Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectrum matching analysis of chaotic binary modulation excitation sequence for sonar systems

Sonar system has a bell-shaped magnitude spectrum. The spectrum matching degree of excitation sequence with that of sonar system is important to increase echo energy, which is related closely with the measurement range. Binary excitation sequences modulated using chaotic series, including chaotic binary amplitude shift keying, chaotic binary frequency shift keying and chaotic binary phase shift keying, are proposed in this paper. The spectrum matching degree of the proposed excitation sequences with that of sonar system is analyzed. Sonar experiments applying SensComp 600 series instrument-grade electrostatic sensors excited with chaotic binary modulation sequences validate the analytical results.
Diagnostic Challenges of Tuberculous Lymphadenitis Using Polymerase Chain Reaction Analysis: A Case Study

This report presents a case of tuberculous lymphadenitis that was difficult to diagnose using polymerase chain reaction analysis. An 80-year-old Japanese female was hospitalized due to swollen cervical lymph nodes. Her lymph node tests revealed paradoxical polymerase chain reaction results. Polymerase chain reaction analysis of two biopsy tissues using the Cobas TaqMan revealed a positive result for Mycobacterium avium and a negative result for Mycobacterium tuberculosis. However, polymerase chain reaction analysis of a cultured colony of acid-fast bacteria from biopsy tissue using the Cobas TaqMan and an alternative polymerase chain reaction analysis of biopsy tissue yielded discordant results. The patient was diagnosed as having tuberculous lymphadenitis. She was treated with antitubercular drugs and subsequently had a reduction in cervical lymph node swelling. Polymerase chain reaction analysis is not 100% accurate; hence, its use as a diagnostic tool for mycobacterial infection requires increased attention.
Regulatory mechanism of photosynthesis that depends on the activation state of Rubisco under sink limitation.

Knowledge of regulatory mechanism of plant photosynthesis under sink-limitation occurring under various environmental conditions is still insufficient. In the present study, two different degrees of sink-limitation were imposed on soybean plants by removing either half or all developing pods and after that, photosynthetic rate and various other characteristics were investigated in fully expanded source leaves of the depodded and control plants. It was found that a larger degree of pod removal (sink-limitation) resulted in lower leaf photosynthetic rate, stomatal conductance and activation ratio (a percentage of initial activity to total activity) of Rubisco and higher leaf sucrose and starch contents without decreasing leaf intercellular CO2 concentration and affecting leaf water, chlorophyll, total protein and Rubisco protein contents. In addition, there were agreements between activation ratios of Rubisco and photosynthetic rates of the depodded plants relative to controls. These results showed a regulatory mechanism (a down regulation mechanism) of leaf photosynthetic rate in soybean, which depends on the activation state (a decrease in activation ratio) of Rubisco rather than leaf Rubisco content or leaf intercellular CO2 concentration under sink-limitation.
Cochlear implant combined with a linear frequency transposing hearing aid.

BACKGROUND Adults with cochlear implants (CIs) are usually implanted unilaterally. To preserve binaural advantages, a noninvasive method involves maintaining the hearing aid (HA) on the contralateral ear; the choice of HA for this purpose is therefore crucial. In recent years, the use of frequency transposition has gained a renewed interest in clinical practice. This type of processing records information from the high-frequency region and conveys it to a low-frequency region where there is still some residual hearing. PURPOSE To conduct an investigation and examine whether adults with unilateral CI derive benefits from a HA utilizing linear frequency transposition (LFT) on the contralateral ear. RESEARCH DESIGN A two-period, single-blind, repeated-measures crossover design was conducted to examine the combination of LFT in conjunction with a CI. Speech recognition tests were performed in quiet and in noise with LFT either activated or deactivated. The Speech, Spatial and Qualities of Hearing Questionnaire (SSQ) was used to measure subjective benefit. STUDY SAMPLE The participants were nine frequent bimodal users, five males and four females, with a moderate to profound high-frequency sensorineural hearing loss in the nonimplanted ear. INTERVENTION The current study was conducted using the Widex Mind440 power (m4-19) behind-the-ear HA. The participants acted as their own control in a total of seven conditions: (1) bimodal with own HA, (2) CI only, (3) own HA alone, (4) bimodal new HA LFT-off, (5) new HA LFT-off, (6) bimodal new HA LFT-on, and (7) new HA LFT-on. DATA COLLECTION AND ANALYSIS Monosyllabic words in quiet and the Swedish version of Hearing in Noise Test (HINT) were used as speech test materials. Stimuli were presented in sound field at a speech level of 65 dB sound pressure level (SPL) via a loudspeaker at a distance of 1 m from the participant in a sound-treated room. The SSQ was administered in each session evaluating the three bimodal conditions. SPSS software was used for statistical analyses. General linear model (GLM) analysis of variance for repeated measures was performed and followed with Bonferroni-adjusted post hoc pairwise comparisons. RESULTS Participants performed better with CI only than with HA alone, and the bimodal conditions were superior to the CI alone. No significant differences (p > .05) were observed when comparing the LFT-on with LFT-off regardless of whether the use of CI was included in the different listening conditions in objective and subjective measurements. CONCLUSIONS The results suggest an advantage for CI patients with a HA in the opposite ear, and that the LFT neither degraded nor enhanced speech performance in conjunction with a CI in quiet or in noise in comparison to when it was deactivated.
Empirical Study on Impact of Logistics Operations Capability on Supply Chain Performance

