Miracle-dz/UniFAR-FTUs huggingface dataset:
Professional Degree Programs for the Development of Accomplished Teachers: A case for the National Board Certification process

This study examines how teachers’ knowledge of teaching and instructional practices was affected by their participation in a graduate-level program designed to prepare teachers for National Board certification while earning a master’s degree in education. Four cohorts of participants were studied over a 5-year period. Quantitative and qualitative findings indicate that program participation affected four aspects of the teachers’ development as professionals: (1) understanding the importance of linking theory and practice, (2) engaging in cycles of inquiry for transforming practice, (3) actively participating in collaborative learning with their peers, and (4) adopting a new professional identity as teacher leaders.
The BRENDA Tissue Ontology (BTO): the first all-integrating ontology of all organisms for enzyme sources

BTO, the BRENDA Tissue Ontology (http://www.BTO.brenda-enzymes.org) represents a comprehensive structured encyclopedia of tissue terms. The project started in 2003 to create a connection between the enzyme data collection of the BRENDA enzyme database and a structured network of source tissues and cell types. Currently, BTO contains more than 4600 different anatomical structures, tissues, cell types and cell lines, classified under generic categories corresponding to the rules and formats of the Gene Ontology Consortium and organized as a directed acyclic graph (DAG). Most of the terms are endowed with comments on their derivation or definitions. The content of the ontology is constantly curated with ∼1000 new terms each year. Four different types of relationships between the terms are implemented. A versatile web interface with several search and navigation functionalities allows convenient online access to the BTO and to the enzymes isolated from the tissues. Important areas of applications of the BTO terms are the detection of enzymes in tissues and the provision of a solid basis for text-mining approaches in this field. It is widely used by lab scientists, curators of genomic and biochemical databases and bioinformaticians. The BTO is freely available at http://www.obofoundry. org.
On contour representation of two dimensional patterns

Two-dimensional patterns are used in many research areas in computer science, ranging from image processing to specification and verification of complex software systems (via scenarios). The contribution of this paper is twofold. First, we present the basis of a new formal representation of two- dimensional patterns based on contours and their compositions. Then, we present efficient algorithms to verify correctness of the contour-representation. Finally, we briefly discuss possible applications, in particular using them as a basic instrument in developing software tools for handling two dimensional words.
Evaluation Mechanism for Web Service Based on Semantics and Reputation

In open network, unfamiliar web services are unavailable due to lack of effective mechanism to evaluation their performances for users. In order to help the user recognizing unknown web services, semantics understanding and reputation based evaluation mechanism is introduced into web service research. Semantics understanding based evaluation is according to the user's requirements semantics and the semantics of candidate web service's capacities. Reputation ranking method is proposed to build up a neutral and whole belief about a web service. Web service reputation is composed by two facets: time limitation and ranking delay. Finally, the experiment shows that our approach is feasible and effective.
End-to-End Task-Completion Neural Dialogue Systems

One of the major drawbacks of modularized task-completion dialogue systems is that each module is trained individually, which presents several challenges. For example, downstream modules are affected by earlier modules, and the performance of the entire system is not robust to the accumulated errors. This paper presents a novel end-to-end learning framework for task-completion dialogue systems to tackle such issues.Our neural dialogue system can directly interact with a structured database to assist users in accessing information and accomplishing certain tasks. The reinforcement learning based dialogue manager offers robust capabilities to handle noises caused by other components of the dialogue system. Our experiments in a movie-ticket booking domain show that our end-to-end system not only outperforms modularized dialogue system baselines for both objective and subjective evaluation, but also is robust to noises as demonstrated by several systematic experiments with different error granularity and rates specific to the language understanding module.
Impact of DSM-5 changes on the diagnosis and acute treatment of schizophrenia.

OBJECTIVE To examine the consequences and validity of changes in Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 diagnostic criteria for schizophrenia, eg, omission of subtypes, using a large dataset of double-blind, randomized, placebo-controlled schizophrenia trials. METHODS Data from 22 short-term efficacy registration trials of second generation antipsychotics for the treatment of acute psychotic episodes in patients with schizophrenia (N = 5233), submitted to the Dutch regulatory authority were analyzed. We examined whether patients in these pre-DSM-5 trials met the diagnostic criteria for schizophrenia according to DSM-5. Using linear regression, we examined differences in effect size between DSM-IV subtypes and between DSM-5 symptom dimensions. RESULTS Over 99.5% of the patients met DSM-5 diagnostic criteria for schizophrenia and no differences in effect size were found between schizophrenia subtypes (P = .65). Symptom dimensions that respond best to treatment with second generation antipsychotics were hallucinations, delusions, disorganized speech, and mania (Hedge's g -0.23 to -0.31). CONCLUSIONS Results of clinical trials in patients with pre-DSM-5 schizophrenia also apply to patients diagnosed with DSM-5 schizophrenia. Omission of the classic subtypes is justified as they are not predictive of response to treatment. The DSM-5 C-RDPSS scale adds valuable information to the categorical diagnosis of schizophrenia, which is relevant for antipsychotic response.
Research on Media Stream Transmission Based on Back-pressure in Mobile Wireless Network

