A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels

In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons, across different time-spans and environments. To achieve this, we devise a new technique to clean and process the channel frequency response (CFR) phase of the Wi-Fi channel, obtaining an estimate of the Doppler shift at a radio monitor device. The Doppler shift reveals the presence of moving scatterers in the environment, while not being affected by (environment-specific) static objects. SHARP is trained on data collected as a person performs seven different activities in a single environment. It is then tested on different setups, to assess its performance as the person, the day and/or the environment change with respect to those considered at training time. In the worst-case scenario, it reaches an average accuracy higher than 95%, validating the effectiveness of the extracted Doppler information, used in conjunction with a learning algorithm based on a neural network, in recognizing human activities in a subject and environment independent way. The collected CFR dataset and the code are publicly available for replicability and benchmarking purposes [1]. © 2002-2012 IEEE

Human NDE1 splicing and mammalian brain development.

Exploring genetic and molecular differences between humans and other close species may be the key to explain the uniqueness of our brain and the selective pressures under which it evolves. Recent discoveries unveiled the involvement of Nuclear distribution factor E-homolog 1 (NDE1) in human cerebral cortical neurogenesis and suggested a role in brain evolution; however the evolutionary changes involved have not been investigated. NDE1 has a different gene structure in human and mouse resulting in the production of diverse splicing isoforms. In particular, mouse uses the terminal exon 8 T, while Human uses terminal exon 9, which is absent in rodents. Through chimeric minigenes splicing assay we investigated the unique elements regulating NDE1 terminal exon choice. We found that selection of the terminal exon is regulated in a cell dependent manner and relies on gain/loss of splicing regulatory sequences across the exons. Our results show how evolutionary changes in cis as well as trans acting signals have played a fundamental role in determining NDE1 species specific splicing isoforms supporting the notion that alternative splicing plays a central role in human genome evolution, and possibly human cognitive predominance

Cognitive stimulation of the default-mode network modulates functional connectivity in healthy aging

A cognitive-stimulation tool was created to regulate functional connectivity within the brain Default-Mode Network (DMN). Computerized exercises were designed based on the hypothesis that repeated task-dependent coactivation of multiple DMN regions would translate into regulation of resting-state network connectivity. Forty seniors (mean age: 65.90 years; SD: 8.53) were recruited and assigned either to an experimental group (n = 21) who received one month of intensive cognitive stimulation, or to a control group (n = 19) who maintained a regime of daily-life activities explicitly focused on social interactions. An MRI protocol and a battery of neuropsychological tests were administered at baseline and at the end of the study. Changes in the DMN (measured via functional connectivity of posterior-cingulate seeds), in brain volumes, and in cognitive performance were measured with mixed models assessing group-by-timepoint interactions. Moreover, regression models were run to test gray-matter correlates of the various stimulation tasks. Significant associations were found between task performance and gray-matter volume of multiple DMN core regions. Training-dependent up-regulation of functional connectivity was found in the posterior DMN component. This interaction was driven by a pattern of increased connectivity in the training group, while little or no up-regulation was seen in the control group. Minimal changes in brain volumes were found, but there was no change in cognitive performance. The training-dependent regulation of functional connectivity within the posterior DMN component suggests that this stimulation program might exert a beneficial impact in the prevention and treatment of early AD neurodegeneration, in which this neurofunctional pathway is progressively affected by the disease

Aberrant brain network connectivity in pre-symptomatic and manifest Huntington's disease: a systematic review

Resting-state functional magnetic resonance imaging (rs-fMRI) has the potential to shed light on the pathophysiological mechanisms of Huntington's disease (HD), paving the way to new therapeutic interventions. A systematic review of the literature was conducted in three online databases according to PRISMA guidelines, using keywords for HD, functional connectivity, and rs-fMRI. We included studies investigating connectivity in pre-symptomatic (pre-HD) and manifest HD gene carriers compared to healthy controls, implementing seed-based connectivity, independent component analysis, regional property and graph analysis approaches. Visual network showed reduced connectivity in manifest HD, while network/areas underpinning motor functions were consistently altered in both manifest HD and pre-HD, showing disease stage-dependent changes. Cognitive networks underlying executive and attentional functions showed divergent anterior-posterior alterations, reflecting possible compensatory mechanisms. The involvement of these networks in pre-HD is still unclear. In conclusion, aberrant connectivity of the sensory-motor network is observed in the early stage of HD while, as pathology spreads, other networks might be affected, such as the visual and executive/attentional networks. Moreover, sensory-motor and executive networks exhibit hyper- and hypo-connectivity patterns following different spatiotemporal trajectories. These findings could help to implement future huntingtin-lowering interventions

Improving water use efficiency in vertical farming: Effects of growing systems, far-red radiation and planting density on lettuce cultivation

