Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship Between Attention, Dyslexia, and Convergence Insufficiency

Dyslexia and attention deficit hyperactivity disorder are two distinct conditions belonging to the same class of frequently and comorbidly diagnosed childhood and adolescent developmental disorders. Further complicating treatment and diagnoses is convergence insufficiency, a visual disorder, with symptoms that can appear similar to dyslexia’s diagnostic criteria. ADHD and dyslexia have a worldwide prevalence of 5-12% each among the school-age population and 4-10% of young adults. As many as 1 million U.S. ADHD diagnoses are situational with undocumented, pre-existing conditions (e.g., convergence insufficiency, dyslexia). Convergence insufficiency, characterized by an inability to converge the eyes smoothly as a focal object moves from distance to near, affects 2-8% of the worldwide population. Given the number of people worldwide who may be diagnosed, misdiagnosed, or undiagnosed by these three disorders, it is of value to explore the intersectionality of these conditions among college-aged students. This project investigated the relationship between self-reported scores on a standard ADHD measure, as well as ADHD diagnoses, dyslexia, and convergence insufficiency using optometric and neuropsychological assessments. We found ADHD diagnosis and its self-reported symptoms were significantly correlated with total scores on the Adult Reading History Questionnaire, dyslexia diagnoses, and the Convergence Insufficiency Symptom Survey. All three self-report assessments and near visual acuity significantly correlated; indicating that as visual acuity improves, total assessment scores decrease. These combined results highlight a distinct and important relationship between vision, attention, and reading and support a more holistic assessment in the identification, diagnosis, intervention, and treatment of cognitive problems pertaining to reading and learning.
Discriminant Analysis: A Comment.

The frequent incorrect application or interpretation of statistical methods in publications that use statistics has been noted by a number of authors (e.g., Altman, 1982; Bartko, 1986; Fletcher, Rice, & Ray, 1978; Oakes, 1986; Strube & Hartmann, 1982; Wade & Hartmann, 1978; White, 1979). Bartko indicated, for example, that about half of publications of this type examined in several recent reviews had statistical errors ranging from minor to major, "including false conclusions" (p. 1199). More recently, the frequent occurrence of statistical errors in substantive articles refereed by Long led him to devote an entire book to this subject (Long, 1988). Perhaps as a consequence of the growing awareness of the problem, articles that attempt to inform researchers about statistical methods and promote their correct use have been appearing with increasing frequency in most of the empirical journals of the American Psychological Association. Betz's (1987) recent article on the use of discriminant function analysis in counseling psychology research is of this type. Betz noted that "it is hoped that [the article] will increase readers' interest in and ability to appropriately use discriminant analysis [DA]" (p. 402). The article, in fact, correctly and accurately describes many features of DA that are of use to researchers in counseling psychology. However, there are also some sections of Betz's article that may result in misinterpretation or misapplication of DA. These sections are concerned with (a) methods of testing the significance of discriminant function weights, (b) goals of classification rules, and (c) methods of testing the significance of differences between observed and chance total hit rates. In this article I present information related to these topics and hope to increase the likelihood of the correct application and interpretation of DA. The first topic is considered more important, and is consequently discussed in more detail, than either the second or third topics.
Alumina Extraction From Low-Grade Diasporic Bauxite By Pyro-Hydro Metallurgical Process

Diasporic bauxite samples obtained from Isparta-Yalvaç region were crashed and sieved with a 100 m sieve. After determining the composition by chemical analysis, grain size distribution of the samples were determined. Then the characterization of the sample was recorded by static and dynamic thermal analysis and XRD studies. Bauxite samples added CaO and Na2CO3 were calcined at 900 oC. Alumina extraction studies were performed for 20, 40, 60, 80 minutes of calcination time and 15, 30, 45, 60 minutes of leach time and 25, 50, 75, 100 oC of leach temperature. It was found that the maximum leach yield (85.04 %) was obtained at 60 minutes of calcination time and 15 minutes of leach time and 50 oC of leach temperature. These results demonstrated that the optimum conditions for dissolving to this type of iron-rich low grade diasporic bauxite minerals at low-temperature and alkaline concentration were
Activation of the T-cell oncogene LMO2 after gene therapy for X-linked severe combined immunodeficiency.

