Miracle-dz/UniFAR-FTUs huggingface dataset:
Drawing as a generative activity and drawing as a prognostic activity.

In this study, 9th-grade students (N = 196) with a mean age of 14.7 years read a scientific text explaining the chemical process of doing laundry with soap and water and then took 3 tests. Students who were instructed to generate drawings during learning scored higher than students who only read on subsequent tests of transfer (d = 0.91), retention (d = 0.87), and drawing (d = 2.00). For students who were instructed to generate drawings during learning, those who generated high-accuracy drawings (according to a median split) scored higher than students who generated low-accuracy drawings on subsequent tests of transfer (d = 0.99), retention (d = 0.79), and drawing (d = 1.87); furthermore, drawing-accuracy scores during learning correlated with learning-outcome scores on transfer (r = .57), retention (r = .50), and drawing (r = .82). Results suggest that drawing can serve as a generative activity and as a prognostic activity
Performance Analysis of the SIFT Operator for Automatic Feature Extraction and Matching in Photogrammetric Applications

In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Cameras or Unmanned Aerial Vehicles do not observe normal acquisition conditions. Feature extraction and matching techniques, which are traditionally used in photogrammetry, are usually inefficient for these applications as they are unable to provide reliable results under extreme geometrical conditions (convergent taking geometry, strong affine transformations, etc.) and for bad-textured images. A performance analysis of the SIFT technique in aerial and close-range photogrammetric applications is presented in this paper. The goal is to establish the suitability of the SIFT technique for automatic tie point extraction and approximate DSM (Digital Surface Model) generation. First, the performances of the SIFT operator have been compared with those provided by feature extraction and matching techniques used in photogrammetry. All these techniques have been implemented by the authors and validated on aerial and terrestrial images. Moreover, an auto-adaptive version of the SIFT operator has been developed, in order to improve the performances of the SIFT detector in relation to the texture of the images. The Auto-Adaptive SIFT operator (A2 SIFT) has been validated on several aerial images, with particular attention to large scale aerial images acquired using mini-UAV systems.
A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams

Abstract. Subgrid processes occur in various ecosystems and landscapes but, because of their small scale, they are not represented or poorly parameterized in climate models. These local heterogeneities are often important or even fundamental for energy and carbon balances. This is especially true for northern peatlands and in particular for the polygonal tundra, where methane emissions are strongly influenced by spatial soil heterogeneities. We present a stochastic model for the surface topography of polygonal tundra using Poisson–Voronoi diagrams and we compare the results with available recent field studies. We analyze seasonal dynamics of water table variations and the landscape response under different scenarios of precipitation income. We upscale methane fluxes by using a simple idealized model for methane emission. Hydraulic interconnectivities and large-scale drainage may also be investigated through percolation properties and thresholds in the Voronoi graph. The model captures the main statistical characteristics of the landscape topography, such as polygon area and surface properties as well as the water balance. This approach enables us to statistically relate large-scale properties of the system to the main small-scale processes within the single polygons.
An efficient clustering technique for cameras identification using sensor pattern noise

In multimedia forensics, source-based image classification problem is a well known problem. It addresses the issue of identifying those images that were captured by a specific source camera from a given set of N data images. This is possible as each camera has a unique Photo Response Non-Uniformity (PRNU) that is registered in every image captured by this camera. Classification is made by clustering images having the same PRNU. In this paper, an efficient technique is proposed to group images originated by the same camera. It is based on evaluating the similarity functions between the estimated PRNUs as well as their Hu's moment invariant information. The proposed technique has the ability to group images taken by a specific camera, even if the input images correspond to the same scene that was captured by different cameras. The classification algorithm is performed by means of a hierarchical clustering. Simulation examples are given to verify the superiority of the proposed technique compared to other techniques.
On adaptive Markov chain Monte Carlo algorithms

We look at adaptive Markov chain Monte Carlo algorithms that generate stochastic processes based on sequences of transition kernels, where each transition kernel is allowed to depend on the history of the process. We show under certain conditions that the stochastic process generated is ergodic, with appropriate stationary distribution. We use this result to analyse an adaptive version of the random walk Metropolis algorithm where the scale parameter o is sequentially adapted using a Robbins Monro type algorithm in order to find the optimal scale parameter aopt. We close with a simulation example.
Continuous state HMM modeling of flat fading channels

There are several discrete state Markov or hidden Markov models (HMMs) of the flat fading. These models assume that there is a finite number of discrete fading levels. The main reason for considering a discrete state model is simplicity of using these models in applications. Continuous state HMMs (CSHMMs) and, in particular, hidden Gauss-Markov models (HGMM) describe fading more accurately. In this paper, we present applications of CSHMMs to model flat fading and develop analytic methods for computing basic characteristics of the fading process by using the notion of operator probability.
Overlapping wavelet packet features for speaker verification

