Miracle-dz/UniFAR-FTUs huggingface dataset:
THESIS SIGNATURE PAGE PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE THE PROJECT HAS BEEN ACCEPTED BY THE PROJECT COMMITTEE IN ARTS IN CURRICULUM AND INSTRUCTION

I saw when I was a student—and I continue to see as a teacher—how a novel study in a high school English class can have a disengaging effect on some students. Some argue, for good reason, that classic literature no longer feels relevant to the students of today. Others point to the importance of giving students agency over what they read. For various reasons, some educators have chosen to do away with classic literature or novel studies altogether. But given the requirements of some districts to teach certain books as well as some of the benefits of reading a book as a class, it’s worth considering what methods teachers can implement to increase engagement during a novel study. In this study, I explore how students describe their engagement during a novel study, how my methods of instruction during a novel study influence engagement, and how that engagement relates to student learning outcomes. Using a combination of student surveys, focus group responses, and student work samples, the findings of this study suggest that students are, indeed, less engaged in a novel study as compared with general engagement in school, but the teacher can influence this with certain methodologies. The findings also suggest students have wide-ranging preferences when it comes to both plot and novel-related activities, both of which significantly influence student engagement. Finally, the findings indicate that student engagement does correlate with learning outcomes. The implications of this research include choosing a novel with broad appeal (or simply adopting a literature circle model), creating student buy-in through teacher-student discussion of the novel, and providing students with various activities and choices for demonstrating learning.
Supplementary Materials for Repopulating Street Scenes

We collected short (stationary camera) image bursts of street scenes from Google Street View, captured between 2014 and 2020. Using GPS and structure from motion, we identified image bursts coming from parked Street View cars. The cooldown between each capture is about five seconds. The training image bursts were captured in major US cities, including San Francisco, Seattle, Los Angeles, San Jose, New York City, Boston, Chicago and Phoenix. We also collected a test set from nearby cities, including Jersey City, Brooklyn, Berkeley, San Diego, Long Beach and Pittsburgh, to ensure there is no overlap with the training set. Each image burst consists of at least 10 images. Given an image stack, we calculated the median image by taking the channelwise median value per pixel for the whole stack. We used the median image of the bursts as a “clean plate,” free of moving objects and their shadows (we also refer to this image as the “background image”). In total, we collected 142,778 image/background pairs for training and 16,034 as a test set.
Prevention Of Cyber Troll And Sarcasm System On Social Networking Using Machine Learning With Bilingual Analytics

: With the recent growth in use of social media, the trend of having an opinion for every content published on the internet has also increased. The internet allows users to remain anonymous in the sense that there is no compulsion for authenticating oneself, because of which many users exhibit indecent behavior by posting trolls, hate comments and spread negativity. The user who is the target of such actions may get seriously affected, he or she may slip into depression or lack of self-worth. To avoid such misconduct and essentially filter out such negativity, this paper proposes a web-application based deep learning solution to perform troll and sarcasm detection on comments received on a user’s post and then using these comments, trace the user spreading hate and block or report him. The model consists of a Gated Recurrent Unit and a 4-layered neural network for troll detection and sarcasm detection respectively. As most of the comments posted in India are usually in Hinglish, which is a way of writing Hindi words using English letters, such comments will also be processed to determine the classification.
Deformation in Sentinel-1 InSAR Data

21 Time series of displacement are now routinely available from satellite InSAR and are used 22 for flagging anomalous ground motion, but not yet forecasting. We test conventional time 23 series forecasting methods such as SARIMA and supervised machine learning approaches 24 such as Long Short Term Memory (LSTM) compared to simple function extrapolation. 25 We focus initially on forecasting periodic signals and begin by characterising the time26 series using sinusoid fitting, seasonal decomposition and autocorrelation functions. We 27 find that the three measures are broadly comparable but identify different types of sea28 sonal characteristic. We use this to select a set of 310 points with highly seasonal char29 acteristics and test the three chosen forecasting methods over prediction windows of 130 9 months. The lowest overall RMSE values are obtained for SARIMA when consider31 ing short term predictions (<1 month), whereas sinusoid extrapolation performs best for 32 longer predictions (>6 months). Machine learning methods (LSTM) perform less well. 33 We then test the prediction methods on 2000 randomly selected points with a range of 34 seasonalities and find that simple extrapolation of a constant function performed bet35 ter overall than any of the more sophisticated time series prediction methods. Compar36 isons between seasonality and RMSE show a statistically significant improvement in per37 formance with increasing seasonality. This proof-of-concept study demonstrates the po38 tential of time-series prediction for InSAR data but also highlights the limitations of ap39 plying these techniques to non-periodic signals or individual measurement points. We 40 anticipate future developments, especially to shorter timescales, will have a broad range 41 of potential applications, from infrastructure stability to volcanic eruptions. 42
The Framework For Ice Sheet–Ocean Coupling (FISOC) V1.1