Gene therapy, in which a retrovirus was used to carry the relevant gene (IL2Rγc) into a patient's hematopoietic stem cells, was used to treat 10 boys with X-linked severe combined immunodeficiency (SCID). A syndrome resembling T-cell leukemia developed in two of the boys. In both boys — and a third in whom leukemia has not developed — the retrovirus integrated into the same genomic site, the locus of LMO2, which is involved in childhood lymphocytic leukemia. This article reviews the molecular biology of these events and discusses their implications for the future of gene therapy.
Decentralized model predictive control for UUV collaborative missions

We describe an approach with considerations for the limitations of operating underwater, including low bandwidth communications, for performing UUV collaborative missions. We implement a decentralized model predictive control (DMPC) algorithm to control teams of unmanned underwater vehicles (UUVs) that simultaneously optimizes vehicle control inputs to explicitly account for the limitations of operating in an underwater environment. We formulate these challenges and limitations, such as vehicle to vehicle communications and collision avoidance, as sub-objectives that are directly including in the optimization problem rather than treating them as constraints. This allows the vehicles to dynamically prioritize the sub-objectives in situ and ensures that a solution to the optimization problem. Additionally, we breakdown the mission into collaborative tasks that allow for a dynamic mission in cases of unplanned circumstances, such as a lost UUV. We demonstrate this scheme in a simulation of a mine counter measure (MCM) scenario in which a heterogeneous mix of UUVs collaborate to detect, locate, and report mine like objects.
Metastability of Asymptotically Well-Behaved Potential Games

One of the main criticisms to game theory concerns the assumption of full rationality. Logit dynamics is a decentralized algorithm in which a level of irrationality (a.k.a. "noise") is introduced in players' behavior. In this context, the solution concept of interest becomes the logit equilibrium, as opposed to Nash equilibria. Logit equilibria are distributions over strategy profiles that possess several nice properties, including existence and uniqueness. However, there are games in which their computation may take time exponential in the number of players. We therefore look at an approximate version of logit equilibria, called metastable distributions, introduced by Auletta et al. [SODA 2012]. These are distributions that remain stable (i.e., players do not go too far from it) for a super-polynomial number of steps (rather than forever, as for logit equilibria). The hope is that these distributions exist and can be reached quickly by logit dynamics. We identify a class of potential games, called asymptotically well-behaved, for which the behavior of the logit dynamics is not chaotic as the number of players increases so to guarantee meaningful asymptotic results. We prove that any such game admits distributions which are metastable no matter the level of noise present in the system, and the starting profile of the dynamics. These distributions can be quickly reached if the rationality level is not too big when compared to the inverse of the maximum difference in potential. Our proofs build on results which may be of independent interest, including some spectral characterizations of the transition matrix defined by logit dynamics for generic games and the relationship of several convergence measures for Markov chains.
Specific Absorption Rate Evaluation for Passengers Using Wireless Communication Devices Inside Vehicles With Different Handedness, Passenger Counts, and Seating Locations

Radiation from mobile phones inside vehicles, which are semiopen metallic enclosures with irregular shapes and apertures, has been a major concern and has warranted investigation in past years. In this paper, the specific absorption rate (SAR) induced in mobile phone users inside a vehicle was evaluated using different scenarios, including handedness, passenger counts, and seating locations. A computer simulation for SAR distributions in a human body was performed based on the finite-difference time-domain method. The SAR values in mobile phone users in free space were also compared to those inside a vehicle; results illustrated that the maximum SAR induced for mobile phone users in a vehicle is 5% higher than those in free space, but the SAR results showed no significant difference for the handedness. By comparing the SAR values between mobile phone users and nonusers inside a vehicle with a passenger count and seating locations, it was observed that the SAR values around the nonusers' body varied much in different situations, and were higher than those in free space, in some circumstances.
From Textual Instructions to Sensor-based Recognition of User Behaviour

