Miracle-dz/UniFAR-FTUs huggingface dataset:
Transesophageal echocardiography induced airway obstruction in a patient in whom the trachea had been intubated via a LMA CTrach.

of the neck persisted. Forty-eight hours after admission, formation of a retropharyngeal abscess and upper mediastinitis were confirmed by computed tomography. After surgical drainage, she required mechanical ventilation for 6 days in the intensive care unit and was finally discharged 17 days after the knee surgery. We found only one report of pharyngeal perforation after anesthesia via a laryngeal mask (LMA). However, occasionally, after even uneventful insertion of the LMA, traces of blood suggesting mucosal injury are seen on the LMA. Although we do not know the precise cause of this patient’s complication, we speculate that pharyngeal injury was caused by a larger than necessary LMA, combined with excessively high cuff pressure, leading to pharyngeal mucosal injury all followed by secondary vomiting in an already damaged hypopharynx. The impact of these issues were accentuated by missing the diagnosis of perforation delaying appropriate treatment.
Link-Adaptive Distributed Coding for Multisource Cooperation

Combining multisource cooperation and link-adaptive regenerative techniques, a novel protocol is developed capable of achieving diversity order up to the number of cooperating users and large coding gains. The approach relies on a two-phase protocol. In Phase 1, cooperating sources exchange information-bearing blocks, while in Phase 2, they transmit reencoded versions of the original blocks. Different from existing approaches, participation in the second phase does not require correct decoding of Phase 1 packets. This allows relaying of soft information to the destination, thus increasing coding gains while retaining diversity properties. For any reencoding function the diversity order is expressed as a function of the rank properties of the distributed coding strategy employed. This result is analogous to the diversity properties of colocated multi-antenna systems. Particular cases include repetition coding, distributed complex field coding (DCFC), distributed space-time coding, and distributed error-control coding. Rate, diversity, complexity and synchronization issues are elaborated. DCFC emerges as an attractive choice because it offers high-rate, full spatial diversity, and relaxed synchronization requirements. Simulations confirm analytically established assessments.
TRACON: Interference-aware scheduling for data-intensive applications in virtualized environments

Large-scale data centers leverage virtualization technology to achieve excellent resource utilization, scalability, and high availability. Ideally, the performance of an application running inside a virtual machine (VM) shall be independent of co-located applications and VMs that share the physical machine. However, adverse interference effects exist and are especially severe for data-intensive applications in such virtualized environments. In this work, we present TRACON, a novel Task and Resource Allocation CONtrol framework that mitigates the interference effects from concurrent data-intensive applications and greatly improves the overall system performance. TRACON utilizes modeling and control techniques from statistical machine learning and consists of three major components: the interference prediction model that infers application performance from resource consumption observed from different VMs, the interference-aware scheduler that is designed to utilize the model for effective resource management, and the task and resource monitor that collects application characteristics at the runtime for model adaption. We simulate TRACON with a wide variety of data-intensive applications including bioinformatics, data mining, video processing, email and web servers, etc. The evaluation results show that TRACON can achieve up to 50% improvement on application runtime, and up to 80% on I/O throughput for data-intensive applications in virtualized data centers.
QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data

Array-based technologies have been used to detect chromosomal copy number changes (aneuploidies) in the human genome. Recent studies identified numerous copy number variants (CNV) and some are common polymorphisms that may contribute to disease susceptibility. We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation from BeadArray™ SNP genotyping data using an Objective Bayes Hidden-Markov Model (OB-HMM). Objective Bayes measures are used to set certain hyperparameters in the priors using a novel re-sampling framework to calibrate the model to a fixed Type I (false positive) error rate. Other parameters are set via maximum marginal likelihood to prior training data of known structure. QuantiSNP provides probabilistic quantification of state classifications and significantly improves the accuracy of segmental aneuploidy identification and mapping, relative to existing analytical tools (Beadstudio, Illumina), as demonstrated by validation of breakpoint boundaries. QuantiSNP identified both novel and validated CNVs. QuantiSNP was developed using BeadArray™ SNP data but it can be adapted to other platforms and we believe that the OB-HMM framework has widespread applicability in genomic research. In conclusion, QuantiSNP is a novel algorithm for high-resolution CNV/aneuploidy detection with application to clinical genetics, cancer and disease association studies.
Motion-blur-free camera system splitting exposure time

In this paper, a motion-blur-free camera system using multi-exposed images is proposed. Advances in image sensors enable a high-speed image readout, which makes it possible to capture multiple images within a normal exposure time. The proposed camera system captures three frames successively at long-short-long exposure times from the same scene. In order to obtain a high-quality image, we utilize the motion-based image merging algorithm that combines the shape information of objects in the under-exposed image captured at the short exposure time and the color information from two blurred images taken at the long exposure time. Simulation results show that the proposed multi-exposure camera system can provide high-quality images mitigating the motion blur.
Structural stability and endonuclease activity of a PI-SceI GFP-fusion protein

