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In this article, a novel dual active clamp converter with high voltage gain is proposed for dc–dc applications. The active clamps’ switches turn on and off under zero-current switching (ZCS). In addition, the main switch turns on under ZCS condition, as well. Therefore, switching losses are significantly reduced. The converter is also capable of operating under quasi-resonance (QR) mode. In this mode, switching losses are reduced further by lowering the voltage and current, at which the main switch turns off . In comparison with the conventional interleaved converter, the voltage gain of the proposed converter is almost the same, but the number of semiconductors and switching loss are significantly reduced. The switching frequency of the active clamps’ switches is half of the main switching frequency. The operation principles of the proposed converter are studied in both pulsewidth modulation and QR modes, and the advantages are investigated. A 200-W prototype is implemented to validate the desired functionality of the converter, and experimental results are compared in both modes.

A novel semi-isolated high step-up double-input converter with current-fed inputs is introduced in this study. The proposed converter can operate in double-input mode and single-input mode. It can manage the collected power from both inputs effectively. In addition, it makes a gentle transition between the modes, without the need for an abrupt change in pulse pattern, and does not utilise a breaker switch. Meanwhile, the converter preserves soft-switching as well as a few number of semiconductors (three switches and three diodes). These items have improved the efficiency of the converter to 94.5%. Moreover, it is a high-voltage gain (more than 13). Also, both input ports are current-fed, so the input currents are smoothed. These features make the converter compatible with hybrid renewable energy applications. Furthermore, all components are engaged in both modes, which results in an improved component's utilisation factor. A thorough analysis has been conducted to prove the characteristics mentioned above of the proposed converter. Theoretical analysis has been verified by simulation and experimental results of a 200 W prototype.

A new partly isolated three-port converter is introduced in this study for hybrid energy applications. Two boost circuits form the main input port and a bidirectional battery port of the converter. Therefore, both of them are of a current-fed type, making the converter more suitable for renewable energy applications. In addition, the boost circuits are benefited from a mutual active clamp circuit. The circuit in cooperation with the leakage inductance of transformers provides soft switching, while employing a few number of semiconductors. Furthermore, on the secondary side, two voltage-doubler rectifiers are merged. As a result, the converter employs less number of components, which participate in all power conversion modes. Since most of the renewable energy sources have a relatively low voltage level, the converter retains high voltage gain. These features have resulted in an efficient and inexpensive converter. A thorough analysis has been made and justified by simulation and experimental results.

Before the 33rd Annual International Society for Heart and Lung Transplantation conference, there was significant intercenter variability in definitions of primary graft dysfunction (PGD). The incidence, risk factors, and outcomes of consensus-defined PGD warrant further investigation. We retrospectively examined 448 adult cardiac transplant recipients at our institution from 2005 to 2017. Patient and procedural characteristics were compared between PGD cases and controls. Multivariable logistic regression was used to model PGD and immediate postoperative high-inotrope requirement for hypothesized risk factors. Patients were followed for a mean 5.3 years to determine longitudinal mortality. The incidence of PGD was 16.5%. No significant differences were found with respect to age, sex, race, body mass index, predicted heart mass mismatch, pretransplant amiodarone therapy, or pretransplant mechanical circulatory support (MCS) between recipients with PGD versus no PGD. Each 10 minute increase in ischemic time was associated with 5% greater odds of PGD (OR = 1.05 [95% CI, 1.00-1.10]; p = 0.049). Pretransplant MCS, predicted heart mass mismatch ≥30%, and pretransplant amiodarone therapy were associated with high-immediate postoperative inotropic requirement. The 30 day, 1 year, and 5 year mortality for patients with PGD were 28.4%, 38.0%, and 45.8%, respectively, compared with 1.9%, 7.1%, and 21.5% for those without PGD (log-rank, p < 0.0001). PGD heralded high 30 day, 1 year, and 5 year mortality. Pretransplant MCS, predicted heart mass mismatch, and amiodarone exposure were associated with high-inotrope requirement, while prolonged ischemic time and multiple perioperative transfusions were associated with consensus-defined PGD, which may have important clinical implications under the revised United Network for Organ Sharing allocation system.

