Miracle-dz/UniFAR-FTUs huggingface dataset:
Systemic Lidocaine to Improve Postoperative Quality of Recovery After Ambulatory Laparoscopic Surgery

BACKGROUND:Perioperative systemic lidocaine has been shown to have beneficial postoperative analgesic effects. The only previous study examining the use of lidocaine in the outpatient setting did not detect an opioid-sparing effect after hospital discharge. More importantly, it is unknown whether systemic lidocaine provides a better postoperative quality of recovery to patients undergoing ambulatory surgery. Our objective in the current study was to examine the effect of systemic lidocaine on postoperative quality of recovery in patients undergoing outpatient laparoscopic surgery. METHODS:The study was a prospective, randomized, double-blind, placebo-controlled clinical trial. Healthy female subjects were randomized to receive lidocaine (1.5 mg/kg bolus followed by a 2 mg/kg/h infusion until the end of the surgical procedure) or the same volume of saline. The primary outcome was the Quality of Recovery-40 questionnaire at 24 hours after surgery. A 10-point difference represents a clinically relevant improvement in quality of recovery based on previously reported values on the mean and range of the Quality of Recovery-40 score in patients after anesthesia and surgery. Other data collected included opioid consumption, pain scores, and time to meet hospital discharge. Data were compared using group t tests and the Wilcoxon exact test. The association between opioid consumption and quality of recovery was evaluated using Spearman &rgr;. P < 0.01 was used to reject the null hypothesis for the primary outcome. RESULTS:Seventy subjects were recruited and 63 completed the study. There were no baseline differences regarding subject and surgical characteristics between the study groups. Patients in the lidocaine group had better global quality of recovery scores compared with the saline group, median difference of 16 (99% confidence interval [CI], 2–28), P = 0.002. Patients in the lidocaine group met hospital discharge criteria faster than the saline group, mean difference of −26 minutes (95% CI, −6 to −46 minutes) (P = 0.03). After hospital discharge, subjects in the lidocaine group required less oral opioids, median difference of −10 (95% CI, 0 to −30) (oral milligrams morphine equivalents), than the saline group (P = 0.01). There was an inverse association between postoperative opioid consumption and quality of recovery (&rgr; = 0.64, P < 0.001). CONCLUSIONS:Systemic lidocaine improves postoperative quality of recovery in patients undergoing outpatient laparoscopy. Patients who received lidocaine had less opioid consumption, which translated to a better quality of recovery. Lidocaine is a safe, inexpensive, effective strategy to improve quality of recovery after ambulatory surgery.
Static and Dynamic Temperature-Aware Scheduling for Multiprocessor SoCs

Thermal hot spots and high temperature gradients degrade reliability and performance, and increase cooling costs and leakage power. In this paper, we explore the benefits of temperature-aware task scheduling for multiprocessor system-on-a-chip (MPSoC). We evaluate our techniques using workload characteristics collected from a real system by Sun's Continuous System Telemetry. We first solve the task scheduling problem statically using integer linear programming (ILP). The ILP solution is guaranteed to be optimal for the given assumptions for tasks. We formulate ILPs for minimizing energy, balancing energy, and reducing hot spots, and provide an extensive comparison of their thermal behavior against our technique. Our static solution can reduce the frequency of hot spots by 35%, spatial gradients by 85%, and thermal cycles by 61% in comparison to the ILP for minimizing energy. We then design dynamic scheduling policies at the OS-level with negligible performance overhead. Our adaptive dynamic policy reduces the frequency of high-magnitude thermal cycles and spatial gradients by around 50% and 90%, respectively, in comparison to state-of-the-art schedulers. Reactive thermal management strategies, such as thread migration, can be combined with our scheduling policy to further reduce hot spots, temperature variations, and the associated performance cost.
Una Experiencia Colaborativa Internacional para la mejora curricular en Ingeniería del Software

El desarrollo de la industria del software se considera desde una perspectiva global, es por eso que la elaboracion de una curricula orientada a Ingenieria del Software debe tomar en cuenta recomendaciones y criterios internacionales. Nuestro trabajo muestra la experiencia colaborativa internacional para la mejora curricular en la Escuela Profesional de Ingenieria de Sistemas de la Universidad Nacional de San Agustin, Arequipa – Peru. La curricula utilizo las recomendaciones de la ACM para Programas de Ingenieria del Software (SE2004). Se tomaron en cuenta los criterios de Acreditacion de ABET, opiniones de la industria nacional e internacional y experiencias de otros programas de Ingenieria del Software ya acreditados. Esta nueva curricula actualmente se encuentra en su tercer ano de funcionamiento. Destacamos los aportes recibidos y las dificultades encontradas. Mejora Curricular, ABET, Ingenieria del Software, SE2004, Experiencia Colaborativa.
X Chromosomes Alternate between Two States prior to Random X-Inactivation