Operations, flexibility and distribution factors in logistics capabilities are examined, and service quality is selected as an intermediate variable in measuring supply chain performance. Based on this, a series of hypotheses are proposed and measurement models are established. A questionnaire survey of nearly 1000 industrial arms in Mainland China is administered, and analysis of the responses adopting structure equation modeling (SEM) leads to the conclusion that operations capability is the key factor in supply chain performance. Analysis of the empirical study also indicates that operations capability has significant impacts on distribution capability, flexibility capability, and service quality, as well as indirect impact on financial performance via service quality.
Temperature-aware dynamic frequency and voltage scaling for reliability and yield enhancement

A novel oscillation-based on-chip thermal sensing architecture for dynamically adjusting supply voltage and clock frequency in System-on-Chip (SoC) is proposed. It is shown that the oscillation frequency of a ring oscillator reduces linearly as the temperature rises, and thus provides a good on-chip temperature sensing mechanism. An efficient Dynamic Frequency-to-Voltage Scaling (DF2VS) algorithm is proposed to dynamically adjust supply voltage according to the oscillation frequencies of the ring oscillators distributed in SoC so that thermal sensing can be carried at all potential hot spots. An on-chip Dynamic Voltage Scaling or Dynamic Voltage and Frequency Scaling (DVS or DVFS) monitor selects the supply voltage level and clock frequency according to the outputs of all thermal sensors. Experimental results on SoC benchmark circuits show the effectiveness of the algorithm that a 10% reduction in supply voltage alone can achieve about 20% power reduction (DVS scheme), and nearly 50% reduction in power is achievable if the clock frequency is also scaled down (DVFS scheme). The chip temperature is reduced accordingly.
The Strongly-Interacting Light Higgs

We develop a simple description of models where electroweak symmetry breaking is triggered by a light composite Higgs, which emerges from a strongly-interacting sector as a pseudo-Goldstone boson. Two parameters broadly characterize these models: mρ, the mass scale of the new resonances and gρ, their coupling. An effective low-energy Lagrangian approach proves to be useful for LHC and ILC phenomenology below the scale mρ. We identify two classes of operators: those that are genuinely sensitive to the new strong force and those that are sensitive to the spectrum of the resonances only. Phenomenological prospects for the LHC and the ILC include the study of high-energy longitudinal vector boson scattering, strong double-Higgs production and anomalous Higgs couplings. We finally discuss the possibility that the top quark could also be a composite object of the strong sector.
Online Bayesian Passive-Aggressive Learning

Online Passive-Aggressive (PA) learning is an effective framework for performing max-margin online learning. But the deterministic formulation and estimated single large-margin model could limit its capability in discovering descriptive structures underlying complex data. This paper presents online Bayesian Passive-Aggressive (BayesPA) learning, which subsumes the online PA and extends naturally to incorporate latent variables and perform nonparametric Bayesian inference, thus providing great flexibility for explorative analysis. We apply BayesPA to topic modeling and derive efficient online learning algorithms for max-margin topic models. We further develop nonparametric methods to resolve the number of topics. Experimental results show that our approaches significantly improve time efficiency while maintaining comparable results with the batch counterparts.
The Matrix Protein Hikaru genki Localizes to Cholinergic Synaptic Clefts and Regulates Postsynaptic Organization in the Drosophila Brain

The synaptic cleft, a crucial space involved in neurotransmission, is filled with extracellular matrix that serves as a scaffold for synaptic differentiation. However, little is known about the proteins present in the matrix and their functions in synaptogenesis, especially in the CNS. Here, we report that Hikaru genki (Hig), a secreted protein with an Ig motif and complement control protein domains, localizes specifically to the synaptic clefts of cholinergic synapses in the Drosophila CNS. The data indicate that this specific localization is achieved by capture of secreted Hig in synaptic clefts, even when it is ectopically expressed in glia. In the absence of Hig, the cytoskeletal scaffold protein DLG accumulated abnormally in cholinergic postsynapses, and the synaptic distribution of acetylcholine receptor (AchR) subunits Dα6 and Dα7 significantly decreased. hig mutant flies consistently exhibited resistance to the AchR agonist spinosad, which causes lethality by specifically activating the Dα6 subunit, suggesting that loss of Hig compromises the cholinergic synaptic activity mediated by Dα6. These results indicate that Hig is a specific component of the synaptic cleft matrix of cholinergic synapses and regulates their postsynaptic organization in the CNS.
Performance analysis of the MVDR channel estimator for space-frequency block coded MC-CDMA systems