With the development of smart-phone devices, media stream transmission is bound to make wireless network communication resources that are in short supply cause greater pressure. Due to the user's move in the media stream transmission process in the mobile wireless network, it may be possible to lead to the following questions: the established connection is interrupted; the effect in data transmission structure becomes poor or invalid; wireless connection changes more frequently. All these problems will directly result in the QoS of media stream transmission. Back pressure algorithm is a control method which is firstly proposed by Tassinlas and Ephremides in the control theory. We choose back pressure algorithm as the basic research method of mobile media stream transmission because of the conclusion that back pressure algorithm can make the network load balance and maximize network utilization. According to the above problem, the article proposes the back-pressure algorithm guaranteeing deadline, and the proposed algorithm can well guarantee deadline of packet transmission. It not only can remove the packets which are redundant or staying too long time in the network, but also can make network throughput optimal. And in order to speed up the network's convergence speed and improve user's satisfaction index. We proposed cluster-based back pressure algorithm guaranteeing deadline.
The Nexus between Natural Gas Spot and Futures Prices at NYMEX: Do Weather Shocks and Non-Linear Causality in Low Frequencies Matter?

The existence of non-linear dynamics in the prices of financial commodities is an endemic feature and one of the most fundamental stylized facts in the literature. This study, conditioning on weather shocks, investigates the nature of the existing predictive power between natural gas spot and futures prices with one-month maturity at the NYMEX market. By implementing successively, before and after a first-moment filtering, a frequency domain causality test [Breitung J., Candelon B. , 2006. Testing for short- and long-run causality: a frequency domain approach. Journal of Econometrics 132, 363-378], we corroborated a unidirectional non-linear forecasting ability in low frequencies that runs from the short maturity futures market towards the spot market.
Strategic Subcarrier Allocation for Cooperative OFDMA Relaying Network

Performance optimization of communication networks with quality of services (QOS) considerations for all active users is highly desirable. The growth of wireless multimedia applications requires high-speed and reliable communication over wireless channels of system. Throughput and fairness are important conflicting performance parameter in resource allocation for non-cooperative and cooperative OFDMA system for downlink transmission. Maximize the system throughput creates problem of unfairness among all user and while maintaining fairness, system throughput will degrade accordingly. In this paper, we proposed algorithm to provide a balanced approach to maintain throughput and fairness in the system and we designed the resources allocation algorithm for cooperative OFDMA system for downlink transmission, that algorithm maintain the fairness among the all user without affecting the throughput of the system. Our proposed subcarrier allocation fills the gap between the fairness-oriented and throughput-oriented algorithms and provides a balanced solution for subcarrier allocation in the system.
Decoupling control for the speed synchronization task in the powertrain of a hybrid electric vehicle

In this paper a novel framework for a multivariable control design task in the field of hybrid electric vehicles is introduced. The problem under consideration consists of a speed synchronization task of two propulsion aggregates using a controllable separation clutch. During this synchronization period the longitudinal vehicle motion of the vehicle should not be affected. The proposed control strategy is based on a decoupling network and two optimized controllers. The performance and robustness properties of the closed-loop system are shown by nonlinear simulation results.
Music from behind the bridge : steelband spirit and politics in Trinidad and Tobago

Dedication Acknowledgements Chapter One Introduction Chapter Two The Steelband Movement and Music Chapter Three An Unlikely Instrument Chapter Four The National Instrument Chapter Five Dropping the Bomb Chapter Six A Showcase for Pan Chapter Seven Rise of the Arranger Chapter Eight Community Participation Chapter Nine Contest and Control Chapter Ten Writing Their Own Tunes Chapter Eleven From Panman to Pannist Chapter Twelve Popular culture and Nationalism Appendix I: Instruments Appendix II: Repertoire Appendix III: Panorama Winners Bibliography Recordings Cited Index
Quantitative voxel-based analysis of T 1-weighted MRI signal intensity

Abnormalities in the brain generally manifest on MRI as changes in shape (morphometry) or changes in the nature of the tissue (signal intensity). Voxel-based statistical analysis approaches are able to objectively detect such changes throughout the brain. For example, Voxel Based Morphometry (VBM) [2] and Voxel Based T2relaxometry (VBR) [3] can detect subtle changes in tissue volume and T2 signal intensity respectively. Whilst VBM can be applied to any imaging modality with sufficient contrast between tissue classes (such as T1-weighted MRI), a fully quantitative modality is usually required for the direct detection of signal intensity changes. Thus the application of a voxel-based approach for direct detection of signal differences in T1-weighted MRI would not normally be considered. The intensity of conventional T1-weighted images depends on multiple factors such as shim, coil loading and receiver gain settings, and can vary markedly across imaging sessions and subjects. Whilst quantitative T1-relaxomety may be able to avoid these problems, sequences to achieve this at high-resolution and a reasonable imaging time are not routinely available on clinical scanners. We therefore sought to determine the sensitivity of the Voxel-Based Iterative Sensitivity (VBIS) approach when applied to T1weighted images.
Intergenerational Risk Sharing under Loss Averse Preferences