A generalization of the Discrete Wavelet Packet Transform (DWPT), referred to as Overlapping Discrete Wavelet Packet Transform (ODWPT), is proposed. In contrast to the traditional DWPT, the ODWPT assumes overlapping among the frequency sub-bands at various levels of the transform. Based on this overlapping strategy, a new set of speech features that is specially designed for speaker recognition is derived. The practical significance of our approach has been evaluated in comparative experiments performed on the 2001 NIST Speaker Recognition Evaluation database. The proposed feature set has proved to outperform the widely-used Mel-frequency cepstral coefficients (MFCCs) and other wavelet packet-based speech features that were successfully utilized for speaker recognition.
Change Detection in Streaming Multivariate Data Using Likelihood Detectors

Change detection in streaming data relies on a fast estimation of the probability that the data in two consecutive windows come from different distributions. Choosing the criterion is one of the multitude of questions that need to be addressed when designing a change detection procedure. This paper gives a log-likelihood justification for two well-known criteria for detecting change in streaming multidimensional data: Kullback-Leibler (K-L) distance and Hotelling's T-square test for equal means (H). We propose a semiparametric log-likelihood criterion (SPLL) for change detection. Compared to the existing log-likelihood change detectors, SPLL trades some theoretical rigor for computation simplicity. We examine SPLL together with K-L and H on detecting induced change on 30 real data sets. The criteria were compared using the area under the respective Receiver Operating Characteristic (ROC) curve (AUC). SPLL was found to be on the par with H and better than K-L for the nonnormalized data, and better than both on the normalized data.
Using Line and Ellipse Features for Rectification of Broadcast Hockey Video

To use hockey broadcast videos for automatic game analysis, we need to compensate for camera viewpoint and motion. This can be done by using features on the rink to estimate the homography between the observed rink and a geometric model of the rink, as specified in the appropriate rule book (top down view of the rink). However, player occlusion, wide range of camera motion, and frames with few reliable key-points all pose significant challenges for robustness and accuracy of the solution. In this work, we describe a new method to use line and ellipse features along with key-point based matches to estimate the homography. We combine domain knowledge (i.e., rink geometry) with an appearance model of the rink to detect these features accurately. This over determines the homography estimation to make the system more robust. We show this approach is applicable to real world data and demonstrate the ability to track long sequences on the order of 1,000 frames.
The 7 Th Ieee International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications Security Metrics for Risk Assessment of Distributed Information Systems

—The paper considers the main issues and recommendations for using the risk assessment techniques based on the analysis of static, dynamic and historical security information. The system of security metrics and techniques for their calculation are suggested. Proposed techniques are based on attack graphs and service dependencies. They allow evaluating security of network topologies, malefactors and attack characteristics, and integral security properties and characteristics calculated on the basis of the cost-benefit and zero-day vulnerability analysis. The approach is intended to be implemented in the framework of the FP7 EU MASSIF project.
Mining energy-greedy API usage patterns in Android apps: an empirical study

Energy consumption of mobile applications is nowadays a hot topic, given the widespread use of mobile devices. The high demand for features and improved user experience, given the available powerful hardware, tend to increase the apps’ energy consumption. However, excessive energy consumption in mobile apps could also be a consequence of energy greedy hardware, bad programming practices, or particular API usage patterns. We present the largest to date quantitative and qualitative empirical investigation into the categories of API calls and usage patterns that—in the context of the Android development framework—exhibit particularly high energy consumption profiles. By using a hardware power monitor, we measure energy consumption of method calls when executing typical usage scenarios in 55 mobile apps from different domains. Based on the collected data, we mine and analyze energy-greedy APIs and usage patterns. We zoom in and discuss the cases where either the anomalous energy consumption is unavoidable or where it is due to suboptimal usage or choice of APIs. Finally, we synthesize our findings into actionable knowledge and recipes for developers on how to reduce energy consumption while using certain categories of Android APIs and patterns
Acute Stress Disorder Symptoms Among Female Sexual Abuse Survivors Seeking Treatment

ABSTRACT This exploratory study examined relationships between acute stress disorder (ASD) symptoms and sexual abuse history, distress, and social support among sexual abuse survivors seeking treatment. Participants were 32 women recruited for a pilot study of group treatment for sexual abuse survivors who completed self-report and interview measures. Many participants (37.5%) met criteria for all ASD symptoms. Also, ASD symptoms were significantly related to seeing the self as the causal locus of the abuse, forgetting the abuse for a period of time, and the number of abusers, the distress of a recent life event, other forms of distress, and poor social support, Acute stress disorder may occur among many sexual abuse survivors seeking treatment, requiring special intervention to help these patients to manage their reactions to ongoing stresses.
Deletion of the chemokine receptor CCR1 prolongs corneal allograft survival.

