Miracle-dz/UniFAR-FTUs huggingface dataset:
Speech Comprehension in Children and Adolescents After Sequential Bilateral Cochlear Implantation With Long Interimplant Interval

Objective Identify likely predictors for the outcome after contralateral cochlear implantation with a long interimplant delay. Study Design Retrospective case reviews. Setting Outpatient cochlear implant (CI) center. Patients Seventy-three children and adolescents who underwent sequential bilateral cochlear implantation with an interval between both implantations of 5 years or longer. The mean age of the patients at the first and second cochlear implantations was 2.72 ± 1.52 and 11.57 ± 2.9 years, respectively. The mean duration of experience with both implants was 4.01 ± 1.57 years. Intervention Rehabilitative. Main Outcome Measures All 73 patients underwent periodic speech perception testing in quiet and noise. The most recent unilateral data for each side were statistically analyzed. The speech test results were evaluated by the age at first implantation, the interval between both implantations, the duration of hearing aid use in the second side, and the duration of the bilateral CI use. Results A statistically significant difference for speech test results was obtained between the early-implanted ears and the late-implanted ears for all children. These results were dependent on the interimplant interval. All age groups demonstrated significant differences (p > 0.05) for the second side between the speech test results and the interval between both cochlear implantations. In addition, statistically significant differences influenced by the duration of hearing aid use were found for speech test results for the second side. Experience was also a factor for the second CI, yielding significantly higher speech test scores with longer use. Conclusion The development of hearing abilities in a second-implanted side depends on the interimplant interval, the hearing aid use, and the duration of the second CI use.
Synthesis of Cyclic Motions with Texture

Motion capture data is useful to an animator because it captures the exact style of a particular individual’s movements and has a life-like quality. However, often the data is not exactly what the animator needs. We demonstrate a method for using motion capture data as a starting point for creating synthetic motion data that addresses this problem by allowing the animator to specify hard constraints such as where the feet should contact the floor. The method captures the style of the motion as well as the life-like quality. It begins with an analysis phase, in which the data is divided into features such as frequency bands and correlations among joint angles, and represented with multidimensional kernel-based probability distributions. These distributions are then sampled in a synthesis phase, and optimized to yield the final animation.
Dietary fat, fat subtypes and hepatocellular carcinoma in a large European cohort

The role of amount and type of dietary fat consumption in the etiology of hepatocellular carcinoma (HCC) is poorly understood, despite suggestive biological plausibility. The associations of total fat, fat subtypes and fat sources with HCC incidence were investigated in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, which includes 191 incident HCC cases diagnosed between 1992 and 2010. Diet was assessed by country‐specific, validated dietary questionnaires. A single 24‐hr diet recall from a cohort subsample was used for measurement error calibration. Hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated from Cox proportional hazard models. Hepatitis B and C viruses (HBV/HCV) status and biomarkers of liver function were assessed separately in a nested case–control subset with available blood samples (HCC = 122). In multivariable calibrated models, there was a statistically significant inverse association between total fat intake and risk of HCC (per 10 g/day, HR = 0.80, 95% CI: 0.65–0.99), which was mainly driven by monounsaturated fats (per 5 g/day, HR = 0.71, 95% CI: 0.55–0.92) rather than polyunsaturated fats (per 5 g/day, HR = 0.92, 95% CI: 0.68–1.25). There was no association between saturated fats (HR = 1.08, 95% CI: 0.88–1.34) and HCC risk. The ratio of polyunsaturated/monounsaturated fats to saturated fats was not significantly associated with HCC risk (per 0.2 point, HR = 0.86, 95% CI: 0.73–1.01). Restriction of analyses to HBV/HCV free participants or adjustment for liver function did not substantially alter the findings. In this large prospective European cohort, higher consumption of monounsaturated fats is associated with lower HCC risk.
Effectiveness of SRTM and ALOS-PALSAR data for identifying morphostructural lineaments in northeastern Brazil

