Miracle-dz/UniFAR-FTUs huggingface dataset:
Sheet 1 of 10 US 9 . 408 , 885 B 2 Primary Melanoma c Regional Dermal

(51) Int. Cl. C07K 700 (2006.01) A6 IK38/02 (2006.01) A6 IK33/24 (2006.01) A6 IK3I/496 (2006.01) A 6LX3L/95 (2006.01) CI2O I/68 (2006.01) GOIN33/50 (2006.01) GOIN33/574 (2006.01) A6 IK 45/06 (2006.01) A6 IK38/8 (2006.01) A6 IK38/30 (2006.01) (52) U.S. Cl. CPC . A61K 38/02 (2013.01); A61 K31/195 (2013.01); A61 K3I/496 (2013.01); A61 K 33/24 (2013.01); A61 K38/1866 (2013.01); A6 IK38/30 (2013.01); A61K 45/06 (2013.01); CI2O I/6886 (2013.01); G0IN33/5005 (2013.01); G0IN33/5743 (2013.01); C12O 2600/156 (2013.01); G0IN 2800/52 (2013.01) (58) Field of Classification Search CPC . CO7K 7700 USPC . 514f19.3 See application file for complete search history.
Predicament and Outlet: The Deep Fusion of Information Technology and Political Thought Teaching in Institution of Higher Learning under the Background of Fragmented Learning Environment

The ongoing integration of IT with various disciplines is a result of IT's constant penetration of the educational sector. This paper investigates how to further promote the deep integration of IT and political thought courses in institution of higher learning based on the fragmented learning background, starting from the current teaching situation of political thought courses in institution of higher learning, based on modern educational theory and supported by IT. Strengthening the relevance and affinity of political thought courses in institutions of higher learning and more effectively implementing the political thought instructional resource are examples of new approaches that can be explored to increase the effectiveness of political thought education and teaching. The integration model of political thought course instructional resources in higher education institutions is also constructed in this paper. According to the user's interest characteristics, the instructional resources are filtered, and the search service and recommendation service of political thought instructional resources are few but adequate. This model introduces personalized information service based on network into the instructional resource system, learning, and tracking users' personalized interests. The results of the experiments demonstrate that this algorithm has an accuracy of up to 95.03 percent. IT has a certain degree of applicability and dependability, and this study can offer valuable reference material for the deep integration of IT and political thought teaching in institutions of higher education against the backdrop of fragmented learning.
Ignition probabilities of wildland fuels based on simulated lightning discharges. Forest Service research paper

Ignition of wildland fine fuels by lightning was simulated with an electric arc discharge in the laboratory. The results showed that fuel parameters such as depth, moisture content, bulk density, and mineral content can be combined with the duration of the simulated continuing current to give ignition probabilities. The fuel state parameters of importance and the ignition probabilities were determined using logistic regression. Graphs, tables, formulas, and a FORTRAN computer program are given for field use.
Dilemmas in the Management of Pseudoaneurysms, Treatment Approaches, and Clinical Outcomes

A review was conducted of all patients who were investigated for pseudoaneurysms, including those who were treated with ultrasound guided percutaneous thrombin injection(s) – (UGTI) in the medical imaging department since 2014. Our institute’s electronic database was searched and data was extracted using the keywords “thrombin” and “pseudoaneurysm”. A total of 87 cases were identified. Out of these, we present a series of six interesting pseudoaneurysms cases, its associated management dilemmas, treatment approaches, and clinical outcomes. Key learning point for each case is discussed.
Examining the Multi-Seasonal Consistency of Individual Tree Segmentation on Deciduous Stands Using Digital Aerial Photogrammetry (DAP) and Unmanned Aerial Systems (UAS)

