Miracle-dz/UniFAR-FTUs huggingface dataset:
An Analysis of Resting-State Functional Transcranial Doppler Recordings from Middle Cerebral Arteries

Functional transcrannial Doppler (fTCD) is used for monitoring the hemodynamics characteristics of major cerebral arteries. Its resting-state characteristics are known only when considering the maximal velocity corresponding to the highest Doppler shift (so called the envelope signals). Significantly more information about the resting-state fTCD can be gained when considering the raw cerebral blood flow velocity (CBFV) recordings. In this paper, we considered simultaneously acquired envelope and raw CBFV signals. Specifically, we collected bilateral CBFV recordings from left and right middle cerebral arteries using 20 healthy subjects (10 females). The data collection lasted for 15 minutes. The subjects were asked to remain awake, stay silent, and try to remain thought-free during the data collection. Time, frequency and time-frequency features were extracted from both the raw and the envelope CBFV signals. The effects of age, sex and body-mass index were examined on the extracted features. The results showed that the raw CBFV signals had a higher frequency content, and its temporal structures were almost uncorrelated. The information-theoretic features showed that the raw recordings from left and right middle cerebral arteries had higher content of mutual information than the envelope signals. Age and body-mass index did not have statistically significant effects on the extracted features. Sex-based differences were observed in all three domains and for both, the envelope signals and the raw CBFV signals. These findings indicate that the raw CBFV signals provide valuable information about the cerebral blood flow which can be utilized in further validation of fTCD as a clinical tool.
The Ambiguity of Simplicity

A system's apparent simplicity depends on whether it is represented classically or quantally. This is not so surprising, as classical and quantum physics are descriptive frameworks built on different assumptions that capture, emphasize, and express different properties and mechanisms. What is surprising is that, as we demonstrate, simplicity is ambiguous: the relative simplicity between two systems can change sign when moving between classical and quantum descriptions. Thus, notions of absolute physical simplicity---minimal structure or memory---at best form a partial, not a total, order. This suggests that appeals to principles of physical simplicity, via Ockham's Razor or to the "elegance" of competing theories, may be fundamentally subjective, perhaps even beyond the purview of physics itself. It also raises challenging questions in model selection between classical and quantum descriptions. Fortunately, experiments are now beginning to probe measures of simplicity, creating the potential to directly test for ambiguity.
Measure of Quality of Source Separation for Sub- and Super-Gaussian Audio Mixtures

Conventional Blind Source Separation (BSS) algorithms separate the sources assuming the number of sources equals to that of observations. BSS algorithms have been developed based on an assumption that all sources have non-Gaussian distributions. Most of the instances, these algorithms separate speech signals with super-Gaussian distributions. However, in real world examples there exist speech signals which are sub-Gaussian. In this paper, a novel method is proposed to measure the separation qualities of both super-Gaussian and sub-Gaussian distributions. This study measures the impact of the Probability Distribution Function (PDF) of the signals on the outcomes of both sub and super-Gaussian distributions. This paper also reports the study of impact of mixing environment on the source separation. Simulation improves the results of the separated sources by 7 dB to 8 dB, and also confirms that the separated sources always have super-Gaussian characteristics irrespective of PDF of the signa ls or mixtures.
Identifying compositionally homogeneous and nonhomogeneous domains within the human genome using a novel segmentation algorithm

It has been suggested that the mammalian genome is composed mainly of long compositionally homogeneous domains. Such domains are frequently identified using recursive segmentation algorithms based on the Jensen–Shannon divergence. However, a common difficulty with such methods is deciding when to halt the recursive partitioning and what criteria to use in deciding whether a detected boundary between two segments is real or not. We demonstrate that commonly used halting criteria are intrinsically biased, and propose IsoPlotter, a parameter-free segmentation algorithm that overcomes such biases by using a simple dynamic halting criterion and tests the homogeneity of the inferred domains. IsoPlotter was compared with an alternative segmentation algorithm, DJS, using two sets of simulated genomic sequences. Our results show that IsoPlotter was able to infer both long and short compositionally homogeneous domains with low GC content dispersion, whereas DJS failed to identify short compositionally homogeneous domains and sequences with low compositional dispersion. By segmenting the human genome with IsoPlotter, we found that one-third of the genome is composed of compositionally nonhomogeneous domains and the remaining is a mixture of many short compositionally homogeneous domains and relatively few long ones.
Comparison Between Eigenface Epace and Wavelet Technique as Methods of Face Recognition

In this paper we compare between two methods which are used efficient in extracting feature spaces of human faces. These two methods are wavelets technique and eigenface space. Three Multi layer perceptron (MLP) neural networks with conjugate gradient learning are used in this paper as a recognizer. The inputs to the neural network are the features (coefficients) of these two methods extracted from face images at a particular scale. An accuracy of average of 95% is observed for test images under different environment conditions not included during training.
A modeling study to explain mathematical problem-solving performance through metacognition, self-efficacy, motivation, and anxiety

