Miracle-dz/UniFAR-FTUs huggingface dataset:
Multispectrum Approach in Quantitative EEG: Accuracy and Physical Effort

The detection of neurophysiological features by means of electroencephalogram (EEG) is one of the most recurrent medical exams to be performed on human beings. As it stands, EEG trials are not always sufficient to deliver a clear and precise diagnosis for much pathology. Hence, it must be integrated with other exams. However, we can use all additional instrumental exams to improve the quality of the diagnosis because there are other constraints, namely, financial, medical, and individual. This paper presents an original implementation of EEG signal processing using filter diagonalization method to build a bispectrum and contour representation to discover possible abnormalities hidden in the signal for aided-diagnosis. Two different EEG signals are used for this scope. EEG signals are acquired simultaneously with electrocardiograms (ECG) and ergospirometric ones. ECG signals are also processed along with EEGs. A comparison is made with high order spectra approach. All experimental data regarding EEG, ECG, and ergospirometry are acquired during suspected-patient walking along a path of ~32 m for verifying the impact of fatigue on neurophysiological processes and vice versa.
Fast and precise Fourier transforms

Many applications of fast Fourier transforms (FFTs), such as computer tomography, geophysical signal processing, high-resolution imaging radars, and prediction filters, require high-precision output. An error analysis reveals that the usual method of fixed-point computation of FFTs of vectors of length 2/sup l/ leads to an average loss of l/2 bits of precision. This phenomenon, often referred to as computational noise, causes major problems for arithmetic units with limited precision which are often used for real-time applications. Several researchers have noted that calculation of FFTs with algebraic integers avoids computational noise entirely. We combine a new algorithm for approximating complex numbers by cyclotomic integers with Chinese remaindering strategies to give an efficient algorithm to compute b-bit precision FFTs of length L. More precisely, we approximate complex numbers by cyclotomic integers in Z[e(2/spl pi/i/2/sup n/)] whose coefficients, when expressed as polynomials in e(2/spl pi/i/2/sup n/), are bounded in absolute value by some integer M. For fixed n our algorithm runs in time O(log(M)), and produces an approximation with worst case error of O(1/M(2/sup n-2/-1)). We prove that this algorithm has optimal worst case error by proving a corresponding lower bound on the worst case error of any approximation algorithm for this task. The main tool for designing the algorithms is the use of the cyclotomic units, a subgroup of finite index in the unit group of the cyclotomic field. First implementations of our algorithms indicate that they are fast enough to be used for the design of low-cost high-speed/high-precision FFT chips.
Development and characterization of 11 polymorphic microsatellite markers in Tapiscia sinensis (Staphyleaceae)

Premise of the study: We developed and characterized five polymorphic microsatellite loci from an AC-enriched genomic library of a rare tree, Tapiscia sinensis, and six compound microsatellite primers using a dual-suppression-PCR–based approach, to investigate geographical genetic structure. Methods and Results: The polymorphism of these loci was assessed in 102 samples collected from three populations. The number of alleles per locus ranged from one to nine. Expected heterozygosity per locus ranged from 0.000 to 0.709 and observed heterozygosity ranged from 0.000 to 0.750. Five loci deviated from Hardy–Weinberg equilibrium after Bonferroni correction. Conclusions: This set of microsatellites may be useful for investigating broad-scale genetic variation in the extant populations of the endangered tree species T. sinensis.
Masked Syllable Priming of English Nouns

This study investigates the role of sublexical units in the phonological encoding of English single-word production in a word-naming task (Experiment 1) and a picture-naming task (Experiment 2). Targets corresponded to bisyllabic English nouns with word-initial stress which varied on the structure of their first syllable: CV (e.g., pi.lot), CVC (e.g., pic.nic), or CV[C] (e. g., pi[ll]ow). 1 Targets were preceded by a visually masked prime that either matched their first syllable (e.g., pi%%% - pi.lot) or that was one segment longer (e.g., pil%% - pi.lot) or shorter (e.g., pi%%%% - pic.nic) than the first syllable. Response times were compared to a neutral control condition (e.g., %&$%% - pi.lot) to measure the priming effects (either facilitation or inhibition). Results showed significant facilitation for both the CV and the CVC conditions. However, contrary to previous findings, there was no interaction between the syllabic structure of the prime and the target.
How to understand linear minimum mean-square-error transceiver design for multiple-input-multiple-output systems from quadratic matrix programming

