Miracle-dz/UniFAR-FTUs huggingface dataset:
Locally adaptive linear mixture model-based super-resolution land-cover mapping based on a structure tensor

ABSTRACT Super-resolution land-cover mapping (SRM) is a technique for generating land-cover thematic maps with a finer spatial resolution than the input image. Linear mixture model-based SRM (LSRM) is applied directly to a remotely sensed image and is composed of a spatial term that integrates the land-cover spatial pattern prior information, a spectral term that assumes that the spectral signature of each mixed pixel is composed of a weighted linear sum of endmember spectral signatures within that pixel and a balance parameter that defines the weight of the spatial term. The traditional LSRM adopts an isotropic spatial autocorrelation model in the land-cover spatial term for different classes and a fixed balance parameter for the entire image, and ignores the image local properties. The class boundaries are at risk of oversmoothing and may be imprecise, and the homogeneous regions may be unsmoothed and contain speckle-like artefacts in the result. This study proposes a locally adaptive LSRM (LA-LSRM) that integrates image local properties to predict fine spatial resolution pixel labels. The structure tensor is applied to detect the image local information. The LA-LSRM spatial term is locally adaptive and is composed of an anisotropic spatial autocorrelation model in which the spatial autocorrelation orientations of different classes may vary. The LA-LSRM balance parameter is locally adaptive to the different regions of the image. Such parameter obtains a relatively large value when the fine-resolution pixel is located in the homogeneous region to remove speckle-like artefacts and a relatively small value when the fine-resolution pixel is at the class boundary to preserve the edge. The LA-LSRM performance was assessed using a simulated multi-spectral image, an IKONOS multi-spectral image, a hyperspectral image produced by Airborne Visible/Infrared Imaging Spectrometer and a hyperspectral image produced by reflective optics system imaging spectrometer. Results show that the homogeneous regions were smoothed, the boundaries were better preserved and the overall accuracies were increased by LA-LSRM compared with traditional LSRM in all experiments.
Determination of Critical and Cancellation Speeds of Euler–Bernoulli Beam Subject to a Continuously Moving Load

Treated herein is an elastic beam that is subjected to a constant load that travels continuously (back and forth) along its span. The dynamic deflection of the beam is investigated analytically so as to predict the critical and cancellation speeds. Closed-form solutions are obtained for the damped system for each load condition and superimposed to determine the total solution of the response. Unlike the classical case of load traveling at constant speed in one direction, multiple resonance peaks are observed for reciprocating load at speeds that are lower than the classical critical speed. It is also observed that resonance may not exist at the classical critical speed for simply supported beams due to the symmetry of the beam. The dynamic deflection is examined for simply supported beams to determine the speeds that cause amplification or cancellation of the free response. The current load condition may have possible application in view of its potential use for vibration suppression, as a moving vibration absorber, or for magnification, in energy harvesting. The results are interpreted in order to understand the variation of dynamic deflection and to estimate the critical speeds for different load conditions.
DESIGN OF FRACTIONAL ORDER SLIDING MODE CONTROLLER FOR 2 DOF HELICOPTER SYSTEM

This paper presents a real time application for a prototype helicopter system by using sliding mode control strategy enhanced with small differential deviations. Experimental and simulation studies of the proposed controller demonstrate the control performance for a class of flight systems with unstable dynamics. It is shown that the controller decreases the steady state errors of the vertical and horizontal rotation of the system. Principally, small differential deviations successfully strengthen or weaken the effect of the differentiation to obtain better response in case of external disturbances. Numerical and experimental results are in agreement and confirm effectively tracking of desired rotor angles and suppression disturbances.
Resolution criterion based on wigner distribution function for two point-objects in incoherent light

