Differential susceptibility to performance degradation across categories of facial emotion - a model confirmation

Patients with a number of psychiatric and neuropathological conditions demonstrate problems in recognising facial expressions of emotion. Research indicating that patients with schizophrenia perform more poorly in the recognition of negative valence facial stimuli than positive valence stimuli has been interpreted as evidence of a negative emotion specific deficit. An alternate explanation rests in the psychometric properties of the stimulus materials. This model suggests that the pattern of impairment observed in schizophrenia may reflect initial discrepancies in task difficulty between stimulus categories, which are not apparent in healthy subjects because of ceiling effects. This hypothesis is tested, by examining the performance of healthy subjects in a facial emotion categorisation task with three levels of stimulus resolution. Results confirm the predictions of the model, showing that performance degrades differentially across emotion categories, with the greatest deterioration to negative valence stimuli. In the light of these results, a possible methodology for detecting emotion specific deficits in clinical samples is discussed.

Cryptanalysis of SIMON Variants with Connections

SIMON is a family of 10 lightweight block ciphers published by Beaulieu et al. from the United States National Security Agency (NSA). A cipher in this family with K -bit key and N -bit block is called SIMON N/K . We present several linear characteristics for reduced-round SIMON32/64 that can be used for a key-recovery attack and extend them further to attack other variants of SIMON. Moreover, we provide results of key recovery analysis using several impossible differential characteristics starting from 14 out of 32 rounds for SIMON32/64 to 22 out of 72 rounds for SIMON128/256. In some cases the presented observations do not directly yield an attack, but provide a basis for further analysis for the specific SIMON variant. Finally, we exploit a connection between linear and differential characteristics for SIMON to construct linear characteristics for different variants of reduced-round SIMON. Our attacks extend to all variants of SIMON covering more rounds compared to any known results using linear cryptanalysis. We present a key recovery attack against SIMON128/256 which covers 35 out of 72 rounds with data complexity 2123 . We have implemented our attacks for small scale variants of SIMON and our experiments confirm the theoretical bias presented in this work.

Low probability differentials and the cryptanalysis of full-round CLEFIA-128

So far, low probability differentials for the key schedule of block ciphers have been used as a straightforward proof of security against related-key differential analysis. To achieve resistance, it is believed that for cipher with k-bit key it suffices the upper bound on the probability to be 2− k . Surprisingly, we show that this reasonable assumption is incorrect, and the probability should be (much) lower than 2− k . Our counter example is a related-key differential analysis of the well established block cipher CLEFIA-128. We show that although the key schedule of CLEFIA-128 prevents differentials with a probability higher than 2− 128, the linear part of the key schedule that produces the round keys, and the Feistel structure of the cipher, allow to exploit particularly chosen differentials with a probability as low as 2− 128. CLEFIA-128 has 214 such differentials, which translate to 214 pairs of weak keys. The probability of each differential is too low, but the weak keys have a special structure which allows with a divide-and-conquer approach to gain an advantage of 27 over generic analysis. We exploit the advantage and give a membership test for the weak-key class and provide analysis of the hashing modes. The proposed analysis has been tested with computer experiments on small-scale variants of CLEFIA-128. Our results do not threaten the practical use of CLEFIA.

Optimizing preventative maintenance strategies for linear assets

Linear assets are engineering infrastructure, such as pipelines, railway lines, and electricity cables, which span long distances and can be divided into different segments. Optimal management of such assets is critical for asset owners as they normally involve significant capital investment. Currently, Time Based Preventive Maintenance (TBPM) strategies are commonly used in industry to improve the reliability of such assets, as they are easy to implement compared with reliability or risk-based preventive maintenance strategies. Linear assets are normally of large scale and thus their preventive maintenance is costly. Their owners and maintainers are always seeking to optimize their TBPM outcomes in terms of minimizing total expected costs over a long term involving multiple maintenance cycles. These costs include repair costs, preventive maintenance costs, and production losses. A TBPM strategy defines when Preventive Maintenance (PM) starts, how frequently the PM is conducted and which segments of a linear asset are operated on in each PM action. A number of factors such as required minimal mission time, customer satisfaction, human resources, and acceptable risk levels need to be considered when planning such a strategy. However, in current practice, TBPM decisions are often made based on decision makers’ expertise or industrial historical practice, and lack a systematic analysis of the effects of these factors. To address this issue, here we investigate the characteristics of TBPM of linear assets, and develop an effective multiple criteria decision making approach for determining an optimal TBPM strategy. We develop a recursive optimization equation which makes it possible to evaluate the effect of different maintenance options for linear assets, such as the best partitioning of the asset into segments and the maintenance cost per segment.

High order unconditionally stable difference schemes for the Riesz space-fractional telegraph equation

In this paper, a class of unconditionally stable difference schemes based on the Pad´e approximation is presented for the Riesz space-fractional telegraph equation. Firstly, we introduce a new variable to transform the original dfferential equation to an equivalent differential equation system. Then, we apply a second order fractional central difference scheme to discretise the Riesz space-fractional operator. Finally, we use (1, 1), (2, 2) and (3, 3) Pad´e approximations to give a fully discrete difference scheme for the resulting linear system of ordinary differential equations. Matrix analysis is used to show the unconditional stability of the proposed algorithms. Two examples with known exact solutions are chosen to assess the proposed difference schemes. Numerical results demonstrate that these schemes provide accurate and efficient methods for solving a space-fractional hyperbolic equation.

