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The architectural design process may utilize decision-making algorithms; usually, this takes a long time when using analog methods. Today, sequential processing (CPU) or parallel processing (GPU) works with architectural design in different ways, such as Graphical User Interfaces using CPU or ray-tracing rendering using GPU. Architectural design paradigms have not yet fully adapted to the processing computer core paradigm. Thus, this research proposes design guidelines to take the computing core paradigm and transport it to architectural design with a practical case that tests the core's performance with a genetic algorithm (form-finding process). The genetic algorithm was tested on a computer based on a central processing unit (CPU), another on a graphics processing unit (GPU), and the last one on quantum computers (Quantum Gates). The guidelines operate these cores under the cloud computing paradigm, supported by new components made in Rhinoceros–Grasshopper 3D. The discussion shows the integration of the computation core paradigm with the current digital architecture design process. [ABSTRACT FROM AUTHOR]

The oyster shell is a valuable calcium resource; however, its application is limited by its high NaCl content. Therefore, to establish the use of oyster shells as a viable resource, conditional experiments were conducted to select optimum parameters for NaCl removal. For this purpose, we compared leaching methods with batch and sequential procedures, determined the volume of water used for washing, and evaluated the mixing speed. The batch system removed NaCl when washed for >24 h over a shell to water ratio of 1:5. Results from the batch experiments confirmed that washing twice can completely remove NaCl from the shells on a like-for-like basis. Additionally, the efficiency of washing was sequentially evaluated in terms of the number of washing cycles. Compared to batch experiments, continuous washing could remove NaCl in approximately 10 min at a shell to water ratio of 1:4. We found that regardless of the washing methods, the volume of water used for washing is key for enhancing NaCl removal. Consequently, increasing the volume of water used for washing coupled with a proper sorting of fine particles can help enhance the purity of calcium, which will enable the use of oyster shell as an alternate Ca-resource. [ABSTRACT FROM AUTHOR]

Recently, researchers have proposed a novel and computationally efficient method to design optimal control places and an iteration approach that computes the reachability graph once to obtain a maximally permissive, if any, liveness-enforcing supervisor of flexible manufacturing systems (FMS). The approach solves the set of integer linear inequalities to compute control places. If, given a Petri net model, no solution exists, the optimal control place does not exist for the Petri net model. We discover that a solution always exists for systems of simple sequential processes with resources (S3PR), but not for the case of FMS modelled by generalised Petri nets (GPN). We propose a theory to prove that there are no good states that will be forbidden by the control policy for S3PR, in which live and dead states cannot have the same weighted sum of tokens in the complimentary set of a siphon. For a system of simple sequential processes with general resource requirements (S3PGR2) modelled by GPN, we find the reason why the integer linear programming (ILP) may not have solutions, which is consistent with the fact that optimal supervisor synthesis for GPN remains unknown. We show that live and dead states may have the same weighted sum of tokens in the complimentary set of a siphon in a GPN. These theoretical results are verified by case studies. [ABSTRACT FROM AUTHOR]

There are many studies reported in the literature comparing the effectiveness of new control policies by testing them against a well-known S3PR (systems of simple sequential processes with resources) model. We propose a new approach that recovers the system from empty-siphon states to former live states. It therefore attains the same number of states as the original uncontrolled model by adding monitors (and control arcs) similar to the prevention approach. There is no need to perform a reachability analysis. INA (integrated net analyser) analysis indicates that the resulting controlled model is live and reaches all 26,750 states (in the uncontrolled model), more than the maximally permissive 21,581 states. Only seven monitors are employed, fewer than in most other approaches. This arises from the fact that no new problematic siphons are generated due to the added monitors. We discuss the disadvantages (a variant of the scheme to overcome the disadvantages is also discussed) and physical meaning of the policy. We further propose a lossless approach by colouring some arcs. This not only avoids material loss, but also tackles the livelock problem. [ABSTRACT FROM AUTHOR]

