Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Index based on LZ77 (thesis)

Domains like bioinformatics, version control systems, collaborative editing systems (wiki), and others, are producing huge data collections that are very repetitive. That is, there are few differences between the elements of the collection. This fact makes the compressibility of the collection extremely high. For example, a collection with all different versions of a Wikipedia article can be compressed up to the 0.1% of its original space, using the Lempel-Ziv 1977 (LZ77) compression scheme. Many of these repetitive collections handle huge amounts of text data. For that reason, we require a method to store them efficiently, while providing the ability to operate on them. The most common operations are the extraction of random portions of the collection and the search for all the occurrences of a given pattern inside the whole collection. A self-index is a data structure that stores a text in compressed form and allows to find the occurrences of a pattern efficiently. On the other hand, self-indexes can extract any substring of the collection, hence they are able to replace the original text. One of the main goals when using these indexes is to store them within main memory. In this thesis we present a scheme for random text extraction from text compressed with a Lempel-Ziv parsing. Additionally, we present a variant of LZ77, called LZ-End, that efficiently extracts text using space close to that of LZ77. The main contribution of this thesis is the first self-index based on LZ77/LZ-End and oriented to repetitive texts, which outperforms the state of the art (the RLCSA self-index) in many aspects. Finally, we present a corpus of repetitive texts, coming from several application domains. We aim at providing a standard set of texts for research and experimentation, hence this corpus is publicly available.
Heterogeneity in fibromyalgia based upon cognitive and physical performance and psychological symptomology

Purpose:This study sought to investigate the existence of subgroups within a fibromyalgia (FM) sample based on physical and cognitive performance measures, as well as self‐report psychological measures. A multisystem disorder characterized by widespread musculoskeletal pain and co‐morbid conditions, FM can lead to declines in cognitive functioning and difficulty with psychological health. Data sources:Community participants (n = 57 women) recruited from support groups and university center databases provided documentation of having met the criteria for diagnosis of FM. Measures included validated performance and self‐report instruments. Analysis was completed using hierarchical cluster analysis; a four cluster solution was chosen for its level of interpretability. The resulting model identified four distinct subgroups based upon patterns of performance and symptomology. Significant group differences were found on pain, fatigue, stiffness, and level of physical activity. Conclusions:Study results support the existence of subgroups among the FM population based on levels of cognitive and physical performance and psychological symptoms. Implications for practice:Nurse practitioners aware of potential subgroups within FM should be better prepared to recommend treatment options for patients that target subgroup characteristics (e.g., high vs. low levels of psychological symptoms).
Association of intracluster correlation measures with outcome prevalence for binary outcomes in cluster randomised trials

In cluster randomised trials, a measure of intracluster correlation such as the intraclass correlation coefficient (ICC) should be reported for each primary outcome. Providing intracluster correlation estimates may help in calculating sample size of future cluster randomised trials and also in interpreting the results of the trial from which they are derived. For a binary outcome, the ICC is known to be associated with its prevalence, which raises at least two issues. First, it questions the use of ICC estimates obtained on a binary outcome in a trial for sample size calculations in a subsequent trial in which the same binary outcome is expected to have a different prevalence. Second, it challenges the interpretation of ICC estimates because they do not solely depend on clustering level. Other intracluster correlation measures proposed for clustered binary data settings include the variance partition coefficient, the median odds ratio and the tetrachoric correlation coefficient. Under certain assumptions, the theoretical maximum possible value for an ICC associated with a binary outcome can be derived, and we proposed the relative deviation of an ICC estimate to this maximum value as another measure of the intracluster correlation. We conducted a simulation study to explore the dependence of these intracluster correlation measures on outcome prevalence and found that all are associated with prevalence. Even if all depend on prevalence, the tetrachoric correlation coefficient computed with Kirk’s approach was less dependent on the outcome prevalence than the other measures when the intracluster correlation was about 0.05. We also observed that for lower values, such as 0.01, the analysis of variance estimator of the ICC is preferred.
Performance Analysis and Sampled-Data Controller Synthesis for Bounded Persistent Disturbances

