Miracle-dz/UniFAR-FTUs huggingface dataset:
CAN REHABILITATIVE PROGRAMS REDUCE THE RECIDIVISM OF JUVENILE OFFENDERS

iii ACKNOWLEDGEMENTS v LIST OF TABLES viii LIST OF FIGURES ix CHAPTER ONE: INTRODUCTION 1 History of Juvenile Hall in the United States 2 History of Juvenile Hall in California 4 Court Case: Farrell v. Harper 4 History of Juvenile Court 5 Problem Statement 6 Definitions 7 Statistics 8 CHAPTER TWO: LITERATURE REVIEW 9 Introduction 9 Multisystemic Therapy and Juvenile Recidivism 10 Cognitive Behavioral Therapy and Juvenile Recidivism 14 CHAPTER THREE: METHODS 18 Introduction 18 Study Design 18 Sampling 19 Data Collection and Instruments 19 Procedures 20
Core Depressive Symptoms In Depressed Cancer OutpatientsB

Objective: This study aimed to estimate the prevalence of core depressive symptoms among cancer outpatients diagnosed with depressive or adjustment disorders with depressed mood. We also aimed to detect potential differences between patient self-assessment and psychiatrist evaluation in classifying the severity of depression. Methods: Fifty-two outpatients diagnosed with solid tumor malignancy and depressive or adjustment disorder with depressed mood were assessed using the Hamilton Depression Rating Scale (HAMD-17) (and its shortened version the HAMD-7) and the Zung Self-Rating Depression Scale (ZSDS) (and its shortened version BZSDS). Results: Based on HAMD-7 results, the prevalence of moderate depression was low (7.7%); using the BZSDS moderate depression was absent. Mild depression was identified in 82.3% and 73% of our subjects using the HAMD-7 and the BZSDS, respectively. The strength of agreement between psychiatrist and patients’ self-evaluation for mild depression was “slight”, employing the original and the abbreviated versions of both scales. Conclusion: Our findings suggest that the prevalence of core depressive symptoms is very low in cancer patients diagnosed with depressive disorder. The lack of a strong agreement between psychiatrist and patient in classifying the severity of depression highlights the importance of factors such as well-being and functional status among depressed cancer patients in their self assessment of depression.
An Algorithm for Mining Multidimensional Fuzzy Association Rules

Multidimensional association rule mining searches for interesting relationship among the values from different dimensions or attributes in a relational database. In this method the correlation is among set of dimensions i.e., the items forming a rule come from different dimensions. Therefore each dimension should be partitioned at the fuzzy set level. This paper proposes a new algorithm for generating multidimensional association rules by utilizing fuzzy sets. A database consisting of fuzzy transactions, the Apriory property is employed to prune the useless candidates, itemsets.
Variable window power spectral density attack

Side channel attacks permit the recovery of the secret key held within a cryptographic device. This paper presents a new EM attack in the frequency domain, using a power spectral density analysis that permits the use of variable spectral window widths for each trace of the data set and demonstrates how this attack can therefore overcome both inter-and intra-round random insertion type countermeasures. We also propose a novel re-alignment method exploiting the minimal power markers exhibited by electromagnetic emanations. The technique can be used for the extraction and re-alignment of round data in the time domain.
Towards Realistic Soft Tissue Modeling in Medical

Most of today's medical simulation systems are based on geometric representations of anatomical structures that take no account of their physical nature. Representing physical phenomena and, more speciically the realistic modeling of soft tissue will not only improve current medical simulation systems but will considerably enlarge the set of applications and the credibility of medical simulation, from neurosurgery planning to laparoscopic surgery simulation. In order to achieve realistic tissue deformation, it is necessary to combine deformation accuracy with computer eeciency. On the one hand, biomechanics has studied complex mathematical models and produced a large amount of experimental data for representing the deformation of soft tissue. On the other hand, computer graphics has proposed many algorithms for the real-time computation of deformable bodies, often at the cost of ignoring the physics principles. In this paper, we survey existing models of deformation in medical simulation and we analyze the impediments to combining computer-graphics representations with biomechanical models. In particular, the diierent geometric representations of deformable tissue are compared in relation to the tasks of real-time deformation, tissue cutting and force-feedback interaction. Finally, we inspect the potential of medical simulation under the development of this key technology.
Online Myopic Network Covering

