Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing for the Next Generation Science Standards: Educative Curriculum Materials and Measures of Teacher Knowledge

ABSTRACT Focusing on the science knowledge and pedagogical content knowledge that teachers need to realize the vision of the Next Generation Science Standards (NGSS) in their classrooms, this article presents findings from efforts to (a) adapt existing criteria and design heuristics for educative features of curriculum materials and apply them in the development of materials to support NGSS and (b) develop an authentic measure of teachers’ knowledge and practice based on an analysis of teachers’ evaluations of their students’ written explanations of phenomena. The study demonstrates that existing criteria and heuristics for designing educative features of curriculum materials can be used productively, with minor modifications, to design features that support teachers in their use of materials that support NGSS. It also provides quantitative and qualitative data to show that teachers’ analyses of the explanation task produced useful information about their understanding of the science ideas targeted in the assessment; of the misconceptions their students held; and of their students’ ability to reason from evidence, science ideas, and models in explaining phenomena. This study builds on and contributes to a body of work on the design and use of educative curriculum materials and the evaluation of teacher knowledge. It suggests a practical approach to the design of NGSS-aligned curriculum materials that support both student and teacher learning based on findings from analysis and empirical studies.
A 0 . 18 μ m Variable Gain Transimpedance Amplifier for 2 . 4 GHz IEEE 802 . 15 . 4 Direct Conversion Receiver

A variable transimpedance amplifier suitable for low power wireless personal area network is presented from toplevel specifications to circuit level design. Its specifications are defined and justified for a direct conversion receiver architecture. A multiple-feedback-loop topology which allows for programmable gain, constant bandwidth, and DC attenuation is proposed. The design methodology is performed over a 60 dB gain range with 4 dB step and achieves 12mVRMS of noise and 3.4mW of power consumption.
Jointly optimizing sensor selection and power control for nonlinear sensor networks

Problem of joint optimization of active sensor selection and power control for nonlinear sensor networks is considered. The proposed solution expresses binary (discrete) constraints of the sensor selection problem as continuous d.c. (difference of two convex functions/sets) constraint along with an exact penalty function approach. Thus, the problem is expressed as minimization of a d.c. function subject to convex constraints. Subsequent simulation results indicate that the proposed method is able to locate its optimal solution and that the network performance can be fully achieved by activating half of the available sensor nodes.
Cognitive profile of patients with alcoholic Korsakoff's syndrome

Presents an overview of empirical research on cognitive dysfunctions characteristic of alcoholic Korsakoff's syndrome (KS). Recent evidence shows that, apart from severe anterograde and retrograde memory deficits, Korsakoff's pathology can include pronounced emotional abnormalities and impairments in executive functioning (e.g., problem solving, cognitive flexibility, set shifting, and task monitoring). Neurological studies have consistently revealed lesions in diencephalic and prefrontal brain areas among KS patients. It is assumed that damage in mammillary regions and the thalamus are determinants of amnesic symptoms, whereas observed executive dysfunctions more likely result from damage in the prefrontal lobe. Future research will more closely examine the causes of brain changes in KS, discerning between the primary neurotoxic effects of alcohol consumption on the one hand, and the secondary effects of malnutrition and/or vitamin deficiencies on the other. A further topic of inquiry will concern symptom specificity in KS, alcohol-addiction, and alcohol-related dementia.
Low-Dimensional Dynamics in Agent-Based Models

Within recent years, agent-based models have achieved growing prominence in several fields of study. Although powerful and expressive for characterizing the evolution of large populations exhibiting persistent interactions between individuals and high heterogeneity, agent-based methods do not come without tradeoffs. Such methods are burdened by relatively high runtime, lack a formal canonical, declarative, and transparent mathematical semantics, and are often challenging to program, understand, calibrate, generalize and validate. It is therefore important to help modelers recognize modeling contexts requiring the full generality of such models. This paper takes a preliminary step in that direction. Specifically, we built and apply a framework that applies the theory of delay embedding and generic algorithms for intrinsic dimensionality assessment in order to estimate the intrinsic dimensionality of the trajectory of agent-based models. This dimensionality provides a lower bound on the number of state variables required in any model that seeks to reproduce the behavior of these agent based models. Although results are tentative and particularly sensitive to noise, our work appears to indicate that many highly descriptively complex agent-based models may give rise to exceptionally low dimensional global behavior. We suggest that there may be opportunities for expressing the behavior of many complex agent-based models using state equation models offering much far smaller size and greater computational economy.
A Distributed Approach for Inferring Production Systems

