Miracle-dz/UniFAR-FTUs huggingface dataset:
The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. We show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open‐source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large‐scale fire experiment in the Brazilian Amazon region. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape‐level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top‐of‐the‐canopy information (e.g. canopy height models based on LiDAR data). By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.
High-spatial-resolution remote sensing image segmentation using adaptive watershed-driven joint MDEDNet

Abstract When segmenting high-spatial-resolution remote sensing images using convolution neural networks, it is difficult to balance the number of segmented regions against the contour accuracy. This article proposes a segmentation method that combines the minimum area adaptive watershed transform based on morphological reconstruction with the modified deep edge detection network (MDEDNet). First, the minimum area adaptive watershed algorithm is adopted to reconstruct the gradient features of the image and perform watershed segmentation, giving the initial segmentation results. A ground object contour optimization method and MDEDNet are then used to further improve the accuracy of the segmentation, resulting in the final segmented image. Experiments on image sets of varying complexity indicate that the algorithm proposed in this article can achieve accurate image segmentation with good segmentation results and fast operation efficiency.
“I Don’t want to Commit Academic Dishonesty”: the Role of Grit and Growth Mindset in Reducing Academic Dishonesty

Online learning is a substitute for learning in the classroom during a global pandemic. The problem that arises is that academic dishonesty behavior increases when online learning takes place. We assess how academic dishonesty occurs during online learning. Purpose. We examine how academic dishonesty occurs during online learning. We review unethical behavior based on growth mindset and Grit as mediator variables. Materials and methods. The questionnaire was filled out by 266 students (196 female; 70 male) from universities in Indonesia. Data collection uses three scales, namely the academic dishonesty scale (α = 0.862), the growth mindset scale (α = 0.826), and the grit scale (α = 0.760). The path analysis using the multiple linear regression techniques was utilized to analyze the data in this study. Results. This study demonstrates a negative correlation between growth mindset and academic dishonesty, indicating that the more growth mindset, the less academic dishonesty. Additionally, there is a considerable negative correlation between Grit and academic dishonesty, such that the greater a person’s Grit, the less academic dishonesty there is. Additionally, a positive correlation exists between the growth mindset and Grit. The greater one’s growth attitude, the greater one’s Grit. The primary finding is that Grit mediates the growth mindset’s attitude toward academic dishonesty, implying that the growth mindset affects academic dishonesty by Grit. Conclusions. The conclusion is that the growth mindset acts as a buffer against academic dishonesty. However, Grit’s position is ideal for mediating the association between growth mindset and academic dishonesty. Thus, a growth mindset can boost students’ Grit, which can help prevent academic dishonesty. We reviewed recommendations for decreasing unethical behavior in online education and its consequences for higher education.
Comparison of oxygenated flow patterns in diabetic foot ulcers subjects and controls in response to breath holding

Approximately 34% of people with diabetes will experience a diabetic foot ulcer (DFU) at some point throughout their lifetime. The perfusion of oxygen to the DFU is critical for promoting wound healing and closure. However, complications from diabetes can compromise the oxygenated flow to the wound site. Techniques such as transcutaneous oximetry and laser Doppler imaging have been used to assess perfusion to DFUs at discrete point-locations in the peri-wound. Widearea measurements of temporal oxygenation changes, as an indirect measure of perfusion, can provide additional insight of the oxygenated flow in the (peri-)wound and background tissue. Herein, our objective is to assess the differences in oxygenation flow patterns in and around the DFU regions and in the feet of control subjects as a potential biomarker for monitoring wound healing. Breath-holding (BH), as a stimulus, holds the potential to induce oxygenated flow pattern changes in the presence of wounds. In this study, 10 DFU and 3 control subjects were imaged using a hand-held nearinfrared optical scanner (NIROS). Spatial-temporal oxygenation maps of hemoglobin-based parameters were acquired across an 120-second paradigm with 20 seconds of breath-hold. The oxygenation flow patterns obtained from Pearson'sbased correlation maps across controls, healing DFU, and non-healing DFU indicated that flow patterns varied distinctly. Ongoing work is to correlate oxygenated flow patterns to clinical assessment of healing status in DFUs.
NATURAL SCIENCE AND GENERAL EDUCATION COURSES PLANNING AT THE TIME OF INTRODUCTON OF THE NEW FEDERAL EDUCATIONAL STANDARDS IN RUSSIA

