Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying Emotion Segments in Music by Discovering Motifs in Physiological Data

Music can induce different emotions in people. We propose a system that can identify music segments which induce specific emotions from the listener. The work involves building a knowledge base with mappings between affective states (happiness, sadness, etc.) and music features (rhythm, chord progression, etc.). Building this knowledge base requires background knowledge from music and emotions psychology. Psychophysiological responses of a user, particularl y, the blood volume pulse, are taken while he listens to music. These signals are analyzed and mapped to various musical features of the songs he listened to. A motif discovery algorithm used in data mining is adapted to analyze signals of physiological data. Motif discovery finds patterns in the data that indicate points of interest in the music. The diffe rent motifs are stored in a library of patterns and used to iden tify other songs that have similar musical content. Results show that motifs selected have similar chord progressions. Some of which include frequently used chords in western pop music.
Fast variability as a tracer of accretion regimes in black hole transients

We present the root mean square (rms)–intensity diagram for black hole transients. Using observations taken with the Rossi X-ray Timing Explorer, we study the relation between the rms amplitude of the variability and the net count rate during the 2002, 2004 and 2007 outbursts of the black hole X-ray binary GX 339−4. We find that the rms–flux relation previously observed during the hard state in X-ray binaries does not hold for the other states, when different relations apply. These relations can be used as a good tracer of the different accretion regimes. We identify the hard, soft and intermediate states in the rms–intensity diagram. Transitions between the different states are seen to produce marked changes in the rms–flux relation. We find that one single component is required to explain the ∼40 per cent variability observed at low count rates, whereas no or very low variability is associated to the accretion-disc thermal component.
Test Construction: Theory and Practice

Professor Schepers has written a text on the theory and practice of psychological test construction that will help students, teachers, and professional psychologists to master the complexities of the art and science of test construction. The book has many strengths, but two in particular stand out. Firstly, Professor Schepers expertly derives all the formulas of reliability from a single formal definition. The second strength is the way in which Professor Schepers extends concepts and techniques that were originally developed for dichotomous test items (as typically found in ability tests) to polytomous items (as typically found in attitude and personality inventories). The book contains “psychometric wisdom” and insight—the product of many years of deep study and experience in test construction and development
When the Marae Moves into the City: Being Māori in Urban Palmerston North

Through processes of colonization, many indigenous peoples have become absorbed into settler societies and new ways of existing within urban environments. Settler society economic, legal, and social structures have facilitated this absorption by recasting indigenous selves in ways that reflect the cultural values of settler populations. Urban enclaves populated and textured by indigenous groups such as Māori (indigenous people of New Zealand) can be approached as sites of existential resistance to the imposition of colonial ways of seeing and understanding the self. In maintaining everyday social practices and ways–of–being that traverse rural and urban locales, Māori preserve and reproduce cultural selves in ways that make aspects of cityscapes more homely for Māori ways–of–being. This article brings issues of place and being to the fore by investigating Māori reassemblage of cultural selves within a low SES urban environment as an ongoing resistance to colonial absorption.
The Viterbi optimal runlength-constrained approximation nonlinear filter

Simple nonlinear filters are often used to enforce "hard" syntactic constraints while remaining close to the observation data, e.g., in the binary case, it is common practice to employ iterations of a suitable median, or a one-pass recursive median, openclose, or closeopen filter to impose a minimum symbol runlength constraint while remaining "faithful" to the observation. Unfortunately, these filters are-in general-suboptimal. Motivated by this observation, we pose the following optimization: given a finite-alphabet sequence of finite extent y={y(n)}/sub n=0//sup N-1/, find a sequence x={x(n)}/sub n=0//sup N-1/ that minimizes d(x,y)=/spl Sigma//sub n=0//sup N-1/d/sub n/(y(n), x(n)) subject to the following: x is piecewise constant of plateau run-length /spl ges/M. We show how a suitable reformulation of the problem naturally leads to a simple and efficient Viterbi-type optimal algorithmic solution. We call the resulting nonlinear input-output operator the Viterbi optimal runlength-constrained approximation (VORCA) filter. The method can be easily generalized to handle a variety of local syntactic constraints. The VORCA is optimal, computationally efficient, and possesses several desirable properties (e.g., idempotence); we therefore propose it as an attractive alternative to standard median, stack, and morphological filtering. We also discuss some applications.
Sparse regressions for joint segmentation and linear prediction

