Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multigrid Method for the Helmholtz Equation with Optimized Coarse Grid Corrections

We study the convergence of multigrid schemes for the Helmholtz equation, focusing in particular on the choice of the coarse scale operators. Let $G_{\rm c}$ denote the number of points per wavelength at the coarse level. If the coarse scale solutions are to approximate the true solutions, then the oscillatory nature of the solutions implies the requirement $G_{\rm c} > 2$. However, in examples the requirement is more like $G_{\rm c} \gtrsim 10$, in a trade-off involving also the amount of damping present and the number of multigrid iterations. We conjecture that this is caused by the difference in phase speeds between the coarse and fine scale operators. Standard 5-point finite differences in two dimensions are our first example. A new coarse scale 9-point operator is constructed to match the fine scale phase speeds. We then compare phase speeds and multigrid performance of standard schemes with a scheme using the new operator. The required $G_{\rm c}$ is reduced from about 10 to about 3.5, with less dam.
Resolving Named Entities and Relations in Text for Applications in Literary Studies

Lately, there has been an increase of texts available in digital libraries. There is also an increased interest in capturing semantic relations expressed between entities from a large amount of texts, hoping to conduct more complex semantic tasks, such as question answering. However, traditional information extraction techniques have a hard time following this sudden trend, as these techniques rely heavily on manually annotated resources for training statistical models. This research work had one main objective: to adapt and evaluate two relation extraction systems that follow a new Information Extraction paradigm, usually referred to as Open-Domain Information Extraction (OIE), in order to extract relations from Portuguese literary texts. This new information extraction technique is able to scale to a massive amount of texts, without requiring as much human involvement. The two systems in focus are named ReVerb and OLLIE. Many tasks were addressed in order to obtain the results presented in this document, starting with the development of NLP models to process Portuguese texts, followed by the incorporation of these models into the OIE tools, and further changes in implementation details, resulting in two adapted systems that are able to process Portuguese texts. This document, therefore, formalizes the approaches in the relation extraction problems, involving the new OIE paradigm on literary texts, presenting an extensive evaluation with four diﬀerent literary books.
ICNIRP GUIDELINES ICNIRP GUIDELINES ON LIMITS OF EXPOSURE TO LASER RADIATION OF WAVELENGTHS BETWEEN 180 nm AND 1,000 mm International Commission on Non-Ionizing Radiation Protection*

VSince the publication of the ICNIRP Revision of the Guidelines on Limits of Exposure to Laser Radiation (ICNIRP 1996, 2000), further research supports amending the retinal thermal exposure limits in terms of spot size dependence, pulse duration dependence for short pulses and wavelength dependence between 1,200 nm and 1,400 nm. A detailed discussion of the rational for the changes is presented in the Appendix of these Guidelines (Rationale for updating the Guidelines). Health Phys. 105(3):271Y295; 2013
Securing and sharing clinical data

The low success rate of clinical trials for rare diseases is a growing concern. The cause for this failure lies in the segregation of clinical data, promoted by informed consents and international data protection laws. Only on the second half of 2012 medical and research communities have started the discussions and debates to address this problem. Some of the proposals are to put the majority of patient data openly available on the internet. However, studies on personal data exposure and usurpation reveal worrying consequences in cases of identity theft, as well as high ﬁnancial impacts for the state and insurance companies due to resulting lawsuits. The purpose of this work is to synthesize and formalize the legal requirements to deal with clinical data, resorting to an analysis targeting speciﬁcation beyond the sole technological perspective of the problem. Moreover, it properly frames the problem in the context of the already known data access control models. Additionally, it uses recent proposals in distributed authentication protocols to simplify the implementation process on a global scale. Finally, it demonstrates the applicability of Linked Data technologies to cope with the required heterogeneity of clinical data, as well as to promote the integration of data across multiple healthcare institutions.
Overexpression of Mitochondrial Transcription Factor A Ameliorates Mitochondrial Deficiencies and Cardiac Failure After Myocardial Infarction

Background— Mitochondrial DNA (mtDNA) copy number is decreased not only in mtDNA-mutation diseases but also in a wide variety of acquired degenerative and ischemic diseases. Mitochondrial transcription factor A (TFAM) is essential for mtDNA transcription and replication. Myocardial mtDNA copy number and TFAM expression both decreased in cardiac failure. However, the functional significance of TFAM has not been established in this disease state. Methods and Results— We have now addressed this question by creating transgenic (Tg) mice that overexpress human TFAM gene and examined whether TFAM could protect the heart from mtDNA deficiencies and attenuate left ventricular (LV) remodeling and failure after myocardial infarction (MI) created by ligating the left coronary artery. TFAM overexpression could ameliorate the decrease in mtDNA copy number and mitochondrial complex enzyme activities in post-MI hearts. Survival rate during 4 weeks of MI was significantly higher in Tg-MI than in wild-type (WT) littermate.
Normative comparisons for large neuropsychological test batteries: User-friendly and sensitive solutions to minimize familywise false positives