There are various activity recognition approaches that rely on manual definition of precondition-effect rules to describe user behaviour. These rules are later used to generate computational models of human behaviour that are able to reason about the user behaviour based on sensor observations. One problem with these approaches is that the manual rule definition is time consuming and error prone process. To address this problem, in this paper we outline an approach that extracts the rules from textual instructions. It then learns the optimal model structure based on observations in the form of manually created plans and sensor data. The learned model can then be used to recognise the behaviour of users during their daily activities.
Conceptual annotation of text patterns

Patterns are used as a fundamental means for analyzing data in many data mining applications. Many efficient techniques have been developed to discover patterns. However, the excessive number of discovered patterns and the lack of semantic information have made it difficult for a user to interpret and explore the patterns. A rough idea of the meanings of patterns can benefit the user in the process of exploring them. To address this issue, this paper presents a model for automatically annotating patterns with concepts. In addition, in a given context, the relative importance of each term that defines a concept is not the same. To define a context, there are a number of related information sources, such as documents, patterns, concepts, and an ontology. The question is which information sources are useful for estimating the relative importance of the terms? Should the most accurate one to be focused on or all of them be used to define the context? This research investigated these questions and defined an effective annotation context to estimate the relative importance of the terms, where the aim is to improve the performance of a machine that relies on the subject matter of a pattern set. The model is evaluated by comparing it with different baseline models on 2 standard datasets. The results show that the performance of the proposed model is significantly better.
The Relationship between Cartels and Economic Fluctuations

Various actions of market players, which violate fair competition, are harmful to the economy. But the most dangerous are cartels. It is recognized that cartels make a great harm to all market players and adversely affect national economy and its competitiveness. The question is whether the companies are more likely to make the cartel agreement in growing economy, or on the contrary – in recession? Various authors’ studies present different conclusions: 1) the economic downturn and demand uncertainty promotes the formation of cartels and 2) the economy increases, especially in emerging markets, firms tend to increase profits by making cartels. Probably there is no single answer, what relationship exists between the cartels and economic fluctuations, as it can be affected by various factors. This paper analyzes the situation of cartels in the country of small economy with developing culture of competition and evaluates the relationship between the cartels and the economic fluctuations. The empirical analysis is based on Lithuanian cases. This country is chosen because it corresponds to the features of the small economy with developing culture of competition. The specific of Lithuanian cartels justifies the necessity of evaluation the relationship between the cartels and the economic fluctuations. The lack of information is an obstacle to efficient and successful implementation of strategic decisions directing to the minimization of the number of cartel agreements and their negative impact on the economy. The research has shown that there is a moderate linear correlation between the cartels and the Lithuanian economic fluctuations. DOI: http://dx.doi. org/10.5755/j01.ee. 26.3. 7331
Strategies to Inject Spoofed Measurement Data

We study the problem of designing false measurement data that is injected to corrupt and mislead the output of a Kalman filter. Unlike existing works that focus on detection and filtering algorithms for the observer, we study the problem from the attacker's point-of-view. In our model, the attacker can corrupt the measurements by injecting additive spoofing signals. The attacker seeks to create a separation between the estimate of the Kalman filter with and without spoofed signals. We present a number of results on how to inject spoofing signals while minimizing the magnitude of the injected signals. The resulting strategies are evaluated through simulations along with theoretical proofs. We also evaluate the spoofing strategy in the presence of a $\chi^2$ spoof detector. The results show that the proposed strategy can successfully mislead a Kalman filter while ensuring it is not detected.
Jasmonic Acid Is a Key Regulator of Spider Mite-Induced Volatile Terpenoid and Methyl Salicylate Emission in Tomato1[w]