PURPOSE Many corneal grafts undergo immune rejection, and current therapies are associated with many side effects. The purpose of this study was to identify critical chemokine pathways involved in generating the alloimmune response to corneal transplants. METHODS Orthotopic corneal transplantation was performed in fully mismatched strains. Cytokine and chemokine receptor gene expression was determined by the RNase protection assay. Knockout (KO) strains for chemokine-chemokine receptors that are upregulated after transplantation underwent corneal transplantation. Results derived from KO murine hosts were compared with cyclosporine (Cy) therapy. In addition to graft survival, graft infiltration, allospecific delayed-type hypersensitivity (DTH), and cytokine expression were compared among the recipient groups. RESULTS Initial experiments revealed gene upregulation of the chemokine receptors CCR1, -2, and -5 after corneal allorejection. Although CCR1 KO hosts showed a significant increase in graft survival compared with wild-type (WT) hosts, allografts in CCR5, CCR2/CCL3(MIP-1alpha), CXCR3, CXCL10/IP-10, and CCL3/MIP-1alpha KO mice did not show a significant improvement in graft survival. Further, CCR1 KO hosts showed a significantly higher survival rate than with systemic Cy therapy in WT hosts. Moreover, graft infiltration by leukocytes and gene expression of proinflammatory cytokines were reduced in CCR1 KO mice compared with both Cy treated and untreated WT mice, as was the induction of allospecific DTH. CONCLUSIONS These studies provide, for the first time, evidence that targeting of specific chemokine pathways can significantly promote survival of corneal transplants, and suggest that select deletion or suppression of CCR1 can be a useful therapeutic target in corneal transplant immunity.
QZ Serpentis: A Dwarf Nova with a 2 Hour Orbital Period and an Anomalously Hot, Bright Secondary Star

We present spectroscopy and time‐series photometry of the dwarf nova QZ Ser. The spectrum shows a rich absorption‐line spectrum of type K4 ± 2. K‐type secondary stars are generally seen in dwarf novae with orbital periods Porb ∼ 6 hr, but in QZ Ser the absorption radial velocities show an obvious modulation [semiamplitude 207(5) km s-1] at Porb = 119.752(2) minutes, much shorter than typical for such a relatively warm and prominent secondary spectrum. The Hα emission‐line velocity is modulated at the same period and roughly opposite phase. Time‐series photometry shows flickering superposed on a modulation with two humps per orbit, consistent with ellipsoidal variation of the secondary’s light. QZ Ser is a second example of a relatively short period dwarf nova with a surprisingly warm secondary. Model calculations suggest that the secondary is strongly enhanced in helium and had already undergone significant nuclear evolution when mass transfer began. Several sodium absorption features in the secondary spectrum are unusually strong, which may indicate that the present‐day surface was the site of CNO‐cycle hydrogen burning in the past.
Increased Understanding of Stem Cell Behavior in Neurodegenerative and Neuromuscular Disorders by Use of Noninvasive Cell Imaging

Numerous neurodegenerative and neuromuscular disorders are associated with cell-specific depletion in the human body. This imbalance in tissue homeostasis is in healthy individuals repaired by the presence of endogenous stem cells that can replace the lost cell type. However, in most disorders, a genetic origin or limited presence or exhaustion of stem cells impairs correct cell replacement. During the last 30 years, methods to readily isolate and expand stem cells have been developed and this resulted in a major change in the regenerative medicine field as it generates sufficient amount of cells for human transplantation applications. Furthermore, stem cells have been shown to release cytokines with beneficial effects for several diseases. At present however, clinical stem cell transplantations studies are struggling to demonstrate clinical efficacy despite promising preclinical results. Therefore, to allow stem cell therapy to achieve its full potential, more insight in their in vivo behavior has to be achieved. Different methods to noninvasively monitor these cells have been developed and are discussed. In some cases, stem cell monitoring even reached the clinical setting. We anticipate that by further exploring these imaging possibilities and unraveling their in vivo behavior further improvement in stem cell transplantations will be achieved.
Digital Storytelling as a Signature Pedagogy for the New Humanities

This essay argues that digital storytelling is a hybrid, multimedia narrative form that enables critical and creative theorizing. As an assets-based social pedagogy, digital storytelling constructs a safe and empowering space for cross-cultural collaboration and learning. As illustration, the essay analyzes in detail one student story, using as primary evidence the story script, visual images from the digital story, and excerpts from a recorded interview with the author. It concludes that the process of digital story making and theorizing empowers and transforms students intellectually, creatively and culturally. Thus, digital storytelling can be seen as a signature pedagogy for the new Humanities in the 21st century.
Nuclear factors that bind two regions important to transcriptional activity of the simian immunodeficiency virus long terminal repeat

