Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiband treatment of quantum transport in interband tunnel devices.

We describe a method for computing transmission coefficients for multiband tight-binding band-structure models. In this method, the transmission probability can be calculated simply by solving a system of linear equations representing the tight-binding form of the Schro¨dinger equation over a finite region of interest, with specially formulated boundary and inhomogeneous terms to account for the effects of the incoming and outgoing plane-wave states. In addition to being efficient, and simple to implement, our method is numerically stable in treating device structures with large active regions, and therefore capable of modeling realistic band-bending effects. Using this method, we examine transport properties in InAs/GaSb/AlSb-based interband tunnel structures with a realistic band-structure model. We compare our results with calculations obtained with a two-band model, which includes only the lowest conduction band and the light-hole band. We find that while the primary interband transport mechanism arises from the coupling between the InAs conduction-band states and GaSb light-hole states, in device structures containing GaSb quantum wells, the inclusion of heavy-hole states can introduce additional transmission resonances and substantial hole-mixing effects. These effects are found to have a significant influence on the current-voltage characteristics of interband devices.
Combining Gabor filtering and classification dictionaries learning for fingerprint enhancement

This study presents a new method for enhancing fingerprint image. The process of the enhancement is divided into two phases: fingerprint is first enhanced using Gabor filtering and then the enhanced fingerprint can be further enhanced by using sparse representation with the priori information of ridge pattern based on classification dictionaries learning. In the second stage, first, the orientations of fingerprint patches are estimated by the weighted linear projection analysis and the quality of patches are evaluated by the coherence of point orientations. Second, the training patches are classified into eight groups based on their own orientations, and the training samples of each class are selected from candidate patches by their own quality. The corresponding classification dictionaries are learned in frequency domain. Finally, the fingerprint image is enhanced based on spectra diffusion by using classification dictionaries learning. The experiments are carried out using various fingerprint enhancement methods. The experiments show that the proposed method achieves better results in comparison with other methods, and can significantly improve the performance of automatic fingerprint identification system.
Exercise Training Enhances Relaxation of the Isolated Guinea‐Pig Saphenous Artery in Response to Acetylcholine

The effects of exercise training were investigated on the vascular responses in the isolated guinea‐pig saphenous artery. Exercising animals swam 5 days week‐1 for 6 weeks (60 min day‐1 for weeks 1 and 2; 75 min day‐1 for weeks 3 and 4; 90 min day‐1 for weeks 5 and 6), while control animals were placed into shallow water for the same duration. Trained animals had significantly higher ventricular:body weight ratios, increased citrate synthase activity in the latissimus dorsi, and enhanced Na+ pump concentrations in the latissimus dorsi and gastrocnemius muscles (P < 0.05). In vitro isometric techniques were used to measure constriction and relaxation responses of saphenous artery rings from trained and control animals. There were no significant differences in the constriction responses to KCl (50 mm) and phenylephrine (0.3‐100 μM) in arterial rings from control versus trained animals. Relaxation responses to acetylcholine (10 μM; ACh‐relaxation), following preconstriction with phenylephrine (10 μM), were significantly enhanced in rings from trained animals (P < 0.05). Acetylcholine relaxed the vessels to 47 ± 6% (control) and 18 ± 3% (trained) of the preconstriction responses to phenylephrine. The nitric oxide synthase inhibitor N G‐nitro‐L‐arginine (L‐NA; 50 μM) significantly attenuated the ACh‐relaxation in control and trained animals (P < 0.05). The effect of L‐NA on the ACh‐relaxation was significantly larger in trained (change in ACh‐relaxation with L‐NA = 29 ± 9%) than control (14 ± 3%) animals (P < 0.05). In conclusion, exercise training enhanced the ACh‐relaxation of the isolated guinea‐pig saphenous artery. Inhibition of nitric oxide synthase attenuated the ACh‐relaxation of rings from control and trained animals, but this effect was significantly larger in the vessels from trained animals. These results are consistent with the idea that nitric oxide could contribute to the enhanced ACh‐relaxation of the saphenous artery with exercise training.
Switching time analysis for non-uniform serpentine flexure based RF-MEMS switches

In this paper we present, the switching time analysis for non-uniform serpentine flexure based capacitive radio frequency (RF) micromechanical systems (MEMS) switches. The general equations of spring constant and switching time are developed analytically for the proposed switch and further used to improve the switching time of serpentine flexure based RF MEMS switches. The calculated switching time for 640 μm long fixed-fixed beam is found to be 1-4 millisecond with varying span beam length of 100 to 280 μm.
Learning by Exporting: Do Firm Characteristics Matter? Evidence from Argentinian Panel Data

