Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-band UWB sensor networks for high density sub-surface diagnostic: energy consumption and network set-up delay

Acquisition systems for sub-surface diagnostic (e.g., earthquake monitoring) require large number of sensors (geo-phones or accelerometers) to be deployed outdoor over large areas (tens of sqkm) to measure backscattered wave fields that are collected into a storage/processing unit (sink node). Aggregated data sets are analyzed to obtain an image of the sub-surface, monitor seismic activity, and declare possible alarm conditions. Cable based connectivity is the bottleneck of current systems, in terms of power consumption and degradation in accuracy. Replacing cables with wireless is now becoming attractive to improve the monitoring quality and reduce the probability of false negatives. Strict sampling synchronization constraint over large geographic areas, high precision sensor localization, high data-rate, and low delay are all topics that call for a scalable network system: Multi-Band Ultra Wide-Band radio transmissions (MB-UWB) play a key role as the only viable technology. This paper introduces the system and UWB network architecture based on ECMA-368 standard, moreover it provides a novel analytical tool to evaluate the energy consumption and delay during network set-up.
Price change and trading volume in a speculative market

This thesis is concerned with the daily dynamics of price change and trading volume in a speculative market. The first part examines the news-driven model of Tauchen and Pitts (1983), and develops this model to the point where it is directly testable. In order to implement the test a new method for creating a price index from futures contracts is proposed. It is found that news effects can explain some but not all of the structure of the daily price/volume relationship. An alternative explanation is presented, in which the model of Tauchen and Pitts is generalized in a non-linear fashion. In the second part of the thesis, the presence of a small amount of positive autocorrelation in daily returns is exploited through the development of a timing rule. This timing rule applies to investors who are committed to a purchase but flexible about the precise timing. The computation of the timing rule is discussed in detail. In practice it is found that this timing rule is unlikely to generate sufficiently large returns to be of interest to investors in a typical stock market, supporting the hypothesis of market efficiency. However, the incorporation of extra information regarding price/volume dynamics, as suggested by the analysis of Part I, might lead to a much improved rule.
Sectoral Shift and the Labor-Force Participation of Older Males in the United States, 1880-1940

A Traditional explanation for the fall in the labor force participation of older males in the era of industrialization is that it was in part produced by the decline in agriculture. A number of recent studies rejected this view based on the result that farmers were no less likely to retire than were nonfarmers. An examination of a longer period, however, shows that farmers were less likely to retire than were nonfarmers, as the conventional view suggests. Only the first decade of the twentieth century, which the revisionist view drew evidence from, exhibits the opposite pattern. This peculiarity of the years between 1900 to 1910 is likely to have resulted from the unusually high appreciation of farm property during the same period that would have stimulated retirement of farmers. According to the counterfactual LFPR of older males that would have resulted had there been no decline in the relative size of agriculture since 1820, the decrease in the labor force employed in farming accounts for about 20 percent of the fall in the LFPR of men 60 and older between 1880 and 1940.
Context-dependent Deactivation of the Amygdala during Pain

The amygdala has been implicated in fundamental functions for the survival of the organism, such as fear and pain. In accord with this, several studies have shown increased amygdala activity during fear conditioning and the processing of fear-relevant material in human subjects. In contrast, functional neuroimaging studies of pain have shown a decreased amygdala activity. It has previously been proposed that the observed deactivations of the amygdala in these studies indicate a cognitive strategy to adapt to a distressful but in the experimental setting unavoidable painful event. In this positron emission tomography study, we show that a simple contextual manipulation, immediately preceding a painful stimulation, that increases the anticipated duration of the painful event leads to a decrease in amygdala activity and modulates the autonomic response during the noxious stimulation. On a behavioral level, 7 of the 10 subjects reported that they used coping strategies more intensely in this context. We suggest that the altered activity in the amygdala may be part of a mechanism to attenuate pain-related stress responses in a context that is perceived as being more aversive. The study also showed an increased activity in the rostral part of anterior cingulate cortex in the same context in which the amygdala activity decreased, further supporting the idea that this part of the cingulate cortex is involved in the modulation of emotional and pain networks.
Number Theory: On the Central Critical Value of the Triple Product L–Function

We compute the central critical value of the triple product $L$-function associated to three cusp forms $f_1,f_2,f_3$ with trivial character for groups $\Gamma_0(N_i)$ with square free levels $N_i$ not all of which are $1$ and weights $k_i$ satisfying $k_1\ge k_2\ge k_3$ and $k_1<k_2+k_3$. This generalizes work of Gross and Kudla and gives an alternative classical proof of their results in the case $N_1=N_2=N_3$ with $k_1=k_2=k_3=2$.
The Effects of Note-Taking Strategy Training on Students’ Notes During Academic English Listening Tests

