Miracle-dz/UniFAR-FTUs huggingface dataset:
Birdsong recognition using backpropagation and multivariate statistics

An investigation has been made of bird species recognition using recordings of birdsong. Six species of birds native to Manitoba were chosen: song sparrows, fox sparrows, marsh wrens, sedge wrens, yellow warblers, and red-winged blackbirds. These species exhibit overlapping characteristics in terms of frequency content, song components, and length of songs. Songs from multiple individuals in each of these species were employed, with discernible recording noise such as tape hiss and, in some cases, other competing songs in the background. These songs were analyzed using backpropagation learning in two-layer perceptrons, as well as methods from multivariate statistics that included principal components and quadratic discriminant analysis. Preprocessing methods included linear predictive coding and windowed Fourier transforms. Generalization performance ranged from 82-93 % correct identification, with the lower figures corresponding to smaller networks employing more preprocessing for dimensionality reduction. At the same time, the computational requirements were significantly reduced in this case.
Complete Separation of Carriers in the GeS/SnS Lateral Heterostructure by Uniaxial Tensile Strain.

The strategy of forming lateral heterostructures by stitching various two-dimensional materials overcomes the limitations due to the restricted properties of single-component materials. In this work, by using first-principles calculations, the electronic properties of GeS/SnS lateral heterostructures, together with the effect of strain, were systematically investigated. The results showed that with increasing tensile strain along the zigzag direction the band gap displays an extremely interesting variation: it linearly increases in the beginning until 2.4% strain (region I), then remains nearly constant until 5.7% (region II), and finally linearly decreases within the tensile limit (region III). Meanwhile, the electronic properties successively change from quasi-type II alignment to direct band gap to type II alignment with complete carrier separation. Analysis of the densities of states and partial charge densities indicates that the band gap increase in region I is due to the change in the orbital contributions to the states of the conduction band minimum (CBM) from Sn-pz to Sn-px, whereas the band gap decrease in region III is caused by an increasingly loose distribution of antibonding electrons at the CBM. Moreover, it was found that the changes in the orbital constituents from Sn-pz to Sn-px in the CBM and from S-px to S-py in the valence band maximum are responsible for the indirect-direct and direct-indirect band gap crossovers at the junctions of regions I and II and regions II and III, respectively. Finally, through calculations of the carrier concentrations on the basis of deformation potential theory, electrons and holes are demonstrated to be largely separated with the enhancement of strain, and the predicted electron mobilities in the armchair direction at 7% strain are as high as 5860-11 220 cm2 V-1 s-1. We believe our work may lead to potential applications for GeS-SnS heterostructures in electronics, optoelectronics, and straintronics.
Panel 1

Background The First International Symposium on Recent Advances in Otitis Media (OM) with Effusion was held in Columbus, Ohio, in 1975. The symposium has been organized in the United States every 4 years since, followed by a research conference to (a) assess major research accomplishments, (b) identify important research questions and opportunities, (c) develop consensus on definitions and terminology, and (d) establish priorities with short- and long-term research goals. One of the principal areas reviewed quadrennially is Epidemiology, Natural History, and Risk Factors. Objective To provide a review of recent literature on the epidemiology, natural history, and risk factors for OM. Data Sources and Review Methods A search of OM articles in English published July 2007 to June 2011 was conducted using PubMed and related databases. Those with findings judged of importance for epidemiology, public health, and/or statistical methods were reviewed. Results The literature has continued to expand, increasing understanding of the worldwide burden of OM in childhood, complications from treatment failures, and comorbidities. Novel risk factors, including genetic factors, have been examined for OM susceptibility. Population-based studies in Canada, the United States, and other countries confirmed reductions in OM prevalence. Although most studies concentrated on acute OM (AOM) or OM with effusion (OME), a few examined severe chronic suppurative OM (CSOM), a major public health problem in developing countries and for certain indigenous populations around the world. Conclusions and Implications for Practice Recent publications have reinforced earlier epidemiological findings, while extending our knowledge in human population groups with high burden of OM.
The dynamic range of useful temporal fine structure cues for speech in the presence of a competing talker.

