Time Epochs Research Articles

Buckling down on torus fractures: Has evolving evidence affected practice?

PurposeThe purpose of this study was to evaluate the management of paediatric torus fractures of the distal forearm in current practice in light of growing evidence supporting a ‘minimalist’ approach with splint immobilization and limited follow-up. We hypothesized that ‘traditional’ cast-based management has persisted despite alternative evidence.MethodsA retrospective review was performed of a consecutive series of paediatric patients diagnosed with torus fractures of the distal forearm between 2011 and 2014. Records were reviewed to abstract the type of immobilization (splint versus cast) prescribed at each visit, number of radiographic exams, duration of immobilization, number of clinical visits and complications. The primary outcome was the proportion of patients exclusively managed in splints. Injuries were grouped based on treatment into a cast group (CG) and a splint group (SG) for statistical analyses. Additionally, injuries were grouped by epoch of time to determine if immobilization usage patterns evolved.ResultsA total of 240 forty injuries met criteria for inclusion. Of these, 16 (6.7%) were exclusively splinted (SG). Relative to the CG, the SG had fewer clinical visits (p < 0.001), fewer radiographic exams (p < 0.001) and a shorter total encounter time (p = 0.015). No change in immobilization use occurred over the study period. In all, 21 (9.4%) of the CG experienced complications. No clinically significant displacements occurred in either group.ConclusionCast utilization and frequent radiographic follow-up remain prevalent at our institution in the management of paediatric torus fractures. Splint-only management was associated with fewer clinical visits, fewer radiographic exams and a shorter total encounter time.Level of Evidence Level IIITherapeutic retrospective cohort study

Performance characteristics of a batch service queueing system with functioning server failure and multiple vacations

This paper examines bulk arrival and batch service queueing system with functioning server failure and multiple vacations. Customers are arriving into the system in bulk according to Poisson process with rate λ. Arriving customers are served in batches with minimum of ‘a’ and maximum of ‘b’ number of customers according to general bulk service rule. In the service completion epoch if the queue length is less than ‘a’ then the server leaves for vacation (secondary job) of random length. After a vacation completion, if the queue length is still less than ‘a’ then the server leaves for another vacation. The server keeps on going vacation until the queue length reaches the value ‘a’. The server is not stable at all the times. Sometimes it may fails during functioning of customers. Though the server fails service process will not be interrupted.It will be continued for the current batch of customers with lower service rate than the regular service rate. The server will be repaired after the service completion with lower service rate. The probability generating function of the queue size at an arbitrary time epoch will be obtained for the modelled queueing system by using supplementary variable technique. Moreover various performance characteristics will also be derived with suitable numerical illustrations.

Directed and undirected network evolution from Euler–Lagrange dynamics

In this paper, we investigate both undirected and directed network evolution using the Euler–Lagrange equation. We use the Euler–Lagrange equation to develop a variational principle based on the von Neumann entropy for time-varying network structure. Commencing from recent work to approximate the von Neumann entropy using simple degree statistics, the changes in entropy between different time epochs are determined by correlations in the degree difference in the edge connections. Our Euler–Lagrange equation minimises the change in entropy and allows to develop a dynamic model to simulate the changes of node degree with time. We first explore the effect of network dynamics on the three widely studied complex network models, namely (a) Erdős-Rényi random graphs, (b) Watts-Strogatz small-world networks, and (c) Barabási-Albert scale-free networks. Our model effectively captures both undirected and directed structural transitions in the dynamic network models. We apply our model to a network time sequence representing the evolution of stock prices on the New York Stock Exchange(NYSE) and sequences of Drosophila gene regulatory networks containing different developmental phases of the organism from embryo to adult. Here we use the model to differentiate between periods of stable and unstable stock price trading and to detect periods of anomalous network evolution. Our experiments show that the presented model not only provides an accurate simulation of the degree statistics in time-varying networks but also captures the topological variations taking place when the structure of a network changes violently.