Reliable prediction of epileptic seizures is of prime importance as it can drastically change the quality of life for patients. This study aims to propose a real-time low computational approach for the prediction of epileptic seizures and to present an efficient hardware implementation of this approach for portable prediction systems. Three levels of feature extraction are performed to characterize the pre-ictal activities of the EEG signal. In the first-level, the line length algorithm is applied to the pre-ictal region. The features obtained in the first-level are mathematically integrated to extract the second-level features and then the line lengths of the second-level features are calculated to obtain our third-level feature. The third-level information is compared with predefined threshold levels to make a decision on whether the extracted characteristics are relevant to a seizure occurrence or not. The validity of this algorithm was tested by EEG recordings in the CHB-MIT database (97 seizures, 834.224 h) for 19 epileptic patients. The results showed that the average sensitivity was 90.62%, the specificity was 88.34%, the accuracy was 88.76% with the average false prediction rate as low as 0.0046 h−1, and the average prediction time was 23.3 min. The low computational complexity is the superiority of the proposed approach, which provides a technologically simple but accurate way of predicting epileptic seizures and enables hardware implantable devices.

In this paper, a novel single-switch high step-up DC/DC converter based on SEPIC topology is presented. The proposed converter operates in quasi-resonant (QR) mode, which comes with many advantages. There are soft-switching conditions in the operation of this converter. In such a way that the power switch turns on under zero-current-switching condition. Besides, the diodes currents are zero during their switching process (ZCS). This will greatly reduce switching losses and increase the efficiency of the converter. Also, due to the use of coupling inductance capacity, the converter voltage gain is high compared to the converters provided so far. In addition, the voltage gain of this converter is completely independent of leakage inductance value. The operating principles of this converter is studied in detail. In order to verify the theoretical discussion, the simulation process is performed in Simulink/MATLAB software. The simulation results show the accuracy of the converter specifications, well.

Objective To report the establishment of a new center for deep brain stimulation (DBS) as a surgical treatment for Parkinson disease and the surgical outcomes, from 2014 to 2017 in Shiraz, Southern Iran. Methods A new treatment program was established in Shiraz through a multidisciplinary team in 2014. Thirty-four patients underwent implantation of subthalamic nucleus (STN) electrodes during the last 3 years. Twenty-five patients fulfilled the minimum 6-month follow-up criteria. The baseline Unified Parkinson Disease Rating Scale (UPDRS) was assessed 1 month before surgery in both off-medication and on-medication states by a movement disorder neurologist. To evaluate the outcomes, subscores of the UPDRS were assessed in all patients before surgery and at least 6 months after the operation. Results All 25 patients had advanced Parkinson disease categorized as stage 3 or 4 using the Hoehn and Yahr scale. STN DBS resulted in a dramatic improvement in motor function of most patients. A reduction in dopaminergic medication dosage (average 60% reduction) was observed. The mean improvement was 40% in UPDRS II and 67% in UPDRS III. No surgical or hardware complications were observed. Stimulation-related adverse effects, including increased falling and worsening of speech, occurred in a few patients after surgery. Most of the patients experienced weight gain after surgery. Conclusions Bilateral STN DBS is a satisfactory and safe treatment for carefully selected patients with advanced Parkinson disease. According to the results, the procedure can be performed safely and with comparable results in developing countries around the world.