Regularizing the least-squares criterion with the total number of coefficient changes, it is possible to estimate time-varying (TV) autoregressive (AR) models with piecewise-constant coefficients. Such models emerge in various applications including speech segmentation using linear predictors. To cope with the large-size optimization task, the problem is cast as a sparse regression one, and is solved by resorting to an efficient block-coordinate descent algorithm. This enables joint segmentation and linear predictor coefficients identification with linear computational complexity per iteration. Modern trends in linear prediction for speech processing also envision sparsity in the model residuals. Indeed, sparse residuals allow for an improved representation of voiced speech. So far, sparse linear coding was proposed in a stationary scenario, i.e, after speech segmentation. This paper extends joint segmentation and linear prediction coefficients identification to sparse linear coding. Fortunately, coordinate descent approaches are still applicable to carry out the optimization tasks. Numerical tests have shown the benefits of the proposed algorithm.
Daily interpersonal coping strategies

An important pathway by which relationships influence health may involve how people cope with interpersonal tensions. This study examined whether same day and previous day avoidance and engagement in arguments are differentially associated with self-reported well-being (emotional and physical) and diurnal cortisol patterns. Participants from Wave 2 of the National Study of Daily Experiences (N = 1,512; aged 33–84, 57% women) completed daily phone interviews for eight consecutive days and provided useable saliva samples that were assayed for cortisol for four of those days at specific times: waking, 30 min after waking, before lunch, and at bedtime. Multilevel models revealed same day arguments were associated with lower well-being (higher negative affect and lower positive affect) than same day avoidance or no tension. In contrast, previous day avoidance was associated with lower next day well-being (higher negative affect and more physical symptoms) and higher next day cortisol than having no interpersonal tension the previous day. Arguments have greater same day consequences for well-being, whereas avoided arguments have greater next day consequences, which may indicate delayed effects of avoidance.
Bayesian Inference using Markov Chain Monte Carlo in Phylogenetic Studies

Phylogeny is the evolutionary development and history of a species or higher taxonomic grouping of organisms. Much effort is put into reconstructing phylogenies, since understanding evolutionary relationships is needed to draw general conclusions about the mechanisms of evolution. One must be aware that much of the terminology used in biology is quite vague – concepts such as 'species', 'individual', 'organism', and even 'life' are arbitrary terms whose definitions may vary. Some of the entities studied are not regarded as organisms, e.g. viruses. Still, the generally accepted conception within the scientific community is that all these entities have a common ancestor. Ancestry in this case refers to the passing on of genetic material, DNA and RNA. These substances carry information on how to build and operate an organism, and they are copied and passed on to offspring. However, the copies made are often not perfect. Mutations occur, and it is the accumulated weight of these mutations along with natural selection that constitute the driving forces of evolution. In other words, 'life' has arisen on earth once only, and from this origin all other life forms have evolved. The conception that all life forms have a common origin has led to the use of trees (usually binary) for representing the interrelationships among organisms. At the root is the most recent ancestor, and at the tips are the organisms studied. Branch lengths correspond to time, or sometimes to evolutionary distance, meaning the mutational changes that have occurred.
Property mining using dynamic dependency graphs

We present a technique to automatically generate System Verilog-Assertions from designs using dynamic dependency graphs. We extract relations between signals of the design using only a few simulation runs, which drastically reduces the required number of use cases compared to other approaches. Additionally, unlike previous approaches, we do not use expression templates to establish those relations. We abstract from the concrete use cases by inserting symbolic values and by merging similar conditions in time. A model-checker verifies the correctness of the generated properties. The evaluation shows that our approach is able to create more expressive properties than state of the art techniques, while requiring less simulation data.
Robust Large-Scale Localization in 3D Point Clouds Revisited

