Sequential Elements Research Articles

SERAD: Soft Error Resilient Asynchronous Design Using a Bundled Data Protocol

The risk of soft errors due to radiation continues to be a significant challenge for engineers trying to build systems that can handle harsh environments. Building systems that are Radiation Hardened by Design (RHBD) is the preferred approach, but existing techniques are expensive in terms of performance, power, and/or area. This paper introduces a novel soft-error resilient asynchronous bundled-data design template, SERAD, which uses a combination of temporal and spatial redundancy to mitigate Single Event Transients (SETs) and upsets (SEUs). SERAD uses Error Detecting Logic (EDL) to detect SETs at the inputs of sequential elements and correct them via re-sampling. Because SERAD only pays the delay penalty in the presence of an SET, which rarely occurs, its average performance is comparable to the baseline synchronous design. We tested the SERAD design using a combination of Spice and Verilog simulations and evaluated its impact on area, frequency, and power on an open-core MIPS-like processor using a NCSU 45nm cell library. Our post-synthesis results show that the SERAD design consumes less than half of the area of the Triple Modular Redundancy (TMR), exhibits significantly less performance degradation than Glitch Filtering (GF), and consumes no more total power than the baseline unhardened design.

Informal sport and curriculum futures: An investigation of the knowledge, skills and understandings for participation and the possibilities for physical education

Internationally, patterns of participation in sport are changing, with so-called ‘informal’ participation displacing club-based and other formally structured involvement in sport. This paper reports research that is investigating changing forms of participation from an educational perspective. It directs attention to what physical education can learn from informal sport and how physical education can align pedagogically with contemporary participation trends, to help grow and sustain young people’s engagement in sport beyond schools. The paper presents findings from two sequential elements of an ongoing research project. The first is a systematic review of literature pertaining to informal participation that examined the skills, knowledge and understanding central to participation that occurs outside of traditional sport structures. Findings from this review highlight that social skills, cultural understandings, and knowledge relating to environment, alongside movement skills, are important in enabling participants to become engaged in, and maintain their involvement in, informal participation. The second element of the research involved documentary analysis to examine the alignment of contemporary curricula, and specifically, the Australian Curriculum Health and Physical Education (AC HPE), with the learning identified as important for informal participation. Findings illustrate clear opportunities for the AC HPE to bring to the fore knowledge, skills and understandings that may extend young people’s engagement with informal participation through their lives. The discussion addresses key issues for policy makers, teachers and teacher educators to consider in the light of this research, if they are to leverage the opportunities for teaching and learning that informal sport presents.

Determinants of unintended pregnancies among nursing mothers in southwest Nigeria

Background/aims Studies have identified risks for unintended pregnancies, globally and in Nigeria, which include ineffective contraception, strong opposition to family planning by partners, number of living children and birth interval. These factors have contributed to the increasing rate of unintended pregnancy and the high rate of induced abortion, with associated consequences such as obstetric haemorrhage, infection and increased maternal morbidity and mortality. However, there is a paucity of information regarding the influence of culture and religion on pregnancy intentions. This study aimed to examine the influence of culture, religion, sociodemographic characteristics, and reproductive characteristics on nursing mothers' perception of unintended pregnancy in southwest Nigeria. Methods This study used a sequential explanatory mixed-method approach, with both quantitative and qualitative elements. A conceptual hierarchical model was used to analyse the influence of three levels of characteristics (sociodemographic, religious and cultural, reproductive) on unintended pregnancy in southwest Nigeria. A total of 400 nursing mothers attending either a postnatal, immunisation, infant welfare or under-five clinic were selected via multistage sampling from primary healthcare centres. Quantitative data were collected from these participants using a semi-structured questionnaire, administered by a researcher. These data were analysed using both bivariate and multivariate analysis. First, they were analysed with either a chi-squared or Fisher exact test, then subjected to a regression model analysis. Qualitative data were collected and subjected to content analysis via focus group discussions with a total of 32 purposively selected participants. Results Approximately 36.5% participants reported their index pregnancy as being unintended. With regression analysis, age (25–34 years: relative risk ratio=0.42, P=0.02; 35–44 years: relative risk ratio=0.21, P=0.003), parity (relative risk ratio=10.38, P<0.00), ethnicity (relative risk ratio=0.13, P=0.002) and religion (relative risk ratio=0.26, P=0.048) were found to be significant risk factors for unintended pregnancy. Conclusions Age, parity, ethnicity and religion were the main determinants of unintended pregnancies. Intervention programmes should therefore be aware of these variables and address myths and misconceptions about pregnancy intentions.