Abstract. A number of important questions concern processes at the margins of ice sheets where multiple components of the Earth system, most crucially ice sheets and oceans, interact. Such processes include thermodynamic interaction at the ice–ocean interface, the impact of meltwater on ice shelf cavity circulation, the impact of basal melting of ice shelves on grounded ice dynamics and ocean controls on iceberg calving. These include fundamentally coupled processes in which feedback mechanisms between ice and ocean play an important role. Some of these mechanisms have major implications for humanity, most notably the impact of retreating marine ice sheets on the global sea level. In order to better quantify these mechanisms using computer models, feedbacks need to be incorporated into the modelling system. To achieve this, ocean and ice dynamic models must be coupled, allowing runtime information sharing between components. We have developed a flexible coupling framework based on existing Earth system coupling technologies. The open-source Framework for Ice Sheet–Ocean Coupling (FISOC) provides a modular approach to coupling, facilitating switching between different ice dynamic and ocean components. FISOC allows fully synchronous coupling, in which both ice and ocean run on the same time step, or semi-synchronous coupling in which the ice dynamic model uses a longer time step. Multiple regridding options are available, and there are multiple methods for coupling the sub-ice-shelf cavity geometry. Thermodynamic coupling may also be activated. We present idealized simulations using FISOC with a Stokes flow ice dynamic model coupled to a regional ocean model. We demonstrate the modularity of FISOC by switching between two different regional ocean models and presenting outputs for both. We demonstrate conservation of mass and other verification steps during evolution of an idealized coupled ice–ocean system, both with and without grounding line movement.
Smartphone Based Alerting of First Responders During the COVID-19 Pandemic

Background: Smartphone Alerting Systems (SAS) for first responders potentially shorten the resuscitation-free interval of patients with acute cardiac arrest. During the COVID-19 pandemic, many systems were suspended due to potential risks for the responders. Therefore, a COVID-19 concept for the SAS in Freiburg/Germany was established and evaluated. Methods: Due to the pandemic, SAS was stopped in March 2020. A concept for a safe restart was elaborated with provision of a set with ventilation bag/mask, airway filter and personal protective equipment (PPE) for every volunteer. A standard operating procedure followed the COVID-19 guidelines of the European Resuscitation Council (ERC). Willingness of the participants to respond alarms during the pandemic was investigated using an online survey. Results: The system was restarted in May 2020. The willingness to respond to alarms was lower during the pandemic without PPE. It remained lower than before the pandemic when the volunteers had been equipped with PPE, but the alarm response rate remained at approximately 50% during the ongoing pandemic. Conclusions: When volunteers are equipped with PPE, the operation of a SAS does not need to be paused, and the willingness to respond remains high among first responders.
Regional CO2 fluxes from 2010 to 2015 inferred from GOSAT XCO2 retrievals using a new version of the Global Carbon Assimilation System

Abstract. Satellite retrievals of the column-averaged dry air mole fractions of CO 2 (XCO 2 ) could help to improve carbon flux estimation due to their good spatial coverage. In this study, in order to assimilate the GOSAT (Greenhouse Gases Observing Satellite) XCO 2 retrievals, the Global Carbon Assimilation System (GCAS) is upgraded with new assimilation algorithms, procedures, a localization scheme, and a higher assimilation parameter resolution. This upgraded system is referred to as GCASv2. Based on this new system, the global terrestrial ecosystem (BIO) and ocean (OCN) carbon fluxes from 1 May 2009 to 31 December 2015 are constrained using the GOSAT ACOS (Atmospheric CO 2 Observations from Space) XCO 2 retrievals (Version 7.3). The posterior carbon fluxes from 2010 to 2015 are independently evaluated using CO 2 observations from 52 surface flask sites. The results show that the posterior carbon fluxes could significantly improve the modeling of atmospheric CO 2 concentrations, with global mean bias decreases from a prior value of 1.6 ± 1.8 ppm to − 0.5 ± 1.8 ppm. The uncertainty reduction (UR) of the global BIO flux is 17 %, and the highest monthly regional UR could reach 51 %. Globally, the mean annual BIO and OCN carbon sinks and their interannual variations inferred in this study are very close to the estimates of CarbonTracker 2017 (CT2017) during the study period, and the inferred mean atmospheric CO 2 growth rate and its interannual changes are also very close to the observations. Regionally, over the northern lands, the strongest carbon sinks are seen in temperate North America, followed by Europe, boreal Asia, and temperate Asia; in the tropics, there are strong sinks in tropical South America and tropical Asia, but a very weak sink in Africa. This pattern is significantly different from the estimates of CT2017, but the estimated carbon sinks for each continent and some key regions like boreal Asia and the Amazon are comparable or within the range of previous bottom-up estimates. The inversion also changes the interannual variations in carbon fluxes in most TransCom land regions, which have a better relationship with the changes in severe drought area (SDA) or leaf area index (LAI), or are more consistent with previous estimates for the impact of drought. These results suggest that the GCASv2 system works well with the GOSAT XCO 2 retrievals and shows good performance with respect to estimating the surface carbon fluxes; meanwhile, our results also indicate that the GOSAT XCO 2 retrievals could help to better understand the interannual variations in regional carbon fluxes.
Temporal Evolution of Flux Rope/Tube Entanglement in 3‐D Hall MHD Simulations