Downlink user association and uplink scheduling for energy harvesting users in software-defined mobile networks

In this paper we consider a heterogeneous network which consists of a macro base station and some pico base stations utilizing massive MIMO and MIMO techniques, respectively. A central software-defined mobile network (SDMN) controller is adopted in order to provide user association and energy scheduling. The users are considered battery limited and are capable of simultaneous wireless information and power transfer (SWIPT) in order to harvest energy and address the energy shortage issue. These users harvest energy from the received signals in the downlink and consume it via their uplink communications. This paper deals with the downlink user association by jointly optimizing the overall sum-rate of the network and the harvested energy by introducing an appropriate utility function. In this regard, the optimum user association and power splitting factor for each user are calculated via the downlink optimization stage. Then, the process of uplink scheduling is defined as choosing the best users in each time epoch to transfer data as well as optimizing their transmit power by solving Lyapunov drift-plus-penalty function. Simulation results are provided in order to confirm the optimality of the proposed algorithm in comparison with the previous user association and uplink scheduling approaches in terms of providing fairness and battery management among users.

Univariate and multivariate stochastic comparisons and ageing properties of the generalized Pólya process

Abstract In this work we consider the generalized Pólya process with baseline intensity function r and parameters α and β recently studied by Cha (2014). The aim of this work is to provide both univariate and multivariate stochastic comparisons between two generalized Pólya processes with different baseline intensity functions and the same parameters α and β for the epoch and inter-epoch times of the two processes. The comparisons are analogous to stochastic comparisons in Belzunce et al. (2001) for two nonhomogeneous Poisson or pure-birth processes with different intensity functions. Moreover, we study both univariate and multivariate ageing properties of the epoch and inter-epoch times of the generalized Pólya process.

Dynamic Connectivity Game for Adversarial Internet of Battlefield Things Systems

In this paper, the problem of network connectivity is studied for an adversarial Internet of Battlefield Things (IoBT) system in which an attacker aims at disrupting the connectivity of the network by choosing to compromise one of the IoBT nodes at each time epoch. To counter such attacks, an IoBT defender attempts to reestablish the IoBT connectivity by either deploying new IoBT nodes or by changing the roles of existing nodes. This problem is formulated as a dynamic multistage Stackelberg connectivity game that extends classical connectivity games and that explicitly takes into account the characteristics and requirements of the IoBT network. In particular, the defender’s payoff captures the IoBT latency as well as the sum of weights of disconnected nodes at each stage of the game. Due to the dependence of the attacker’s and defender’s actions at each stage of the game on the network state, the feedback Stackelberg solution [feedback Stackelberg equilibrium (FSE)] is used to solve the IoBT connectivity game. Then, sufficient conditions under which the IoBT system will remain connected, when the FSE solution is used, are determined analytically. Numerical results show that the expected number of disconnected sensors, when the FSE solution is used, decreases up to 46% compared to a baseline scenario in which a Stackelberg game with no feedback is used, and up to 43% compared to a baseline equal probability policy.

Interplanetary Parameters Leading to Relativistic Electron Enhancement and Persistent Depletion Events at Geosynchronous Orbit and Potential for Prediction

AbstractWe have identified 61 relativistic electron enhancement events and 21 relativistic electron persistent depletion events during 1996 to 2006 from the Geostationary Operational Environmental Satellite (GOES) 8 and 10 using data from the Energetic Particle Sensor (EPS) &gt;2 MeV fluxes. We then performed a superposed epoch time analysis of the events to find the characteristic solar wind parameters that determine the occurrence of such events, using the OMNI database. We found that there are clear differences between the enhancement events and the persistent depletion events, and we used these to establish a set of threshold values in solar wind speed, proton density and interplanetary magnetic field (IMF) Bz that can potentially be useful to predict sudden increases in flux. Persistent depletion events are characterized by a low solar wind speed, a sudden increase in proton density that remains elevated for a few days, and a northward turning of IMF Bz shortly after the depletion starts. We have also found that all relativistic electron enhancement or persistent depletion events occur when some geomagnetic disturbance is present, either a coronal mass ejection or a corotational interaction region; however, the storm index, SYM‐H, does not show a strong connection with relativistic electron enhancement events or persistent depletion events. We have tested a simple threshold method for predictability of relativistic electron enhancement events using data from GOES 11 for the years 2007–2010 and found that around 90% of large increases in electron fluxes can be identified with this method.