Elimination of spatiotemporal bias of asynchronous multiple sensors is the foundation of accurate multi-sensor data fusion. In this article, a sequential processing simultaneous spatiotemporal bias and state estimation algorithm for asynchronous multi-sensor system is proposed. The spatiotemporal bias is combined with target state to obtain an augmented state vector, and the augmented state model is formulated. For asynchronous multi-sensor with known but different sampling periods, a sequential processing method is proposed to handle the multiple measurements. The relationship of sensor measurements, target state and spatiotemporal bias is analysed, and the corresponding measurement model is formulated. A novel algorithm, in which the unscented Kalman filter is used to handle the nonlinearity between the augmented measurement and state vectors, is proposed to jointly estimate the spatiotemporal bias and target state. Simulation results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Fitting facial landmarks on unconstrained videos is a challenging task with broad applications. At present, many methods of one-shot landmark fitting have been proposed with varying degrees of success. However, most of them are heavily sensitive to initializations and usually rely on offline-trained static models, which limit their performance on sequential images with extensive variations. Therefore, they usually can't align the deformed face very well. To address these limitations, we propose a method of deformed landmark fitting (DLF) for sequential faces, which is designed based on active shape model (ASM) and deformation tracking/correction. This method overcomes the loss of consecutive information between frames, and makes full use of the motion variation information of video sequences in time and space dimensions. Firstly, the optical flow values of several possible deformation points on the face are calculated by the large displacement optical flow (LDOF) model, and the tracking of these points in the current frame are performed through the optical flow motion vector. Secondly, the initial shape of face in each frame is established by the locations of these deformation points and the global shape model in ASM algorithm. Finally, on the basis of initial shape, according to the guidance of local texture model in ASM algorithm, different correction strategies are applied to different landmarks for local search, and then each landmark is reasonably suppressed to obtain the ultimate results. Our DLF observably improves the fitting accuracy for deformed faces, and takes full advantage of the continuity among video sequences. Compared with some state-of-the-art landmarkers, extensive experiments on landmark fitting for sequential faces show that our DLF performs outstandingly in terms of accuracy and robustness. [ABSTRACT FROM AUTHOR]

The authors set out to determine the brain dominance characteristics of students enrolled in business statistics courses in a historically Black university in a major southeastern Texas city. Thereafter, the authors investigated the relationship between a student's brain hemispheric preference and academic performance in college courses, which emphasize problem solving. The results reported in this study reveal that left brain– and right brain–dominant students are at parity when it comes to performance in a problem-solving course. Moreover, both left brain– and right brain–dominant learners perform better than whole-brain dominant learners in a problem-solving course. [ABSTRACT FROM AUTHOR]

Scoliosis is a common spinal condition where the spine curves to the side and thus deforms the spine. Curvature estimation provides a powerful index to evaluate the deformation severity of scoliosis. In current clinical diagnosis, the standard curvature estimation method for assessing the curvature quantitatively is done by measuring the Cobb angle, which is the angle between two lines, drawn perpendicular to the upper endplate of the uppermost vertebra involved and the lower endplate of the lowest vertebra involved. However, manual measurement of spine curvature requires considerable time and effort, along with associated problems such as interobserver and intraobserver variations. In this article, we propose an automatic system for measuring spine curvature using the anterior-posterior (AP) view spinal X-ray images. Due to the characteristic of AP view images, we first reduced the image size and then used horizontal and vertical intensity projection histograms to define the region of interest of the spine which is then cropped for sequential processing. Next, the boundaries of the spine, the central spinal curve line, and the spine foreground are detected by using intensity and gradient information of the region of interest, and a progressive thresholding approach is then employed to detect the locations of the vertebrae. In order to reduce the influences of inconsistent intensity distribution of vertebrae in the spine AP image, we applied the deep learning convolutional neural network (CNN) approaches which include the U-Net, the Dense U-Net, and Residual U-Net, to segment the vertebrae. Finally, the segmentation results of the vertebrae are reconstructed into a complete segmented spine image, and the spine curvature is calculated based on the Cobb angle criterion. In the experiments, we showed the results for spine segmentation and spine curvature; the results were then compared to manual measurements by specialists. The segmentation results of the Residual U-Net were superior to the other two convolutional neural networks. The one-way ANOVA test also demonstrated that the three measurements including the manual records of two different physicians and our proposed measured record were not significantly different in terms of spine curvature measurement. Looking forward, the proposed system can be applied in clinical diagnosis to assist doctors for a better understanding of scoliosis severity and for clinical treatments. [ABSTRACT FROM AUTHOR]

