Perceptual Context in Cognitive Hierarchies

Cognition does not only depend on bottom-up sensor feature abstraction, but also relies on contextual information being passed top-down. Context is higher level information that helps to predict belief states at lower levels. The main contribution of this paper is to provide a formalisation of perceptual context and its integration into a new process model for cognitive hierarchies. Several simple instantiations of a cognitive hierarchy are used to illustrate the role of context. Notably, we demonstrate the use context in a novel approach to visually track the pose of rigid objects with just a 2D camera

Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials

BACKGROUND: Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied to measurements registered in a controlled setting and under exposure to an external stimulus, it can facilitate analysis of the impact of the stimulus on those sources. The link between the stimulus and a given source can be verified by a classifier that is able to "predict" the condition a given signal was registered under, solely based on the components. However, the ICA's assumption about statistical independence of sources is often unrealistic and turns out to be insufficient to build an accurate classifier. Therefore, we propose to utilize a novel method, based on hybridization of ICA, multi-objective evolutionary algorithms (MOEA), and rough sets (RS), that attempts to improve the effectiveness of signal decomposition techniques by providing them with "classification-awareness." RESULTS: The preliminary results described here are very promising and further investigation of other MOEAs and/or RS-based classification accuracy measures should be pursued. Even a quick visual analysis of those results can provide an interesting insight into the problem of neural activity analysis. CONCLUSION: We present a methodology of classificatory decomposition of signals. One of the main advantages of our approach is the fact that rather than solely relying on often unrealistic assumptions about statistical independence of sources, components are generated in the light of a underlying classification problem itself

Urachal carcinoma presenting with chronic mucusuria: a case report

Urachal adenocarcinoma is a rare tumor and represents 0.17–0.34% of all bladder tumors. It has an insidious course and variable clinical presentation. We present a case report of a 58 year old white male with an urachal cyst who suffered irritative voiding symptoms and long term mucusuria, since childhood. After surgical removal of the cyst with a partial cystectomy a mucus adenocarcinoma was diagnosed histologically

Salmonella enteritidis meningitis in a first time diagnosed AIDS patient: Case report

We describe a patient with salmonella enteritidis meningitis and unknown HIV infection

Very rapid long-distance sea crossing by a migratory bird

Landbirds undertaking within-continent migrations have the possibility to stop en route, but most long-distance migrants must also undertake large non-stop sea crossings, the length of which can vary greatly. For shorebirds migrating from Iceland to West Africa, the shortest route would involve one of the longest continuous sea crossings while alternative, mostly overland, routes are available. Using geolocators to track the migration of Icelandic whimbrels (Numenius phaeopus), we show that they can complete a round-trip of 11,000 km making two non-stop sea crossings and flying at speeds of up to 24 m s-1; the fastest recorded for shorebirds flying over the ocean. Although wind support could reduce flight energetic costs, whimbrels faced headwinds up to twice their ground speed, indicating that unfavourable and potentially fatal weather conditions are not uncommon. Such apparently high risk migrations might be more common than previously thought, with potential fitness gains outweighing the costs

Unguided low intensity cognitive behaviour therapy for anxiety and depression during the COVID-19 pandemic: A randomised trial.

The COVID-19 pandemic has had a severe impact on mental health worldwide, with increased rates of anxiety and depression widely documented. The aim of this study was to examine unguided low intensity cognitive behaviour therapy for anxiety and depression during the pandemic. A sample of 225 individuals in Australia and the United Kingdom (M age 37.79, SD = 14.02, range 18-80 years; 85% female) were randomised into intervention or waitlist control. The intervention group demonstrated significant decreases in anxiety (d = 0.36 [0.18, 0.54]) and depression (d = 0.28 [0.11, 0.45]) compared to controls. The majority of participants (96%) rated the intervention as useful, and most (83%) reported they spent 30 min or less reading the guide, with 83% agreeing the intervention was easy to read. The results indicate that low intensity cognitive behaviour therapy has efficacy in reducing anxiety and depression during the COVID-19 pandemic. There is an urgent need to disseminate low intensity psychological therapies to improve mental health in this challenging time