In this study, a unified linear minimum mean-square-error (LMMSE) transceiver design framework is investigated, which is suitable for a wide range of wireless systems. The unified design is based on an elegant and powerful mathematical programming technology termed as quadratic matrix programming (QMP). Based on QMP it can be observed that for different wireless systems, there are certain common characteristics which can be exploited to design LMMSE transceivers, for example, the quadratic forms. It is also discovered that evolving from a point-to-point multiple-input–multiple-output (MIMO) system to various advanced wireless systems such as multi-cell coordinated systems, multi-user MIMO systems, MIMO cognitive radio systems, amplify-and-forward MIMO relaying systems and so on, the quadratic nature is always kept and the LMMSE transceiver designs can always be carried out via iteratively solving a number of QMP problems. A comprehensive framework on how to solve QMP problems is also given. The work presented in this study is likely to be the first shot for the transceiver design for the future ever-changing wireless systems.
Identifying Target Areas of Treatment for Depressed Early Inflammatory Arthritis Patients

Background: The goal of this study was to identify target areas for psychosocial intervention for depressed patients with earlyinflammatory arthritis. Methods:One hundred and sixty-five patients with early inflammatory arthritis (≧1 joint with synovitis for ≧6 weeks and <1 year with a diagnosis of either rheumatoid or undifferentiated inflammatory arthritis) were referred to the McGill Early Arthritis Registry (McEAR) by their rheumatologist. McEAR patients agree to periodic physical exams and to completing questionnaires. Demographic, disease and psychosocial factors were compared between patients screening positive and negative for depression using independent samples t tests and Pearson’s χ2 test and then were entered into a logistic regression model examining the likelihood of screening positive for depression. Results: Thirty-eight (23%) patients screened positive for depressive symptoms. Patients with symptoms of depression had significantly worse disease severity, disability, and pain, engaged in more emotional preoccupation coping, had less self-efficacy for pain and other arthritis-related symptoms, smaller social networks and were less satisfied with social support than the nondepressed group. In logistic regression analyses, pain and emotional preoccupation coping were positively related to the likelihood of screening positive for depression, while satisfaction with social support was negatively related to the likelihood of screening positive for depression Conclusion: Higher pain levels, emotional preoccupation coping and dissatisfaction with social support were related to depressive symptoms in this study. This suggests that the optimal care of depressed patients with inflammatory arthritis would include a psychosocial approach that addresses these specific target areas.
Enabling high performance computing in cloud computing environments

Cloud Computing is a server based model which provides shared pool of resources for the clients to access from a remote location. It provides various advantages to the users such as Pay-as-you-go model, elasticity, flexibility and dynamic customization offered by the virtualization. The present high speed networks and low cost devices led to the growth of cloud computing. Currently, High Performance Computing (HPC) applications are run in computing clusters which are set-up on their own. It requires ownership, high initial set-up cost and recurring maintenance cost which are unwanted burden for the HPC application users. So, it would be advantageous to use cloud service for the HPC applications which would result in huge savings. But, due to the interconnect bandwidth and heterogeneity involved in the cloud service, HPC applications provide poor performance in the cloud. We evaluate the current performance of HPC applications in the existing cloud infrastructures and then discuss various techniques to mitigate interference, virtualization overhead and problems due to shared resources in the cloud. In the end, we conclude with future works that can be done to ensure that HPC applications are more suitable for the cloud.
Automatic chord transcription from audio using computational models of musical context

