Miracle-dz/UniFAR-FTUs huggingface dataset:
The multichord stellar occultation on 2019 October 22 by the trans-Neptunian object (84922) 2003 VS$_2$

Context. Stellar occultations have become one of the best techniques to gather information about the physical properties of trans-Neptunian objects (TNOs), which are critical objects for understanding the origin and evolution of our Solar System. Aims. The purpose of this work is to determine, with better accuracy, the physical characteristics of the TNO (84922) 2003 VS 2 through the analysis of the multichord stellar occultation on 2019 October 22 and photometric data collected afterward. Methods. We predicted, observed, and analyzed the multichord stellar occultation of the Second Gaia Data Release (Gaia DR2) source 3449076721168026624 (m v = 14.1 mag) by the plutino object 2003 VS 2 on 2019 October 22. We performed aperture photometry on the im- ages collected and derived the times when the star disappeared and reappeared from the observing sites that reported a positive detection. We ﬁt the extremities of such positive chords to an ellipse using a Monte Carlo method. We also carried out photometric observations to derive the rotational light curve amplitude and rotational phase of 2003 VS 2 during the stellar occultation. Combining the results and assuming a triaxial shape, we derived the 3D shape of 2003 VS 2 . Results. Out of the 39 observatories involved in the observational campaign, 12 sites, located in Bulgaria (one), Romania (ten), and Serbia (one), reported a positive detection; this makes it one of the best observed stellar occultations by a TNO so far. Considering the rotational phase of 2003 VS 2 during the stellar occultation and the rotational light curve amplitude derived ( ∆ m = 0.264 ± 0.017mag), we obtained a mean area-equivalent diameter of D A eq = 545 ± 13km and a geometric albedo of 0.134 ± 0.010. By combining the rotational light curve information with the stellar occultation results, we derived the best triaxial shape for 2003 VS 2 , which has semiaxes a = 339 ± 5km, b = 235 ± 6km, and c = 226 ± 8km. The derived aspect angle of 2003 VS 2 is θ = 59° ± 2°or its supplementary θ = 121° ± 2°, depending on the north-pole position of the TNO. The spherical-volume equivalent diameter is D V eq = 524 ± 7km. If we consider large albedo patches on its surface, the semi-major axis of the ellipsoid could be ∼ 10 km smaller. These results are compatible with the previous ones determined from the single-chord 2013 and four-chord 2014 stellar occultations and with the e ﬀ ective diameter and albedo derived from Herschel and Spitzer data. They provide evidence that 2003 VS 2 ’s 3D shape is not compatible with a homogeneous triaxial body in hydrostatic equilibrium, but it might be a di ﬀ erentiated body and / or might be sustaining some stress. No secondary features related to rings or material orbiting around 2003 VS 2 were detected.
An object-oriented research of automatic train operation simulation system

This paper presents a model-based design scheme of automatic train operation (ATO) simulation system so that the simulation system could have good extensibility, reusability and maintainability. The analysis, design and implementation of such a system have been completed and it has been used to simulate the Beijing Metro Line 1 Automatic Train Operation System.
Relationship of Smoking and COVID-19: Myths and Reality

The alarming spread of novel corona virus, severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), has resulted to an ongoing pandemic of corona virus disease since 2019. Due to this the virus is popularly known as Covid 19 virus. The world has not been able to get rid of this disease and we are into the fourth wave. There have been numerous changes in the nature of the disease but it is still causing major disruptions all over the world. Tobacco use as smoking is a major cause of mortality as well as morbidity around the world. Nobody can dispute the ill effects of smoking on health. Surprisingly, there have been few reports about low incidence of smokers among Covid 19 patients. This article aims to review available literature on the subject and try to clear the misconceptions on this topic.
A M-Health Platform for Supporting Clinical Data Integration and Service Delivery: An Example from Augmentative and Alternative Communication Intervention.