Let us consider an optical imaging system formed by two point-objects incoherently illuminated and a thin positive lens delimited for circular pupil. The two point-objects image has two issues well-established. The first is when the two point-objects are close together and their images overlap considerably and the second one is when the distance between the two point-objects is widely large so that their images are separated. However, what happens when you can only see the image without you have the objects that formed this image? In this regard the resolution criteria are used. A resolution criterion gives the minimum distance in which the optical system is able to resolve the image of two objects when these are closely spaced. In this context, in the present master thesis we propose a new resolution criterion based on the Wigner distribution function properties (WDF) for two point-objects and its generalization for two quasi-point objects. Additionally, for a particular numerical example, this criterion is compared with the Rayleigh, Dawes and Sparrow criteria.
Impacts of product structural characteristics on modular performance with virtual DSM data mining

ABSTRACT Increasingly fierce market competition and rapidly changing customer demand has led many manufacturing enterprises to actively adopt modular architecture for product design and development. This helps them to effectively control their production costs while maintaining the diversity of product variants. However, there are considerable differences between the structure of different products; the degree to which each product is suitable for adopting a modular architecture also varies. Here, we explored the impact of product structural features (the number of parts and the average number of connected nodes) on its modular performance, based on virtual product design structure matrix (DSM) data. We first propose a method for constructing a DSM of a virtual product and randomly generate a database of DSMs with different structural parameters. We then carry out hierarchical clustering and modularity evaluation on a DSM model to obtain the optimal modularity scheme and corresponding Q value. Finally, based on numerical simulation data, the relationship between the structural features of virtual products and their modular performance was analyzed. In addition, eight actual products were selected to verify the simulation results and ensure the credibility of these results. Abbreviations: ANCN, Average number of connected nodes; CE, Clustering efficiency index; DSM, Design structure matrix; HC, Hierarchical clustering; IC, Integrative complexity; LCA, Life cycle assessment; MDL, Minimum description length; MDS, Multi-dimensional scaling; MI, Modular index; MSI, Module strength indicator; PC(c), Partition coefficient c; PDM, Product data management; PLM, Product lifecycle management.
Glandular and Non-Glandular Trichomes from Phlomis herba-venti subsp. pungens Leaves: Light, Confocal, and Scanning Electron Microscopy and Histochemistry of the Secretory Products

The purpose of this paper is to highlight the morphological peculiarities of glandular and non-glandular trichomes from leaves of Phlomis herba-venti subsp. Pungens using light, confocal, and scanning electron microscopy. Histochemistry techniques were used to analyze the localization of different chemical compounds in secretory trichomes. Two types of non-glandular trichomes were identified: unicellular and branched. They were found more frequently on the lower epidermis of leaves in different stages of ontogenetic development. Glandular trichomes were categorized as capitate (C1 and C2) with different stalk lengths and one–four secretory cells and dendroids (D) with one–four secretory cells. The histochemical analyses revealed distinct secretory products in terms of composition and distribution among the three types of glandular trichomes. The dendroid category of glandular trichomes is rarely found in plants and is not characteristic of the Lamiaceae species. They were described and characterized from a micromorphological and histochemical point of view for the first time in P. herba-venti.
Effect of sintering temperatures on temperature coefficient of capacitance of KCa2Nb3O10 bulk-layered perovskite

ABSTRACT Multilayer ceramic capacitors (MLCCs) for electric vehicles require their room temperature capacitance to change ≤ ±15% at −55°C to 200°C. The dielectric constant (ε) of BaTiO3, a dielectric material widely used in MLCCs, drops at >125°C making its application to electric vehicles difficult. Here, we propose KCa2Nb3O10 (KCNO)-layered perovskite as a strong candidate for electric vehicle MLCCs as its ε does not change abruptly with temperature. The effect of sintering temperature on the temperature coefficient of capacitance (TCC) of KCNO is studied. The KCNO powder calcined at 900–1200°C is sintered at 1200°C–1300°C. Microstructure and temperature-dependent ε are determined by the sintering temperature, while the sintered density is related to the difference between the calcining and sintering temperatures. Only the room temperature ε of the samples sintered at 1300°C (except the one calcined at 900°C) varies ≤ ±15% at 25°C–200°C (ε ~250 at room temperature). The sample calcined at 1100°C and sintered at 1300°C has highly elongated grains and the highest activation energy. These factors are responsible for the TCC of the 1300°C sintered KCNO being ≤ ±15% at 25–200°C.
An Effective Smart Goggle to Address the Problem Faced by the Visually Impaired People