The article presents an experience of educational courses planning and technologies of it realization considering level and type of training at the time of new educational standards introduction in Russia. The research was conducted on the basis of specially developed questionnaire, the experimental educational courses and programs observation, the study of existing teachers experience, that permitted to develop methodical recommendations, didactic and experimental supplies. It reveals that planning of educational course within the framework of educational module and student’s competence forming approaches in accordance with the requirements of The Federal State Educational Standards (FSES), is accompanied with the range of difficulties. They are: determination of the course related to the formation of certain required competences; defining the content of the modules; establishing of inter subject connections (preliminary, parallel, and subsequent); strengthening of student’s vocational determination (professional abilities development of the future employee).
Study on Application of Two New Types of Piezoelectric Actuators to the Vibration Control

The applications of two novel bending piezoelectric actuators,that is the arching PZT patch actuator (APA) andⅡ(pi)shape PZT stack actuator(PISA),to the vibration control have been studied in this paper.The relational expressions between the actuating moment and the driving voltage of the these two actuators have also been presented.The relational expressions have been applied to the first-order bending(first bending) and the first-order torsion(first torsion) mode response in a fin model.The state space model of this piezoelectric active vibration control system has been established by the thermal analogy modeling method.Linear quadratic regulator(LQR) control algorithm was used to design the controller.Loop simulation of the active vibration control system was conducted and the results demonstrateed that APA show better performance than PISA in the vibration control of the first bending and torsion modes control of the fin model.
Estimating urban functional distributions with semantics preserved POI embedding

Abstract We present a novel approach for estimating the proportional distributions of function types (i.e. functional distributions) in an urban area through learning semantics preserved embeddings of points-of-interest (POIs). Specifically, we represent POIs as low-dimensional vectors to capture (1) the spatial co-occurrence patterns of POIs and (2) the semantics conveyed by the POI hierarchical categories (i.e. categorical semantics). The proposed approach utilizes spatially explicit random walks in a POI network to learn spatial co-occurrence patterns, and a manifold learning algorithm to capture categorical semantics. The learned POI vector embeddings are then aggregated to generate regional embeddings with long short-term memory (LSTM) and attention mechanisms, to take account of the different levels of importance among the POIs in a region. Finally, a multilayer perceptron (MLP) maps regional embeddings to functional distributions. A case study in Xiamen Island, China implements and evaluates the proposed approach. The results indicate that our approach outperforms several competitive baseline models in all evaluation measures, and yields a relatively high consistency between the estimation and ground truth. In addition, a comprehensive error analysis unveils several intrinsic limitations of POI data for this task, e.g. ambiguous linkage between POIs and functions.
Review of graphene for the generation, manipulation, and detection of electromagnetic fields from microwave to terahertz

Graphene has attracted considerable attention ever since the discovery of its unprecedented properties, including its extraordinary and tunable electronic and optical properties. In particular, applications within the microwave to terahertz frequency spectrum can benefit from graphene’s high electrical conductivity, mechanical flexibility and robustness, transparency, support of surface-plasmon-polaritons, and the possibility of dynamic tunability with direct current to light sources. This review aims to provide an in-depth analysis of current trends, challenges, and prospects within the research areas of generating, manipulating, and detecting electromagnetic fields using graphene-based devices that operate from microwave to terahertz frequencies. The properties of and models describing graphene are reviewed first, notably those of importance to electromagnetic applications. State-of-the-art graphene-based antennas, such as resonant and leaky-wave antennas, are discussed next. A critical evaluation of the performance and limitations within each particular technology is given. Graphene-based metasurfaces and devices used to manipulate electromagnetic fields, e.g. wavefront engineering, are then examined. Lastly, the state-of-the-art of detecting electromagnetic fields using graphene-based devices is discussed.
Loss and Efficiency Comparisons of Four type SynRMs Using Preisach Models and Experimental Verification

This paper presents the loss and efficiency evaluations of synchronous reluctance motors (SynRM) with permanent magnet assisted (PMA), non-PMA and concentrated winding (CW), distributed winding (DW) by finite element method (FEM) and experiment. In this paper, the performance characteristic is compared according to the stator and rotor types in SynRM. In addition, the efficiency evaluation is also compared including hysteresis loss, copper loss, other loss on the basis of rated load condition.
“Expecting children to be dragons” in an east asian context: Parental expectations of children choosing a career in the public sector

