Design and experimental validation of liquid crystal-based reconfigurable reflectarray elements with improved bandwith in F-band

A reconfigurable reflectarray which exploits the dielectric anisotropy of liquid crystals (LC) has been designed to operate in the frequency range from 96 to 104 GHz. The unit cells are composed of three unequal length parallel dipoles placed above an LC substrate. The reflectarray has been designed using an accurate model which includes the effects of anisotropy and inhomogeneity. An effective permittivity that accounts for the real effects of the LC has also been used to simplify the analysis and design of the unit cells. The geometrical parameters of the cells have been adjusted to simultaneously improve the bandwidth, maximize the tunable phase-range and reduce the sensitivity to the angle of incidence. The performance of the LC based unit cells has been experimentally evaluated by measuring the reflection amplitude and phase of a reflectarray consisting of 52x54 identical cells. The good agreement between measurements and simulations validate the analysis and design techniques and demonstrate the capabilities of the proposed reflectarray to provide beam scanning in F band.

Kinematic Analysis and Dimensional Synthesis of Exechon Parallel Kinematic Machine for Large Volume Machining

A parallel kinematic machine (PKM) topology can only give its best performance when its geometrical parameters are optimized. In this paper, dimensional synthesis of a newly developed PKM is presented for the first time. An optimization method is developed with the objective to maximize both workspace volume and global dexterity of the PKM. Results show that the method can effectively identify design parameter changes under different weighted objectives. The PKM with optimized dimensions has a large workspace to footprint ratio and a large well-conditioned workspace, hence justifies its suitability for large volume machining.

A language-independent parallel refactoring framework

Recent trends towards increasingly parallel computers mean that there needs to be a seismic shift in programming practice. The time is rapidly approaching when most programming will be for parallel systems. However, most programming techniques in use today are geared towards sequential, or occasionally small-scale parallel, programming. While refactoring has so far mainly been applied to sequential programs, it is our contention that refactoring can play a key role in significantly improving the programmability of parallel systems, by allowing the programmer to apply a set of well-defined transformations in order to parallelise their programs. In this paper, we describe a new language-independent refactoring approach that helps introduce and tune parallelism through high-level design patterns targeting a set of well-specified parallel skeletons. We believe this new refactoring process is the key to allowing programmers to truly start thinking in parallel. © 2012 ACM.

Evaluating Many Treatments and Biomarkers in Oncology: A New Design

There is a pressing need for more-efficient trial designs for biomarker-stratified clinical trials. We suggest a new approach to trial design that links novel treatment evaluation with the concurrent evaluation of a biomarker within a confirmatory phase II/III trial setting. We describe a new protocol using this approach in advanced colorectal cancer called FOCUS4. The protocol will ultimately answer three research questions for a number of treatments and biomarkers: (1) After a period of first-line chemotherapy, do targeted novel therapies provide signals of activity in different biomarker-defined populations? (2) If so, do these definitively improve outcomes? (3) Is evidence of activity restricted to the biomarker-defined groups? The protocol randomizes novel agents against placebo concurrently across a number of different biomarker-defined population-enriched cohorts: BRAF mutation; activated AKT pathway: PI3K mutation/absolute PTEN loss tumors; KRAS and NRAS mutations; and wild type at all the mentioned genes. Within each biomarker-defined population, the trial uses a multistaged approach with flexibility to adapt in response to planned interim analyses for lack of activity. FOCUS4 is the first test of a protocol that assigns all patients with metastatic colorectal cancer to one of a number of parallel population-enriched, biomarker-stratified randomized trials. Using this approach allows questions regarding efficacy and safety of multiple novel therapies to be answered in a relatively quick and efficient manner, while also allowing for the assessment of biomarkers to help target treatment.

Paraphrasing:Generating parallel programs using refactoring

Refactoring is the process of changing the structure of a program without changing its behaviour. Refactoring has so far only really been deployed effectively for sequential programs. However, with the increased availability of multicore (and, soon, manycore) systems, refactoring can play an important role in helping both expert and non-expert parallel programmers structure and implement their parallel programs. This paper describes the design of a new refactoring tool that is aimed at increasing the programmability of parallel systems. To motivate our design, we refactor a number of examples in C, C++ and Erlang into good parallel implementations, using a set of formal pattern rewrite rules. © 2013 Springer-Verlag Berlin Heidelberg.

An accelerated method of developing DBT projects using CDIO partner institutions as parallel processors

The cycle of the academic year impacts on efforts to refine and improve major group design-build-test (DBT) projects since the time to run and evaluate projects is generally a full calendar year. By definition these major projects have a high degree of complexity since they act as the vehicle for the application of a range of technical knowledge and skills. There is also often an extensive list of desired learning outcomes which extends to include professional skills and attributes such as communication and team working. It is contended that student project definition and operation, like any other designed product, requires a number of iterations to achieve optimisation. The problem however is that if this cycle takes four or more years then by the time a project’s operational structure is fine tuned it is quite possible that the project theme is no longer relevant. The majority of the students will also inevitably experience a sub-optimal project experience over the 5 year development period. It would be much better if the ratio were flipped so that in 1 year an optimised project definition could be achieved which had sufficient longevity that it could run in the same efficient manner for 4 further years. An increased number of parallel investigators would also enable more varied and adventurous project concepts to be examined than a single institution could undertake alone in the same time frame.
This work-in-progress paper describes a parallel processing methodology for the accelerated definition of new student DBT project concepts. This methodology has been devised and implemented by a number of CDIO partner institutions in the UK & Ireland region. An agreed project theme was operated in parallel in one academic year with the objective of replacing a multi-year iterative cycle. Additionally the close collaboration and peer learning derived from the interaction between the coordinating academics facilitated the development of faculty teaching skills in line with CDIO standard 10.