The disturbance rejection problem is one of the main issues in control system analysis and synthesis, and system norms are used to evaluate the effect of disturbances on the system outputs. Depending on the nature of the disturbance affecting the system and performance measures, one can define a number of different system norms. Among various system norms, the L∞-induced norm of control systems is used to deal with the maximum amplitude of the regulated output for the worst persistent exogenous input with a unit magnitude. Because evaluating the maximum magnitude of the regulated output is very important in many control systems and bounded persistent disturbances such as steps and sinusoids are often encountered in control systems, the L∞-induced norm control problem should be solved for performance evaluation and performance improvement. For the computation of the L∞induced norm of continuous-time linear time-invariant systems, we need to integrate the absolute value of the impulse response of the given system (i.e., we nee to compute the L1 norm of the impulse response), where the response corresponds to the kernel function in the convolution formula for the input/output relation. Hence, the study associated with the treatment of the L∞-induced norm has been called the L1 problem. However, it is very difficult to compute this integral exactly or even approximately with an explicit upper bound and lower bound. Indeed, there have been no results on an exact computation of the L∞-induced norm as well as its upper and lower bounds. On the other hand, sampled-data systems arise in feedback control when continuoustime plants are to be controlled by discrete-time controllers, and they occur naturally in feedback control applications, such as process control, attitude control and so on. The study associated with sampled-data systems shows promise in providing deeper insight and improved performance in many applications since discrete-time controllers are so widespread in feedback control systems. Thus, the study associated with sampled-data systems plays important roles in practical senses and is one of the main issues in the analysis and synthesis of control systems. In particular, a number of studies of sampled-data systems relevant to the disturbance rejection problem have been addressed by many researchers. However, there have been no studies on giving an exact computation of the L∞-induced norm as well as its
Studies on the composition and distribution of the different sibling species of Anopheles gambiae complex within Katagum area in Bauchi state, Nigeria

A study of the adult indoor resting mosquitoes was conducted to identify the different sibling species of Anopheles gambiae s.l. , their abundance and distribution in Katagum area of Bauchi State, Nigeria. A total of two hundred (200) females mosquitoes were collected from June to December, 2016 in the study area. Out of these, 40 (20%) were Anophelines while 160 (80%) were Culicines. The month of July recorded the highest number of mosquitoes with peak values of 17 and 62 for the An. gambiae s.l. and the culicine species respectively. Then there after the number of both species of mosquitoes started to decline. However, in December no mosquito species was recorded at all from the sampling sites. Results from the molecular identification (PCR) of the different sibling species of the An. gambiae s.l. collected from the study areas, revealed that An. gambiae s.s. and An. arabiensis were the only two sibling species of the An. gambiae complex were recorded during this period of study. These two sibling species were found to occur together in all the sampling sites except in Azare where An. gambiae s.s was only found alone. With regards to the indoor resting density of these sibling species of the An. gambiae complex in this study, it was found that higher population of An. gambiae s.s were recorded indoors than An. arabiensis which were more recorded outdoors.
Chapter 7 Species Survival Probabilities 7 . 1

As in the previous chapters, we are interested in a set of threatened species, S = {s1, s2,. , sm}, and a set of zones that we can decide whether or not to protect, Z = {z1, z2,. , zn}. It is hypothesized that protecting a zone increases the chances of survival, in that zone, of the species that live there and in which we are interested. It is also assumed that the effects generated by the protection of the zones are independent. In other words, the chances of survival of a species in one zone depend only on whether the zone is protected or not; they do not depend on decisions that are made with regard to other zones. Thus, the main characteristic of the different models presented in this chapter lies in the fact that the uncertainty – which has many sources – concerning the survival of species sk in zone zi is reflected by a certain probability, and this for all i 2 Z 1⁄4 f1; 2;:::; ng and for all k 2 S 1⁄4 f1; 2;:::;mg. Note that these probabilities are generally difficult to establish since it is particularly difficult, in this field as in many others, to predict the future based on past events. First, it is assumed that the survival probability of species sk in zone zi is equal to pik if zone zi is not protected and qik in the opposite case. Note that this model is very general since the values pik and qik can be equal to 0 for some couples (i, k). In particular, some protected zones do not contribute to the protection of certain species. This also enables, for example, to consider a zero survival probability for certain species in unprotected zones. In a second step, it is assumed, as before, that the protection of zone zi ensures the survival of species sk in this zone with the probability qik but it is realistically admitted that a certain error may affect this probability. More precisely, it is assumed that the survival probability of species sk in the protected zone zi belongs to the interval 1⁄2qik dik ; qik þ cik , and this for all i 2 Z and for all k 2 S . On the other hand, to simplify the presentation, it is considered, in this case, that there is no uncertainty about the survival probabilities of the species in unprotected zones and that all these probabilities are equal to 0.
Speech emotion recognition based on improved masking EMD and convolutional recurrent neural network