Homing endonucleases are site-specific and rare cutting endonucleases often encoded by intron or intein containing genes. They lead to the rapid spread of the genetic element that hosts them by a process termed 'homing'; and ultimately the allele containing the element will be fixed in the population. PI-SceI, an endonuclease encoded as a protein insert or intein within the yeast V-ATPase catalytic subunit encoding gene (vma1), is among the best characterized homing endonucleases. The structures of the Sce VMA1 intein and of the intein bound to its target site are known. Extensive biochemical studies performed on the PI-SceI enzyme provide information useful to recognize critical amino acids involved in self-splicing and endonuclease functions of the protein. Here we describe an insertion of the Green Fluorescence Protein (GFP) into a loop which is located between the endonuclease and splicing domains of the Sce VMA1 intein. The GFP is functional and the additional GFP domain does not prevent intein excision and endonuclease activity. However, the endonuclease activity of the newly engineered protein was different from the wild-type protein in that it required the presence of Mn(2+) and not Mg(2+) metal cations for activity.
Partial response, nonresponse, and relapse with selective serotonin reuptake inhibitors in major depression: a survey of current "next-step" practices.

BACKGROUND Many patients treated for major depression require more than one antidepressant trial to achieve or sustain response. However, the literature provides few treatment algorithms or effectiveness studies that empirically support "next-step" options available to clinicians. We conducted a survey of psychiatrists and other medical specialists who treat depression to ascertain what clinicians actually do when faced with patients who suboptimally respond to an adequate course of selective serotonin reuptake inhibitor (SSRI) therapy. METHOD Attendees at a psychopharmacology course (N = 801) were queried about their top choices for antidepressant-treatment nonresponders: a minimal responder after 4 weeks of adequate SSRI treatment, a partial responder after 8 weeks of adequate SSRI therapy, a nonresponder after 8 weeks of adequate SSRI therapy, and a relapser on long-term SSRI maintenance therapy. Choices included raising the dose, augmenting or combining with another agent, switching to a second SSRI. or switching to a non-SSRI agent. RESULTS 432 (54%) of the surveys were returned. Raising the dose was the most frequently reported next-step strategy for a patient with minimal response after 4 weeks of adequate SSRI therapy, partial response after 8 weeks of adequate SSRI therapy, and relapse on long-term SSRI therapy. Switching to a non-SSRI agent was the most frequently chosen option for nonresponders to an adequate trial of SSRI therapy. CONCLUSION Our findings suggest that clinicians select different next-step strategies when patients are nonresponders versus when patients are partial responders or relapsers.
Does contralateral suppression at adrenal venous sampling predict outcome following unilateral adrenalectomy for primary aldosteronism? A retrospective study.

CONTEXT In primary aldosteronism (PA), adrenal vein sampling (AVS) distinguishes unilateral and bilateral disease by comparison of aldosterone/cortisol (A/F) ratios. There is controversy about the criteria for interpretation, however, and in particular it is not clear whether contralateral suppression (CS) (defined as A/F(adrenal) ≤ A/F(peripheral) on the unaffected side) is important. We therefore performed a retrospective study to determine whether CS in surgically treated unilateral PA was associated with blood pressure (BP) and biochemical outcomes. SETTING AND DESIGN Patients who underwent unilateral adrenalectomy for PA after successful AVS were included if the lateralization index (A/F(dominant):A/F(nondominant)) was ≥ 2. Cases were reviewed at 6 to 24 months follow-up for outcomes with respect to the presence and degree of CS. RESULTS Sixty-six of 80 patients had CS. Baseline characteristics were similar. At postoperative follow-up, those with CS had lower systolic BP (SBP) (128 mm Hg vs 144 mm Hg, P = .001), a greater proportion with cure or improvement of hypertension (96% vs 64%, P = .0034), a greater proportion with biochemical cure of PA on fludrocortisone suppression testing (43 of 49 [88%] vs 4 of 9 [44%], P = .002) and were taking a lower median number of antihypertensive medications (0 vs 1.5, P = .0032). In a multivariate model, the degree of CS and preoperative SBP were both significantly correlated with postoperative SBP, but the lateralization index, sex, and age were not. CONCLUSION In this study, the presence of CS correlated with good BP and biochemical outcomes from surgery. This finding suggests that CS should be a factor in deciding whether to offer surgery for treatment of PA.
An Information-Theoretical Approach to High-Speed Flow Nature Identification

