Miracle-dz/UniFAR-FTUs huggingface dataset:
All-optical 2R regeneration based on polarization rotation in a linear optical amplifier

All-optical 2R-regeneration based on polarization rotation in a single semiconductor linear optical amplifier is experimentally demonstrated. An extinction ratio (ER) improvement of 15 dB has been obtained for an input ER of 5 dB under static operation. With a degraded input signal, a receiver-sensitivity improvement of >3 dB at a bit error rate of 10/sup -9/ was found for 2.5 Gb/s. Regenerative capability for 10 Gb/s has also been verified.
A Scalable Flow-Sensitive Points-to Analysis

Points-to analysis for large object-oriented systems is currently too imprecise or too slow. This prevents or hampers many useful client analyses, refactorings, or optimizations. In this paper, we present an SSA-based approach to points-to analysis that simulates the actual execution of a program. It is precise since it is both locally and globally flow-sensitive, more precise by construction compared to other scalable approaches. We confirm this statement with experiments. The experiments also show that in practice our approach is also more efficient (on average) in spite of a higher worst-case time complexity.
A SHAPE DESCRIPTOR USING COMPLEX MOMENT INVARIANTS

This paper proposes a robust and effective shape feature, which is based on a set of orthogonal complex moments of images known as Zernike moments. Zernike moment phase is usually not used in image description since its sensitive to image rotations. However, phase captures important image information, which is revealed by our numerical analysis of image reconstruction. We therefore propose combining both the magnitude and phase coefficients to form a new shape descriptor, named as invariant ZM descriptor (IZMD). Its scale and translation invariance of IZMD are obtained by pre-normalizing the image using the geometrical moments. To make the phase invariant to rotation, we propose a method of phase correction. Experiment results show that IZMD is, in general, robust to changes such as rotation, translation and scaling. It also outperforms the commonly used magnitude-only Zernike moment descriptor in noise robustness and object discriminability. Keyword: Zernike moment, invariants, shape matching
Run-time classification of malicious processes using system call analysis

This study presents a malware classification system designed to classify malicious processes at run-time on production hosts. The system monitors process-level system call activity and uses information extracted from system call traces as inputs to the classifier. The system is advantageous because it does not require the use of specialized analysis environments. Instead, a `lightweight' service application monitors process execution and classifies new malware samples based on their behavioral similarity to known malware. This study compares the effectiveness of multiple feature sets, ground truth labeling schemes, and machine learning algorithms for malware classification. The accuracy of the classification system is evaluated against processlevel system call traces of recently discovered malware samples collected from production environments. Experimental results indicate that accurate classification results can be achieved using relatively short system call traces and simple representations.
Contradictory Reasoning Network: An EEG and fMRI Study

Contradiction is a cornerstone of human rationality, essential for everyday life and communication. We investigated electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) in separate recording sessions during contradictory judgments, using a logical structure based on categorical propositions of the Aristotelian Square of Opposition (ASoO). The use of ASoO propositions, while controlling for potential linguistic or semantic confounds, enabled us to observe the spatial temporal unfolding of this contradictory reasoning. The processing started with the inversion of the logical operators corresponding to right middle frontal gyrus (rMFG-BA11) activation, followed by identification of contradictory statement associated with in the right inferior frontal gyrus (rIFG-BA47) activation. Right medial frontal gyrus (rMeFG, BA10) and anterior cingulate cortex (ACC, BA32) contributed to the later stages of process. We observed a correlation between the delayed latency of rBA11 response and the reaction time delay during inductive vs. deductive reasoning. This supports the notion that rBA11 is crucial for manipulating the logical operators. Slower processing time and stronger brain responses for inductive logic suggested that examples are easier to process than general principles and are more likely to simplify communication.
The Emergence of Episodic Foresight and Its Consequences

Imagining future events and adjusting current behavior accordingly is a hallmark of human cognition. The development of such episodic foresight is attracting increasing research attention. In this article, I review a selection of recent work on the emergence of episodic foresight and its role in different domains, including learning, deliberate practice, affective forecasting, intertemporal choices, and anxiety. Studies suggest that during the preschool years, children begin to consider future scenarios, enabling them to plan, prepare, and shape their future, but many other consequences, such as the role of developing foresight in anticipating hazards, remain unexamined. The potential predictive effects of early individual differences in episodic foresight on later cognitive capacities and developmental outcomes deserve closer scrutiny.
Preference Semantics, III-Formedness, and Metaphor