This thesis is concerned with the automatic transcription of chords from audio, with an emphasis on modern popular music. Musical context such as the key and the structural segmentation aid the interpretation of chords in human beings. In this thesis we propose computational models that integrate such musical context into the automatic chord estimation process. We present a novel dynamic Bayesian network (DBN) which integrates models of metric position, key, chord, bass note and two beat-synchronous audio features (bass and treble chroma) into a single high-level musical context model. We simultaneously infer the most probable sequence of metric positions, keys, chords and bass notes via Viterbi inference. Several experiments with real world data show that adding context parameters results in a significant increase in chord recognition accuracy and faithfulness of chord segmentation. The proposed, most complex method transcribes chords with a state-of-the-art accuracy of 73% on the song collection used for the 2009 MIREX Chord Detection tasks. This method is used as a baseline method for two further enhancements. Firstly, we aim to improve chord confusion behaviour by modifying the audio front end processing. We compare the effect of learning chord profiles as Gaussian mixtures to the effect of using chromagrams generated from an approximate pitch transcription method. We show that using chromagrams from approximate transcription results in the most substantial increase in accuracy. The best method achieves 79% accuracy and significantly outperforms the state of the art. Secondly, we propose a method by which chromagram information is shared between repeated structural segments (such as verses) in a song. This can be done fully automatically using a novel structural segmentation algorithm tailored to this task. We show that the technique leads to a significant increase in accuracy and readability. The segmentation algorithm itself also obtains state-of-the-art results. A method that combines both of the above enhancements reaches an accuracy of 81%, a statistically significant improvement over the best result (74%) in the 2009 MIREX Chord Detection tasks.
Assessment of physician-patient trust in the obstetrics and gynecology departments in Poland and Greece.

AIM To evaluate patient trust in their physicians of the obstetrics and gynecology departments. MATERIAL AND METHODS We used the Trust in Physician Scale comprising 11-items. Data were collected from 150 women hospitalized in the obstetrics and gynecology departments in Poland and 109 in Greece. RESULTS Of the surveyed, 25.3% from Poland and 47.4% from Greece did not doubt their doctors' proper care. Almost 90% of the respondents from Poland and 58.8% from Greece agreed with the statement "I trust my doctor very much, that is why I always comply with his/her advice". More than 68% of the patients from Poland and 56.9% from Greece were convinced that "if my physician tells me something, this has to be the truth": Almost 77% of patients from Poland and 43.1% from Greece declared trust in their physicians therapy. Eighty-four percent of women from Poland and 49.55% from Greece were convinced that their doctor is a true expert in the treatment of their diseases. Nearly 97% of the patients from Poland and 35.8% from Greece did not declare fear of their physician not keeping the professional secret. CONCLUSIONS The Trust in Physician Scale is an appropriate tool for assessing levels of patient trust in their gynecologist. Patients reported a relatively high degree of trust in their gynecologists. Women from Greece more often than from Poland did not trust their physicians, and declared that doctors did not do all for their care.
Caring for a dying spouse at the end of life: 'It's one of the things you volunteer for when you get married': a qualitative study of the oldest carers' experiences.

BACKGROUND older people aged 80 and over are increasingly providing end-of-life care to spouses at home and often do so for long periods of time, while also trying to manage their own illnesses and disabilities. Little of the research on older spousal carers has focussed on the oldest carers; hence, the needs of this particular population are not fully known. OBJECTIVE to explore the experiences of the 'oldest carers' in caring for a dying spouse at home. METHODS secondary analysis was undertaken on a subset of data from a larger qualitative interview study; this dataset comprised 17 interviews from participants aged 80 or over. Framework analysis methods were used, with items derived from the thematic analysis of the main study. RESULTS the oldest carers in this subset demonstrated high levels of resilience and the ability to adapt to their caring role. Caring until death was accepted as an integral part of the commitment made to their partner as part of the 'wedding contract'. Carers felt they benefitted from the support provided by family, friends and care services; however, their own care needs were not always recognised by health and social care services. CONCLUSIONS these findings underscore the complexity of the oldest carers' experiences and challenges in times of illness and end of life. Healthcare professionals should be alerted to the myriad ways caregiving is enacted in serious illness and seek opportunities for developing supportive interventions specifically for older carers.
A selective approach to neural network ensemble based on clustering technology