This paper concerns the fundamental problem of identifying the content nature of a flow-namely text, binary, or encrypted-for the first time. We propose Iustitia, a framework for identifying flow nature on the fly. The key observation behind Iustitia is that text flows have the lowest entropy and encrypted flows have the highest entropy, while the entropy of binary flows stands in between. We further extend Iustitia for the finer-grained classification of binary flows so that we can differentiate different types of binary flows (such as image, video, and executables) and even the file formats (such as JPEG and GIF for images, MPEG and AVI for videos) carried by binary flows. The basic idea of Iustitia is to classify flows using machine learning techniques where a feature is the entropy of every certain number of consecutive bytes. Our experimental results show that the classification can be done with high speed and high accuracy. On average, Iustitia can classify flows with 88.27% of accuracy using a buffer size of 1 K with a classification time of less than 10% of packet interarrival time for 91.2% of flows.
Foot orthoses and physiotherapy in the treatment of patellofemoral pain syndrome: randomised clinical trial

Objective To compare the clinical efficacy of foot orthoses in the management of patellofemoral pain syndrome with flat inserts or physiotherapy, and to investigate the effectiveness of foot orthoses plus physiotherapy. Design Prospective, single blind, randomised clinical trial. Setting Single centre trial within a community setting in Brisbane, Australia. Participants 179 participants (100 women) aged 18 to 40 years, with a clinical diagnosis of patellofemoral pain syndrome of greater than six weeks’ duration, who had no previous treatment with foot orthoses or physiotherapy in the preceding 12 months. Interventions Six weeks of physiotherapist intervention with off the shelf foot orthoses, flat inserts, multimodal physiotherapy (patellofemoral joint mobilisation, patellar taping, quadriceps muscle retraining, and education), or foot orthoses plus physiotherapy. Main outcome measures Global improvement, severity of usual and worst pain over the preceding week, anterior knee pain scale, and functional index questionnaire measured at 6, 12, and 52 weeks. Results Foot orthoses produced improvement beyond that of flat inserts in the short term, notably at six weeks (relative risk reduction 0.66, 99% confidence interval 0.05 to 1.17; NNT 4 (99% confidence interval 2 to 51). No significant differences were found between foot orthoses and physiotherapy, or between physiotherapy and physiotherapy plus orthoses. All groups showed clinically meaningful improvements in primary outcomes over 52 weeks. Conclusion While foot orthoses are superior to flat inserts according to participants’ overall perception, they are similar to physiotherapy and do not improve outcomes when added to physiotherapy in the short term management of patellofemoral pain. Given the long term improvement observed in all treatment groups, general practitioners may seek to hasten recovery by prescribing prefabricated orthoses. Trial registration Australian Clinical Trials Registry ACTRN012605000463673 and ClinicalTrials.gov NCT00118521.
Near-optimal energy-efficient joint resource allocation for multi-hop MIMO-AF systems

Energy efficiency (EE) is becoming an important performance indicator for ensuring both the economical and environmental sustainability of the next generation of communication networks. Equally, cooperative communication is an effective way of improving communication system performances. In this paper, we propose a near-optimal energy-efficient joint resource allocation algorithm for multi-hop multiple-input-multiple-output (MIMO) amplify-and-forward (AF) systems. We first show how to simplify the multivariate unconstrained EE-based problem, based on the fact that this problem has a unique optimal solution, and then solve it by means of a low-complexity algorithm. We compare our approach with classic optimization tools in terms of energy efficiency as well as complexity, and results indicate the near-optimality and low-complexity of our approach. As an application, we use our approach to compare the EE of multi-hop MIMO-AF with MIMO systems and our results show that the former outperforms the latter mainly when the direct link quality is poor.
Multiperiod Auction for a Pool-Based Electricity Market

This paper presents a market clearing tool for the market operator of a pool-based electricity market for energy. This tool is transparent and fair for the market participants and simple to implement and interpret. It preserves the privacy of the corporate information of the participants and provides the right signals to achieve economic efficiency. It recognizes and properly models the technical (physical and intertemporal) constraints of the participant thermal power generators. From a mathematical point of view, the proposed tool results in a mixed-integer linear programming problem that can be efficiently solved using currently available branch and cut software. To illustrate the adequate functioning of the proposed market clearing procedure, different realistic ease studies are analyzed in detail.
Learning curves for stochastic gradient descent in linear feedforward networks

Gradient-following learning methods can encounter problems of implementation in many applications, and stochastic variants are frequently used to overcome these difficulties. We derive quantitative learning curves for three online training methods used with a linear perceptron: direct gradient descent, node perturbation, and weight perturbation. The maximum learning rate for the stochastic methods scales inversely with the first power of the dimensionality of the noise injected into the system; with sufficiently small learning rate, all three methods give identical learning curves. These results suggest guidelines for when these stochastic methods will be limited in their utility, and considerations for architectures in which they will be effective.
Medical linear accelerator mounted mini-beam collimator: design, fabrication and dosimetric characterization

