Miracle-dz/UniFAR-FTUs huggingface dataset:
A Mixed Property-Based Automatic Shadow Detection Approach for VHR Multispectral Remote Sensing Images

Shadows in very high-resolution multispectral remote sensing images hinder many applications, such as change detection, target recognition, and image classification. Though a wide variety of significant research has explored shadow detection, shadow pixels are still more or less omitted and are wrongly confused with vegetation pixels in some cases. In this study, to further manage the problems of shadow omission and vegetation misclassification, a mixed property-based shadow index is developed for detecting shadows in very high-resolution multispectral remote sensing images based on the difference of the hue component and the intensity component between shadows and nonshadows, and the difference of the reflectivity of the red band and the near infrared band between shadows and vegetation cover in nonshadows. Then, the final shadow mask is achieved, with an optimal threshold automatically obtained from the index image histogram. To validate the effectiveness of our approach for shadow detection, three test images are selected from the multispectral WorldView-3 images of Rio de Janeiro, Brazil, and are tested with our method. When compared with other investigated standard shadow detection methods, the resulting images produced by our method deliver a higher average overall accuracy (95.02%) and a better visual sense. The highly accurate data show the efficacy and stability of the proposed approach in appropriately detecting shadows and correctly classifying shadow pixels against the vegetation pixels for very high-resolution multispectral remote sensing images.
Measuring Health-Related Quality of Life in Thyroid Eye Disease

Abstract Health-related quality of life (HQOL) is a concept that aims to understand the totality of an individual’s experience of their disease state. This can include the physical, psychosocial, emotional, and psychological effects of a disease state. A complex and multifactorial concept, HQOL can be challenging to measure accurately and reliably. Thyroid eye disease (TED), as a multifaceted physically debilitating and facial disfiguring disorder, presents unique challenges and opportunities in the measurement of HQOL. Multiple distinct tools have been developed for this purpose, each has been constructed, assessed, and utilized. This discussion surveys the landscape of TED-related QOL measurement and presents challenges for the future. Clinicians and clinical researchers should implement TED-related QOL measurement as part of routine TED care and as a primary outcome in TED clinical trials. We recommend utilizing the Graves’ ophthalmopathy (GO)-QOL routinely in clinical practice and as a primary outcome in TED clinical trials. If the GO-QOL is too time-consuming or in mild TED, a faster alternative is the TED-QOL.
Identification of Novel Regulators of Radiosensitivity Using High-Throughput Genetic Screening

The biological impact of ionizing radiation (IR) on humans depends not only on the physical properties and absorbed dose of radiation but also on the unique susceptibility of the exposed individual. A critical target of IR is DNA, and the DNA damage response is a safeguard mechanism for maintaining genomic integrity in response to the induced cellular stress. Unrepaired DNA lesions lead to various mutations, contributing to adverse health effects. Cellular sensitivity to IR is highly correlated with the ability of cells to repair DNA lesions, in particular coding sequences of genes that affect that process and of others that contribute to preserving genomic integrity. However, accurate profiling of the molecular events underlying individual sensitivity requires techniques with sensitive readouts. Here we summarize recent studies that have used whole-genome analysis and identified genes that impact individual radiosensitivity. Whereas microarray and RNA-seq provide a snapshot of the transcriptome, RNA interference (RNAi) and CRISPR-Cas9 techniques are powerful tools that enable modulation of gene expression and characterizing the function of specific genes involved in radiosensitivity or radioresistance. Notably, CRISPR-Cas9 has altered the landscape of genome-editing technology with its increased readiness, precision, and sensitivity. Identifying critical regulators of cellular radiosensitivity would help tailor regimens that enhance the efficacy of therapeutic treatments and fast-track prediction of clinical outcomes. It would also contribute to occupational protection based on average individual sensitivity, as well as the formulation of countermeasures to the harmful effects of radiation.
Interacitve motion planning among decision-making agents

T dissertation is concerned with safe robotic navigation in cluttered, dynamic and (un-)structured environments – amid other decisionmaking agents. As such, it follows an important trend that aims to bring robots from factory and laboratory settings into our everyday living spaces. From the navigation side this calls for collision-aware systems which respect system and environmental constraints and which are able to plan and perform highly complex maneuvers in constrained areas online. In line with these requirements, this dissertation proposes a comprehensive optimization framework that retains its vast scope through a restriction of robot physiologies considered – namely to holonomic robots (i.e. integrators of arbitrary order) and simple, non-holonomic systems (i.e. kino-dynamic unicycles and bicycles). The exposition of this work is structured into three main parts that survey system-compliance, interactive search, and safety properties, respectively. In the first part, a global graph-based approach to system-compliant planning is developed. The approach is built around traditional graph search principles, which confer some desirable characteristics (such as deterministic (sub-)optimality guarantees and resolution completeness) to the solution and enable online operation among hard obstacles at the same time. Located at the heart of this approach is a method suitable for designing systemcompliant graph structures. Its output forms a lattice in state-space that satisfies C2-continuity and may be adequately tracked by a large share of practically relevant robot types, including differential-drive robots, cars, simple airplanes, helicopters, and boats. The approach is suitable for global motion planning in static or fully predictable environments, where strict requirements on tracking behavior need to be enforced. Conversely, it faces difficulties among decision-making agents, as interaction effects are not directly modeled and thus need to be compensated for via re-planning.
Dietary Exposure to United States Food and Drug Administration-Approved Synthetic Food Colors in Children, Pregnant Women, and Women of Childbearing Age Living in the United States