According to our research and the studies, there are around 4.95 million people who are blind and at the same time70 million people who are partially visually impaired in India. Without vision, it becomes difficult for the blind people to find their way without encountering obstacles. Avoiding obstacles can be uncomfortable, clumsy, and inaccurate, even with aids such as walking sticks. People with vision or vision problems have to deal with multiple issues in their daily lives, as modern assistive devices often do not meet consumer needs in terms of price and level of support. Our project presents a new design of assistive glasses for the visually impaired person. It is intended to assist in multiple daily tasks utilizing a portable design format. The overall build cost is kept low by using a Raspberry Pi 4 single board computer for processing and a camera for image acquisition. Our proposed glasses use Machine Learning (ML) to extract information from images and verbally communicate what the wearer is seeing through the audio output. As a result, ML-enabled glasses enable blind and partially sighted users to find personal items at home, read documents at workplace, take public transportation without any overhead, recognize friends, and many more such applications, can make them more independent, freer, and more aware of their surroundings. We made use of YOLOv3 algorithm for object detection and got the accuracy of 94.3% and which was able to detect majority of the objects in the surroundings of the user.
Risks & Protective Factors for Depression & Suicide Among Hawai‘i Agricultural Producers

ABSTRACT Studies have consistently shown that agricultural producers in the continental United States have disproportionately high rates of depression and suicide as compared to other occupations. It is not known whether this is true in Hawaiʻi, which is both geographically distinct and ethnically diverse. To examine rates of depression and suicide as well as potential risk and protective factors, a state-wide mental health needs assessment was conducted from November 2021 to September 2022. We conducted a survey with a nonprobability-based convenience sample targeting agricultural producers across Hawaiʻi, and performed descriptive statistics and logistic regression analyses. In a sample of 408 respondents, 35% (n = 143) had clinical depression symptomatology, and 8% (n = 33) had suicidal ideation based on the Patient Health Questionnaire−9. Older age was slightly protective in that every year of increase in age was associated with 0.98 times (95% CI: 0.96, 0.99) reduced odds of depression symptomatology, and 0.96 times (95% CI:0.94, 0.98) reduced odds of suicidal ideation. Identifying as East Asian had 2.04 times (95% CI: 1.16, 3.61) higher odds of depression symptomatology, and Southeast Asian had 3.04 times odds (95% CI:1.15, 8.00) of suicidal ideation. However, in the presence of stress and coping variables, the demographic factors became statistically non-significant. Instead, feeling stressed, uncertainty as the stressor, and media-focused coping were significant risk factors in increasing two to eight times the odds of depressive symptoms. For suicidal ideation, depression symptomatology increased odds by 31.95 (95% CI: 5.60–182.32), using media-focused coping increased 5.20 odds (95% CI: 1.66, 16.27), but problem-focused coping decreased 0.32 times odds (0.10, 0.99). Culturally specific prevention and intervention measures should be tailored for Hawai‘i agricultural producers with an emphasis toward younger, East, and Southeast Asian producers and attention toward providing skillful coping strategies for effective stress regulation and management.
Toward Global Harmonization of Derived Cloud Products

