Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the state of the art 2 . 1 Support Vector Machines

The aim of this research is to forecast the movement of SP&500 weekly. Support Vector Machine Classifier (SVMC) is used in order to examine the data. The data covers the period between 28/11/1997 and 29/12/2010. The inputs are technical analysis indicators such as the Moving Average Convergence Divergence (MACD) and the Relative Strength Index (RSI). SVMC is used to optimize the values of the MACD and RSI in order to determine the best situations to buy or sell the index. The two SVM outputs are the movement of the index and the probability of success to each forecast move. The best result has been achieved is a hit ratio of 92,3% using the SVM Classifier. The training data covers the period between 06/03/2009 and 06/10/2010. The testing data covers the period between 07/10/2010 and 29/12/2010. In conclusion, better results have been obtained analyzing short periods of S&P500 than using large periods.
Optimal Perimeter Control for Two Urban Regions With Macroscopic Fundamental Diagrams: A Model Predictive Approach

Recent analysis of empirical data from cities showed that a macroscopic fundamental diagram (MFD) of urban traffic provides for homogenous network regions a unimodal low-scatter relationship between network vehicle density and network space-mean flow. In this paper, the optimal perimeter control for two-region urban cities is formulated with the use of MFDs. The controllers operate on the border between the two regions and manipulate the percentages of flows that transfer between the two regions such that the number of trips that reach their destinations is maximized. The optimal perimeter control problem is solved by model predictive control, where the prediction model and the plant (reality) are formulated by MFDs. Examples are presented for different levels of congestion in the regions of the city and the robustness of the controller is tested for different sizes of error in the MFDs and different levels of noise in the traffic demand. Moreover, two methods for smoothing the control sequences are presented. Comparison results show that the performances of the model predictive control are significantly better than a “greedy” feedback control. The results in this paper can be extended to develop efficient hierarchical control strategies for heterogeneously congested cities.
Tree mortality of five major species on Hokkaido Island, northern Japan

The mortality rates of five major tree species (Abies sachalinensis, Acer mono, Magnolia obovata, Quercus crispula, Tilia japonica) on Hokkaido Island, northern Japan were modeled using logistic regressions based on the long-term observation of 8929 individuals in 65 permanent plots. Individual size, recent growth, one-sided and two-sided interactions with neighbors, climatic and topographic factors were used as independent variables in the logistic regressions, and relevant variables were selected using the stepwise method. For all species analyzed, the final models significantly explained tree mortality rates. The regression analyses indicated that individual size and/or recent growth had effects on tree mortality. A significant effect of one-sided interaction on tree mortality was detected for three species, and a significant effect of two-sided interaction was detected for two species. The interactions with neighbors were not necessarily competitive. For all species analyzed, climatic and topographic factors affected tree mortality. The mortality models obtained can be used for forest dynamics simulations. One ecological question was examined using these models. Species that can grow fast in forest stands with smaller basal areas tended to have high mortality rates in forest stands with larger basal areas. Some ecological characteristics of the analyzed species are described based on the results of the regressions.
Cognitive function in patients with stable coronary heart disease: Related cerebrovascular and cardiovascular responses