Within an auditory channel, the speech waveform contains both temporal envelope (E(O)) and temporal fine structure (TFS) information. Vocoder processing extracts a modified version of the temporal envelope (E') within each channel and uses it to modulate a channel carrier. The resulting signal, E'(Carr), has reduced information content compared to the original "E(O) + TFS" signal. The dynamic range over which listeners make additional use of E(O) + TFS over E'(Carr) cues was investigated in a competing-speech task. The target-and-background mixture was processed using a 30-channel vocoder. In each channel, E(O) + TFS replaced E'(Carr) at either the peaks or the valleys of the signal. The replacement decision was based on comparing the short-term channel level to a parametrically varied "switching threshold," expressed relative to the long-term channel level. Intelligibility was measured as a function of switching threshold, carrier type, target-to-background ratio, and replacement method. Scores showed a dependence on all four parameters. Derived intensity-importance functions (IIFs) showed that E(O) + TFS information from 8-13 dB below to 10 dB above the channel long-term level was important. When E(O) + TFS information was added at the peaks, IIFs peaked around -2 dB, but when E(O) + TFS information was added at the valleys, the peaks lay around +1 dB.
Recent advances in MEMS sensor technology – biomedical applications

Micro-electromechanical systems (MEMS) use microminiature sensors and actuators. MEMS technology provides the benefits of small size, low weight, high performance, easy mass-production and low cost. This article is the first part of a three-part series on MEMS sensors. In the present article, we provide a general introduction to MEMS sensing and the primary sensing techniques. Next, MEMS-based bio-medical sensors are explained. We consider MEMS devices that are: designed to detect triglycerides, c-reactive protein, and glucose, respectively; bio-inspired robotic fingers with tissue softness characterization sensors for pressure measurement during surgical procedures; for counting blood cells; acoustic sensors for 2-D sound source localization; pressure measurement sensors on the wings of an insect-like flying robot; and ultra-miniature sensors for intramuscular pressure measurement. The second part of the series will be dedicated to mechanical sensors. There, some related technologies of MEMS sensors will be discussed including compensation for environmental effects, the Casimir effect, and harvesting of energy for self-powered sensors. Also, the subject of sensor selection will be addressed. The third part will treat MEMS sensing in the thermo-fluid and electro-magnetic domains.
Analysis and synthesis of 1/f processes via Shannon wavelets

1/f processes can be very useful in modeling processes with long-term correlation. We propose analysis and synthesis procedures to express these processes in terms of the Shannon wavelet. Unlike previous techniques, our analysis procedure generates uncorrelated decomposition coefficients for the 1/f process. This is done by taking onto account, and then removing, the residual correlation between the wavelet components, The analysis procedure is the major contribution of this work. The proposed synthesis algorithm, which is a byproduct of the proposed analysis algorithm, is competitive with other techniques.
Secrecy coding for the binary symmetric wiretap channel

In this paper, we investigate the binary symmetric wiretap channel. We show that the secrecy capacitycan be achieved by using random linear codes. The random coding scheme gives insight into the structure of secrecy capacity achieving code but unfortunately involves a rather impractical decoder. We further explore the coset-coding schemeconstructed by linear codes. As a result, we give an upper bound on the total information loss, which sheds light on the design of the applicable coset codes for the secure transmission with limited information leakage. Copyright © 2010 John Wiley & Sons, Ltd.
Screening and Referral of Alcoholic Patients in a General Hospital

A clinical trial investigating the evaluation and individualized referral of alcoholic patients in general medical wards, as compared to simple abstinence counselling, is reported. Individualized referral included a complete medical and psychosocial evaluation of the patient’s condition, followed by a multidisciplinary meeting aimed at defining individualized therapeutic proposals organized in a network of specific therapy and support. Screening (using the Michigan Alcoholism Screening Test) identified 107 patients. Eligible patients (n = 53), including those who refused to be randomized (n = 17) as well as those who were randomized (n = 36), were followed for 1 year. The study was limited by several problems arising from trial-related methods as well as from patient-related characteristics, such as a low rate of screening by residents, a high rate of exclusion (51 %), a high rate of randomization refusal (32%) as well as a high attrition rate after 1 year (42%). Among patients who were followed, we observed a high rate of abstinence (57%), which was longer in the intervention group, and was correlated with improved biological markers and scores in a quality-of-life questionnaire. This study emphasizes the need for other similar but larger trials; their design should take into consideration the methodological difficulties encountered in the present study, in order to limit the high exclusion and attrition rates.
Microwave Absorption and the Magnetic Hyperthermia Applications of Li0.3Zn0.3Co0.1Fe2.3O4 Nanoparticles in Multiwalled Carbon Nanotube Matrix.