Digital aerial photogrammetric (DAP) techniques applied to unmanned aerial system (UAS) acquired imagery have the potential to offer timely and affordable data for monitoring and updating forest inventories. Development of methods for individual tree crown detection (ITCD) and delineation enables the development of individual tree-based, rather than stand based inventories, which are important for harvesting operations, biomass and carbon stock estimations, forest damage assessment, and forest monitoring in mixed species stands. To achieve these inventory goals, consistent and robust DAP estimates are required over time. Currently, the influence of seasonal changes in deciduous tree structure on the consistency of DAP point clouds, from which tree-based inventories can be derived, is unknown. In this study, we investigate the influence of the timing of DAP acquisition on ITCD accuracies and estimation of tree attributes for a deciduous-dominated forest stand in New Brunswick, Canada. UAS imagery was acquired five times between June and September 2017 over the same stand and consistently processed into DAP point clouds. Airborne laser scanning (ALS) data, acquired the same year, was used to reconstruct a digital terrain model (DTM) and served as a reference for UAS-DAP-based ITCD. Marker-controlled watershed segmentation (MCWS) was used to delineate individual tree crowns. Accuracy index percentages between 55% (July 25) and 77.1% (September 22) were achieved. Omission errors were found to be relatively high for the first three DAP acquisitions (June 7, July 5, and July 25) and decreased gradually thereafter. The commission error was relatively high on July 25. Point cloud metrics were found to be predominantly consistent over the 4-month period, however, estimated tree heights gradually decreased over time, suggesting a trade-off between ITCD accuracies and measured tree heights. Our findings provide insight into the potential influence of seasonality on DAP-ITCD approaches to derive individual tree inventories.
Enhancing Self-Regulation through the Growth Mindset Stimulation

Abstract. Self-regulation is highly needed during pandemics learning. It supports students with appropriate actions, thoughts, and feelings in learning. Embedding self-regulation in the class will anticipate the learning loss. The objective of this research is to enhance self-regulation through growth mindset stimulation specifically through the implementation of an e-module. This research is applying a research & development method. The research was conducted with samples of 126 students from the 7th grade of junior high school. Students mindset were measured with mindset check up (Brainology), while student’s self-regulation was identified based on the Learning and Study Strategies Inventory (LASSI) test. The result of the study shows that the stimulation given from the growth mindset is effective to enhance self-regulation. Students’ attitude toward their learning is improving due to the growth mindset stimulation.
Human‐in‐the‐loop development of spatially adaptive ground point filtering pipelines—An archaeological case study

LiDAR data have become indispensable for research in archaeology and a variety of other topographic applications. To derive products (e.g. digital terrain or feature models, individual trees, buildings), the 3D LiDAR points representing the desired objects of interest within the acquired and georeferenced point cloud need to be identified. This process is known as classification, where each individual point is assigned to an object class. In archaeological prospection, classification focuses on identifying the object class ‘ground points’. These are used to interpolate digital terrain models exposing the microtopography of a terrain to be able to identify and map archaeological and palaeoenvironmental features. Setting up such classification workflows can be time‐consuming and prone to information loss, especially in geographically heterogeneous landscapes. In such landscapes, one classification setting can lead to qualitatively very different results, depending on varying terrain parameters such as steepness or vegetation density. In this paper, we are focussing on a special workflow for optimal classification results in these heterogeneous environments, which integrates expert knowledge. We present a novel Python‐based open‐source software solution, which helps to optimize this process and creates a single digital terrain model by an adaptive classification based on spatial segments. The advantage of this approach for archaeology is to produce coherent digital terrain models even in geomorphologically heterogenous areas or areas with patchy vegetation. The software is also useful to study the effects of different algorithm and parameter combinations on digital terrain modelling with a focus on a practical and time‐saving implementation. As the developed pipelines and all meta‐information are made available with the resulting data set, classification is white boxed and consequently scientifically comprehensible and repeatable. Together with the software's ability to simplify classification workflows significantly, it will be of interest for many applications also beyond the examples shown from archaeology.
Structural and Optical Properties of Silver Nanoparticles In Situ Synthesized in ZnO Film by Sol–Gel Method