Efficient marketing or awareness-raising campaigns seek to recruit $n$ influential individuals -- where $n$ is the campaign budget -- that are able to cover a large target audience through their social connections. So far most of the related literature on maximizing this network cover assumes that the social network topology is known. Even in such a case the optimal solution is NP-hard. In practice, however, the network topology is generally unknown and needs to be discovered on-the-fly. In this work we consider an unknown topology where recruited individuals disclose their social connections (a feature known as {\em one-hop lookahead}). The goal of this work is to provide an efficient greedy online algorithm that recruits individuals as to maximize the size of target audience covered by the campaign. We propose a new greedy online algorithm, Maximum Expected $d$-Excess Degree (MEED), and provide, to the best of our knowledge, the first detailed theoretical analysis of the cover size of a variety of well known network sampling algorithms on finite networks. Our proposed algorithm greedily maximizes the expected size of the cover. For a class of random power law networks we show that MEED simplifies into a straightforward procedure, which we denote MOD (Maximum Observed Degree). We substantiate our analytical results with extensive simulations and show that MOD significantly outperforms all analyzed myopic algorithms. We note that performance may be further improved if the node degree distribution is known or can be estimated online during the campaign.
Entity disambiguation in tweets leveraging user social profiles

Pervasive web and social networks are becoming part of everyone's life. Users through their activities on these networks are leaving traces of their expertise, interests and personalities. With the advances in Web mining and user modeling techniques it is possible to leverage the user social network activity history to extract the semantics of user-generated content. In this work we explore various techniques for constructing user profiles based on the content they publish on social networks. We further show that one of the advantages of maintaining social network user profiles is to provide the context for better understanding of microposts. We propose and experimentally evaluate different approaches for entity disambiguation in social networks based on syntactic and semantic features on top of two different social networks: a general-interest network (i.e., Twitter) and a domain-specific network (i.e., StackOverflow). We demonstrate how disambiguation accuracy increases when considering enriched user profiles integrating content from both social networks.
Screening early stage metal mining projects A simulation approach

This paper presents a simulation-based analysis method for the screening of early stage metal mining projects that face with multiple uncertainties. Evaluation of metal mining projects is discussed, the proposed method is presented and illustrated numerically, and the benefits of the proposed method are discussed. Analyzing the possible value of postponing investment with the proposed method is also presented.
Visual Gene Ontology Based Knowledge Discovery in Functional Genomics

The molecular biology and the study of the genome has been transformed in the last decade by the avalanche of a conspicuous amount of data produced by high-throughput technologies. The accessibility to massive sequencing, microarrays and proteomics methods implies that studies on the genome-wide scale has become feasible for a large number of laboratories throughout the world. The great challenge in current genome research is to transform these data into knowledge, knowledge that will lead to a better understanding of the molecular processes underlying the observed biological phenomena. The discipline of functional genomics has arisen to integrate genomic sequences, experimental genome screening and novel bioinformatics methods to facilitate comprehension of genome-wide data. Within this framework, visualization appears as a helpful component to interpret results from high-throughput experiments and can be indispensable when working with large datasets. Typically, functional genomics makes use of structured functional terms like the Gene Ontology (GO) vocabulary (Ashburner M, 2000) and in this case the “natural” visualization format is a graph of a group of functionally annotated elements. In this graph, nodes represent the functional labels (the GO terms) to which genes or proteins are annotated to and arcs represent the relationships among them. Visualization of genomics data within the GO graph structure is effective in providing a rapid insight into the functional composition of a dataset and for understanding functional information within its biological context. This is of outermost importance in functional genomics research where both the overview and the detail are essential to create hypothesis over the functioning of biological systems. However, a problem when visualizing GO functional information is that graphs can become extremely large and difficult to navigate if the number of represented elements (genes, proteins or simply GO terms) is high. Moreover, not all nodes are equally important and different kind of information might be associated to them. Therefore, the goal of a good visualization technique is to provide an informative view of the data that is efficient in generating new knowledge. In this chapter we review current methods to visualize and perform data mining from GO contained genomic data. We start with a brief introduction to the Gene Ontology and present several third-party approaches for the visualization of GO data. The body of this document will focus on visual solutions for GO-based data mining available in the
Multi-spectral information regarding face recognition

Recently, hyper-spectral facial image capturing techniques have opened a new door for creating innovative techniques aiming to improve these systems features. In our work, we have developed a verification approach based on Principal Component Analysis, and doing channel fusion (data fusion), in particular 5, 13, 14, 16, 24, 33, and 34 channels, reaching an Equal Error Rate of 97.37%; showing a good behavior of the kind of images.
Adaptive Coding and Modulation in OFDM Systems using BICM and Rate-Compatible Punctured Codes