The Food and Drug Administration (FDA) regulates artificial food colors (AFCs) in the United States. Exposure to AFCs has raised concerns about adverse behavioral effects in children. We quantified AFC exposure in women of childbearing age, pregnant women, and children and compared them to FDA and World Health Organization acceptable daily intakes (ADIs). We estimated the “typical” and “high” single-day and two-day average dietary exposure to each AFC (mg/kg/day) based on laboratory measurements and food consumption data from the 2015–2016 National Health and Nutrition Examination Survey (NHANES). We also examined whether AFC intake differed by income, education, and ethnicity. Exposure tended to be higher in children and the highest AFC exposure was found for Red No. 40. Children’s mean and 95th percentile FD&C Red No. 3 estimated intakes exceeded the ADIs in some instances. Juice drinks, soft drinks, icings, and ice cream cones were major foods contributing to children’s (<16 years old) AFC exposure. AFC intake was higher in participants with lower incomes and education and of African American ethnicity. The findings indicate widespread AFC exposure including in very young children. Research is needed on the sociodemographic determinants of exposure and AFC toxicokinetics to better describe the absorption and organ-specific exposure.
Chemical Composition of Kombucha

Kombucha is a fermented sweetened tea with a mixed fermenting culture of yeast and acetic acid bacteria. While the history of kombucha is not completely clear, it is now available around the world and has shown an increase in availability and demand in the United States market. The proponents of kombucha consumption tout the varied health benefits it can provide. The final kombucha flavor and composition is a function of both the initial tea used and the fermentation process. While the ascribed benefits are varied and numerous, the number of direct studies has been limited. This review focuses on the current state of understanding of the chemical composition and the potential health effects both positive and negative reported in the literature.
Female Cuckoo Calls Deceive Their Hosts by Evoking Nest-Leaving Behavior: Variation under Different Levels of Parasitism

Simple Summary Obligate brood parasite birds such as the common cuckoo (Cuculus canorus) can trick their hosts via a variety of means. Cuckoos are threats to the host nests but not to the host adults themselves. To successfully parasitize the host nests, female cuckoos have been hypothesized to distract the hosts’ attention from their nests by mimicking the calls of sparrowhawks (Accipiter nisus), a predator of the hosts. We performed playback experiments in two populations of the host oriental reed warbler (Acrocephalus orientalis) that have experienced different levels of parasitic pressure. We found that female cuckoo calls evoked both populations of the hosts to leave their nests more frequently than did the calls of male cuckoos or doves that do not pose threats to the hosts. This indicated that the call of the female cuckoo functions to deceive the host and thus favors host brood parasitism. However, we propose that such a deceiving effect of the female cuckoo call is due to the rapid cadence of the call rather than sparrowhawk mimicry. Abstract The common cuckoo (Cuculus canorus) is an obligate brood parasite that has evolved a series of strategies to trick its hosts. The female cuckoo has been hypothesized to mimic the appearance and sounds of several raptors to deceive the hosts into exhibiting anti-predator behavior. Such behavior would relax the protection of the host nest and thus allow the female cuckoo to approach the host nest unopposed. Many anti-parasite strategies have been found to vary among geographical populations due to different parasitic pressures from cuckoos. However, the effect of female cuckoo calls related to different levels of parasitic pressure has not been examined. Here, we studied the effect of female cuckoo calls on the oriental reed warbler (Acrocephalus orientalis), one of the major hosts of the common cuckoo, in two geographical populations experiencing different levels of parasite pressure. Four kinds of sounds were played back to the hosts: the calls from female common cuckoos, male common cuckoos, sparrowhawks (Accipiter nisus), and oriental turtle doves (Streptopelia orientalis). The results showed that the female cuckoo calls induced the hosts to leave their nests more frequently than the male cuckoo or dove calls in both populations, and two populations of the hosts reacted similarly to the female cuckoo calls, implying that the function of female cuckoo calls would not be affected by the difference in parasitism rate. This study indicates that female cuckoo calls function to distract the hosts’ attention from protecting their nests. However, we propose that such a deception by the female cuckoo call may not be due to the mimicry of sparrowhawk calls, but rather that the rapid cadence of the call that causes a sense of anxiety in the hosts.
Overexpression of the Arabidopsis MACPF Protein AtMACP2 Promotes Pathogen Resistance by Activating SA Signaling