Mechanical Characteristics Generated by Solidification Crack During High Strength Steel Welding

A multiscale method was developed to elaborate weld solidification crack mechanical field. A sequential thermo-mechanical finite element method (FEM) of butt-joint was performed to provide both of geometry and loading condition of submoel. Then mechanical behaviours generated by impurity was achieved by submodelling with embedded solidification cracks in terms of elasto-plastic FEM. The solidification initial cracks were geometrical discontinuity in nature and modelled as mechanical property discontinuity. Results show that additive stress and back stress are built-up at impurity-weld matrix interface. The developed modelling method was validated by solidification crack tests, X-ray tests together with fractography. The underlying mechanisms in suppression solidification cracking by adjustment of alloy contents in flux cored wire aiming to diminish the impurity size and improve the ductility of weld metal were revealed by developed method. Results show that, given a 9 percent increase of the weld metal ductility, a 29.6 percent decrease of the additive stress is achieved; and the longitudinal oriented impurity readily propagates crossing section rather than along impurity longitudinal tip. The susceptibility to cracking is distance-dependent, heavily on fields near to impurity and little on far field.

Educational Paradigm of Academic Writing

The article reveals the concept of academic writing educational paradigm, which is made up of several different didactic aspects to be taken into account in planning and organising the learning process. The aim of the article is to make an overview of these aspects in order to show how academic writing can be incorporated in the existing higher educational curricula, in particular the foreign language course, and to design an effective didactic mechanism of academic writing acquisition. The authors formulate the major principles of organising and implementing the training process, the most important being the competence-and-activity-based approach to teaching, relying on the competence-based model of academic writing worked out by the authors and applying the step-bystep strategy of training. Regarding academic writing as a long process of knowledge, abilities and skills acquisition in which further development always relies on previous achievements allows the authors to presuppose that there are certain corner stones on the way to academic writing competence formation. These are writing a scientific essay, writing a synopsis and writing a research article, which are sequential elements of the paradigm. Correspondingly, the competence in research article writing can be acquired successfully on the basis of similar verbal activities which have very close competence-based patterns. This supposition is confirmed by the results of the experiment in which the students failed to write a research article without special training and wrote a scientific essay instead because they could rely on the skill of essay writing available in their verbal experience. The analysis carried out by the authors allows them to conclude that the way to academic writing, which is rather long and complicated, requires profound understanding of its educational paradigm for implementing the training process within the framework of the higher educational foreign language course.

Material characterization and precise finite element analysis of fiber reinforced thermoplastic composites for 4D printing

Four-dimensional (4D) printing, a new technology emerged from additive manufacturing (3D printing), is widely known for its capability of programming post-fabrication shape-changing into artifacts. Fused deposition modeling (FDM)-based 4D printing, in particular, uses thermoplastics to produce artifacts and requires computational analysis to assist the design processes of complex geometries. However, these artifacts are weak against structural loads, and the design quality can be limited by less accurate material models and numerical simulations. To address these issues, this paper propounds a composite structure design made of two materials – polylactic acid (PLA) and carbon fiber reinforced PLA (CFPLA) – to increase the structural strength of 4D printed artifacts and a workflow composed of several physical experiments and series of dynamic mechanical analysis (DMA) to characterize materials. We apply this workflow to 3D printed samples fabricated with different printed parameters to accurately characterize the materials and implement a sequential finite element analysis (FEA) to achieve accurate simulations. The accuracy of deformation induced by the triggering process is both computationally and experimentally verified with several creative design examples and is measured to be at least 95%, with a confidence interval of (0.972,0.985). We believe the presented workflow is essential to the combination of geometry, material mechanism and design, and has various potential applications.

Hybrid Computing and Decision Technologies in Improving Accuracy of Structural Equation Model for Sustainable Environmentally Friendly Product Management

Main purpose of this research is to study influential variables of green innovation strategy, corporate social responsibility, government policy, transformation leadership including human resource development on the success level in managing sustainable environmentally friendly products of industrial plants. The sequential procedures on statistical techniques are proposed with the survey data on both quantitative and qualitative research elements. Confirmatory factor and path analysis including the structural equation modeling are mixed to identify the causal relationship between variables and the dependent variables. In this article, two metaheuristic algorithms namely sequential evolutionary elements based on variable neighborhood search and particle swarm optimization algorithms are proposed to enhance the sustainable environmentally friendly product management model. The results show that all performance measures of the particle swarm optimization algorithm are better, but not statistically significant when compared. Evolutionary elements from Metaheuristic approaches are the powerful tool for generating the management model and aiding the industries for decision making. The qualitative research was from the multistage sampling and in-depth interviews to finally provide guidelines for managing environmentally friendly products. From the numerical results all of proposed variables affected the success at a high level of opinions. The results of this research will be efficiently used to promote sustainable environmentally friendly products for the manufacturing in Thailand.

