Ultrafast nonlinear optical response of Dirac fermions in graphene

The speed of solid-state electronic devices, determined by the temporal dynamics of charge carriers, could potentially reach unprecedented petahertz frequencies through direct manipulation by optical fields, consisting in a million-fold increase from state-of-the-art technology. In graphene, charge carrier manipulation is facilitated by exceptionally strong coupling to optical fields, from which stems an important back-action of photoexcited carriers. Here we investigate the instantaneous response of graphene to ultrafast optical fields, elucidating the role of hot carriers on sub-100 fs timescales. The measured nonlinear response and its dependence on interaction time and field polarization reveal the back-action of hot carriers over timescales commensurate with the optical field. An intuitive picture is given for the carrier trajectories in response to the optical-field polarization state. We note that the peculiar interplay between optical fields and charge carriers in graphene may also apply to surface states in topological insulators with similar Dirac cone dispersion relations.Peer ReviewedPostprint (published version

Generation of photovoltage in graphene on a femtosecond time scale through efficient carrier heating

Graphene is a promising material for ultrafast and broadband photodetection. Earlier studies addressed the general operation of graphene-based photo-thermoelectric devices, and the switching speed, which is limited by the charge carrier cooling time, on the order of picoseconds. However, the generation of the photovoltage could occur at a much faster time scale, as it is associated with the carrier heating time. Here, we measure the photovoltage generation time and find it to be faster than 50 femtoseconds. As a proof-of-principle application of this ultrafast photodetector, we use graphene to directly measure, electrically, the pulse duration of a sub-50 femtosecond laser pulse. The observation that carrier heating is ultrafast suggests that energy from absorbed photons can be efficiently transferred to carrier heat. To study this, we examine the spectral response and find a constant spectral responsivity between 500 and 1500 nm. This is consistent with efficient electron heating. These results are promising for ultrafast femtosecond and broadband photodetector applications.Comment: 6 pages, 4 figure

Tuning ultrafast electron thermalization pathways in a van der Waals heterostructure

Ultrafast electron thermalization - the process leading to Auger recombination, carrier multiplication via impact ionization and hot carrier luminescence - occurs when optically excited electrons in a material undergo rapid electron-electron scattering to redistribute excess energy and reach electronic thermal equilibrium. Due to extremely short time and length scales, the measurement and manipulation of electron thermalization in nanoscale devices remains challenging even with the most advanced ultrafast laser techniques. Here, we overcome this challenge by leveraging the atomic thinness of two-dimensional van der Waals (vdW) materials in order to introduce a highly tunable electron transfer pathway that directly competes with electron thermalization. We realize this scheme in a graphene-boron nitride-graphene (G-BN-G) vdW heterostructure, through which optically excited carriers are transported from one graphene layer to the other. By applying an interlayer bias voltage or varying the excitation photon energy, interlayer carrier transport can be controlled to occur faster or slower than the intralayer scattering events, thus effectively tuning the electron thermalization pathways in graphene. Our findings, which demonstrate a novel means to probe and directly modulate electron energy transport in nanoscale materials, represent an important step toward designing and implementing novel optoelectronic and energy-harvesting devices with tailored microscopic properties.Comment: Accepted to Nature Physic

Rare Complications of Cervical Spine Surgery: Pseudomeningocoele.

STUDY DESIGN: This study was a retrospective, multicenter cohort study. OBJECTIVES: Rare complications of cervical spine surgery are inherently difficult to investigate. Pseudomeningocoele (PMC), an abnormal collection of cerebrospinal fluid that communicates with the subarachnoid space, is one such complication. In order to evaluate and better understand the incidence, presentation, treatment, and outcome of PMC following cervical spine surgery, we conducted a multicenter study to pool our collective experience. METHODS: This study was a retrospective, multicenter cohort study of patients who underwent cervical spine surgery at any level(s) from C2 to C7, inclusive; were over 18 years of age; and experienced a postoperative PMC. RESULTS: Thirteen patients (0.08%) developed a postoperative PMC, 6 (46.2%) of whom were female. They had an average age of 48.2 years and stayed in hospital a mean of 11.2 days. Three patients were current smokers, 3 previous smokers, 5 had never smoked, and 2 had unknown smoking status. The majority, 10 (76.9%), were associated with posterior surgery, whereas 3 (23.1%) occurred after an anterior procedure. Myelopathy was the most common indication for operations that were complicated by PMC (46%). Seven patients (53%) required a surgical procedure to address the PMC, whereas the remaining 6 were treated conservatively. All PMCs ultimately resolved or were successfully treated with no residual effects. CONCLUSIONS: PMC is a rare complication of cervical surgery with an incidence of less than 0.1%. They prolong hospital stay. PMCs occurred more frequently in association with posterior approaches. Approximately half of PMCs required surgery and all ultimately resolved without residual neurologic or other long-term effects

Low complexity frequency monitoring filter for fast exon prediction sequence analysis

Over the last few years, the application of Digital Signal Processing (DSP) techniques for genomic sequence analysis has received great interest. Indeed, among its applications in genomic analysis, it has been demonstrated that DSP can be used to detect protein coding regions (exons) among non-coding regions in a DNA sequence. The period-3 behavior exhibited by exons is one of its features that has been exploited in several developed algorithms for exon prediction. Identification of this periodicity in genomic sequences can be done by using different methods such as the well-known Fast Fourier Transform (FFT) and the Goertzel algorithm for complexity reduction in which the reduction of computational time is a great challenge in genomic analysis. Therefore, this paper presents a novel one frequency analysis by using half of the arithmetic complexity of the Goertzel algorithm for gene prediction. Compared to the Intel®’s FFT (MKL) optimized function, the Goertzel’s (IPP) and the dedicated Goertzel compiled function with ICC on Xeon CPU (24 cores), the proposed method conserves the same accuracy provided by the referenced methods which will manifest a speedup of 3000, 10 and 2 compared to MKL FFT, IPP Goertzel and the dedicated Goertzel with ICC, respectively

C5 Palsy After Cervical Spine Surgery: A Multicenter Retrospective Review of 59 Cases.