Minimum variance distortionless response (MVDR)-type blind channel estimation algorithms for the downlink of space-frequency block coded multi-carrier code division multiple access (SFBC-MC-CDMA) schemes are developed and analyzed. The performance of the channel estimator under sufficiently large data record size and small noise assumptions is studied by deriving analytical expressions for the bias and the variance of the estimator. Analysis of the mean-squared error (MSE) of the proposed estimator shows that at sufficiently high SNRs the squared norm of the bias can be considered negligible compared to the variance of the estimator. Furthermore, we establish a bound on the MSE of the biased estimates which is specifically derived for downlink transmissions where the knowledge of only the spreading code of the desired user is available. Finally, simulation examples illustrate the performance of the MVDR channel estimator and the accuracy of our analytical results
Deleterious oral habits in children with hearing impairment

Background and aims Deleterious oral habits represent a serious public health issue. The information available about this problem in children with hearing impairment is insufficient. The purpose of this study was to investigate the prevalence of deleterious oral habits among children with hearing impairment and comparing results against children without hearing impairment. Method This epidemiological study was carried out in a sample size of 315 children. We used a random sampling technique that included 150 children with hearing impairment and 165 without hearing impairment. All subjects were submitted to a clinical examination. The parents/legal guardians were asked to complete a questionnaire regarding the deleterious habits of their children. Results The data collected indicated a higher prevalence of deleterious oral habits among children with hearing impairment: 53.3% as opposed to 40.6% among children without hearing impairment. There was a higher incidence of malocclusion in children with hearing impairment (79.3%) compared to children without hearing impairment (57%). Conclusions This study highlighted the need to establish protocols for preventive orthodontic treatment at an early age, in order to reduce the deleterious oral habits and prevent malocclusion. Dental institutions/clinicians need to implement oral care programs including proper oral education aiming to promote oral health.
Can Multiscale-Multiphysics Methods Predict Softening Damage and Structural Failure?

The multi scale approach was pioneered by Tadmor, Ortiz and Phillips [1] for atomistic-based quasi-continuum analysis of dislocations and hardening plasticity of polycrystalline metals. In that case, the structural failure is due to necking, which is caused by nonlinear geometric effects of finite strain, or to sharp fracture, which is modelled separately (see also [2]). There can be no dispute that the multi scale approach is realistic, delivering to the continuum macroscale an essential information on the physical behavior on the subscale. However, applying the multi scale approach to failure due to interacting crack systems, or to softening damage such as distributed cracking, is an entirely different matter. To clarify it, let us discuss a few typical multi-scale approaches representative of a flood of recent publications.
Unmixing-based multisensor multiresolution image fusion

Constrained and unconstrained algorithms of the multisensor multiresolution technique (MMT) are discussed. They can be applied to unmix low-resolution images using the information about their pixel composition from co-registered high-resolution images. This makes it possible to fuse the low- and high-resolution images for a synergetic interpretation. The constrained unmixing preserves all the available radiometric information of the low-resolution image. On the other hand, the unconstrained unmixing may be preferable in case of noisy data. An analysis of the MMT sensitivity to sensor errors showed that the strongest requirement is the accuracy of geometric co-registration of the data; the co-registration errors should not exceed 0.1-0.2 of the low-resolution pixel size. Applications of the constrained and unconstrained algorithms are illustrated on examples of unmixing and fusion of the multiresolution reflective and thermal bands of a real TM/LANDSAT image as well as of a simulated image of the future ASTER/EOS-AMI sensor.
Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm

In this paper, we propose a new AQM algorithm that considers both the average queue length and the estimated packet arrival rate together in order to detect incipient congestion. The proposed algorithm predicts the average queue length and controls it to maintain a certain reference value to achieve high link utilization and low queueing delay. It also has low complexity and easy configuration. Simulation results validate the performance of the proposed algorithm under various environments and show its advantage over other existing AQM algorithms.
Acoustic analysis toolkit for biomedical speech signal processing : concepts and algorithms

