Miracle-dz/UniFAR-FTUs huggingface dataset:
Photopic and scotopic spatiotemporal tuning of adult zebrafish vision

Sensitivity to spatial and temporal patterns is a fundamental aspect of vision. Herein, we investigated this sensitivity in adult zebrafish for a wide range of spatial (0.014 to 0.511 cycles/degree [c/d]) and temporal frequencies (0.025 to 6 cycles/s) to better understand their visual system. Measurements were performed at photopic (1.8 log cd m(-2)) and scotopic (-4.5 log cd m(-2)) light levels to assess the optokinetic response (OKR). The resulting spatiotemporal contrast sensitivity (CS) functions revealed that the OKR of zebrafish is tuned to spatial frequency and speed but not to temporal frequencies. Thereby, optimal test parameters for CS measurements were identified. At photopic light levels, a spatial frequency of 0.116 ± 0.01 c/d (mean ± SD) and a grating speed of 8.42 ± 2.15 degrees/second (d/s) was ideal; at scotopic light levels, these values were 0.110 ± 0.02 c/d and 5.45 ± 1.31 d/s, respectively. This study allows to better characterize zebrafish mutants with altered vision and to distinguish between defects of rod and cone photoreceptors as measurements were performed under different light conditions.
The Application of Speech Recognition in Radiology Information System

The Radiology report is the fundamental means by which radiologists communicate with clinicians and patients. The traditional method of generating reports is time consuming and expensive. Recent advances in computer hardware and software technology have improved Speech Recognition systems used for radiology reporting. In this paper, we design a continuous Mandarin Speech Recognition dictation system for radiology reporting in Radiology Information System based on the CMU Sphinx recognition engine. We compare our system with IBM ViaVoice pro v9.1. The experiment results show that both systems can achieve a high accuracy rate when using recognition for Brain Skull CT report generation in the laboratory environment. Furthermore, our system performs slightly better than ViaVoice when training and testing data are both randomly selected from the same text corpora. We conclude that it is technically feasible to employ Speech Recognition for report generating in Radiology Information System. In summary, the Speech Recognition technology has matured to the point where it is now viable as a mean of providing more timely delivery and better quality of medical services to patients, and this technology will be widely applied in the healthcare industry in the near future.
Integrating logical and physical file models in the MPI-IO implementation for "Clusterfile"

This paper presents the design and implementation of the MPI-IO interface for the Clusterfile parallel file system. The approach offers the opportunity of achieving a high correlation between the file access patterns of parallel applications and the physical file distribution. First, any physical file distribution can be expressed by means of MPI data types. Second, mechanisms such as views and collective I/O operations are portably implemented inside the file system, unifying the I/O scheduling strategies of the MPI-IO library and the file system. The experimental section demonstrates performance benefits of more than one order of magnitude.
Improved speech understanding using dialogue expectation in sentence parsing

In dialogue systems, speech recognition errors force the user to repeat information resulting in more turns, lower dialogue efficiency and maybe complete failure. Higher level information such as history, expectation, discourse knowledge and pragmatics can improve performance but are hard to quantify and effectively include in the recognition process. In this paper, dialogue expectation is used to improve recognition. By permitting the dialogue manager to guide the interaction it is possible to track the dialogue state and thus estimate the expected semantic content of the user’s response. The parser is allowed to process a large number of sentences provided by the decoder. Expectation is used as an effective criterion for selecting among competing hypotheses. This approach was tested with a simple flight reservation task and results show improvement in concept recognition without adding significant computation.
A Workflow Frequent Pattern Mining Algorithm

To improve workflow for adapting to the uncertainty of business environments, workflow frequent patterns are used. First, the frequent pattern discovery problem is defined, and a frequent pattern-mining algorithm based on Apriori algorithm is proposed. Frequent patterns can quantify the strength of logical relations between activities and trend forecast and crucial business decision-making can be supported by frequent patterns in key activities.
Technical system interface design: An analysis on human cognitive model

Dilemma in understanding how user react towards systems and how systems can be more usable for user is a great concern among researchers in computer science. Thus, this study is aiming to come out with a cognitive design checklist by analyzing existing design principles, human cognitive models and situation awareness model. Secondly is to discover the most dominant cognitive design elements and to identify whether these cognitive design elements has been applied in the current system design. Least dominant design elements also has been discussed as to make sure that cognitive design elements should be integrated into system design in order to increase the ease of use of a particular system. For that, the cognitive design checklist will be used in order to evaluate five technical systems design via online. Three experts involved in this study and most of the experts have more than five years experiences in computer science and engineering field.
Parallel Virtual Memory for Time Shared Environments

