Artificial neural-network technique for precipitation nowcasting from satellite imagery

The term nowcasting reflects the need of timely and accurate predictions of risky situations related to the development of severe meteorological events. In this work the objective is the very short term prediction of the rainfall field from geostationary satellite imagery entirely based on neural network approach. The very short-time prediction (or nowcasting) process consists of two steps: first, the infrared radiance field measured from geostationary satellite (Meteosat 7) is projected ahead in time (30 min or 1 h); secondly, the projected radiances are used to estimate the rainfall field by means of a calibrated microwave-based combined algorithm. The methodology is discussed and its accuracy is quantified by means of error indicators. An application to a satellite observation of a rainfall event over Central Italy is finally shown and evaluated

Fatigue behavior of foreign object damaged 7075 heat treated aluminum alloy coated with PVD WC/C

AbstractThe effect of a physically vapor deposited (PVD) WC/C coating on the fatigue behavior of as produced and foreign object damaged (FOD) solution heat treated and aged 7075 aluminum alloy was studied. Coated and uncoated samples were tested under rotating bending to determine the fatigue strengths between 104 and 106 cycles in both damaged and smooth condition. FOD was produced with single shots of small hard steel spheres impacting at 100 m/s in the minimum cross section. SEM was used to characterize the features of the fracture surfaces

Two trans-acting eQTLs modulate the penetrance of PRPF31 mutations

Dominant mutations in the gene encoding the ubiquitously-expressed splicing factor PRPF31 cause retinitis pigmentosa, a form of hereditary retinal degeneration, with reduced penetrance. We and others have previously shown that penetrance is tightly correlated with PRPF31 expression, as lymphoblastoid cell lines (LCLs) from affected patients produce less abundant PRPF31 transcripts than LCLs from their unaffected relatives carrying the same mutation. We have investigated the genetic elements determining the variable expression of PRPF31, and therefore possibly influencing the penetrance of its mutations, by quantifying PRPF31 mRNA levels in LCLs derived from 15 CEPH families (200 individuals), representative of the general population. We found that PRPF31 transcript abundance was a highly variable and highly heritable character. Moreover, by linkage analysis we showed that PRPF31 expression was significantly associated with at least one expression quantitative trait locus (eQTL), spanning a 8.2-Mb region on chromosome 14q21-23. We also investigated a previously mapped penetrance factor located near PRPF31 itself in LCLs from individuals belonging to selected families segregating PRPF31 mutations that displayed reduced penetrance. Our results indicate that, despite its constant association with the non-mutant allele, this factor was able to modulate the expression of both PRPF31 alleles. Furthermore, we showed that LCLs from affected patients have less PRPF31 RNA than those of asymptomatic patients, even at the pre-splicing stage. Altogether, these data demonstrate that PRPF31 mRNA expression and consequently the penetrance of PRPF31 mutations is managed by diffusible compounds encoded by at least two modifiers, acting in a co-regulatory system on both PRPF31 alleles during transcriptio

The Digital Image Correlation technique applied to the deformation behavior of welded sheet joints

The existence of a welded zone generally influences the local strain and stress distribution especially in case of welding defects. A method able to measure the local deformability can hence give many important information about the real stress and strain fields useful to improve the welded structure design. In this experimental work, some new generation automotive steels have been considered, because of the well known welding problems due to their unstable microstructural condition. Such materials, known as Q&P steels and available only as thin sheets, require a suitable quenching process able to give high mechanical resistance and satisfying deformability. Some sheet samples were welded by electron beam technique, because it is able to reduce the width of the heat affected zone where the main microstructural changes are concentrated. From such samples, tensile specimens were machined. During the tensile tests, the deformations were measured both by a traditional extensometer and by a 3D Digital Image Correlation (3D DIC) technique. A preliminary investigation of the melted and the heat affected zones resulted in small dimensions (about 10 mm) and hence the measuring setup has been optimized in order maximize the achievable measuring resolution minimizing the resulting uncertainty. This result can be achieved by a pattern generated by a suitable software and by an accurate preparation of the surface where the pattern will be deposited on

Design and Validation of a Minimal Complexity Algorithm for Stair Step Counting

Wearable sensors play a significant role for monitoring the functional ability of the elderly and in general, promoting active ageing. One of the relevant variables to be tracked is the number of stair steps (single stair steps) performed daily, which is more challenging than counting flight of stairs and detecting stair climbing. In this study, we proposed a minimal complexity algorithm composed of a hierarchical classifier and a linear model to estimate the number of stair steps performed during everyday activities. The algorithm was calibrated on accelerometer and barometer recordings measured using a sensor platform worn at the wrist from 20 healthy subjects. It was then tested on 10 older people, specifically enrolled for the study. The algorithm was then compared with other three state-of-the-art methods, which used the accelerometer, the barometer or both. The experiments showed the good performance of our algorithm (stair step counting error: 13.8%), comparable with the best state-of-the-art (p > 0.05), but using a lower computational load and model complexity. Finally, the algorithm was successfully implemented in a low-power smartwatch prototype with a memory footprint of about 4 kB

Self-reported face recognition abilities moderately predict face-learning skills: Evidence from Italian samples

Face Recognition Ability (FRA) varies widely throughout the population. Previous research highlights a positive relationship between self-perceived and objectively measured FRA in the healthy population, suggesting that people do have insight into their FRA. Given that this relationship has not been investigated in Italian samples yet, the main aim of the present work was to develop an Italian translation of the Prosopagnosia Index-20 (PI-20), a self-report measure of FRA, to investigate the relationship between PI-20 performances and an objective assessment given by the Cambridge Face Memory Test Long Form (CFMT+) in the Italian population. A sample of 553 participants filled in the PI-20 Italian version 1 or 2 (PI-20_GE or PI-20_BA) and completed the CFMT+. Results showed a negative correlation between both versions of the Italian PI-20 and CFMT+ scores, meaning that the more self-evaluations were negative, the worse they objectively performed. The same results applied to the extreme limits of the distribution (i.e., 10% of the highest and lowest PI-20 scores). Furthermore, both age and administration order of the tests were predictor variables of CFMT+ scores. Overall, our results suggest that people possess insight, although relatively limited, into their FRA