Many noncognitive constructs affect mathematical problem-solving performance. The aim of the present study is to investigate the direct and indirect effects of a number noncognitive constructs such as mathematics self-efficacy, mathematics anxiety, and metacognitive experience on the mathematical problem solving of middle-school students. The sample consisted of 517 seventh-grade Turkish students of whom 252 were male (49%) and 265 were females (51%). The instruments used in this study were a mathematical problem-solving performance test, a mathematics self-efficacy scale, a mathematics anxiety scale, a metacognitive experience scale, and a mathematics motivation scale. Two-stage structural equation modeling was used to examine the relationships between the noncognitive contructs and problem solving. Metacognitive experience was the only noncognitive construct, which had a direct effect on mathematical problem-solving performance; it also mediated the effects of self-efficacy, motivation, and mathematics anxiety on performance. Motivation and mathematics anxiety had an indirect effect on mathematical problem-solving performance through self-efficacy.
A power-aware multi harvester power unit with hydrogen fuel cell for embedded systems in outdoor applications

Energy availability and long term operation are key challenges for wireless sensor networks and the applications where embedded devices are battery-operated and they should operate unattended for tens of years. For this reason energy harvesting (EH) is becoming very important for powering ubiquitously deployed sensor networks and mobile electronics. In this paper we introduce a Smart Power Unit (SPU) for embedded systems which integrates energy harvesters from the sun and wind with hydrogen fuel cells especially designed for outdoor applications. The power unit can work as a standard battery or providing serial communication to exchange power information to achieve power management.Experimental results show the high efficiency (up to 90%) of the power conversion subsystem and the perpetual work. Deployment in a structural health monitoring in Switzerland demonstrates that perpetual energy sustainability is achievable in real-life conditions.
Cooperative Coding Using Parallel Concatenated LDPC Codes

When mobiles cannot support multiple antennas due to size or other constraints, cooperative diversity is an efficient way to provide uplink transmit diversity. This paper presents a novel cooperative coding scheme in use of rate-compatible parallel concatenated LDPC codes. We evaluate its performance in terms of bit error rate. Simulation results show our scheme provides significant performance gains for a variety of channel conditions. By allowing different code rates and partitions, parallel concatenated LDPC coded cooperation provides a great degree of flexibility to adapt to channel conditions
Evaluation of Gastroesophageal Reflux Disease Using the Bravo Capsule pH System

Gastroesophageal reflux disease (GERD) is a disease predominantly seen in the West but there is a rising trend in Asia. Ambulatory 24-hour catheter-based pH monitoring has been the de facto gold standard test for GERD that correlates symptoms with acid reflux episodes. However, drawbacks such as patients’ discomfort, and catheter displacement render the test as cumbersome and error-prone. The Bravo pH wireless system is designed to be user-friendly and has an added advantage of prolonged pH monitoring. The system is comparable to the catheter-based pH monitoring system in terms of diagnostic yield and symptom-reflux association. Indications include evaluation of patients with refractory GERD symptoms and prior to anti-reflux surgery. Bravo utilizes a wireless pH-sensing capsule with a complete prepackaged system, and a data processing software. The capsule may be positioned indirectly using endoscopic or manometric landmarks or under direct endoscopic guidance. Optimal threshold cut-off values are yet to be standardized but based on available studies, for the Asian population, it may be recommended for total % time pH < 4 of 5.8 over 48 hours. Cost is a limitation but capsule placement is relatively safe although technical failures may be seen in small percentage of cases.
Power aware routing protocol based on OLSR in Ad Hoc network

PA-OLSR makes an improvement on the routing algorithm, frame format, information storage table of OLSR. The key concept of PA-OLSR is finding a lowest energy cost between souce and destination, and choosing the longer lifetime nodes as MPR. PA-OLSR uses the power control mechanism based on signal attenuation rate that can estimation the minimum transmission power to neighbor nodes, and considers the energy loosing rate in the node lifetime assessment. According to the theoretic analysis, this dissertation gives the simulation models based on the OPNET Modeler platform, and analyzes three performances parameters: the success rate of the packet transmitting, end-to-end delay, and network lifetime. The simulation results show that PA-OLSR can improve the channel utilization and network lifetime.
Modeling and Solving Human-Robot Collaborative Tasks Using POMDPs