ABSTRACT In East Asia, where a culture of submission to authority dominates, parental expectations significantly influence children’s career choices. A recent empirical study conducted in Taiwan shows that children are more inclined to pursue a public service career when influenced by their parents’ expectations. The present study asks two questions: why do parents in East Asia expect children to secure a career in public service? Is it a result of social pressure, parents’ own values, their socio-economic status, or all of these possible reasons? The present study uses data collected in Taiwan to answer these questions. Our findings broaden the current knowledge base of parental socialisation and its effect on children’s preference for public sector careers.
Enhancing Locomotor Learning With Transcutaneous Spinal Electrical Stimulation and Somatosensory Augmentation: A Pilot Randomized Controlled Trial in Older Adults

This study investigated locomotor learning of a complex terrain walking task in older adults, when combined with two adjuvant interventions: transcutaneous spinal direct current stimulation (tsDCS) to increase lumbar spinal cord excitability, and textured shoe insoles to increase somatosensory feedback to the spinal cord. The spinal cord has a crucial contribution to control of walking, and is a novel therapeutic target for rehabilitation of older adults. The complex terrain task involved walking a 10-meter course consisting of nine obstacles and three sections of compliant (soft) walking surface. Twenty-three participants were randomly assigned to one of the following groups: sham tsDCS and smooth insoles (sham/smooth; control group), sham tsDCS and textured insoles (sham/textured), active tsDCS and smooth insoles (active/smooth), and active tsDCS and textured insoles (active/textured). The first objective was to assess the feasibility, tolerability, and safety of the interventions. The second objective was to assess preliminary efficacy for increasing locomotor learning, as defined by retention of gains in walking speed between a baseline visit of task practice, and a subsequent follow-up visit. Variability of the center of mass while walking over the course was also evaluated. The change in executive control of walking (prefrontal cortical activity) between the baseline and follow-up visits was measured with functional near infrared spectroscopy. The study results demonstrated feasibility based on enrollment and retention of participants, tolerability based on self-report, and safety based on absence of adverse events. Preliminary efficacy was supported based on trends showing larger gains in walking speed and more pronounced reductions in mediolateral center of mass variability at the follow-up visit in the groups randomized to active tsDCS or textured insoles. These data justify future larger studies to further assess dosing and efficacy of these intervention approaches. In conclusion, rehabilitation interventions that target spinal control of walking present a potential opportunity for enhancing walking function in older adults.
ProRes: Proactive re-selection of materialized views

Materialized View Selection is one of the most studied problems in the database field, covering SQL and NoSQL technologies as well as different deployment infrastructures (centralized, parallel, cloud). This problem has become more complex with the arrival of data warehouses, being coupled with the physical de sign phase that aims at optimizing query performance. Selecting the best set of materialized views to optimize query performance is a challenging task. Given their importance and the complexity of their selection, several research efforts both from academia and industry have been conducted. Results are promising - some solutions are being implemented by commercial and open-source DBMSs -, but they do not factor in the following properties of nowadays analytical queries: (i) large scale queries, (ii) their dynamicity, and (iii) their high interaction. Studies to date fail to consider that complete set of properties. Considering the three properties simultaneously is crucial regarding today? s analytical requirements, which involve dynamic and interactive queries. In this paper, we first present a concise state of the art of the materialized view selection problem (VSP) by analyzing its ecosystem. Secondly, we propose a proactive re-selection approach that considers the three properties concurrently. It features twomain phases: offline and online. In the offline phase, we manage a set of the first queries based on a given threshold _ by selecting materialized views through a hypergraph structure. The second phase manages the addition of new queries by scheduling them, updates the structure of the hypergraph, and selects new views by eliminating the least beneficial ones. Finally, extensive experiments are conducted using the Star Schema Benchmark data set to evaluate the effectiveness and efficiency of our approach.
Segmenting quantitative phase images of neurons using a deep learning model trained on images generated from a neuronal growth model