Self-Feedback Motion Control for Cable-Driven Parallel Manipulators

This article proposes a closed-loop control scheme based on joint-angle feedback for cable-driven parallel manipulators (CDPMs), which is able to overcome various difficulties resulting from the flexible nature of the driven cables to achieve higher control accuracy. By introducing a unique structure design that accommodates built-in encoders in passive joints, the seven degrees of freedom (7-DOF) CDPM can obtain joint angle values without external sensing devices, and it is used for feedback control together with a proper closed-loop control algorithm. The control algorithm has been derived from the time differential of the kinematic formulation, which relates the joint angular velocities to the time derivative of cable lengths. In addition, the Lyapunov stability theory and Monte Carlo method have been used to mathematically verify the self-feedback control law that has tolerance for parameter errors. With the aid of co-simulation technique, the self-feedback closed-loop control is applied on a 7-DOF CDPM and it shows higher motion accuracy than the one with an open-loop control. The trajectory tracking experiment on the motion control of the 7-DOF CDPM demonstrated a good performance of the self-feedback control method.

Parallel Robot

Parallel robot (PR) is a mechanical system that utilized multiple computer-controlled limbs to support one common platform or end effector. Comparing to a serial robot, a PR generally has higher precision and dynamic performance and, therefore, can be applied to many applications. The PR research has attracted a lot of attention in the last three decades, but there are still many challenging issues to be solved before achieving PRs’ full potential. This chapter introduces the state-of-the-art PRs in the aspects of synthesis, design, analysis, and control. The future directions will also be discussed at the end.

Shortening design time through multiplatform simulations with a portable OpenCL golden-model: the LDPC decoder case

Hardware designers and engineers typically need to explore a multi-parametric design space in order to find the best configuration for their designs using simulations that can take weeks to months to complete. For example, designers of special purpose chips need to explore parameters such as the optimal bitwidth and data representation. This is the case for the development of complex algorithms such as Low-Density Parity-Check (LDPC) decoders used in modern communication systems. Currently, high-performance computing offers a wide set of acceleration options, that range from multicore CPUs to graphics processing units (GPUs) and FPGAs. Depending on the simulation requirements, the ideal architecture to use can vary. In this paper we propose a new design flow based on OpenCL, a unified multiplatform programming model, which accelerates LDPC decoding simulations, thereby significantly reducing architectural exploration and design time. OpenCL-based parallel kernels are used without modifications or code tuning on multicore CPUs, GPUs and FPGAs. We use SOpenCL (Silicon to OpenCL), a tool that automatically converts OpenCL kernels to RTL for mapping the simulations into FPGAs. To the best of our knowledge, this is the first time that a single, unmodified OpenCL code is used to target those three different platforms. We show that, depending on the design parameters to be explored in the simulation, on the dimension and phase of the design, the GPU or the FPGA may suit different purposes more conveniently, providing different acceleration factors. For example, although simulations can typically execute more than 3x faster on FPGAs than on GPUs, the overhead of circuit synthesis often outweighs the benefits of FPGA-accelerated execution.

An efficacy and mechanism evaluation study of Levosimendan for the Prevention of Acute oRgan Dysfunction in Sepsis (LeoPARDS): Protocol for a randomized controlled trial

Background

Organ dysfunction consequent to infection (‘severe sepsis’) is the leading cause of admission to an intensive care unit (ICU). In both animal models and early clinical studies the calcium channel sensitizer levosimendan has been demonstrated to have potentially beneficial effects on organ function. The aims of the Levosimendan for the Prevention of Acute oRgan Dysfunction in Sepsis (LeoPARDS) trial are to identify whether a 24-hour infusion of levosimendan will improve organ dysfunction in adults who have septic shock and to establish the safety profile of levosimendan in this group of patients.

This is a multicenter, randomized, double-blind, parallel group, placebo-controlled trial. Adults fulfilling the criteria for systemic inflammatory response syndrome due to infection, and requiring vasopressor therapy, will be eligible for inclusion in the trial. Within 24 hours of meeting these inclusion criteria, patients will be randomized in a 1:1 ratio stratified by the ICU to receive either levosimendan (0.05 to 0.2 μg.kg^-1.min^-1 or placebo for 24 hours in addition to standard care. The primary outcome measure is the mean Sequential Organ Failure Assessment (SOFA) score while in the ICU. Secondary outcomes include: central venous oxygen saturations and cardiac output; incidence and severity of renal failure using the Acute Kidney Injury Network criteria; duration of renal replacement therapy; serum bilirubin; time to liberation from mechanical ventilation; 28-day, hospital, 3 and 6 month survival; ICU and hospital length-of-stay; and days free from catecholamine therapy. Blood and urine samples will be collected on the day of inclusion, at 24 hours, and on days 4 and 6 post-inclusion for investigation of the mechanisms by which levosimendan might improve organ function. Eighty patients will have additional blood samples taken to measure levels of levosimendan and its active metabolites OR-1896 and OR-1855. A total of 516 patients will be recruited from approximately 25 ICUs in the United Kingdom.