At the Earth’s magnetopause, flux tubes observed by the Magnetospheric Multiscale (MMS) spacecraft in “entangled” pairs have been interpreted as a precursory stage to the formation of a new pair of flux tubes by magnetic reconnection, of which one reconnected tube joins the magnetosphere. Understanding the connectivity of these tubes before and after the entanglement is essential to understanding the transport of particles and energy between the magnetosphere and the solar wind. In this study, we use a three‐dimensional Hall Magnetohydrodynamics (MHD) model to simulate the interaction of two entangled flux tubes in the ambient plasma. Four types of interactions are simulated: Two types of magnetic field geometry (flux tube‐flux tube and flux rope‐flux rope) are tested separately, each under two different boundary conditions. With the boundary condition that drives the interaction with ambient flow, magnetic reconnection transforms the two tubes/ropes into new pairs. The process is performed under plasma conditions comparable to those of such events identified in recent MMS observations. The detailed three‐dimensional evolution is shown at representative stages, with key parameters shown across the entanglement interface. The shape of the central current sheet and evolution of magnetic field curvature are also discussed. Our study supports the feasibility of reconnection between entangled flux tubes, recognizes the importance of ambient plasma conditions for the completion of such processes, and quantifies how such structures evolve to modify the solar wind‐geomagnetic field interaction. In addition, this model is applicable to flux rope interactions in the solar corona.
Structure-dependent electronic properties of oxides from first principles

OF THE DISSERTATION Structure-dependent electronic properties of oxides from first principles by Yuanjun Zhou Dissertation Director: Professor Karin M. Rabe This thesis contains several investigations on the structure dependent electronic properties of oxides, studied via first-principle calculations or tight-binding models. We start by reviewing the background of structure correlated properties and functionalities in transition metal oxides, followed by the introduction of the density functional theory which will be used throughout this thesis. We next consider the spin-phonon coupling effect for SrMnO3/LaMnO3 superlattice with epitaxial strain. We explain the origin of the intriguing emergence of the large spin-phonon coupling effect for tensile strain. As the study of superlattice goes on, we realize the emergent need of a systematic way to determine the ground state structure for superlattices. Thus we develop the “stacking method” to solve this problem, and test it using PbTiO3/SrTiO3 whose structure is known to be complicated. We then use the stacking method for the further study on epitaxially strained SrCrO3/SrTiO3 superlattice, and find a nonpolar-polar structural transition along with a metal-insulator transition. We conclude that the polar structure induces an orbital ordering, leading to the insulating state. We also study the interband transition effect in the epitaxially strained SrVO3, and show that the suppressed interband transitions lead to the significant transmittance for SrVO3 thin films. Finally we
Key drivers of pyrogenic carbon redistribution during a simulated rainfall event