Maximum principle and numerical method for the multi-term time–space Riesz–Caputo fractional differential equations

The maximum principle for the space and time–space fractional partial differential equations is still an open problem. In this paper, we consider a multi-term time–space Riesz–Caputo fractional differential equations over an open bounded domain. A maximum principle for the equation is proved. The uniqueness and continuous dependence of the solution are derived. Using a fractional predictor–corrector method combining the L1 and L2 discrete schemes, we present a numerical method for the specified equation. Two examples are given to illustrate the obtained results.

Novel non-linear elastic structural analysis with generalised transverse element loads using a refined finite element

In the finite element modelling of structural frames, external loads such as wind loads, dead loads and imposed loads usually act along the elements rather than at the nodes only. Conventionally, when an element is subjected to these general transverse element loads, they are usually converted to nodal forces acting at the ends of the elements by either lumping or consistent load approaches. In addition, it is especially important for an element subjected to the first- and second-order elastic behaviour, to which the steel structure is critically prone to; in particular the thin-walled steel structures, when the stocky element section may be generally critical to the inelastic behaviour. In this sense, the accurate first- and second-order elastic displacement solutions of element load effect along an element is vitally crucial, but cannot be simulated using neither numerical nodal nor consistent load methods alone, as long as no equilibrium condition is enforced in the finite element formulation, which can inevitably impair the structural safety of the steel structure particularly. It can be therefore regarded as a unique element load method to account for the element load nonlinearly. If accurate displacement solution is targeted for simulating the first- and second-order elastic behaviour on an element on the basis of sophisticated non-linear element stiffness formulation, the numerous prescribed stiffness matrices must indispensably be used for the plethora of specific transverse element loading patterns encountered. In order to circumvent this shortcoming, the present paper proposes a numerical technique to include the transverse element loading in the non-linear stiffness formulation without numerous prescribed stiffness matrices, and which is able to predict structural responses involving the effect of first-order element loads as well as the second-order coupling effect between the transverse load and axial force in the element. This paper shows that the principle of superposition can be applied to derive the generalized stiffness formulation for element load effect, so that the form of the stiffness matrix remains unchanged with respect to the specific loading patterns, but with only the magnitude of the loading (element load coefficients) being needed to be adjusted in the stiffness formulation, and subsequently the non-linear effect on element loadings can be commensurate by updating the magnitude of element load coefficients through the non-linear solution procedures. In principle, the element loading distribution is converted into a single loading magnitude at mid-span in order to provide the initial perturbation for triggering the member bowing effect due to its transverse element loads. This approach in turn sacrifices the effect of element loading distribution except at mid-span. Therefore, it can be foreseen that the load-deflection behaviour may not be as accurate as those at mid-span, but its discrepancy is still trivial as proved. This novelty allows for a very useful generalised stiffness formulation for a single higher-order element with arbitrary transverse loading patterns to be formulated. Moreover, another significance of this paper is placed on shifting the nodal response (system analysis) to both nodal and element response (sophisticated element formulation). For the conventional finite element method, such as the cubic element, all accurate solutions can be only found at node. It means no accurate and reliable structural safety can be ensured within an element, and as a result, it hinders the engineering applications. The results of the paper are verified using analytical stability function studies, as well as with numerical results reported by independent researchers on several simple frames.

Meltdown : a tool to help in the interpretation of thermal melt curves acquired by differential scanning fluorimetry

The output of a differential scanning fluorimetry (DSF) assay is a series of melt curves, which need to be interpreted to get value from the assay. An application that translates raw thermal melt curve data into more easily assimilated knowledge is described. This program, called “Meltdown,” conducts four main activities—control checks, curve normalization, outlier rejection, and melt temperature (Tm) estimation—and performs optimally in the presence of triplicate (or higher) sample data. The final output is a report that summarizes the results of a DSF experiment. The goal of Meltdown is not to replace human analysis of the raw fluorescence data but to provide a meaningful and comprehensive interpretation of the data to make this useful experimental technique accessible to inexperienced users, as well as providing a starting point for detailed analyses by more experienced users.

Prior and posterior linear pooling for combining expert opinions: Uses and impact on Bayesian Networks

The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions then places them into the BN is a common method. This paper firstly proposes an alternative pooling method, Posterior Linear Pooling (PoLP). This method constructs a BN for each expert, then pools the resulting probabilities at the nodes of interest. Secondly, it investigates the advantages and disadvantages of using these pooling methods to combine the opinions of multiple experts. Finally, the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behaviour of different groups of people and how these different methods may be able to capture such differences. The paper focusses on 6 nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (female, male),Travel Experience (experienced, inexperienced), and Travel Purpose (business, personal) and finds that different behaviors can indeed be captured by the different methods.