Classification accuracy of blood-based and neurophysiological markers in the differential diagnosis of Alzheimer’s disease and frontotemporal lobar degeneration

Background: In the last decade, non-invasive blood-based and neurophysiological biomarkers have shown great potential for the discrimination of several neurodegenerative disorders. However, in the clinical workup of patients with cognitive impairment, it will be highly unlikely that any biomarker will achieve the highest potential predictive accuracy on its own, owing to the multifactorial nature of Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD). Methods: In this retrospective study, performed on 202 participants, we analysed plasma neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and tau phosphorylated at amino acid 181 (p-Tau181) concentrations, as well as amyloid β42 to 40 ratio (Aβ1–42/1–40) ratio, using the ultrasensitive single-molecule array (Simoa) technique, and neurophysiological measures obtained by transcranial magnetic stimulation (TMS), including short-interval intracortical inhibition (SICI), intracortical facilitation (ICF), long-interval intracortical inhibition (LICI), and short-latency afferent inhibition (SAI). We assessed the diagnostic accuracy of combinations of both plasma and neurophysiological biomarkers in the differential diagnosis between healthy ageing, AD, and FTLD. Results: We observed significant differences in plasma NfL, GFAP, and p-Tau181 levels between the groups, but not for the Aβ1–42/Aβ1–40 ratio. For the evaluation of diagnostic accuracy, we adopted a two-step process which reflects the clinical judgement on clinical grounds. In the first step, the best single biomarker to classify “cases” vs “controls” was NfL (AUC 0.94, p < 0.001), whilst in the second step, the best single biomarker to classify AD vs FTLD was SAI (AUC 0.96, p < 0.001). The combination of multiple biomarkers significantly increased diagnostic accuracy. The best model for classifying “cases” vs “controls” included the predictors p-Tau181, GFAP, NfL, SICI, ICF, and SAI, resulting in an AUC of 0.99 (p < 0.001). For the second step, classifying AD from FTD, the best model included the combination of Aβ1–42/Aβ1–40 ratio, p-Tau181, SICI, ICF, and SAI, resulting in an AUC of 0.98 (p < 0.001). Conclusions: The combined assessment of plasma and neurophysiological measures may greatly improve the differential diagnosis of AD and FTLD

Genomic analysis of the function of the transcription factor gata3 during development of the Mammalian inner ear

We have studied the function of the zinc finger transcription factor gata3 in auditory system development by analysing temporal profiles of gene expression during differentiation of conditionally immortal cell lines derived to model specific auditory cell types and developmental stages. We tested and applied a novel probabilistic method called the gamma Model for Oligonucleotide Signals to analyse hybridization signals from Affymetrix oligonucleotide arrays. Expression levels estimated by this method correlated closely (p<0.0001) across a 10-fold range with those measured by quantitative RT-PCR for a sample of 61 different genes. In an unbiased list of 26 genes whose temporal profiles clustered most closely with that of gata3 in all cell lines, 10 were linked to Insulin-like Growth Factor signalling, including the serine/threonine kinase Akt/PKB. Knock-down of gata3 in vitro was associated with a decrease in expression of genes linked to IGF-signalling, including IGF1, IGF2 and several IGF-binding proteins. It also led to a small decrease in protein levels of the serine-threonine kinase Akt2/PKB beta, a dramatic increase in Akt1/PKB alpha protein and relocation of Akt1/PKB alpha from the nucleus to the cytoplasm. The cyclin-dependent kinase inhibitor p27(kip1), a known target of PKB/Akt, simultaneously decreased. In heterozygous gata3 null mice the expression of gata3 correlated with high levels of activated Akt/PKB. This functional relationship could explain the diverse function of gata3 during development, the hearing loss associated with gata3 heterozygous null mice and the broader symptoms of human patients with Hearing-Deafness-Renal anomaly syndrome

Mutational screening of splicing factor genes in cases with autosomal dominant retinitis pigmentosa.

PURPOSE: Mutations in genes encoding proteins from the tri-snRNP complex of the spliceosome account for more than 12% of cases of autosomal dominant retinitis pigmentosa (adRP). Although the exact mechanism by which splicing factor defects trigger photoreceptor death is not completely clear, their role in retinitis pigmentosa has been demonstrated by several genetic and functional studies. To test for possible novel associations between splicing factors and adRP, we screened four tri-snRNP splicing factor genes (EFTUD2, PRPF4, NHP2L1, and AAR2) as candidate disease genes. METHODS: We screened up to 303 patients with adRP from Europe and North America who did not carry known RP mutations. Exon-PCR and Sanger methods were used to sequence the NHP2L1 and AAR2 genes, while the sequences of EFTUD2 and PRPF4 were obtained by using long-range PCRs spanning coding and non-coding regions followed by next-generation sequencing. RESULTS: We detected novel missense changes in individual patients in the sequence of the genes PRPF4 and EFTUD2, but the role of these changes in relationship to disease could not be verified. In one other patient we identified a novel nucleotide substitution in the 5' untranslated region (UTR) of NHP2L1, which did not segregate with the disease in the family. CONCLUSIONS: The absence of clearly pathogenic mutations in the candidate genes screened in our cohort suggests that EFTUD2, PRPF4, NHP2L1, and AAR2 are either not involved in adRP or are associated with the disease in rare instances, at least as observed in this study in patients of European and North American origin