Robots have helped in the automation of repetitive tasks. However, they have limited roles as co-workers or assistants to humans because of their limited sensing and perception abilities, which in turn leads to limited inference capabilities. To help with a task a robot can learn to infer its human user’s state in a process, which is hidden information. This inference is multimodal and over a large set of observations. Previous dialogue modeling work [22] has framed collaborative tasks, but they do not consider physical state-action spaces. In this work we first model a joint task between a human and a robot as a POMDP [7] with turn taking and common goals. Next we present a POMDP solver capable of handling large state spaces and an infinite number of observations to perform multimodal inference. We compare this POMDP solver with other state of the art POMDP solvers. Further we used this solver for the collaborative task of changing a child’s diaper on a robotic platform.
Deleting species from model food webs

In natural biological communities the disappearance of one species can have knock-on effects causing extinction of further species from the food web. To investigate these effects we used an evolutionary model to assemble many independent simulated food webs, and studied their dynamical behaviour when one species was deleted. On average, only 2.1% of the remaining species went extinct as a result of the deletion. However, the probability of extinction of predators and indirect predators (more than one link up the chain) of the deleted species was several times larger than for an average species. The model allows predators to adapt their choice of prey in response to changing frequencies of the prey. It was found that the larger the proportion of the deleted species in the predator's diet, the greater its probability of extinction. The probability of extinction of prey of the deleted species was also significantly higher than for an average species. This is due to increased competition between prey species after removal of their predator. The effect was largest for prey species that formed an intermediate fraction of the diet of the deleted species. The number of further extinctions increased significantly with the number of links in the food web to the deleted species prior to deletion, and was also correlated with the bottom-up and top-down keystone species indices. We also considered which properties of the web as a whole influenced its robustness to species deletion. This revealed a significant correlation between ecosystem redundancy and deletion stability, but no clear relationship with complexity.
Wavelet Reduced Support Vector Regression for Efficient and Robust Head Pose Estimation

In this paper, we introduce concepts to reduce the computational complexity of regression, which are successfully used for Support Vector Machines. To the best of our knowledge, we are the first to publish the use of a cascaded Reduced Set Vector approach for regression. The Wavelet-Approximated Reduced Vector Machine classifiers for face and facial feature point detection are extended to regression for efficient and robust head pose estimation. We use synthetic data, generated by the 3D Morph able Model, for optimal training sets and demonstrate results superior to state-of-the-art techniques. The new Wavelet Reduced Vector Regression shows similarly good results on natural data, gaining a reduction of the complexity by a factor of up to 560. The introduced Evolutionary Regression Tree uses coarse-to-fine loops of strongly reduced regression and classification up to most accurate complex machines. We demonstrate the Cascaded Condensation Tracking for head pose estimation for a large pose range up to ±90 degrees on videostreams.
Predictors of Change in CD4 Lymphocyte Count and Weight among HIV Infected Patients on Anti-Retroviral Treatment in Ethiopia: A Retrospective Longitudinal Study

Background Antiretroviral treatment (ART) has been introduced in Ethiopia a decade ago and continues to be scaled up. However, there is dearth of literature on the impact of ART on changes in CD4 lymphocyte count and weight among patients on treatment. Objective To determine the predictors of change in CD4 lymphocyte count and weight among HIV/AIDS infected patients taking antiretroviral treatment in eastern Ethiopia. Methods A retrospective cohort study was conducted among HIV/AIDS patients taking ART from 2005 to 2010. A sample of 1540 HIV infected adult patients who started antiretroviral therapy in hospitals located in eastern Ethiopia were included in the study. The primary outcomes of interest were changes in CD4 count and weight. Descriptive statistics and multivariable regression analyses were performed to examine the outcomes among the cohort. Results Both the median CD4 lymphocyte counts and weight showed improvements in the follow up periods. The multivariate analysis shows that the duration of ART was an important predictor of improvements in CD4 lymphocyte count (beta 7.91; 95% CI 7.48–8.34; p 0.000) and weight (beta 0.15; 95% CI 0.13–0.18; p 0.000). Advanced WHO clinical stage, lower baseline CD4 cell count, and baseline hemoglobin levels were factors associated with decline in weight. Actively working patients had higher CD4 lymphocyte count and weight compared to those that were ambulatory (p<0.05). Conclusion We detected a substantial increment in weight and CD4 lymphocyte count among the patients who were taking ART in eastern Ethiopia. Patients who are of older age, with low initial CD4 lymphocyte count, late stage of the WHO clinical stages and lower hemoglobin level may need special attention. The reasons for the improved findings on CD4 count and weight throughout the five years of follow up merit further investigation.
Time-varying fuzzy sets in adaptive control

This paper deal with the use of fuzzy sets whose shape evolves as the error to construct a robust PDC fuzzy controller for nonlinear system in continuous time described by the T-S fuzzy model. This controller is based on time-Varying Fuzzy Sets (VFS) characterized by the displacement of the support points to both right and left side of the universe of discourse, and they are directed by a well-defined criterion. This note focuses only on the displacement of the midpoint of the universe. The functions defining these displacements are determined by an adaptive temporal Lyapunov function depending on the error, that is the difference between desired and current system response evolves.
The effect of takeovers on the fundamental value of acquirers