This study explored the effects of note-taking training on Korean college students’ notes during academic English listening tests. A total of 61 college students were randomly assigned to two different groups: Group A that later received training in note-taking strategy and Group B that did not. Group A received note-taking strategy training on three separate times, totaling 60 minutes (30 minutes, 15 minutes, and 15 minutes) that spread out over two months. The two groups took listening tests before and after Group A was trained. The results showed the positive effects of the notetaking training in relation with the groups’ note-taking behaviors. After training, the trained group used more and frequent notes whereas the untrained group’s number of notes decreased. Individual students who drastically increased the number of notes after training (in Test II) showed more systemic framework of notes for Test II than before training (in Test I). The present study is meaningful in that it utilized the different analyzing methods on the quality of notes compared with previous studies.
Molecular analysis of pancreatic acinar cell cystadenomas: Evidence of a non-neoplastic nature

The biology of pancreatic acinar cell cystadenomas has not been clearly defined. However, a non-neoplastic process, caused by a cell differentiation failure leading to a cystic transformation, has been discussed, as well as a benign neoplastic lesion. Pancreatic acinar cell cystadenomas usually consist of thin-walled unilocular or multilocular cysts, and mural nodules have been described in two cases of a recent series. In one of these nodules, chromosomal imbalances were detected, which provided preliminary evidence for a neoplastic process. The aim of the current study was to further characterize the lesions by molecular analyses. In four cases without mural nodules, the clonality was assessed by performing mutational analyses within the highly variable displacement-loop region of the mitochondrial DNA. As a result, no closer correlation was identified between different foci within the tumors than between the tumors and adjacent normal pancreatic acinar tissue, indicating polyclonality of these lesions. Further molecular analyses revealed no mutations of the β-catenin and K-ras genes. In addition, no immunohistochemical evidence was identified for mutations of Smad4 or p53. In conclusion, the results of the current study demonstrated that pancreatic acinar cell cystadenomas are non-neoplastic lesions, with the potential exception of those rare cases with mural nodules.
A Neural Mechanism Mediating the Impact of Episodic Prospection on Farsighted Decisions

Humans can vividly imagine possible future events. This faculty, episodic prospection, allows the simulation of distant outcomes and desires. Here, we provide evidence for the adaptive function of this capacity and elucidate its neuronal basis. Participants either imagined specific events of spending money (e.g., £35 in 180 days at a pub), or merely estimated what the money could purchase in the scenario. Imagining the future biased subsequent monetary decisions toward choices associated with a higher long-term pay-off. It thus effectively attenuated temporal discounting, i.e., the propensity to devalue rewards with a delay until delivery. Using functional magnetic resonance imaging, we implicate the medial rostral prefrontal cortex (mrPFC) in this effect. Blood oxygen level-dependent signal in this region predicted future-oriented choices on a trial-by-trial basis. Activation reflected the reward magnitude of imagined episodes, and greater reward sensitivity was related to less discounting. This effect was also associated with increased mrPFC–hippocampal coupling. The data suggest that mrPFC uses information conveyed by the hippocampus to represent the undiscounted utility of envisaged events. The immediate experience of the delayed reward value might then bias toward farsighted decisions.
An Abundance of Rare Functional Variants in 202 Drug Target Genes Sequenced in 14,002 People

A Deep Look Into Our Genes Recent debates have focused on the degree of genetic variation and its impact upon health at the genomic level in humans (see the Perspective by Casals and Bertranpetit). Tennessen et al. (p. 64, published online 17 May), looking at all of the protein-coding genes in the human genome, and Nelson et al. (p. 100, published online 17 May), looking at genes that encode drug targets, address this question through deep sequencing efforts on samples from multiple individuals. The findings suggest that most human variation is rare, not shared between populations, and that rare variants are likely to play a role in human health. A pharmacogenomics analysis shows how challenging it will be to associate rare variants with phenotypes. Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find rare variants are abundant (1 every 17 bases) and geographically localized, so that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. We conclude that because of rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk.
Prediction of assets behavior in financial series using machine learning algorithms

The prediction of financial assets using either classification or regression models, is a challenge that has been growing in the recent years, despite the large number of publications of forecasting models for this task. Basically, the non-linear tendency of the series and the unexpected behavior of assets (compared to forecasts generated in studies of fundamental analysis or technical analysis) make this problem very hard to solve. In this work, we present for this task some modeling techniques using Support Vector Machines (SVM) and a comparative performance analysis against other basic machine learning approaches, such as Logistic Regression and Naive Bayes. We use an evaluation set based on company stocks of the BVM&F, the official stock market in Brazil, the third largest in the world. We show good prediction results, and we conclude that it is not possible to find a single model that generates good results for every asset. We also present how to evaluate such parameters for each model. The generated model can also provide additional information to other approaches, such as regression models.
A PRELIMINARY STUDY EXPLORING THE PERFORMANCE OF SYSTEMS DEVELOPMENT IN FACE-TO-FACE SETTING IN RELATION TO TELEVISION VIDEO CONFERENCING

