Mixtures of robust probabilistic principal component analyzers

Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to extract the local principal orientations in the data. An important issue with this generative model is its sensitivity to data lying off the low-dimensional manifold. In order to address this problem, the mixtures of robust probabilistic principal component analyzers are introduced. They take care of atypical points by means of a long tail distribution, the Student-t. It is shown that the resulting mixture model is an extension of the mixture of Gaussians, suitable for both robust clustering and dimensionality reduction. Finally, we briefly discuss how to construct a robust version of the closely related mixture of factor analyzers.     

Effective Evolutionary Algorithms for Many-Specifications Attainment: Application to Air Traffic Control Tracking Filters

This paper addresses a real-world engineering design requiring the application of effective and global optimization techniques. The problem it deals with is the design of nonlinear tracking filters under up to several hundreds of performance specifications. The suitability of different evolutionary computation techniques for solving multiobjective problems is explored, contrasting the performance achieved with recent multiobjective evolutionary algorithm (MOEAs) proposals and different aggregation schemes. In particular, a new scheme is proposed to build a fitness function based on an operator that selects worst cases of multiple specifications in different situations. They have been evaluated in the design of an air traffic control (ATC) tracking filter that should accomplish a specific normative with 264 specifications. Results show their performance in terms of effectiveness and computational load, comparing their capability to scale the problem with respect to problem size.     

Self-adaptive utility-based web session management

In the Internet, where millions of users are a click away from your site, being able to dynamically classify the workload in real time, and predict its short term behavior, is crucial for proper self-management and business efficiency. As workloads vary significantly according to current time of day, season, promotions and linking, it becomes impractical for some ecommerce sites to keep over-dimensioned infrastructures to accommodate the whole load. When server resources are exceeded, session-based admission control systems allow maintaining a high throughput in terms of properly finished sessions and QoS for a limited number of sessions; however, by denying access to excess users, the website looses potential customers.In the present study we describe the architecture of AUGURES, a system that learns to predict Web user’s intentions for visiting the site as well its resource usage. Predictions are made from information known at the time of their first request and later from navigational clicks. For this purpose we use machine learning techniques and Markov-chain models. The system uses these predictions to automatically shape QoS for the most profitable sessions, predict short-term resource needs, and dynamically provision servers according to the expected revenue and the cost to serve it. We test the AUGURES prototype on access logs from a high-traffic, online travel agency, obtaining promising results.     

A wireless embedded tongue tactile biofeedback system for balance control

We describe the architecture of an original biofeedback system for balance improvement for fall prevention and present results of a feasibility study. The underlying principle of this biofeedback consists of providing supplementary information related to foot sole pressure distribution through a wireless embedded tongue-placed tactile output device.Twelve young healthy adults voluntarily participated in this experiment. They were asked to stand as immobile as possible with their eyes closed in two conditions of no-biofeedback and biofeedback. Centre of foot pressure (CoP) displacements were recorded using a force platform. Results showed reduced CoP displacements in the biofeedback relative to the no-biofeedback condition.On the whole, the present findings evidence the effectiveness of this system in improving postural control on young healthy adults. Further investigations are needed to strengthen the potential clinical value of this device.     

Visual evoked potentials generator model derived from different spatial frequency stimuli of visual field regions and magnetic resonance imaging coordinates of V1, V2, V3 areas in man