Design of testable reversible latches by using a novel efficient implementation of Fredkin gate

ABSTRACTEnergy dissipation caused by information loss in irreversible computations will be an important limitation for the development of nano-scale circuits in the near future. Reductions in energy dissipation comprise one of the important goals of nanotechnology-based methods, including Quantum dot Cellular Automata (QCA), and so it is desirable to consider reversibility in the design of QCA circuits. In this research, a novel reversible Fredkin gate based on QCA is proposed, which is more efficient and less complex than the conventional Fredkin gate. Conservative reversible logic is parity preserving; hence, any permanent or transient fault can be caused a mismatch between the inputs and the outputs and can be concurrently detected if a reversible circuit is implemented with the conservative Fredkin gate. A single missing/additional cell defect is investigated in the proposed Fredkin gate and fault patterns are presented. To demonstrate the efficiency of the proposed design, some testable reversible sequential elements, such as D-latch, JK-latch, T-latch and SR-latch, are designed by using it. Our proposed concurrent testable designs greatly reduce the occupied area and maximise the circuit density in comparison with previously reported designs. The proposed designs are simulated and verified using QCA Designer ver.2.0.3 and HDLQ.

Shear stiffness in the lower cervical spine: Effect of sequential posterior element injury.

The aim of this study was to determine the effect of the posterior ligaments and facet joints on the shear stiffness of lower cervical functional spinal units in anterior, posterior, and lateral shear. Five functional spinal units were loaded in anterior, posterior, and right lateral shear up to 100 N using a custom-designed apparatus in a materials testing machine. Specimens were tested in three conditions: intact, with the posterior ligaments severed, and with the facet joints removed. There was a significant decrease in anterior stiffness in the 20-100 N load range from 186 (range: 98-327) N/mm in the intact condition to 105 (range: 78-142) N/mm in the disc-only condition (p = 0.03). Posterior stiffness between these condition decreased significantly from 134 (range: 92-182) N/mm to 119 (range: 83-181) N/mm (p = 0.03). There was no significant effect of posterior ligament removal on shear stiffness. No significant differences were found in the lateral direction or in the 0-20 N range for any direction. Under a 100-N shear load, the facet joints played a significant role in the stiffness of the cervical spine in the anterior-posterior direction, but not in the lateral direction.

A Novel Strong Decorrelation Approach for Image Subband Coding Using Polynomial EVD Algorithms

Subband coding is a popular technique to achieve multichannel data compression and efficient data transmission in image and video communications. In this paper, we focus on designing a data-dependent image subband coder which divides the image into strongly (total) decorrelated and spectrally majorized subbands, which seeks to reduce the redundancy to achieve better compression and efficient transmission. To achieve strong decorrelation and spectral majorization between the subbands, we adopt a set of new iterative polynomial eigenvalue decomposition (PEVD) algorithms: sequential matrix diagonalization (SMD) and maximum element sequential matrix diagonalization (ME-SMD). Using this SMD-based PEVD approach, we design the data dependent subband coder (DDSC) for image subband coding. We compare the performance of the proposed SMD/ME-SMD algorithms with the existing DDSC methods like SBR2, SBR2C, K–L transform (KLT) coder and data independent subband coder (DISC)-based discrete wavelet transform (DWT) technique. To measure the performance, we use the parameters like coding gain, correlation coefficient, MSE (mean square error) and peak signal-to-noise ratio (PSNR). The presented simulation results for standard images in the absence of quantization show that the proposed SMD-based PEVD technique performs far better than the existing techniques.

A Numerical Investigation of a Single-Shot in a DEM-FEM Approach to Shot Peening Simulation

Shot peening (SP) is a controlled and systematic process of surface treatment that has a large number of controllable process parameters that make its application highly challenging. It involves the shooting of small and hard metallic balls at a targeted surface, with the aim of enhancing the fatigue strength of the workpiece under unfavorable service conditions. The compressive residual stress (CRS) induced by this application is expensive to evaluate experimentally. This paper presents a numerical model of the impact of a single-shot on a metallic surface, with the aim to set the stage for a realistic multiple shots peening simulation. The approach proposed herein is a sequential Discrete Element-Finite Element (DE-FE) coupled simulation, based on the use of different types of coefficients of restitution (CoRs) with emphasis on the energetic CoR. The energetic CoR relates the shot/target contact forces to the fractional strain energy needed for localized plastic deformation of the near-surface layer in the workpiece. The generated results of the induced compressive residual stresses (CRS) and equivalent plastic strain (PEEQ) from single-shot simulations are validated with similar results from the literature. Our study clarifies the strain energy aspects of a single-shot impact responsible for the desired effects of CRS and PEEQ, thereby laying the groundwork for accurate and realistic modeling of the SP process via the DEM-FEM approach.