Chronic exercise has been shown to prevent or slow age-related decline in cognitive functions in otherwise healthy, asymptomatic individuals. We sought to assess cognitive function in a stable coronary heart disease (CHD) sample and its relationship to cerebral oxygenation-perfusion, cardiac hemodynamic responses, and V˙O2 peak compared to age-matched and young healthy control subjects. Twenty-two young healthy controls (YHC), 20 age-matched old healthy controls (OHC) and 25 patients with stable CHD were recruited. Cognitive function assessment included short term—working memory, perceptual abilities, processing speed, cognitive inhibition and flexibility and long-term verbal memory. Maximal cardiopulmonary function (gas exchange analysis), cardiac hemodynamic (impedance cardiography) and left frontal cerebral oxygenation-perfusion (near-infra red spectroscopy) were measured during and after a maximal incremental ergocycle test. Compared to OHC and CHD, YHC had higher V˙O2 peak, maximal cardiac index (CI max), cerebral oxygenation-perfusion (ΔO2 Hb, ΔtHb: exercise and recovery) and cognitive function (for all items) (P<0.05). Compared to OHC, CHD patients had lower V˙O2 peak, CI max, cerebral oxygenation-perfusion (during recovery) and short term—working memory, processing speed, cognitive inhibition and flexibility and long-term verbal memory (P<0.05). V˙O2 peak and CI max were related to exercise cerebral oxygenation-perfusion and cognitive function (P<0.005). Cerebral oxygenation-perfusion (exercise) was related to cognitive function (P<0.005). Stable CHD patients have a worse cognitive function, a similar cerebral oxygenation/perfusion during exercise but reduced one during recovery vs. their aged-matched healthy counterparts. In the all sample, cognitive functions correlated with V˙O2 peak, CI max and cerebral oxygenation-perfusion.
Quantitative contrast-enhanced ultrasound imaging: a review of sources of variability

Ultrasound provides a valuable tool for medical diagnosis offering real-time imaging with excellent spatial resolution and low cost. The advent of microbubble contrast agents has provided the additional ability to obtain essential quantitative information relating to tissue vascularity, tissue perfusion and even endothelial wall function. This technique has shown great promise for diagnosis and monitoring in a wide range of clinical conditions such as cardiovascular diseases and cancer, with considerable potential benefits in terms of patient care. A key challenge of this technique, however, is the existence of significant variations in the imaging results, and the lack of understanding regarding their origin. The aim of this paper is to review the potential sources of variability in the quantification of tissue perfusion based on microbubble contrast-enhanced ultrasound images. These are divided into the following three categories: (i) factors relating to the scanner setting, which include transmission power, transmission focal depth, dynamic range, signal gain and transmission frequency, (ii) factors relating to the patient, which include body physical differences, physiological interaction of body with bubbles, propagation and attenuation through tissue, and tissue motion, and (iii) factors relating to the microbubbles, which include the type of bubbles and their stability, preparation and injection and dosage. It has been shown that the factors in all the three categories can significantly affect the imaging results and contribute to the variations observed. How these factors influence quantitative imaging is explained and possible methods for reducing such variations are discussed.
Visuomotor Adaptation and Sensory Recalibration in Reversed Hand Movement Task

Visuomotor adaptation plays an important role in motor planning and execution. However, it remains unclear how sensorimotor transformations are recalibrated when visual and proprioceptive feedback are decoupled. To address this question, the present study asked participants to reach toward targets in a virtual reality (VR) environment. They were given visual feedback of their arm movements in VR that was either consistent (normal motion) with the virtual world or reflected (reversed motion) with respect to the left-right and vertical axes. Participants completed two normal motion experimental sessions, with a reversed motion session in between. While reaction time in the reversed motion session was longer than in the normal motion session, participants showed the learning improvement by completing trials in the second normal motion session faster than in the first. The reduction in reaction time was found to correlate with greater use of linear reaching trajectory strategies (measured using dynamic time warping) in the reversed and second normal motion sessions. This result appears consistent with linear motor movement planning guided by increased attention to visual feedback. Such strategical bias persisted into the second normal motion session. Participants in the reversed session were grouped into two clusters depending on their preference for proximal/distal and awkward/smooth motor movements. We found that participants who preferred distal-smooth movements produced more linear trajectories than those who preferred proximal-awkward movements.
Methods for Improving Resilience in Communication Networks and P2P Overlays