This paper analyses the issues involved in providing virtual distributed shared memory for time-shared parallel machines. We study the performance of two different page management policies, namely, static and dynamic page allocation under two widely accepted scheduling policies: Gang scheduling and independent processor scheduling. The performance of each page management policy is studied under different replacement scopes (local versus global replacement). Results obtained after extensive simulations show that dynamic page allocation performs better throughout all the environments simulated. We also observe a better performance of independent processor over gang scheduling as well as a similar performance between local and global replacement scope.
Characterizing P300 Speller Performance: The Effects of Stimulus Timing Features and Search for a Physiological Biomarker

Copyright Information: All rights reserved unless otherwise indicated. Contact the author or original publisher for any necessary permissions. eScholarship is not the copyright owner for deposited works. Learn more at This thesis presents two studies that focus on improving P300 speller system efficiency by examining fundamental stimulus timing parameters and the possibility of a physiological biomarker to identify user performance. By analyzing four distinct stimulus presentation features, the first study reports that both stimulus-off time and interstimulus interval can significantly affect both accuracy and characters per minute. Optimization of stimulus timing parameters should not only consider accuracy rates, but also bit rates (i.e. characters per minute), considering that reductions in accuracy may be more than offset than the time saved resulting in overall improvements in system efficiency. Subsets of the entire group were compared to show iii consistency of performance trends despite great variance among subjects. The next study explored the possibility of an EEG biomarker that distinguished performer differences. Multiple extensive analyses showed no strong correlation between power in the EEG signal and user performance in spelling the temporally associated letter or word. iv The thesis of Jessica Lu is approved. Figure 1. Average classification accuracy for all subjects grouped by (A) stimulus timing pattern, (B) ISI*, (C) ISI, (D) flash duration, and (E) ratio of flash duration to ISI. SEM error bars are included in (A). Figure 3. Average characters per minute for all subjects grouped by (A) stimulus timing pattern, (B) flash duration, (C) ISI*, (D) ISI, and (E) ratio of flash duration to ISI. SEM error bars are included for the largest CPM point of each average trend line. Figure 5. Average group waveforms at Pz for each stimulus timing pattern. Waveforms for targets are represented by the solid black line and waveforms for non-targets are represented by Figure 6. Average classification accuracy (AD) and CPM (E-H) under the 32-channel set (represented by the solid black line) compared to the 8-channel set (represented by the dashed black line) for each of the four patterns. Figure 8a and b. Sections highlighted in gray indicate the time in the EEG signal used to vii Figure 9. Power spectral density estimate in channel Cz of the top three performers (solid black) compared to the bottom three performers (dotted black). The low gamma (30-70Hz) frequency Figure 10. Gamma power in electrode Cz along the x-axis is plotted against a measurement …
Localization for Mobile Robots using Panoramic Vision, Local Features and Particle Filter

In this paper we present a vision-based approach to self-localization that uses a novel scheme to integrate feature-based matching of panoramic images with Monte Carlo localization. A specially modified version of Lowe’s SIFT algorithm is used to match features extracted from local interest points in the image, rather than using global features calculated from the whole image. Experiments conducted in a large, populated indoor environment (up to 5 persons visible) over a period of several months demonstrate the robustness of the approach, including kidnapping and occlusion of up to 90% of the robot’s field of view.
Two New Beggiatoa Species Inhabiting Marine Mangrove Sediments in the Caribbean

Beggiatoaceae, giant sulphur-oxidizing bacteria, are well known to occur in cold and temperate waters, as well as hydrothermal vents, where they form dense mats on the floor. However, they have never been described in tropical marine mangroves. Here, we describe two new species of benthic Beggiatoaceae colonizing a marine mangrove adjacent to mangrove roots. We combined phylogenetic and lipid analysis with electron microscopy in order to describe these organisms. Furthermore, oxygen and sulphide measurements in and ex situ were performed in a mesocosm to characterize their environment. Based on this, two new species, Candidatus Maribeggiatoa sp. and Candidatus Isobeggiatoa sp. inhabiting tropical marine mangroves in Guadeloupe were identified. The species identified as Candidatus Maribeggiatoa group suggests that this genus could harbour a third cluster with organisms ranging from 60 to 120 μm in diameter. This is also the first description of an Isobeggiatoa species outside of Arctic and temperate waters. The multiphasic approach also gives information about the environment and indications for the metabolism of these bacteria. Our study shows the widespread occurrence of members of Beggiatoaceae family and provides new insight in their potential role in shallow-water marine sulphide-rich environments such as mangroves.
Reduced space optimal analysis for historical data sets: 136 years of Atlantic sea surface temperatures

