Predicting the spontaneous termination of atrial fibrillation based on poincare section in the electrocardiogram phase space

Atrial fibrillation (AF) is a commonly encountered cardiac arrhythmia. Predicting the conditions under which AF terminates spontaneously is an important task that would bring great benefit to both patients and clinicians. In this study, a new method was proposed to predict spontaneous AF termination by employing the points of section (POS) coordinates along a Poincare section in the electrocardiogram (ECG) phase space. The AF Termination Database provided by PhysioNet for the Computers in Cardiology Challenge 2004 was applied in the present study. It includes one training dataset and two testing datasets, A and B. The present investigation was initiated by producing a two-dimensional reconstructed phase space (RPS) of the ECG. Then, a Poincare line was drawn in a direction that included the maximum point distribution in the RPS and also passed through the origin of the RPS coordinate system. Afterward, the coordinates of the RPS trajectory intersections with this Poincare line were extracted to capture the local behavior related to the arrhythmia under investigation. The POS corresponding to atrial activity were selected with regard to the fact that similar ECG morphologies such as P waves, which are corresponding to atrial activity, distribute in a specific region of the RPS. Thirteen features were extracted from the selected intersection points to quantify their distributions. To select the best feature subset, a genetic algorithm (GA), in combination with a support vector machine (SVM), was applied to the training dataset. Based on the selected features and trained SVM, the performance of the proposed method was evaluated using the testing datasets. The results showed that 86.67% of dataset A and 80% of dataset B were correctly classified. This classification accuracy is in the same range as or higher than that of recent studies in this area. These results show that the proposed method, in which no complicated QRST cancelation algorithm was used, has the potential to predict AF termination.     

Nanomembrane‐Based,Thermal‐Transport Biosensor for Living Cells

Knowledge of materials' thermal‐transport properties, conductivity and diffusivity, is crucial for several applications within areas of biology, material science and engineering. Specifically, a microsized, flexible, biologically integrated thermal transport sensor is beneficial to a plethora of applications, ranging across plants physiological ecology and thermal imaging and treatment of cancerous cells, to thermal dissipation in flexible semiconductors and thermoelectrics. Living cells pose extra challenges, due to their small volumes and irregular curvilinear shapes. Here a novel approach of simultaneously measuring thermal conductivity and diffusivity of different materials and its applicability to single cells is demonstrated. This technique is based on increasing phonon‐boundary‐scattering rate in nanomembranes, having extremely low flexural rigidities, to induce a considerable spectral dependence of the bandgap‐emission over excitation‐laser intensity. It is demonstrated that once in contact with organic or inorganic materials, the nanomembranes' emission spectrally shift based on the material's thermal diffusivity and conductivity. This NM‐based technique is further applied to differentiate between different types and subtypes of cancer cells, based on their thermal‐transport properties. It is anticipated that this novel technique to enable an efficient single‐cell thermal targeting, allow better modeling of cellular thermal distribution and enable novel diagnostic techniques based on variations of single‐cell thermal‐transport properties.     

Synthesis and Physical Properties of Mn Doped ZnO Dilute Magnetic Semiconductor Nanostructures

Mn doped ZnO nanostructures have been prepared using low temperature simple, quick, and versatile synthesis approach. The structural, microstructural, and vibrational investigations reveal that as prepared nanostructures with low Mn doping concentration have single hexagonal phase and are grown along the preferred c-axis. The X-rays photoelectron spectroscopy demonstrates that the Mn ions are in mixed oxidation states for high doping concentration of Mn, while are in 2+ oxidation state for low concentration into ZnO lattice. The photoluminescence spectrum (PL) exhibits a significant red-shift of 22 nm in the optical band gap of doped ZnO and shows the improved luminescence properties, which makes it potential for its use in the photocatalyst, optoelectronics and solar cell nanodevices. Furthermore, the magnetic measurement of Mn doped ZnO nanostructures exhibits the ferromagnetism at room temperature.     