This article presents the findings of a preliminary study exploring the performance of systems development in a faceto-face setting in relation to a dispersed setting using television video conference. The study finds that systems development in the dispersed setting using television video conference can produce at the least same performance as in the face-to-face setting. It indicates that better training in virtual work and technologies can produce same performance in lesser amount of time. The study also explored the nature and content of interactions in both the groups, and found that the group using television video conferencing interacted for lesser amount of time on task-related activities.
Graphical Models for Structural Vector Autoregressions Alessio Moneta

The identification of a VAR requires differentiating between correlation and causation. This paper presents a method to deal with this problem. Graphical models, which provide a rigorous language to analyze the statistical and logical properties of causal relations, associate a particular set of vanishing partial correlations to every possible causal structure. The structural form is described by a directed graph and from the analysis of the partial correlations of the residuals the set of acceptable causal structures is derived. This procedure is applied to an updated version of the King et al. (American Economic Review, 81, (1991), 819) data set and it yields an orthogonalization of the residuals consistent with the causal structure among contemporaneous variables and alternative to the standard one, based on a Choleski factorization of the covariance matrix of the residuals. JEL classification: C32, C49, E32.
Competition in Multi-Modal Transport Networks: A Dynamic Approach

We analyze the behavior of market participants in a multi-modal commuter network, where roads are not priced, but public transport has a usage fee, which is set while taking the effects on the roads into account. In particular, we analyze the difference between markets with a monopolistic public transport operator, which operates all public transport links, and markets in which separate operators own each public transport link. To do so, we consider a simple dynamic transport network consisting of two serial segments and two parallel congestible modes of transport. We obtain a reduced form of the public transport operator’s optimal fare setting problem and show that, even if the total travel demand is inelastic, serial Bertrand–Nash competition on the public transport links leads to different fares than a serial monopoly; a result not observed in a static model. This results from the fact that trip timing decisions, and therefore the generalized prices of all commuters, are influenced by all fares in the network. We then use numerical simulations to show that, contrary to the results obtained in classic studies on vertical competition, monopolistic fares are not always lower than duopolistic fares; the opposite can also occur. We also explore how different parameters influence the price differential, and how this affects welfare.
Different Localizations and Cellular Behaviors of Leiomodin and Tropomodulin in Mature Cardiomyocyte Sarcomeres

Lmod is a muscle-specific actin nucleator that displays structural similarity to the filament pointed-end–capping protein, Tmod. The mechanisms of localizations of Lmod and Tmod in muscle sarcomeres are strikingly different. Lmod contributes to the organization of mature myofibrils through a mechanism that requires interaction with tropomyosin.
The Chandra Deep Field-North Survey. VIII. X-Ray Constraints on Spiral Galaxies from 0.4 < z < 1.5

We present a statistical X-ray study of spiral galaxies in the Hubble Deep Field-North and its flanking fields using the Chandra Deep Field-North 1 Ms data set. We find that ≈L* galaxies with 0.4 ≲ z ≲ 1.5 have X-ray luminosity and ratios of X-ray to B-band luminosity similar to those in the local universe. The data, however, are consistent with an increase in both by a factor of ≈2-3. We have also determined that typical spiral galaxies at 0.4 ≲ z ≲ 1.5 should be detected in the 0.5-2 keV band in the flux range (3-6) × 10-18 erg cm-2 s-1.
Comments on the construction of near-singularity cancellation transformations for triangle domains

Aspects of the construction of near-singularity cancellation transformations for triangular integration domains are discussed. Such transformations form the basis of near-singularity cancellation quadrature rules used in the method of moments (MoM). The main benefits of such rules are that they can easily be applied to curvilinear domains as well as in cases where higher-order basis functions are employed. Case studies are presented for the Duffy transformation, Arcsinh transformation and Radial-Angular / Augmented-Duffy transformation. The aim is to contribute to a better understanding of the construction and performance of such rules.
CrashLocator: locating crashing faults based on crash stacks