Morphological changes in neurons are closely related to neurological disorders. Quantitative Phase Imaging (QPI) has been used to assess neuronal changes over time, using mass-sensitive contrast to quantitatively track network growth. QPI requires high quality segmentation of neurons in order to measure neuron cell body and neurite mass distributions. Neural networks are the state of the art for segmentation, but require thousands of images in order to generalize well. However, recent work on network functionality has shown that networks generalize by learning simple functions. Whether low data complexity hinders this has yet to be seen. Here we test this by simulating low complexity data, specifically, QPI images of neurons simulated using a neuronal growth model. We show segmentation results for feeding the network lab-acquired data.
Anchoring Apparatus of Long Head of the Biceps Tendon: Ultrasonographic Anatomy and Pathologic Conditions

The long head of the biceps tendon (LHBT) has been recognized as an important generator of anterior shoulder pain, causing a significant reduction in the shoulder flexion range. Various tendinous and ligamentous structures form the anchoring apparatus of the LHBT along its course to maintain its appropriate location during shoulder movements, including the coracohumeral ligament (CHL), superior glenohumeral ligament (SGHL), subscapularis (SSC) tendon and supraspinatus (SSP) tendon as well as the less recognized tendons of pectoralis major (PM), latissimus dorsi (LD) and teres major (TM). Lesions of this stabilizing apparatus may lead to an instability of the LHBT, resulting in pain at the anterior shoulder. Ultrasonography (US) has been increasingly used in the assessment of shoulder injuries, including the anchoring apparatus of the LHBT. An accurate diagnosis of these injuries is often challenging, given the complex anatomy and wide spectrum of pathologies. In this review article, US anatomy and common pathologic conditions that affect the anchoring apparatus of the LHBT are discussed, including biceps pulley lesions, adhesive capsulitis, chronic pathology of SSC and SSP tendons, tears in the PM tendon and injuries to the LD and TM. Knowledge of a normal anatomy, an appropriate scanning technique and US findings of common pathologic conditions are the keys to accurate diagnoses.
Salting Reduces Mercury Concentrations in Odontocete Muscle Tissue

Abstract High mercury (Hg) concentrations in seafood present a major global public health concern, especially in regions heavily dependent upon seafood like the Caribbean. Tissues from predatory fishes and other high trophic-level marine organisms such as odontocetes (toothed whales and dolphins) are often elevated in mercury, owing to biomagnification. We investigated whether salting reduces the total mercury (THg) concentration in muscle tissue from odontocetes (“blackfish”) taken for human consumption in St. Vincent and the Grenadines. Muscle from 21 odontocetes was coated in table salt or sea salt and dried for one, three, or seven days, after which the THg concentration in each sample was determined and compared to the THg concentration in the corresponding unsalted control. Every salted sample had a lower THg concentration than the unsalted control (mean decrease = 29.4%). There was no difference in the effectiveness of table salt versus sea salt at reducing the THg concentration. Our results show that, while salting successfully removed Hg, only 11% of samples had a methylmercury (MeHg) concentration below the World Health Organization's 1.0 µg/g wet weight advisory level, indicating that consuming odontocete muscle still poses a risk to human health—though that risk may be reduced by the application of salt during drying. The method that we present here may also be applicable to tissues from other marine species with lower initial THg concentrations and may be effective at rendering those tissues safer for human consumption.
28-nm FD-SOI CMOS Submilliwatt Ring Oscillator-Based Dual-Loop Integer-N PLL for 2.4-GHz Internet-of-Things Applications

This article presents a 2.4-GHz low-power compact integer-<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> ring oscillator-based phase-locked loop (PLL) for Internet of Things (IoT) applications. The proposed integer-<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> PLL is based on a dual loop Offset-PLL topology to achieve a fine frequency resolution similar to conventional fractional-<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> PLL. Not using a delta-sigma modulator (DSM) allows an expanded PLL bandwidth without deteriorating the overall noise performance. Implemented in 28 nm CMOS fully depleted silicon on insulator (FD-SOI) technology, the proposed architecture requires a 22-MHz internal reference frequency while achieving a 2-MHz frequency resolution and a 3-MHz PLL bandwidth. Measured prototypes perform −43.9 dBc reference spur, as an average value over all the bluetooth low energy (BLE) band and numerous tested dies, a jitter Figure-of-Merit of −229.6 dB for a power consumption of 0.87 mW and a core area of 0.0256 mm<sup>2</sup>.