Miracle-dz/UniFAR-FTUs huggingface dataset:
Delays in referral and diagnosis for chronic hematologic malignancies: A literature review

To better understand the extent of diagnostic and referral delays from primary care providers (PCPs) for chronic hematologic malignancies, causes of these delays, and their possible effects on cancer outcomes, an extensive review of the literature was performed. Over 50 studies were reviewed, including many that concern delays in referral and diagnosis for solid tumors, as there was only sparse literature on delays specific to the liquid tumors. Delays for some chronic hematologic malignancies have been documented, mainly in centralized health care systems. Possible reasons for delays include PCPs' lack of exposure to hematologic malignancies, limited knowledge of associated signs and symptoms, and a reliance on patient symptoms to prompt referral (as opposed to signs and screening). Patient characteristics such as age, gender and race-ethnicity are also likely to play a role, although it is unclear if these exert their effect primarily via patient or provider mechanisms. Unfortunately, the outcomes associated with such delays are largely unreported, possibly because delay is complex to define and difficult to measure.
A robust Brain Computer Interface system for classifying multi motor imagery tasks over daily sessions

In Brain Computer Interface (BCI), the thoughts of a subject is read to provide an appropriate way of communication using only brain signals. The Information of electroencephalogram (EEG) signals defer between subjects depending on their thoughts according to research. In this paper, a comparison between different types of features tested by several classifiers is done to propose a model for classifying multi motor imagery (MI) tasks through offline analysis for a single subject performing one session daily for a week. Several classifiers and feature extraction techniques were used. Common Spatial Pattern (CSP) as a feature classified by Linear Discriminant Analysis (LDA) was found to outperform all other combinations with an average classification accuracy above 88%.
A Comparative Study of Wavelet Based Feature Extraction Techniques in Recognizing Isolated Spoken Words

Speech is a natural mode of communication for people and speech recognition is an intensive area of research due to its versatile applications. This paper presents a comparative study of various feature extraction methods based on wavelets for recognizing isolated spoken words. Isolated words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. This work includes two speech recognition methods. First one is a hybrid approach with Discrete Wavelet Transforms and Artificial Neural Networks and the second method uses a combination of Wavelet Packet Decomposition and Artificial Neural Networks. Features are extracted by using Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The proposed method is implemented for 50 speakers uttering 20 isolated words each. The experimental results obtained show the efficiency of these techniques in recognizing speech.
Cardiac memory in human atria and relation to arrhythmogenesis

Abnormal adaptation of action potential duration (APD) to changes in heart rate (HR) has been suggested as an indicator of increased arrhythmic risk. In this study, we investigate the mechanisms underlying APD rate adaptation in human atrial cells and its relationship to arrhythmogenesis. Simulations are performed using action potential computational models and results are compared with experimental data from the literature. APD rate adaptation in response to sudden sustained HR changes is shown to take more than 8 minutes to be completed in the simulations and two main adaptation phases can be identified: a fast initial one due to the Na+/Ca2+ exchanger and the L-type calcium current; and a subsequent slow accommodation determined by intracellular Na dynamics. Both APD adaptation dynamics and its underlying mechanisms are found to be consistent in different species. Alterations in ionic mechanisms leading to delayed APD adaptation are associated with increased proarrhythmic risk.
An Efficient and Effective Methodology to Control Turn-On Sequence of Power Switches for Power Gating Designs

As technology advances, power consumption becomes a big challenge in modern very large-scale integration designs. To resolve this problem, power-gated technology has been widely adopted in circuit designs. Since the turn-on sequence of power switches has a great impact on the rush current, wake-up, and sequence times of a power gating design, this paper proposes a methodology to construct a hybrid routing structure to connect power switches. Our hybrid routing structure can induce less rush current and satisfy timing constraints because a better daisy chain is constructed. To find members of the daisy chain, an integer linear programming algorithm is used to pick up suitable power switches. To determine suitable depth of a daisy chain, we propose a model for a power gating design and induct precise equations to estimate voltage and rush current equations according to the model. All of our experiments are based on industrial designs and measured by vendor tools. The experimental results demonstrate the efficiency and effectiveness of our design methodology.
Temporal relation between acoustic and force responses at the adductor pollicis during nondepolarizing neuromuscular block.

