Miracle-dz/UniFAR-FTUs huggingface dataset:
EVALUATION OF AN UNMANNED AERIAL VEHICLE (UAV) FOR MEASURING AND MONITORING NATURAL DISASTER RISK AREAS

Abstract. This work presents an evaluation of a small UAV-RPAS-PPK to be used in the generation of digital surface models (DSM), without the need for control points, having as main application the monitoring of disaster risk areas (landslide and flooding). The areas to be measured are difficult to access, which prevents or makes access to the land difficult. In this evaluation, a study area of approximately 13 km2 was flown over, an average pixel of 11.6 cm and a total of 417 photos. The equipment used to acquire the images was a SenseFly eBee X, equipped with GNSS PPK for Direct Georeferencing (DG) and a camera model S.O. D.A. In all, 42 ground checkpoints were measured using a dual-frequency GNSS receiver. For both the measurement of the checkpoints and for the Direct Georeferencing (DG) base of the Unmanned Aerial Vehicles (UAV), a relative processing was performed, using the Brazilian Network for Continuous Monitoring (RBMC) as a reference. With this evaluation, it was possible to achieve a result (RMSE) for phototriangulation better than 1.2 pixels for horizontal and 1.5 pixels for vertical, without the need to measure any control points on the ground.
Corpus-assisted analysis of legitimation strategies in government social media communication

When governments introduce controversial policies that many citizens disapprove of, officeholders increasingly use discursive legitimation strategies in their public communication to ward off blame. In this paper, we contribute to the study of blame avoidance in government social media communication by exploring how corpus-assisted discourse analysis helps to identify three types of common legitimations: self-defensive appeals to (1) personal authority of policymakers, (2) impersonal authority of rules or documents and (3) goals or effects of policies. We use a specialised corpus of tweets by the Brexit department of the British government (42,618 words) which we analyse both qualitatively and quantitatively. We demonstrate how the analysis of lexical bundles that characterise each type of legitimation might provide a new avenue for identifying the presence, characteristics and uses of these legitimations in larger datasets.
Microsatellite Signature of Reference Genome Sequence of SARS-CoV-2 and 32 Species of Coronaviridae Family

Background: Simple sequence repeats (SSRs) are 1 - 6 bp repeat motif sequences present across both prokaryotic and eukaryotic genomes with various clinical implications besides being tools for conservation and evolutionary studies. Objectives: Analysis of 33 Coronavirus genomes, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), for incidence, distribution, and complexity of SSRs patterns to understand their role in host divergence and evolution. Methods: Full-length genome sequences were extracted from National Center for Biotechnology Information (NCBI). Extraction of microsatellites was done using imperfect microsatellite extractor (IMEx) in “Advanced Mode”. Sequences were aligned with MAFFT v6.861b and the maximum likelihood tree was inferred using RAxML v8.1. 20 of the GTR + GAMMA+I model with default specifications. Results: A total of 3,442 SSRs and 136 complex sequence repeats (cSSRs) were extracted from the studied 33 genomes. SSR incidence ranged from 82 (CV09) to 144 (CV60). cSSR incidence ranged from 1 (CV42, CV43, CV53) to 11 (CV32). CV61 (SARS-CoV-2) had 107 SSRs and 6 SSRs. Di-nucleotide motifs were the most prevalent followed by tri- and mono-nucleotide motifs. TG/GT was the most represented di-nucleotide motif, followed by CA/AC. In tri-nucleotide SSRs, ACA/TGT was the most represented motif followed by CAA/GTT, whereas in mono-nucleotide SSRs, T was the most observed nucleotide, followed by A. About 94% of SSRs were localized to the coding region. Twenty species, including CV61 (SARS-CoV-2), exhibit mono-nucleotide repeats exclusively in the A/T region, which were clustered in phylogenetic analysis. The sequence similarity of the genomes was assessed through heat map analysis and revealed similar sequences are expectedly placed in proximity on the phylogenetic tree. Conclusions: Mono-nucleotide exclusivity to A/T region and SSR genome signature can be a possible basis for predicting the evolution of viruses in terms of host range.
1023-P: Clusters of Depressive Symptoms and Glycemic Outcomes in Youth with Type 1 Diabetes (T1D)

