Testing the channel-based model of duration perception

The channel-based model of duration perception postulates the existence of neural mechanisms that respond selectively to a narrow range of stimulus durations centred on their preferred duration (Heron et al Proceedings of the Royal Society B 279 690–698). In principle the channel-based model could
explain recent reports of adaptation-induced, visual duration compression effects (Johnston et al Current Biology 16 472–479; Curran and Benton Cognition 122 252–257); from this perspective duration compression is a consequence of the adapting stimuli being presented for a longer duration than the test stimuli. In the current experiment observers adapted to a sequence of moving random dot patterns at the same retinal position, each 340ms in duration and separated by a variable (500–1000ms) interval. Following adaptation observers judged the duration of a 600ms test stimulus at the same location. The test stimulus moved in the same, or opposite, direction as the adaptor. Contrary to the channel-based
model’s prediction, test stimulus duration appeared compressed, rather than expanded, when it moved in the same direction as the adaptor. That test stimulus duration was not distorted when moving in the opposite direction further suggests that visual timing mechanisms are influenced by additional neural processing associated with the stimulus being timed.

Spatio-Temporal Rich Model For Motion Vector Steganalysis

We propose a spatio-temporal rich model of motion vector planes as a part of a full steganalytic system against motion vector based steganography. Superior detection accuracy of the rich model over the previous methods has been lately demonstrated for digital images in both spatial and DCT domain. It has not been heretofore used for detection of motion vector steganography. We also introduced a transformation so as to extend the feature set with temporal residuals. We carried out the tests along with most recent motion vector steganalysis and steganography methods. Test results show that the proposed model delivers an outstanding performance compared to the previous methods.

Psychosocial interventions to improve quality of life and emotional wellbeing for recently diagnosed cancer patients

BACKGROUND:
A cancer diagnosis may lead to significant psychological distress in up to 75% of cases. There is a lack of clarity about the most effective ways to address this psychological distress.
OBJECTIVES:
To assess the effects of psychosocial interventions to improve quality of life (QoL) and general psychological distress in the 12-month phase following an initial cancer diagnosis.
SEARCH METHODS:
We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2010, Issue 4), MEDLINE, EMBASE, and PsycINFO up to January 2011. We also searched registers of clinical trials, abstracts of scientific meetings and reference lists of included studies. Electronic searches were carried out across all primary sources of peer-reviewed publications using detailed criteria. No language restrictions were imposed.
SELECTION CRITERIA:
Randomised controlled trials of psychosocial interventions involving interpersonal dialogue between a 'trained helper' and individual newly diagnosed cancer patients were selected. Only trials measuring QoL and general psychological distress were included. Trials involving a combination of pharmacological therapy and interpersonal dialogue were excluded, as were trials involving couples, family members or group formats.
DATA COLLECTION AND ANALYSIS:
Trial data were examined and selected by two authors in pairs with mediation from a third author where required. Where possible, outcome data were extracted for combining in a meta-analyses. Continuous outcomes were compared using standardised mean differences and 95% confidence intervals, using a random-effects model. The primary outcome, QoL, was examined in subgroups by outcome measurement, cancer site, theoretical basis for intervention, mode of delivery and discipline of trained helper. The secondary outcome, general psychological distress (including anxiety and depression), was examined according to specified outcome measures.
MAIN RESULTS:
A total of 3309 records were identified, examined and the trials subjected to selection criteria; 30 trials were included in the review. No significant effects were observed for QoL at 6-month follow up (in 9 studies, SMD 0.11; 95% CI -0.00 to 0.22); however, a small improvement in QoL was observed when QoL was measured using cancer-specific measures (in 6 studies, SMD 0.16; 95% CI 0.02 to 0.30). General psychological distress as assessed by 'mood measures' improved also (in 8 studies, SMD - 0.81; 95% CI -1.44 to - 0.18), but no significant effect was observed when measures of depression or anxiety were used to assess distress (in 6 studies, depression SMD 0.12; 95% CI -0.07 to 0.31; in 4 studies, anxiety SMD 0.05; 95% CI -0.13 to 0.22). Psychoeducational and nurse-delivered interventions that were administered face to face and by telephone with breast cancer patients produced small positive significant effects on QoL (in 2 studies, SMD 0.23; 95% CI 0.04 to 0.43).
AUTHORS' CONCLUSIONS:
The significant variation that was observed across participants, mode of delivery, discipline of 'trained helper' and intervention content makes it difficult to arrive at a firm conclusion regarding the effectiveness of psychosocial interventions for cancer patients. It can be tentatively concluded that nurse-delivered interventions comprising information combined with supportive attention may have a beneficial impact on mood in an undifferentiated population of newly diagnosed cancer patients.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

Implementation of a cogeneration plant for a food processing facility. A case study

The present work presents an investigation regarding the feasibility analysis of a cogeneration plant for a food processing facility with the aim to decrease the cost of energy supply. The monthly electricity and heat consumption profiles are analyzed, in order to understand the consumption profiles, as well as the costs of the current furniture of electricity and gas. Then, a detailed thermodynamic model of the cogeneration cycle is implemented and the investment costs are linked to the thermodynamic variables by means of cost functions. The optimal electricity power of the co-generator is determined with reference to various investment indexes. The analysis highlights that the optimal dimension varies according to the chosen indicator, therefore it is not possible to establish it univocally, but it depends on the financial/economic strategy of the company through the considered investment index.