We fabricate the samples with two layers of silver nanoparticles embedded in ZnO film exploring sol–gel method by varying the annealing temperatures. The structural properties of the samples are determined by transmission electron microscopy. The effect of the annealing temperature on the nanoparticles plasmon absorption spectra is studied. Annealing at 570 °C results in a shift of the plasmon absorption maximum from 580 nm to 620 nm, due to an increase in the nanoparticles average size from 63 nm to 74 nm. Increasing the annealing temperature to 650 °C results in a shift of plasmon absorption maximum back to 580 nm due to a decrease in the nanoparticles size to 61 nm. Before annealing, the silver nanoparticles of the upper layer locate on top of the nanoparticles of the bottom layer, however, in the plane of the layers, they are arranged randomly at a distance of 30 to 150 nm from each other. As a result of the annealing, the system tended to be ordered, as a result, the nanoparticles in the layers become to be distributed equidistant at 40–70 nm between them; the nanoparticles of the upper layer tend being located between the nanoparticles of the bottom layer.
Formation Mechanisms of Co-existence of α-Fe and Iron Oxides Nanoparticles Decorated on Carbon Nanofibers by a Simple Liquid Phase Adsorption-Thermal Oxidation

We propose formation mechanisms of co-existence of α-Fe and iron oxides nanoparticles decorated on CNFs. The α-Fe nanoparticles are produced via oxidation-reduction mechanisms, which occur in liquid phase adsorption (LPA) assisted by ultrasonic energy, while α-Fe2O3 nanoparticles are thermally formed through mechanisms of Lewis acidbase. In addition, Fe3O4 is thermally formed by reducing Fe2O3 by CNFs. Liquid phase adsorption assisted by ultrasonic energy under ambient temperature using Fe(NO3)3•9H2O as a precursor of iron oxides and α-Fe has been applied. Then, as prepared, Fe(III)@CNFs were thermally calcined at 573 K under air atmosphere in various holding times ranging from 0.5 to 2 h. XRD data confirmed that α- Fe2O3 and Fe3O4 had been successfully grown onto CNFs. Moreover, the presence of the iron oxides and iron nanoparticles was studied by the SEMEDX technique. The iron oxide nanoparticles appeared after a heating period of 0.5h. However, at a holding time of 0.5 h, we found an exciting and unexpected phenomenon where oxygen content is zero percent while Fe is 0.23 wt %. It implies that α-Fe nanoparticles were formed earlier than α-Fe2O3 and Fe3O4 as the proposed mechanisms. Formation mechanisms of iron and its oxides such as α-Fe2O3 and Fe3O4 decorated on CNFs through liquid-phase adsorption followed by thermally treatment technique in this work is expected to give significant contribution in the field of nanocomposite materials, especially for anode materials based on iron oxides.
Iron status and developmental delay among children aged 24–36 months

Background Optimal child development is needed for adequate learning. Children, particularly toddlers, require iron for brain development, and consequently, overall development. Objective To analyze for an association between iron status and developmental status in children aged 24–36 months. Methods This explorative cross-sectional study was held in Kampung Melayu, Jakarta. Subjects were recruited using a total population sampling method. Data were collected through interview with parents, anthropometric examinations, and blood tests. Developmental status was determined using the Ages and Stages Questionnaire-3 (ASQ-3) and iron status was based on ferritin, high sensitivity C-reactive protein (hs-CRP), and hemoglobin levels. Data analyses included Chi-square/Fisher’s exact, Mann-Whitney, and logistic regression tests. Results Of 80 subjects, 17.5% had developmental delay and 41.3% had deficient iron status. There was no significant association between iron status and developmental status in bivariate analysis, but the logistic regression analysis revealed that iron status (OR=6.9; 95%CI 1.328 to 35.633; P=0.022) and nutritional status (OR=11.75; 95%CI 1.551 to 88.979; P=0.017) contributed to developmental delay. Conclusion Better iron status and nutritional status are associated with better child development of children aged 24–36 months. So efforts are needed to maintain iron status as well as nutritional status.
MULTIMODAL DIFFERENTIAL EMISSION MEASURE IN THE SOLAR CORONA