Aim: Depression is a heterogeneous construct that includes various symptoms (e.g., cognitive, somatic) and is linked to worse diabetes outcomes. We examined the associations of depressive symptom clusters with glycemic outcomes using continuous glucose monitoring (CGM) data in youth with T1D. Methods: Participants (N=120) provided blood samples for HbA1c, completed a validated survey for depressive symptoms (CES-DC) , and wore CGM for one week. CGM glucose metrics were derived: % time in range (TIR) 70-180 mg/dL; % time <70 mg/dL; % time >180 mg/dL; % time >250 mg/dL; mean glucose; and glucose variability (GCV) . CES-DC items were categorized as somatic, cognitive, anhedonic, and interpersonal for analyses. Results: Youth (49% male) had a mean (±SD) age of 12.7±2.7 years, T1D duration 6.1±3.5 years, HbA1c 7.9±0.8%. Overall, higher total CES-DC score was associated with higher HbA1c (r=0.21, p=0.02) . In youth with HbA1c ≤8% (n=68) , there were no significant associations between depressive clusters and glycemic outcomes, but several significant associations emerged in youth with HbA1c >8% (n=52) . For those with HbA1c >8%, higher CES-DC total score was associated with higher HbA1c (r=0.55, p<0.0001) , greater % time >250 (r=0.29, p=0.03) , and higher mean glucose (r=0.33, p=0.02) . More symptoms on the cognitive and interpersonal clusters were associated with higher HbA1c (r=0.29, p=0.03; r=0.43, p=0.002, respectively) . More somatic symptoms were associated with greater % time >180 (r=0.34, p=0.01) , less % TIR (r=-0.34, p=0.01) , and higher mean glucose (r=0.31, p=0.03) . Conclusions: In our sample of youth with T1D, associations between depressive symptoms and glucose varied according to overall glycemic control, with notable associations in youth with HbA1c >8%. Somatic depressive symptoms were especially related to uncontrolled glucose levels, highlighting the importance of targeting glucose TIR to reduce adverse physical complaints. A.Shapira: None. L.K. Volkening: None. L.M. Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. T32DK007260, P30DK036836, R01DK089349
Ad libitum feeding alters mRNA abundance in the ovarian cortex of broiler breeder hens

Ad libitum feeding in broiler breeder (BB) hens causes reduced egg production, lower fertility, and improper eggshell deposition. Restricted feeding (RF) is the only effective intervention available to normalize ovarian function and improve reproductive efficiency. This study aimed to assess the transcriptional changes in ovarian cortex of BB hens with free access to feed compared to those on a RF diet. RNA was isolated from the ovarian cortex of Cobb 500 pullets raised to 10 and 16 weeks of age on either a full-feeding (FF) or RF diet. Microarray analysis identified 386 differentially expressed genes between the two feeding groups at 16 weeks of age. Gene ontology enrichment identified overrepresentation of Neuroactive ligand–receptor interaction pathways, Cell adhesion molecules, Steroid hormone biosynthesis, and various KEGG pathways. From these groups, 46 genes were selected for follow-up validation by quantitative PCR. The findings show that 33 of the 46 genes had significantly different abundance by age and/or feeding level. Most of these genes were repressed in RF hens and belonged to the steroid biosynthesis and neuropeptide signaling groups. The VIPR2 receptor was higher in the FF group leading us to hypothesize that vasoactive intestinal peptide (VIP) is an important regulator of small cortical follicles. Culture of hen cortical follicles with VIP increased Star, an indication of increased steroidogenic activity, although did not elevate Cyp11a1. These results offer insights and suggest the possible mechanisms and pathways responsible for the increases in cortical follicle growth associated with excess feed intake in BB hens. Lay summary Giving breeder hens unrestricted access to feed can lead to problems with their ovaries, including excessive growth of the ovary and reduced fertility. Giving a limited amount of feed is the only effective way to reduce this growth of the ovaries and improve fertility. This study aimed to assess the changes in the molecules that make proteins in the body in hens fed unrestricted and restricted diets. In the hens fed a limited amount of feed, there were more of one type of molecules, while there were more of another type in the ovaries of hens with unrestricted access to feed. These results show that how much a hen eats can alter the number of these molecules in the ovary and this could help us understand why their ovaries grow excessively and why their eggs are less fertile.
Ceramic Nanofiber Materials for Wound Healing and Bone Regeneration: A Brief Review