Vertical farms (VFs) are innovative urban production facilities consisting of multi-level indoor systems equipped with artificial lighting in which all the environmental conditions are controlled independently from the external climate. VFs are generally provided with a closed loop fertigation system to optimize the use of water and nu-trients. The objective of this study, performed within an experimental VF at the University of Bologna, was to quantify the water use efficiency (WUE, ratio between plant fresh weight and the volume of water used) for a lettuce (Lactuca sativa L.) growth cycle obtained in two different growing systems: an ebb-and-flow substrate culture and a high pressure aeroponic system. Considering the total water consumed (water used for irrigation and climate management), WUE of ebb-and-flow and aeroponics was 28.1 and 52.9 g L-1 H2O, respectively. During the growing cycle, the contribution generated by the recovery of internal air moisture from the heating, ventilation and air conditioning (HVAC) system, was quantified. Indeed, by recovering water from the dehu-midifier, water use decreases dramatically (by 67 %), while WUE increased by 206 %. Further improvement of WUE in the ebb-and-flow system was obtained through ameliorated crop management strategies, in particular, by increasing planting densities (e.g., 153, 270 and 733 plants m-2) and by optimizing the light spectrum used for plant growth (e.g., adjusting the amount of far-red radiation in the spectrum). Strategies for efficient use of water in high-tech urban indoor growing systems are therefore proposed

Measuring and modelling the energy cost of reconfiguration in sensor networks [forthcoming]

As Wireless Sensor Networks (WSN) must operate for long periods on a limited power budget, estimating the energy cost of software operations is critical. Contemporary reconfiguration approaches for WSN allow for software evolution at various granularities; from reflashing of a complete software image, through replacement of complete applications, to the reconfiguration of individual software components. This paper contributes a generic model for measuring and modelling the energy cost of reconfiguration in WSN. We validate that this model is accurate in the face of different hardware platforms, software stacks and software encapsulation approaches. We have embedded this model in the LooCI middleware, resulting in the first energy aware reconfigurable component model for sensor networks. We evaluate our approach using two real-world WSN applications and demonstrate that our model predicts the energy cost of reconfiguration with 93% accuracy. Using this model we demonstrate that selecting the most appropriate software modularisation approach is key to minimising energy consumption

White matter tract disconnection in Gerstmann's syndrome: Insights from a single case study

It has been suggested that Gerstmann's syndrome is the result of subcortical disconnection rather than emerging from damage of a multifunctional brain region within the parietal lobe. However, patterns of white matter tract disconnection following parietal damage have been barely investigated. This single case study allows characterising Gerstmann's syndrome in terms of disconnected networks. We report the case of a left parietal patient affected by Gerstmann's tetrad: agraphia, acalculia, left/right orientation problems, and finger agnosia. Lesion mapping, atlas-based estimation of probability of disconnection, and DTI-based tractography revealed that the lesion was mainly located in the superior parietal lobule, and it caused disruption of both intraparietal tracts passing through the inferior parietal lobule (e.g., tracts connecting the angular, supramarginal, postcentral gyri, and the superior parietal lobule) and fronto-parietal long tracts (e.g., the superior longitudinal fasciculus). The lesion site appears to be located more superiorly as compared to the cerebral regions shown active by other studies during tasks impaired in the syndrome, and it reached the subcortical area potentially critical in the emergence of the syndrome, as hypothesised in previous studies. Importantly, the reconstruction of tracts connecting regions within the parietal lobe indicates that this critical subcortical area is mainly crossed by white matter tracts connecting the angular gyrus and the superior parietal lobule. Taken together, these findings suggest that this case study might be considered as empirical evidence of Gerstmann's tetrad caused by disconnection of intraparietal white matter tracts

Energy aware software evolution for wireless sensor networks

Wireless Sensor Networks (WSNs) are subject to high levels of dynamism arising from changing environmental conditions and application requirements. Reconfiguration allows software functionality to be optimized for current environmental conditions and supports software evolution to meet variable application requirements. Contemporary software modularization approaches for WSNs allow for software evolution at various granularities; from monolithic re-flashing of OS and application functionality, through replacement of complete applications, to the reconfiguration of individual software components. As the nodes that compose a WSN must typically operate for long periods on a single battery charge, estimating the energy cost of software evolution is critical. This paper contributes a generic model for calculating the energy cost of the reconfiguration in WSN. We have embedded this model in the LooCI middleware, resulting in the first energy aware reconfigurable component model for sensor networks. We evaluate our approach using two real-world WSN applications and find that (i.) our model accurately predicts the energy cost of reconfiguration and (ii.) component-based reconfiguration has a high initial cost, but provides energy savings during software evolution