Selective Dorsal Rhizotomy (SDR) is a neurosurgical procedure currently used as a surgical treatment of children with spasticity in their legs. In SDR, the dorsal roots from L2 to S1 or S2 is partially sectioned. The primary goal of SDR is to reduce spasticity and improve the range of movement with preservation of muscle strength. The dorsal roots involved in spasticity are identified on the basis of intraoperative electrophysiological stimulation. Currently, SDR is most commonly performed for the treatment of spastic cerebral palsy in children. We report an 8-year-old child with spastic cerebral palsy who underwent intraoperative neurophysiology monitoring during SDR for treating his spasticity. Before the operation, patient’s examination revealed more spasticity at the lower extremities, mild spasticity at the upper extremities, and occurrence of fixed contracture of his both ankle joints. Intraoperative neuromonitoring (consisting of motor evoked als, direct nerve root stimulation, and free run electromyography) was performed during the operation. Electrophysiological monitoring was initially used to help differentiate between the ventral and dorsal roots and cutting the abnormal sensory rootlets. After the operation, his motor power of the lower extremities in the proximal and distal muscles was 4 out of 5, his saddle sensation became normal, and there was no urinary and stool incontinency. Four weeks after the surgery, he could walk about 10 m without help. His examination at 2 and 4 weeks after the operation showed was no sign of sensory deficits, urinary, or stool incontinency. Two months after the operation, the patient could walk independently without help while before the operation, he could not.

The representation of visual objects in primate brain is distributed and multiple neurons are involved in encoding each object. One way to understand the neural basis of object representation is to estimate the number of neural dimensions that are needed for veridical representation of object categories. In this study, the characteristics of the match between physical-shape and neural representational spaces in monkey inferior temporal (IT) cortex were evaluated. Specifically, we examined how the number of neural dimensions, stimulus behavioral saliency and stimulus category selectivity of neurons affected the correlation between shape and neural representational spaces in IT cortex. Single-unit recordings from monkey IT cortex revealed that there was a significant match between face space and its neural representation at lower neural dimensions, whereas the optimal match for the non-face objects was observed at higher neural dimensions. There was a statistically significant match between the face and neural spaces only in the face-selective neurons, whereas a significant match was observed for non-face objects in all neurons regardless of their category selectivity. Interestingly, the face neurons showed a higher match for the non-face objects than for the faces at higher neural dimensions. The optimal representation of face space in the responses of the face neurons was a low dimensional map that emerged early (~150 ms post-stimulus onset) and was followed by a high dimensional and relatively late (~300 ms) map for the non-face stimuli. These results support a multiplexing function for the face neurons in the representation of very similar shape spaces, but with different dimensionality and timing scales.

A quasi-resonant dc–dc converter with high voltage gain and low current stresses on switches is proposed in this paper. This converter preserved inherent advantages of current-fed structures, for instance, zero magnetizing dc offset, low input ripple, and low transformer turn ratio. Moreover, by employing the active-clamp circuit, the voltage spikes across the main switch, due to the existence of leakage inductance of the isolating transformer, is absorbed, and switches work in zero voltage switching. Since quasi-resonant switching strategy is employed, turn-off current (TOC) and losses of switches are considerably reduced. Because of zero current switching (ZCS), reverse recovery problem of diodes is alleviated. Experimental results on a 150-W prototype are provided to validate the proposed concept.

This study describes a duty-cycle-controlled resonant dual-half-bridge converter with multifunctional capacitors for enhancing the voltage level of fuel cell and photovoltaic sources to 380 V. Owing to the incorporation of dc-link capacitors and leakage inductance into two various resonant circuits, both switches turn-on under the zero-voltage-switching circumstance and turn-off with low current because of quasi-resonant operation. Since the currents of diodes are controlled by the leakage inductances of transformers, it is not obligatory for a designer to employ the diodes with reverse-recovery current specification; consequently, less expensive diodes can be adopted. The complementary effects of series-connected secondary windings of transformers and switched-capacitor circuits result in forming the balanced voltage multiplier stage, augmenting the voltage conversion ratio substantially without the need for utilising a transformer having higher turns ratio; so, one of the magnificent factors of growth of the conduction losses has been avoided. Ultimately, the results of the laboratory prototype operating with 58 kHz switching frequency, 18 V input voltage, 380 V output voltage, and 500 W output power prove that the proposed topology would be proficient to fulfil its function in systems using distributed generation resources.