STUDY DESIGN: A multicenter, retrospective review of C5 palsy after cervical spine surgery. OBJECTIVE: Postoperative C5 palsy is a known complication of cervical decompressive spinal surgery. The goal of this study was to review the incidence, patient characteristics, and outcome of C5 palsy in patients undergoing cervical spine surgery. METHODS: We conducted a multicenter, retrospective review of 13 946 patients across 21 centers who received cervical spine surgery (levels C2 to C7) between January 1, 2005, and December 31, 2011, inclusive. P values were calculated using 2-sample t test for continuous variables and χ(2) tests or Fisher exact tests for categorical variables. RESULTS: Of the 13 946 cases reviewed, 59 patients experienced a postoperative C5 palsy. The incidence rate across the 21 sites ranged from 0% to 2.5%. At most recent follow-up, 32 patients reported complete resolution of symptoms (54.2%), 15 had symptoms resolve with residual effects (25.4%), 10 patients did not recover (17.0%), and 2 were lost to follow-up (3.4%). CONCLUSION: C5 palsy occurred in all surgical approaches and across a variety of diagnoses. The majority of patients had full recovery or recovery with residual effects. This study represents the largest series of North American patients reviewed to date

ECMO Biocompatibility: Surface Coatings, Anticoagulation, and Coagulation Monitoring

The interaction between the patient and the ECMO (extracorporeal membrane oxygenation) circuit initiates a significant coagulation and inflammatory response due to the large surface area of foreign material contained within the circuit. This response can be blunted with the appropriate mix of biocompatible materials and anticoagulation therapy. The use of anticoagulants, in turn, requires appropriate laboratory testing to determine whether the patient is appropriately anticoagulated. Physicians must balance the risks of bleeding with the risks of thrombosis; the proper interpretation of these tests is often shrouded in mystery. It is the purpose of this chapter to help demystify the coagulation system, anticoagulants, biocompatible surfaces, and coagulation testing so that ECMO practitioners can make informed decisions about their patients and to spur coordinated efforts for future research to improve our understanding of these complex processes

Boolean Compressive Sensing: An Approximate Trust Region reconstruction

In this paper, we propose a direct nonlinear optimization method to solve the Boolean Compressive Sensing (BCS) problem for large signals when sparsity level is unknown. While traditional CS results from linear Algebra, BCS, is given by logical operation in the Boolean workspace. To overcome this inconvenience, we relax the problem in an equivalent formulation in the Real workspace using appropriate modeling as a first step. Thereafter we turn out the problem in an unconstrained form that can be solved directly by nonlinear optimization method called Trust Region methods (TRM). Our solution is based on an Approximate version of (TRM). Numerical results are presented to sustain efficiency of our proposal

Sliding mode tracking control of a class of fractional-order nonstrict-feedback nonlinear systems

Since the Leibniz rule for integer-order derivatives of the product of functions, which includes a finite number of terms, is not true for fractional-order (FO) derivatives of that, all sliding mode control (SMC) methods introduced in the literature involved a very limited class of FO nonlinear systems. This article presents a solution for the unsolved problem of SMC of a class of FO nonstrict-feedback nonlinear systems with uncertainties. Using the Leibniz rule for the FO derivative of the product of two functions, which includes an infinite number of terms, it is shown that only one of these terms is needed to design a SMC law. Using this point, an algorithm is given to design the controller for reference tracking, that significantly reduces the number of design parameters, compared to the literature. Then, it is proved that the algorithm has a closed-form solution which presents a straightforward tool to the designer to obtain the controller. The solution is applicable to the systems with a mixture of integer-order and FO dynamics. Stability and finite-time convergence of the offered control law are also demonstrated. In the end, the availability of the suggested SMC is illustrated through a numerical example arising from a real system

Surface EMG-based inter-session/inter-subject gesture recognition by leveraging lightweight All-ConvNet and transfer learning

Gesture recognition using low-resolution instantaneous high-density surface electromyography (HD-sEMG) images opens up new avenues for the development of more fluid and natural muscle-computer interfaces. However, the data variability between inter-session and inter-subject scenarios presents a great challenge. The existing approaches employed very large and complex deep ConvNet or 2SRNN-based domain adaptation methods to approximate the distribution shift caused by these inter-session and inter-subject data variability. Hence, these methods also require learning over millions of training parameters and a large pre-trained and target domain dataset in both the pre-training and adaptation stages. As a result, it makes high-end resource-bounded and computationally very expensive for deployment in real-time applications. To overcome this problem, we propose a lightweight All-ConvNet+TL model that leverages lightweight All-ConvNet and transfer learning (TL) for the enhancement of inter-session and inter-subject gesture recognition performance. The All-ConvNet+TL model consists solely of convolutional layers, a simple yet efficient framework for learning invariant and discriminative representations to address the distribution shifts caused by inter-session and inter-subject data variability. Experiments on four datasets demonstrate that our proposed methods outperform the most complex existing approaches by a large margin and achieve state-of-the-art results on inter-session and inter-subject scenarios and perform on par or competitively on intra-session gesture recognition. These performance gaps increase even more when a tiny amount (e.g., a single trial) of data is available on the target domain for adaptation. These outstanding experimental results provide evidence that the current state-of-the-art models may be overparameterized for sEMG-based inter-session and inter-subject gesture recognition tasks