Manufacturing semiconductor wafers involves many sequential processes, and each process has various equipment-related variables or factors, which results in high-dimensional data. However, measuring the quality of all wafers is time and cost intensive, and only a small proportion of the wafers is labeled. Further, equipment factors are not always measured by sensors due to the complicated process. Variable selection, which is performed to reduce the dimensionality of the input variable space while improving or preserving regression performance by selecting important input factors, plays an important role in regression problems. We propose a variable selection procedure to find the main equipment factors that affect in-process wafer quality in consideration of the following issues: 1) imputation for missing values; 2) semi-supervised regression for unlabeled data; and 3) redundancy among variables. In the proposed procedure, partial least squares and least absolute shrinkage and selection operator regression are utilized as prediction models. Experiments using two semiconductor equipment datasets were conducted to evaluate the performance of the proposed procedure. [ABSTRACT FROM AUTHOR]

Abstract Demonic and angelic nondeterminism play fundamental roles as abstraction mechanisms for formal modelling. In contrast with its demonic counterpart, in an angelic choice failure is avoided whenever possible. Although it has been extensively studied in refinement calculi, in the context of process algebras, and of the Communicating Sequential Processes (CSP) algebra for refinement, in particular, it has been elusive. We show here that a semantics for an extended version of CSP that includes both demonic and angelic choice can be provided using Hoare and He's Unifying Theories of Programming (UTP). Since CSP is given semantics in the UTP via reactive designs (pre and postcondition pairs) we have developed a theory of angelic designs and a conservative extension of the CSP theory using reactive angelic designs. To characterise angelic nondeterminism appropriately in an algebra of processes, however, a notion of divergence that can undo the history of events needs to be considered. Taking this view, we present a model for CSP where angelic choice completely avoids divergence just like in the refinement calculi for sequential programs. Highlights • Angelic nondeterminism, as understood in refinement calculi, is considered in CSP. • The UTP framework enables the systematic study of angelic nondeterminism. • A multirelational model for angelic choice in CSP requires a complete lattice. • Process algebras may be endowed with angelic choices that avoid divergence. [ABSTRACT FROM AUTHOR]

Making value judgements on one's academic work is a fundamental skill, particularly for those within the higher education sector. Evaluative practices such as reflection in and on action (Schön, 1987; Cowan, 2006) and surveys on teaching effectiveness (Jones, Gaffney-Rhys and Jones, 1987; Praslova, 2010) are often proposed as a means of gathering evidence. The aim of this paper is to ask what theories of change (ToC) (Connell and Kubisch, 1999), selfevaluative practices, and barriers to effective implementation could be identified and what level of freedom and autonomy lecturers experience in evaluating their own work. This small study used a RUFDATA evaluative tool (Saunders, 2000) with sixteen full-time lecturers and took place in an Institute of Technology (IoT) in Ireland. Five theories of change were identified (1) transformative focused, (2) profession focused, (3) discipline focused, (4) workplace focused and (5) module focused, along with six self-evaluation practice themes and nine barriers to effective practice. Utilising Bamber's (2011b) discretion framework, participants were found to have autonomy in choosing what and how to evaluate their practice. The practical knowledge (Habermas, 1971) presented here offers an alternative approach to how academic work is 'valued', judged and understood from the lecturer's perspective. This paper proposes the view of self-evaluation, not as a set of standalone practices, but as part of a sequential process arising from a lecturer's purposeful academic intentions. The theories of change are used to judge the value of their work within the setting. Therefore, the proposed categories can offer a discourse to justify specific self-evaluative practices for quality assurance and enhancement. [ABSTRACT FROM AUTHOR]