Differential segmentation responses to an alcohol social marketing program

Objective This study seeks establish whether meaningful subgroups exist within a 14-16 year old adolescent population and if these segments respond differently to the Game On: Know Alcohol (GOKA) intervention, a school-based alcohol social marketing program. Methodology This study is part of a larger cluster randomized controlled evaluation of the Game On: Know Alcohol (GOKA) program implemented in 14 schools in 2013/2014. TwoStep cluster analysis was conducted to segment 2114 high school adolescents (14-16 years old) on the basis of 22 demographic, behavioral and psychographic variables. Program effects on knowledge, attitudes, behavioral intentions, social norms, expectancies and refusal self-efficacy of identified segments was subsequently examined. Results Three segments were identified: (1) Abstainers (2) Bingers (3) Moderate Drinkers. Program effects varied significantly across segments. The strongest positive change effects post participation were observed for the Bingers, while mixed effects were evident for Moderate Drinkers and Abstainers. Conclusions These findings provide preliminary empirical evidence supporting application of social marketing segmentation in alcohol education programs. Development of targeted programs that meet the unique needs of each of the three identified segments is indicated to extend the social marketing footprint in alcohol education.

A review on prognostic techniques for non-stationary and non-linear rotating systems

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

Improving PLDA speaker verification using WMFD and linear-weighted approaches in limited microphone data conditions

This paper proposes the addition of a weighted median Fisher discriminator (WMFD) projection prior to length-normalised Gaussian probabilistic linear discriminant analysis (GPLDA) modelling in order to compensate the additional session variation. In limited microphone data conditions, a linear-weighted approach is introduced to increase the influence of microphone speech dataset. The linear-weighted WMFD-projected GPLDA system shows improvements in EER and DCF values over the pooled LDA- and WMFD-projected GPLDA systems in inter-view-interview condition as WMFD projection extracts more speaker discriminant information with limited number of sessions/ speaker data, and linear-weighted GPLDA approach estimates reliable model parameters with limited microphone data.

Differential interaction between the C2B domain of synaptotagmin-I and the Drosophila stonedA and stonedB proteins

The stoned locus in Drosophila encodes two proteins StonedA (STNA) and StonedB (STNB), both of which have been suggested to act as adaptins in mediating synaptic vesicle recycling. A combination of immunological, genetic and biochemical studies have shown an interaction of STNA and STNB with the C2B domain of Synaptotagmin-I (SYT-1), an integral synaptic vesicle protein that mediates Ca2+-dependent exocytosis, as well as endocytosis. The C2B domain of SYT-1 contains an AP-2 binding site that controls the size of recycled vesicles, and a C-terminal tryptophan-containing motif that acts as an internalization signal. Investigation of SYT-1 mutations in Drosophila has shown that altering the Ca2+ binding region of the C2B domain, results in a reduction in the rate of vesicle recycling, implicating this region in SYT-I endocytosis. In this poster, we report the molecular dissection of the interactions between the STNA and STNB proteins and the C2B domain of SYT-1. Deletion of the AP-2 binding site decreased the binding of both STNA and STNB. However, C-terminal deletions of the C2B domain significantly increased STNB binding. In contrast, the same C-terminal deletions reduced the affinity of the C2B domain for STNA. The possible interactions of both STNB and STNA with the Ca2+ binding region of SYT-1 will be also investigated.

An evaluation of differential reinforcement of other behavior, differential reinforcement of incompatible behavior, and restitution for the management of aggressive behaviors

A 46 year old institutionalized retarded woman was referred for treatment because of frequent verbal abuse and physically aggressive behaviors. A multicomponent behavioral intervention consisting of differential reinforcement of other behaviors, differential reinforcement of incompatible behaviors, and restitution was implemented. A sequential withdrawal design was used in order to evaluate the effects of components of the original intervention, and to provide a measure of response maintenance. Results indicated a marked decrease in verbal abuse and elimination of physical aggression. Verbal abuse recurred when the restitution procedure was withdrawn. The relative efficacy of the different interventions is discussed with respect to the behavioral management of aggression.

Differential processing of thematic and categorical conceptual relations in spoken word production

Studies of semantic context effects in spoken word production have typically distinguished between categorical (or taxonomic) and associative relations. However, associates tend to confound semantic features or morphological representations, such as whole-part relations and compounds (e.g., BOAT-anchor, BEE-hive). Using a picture-word interference paradigm and functional magnetic resonance imaging (fMRI), we manipulated categorical (COW-rat) and thematic (COW-pasture) TARGET-distractor relations in a balanced design, finding interference and facilitation effects on naming latencies, respectively, as well as differential patterns of brain activation compared with an unrelated distractor condition. While both types of distractor relation activated the middle portion of the left middle temporal gyrus (MTG) consistent with retrieval of conceptual or lexical representations, categorical relations involved additional activation of posterior left MTG, consistent with retrieval of a lexical cohort. Thematic relations involved additional activation of the left angular gyrus. These results converge with recent lesion evidence implicating the left inferior parietal lobe in processing thematic relations and may indicate a potential role for this region during spoken word production.