This paper is about the relationships between Preference Semantics (PS) and ill-formedness, and between Preference Semantics and metaphor. Two types of "preference", declarative and procedural, are distinguished. The PS framework is examined with respect to notions of well- and ill-formedness, and two criteria for ill-formedness are distinguished, both of which are possessed by PS: an absolute criterion that corresponds to conventional notions of well- and ill-formedness, and a relative criterion that does not.Four possible strategies are described for representing ill-formed input in general, and metaphors in particular. The strategies and the semantic representations produced by them are compared regarding their correspondence to human understanding (admittedly superficial given the shallowness of the PS representation) and their ability to produce correct sentence translations. We conclude that, because of the ambiguity of many individual and extended metaphors, two broad types of metaphor representation strategy are needed. A control mechanism is described that uses both these major types of strategy and that permits the temporary semantic representation of metaphorical ambiguity.
Global trade will accelerate plant invasions in emerging economies under climate change

Trade plays a key role in the spread of alien species and has arguably contributed to the recent enormous acceleration of biological invasions, thus homogenizing biotas worldwide. Combining data on 60‐year trends of bilateral trade, as well as on biodiversity and climate, we modeled the global spread of plant species among 147 countries. The model results were compared with a recently compiled unique global data set on numbers of naturalized alien vascular plant species representing the most comprehensive collection of naturalized plant distributions currently available. The model identifies major source regions, introduction routes, and hot spots of plant invasions that agree well with observed naturalized plant numbers. In contrast to common knowledge, we show that the ‘imperialist dogma,’ stating that Europe has been a net exporter of naturalized plants since colonial times, does not hold for the past 60 years, when more naturalized plants were being imported to than exported from Europe. Our results highlight that the current distribution of naturalized plants is best predicted by socioeconomic activities 20 years ago. We took advantage of the observed time lag and used trade developments until recent times to predict naturalized plant trajectories for the next two decades. This shows that particularly strong increases in naturalized plant numbers are expected in the next 20 years for emerging economies in megadiverse regions. The interaction with predicted future climate change will increase invasions in northern temperate countries and reduce them in tropical and (sub)tropical regions, yet not by enough to cancel out the trade‐related increase.
Performance of Philips Audio Fingerprinting under Desynchronisation

An audio fingerprint is a compact representation (robust hash) of an audio signal which is linked to its perceptual content. Perceptually equivalent instances of the signal must lead to the same hash value. Fingerprinting finds application in efficient indexing of music databases. We present a theoretical analysis of the Philips audio fingerprinting method under desynchronisation for correlated stationary Gaussian sources.
Building Classifiers to Identify Split Files

We apply machine-learning techniques to help automate the process of mining the version history of software projects. Analysis of version histories is important in the study of software evolution. One of the associated problems is tracing program elements which have changed or moved as the result of file restructuring. As an initial application, we have developed classifiers to identify one such type of file change, ‘split files’. Our process involves extracting features through syntactic analysis of the original source code, and then training and evaluating classifiers against a set of data assessed by visual inspection. We analysed 266K files from 84 open-source projects, filtering out a set of candidate files for which our classifiers achieve either 89% overall accuracy, or a false positive rate of 5%.
Amplitude-Based Approach to Evidence Accumulation

We point out the need to use probability amplitudes rather than probabilities to model evidence accumulation in decision processes involving real physical sensors. Optical information processing systems are given as typical examples of systems that naturally gather evidence in this manner. We derive a new, amplitude-based generalization of the Hough transform technique used for object recognition in machine vision. We argue that one should use complex Hough accumulators and square their magnitudes to get a proper probabilistic interpretation of the likelihood that an object is present. Finally, we suggest that probability amplitudes may have natural applications in connectionist models, as well as in formulating knowledge-based reasoning problems.
Advanced modular self-inactivating lentiviral expression vectors for multigene interventions in mammalian cells and in vivo transduction.