BACKGROUND Contracting muscle emits sounds. The purpose of this study was to compare the time course of muscular paralysis at the adductor pollicis muscle (AP) with use of acoustic myography and mechanomyography. METHODS Thirteen elective surgery patients, American Society of Anesthesiologists physical status I, received rocuronium (0.6 mg/kg intravenously) as a bolus dose during general anesthesia. Force of AP was measured with use of a strain gauge, and sounds were recorded simultaneously with use of a small condenser microphone fixed on the palmar surface of the hand over the AP. Supramaximal stimulation was applied to the ulnar nerve at 0.1 Hz for 45-60 min. In seven patients, the response to train-of-four stimulation was also recorded during recovery. RESULTS Force and sounds both were equally sensitive in measuring maximum block. The relation between sound and force was curvilinear, with good agreement near 0 and 100% and acoustic response exceeding mechanical response at intermediate levels of block. The acoustic signal had a slower onset and a faster recovery than the force response. The fade response of sound to train-of-four stimulation also recovered faster than that of force. CONCLUSION Acoustic myography is an alternative method to monitor muscular paralysis that is easy to set up and applicable to most superficial muscles. However, the time course of relaxation at AP using acoustic myography differs from the time course of force relaxation. Therefore, these two methods are not equivalent when applied to AP.
Parallel molecular dynamics simulations of antimicrobial peptides

SuperHelix for the scaling tests. Finally, I wish to express my gratitude to my dear family for supporting me throughout years of study. ABSTRACT Molecular dynamics (MD) simulations of the wheat antimicrobial peptide β-purothionin were carried out in explicit water (~14,000 atoms) using an all-atom model. The structural properties of the peptide as a function of MD simulation, temperature, and presence of the mono-and divalent metal ions were investigated. The accuracy and scalability tests of the code Peach 3.8 for our system were performed on the Intel Xeon-based Linux cluster SuperHelix at Louisiana State University (LSU). The code showed the reliable accuracy and the parallel efficiency of 0.61 for ~14,000 particles on 16 processors. The microcanonical (MC) MD simulation of β-purothionin in water showed that all secondary structures were stable and exhibited normal conformation at 300 K initial temperature. Helicity of the peptide was found to depend strongly on temperature, consistent with experimental data. Analysis of the MD trajectories elucidated new details of temperature effects on purothionin. Thus, the α-helix α1 displayed unusual temperature resistance. The β-sheets and all four disulphide bonds were not affected by change in the range of temperature from 0 to 400 K. The residues Tyr13 and Arg30 thought to be involved in antimicrobial activity of purothionin displayed increased stability. Decrease in flexibility of the peptide largely decreased upon interaction with K + and Mg 2+ ions. The MD simulations indicated that Mg 2+ ions impaired the α-helix α2 and both ions interacted with Tyr13 and Agr30, suggesting the mechanism of cation inhibition for antimicrobial activity of purothionin. Therefore, the results reported here showed that the MC MD simulations reproduced effects of temperature and metal ions on structure of purothionin. Moreover, this study provided new insights into structural properties, and effects of temperature and metal ions on structure stability and conformation of the purothionin molecule.
Application of Neural Networks to Modeling and Control of Parallel Manipulators

There are mainly two types of the manipulators: serial manipulators and parallel manipulators. The serial manipulators are open-ended structures consisting of several links connected in series. Such a manipulator can be operated effectively in the whole volume of its working space. However, as the actuator in the base has to carry and move the whole manipulator with its links and actuators, it is very difficult to realize very fast and highly accurate motions by using such manipulators. As a consequence, there arise the problems of bad stiffness and reduced accuracy. Unlike serial manipulators their counterparts, parallel manipulators, are composed of multiple closed-loop chains driving the end-effector collectively in a parallel structure. They can take a large variety of form. However, most common form of the parallel manipulators is known as platform manipulators having architecture similar to that of flight simulators in which two special links can be distinguished, namely, the base and moving platform. They have better positioning accuracy, higher stiffness and higher load capacity, since the overall load on the system is distributed among the actuators. The most important advantage of parallel manipulators is certainly the possibility of keeping all their actuators fixed to base. Consequently, the moving mass can be much higher and this type of manipulators can perform fast movements. However, contrary to this situation, their working spaces are considerably small, limiting the full exploitation of these predominant features (Angeles, 2007). Furthermore, for the fast and accurate movements of parallel manipulators it is required a perfect control of the actuators. To minimize the tracking errors, dynamical forces need to be compensated by the controller. In order to perform a precise compensation, the parameters of the manipulator’s dynamic model must be known precisely. However, the closed mechanical chains make the dynamics of parallel manipulators highly complex and the dynamic models of them highly non-linear. So that, while some of the parameters, such as masses, can be determined, the others, particularly the firiction coefficients, can’t be determined exactly. Because of that, many of the control methods are not efficient satisfactorly. In addition, it is more difficult to investigate the stability of the control methods for such type manipulators (Fang et al., 2000). Under these conditions of uncertainty, a way to identify the dynamic model parameters of parallel manipulators is to use a non-linear adaptive control algorithm. Such an algorithm
Incidence and prediction of falls in Parkinson's disease: a prospective multidisciplinary study