Abstract This paper develops a new methodology to examine the financial impact of acquisitions, designed to address whether takeovers yield a positive net present value for the acquiring company. Specifically, we employ the residual income valuation method to compare the fundamental value of the acquiring company before acquisition with the fundamental value after acquisition.We apply this methodology to 303 UK acquisitions completed during 1985–1996, and compare the results with the effects of takeover on profitability and short‐ and long‐run share returns. We find that the impact of acquisition on fundamental value is slightly negative but statistically insignificant. This result differs from the effect of takeover on profitability, which is significantly positive, and the effect of takeover on share returns, which is significantly negative.
Feature Extraction of Speech Signal and Heartbeat Detection in Angry Emotion Identification

Angry is one of emotions that play an essential role in decision making, perception, learning and more. This paper detects the angry emotion by analyzing and recognizing angry speech signal as well as detecting the heartbeat condition. The speech database was uttered by various speakers in different gender and emotions. For the analyzing experiment, several digital signal processing methods such as autocorrelation and linear predication technique was introduced to analyze the features. Then, Artificial Neural Network (ANN) was used to classify each parameter features such as mean fundamental frequency, maximum fundamental frequency, standard deviation fundamental frequency, mean amplitude, pause length ratio and first formant frequency to recognize the emotion. Meanwhile, a heartbeat monitoring circuit was developed to measure the heartbeat. The accuracy of the result has achieved over than 80 percent during emotional recognition test. This method can be used further to recognize angry emotion of patient during counseling session.
Influence of contrast on the spatial frequency tuning of neuronal populations in the cat visual thalamus

While spatial frequency tuning was traditionally thought to be independent of contrast, recent studies have demonstrated clear contrast-dependent changes in both thalamus and cortex. To investigate the consequences of these changes at the level of neuronal populations, we made simultaneous recordings from neighboring cat geniculate cells and measured spatial frequency tuning of each individual neurons and the neuronal populations at different contrasts. Increasing the contrast not only broadened the spatial frequency tuning of the individual cells, but also caused shifts in their optimal spatial frequencies that could be either towards lower or higher frequencies (peak shifts). Interestingly, these peak shifts were not random but depended on the optimal spatial frequency of the cell: cells with low optimal spatial frequencies ( 0.5 c/d) shifted towards higher frequencies. The value of peak shift was significantly correlated with the optimal spatial frequency of the cell measured at high contrast in our data and similar unreported correlations were found when we re-analyzed the thalamic and cortical data from previous studies. Our results indicate that increasing the contrast has a major effect on the spatial frequency tuning of cell populations within LGN and that this population tuning is broadened by two different mechanisms: tuning-broadening of single-cell spatial-frequency bandwidth and tuning-stretching of the cell-population bandwidth, the latter one caused by peak shifts in opposite directions of the spatial frequency spectrum. Weng, Jin, Yeh & Alonso, 2007 Page-3
0.9% saline is neither normal nor physiological

The purpose of this review is to objectively evaluate the biochemical and pathophysiological properties of 0.9% saline (henceforth: saline) and to discuss the impact of saline infusion, specifically on systemic acid-base balance and renal hemodynamics. Studies have shown that electrolyte balance, including effects of saline infusion on serum electrolytes, is often poorly understood among practicing physicians and inappropriate saline prescribing can cause increased morbidity and mortality. Large-volume (>2 L) saline infusion in healthy adults induces hyperchloremia which is associated with metabolic acidosis, hyperkalemia, and negative protein balance. Saline overload (80 ml/kg) in rodents can cause intestinal edema and contractile dysfunction associated with activation of sodium-proton exchanger (NHE) and decrease in myosin light chain phosphorylation. Saline infusion can also adversely affect renal hemodynamics. Microperfusion experiments and real-time imaging studies have demonstrated a reduction in renal perfusion and an expansion in kidney volume, compromising O2 delivery to the renal parenchyma following saline infusion. Clinically, saline infusion for patients post abdominal and cardiovascular surgery is associated with a greater number of adverse effects including more frequent blood product transfusion and bicarbonate therapy, reduced gastric blood flow, delayed recovery of gut function, impaired cardiac contractility in response to inotropes, prolonged hospital stay, and possibly increased mortality. In critically ill patients, saline infusion, compared to balanced fluid infusions, increases the occurrence of acute kidney injury. In summary, saline is a highly acidic fluid. With the exception of saline infusion for patients with hypochloremic metabolic alkalosis and volume depletion due to vomiting or upper gastrointestinal suction, indiscriminate use, especially for acutely ill patients, may cause unnecessary complications and should be avoided. More education regarding saline-related effects and adequate electrolyte management is needed.