Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase I Pharmacokinetic and Pharmacodynamic Study of Carboplatin and Topotecan Administered Intravenously Every 28 Days to Patients with Malignant Solid Tumors

Purpose: Preclinical studies have shown that the combination of topotecan and carboplatin is synergistic. To evaluate the schedule dependency of this interaction, the following phase I trial was designed to determine the safety and maximum tolerated dose (MTD), pharmacokinetics, and pharmacodynamics of carboplatin and topotecan in patients with malignant solid tumors. Experimental Design: In part 1, patients received carboplatin on day 1 and topotecan on days 1, 2, and 3 (C→T schedule). In part 2, topotecan was administered on days 1, 2, and 3, followed by carboplatin on day 3 (T→C schedule). Pharmacokinetics were determined in plasma and DNA topoisomerase I catalytic activity and Pt-DNA adducts in WBC and tumor tissue. Results: Forty-one patients were included. Dose-limiting toxicities during the C→T schedule were grade 4 thrombocytopenia and febrile neutropenia (MTD: carboplatin target area under the free carboplatin plasma concentration versus time curve, 4 min mg/mL; topotecan, 0.5 mg/m2/d). Dose-limiting toxicities during the T→C schedule included grade 4 neutropenia, thrombocytopenia, neutropenic fever, and grade 4 nausea and vomiting (MTD: carboplatin target area under the free carboplatin plasma concentration versus time curve, 6 min mg/mL; topotecan, 0.9 mg/m2/d). One complete response and five partial responses were observed. The clearance of and exposure to carboplatin and topotecan did not depend on the sequence of drug administration. No schedule-dependent effects were seen in Pt-DNA levels and DNA topoisomerase I catalytic activity in WBC and tumor tissue. However, myelotoxicity was clearly more evident in the C→T schedule. Conclusion: The T→C schedule was better tolerated because both hematologic and nonhematologic toxicities were milder. Other pharmacodynamic factors than the ones investigated must explain the schedule-dependent differences in toxicities.
Genetic programming and emergent intelligence

Angeline 23 Fogel, D. B (1993). Using evolutionary programming to create neural networks that are capable of playing Tic-Tac-Toe. (1992). Evolution as a theme in artificial life: The genesys/tracker system. In Artificial Life II, C. Angeline 22 4.6 Conclusion Artificial intelligence has made great strides in computational problem solving using explicitly represented knowledge extracted from the task. If we continue to use explicitly represented knowledge exclusively for computational problem solving, we may never computationally accomplish a level of problem solving performance equal to humans. Emergent intelligence de-emphasizes the role of explicit knowledge and encourages the development of solutions that incorporate the task description as a component of the problem solver. This allows the constraints of the task to be represented more naturally and permits only pertinent task specific knowledge to emerge in the course of solving the problem.
FLOUTED MAXIM AND VERBAL HUMOR IN THE TELEVISION SERIES THE BABY DADDY (A PRAGMATIC APPROACH)

This research analyzed the types of humor appeared in the situation comedy The Baby Daddy and their relation to Grice’s Maxims. It is conducted to find out the types of humor based on theory by Audrieth, define whether those humors disobey the Grice’s Maxims as the standard conversational norms and find the relation between types of humor and flouted maxim and its purposes. This research deals with a pragmatic approach. It is a descriptive study. The data are all the humor utterances, which are able to arouse laughter from the audiences that have significant relationship with the problem statement. The result of this research reveals that there are seven types of humor which can be found in this episode. They are Banter, Blunder, Freudian slip, Exaggerism, Mistaken identity, Relapse and Repartee. Concerning with the maxims, it is found that the humors, which are used in every utterances flouted the maxims. The analysis of the maxims is conducted through the context of situation available in each data. The researcher also found that the flouted maxim is done by the characters in delivering the humor. There are also found relation between the flouted maxim and the type of humor in the way it is used by the character. Keywords : pragmatic, humor, flouted maxim
Psychophysical Detection Testing with Bayesian Active Learning

Psychophysical detection tests are ubiquitous in the study of human sensation and the diagnosis and treatment of virtually all sensory impairments. In many of these settings, the goal is to recover, from a series of binary observations from a human subject, the latent function that describes the discriminability of a sensory stimulus over some relevant domain. The auditory detection test, for example, seeks to understand a subject's likelihood of hearing sounds as a function of frequency and amplitude. Conventional methods for performing these tests involve testing stimuli on a pre-determined grid. This approach not only samples at very uninformative locations, but also fails to learn critical features of a subject's latent discriminability function. Here we advance active learning with Gaussian processes to the setting of psychophysical testing. We develop a model that incorporates strong prior knowledge about the class of stimuli, we derive a sensible method for choosing sample points, and we demonstrate how to evaluate this model efficiently. Finally, we develop a novel likelihood that enables testing of multiple stimuli simultaneously. We evaluate our method in both simulated and real auditory detection tests, demonstrating the merit of our approach.
Bandwidth Allocation of Cognitive Relay Networks with Energy Harvesting for Smart Grid