Individual retirement savings schemes could benefit from risk-sharing mechanisms between generations that take behavioral aspects into account. We introduce a novel risk-sharing mechanism that incorporates nominal loss-aversion in two ways. First, the system avoids out-of-pocket wealth transfers by sharing only a fraction of positive returns over a high-water mark of pension assets. Secondly, payments from a generation insurance fund are targeted at nominal pension shortfalls below a reference point, which mitigates the loss experience at retirement. From a simulation of overlapping generations with stochastic asset returns and interest rates we find that the generation insurance scheme outperforms a pure individual retirement scheme by a significant margin: a similar risk of pension shortfall can be achieved with a contribution rate that is up to 20% lower. The efficiency gains vary with the extent of risk sharing over generations but remain large for sensible parameter values.
Frame Selection in Parsing

The problem of frame selection in parsing is discussed, with the focus on the selection of a frame for texts which contain highly ambiguous or vague words. An approach to frame selection is presented which involves the use of a small number of general inference rules, in conjunction with a hierarchically-organized conceptual memory. This is in contrast to various other methods, which rely either on disambiguation rules stored in the dictionary definitions of ambiguous words, or on previously-activated frames to guide the selection of new frames. The selection of frames for vague or ambiguous words using these previous methods is shown to be problematic. The method presented here does not suffer from these same problems because of the hierarchical organization of memory and the general inference rules used.
Geometric-component modeling in charge-pumping technique

A semi-analytical-model is proposed to predict the geometric component in charge pumping (CP) measurements for transistors. It is based on contributing of active CP-area and low-level voltage (VL) of the gate signal, thermal diffusion, drift field, and self-induced drift field. The calculated ICP-VL characteristics with geometric component model are found in good correlation with the experimental ICP-VL data and are more accurate than the calculated CP without geometric component. This modeling approach can be extended for MOSFET stress reliability evaluation such as negative bias temperature instability (NBTI) and radiation degradations.
Longevity and Redistribution in the German Pension System

There are theoretical foundations which allow hypothesizing on a positive association of life expectancy or retirement age with income. If both cannot be falsified, the relationship of income and the internal rate of return of a public pension system is not straight forward. By application of a partially linear model to micro data from the German public pension system, it is found that neither life expectancy, nor retirement age is monotonously increasing in income, as measured in benefit claims. The relation of benefit claims and duration under the benefit spell (which determines the rate of return) depends on the set of covariates. Including pensions for disabled individuals, three out of four specifications exhibit a duration decreasing in benefit claims.
Identifying Neutral Technology Shocks

The role of neutral technology shocks in driving business cycle fluctuations is hotly debated. Yet, we argue that there is no existing empirical methodology that allows to identify neutral shocks in the data in the presence of input heterogeneity in the aggregate production function. We develop a method that identifies a neutral technology shock based on the result that it is the only shock consistent with balanced growth properties. Monte Carlo simulations using benchmark business cycle models imply that the proposed method performs very well in small samples. We apply the method to assess the role of neutral technology in driving business cycle fluctuations in U.S. data. JEL Classification: E32, E24
Australia's National School Data and the ‘Big Data’ Revolution in Education Economics

type="main" xml:lang="en"> The increasing availability of large-N datasets on students, schools and student achievement has produced an explosion of research in education economics over the past 20 years. In this data survey, we first review the micro-level education datasets presently available around the world, focusing on their strengths and data access protocols, and we highlight samples of research by economists that have drawn upon them. We then discuss Australia's forays into ‘Big Data’ in education, with our main objective a description and assessment of the national school data recently made available to researchers through the Australian Curriculum, Assessment and Reporting Authority.
Alphavirus Replicon Particles Expressing TRP-2 Provide Potent Therapeutic Effect on Melanoma through Activation of Humoral and Cellular Immunity