Improving the quality of healthcare while simultaneously reducing its overall costs remains a challenge. One of the recommended approaches for achieving this goal is to build high quality data collection and reporting systems to facilitate evidence-based practice (EBP), which emphasizes the importance of using the solid evidence available to make optimal clinical decisions. Along with the rapid adoption of mobile technologies in health care, many clinicians also use smartphones and tablets to collect and integrate clinical data. Verbal communication is an essential skill for human beings and a major factor that influences the overall quality of life. People with communication disabilities (PwCD) may benefit from Augmentative and Alternative Communication (AAC) intervention. However, existing AAC technologies are not currently able to provide efficient real-time and clinically relevant performance measures to speech language pathologists. This work combines mobile and web technologies with AAC intervention to create an integrated platform with a better data analytics approach to support data collection, integration, and reporting, as well as to streamline the workflow of AAC clinical service delivery. To achieve these research goals, three studies were conducted: 1) Exploration; 2) Design & Implementation; and 3) Evaluation. The first study identified the clinical needs and IT requirements of the platform. The second study implemented this platform, including a mobile AAC app, a web-based portal, and data analysis procedures. The last study evaluated the integrated platform and compared the platform to other existing data collection and reporting approaches. The usability and feasibility studies of the mobile AAC app were conducted with able-bodied individuals, health professionals, and PwCD. All participants agreed that the app establishes an alternative treatment protocol for communication rehabilitation, which incorporates AAC intervention with self-learning and real-time monitoring. Overall, the study results confirm that the integrated platform provides the ability to collect comprehensive clinical evidence, automatically analyze collected data in real time, and generate clinically relevant performance measures through an easily accessible web portal. The evaluation concluded that the integrated platform offers a better clinical data analytics approach for AAC clinical service delivery.
Restoration options for the Amazon

The Science Panel for the Amazon is an unprecedented initiative convened under the auspices of the United Nations Sustainable Development Solutions Network (SDSN). The SPA is composed of over 200 preeminent scientists and researchers from the eight Amazonian countries, French Guiana, and global partners. These experts came together to debate, analyze, and assemble the accumulated knowledge of the scientific community, Indigenous peoples, and other stakeholders that live and work in the Amazon. The Panel is inspired by the Leticia Pact for the Amazon. This is a first-of-its-kind Report which provides a comprehensive, objective, open, transparent, systematic, and rigorous scienti fic assessment of the state of the Amazon’s ecosystems, current trends, and their implications for the long-term well-being of the region, as well as opportunities and policy relevant options for conservation and sustainable development. Abstract This chapter examines site-specific opportunities and approaches for restoring terrestrial and aquatic systems, focusing on local actions and their immediate benefits. Landscape, catchment, and biome-wide considerations are addressed in Chapter 29. Conservation approaches are addressed in Chapter 27
A Measuring Device for Residual Thickness of Brake Shoe of Railcar Based on Deep Learning

At present, the residual thickness of brake shoe of metro vehicles is mainly measured manually by naked eyes or simple ruler, which has some problems such as low detection efficiency, large subjective randomness and poor engineering applicability. Therefore, this paper proposes a device for measuring the residual thickness of brake shoes of railcar based on deep learning method. Firstly, a residual thickness measuring device includes parts of image acquisition module, image positioning and segmentation module, and image correction module. Then for each module, the article conducted the related experiments for verifying the accuracy of the system. The results show that the brake shoe residual thickness measurement device proposed in this paper has higher accuracy and better robustness than manual detection, and has obvious advantages in detection time consumption.
Segmented Thermoelectric Generator Modeling Using Artificial Neural Networks

With the goal of net-zero expected to be accomplished in recent decades, the development of a thermoelectric generator, one of the energy harvesting technologies, is important. Along with efforts to discover more cost-effective thermoelectric materials, geometric and structural optimization of thermoelectric generators is essential to maximize power and efficiency. This work demonstrates a segmented thermoelectric generator, one of the advanced structures of a thermoelectric generator, modeling using artificial neural networks. After training the artificial neural networks, we have achieved 98.9% accuracy compared to COMSOL simulation results under constant temperature difference while speeding up the computational speed over a few thousand times. This new approach illustrates the advantages of the modeling of segmented thermoelectric generators
Effects of topsoiling on rates of erosion and erosion processes in coal mine spoil banks in Utrillas, Teruel, Spain

ABSTRACT Runoff production and soil erosion, produced by energetic Mediterranean storms, are amongst the first environmental impacts of opencast mining activity and amongst the main limiting factors in achieving self-sustaining reclaimed landscapes in Teruel. This paper aims to understand the geomorphological response of topsoiled and overburden-covered banks. This is considered essential in improving soil management and designing accurate erosion control plans. Runoff and erosion rates were recorded after every rainfall in permanent plots for one year in both overburden and topsoiled banks. In the same way experiments were conducted with a portable rainfall simulator to follow the response evolution throughout time. Grass communties control topsoiled bank evolution, leading to an improvement in the hydric characteristics of the topsoil during ecological succession. Physical-chemical soil properties condition the erosion processes in overburden-covered banks. No improvement in infiltration rate nor in cre.
zk-SNARKs Analysis and Implementation on Ethereum