Early in the development of female mammals, one of the two X chromosomes is silenced in half of cells and the other X chromosome is silenced in the remaining half. The basis of this apparent randomness is not understood. We show that before X-inactivation, the two X chromosomes appear to exist in distinct states that correspond to their fates as the active and inactive X chromosomes. Xist and Tsix, noncoding RNAs that control X chromosome fates upon X-inactivation, also determine the states of the X chromosomes prior to X-inactivation. In wild-type ES cells, X chromosomes switch between states; among the progeny of a single cell, a given X chromosome exhibits each state with equal frequency. We propose a model in which the concerted switching of homologous X chromosomes between mutually exclusive future active and future inactive states provides the basis for the apparently random silencing of one X chromosome in female cells.
On mitigating memory bandwidth contention through bandwidth-aware scheduling

Shared-memory multiprocessors have dominated all platforms from high-end to desktop computers. On such platforms, it is well known that the interconnect between the processors and the main memory has become a major bottleneck. The bandwidth-aware job scheduling is an effective and relatively easy-to-implement way to relieve the bandwidth contention. Previous policies understood that bandwidth saturation hurt the throughput of parallel jobs so they scheduled the jobs to let the total bandwidth requirement equal to the system peak bandwidth. However, we found that intra-quantum fine-grained bandwidth contention still happened due to a program's irregular fluctuation in memory access intensity, which is mostly ignored in previous policies. In this paper, we quantify the impact of bandwidth contention on overall performance. We found that concurrent jobs could achieve a higher memory bandwidth utilization at the expense of super-linear performance degradation. Based on such an observation, we proposed a new workload scheduling policy. Its basic idea is that interference due to bandwidth contention could be minimized when bandwidth utilization is maintained at the level of average bandwidth requirement of the workload. Our evaluation is based on both SPEC 2006 and NPB workloads. The evaluation results on randomly generated workloads show that our policy could improve the system throughput by 4.1% on average over the native OS scheduler, and up to 11.7% improvement has been observed.
Collaborative web browsing: multiple users, multiple pages, concurrent access, one display

Situations where users want to engage in collaborative web browsing are becoming increasingly common. However, current web technologies aren't designed to allow multiple users to browse the web simultaneously within a single common browser or application since they are unable to handle issues such as simultaneous access by multiple pointers, and multiple simultaneous points of focus within an application. The web-based solution that we propose is an implementation of a forward proxy that injects third-party web pages with specialized JavaScript that provides the aforementioned functionalities transparently, without affecting the original third-party web pages, and thus effectively extending them for collaborative web browsing scenarios. Moreover, our solution provides functionalities for cloning web screens to encourage awareness of the browsing activities of collaborators, and does not require any configuration or software installation on web-enabled client devices, allowing for easy walk-up-and-use interaction.
EUD for enterprise process and information management

This position paper presents research on End-User Development (EUD) for enterprise systems, which is aiming at improving the ability of Small and Medium Enterprises (SMEs) to adapt their software systems to individual and changing needs. These research efforts can be divided into two main directions: process-centric EUD and data-centric EUD. In particular, two basic sub-domains are addressed: (i) end-user driven business process composition and management as well as (ii) end-user driven composition of data-centric and analytic applications. Both topics are closely related since analytic applications may provide decision support in processes and processes may be the subject of analysis, e.g. for process optimization purposes. Advances in these research topics are presented through a brief overview of the developed concepts.
Improvement of model-mediated teleoperation using a new hybrid environment estimation technique

In a haptic teleoperation system, the incorporation of knowledge about the remote environment in the controller design can improve stability and performance. Model-mediated teleoperation adopts this idea by rendering an estimated model of the remote environment on local site instead of transmitting force/velocity flows. Thus, the user perceives locally generated forces corresponding to the estimated and transmitted model parameters and the control loop between master and slave is opened. Less conservative stability boundaries and the applicability to teleoperation systems with arbitrary time delay are the main advantages of this approach. In order to guarantee a high fidelity, the estimation has to fit well with the measurements. In this paper, we extend the approach of model-mediated teleoperation to a full 6 degrees-of-freedom (DOF) teleoperation system with negligible time delay. We furthermore propose a hybrid approach for the estimation of the remote environment by combining the classical Kelvin-Voigt model and the nonlinear Hunt-Crossley model. Persistent excitation and device-dependent limitations of the estimation algorithm are discussed. Experimental results show stability and accuracy of the estimation technique as well as a superior fidelity of the proposed approach compared to a position-based admittance controller with fixed parameters even with negligible time delay.
Discovery of a dust cloud next to σ Orionis