In this paper, we investigate an energy harvesting scheme in a smart grid based on the cognitive relay protocol, where a primary transmitter scavenges energy from the nature sources and then employs the harvested energy to forward the primary signal. Depending on the intensity of the energy harvesting from nature, a secondary user dynamically acts as a relay node to assist the primary transmission or does not. When the energy is not enough powerful to support the direct transmission between two primary users, the secondary users share the spectrum by assisting the primary transmission. For the relaying scheme, both amplify-and-forward (AF) and decode-and-forward (DF) protocols are investigated. We analytically obtain the exact transmission rates for both primary and secondary networks and derive the exact expressions of the system outage probabilities for both primary and secondary users in the smart grid. Moreover, we develop the analytically optimal bandwidth allocation strategy to maximize the total sum rate of the proposed scheme. Numerical results are presented to demonstrate the performance gain of the proposed scheme over the nonoptimal scheme.
Attribute value-range detection in identification of paraphrase sentence pairs

Identification of paraphrase sentence pairs becomes increasingly prominent in natural language processing area (e.g plagiarism detection, summarization, machine translation). In this study, it is proposed to employ information gain measure in determining the value-ranges of the paraphrase classification features on the renown paraphrase corpus of Microsoft Research (MSRP). The classification performances of value-ranges that are determined by information gain measure and an alternative heuristic method are compared by the use of Bayes classifier. The results show that the proposed method performs better than the heuristic method.
Real-Time Estimation of Fault Rupture Extent Using Near-Source versus Far-Source Classification

To estimate the fault dimension of an earthquake in real time, we present a methodology to classify seismic records into near-source or far-source records. Characteristics of ground motion, such as peak ground acceleration, have a strong correlation with the distance from a fault rupture for large earthquakes. This study analyzes peak ground motions and finds the function that best classifies near-source and far-source records based on these parameters. We perform (1) Fisher’s linear discriminant analysis and two different Bayesian methods to find the coefficients of the linear discriminant function and (2) Bayesian model class selection to find the best combination of the peak ground-motion parameters. Bayesian model class selection shows that the combination of vertical acceleration and horizontal velocity produces the best performance for the classification. The linear discriminant function produced by the three methods classifies near-source and far-source data, and in addition, the Bayesian methods give the probability for a station to be near-source, based on the ground-motion measurements. This discriminant function is useful to estimate the fault rupture dimension in real time, especially for large earthquakes.
Chinese and British teachers' emotional reactions towards students' classroom behaviours

The primary objective of this research is to investigate whether Chinese instructors who work in the UK experience different emotions in comparison with British instructors when facing students’ disruptive behaviour. With the increase of the globalization, lager numbers of teachers are teaching abroad (Weber, 2007). Working as international teachers, this group of teachers’ built-in beliefs and cultural values may be challenged by the new cultural context in which they work (Hofstede, 1986; Volet & Ang, 1998). Moreover, according to appraisal theory, when judging an antecedent to an emotion, a person’s cultural beliefs and goals are drawn on (Lazarus, 1991; Frijda, 1986); as such, it can be assumed that, compared with local teachers, international teachers may experience different or more intense emotions due to their different beliefs and goals when they both confront the same students’ behaviours (Sutton & Wheatley 2003). In order to examine this assumption, three phases of studies (a questionnaire survey with video scenarios, a diary study and interviews) were designed. The questionnaire survey with video scenarios of classroom misbehavior contained 47 Chinese and 52 British instructors/teachers as participants and discovered that teachers from China experienced a significantly higher level of anxiety and shame than British teachers. Interestingly, there is a trend showing that British instructors perceived students’ misbehaviours were more troublesome than Chinese instructors, however, when they watched the video clips their emotional reactions to those behaviours in the classroom are less intensive than that of Chinese instructors in general. Finally, according to results from interview study, the depth of tolerance, accountability and teacher’s self-efficacy could be factors that result in these differences discovered between British and Chinese instructors.
Classification of Urinary Sediments Image Based on Bayesian Classifier

In this paper a new method of classification of image in medical domain was introduced. Since the traditional way of diagnosis is slow, time-consuming and heavy-workload, the result is largely influenced by the experience of doctor. The new way of classification can largely improve the efficiency and accuracy in diagnosis. The method is based on Naive Bayesian classification. After distinguishing the visible compositions, feature extraction and feature selection, we can get a naive Bayesian classifier which can be used in classifying of object entities. Experiments show that the new method is suitable for image classification.
Skill mismatch Identifying priorities for future research