Localized Heat Therapy Improves Mitochondrial Respiratory Capacity but Not Fatty Acid Oxidation

AIM: Mild heat stress can improve mitochondrial respiratory capacity in skeletal muscle. However, long-term heat interventions are scarce, and the effects of heat therapy need to be understood in the context of the adaptations which follow the more complex combination of stimuli from exercise training. The purpose of this work was to compare the effects of 6 weeks of localized heat therapy on human skeletal muscle mitochondria to single-leg interval training. METHODS: Thirty-five subjects were assigned to receive sham therapy, short-wave diathermy heat therapy, or single-leg interval exercise training, localized to the quadriceps muscles of the right leg. All interventions took place 3 times per week. Muscle biopsies were performed at baseline, and after 3 and 6 weeks of intervention. Mitochondrial respiratory capacity was assessed on permeabilized muscle fibers via high-resolution respirometry. RESULTS: The primary finding of this work was that heat therapy and exercise training significantly improved mitochondrial respiratory capacity by 24.8 ± 6.2% and 27.9 ± 8.7%, respectively (p < 0.05). Fatty acid oxidation and citrate synthase activity were also increased following exercise training by 29.5 ± 6.8% and 19.0 ± 7.4%, respectively (p < 0.05). However, contrary to our hypothesis, heat therapy did not increase fatty acid oxidation or citrate synthase activity. CONCLUSION: Six weeks of muscle-localized heat therapy significantly improves mitochondrial respiratory capacity, comparable to exercise training. However, unlike exercise, heat does not improve fatty acid oxidation capacity.     

Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines

This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the predictor stage, machine-learning approaches of K-nearest neighbor (KNN) and support vector machines (SVM) are used to develop hybrid MTD-SVM and MTD-KNN prediction models. MTD-SVM model has provided the best values of accuracy, G-mean and Matthew's correlation coefficient of 96.71%, 96.70% and 71.98% for cancer/non-cancer dataset, breast/non-breast cancer dataset and colon/non-colon cancer dataset, respectively. We found that hybrid MTD-SVM is the best with respect to prediction performance and computational cost. MTD-KNN model has achieved moderately better prediction as compared to hybrid MTD-NB (Naïve Bayes) but at the expense of higher computing cost. MTD-KNN model is faster than MTD-RF (random forest) but its prediction is not better than MTD-RF. To the best of our knowledge, the reported results are the best results, so far, for these datasets. The proposed scheme indicates that the developed models can be used as a tool for the prediction of cancer. This scheme may be useful for study of any sequential information such as protein sequence or any nucleic acid sequence.     

Moisture Sensitive Smart Yarns and Textiles from Self‐Balanced Silk Fiber Muscles

Smart textiles that sense, interact, and adapt to environmental stimuli have provided exciting new opportunities for a variety of applications. However, current advances have largely remained at the research stage due to the high cost, complexity of manufacturing, and uncomfortableness of environment‐sensitive materials. In contrast, natural textile materials are more attractive for smart textiles due to their merits in terms of low cost and comfortability. Here, water fog and humidity‐driven torsional and tensile actuation of thermally set twisted, coiled, plied silk fibers, and weave textiles from these silk fibers are reported. When exposed to water fog, the torsional silk fiber provides a fully reversible torsional stroke of 547° mm^?1. Coiled‐and‐thermoset silk yarns provide a 70% contraction when the relative humidity is changed from 20% to 80%. Such an excellent actuation behavior originates from water absorption‐induced loss of hydrogen bonds within the silk proteins and the associated structural transformation, which are corroborated by atomistic and macroscopic characterization of silk and molecular dynamics simulations. With its large abundance, cost‐effectiveness, and comfortability for wearing, the silk muscles will open up additional possibilities in industrial applications, such as smart textiles and soft robotics.     

Insight into the Impact of Oxidative Stress on the Barrier Properties of Lipid Bilayer Models

As a new field of oxidative stress-based therapy, cold physical plasma is a promising tool for several biomedical applications due to its potential to create a broad diversity of reactive oxygen and nitrogen species (RONS). Although proposed, the impact of plasma-derived RONS on the cell membrane lipids and properties is not fully understood. For this purpose, the changes in the lipid bilayer functionality under oxidative stress generated by an argon plasma jet (kINPen) were investigated by electrochemical techniques. In addition, liquid chromatography-tandem mass spectrometry was employed to analyze the plasma-induced modifications on the model lipids. Various asymmetric bilayers mimicking the structure and properties of the erythrocyte cell membrane were transferred onto a gold electrode surface by Langmuir-Blodgett/Langmuir-Schaefer deposition techniques. A strong impact of cholesterol on membrane permeabilization by plasma-derived species was revealed. Moreover, the maintenance of the barrier properties is influenced by the chemical composition of the head group. Mainly the head group size and its hydrogen bonding capacities are relevant, and phosphatidylcholines are significantly more susceptible than phosphatidylserines and other lipid classes, underlining the high relevance of this lipid class in membrane dynamics and cell physiology.     