ABSTRACT Resilience to failures and deliberate attacks is becoming an essential requirement in most communication networks today. This also applies to P2P Overlays which on the one hand are created on top of communication infrastructures, and therefore are equally affected by failures of the underlying infrastructure, but which on the other hand introduce new possibilities like the creation of arbitrary links within the overlay. In this article, we present a survey of strategies to improve resilience in communication networks as well as in P2P overlay networks. Furthermore, our intention is to point out differences and similarities in the resilience-enhancing measures for both types of networks. By revising some basic concepts from graph theory, we show that many concepts for communication networks are based on well-known graph-theoretical problems. Especially, some methods for the construction of protection paths in advance of a failure are based on very hard problems, indeed many of them are in NP and can only be solved heuristically or on certain topologies. P2P overlay networks evidently benefit from resilience-enhancing strategies in the underlying communication infrastructure, but beyond that, their specific properties pose the need for more sophisticated mechanisms. The dynamic nature of peers requires to take some precautions, like estimating the reliability of peers, redundantly storing information, and provisioning a reliable routing.
The effect of past antibiotic exposure on diabetes risk.

OBJECTIVE Gut microbiota influence metabolic pathways related to the pathogenesis of obesity, insulin-resistance and diabetes. Antibiotic therapy can alter the microbiota, and is commonly used in western countries. We sought to evaluate whether past antibiotic exposure increases diabetes risk. RESEARCH DESIGN AND METHODS We conducted a nested case-control study using a large population-based database from the UK. The cases were defined as those with incident diagnosis of diabetes. For every case, four eligible controls matched on age, sex, practice-site, and duration of follow-up before index-date were selected using incidence-density sampling. Exposure of interest was antibiotic therapy >1 year before index-date. Odds ratios (ORs) and 95% CIs were estimated using conditional logistic regression. The risk was adjusted for BMI, smoking, last glucose level, and number of infections before index-date, as well as past medical history of coronary artery disease and hyperlipidaemia. RESULTS The study included 208 002 diabetic cases and 815 576 matched controls. Exposure to a single antibiotic prescription was not associated with higher adjusted diabetes risk. Treatment with two to five antibiotic courses was associated with increase in diabetic risk for penicillin, cephalosporins, macrolides and quinolones with adjusted OR ranging from 1.08 (95% CI 1.05-1.11) for penicillin to 1.15 (95% CI 1.08-1.23) for quinolones. The risk increased with the number of antibiotic courses and reached 1.37 (95% CI 1.19-1.58) for more than 5 courses of quinolones. There was no association between exposure to anti-virals and anti-fungals and diabetes risk. CONCLUSIONS Exposure to certain antibiotic groups increases diabetes risk.
Partidos políticos, preferência partidária e decisão eleitoral no Brasil (1989/2002)

This study analyzes the party preferences of Brazilian voters from 1989 to 2002 and some data on party rejection, relating these manifestations to voters decisions. There is a non-negligible share of voters who vote according to their party preferences, as well as a significant contingent of voters who express rejection of some party and do not vote for any of its candidates. The conclusions point to the need to reformulate the way Brazilian voters party inclinations are measured, including party rejection as a component of this measurement.
Comprehension of competing argument marking systems in two Australian mixed languages*

Crosslinguistic influence has been seen in bilingual adult and child learners when compared to monolingual learners. For speakers of Light Warlpiri and Gurindji Kriol there is no monolingual group for comparison, yet crosslinguistic influence can be seen in how the speakers resolve competition between case-marking and word order systems in each language. Light Warlpiri and Gurindji Kriol are two new Australian mixed languages, spoken in similar, yet slightly different, sociolinguistic contexts, and with similar, yet slightly different, argument marking systems. The different sociolinguistic situations and systems of argument marking lead to a difference in how speakers of each language interpret simple transitive sentences in a comprehension task. Light Warlpiri speakers rely on ergative case-marking as an indicator of agents more often than Gurindji Kriol speakers do. Conversely, Gurindji Kriol speakers rely on word order more often than Light Warlpiri speakers do.
Coordinated Multi-Robot Formation Control