Learning for prediction using neural network ensemble can give improved accuracy, and reliable estimation of the generalization error. At present, most approaches ensemble all the available neural networks at hand. In this paper, based on clustering technology, a selective approach to neural network ensemble is presented. After component neural networks are trained, the clustering algorithm is used to select some component neural networks instead of all of the neural networks in order to reduce their similarity. Then selected neural networks are made up to ensemble using simple means method. Finally, an empirical study is conducted and compared with popular ensemble approaches such as bagging. Experimental results show that this approach outperforms the traditional ones that ensemble all of the individual networks.
A comparison of the mother's and a stranger's control over the behavior of infants.

CORTER, CARL M. A Comparison of the Mother's and a Stranger's Control over the Behavior of Infants. CHILD DEVELOPMENT, 1973, 44, 705-713. 10-month-old infants were placed in a test room under 3 conditions: with the mother, an adult female stranger, or both, present in adjoining rooms. The infants generally directed their social responses more to the mother than to the stranger; they followed her almost exclusively, although they looked and smiled less selectively. The mother's presence also delayed crying. The stranger did not increase crying but instead evoked looking, some smiling, and delayed the infant's following his mother. The findings affirm that following is one of the responses comprising the infant's attachment to his mother, but also suggest that the tie need not imply fear of a stranger since the stranger evoked exploration more than distress.
Adult Urology Oncology : Adrenal / Renal / Upper Tract / Bladder Patient Function and the Value of Surgical Care for Kidney Cancer

Accepted for publication December 6, 2016. No direct or indirect commercial incentive associated with publishing this article. The corresponding author certifies that, when applicable, a statement(s) has been included in the manuscript documenting institutional review board, ethics committee or ethical review board study approval; principles of Helsinki Declaration were followed in lieu of formal ethics committee approval; institutional animal care and use committee approval; all human subjects provided written informed consent with guarantees of confidentiality; IRB approved protocol number; animal approved project number. Supported by American Cancer Society Grant 126217-PF-14-028-01-CPHPS (HJT) and a National Institutes of Health Loan Repayment Program grant (HJT, KC). * Correspondence: Department of Urology, University of North Carolina at Chapel Hill, 170 Manning Dr., CB #7235, Chapel Hill, North Carolina 27599 (telephone: 919-966-2571; e-mail: hjtan@med.unc.edu).
Accurate and efficient N-6-adenosine methylation in spliceosomal U6 small nuclear RNA by HeLa cell extract in vitro

Human U6 small nuclear RNA (U6 snRNA), an abundant snRNA required for splicing of pre-mRNAs, contains several post-transcriptional modifications including a single m6A (N-6-methyladenosine) at position 43. This A-43 residue is critical for the function of U6 snRNA in splicing of pre-mRNAs. Yeast and plant U6 snRNAs also contain m6A in the corresponding position showing that this modification is evolutionarily conserved. In this study, we show that upon incubation of an unmodified U6 RNA with HeLa cell extract, A-43 residue in human U6 snRNA was rapidly converted to m6A-43. This conversion was detectable as early as 3 min after incubation and was nearly complete in 60 min; no other A residue in U6 snRNA was converted to m6A. Deletion studies showed that the stem-loop structure near the 5' end of U6 snRNA is dispensable for m6A formation; however, the integrity of the 3' stem-loop was necessary for efficient m6A formation. These data show that a short stretch of primary sequence flanking the methylation site is not sufficient for U6 m6A methyltransferase recognition and the enzyme probably recognizes secondary and/or tertiary structural features in U6 snRNA. The enzyme that catalyzes m6A formation in U6 snRNA appears to be distinct from the prolactin mRNA methyltransferase which is also present in HeLa nuclear extracts.
Imaging PEC through innovative compressive sensing approaches