Background Malignant melanoma is the deadliest form of skin cancer and is refractory to conventional chemotherapy and radiotherapy. Therefore alternative approaches to treat this disease, such as immunotherapy, are needed. Melanoma vaccine design has mainly focused on targeting CD8+ T cells. Activation of effector CD8+ T cells has been achieved in patients, but provided limited clinical benefit, due to immune-escape mechanisms established by advanced tumors. We have previously shown that alphavirus-based virus-like replicon particles (VRP) simultaneously activate strong cellular and humoral immunity against the weakly immunogenic melanoma differentiation antigen (MDA) tyrosinase. Here we further investigate the antitumor effect and the immune mechanisms of VRP encoding different MDAs. Methodology/Principal Findings VRP encoding different MDAs were screened for their ability to prevent the growth of the B16 mouse transplantable melanoma. The immunologic mechanisms of efficacy were investigated for the most effective vaccine identified, focusing on CD8+ T cells and humoral responses. To this end, ex vivo immune assays and transgenic mice lacking specific immune effector functions were used. The studies identified a potent therapeutic VRP vaccine, encoding tyrosinase related protein 2 (TRP-2), which provided a durable anti-tumor effect. The efficacy of VRP-TRP2 relies on a novel immune mechanism of action requiring the activation of both IgG and CD8+ T cell effector responses, and depends on signaling through activating Fcγ receptors. Conclusions/Significance This study identifies a VRP-based vaccine able to elicit humoral immunity against TRP-2, which plays a role in melanoma immunotherapy and synergizes with tumor-specific CD8+ T cell responses. These findings will aid in the rational design of future immunotherapy clinical trials.
Macro-Financial Linkages: Evidence from Country-Specific VARs

This paper estimates the contribution of financial shocks to fluctuations in the real economy by augmenting the standard macroeconomic vector autoregression (VAR) with five financial variables (real stock prices, real house prices, term spread, loans-to-GDP ratio and loans-to-deposits ratio). This VAR is estimated separately for 19 industrialised countries over 1980Q1-2010Q4 using three alternative measures of economic activity: GDP, private consumption or total investment. Financial shocks are identified by imposing a recursive structure (Choleski decomposition). Several results stand out. First, the effect of financial shocks on the real economy is fairly heterogeneous across countries, confirming previous findings in the literature. Second, the five financial shocks provide a surprisingly large contribution to explaining real fluctuations (33% of GDP variance at the 3-year horizon on average across countries) exceeding the contribution from monetary policy shocks. Third, the most important source of real fluctuations appears to be shocks to asset prices (real stock prices account for 12% of GDP variance and real house prices for 9%). Shocks to the term spread or to leverage (credit-to-GDP ratio or loans-to-deposits ratio) each contribute an additional 3-4% of GDP variance. Fourth, the combined contribution of the five financial shocks is usually higher for fluctuations in investment than in private consumption. Fifth, historical decompositions indicate that financial shocks provide much more important contributions to output fluctuations during episodes associated with financial imbalances (both booms and busts). This suggests possible time-variation or non-linearities in macrofinancial linkages that are left for future research.
Power over reproduction in social hymenoptera.

Inclusive fitness theory has been very successful in predicting and explaining much of the observed variation in the reproductive characteristics of insect societies. For example, the theory correctly predicts sex-ratio biasing by workers in relation to the queen's mating frequency. However, within an insect society there are typically multiple reproductive optima, each corresponding to the interest of different individual(s) or parties of interest. When multiple optima occur, which party's interests prevail? Presumably, the interests of the party with the greatest 'power'; the ability to do or act. This article focuses on factors that influence power over colony reproduction. In particular, we seek to identify the principles that may cause different parties of interest to have greater or lesser power. In doing this, we discuss power from two different angles. On the one hand, we discuss general factors based upon non-idiosyncratic biological features (e.g. information, access to and ability to process food) that are likely to be important to all social Hymenoptera. On the other hand, we discuss idiosyncratic factors that depend upon the biology of a taxon at any hierarchical level. We propose that a better understanding of the diversity of reproductive characteristics of insect societies will come from combining inclusive fitness theory with a wide range of other factors that affect relative power in a conflict situation.
A 24 GHz Subharmonic Direct Conversion Receiver in 65 nm CMOS

Scaled CMOS proves to be suitable for the design of transceiver ICs at micro- and millimeter-waves. The effort is presently toward compact and low-power solutions in view of integrating several transceivers on the same chip enabling phased array systems. In this paper we present a 24 GHz receiver, based on a subharmonic direct conversion architecture, designed in a 65 nm node. The local oscillator takes advantage of the half frequency operation proving significantly lower power consumption when compared to conventional solutions running at received frequency. Stacked switches for subharmonic down-conversion are passive to save voltage room, current driven and loaded by a transresistance amplifier. Optimum biasing of the switches allows maximizing linearity while saving power in the baseband. The integrated LNA matching network is the bottleneck toward low sensitivities. The LNA design trades-off power consumption, gain and sensitivity. Detailed insights into implementation issues, critical in a single-ended topology where both forward and return signal paths have to be supported, are provided. The chip consumes 78 mW and occupies 1.4 mm2 of active area. Experiments show: 30.5 dB gain, 6.7 dB NF, -13 dBm IIP3.