Visual evoked potentials (VEPs) to pattern reversal vertical bar stimuli were recorded from 24 scalp derivations (including zygomatic and inion) referenced to digitally linked earlobes in 50 controls. 1, 2 and 4 cpd patterns were presented as full field (FF) stimuli, on Upper Hemifields (UHF) and Lower Hemifields (LHF), upper and lower quadrants and with the occlusion of central and peripheral UHF and LHF. VEPs to octant stimuli were also recorded with 2 cpd patterns. N1, P1 and N2 components were recorded from posterior and inion derivations with FF stimuli, from posterior derivations with LHF stimuli, only from inion leads with UHF stimuli, from derivations ipsilateral to stimuli with quadrants and octants, and consistently from midline derivations only with lower quadrants. Polarity inverted sequences (iN1-iP1-iN2) were recorded from the other scalp derivations, with similar latency and spatial frequency sensitivity as N1-P1-N2. Single Equivalent Dipole (ED) calculations were performed on N1 and P1 recorded in the different stimulus conditions. Our findings contradict previous hypotheses on VEP generators and contradict the predictions of VEPs polarity and distribution based on the "cruciform model" of VEPs generators. In order to explain the distribution of VEPs to upper and lower half fields and to quadrant and octants, we propose a model based on the position of the medial and occipito-polar surface of visual cortex in man.     

Hierarchical learning from human preferences and curiosity

Applied Intelligence - Recent success in scaling deep reinforcement algorithms (DRL) to complex problems has been driven by well-designed extrinsic rewards, which limits their applicability to many...     

Flexural behavior of stratified reinforced concrete: construction,testing, analysis,and design

Stratified concrete poses a promising alternative for construction. Its fresh and hardened properties have been studied at the material level; however, structural behavior in steel reinforced specimens has not been studied. This paper focuses on the flexural behavior of eight stratified reinforced concrete (SRC) specimens representing slices from a slab or non-bearing wall. Specimens with two stratified concrete designs and three steel ratios were tested and compared to estimates from a fiber element numerical model and rectangular stress-block design methods from ACI 318 and Eurocode 2. The results suggest that SRC has similar damage modes as ordinary reinforced concrete (ORC). The fiber element model accurately estimated the measured behavior, while ACI 318 and Eurocode 2 differed from the experimental results by <25%. These prediction accuracies are similar to those for ORC. Therefore, the flexural design of SRC can be done using both fiber element and rectangular stress-block approaches.     

Dual‐Action Cancer Therapy with Targeted Porous Silicon Nanovectors

There is a pressing need to develop more effective therapeutics to fight cancer. An idyllic chemotherapeutic is expected to overcome drug resistance of tumors and minimize harmful side effects to healthy tissues. Antibody‐functionalized porous silicon nanoparticles loaded with a combination of chemotherapy drug and gold nanoclusters (AuNCs) are developed. These nanocarriers are observed to selectively deliver both payloads, the chemotherapy drug and AuNCs, to human B cells. The accumulation of AuNCs to target cells and subsequent exposure to an external electromagnetic field in the microwave region render them more susceptible to the codelivered drug. This approach represents a targeted two‐stage delivery nanocarrier that benefits from a dual therapeutic action that results in enhanced cytotoxicity.     

Writing with Fluid: Structuring Hydrogels with Micrometer Precision by AFM in Combination with Nanofluidics

Hydrogels have many applications in biomedical surface modification and tissue engineering. However, the structuring of hydrogels after their formation represents still a major challenge, in particular due to their softness. Here, a novel approach is presented that is based on the combination of atomic force microscopy (AFM) and nanofluidics, also referred to as FluidFM technology. Its applicability is demonstrated for supramolecular hydrogel films that are prepared from low‐molecular weight hydrogelators, such as derivates of 1,3,5‐benzene tricarboxamides (BTAs). BTA films can be dissolved selectively by ejecting alkaline solution through the aperture of a hollow AFM‐cantilever connected to a nanofluidic controller. The AFM‐based force control is essential in preventing mechanical destruction of the hydrogels. The resulting “chemical writing” process is studied in detail and the influence of various parameters, such as applied pressure and time, is validated. It is demonstrated that the achievable structuring precision is primarily limited by diffusion and the aperture dimensions. Recently, various additive techniques have been presented to pattern hydrogels. The here‐presented subtractive approach can not only be applied to structure hydrogels from the large class of reversibly formed gels with superior resolution but would also allow for the selective loading of the hydrogels with active substances or nanoparticles.