This work provides a comparison between ALOS Advanced Land Observing Satellite PALSAR Phased Array type L-band Synthetic Aperture Radar and DEM Digital Elevation Model SRTM Shuttle Radar Topography Mission data aiming to evaluate their efficiency to detect morphostructural lineaments. An area in Northeastern Brazil was selected to perform this investigation because of its unambiguous evidence of tectonic fault activity from the Precambrian to the Quaternary. DEM enhanced by shading schemes and palettes was integrated with images representative of morphometric variables as aspect and horizontal curvature in order to enable the recognition of linear features. Images derived from HIS transformation and arithmetic operations of fine beam dual HH+HV polarization PALSAR images were processed to provide RGB compositions. Comparisons among lineament maps based on these two remote-sensing products attest to the highest efficacy of SRTM data in detecting geologically meaningful lineaments in the study area. These indicate a main E–W trend and secondary, NE–SW and NW–SE trends, which conform to dominant directions of tectonic fault zones previously mapped in northeastern Brazil. Geomorphological and geological field investigations carried out in the course of the current research further contributed to showing the best performance of this product for unravelling details of three expressive tectonic structures in the study area. This study shows that lineament attenuation in PALSAR images augments proportionally with increased land use. Other important interferences that either rule out or significantly attenuate linear structures are imposed by natural characteristics of the L-band PALSAR sensor, including layover and high-look azimuth in equatorial latitude. The latter might have particularly attenuated detection of lineaments parallel to illumination azimuth. Taking into account these interferences in PALSAR images, integration of DEM-SRTM data used herein offers a much more robust tool to help carry out morphostructural studies in terrains displaying characteristics similar to the ones in the study area.
Flow cytometry evaluation of red blood cells mimicking naturally occurring ABO subgroups after modification with variable amounts of function‐spacer‐lipid A and B constructs

BACKGROUND: Kodecytes bearing synthetic blood group A and B antigens are increasingly being used in transfusion laboratories as serologic mimics of red blood cell (RBC) Aweak and Bweak subtypes. The aim of this study was to compare the flow cytometry profile of kodecytes with native ABO subgroups.
Did Executive Compensation Encourage Extreme Risk-taking in Financial Institutions ?

The effect of executive compensation on extreme risk is frequently cited as a leading candidate for the financial crisis. The evidence for or against is scarce. This paper assembles panel data on 117 financial firms from 1995 through 2008, using the financial crisis as a type of ‘stress test’ experiment to determine the relation of equity-based incentives on the probability of default. After estimating default probabilities using a Heston-Nandi specification, we apply a dynamic panel model to estimate statistically the effect of compensation on default risk. The results indicate uniformly that equity-based pay (i.e. restricted stock and options) increases the probability of default, while non-equity pay (i.e. cash bonuses) decreases it.
A Preventive Traffic Adaptation Model for Wireless Mesh Networks Using Fuzzy Logic

Nowadays, real time traffic over wireless networks is increasing sharply. In addition, network scale is larger due to new facilities as offered by wireless mesh networks. However, the differences between (1) the infrastructure capacities, (2) the end users devices technologies, (3) the number of users, and (4) the number of real time applications are implying the need of more dynamic quality of service (QoS) models. Traditional QoS models are not always suitable to fill out the gap between the four cited points. We are mentioning more QoS degradation due to network congestion. Therefore, in this paper, we propose a novel, dynamic and persistent traffic adaption model, called FTAM. Its main role is to avoid as maximum as possible network congestion. FTAM is based on the fuzzy logic, which is known by its dynamicity and efficiency in uncertain environment. By monitoring the nodes queues evolution, FTAM estimates network congestion and makes the suitable traffic adaptation step. Extensive simulations have proved the efficiency of FTAM in terms of real time traffic QoS guarantee and preventive congestion control.
BEACH INUNDATION PREDICTION DURING STORMS USING DIFFERENT WAVE HEIGHTS AS INPUTS

Beach inundation prediction is evaluated at an artificial, tideless embayed beach located in the city of Barcelona (NW Mediterranean, Spain). To this end, inundation measurements using video observations are compared with estimations including the tidal variations and the wave runup formulation of Stockdon et al. (2006), introducing deep water, local wave measurements and local wave computations as inputs. As the observations consider the mean runup and the estimations use the 2% runup exceedance (R2%), the inundation is overestimated if any of the wave heights in the formulation are used. Nonetheless, results are improved if a local wave height at 10 m depth is used, in particular for waves approaching the shore obliquely. Finally, it is stated that the differences between the observations and the estimations vary along the beach, being higher in the curved zone of the embayment.
Research into automatic recognition of joints in human symmetrical movements

High speed photography is a major means of collecting data from human body movement. It enables the automatic identification of joints, which brings great significance to the research, treatment and recovery of injuries, the analysis to the diagnosis of sport techniques and the ergonomics. According to the features that when the adjacent joints of human body are in planetary motion, their distance remains the same, and according to the human body joint movement laws (such as the territory of the articular anatomy and the kinematic features), a new approach is introduced to process the image thresholding of joints filmed by the high speed camera, to automatically identify the joints and to automatically trace the joint points (by labeling markers at the joints). Based upon the closure of marking points, automatic identification can be achieved through thresholding treatment. Due to the screening frequency and the laws of human segment movement, when the marking points have been initialized, their automatic tracking can be achieved with the progressive sequential images.Then the testing results, the data from three-dimensional force platform and the characteristics that human body segment will only rotate around the closer ending segment when the segment has no boding force and only valid to the conservative force all tell that after being analyzed kinematically, the approach is approved to be valid.
Ieee Transactions on Wireless Communications, Accepted for Publication the Impact of Transmit Rate Control on Energy-efficient Estimation in Wireless Sensor Networks