Formerly known as the Cloud Retrieval Evaluation Workshop (CREW; see the list of acronyms used in this paper below) group (Roebeling et al. 2013, 2015), the International Cloud Working Group (ICWG) was created and endorsed during the 42nd Meeting of CGMS. The CGMS-ICWG provides a forum for space agencies to seek coherent progress in science and applications and also to act as a bridge between space agencies and the cloud remote sensing and applications community. The ICWG plans to serve as a forum to exchange and enhance knowledge on state-of-the-art cloud parameter retrievals algorithms, to stimulate support for training in the use of cloud parameters, and to encourage space agencies and the cloud remote sensing community to share knowledge. The ICWG plans to prepare recommendations to guide the direction of future research-for example, on observing severe weather events or on process studies-and to influence relevant programs of the WMO, WCRP, GCOS, and the space agencies.
Design and Validation of a Low-Cost Mobile EEG-Based Brain–Computer Interface

Objective: We designed and validated a wireless, low-cost, easy-to-use, mobile, dry-electrode headset for scalp electroencephalography (EEG) recordings for closed-loop brain–computer (BCI) interface and internet-of-things (IoT) applications. Approach: The EEG-based BCI headset was designed from commercial off-the-shelf (COTS) components using a multi-pronged approach that balanced interoperability, cost, portability, usability, form factor, reliability, and closed-loop operation. Main Results: The adjustable headset was designed to accommodate 90% of the population. A patent-pending self-positioning dry electrode bracket allowed for vertical self-positioning while parting the user’s hair to ensure contact of the electrode with the scalp. In the current prototype, five EEG electrodes were incorporated in the electrode bracket spanning the sensorimotor cortices bilaterally, and three skin sensors were included to measure eye movement and blinks. An inertial measurement unit (IMU) provides monitoring of head movements. The EEG amplifier operates with 24-bit resolution up to 500 Hz sampling frequency and can communicate with other devices using 802.11 b/g/n WiFi. It has high signal–to–noise ratio (SNR) and common–mode rejection ratio (CMRR) (121 dB and 110 dB, respectively) and low input noise. In closed-loop BCI mode, the system can operate at 40 Hz, including real-time adaptive noise cancellation and 512 MB of processor memory. It supports LabVIEW as a backend coding language and JavaScript (JS), Cascading Style Sheets (CSS), and HyperText Markup Language (HTML) as front-end coding languages and includes training and optimization of support vector machine (SVM) neural classifiers. Extensive bench testing supports the technical specifications and human-subject pilot testing of a closed-loop BCI application to support upper-limb rehabilitation and provides proof-of-concept validation for the device’s use at both the clinic and at home. Significance: The usability, interoperability, portability, reliability, and programmability of the proposed wireless closed-loop BCI system provides a low-cost solution for BCI and neurorehabilitation research and IoT applications.
Multiple micronutrient deficiencies alter energy metabolism in host and gut microbiome in an early-life murine model

Introduction Micronutrients perform a wide range of physiological functions essential for growth and development. However, most people still need to meet the estimated average requirement worldwide. Globally, 2 billion people suffer from micronutrient deficiency, most of which are co-occurring deficiencies in children under age five. Despite decades of research, animal models studying multiple micronutrient deficiencies within the early-life period are lacking, which hinders our complete understanding of the long-term health implications and may contribute to the inefficacy of some nutritional interventions. Evidence supporting the Developmental Origins of Health and Disease (DOHaD) theory demonstrates that early-life nutritional deficiencies carry life-long consequences mediated through various mechanisms such as abnormal metabolic programming, stunting, altered body composition, and the gut microbiome. However, this is largely unexplored in the multiple micronutrient deficient host. Methods we developed a preclinical model to examine undernutrition’s metabolic and functional impact on the host and gut microbiome early in life. Three-week-old weanling C57BL/6N male mice were fed a low-micronutrient diet deficient in zinc, folate, iron, vitamin A, and vitamin B12 or a control diet for 4-weeks. Results Our results showed that early-life multiple micronutrient deficiencies induced stunting, altered body composition, impaired glucose and insulin tolerance, and altered the levels of other micronutrients not depleted in the diet within the host. In addition, functional metagenomics profiling and a carbohydrate fermentation assay showed an increased microbial preference for simple sugars rather than complex ones, suggestive of a less developed microbiome in the low-micronutrient-fed mice. Moreover, we found that a zinc-only deficient diet was not sufficient to induce these phenotypes, further supporting the importance of studying co-occurring deficiencies. Discussion Together, these findings highlight a previously unappreciated role of early-life multiple micronutrient deficiencies in shaping the metabolic phenome of the host and gut microbiome through altered glucose energy metabolism, which may have implications for metabolic disease later in life in micronutrient-deficient survivors.
A novel approach in the WIMP quest: Cross-correlation of gamma-ray anisotropies and cosmic shear