Previous studies identified two regions in the U3 region of a molecular clone of simian immunodeficiency virus, SIVmac142, that are important to transcriptional activity under conditions of induction as well as basal-level expression (B. Renjifo, N. A. Speck, S. Winandy, N. Hopkins, and Y. Li, J. Virol. 64:3130-3134, 1990). One region includes the NF-kappa B binding site, while the other lies just 5' of this site between nucleotides -162 and -114 (the -162 to -114 region). The fact that the NF-kappa B site mutation attenuated transcriptional activity in uninduced T cells and fibroblasts where activated NF-kappa B would not be present suggested that a factor(s) other than NF-kappa B could be acting through this site. In this study, we have identified a factor which binds to a cis element overlapping the NF-kappa B site. This factor, which we call simian factor 3 (SF3), would play a role in regulation under conditions of basal level expression, whereas under conditions of induction, NF-kappa B would act via this region. SF3 may also bind to an element in the -162 to -114 region. In addition, we have identified two other factors that bind the -162 to -114 region. One, which we designated SF1, is a ubiquitous basal factor, and the other, SF2, is a T-cell-predominant phorbol myristate acetate-inducible factor. Through identification of nuclear factors that interact with the U3 region of the SIVmac142 long terminal repeat, we can gain insight into how this virus is transcriptionally regulated under conditions of basal-level expression as well as conditions of T-cell activation.
Automated Configuration Design and Analysis for ServiceHigh-Availability

The need for highly available services is ever increasing in various domains ranging from mission critical systems to transaction based ones such as online banking. The Service Availability Forum (SAForum) has defined a set of services and related Application Programming Interface (API) specifications to address the growing need of commercial-off-the-shelf high availability solutions. Among these services, the Availability Management Framework (AMF) is the service responsible for managing the high availability of the application services. To achieve this task, an AMF implementation requires a specific logical view of the organization of the application’s services and components, known as an AMF configuration. Any AMF configuration must be compliant to the concepts and constraints defined in the AMF specifications. The process of defining AMF configurations is error prone and requires extensive domain knowledge. Another major issue is being able to analyze the designed AMF configuration to quantify the anticipated service availability. This requires a different set of modeling and analysis skills that system integrators might not necessarily possess. In this dissertation we propose the automation of this process. The premise is to define a generation method within which we embed the domain knowledge and the domain constraints, and by that generating AMF configurations that are valid by construction. We also define an approach for the service availability analysis of AMF configurations. Our method is based on generating an analysis stochastic model that captures the middleware behavior and the application configuration. This model is thereafter solved to quantify the service availability.
Microfabricated devices for DNA extraction toward realization of deep-sea in situ gene analysis

This study presents microfabricated devices for in situ gene analysis in deep-sea environments. Two kinds of microfabricated devices, one for cell lysis and the other for DNA purification, are developed and evaluated using living bacterial cells, Escherichia coli (E. coli), and /spl lambda/DNA, respectively, through laboratory experiments. Both devices are composed of a silicone-elastomer based "microchannel chip" and a glass based "temperature control chip". In the cell lysis device, E. coli cells are lysed by applying a chemical or an enzyme, and can be broken into DNA and impurities. And in the DNA purification device, /spl lambda/DNA is selectively bound to glass beads in the solution with higher ionic concentration. Then, the DNA is eluted by the solution with lower ionic concentration, such as TE buffer. As a result, obtained DNA can be applied to various molecular biological analyses including PCR (polymerase chain reaction). By further integration and automation, the developed devices will contribute to in situ gene analysis systems to be mounted on ROVs and AUVs.
Weighted Model Counting With Function Symbols

Probabilistic relational languages lift the syntax of relational logic for the speciﬁcation of large-scale probabilistic graphical models, often admitting concise descriptions for interacting random variables over classes, hierarchies and constraints. The emergence of weighted model counting as an e ﬀ ective and general approach to probabilistic inference has further allowed practitioners to reason about heterogeneous representations, such as Markov logic networks and ProbLog programs, by encoding them as a logical theory. However, much of this work has been limited to an essentially propositional setting: the logical model is understood in terms of ground formulas over a ﬁxed and ﬁnite domain; no inﬁnite domains, and certainly no function symbols (other than constants). On the one hand, this is not surprising, because such features are very problematic from a decidability viewpoint, but on the other, they turn out to be very attractive from the point of view of machine learning applications when there is uncertainty about the existence and identity of objects. In this paper, we reconsider the problem of probabilistic reasoning in a logical language with function symbols, and establish some key results that permit e ﬀ ective algorithms.