This study aims to develop a semi-automatic system for brain tumor segmentation in 3D MR images. For a given image, noise was corrected using SUSAN algorithm first. A specific region of interest (ROI) that contains tumor was identified and then the intensity non-uniformity in ROI was corrected via the histogram normalization and intensity scaling. Each voxel in ROI was presented using 22 features and then was categorized as tumor or non-tumor by a multiple-classifier system. T1- and T2-weighted images and fluid-attenuated inversion recovery (FLAIR) were examined. The system performance in terms of Dice index (DI), sensitivity (SE) and specificity (SP) was evaluated using 150 simulated and 30 real images from the BraTS 2012 database. The results showed that the presented system with an average DI > 0.85, SE > 0.90, and SP > 0.98 for simulated data and DI > 0.80, SE > 0.84, and SP > 0.98 for real data might be used for accurate extraction of the brain tumors. Moreover, this system is 6 times faster than a similar system that processes the whole image. In comparison with two state-of-the-art tumor segmentation methods, our system improved DI (e.g., by 0.31 for low-grade tumors) and outperformed these algorithms. Considering the costs of imaging procedures, tumor identification accuracy and computation times, the proposed system that augmented general pathological information about tumors and used only 4 features of FLAIR images can be suggested as a brain tumor segmentation system for clinical applications.

This paper presents a 4th order CLCL resonant converter that has a simple and unique design, and also it has the constant current power supply characteristic that is used for many constant current applications in various laboratories and industries. This converter is designed with Immittance two inductors and two capacitors, to property for constant current power supply. A detailed analysis, design and control process of a 200w converter is given, and simulation results are verified with results of a constructed converter. This converter with its unique structure, a combination of series and parallel resonant converter, has the advantages of both. As a constant current supply, CLCL resonant converter has the advantages of rigidity against short circuit even without a controller, easy operation in parallel mode, low circulating currents and high efficiency due to its soft switching operation. For this converter, leakage and magnetizing inductance of a transformer can be used as a part in the resonance network, and it decreases the converter size. Furthermore, series capacitor, eliminates the DC component and prevents the transformer saturation in unbalance conditions. With fixed-frequency performance, filter design also will be easier. Considering these advantages, the proposed topology can be used in a variety of applications such as magnetic power supplies, capacitor charging power supplies and agitator for laser diodes.

Summary This paper presents a high step-up soft switched dc–dc converter having the feature of current ripple cancelation in the input stage that is specialized for power conditioning of fuel cell systems. The converter comprises a special half-bridge converter and a rectifier stage based upon the voltage-doubler circuit, in which the coupled-inductor technology is amalgamated with switched-capacitor circuit. The input current with no ripple is the principal characteristics of this topology that is achieved by utilizing a small coupled inductor. In addition, the low clamped voltage stress across both power switches and output diodes is another advantage of the proposed converter, which allows employing the metal–oxide–semiconductor field-effect transistors with minuscule on-state resistance and diodes with lower forward voltage-drop, and thereby, the semiconductors' conduction losses diminish considerably. The inherent nature of this topology handles the switching scheme based on the asymmetrical pulse width modulation in order for switches to establish the zero voltage switching, leading to lower switching losses. Besides, because of the absence of the reverse-recovery phenomenon, all diodes turn off with zero current switching. At last, a 250-W laboratory prototype with the input voltage 24 V and output voltage 380 V is implemented to verify the especial features of the proposed converter. Copyright © 2015 John Wiley & Sons, Ltd.

A soft-switched dual-boost coupled-inductor-based converter is proposed which possesses an intrinsic advantage, in terms of transferring the energy directly to output to provide the essential voltage and power for load. The fabulous characteristic of the proposed structure, the combination of forward and flyback converter, makes it possible to utilise one magnetic core for two coupled inductors, advancing the power density. Another implication of proposed converter is the fact that leakage inductances pave the way for the zero-current-switching implementation by confining the diodes current slope during turn-off period. As regards the voltage conversion ratio, the secondary windings of the coupled inductors operate in series with the capacitors of both voltage-doubler stage and capacitor-diode stages; consequently, designer is under no obligation to use coupled inductors with extreme turn ratio. Concerning the mentioned features of converter besides its high-efficiency power conversion over a broad range of input voltage, the proposed structure is well suited for the purpose of high step-up dc–dc converter. Lastly, the results of laboratory prototype, working with switching frequency of 50 kHz and output voltage 380 V, are convincingly in line with the mathematical analysis.