Nanoparticles of Li0.3Zn0. 3Co0.1Fe2. 3O4 (LZC) were prepared by the sol-gel method and dried in a furnace at ∼200 °C. The dried sample was annealed at 500, 600, 700, and 800 °C for 5 h each. Rietveld analysis of X-ray diffraction patterns confirms the cubic Fd3̅m phase formation with lattice parameters ranged from 8.376 up to 8.390 Å and allows the crystallite sizes (dcryst) to be estimated. To enhance microwave (MW) absorption as well as the effectiveness for hyperthermia treatment, nanoparticles are taken in the matrix of multiwalled carbon nanotubes (MWCNTs) and the morphology of the so-prepared samples (LZC@MWCNT) was studied by scanning electron microscopy and transmission electron microscopy analyses. Both static and dynamic magnetic properties were investigated on the samples of LZC nanoparticles and compared to those of the samples of LZC@MWCNT. The samples annealed at 500, 600, and 800 °C are excellent candidates in cancer treatment as ac magnetic heating analysis shows that the hyperthermia temperature (42 °C) was successfully achieved for an applied ac magnetic field of 420 Oe and 300 kHz frequency. MW absorption study also reveals that the samples of LZC@MWCNT could be used as a potential MW absorbing material for which a maximum reflection loss (RL) of ∼-21 dB was achieved at a frequency of 15.27 GHz for only 1 mm layer thickness.
Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection

Advancement in proteomics methods for interrogating biological samples has helped identify disease biomarkers for early diagnostics and unravel underlying molecular mechanisms of disease. Herein, we examined the serum proteomes of 23 study participants presenting with one of two common arthropod-borne infections: Lyme disease (LD), an extracellular bacterial infection or West Nile virus infection (WNV), an intracellular viral infection. The LC/MS based serum proteomes of samples collected at the time of diagnosis and during convalescence were assessed using a depletion-based high-throughput shotgun proteomics (dHSP) pipeline as well as a non-depleting blotting-based low-throughput platform (MStern). The LC/MS integrated analyses identified host proteome responses in the acute and recovery phases shared by LD and WNV infections, as well as differentially abundant proteins that were unique to each infection. Notably, we also detected proteins that distinguished localized from disseminated LD and asymptomatic from symptomatic WNV infection. The proteins detected in both diseases with the dHSP pipeline identified unique and overlapping proteins detected with the non-depleting MStern platform, supporting the utility of both detection methods. Machine learning confirmed the use of the serum proteome to distinguish the infection from healthy control sera but could not develop discriminatory models between LD and WNV at current sample numbers. Our study is the first to compare the serum proteomes in two arthropod-borne infections and highlights the similarities in host responses even though the pathogens and the vectors themselves are different.
Client cloud Web service: reducing traffic consumption

The availability of the Web service has been exposed to several threats such as distributed denial-of-service attack, which is not an unfamiliar terminology anymore. Sustaining availability against various attacks becomes the critical issue for high-profile Web sites. In this paper, we propose a novel architecture providing Web service among client, called client cloud Web service, by utilizing resources of clients to enhance the availability. Client cloud Web service can be easily integrated into the current Internet protocol suite by providing a transparent layer in the middle of Hypertext Transfer Protocol layer and Transmission Control Protocol/Internet Protocol layer. It is shown by simulations that the proposed architecture can efficiently reduce the traffic when both the size of Web items and the number of requests from clients increase. Copyright © 2012 John Wiley & Sons, Ltd.
Auction-based task allocation with trust management for shared sensor networks

Task allocation for wireless sensor networks with multiple concurrent applications (such as target tracking and event detection) requires sharing applications' tasks (such as sensing and computation) and available network resources. In this paper, we model the distributed task allocation problem for multiple concurrent applications by using a reverse combinatorial auction, in which the bidders (sensor nodes) are supposed to bid cost values (according to their available resources) for accomplishing the subset of the applications' tasks. Trust management schemes consist of a powerful tool for the detection of unexpected node behaviors (such as faulty or malicious). It is critical for participants (i.e., bidders and auctioneer) to estimate each other's trustworthiness before initiating the task allocation procedure. To address this issue, we introduce a real-time trust management module for our auction system that is able to validate the reliable bid value and determine faulty nodes and malicious entities. The main objective of our task allocation scheme is to maximize the network lifetime by sharing tasks and network resources within applications, while enhancing the overall application quality of service (e.g., deadline). We also propose a heuristic two-phase winner determination protocol to deal with the combinatorial reverse auction problem. Simulation results show that the proposed scheme offers the promising performance and efficiency. Copyright © 2012 John Wiley & Sons, Ltd.
Pattern and magnitude of treatment delay among TB patients in five states in southern Nigeria