ABSTRACT Introduction. In neuropsychological research and clinical practice, a large battery of tests is often administered to determine whether an individual deviates from the norm. We formulate three criteria for such large battery normative comparisons. First, familywise false-positive error rate (i.e., the complement of specificity) should be controlled at, or below, a prespecified level. Second, sensitivity to detect genuine deviations from the norm should be high. Third, the comparisons should be easy enough for routine application, not only in research, but also in clinical practice. Here we show that these criteria are satisfied for current procedures used to assess an overall deviation from the norm—that is, a deviation given all test results. However, we also show that these criteria are not satisfied for current procedures used to assess test-specific deviations, which are required, for example, to investigate dissociations in a test profile. We therefore propose several new procedures to assess such test-specific deviations. These new procedures are expected to satisfy all three criteria. Method. In Monte Carlo simulations and in an applied example pertaining to Parkinson disease, we compare current procedures to assess test-specific deviations (uncorrected and Bonferroni normative comparisons) to new procedures (Holm, one-step resampling, and step-down resampling normative comparisons). Results. The new procedures are shown to: (a) control familywise false-positive error rate, whereas uncorrected comparisons do not; (b) have higher sensitivity than Bonferroni corrected comparisons, where especially step-down resampling is favorable in this respect; (c) be user-friendly as they are implemented in a user-friendly normative comparisons website, and as the required normative data are provided by a database. Conclusion. These new normative comparisons procedures, especially step-down resampling, are valuable additional tools to assess test-specific deviations from the norm in large test batteries.
PulsekCompressionkofkShortkWavekInfraredk OpticalkParametrickAmplifiedkPulseskusingkak HollowkCorekCapillary

In this thesis, a method for producing few-cycle short wavelength infrared pulses is presented. The pulses are created by down converting the 800 nm output of a Ti:Sapphire laser in an optical parametric amplifier to 1300 nm, and spectrally broadened in a hollow core fiber in order to obtain a short transform limited pulse duration. Further, they are to be compressed using the anomalous dispersion of a potassium dihydrogen phostphate crystal. The aim of the compression is to generate few cycle pulses in the short wave infrared regime for future high-order harmonic generation experiments. By increasing the wavelength, the energy of the harmonics will be increased, which would allow for new kinds of experiments to be conducted. The pulses have been successfully broadened to support a four cycle duration, however, compression of the pulses remains to be done.
Cone Tracing of Human Hair Fibers

Rendering hair presents several challenges. Hair ﬁbers are very thin, requiring very high super-sampling rates in order to render images without aliasing artifacts. Moreover, typical bounding volume hierarchy acceleration structures only use axis aligned bounding boxes, which do not tightly ﬁt the hair primitives, generating a very large number of intersection tests with few actual hits. Both these facts have a negative impact on the rendering performance. In this work we aim at improving the rendering performance with two contributions: a cone based solution and a hybrid bounding volume hierarchy solution. With the cone based solution we are able to produce aliasing free images with just a super-sampling of 2x2 and produce images of comparable quality to the ones produced with a stochastic ray tracer with a 16x16 super-sampling rate while requiring a much lower rate and achieving speedups of up to 4. With the hybrid bounding volume hierarchy, which uses both axis aligned and oriented bounding boxes to bound hair primitives, we are able to achieve an average intersection test reduction of 53%, while only increasing the memory footprint by 11%.
Economic costs of gender inequality in health and the labor market: India's untapped potential

COPYRIGHT © 2023 Khan, Khan, Khan, Zaman, Khan, Rosman, Indrianti and Hassan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Economic costs of gender inequality in health and the labor market: India’s untapped potential
ROP chain generation: a semantic approachs