Ceramic nanofibers have been shown to be a new horizon of research in the biomedical area, due to their differentiated morphology, nanoroughness, nanotopography, wettability, bioactivity, and chemical functionalization properties. Therefore, considering the impact caused by the use of these nanofibers, and the fact that there are still limited data available in the literature addressing the ceramic nanofiber application in regenerative medicine, this review article aims to gather the state-of-the-art research concerning these materials, for potential use as a biomaterial for wound healing and bone regeneration, and to analyze their characteristics when considering their application.
An Inverse Reinforcement Learning Approach for Customizing Automated Lane Change Systems

Vehicle automation seeks to enhance road safety and improve the driving experience. However, a standard system does not account for variations in users and driving conditions. Customizing vehicle automation based on users' preferences aims to improve the user experience and adoption of the technologies. This study introduces a systematic paradigm that starts with naturalistic driving data to identify the driving behaviors and styles for a customized automated lane change system. The driving behaviors are first extracted using Multivariate Functional Principal Component Analysis (MFPCA) with minimum prior expert knowledge. The driving styles are identified by clustering the extracted driving behaviors. An Inverse Reinforcement Learning (IRL) algorithm is then used to train the automated lane change system from grouped demonstrations of the identified driving styles to capture the preferences of a group of drivers with a similar driving style. The performance of the proposed customized automated lane change system is compared to (1) a non-customized system trained on all the sample trips, (2) customized systems built on expert-coded reward functions, and (3) customized systems trained using a Generative Adversarial Imitation Learning (GAIL) algorithm. The results show that our method outperforms all the other systems with respect to the prediction accuracy of the lane change actions. Additionally, our method gains insights on the representative behaviors of different driving styles to enable customization of automated lane change systems.
Unsupervised Domain Adaptive 1D-CNN for Fault Diagnosis of Bearing

Fault diagnosis (FD) plays a vital role in building a smart factory regarding system reliability improvement and cost reduction. Recent deep learning-based methods have been applied for FD and have obtained excellent performance. However, most of them require sufficient historical labeled data to train the model which is difficult and sometimes not available. Moreover, the big size model increases the difficulties for real-time FD. Therefore, this article proposed a domain adaptive and lightweight framework for FD based on a one-dimension convolutional neural network (1D-CNN). Particularly, 1D-CNN is designed with a structure of autoencoder to extract the rich, robust hidden features with less noise from source and target data. The extracted features are processed by correlation alignment (CORAL) to minimize domain shifts. Thus, the proposed method could learn robust and domain-invariance features from raw signals without any historical labeled target domain data for FD. We designed, trained, and tested the proposed method on CRWU bearing data sets. The sufficient comparative analysis confirmed its effectiveness for FD.
An Industrial Fault Diagnostic System Based on a Cubic Dynamic Uncertain Causality Graph