—We study the impact of physical layer (PHY) transmit rate control on energy efficient estimation in wireless sensor networks. A sensor network collects measurements about an unknown evolving process. Each sensor controls its sampling rate and its PHY transmit rate to the next hop or to the Fusion Center (FC). The FC performs estimation of the unknown process based on sensor measurements and needs to adhere to an estimation accuracy constraint. The objective is to maximize sensor network lifetime. The tradeoff is that, high PHY transmit rates consume more energy per transmitted bit, but they increase the amount of transmitted sensor measurement data per unit time, and thus they aid in improving estimation quality and in satisfying the estimation error constraint. First, we study a single-hop network where sensors transmit directly to the FC. In this case, sensor sampling rates are directly mapped onto PHY transmit rates. We identify fundamental structural properties of the optimal solution, and we propose a distributed, iterative sensor PHY rate adaptation algorithm for reaching a solution, based on lightweight feedback from the FC. Next, we consider the multi-hop version of the problem, where the sensor measurement (sampling) rates, PHY transmit rates and data flows to the FC are controlled. We extend the distributed optimization framework above to include all controllable parameters, and we devise an iterative algorithm for maximizing network lifetime.
Draft Genome Sequence of a Pseudomonas aeruginosa NA04 Bacterium Isolated from an Entomopathogenic Nematode

ABSTRACT We report the draft genome sequence of Gram-negative bacterium Pseudomonas aeruginosa NA04, isolated from the entomopathogenic nematode Heterorhabditis indica MOR03. The draft genome consists of 54 contigs, a length of 6.37 Mb, and a G+C content 66.49%.
A distributed approximation scheme for sleep sceduling in sensor networks

We investigate the theoretical feasibility of near-optimal, distributed sleep scheduling in energy- constrained sensor networks with pairwise sensor redundancy. In this setting, an optimal sleep schedule is equivalent to an optimal fractional domatic partition of the associated redundancy graph. We present a set of realistic assumptions on the structure of the communication and redundancy relations; for the family of networks meeting these assumptions, we develop an efficient distributed approximation scheme for sleep scheduling. For any e > 0, we demonstrate that it is possible to schedule the sensing activities of the nodes in a local and distributed manner so that the ratio of the optimum lifetime to the achieved lifetime of the network is at most 1+ isin. The computational effort (time, memory and communication) required at each node depends on e and the parameters of the network family, but given so-called anchor nodes (a set of nodes meeting certain density constraints) and locally unique node identifiers, the effort is independent of the actual network at hand; in particular, the required effort at each node remains constant as the size of the network is scaled up.
A Multilingual Dependency Analysis System Using Online Passive-Aggressive Learning

This paper presents an online algorithm for dependency parsing problems. We propose an adaptation of the passive and aggressive online learning algorithm to the dependency parsing domain. We evaluate the proposed algorithms on the 2007 CONLL Shared Task, and report errors analysis. Experimental results show that the system score is better than the average score among the participating systems.
Progress Toward Automation of Salmon Escapement Counts

The number of adult salmon that escape predators and fishing to successfully return to their natal streams to spawn, known as escapement counts, are vital to ensure sustainability of the salmon fisheries. Sufficient numbers of salmon must reach the spawning grounds each year to ensure the long term viability of the various species. Once a critical threshold is reached, the fishery is opened to commercial exploitation. To ensure the viability of salmon in Alaska, the Alaska Department of Fish and Game conducts escapement counts using a variety of techniques. One well established technique is to use remote video stations to record salmon passing upstream and periodically use human operators to view the video sequences to determine the escapement counts. This paper presents the initial stages of the development of a technique to automate the escapement counts and thereby relieve the demand for human operators. The technique uses a global segmentation and image morphology operations followed by a Kalman filter to identify and track the candidate salmon as they pass through the region of interest on the video recording. Candidates that complete the journey across the region of interest are counted. Finally, some of the future challenges posed by real time processing, water surface turbulence and lighting changes are discussed.
Stomatal Closure during Leaf Dehydration, Correlation with Other Leaf Physiological Traits1