Prompt diagnosis and early treatment of Tuberculosis (TB) cases is an important strategy in TB prevention and control. Thus, passive case finding of TB suspects, sputum examination for diagnosis, and prompt treatment using Directly Observed Treatment Short Course (DOTS) are key elements in the national guideline for TB control programme. The aim of this study is to determine the time interval between diagnosis of smear-positive TB cases and the commencement of treatment in DOTS facilities in southern Nigeria. The study was carried out in 20 healthcare facilities supported by TB Control Assistance Program (TB-CAP) involved in TB management in southern Nigeria, which comprised tertiary, secondary, and primary healthcare facilities including public and private facilities. Data were collected through review of clients' and facility records covering July-September 2009. Data collected were sociodemographic characteristics, sputum-smear result, date of diagnosis, and date of commencement of treatment. Data were analyzed using SPSS version 15.0 software. Of the total 2,507 TB suspects examined for Acid-Fast Bacillus (AFB), 323 were diagnosed to be Sputum-Smear-Positive (SS+ve), However, 269 new smear positive cases were commenced on treatment within the period, thus 54 (17.0%) of the new SS+ve cases defaulted initially. One hundred and two (38%) of them commenced TB treatment within 3 days of smear examination for diagnosis, while 59 (22%) commenced 4-6 days after diagnosis. The study revealed significant delay in commencement of TB treatment for most new smear positive TB cases in southern Nigeria and underlines the need to further explore factors responsible for delay in commencement of TB treatment following diagnosis.
SVD analysis by synthesis of harmonic signals

An analysis by synthesis procedure based on the singular value decomposition (SVD) methodology is proposed. Using this procedure, a criterion for detecting the number of sinusoidal signals in the presence of noise is defined. Consecutive reconstructions are performed, and the resulting error power is compared to the noise variance in order to get the best approximation of the original noncorrupted signal. The number of the singular values corresponding to a reconstruction error power as close as possible to the noise variance gives the parsimonious order. The existence of such a criterion is important for both high-quality reconstruction and spectral analysis. Various spectral estimation techniques used on a reconstructed signal make it possible to retrieve harmonics in a highly noisy environment with very short data lengths. >
An experimental investigation of swimbladder resonance in fishes

An investigation of the resonant behavior of the swimbladder for different species and sizes has been performed. Most measurements have been done using the ring‐hydrophone method, but also a few normal echo measurements have been done. The results show the resonance frequency to increase with depth, but also to depend on what degree the fish is adapted to the depth. After a sudden transfer to new depth, the resonance frequency will first oscillate and then gradually adjust to a new resonance frequency given by the necessary swimbladder volume to retain neutral buoyancy. The time required to adapt to a deeper depth is longer than for a transfer in the opposite direction suggesting that gas production takes longer time than letting out gas. The observed Q values are also dependent on adaption, but appears to increase almost linearly with the resonance frequency at least for low Q values. The measured values are compared with a model for scattering from swimbladder fish and values for the swimbladder tension.
The development and modification of children's eating habits

The development of children's food preferences involves a complex interplay of innate, familial and environmental factors, not all of which are likely to promote a healthy and varied diet. Parents employ a variety of strategies to improve their children's eating habits some of which have been found to be counter-productive. Over-control, the offering of rewards, and the provision of nutrition information to children appear to have negative effects on food acceptance patterns. Parents own food preferences, on the other hand, are enormously influential and eating together as a family provides a valuable opportunity for parents to model good eating habits. Together with the evidence that repeated taste exposure can reduce neophobia and increase acceptance of foods, these findings should inform the guidance given to parents during early childhood. © 2004 British Nutrition Foundation Nutrition Bulletin.
A data mining system for distributed abnormal event detection in backbone networks

Detecting distributed abnormal events has become an increasingly significant task for efficient network management and operation. However, it is still challenging to uncover these distributed behaviors in backbone networks because of the voluminous amount of noisy, high-dimensional traffic data. In this paper, we present a novel system for detecting distributed abnormal events in backbone networks. The proposed system emphasizes on detecting distributed correlated abnormal events, which are caused by the same reason. In contrast, existing methods are not able to distinguish correlated abnormal events from the independent abnormal events. In our proposed system, a set of data mining techniques is used for modeling and detecting distributed correlated abnormal events by analyzing the traffic features. Specifically, traffic behavior representation is constructed to define and select traffic features for describing the traffic behaviors of interest, feature clustering is performed to group together similar transformations in each feature, behavioral data mining is employed to discover the most significant patterns in network interactions with respect to typical behavior, and behavior classification is used to expose the behaviors of interest. Experiment results using real traffic data present the effectiveness of our proposed methods for detecting distributed correlated abnormal events in the backbone network. Copyright © 2013 John Wiley & Sons, Ltd.