly model of language

Networks of formal neurons are introduced as paradigms for neuronal structures in the brain underlying language. Linguistic elements, e.g. syllables or words, are assumed to have their neuronal counterparts in Hebbian cell assemblies comprising parts which are located in different areas of the human cortex, in particular within the language regions. We investigate the effects of 'lesions' in artificial 'assemblies' in which only next neighbours are connected reciprocally (simulation A). In addition, we simulate the effects of lesions in a net consisting of several 'assemblies' which was taken as a model of the human language cortex (simulation B). The lesion studies lead to predictions on language disabilities in aphasics, i e. in individual with damage in the language-relevant cartex. The results provide an explanation of the fact that aphasic symptom complexes vary as a function of the damaged brain sites. The explanations cover the multimodal character of aphasias and the occurrences of the following s.
Progress in Emission Efficiency of Organic Light-Emitting Diodes: Basic Understanding and Its Technical Application

The technical history of when and how the basic understanding of the emission efficiency of organic light-emitting diodes (OLEDs) was established over the last 50 years is described. At first, our understanding of emission efficiency in single-crystal and thin-film electroluminescence (EL) devices in the early stages before the Eastman-Kodak breakthrough, that is, the introduction of the concept of multilayer structures, is examined. Then our contemplation travels from the Eastman-Kodak breakthrough towards the presently widely accepted concept of emission efficiency. The essential issues concerning the emission efficiency of OLEDs are summarized to help readers to obtain a common understanding of OLED efficiency problems, and detailed discussions on the primary factors that determine emission efficiency are given. Finally, some comments on remaining issues are presented.
Anemoside B4 Exerts Hypoglycemic Effect by Regulating the Expression of GLUT4 in HFD/STZ Rats

Anemoside B4 (B4) is a saponin that is extracted from Pulsatilla chinensis (Bge.), and Regel exhibited anti-inflammatory, antioxidant, antiviral, and immunomodulatory activities. However, its hypoglycemic activity in diabetes mellitus has not been evaluated. Here, we explored the effect of B4 on hyperglycemia and studied its underlying mechanism of lowering blood glucose based on hyperglycemic rats in vivo and L6 skeletal muscle cells (L6) in vitro. The rats were fed a high-fat diet (HFD) for one month, combined with an intraperitoneal injection of 60 mg/kg streptozotocin (STZ) to construct the animal model, and the drug was administrated for two weeks. Blood glucose was detected and the proteins and mRNA were expressed. Our study showed that B4 significantly diminished fasting blood glucose (FBG) and improved glucose metabolism. In addition, B4 facilitated glucose utilization in L6 cells. B4 could enhance the expression of glucose transporter 4 (GLUT4) in rat skeletal muscle and L6 cells. Mechanistically, B4 elevated the inhibition of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathways. Furthermore, we confirmed the effect of B4 on glucose uptake involved in the enhancement of GLUT4 expression in part due to PI3K/AKT signaling by using a small molecule inhibitor assay and constructing a GLUT4 promoter plasmid. Taken together, our study found that B4 ameliorates hyperglycemia through the PI3K/AKT pathway and promotes GLUT4 initiation, showing a new perspective of B4 as a potential agent against diabetes.
Speed and Scalability of Ambipolar Deep-Subthreshold TFTs for Ultralow-Power Printed Electronics

This work evaluates the speed and scalability potential of ambipolar deep-subthreshold printed-carbon-nanotube thin-film transistors (CNT-TFTs) for the design of ultralow-power CMOS-like circuits. Transistor and circuit simulations are developed based on experimental device measurements. Our simulations allow the assessment of this emerging printed electronics technology in terms of speed, energy/power consumption, and scalability to digital circuits of progressively higher transistor count including elementary logic gates, ring oscillators and other representative digital circuits. It is shown that digital circuits based on this technology are compatible with propagation delays $\le 1$ ms per NOT logic gate, while operating at ultralow supply voltages (0.2 V) and with ultralow static power dissipation (1 pW). Finally, this study develops Monte Carlo simulations to assess the impact of device parameter variations on the viability of large-scale circuit integration based on ambipolar deep-subthreshold printed-CNT-TFTs.
α-stable limits for multiple channel queues in heavy traffic