The question as to what triggers stomatal closure during leaf desiccation remains controversial. This paper examines characteristics of the vascular and photosynthetic functions of the leaf to determine which responds most similarly to stomata during desiccation. Leaf hydraulic conductance (Kleaf) was measured from the relaxation kinetics of leaf water potential (Ψl), and a novel application of this technique allowed the response of Kleaf to Ψl to be determined. These “vulnerability curves” show that Kleaf is highly sensitive to Ψl and that the response of stomatal conductance to Ψl is closely correlated with the response of Kleaf to Ψl. The turgor loss point of leaves was also correlated with Kleaf and stomatal closure, whereas the decline in PSII quantum yield during leaf drying occurred at a lower Ψl than stomatal closure. These results indicate that stomatal closure is primarily coordinated with Kleaf. However, the close proximity of Ψl at initial stomatal closure and initial loss of Kleaf suggest that partial loss of Kleaf might occur regularly, presumably necessitating repair of embolisms.
Orthogonal least squares learning algorithm for radial basis function networks

The radial basis function network offers a viable alternative to the two-layer neural network in many applications of signal processing. A common learning algorithm for radial basis function networks is based on first choosing randomly some data points as radial basis function centers and then using singular-value decomposition to solve for the weights of the network. Such a procedure has several drawbacks, and, in particular, an arbitrary selection of centers is clearly unsatisfactory. The authors propose an alternative learning procedure based on the orthogonal least-squares method. The procedure chooses radial basis function centers one by one in a rational way until an adequate network has been constructed. In the algorithm, each selected center maximizes the increment to the explained variance or energy of the desired output and does not suffer numerical ill-conditioning problems. The orthogonal least-squares learning strategy provides a simple and efficient means for fitting radial basis function networks. This is illustrated using examples taken from two different signal processing applications.
A general datalog-based framework for tractable query answering over ontologies

In this paper, we introduce a family of expressive extensions of Datalog, called Datalog+/-, as a new paradigm for query answering over ontologies. The Datalog+/- family admits existentially quantified variables in rule heads, and has suitable restrictions to ensure highly efficient ontology querying. We show in particular that Datalog+/- generalizes the DL-Lite family of tractable description logics, which are the most common tractable ontology languages in the context of the Semantic Web and databases. We also show how stratified negation can be added to Datalog+/- while keeping ontology querying tractable. Furthermore, the Datalog+/- family is of interest in its own right and can, moreover, be used in various contexts such as data integration and data exchange.
Applicability of RF-based methods for emotion recognition: A survey

Human emotion recognition has attracted a lot of research in recent years. However, conventional methods for sensing human emotions are either expensive or privacy intrusive. In this paper, we explore a connection between emotion recognition and RF-based activity recognition that can lead to a novel ubiquitous emotion sensing technology. We discuss the latest literature from both domains, highlight the potential of body movements for accurate emotion detection and focus on how emotion recognition could be done using inexpensive, less privacy intrusive, device-free RF sensing methods. Applications include environment and crowd behaviour tracking in real time, assisted living, health monitoring, or also domestic appliance control. As a result of this survey, we propose RF-based device free recognition for emotion detection based on body movements. However, it requires overcoming challenges, such as accuracy, to outperform classical methods.
Marine core evidence for reduced deep water production during Termination II followed by a relatively stable substage 5e (Eemian)

We present oxygen and carbon isotope records of benthic foraminifera from the glacial stage 6 through interglacial substage 5e (Eemian) sections of several cores from the subpolar North Atlantic. The cores range in water depth from 1451 to 2658 m. In one core, we generated estimates of sea surface temperature (SST) and of ice-rafted detritus (IRD) delivery for all of stage 5. We reconstruct bathymeric profiles of δ13C for stage 6, Termination II, and three time slices of substage 5e. The δ13C profiles indicate that local deep water geometry during stage 6 was similar to that of the last glaciation, with glacial North Atlantic Intermediate Water (GNAIW) overlying deeper waters partially of southern origin. An anomalously large peak in IRD, coupled with planktonic δ18O evidence for iceberg melting immediately precedes Termination II and is otherwise similar to stage 2 and 3 Heinrich events. During the termination, low δ13C values are observed in cores near and above 2 km, providing evidence of reduced GNAIW production in association with deglacial melting. In the shallowest cores, low δ13C values persist into early substage 5e, indicating that the southward retreat of southern-source waters was not completed until well after the beginning of the substage. In contrast to Termination I, SSTs remained cold until the end of the deglaciation; this may be why there is little evidence from marine and terrestrial sequences for a pronounced climate reversal on Termination II despite what is now clear evidence of a significant reduction in ocean ventilation. The faunal data suggest that SSTs during early 5e were about 7°C warmer than during the glaciation. SST rose several degrees from early to middle substage 5e, peaked in middle substage 5e at about 10°C above glacial values, and then gradually declined by about 5°C. These changes were linked to variations in water mass configuration, as interpreted from benthic δ13C evidence. Most of the evidence suggests that oscillations superimposed on the gradual SST trend were 1°–2°C, in contrast to the larger SST changes (3°–4°C) documented for substage 5d.