Objectives: To accurately establish the incidence of falls in Parkinson's disease (PD) and to investigate predictive risk factors for fallers from baseline data. Methods: 109 subjects with idiopathic PD diagnosed according to the brain bank criteria underwent a multidisciplinary baseline assessment comprising demographic and historical data, disease specific rating scales, physiotherapy assessment, tests of visual, cardiovascular and autonomic function, and bone densitometry. Patients were then prospectively followed up for one year using weekly prepaid postcards along with telephone follow up. Results: Falls occurred in 68.3% of the subjects. Previous falls, disease duration, dementia, and loss of arm swing were independent predictors of falling. There were also significant associations between disease severity, balance impairment, depression, and falling. Conclusions: Falls are a common problem in PD and some of the major risk factors are potentially modifiable. There is a need for future studies to look at interventions to prevent falls in PD.
Revisiting the dependence language model for information retrieval

In this paper, we revisit the dependence language modelfor information retrieval proposed in [1], and show that thismodel is deficient from a theoretical point of view. We thenpropose a new model, well founded theoretically, for integratingdependencies between terms in the language model.This new model is simpler, yet more general, than the oneproposed in [1], and yields similar results in our experiments,on both syntactic and semantic dependencies.
A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer

Lung cancer is the first cause of cancer mortality worldwide, and its early detection is currently the main available strategy to improve disease prognosis. While early diagnosis can be successfully achieved through tomography‐based population screenings in high‐risk individuals, simple methodologies are needed for effective cancer prevention programs. We developed a test, based on the detection of 34 microRNAs (miRNAs) from serum, that could identify patients with early stage non‐small cell lung carcinomas (NSCLCs) in a population of asymptomatic high‐risk individuals with 80% accuracy. The signature could assign disease probability accurately either in asymptomatic or symptomatic patients, is able to distinguish between benign and malignant lesions, and to capture the onset of the malignant disease in individual patients over time. Thus, our test displays a number of features of clinical relevance that project its utility in programs for the early detection of NSCLC.
Measuring Trust and Selecting Cloud Database Services

In a cloud environment, third party controlled asset sharing cloud databases is the motivation for search of trust. Lack of trust appears to be a probable major cause for fear when outsourcing databases. Research literature reviews indicate that the architecture of cloud databases has a potential to mitigate user distrust. In this paper, we focus on measuring trust in cloud database services based on user selected relative or direct factors. Our study proposes a formal trust mechanism in cloud databases where the user can select his most trusted Cloud Service Provider.
Improving Mandarin Prosody Generation Using Alternative Smoothing Techniques

Prosody plays a vital role for conveying both communicative meanings and specific speaking styles in speech communication. In recent years, Hidden Markov Model (HMM)-based synthesis system (HTS) has been developed in triumph, which can synthesize stable and smooth speech. However, the prosody of the synthesized speech suffers from the over-smoothing problem. Thus, a better prosodic model is required to improve the natural variability of the synthesized speech. This study exploits a hybrid method to alleviate this problem by combining the statistical and the template-based unit selection methods. First, a two-level clustering approach is proposed to obtain representative prosodic patterns (denoted by codewords) of the hierarchical prosodic structure modeled by a modified Fujisaki model. The prosodic codewords are then used to represent the prosody of each sentence in the parallel corpus consisting of the real speech corpus and the synthesized counterpart obtained from the HTS. The synthesized speech utterance is then used as the query for retrieving the prosodic codewords of the utterances in the synthesized corpus. The retrieved synthesized prosodic codewords are mapped to the prosodic codewords of the real speech based on linear mapping rules obtained from the parallel corpus. The prosodic codeword language models for prosodic word and prosodic phrase are employed respectively to choose the optimal codeword sequence of the real speech. Finally, the most likely sequence of prosodic codewords can be obtained based on the NURBS-based continuity measure for synthesizing speech with natural prosody. The experimental results of subjective and objective tests demonstrate that the proposed prosodic model substantially improves naturalness of the intonation of the synthesized speech compared to that of the HMM-based method.
N ov 2 00 0 Functional Renormalization Prediction of Rupture

We develop theoretical formulas for the prediction of the ru pture of systems which are known to exhibit a critical behavior, based solely on the knowledge of the early time evo lution of an observable, such as the acoustic emission rate a s a function of time or of stress. From the parameterization of such early time evolution in terms of a low-order polynomial , we use the functional renormalization approach introduced by Yukalov and Gluzman to transform this polynomial into a function which is asymptotically a power law. The value of t he critical timetc, conditioned on the assumption that tc exists, is thus determined from the knowledge of the coeffici nts of the polynomials. We test with success this predictio n scheme with respect to the order of the polynomials and as a fu nction of noise.
of Career Concerns : Theories and Empirics