Memory corruption vulnerabilities are still present in software today. While exploit mitigation techniques like Data Execution Prevention (DEP) prevent code injection, and Address Space Layout Randomization (ASLR), which randomizes the base address of memory regions, have made their exploitation very challenging, it is still feasible. Return Oriented Programming (ROP) is the exploitation technique of choice for all modern exploits, because it requires no code injection and can therefore bypass most of the existing security protections including DEP, and has even been shown powerful in bypassing ASLR. ROP is based on reusing small pieces of code already present in the application that terminate in a ret instruction and chaining them together in what is called a rop-chain to achieve code execution. However, the development of rop-chains by hand can sometimes be a diﬃcult and slow process, due to restrictions in the payload (e.g. no zero bytes; only ASCII characters), a low amount of valuable gadgets available in the binary, etc. and so there are tools that attempt to do this automatically. Most of these tools are capable of extracting gadgets and building a rop-chain for easier to exploit binaries, but fall short on harder examples. In this thesis we propose to evaluate the best existing rop-chain generation tools and develop a new solution that improves on them. This solution, will work by lifting all supported assembly languages to a common intermediate representation, extracting and classifying the gadgets and then, using semantic searches with an SMT solver, try to ﬁnd gadgets that fulﬁl predetermined or user supplied exploitation recipe steps.
CollecTA: Collective Tour Advisor

Every time we visit a new city there is a huge eﬀort made in understanding its dynamic, i.e. what are the relevant locations within that city in each time period, for there are large amounts of data to sift through. Although several attempts have been made to combine information from several sources, the majority focus on geographic data, lacking on time representation. The main motivation for our work is the shortage of most applications in showing a city dynamics in an easy way for the users. In this dissertation we have studied solutions related to 2D and 3D visualizations of spatio-temporal data to understand their adequacy to our objectives. A comparative analysis is then performed between the most relevant solutions, serving as base to the initial decisions made in the design of the developed solutions. Wethen describe four solutions developed to test and validate the key aspects taken from the related work analysis. After the conclusion of the prototypes we performed an experimental evaluation, with the help of real users, to assess which of the visualizations was the most suitable to represent spatio-temporal data and convey a location dynamics. Our main contribution with this work was the development of those four distinct visualizations and its evaluation, which allowed us to take some important conclusions from the results and also some implications to the design of similar techniques.
Online Monte Carlo Planning for Autonomous Robots: Exploiting Prior Knowledge on Task Similarities

Planning in large state spaces is a key problem in robot autonomy applications. In this paper we evaluate an extended version of the Partially Observ-able Monte Carlo Planning (POMCP) algorithm on simulated (Gazebo) and real environments for instances of Rocksample , where a TurtleBot is used as an agent. The extended POMCP planner exploits prior knowledge about task similarities to reduce the explored state space improving robot performance. Results show that the proposed method signiﬁcantly outperforms the standard POMCP with an improvement of average discounted return up to 60.7%. This improvement implies reduced number of steps performed by the robot, shorter path lengths, reduced total running times and better energy management in long-term deployments. The main contributions are the integration of the extended POMCP planner into simulated and real robotic platforms, and performance comparison between standard and extended POMCP planners in these environments.
Using the Order Book and Machine Learning for Cryptocurrency Trading

This thesis presents a new computational approach for proﬁt optimization on cryptocurrency trading, using trade and order book data from a major digital asset trading platform of four digital currencies (Bitcoin, Ethereum, Litecoin and Bitcoin Cash) in the United States Dollar (USD) and Euro (EUR) markets. An end-to-end solution was designed, starting with the database generation, information extraction, trading algorithm, simulation and ending with a dynamic report of the results. All the parts of the system are designed in a microservice architecture to ensure that they are scalable, strongly encapsulated and tightly scoped components. Three use cases where considered for the trading system where the ﬁrst two use order book volume variation to assess suitable trading periods whilst the last one uses an ARIMA model to forecast price ﬂuctuation and consequently serve as a veriﬁcation mechanism to the ﬁrst two test cases during a simulation. Furthermore, a new type of trailing stop called Percentage Stop Order is introduced, allowing proﬁt improvement. Monthly test periods were used alongside diﬀerent types of trading positions to all test scenarios to ﬁnd the most performing strategy according to the market’s situation. The results obtained managed to surpass the gains from the Buy & Hold strategy up to 22,72% and reducing losses up to 33,24%.
Economic integration in North America: Changes in US trade policy and the effects on Texas regional exports to Mexico