Speech emotion recognition (SER) is the key to human-computer emotion interaction. However, the nonlinear characteristics of speech emotion are variable, complex, and subtly changing. Therefore, accurate recognition of emotions from speech remains a challenge. Empirical mode decomposition (EMD), as an effective decomposition method for nonlinear non-stationary signals, has been successfully used to analyze emotional speech signals. However, the mode mixing problem of EMD affects the performance of EMD-based methods for SER. Various improved methods for EMD have been proposed to alleviate the mode mixing problem. These improved methods still suffer from the problems of mode mixing, residual noise, and long computation time, and their main parameters cannot be set adaptively. To overcome these problems, we propose a novel SER framework, named IMEMD-CRNN, based on the combination of an improved version of the masking signal-based EMD (IMEMD) and convolutional recurrent neural network (CRNN). First, IMEMD is proposed to decompose speech. IMEMD is a novel disturbance-assisted EMD method and can determine the parameters of masking signals to the nature of signals. Second, we extract the 43-dimensional time-frequency features that can characterize the emotion from the intrinsic mode functions (IMFs) obtained by IMEMD. Finally, we input these features into a CRNN network to recognize emotions. In the CRNN, 2D convolutional neural networks (CNN) layers are used to capture nonlinear local temporal and frequency information of the emotional speech. Bidirectional gated recurrent units (BiGRU) layers are used to learn the temporal context information further. Experiments on the publicly available TESS dataset and Emo-DB dataset demonstrate the effectiveness of our proposed IMEMD-CRNN framework. The TESS dataset consists of 2,800 utterances containing seven emotions recorded by two native English speakers. The Emo-DB dataset consists of 535 utterances containing seven emotions recorded by ten native German speakers. The proposed IMEMD-CRNN framework achieves a state-of-the-art overall accuracy of 100% for the TESS dataset over seven emotions and 93.54% for the Emo-DB dataset over seven emotions. The IMEMD alleviates the mode mixing and obtains IMFs with less noise and more physical meaning with significantly improved efficiency. Our IMEMD-CRNN framework significantly improves the performance of emotion recognition.
Semi-automated generation of networked vulnerability-attack countermeasure trees for security analysis

Cybersecurity threats are unavoidable in todays world. So there is a need for development of well-researched security formalisms and metrics. If the security of a networked system is measurable in a qualitative and quantitative way, we can enhance security through various techniques. Several theoretical security models have been developed to conduct security analysis, which utilise the security formalisms and metrics in order to quantify security. However, in practice these models are usually constructed manually, which is cumbersome and error prone. Also, with an increase in the size of networks it is no longer feasible to manually construct these models. There are also no reliable tools for automatic extraction of essential information on vulnerabilities of a system, estimation of possible attacks based on the known vulnerabilities and evaluating existing attack detection capabilities and mitigation measures. Hence, there is a need for automated generation of security models for ease of security analysis. While security models have been developed with improved scalability taking into account information about detection and mitigation techniques, semi-automated generation of these models from the information collected from security solutions (such as intrusion detection systems (IDSs), firewalls, vulnerability scanners etc.) presents unique challenges. Furthermore, such models do not incorporate vulnerability information explicitly, which is needed for a better security analysis of a system. So there is a need to develop a new security formalism that also includes the vulnerability information. This thesis presents an approach towards semi-automated generation of a novel security formalism named Networked Vulnerability-Attack Countermeasure Tree (nVACT). nVACT is a two-layered security model consisting of network reachability information in the upper layer and security event information in the lower layer. Security analysis of a networked system using nVACT can be used to assess various security metrics (e.g. return on attack, effectiveness of countermeasures applied, return on investment in countermeasures etc).
Model reduction analysis using Hankel Norm Approximation on discrete-time linear system with the special shape of matrix A

A system can describe real problems that occur in the environment. The system is the result of modeling of real problems. Based on the results of real problem modeling, it often produces a linear system with a special shape of matrix A. In general, to represent the actual conditions of the real problem accurately, a system with a large order is required. While on the other hand, in terms of analysis and computation of the system, it is not desired to have a system with a large order. Therefore, we propose to use a model reduction that produces a system with small orders but without significant errors. One of the commonly used model reduction methods is Hankel Norm Approximation (HNA). In this research, we analyze the process of model reduction with the HNA method in the discrete-time linear system which has special forms of the matrix A. The process of reduction of this model begins with the formulation of the initial system with a special shaped matrix A. Next, we analyze the nature of stability, controllability and observability of the initial system. Then a balanced system is formed and followed by model reduction using HNA. Based on the results of the model reduction simulation using HNA, it was found that the reduced system with HNA has the same performance and properties as the initial system, which is stable, controllable, and observable. Besides that, HNA model reduction is suitable for use at high frequencies and has a fast computation time.
Gag Polyprotein Isolate JH32 of HIV1 group M subtype B 3D Structure Determination by Multithreading Method - A Bioinformatics Approach