Abstract We model an economy-wide production network by cascading binary compounding functions, based on the sequential processing nature of the production activities. As we observe a hierarchy among the intermediate processes spanning the empirical input–output transactions, we utilize a stylized sequence of processes for modeling the intra-sectoral production activities. Under the productivity growth that we measure jointly with the state-restoring elasticity parameters for each sectoral activity, the network of production completely replicates the records of multi-sectoral general equilibrium prices and shares for all factor inputs observed in two temporally distant states. Thereupon, we study propagation of a small exogenous productivity shock onto the structure of production networks by way of hierarchical clustering. Highlights • A Cascaded CES production function is examined for modeling industrial production. • Intra-industrial sequence of processes is emulated from the inter-industrial hierarchy. • Substitution elasticities are calibrated to restore the two observed equilibrium states. • Restoring substitution elasticities endogenize the transition of production networks. • Economic gain of external productivity shock is examined in a dynamical context. [ABSTRACT FROM AUTHOR]

Soelberg (1966, 1967a, 1967b) developed a job search and choice model that is interpreted here as a four-phase, sequential process. An attempt is made to clarify the model, some of its hypotheses, and the measures used in Soelberg's research. Theoretical and practical implications of the model are presented; deficiencies of previous tests of the model are noted; and future research directions are suggested. [ABSTRACT FROM AUTHOR]

Discusses buffer design analysis and optimization algorithms for sequential production lines. Simulation of two-stage tandem queues; Parameters of tandem queues derived from real production environments; Construction of statistical models by the least-squares method for the throughput and the coefficient of the variation of interdeparture times.

Abstract An increasing amount of studies indicates that experiencing increased task demands, triggered for example by conflicting stimulus features or low perceptual fluency, lead to processing adjustments. While these demand-triggered processing adjustments have been shown for different paradigms (e.g., response conflict tasks, perceptual disfluency, task switching, dual tasking), most of them are restricted to the visual modality. The present study investigated as to whether the challenge to understand speech signals in normal-hearing subjects would also lead to sequential processing adjustments if the processing fluency of the respective auditory signals changes from trial to trial. To that end, we used spoken number words (one to nine) that were either presented with high (clean speech) or low perceptual fluency (i.e., vocoded speech as used in cochlear implants—Experiment 1; speech embedded in multi-speaker babble noise as typically found in bars—Experiment 2). Participants had to judge the spoken number words as smaller or larger than five. Results show that the fluency effect (performance difference between high and low perceptual fluency) in both experiments was smaller following disfluent words. Thus, if it's hard to understand, you try harder. Highlights • Vocoded-speech and (multi-speaker) background noise exemplify auditory disfluency. • Auditory (dis-)fluency increases task demands and incurs performance costs. • Auditory (dis-)fluency triggers effort mobilization and sequential adjustments. • Not only conflict, but also disfluency is used for immediate behavioral adjustments. [ABSTRACT FROM AUTHOR]

Formal methods advocate the crucial role played by the algebraic approach in specification and implementation of programs. Traditionally, a top-down approach (with denotational model as its origin) links the algebra of programs with the denotational representation by establishment of the soundness and completeness of the algebra against the given model, while a bottom-up approach (a journey started from operational model) introduces a variety of bisimulations to establish the equivalence relation among programs, and then presents a set of algebraic laws in support of program analysis and verification. This paper proposes a new roadmap for linking theories of programming. Our approach takes an algebra of programs as its foundation, and generates both denotational and operational representations from the algebraic refinement relation. This new approach is applied in this paper to GCL (Guarded Command Language) and CSP (Communicating Sequential Processes) to link their various semantical representations based on their algebraic semantics. [ABSTRACT FROM AUTHOR]