Abstract. Pyrogenic carbon (PyC) is produced by the incomplete combustion of vegetation during wildfires and is a major and persistent pool of the global carbon (C) cycle. However, its redistribution in the landscape after fires remains largely unknown. Therefore, we conducted rainfall simulation experiments on 0.25 m2 plots with two distinct Swiss forest soils (Cambisol (clay loam) and Luvisol (sandy silt)). We applied PyC produced from wood (Picea abies) labeled under FACE conditions and C4 grass (Miscanthus sinensis) to the soil surface to study PyC redistribution by runoff and splash and the vertical mobility of PyC in a 10 cm unsaturated soil column based on the differences in δ13C of soils and PyC. We assessed the effect of soil texture, slope angle and PyC characteristics (feedstock and particle size) on the mobility of PyC during 30 min of intense rainfall (102 mm h−1). Our results highlight that PyC is highly mobile. Surface runoff transported between 0.2 % and 36.0 % of the total added PyC. Erosion by splash further redistributed 10.3 % to 25.3 % of the added PyC. Soil type had a substantial impact on the redistribution of PyC by both runoff and splash: on average, we recovered 10.5 % of the added PyC in runoff and splashed material for the clay-rich Cambisol and 61.3 % of the added PyC for the sandy silt Luvisol combined. PyC feedstock had a clear but contrasting effect on PyC redistribution: relocation in the runoff and splashed material was greater for wood PyC (43.4 % of total added PyC) than grass PyC (28.4 %). However, more wood PyC (11.5 %; fraction of organic C derived from the PyC) remained where it was initially applied compared to grass PyC (7.4 %). The results further suggest that the effect of PyC characteristics on its mobility can be highly variable and depend not only on the material from which it was derived, but also on other factors (e.g., particle size, porosity, density). In particular, the mobility of PyC was almost twice as large for fine-grained PyC (< 63 µm) than for coarse PyC (63 µm–2 mm). Vertical mobility of PyC up to 10 cm depth was greater in the clay-rich, well-aggregated Cambisol but limited in the physically instable Luvisol, likely due to quick aggregate breakdown and surface sealing. The addition of PyC to the surface of the studied soils further induced changes in the export of native soil organic carbon (nSOC) after the 30 min rainfall event. Our study shows that large quantities of PyC can be redistributed by water erosion over short timescales and that the mobility of PyC depends to a great extent on the response of soils to rainfall. Moreover, the addition and redistribution of PyC affects the export of nSOC and thus the C budget of fire-affected soils and catchments.
Determine the performance of selected critical care medical equipment in Teaching Hospital, Peradeniya, Sri Lanka

Background: Medical equipment are imported assets that directly influence the medical management in patient care. To ensure effective and safe health care, medical equipment must be maintained efficiently and effectively with expected performance. The way in which it is used and maintained may greatly affect the reliability and productivity of an equipment (H. Mahfoud, 2016). Objective: The main aim of this study is to determine the performance of selected critical care medical equipment in Teaching Hospital, Peradeniya (THP) and to make recommendation to rectify deficiencies. Method: Descriptive cross sectional study design was adopted in this study. Medical equipment which are used in critical care (Intensive care units and operation theatres) were selected based on Equipment management number (EMN) of which is introduced by Fennigkoh and Smith where numerical value is assigned to each medical equipment type in terms of its function, clinical application, required maintenance and history. Out of 510, 103 of equipment whose EMN was more than 12, were shortlisted for the study. Equipment failure rate, the percentage of equipment failed as an average of total number of same equipment in a given period was selected as the performance indicator of medical equipment. Feasibility and availability of data were summoned to choose this indicator as performance measure. Results: Following medical equipment showed equipment failure rate more than 20%,  ICU ventilators  Anesthetic machines  Incubators  ICU monitors  Syringe pumps and infusion pumps Conclusion: Equipment with failure rate more than 20% need more extensive and comprehensive preventive and corrective maintenance programme. Recommendations: Inspection and preventive maintenance (IPM) programme and effective corrective maintenance programme is a mandatory requirement to harvest optimum performance levels. Training programme for end users, effective monitoring and evaluation mechanism and good asset management system are other recommendations.
An uncertainty-based protocol for the setup and measurement of soot–black carbon emissions from gas flares using sky-LOSA

Abstract. Gas flaring is an important source of atmospheric soot–black carbon, especially in sensitive Arctic regions. However, emissions have traditionally been challenging to measure and remain poorly characterized, confounding international reporting requirements and adding uncertainty to climate models. The sky-LOSA optical measurement technique has emerged as a powerful means to quantify flare black carbon emissions in the field, but broader adoption has been hampered by the complexity of its deployment, where decisions during setup in the field can have profound, non-linear impacts on achievable measurement uncertainties. To address this challenge, this paper presents a prescriptive measurement protocol and associated open-source software tool that simplify acquisition of sky-LOSA data in the field. Leveraging a comprehensive Monte Carlo-based general uncertainty analysis (GUA) to predict measurement uncertainties over the entire breadth of possible measurement conditions, general heuristics are identified to guide a sky-LOSA user toward optimal data collection. These are further extended in the open-source software utility, SetupSkyLOSA, which interprets the GUA results to provide detailed guidance for any specific combination of location, date–time, and flare, plume, and ambient conditions. Finally, a case study of a sky-LOSA measurement at an oil and gas facility in Mexico is used to demonstrate the utility of the software tool, where potentially small regions of optimal instrument setup are easily and quickly identified. It is hoped that this work will help increase the accessibility of the sky-LOSA technique and ultimately the availability of field measurement data for flare black carbon emissions.