Abstract TP12: Distribution and Incidence of Fast versus Slow Progressors of Infarct Growth in Large Vessel Occlusion Stroke

Background and Purpose: Fast and slow progressors of infarct growth due to a large vessel occlusion (LVO) are commonly observed when patients are considered for acute endovascular therapy. However, the incidence of these clinical phenotypes has not been formally quantified. We aimed to measure the frequency and distribution of fast versus slow infarct growth in LVO patients in different time strata after stroke onset. Methods: Retrospective study of consecutive patients with acute LVO admitted to our comprehensive stroke center. Inclusion criteria were: 1. CTA or MRA evidence of intracranial ICA and/or MCA(M1) occlusion, with or without extracranial ICA occlusion. 2. Baseline CTP or MRI DWI before reperfusion therapy and within 25 hours of time of last seen well/stroke onset. Automated core volume measurements were performed using RAPID software (iSchemaView). Fast progressors were defined as having core volumes &gt; 70 cc at early time quantiles (0 - 8 hours). Slow progressors were defined as having core volumes &lt; 10 cc at later time quantiles (&gt; 8 hours). Infarct growth rate was computed using ischemic core volume divided by time from stroke onset to core imaging. Descriptive statistics and univariate analysis were performed. Results: A total of 115 patients were included with mean age 69+/-15.5 and NIHSS 16.5+/-7; 66% were females. Patients had MCA occlusion in 81% and intracranial ICA occlusion in 19% of cases. The median time from stroke onset to baseline core imaging was 9.1 hours (IQR, 4 - 14.7) and 53 patients were imaged before 8 hours. The median core volume was 10 (range 0 - 405 ml). In the early time epoch (&lt; 8 hrs), 5/13 patients (38%) had core &gt; 70ml by 3.65 hours (fast progressors). In the later time epoch (&gt; 8 hrs), 29/62 patients (46%) had ischemic cores &lt; 10ml at 25 hours from stroke onset. The median infarct growth rate was 2.6 ml/hr (0 - 14.6) in patients imaged before 8 hours and 1.2 ml/hr (0 - 5.48) in the later time epoch. Conclusions: The incidence of fast and slow progressors of LVO stroke may be higher than previously anticipated depending on different time quantiles of stroke onset to imaging.

Abstract TMP70: The Need for Speed: Consistently Achieving Arrival to Recanalization Times in 90 Minutes or Less for Large Vessel Occlusion

Introduction: Since the treatment effect of mechanical thrombectomy (MT) is profoundly time-dependent, we created an optimized Comprehensive Stroke Center-Large Vessel Occlusion (CSC-LVO) protocol focusing on three key steps: early vessel imaging on all code stroke patients, standardizing the MT procedure, and integrating a team of stroke-dedicated advanced practice clinicians (APCs) to manage patients across the continuum of initial hospital care. Methods: All direct to CSC (“mothership”) LVO patients treated during the following time periods (Epochs) were retrospectively reviewed: 1/1/2015 to 6/30/2015 (Pre-optimization); 1/1/2016 to 6/30/2016 (Early Vessel Imaging and MT standardization) and 1/1/2017 to 6/30/2017 (Early Vessel Imaging, MT standardization, APC integration). Epochs were separated by 6 months to minimize any “ramp-up” effect. We included all patients who presented with large vessel occlusion stroke (ICA, M1, Basilar), within six hours from symptom onset, and with an NIHSS of 6 or higher. During Epoch 3, APCs were available for 12h/day and 7 days a week. For all cases, the neurointerventional team was activated only after the CTA confirmed large vessel occlusion. To measure efficiency of initial hospital processes, we compared CSC door to CT, door to CTA, door to IV t-PA, door to groin puncture, and door to recanalization across time Epochs. Results: All results are summarized in the table below and there was a marked decrease in median time from CSC arrival to recanalization from 186 to 100 minutes. Within Epoch 3, when APCs were in-house (n=29/44 or 70% of cases), the median [IQR] Door to t-PA, door to groin puncture, and door to recanalization times were lowest 27 [23-31], 53 [42-73], and 86 [72-118] minutes, respectively. Conclusions: A CSC-LVO protocol including early vessel imaging, procedural standardization, and integrating a team of stroke-dedicated APCs enables CSCs to achieve median door to recanalization times in less than 90 minutes.