The essence of psychological theories of memory is highlighted in the article. It is proved that the memory of subjects of communication has a three-component structure: the sensory register, short-term and longterm memory. The specifics of the work of psychological mechanisms of each of its structural and functional components are revealed. Physical signs of new information items that are valuable to communication subjects, are transmitted to processing and preservation, and invaluable and unrecognized - are sent to the sensory register buffer. Two directions of movement of the signs of information units in the short-term memory - incoming and outgoing - are considered. Through the incoming direction, psychological mechanisms supply valuable signs of information units for parallel or sequential processing, integration into a holistic image and encoding, and through the outgoing - direct them to reproduction or to long-term memory for storage. In long-term memory, they activate the appropriate and inappropriate codes and represent their semantic concepts for both recognizing the signs of new information units and for reproducing memorized information in order to enrich, modify, consolidate or implement it. [ABSTRACT FROM AUTHOR]

Language plays a pivotal role in the evolution of human culture, yet the evolution of the capacity for language-uniquely within the hominin lineage-remains little understood. Bringing together insights from cognitive psychology, neuroscience, archaeology and behavioural ecology, we hypothesize that this singular occurrence was triggered by exaptation, or 'hijacking', of existing cognitive mechanisms related to sequential processing and motor execution. Observed coupling of the communication system with circuits related to complex action planning and control supports this proposition, but the prehistoric ecological contexts in which this coupling may have occurred and its adaptive value remain elusive. Evolutionary reasoning rules out most existing hypotheses regarding the ecological context of language evolution, which focus on ultimate explanations and ignore proximate mechanisms. Coupling of communication and motor systems, although possible in a short period on evolutionary timescales, required a multi-stepped adaptive process, involving multiple genes and gene networks. We suggest that the behavioural context that exerted the selective pressure to drive these sequential adaptations had to be one in which each of the systems undergoing coupling was independently necessary or highly beneficial, as well as frequent and recurring over evolutionary time. One such context could have been the teaching of tool production or tool use. In the present study, we propose the Cognitive Coupling hypothesis, which brings together these insights and outlines a unifying theory for the evolution of the capacity for language. [ABSTRACT FROM AUTHOR]

Flexible manufacturing systems exhibit a high degree of resource sharing. Since the parts advancing through the system compete for a finite number of resources, a deadlock may occur. Accordingly, many pioneers make efforts in the issue. However, how to obtain maximally permissive supervisors in deadlock flexible manufacturing system is an extremely difficult and time-consuming problem. In existing literature, place invariant) and graph analysis method are merged called maximal number of forbidding First Bad Marking (FBM) problem to obtained optimal controllers with a small number of control places. However, this prevention just can be used in some special nets. For general cases, deadlocks could still exist. Therefore, this paper tries to propose one improved iterative deadlock prevention policy to solve above disadvantage. Experimental results show that the proposed improved policy can be used in all kinds of nets. In other words, it does improve the drawback of conventional maximal number of forbidding First Bad Marking (FBM) problem technology. [ABSTRACT FROM AUTHOR]

The subject of this paper is a program verification method that takes into account abortion caused by partial functions in program statements. In particular, boolean expressions of various statements will be investigated that are not well-defined. For example, a loop aborts if its execution begins in a state for which the loop condition is undefined. This work considers the program constructs of nondeterministic sequential programs and also deals with the synchronization statement of parallel programs introduced by Owicki and Gries [7]. The syntax of program constructs will be reviewed and their semantics will be formally defined in such a way that they suit the relational model of programming developed at Eőtvős Loránd University [3, 4]. This relational model defines the program as a set of its possible executions and also provides definition for other important programming notions like problem and solution. The proof rules of total correctness [2, 5, 8, 9, 7] will be extended by treating abortion caused by partial functions. The use of these rules will be demonstrated by means of a verification case study. [ABSTRACT FROM AUTHOR]

Sequential fluorescence sensing of Zn 2+ /Cd 2+ ions and phosphate anion by new quinoline based sensors(L1 and L2) have been presented. Sensors exhibit highly selective fluorescence “turn-on” sensing properties to Zn 2+ /Cd 2+ ions in CH 3 OH/H 2 O(1/1, v/v, Tris, 10 mol·L −1 , pH 7.4) solution with a 1:1 binding stoichiometry. The complexes display high selectivity to H 2 PO 4 - and HPO 4 2- anions through fluorescence “turn-off” respond. The results of Zn 2+ /Cd 2+ ions and phosphate anion sequential recognition via fluorescence changes make sensors L1 and L2 have potential utility for Zn 2+ / Cd 2+ ions and phosphate anion detection in aqueous media. [ABSTRACT FROM AUTHOR]