We identify characteristics that affect firms' ability to learn from their export activities. Our analysis is based on a panel of Argentinian firms spanning 1992-2001 and we employ Granger causality tests, propensity score matching techniques and GMM regressions. The characteristics we find to be important are: foreign ownership, intensive use of imported inputs, a skilled workforce and small firm size. Finally, firms that are new to exporting seem to experience particularly high productivity gains but begin enjoying them before entering into the export market.
L/M Speed-Matching Ratio Predicts Reading in Children

Purpose. Many behavioral studies have found impaired perception of dynamic visual stimuli in dyslexia and several neuroimaging studies have found reduced activation of the human motion area MT+ in dyslexia. These results are often interpreted as a magnocellular (MC) deficit in dyslexia. It has also been claimed that colored filters can help dyslexics to read. One defining feature of the MC-pathway is a greater weight for L-cone input than M-cone input, and at most very weak S-cone input. We measured the subjective speed matches between L-, M-, and S-cone isolating stimuli in good and poor readers. Methods. Subjects performed a speed-matching task with drifting cone-isolating stimuli to find the point of subjective equality between two drifting patterns. Such a task is known to activate cortical area MT+, presumably via the MC-pathway. Results. L- to M-cone speed-match ratios were negatively correlated with single-word (r = −0.46) and irregular-word reading (r = −0.56) but not with non-word reading. Conclusions. Results suggest that relative L-cone sensitivity within the MC-pathway may limit orthographic reading performance.
MEMS-Based Tunable LC Bandstop Filter With an Ultra-Wide Continuous Tuning Range

This letter presents a new microelectromechanical system-based tunable LC filter that utilizes a tunable capacitor and a tunable inductor in a single device. An electrically floating metal plate is located between the tunable capacitor and the tunable inductor. As the floating metal plate is thermally moved and used commonly for both the capacitor and inductor, the device provides an ultra-wide continuous frequency tuning range by a simultaneous increase or decrease of the capacitance and inductance. The fabricated tunable LC filter showed a continuous frequency tuning ratio in excess of 127% in a range of 8.8 GHz to more than 20 GHz.
Conserved epitopes dominate cross‐CD8+ T‐cell responses against influenza A H1N1 virus among Asian populations

Novel strains of influenza A viruses (IAVs) have emerged with high infectivity and/or pathogenicity in recent years, causing worldwide concern. T cells are correlated with protection in humans through cross‐reactive immunity against heterosubtypes of IAV. However, the different hierarchical roles of IAV‐derived epitopes with distinct levels of polymorphism in the cross‐reactive T‐cell responses against IAV remain elusive. In this study, immunodominant epitopes scattered throughout the entire proteome of 2009 pandemic influenza A H1N1 virus and seasonal IAVs were synthesized and divided into different pools depending on their conservation. The overall profile of the IAV‐specific CD8+ T‐cell immunity was detected by utilizing these peptide pools and also individual peptides. A dominant role of the conserved peptide‐specific T‐cell immunity was illuminated within the anti‐IAV responses, while the CD8+ T‐cell responses against the variable epitopes were lower than the conserved peptides. As previously demonstrated within a Caucasian population, we determined that GL9‐specific T cells, which also utilize Vβ 17 TCR (BV19), play a pivotal role in IAV‐specific T‐cell immunity within an HLA‐A2+ Asian population. Our study objectively reveals the different predominant roles of T‐cell epitopes among IAV‐specific cross‐reactive cellular immunity. This may guide the development of vaccines with cross‐T‐cell immunogenicity against heterosubtypes of IAV.
DETERMINATION OF THE SPERMICIDES NONOXYNOL-9 IN A GEL PHARMACEUTICAL FORMULATION BY RPLC

The purpose of the research described herein was to develop and validate a reversed-phase liquid chromatographic (RPLC) method for the commercially available spermicides nonoxynol-9 (1.90-2.10%, w/w) in a gel formulation. The chromatographic separation was achieved with methanol-water (83:17, v/v) as mobile phase through a Nucleosil Cyano column by UV detection at 289 nm. The calibration curve was linear over the concentration range of 0.05-0.35 mg/mL (R = 0.9997). The recovery ranges were from 99.87-100.04% from a gel formulation. The mean percent relative standard deviation values for intraand inter-day precision studies were less than 1.0%. The method was adequate sensitive with detection limit of 0.0065 μg/mL. The assay method remains unaffected by small but deliberate variations, thus it was robust.
Reduction of feed-contaminating mycotoxins by ultraviolet irradiation: an in vitro study