The presence of large amounts of dark matter in the Universe is the expected source of two different cosmological effects: small gravitational distortions in the shapes of background galaxies (cosmic shear) and the cosmological emission of gamma rays. In fact, dark matter structures are responsible for the bending of light in the weak lensing regime, and those same cosmological objects can emit gamma-rays, either because they host astrophysical sources (active galactic nuclei or star-forming galaxies) or directly by dark matter annihilations or decays. Gamma-rays emission should therefore exhibit strong correlation with the cosmic shear signal. In this note we report on the computation of the cross-correlation angular power spectrum of cosmic shear and gamma-rays produced by the annihilation/decay of weakly interacting massive composing particle dark matter, as well as by astrophysical sources. We show that the shear/gamma-rays cross-correlation provides novel information on the composition of the extra-g.
Selective measurement of quantronium qubit states by using of mesoscopic non-linear oscillator

We study the process of selective measurements of states of individual quantum systems - Josephson qubit – using nonlinear oscillator, working in the mesoscopic regime, when the number of quanta in the measuring process varies from a few dozen to a few hundred. Quantum Monte-Carlo method simulated dissipative dynamics of the system "qubit - oscillator" and the measurement process of a qubit state to modify the number of quanta of the oscillator. It is shown that for different Rabi-pulses of the recording state of a qubit the discrimination of states is possible, as well as the measurement of the effect of back-action of the measuring device, including separation of the prepared superposition state – carrying out statistical projective measurements.
Cyberbullying in the Metaverse: A Prescriptive Perception on Global Information Systems for User Protection

The emergence of the metaverse, a virtual reality space, has ushered in a new era of digital experiences and interactions in global information systems. With its unique social norms and behaviors, this new world presents exciting opportunities for users to connect, socialize, and explore. However, as people spend more time in the metaverse, it has become increasingly apparent that the issue of cyberbullying needs to be addressed. Cyberbullying is a serious problem that can harm victims psychologically and physically. It involves using technology to harass, intimidate, or humiliate individuals or groups in global information systems. The risk of cyberbullying is high in the metaverse, where users are often anonymous. Therefore, it is crucial to establish a safer and more respectful culture within the metaverse to detect and prevent such incidents from happening.
A Comparative Study between Extended Kalman Filter and Unscented Kalman Filter for Traffic State Estimation

This paper presents a freeway traffic state estimation and METANET traffic flow model. Since the environmental conditions on a freeway may change over time (e.g., changing weather conditions), parameter estimation is also considered. This paper also provides the introduction to Extended Kalman filter and Unscented Kalman filter. We compare the performance of the extended Kalman filter and the unscented Kalman filter for state estimation, parameter estimation, joint estimation and dual estimation. Furthermore, the performance is evaluated for different detector configurations.
Adomian decomposition method for solving the population dynamics model of two species

Adomian decomposition method has been a powerful method to solve differential equations. In this paper, we propose the method to solve the population dynamics model of two species for mutualism, parasitism, and competition. These three scenarios are considered for the completion of our research. Adomian decomposition method uses initial values of the unknowns and provides series of approximate solutions to the problem. We obtain that the Adomian decomposition method provides fast computation for the solution.