Immune response in plants is tightly regulated by the coordination of the cell surface and intracellular receptors. In animals, the membrane attack complex/perforin-like (MACPF) protein superfamily creates oligomeric pore structures on the cell surface during pathogen infection. However, the function and molecular mechanism of MACPF proteins in plant pathogen responses remain largely unclear. In this study, we identified an Arabidopsis MACP2 and investigated the responsiveness of this protein during both bacterial and fungal pathogens. We suggest that MACP2 induces programmed cell death, bacterial pathogen resistance, and necrotrophic fungal pathogen sensitivity by activating the biosynthesis of tryptophan-derived indole glucosinolates and the salicylic acid signaling pathway dependent on the activity of enhanced disease susceptibility 1 (EDS1). Moreover, the response of MACP2 mRNA isoforms upon pathogen attack is differentially regulated by a posttranscriptional mechanism: alternative splicing. In comparison to previously reported MACPFs in Arabidopsis, MACP2 shares a redundant but nonoverlapping role in plant immunity. Thus, our findings provide novel insights and genetic tools for the MACPF family in maintaining SA accumulation in response to pathogens in Arabidopsis.
The Landscape of Robinson Crusoe in China: A Bibliometric Analysis

Daniel Defoe’s novel The Life and Strange Surprising Adventures of Robinson Crusoe has an everlasting impact in China since its first entrance in Cantonese in 1902. Now, it has become a Robinson Crusoe industry in the publishing sector. This paper attempts to give quantitative evidence from bibliometrics to examine its popularity in China. The data collected are based on all articles published in authoritative CSSCI journals from its inception (1999) to January 2021. We also retrieved Robinson Crusoe results from the National Library Reference Alliance and e-commerce China Dangdang to identify its popular Chinese versions. Five themes are concerned with this novel: comparative literature, economic analysis, translation studies, communication, and philosophical thinking. The study has articulated that Robinson Crusoe’s publications in China have increased significantly since the novel was designated as a topic related to China’s National College Entrance Examination in 2018. Hence, rewriting Robinson Crusoe for teenagers has been a driver for a wide readership, which accordingly makes its translation much embraced in the Chinese world due to the recent statistics.
Application of Road Extraction from High-Resolution Remote Sensing Images in Tourism Navigation and GIS

In order to quickly and accurately obtain and process road information and its damage information, to obtain better tourism navigation experience and accurate geographic information, this paper proposes a road extraction method based on high-resolution remote sensing images. Based on the known road width information and the analysis of the gray-scale characteristics of the road surface, the method takes the road center line and straight line in the image as the center line and then deduces the road edge line information, so as to extract the edge information. Then, through the image de redundancy information processing, the final obtained road width parameters are compared to verify the accuracy and reliability of the method. The experiment shows that the road information can be extracted accurately, and the extraction accuracy and efficiency have been significantly improved, reaching more than 90%, and can directly reflect the road edge line, median line, and width information. Conclusion. The road extraction method based on high-resolution remote sensing images can effectively and accurately extract road information, obtain better tourism navigation experience, and accurate geographic information.
Comprehensive Assessment of Acute Isolated or Prominent Dysarthria in the Emergency Department: A Neuro-Emergency Expert’s Experience beyond Stroke

We investigated the clinical characteristics, neuroimaging findings, and final diagnosis of patients with acute isolated or prominent dysarthria who visited the emergency department (ED) between 1 January 2020 and 31 December 2021. Of 2028 patients aged ≥ 18 years with neurologic symptoms treated by a neuro-emergency expert, 75 with acute isolated or predominant dysarthria within 1 week were enrolled. Patients were categorized as having isolated dysarthria (n = 28, 37.3%) and prominent dysarthria (n = 47, 62.7%). The causes of stroke were acute ischemic stroke (AIS) (n = 37, 49.3%), transient ischemic attack (TIA) (n = 14, 18.7%), intracerebral hemorrhage (n = 1, 1.3%), and non-stroke causes (n = 23, 30.7%). The most common additional symptoms were gait disturbance or imbalance (n = 8, 15.4%) and dizziness (n = 3, 13.0%) in the stroke and non-stroke groups, respectively. The isolated dysarthria group had a higher rate of TIA (n = 7, 38.9%), single and small lesions (n = 10, 83.3%), and small-vessel occlusion in Trial of Org 101072 in acute stroke treatment (n = 8, 66.7%). Acute isolated or prominent dysarthria in the ED mostly presented as clinical symptoms of AIS, but other non-stroke and medical causes were not uncommon. In acute dysarthria with ischemic stroke, multiple territorial and small and single lesions are considered a cause.
Feedlot Factors Influencing the Incidence of Dark Cutting in Australian Grain-Fed Beef

