Miracle-dz/UniFAR-FTUs huggingface dataset:
Correction to “Aerosol optical properties and their radiative effects in northern China”

[1] As a fast developing country covering a large territory, China is experiencing rapid environmental changes. High concentrations of aerosols with diverse properties are emitted in the region, providing a unique opportunity for understanding the impact of environmental changes on climate. Until very recently, few observational studies were conducted in the source regions. The East Asian Study of Tropospheric Aerosols: An International Regional Experiment (EAST-AIRE) attempts to characterize the physical, optical and chemical properties of the aerosols and their effects on climate over China. This study presents some preliminary results using continuous high-quality measurements of aerosol, cloud and radiative quantities made at the first EAST-AIRE baseline station at Xianghe, about 70 km east of Beijing over a period of one year (September 2004 to September 2005). It was found that the region is often covered by a thick layer of haze (with a yearly mean aerosol optical depth equal to 0.82 at 500 nm and maximum greater than 4) due primarily to anthropogenic emissions. An abrupt ‘‘cleanup’’ of the haze often took place in a matter of one day or less because of the passage of cold fronts. The mean single scattering albedo is approximately 0.9 but has strong day-to-day variations with maximum monthly averages occurring during the summer. Large aerosol loading and strong absorption lead to a very large aerosol radiative effect at the surface (the annual 24-hour mean values equals 24 W m ), but a much smaller aerosol radiative effect at the top of the atmosphere (one tenth of the surface value). The boundary atmosphere is thus heated dramatically during the daytime, which may affect atmospheric stability and cloud formation. In comparison, the cloud radiative effect at the surface is only moderately higher ( 41 W m ) than the aerosol radiative effect at the surface.
NOISE REDUCTION USING mel-SCALE SPECTRAL SUBTRACTION WITH PERCEPTUALLY DEFINED SUBTRACTION PARAMETERS-A NEW SCHEME

The noise signal does not affect uniformly the speech signal over the whole spectrum isn the case of colored noise. In order to deal with speech improvement in such situations a new spectral subtraction algorithm is proposed for reducing colored noise from noise corrupted speech. The spectrum is divided into frequency sub-bands based on a nonlinear multiband bark scale. For each sub-band, the noise corrupted speech power in past and present time frames is compared to statistics of the noise power to improve the determination of the presence or absence of speech. During the subtraction process, a larger proportion of noise is removed from sub-bands that do not contain speech. For sub-bands that contain speech, a function is developed which allows for the removal of less noise during relatively low amplitude speech and more noise during relatively high amplitude speech . Further the performance of the spectral subtraction is improved by formulating process without neglecting the cross correlation between the speech signal and background noise. Residual noise can be masked by exploiting the masking properties of the human auditory system. In the proposed method subtraction parameters are adaptively adjusted using noise masking threshold. A psychoacoustically motivated weighting filter was included to eliminate residual musical noise. Experimental results show that the algorithm removes more colored noise without removing the relatively low amplitude speech at the beginning and ending of words.
Reconfiguration based failure restoration in wavelength-routed WDM networks

Wavelength-division multiplexed (WDM) optical networks using wavelength routing are considered to be a potential candidate for next-generation wide-area backbone networks. The key component in such networks is the light-path network (LPN) manager. The functions of the LPN manager include setting up the logical topology, sustaining the network by monitoring traffic and network parameters, and handling node and/or link failures. Failure handling in WDM networks is of prime importance due to the nature and volume of traffic these network carry. Failure detection is usually achieved by exchanging control messages among nodes with timeout mechanisms. Failure restoration can be done either by re-routing only the failed light paths (LPs) or by reconfiguring all the existing LPs in the network. The reconfiguration approach involves finding new LPs in the faulty network (LP design) and realizing these new LPs by selectivity removing the old LPs (LP realization) with the objective of minimizing the service disruption to the ongoing calls. Existing work on the reconfiguration approach considers only LP design and ignores LP realization. In this paper, we first propose an architecture for the LPN manager highlighting the importance of LP realization in reconfiguration-based failure restoration, then we propose performance measures and heuristic algorithms for LP realization. We evaluate the effectiveness of the LP realization algorithms through simulation studies.
Polyglot Speech Synthesis Based on Cross-Lingual Frame Selection Using Auditory and Articulatory Features