A computationally efficient method for analyzing meteorological and oceanographic historical data sets has been developed. The method combines data reduction and least squares optimal estimation. The data reduction involves computing empirical orthogonal functions (EOFs) of the data based on their recent, high-quality portion and using a leading EOF subset as a basis for the analyzed solution and for fitting a first-order linear model of time transitions. We then formulate optimal estimation problems in terms of the EOF projection of the analyzed field to obtain reduced space analogues of the optimal smoother, the Kalman filter, and optimal interpolation techniques. All reduced space algorithms are far cheaper computationally than their full grid prototypes, while their solutions are not necessarily inferior since the sparsity and error in available data often make estimation of small-scale features meaningless. Where covariance patterns can be estimated from the available data, the analysis methods fill gaps, correct sampling errors, and produce spatially and temporally coherent analyzed data sets. As with classical least squares estimation, the reduced space versions also provide theoretical error estimates for analyzed values. The methods are demonstrated on Atlantic monthly sea surface temperature (SST) anomalies for 1856–1991 from the United Kingdom Meteorological Office historical sea surface temperature data set (version MOHSST5). Choice of a reduced space dimension of 30 is shown to be adequate. The analyses are tested by withholding a significant part of the data and prove to be robust and in agreement with their own error estimates; they are also consistent with a partially independent optimal interpolation (OI) analysis by Reynolds and Smith [1994] produced in the National Centers for Environmental Prediction (NCEP)(known as the NCEP OI analysis). A simple statistical model is used to depict the month-to-month SST evolution in the optimal smoother algorithm. Results are somewhat superior to both the Kalman filter, which relies less on the model, and the optimal interpolation, which does not use it at all. The method generalizes a few recent works on using a reduced space for data set analyses. Difficulties of methods which simply fit EOF patterns to observed data are pointed out, and the more complete analysis procedures developed here are suggested as a remedy.
Using Continuous Real Functions to Model Timed Histories

Continuous real functions are an important tool in describing the evolution of physical processes through time. Using the theory of topology, this notion of continuity may be generalised to arbitrary data types. This paper demonstrates that (topological) continuity can be a useful tool in describing the evolution of digital processes through time. Several examples are given of the use of continuous functions in modelling and specifying system behaviour. A digital circuit is verified to demonstrate the utility of proof techniques from real analysis.
Les modèles HJM et LMM revisités

In this paper, we study the following models : Heath-Jarrow-Morton (1992) and Libor-Market- Model, also known as Brace-Gatarek-Musiela model (1997). We survey the extensions of these models and their representation in the Black and Scholes world. Our approach is pedagogical and is based on an exhaustive elaboration of the developments of these models. Finally, we discuss the evolution of these models towards the pricing of more complex structured derivatives, like TARN and we also briefly analyse more advanced versions like the SV Cheyette model.
Evaluating template-based and template-free protein-protein complex structure prediction

We compared the performance of template-free (docking) and template-based methods for the prediction of protein-protein complex structures. We found similar performance for a template-based method based on threading (COTH) and another template-based method based on structural alignment (PRISM). The template-based methods showed similar performance to a docking method (ZDOCK) when the latter was allowed one prediction for each complex, but when the same number of predictions was allowed for each method, the docking approach outperformed template-based approaches. We identified strengths and weaknesses in each method. Template-based approaches were better able to handle complexes that involved conformational changes upon binding. Furthermore, the threading-based and docking methods were better than the structural-alignment-based method for enzyme-inhibitor complex prediction. Finally, we show that the near-native (correct) predictions were generally not shared by the various approaches, suggesting that integrating their results could be the superior strategy.
SimpleNLG-IT: adapting SimpleNLG to Italian

This paper describes the SimpleNLG-IT re-aliser, i.e. the main features of the porting of the SimpleNLG API system (Gatt and Reiter, 2009) to Italian. The paper gives some details about the grammar and the lexicon employed by the system and reports some results about a ﬁrst evaluation based on a dependency tree-bank for Italian. A comparison is developed with the previous projects developed for this task for English and French, which is based on the morpho-syntactical differences and similarities between Italian and these languages.
Multiscale distilled sensing: A source detection method for infrared and radio astronomical images

Astronomical images are characterized by having a high component of noise, a non-homogeneous background, and a great number of sources (objects) difficult to identify even by experts. All these factors are especially remarkable in high wavelength images such as infrared and radio. Hence, great efforts have been done to solve the automatic detection of sources in this type of images. In this paper, we propose a new approach based on multiscale decomposition and the recently developed Distilled Sensing method. Their combined use allows the minimization of the complex background effects as well as the highlighting of the sources. The experimental results obtained using public infrared and radio images demonstrate the validity of the approach, detecting a greater number of true sources than the original Distilled Sensing and the well-known SExtractor algorithm.
Achievable Rate of Rician Large-Scale MIMO Channels With Transceiver Hardware Impairments