Simple Summary This study was conducted to investigate feedlot factors that influence the incidence of dark cutting in Australian grain-fed beef. Awareness of factors influencing dark cutting within the supply chain will enable the implementation of management strategies to manage dark cutting risk and reduce incidence. The reduction of dark cutting incidence will increase feedlot productivity as well as profitability across the entire supply chain. Abstract It has been well-established that dark cutting (DC) is a multifactorial issue that is associated with numerous animal and management factors. However, there is limited understanding of the feedlot-based factors that contribute to the influence of DC. The aim of this study was to evaluate the effect of climate, animal, and feedlot factors on the incidence of pH non-compliance in Australian grain-fed cattle. For this study, feedlot and abattoir records from 142,228 individual cattle over a 1-year period were investigated. These data incorporated records from seven feedlots that consigned cattle to three abattoirs. The average incidence of DC in these carcasses was 2.8%. The production factors that were associated with increased risk of DC included feedlot, sex, hormone growth promotants (HGP), cattle health, and days on feed (DOF). Additionally, DC also increased by reduced solar radiation (SR, W/m2), lower wind speeds (WS, m/s), increased ambient temperature (TA, °C), higher rainfall, a higher average temperature–humidity index (THI), and increased duration of time above heat-load-index threshold of 86 (HLI ≥ 86) during the 7 days prior to feedlot departure. This study identified the feedlot factors that increase the risk of DC from a feedlot-management perspective.
Bayesian and non‐Bayesian inference of Weibull lifetime model based on partially observed competing risks data under unified hybrid censoring scheme

In this paper, a competing risk model is analyzed based on unified hybrid censoring scheme (UHCS). It is assumed that the latent failure times follow Weibull distributions with a common shape and different scale parameters. The maximum likelihood estimates (MLEs) and approximate confidence intervals (ACIs) of the distributional parameters are obtained. Sufficient conditions under which the MLEs exist (uniquely) have been studied. Further, the Bayes estimates are obtained with respect to symmetric and asymmetric loss functions. The non‐informative and informative prior distributions are considered for computing the approximate Bayes estimates. Furthermore, the highest posterior density (HPD) credible intervals have been obtained by using Markov Chain Monte Carlo (MCMC) method with the Gibbs sampling technique. The coverage probabilities for each confidence interval are computed. Then, hypothesis testing has been implemented using likelihood ratio statistic. A Monte Carlo simulation study is carried out to compare the performance of the proposed estimates. Finally, two real data sets are provided to illustrate the estimates.
The Role of Machine Learning and the Internet of Things in Smart Buildings for Energy Efficiency

Machine learning can be used to automate a wide range of tasks. Smart buildings, which use the Internet of Things (IoT) to connect building operations, enable activities, such as monitoring temperature, safety, and maintenance, for easier controlling via mobile devices and computers. Smart buildings are becoming core aspects in larger system integrations as the IoT is becoming increasingly widespread. The IoT plays an important role in smart buildings and provides facilities that improve human security by using effective technology-based life-saving strategies. This review highlights the role of IoT devices in smart buildings. The IoT devices platform and its components are highlighted in this review. Furthermore, this review provides security challenges regarding IoT and smart buildings. The main factors pertaining to smart buildings are described and the different methods of machine learning in combination with IoT technologies are also described to improve the effectiveness of smart buildings to make them energy efficient.
Low-Frequency Extrapolation of Prestack Viscoacoustic Seismic Data Based on Dense Convolutional Network

Low-frequency information in seismic data can improve seismic resolution and imaging accuracy, enhance the quality of inversion, and play an essential role in imaging algorithms such as full-waveform inversion (FWI). Sufficiently low-frequency data can avoid the cycle skipping phenomenon during FWI. During seismic data processing, the protection and reconstruction for low-frequency information are therefore of great importance. In this article, we systematically investigate the extrapolation of prestack viscoacoustic seismic low-frequency data using a dense convolutional network (DenseNet) to effectively establish the nonlinear relationship between high- and low-frequency data and realize the extrapolation and reconstruction of viscoacoustic 0–5-Hz low-frequency data using 5–30-Hz high-frequency component. The generalizability of the method for different influencing factors such as wavelets, noise, and models is analyzed using the Marmousi2 velocity model forward data. It is demonstrated that the method has high robustness and can be applied to different situations, and the accuracy is higher than that of the traditional convolutional neural network (CNN) method. The feasibility of the low-frequency extrapolation method based on DenseNet is also verified by synthetic data, physical experiment simulation data, and field data testing and is superior to the traditional CNN method.