Given the high complexity of understanding zero-knowledge SNARK proofs, this document provides a relaxed guide to introduce anyone who can understand how cryptosystems work into zk-SNARKs. Essentially, this master’s thesis aims to be a reference document about zk-SNARKs covering the mathematical composition of these proofs clearly and their application in a general purpose public blockchain such as Ethereum. In this dissertation there is no discussion about security or optimization. Also, real world applications schemes are proposed in order to illustrate the applicability of these proofs.
DESIGN OF A MULTI-MODULE AND FULLY INTEGRATED SWITCHED-CAPACITOR DC-DC POWER CONVERTER

DC-DC converters are one of the main components of a power management unit and, concretely, the Switched-Capacitor DC-DC Power Converters (SCPC) are recently used due to their high efficiency and the possibility of being fully integrated. In this thesis, it is designed a SCPC converter in a 140 nm technology with the objective of replace a low frequency continuous-time regulator. With an input voltage of 20 V, the SCPC converter designed achieve an output voltage of 3.3 V and an output current of 5 mA with a 69% of efficiency. Different mathematical optimization and minimization methods have been developed in order to reduce the losses of the converter and accomplish the specifications. A multi-module structure is implemented with the objective of reducing the total area. Also, it is designed a control loop to provide robustness and load regulation in front of process and temperature variations.
Chapter 2: A Practitioner’s Guide to Measurement in Learning Analytics - Decisions, Opportunities, and Challenges

What is our data measuring, why are we measuring it, and what can we infer from our measurements? These are key questions for models of learning, and the focus of this chapter. This chapter discusses the role of measurement in transitioning from predictive models of learning to models from which meaningful explanations about learning can be inferred. We consider how to associate latent constructs of learning with observable data from a variety of data sources relevant to learning contexts, illustrated with examples from recent LAK proceedings. We also review common sources of errors that arise with a variety of data collection instruments, and highlight the challenges and opportunities for progressing valid and reliable measurement of both learning itself and factors related to the learning process.
Secured Personal Data Storage Platform for Private Clouds

Generated data by users is increasing daily and maintaining the personal data storage hardware is costly. Cloud data storage are getting popular for their user friendly and cost effective features. On the other hand, user privacy violation is an obstacle for adoption of cloud storage. Therefore, the recent growing interest in both public cloud and private storage services, shows the demand for solutions that are focusing on privacy awareness of users. Increasing the security and privacy related issues in cloud storages indicate a demand for an action to improve the security of data storage and increase privacy awareness. In this thesis, a novel trust level based solution for cloud data storage is introduced. This solution emphasizes in utilizing hybrid cloud technologies. This solution provides a simple user interface based on colors and it gives the possibility of selecting the storing places very easily and efficiently. Furthermore, to have a detail requirements of our solution a survey study based on questionnaire is administered and a proof of concept prototype is developed.
University of Birmingham Analysis and adaptive mitigation scheme of low-frequency oscillations in railway traction power systems

—The diffusion of modern electric trains equipped with high-power voltage-source converters has introduced new dynamic interactions with the traction power system that may create unexpected low-frequency oscillations . This paper presents for the first time a detailed analysis of the operating condition of electric trains and traction network, revealing that specific changes of the operating conditions of the train-network system are responsible for the oscillations and may lead to instability. The study is carried out with an analytical dynamic model considering the transient direct current control and focusses on understanding how the mismatch between the actual parameters of the train-network syste and those used by the controller affects system dynamic and stability. It is shown that the retuning of controller parameters improves the dynamic performance of the train-network system, and hence an adaptive control is proposed to mitigate low frequency oscillations with minimal change and cost to the original system. Simulation and experimental results are presented in the paper to fully validate the proposed control method. This paper presents a comprehensive analysis of the stability of the train-network interconnected system for operating conditions different from the rated ones. LFO are analyzed by a new small-signal model of the train-network system adopting transient direct current control that takes into account simultaneously multiple trains and light load conditions for the case of shared converters. The small-signal model is used to investigate the causes and the dynamic effects of LFO for real operating conditions and clearly reveals the mismatch between the actual controller and control objectives, which is a plausible theoretical explanation of LFO in electric railways. Moreover, the stability and dynamic performance analysis with Bode and eigenvalue plots are undertaken to explore the effects of control parameters. This allows a better understanding of the laws for tuning the control-lers and developing a practical way of mitigating LFO. Finall a new adaptive mitigation scheme with minimal impact to the original systems is proposed to adaptively select the suitable parameters of the controller according to the actual load power. The remainder of the paper common trains-network performance
An Explorative Study of Emotional Intelligence in Education Industry: Schutte’s Self Emotional Intelligence Test on Management Students and Technology Acceptance during COVID-19 Pandemic