The tomato (Lycopersicon esculentum) mutant def-1, which is deficient in induced jasmonic acid (JA) accumulation upon wounding or herbivory, was used to study the role of JA in the direct and indirect defense responses to phytophagous mites (Tetranychus urticae). In contrast to earlier reports, spider mites laid as many eggs and caused as much damage on def-1 as on wild-type plants, even though def-1 lacked induction of proteinase inhibitor activity. However, the hatching-rate of eggs on def-1 was significantly higher, suggesting that JA-dependent direct defenses enhanced egg mortality or increased the time needed for embryonic development. As to gene expression, def-1 had lower levels of JA-related transcripts but higher levels of salicylic acid (SA) related transcripts after 1 d of spider mite infestation. Furthermore, the indirect defense response was absent in def-1, since the five typical spider mite-induced tomato-volatiles (methyl salicylate [MeSA], 4,8,12-trimethyltrideca-1,3,7,11-tetraene [TMTT], linalool, trans-nerolidol, and trans-β-ocimene) were not induced and the predatory mite Phytoseiulus persimilis did not discriminate between infested and uninfested def-1 tomatoes as it did with wild-type tomatoes. Similarly, the expression of the MeSA biosynthetic gene salicylic acid methyltransferase (SAMT) was induced by spider mites in wild type but not in def-1. Exogenous application of JA to def-1 induced the accumulation of SAMT and putative geranylgeranyl diphosphate synthase transcripts and restored MeSA- and TMTT-emission upon herbivory. JA is therefore necessary to induce the enzymatic conversion of SA into MeSA. We conclude that JA is essential for establishing the spider mite-induced indirect defense response in tomato.
Boundary Finding with Parametrically Deformable Models

Segmentation using boundary finding is enhanced both by considering the boundary as a whole and by using model-based global shape information. The authors apply flexible constraints, in the form of a probabilistic deformable model, to the problem of segmenting natural 2-D objects whose diversity and irregularity of shape make them poorly represented in terms of fixed features or form. The parametric model is based on the elliptic Fourier decomposition of the boundary. Probability distributions on the parameters of the representation bias the model to a particular overall shape while allowing for deformations. Boundary finding is formulated as an optimization problem using a maximum a posteriori objective function. Results of the method applied to real and synthetic images are presented, including an evaluation of the dependence of the method on prior information and image quality. >
FRAIGs: A Unifying Representation for Logic Synthesis and Verification

AND-INV graphs (AIGs) are Boolean networks composed of twoinput AND-gates and inverters. In the known applications, such as equivalence checking and technology mapping, AIGs are used to represent and manipulate Boolean functions. AIGs powered by simulation and Boolean satisfiability lead to functionally reduced AIGs (FRAIGs), which are “semi-canonical” in the sense that each FRAIG node has unique functionality among all the nodes currently present in the FRAIG. The paper shows that FRAIGs can be used to unify and enhance many phases of logic synthesis: from the representation of the original and the intermediate netlists derived by logic optimization, through technology mapping over multiple logic structures, to combinational equivalence checking. Experimental results on large public benchmarks confirm the practicality of using FRAIGs throughout the logic synthesis flow.
Fixed-Point Implementations of the Reciprocal, Square Root and Reciprocal Square Root Functions

Implementations of the reciprocal, square root and reciprocal square root often share a common structure. This article is a survey and comparison of methods (with only slight variations for the three cases) for computing these functions. The comparisons are made in the context of the same accuracy target (faithful rounding) and of an arbitrary fixed-point format for the inputs and outputs (precisions of up to 32 bits). Some of the methods discussed might require some form of range reduction, depending on the input's range. The objective of the article is to optimize the use of fixed-size FPGA resources (block multipliers and block RAMs). The discussions and conclusions are based on synthesis results for FPGAs. They try to suggest the best method to compute the previously mentioned fixed-point functions on a FPGA, given the input precision. This work compares classical methods (direct tabulation, multipartite tables, piecewise polynomials, Taylor-based polynomials, Newton-Raphson iterations). It also studies methods that are novel in this context: the Halley method and, more generally, the Householder method.
Error Analysis and Verification of an IEEE 802 . 11 OFDM Modem using Theorem Proving 1