In this paper, an approach for polyglot speech synthesis based on cross-lingual frame selection is proposed. This method requires only mono-lingual speech data of different speakers in different languages for building a polyglot synthesis system, thus reducing the burden of data collection. Essentially, a set of artificial utterances in the second language for a target speaker is constructed based on the proposed cross-lingual frame-selection process, and this data set is used to adapt a synthesis model in the second language to the speaker. In the cross-lingual frame-selection process, we propose to use auditory and articulatory features to improve the quality of the synthesized polyglot speech. For evaluation, a Mandarin-English polyglot system is implemented where the target speaker only speaks Mandarin. The results show that decent performance regarding voice identity and speech quality can be achieved with the proposed method.
OWLS : Observational Wireless Life-enhancing System

In personalized care, there is an increasing necessity to allow people with physical limitations or disabilities to continue independent quotidian activities and functions. Socially assistive robotics technologies for individuals, who have been affected by age-related disabilities and similar types of disorders, have become popular options for facilitating natural independence and uninterrupted mobility. Among its diverse applications, therapeutic robotic systems have been utilized in the muscular physiotherapies for movement training, wrist and arm treatment for injuries and overexertions, and other therapies. Applications of wearable sensors for human assistance or health monitoring have been also gaining popularity in recent years. Wireless wearable sensor systems enable proactive personal health management and the ubiquitous monitoring of vital signs to keep an active watch on immediate health conditions. In this paper, we develop a system, called OWLS, where multiple wearable sensors, software agents, robots and health analysis technology, have been integrated into a single personal therapy solution (SPTS). In this system, each robot has the “smart” intelligence to analyze and process its own unique data, as well as the collected sensor data, and is able to aggregate the information received from the other system robots. Our system uses a reinforcement learning algorithm to make decisions about the user’s current health conditions, and to take appropriate actions, as necessary (i.e, contacting outside parties). Our experimental results have shown that the reinforcement learning algorithm developed with our system allows the robots to accurately detect immediate signs for the correct determination of the health conditions in monitored users. We posit that the approach of non-invasive monitoring, when combined with an alert system, will make this a desirable SPTS in future health care.
Outage performance and diversity gain analysis of free-space optical multi-hop parallel relaying

In this paper, we investigate the outage performance of free-space optical mesh networks, which build upon the combination of serial (multi-hop) and parallel relaying. We assume log-normal atmospheric turbulence channels and derive outage probability expressions for the multi-hop parallel relaying scheme under consideration. Our outage probability analysis demonstrates substantial performance improvements with respect to both standalone serial and parallel relaying schemes. Furthermore, we present a diversity gain analysis and quantify the achievable diversity order in terms of the number of relays and the turbulence channel parameters.
Highly Flexible Software for Gaze Path Analysis and Visualization

The growing interest in using eye-movements for human-computer interaction has also increased the need for tools to investigate and analyze the behavior of human eyes. Nowadays, there are many commercial and academic products available for researchers in this field and the quality and accuracy of eye-tracking devices are constantly increasing. Despite the numerous methods developed for analyzing and visualizing gaze paths, however, no universal tools are available yet to accomplish this. To fill in this gap, we developed iComponent – a software product with a highly flexible architecture for easy development of interchangeable plug-in modules to support various eye-tracking devices and experimental software. iComponent has four types of 2D visualizations of gaze data and one type of 1D visualization. The 2D visualizations are superimposed on the stimulus seen by the user during a session. Three of the visualizations are capable of showing several subjects’ gaze paths simultaneously. Ill. 15, bibl. 5 (in English; summaries in English, Russian and Lithuanian).
Anti-phencyclidine monoclonal antibodies provide long-term reductions in brain phencyclidine concentrations during chronic phencyclidine administration in rats.

These studies examined the hypothesis that a single large dose of monoclonal anti-phencyclidine (PCP) antibody could provide long-term reductions in brain PCP concentrations despite continuous PCP administration. PCP (18 mg/kg/day, s.c.) was infused to steady-state (24 h) and then a mole-equivalent dose of a short-acting anti-PCP antigen-binding fragment (Fab) or a long-acting anti-PCP IgG was administered i.v. The PCP infusion continued for up to 27 days, even though the binding capacity of the single dose of antibody used should have been saturated within the first day. At selected time points after antibody administration, brain, testis, and serum PCP concentrations were measured. Serum PCP concentrations rapidly increased approximately 100- and 300-fold after Fab or IgG administration, respectively. Based on the antibody-bound PCP concentrations in serum, the functional elimination half-life (t(1/2lambdaZ)) values for PCP-Fab and PCP-IgG complexes were 9.4 h and 15.4 days, respectively. Fab and IgG administration produced a complete removal of PCP from the brain within 15 min. Although brain PCP concentrations were significantly decreased for only 4 h in Fab-treated animals, IgG administration resulted in significant decreases in brain PCP concentrations lasting for at least 27 days. In contrast, testis PCP concentrations were not substantially affected by antibody administration, suggesting that redistribution of PCP from the testis is too slow to benefit from a limited dose of antibody. These results indicate that anti-PCP IgG can preferentially protect the brain for approximately 4 weeks after IgG administration, even when the antibody binding capacity should have been saturated with continuously administered PCP.
An embedding approach for the design of state‐feedback tracking controllers for references with jumps