The Atmospheric Imaging Assembly (AIA) telescope on board the Solar Dynamics Observatory provides coronal extreme ultraviolet imaging over a broader temperature sensitivity range than the previous generations of instruments (Extreme Ultraviolet Imager; EUVI, EIT, and TRACE). Differential emission measure tomography (DEMT) of the solar corona based on AIA data is presented here for the first time. The main product of DEMT is the three-dimensional distribution of the local differential emission measure (LDEM). While in previous studies, based on EIT or EUVI data, there were three available EUV bands, the present study is based on the four cooler AIA bands (aimed at studying the quiet sun). The AIA filters allow exploration of new parametric LDEM models. Since DEMT is better suited for lower activity periods, we use data from Carrington Rotation 2099, when the Sun was in its most quiescent state during the AIA mission. Also, we validate the parametric LDEM models by using them to perform a bi-dimensional differential emission measure (DEM) analysis on sets of simultaneous AIA images, and comparing results with those obtained using other methods. Our study reveals a ubiquitous bimodal LDEM distribution in the quiet diffuse corona, characterized by two well-defined average centroid temperatures ⟨ T 0,1 ⟩ = ( 1.47 ± 0.05 ) MK ? > and ⟨ T 0,2 ⟩ = ( 2.57 ± 0.05 ) MK . > We argue that the nanoflare heating scenario is less likely to explain these results, and that alternative mechanisms, such as wave dissipation, appear better supported by our results.
A Path-Clustering Driving Travel-Route Excavation

The refueling trajectory of self-driving tourists is sparse, and it is difficult to restore the real travel route. A sparse trajectory clustering algorithm is proposed based on semantic representation to mine popular self-driving travel routes. Different from the traditional trajectory clustering algorithm based on trajectory point matching, the semantic relationship between different trajectory points is researched in this algorithm, and the low-dimensional vector representation of the trajectory is learned. First, the neural network language model is used to learn the distributed vector representation of the fueling station; then, the average of all the station vectors in each trajectory is taken as the vector representation of the trajectory. Finally, the classic k-means algorithm is used to cluster the trajectory vectors. The final visualization results show that the proposed algorithm effectively mines two popular self-driving travel routes.
Hard Real-time Linux on a Raspberry Pi for 3D Printing

The project presents how a Raspberry Pi with hard real-time enabled Linux can control stepper motors to operate the kinematics of a 3D (three-dimensional) printer. The consistent performance of the Raspberry Pi with the PREEMPT-RT (real-time) patch can satisfy real hard-time requirements for 3D printing kinematics, without introducing dedicated microcontrollers. The Klipper 3D printer firmware enables one of the Raspberry Pi processors to act as the Klipper MCU, the primary controller for the hardware components. This project introduces a software implementation of the control logic for controlling the stepper motors, which utilizes the PCA9685 pwm driver and TB6612 motor drivers from Adafruit DC & Stepper Motor Pi HATs (hardware attached on top). This initial investigation shows that the Raspberry Pi itself can perform as a 3D printer satisfactorily and readily utilize Linux software.
State estimation of TakagiSugeno systems with unmeasurable premise variables

: This study is dedicated to the design of observers for non-linear systems described by Takagi–Sugeno (T–S) multiple models with unmeasurable premise variables. Furthermore, this T–S structure can represent a larger class of non-linear systems compared to the T– S systems with measurable premise variables. Considering the state of the system as a premise variable allows one to exactly represent the non-linear systems described by the general form ˙ x ¼ f ( x, u ). Unfortunately, the developed methods for estimating the state of T–S systems with measured premise variable are not directly applicable for the systems that use the state as a premise variable. In the present paper, ﬁrstly, the design of observers for T– S systems with unmeasurable premise variable is proposed and sufﬁcient convergence conditions are established by Lyapunov stability analysis. The linear matrix inequality (LMI) formalism is used in order to express the convergence conditions of the state estimation error in terms of LMI and to obtain the gains of the observer. Secondly, the proposed method is extended in order to attenuate energy-bounded unknown inputs such as disturbances. An academic example is proposed to compare some existing methods and the proposed one.
The Oxford Handbook of Functional Data Analysis