This study presents a new high step-up resonant converter for renewable energy applications. Since, renewable sources introduce relatively low voltage, it is necessary to step up the voltage in order to be used in regular applications. The proposed converter has employed a coupled inductor and a switched capacitor to step up the output voltage. An active clamp circuit has been adopted to guarantee zero voltage switching for the switches. Also, the clamp capacitor has been implemented in series with the output capacitor so as to more extend output voltage. Furthermore, the converter operates in resonant mode, resulting in lower switching losses, zero current switching (ZCS) for diodes with low di/dt, and high voltage gain. The proposed converter has been analyzed thoroughly and the results have been validated through simulation.

A new high step-up DC-DC converter with voltage quadrupler (HCVQ) for Fuel Cell (FC) application is presented in this paper. This converter employs two Quasi-Resonant (QR) and Pulse Width Modulation (PWM) schemes, and the converter's performance in these modes is compared. In both schemes, switches work under Zero Voltage Switching (ZVS) condition, and output diodes work under Zero Current Switching (ZCS). As a result of incorporating the resonant operation for main switch in QR scheme, its turn-off voltage and current is lower than PWM scheme, so total switching loss is reduced, and switches have approximately the same conduction losses. The proposed converter in QR scheme operates in Discontinuous Conduction Mode (DCM). Also it has a higher voltage gain and efficiency in comparison with the one using PWM scheme. Moreover, this converter is compared with conventional half-bridge current-fed converter with voltage doubler (HCVD). Finally, two 150 W HCVQ with QR and PWM schemes and one HCVQ are simulated to validate the theoretical and simulation results.

In this paper a dc/dc converter with large boost ratio arising from isolated interleaved half-bridge converter is proposed that its operation is based on the combination of the Forward and Flyback converters having the merit of minimizing the core size of coupled-inductors. The drawbacks of conventional boost converter do not pose a major problem in the proposed converter because of employing the active clamp structure with asymmetrical pulse width modulation, which limits a suddenly huge increase in the voltage stress of switches and makes the soft switching possible. The secondary windings of coupled inductors operate as voltage sources in series with the voltage doubler capacitors, so the voltage conversion ratio heightens; consequently, the designer is under no obligation to use the coupled inductors with extreme turn ratio. At final, a 500 W laboratory prototype operating at switching frequency 50 kHz and output voltage 380 V by utilizing a input source 20 V is simulated to prove the theoretical analysis.

Background Conventional methods for spike train analysis are predominantly based on the rate function. Additionally, many experiments have utilized a temporal coding mechanism. Several techniques have been used for analyzing these two sources of information separately, but using both sources in a single framework remains a challenging problem. Here, an innovative technique is proposed for spike train analysis that considers both rate and temporal information. Methodology/Principal Findings Point process modeling approach is used to estimate the stimulus conditional distribution, based on observation of repeated trials. The extended Kalman filter is applied for estimation of the parameters in a parametric model. The marked point process strategy is used in order to extend this model from a single neuron to an entire neuronal population. Each spike train is transformed into a binary vector and then projected from the observation space onto the likelihood space. This projection generates a newly structured space that integrates temporal and rate information, thus improving performance of distribution-based classifiers. In this space, the stimulus-specific information is used as a distance metric between two stimuli. To illustrate the advantages of the proposed technique, spiking activity of inferior temporal cortex neurons in the macaque monkey are analyzed in both the observation and likelihood spaces. Based on goodness-of-fit, performance of the estimation method is demonstrated and the results are subsequently compared with the firing rate-based framework. Conclusions/Significance From both rate and temporal information integration and improvement in the neural discrimination of stimuli, it may be concluded that the likelihood space generates a more accurate representation of stimulus space. Further, an understanding of the neuronal mechanism devoted to visual object categorization may be addressed in this framework as well.