The European Centre for the Development of Vocational Training (Cedefop) is the European Union's reference Centre for vocational education and training. We provide information on and analyses of vocational education and training systems, policies, research and practice. Cedefop working papers are unedited documents, available only electronically. They make results of Cedefop's work promptly available and encourage further discussion. 1 Foreword Cedefop's ongoing work on future skill needs and skill supply and the early identification of skill needs in Europe is increasingly recognised as a source of valuable information for policy-makers at national and European levels. The first pan-European forecast of skill needs until 2020 was very well received and fuels European debates on the situation on future labour markets and the upgrading of skill requirements in jobs due to technological innovation and the dynamics of change in work organisations and economies. Cedefop's upcoming skill supply forecasts will complete the picture by analysing how demographic change, patterns of educational choice and other factors and conditions will impact on the supply of people by qualification. Although it is not straightforward to compare future demand to future supply of skills, efforts will be undertaken to develop methods and indicators to provide insights into future mismatch in European labour markets. The nature of Cedefop's skill needs and supply forecasts imply that these mismatches reflect macro-level shortages and surpluses of people with specific qualifications. The resulting information will assist policy-makers and social partners in designing and implementing labour-market and training policies that Europe needs to face its future challenges. Mismatch is a complex and dynamic phenomenon, occurring at different levels and related to the overall economic situation of the economy. Next to quantitative mismatch at macroeconomic level, there are other types of mismatch which impact on employing organisations and individuals. Analyses of mismatch, however, often focus on a single level, without considering links and interdependencies between different types of mismatch and without sufficiently discussing underlying causes and dynamic impacts. This makes a comprehensive understanding of mismatch and the policy implications difficult. Cedefop has recently started new research and analysis to provide more insights on skill mismatch issues and problems in Europe. Several new studies are planned to provide policy-makers with new information needed to anticipate and address mismatch. To establish policy-relevant themes for Cedefop's skill mismatch research in the coming years, experts have been invited to the Centre to share their experience on the most …
Decimation-Whitening Filter in Spectral Band Replication

MPEG-4 High-Efficiency Advanced Audio Coding (HE-AAC) has adopted spectral band replication (SBR) to efficiently compress the high-frequency part of the audio. In SBR, linear prediction is applied to low-frequency subbands to suppress tonal components and smooth the associated spectra for replicating to high-frequency bands. Such a tone-suppressing process is referred to as whitening filtering. In SBR, to avoid the alias artifact incurred by spectral adjustment, a complex filterbank instead of real filterbank is adopted. For QMF subbands, this paper demonstrates that the linear prediction defined in the SBR standard results in a predictive bias. A new whitening filter, called the decimation-whitening filter, is proposed to eliminate the predictive bias and provide advantages in terms of noise-to-signal ratio measure, frequency resolution, energy leakage, and computational complexity for SBR.
Applying classifier systems to learn the reactions in mobile robots

The navigation problem involves how to reach a goal avoiding obstacles in dynamic environments. This problem can be faced considering reactions and sequences of actions. Classifier systems (CSs) have proven their ability of continuous learning, however, they have some problems in reactive systems. A modified CS, namely a reactive classifier system (RCS), is proposed to overcome those problems. Two special mechanisms are included in the RCS: the non-existence of internal cycles inside the CS (no internal cycles) and the fusion of environmental message with the messages posted to the message list in the previous instant (generation list through fusion). These mechanisms allow the learning of both reactions and sequences of actions. This learning process involves two main tasks: first, discriminate between rules and, second, the discovery of new rules to obtain a successful operation in dynamic environments. DiVerent experiments have been carried out using a mini-robot Khepera to find a generalized solution. The results show the ability of the system for continuous learning and adaptation to new situations.
A Systems Engineering Perspective of Aspect-oriented Software Architectural Analysis using UML

Literature on Unified Modeling Language (UML) and aspect-orientation often focus on improving the software development process [2]. This paper presents a systems engineering perspective that motivates an aspect-oriented software architectural analysis approach using representations of UML models. This approach is important in contributing to the direction of applying aspectorientation with UML because it attempts to bridge the gap between software development projects that initiate or follow the recommended research directions in the literature with those that unfortunately, and too frequently, do not. The approach is motivated based on our experiences with a Real-time Embedded Architecture-Centric Testbed (REACT) that was used to perform aspect-oriented software architectural analyses of large military projects and our current applied research in architectural representation using our Software Architectural Representation Analysis and Experimentation Environment (SARAEE). The paper briefly discusses our approach, presents some issues representing cross-cutting architectural concerns that we are investigating and identifies aspect-oriented representation issues relevant to UML.
Labour ’ s Record on Financial Regulation 1