A Deep Convolutional Neural Network Architecture for Boosting Image Discrimination Accuracy of Rice Species

In this paper, we proposed a machine vision system based on deep convolutional neural network (DCNN) architecture for improving the accuracy of classifying three distinct groups of rice kernel images compared with the traditional approaches. The main advantage of the presented method was able to avoid many heuristics as well as manual labor to tune complex parameters according to the domain to reach a modest level of accuracy in the classical feature extraction algorithms. We trained our models using stochastic gradient descent with momentum of 0.9 and weight decay of 0.0005 to optimize the network parameters and minimize the back-propagation error on the training dataset. We used a batch size between 15 and 150 and epochs time configured between 10 and 25. The experiment results showed that the highest accuracy of 99.4% obtained in the training process with batch size of 15 and epoch time of 20. We also compared the DCNN method with the traditional hand-engineered approaches of PHOG-KNN, PHOG-SVM, GIST-KNN, and GIST-SVM for rice kernel classification. The results showed that DCNN routinely outperforms other methods in similar machine vision tasks. The prediction accuracy results for test datasets by PHOG-KNN, PHOG-SVM, GIST-KNN, and GIST-SVM models were 89.1, 76.9, 90.6, and 92.1%, respectively. The highest prediction accuracy of DCNN is 95.5%, which showed the effectiveness of our proposed method for rice kernel classification. The aim of this study is to set up an automatic and accurate intelligent detection system and offering much value to current rice processing industry. With the comparably high classification accuracy, developed neural network could be used as a tool to achieve better and more objective rice quality evaluation at trading points within the rice marketing system.

UNIX time, UTC, and datetime: Jussivity, prolepsis, and incorrigibility in modern timekeeping

ABSTRACTThis paper examines the three entangled systems of the UNIX time data format, the UTC time standard, and the various administratively defined datetimes used to give specific moments in time names. Due to the increasing prevalence of Linux and Unix‐based systems, a large majority of computing devices, from phones to Web servers, utilize these interlocking systems to structure time. The assemblage as a whole is briefly described, from UNIX time integers to the empirical measurements of atomic vibrations and the earth's rotation within its celestial frame, to the open source Internet Assigned Numbers Authority (IANA) maintained time zone database, which declares a distinct name for each instant within the hundreds of administrative time zones world wide. Three theoretical concepts of jussivity, prolepsis and incorrigibility are operationalized to distinguish each system's contribution to the computational assemblage of modern timekeeping. Bowker's conception of the jussive Archive is used to frame the inquiry, foregrounding the things that these timekeeping practices help us exclude and forget. Calendrical prolepsis is examined as what Siegert calls a cultural technique, one that enables each of these systems to extend its reach into the past and condition our conception of any possible future. Each of these systems utilizes the unique and under‐appreciated abilities of digital systems to enact a kind of incorrigibility, which I argue is inextricably linked with what Hayles has called the cognitive nonconscious. By better understanding the jussive, proleptic, and incorrigible powers deployed in the massive cognitive assemblage that arrays vibrations of atoms alongside celestial mechanics to locate our present, past and future, we open up new possibilities for intervening in these technics. Understanding these dynamics may allow future temporal information systems to therapeutically influence our cognition and our consciousness of time. This paper is intended to provide theoretical support for such efforts.

Application of Improved Fast Dynamic Allan Variance for the Characterization of MEMS Gyroscope on UAV

Microelectromechanical systems (MEMS) are core components in unmanned aerial vehicles (UAV). The precision of MEMS sensors is very important when the GPS signal is invalid. However, the precision and performance of MEMS sensors will be degraded by the changing of environment. Therefore, estimation and identification of the various noise terms existing in MEMS sensors are deemed to be necessary. The Allan variance is a common and standard method to analyze MEMS sensors, but it cannot be used to analyze the dynamic characteristics. The dynamic Allan variance (DAVAR) is a sliding version of the Allan variance. It is a practical tool that could represent the nonstationary behavior of the MEMS signal. As the DAVAR needs to estimate the Allan variance at each time epoch, the computation time grows significantly with the length of the signal series. In this paper, in the case of MEMS gyroscope on UAV, an improved fast DAVAR algorithm based on the choice of relevant time is proposed to shorten the computation time. As an experimental validation, numerical experiments are conducted under the proposed method. The results demonstrate that the improved method could greatly increase the computation speed and does not affect the accuracy of estimation.