This trial will test the efficacy of levosimendan to reduce acute organ dysfunction in adult patients who have septic shock and evaluate its biological mechanisms of action.

Barriers to Goals of Care Discussions With Seriously Ill Hospitalized Patients and Their Families: A Multicenter Survey of Clinicians

Importance: Seriously ill hospitalized patients have identified communication and decision making about goals of care as high priorities for quality improvement in end-of-life care. Interventions to improve care are more likely to succeed if tailored to existing barriers.

Objective: To determine, from the perspective of hospital-based clinicians, (1) barriers impeding communication and decision making about goals of care with seriously ill hospitalized patients and their families and (2) their own willingness and the acceptability for other clinicians to engage in this process.

Design, Setting, and Participants: Multicenter survey of medical teaching units of nurses, internal medicine residents, and staff physicians from participating units at 13 university-based hospitals from 5 Canadian provinces.

Main Outcomes and Measures: Importance of 21 barriers to goals of care discussions rated on a 7-point scale (1 = extremely unimportant; 7 = extremely important).

Results: Between September 2012 and March 2013, questionnaires were returned by 1256 of 1617 eligible clinicians, for an overall response rate of 77.7% (512 of 646 nurses [79.3%], 484 of 634 residents [76.3%], 260 of 337 staff physicians [77.2%]). The following family member-related and patient-related factors were consistently identified by all 3 clinician groups as the most important barriers to goals of care discussions: family members' or patients' difficulty accepting a poor prognosis (mean [SD] score, 5.8 [1.2] and 5.6 [1.3], respectively), family members' or patients' difficulty understanding the limitations and complications of life-sustaining treatments (5.8 [1.2] for both groups), disagreement among family members about goals of care (5.8 [1.2]), and patients' incapacity to make goals of care decisions (5.6 [1.2]). Clinicians perceived their own skills and system factors as less important barriers. Participants viewed it as acceptable for all clinician groups to engage in goals of care discussions-including a role for advance practice nurses, nurses, and social workers to initiate goals of care discussions and be a decision coach.

Conclusions and Relevance: Hospital-based clinicians perceive family member-related and patient-related factors as the most important barriers to goals of care discussions. All health care professionals were viewed as playing important roles in addressing goals of care. These findings can inform the design of future interventions to improve communication and decision making about goals of care.

Enhancing design space exploration by extending CPU/GPU specifications onto FPGAs

The design cycle for complex special-purpose computing systems is extremely costly and time-consuming. It involves a multiparametric design space exploration for optimization, followed by design verification. Designers of special purpose VLSI implementations often need to explore parameters, such as optimal bitwidth and data representation, through time-consuming Monte Carlo simulations. A prominent example of this simulation-based exploration process is the design of decoders for error correcting systems, such as the Low-Density Parity-Check (LDPC) codes adopted by modern communication standards, which involves thousands of Monte Carlo runs for each design point. Currently, high-performance computing offers a wide set of acceleration options that range from multicore CPUs to Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs). The exploitation of diverse target architectures is typically associated with developing multiple code versions, often using distinct programming paradigms. In this context, we evaluate the concept of retargeting a single OpenCL program to multiple platforms, thereby significantly reducing design time. A single OpenCL-based parallel kernel is used without modifications or code tuning on multicore CPUs, GPUs, and FPGAs. We use SOpenCL (Silicon to OpenCL), a tool that automatically converts OpenCL kernels to RTL in order to introduce FPGAs as a potential platform to efficiently execute simulations coded in OpenCL. We use LDPC decoding simulations as a case study. Experimental results were obtained by testing a variety of regular and irregular LDPC codes that range from short/medium (e.g., 8,000 bit) to long length (e.g., 64,800 bit) DVB-S2 codes. We observe that, depending on the design parameters to be simulated, on the dimension and phase of the design, the GPU or FPGA may suit different purposes more conveniently, thus providing different acceleration factors over conventional multicore CPUs.

Towards generalized Doherty power amplifier design for multiband operation

This paper presents a new variant of broadband Doherty power amplifier that employs a novel output combiner. A new parameter ∝ is introduced to permit a generalized analysis of the recently reported Parallel Doherty power amplifier (PDPA),and hence offer design flexibility. The circuit prototype of the new DPA fabricated using GaN devices exhibits maximum drain efficiency of 85% at 43-dBm peak power and 63% at 6-dB backoff power (BOP). Measured drain efficiency of >60% at peak power across 500-MHz frequency range and >50% at 6-dB BOP across 480-MHz frequency range were achieved, confirming the  theoretical wideband characteristics of the new DPA.