Hardware-Software Co-Design of BIKE with HLS-Generated Accelerators

In order to mitigate the security threat of quantum computers, NIST is undertaking a process to standardize post-quantum cryptosystems, aiming to assess their security and speed up their adoption in production scenarios. Several hardware and software implementations have been proposed for each candidate, while only a few target heterogeneous platforms featuring CPUs and FPGAs. This work presents a HW/SW co-design of BIKE for embedded platforms featuring both CPUs and small FPGAs and employs high-level synthesis (HLS) to timely deliver the hardware accelerators. In contrast to state-of-the-art solutions targeting performance-optimized HLS accelerators, the proposed solution targets the small FPGAs implemented in the heterogeneous platforms for embedded systems. Compared to the software- only execution of BIKE, the experimental results collected on the systems-on-chip of the entire Xilinx Zynq-7000 family highlight a performance speedup ranging from 1.37x, on Z-7010, to 2.78x, on Z-7020

An analytical, dynamic, power-performance router model for run-time NoC optimizations

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Adaptive routing and Dynamic Frequency Scaling for NoC power-performance optimizations

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Scramble Suit: A Profile Differentiation Countermeasure to Prevent Template Attacks

Ensuring protection against side channel attacks is a crucial requirement in the design of modern secure embedded systems. Profiled side channel attacks, the class to which template attacks and machine learning attacks belong, derive a model of the side channel behavior of a device identical to the target one, and exploit the said model to extract the key from the target, under the hypothesis that the side channel behaviors of the two devices match. We propose an architectural countermeasure against cross-device profiled attacks which differentiates the side-channel behavior of different instances of the same hardware design, preventing the reuse of a model derived on a device other than the target one. In particular, we describe an instance of our solution providing a protected hardware implementation of the AES block cipher and experimentally validate its resistance against both Bayesian templates and machine learning approaches based on support vector machines also considering different state of the art feature reduction techniques to increase the effectiveness of the profiled attacks. Results show that our countermeasure foils the key retrieval attempts via profiled attacks ensuring a key derivation accuracy equivalent to a random guess

Neurocognitive impact of metal exposure and social stressors among schoolchildren in Taranto, Italy

BACKGROUND: Metal exposure is a public health hazard due to neurocognitive effects starting in early life. Poor socio-economic status, adverse home and family environment can enhance the neurodevelopmental toxicity due to chemical exposure. Disadvantaged socio-economic conditions are generally higher in environmentally impacted areas although the combined effect of these two factors has not been sufficiently studied. METHODS: The effect of co-exposure to neurotoxic metals including arsenic, cadmium, manganese, mercury, lead, selenium, and to socio-economic stressors was assessed in a group of 299 children aged 6-12\u2009years, residing at incremental distance from industrial emissions in Taranto, Italy. Exposure was assessed with biological monitoring and the distance between the home address and the exposure point source. Children's cognitive functions were examined using the Wechsler Intelligence Scale for Children (WISC) and the Cambridge Neuropsychological Test Automated Battery (CANTAB). Linear mixed models were chosen to assess the association between metal exposure, socio-economic status and neurocognitive outcomes. RESULTS: Urinary arsenic, cadmium and hair manganese resulted inversely related to the distance from the industrial emission source (\u3b2 -\u20090.04; 95% CI -0.06, -\u20090.01; \u3b2 -\u20090.02; 95% CI -0.05, -\u20090.001; \u3b2 -\u20090.02 95% CI -0.05, -\u20090.003) while the WISC intellectual quotient and its sub-scores (except processing speed index) showed a positive association with distance. Blood lead and urinary cadmium were negatively associated with the IQ total score and all sub-scores, although not reaching the significance level. Hair manganese and blood lead was positively associated with the CANTAB between errors of spatial working memory (\u3b2 2.2; 95% CI 0.3, 3.9) and the reaction time of stop signal task (\u3b2 0.05; 95% CI 0.02, 0.1) respectively. All the other CANTAB neurocognitive tests did not show to be significantly influenced by metal exposure. The highest socio-economic status showed about five points intellectual quotient more than the lowest level on average (\u3b2 4.8; 95% CI 0.3, 9.6); the interaction term between blood lead and the socio-economic status showed a significant negative impact of lead on working memory at the lowest socio-economic status level (\u3b2 -\u20094.0; 95% CI -6.9, -\u20091.1). CONCLUSIONS: Metal exposure and the distance from industrial emission was associated with negative cognitive impacts in these children. Lead exposure had neurocognitive effect even at very low levels of blood lead concentration when socio-economic status is low, and this should further address the importance and prioritize preventive and regulatory interventions

Associations of a metal mixture measured in multiple biomarkers with IQ: Evidence from italian adolescents living near ferroalloy industry