This study presents an industrial fault diagnosis system based on the cubic dynamic uncertain causality graph (cubic DUCG) used to model and diagnose industrial systems without sufficient data for model training. The system is developed based on cloud native technology. It contains two main parts, the diagnostic knowledge base and the inference method. The knowledge base was built by domain experts modularly based on professional knowledge. It represented the causality between events in the target industrial system in a visual and graphical form. During the inference, the cubic DUCG algorithm could dynamically generate the cubic causal graph according to the real-time data and perform the logic and probability calculations based on the generated cubic DUCG models, visually displaying the dynamic causal evolution of faults. To verify the system’s feasibility, we rebuild a fault-diagnosis model of the secondary circuit system of No. 1 at the Ningde nuclear power plant based on the new system. Twenty-four fault cases were used to test the diagnostic accuracy of the system, and all faults were correctly diagnosed. The results showed that it was feasible to use the cubic DUCG platform for fault diagnosis.
STRUCTURE OF CELLULOSE AND ITS USE; A REVIEW

Cellulose is one of the natural resources in abundance and is easily obtained from plants and animals. One of the uses of cellulose in the industry is by utilizing the fiber content in plants to be used as composite materials, paper materials, and bioethanol. To be able to utilize the cellulose contained in plants, researchers must be able to know and analyze the characteristics of the basic materials to be used. With a qualitative approach, it is hoped that data related to cellulose can be obtained so that it can be the basis for further research. From the results of a literature study, it can be seen that cellulose has a unique structure, so it has almost the same mechanical ability as Kevlar and aramid fibers, so it can be used as body armor. This paper is structured to review cellulose and its uses in life
Parking Guidance System Based on Geomagnetic Sensors and Recurrent Neural Networks

The increase of motor vehicles year by year has led to a number of parking difficulties and traffic congestion problems. The intelligent parking system can effectively alleviate the parking difficulties and has received wide attention. Geomagnetic sensors are widely used due to their low cost and easy deployment. However, traditional geomagnetic parking detection algorithms cannot cope with complex parking behaviors and have low vehicle detection performance. Therefore, in this paper, a new parking guidance system is proposed by integrating related technologies such as ZigBee, geomagnetic sensor, and RNN. With our limited knowledge, in the research branch of the parking guidance system, RNN is applied to geomagnetic vehicle detection for the first time to detect the status of parking spaces and obtain more accurate identification results of geomagnetic signals. The training data is obtained from real scenarios. It is experimentally demonstrated that our method receives 96.6% accuracy in the detection of vehicle status, which is 9% higher than the state-of-the-art method. Finally, a robust parking guidance system gets 97% accuracy.
Experimental Characterization and Analysis of Simple Residential Structures Subjected to Simulated Sonic Booms

Commercial aircraft are subject to noise regulations imposed by the Federal Aviation Administration. Currently, the FAA limits overland flight of supersonic airplanes due to the negative effect of the sonic boom on communities. The annoyance produced by the impulsive signature of sonic booms, particularly indoors, cannot exceed that of the broadband, lowoverpressure noise produced by subsonic airplanes for the restriction to be lifted. Therefore, the ability to understand and accurately reproduce the acoustic response of a sonic boom is important for psychoacoustic classification of their tolerability within residences. This thesis presents and interprets results of the propagation and transmission of simulated sonic booms incident on wood-framed structures. The testing environment, sonic boom simulation method, and associated instrumentation are described. The effects of the traveling blast on the structure are investigated through pressure loading and structural response measurements. The ensuing interior acoustic responses for several different configurations are presented, including the effects of room cavity interaction and exposure of the room cavities to the traveling wave through an open door. Calculated transfer functions between the interior acoustic response and the free-field incident wave are computed to assess the extent to which wood-framed buildings transmit energy to their cavities. In all cases tested, significant transmission of the sonic boom’s low frequency content into the structures was apparent through direct apertures and the excitation of structural components. The data show that sonic booms provide significant excitation of structural and acoustic modes that drives the interior acoustic response in residential structures.
Parameterized Dynamic Range Reduction for UWB SAR Image