The discovery of potential drug to arrest the replication of HIV-1 even in these modern days is a growing task. Drugs in market are targets the enzymes reverse transcriptase, integrase and protease. The encapsulation gene of HIV genome that is GAG is found to be more conserve. So the functional and structural conservation of HIV-1 Gag implies structure based drug design. Now HIV-1 replication can be successfully blocked by targeting gag polyprotein, a new promising avenue for the drug class. Gag’s role is helping in forming the encapsulation of the virus if that is disturbed the whole Virus is vulnerable. The challenge is to determine the structure of Gag poly-protein as its structure is still unknown. The crystal structure is unavailable in the structural databases like PDB. The sequence of gag polyprotein of HIV1 group M subtype B (isolate JH32) (HIV-1) was downloaded to determine its structure. As there is no template close to the target a method called refinement through multi threading was used. The percentage of favored regions by Ramchandran diagram is 89.6%, allowed region is 5.0% and amino acids in outlier region is 5.4%.
Magnetic Resonance Imaging Findings in Patients with Brugada Syndrome

In 1992, Brugada and Brugada1 described a disease entity in patients with a history of aborted sudden cardiac death and a distinct ECG pattern, consisting of right bundle branch block with ST segment elevation in the right precordial leads and normal QT interval in the absence of any structural heart disease (as determined by routine clinical, biochemical, echocardiographic, and angiographic examinations). This subgroup of patients appears to be at much greater risk for cardiac arrest due to ventricular fibrillation (VF). 2 Brugada et al.3 found no clear underlying heart disease in their patients and as recently as 2001 argued that there is no structural basis for this disorder. Other centers, however, have shown morphologic and functional abnormalities, mainly in the right ventricle (RV) of this group of patients.4-7 It has been suggested that Brugada syndrome was a minor form of RV dysplasia (arrhythmogenic right ventricular cardiomyopathy [ARVC]). 8-10 In 1998, the first genetic mutations associated with Brugada syndrome were reported.11 Mutations in the SCN5A gene that encodes for the human cardiac sodium channel (located in chromosome 3) have been linked with this syndrome. These genes do not appear to be related to loci described in RV dysplasia in other chromosomes. However, in several studies patients with Brugada syndrome had findings in common with patients with ARVC. The findings included fatty or fibrofatty replacement of the RV free wall, RV dilation, and regional wall-motion abnormalities. This has led to the debate of whether, despite the genetic etiology identified for Brugada patients, the syndrome is one of a number of disease entities involving structural and functional abnormalities of the RV with resulting arrhythmias. In this issue of the Journal, Papavassiliu et al.12 report on the use of magnetic resonance imaging (MRI) in finding morphologic and functional differences between patients diagnosed with Brugada syndrome and a group of controls. Cardiac MRI is becoming one of the most versatile imaging tools in cardiology. It affords an excellent view of the structure of the heart and provides not only morphologic data but also tissue characterization. This has been helpful in studying the RV abnormalities usually seen with ARVC, such as fatty infiltration of the RV free wall. In addition, MRI currently is considered the best method for studying global and regional function of the right and left ventricles. Volumetric and mass information from MRI are the most accurate and reproducible of any available technique. MRI is particularly useful for studying the RV because the other methods avail-
Caracterización de la región cromosómica 15q11-q13 del genoma humano. Variabilidad genómica en el autismo e identificación de ncRNAs

La tesis doctoral con titulo "Caracterizacion de la region cromosomica 15q11-13 del genoma humano. Variabilidad genomica en el autismo e identificacion de ncRNAs" se basa en el estudio de la region cromosomica 15q11-q13, centrandonos en los aspectos de la variabilidad genomica y su significado funcional. En la primera parte del estudio buscamos reordenamientos de 15q11-q13 en pacientes con autismo, mediante la genotipacion de marcadores microsatelites cubriendo dicha region, y definimos una delecion polimorfica de origen y tamano variable en la region 15q11.2. Segun los resultados del test FBAT, la delecion esta asociada al trastorno autista. Analizamos la organizacion de esta region delecionada y encontramos evidencias que sugerian la presencia de ncRNAs en esta region. Identificamos 2 nuevos miRNAs y 19 RNAs funcionales de una clase no conocida hasta hoy, especificos de primates y con bajos niveles de expresion al menos en cerebro, higado, rinon y testiculo. Segun los estudios de prediccion de targets de los miRNAs identificados en la region 15q11.2 del genoma humano, estos podrian participar en el desarrollo y funcionamiento del sistema nervioso central, asi como en el origen del autismo, los sindromes de Angelman y de Prader-Willi y otras enfermedades genomicas