Ultraviolet (UV) germicidal irradiation has been applied to the sterilization of agricultural products including stored grain for foodstuffs or animal feed. Although UV treatment is known to be effective for killing pathogenic moulds that contaminate the surface of grain, it remains unclear how and to what extent such irradiation is able to eliminate mycotoxins, the fungal metabolites that have adverse effects on human and animal health. We evaluated in vitro the effects of mild (intensity = 0.1 mW cm−2 at 254 nm UV-C) and strong (24 mW cm−2) UV irradiation on two feed-contaminating mycotoxins, zearalenone (ZEN) and deoxynivalenol (DON). When exposed to mild irradiation, the levels of ZEN and DON (both 30 mg kg−1 initially) were reduced as irradiation time increased, and became undetectable at 60 min. Strong UV irradiation also reduced the mycotoxin levels in the same time-dependent manner, but more rapidly. It was therefore confirmed in vitro that UV irradiation is effective at reducing the levels of ZEN and DON. The present study provides preliminary data for establishing a practical method of using UV irradiation to reduce mycotoxin contamination in grain intended for use in feed.
Transient stability constrained optimal power flow based on trajectory sensitivity, one-machine infinite bus equivalence and differential evolution

This paper proposes an improved trajectory sensitivity method for transient stability constrained optimal power flow (TSCOPF) based on one-machine infinite bus (OMIB) equivalence after analyzing several problems existing in the trajectory sensitivity method for TSCOPF under multi-contingency condition, in which critical stable rotor angle is used as a threshold in stability constraint and the prediction-correction method is introduced to modify this threshold to highly improve this threshold's precision and optimization accuracy. According to OMIB equivalence, faults are classified into stable, extreme stable, generally unstable, and very unstable faults. Extreme stable faults are filtered out from transient stability constraints to avoid computing of relative trajectory sensitivity to these faults. Furthermore, in order to take advantage of fast convergence of the improved trajectory sensitivity method and global search capability of the differential evolution (DE) method, a hybrid algorithm for TSCOPF under multi-contingency condition is constructed by the combination of these two methods. Population size and computational burden are greatly decreased in this DE method. The DE's fitness value better evaluates the individual's stability and economic index by means of normalized stable margin for unstable faults. Efficiency and practicality of the proposed method are validated on the 10-machine 39-bus New England system.
Fast and de-noise support vector machine training method based on fuzzy clustering method for large real world datasets

Classifying large and real-world datasets is a challenging problem in machine learning algorithms. Among the machine learning methods, the support vector machine (SVM) is a well-known approach with high generalization ability. Unfortunately, while the number of training data increases and the data contain noise, the performance of SVM signicantly decreases. In this paper, a fast and de-noise two-stage method for training SVMs to deal with large, real- world datasets is proposed. In therst stage, data that contain noises or are suspected to be noisy are identied and eliminated from the genuine training dataset. The process of elimination and identication is based on the movement of the center of the convex hull data in the training dataset. The convex hull data are computed via the QHull algorithm. On the other hand, the well-known fuzzy clustering method (FCM) is applied to compress and reduce the size of the training dataset. Finally, the reduced and puried cluster centers are used for training the SVM. A set of experiments is conducted on the four benchmarking datasets of the UCI database. Moreover, the amount of training time and the generalization of the proposed approach are compared with FCM-SVM and normal SVM. The results indicate that the proposed method reduces the amount of training time and has a considerable success in removing noisy data from the training dataset. Therefore, the proposed method can achieve a higher generalization performance in comparison with the other methods in large, real-world datasets.
Evaluation of the in vivo and ex vivo optical properties in a mouse ear model

Determination of in vivo optical properties is a challenging problem. Absorption and scattering measured ex vivo are often used for in vivo applications. To investigate the validity of this approach, we have obtained and compared the optical properties of mouse ears in vivo and ex vivo in the spectral range from 370 to 1650 nm. Integrating sphere spectrophotometry in combination with the inverse Monte Carlo technique was employed to determine absorption coefficients, μa, scattering coefficients, μs, and anisotropy factors, g. Two groups of mice were used for the study. The first group was measured in vivo and ex vivo within 5–10 min post mortem. The second group was measured in vivo and ex vivo every 24 h for up to 72 h after sacrifice. Between the measurements the tissues were kept at 4 °C wrapped in a gauze moistened with saline solution. Then the specimens were frozen at −25 °C for 40 min, thawed and measured again. The results indicate that the absorption coefficients determined in vivo and ex vivo within 5–10 min post mortem differed considerably only in the spectral range dominated by hemoglobin. These changes can be attributed to rapid deoxygenation of tissue and blood post mortem. Absorption coefficients determined ex vivo up to 72 h post mortem decreased gradually with time in the spectral regions dominated by hemoglobin and water, which can be explained by the continuing loss of blood. Absorption properties of the frozen-thawed ex vivo tissues showed increase in oxygenation, which is likely caused by the release of hemoglobin from hemolyzed erythrocytes. Scattering of the ex vivo tissues decreased gradually with time in the entire spectral range due to the continuing loss of blood and partial cell damage. Anisotropy factors did not change considerably.
Physiotherapists' stories about professional development