The visualization of ultra wide bandwidth synthetic aperture radar (UWB SAR) image data involves mapping from high dynamic range amplitude values to gray values of a lower dynamic range display device. In order to compress dynamic range of the UWB SAR image data appropriately, we examine several difierent dynamic range reduction techniques and come up to a new method with better visualization performance. This new arithmetical technique is analyzed based on the 3ae measurement and the amended mapping function. Compared with the original method, the new method has higher computational e-ciency with the dark pixels are stretched appropriately and the bright details are well preserved. 1. INTRODUCTION Low-frequency ultra-wide bandwidth synthetic aperture radar (UWB SAR) is a new domain, which combines the ultra-wideband technology with synthetic aperture radar imaging technology. How- ever, it is more di-cult for researchers to obtain useful information from the UWB SAR images due to their high dynamic range and great quantity of calculation (1). Therefore, developing a fast visual method for the UWB SAR amplitude values is essentially important and necessary. In the UWB SAR images, corner re∞ectors, which are used for calibration and geocoding pur- poses, generate a large dynamic range of amplitude values. Therefore the dynamic range compres- sion is a crucial step in the processing. There are logarithmic transformation (2), linear mapping and many other traditional methods that are used in dealing with the data of UWB SAR images. Generally, the dynamic range of primary amplitude values is typically much wider than conven- tional display devices. The logarithmic transformation may map a great number of amplitude values in one same gray level. All information in similar amplitude values is lost when using this method. In order to reserve more information in images, some researchers have proposed partial linear mapping method for UWB SAR images. This method divides the gray values into difierent parts by previous experience. However, when the input date changed the original divided model may not available. So, if we want to process the UWB SAR data real-time, we need to explore a new visual method. In this paper, we proposed a fast visualization method based on the idea that the 3ae measure- ment can reduce the impact of intense echo signal and has a good performance in dynamic range reduction. This paper is developed as follows. The Section 2 introduces commonly used methods for the SAR image data visualization. The Section 3 analyzes the distribution of UWB SAR image data and presents a fast visualization method for UWB SAR images visualization. The Section 4 compares the performance of the traditional visual methods with the new method by simulation and then reaches a conclusion that the proposed method is adaptive, improve the visibility of local details, and suit for real-time visualization system.
Long-Term Pterostilbene Supplementation of a High-Fat Diet Increases Adiponectin Expression in the Subcutaneous White Adipose Tissue

Pterostilbene (Pt) is a natural phenol found in blueberries and grapes; it shows remarkable biomedical activities similar to those of resveratrol, but its higher bioavailability is a major advantage for possible biomedical applications. Our group has recently demonstrated that long-term (30 weeks) administration of Pt to mice maintained on a high-fat diet counters weight gain and promotes browning of subcutaneous white adipose tissue (sWAT). By Real-time quantitative PCR and Western Blot analysis of the sWAT and visceral white adipose tissue (vWAT) from the same mice used in the previous study, we show here that Pt induced a long-term increase of Adiponectin, Interleukin 10 and of M2 macrophage marker Cd206. The effects were observed in sWAT, while no significant changes were detected in vWAT. The process taking place seems to mimic that occurring in sWAT during cold-induced browning. Analysis of a few pro-inflammatory cytokines (Interleukin 6, Tumor necrosis factor α) and of the NFkB pathway did not reveal marked effects of Pt supplementation. In summary, the mechanisms and processes through which Pt acts in adipose tissue appear to closely mimic those set in motion by cold-induced browning, and point to a possible impact of experimental conditions in the final output of a nutraceutical intervention.
PENGEMBANGAN PERMAINAN REDI DALAM PENINGKATAN EFIKASI DIRI BAGI SISWA SMA

The purpose of this research is to develop REDI (Roda Efikasi Diri) game to increase the self-efficacy of students. This research and development method uses a Research and Development procedure, using steps: 1) preliminary study, 2) media development, and 3) media testing. Based on the material expert’s assessment, an average score of 0.81 was produced with a decent category. Based on the media expert’s assessment, an average score of 0.93 was obtained with a decent category. The result of the user test assessment is 96.67% in the very valid category. Based on the result of a limited field test, it was obtained tcount 1.172 ttable 0.727, so that H0 is rejected and Ha is accepted. So it can be concluded that REDI game is effective for increasing students self-efficacy.