We consider a sequence of renewal processes constructed from a sequence of random variables belonging to the domain of attraction of a stable law (1 < α < 2). We show that this sequence is not tight in the Skorokhod J1 topology but the convergence of some functionals of it is derived. Using the structure of the sample paths of the renewal process we derive the convergence in the Skorokhod M1 topology to an α-stable Lévy motion. This example leads to a weaker notion of weak convergence. As an application, we present limit theorems for multiple channel queues in heavy traffic. The convergence of the queue length process to a linear combination of α-stable Lévy motions is derived.
Gender Differences in the Association between Physical Activity and Mortality in Chronic Kidney Disease: Results from the National Health and Nutrition Examination Survey (2011–2018)

Background: Physical activity is indispensable in the management of chronic kidney disease (CKD). The aim of this study was to investigate gender difference in the association of physical activity with mortality among the CKD population. Methods: In total, 3701 participants with CKD from the 2011 to 2018 NHANES with linked mortality data were classified into different groups based on the intensity of self-reported physical activity. Multivariable-adjusted Cox proportional hazards models were used to examine the associations between physical activity and mortality. Results: During the median follow-up of 53.7 months, 694 all-cause deaths and 226 cardiovascular deaths were recorded. Patients were categorized into extremely highly active (>1500 MET-min/week), highly active (>600, ≤1500 MET-min/week), low-active (>0, ≤600 MET-min/week), or inactive (0 MET-min/week) groups. Among males, the multivariable Cox regression showed that the low-active group (HR, 0.67; 95% CI, 0.48–0.93) and highly active group (HR, 0.60; 95% CI, 0.41–0.88) were independently associated with lower risks for all-cause mortality, compared to the inactive group. The risks of all-cause mortality did not further decrease once physical activity surpassed 1500 MET-min/week, indicating a U-shaped association in males. In females, only the extremely highly active group (>1500 MET-min/week) was significantly associated with a mortality risk compared to inactivity (HR, 0.59; 95% CI, 0.39–0.89). Conclusions: Any amount of physical activity is associated with reduced all-cause mortality in male CKD participants, while in female patients, only the extremely highly active group shows the significant association.
Role of twin boundaries in semiconductor to metal transition characteristics of VO2 films

Epitaxial (002) VO2 films were grown on c-sapphire with Ga:ZnO and ZnO buffer layers. We investigated the influence of twin boundaries on the semiconductor-to-metal transition (SMT) characteristics of VO2, when current flows parallel and perpendicular to the twin boundaries. The structure of the twin boundary was kept the same for these two configurations. The hysteresis in SMT characteristics is considerably reduced when current flows parallel to the boundaries compared to that in the normal direction of the boundaries. We present a model to explain these observations and discuss the role of these boundaries on the SMT characteristics, and the importance of grain boundary engineering in the design of VO2 based devices.
Integrating spatial dependence into functional clustering of NDVI in the Ecuadorian Andes

Spatial dependence into environmental data is an influential criterion in clustering processes, as the resulting clustering outputs depend very much upon such spatial structure. As classical methods do not take spatial dependence in consideration, the inclusion of this structure produces unexpected but more realistic results and clusters of curves that may not be similar in shape or behavior. In this paper, clustering is made using the KMSCFD algorithm for spatially correlated functional data. The methodology was developed through weighting the distance matrix between the curves with the trace‐variogram calculated with the coefficients of the basis functions resulting from a data smoothing operation. For the validation of the method, a number of simulated scenarios were tested together with an application to Normalized Difference Vegetation Index data derived from a high elevation ecosystem in the Ecuadorian Andes. Quality indices are implemented to obtain the appropriate number of clusters. The analysis showed five different regions that were latitudinally distributed.
Achieving high precision photometry for transiting exoplanets with a low cost robotic DSLR-based imaging system

We describe a low cost high precision photometric imaging system, which has been in robotic operation for one and half year on the Mauna Loa observatory (Hawaii). The system, which can be easily duplicated, is composed of commercially available components, offers a 150 sq deg field with two 70mm entrance apertures, and 6-band simultaneous photometry at a 0.01 Hz sampling. The detectors are low-cost commercial 3-color CMOS array, which we show is an attractive costeffective choice for high precision transit photometry. We describe the design of the system and show early results. A new data processing technique was developed to overcome pixelization and color errors. We show that this technique, which can also be applied on non-color imaging systems, essentially removes pixelization errors in the photometric signal, and we demonstrate on-sky photometric precision approaching fundamental error sources (photon noise and atmospheric scintillation). We conclude that our approach is ideally suited for exoplanet transit survey with multiple units. We show that in this scenario, the success metric is purely cost per etendue, which is at less than $10000s per square meter square degree for our system.