We tackle the problem of getting a full 6-DOF pose estimation of a query image inside a given point cloud. This technical report re-evaluates the algorithms proposed by Y. Li et al. "Worldwide Pose Estimation using 3D Point Cloud". Our code computes poses from 3 or 4 points, with both known and unknown focal length. The results can easily be displayed and analyzed with Meshlab. We found both advantages and shortcomings of the methods proposed. Furthermore, additional priors and parameters for point selection, RANSAC and pose quality estimate (inlier test) are proposed and applied.
Waveform Scheduling in Wideband Environments

The time-variation due to Doppler scaling effects, coupled with scattering due to multipath propagation, can severely limit the performance of wideband systems. In this paper, we examine the dynamic configuration of transmitted waveforms for agile sensing to increase tracking performance in wideband environments. Using wideband frequency modulated waveforms, we present an algorithm for predicting the mean square tracking error and selecting the waveform that minimizes it in a target tracking application with a nonlinear observations model. The algorithm is based on the Cramer-Rao lower bound on the measurement errors that is computed using the wideband ambiguity function. Using simulations, we demonstrate the improved performance provided by scheduling over fixed configurations
Analysis of a multi-domain recommender system

Recommending items in a multi-domain environment are more challenging than that in a single-domain one. In this paper, we report our findings on uncovering the association between user's interests of items across domains that are related to each other to a certain degree using two datasets collected from users with different cultural background. Results lead us to believe that due to cultural influences, user preferences over Western and Eastern items (both entertaining item and entertainer) are significantly different. In addition, results suggest the value of the cross-domain RS and reveal that cross-domain recommendation is sensitive to genre among certain domains (Book, Game and Movie), which is valuable for the algorithmic design and implementation of the RS. The results are valuable for the algorithmic design and implementation of the cross-domain RS targeting at users from different countries. Another most significant potential of cross-domain RS is its ability to exploit users' versatile interest on items in different domains to make serendipity and novel recommendations especially in large-scale commercial systems.
Dynamic structure factor study of diffusion in strongly sheared suspensions

Diffusion of neutrally buoyant spherical particles in concentrated monodisperse suspensions under simple shear flow is investigated. We consider the case of non-Brownian particles in Stokes flow, which corresponds to the limits of infinite Péclet number and zero Reynolds number. Using an approach based upon ideas of dynamic light scattering we compute self- and gradient diffusion coefficients in the principal directions normal to the flow numerically from Accelerated Stokesian Dynamics simulations for large systems (up to 2000 particles). For the self-diffusivity, the present approach produces results identical to those reported earlier, obtained by probing the particles' mean-square displacements (Sierou & Brady, J. Fluid Mech. vol. 506, 2004 p. 285). For the gradient diffusivity, the computed coefficients are in good agreement with the available experimental results. The similarity between diffusion mechanisms in equilibrium suspensions of Brownian particles and in non-equilibrium non-colloidal sheared suspensions suggests an approximate model for the gradient diffusivity: ${\textsfbi D}^\triangledown\,{\approx}\,{\textsfbi D}^s/S^{eq}(0)$, where ${\textsfbi D}^s$ is the shear-induced self-diffusivity and $S^{eq}(0)$ is the static structure factor corresponding to the hard-sphere suspension at thermodynamic equilibrium.
Maximum Matchings in Dynamic Graph Streams and the Simultaneous Communication Model