—Within the EU FP6 Integrated Project WINNER, adaptive transmission in a TDMA/OFDMA system is investigated as a key technology for boosting the spectral efﬁciency of a new radio interface for 4G systems. Adaptive allocation and link-adaptation of subcarriers or groups of subcarriers based on short-term channel quality prediction offer signiﬁcant adaptation and multi-user scheduling gains. The smallest time-frequency unit for resource partitioning and link-adaptation is a group of adjacent subcarriers and OFDM symbols, denoted as “chunk”. An open issue is joint adaptive coding and mapping of long codewords onto multiple chunks if link-adaptation is performed chunk-wise. In this paper, we present an adaptive coding and modulation scheme for bit-interleaved coded OFDM systems using Rate-Compatible Punctured Block-circulant LDPC codes (RCP-BLDPC). The average mutual information per code bit is used as single parameter for the codeword error probability estimation of a Forward Error Correction (FEC) codeword that is transmitted on chunks with different modulation formats and Channel gain to Noise Ratios (CNR).
External Validation of the Simple Clinical Score and the HOTEL Score, Two Scores for Predicting Short-Term Mortality after Admission to an Acute Medical Unit

Background Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs. Methods Pre-planned prospective observational cohort study. Setting Danish 460-bed regional teaching hospital. Findings We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774–0.879) for 30-day mortality, and goodness-of-fit test, χ2 = 2.68 (10 degrees of freedom), P = 0.998 and χ2 = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901–0.962) for 24-hours mortality and goodness-of-fit test, χ2 = 5.56 (10 degrees of freedom), P = 0.234. Conclusion We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision.
Rapid Detection of Chloramphenicol Residues in Aquatic Products Using Colloidal Gold Immunochromatographic Assay

A colloidal gold immunochromatographic assay (GICA) was developed for rapid detection of chloramphenicol (CAP) residues in aquatic products. A nitrocellulose (NC) membrane was used as the carrier, and the polyclonal CAP antibody was used as the marker protein. The average diameter of as-prepared colloidal gold nanoparticles (AuNPs) was about 20 nm. The optimal pH value of colloidal gold solutions and the amount of the antibody of CAP were 8.0 and 7.2 μg/mL, respectively. The CAP antibody was immobilized onto the conjugate pad after purification. The CAP conjugate and goat anti-rabbit IgG (secondary antibody) were coated onto the NC membrane. Next, the non-specific sites were blocked with 1% bovine serum albumin. The minimum detectable concentration of CAP in standard solution is 0.5 ng/mL, with good reproducibility. For the real samples from crucian carps injected with a single-dose of CAP in the dorsal muscles, the minimum detectable concentration of CAP residues was 0.5 μg/kg. The chromatographic analysis time was less than 10 min, and the strip had a long storage lifetime of more than 90 days at different temperatures. The strips provide a means for rapid detection of CAP residues in aquatic products.
Yield Spread and Term to Maturity: Default vs. Liquidity

The aim of this paper is the analysis of the yield spreads between Treasury and non–Treasury Spanish fixed income assets and its relationship with the term to maturity. We find a downward sloping term structure of yield spreads for investment–grade bonds that seems to be contrary to the ‘crisis at maturity’ theory. However, we claim that this outcome is caused mainly by the effect of liquidity on yield spreads. Once the effect of liquidity and other factors are removed we find that there is a positive relationship between default premiums and term to maturity. That result is now consistent with the existing literature.
Symmetric Walking Control: Invariance and Global Stability

This paper first presents a novel control strategy for periodic motion control based on a Hamiltonian system. According to the strategy, hybrid symmetric orbits (ideal walking gaits) are explored using reversal symmetry of the Hamiltonian system. Then, an invariance controller, a Symmetric Walking Controller, is derived systematically to distribute the symmetric orbits densely throughout the entire phase space. Finally, a new robust walking speed controller is formulated based on the passivity of the controlled system. Consequently, solutions starting from any point globally converge to a stable limit cycle having a desired energy level. The controller has strong passivity and robustness, thereby rendering it capable of using external disturbances as energy for walking propulsion. It requires no model parameters and can be implemented in a very small program size. Furthermore, it is applicable to any biped robot without major modification. In this report, the effectiveness of this controller is proved mathematically, validated numerically, and confirmed experimentally.
Mechanism and evaluation of a haptic interface “Force Blinker 2” for navigation of the visually impaired

In the navigation of the visually impaired, an external input such as force or sound is required about the direction of travel to reach a particular target position. We develop a new haptic interface called “Force Blinker 2” to navigate the visually impaired. In Force Blinker 2, rotating weights and repulsive magnets are used to reduce the force generated to the direction opposite the traveling direction, which caused false recognition in the previous system, “Force Blinker 1. ” In Force Blinker 2, the rotational radius of the weight varies depending on the velocity of the rotational weight. Ten visually impaired subjects evaluated Force Blinker 2 by comparing it with Force Blinker 1, a fixed radius type interface. The directions presented by Force Blinker 2 were correctly recognized at a rate of approximately 85%, which is approximately a 10% improvement over the rate by Force Blinker 1.
Detection of an Iron Emission Feature from the Lensed Broad Absorption Line QSO H1413+117 at z = 2.56