BACKGROUND: Research on the health effects of chemical mixtures has focused mainly on early life rather than adolescence, a potentially important developmental life stage. OBJECTIVES: We examined associations of a metal mixture with general cognition in a cross-sectional study of adolescents residing near ferromanga-nese industry, a source of airborne metals emissions. METHODS: We measured manganese (Mn), lead (Pb), copper (Cu), and chromium (Cr) in hair, blood, urine, nails, and saliva from 635 Italian adolescents 10–14 years of age. Full-scale, verbal, and performance intelligence quotient (FSIQ, VIQ, PIQ) scores were assessed using the Wechsler Intelligence Scale for Children-III. Multivariable linear regression and Bayesian kernel machine regression (BKMR) were used to estimate associations of the metal mixture with IQ. In secondary analyses, we used BKMR’s hierarchical variable selection option to inform biomarker selection for Mn, Cu, and Cr. RESULTS: Median metal concentrations were as follows: hair Mn, 0:08 lg=g; hair Cu, 9:6 lg=g; hair Cr, 0:05 lg=g; and blood Pb, 1:3 lg=dL. Adjusted models revealed an inverted U-shaped association between hair Cu and VIQ, consistent with Cu as an essential nutrient that is neurotoxic in excess. At low levels of hair Cu (10th percentile, 5:4 lg=g), higher concentrations (90th percentiles) of the mixture of Mn, Pb, and Cr (0:3 lg=g, 2:6 lg=dL, and 0:1 lg=g, respectively) were associated with a 2.9 (95% CI: −5:2, −0:5)–point decrease in VIQ score, compared with median concentrations of the mixture. There was suggestive evidence of interaction between Mn and Cu. In secondary analyses, saliva Mn, hair Cu, and saliva Cr were selected as the biomarkers most strongly associated with VIQ score. DISCUSSION: Higher adolescent levels of Mn, Pb, and Cr were associated with lower IQ scores, especially at low Cu levels. Findings also support fur-ther investigation into Cu as both beneficial and toxic for neurobehavioral outcomes

Metabolic Outcomes in Southern Italian Preadolescents Residing Near an Industrial Complex: The Role of Residential Location and Socioeconomic Status

Evidence suggests that environmental exposures and socioeconomic factors may interact to produce metabolic changes in children. We assessed the influence of residential location and socioeconomic status (SES) on pediatric body mass index (BMI) Z-score and fasting blood glucose (FBG) concentration. Participants included 214 children aged 6-11 years who live near a large industrial complex in Taranto, Italy. Participants were grouped into residential zones based on the distance between their home address and the complex periphery (Zone 1: 0.000-4.999 km, Zone 2: 5.000-9.999 km, Zone 3: 10.000-15.000 km). BMI Z-scores were calculated via World Health Organization (WHO) pediatric reference curves. FBG was obtained via venous blood sampling. Closer residential location to the industrial complex on the order of 5.000 km was significantly associated with worsened metabolic outcomes, particularly in female children. Zone 1 participants had higher BMI-adjusted FBG than Zone 2 and 3 participants (p < 0.05 versus Zone 2; p < 0.01 versus Zone 3). SES did not significantly influence BMI-adjusted FBG. Moreover, BMI Z-scores indicated high rates of overweight (22.0%) and obesity (22.9%) in the cohort. BMI Z-score was not significantly associated with SES or residential zone but was negatively associated with maternal education level (p < 0.05). These results offer new evidence that residing near industrial activity may predict adverse effects on child metabolic health

Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss

International audienceRadiological imaging offers effective measurement of anatomy, which is useful in disease diagnosis and assessment. Previous study has shown that the left atrial wall remodeling can provide information to predict treatment outcome in atrial fibrillation. Nevertheless, the segmentation of the left atrial structures from medical images is still very time-consuming. Current advances in neural network may help creating automatic segmentation models that reduce the workload for clinicians. In this preliminary study, we propose automated, two-stage, three-dimensional U-Nets with convolutional neural network, for the challenging task of left atrial segmentation. Unlike previous two-dimensional image segmentation methods, we use 3D U-Nets to obtain the heart cavity directly in 3D. The dual 3D U-Net structure consists of, a first U-Net to coarsely segment and locate the left atrium, and a second U-Net to accurately segment the left atrium under higher resolution. In addition, we introduce a Contour loss based on additional distance information to adjust the final segmentation. We randomly split the data into training datasets (80 subjects) and validation datasets (20 subjects) to train multiple models, with different augmentation setting. Experiments show that the average Dice coefficients for validation datasets are around 0.91 - 0.92, the sensitivity around 0.90-0.94 and the specificity 0.99. Compared with traditional Dice loss, models trained with Contour loss in general offer smaller Hausdorff distance with similar Dice coefficient, and have less connected components in predictions. Finally, we integrate several trained models in an ensemble prediction to segment testing datasets

CRIPTO and its signaling partner GRP78 drive the metastatic phenotype in human osteotropic prostate cancer

CRIPTO (CR-1, TDGF1) is a cell surface/secreted oncoprotein actively involved in development and cancer. Here, we report that high expression of CRIPTO correlates with poor survival in stratified risk groups of prostate cancer (PCa) patients. CRIPTO and its signaling partner glucose-regulated protein 78 (GRP78) are highly expressed in PCa metastases and display higher levels in the metastatic ALDHhigh sub-population of PC-3M-Pro4Luc2 PCa cells compared with non-metastatic ALDHlow. Coculture of the osteotropic PC-3M-Pro4Luc2 PCa cells with differentiated primary human osteoblasts induced CRIPTO and GRP78 expression in cancer cells and increases the size of the ALDHhigh sub-population. Additionally, CRIPTO or GRP78 knockdown decreases proliferation, migration, clonogenicity and the size of the metastasis-initiating ALDHhigh sub-population. CRIPTO knockdown reduces the invasion of PC-3M-Pro4Luc2 cells in zebrafish and inhibits bone metastasis in a preclinical mouse model. These results highlight a functional role for CRIPTO and GRP78 in PCa metastasis and suggest that targeting CRIPTO/GRP78 signaling may have significant therapeutic potential.Oncogene advance online publication, 10 April 2017; doi:10.1038/onc.2017.87