The goal of this work was to design, build and experimentally characterize a linear accelerator mounted mini-beam collimator for use at a nominal 6 MV beam energy. Monte Carlo simulation was used in the design and dosimetric characterization of a compact mini-beam collimator assembly mounted to a medical linear accelerator. After fabrication, experimental mini-beam dose profiles and central axis relative output were measured and the results used to validate the simulation data. The simulation data was then used to establish traceability back to an established dosimetric code of practice. The Monte Carlo simulation work revealed that changes in collimator blade width have a greater influence on the valley-to-peak dose ratio than do changes in blade height. There was good agreement between the modeled and measured profile data, with the exception of small differences on either side of the central peak dose. These differences were found to be systematic across all depths and result from limitations associated with the collimator fabrication. Experimental mini-beam relative output and simulation data agreed to better than ±2.0%, which is well within the level of uncertainty required for dosimetric traceability of non-standard field geometries. A mini-beam collimator has now been designed, built and experimentally characterized for use with a commercial linear accelerator operated at a nominal 6 MV beam energy.
A Priori Error Estimates for Space-Time Finite Element Discretization of Parabolic Optimal Control Problems Part II: Problems with Control Constraints

This paper is the second part of our work on a priori error analysis for finite element discretizations of parabolic optimal control problems. In the first part [SIAM J. Control Optim. , 47 (2008), pp. 1150–1177] problems without control constraints were considered. In this paper we derive a priori error estimates for space-time finite element discretizations of parabolic optimal control problems with pointwise inequality constraints on the control variable. The space discretization of the state variable is done using usual conforming finite elements, whereas the time discretization is based on discontinuous Galerkin methods. For the treatment of the control discretization we discuss different approaches, extending techniques known from the elliptic case.
Comprehensive study of a binary technique for brushless DC motor control

Brushless DC (BLDC) motor applications are increasing rapidly in electrical drives due to its advantages of low weight, low volume and high efficiency. However, the cost of these drives is higher due to higher magnet cost and complex control. Although efforts are being made to avoid the mechanical position sensors, still they are used in most applications. In this paper, a simple binary controller is selected for detailed study. The two performance indices, speed ripple and steady state speed error, are used for evaluation towards a number of speed ranges keeping the load torque constant. The steady state speed error is minimised for each speed range. The performance indices are further calculated for the same speed ranges with different load torques. It has been demonstrated in this work that the variations of speed ripple with speed and torque provide definite patterns which can be used to meet the system design for specific applications. The effect of varying the current conduction ratio of the controller on the speed ripple has also been discussed.
Determining Ideal Impulse Generator Settings from a Generator-Transformer Circuit Model

Impulse testing of large power transformers is a routine test, which is designed to mimic a lightning strike in service. At the design stage, it is useful to have a detailed circuit model of the transformer in order to simulate the impulse test and to check for possibly damaging voltage stress levels. In our model, which includes capacitive and inductive couplings as well as resistive effects, we apply an ideal full or chopped waveform to the impulsed terminal. In an actual impulse test, it is sometimes difficult to approximate the ideal waveform, particularly the full wave one, and a trial-and-error approach is often taken. Here we describe an approach that couples a circuit model of the impulse generator with a transformer circuit model and show how, from this combination, we can arrive at close to ideal settings for the generator, provided such settings are possible.
Bioreactor design for clinical‐grade expansion of stem cells

The many clinical trials currently in progress will likely lead to the widespread use of stem cell‐based therapies for an extensive variety of diseases, either in autologous or allogeneic settings. With the current pace of progress, in a few years' time, the field of stem cell‐based therapy should be able to respond to the market demand for safe, robust and clinically efficient stem cell‐based therapeutics. Due to the limited number of stem cells that can be obtained from a single donor, one of the major challenges on the roadmap for regulatory approval of such medicinal products is the expansion of stem cells using Good Manufacturing Practices (GMP)‐compliant culture systems. In fact, manufacturing costs, which include production and quality control procedures, may be the main hurdle for developing cost‐effective stem cell therapies. Bioreactors provide a viable alternative to the traditional static culture systems in that bioreactors provide the required scalability, incorporate monitoring and control tools, and possess the operational flexibility to be adapted to the differing requirements imposed by various clinical applications. Bioreactor systems face a number of issues when incorporated into stem cell expansion protocols, both during development at the research level and when bioreactors are used in on‐going clinical trials. This review provides an overview of the issues that must be confronted during the development of GMP‐compliant bioreactors systems used to support the various clinical applications employing stem cells.