Tools for building production systems encounter the problem of low performance, and many researchers are working on the improvements of performance of these tools. This paper proposes a distributed approach for inferring production systems. The resulting distributed production systems are expected to be built over distributed systems with broadcast capability, and production rules on different sites work in a cooperative way with only a few communications between them. Working memory on a local site is made visible to rules on remote sites. A tool for building distributed production systems, called DPS, has been implemented. DPS not only supports elegant constructs for expressing the capacity of distributed inference but also provides the facilities for building clusters of rules. With these facilities, DPS allows users to make the inference engine focus on a particular set of rules. This paper also describes the knowledge representation and other features about DPS.
Upplevelsen och förekomsten av fenomen i arbetsplatsrelaterade konflikter : Två delstudier

Pa arbetsplatsen sker mansklig interaktion och det ar oundvikligt att konflikter uppstar. Syftet var att utifran individers upplevelse av en arbetsplatsrelaterad konflikt se pa vilka faktorer som p .
Feature Selection to Relate Words and Images

Image annotation, i.e. mapping words into images, is currently a major research problem in image retrieval. In particular, images are usually segmented into a number of regions, and then low-level image features are extracted from the segmented regions for annotation. As the extracted image features may contain some noisy features, which could de- grade the recognition performance when the number of keywords assigned to images is very large, image feature selection needs to be considered. In this paper, a Pixel Density filter (PDfilter) and Information Gain (IG) are used as the feature se- lection techniques. By using Corel as the dataset, 10, 50, 100, 150 and 190 keywords annotation are setup for compari- sons. The experimental result shows that PDfilter and IG can increase the precision of image annotation by colour or tex- ture features. However, they do not enhance the annotation performance by the combined colour and texture features.
9th International Conference on Knowledge Based and Intelligent Information and Engineering Systems Pattern-based Transformation of Diagrammatic Conceptual Models for Semantic Enrichment in the Web of Data

The goal of this paper is to bridge the paradigms of Linked Data and Conceptual Modeling, which have been developed from quite distinct concerns, although certain opportunities may stimulate the evolution of the Web towards a new type of knowledge space driven by diagrammatic models. To this end, the work at hand investigates structural patterns in a multitude of modeling languages accumulated over time within the Open Model Initiative Laboratory and defines for each pattern transformation rules that produce graph-based model serializations, thus enabling the processing of diagrammatic models using the Web of Data technological space and practices.
A combined comparative genomic hybridization and expression microarray analysis of gastric cancer reveals novel molecular subtypes.

Comparative genomic hybridization (CGH), microsatellite instability (MSI) assays, and expression microarrays were used to molecularly subclassify a common set of gastric tumor samples. We identified a number of novel genomic aberrations associated with gastric cancer and discovered that gastric tumors could be grouped by their expression profiles into three broad classes: "tumorigenic," "reactive," and "gastric-like. " Patients with gastric-like tumors exhibited a significantly better overall survival than patients belonging to the other two classes (P < 0.05). A novel supervised learning methodology for multiclass prediction was used to identify optimal predictor gene sets that accurately predicted the class of an unknown tumor sample. These predictor sets may prove useful in the development of new diagnostic applications for gastric cancer staging and prognostication.
Gaussian Process Regression Plus Method for Localization Reliability Improvement

Location data are among the most widely used context data in context-aware and ubiquitous computing applications. Many systems with distinct deployment costs and positioning accuracies have been developed over the past decade for indoor positioning. The most useful method is focused on the received signal strength and provides a set of signal transmission access points. However, compiling a manual measuring Received Signal Strength (RSS) fingerprint database involves high costs and thus is impractical in an online prediction environment. The system used in this study relied on the Gaussian process method, which is a nonparametric model that can be characterized completely by using the mean function and the covariance matrix. In addition, the Naive Bayes method was used to verify and simplify the computation of precise predictions. The authors conducted several experiments on simulated and real environments at Tianjin University. The experiments examined distinct data size, different kernels, and accuracy. The results showed that the proposed method not only can retain positioning accuracy but also can save computation time in location predictions.
Perspectives on diagnostic failure and patient safety.