IEEE 802.11 is a widely used technology which powers many of the digital wireless communication revolutions currently taking place. It uses OFDM (Orthogonal Frequency Division Multiplexing) in its physical layer which is an efficient way to deal with multipath, good for relatively slow time-varying channels, and robust against narrowband interference. In this paper, we formally specify and verify an implementation of the IEEE 802.11 standard physical layer based OFDM modem using the HOL (Higher Order Logic) theorem prover. The versatile expressive power of HOL helped us model the original design at all abstraction levels starting from a floating-point model to the fixed-point design and then synthesized and implemented in FPGA technology. We have been able to find a bug in one of the blocks of the design that is responsible for modulation which implementation diverts from the constellation provided in the IEEE standard specification. The paper also derives new expressions for the rounding error accumulated during ideal real to floating-point and fixed-point transitions at the algorithmic level and performs a formal error analysis for the OFDM modem in HOL.
A Graphical Visualization Tool for Analyzing the Behavior of Metaheuristic Algorithms

This paper proposes a visualization tool for analyzing the behavior of metaheuristic algorithms. It works by reproducing graphically the solutions generated in execution time. The tool was evaluated analyzing the Hybrid Grouping Genetic Algorithm for Bin Packing (HGGA_BP). It was used to solve a benchmark with 17 instances of the one dimensional Bin Packing problem (1D-BPP). The use of the visualization tool allowed identifying some logical errors in the program code which avoided the algorithm converge in some cases to the optimal solution. After correcting errors the HGGA_BP algorithm increased its efficiency until 48%, in some cases.
T 2 relaxometry to image fibrosis in patients with Crohn ’ s disease

(153.6±6.9 c.u. vs 108.3±3.9 c.u.). The ration between B1and B2-cells SDH activities characterized with 3 times B1-cells activity domination compared with control group (80% vs 20%). B-cells SDH activity and their number gradually decreased with increasing duration of the disease, mainly by virtue of the B2-cells parameters change. After the year of infliximab therapy it was observed significant B1-cells number augmentation in patients with nonsustained efficacy of the therapy (16% before 1 infusion vs 26.6% after 1 year). Moreover the period of infliximab tolerance development corresponded to B1-cells SDH activity augmentation. Patients with sustained infliximab therapy efficacy had higher B2-cells SDH activity compared with patients with nonsustained effect (113.0±3.2 c.u. vs 94.1±2.7 c.u.). Conclusions: Children with IBD were characterized with increase SDH activity of circulating B1-lymphocytes. Patients with nonsustained effect of infliximab therapy demonstrated gradually circulating B1-cells number increase along with B2-cells mitochondrial activity depression. The period of infliximab tolerance development corresponded to B1-cells SDH activity augmentation.
Human body orientation estimation using a committee based approach

Human body orientation estimation is useful for analyzing the activities of a single person or a group of people. Estimating body orientation can be subdivided in two tasks: human tracking and orientation estimation. In this paper, the second task of orientation estimation is accomplished by using HoG descriptors and other cues such as the velocity direction, the presence of face, and temporal smoothness. Three different classifiers: Gaussian Mixture Model, Neural Network and Support Vector Machine, are combined with the information from those cues to form a committee. The performance of the method is evaluated and the contribution to the final prediction of each classifier is assessed. Overall, the performance of the proposed approach outperforms the state-of-the-art method, both in terms of estimation accuracy, as well as computation time.