Models based on deep convolutional networks have dominated recent image interpretation tasks; we investigate whether models which are also recurrent are effective for tasks involving sequences, visual and otherwise. We describe a class of recurrent convolutional architectures which is end-to-end trainable and suitable for large-scale visual understanding tasks, and demonstrate the value of these models for activity recognition, image captioning, and video description. In contrast to previous models which assume a fixed visual representation or perform simple temporal averaging for sequential processing, recurrent convolutional models are “doubly deep” in that they learn compositional representations in space and time. Learning long-term dependencies is possible when nonlinearities are incorporated into the network state updates. Differentiable recurrent models are appealing in that they can directly map variable-length inputs (e.g., videos) to variable-length outputs (e.g., natural language text) and can model complex temporal dynamics; yet they can be optimized with backpropagation. Our recurrent sequence models are directly connected to modern visual convolutional network models and can be jointly trained to learn temporal dynamics and convolutional perceptual representations. Our results show that such models have distinct advantages over state-of-the-art models for recognition or generation which are separately defined or optimized. [ABSTRACT FROM PUBLISHER]

In this brief overview paper, we analyse information flow in the brain. Although Shannon's information concept, in its pure algebraic form, has made a number of valuable contributions to neuroscience, information dynamics within the brain is not fully captured by its classical description. These additional dynamics consist of self-organisation, interplay of stability/instability, timing of sequential processing, coordination of multiple sequential streams, circular causality between bottom-up and top-down operations, and information creation. Importantly, all of these processes are dynamic, hierarchically nested and correspond to continuous brain state change, even if the external environment remains constant. This is where metastable coordination comes into play. In a metastable regime of brain functioning, as a result of the simultaneous co-existence of tendencies for independence and cooperation, information is continuously created, preserved for some time and then dissipated through the formation of dynamical and nested spatio-temporal coalitions among simple neuronal assemblies and larger coupled conglomerates of them--so-called delocalised operational modules. [ABSTRACT FROM AUTHOR]

A multicore processor has multiple processing cores on the same chip. Unicore and multicore processors are architecturally different. Since individual instructions are needed to be scheduled onto one of the available cores, it effectively decreases the number of instructions executed on the individual core of a multicore processor. As each core of a multicore processor has a private register file, it results in reduced register pressure. To effectively utilize the potential benefits of the multicore processor, the sequential program must be split into small parallel regions to be run on different cores, and the register allocation must be done for each of these cores. This article discusses register allocating heuristics for fine grained threads which can be scheduled on multiple cores. Spills are computed and its effect on speed-up, power consumption and performance per power is compared for a RAW benchmark suite. [ABSTRACT FROM AUTHOR]

As biological image databases are growing rapidly, automated species identification based on digital data becomes of great interest for accelerating biodiversity assessment, research and monitoring. This research applied high performance computing (HPC) to a medicinal plant identification system. A parallel technique for medicinal plant image processing using Fuzzy Local Binary Pattern (FLBP) is proposed. The FLBP method extends the Local Binary Pattern (LBP) approach by employing fuzzy logic to represent texture images. The main goal of this research was to measure the efficiency of using the proposed parallel technique for medicinal plant image processing and evaluation in order to find out whether this approach is reasonable for handling large data sets. The parallel processing technique was designed in a message-sending model. 30 species of Indonesian medical plants were analyzed. Each species was represented by 48 leaf images. Performance evaluation was measured using the speed-up, efficiency, and isoefficiency of the parallel computing technique. Preliminary results show that HPC worked well in reducing the execution time of medical plant identification. In this work, parallel processing of training images was 7.64 times faster than with sequential processing, with efficiency values greater than 0.9. Parallel processing of testing images was 6.73 times faster than with sequential processing, with efficiency values over 0.9. The system was able to identify images with an accuracy of 68.89%. [ABSTRACT FROM AUTHOR]