A multi-robot system is formed when a group of robots interact with the environment as a single system. This system can also be in formation in order to accomplish tasks rather difficult or impossible to achieve with a single robot. This work presents results for a doctoral thesis research aiming the formation control of a mobile robot group in the active target tracking problem. All robots exchange information about their position (localization) in the world frame, and the target position and velocity forming a distributed system. Therefore, the main objective of this work is to search and track a target minimizing the total amount of uncertainty in the target’s observation, avoiding mates and obstacles, and obeying the characteristics imposed to the formation. A nonlinear model predictive controller was proposed in order to deal with the active target tracking problem through the formation of a multi-robot system. The formation controller created as the major contribution of this thesis is a nonlinear model predictive formation controller (NMPFC). This work also presents some contributions in the formation control concerning the obstacle avoidance, the temporary absence of the target and the formation control of a heterogeneous group (holonomic and nonholonomic robots). These contributions improved the formation making it versatile with dynamic uncertainties as well as the search and track of an initially absent target. Simulations and experiments with real robots were made, presented and discussed. Finally, this work is inserted in the FCT project PTDC/EEA-CRO/100692/2008 Perception-Driven Coordinated Multi-Robot Motion Control.
Sar optimum waveform design for target detection based on prior knowledge

With the development of SAR technology, it is now possible to transmit proper waveforms according to different missions. In this paper, we apply the optimum waveform design method to meet the application of special known-target detection and aim at enhance the target detection rate. Not only transmitted waveforms, but also both range and azimuth matched filters are designed based on maximizing the signal to interference plus noise ratio (SINR). Three waveform design solutions are given theoretically corresponding to different situations, and numerical simulation results are presented to prove the accuracy and effectiveness of our algorithm. Then conclusions are drawn based on our analysis and simulations.
Routing for Maximum System Lifetime in Wireless Ad-hoc Networks

An ad-hoc network of wireless static nodes is considered as it arises in a rapidly deployed, sensor based, monitoring system. Information is generated in certain nodes and needs to reach some designated gateway node. Each node may adjust its power within a certain range that determines the set of possible one hop away neighbors. Traac forwarding through multiple hops is employed when the intended destination is not within immediate reach. The nodes have limited initial amounts of energy that are consumed in diierent rates depending on the power level and the intended receiver. We propose algorithms to select the routes and the corresponding power levels such that the time until the batteries of the nodes drain-out is maximized. The algorithms are local and amenable to distributed implementation. When there is a single power level, the problem is reduced to a maximum ow problem with node capacities and the algorithm converges to the optimal solution. When there are multiple power levels then the achievable lifetime is within 90% of the optimal (that is computed by linear programming) most of the time. It turns out that in order to maximize the lifetime, the traac should be routed such that the energy consumption is balanced among the nodes in proportion to their energy reserves, instead of routing to minimize the absolute consumed power.
Point mutations in the leader boxA of a plasmid-encoded Escherichia coli rrnB operon cause defective antitermination in vivo

We have introduced point mutations into the leader boxA of a plasmid-encoded Escherichia coli rrnB operon to study the in vivo role of this regulatory element in the natural context of rRNA synthesis. The same mutations were previously shown to cause severe antitermination defects in vitro and in the context of a reporter gene assay. The plasmid-encoded rrnB mutant constructs studied here also contained point mutations in the 16S and 23S rRNA genes, which were used to distinguish rRNAs derived from plasmid and chromosomal rrn operons by primer extension analysis. Point mutations in boxA reduced the fraction of plasmid-derived rRNA in the cell from 75% to about 50%. The reduction was similar for both 30S and 50S subunits as well as 70S ribosomes, suggesting that no transcriptional polarity occurred between the expression of the 16S and 23S rRNA genes in plasmid rrnB operons carrying a mutant boxA. The boxA mutations do not affect the amount of transcription initiation, suggesting that a suboptimal leader boxA causes premature transcription termination at an early stage of transcription. Our results are consistent with a role for antitermination in the completion of full-length rrn transcripts but give no indications of posttranscriptional boxA functions.
Exploring the Metaphorical Models of Transgenderism