T he Institute of Medicine (IOM) report To Err Is Human (Kohn et al. 1999), published at the turn of the century, signalled the beginning of the modern era of patient safety. Although a variety of good work followed, in hindsight what appears to have been missing at the beginning was sufficient pause to ask which of the many possible directions should be taken to achieve the most value for effort; only recently has this question been framed (Pronovost and Faden 2009). At the outset, it was understandable that the focus should be put on the tangible, obvious and most easily fixed problems. Medication error, for example, was quickly identified, and considerable work followed in this area. Other less tangible areas attracted less attention. Diagnostic failure appears to have been a major oversight and remains a major threat to patient safety. Wachter (2010) notes that the term medication error is mentioned more than 70 times in the IOM report (Leape et al. 1991), whereas diagnostic error appears only twice – even though physician errors that lead to adverse events are significantly more likely to be diagnostic (14%) than medication related (9%) (Leape et al. 1991). In both Canada (Canadian Medical Protective Association, personal communication , 2011) and the United States (Chandra 2005), diagnostic error is the leading cause of malpractice litigation. At the end of a long career in medical decision-making, Elstein (2009) estimated that diagnostic failure across the board in medicine was in the order of 15%. The Invisibility of Diagnostic failure A major part of the problem is the inherent obscurity, complexity and irreducible uncertainty associated with human illness. In turn, the diagnostic process that attempts to identify it is similarly obscure. These issues have been well articulated by Montgomery (2006). As she notes, if illness were to follow scientific rules, our difficulties in this area would have been solved long ago. Instead, physicians often have to deal with a process that has " mushy but unavoidable ineffabilities " (Montgomery 2006). This is the process that takes place at the dynamic interface between the patient's and the physician's thoughts, feelings, reasoning and decisions. Part of the problem, too, has been the tight control that physicians have exerted over diagnosis as well as an attendant culture of silence and secrecy – both have led to further obfusca-tions of the process. Other healthcare workers have been largely excluded, sharing little …
Progress in diffraction-limited imaging at the Multiple Mirror Telescope with adaptive optics

Low spatial frequencies of atmospheric turbulence are especially troublesome to astronomers because the phase distortions that these frequencies cause have a large amplitude. We have begun experiments at the Multiple Mirror Telescope to remove these errors with tip, tilt, and piston control of pieces of the wave front that are defined by the telescope’s six 1.8-m primary mirrors. We present long-exposure images that were recorded at the telescope with a resolution of as high as 0.08 arcsec under piston control, and 0.32 arcsec under tilt control, by use of an adaptive instrument designed to restore diffraction-limited imaging in the near infrared. Of particular importance for high-resolution imaging is the control of the piston or the mean phase errors between the segments. These errors can be calculated from the Fourier transform of the short-exposure combined-focus image, but the accuracy of the reconstructed wave front depends critically on the signal-to-noise ratio of the data. We present a theoretical analysis of the effects of photon and detector read noise on the derived piston errors and computer simulations of wave-front reconstructor algorithms. We find that a Wiener filter combined with nonlinear weighting of the piston errors minimizes the impact of noise. Finally, we summarize expected improvements to our system and discuss the application of these techniques to forthcoming large telescopes.
Efficient Surface Interpolation with Occlusion Detection

In this paper we present a novel dense matching algorithm that relies on sparse stereo data in order to build a dense disparity map. The algorithm uses a recursive updating scheme to estimate the dense stereo data using various interpolation techniques. The major problem of classical template matching techniques is their reliance on a fixed template shape and poor performance around untextured regions. In this paper we attempt to alleviate the problem of template matching techniques by using an adaptive window shape and also by avoiding searching in homogenous image regions that are difficult to match by templates. The outcome is an algorithm that performs at least ten times faster than template matching, and yet it achieves higher accuracy. Moreover, our algorithm preserves depth discontinuities and assigns disparities at occluded regions.
Multiferroic properties of Pb(Zr,Ti)O3∕CoFe2O4 composite thin films