Transceiver hardware impairments (e.g., phase noise, in-phase/quadrature-phase imbalance, amplifier nonlinearities, and quantization errors) have obvious degradation effects on the performance of wireless communications. While prior works have improved our knowledge of the influence of hardware impairments of single-user multiple-input multiple-output (MIMO) systems over Rayleigh fading channels, an analysis encompassing the Rician fading channel is not yet available. In this paper, we pursue a detailed analysis of regular and large-scale (LS) MIMO systems over Rician fading channels by deriving new closed-form expressions for the achievable rate to provide several important insights for practical system design. More specifically, for regular MIMO systems with hardware impairments, there is always a finite achievable rate ceiling, which is irrespective of the transmit power and fading conditions. For LS-MIMO systems, it is interesting to find that the achievable rate loss depends on the Rician K- factor, which reveals that the favorable propagation in LS-MIMO systems can remove the influence of hardware impairments. However, we show that the nonideal LS-MIMO system can still achieve high spectral efficiency due to its huge degrees of freedom.
HARMONIC-TEMPORAL-STRUCTURED CLUSTERING VIA DETERMINISTIC ANNEALING EM ALGORITHM FOR AUDIO FEATURE EXTRACTION

This paper proposes “harmonic-temporal structured clustering (HTC) method”, that allows simultaneous estimation of pitch, intensity, onset, duration, etc., of each underlying source in multi-stream audio signal, which we expect to be an effective feature extraction for MIR systems. STC decomposes the energy patterns diffused in timefrequency space, i.e., a time series of power spectrum, into distinct clusters such that each of them is originated from a single sound stream. It becomes clear that the problem is equivalent to geometrically approximating the observed time series of power spectrum by superimposed harmonictemporal structured models (HTMs), whose parameters are directly associated with the specific acoustic characteristics. The update equations in DA(Deterministic Annealing)EM algorithm for the optimal parameter convergence are derived by formulating the model with Gaussian kernel representation. The experiment showed promising results, and verified the potential of the proposed method.
Measuring the perceived quality of VoIP under various wireless network conditions

This paper focuses on the performance of VoIP calls under various situations, namely, during a handover, under different background traffic conditions (normal and heavy traffic load/saturation conditions) at a wireless access point, and in the presence of interference. Using empirical-based measurements, we demonstrate that various network conditions exhibit distinct statistical behaviour in terms of SNR, packet losses and end-toend delays, and thus, impact the VoIP user quality in a different manner. A novel part of this work is the comparative analysis of these conditions with respect to network and user experience benchmarks. It also proposes a Markov-chain based model for the auto-rate fallback (ARF) algorithm of the IEEE802.11 and derives analytically the packet losses and mean delays at the application layer under the presence of constant interference and a single traffic CBR source at the WLAN. The paper shows that only very low SNR values affect the user experience of a VoIP call, since the ARF algorithm conceals the packet losses at the MAC layer and only the losses at the most robust (and lowest bit-rate) modulation scheme at the MAC layer become noticeable at the application layer. Furthermore, it demonstrates situations in which common “rule-of-thumb” metrics cannot reflect the perceived user experience and finer cross-layer data are required for identifying the network conditions and performing an effective adaptation.
Soundness and Completeness versus Lifting Property 1

We give new formulations of the property of soundness and completeness of a resolution system and of the lifting lemma, and we discuss their relationship. The discussion points out why certain resolution systems are not complete, and that there is a simple method for showing that a resolution system is \absolutely incomplete" { that there is no notion of program completion and no logic which could give soundness and completeness. The method is demonstrated on the case of basic variants of the SLDNF-resolution. The same approach can be used to analyze other resolution systems.
Aging, obesity, and post-therapy cognitive recovery in breast cancer survivors

Therapy-induced cognitive impairment is prevalent and long-lasting in cancer survivors, but factors affecting post-therapy cognitive recovery are unclear. We conducted this study to evaluate the associations of age, body mass index (BMI), waist-to-hip ratio (WHR), and physical activity (PA) with post-therapy cognitive changes in a population-based breast cancer (BC) survivor cohort. We collected information on PA, weight, height, waist and hip circumferences of 1286 BC survivors aged 20-75. We assessed their cognitive functions, including immediate memory, delayed memory, verbal fluency, and attention, at 18 and 36 months after cancer diagnosis. Linear regression models were used to examine the associations of age, BMI, WHR and PA with mean changes in cognitive scores from 18- to 36-month follow-up interview. We found that the post-therapy cognitive changes differed by age and obesity status. Verbal fluency and attention improved in younger patients aged <60 and non-abdominally obese patients, but deteriorated in older patients aged =60 (i.e. verbal fluency and attention) and abdominally obese patients (i.e. verbal fluency). Memory improved in all patients, with a smaller improvement in obese patients compared with normal-weight patients. No significant association was found between PA and post-therapy cognitive change. Due to the novelty of our findings and the limitations of our study, further research, including intervention trials, is warranted to confirm the causal relationship between obesity and cognitive impairments.