The role of levodopa in improving procedural motor training for patients with chronic stroke

To test the hypothesis that administration of dopamine precursor levodopa improves procedural motor learning (defined as the ability to acquire novel movement patterns gradually through practice) in patients with residual motor deficits in the chronic phase after stroke(> or =1 y after stroke). Neurology department in a Tashkent Medical Academy. Eighteen patients with chronic motor dysfunction because of stroke (33 men, 25 women; age range, 53-78 y; mean time poststroke +/- SD, 3.3+/-2.1 y). Patients received 3 doses of levodopa (100mg of levodopa plus 25mg of carbidopa) or placebo before 1 session of procedural motor learning. Procedural motor learning performed by using the paretic hand assessed by using a modified version of the serial reaction time task with a prbabilistic sequence. The primary outcome measure was the difference in reaction times between random and sequential elements. Levodopa significantly improved our primary outcome measure, procedural motor learning, compared with placebo (P<.05). Reaction times to random elements, analysis of error rates, psychophysical assessments, and performance in a simple motor task were comparable between conditions, indicating that better learning under levodopa was not caused by differences in response styles, arousal, mood, or motor reaction times but that levodopa modulated learning. Our results show that levodopa may improve procedural motor learning in patients with chronic stroke, in line with our hypothesis. These findings suggest that this interventional strategy in combination with customary rehabilitative treatments could significantly improve the outcome of neurorehabilitation in the chronic stage after stroke.

A Highly Efficient Conditional Feedthrough Pulsed Flip-Flop for High-Speed Applications

A novel type of highly efficient conditional feedthrough pulse-triggered flip-flop (P-FF) is proposed and demonstrated. The data-to-output (D-to-Q) delay in this circuit was highly optimized using predischarging and conditional signal feedthrough schemes. Power consumption was also reduced using a shared pulse generator and an output feedback-controlled conditional keeper, which diminished the floating status of the internal node. The driving strength of this design was further enhanced by including an additional pull-down path at the output node. Various postlayout simulation results applied to 16-nm FinFET technology demonstrated a higher energy efficiency (at all input data toggle rates) for the proposed topology than comparable P-FF devices. Notably, the proposed model achieved a 62% D-to-Q delay reduction, compared to a transmission gate FF, outperforming the device by more than 66% in terms of power efficiency and 87% in energy efficiency (at a 50% input data toggle rate). Improvements were even more significant in comparison with other conventional P-FFs. These results suggest the proposed design to be a viable new option for high-efficiency sequential elements in high-speed applications.

A Physics-Based Variability-Aware Methodology to Estimate Critical Charge for Near-Threshold Voltage Latches

Near-threshold voltage (NTV) digital VLSI circuits, though important, have their sequential elements vulnerable to soft errors. The critical charge for a single event upset for a D-latch depends on its fan-out load, supply voltage, and transistor level parameters. A SPICE simulation-based estimation of the critical charge is highly resource/time intensive. In this paper, we propose a physics-based semianalytical model to estimate the critical charge of a static D-latch as a function of its fan-out load, supply voltage, temperature, and transistor levels parameters. It can, therefore, be used while considering process voltage temperature (PVT) variations. The critical charge estimated by the model is in good agreement with SPECTER simulations with a maximum error of less than 3.4% employing STMicroelectronics 65-nm process design kit (PDK). We also validated the model at 32-nm technology node using technology computer-aided design (TCAD) mixed-mode simulations (a maximum error of less than 7.5% is observed). Using this model, we devise a methodology to estimate the critical charge using a few dc simulations and a single transient SPICE simulation for a given PDK. This is an end-to-end method to include an accurate estimation of the critical charge for latches in NTV standard cell library characterization.

Skyrmion latch and flip-flop in magnetic nanotracks with gradient anisotropy

Skyrmion sequential elements are proposed and demonstrated. A skyrmion latch is implemented in a single device where skyrmion motion is controlled by spin-orbit torque and voltage-controlled magnetic anisotropy in a magnetic nanotrack with gradient anisotropy. Micromagnetic simulations have been carried out to verify the feasibility of the latch function and to study device performance. The results indicate that the proposed skyrmion latch have potential advantages, including a small device footprint, a tunable switching speed, and low power consumption. Furthermore, a master-slave skyrmion flip-flop can be simply implemented by cascading two skyrmion latches to be further used for constructing a skyrmion register. This work provides a guideline to design spintronics for sequential logic circuits.