A Provident Resource Defragmentation Framework for Mobile Cloud Computing

To facilitate mobile cloud computing, a cloud service provider must dynamically create and terminate a large number of virtual machines (VMs), causing fragmented resources that cannot be further utilized. To solve this problem proactively, most of the existing studies have been based on server consolidation, with the main objective of minimizing the number of active servers. Although this approach can minimize resource fragmentation at a particular time, it may be over aggressive at the price of too frequent VM migration and low system stability. To address this issue, we propose a novel provident resource defragmentation framework that is revenue-oriented with the goal to reduce unnecessary VM migration. Within the proposed framework, we formulate an optimization problem for resource defragmentation at a particular time epoch, with the consideration of the future impact of any VM migration. We then develop an efficient heuristic algorithm that can obtain near-optimal results. Extensive numerical results confirm that our framework can provide the highest profit and can significantly reduce the VM migration cost in practical scenarios.

Optimal Control of Customers to the Service Facility with Two Types of Customers

In this article, we considered a discrete-time service facility system, viewed as a Markov Decision Process (MDP). Decisions are taken at discrete time epochs to control admissions to the system. Here the queue before the server is divided into eligible queue and potential queue. Potential queue has two types of customers (Priority and nonpriority). It is assumed that demands arrived throughout the period but they are satisfied only at the end of the period. The MDP based on average cost criteria is used to find the optimal policy to be implemented for the system. Numerical example is provided to illustrate the problem.

Determination of Minimum Detectable Deformation of Terrestrial Laser Scanning Based on Error Entropy Model

Terrestrial laser scanning (TLS) is a widely used remote sensing technique which can produce very dense point cloud data very promptly and is particularly suited for surface deformation monitoring. Deformation magnitude is typically estimated by comparing TLS scans over the same area but at different time epochs of interest. However, there is an issue related to such a method, which is not clear that whether the difference between two successive surveys results from the surface deformation. Hence, it is vital to determine the minimum detectable deformation (MDD) by a TLS device with a given registration and point cloud error level. In this paper, the MDD is determined based on the computation of the point cloud error entropy. The performance of the proposed method is extensively evaluated numerically using simulated plane board deformation point clouds under a range of distances and incidence angles. This proposed method was also successfully applied to deformation monitoring of one landslide test site located in the Wuhan University of Technology. The experimental results demonstrate that the theoretical MDD has a good match with the actual deformation, and the deformation greater than MDD can be accurately detected by the TLS device.

Dynamic Changes in Upper-Limb Corticospinal Excitability during a 'Pro-/Anti-saccade' Double-Choice Task.

Under natural behavioral conditions, visually guided eye movements are linked to direction-specific modulations of cortico-spinal system (CSS) excitability in upper-limb muscles, even in absence of a manual response. These excitability changes have been shown to be compatible with a covert motor program encoding a manual movement toward the same target of the eyes. The aim of this study is to investigate whether this implicit oculo-manual coupling is enforced following every saccade execution or it depends on the behavioral context. Twenty-two healthy young adults participated in the study. Single-pulse transcranial magnetic stimulation was applied to the motor cortex at nine different time epochs during a double-choice eye task, in which the decision to execute a prosaccade or an antisaccade was made on the color of a peripheral visual cue. By analyzing the amplitude of the motor evoked potentials (MEP) in three distal muscles of the resting upper-limb, a facilitation peak of CSS excitability was found in two of them at 120 ms before the eyes begin to move. Furthermore, a long-lasting, generalized reduced corticomotor excitability develops following the eye response. Finally, a quite large modulation of MEP amplitude, depending on the direction of the saccade, is observed only in the first dorsal interosseous muscle, in a narrow time window at about 150 ms before the eye movement, irrespective of the type of the ocular response (pro-/anti-saccade). This change in CSS excitability is not tied up to the timing of the occurrence of the visual cue but, instead, appears to be tightly time-related to the saccade onset. Observed excitability changes differ in many respects from those previously reported with different behavioral paradigms. A main finding of our study is that the implicit coupling between eye and hand motor systems is contingent upon the particular motor set determined by the cognitive aspects of the performed oculomotor task. In particular, the direction-specific modulation in CSS excitability described in this study appears to be related to perceptual and decision-making processes rather than representing an implicit upper-limb motor program, coupled to the saccade execution.