We present the X-ray energy spectrum of the lensed broad absorption line QSO H1413+117 (the Cloverleaf) at z = 2.56 observed with the Chandra X-ray observatory. We detected 293 photons in a 40 ks Advanced CCD Imaging Spectrometer (ACIS-S) observation. The X-ray image consists of four lensed image components, thus the photons are from the lensed QSO itself. The overall spectrum can be described with a power-law function heavily absorbed by neutral matter at a redshift consistent with the QSO redshift. This supports the idea that intrinsic absorption is significant for BAL QSOs. The spectral fit significantly (99% confidence) improves when we include an emission line. The centroid energy and intrinsic width (Gaussian σ) of the line are 6.21 ± 0.16 keV and 220 eV (90% errors), respectively, in the QSO rest frame, assuming the absorbed power law as the continuum. The equivalent width of the line in the QSO rest frame is 960 eV. We suggest that the large equivalent width, the centroid energy, and the line broadness can be explained by iron K emission arising from X-ray reprocessing in the BAL flow, assuming it has a conical thin-sheet structure.
Video saliency detection using motion saliency filter

In this paper, we propose a motion saliency filter to detect the salient regions in the video sequences. The motion vector field of each frame is first grouped into several elements with the aid of superpixel segmentation. Then, two measures are defined to rate the motion uniqueness and motion distribution of each element. The motion saliency of each element is derived as the fusion of the two measures. The final pixel-accurate saliency map is generated from a linear combination of the element motion saliency values. Moreover, the complete saliency computing process can be formulated with the N-D Gaussian filters which are with only linear computing complexity. Experimental results indicate that the proposed method could achieve better performance as compared to the state-of-the-art methods.
Quality Assessment of Stereo Images with Stereo Vision

A quality assessment method of stereo images is proposed firstly, which is based on the theories and methods of planar quality assessment-SSIM. It takes stereo (three- dimensional) vision into account, including the physiological stereoscopy and the psychological stereoscopy. Dense disparity of stereo images is extracted, then division into segments is carried out . The weighted structural similarity is achieved as the assessing index of stereo image quality. Experimental results show that the proposed method is more accurate than PPSNR, in accordance with human visual characteristic, and consistent with the result of subjective assessment.
Red-Eyes Removal through Cluster-Based Boosting on Gray Codes

Since the large diffusion of digital camera and mobile devices with embedded camera and flashgun, the redeyes artifacts have de facto become a critical problem. The technique herein described makes use of three main steps to identify and remove red eyes. First, red-eye candidates are extracted from the input image by using an image filtering pipeline. A set of classifiers is then learned on gray code features extracted in the clustered patches space and hence employed to distinguish between eyes and non-eyes patches. Specifically, for each cluster the gray code of the red-eyes candidate is computed and some discriminative gray code bits are selected employing a boosting approach. The selected gray code bits are used during the classification to discriminate between eye versus non-eye patches. Once red-eyes are detected, artifacts are removed through desaturation and brightness reduction. Experimental results on a large dataset of images demonstrate the effectiveness of the proposed pipeline that outperforms other existing solutions in terms of hit rates maximization, false positives reduction, and quality measure.
A search method for notated polyphonic music with pitch and tempo fluctuations

We compare two methods of measuring melodic similarity for symbolically represented polyphonic music. Both exploit advantages of transportation distances such as continuity and partial matching in the pitch dimension. By segmenting queries and database documents, one of them also offers partial matching in the time dimension. This method can find short queries in long database documents and is more robust against pitch and tempo fluctuations in the queries or database documents than the method that uses transportation distances alone. We compare the use of transportation distances with and without segmentation for the RISM A/II collection and find that segmentation improves recall and precision. With everything else being equal, the segmented search found 80 out of 114 relevant documents, while the method relying solely on transportation distances found only 60.
Relative Age Effect and Gender Differences in Physical Education Attainment in Norwegian Schoolchildren

ABSTRACT The relative age effect (RAE) refers to that children born early in their year of birth show higher performance compared to children born late in the same cohort. The present study evaluated whether RAE exists within non-competitive physical education (PE) attainments, change in RAE magnitude with age, and possible gender differences. The results show a drop in PE attainment and a difference in number of high and low marks between the first and second half-year. Of the pupils who attained the highest mark, 73% were born in the first 6 months. In lower-secondary school, RAEs were larger in girls compared with boys. A possible explanation for the results is that the PE-teachers might be inspired by product-oriented criteria.