[Abstract] Educationists in India facing heat in terms of changing competency requirements and challenges. The quality of education depends on effective teaching methods and the efficiency of learning. The application of emotional intelligence in and outside the classroom improves teaching-learning processes, as it involves positive psychological behaviors and active interaction to speed up the emotions involved in the learning process. With the arrival of the COVID-19 pandemic crisis, it is more challenging to balance online classes and personal interaction to realize, understand, and regulate the emotions of the students. Therefore, the study explored and analyzed the literature on emotional intelligence in the education industry concerning students. Additionally, the study aimed to measure the emotional intelligence of management students on an instrument based on 33-items measured on a 5-point Likert scale from seven management colleges including both bachelor’s and master’s degrees. The responses were collected from 450 students of various management colleges of Pune city using an online survey questionnaire. The study also put some light on demographic traits and digital tools used by them during the COVID-19 pandemic lockdown to maintain online classes conceivable and includes suggestions for academic institutions in the context of emotional intelligence and technology acceptance by the students.
Oops... Code Execution and Content Spoofing: The First Comprehensive Analysis of OpenDocument Signatures

OpenDocument is one of the major standards for inter-operable office documents. Supported by office suites like Apache OpenOffice, LibreOffice, and Microsoft Office, the OpenDocument Format (ODF) is available for text processing, spreadsheets, and presentations on all major desktop and mobile operating systems. When it comes to governmental and business use cases, OpenDocument signatures can protect the integrity of a doc-ument’s content, for example, for contracts, amendments, or bills. Moreover OpenDocument signatures also protect document’s macros. Since the risks of using macros in documents is well-known, modern office applications only enable their execution if a trusted entity signs the macro code. Thus, the security of ODF documents often depends on the correct signature verification. In this paper, we conduct the first comprehensive analysis of OpenDocument signatures and reveal numerous severe threats. We identified five new attacks and evaluated them against 16 office applications on Windows, macOS, Linux, iOS, Android, and two online services. Our investigation revealed 12 out of 18 applications to be vulnerable for macro code execution, although the application only executes macros signed by trusted entities. For 17 of 18 applications, we could spoof the content in a signed ODF document while keeping the signature valid and trusted. Finally, we showed that at-tackers possessing a signed ODF could alter and forge the signature creation time in 16 of 18 applications. Our research was acknowledged by Microsoft, Apache OpenOffice, and LibreOffice during the coordinated disclosure.
Determination of Crude Fiber Content and Total Sugars in Correlation with the Production Process and Storage Time

In this original scientific paper, the content of crude fiber and total sugars in three different fruit products (cherry compote, rosehip marmalade and plum jam) in correlation with the production process and storage time was examined. All tests were conducted in the Laboratory of Food Technology, Faculty of Technology, University of Tuzla. The test results showed that in all fruit products a higher content of non-reducing sugars than reducing and sucrose was recorded. Also, the highest content of crude fiber was obtained in the S5 sample for rosehip marmalade and was 1.11%, while the lowest was recorded in the S1 sample for cherry compote and was 0.011%.
Next Generation GaN-based Architectures: From 240W USB-C Adapters to 11kW EV On-Board Chargers with Ultra-high Power Density and Wide Output Voltage Range

The Power Point Presentation will be available the conference. Abstract The inherent advantages of GaN devices compared to their Silicon counterparts, i.e. absence of reverse recovery charge, lower output and gate charges, etc., enable the operation of power electronic systems based on GaN devices at considerably higher switching frequencies. This facilitates the design of systems with power densities far beyond the limits of state-of-the-art Si systems, which is demonstrated in this paper with two very different examples: a 240 W mobile charger with two USB-C output ports covering very wide output voltages of 5-48 V, and a three-phase 11 kW on-board charger with an output voltage range of 250-1000 V.
Modeling Temporal effects of Group Dynamics on user preferences using Hypergraphs

Personalized recommendations based upon previous behavioral and personal data of a user is an increasingly important problem. Specially, with internet becoming ubiquitous in tandem with ongoing enhancements in human computer interaction, the amount of ﬁne grained user data like social interaction, group interaction, user-item/ user-user transaction data, etc. is ever increasing and therefore, posing new challenges in modelling user preferences. This work aims to model evolving user behavior using Hypergraphs which have been proposed as an effective tool to capture such complex higher order user relationships with multiple entities (like users, items, etc) involved. Most of the current hypergraph based models lack the temporal dimension which is an essentially important aspect, specially when modeling user preferences which are inherently variable over time. We are proposing a hyper-graph label propagation approach with temporal regularization framework which is shown to be easily adaptable to capture various temporal constraints through penalization. Given a user’s previous transactions and social interaction history the model ranks the various items for a queried user.