Abstract Introduction: A professional career may extend over a period of 40 years. Although learning is a feature of professional competence, little is known about learning and development after professional entry education. Methods: Narrative inquiry was used to understand how physiotherapists learned and developed over time, and stories from a purposeful sample of 12 physiotherapists were collected. Stories were thematically analyzed with regard to key elements related to learning and development, and common themes were identified across stories. Findings: Four themes emerged from the analysis where physiotherapists learned and developed in working life: (1) facing challenges; (2) contrasting perspectives; (3) drawing on hundreds of educators; and (4) building on personal experience. Conclusion: Non-formal ways of learning in working life may help physiotherapists learn and develop confidence, communication strategies and different approaches to treatment. Besides reflection on personal experience and patient encounters, learning and development may be promoted and supported by taking on challenges and changing settings.
Dynamic Characteristics of Current-Fed Superbuck Converter

A photovoltaic generator is internally a current source having features resembling either a current or voltage source depending on the operating point in respect to its maximum power point (MPP). Therefore, the MPP-tracking converter can be implemented either as a voltage-fed (VF) or current-fed (CF) converter. This paper investigates the dynamic properties of a CF superbuck converter developed from the corresponding VF superbuck converter by applying duality-transformation methods. The dynamic characterization of CF converters is not publicly presented earlier although the duality-transformation methods are known from late 1960s or even earlier. The investigations show that the state-space-averaging technique yields accurate dynamic models also in CF domain. Experimental evidence is provided based on a 400-kHz superbuck converter supplied by a real photovoltaic or solar generator and loaded by a storage battery.
Response surface methodology: A non-conventional statistical tool to maximize the throughput of Streptomyces species biomass and their bioactive metabolites

Abstract Among diverse actinobacteria, Streptomyces is a renowned ongoing source for the production of a large number of secondary metabolites, furnishing immeasurable pharmacological and biological activities. Hence, to meet the demand of new lead compounds for human and animal use, research is constantly targeting the bioprospecting of Streptomyces. Optimization of media components and physicochemical parameters is a plausible approach for the exploration of intensified production of novel as well as existing bioactive metabolites from various microbes, which is usually achieved by a range of classical techniques including one factor at a time (OFAT). However, the major drawbacks of conventional optimization methods have directed the use of statistical optimization approaches in fermentation process development. Response surface methodology (RSM) is one of the empirical techniques extensively used for modeling, optimization and analysis of fermentation processes. To date, several researchers have implemented RSM in different bioprocess optimization accountable for the production of assorted natural substances from Streptomyces in which the results are very promising. This review summarizes some of the recent RSM adopted studies for the enhanced production of antibiotics, enzymes and probiotics using Streptomyces with the intention to highlight the significance of Streptomyces as well as RSM to the research community and industries.
Intensive Working Memory Training Produces Functional Changes in Large-scale Frontoparietal Networks

Working memory is central to human cognition, and intensive cognitive training has been shown to expand working memory capacity in a given domain. It remains unknown, however, how the neural systems that support working memory are altered through intensive training to enable the expansion of working memory capacity. We used fMRI to measure plasticity in activations associated with complex working memory before and after 20 days of training. Healthy young adults were randomly assigned to train on either a dual n-back working memory task or a demanding visuospatial attention task. Training resulted in substantial and task-specific expansion of dual n-back abilities accompanied by changes in the relationship between working memory load and activation. Training differentially affected activations in two large-scale frontoparietal networks thought to underlie working memory: the executive control network and the dorsal attention network. Activations in both networks linearly scaled with working memory load before training, but training dissociated the role of the two networks and eliminated this relationship in the executive control network. Load-dependent functional connectivity both within and between these two networks increased following training, and the magnitudes of increased connectivity were positively correlated with improvements in task performance. These results provide insight into the adaptive neural systems that underlie large gains in working memory capacity through training.