In the present work we report multiferroic behavior in lead zirconate titanate (PZT)–cobalt iron oxide (CFO) composite thin films. It is found that upon annealing, the multilayered structures are intermixed at least partially, and CFO is phase separated into PZT matrix to form a composite film. The phase separation behavior has been characterized by x-ray photoelectron spectroscopy depth profiling of the constituent elements in conjunction with dielectric spectroscopy measurements. The composite films exhibited ferroelectric as well as ferromagnetic characteristics at room temperature. The coupling between the ferroelectric and the ferromagnetic order parameters has been demonstrated through the reduction of ferroelectric polarization when measured under an applied magnetic field.
InfoSlim: An Ontology-Content Based Personalized Mobile News Recommendation System

This paper proposes a novel personalized news recommendation system named InfoSlim. The new system uses semantic technique to annotate news items and user preference in order to add rich metadata information into traditional keyword vector. By doing this, the similarity measure between item profile and user profile can be done by not only lexical-level cosine-based method but also by semantic-level ontology-based method. Such recommendation method can efficiently improve the accuracy of recommendation and therefore can better reflect user's interest and save mobile resources.
An Adaptive Workflow Scheduling Scheme Based on an Estimated Data Processing Rate for Next Generation Sequencing in Cloud Computing

Abstract —The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.
Politicians, Photographers, and a Pope

Pope Francis’s 2015 visit to Cuba provided a unique opportunity for a comparative study of state-controlled and independent media systems. This study, grounded in the interpretivist tradition, uses symbolic convergence theory and fantasy theme analysis to explore how visuals created by United States-based AP Images, United Kingdom-based Reuters, and Cuba-based Prensa Latina reveal the underlying rhetorical visions, ideologies, and priorities of each culture’s media system. More specifically, state-controlled and independent media depicted the Pope’s visit differently in the degree of personalization shown, the social actors who were depicted, the purpose of the visit, how the Pope was shown in relation to others, and the location where the action occurred. Each media system highlighted its news values and priorities through these differences. Additionally, the images revealed two master narratives: Cuba as a model of Catholicism and the Pope as a model of hierarchy and conformity.
Control of mechanical systems with second-order nonholonomic constraints: underactuated manipulators

An analysis of underactuated manipulators from both the dynamic and the control points of view is presented. While the unactuated joints dynamic equation is recognized to be a nonholonomic constraint in the general case, necessary and sufficient conditions are given to identify special cases in which such a constraint is integrable. In contrast to most examples in the literature, the unactuated joints dynamics is an instance of a second-order nonholonomic constraint. it is shown that smooth feedback stabilization to a single equilibrium point is not possible, and a feedback scheme providing stabilization to a manifold of equilibrium positions is proposed. <<ETX>>
CloudBridge: a Simple Cross-Cloud Python Library

With clouds becoming a standard target for deploying applications, it is more important than ever to be able to seamlessly utilize resources and services from multiple providers. Proprietary vendor APIs make this challenging and lead to conditional code being written to accommodate various API differences, requiring application authors to deal with these complexities and to test their applications against each supported cloud. In this paper, we describe an open source Python library called CloudBridge that provides a simple, uniform, and extensible API for multiple clouds. The library defines a standard 'contract' that all supported providers must implement, and an extensive suite of conformance tests to ensure that any exposed behavior is uniform across cloud providers, thus allowing applications to confidently utilize any of the supported clouds without any cloud-specific code or testing.
Epigenetic regulatory elements associate with specific histone modifications to prevent silencing of telomeric genes

In eukaryotic cells, transgene expression levels may be limited by an unfavourable chromatin structure at the integration site. Epigenetic regulators are DNA sequences which may protect transgenes from such position effect. We evaluated different epigenetic regulators for their ability to protect transgene expression at telomeres, which are commonly associated to low or inconsistent expression because of their repressive chromatin environment. Although to variable extents, matrix attachment regions (MARs), ubiquitous chromatin opening element (UCOE) and the chicken cHS4 insulator acted as barrier elements, protecting a telomeric-distal transgene from silencing. MARs also increased the probability of silent gene reactivation in time-course experiments. Additionally, all MARs improved the level of expression in non-silenced cells, unlike other elements. MARs were associated to histone marks usually linked to actively expressed genes, especially acetylation of histone H3 and H4, suggesting that they may prevent the spread of silencing chromatin by imposing acetylation marks on nearby nucleosomes. Alternatively, an UCOE was found to act by preventing deposition of repressive chromatin marks. We conclude that epigenetic DNA elements used to enhance and stabilize transgene expression all have specific epigenetic signature that might be at the basis of their mode of action.