In recent years, lentiviral expression systems have gained an unmatched reputation among the gene therapy community for their ability to deliver therapeutic transgenes into a wide variety of difficult-to-transfect/transduce target tissues (brain, hematopoietic system, liver, lung, retina) without eliciting significant humoral immune responses. We have cloned a construction kit-like self-inactivating lentiviral expression vector family which is compatible to state-of-the-art packaging and pseudotyping technologies and contains, besides essential cis-acting lentiviral sequences, (i) unparalleled polylinkers with up to 29 unique sites for restriction endonucleases, many of which recognize 8 bp motifs, (ii) strong promoters derived from the human cytomegalovirus immediate-early promoter (P(hCMV)) or the human elongation factor 1alpha (P(hEF1)(alpha)), (iii) P(hCMV-) or P(PGK-) (phosphoglycerate kinase promoter) driven G418 resistance markers or fluorescent protein-based expression tracers and (iv) tricistronic expression cassettes for coordinated expression of up to three transgenes. In addition, we have designed a size-optimized series of highly modular lentiviral expression vectors (pLenti Module) which contain, besides the extensive central polylinker, unique restriction sites flanking any of the 5'U3, R-U5-psi+-SD, cPPT-RRE-SA and 3'LTR(DeltaU3) modules or placed within the 5'U3 (-78 bp) and 3'LTR(DeltaU3) (8666 bp). pLentiModule enables straightforward cassette-type module swapping between lentiviral expression vector family members and facilitates the design of Tat-independent (replacement of 5'LTR by heterologous promoter elements), regulated and self-excisable proviruses (insertion of responsive operators or LoxP in the 3'LTR(DeltaU3) element). We have validated our lentiviral expression vectors by transduction of a variety of insect, chicken, murine and human cell lines as well as adult rat cardiomyocytes, rat hippocampal slices and chicken embryos. The novel multi-purpose construction kit-like vector series described here is compatible with itself as well as many other (non-viral) mammalian expression vectors for straightforward exchange of key components (e.g. promoters, LTRs, resistance genes) and will assist the gene therapy and tissue engineering communities in developing lentiviral expression vectors tailored for optimal treatment of prominent human diseases.
An Improved Method for Designing Prototype Filter for M-Band Pseudo QMF Banks

This paper presents an iterative algorithm for the design of multichannel cosine modulated pseudo quadrature mirror filter (QMF) banks. In this algorithm, passband frequency is optimized to satisfy new perfect reconstruction condition at frequency ( ). The proposed algorithm is simple, and has high design efficiency. The performance of this algorithm is evaluated in terms of computational time (CPU time), reconstruction error (RE), number of iterations (NOI), aliasing distortion (AD) and signal to noise ratio (SNR). Several design examples are included to illustrate the proposed algorithm and its improved performances over other exiting methods.
Effectiveness of a structured educational intervention using psychological delivery methods in children and adolescents with poorly controlled type 1 diabetes: a cluster-randomized controlled trial of the CASCADE intervention

Introduction Type 1 diabetes (T1D) in children and adolescents is increasing worldwide with a particular increase in children <5 years. Fewer than 1 in 6 children and adolescents achieve recommended glycated hemoglobin (HbA1c) values. Methods A pragmatic, cluster-randomized controlled trial assessed the efficacy of a clinic-based structured educational group incorporating psychological approaches to improve long-term glycemic control, quality of life and psychosocial functioning in children and adolescents with T1D. 28 pediatric diabetes services were randomized to deliver the intervention or standard care. 362 children (8–16 years) with HbA1c≥8.5% were recruited. Outcomes were HbA1c at 12 and 24 months, hypoglycemia, admissions, self-management skills, intervention compliance, emotional and behavioral adjustment, and quality of life. A process evaluation collected data from key stakeholder groups in order to evaluate the feasibility of delivering the intervention. Results 298/362 patients (82.3%) provided HbA1c at 12 months and 284/362 (78.5%) at 24 months. The intervention did not improve HbA1c at 12 months (intervention effect 0.11, 95% CI −0.28 to 0.50, p=0.584), or 24 months (intervention effect 0.03, 95% CI −0.36 to 0.41, p=0.891). There were no significant changes in remaining outcomes. 96/180 (53%) families in the intervention arm attended at least 1 module. The number of modules attended did not affect outcome. Reasons for low uptake included difficulties organizing groups and work and school commitments. Those with highest HbA1cs were less likely to attend. Mean cost of the intervention was £683 per child. Conclusions Significant challenges in the delivery of a structured education intervention using psychological techniques to enhance engagement and behavior change delivered by diabetes nurses and dietitians in routine clinical practice were found. The intervention did not improve HbA1c in children and adolescents with poor control. Trial registration number ISRCTN52537669, results.
Structural changes estimation for strongly dependent processes

In this paper, we consider the problem of estimating multiple structural breaks in a long-memory fractional autoregressive integrated moving-average time series. The number of break points as well as their locations, the orders and the parameters of each regime are assumed to be unknown. A selection criterion based on the minimum description length principle is proposed and a genetic algorithm is implemented for its optimization. Monte Carlo simulation results show the effectiveness of this criterion and an application to the Nile River data is considered.
Conductor thickness based dispersion models of slot-line in lossy media

The CAD oriented closed-form model is presented to compute frequency dependent effective relative permittivity and characteristic impedance of a slot-line with finite conductor thickness in the range 3 mum-50 mum. The model has average accuracy of about 2% against the fullwave results from different sources in the frequency range 2 GHz-60 GHz, 2.22lesepsivrles20, 0.02lesw/hles1.0, 0.01lesh/lambda0les0.25/radic(epsivr-1). The dielectric loss and conductor loss for slot lines have been computed and are found to be in excellent agreement with the practical and theoretical data available in the literature.
No-training, no-reference image quality index using perceptual features