This handbook presents the state-of-the-art of the statistics dealing with functional data analysis. With contributions from international experts in the field, it discusses a wide range of the most important statistical topics (classification, inference, factor-based analysis, regression modeling, resampling methods, time series, random processes) while also taking into account practical, methodological, and theoretical aspects of the problems. The book is organised into three sections. Part I deals with regression modeling and covers various statistical methods for functional data such as linear/nonparametric functional regression, varying coefficient models, and linear/nonparametric functional processes (i.e. functional time series). Part II considers related benchmark methods/tools for functional data analysis, including curve registration methods for preprocessing functional data, functional principal component analysis, and resampling/bootstrap methods. Finally, Part III examines some of the fundamental mathematical aspects of the infinite-dimensional setting, with a focus on the stochastic background and operatorial statistics: vector-valued function integration, spectral and random measures linked to stationary processes, operator geometry, vector integration and stochastic integration in Banach spaces, and operatorial statistics linked to quantum statistics.
Eustachian tube dysfunction and Allergic rhinitis in young adult population of Saudi Arabia

Introduction: Eustachian tube dysfunction (ETD) is a well-known co-morbid manifestation of inflammatory diseases of the nasal cavity. Allergic rhinitis (AR) is a common chronic condition that causes a significant amount of disease burden in the population. However, studies on ETD in patients with AR are still very limited. Materials and methods: A total of 60 healthy and 60 AR patients participated in the prospective comparative study. All of the subjects were subjected to a skin prick test. According to ARIA criteria, the severity of AR was classified as "mild" or "moderate-severe" and "persistent" or "intermittent. " Eustachian Tube Dysfunction Questionnaire (ETDQ-7) subjective scores were obtained for both groups. For objective examinations, nasal cytology, Tympanometry, and Tubomanometry were used, and the data were statistically analyzed. Results: The mean eosinophil and neutrophil counts in nasal smears demonstrated a significant difference between the two groups. In the AR and control groups, the overall ETDQ-7 score was 21.6 and 9.7 respectively (p<0.001). Tympanometry reports that ETD was significantly higher in the AR group (83.3%) than in the control group (p<0.001). TMM also established that 84.2% of AR subjects had ETD, which was statistically significant.
Evaluation of the necessity of Pulmonary Ligament Lymph Node Dissection for Upper Lobe Stage IB NSCLC: A Propensity Score-matched Study

Objective: The purpose of this study was to explore whether the resection of pulmonary ligament lymph nodes would affect the prognosis of patients with stage IB non-small cell lung cancer (NSCLC). Methods: We retrospectively analyzed 341 patients with upper lobe stage IB NSCLC who underwent radical surgery for lung cancer at Sun Yat-Sen University Cancer Center from 1999 to 2009. The Cox proportional hazard regression model was used to analyze the prognostic factors. After propensity score matching (PSM), 204 cases were selected. The Kaplan-Meier method and log-rank test were applied to compare overall survival (OS) and recurrence-free survival (RFS). Results: Among the 341 cases included in the study, 217 had no pulmonary ligament lymph nodes resected, and 124 had pulmonary ligament lymph nodes resected. They were divided into two groups according to whether the pulmonary ligament lymph nodes were resected; there were significant differences between the two groups in laterality, resected lymph node stations, and resected lymph node numbers (P<0.05). Univariate and multivariate analyses by the Cox proportional hazards model showed that age and family history of malignant tumors were prognostic factors for OS, and no variables were prognostic factors for RFS (P<0.05). Resection of the pulmonary ligament lymph node was not associated with OS or RFS. After propensity score matching (PSM), survival analysis was performed again using the Kaplan-Meier method and log-rank test; the results suggested that resection of the pulmonary ligament lymph node is not statistically associated with OS and RFS (P>0.05). Conclusions: For stage IB NSCLC, resection of the pulmonary ligament lymph nodes was not statistically associated with OS or RFS. Pulmonary ligament lymph node resection is not necessary for early-stage NSCLC.