Texas is the leading US state exporter to Mexico, trading oil products, automobile components and electronics. The USMCA will impose a restructuring of the North American supply chains to meet the new input content requirements. In order to evaluate the impact of the changes in tariffs arising from the new rules of origin requirements, an econometric model with different tariff scenarios was estimated. The estimations indicate that the distance to Texas and the size of the economies of the states of Mexico are factors that impact Texas exports to Mexico. Tariffs under the USMCA would have a minor but positive effect if the input content requirement of the USMCA are met. Foreign direct investment showed positive effects on trade, indicating the existence of value chains between Texas and Mexico. The results suggest that polices to encourage trade between Texas and Mexico would require the development of transportation infrastructure and the strengthening of the communication channels between the private sector and institutions in Texas and Mexico to promote investment in strategic sectors.
Distributed Stochastic Gradient MCMC

Probabilistic inference on a big data scale is becoming increasingly relevant to both the machine learning and statistics communities. Here we introduce the first fully distributed MCMC algorithm based on stochastic gradients. We argue that stochastic gradient MCMC algorithms are particularly suited for distributed inference because individual chains can draw mini-batches from their local pool of data for a flexible amount of time before jumping to or syncing with other chains. This greatly reduces communication overhead and allows adaptive load balancing. Our experiments for LDA on Wikipedia and Pubmed show that relative to the state of the art in distributed MCMC we reduce compute time from 27 hours to half an hour in order to reach the same perplexity level.
The User-Level Scheduling of Divisible Load Parallel Applications With Resource Selection and Adaptive Workload Balancing on the Grid

This paper presents a hybrid resource management environment, operating on both application and system levels developed for minimizing the execution time of parallel applications with divisible workload on heterogeneous grid resources. The system is based on the adaptive workload balancing algorithm (AWLB) incorporated into the distributed analysis environment (DIANE) user-level scheduling (ULS) environment. The AWLB ensures optimal workload distribution based on the discovered application requirements and measured resource parameters. The ULS maintains the user-level resource pool, enables resource selection and controls the execution. We present the results of performance comparison of default self-scheduling used in DIANE with AWLB-based scheduling, evaluate dynamic resource pool and resource selection mechanisms, and examine dependencies of application performance on aggregate characteristics of selected resources and application profile.
Spoken Interaction with Synthetic Entities

The way man interacts with the machine has been changing over the years. Technologies thought in the science fiction domain are becoming a reality. Examples of this are recent advances in systems based on touch, gesture and speech. Dialogue systems are an example of interactive systems that allow users to interact using natural language. This type of systems is intended to simplify the interaction, making it more natural as if interacting with another human. Using voice to control machinery is not new. Even the first personal computers had sufficient computing power to recognize simple dialog and synthesize rudimentary speech. Nonetheless, we are seeing this form of interaction increasingly being used to interact with cars (allowing the driver to concentrate on the road), homes, telephony services, and even news casting. Because it is natural to communicate verbally, using this means of communication to interact with physical devices would be interesting. With the developments in robotics and automation, we can see a future where we have machines capable of imitating the human behavior or create emotional connections with their users. To communicate with these machines it would be interesting to use natural language. Unfortunately, the current Dialog Systems main focus is to handle problems directly related with natural language processing/generation, discourse context, etc. However, even with the state of the art dialogue systems, the difficulty is not on how to understand or generate speech, but how to perceive the meaning of what is said, or planning what is going to be said. There is another class of systems that focuses on mimicking human behavior. Agent systems [16] provide the software backbone for synthetic characters. Those systems react to stimuli, normally called perceptions, from the environment, producing actions that affect that environment, and handle tasks like planning, reasoning, and acting. They are normally used to design agents that live in a world (real or virtual). They also maintain complex representations of world knowledge.
A Sketch-Based Interface for Modeling Articulated Figures

Building articulated models with contact surfaces is a common task in Computer Graphics and Multibody Dynamics settings. However, articulated models such as armatures, rigs or kinematic structures are usually built with tedious mouse-keyboard inputs or, even worse, text-based interfaces where the user numerically specifies body transformations and joint types. Programs like Blender, Maya or OpenSim use this kind of approach. Alternatively, sketching on an interactive surface provides a familiar way to define such articulated models as the user can draw directly the content. In this paper, a sketch-based interface which aids the design of articulated models is here presented. In order to evaluate modeling efficiency, we did a comparative study between the proposed interface and conventional WIMP software, as well as integrating superovoidal shapes as primitives in our piece of software due to its vast use in illustration. User tests were done on both lay and professional users that did 3D modeling, along with some others trying to determine how to calligraphically recognize superovoids. We prove that the interface enables speed sculpting that can be used not only in humanoid design but for an arbitrary character or mechanical system and determine a way to classify superovoids calligraphically. A type of interface that, even though it gained the reputation of being used for “quick and dirty” tasks, has increasingly surprised us of its viability in the completion of highly detailed tasks.