Epidemiological studies suggest that lifetime prevalence of voice disorders is about 30% for the general adult population. Moreover, vocal performance degradation may be amongst the earliest indicators of a neurodegenerative disease onset, such as Parkinson’s disease. Lacking alternative cost-effective biomarkers, biomedical speech signal processing has been gaining increasing impetus towards developing clinical decision support tools. Acoustic analysis of speech signals provides a convenient, automatic, accurate, robust, inexpensive, scalable approach assisting medical diagnosis and symptom severity monitoring. Nevertheless, the algorithmic tools developed for biomedical speech signal processing are spread across different software platforms, hindering direct algorithmic comparisons and the further development of this impending field. This study brings many biomedical speech signal processing algorithms together under the same software platform, and has led to the development of a practical free toolkit which can be accessed over the Internet using a simple application.
Symbiosis Between Tall Fescue and a Fungal Shoot Endophyte Affects Soil Microbial Communities

The symbiosis between tall fescue (Festuca arundinaceum) and a shoot-specific fungal endophyte (Neotyphodium coenophialum) has been relatively well studied but little attention has been given to how this relationship may impact the soil microbial community. Understanding how the symbiosis may structure soil microbial communities is important for understanding the cascade of effects that this symbiosis can have on belowground ecosystems. We used high-throughput DNA sequencing of selected microbial genes (the 16S rRNA gene and fungal ITS rRNA region) to examine bacterial and fungal microbial communities in the soil, respectively, to address the following questions: (1) How do the microbial communities differ between rhizosphere and bulk soil in a tall fescue grassland? (2) How are belowground microbial communities affected by the presence of various strains of endophyte N. coenophialum? We found that rhizosphere and bulk soils harbored distinct microbial communities, with rhizosphere communities containing significantly higher relative abundances of Bacteroidetes, α-Zygomycota. We also found that endophyte presence significantly influenced rhizosphere microbial communities, with a greater effect on fungal versus bacterial communities. In particular, we observed an increased relative abundance of root-associated (arbuscular mycorrhizal) fungi in fescue plants containing shoot fungal endophytes. Our data suggests a complex, tripartite interaction between shoot endophytes, tall fescue and root associated fungi, which could have greater implications for grassland soils.
Assessment of Off-road Traversability using Linear Discriminant Analysis in Dense Disparity Space

The topographic variations and unstructured nature of cross-country environments pose a great deal of challenges to vision based autonomous navigation. Algorithms that search for geometric descriptions of such undulating terrains, usually suffer from the lack of viable assumptions. This paper presents an innovative obstacle-ground discrimination method for cross-country navigation using stereo vision. We describe well known methods such as planar ground approximation and “v-disparity” analysis using a common mathematical framework, and investigate their failure modes under off-road conditions. In order to mitigate these deficiencies we define a classifier, which is uniquely described by a family of loosely coupled linear decision boundaries, with optimized parameters under a set of soft constraints. Results for simulated and real world test data are presented, and compared with pre-existing obstacle detection algorithms.
Facial Normal Map Capture using Four Lights - An Effective and Inexpensive Method of Capturing the Fine Scale Detail of Human Faces using Four Point Lights

Obtaining photorealistic scans of human faces is both challenging and expensive. Capturing thehigh-frequency components of skin surface structure requires the face to be scanned at very highresolutions, outside the range of most structured light 3D scanners.We present a novel and simple enhancement to the acquisition process, requiring only four photo-graphic ash-lights and three texture cameras attached to the structured light scanner setup.The three texture cameras capture one texture map (luminance map) of the face as illuminatedby each of the four ash-lights. Based on those four luminance textures, three normal maps ofthe head are approximated, one for each color channel. Those normal maps are then used toreconstruct a 3D model of the head at a much higher mesh resolution, in order to validate thenormals. Finally, the validated normals are used as a normal map at rendering time. Alternatively,the reconstructed high resolution model can also be used for rendering.
Generalizing Policy Advice with Gaussian Process Bandits for Dynamic Skill Improvement

We present a ping-pong-playing robot that learns to improve its swings with human advice. Our method learns a reward function over the joint space of task and policy parameters T×P, so the robot can explore policy space more intelligently in a way that trades off exploration vs. exploitation to maximize the total cumulative reward over time. Multimodal stochastic polices can also easily be learned with this approach when the reward function is multimodal in the policy parameters. We extend the recently-developed Gaussian Process Bandit Optimization framework to include exploration-bias advice from human domain experts, using a novel algorithm called Exploration Bias with Directional Advice (EBDA).
Isomorphisms between Artin-Schreier towers

We give a method for efficiently computing isomorphisms between towers of Artin-Schreier extensions over a finite field. We find that isomorphisms between towers of degree p over a fixed field Fq can be computed, composed, and inverted in time essentially linear in p n . The method relies on an approximation process.