We study the problem of finding an approximate maximum matching in two closely related computational models, namely, the dynamic graph streaming model and the simultaneous multi-party communication model. In the dynamic graph streaming model, the input graph is revealed as a stream of edge insertions and deletions, and the goal is to design a small space algorithm to approximate the maximum matching. In the simultaneous model, the input graph is partitioned across k players, and the goal is to design a protocol where the k players simultaneously send a small-size message to a coordinator, and the coordinator computes an approximate matching. Dynamic graph streams. We resolve the space complexity of single-pass turnstile streaming algorithms for approximating matchings by showing that for any e > 0, Θ(n2-3e) space is both sufficient and necessary (up to polylogarithmic factors) to compute an ne-approximate matching; here n denotes the number of vertices in the input graph. The simultaneous communication model. Our results for dynamic graph streams also resolve the (per-player) simultaneous communication complexity for approximating matchings in the edge partition model. For the vertex partition model, we design new randomized and deterministic protocols for k players to achieve an α-approximation. Specifically, for α ≥ [EQUATION], we provide a randomized protocol with total communication of O(nk/α2) and a deterministic protocol with total communication of O(nk/α). Both these bounds are tight. Our work generalizes the results established by Dobzinski et al. (STOC 2014) for the special case of k = n. Finally, for the case of α = o([EQUATION]), we establish a new lower bound on the simultaneous communication complexity which is super-linear in n.
A Symmetrical Binomial Lattice Approach , for Modeling Generic One Factor Markov Processes

In this paper we propose a Symmetrical Binomial Lattice Approach that is equivalent to the well‐known and widely utilized Lattice of Cox, Ross & Rubinstein (1979) when modeling Geometric Brownian Motion type of processes, but can be utilized for a wide variety of other Markov style stochastic processes. This is due to the highly intuitive construction in which first the expected value expression of the process is directly used and the variance is modeled in a symmetrical lattice, which is added to the first. We then demonstrate its applicability with several Real Options examples, comparing to the Cox model.
Potential of X-Band Images from High-Resolution Satellite SAR Sensors to Assess Growth and Yield in Paddy Rice

The comprehensive relationship of backscattering coefficient (σ0) values from two current X-band SAR sensors (COSMO-SkyMed and TerraSAR-X) with canopy biophysical variables were investigated using the SAR images acquired at VV polarization and shallow incidence angles. The difference and consistency of the two sensors were also examined. The chrono-sequential change of σ0 in rice paddies during the transplanting season revealed that σ0 reached the value of nearby water surfaces a day before transplanting, and increased significantly just after transplanting event (3 dB). Despite a clear systematic shift (6.6 dB) between the two sensors, the differences in σ0 between target surfaces and water surfaces in each image were comparable in both sensors. Accordingly, an image-based approach using the “water-point” was proposed. It would be useful especially when absolute σ0 values are not consistent between sensors and/or images. Among the various canopy variables, the panicle biomass was found to be best correlated with X-band σ0. X-band SAR would be promising for direct assessments of rice grain yields at regional scales from space, whereas it would have limited capability to assess the whole-canopy variables only during the very early growth stages. The results provide a clear insight on the potential capability of X-band SAR sensors for rice monitoring.
Measuring Generalized Preferential Attachment in Dynamic Social Networks

The mechanism of preferential attachment underpins most recent social network formation models. Yet few authors attempt to check or quantify assumptions on this mechanism. We call generalized preferential attachment any kind of preference to interact with other agents with respect to any node property. We then introduce tools for measuring empirically and characterizing comprehensively such phenomena, and apply these tools to a socio-semantic network of scientific collaborations, investigating in particular homophilic behavior. This opens the way to a whole class of realistic and credible social network morphogenesis models.
Alat Pemantau Kondisi Infus Dengan Internet Of Things (IoT) Berbasis Mikrokontroler ATmega16