Inhibiting Mesolimbic Dopamine Neurons Reduces the Initiation and Maintenance of Instrumental Responding

Mesolimbic dopamine perturbations modulate performance of reward-seeking behavior, with tasks requiring high effort being especially vulnerable to disruption of dopamine signaling. Previous work primarily investigated long-term perturbations such as receptor antagonism and dopamine depletion, which constrain the ability to assess dopamine contributions to effort expenditure in isolation from other behavior events, such as reward consumption. Also unclear is if dopamine is required for both initiation and maintenance when a sequence of multiple instrumental responses is required. Here we used optogenetic inhibition of midbrain TH+ neurons to probe the role of dopamine neuron activity during instrumental responding for reward by varying the time epoch of neural inhibition relative to the time of response initiation. Within a fixed-ratio procedure, requiring eight nosepoke responses per reinforcer delivery, or a progressive ratio (PR) procedure, in which within-session response requirements increased exponentially, inhibiting dopamine neurons while mice were engaged in response bouts decreased the probability of continued responding. If inhibition occurred during each attempted bout, the effect was to decrease total responses, and thus amount of rewards earned, over a session. In contrast, if inhibition was applied only during some bouts, mice increased the number of bouts initiated to earn control levels of reward. Inhibiting dopamine neurons while mice were not responding decreased the probability of initiating an instrumental response but had no effect on the amount of effort exerted over the entire session. We conclude that midbrain dopamine signaling promotes initiation of instrumental responding and maintains motivation to continue ongoing bouts of effortful responses.

Validation of a Real-Time Minute-to-Minute Urine Output Monitor and the Feasibility of Its Clinical Use for Patients Undergoing Cardiac Surgery.

Acute kidney injury after cardiac surgery is associated with increased morbidity and mortality. Methods for measuring urine output in real time may better ensure renal perfusion perioperatively in contrast to the current standard of care where urine output is visually estimated after empiric epochs of time. In this study, we describe an accurate method for monitoring urine output continuously during cardiopulmonary bypass. This may provide a means for setting patient-specific targets for blood pressure and cardiopulmonary bypass flow as a potential strategy to reduce the risk for acute kidney injury.

Duration-Variable Participant Recruitment for Urban Crowdsourcing With Indeterministic Trajectories

For urban crowdsourcing applications, the data sensing tasks can be achieved by vehicles traveling on the roads, which can save the expenses on constructing dedicated infrastructures. In this paper, to efficiently handle the crowdsourcing recruitment problem, we propose to recruit participants with the duration-variable principle and prove that it performs better compared to the strategy that recruits vehicles for all required time periods. The duration-variable principle enables recruitment of vehicular sensing resources across different time epochs to maximize the crowdsourcing profits. To ensure the utilization of limited budget, we formulate the duration-variable participant recruitment (DPR) problem with the consideration of indeterministic trajectories to determine which vehicle subset is chosen and how many epochs are provided for each selected vehicle. Since the formulated problem is NP-hard, we propose a two-step DPR algorithm by maximizing the available sensing resource utilization efficiency in each recruitment round, which is shown to be near-optimal and has low computational complexity. Experiments on real traces show that the proposed DPR scheme exceeds three other solutions in providing higher spatial coverage for urban crowdsourcing applications.

General bulk service queueing system with N-policy, multiplevacations, setup time and server breakdown without interruption

In this paper, we have considered an MX / (a,b) / 1 queueing system with server breakdown without interruption, multiple vacations, setup times and N-policy. After a batch of service, if the size of the queue is ξ (< a), then the server immediately takes a vacation. Upon returns from a vacation, if the queue is less than N, then the server takes another vacation. This process continues until the server finds atleast N customers in the queue. After a vacation, if the server finds at least N customers waiting for service, then the server needs a setup time to start the service. After a batch of service, if the amount of waiting customers in the queue is ξ (≥ a) then the server serves a batch of min(ξ,b) customers, where b ≥ a. We derived the probability generating function of queue length at arbitrary time epoch. Further, we obtained some important performance measures.