Influence of Y~(3+),Yb~(3+),Gd~(3+) cations on structural and electromagnetic properties of CuFe_2O_4 nanoferrites prepared via one step sol-gel method

Rare earths(REs) play a key role in distorting spinel structure by creating some defects at the lattice sites and make them suitable for magnetodielectric applications.In the present study,the nanoferrites of CuRE_(0.02)Fe_(1.98)O_4,where REs=Y~(3+),Yb~(3+),Gd~(3+),were prepared using one step sol-gel method.The prepared samples are copper ferrite(CFO),yttrium doped copper ferrite(Y-CFO),ytterbium doped copper ferrite(Yb-CFO) and gadolinium doped copper ferrite(Gd-CFO),respectively.The single-phase structure of all the REs doped nanoferrites was determined by X-ray diffraction(XRD) analysis.The porosity,agglomerations and grain size of the REs doped copper ferrite were examined using field emission scanning electron microscopy(FESEM) analysis.Fourier transform infrared spectroscopy(FTIR)elaborates the phase formation and environmental effects on the REs doped nanoparticles(NPs).The recorded room temperature M-H loops from a vibrating sample magnetometer(VSM) elucidate the magnetic properties of the REs doped spinel nanoferrites.The magnetic saturation(M_s) was calculated in the range of 23.08 to 51.78 emu/g.The calculated coercivity values(272.6 to 705.60 Oe) confirm the soft magnetic behavior of REs doped copper ferrites.Furthermore,the electromagnetic and dielectric properties were assessed using a Vector network analyzer(VNA) from 1 to 6 GHz.The permeability,permittivity,dielectric tangent loss and electric modulus of the REs doped spinel ferrites illustrate that the prepared NPs may be suitable for microwave and high frequency applications.     

BUILDING USER TASK SPACE BY MINING TEMPORALLY PROXIMATE DESKTOP ACTIONS

Awareness of the user's current context, that is, the task the user resides in, can allow for various ways of supporting their work. In this article we present a novel approach for mining user's regular tasks on the basis of temporal proximity of users’ desktop actions without user intervention in a completely automatic, unobtrusive, and unsupervised manner. The proposed method is based on time-based clustering of a user's desktop actions and, in contrast to previous approaches, it does not enforce fixed time constraints on the mined actions, and typical transition times, when they exist, emerge from the logged activity data for that specific user. The performance of our technique was evaluated on a large data set of 724 days of desktop work by five knowledge workers. The results showed that our approach performed very well and was able to cluster those temporally proximate user actions that commonly used fix time window techniques fail to deal with. Notably, the main improvement is in the recall of the tasks, where our approach recalled 10.18% more actions than the predefined time window technique.     

Thermoeconomic optimization of a shell and tube condenser using both genetic algorithm and particle swarm

This paper presents a thermoeconomic optimization of a shell and tube condenser, based on two new optimization methods, namely genetic and particle swarm (PS) algorithms. The procedure is selected to find the optimal total cost including investment and operation cost of the condenser. Initial cost includes condenser surface area and operational cost includes pump output power to overcome the pressure loss. Design parameters are tube number, number of tube pass, inlet and outlet tube diameters, tube pitch ratio and tube arrangements (30, 45, 60 and 90°). Therefore, shell diameter should be selected less than 7 m, tube length should be less than 15 m, and ratio of diameter to tube length should be in the range of 1/12 to 1/3. In addition, it is found that GA provides better results for computer CPU running time, compared to PS algorithm. Finally, a sensitivity analysis of design parameters at the optimal point is conducted. Results show that an increase in the tube number leads to decrease in the objective function first then it leads to a considerable increment in objective function.