In this paper, an innovative multi-task Bayesian Compressive Sensing (MT-BCS)-based approach is proposed to image sparse metallic objects. Towards this end, the problem of estimating the position of the contrast currents is formulated in a Bayesian framework, and a thresholding procedure is applied to derive the binary function describing the scatterer profile. A preliminary set of numerical examples is presented to assess the effectiveness of the considered methodology.
Strategies for Fault-Tolerant Distributed Visualization

As systems grow at an increasing pace to keep up with the demand for larger data and ever more detailed simulations, failures also occur more frequently on various levels. Traditionally, fault tolerance for visualization is either disregarded due to performance reasons or handled analogously to the state of the art for high performance computing (HPC), for example rollback-recovery. In this paper we summarize the inherent challenges of distributed visualization as well as the applicability and differences of fault tolerance methods used in HPC and distributed visualization. We derive complementary methods to increase the resilience of such systems and present visualization specific methods for failure semantics and masking.
A Secure Authentication Scheme for WiMax Network and Verification using Scyther Tool

Recently, the wireless Communication technologies are replacing the wired one. WiMax is one of the wireless communication technologies which provides high speed internet. Like other network technologies the wireless network technologies are also not secured. A lot of security issues were reported in WiMax in various articles. To protect from unauthorized use of resources of a network, authorization and authentication models are developed. Various authentication and encryption mechanisms were proposed for WiMax security but still the WiMax networks are not fully secure and are under the attacks like replay attack, Rouge Base station Attack, Man in the Middle Attack, DoS Attack etc. To increase the capability and functionality of existing models we will propose a security scheme in this article. We will also verify our proposed security scheme using the scyther tool.
In-Membrane Chemical Modification (IMCM) for Site-Specific Chromophore Labeling of GPCRs.

We present in-membrane chemical modification (IMCM) for obtaining selective chromophore labeling of intracellular surface cysteines in G-protein-coupled receptors (GPCRs) with minimal mutagenesis. This method takes advantage of the natural protection of most cysteines by the membrane environment. Practical use of IMCM is illustrated with the site-specific introduction of chromophores for NMR and fluorescence spectroscopy in the human κ-opioid receptor (KOR) and the human A2A adenosine receptor (A2A AR). IMCM is applicable to a wide range of in vitro studies of GPCRs, including single-molecule spectroscopy, and is a promising platform for in-cell spectroscopy experiments.
PHARMACOLOGIC TREATMENT OF BEHAVIORAL AND NEUROPSYCHIATRIC SYMPTOMS —

The frequency and severity of neuropsychiatric and behavioral symptoms in Alzheimer’s disease (AD) typically reach a peak by the middle or moderate stage of the disease. By this point, language and memory abilities are also significantly impaired, limiting the patients’ ability to adequately express any discomforts or concerns and compelling them to communicate their thoughts and distress in the only way they can— through behaviors. There are often multiple concurrent causes of distressed behavior; identifying them requires a methodical approach. Assessment should include environmental, medical, and psychiatric evaluations, which can be considered together to form a list of “working diagnoses. ” Nonpharmacologic interventions should be implemented whenever possible, even when pharmacologic treatment may be considered the primary intervention. Although many medications can temporarily calm a patient, they can place the patient at unnecessary risk of adverse events if underlying conditions remain untreated. Pharmacologic treatment of behavioral symptoms is warranted when the acuity of the symptom compels the need for immediate relief or when a medical or psychiatric condition has been identified that requires medical management. This article discusses common presentations of distress in dementia patients and information on many of the medications frequently used for treatment (ie, the cholinesterase inhibitors, mood stabilizers, antipsychotics, antidepressants, and anxiolytics). To optimally care for our residents, it is essential for all members of the healthcare team to contribute to our understanding and identification of the various causes of distress. Beyond aiding the patient in achieving a better quality of life, we also avoid inappropriate or dangerous drug choices in this fragile population. (Adv Stud Pharm. 2005;2(5):175-190)