Dalam dunia medis, infus adalah alat yang paling sering digunakan. Infus berfungsi untuk memasukkan cairan melalui pembuluh vena sebagai nutrisi untuk pasien yang tidak bisa memenuhi nutrisi dengan cara makan. Nutrisi yang diberikan disesuaikan dengan kebutuhan pasien. Pemberian infus yang tidak tepat, tentunya akan berdampak pada pasien. Maka dari itu, perawat selalu melakukan pemeriksaan terhadap kondisi cairan infus di ruang pasien dan masih dilakukan manual. Pemeriksaan yang dilakukan adalah kondisi kecepatan tetesan dan sisa cairan infus. Untuk mempermudah pekerjaan perawat, maka dibuat sebuah alat untuk melakukan pemeriksaan terhadap kondisi infus, sekaligus mengatur kecepatan tetesan sesuai setpoint . Untuk memeriksa kondisi tetesan, dipasang sensor yang terdiri dari LED ( Light Emitting Diode ) infrared dan Photodiode . Untuk mengetahui sisa cairan infus, dipasang sensor load cell sehingga sisa cairan dapat diketahui dalam satuan mililiter (ml). Sedangkan aksi yang diberikan ketika kondisi tetesan tidak sesuai adalah dengan menggunakan motor servo sebagai penjepit selang. Data hasil pembacaan sensor kemudian diproses di sebuah perangkat mikrokontroler ATmega16 yang telah dipasang modul Wi-Fi ESP8266-01. Data yang telah diproses kemudian ditampilkan di komputer. Alat dapat menghitung tetesan dengan error rata-rata 0.59%, mendeteksi sisa cairan dengan error rata-rata 0.83% serta dapat mengirimkan data dengan waktu paling cepat 30 detik.
Involvement of ERK-Nrf-2 Signaling in Ionizing Radiation Induced Cell Death in Normal and Tumor Cells

Prolonged oxidative stress favors tumorigenic environment and inflammation. Oxidative stress may trigger redox adaptation mechanism(s) in tumor cells but not normal cells. This may increase levels of intracellular antioxidants and establish a new redox homeostasis. Nrf-2, a master regulator of battery of antioxidant genes is constitutively activated in many tumor cells. Here we show that, murine T cell lymphoma EL-4 cells show constitutive and inducible radioresistance via activation of Nrf-2/ERK pathway. EL-4 cells contained lower levels of ROS than their normal counterpart murine splenic lymphocytes. In response to radiation, the thiol redox circuits, GSH and thioredoxin were modified in EL-4 cells. Pharmacological inhibitors of ERK and Nrf-2 significantly enhanced radiosensitivity and reduced clonogenic potential of EL-4 cells. Unirradiated lymphoma cells showed nuclear accumulation of Nrf-2, upregulation of its dependent genes and protein levels. Interestingly, MEK inhibitor abrogated its nuclear translocation suggesting role of ERK in basal and radiation induced Nrf-2 activation in tumor cells. Double knockdown of ERK and Nrf-2 resulted in higher sensitivity to radiation induced cell death as compared to individual knockdown cells. Importantly, NF-kB which is reported to be constitutively active in many tumors was not present at basal levels in EL-4 cells and its inhibition did not influence radiosensitivity of EL-4 cells. Thus our results reveal that, tumor cells which are subjected to heightened oxidative stress employ master regulator cellular redox homeostasis Nrf-2 for prevention of radiation induced cell death. Our study reveals the molecular basis of tumor radioresistance and highlights role of Nrf-2 and ERK.
Conhecimento Interpretativo para Ensinar Matemática e História da (Educação) Matemática: contributos para a Formação

Este texto discute a necessidade de potenciar o desenvolvimento de um conhecimento do professor que permita assumir como ponto de partida para a pratica posterior os conhecimentos, raciocinios e producoes dos alunos (Conhecimento Interpretativo) no âmbito dos racionais. Debate potencialidades – para a formacao, a pratica e a investigacao – de considerar a Historia da (Educacao) Matematica simultaneamente uma ferramenta e um contexto, efetuando uma discussao centrada no conteudo ideal de cada um dos diferentes subdominios do Mathematical Knowledge for Teaching e nos beneficios de considerar as diferentes historias como elemento sustentador dessa discussao. Apresentam-se algumas problematicas ainda existentes e oportunidades para investigacoes futuras.
Licensed under Creative Commons Attribution Cc by a Prospective Study to Assess the Morphology of Pedicles of Lower Thoracic and Lumbar Vertebrae Using Computerized Tomography Scan Measurements in North-indian Population

Sound knowledge of various features of morphology of pedicles is required for accurate pedicle screw placement. Previous studies suggest variation in morphology of pedicles in different population groups. This prospective study was done to assess the morphological features of the pedicles in north Indian population using computerized tomography scans and Orthopaedic digital imaging software. The tranverse pedicle width, transverse pedicle angle and screw path length were measured at lower thoracic and lumbar levels and these values were compared with those of previous such studies.