Software crash is common. When a crash occurs, software developers can receive a report upon user permission. A crash report typically includes a call stack at the time of crash. An important step of debugging a crash is to identify faulty functions, which is often a tedious and labor-intensive task. In this paper, we propose CrashLocator, a method to locate faulty functions using the crash stack information in crash reports. It deduces possible crash traces (the failing execution traces that lead to crash) by expanding the crash stack with functions in static call graph. It then calculates the suspiciousness of each function in the approximate crash traces. The functions are then ranked by their suspiciousness scores and are recommended to developers for further investigation. We evaluate our approach using real-world Mozilla crash data. The results show that our approach is effective: we can locate 50.6%, 63.7% and 67.5% of crashing faults by examining top 1, 5 and 10 functions recommended by CrashLocator, respectively. Our approach outperforms the conventional stack-only methods significantly.
In vivo study of myocardial elastography under graded ischemia conditions

The capability of currently available echocardiography-based strain estimation techniques to fully map myocardial abnormality at early stages of myocardial ischemia is yet to be investigated. In this study, myocardial elastography (ME), a radio-frequency (RF)-based strain imaging technique that maps the full 2D transmural angle-independent strain tensor in standard echocardiographic views at both high spatial and temporal resolution is presented. The objectives were to (1) evaluate the performance of ME on mapping the onset, extent and progression of myocardial ischemia at graded coronary constriction levels (from partial to complete coronary flow reduction), and (2) validate the accuracy of the strain estimates against sonomicrometry (SM) measurements. A non-survival canine ischemic model (n = 5) was performed by gradually constricting the left anterior descending (LAD) coronary blood flow from 0% (baseline blood flow) to 100% (zero blood flow) at 20% increments. An open-architecture ultrasound system was used to acquire RF echocardiograms in a standard full short-axis view at the frame rate of 211 fps, at least twice higher than what is typically used in conventional echocardiographic systems, using a previously developed, fully automated composite technique. Myocardial deformation was estimated by ME and validated against sonomicrometry. ME estimates and maps transmural (1) 2D displacements using RF cross-correlation and recorrelation; and (2) 2D polar (radial and circumferential) strains, derived from 2D (i.e. both lateral and axial) displacement components, at high accuracy. Full-view strain images were shown and found to reliably depict decreased myocardial function in the region at risk at increased levels of coronary flow reduction. The ME radial strain was deemed to be a more sensitive, quantitative, regional measure of myocardial ischemia as a result of coronary flow reduction when compared to the conventional wall motion score index and ejection fraction. Good agreement (0.22% strain bias, 95% limits of agreement) using Bland–Altman analysis and good correlation (r = 0.84) were found between the ME and SM measurements. These findings demonstrate for the first time that ME could map angle-independent strains to non-invasively detect, localize and characterize the early onset of myocardial ischemia, i.e. at 40%, and possibly as low as 20%, LAD flow reduction, which could be further associated with the severity of coronary stenosis.
Memory for Expectation-Violating Concepts: The Effects of Agents and Cultural Familiarity

Previous research has shown that ideas which violate our expectations, such as schema-inconsistent concepts, enjoy privileged status in terms of memorability. In our study, memory for concepts that violate cultural (cultural schema-level) expectations (e.g., “illiterate teacher”, “wooden bottle”, or “thorny grass”) versus domain-level (ontological) expectations (e.g., “speaking cat”, “jumping maple”, or “melting teacher”) was examined. Concepts that violate cultural expectations, or counter-schematic, were remembered to a greater extent compared with concepts that violate ontological expectations and with intuitive concepts (e.g., “galloping pony”, “drying orchid”, or “convertible car”), in both immediate recall, and delayed recognition tests. Importantly, concepts related to agents showed a memory advantage over concepts not pertaining to agents, but this was true only for expectation-violating concepts. Our results imply that intuitive, everyday concepts are equally attractive and memorable regardless of the presence or absence of agents. However, concepts that violate our expectations (cultural-schema or domain-level) are more memorable when pertaining to agents (humans and animals) than to non-agents (plants or objects/artifacts). We conclude that due to their evolutionary salience, cultural ideas which combine expectancy violations and the involvement of an agent are especially memorable and thus have an enhanced probability of being successfully propagated.
The Temporal Reasoning Systems Timegraph I-II

We describe two domain-independent temporal reasoning systems called TimeGraph I and II, which can be used in AI-applications as tools for efficiently managing large sets of relations in the Point Algebra, in the Interval Algebra, and metric information such as absolute times and durations. Our representation of time is based on timegraphs, graphs partitioned into a set of chains on which the search is supported by a metagraph data structure. TimeGraph I was originally developed by Taugher, Schubert, and Miller in the context of story comprehension. TimeGraph II provides useful extensions, including efficient algorithms for handing inequations, and relations expressing point-interval exclusion and interval disjointness. These extensions make the system much more expressive in the representation of qualitative information and suitable for a large class of applications.