We study the problem of designing state‐feedback controllers to track time‐varying state trajectories that may exhibit jumps. Both plants and controllers considered are modeled as hybrid dynamical systems, which are systems with both continuous and discrete dynamics, given in terms of a flow set, a flow map, a jump set, and a jump map. Using recently developed tools for the study of stability in hybrid systems, we recast the tracking problem as the task of asymptotically stabilizing a set, the tracking set, and derive conditions for the design of state‐feedback tracking controllers with the property that the jump times of the plant coincide with those of the given reference trajectories. The resulting tracking controllers guarantee that solutions of the plant starting close to the reference trajectory stay close to it and that the difference between each solution of the controlled plant and the reference trajectory converges to zero asymptotically. Constructive conditions for tracking control design in terms of LMIs are proposed for a class of hybrid systems with linear maps and input‐triggered jumps. The results are illustrated by various examples. Copyright © 2013 John Wiley & Sons, Ltd.
MOVING OBJECT DETECTION AND TRACKING IN VIDEO

Object tracking means to track an object over a sequence of images. Video tracking is to associate target objects in consecutive video frames. Object detection in videos involves verifying the presence of an object in image sequences and possibly locating it precisely for recognition object tracking is to monitor and objects spatial and temporal changes during a video sequence, including its presence, position, size, shape, etc.
Semantics and Logics of Computation: Categories in Concurrency

These notes survey a range of models for parallel computatio n, including interleaving models like transition systems, synchron isation trees and languages (often called Hoare traces in this context), and m o els like asynchronous transition systems, event structures, pomsets an d Mazurkiewicz traces where concurrency is represented more explicitly by a form of causal independence. The presentation is unified by casting the mod ls in a categorytheoretic framework. One aim is to use category theory to pro vide abstract characterisations of constructions like parallel composi ti n valid throughout a range of different models and to provide formal means for tr anslating between different models. The framework helps in extending th e useful concept of bisimulation equivalence from its familiar situation on transition systems, to independence models where without a careful analysis eve n the appropriate definition of bisimulation is not clear-cut. 1
Using Network Component Analysis to Dissect Regulatory Networks Mediated by Transcription Factors in Yeast

Understanding the relationship between genetic variation and gene expression is a central question in genetics. With the availability of data from high-throughput technologies such as ChIP-Chip, expression, and genotyping arrays, we can begin to not only identify associations but to understand how genetic variations perturb the underlying transcription regulatory networks to induce differential gene expression. In this study, we describe a simple model of transcription regulation where the expression of a gene is completely characterized by two properties: the concentrations and promoter affinities of active transcription factors. We devise a method that extends Network Component Analysis (NCA) to determine how genetic variations in the form of single nucleotide polymorphisms (SNPs) perturb these two properties. Applying our method to a segregating population of Saccharomyces cerevisiae, we found statistically significant examples of trans-acting SNPs located in regulatory hotspots that perturb transcription factor concentrations and affinities for target promoters to cause global differential expression and cis-acting genetic variations that perturb the promoter affinities of transcription factors on a single gene to cause local differential expression. Although many genetic variations linked to gene expressions have been identified, it is not clear how they perturb the underlying regulatory networks that govern gene expression. Our work begins to fill this void by showing that many genetic variations affect the concentrations of active transcription factors in a cell and their affinities for target promoters. Understanding the effects of these perturbations can help us to paint a more complete picture of the complex landscape of transcription regulation. The software package implementing the algorithms discussed in this work is available as a MATLAB package upon request.
Development of a cost-effective metabarcoding strategy for analysis of the marine phytoplankton community