We report on the discovery of a mid-infrared source at a projected distance of only 1200 AU from the O9.5 V star σ Orionis. The spatially resolved, fan-shaped morphology and the presence of an ionization front, as well asevidence in the spectrum for processed dust grains, all suggest that it is a proto-planetary disk being dispersed by the intense ultraviolet radiation from σ Orionis. We compute the mass budget and the photo-evaporation timescale, and discuss the possible nature of this remarkable object.
A novel navigation system using augmented reality technology for distribution work at optical connector panels

This paper proposes a new navigation system using augmented reality (AR) technology for distribution work in central offices. This system helps operators to work accurately and effectively when they perform installation or removal work at connector panels accommodating a large number of optical fiber cords, and it also enables a database to be accurately constructed. We employ AR technology, which overlays virtual information (or images) on real-world images to support the connection or disconnection of optical fiber cords at a connector panel. The work can be undertaken accurately because image-guided navigation information is provided via an augmented view on a monitor. The proposed system has the potential to be applied to other maintenance scenarios, and to lead to innovations in maintenance work. In this paper, we describe the current issues for optical distribution work at connector panels and show the requirements for the work. Next, we detail the design of our prototype system, and demonstrate the performance of this system experimentally on three conditions (fixed, hand-held and hand-carried). We found that a graphically assisted image was provided to the operators and the support by image-guided navigation was useful for them. Moreover, we discuss the goal and the features of the proposed system. This proposed system when used with AR technology has the advantages of flexibility as well as cost-effectiveness by comparison with LED, VLC and RFID navigation systems .
Using CDISC ODM and the RDF Data Cube for the Semantic Enrichment of Longitudinal Clinical Trial Data

The development of ontology, linked data standards and tools for semantic enrichment, opens new opportunities to analyse and reuse the clinical data collected as part of clinical trials and longitudinal studies. This paper presents our approach on the semantic enrichment of the data collected as part of the Australian, Imaging, Biomarker and Lifestyle study of Ageing (AIBL). AIBL is a large scale longitudinal clinical study into neurodegenerative diseases that has been designed to support investigations of the predictive utility of various biomarkers, cognitive parameters and lifestyle factors as indicators of Alzheimer’s disease. The objective of this paper is to highlight the complementarities of Clinical Data Management Systems standards, such as CDISC ODM, with novel approaches to manage large volume of heterogeneous linked data resources, such as the W3C RDF Data Cube. We start by describing the standards, ontologies, linked data resources and tools that we use to aggregate the study data. Next, we describe the structure of the Linked Clinical Data Cube and the tools that we use to map the recorded medication intake information to the relevant standards in the Australian context: SNOMED CT and the Australian Medical Terminology. We also discuss how our approach could be extended to take advantage of past and present Linked Open Data initiatives in the Health Care and Life Sciences community.
Protein trafficking mechanisms associated with neurite outgrowth and polarized sorting in neurons

Neuronal differentiation in vitro and in vivo involves coordinated changes in the cellular cytoskeleton and protein trafficking processes. I review here recent progress in our understanding of the membrane trafficking aspects of neurite outgrowth of neurons in culture and selective microtubule‐based polarized sorting in fully polarized neurons, focusing on the involvement of some key molecules. Early neurite outgrowth appears to involve the protein trafficking machineries that are responsible for constitutive trans‐Golgi network (TGN) to plasma membrane exocytosis, utilizing transport carrier generation mechanisms, SNARE proteins, Rab proteins and tethering mechanisms that are also found in non‐neuronal cells. This vectorial TGN‐plasma membrane traffic is directed towards several neurites, but can be switch to concentrate on the growth of a single axon. In a mature neuron, polarized targeting to the specific axonal and dendritic domains appears to involve selective microtubule‐based mechanisms, utilizing motor proteins capable of distinguishing microtubule tracks to different destinations. The apparent gaps in our knowledge of these related protein transport processes will be highlighted.
On the Integrability and Chaos of an N=2 Maxwell-Chern-Simons-Higgs Mechanical

We apply different integrability analysis procedures to a reduced (spatially homogeneous) mechanical system derived from an off-shell non-minimally coupled N=2 Maxwell-Chern-Simons-Higgs model that presents BPS topological vortex excitations, numerically obtained with an ansatz adopted in a special critical coupling parametric regime. As a counterpart of the regularity associated to the static soliton-like solution, we investigate the possibility of chaotic dynamics in the evolution of the spatially homogeneous reduced system, descendant from the full N=2 model under consideration. The originally rich content of symmetries and interactions, N=2 susy and non-minimal coupling, singles out the proposed model as an interesting framework for the investigation of the role played by (super-)symmetries and parametric domains in the triggering/control of chaotic behavior in gauge systems. After writing down effective Lagrangian and Hamiltonian functions, and establishing the corresponding canonical Hamilton equations, we apply global integrability Noether point symmetries and Painleve property criteria to both the general and the critical coupling regimes. As a non-integrable character is detected by the pair of analytical criteria applied, we perform suitable numerical simulations, as we seek for chaotic patterns in the system evolution. Finally, we present some Comments on the results and perspectives for further investigations and forthcoming communications.
Comments on "Data Mining Static Code Attributes to Learn Defect Predictors"