In 1997 the New Labour government launched major initiatives in the area of financial regulation, consolidating regulation under a new Financial Services Authority and enacting new legislation that was proclaimed to be ‘light-touch’ and yet comprehensive. The new regime, widely admired in its initial years, came to be severely tested by the events of global financial crisis that started in 2007. We evaluate the Labour government’s on financial regulation in terms of its achievements and failures, but also assess, more generally, the limits of financial regulation.
Re-engineering OntoSem Ontology Towards OWL DL Compliance

Re-engineering of successful pre-OWL ontologies or other formal ER or UML system models towards OWL DL compliance opens new possibilities in ontology debugging, enabled by the formal semantics and automated reasoners developed for OWL DL. Meanwhile the transformation of legacy ontologies to OWL DL is a challenging and interesting task, which we illustrate in this paper on the example of OntoSem ---a lexical common-sense ontology and an application framework for deep semantic analysis of natural language texts.
Generating the bounded derived category and perfect ghosts

We show, for a wide class of abelian categories relevant in representation theory and algebraic geometry, that the bounded derived categories have no non‐trivial strongly finitely generated thick subcategories containing all perfect complexes. In order to do so, we prove a strong converse of the Ghost Lemma for bounded derived categories.
GAPS : Genetic Algorithm Optimised

The compilation of FORTRAN programs for SPMD execution on parallel architectures often requires the application of program restructuring transformations such as loop interchange, loop distribution, loop fusion, loop skewing and statement reordering. Determining the optimal transformation sequence that minimises execution time for a given program is an NP-complete problem. The hypothesis of the research described here is that genetic algorithm (GA) techniques can be used to determine the sequence of restructuring transformations which are better, or, as good as, those produced by more conventional compiler search techniques. The Genetic Algorithm Parallelisation System (GAPS) compiler framework is presented. GAPS uses GA optimisation to determine the restructuring transformation applied to each statement and its associated iteration space. The hypothesis of GAPS is tested with a comparison of the performance of SPMD code produced by PFA, petit from the Omega Project at the University of Maryland and GAPS for an ADI 10241024 benchmark on an SGI Origin 2000. On this benchmark GAPS produces code having 21? 25% improvements in parallel execution time when measured execution time is used as the evaluation function.
Fuzzy demand forecasting in a predictive control strategy for a renewable-energy based microgrid

In model based control approaches for the dynamic operation of renewable-energy based microgrid, an accurate demand forecast is crucial. However, the high level of uncertainties in the system and non-linearities make the task of prediction not easy. In this context, we propose the use of a stable Takagi & Sugeno (T&S) fuzzy model to perform the demand forecasting in a real-life microgrid located in Huatacondo, Chile. Based on real-data from the microgrid, located in northern Chile, the T&S fuzzy model was identified and compared with an adaptive neural network, showing the T&S fuzzy model better open-loop prediction capabilities. To increase the prediction capability, an analysis of the amount of historical data needed, and the frequency required for training purposes was also done. For the case study, it is suggested to use a large amount of data rather than increasing the training frequency.
Coupling BCI and cortical stimulation for brain-state-dependent stimulation: methods for spectral estimation in the presence of stimulation after-effects

Brain-state-dependent stimulation (BSDS) combines brain-computer interfaces (BCIs) and cortical stimulation into one paradigm that allows the online decoding for example of movement intention from brain signals while simultaneously applying stimulation. If the BCI decoding is performed by spectral features, stimulation after-effects such as artefacts and evoked activity present a challenge for a successful implementation of BSDS because they can impair the detection of targeted brain states. Therefore, efficient and robust methods are needed to minimize the influence of the stimulation-induced effects on spectral estimation without violating the real-time constraints of the BCI. In this work, we compared four methods for spectral estimation with autoregressive (AR) models in the presence of pulsed cortical stimulation. Using combined EEG-TMS (electroencephalography-transcranial magnetic stimulation) as well as combined electrocorticography (ECoG) and epidural electrical stimulation, three patients performed a motor task using a sensorimotor-rhythm BCI. Three stimulation paradigms were varied between sessions: (1) no stimulation, (2) single stimulation pulses applied independently (open-loop), or (3) coupled to the BCI output (closed-loop) such that stimulation was given only while an intention to move was detected using neural data. We found that removing the stimulation after-effects by linear interpolation can introduce a bias in the estimation of the spectral power of the sensorimotor rhythm, leading to an overestimation of decoding performance in the closed-loop setting. We propose the use of the Burg algorithm for segmented data to deal with stimulation after-effects. This work shows that the combination of BCIs controlled with spectral features and cortical stimulation in a closed-loop fashion is possible when the influence of stimulation after-effects on spectral estimation is minimized.