Brain-Inspired Intelligent Systems for Daily Assistance

The fields of machine learning and cognitive computing have been in the last decade revolutionised with neural-inspired algorithms (e.g., deep ANNs and deep RL) and brain-intelligent systems that assist in many real-world learning tasks from robot monitoring and interaction at home to complex decision-making about emotions and behaviours in humans and animals. While there are remarkable advances in these brain-inspired algorithms and systems, they need to be trained with huge data sets, and their results lack flexibility to adapt to diverse learning tasks and sustainable performance over long periods of time. To address these challenges, it is essential to gain an analytical understanding of the principles that allow biological inspired intelligent systems to leverage knowledge and how they can be translated to hardware for daily assistance and practical applications. This special issue brings researchers from interdesciplinary domains to report their latest research work on algorithms and neural-inspired systems that flexibly adapt to new learning tasks, learn from the environment using multimodal signals (e.g., neural, physiological, and kinematic), and produce autonomous adaptive agencies, which utilise cognitive and affective data, within a social neuroscientific framework. In this special issue, we have selected five papers out of fourteen high-quality papers after a careful reviewing process, which brings the acceptance rate to 35.7 percent. The five papers are representative of the current state-of-the-art in this area

Microarray evidence for off target effects in tick RNA interference experiments, and the lack of strong correlation between DSRNA and antibody phenotypes in tick In vitro treatments for vaccine candidate screening

No abstract availabl

A general Markov chain approach for disease and rumour spreading in complex networks

Spreading processes are ubiquitous in natural and artificial systems. They can be studied via a plethora of models, depending on the specific details of the phenomena under study. Disease contagion and rumour spreading are among the most important of these processes due to their practical relevance. However, despite the similarities between them, current models address both spreading dynamics separately. In this article, we propose a general spreading model that is based on discrete time Markov chains. The model includes all the transitions that are plausible for both a disease contagion process and rumour propagation. We show that our model not only covers the traditional spreading schemes but that it also contains some features relevant in social dynamics, such as apathy, forgetting, and lost/recovering of interest. The model is evaluated analytically to obtain the spreading thresholds and the early time dynamical behaviour for the contact and reactive processes in several scenarios. Comparison with Monte Carlo simulations shows that the Markov chain formalism is highly accurate while it excels in computational efficiency. We round off our work by showing how the proposed framework can be applied to the study of spreading processes occurring on social networks

The Benefit of Menopausal Hormone Therapy on Bone Density and Microarchitecture Persists After its Withdrawal.

Menopausal hormone therapy (MHT) favorably affects bone mineral density (BMD). Whether MHT also affects bone microarchitecture, as assessed by trabecular bone score (TBS), has never been evaluated. Our objective was to assess the effect of MHT on TBS and BMD before and after its withdrawal. This was a cross-sectional study. This study included the general community. Data were collected from the OsteoLaus cohort (1500 women aged 50-80 years). After exclusion of women with bone-modulating treatments, 1279 women were categorized according to MHT status into current (CU), past (PU), and never (NU) users. Spine TBS and BMD at lumbar spine, femoral neck, and total hip were assessed by dual X-ray absorptiometry. Age- and body mass index-adjusted analysis showed higher TBS values in CU vs PU or NU (1.31 ± 0.01, 1.29 ± 0.01, and 1.27 ± 0.01, respectively; P < .001). All BMD values were significantly higher in CU vs PU or NU. Compared to NU, PU exhibited higher lumbar spine (0.94 ± 0.01 vs 0.91 ± 0.01 g/cm(2); P = .017) and total hip (0.86 ± 0.01 vs 0.84 ± 0.01 g/cm(2); P = .026) BMD and a trend for higher TBS (P = .066). The 10-year loss of TBS and BMD at lumbar spine and total hip was significantly lower for both CU and PU vs NU. MHT duration had no effect on bone parameters. In PU, the residual effect on TBS and BMD was significantly more prominent in early discontinuers (<2 years). MHT is associated with bone microarchitecture preservation, as assessed by TBS. The effect of MHT on TBS and BMD persists at least 2 years after withdrawal

Backward Cherenkov radiation emitted by polariton solitons in a microcavity wire

Exciton-polaritons in semiconductor microcavities form a highly nonlinear platform to study a variety of effects interfacing optical, condensed matter, quantum and statistical physics. We show that the complex polariton patterns generated by picosecond pulses in microcavity wire waveguides can be understood as the Cherenkov radiation emitted by bright polariton solitons, which is enabled by the unique microcavity polariton dispersion, which has momentum intervals with positive and negative group velocities. Unlike in optical fibres and semiconductor waveguides, we observe that the microcavity wire Cherenkov radiation is predominantly emitted with negative group velocity and therefore propagates backwards relative to the propagation direction of the emitting soliton. We have developed a theory of the microcavity wire polariton solitons and of their Cherenkov radiation and conducted a series of experiments, where we have measured polariton-soliton pulse compression, pulse breaking and emission of the backward Cherenkov radiation

Insights on the laccase extraction and activity in ionic-liquid-based aqueous biphasic systems

Due to their catalytic properties, selectivity, and efficiency, enzymes are excellent biocatalysts. In particular, laccases are versatile multi-copper oxidases with great interest for a wide plethora of biotechnological and environmental applications. Even though several laccase-catalysed processes have been reported at an industrial level, the high costs of their downstream processing required to provide biocatalysts with high purity levels, stability and activity remains one of the main drawbacks when economically evaluating the overall processes. Aqueous biphasic systems based on ionic liquids (ILs) can be foreseen as a promising alternative approach for the extraction and activity maintenance/improvement of enzymes, essentially due to the designer solvents ability of ionic liquids. However, to take advantage of this feature and to use the full potential of IL-based aqueous biphasic systems, it is necessary to understand the effect of ILs as phase-forming constituents and how they affect the enzymes extraction and activity. In order to overcome the lack of information on this topic in the literature, in this work, IL-based aqueous biphasic systems were investigated to extract and enhance the laccase activity, in order to gather evidences that could be used to improve the enzymes downstream processing. To this end, a wide screening of imidazolium-, pyridinium-, pyrrolidinium-, piperidinium-, tetraalkylphosphonium-, and tetraalkylammonium-based ILs as phase-forming components of ABS was carried out. Furthermore, these ILs were used to create ABS combined with salts, polymers and used as adjuvants in polymer-based ABS. Most ABS comprising ILs revealed to be highly efficient extraction platforms, allowing the complete extraction of laccase for all the conditions tested, and with an enzyme activity enhancement by more than 50%. Overall, the obtained results demonstrate that laccase preferentially partitions to the most hydrophilic phase in ABS comprising ILs, both used as adjuvants or as phase-forming components, corresponding to the phase in which the IL is enriched. Furthermore, the IL chemical structure of the IL plays a significant role in the enzyme activity, where ILs with a higher number of hydroxyl groups seem to be relevant to improve the laccase activity.publishe

Supersymmetric D-branes in the D1-D5 background

We construct supersymmetric D-brane probe solutions in the background of the 2-charge D1-D5 system on M, where M is either K3 or T^4. We focus on `near-horizon bound states' that preserve supersymmetries of the near-horizon AdS_3 x S^3 x M geometry and are static with respect to the global time coordinate. We find a variety of half-BPS solutions that span an AdS_2 subspace in AdS_3, carry worldvolume flux and can wrap an S^2 within S^3 and/or supersymmetric cycles in M.Comment: Latex, 24 pages. v2: references added, modified Discussion, published versio