We developed a cost-effective metabarcoding strategy to analyze phytoplankton community structure using the Illumina MiSeq system. The amplicons (404–411 bp) obtained by end-pairing of two reads were sufficiently long to distinguish algal species and provided barcode data equivalent to those generated with the Roche 454 system, but at less than 1/20th of the cost. The original universal primer sequences targeting the 23S rDNA region and the PCR strategy were both modified, and this resulted in higher numbers of eukaryotic algal sequences by excluding non-photosynthetic proteobacterial sequences supporting effectiveness of this strategy. The novel strategy was used to analyze the phytoplankton community structure of six water samples from the East/Japan Sea: surface and 50 m depths at coastal and open-sea sites, with collections in May and July 2014. In total, 345 operational taxonomic units (OTUs) were identified, which covered most of the prokaryotic and eukaryotic algal phyla, including Dinophyta, Rhodophyta, Ochrophyta, Chlorophyta, Streptophyta, Cryptophyta, Haptophyta, and Cyanophyta. This highlights the importance of plastid 23S primers, which perform better than the currently used 16S primers for phytoplankton community surveys. The findings also revealed that more efforts should be made to update 23S rDNA sequences as well as those of 16S in the databases. Analysis of algal proportions in the six samples showed that community structure differed depending on location, depth and season. Across the six samples evaluated, the numbers of OTUs in each phylum were similar but their relative proportions varied. This novel strategy would allow laboratories to analyze large numbers of samples at reasonable expense, whereas this has not been possible to date due to cost and time. In addition, we expect that this strategy will generate a large amount of novel data that could potentially change established methods and tools that are currently used in the realms of oceanography and marine ecology.
Multi-Criteria Analysis in Ecotourism: Using Goal Programming to Explore Sustainable Solutions

The paper examines issues pertinent to the strategic planning and management of ecotourism. The use of Multi-Criteria Analysis in ecotourism is an innovative application of an existing methodology that has been traditionally employed in environmental planning and project appraisal to address conflicting stakeholder objectives over scarce natural resources. Using data from a case study of community-managed ecotourism in Ecuador, the paper demonstrates how this methodology can be usefully applied to integrate qualitative and quantitative research, consider stakeholder preferences in the decision-making process and provide policy information helpful in conceptualising the interplay of social and environmental objectives of sustainable tourism. In this way the methodology can help improve the participatory community management and planning of ecotourism as a livelihood economic activity.
Computing Stability Derivatives and Their Gradients for Aerodynamic Shape Optimization

Aerodynamic shape optimization of aircraft configurations often ignores stability considerations. To address this, a method for the computation of static, dynamic, and transient aircraft stability derivatives and their sensitivities for use in gradient-based optimization is introduced and evaluated. Computational fluid dynamics in the form of a three-dimensional structured-grid multiblock flow solver with both Euler and Reynolds-averaged Navier–Stokes equations is used. To compute the stability derivatives, a time-spectral formulation is used to compute an oscillating solution for the configuration of interest. From this oscillating solution, a series of linear regressions is performed to calculate the various stability derivatives. Because the solution is time dependent, it contains the information required to compute the transient, or “dot,” derivatives for the configuration. An adjoint method is used to compute the gradients of the stability derivatives of interest, enabling gradient-based stability-co.
Enhanced Matrix Completion with Manifold Learning

We study the problem of matrix completion when infor- mation about row or column proximities is available, in the form of weighted graphs. The problem can be formulated as the optimization of a convex function that can be solved efficiently using the alternating direction multipliers method. Experiments show that our model offers better reconstruction than the standard method that only uses a low rank assumption, especially when few observations are available.
MEVO : Multi-Environment Visual Odometry

The ego motion estimation from an image sequence, commonly known as visual odometry, has been thoroughly studied in recent years. Different solutions have been developed depending on the particular scenario the system interacts in. In highly textured environments point features are abundant and visual odometry approaches focus on complementary steps, such as sparse bundle adjustment or keyframe techniques, to improve the accuracy of the motion estimation. In textureless scenarios, the absence of point features motiva tes the use of different image features. Lines have proven to be an interesting alternative to points in man-made environments, but very few visual odometry approaches have been developed using these types of features. Moreover, the combination of point and line features has not been considered in the development of real-time visual odometry algorithms. In this paper, we explore the combination of point and line features to robustly compute the six degree of freedom motion transformation between consecutive stereo frames. Additionally, we deal with the problem of line stereo matching, since our approach is based on 3D-2D correspondences to estimate motion. We develop an efficient algorithm to compute the stereo line matching, even in situations where one of the endpoints describing the line segment in the left image is not visible in the right image. Several experiments with synthetic and real image sequences show that a simple but effective combination of point and line features improves the motion estimate compared to approaches using only one type of these features with a slight increase in computational cost.