This article explores the metaphorical models English speakers employ in their understanding of transgenderism. Transgender is the term ascribed to those who have begun or completed a change in their sex characteristics from male to female or female to male. Using both qualitative and quantitative measures, I examine an archive of narrative data and a transition-specific corpus to show how spoken and written narrative support a spatially based representation of gender identity and transition. Two robust models are revealed in the data, each carrying a set of suppositions consequential to how speakers understand their lived experience. I show how metaphor-evoking trigger lexemes relate to each model and can be used jointly to demonstrate conceptual salience. This investigation should be seen as part of an ever-growing body of research directed at revealing the unconscious assumptions, which organize speakers’ comprehension of complex topics with political relevance (cf. Charteris-Black, 2004; Lakoff, 2002, 2004; Musolff, 2004).
Reducing a Biomarkers List via Mathematical Programming: Application to Gene Signatures to Detect Time-Dependent Hypoxia in Cancer

In biology and medical sciences, highly parallel biological assays spurred a revolution leading to the emergence of the '-omics' era. Dimensionality reduction techniques are necessary to be able to analyze, interpret, validate and take advantage of the tremendous wealth of highly dimensional data they provide. This paper is based on a DNA microarray study providing gene signatures for hypoxia. These gene signatures were tested on a large breast cancer data set for assessing their prognostic power by means of Kaplan-Meier survival, univariate, and multivariate analyses. We explore the use of several mathematical programming-based techniques that aim to reduce the gene signature sizes as much as possible while maintaining the key characteristics of the original signature, more precisely: the signature prognostic and diagnostic significance. The proposed signature reduction techniques have very interesting potential uses. Indeed, by downsizing the relevant data to a manageable size, one can then patent the core set of biomarkers and also create a dedicated assay (e.g.: on a customized array) for routine applications (e.g.: in the clinical set up) leading to individualized medicine capabilities. Our experiments show that the reduced hypoxia signatures reproduced qualitatively and quantitatively in a similar way that of the original ones.
Toll-like Receptor 2 and 4 (TLR2 and TLR4) Agonists Differentially Regulate Secretory Interleukin-1 Receptor Antagonist Gene Expression in Macrophages*

Treatment of macrophages with lipopolysaccharide (LPS) from Gram-negative bacteria or peptidoglycan (PGN) from Gram-positive bacteria activates multiple intracellular signaling pathways and a large, diverse group of nuclear transcription factors. The signaling receptors for PGN and LPS are now known to be the Toll-like receptors 2 and 4 (TLR2 and -4, respectively). While a large body of literature indicates that the members of the TLR family activate nearly identical cytoplasmic signaling programs, several recent reports have suggested that the functional outcomes of signaling via TLR2 or TLR4 are not equivalent. In the current studies, we compared the responses of the secretory IL-1 receptor antagonist (sIL-1Ra) gene to both LPS and PGN. Both LPS and PGN induced IL-1Ra gene expression; however, the combination of both stimuli synergistically increased sIL-1Ra mRNA expression and promoter activity, suggesting that the signals induced by PGN and LPS are not equivalent. While both LPS and PGN utilized the PU.1-binding sites in the proximal sIL-1Ra promoter region to generate a full response, additional distinct promoter elements were utilized by LPS or PGN. Activation of p38 stress-activated protein kinase was required for LPS- or PGN-induced IL-1Ra gene expression, but the p38-responsive promoter elements localized to distinct regions of the sIL-1Ra gene. Additionally, while the LPS-induced, p38-dependent response was dependent upon PU.1 binding, the PGN-induced, p38 response was not. Collectively, these data indicated that while some of the intracellular signaling events by TLR2 and TLR4 agonists are similar, there are clearly distinct differences in the responses elicited by these two bacterial products.