In this correspondence, we point out a discrepancy in a recent paper, "data mining static code attributes to learn defect predictors," that was published in this journal. Because of the small percentage of defective modules, using probability of detection (pd) and probability of false alarm (pf) as accuracy measures may lead to impractical prediction models.
Motion Estimation Based on Hidden Segmentation

A new algorithm for computing precise estimates of the motion vectors of moving objects in a sequence of images is presented. The proposed method is a fusion of block-matching motion estimation and global optimization technique. To avoid some contradictions between global optimization techniques and piece-wise smooth values of sought motion vectors, a hidden segmentation model is utilized. Computer simulation and experimental results demonstrate a good performance of the method in terms of dynamic motion analysis.
Affect in meetings: An interpersonal construct in dynamic interaction processes

Team meetings are affect-laden environments where team members may motivate and energize, or frustrate and agitate each other. The importance of affect in teams generally and in team meetings particularly has led to a growing body of research that focuses on group affect. Existing conceptual and empirical work has contributed to our understanding of the nature of group affect and its implications for critical organizational phenomena, including emotion convergence and divergence, emotional contagion, emotional norms, and leadership. In this chapter, we review and integrate this literature and suggest directions for future research on affective dynamics during team meetings. We first briefly review contemporary research that has used a compositional approach to group affect. We highlight the need for a dynamic approach to group affect and call for more research in this area. We assess what has been learned and discuss suggestions for future theoretical development and methodological approaches for meetings researchers invested in this important interpersonal, dynamic construct.
Modeling Event-Based Systems in Ptolemy II EE 249 : Design of Embedded Systems : Models , Validation , and Synthesis Fall 2001

Networked sensors are becoming an increasingly important field of research as power and size requirements grow smaller and it becomes easier to embed thousands or millions of these devices in our environment. However, there is currently very little programming support for these and other event-based systems. In this paper, we focus on TinyOS, an event-based operating system for Smart Dust networked sensors. We show how to model and simulate TinyOS at the scheduler level in Ptolemy II.
Tokenisation of Class Files for an Embedded Java Processor

We present a new approach to extend the tokenisation scheme used in Java card to allow for both invokevirtual and invokeinterface calls to be dispatched using the same virtual method table. An algorithm is described for token assignment to identify methods that can use the same token, even in the presence of interfaces. As a consequence much of the string data in the class files is no longer required at runtime, resulting in compression of the class files by a factor of two. This is applied to the Java 2 micro edition (J2ME) platform and simplifies the method dispatch process to the point where it can be implemented directly in hardware.
Dendritic Cell Regulation by Cannabinoid-Based Drugs

Cannabinoid pharmacology has made important advances in recent years after the cannabinoid system was discovered. Studies in experimental models and in humans have produced promising results using cannabinoid-based drugs for the treatment of obesity and cancer, as well as neuroinflammatory and chronic inflammatory diseases. Moreover, as we discuss here, additional studies also indicates that these drugs have immunosuppressive and anti-inflammatory properties including modulation of immune cell function. Thus, manipulation of the endocannabinoid system in vivo may provide novel therapeutic strategies against inflammatory disorders. At least two types of cannabinoid receptors, cannabinoid 1 and cannabinoid 2 receptors are expressed on immune cells such as dendritic cells (DC). Dendritic cells are recognized for their critical role in initiating and maintaining immune responses. Therefore, DC are potential targets for cannabinoid-mediated modulation. Here, we review the effects of cannabinoids on DC and provide some perspective concerning the therapeutic potential of cannabinoids for the treatment of human diseases involving aberrant inflammatory processes.
SOM-GA-SVM Detection Based Spectrum Sensing in Cognitive Radio

Spectrum sensing is a key function for the second users (SUs) to determine availability of a channel in the primary user's (PUs) spectrum in cognitive radio(CR). In order to achieve that, much research of energy detection has been studied, but they play poor performance in low signal-to-noise (SNR) environment. In this paper, we proposed Support Vector Machines (SVM) based on Genetic Algorithms (GA), which is a novel method of classifying in real time. GA has the ability to find out the optimal nuclear function parameter and penalty parameter of SVM. Due to the massive training data increase the computational complexity and make lower performance of SVM. So we re-sample the massive data by using Self Organizing Map (SOM) to obtain representative compressed data. So we set up the SOM-GA-SVM classification model for detecting and it has idle recognized ability in low SNR compared with SVM model and energy detection. Simulation results show that the proposed sensing method can obtain excellent performance.