Many procedures have been proposed in the literature to select the simulated alternative with the best mean performance from a finite set of alternatives. Among these procedures, frequentist procedures are typically designed under either the subset-selection (SS) formulation or the indifference-zone (IZ) formulation. Both formulations may encounter problems when the goal is to select the unique best alternative for any configuration of the means. In particular, SS procedures may return a subset that contains more than one alternative, and IZ procedures hinge on the relationship between the chosen IZ parameter and the true mean differences that is unknown to decision makers a priori. In this paper, we propose a new formulation that guarantees to select the unique best alternative with a user-specified probability of correct selection (PCS), as long as the means of alternatives are unique, and we design a class of fully sequential procedures under this formulation. These procedures are parameterized by the PCS value only, and their continuation boundaries are determined based on the Law of the Iterated Logarithm. Furthermore, we show that users can add a stopping criterion to these procedures to convert them into IZ procedures, and we argue that these procedures have several advantages over existing IZ procedures. Lastly, we conduct an extensive numerical study to show the performance of our procedures and compare their performance to existing procedures. [ABSTRACT FROM AUTHOR]

Faults modelling is essential to anticipate failures in critical systems. Traditionally, Static Fault Trees are employed to this end, but Temporal and Dynamic Fault Trees are gaining evidence due to their enriched power to model and detect intricate propagation of faults that lead to a failure. In previous work, we showed a strategy based on the process algebra CSP and Simulink models to obtain fault traces that lead to a failure. Although that work used Static Fault Trees, it could be used with Temporal or Dynamic Fault Trees. In the present work we define an algebra of temporal faults (with a notion of fault propagation) and prove that it is indeed a Boolean algebra. This allows us to inherit Boolean algebra's properties, laws and existing reduction techniques, which are very beneficial for faults modelling and analysis. We illustrate our work on a simple but real case study supplied by our industrial partner EMBRAER. [ABSTRACT FROM AUTHOR]

Efficient polymer solar cells based on poly[2, 6-(4, 4-bis-(2-ethylhexyl)-4 H -cyclopenta[2,1- b ;3,4- b ′]dithiophene)- alt -4,7-(2,1,3-fluorobenzothiadiazole)] (PCPDTFBT) and [6,6]-phenyl-C 71 -butyric acid methyl ester (PC 71 BM) are successfully fabricated by a sequential processing (SqP). With appropriate orthogonal solvent and thermal treatment, the SqP film can form an inter-diffused layer, and the SqP devices show efficient photovoltaic performance in both conventional and inverted layouts. The SqP inverted device was firstly demonstrated and the highest power conversion efficiency (PCE) of 5.84% with the enhanced J sc of 16.4 mA cm −2 was able to be achieved with the high internal quantum efficiency (IQE). Photoluminescence quenching shows the SqP films can provide efficient exciton quenching. X-ray photoemission spectroscopy (XPS) and ellipsometry analysis shows a polymer-rich surface in SqP films after thermal annealing. The charge mobilities in the SqP films were significantly enhanced as measured by space-charge-limited-current (SCLC) method. All these contribute to the improved photovoltaic performance in the inverted SqP device. We believe that these results inspire a new way of forming the active layer with controllable morphology, efficient charge separation and collection in polymer solar cells. [ABSTRACT FROM AUTHOR]

This paper critically analyses a recent attempt to account for what is special about aesthetic experiences in terms of how one deploys one’s attentional resources, i.e. how so-called aesthetic attention is exercised. While the paper defends this general framework of thinking about aesthetic experiences, it argues that the specific characterization of aesthetic attention that has been proposed is unsatisfactory, since it is incompatible with recent empirical findings on how the allocation of attention works. The major aim of this paper is to explore empirically plausible ways of attending, and to determine what scientifically legitimate kind of attention could account for at least some of the distinctive features of aesthetic experiences. The paper argues that the rapid sequential reallocation of the focus of attention to different properties of a single object plays a crucial role in this context. [ABSTRACT FROM AUTHOR]