Coronary fly-through or virtual angioscopy using dual-source MDCT data

Coronary fly-through or virtual angioscopy (VA) has been studied ever since its invention in 2000. However, application was limited because it requires an optimal computed tomography (CT) scan and time-consuming post-processing. Recent advances in post-processing software facilitate easy construction of VA, but until now image quality was insufficient in most patients. The introduction of dual-source multidetector CT (MDCT) could enable VA in all patients. Twenty patients were scanned using a dual-source MDCT (Definition, Siemens, Forchheim, Germany) using a standard coronary artery protocol. Post-processing was performed on an Aquarius Workstation (TeraRecon, San Mateo, Calif.). Length travelled per major branch was recorded in millimetres, together with the time required in minutes. VA could be performed in every patient for each of the major coronary arteries. The mean (range) length of the automated fly-through was 80 (32–107) mm for the left anterior descending (LAD), 75 (21–116) mm for the left circumflex artery (LCx), and 109 (21–190) mm for the right coronary artery (RCA). Calcifications and stenoses were visualised, as well as most side branches. The mean time required was 3 min for LAD, 2.5 min for LCx, and 2 min for the RCA. Dual-source MDCT allows for high quality visualisation of the coronary arteries in every patient because scanning with this machine is independent of the heart rate. This is clearly shown by the successful VA in all patients. Potential clinical value of VA should be determined in the near future

Incremental dimension reduction of tensors with random index

We present an incremental, scalable and efficient dimension reduction technique for tensors that is based on sparse random linear coding. Data is stored in a compactified representation with fixed size, which makes memory requirements low and predictable. Component encoding and decoding are performed on-line without computationally expensive re-analysis of the data set. The range of tensor indices can be extended dynamically without modifying the component representation. This idea originates from a mathematical model of semantic memory and a method known as random indexing in natural language processing. We generalize the random-indexing algorithm to tensors and present signal-to-noise-ratio simulations for representations of vectors and matrices. We present also a mathematical analysis of the approximate orthogonality of high-dimensional ternary vectors, which is a property that underpins this and other similar random-coding approaches to dimension reduction. To further demonstrate the properties of random indexing we present results of a synonym identification task. The method presented here has some similarities with random projection and Tucker decomposition, but it performs well at high dimensionality only (n>10^3). Random indexing is useful for a range of complex practical problems, e.g., in natural language processing, data mining, pattern recognition, event detection, graph searching and search engines. Prototype software is provided. It supports encoding and decoding of tensors of order >= 1 in a unified framework, i.e., vectors, matrices and higher order tensors.Comment: 36 pages, 9 figure

Dual-source CT for chest pain assessment

Comprehensive CT angiography protocols offering a simultaneous evaluation of pulmonary embolism, coronary stenoses and aortic disease are gaining attractiveness with recent CT technology. The aim of this study was to assess the diagnostic accuracy of a specific dual-source CT protocol for chest pain assessment. One hundred nine patients suffering from acute chest pain were examined on a dual-source CT scanner with ECG gating at a temporal resolution of 83 ms using a body-weight-adapted contrast material injection regimen. The images were evaluated for the cause of chest pain, and the coronary findings were correlated to invasive coronary angiography in 29 patients (27%). The files of patients with negative CT examinations were reviewed for further diagnoses. Technical limitations were insufficient contrast opacification in six and artifacts from respiration in three patients. The most frequent diagnoses were coronary stenoses, valvular and myocardial disease, pulmonary embolism, aortic aneurysm and dissection. Overall sensitivity for the identification of the cause of chest pain was 98%. Correlation to invasive coronary angiography showed 100% sensitivity and negative predictive value for coronary stenoses. Dual-source CT offers a comprehensive, robust and fast chest pain assessment

Observation of coherent many-body Rabi oscillations

A two-level quantum system coherently driven by a resonant electromagnetic field oscillates sinusoidally between the two levels at frequency $\Omega$ which is proportional to the field amplitude [1]. This phenomenon, known as the Rabi oscillation, has been at the heart of atomic, molecular and optical physics since the seminal work of its namesake and coauthors [2]. Notably, Rabi oscillations in isolated single atoms or dilute gases form the basis for metrological applications such as atomic clocks and precision measurements of physical constants [3]. Both inhomogeneous distribution of coupling strength to the field and interactions between individual atoms reduce the visibility of the oscillation and may even suppress it completely. A remarkable transformation takes place in the limit where only a single excitation can be present in the sample due to either initial conditions or atomic interactions: there arises a collective, many-body Rabi oscillation at a frequency $N^0.5\Omega$ involving all N >> 1 atoms in the sample [4]. This is true even for inhomogeneous atom-field coupling distributions, where single-atom Rabi oscillations may be invisible. When one of the two levels is a strongly interacting Rydberg level, many-body Rabi oscillations emerge as a consequence of the Rydberg excitation blockade. Lukin and coauthors outlined an approach to quantum information processing based on this effect [5]. Here we report initial observations of coherent many-body Rabi oscillations between the ground level and a Rydberg level using several hundred cold rubidium atoms. The strongly pronounced oscillations indicate a nearly complete excitation blockade of the entire mesoscopic ensemble by a single excited atom. The results pave the way towards quantum computation and simulation using ensembles of atoms