The paper conducts a literature review on the topic of career concerns covering both theory and empirics. Career concerns describe a class of dynamic games with asymmetric information, endogenous feedback and reputational concerns. As a mixture of adverse selection and moral hazard, the principal-agent models of career concerns are grouped into three categories based on different interpretation of the agent’s type: productivity, taste and preferences, and expertise. Career concerns possess explanatory power in many aspects of real life, from labor markets to social media, and from financial industries to political institutions.
On the Credibility of Punishment in Repeated Social Dilemma Games

Various experimental studies have shown that the availability of a punishment option can increase the prevalence of cooperative behaviour in repeated social dilemmas. A punishment option should only matter if it is a credible threat. We investigate if the degree of credibility depends on standard strategic equilibrium considerations (i.e. SPNE or NE logic) or stems from a non-strategic motivation such as reciprocity. We find that for punishment to be credible non-strategic motivations are sufficient and that subgame perfection does not further improve credibility.
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This thesis investigates the idea of using phoneme recognition as a telephone communication aid aimed at hearing-impaired people. A laboratory ASR system has been developed with which on-line trials (user studies) have been conducted in order to investigate and evaluate the idea of using state-of-the-art phoneme recognition as a " hearing aid ". Results from the on-line trials indicate that a significant improvement in communication quality may be achieved when using the phoneme recognition aid. The trials show an average 76% decrease in misunderstood words and an average 21% increase in communication speed when using the phoneme recognition aid. I would like to thank my supervisors at TMH/KTH, Mats Blomberg and Kjell Elenius for their help and continuous encouragement during this work, and my supervisor Lars Borin at the Department of Linguistics, Uppsala University for valuable feedback on the report and for his input regarding measures of significance. I also want to thank Anders Torberger at Polycom AB for giving me the opportunity to work with an inspiring project. A huge thank you to Håkan Melin for his untiring readiness in helping me out with Atlas, HMM theory, HTK,…. Many thanks also to: Giampiero Salvi for valuable help with HTK; Karl-Erik Spens for introducing me to the Speech Tracking procedure; Martin Dahlquist for his help with programming the simulation of the hearing impairment, and for valuable hints on methodology; Markku Haapakorpi for helping me out with numerous hardware issues; Botond Pakus, Kåre Sjölander and Jonas Beskow for hints on everything from tcsh programming to speaker adaptation. Thanks also to the rest of the staff at TMH for making this an instructive and pleasant time. Finally, many thanks to all of you who volunteered as subjects in the on-line experiments. 3UHIDFH This work constitutes phase two in the CTT 1 project " HörStöd " – a collaboration between the Department of Speech, Music and Hearing (TMH) at KTH and Polycom Technologies AB. The first phase (Sahlin, forthcoming), which was carried out at TMH in the fall of 1999, dealt with readability of phoneme strings. In that work off-line experiments were conducted, investigating the possibility of using the output of a phoneme recognizer as an aid in interpreting distorted (low pass filtered) speech. It also involved the development of a spelling dictionary word recognizer. The work described in this thesis is a continuation of the phoneme recognition part of the first phase. …
Principles of Cortical Processing Applied to and Motivated by Artificial Object Recognition

In this paper we discuss the biological plausibility of the object recognition system described in detail in (Krüger, Peters and v.d. Malsburg, 1996). We claim that this system realizes the following principles of cortical processing: hierarchical processing, sparse coding, and ordered arrangement of features. Furthermore, our feature selection is motivated by response properties of neurons in striate cortex and by Biederman’s theory of object representation on higher stages of visual processing (Biederman, 1987). Inspired by the current discussion about aspects of cortical processing, we hope to derive more efficient algorithms. By discussing the functional meaning of these aspects in our object recognition system, we hope to attain a deeper understanding of their meaning for brain processing.
Breeding a diversity of Super Mario behaviors through interactive evolution

Creating controllers for NPCs in video games is traditionally a challenging and time consuming task. While automated learning methods such as neuroevolution (i.e. evolving artificial neural networks) have shown promise in this context, they often still require carefully designed fitness functions. In this paper, we show how casual users can create controllers for Super Mario Bros. through an interactive evolutionary computation (IEC) approach, without prior domain or programming knowledge. By iteratively selecting Super Mario behaviors from a set of candidates, users are able to guide evolution towards behaviors they prefer. The result of a user test show that the participants are able to evolve controllers with very diverse behaviors, which would be difficult through automated approaches. Additionally, the user-evolved controllers perform as well as controllers evolved with a traditional fitness-based approach in terms of distance traveled. The results suggest that IEC is a viable alternative in designing diverse controllers for video games that could be extended to other games in the future.