The dynamic layering of relational pairs in L2 classrooms

AbstractThe focus of this paper will be placed upon the methods people use to interact in second language learning settings, discussing interactional aspects of language use in the ongoing production of classroom events. The extracts selected for analysis were drawn from Portuguese language lessons (for beginner and advanced students) in a Chinese university. The results show how L2 classroom participants secure joint orientation and mutual understanding of the categorial pairs (such as ‘teacher-student’ and ‘native-non-native’) being invoked in the sequential organization of the utterances. In other words, when classroom members show orientation to a categorial pair, their subsequent moves will exhibit predicates (actions) of that pair, which will be available to the analyst as phenomena to be explored. This suggests that the sequential elements of the interaction and the membership categorization work carried out by the participants require attention for praxiological enquiries.

Proposition of Machine Learning Driven Personalized Marketing Approach for E-Commerce

The ubiquity of digital devices and Internet has formed a constantly connected online environment which led to the extensive adoption of e-commerce. However, the active participation of growing number of stakeholders intensifies the highly competitive landscape of the dynamic e-commerce market and the scarcity of trust in e-commerce business impede the generation of consistent sales growth. The obstruction necessitates the implementation of innovative marketing strategies to enhance the relationships with customers to develop customer loyalty. Therefore, a machine learning driven personalized marketing approach is proposed to facilitate the implementation of personalized marketing in which there are 2 significant sequential elements namely, the development of personalized marketing contents and delivery of the contents to prospective customers. Cluster analysis is employed to perform customer segmentation to discover customer segments due to the capability of the analysis to identify similarities in customer preferences in which the discovered customer segments are used to construct personalized marketing contents. In addition, artificial neural network is employed to predict prospective customers due to the capability of artificial neural network to comprehend complex relationships between customer demographics and buying behaviour in which the prediction facilitates the delivery of the constructed personalized marketing contents to potential repeat customer to optimize the marketing initiative. The combination of cluster analysis and artificial neural network empowers the construction of an efficacious marketing pipeline which enhances the competency of e-commerce businesses.

Sequential finite element modelling of lightning arc plasma and composite specimen thermal-electric damage

Highly complex phenomena such as lightning strikes require simulation methods capable of capturing many different physics. However, completing this in one simulation is not always desired or possible. In such instances there can be a need for a methodology to transfer loading boundary conditions from one simulation to the next while accounting for the characteristic form of the loading and the dissimilar domain and mesh geometries. Herein, the objective is to combine two models to enable the automatic sequential simulation of a lightning arc and a composite test specimen. The approach is developed using Finite Element models, with a Magnetohydrodynamics model representing the lightning plasma and a thermal-electric model representing the specimen. The specimen mesh and loading boundary conditions are automatically generated based on the predicted output of the preceding plasma model. The precision, run-time and flexibility of the proposed approach is demonstrated, with thermal damage predictions generated in approximately 33 h. Resulting from the integrated modelling capability is the first time prediction of damage representing the test electric boundary conditions rather than assumed specimen boundary conditions (herein using test ‘Waveform B’).

Design of Asynchronous Genetic Circuits

Most digital electronic circuits utilize a timing reference to synchronize the progression of signals and enable sequential memory elements. These designs may not be realizable in biological substrates due to the lack of a reliable high-frequency clock signal. Asynchronous designs eliminate the need for a clock with data encodings and request/acknowledge handshake protocols. This paper proposes a workflow to automate the design of asynchronous genetic circuits. This workflow extends genetic design tools by leveraging asynchronous logic design methods customized for this technology. This workflow is demonstrated on a genetic sensor that uses filtering and cellular communication to improve its reliability.

A Multiscale Topology Optimization Methodology Based on Sequential Element Rejection–Admission and Boundary Element Evolvement

To enhance both the solution speed and quality of a topology optimization (TO), a multiscale TO methodology by combining the sequential element rejection–admission (SERA) and boundary element evolvement is presented. In the proposed SERA approach, only the sensitivities of the boundary elements need to be computed and used, and an adaptive parameter updating strategy is introduced to balance the requirements on both convergence and quality performances. To eliminate the dependence of the final solution on the initial topology, a new hole generating mechanism is proposed. In addition, a sensitivity filter is designed to remove the checkerboard patterns as well as to further eliminate the mesh-dependent problem. Numerical results are reported to showcase the merits of the proposed methodology.