Abstract. We propose a universal no-reference (NR) image quality assessment (QA) index that does not require training on human opinion scores. The new index utilizes perceptually relevant image features extracted from the distorted image. These include the mean phase congruency (PC) of the image, the entropy of the phase congruencyPC image, the entropy of the distorted image, and the mean gradient magnitude of the distorted image. Image quality prediction is accomplished by using a simple functional relationship of these features. The experimental results show that the new index accords closely with human subjective judgments of diverse distorted images.
Performance of RLS identification algorithms with forgetting factor : A Φ-mixing approach

In this paper, systems with unknown time-varying parameters and subject to stochastic disturbances are considered. The problem of tracking the parameters is tackled by resorting to a class of adaptive recursive least squares algorithms, equipped with variable forgetting factor. The basic assumption in the analysis is that the observation vector, the noise and the parameter drift are stochastic processes satisfying a {mixing condition. Furthermore, it is assumed that the observation vector satisses an excitation condition imposed on its minimum power. It is shown that the algorithm provides estimates with bounded error whenever the so-called \co-variance matrix" of the algorithm keeps bounded. Moreover, the size of such a matrix can be controlled by a suitable choice of the feasible range for the forgetting factor.
A Novel Generation Algorithm of Pair-Wise Testing Cases

Pair-wise testing is a practical and effective method which has already been used in the software testing. Extensive research has been made on the generation of pair-wise testing. In order to make it easy to analyze the current generation methods, we propose a method to ease the process. That is we transform the problem of pair-wise testing to a graphic one. The IPO algorithm is based on parameters and can ensure the optimization of test cases in each expansion. Though it has many advantages, it is still not sustainable enough because of its flexibility. We studied the three elements which affect its sustainability. The three elements are the horizontal growth of pair-wise testing, the combination of pair-wise testing cases and the extension sequence of the parameters to be extended. Thus we propose a HIPO algorithm based on IPO algorithm to solve those problems. The HIPO algorithm inherits the merits of high extension of IPO algorithm and introduces a new concept of contribution extent. It adopts the methods of preferential sequence as well as minimization algorithm to optimize the problems above. We develop the test case generation tool based on the HIPO algorithm by means of . Net technology. And we also prove its effectiveness in our experiment.
The 400 Square Degree ROSAT PSPC Galaxy Cluster Survey: Catalog and Statistical Calibration

We present a catalog of galaxy clusters detected in a new ROSAT PSPC survey. The survey is optimized to sample, at high redshifts, the mass range corresponding to T > 5 keV clusters at z = 0. Technically, our survey is the extension of the 160 square degree survey (160d). We use the same detection algorithm, thus preserving high quality of the resulting sample; the main difference is a significant increase in sky coverage. The new survey covers 397 deg2 and is based on 1610 high Galactic latitude ROSAT PSPC pointings, virtually all pointed ROSAT data suitable for the detection of distant clusters. The search volume for X-ray luminous clusters within z < 1 exceeds that of the entire local universe (z < 0.1). We detected 287 extended X-ray sources with fluxes f > 1.4 × 10-13 ergs s-1 cm-2 in the 0.5-2 keV energy band, of which 266 (93%) are optically confirmed as galaxy clusters, groups or individual elliptical galaxies. This paper provides a description of the input data, the statistical calibration of the survey via Monte Carlo simulations, and the catalog of detected clusters. We also compare the basic results to those from previous, smaller area surveys and find good agreement for the log N- log S distribution and the local X-ray luminosity function. Our sample clearly shows a decrease in the number density for the most luminous clusters at z > 0.3. The comparison of our ROSAT-derived fluxes with the accurate Chandra measurements for a subset of high-redshift clusters demonstrates the validity of the 400 square degree survey's statistical calibration.
Centroid-based Classification Enhanced with Wikipedia

Most of the traditional text classification methods employ Bag of Words (BOW) approaches relying on the words frequencies existing within the training corpus and the testing documents. Recently, studies have examined using external knowledge to enrich the text representation of documents. Some have focused on using WordNet which suffers from different limitations including the available number of words, synsets and coverage. Other studies used different aspects of Wikipedia instead. Depending on the features being selected and evaluated and the external knowledge being used, a balance between recall, precision, noise reduction and information loss has to be applied. In this paper, we propose a new Centroid-based classification approach relying on Wikipedia to enrich the representation of documents through the use of Wikpedia’s concepts, categories structure, links, and articles text. We extract candidate concepts for each class with the help of Wikipedia and merge them with important features derived directly from the text documents. Different variations of the system were evaluated and the results show improvements in the performance of the system.