Stationary Wavelet Transform for denoising Pulsed Thermography data: optimization of wavelet parameters for enhancing defects detection

Innovative denoising techniques based on Stationary Wavelet Transform (SWT) have started being applied to Pulsed Thermography (PT) sequences, showing marked potentialities in improving defect detection. In this contribution, a SWT-based denoising procedure is performed on high and low resolution PT sequences. Samples under test are two composite panels with known defects. The denoising procedure undergoes an optimization step. An innovative criterion for selecting the optimal decomposition level in multi-scale SWT-based denoising is proposed. The approach is based on a comparison, in the wavelet domain, of the information content in the thermal image with noise propagated. The optimal wavelet basis is selected according to two performance indexes, respectively based on the probability distribution of the information content of the denoised frame, and on the Energy-to-Shannon Entropy ratio. After the optimization step, denoising is applied on the whole thermal sequence. The approximation coefficients at the optimal level are moved to the frequency domain, then low-pass filtered. Linear Minimum Mean Square Error (LMMSE) is applied to detail coefficients at the optimal level. Finally, Pulsed Phase Thermography (PPT) is performed. The performance of the optimized denoising method in improving the defect detection capability respect to the non-denoised case is quantified using the Contrast Noise Ratio (CNR) criterion

An Integrated Caco-2TC7cells/biosensors Device for the Real Time Monitoring of Intestinal Glucose and Polyphenols Absorption and Hypoglycemic Effect of Phytochemicals

Abstract An integrated device, for real-time monitoring of glucose and phenols absorption, that consists of a sensors/biosensors system (SB) and a Caco-2TC7 human intestinal cell culture, is shown here. The SB was made of a glucose oxidase-based biosensor, a sentinel platinum sensor, a laccase/tyrosinase-based biosensor and a sentinel carbon sensor located in the basolateral compartment (BC) of a cell culture plate. This system was able to monitor the glucose absorption and the hypoglycemic effect induced by different polyphenols and could be proposed to provide an effective strategy to manage postprandial hyperglycemia with natural compounds

Caratterizzazione della dinamica produttiva di pascoli naturali italiani

This work studies herbage production and its seasonal distribution in indigenous pastures, and analyses the relationship between the environmental factors (soil, clima, vegetation) and the productivity of these resources. The investigations have been carried on during the period 1983-90 by the joint activity of 10 different University Istitutions in 23 different environments distributed along the Italian peninsula and the main islands. For each environment, pasture production has been measured with the Corrall and Fenlon method, analysing the more important vegetational and ecological conditions; altogether the total yearly production and the seasonal pattern of herbage production have been detected on 104 pastures. The total herbage yield is not significantly influenced by the latitudinal gradient, and the overall regional (alps, central Appenine, south Apennine and islands) production is about 2.3 t ha-1 year-1 The wide range (0.5-6.3 t ha-1 year-1) of herbage production, on small or medium scale, seems to be due to evident changeof environmental or management factors. Five types of seasonal distribution of herbage growth are evidenced with multivariate analysis methods, based on the growing season and the amplitude of the growth. With mean temperature above 12°C and total rainfall below 800 mm, herbage distribution shows a standstill during summer period and an evident regrowth in autumn. On the contrary, for the 4 other distribution types, the winter standstill become important, and the types are distinct by summer growth amplitude and by the growing season lenght. With cluster analysis method, for each type of herbage distribution, have been pointed out under-types characterized by interannual herbage production variation. Among the environmental factors, vegetation characheristics, expressed as Pasture Value following Daget and Poissonet seems to be strictly correlated with total production. The comparative poor role played by the soil and climatic factor, may be due to the strong past and present antropic influence, related with management and utilization techniques. Il presente lavoro ha come scopo l'approfondimento delle conoscenze sulla produzione e sulla distribuzione stagionale della crescita dell'erba dei pascoli naturali, nonché l'analisi delle interazioni tra i fattori ambientali, pedo-climatici e vegetazionali, e la risposta produttiva di queste risorse. La ricerca è stata condotta nel periodo 1983-90 da 10 diverse Istituzioni Universitarie, in 23 ambienti differenti, distribuiti lungo tutta la penisola e le isole maggiori. Per ogni ambiente, con il metodo di rilievo di Corrall e Fenlon, è stata saggiata la risposta produttiva di pascoli rappresentativi delle principali situazioni vegetazionali e di giacitura; complessivamente sono state rilevate la produzione totale annua e la curva di produttività media pluriennale di 104 pascoli. Riguardo la produzione annua complessiva si è osservato che essa non presenta variazioni significative lungo il gradiente latitudinale, collocandosi tra le diverse regioni (alpina, centro appenninica, suq, appenninica e insulare) attorno a 2.3 t ha-1 anno-1. La fitomassa raccolta è soggetta invece a variazioni sensibili (0.5-6.3 t ha-1 anno-1) riconducibili a fattori ambientali e gestionali che si esprimono su piccola e media scala. Con metodi di analisi multivariata si sono individuate 5 tipologie distributive della crescita dell'erba, in rapporto alla stagione vegetativa e alle variazioni dell'intensità di crescita nel corso della stagione stessa. Con temperature medie e precipitazioni annue rispettivamente maggiori di 12°C e minori di 800 mm, risulta evidente la stasi vegetativa nel trimestre estivo e la ripresa vegetativa autunnale. Nel caso opposto la stasi è invernale e le 4 tipologie afferenti a questo modello, sono distinguibili dall'entità della crescita nei mesi estivi e dalla durata della stagione vegetativa. Per ogni tipologia produttiva, sono state evidenziate, tramite l'analisi cluster, sotto-tipologie distinte per la variabilità produttiva interannuale. Tra i fattori ambientali, la vegetazione, espressa attraverso l'indice del valore pastorale di Daget e Poissonet, presenta una buona capacità predittiva nei confronti del livello produttivo dei pascoli. Il contributo comparativamente modesto offerto dai fattori pedoclimatici sembra attribuibile alla forte influenza antropica, pregressa e attuale, attraverso le cure colturali e l'utilizzazione

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

A new hybrid soft-sensing approach (based on IR Sensor data) for the assessment of the properties characterizing the dynamic thermal behaviour of a building component

Uno degli aspetti principali in termini di risparmio energetico è legato alle performance energetiche dei component da edilizia. Per questa ragione, in letteratura è possibile trovare sempre più lavori riguardanti la valutazione delle proprietà termiche dei component da edilizia (conducibilità termica, trasmittanza termica, sfasamento). Molti lavori e standard descrivono la valutazione delle proprietà termiche in condizioni di regime stazionario ma in molti casi, ad esempio in applicazioni in opera, queste condizioni sono estramamente complicate da riprodurre. Per questa ragione, la ricerca si è focalizzata sul comportamento termico dinamico dei materiali che consente di caratterizzare le proprietà termiche dinamiche in condizioni più facilmente riproducibili. Le metodologie attuali per la valutazione del comportamento termico dinamico di un material presentano diversi problemi e difficoltà:  Sensori a contatto: gli standard attuali prevedono una valutazione puntuale che non è spesso rappresentativa del comportamento termico dinamico dell’intero muro;  Condizioni ambientali: uno degli aspetti più importati in termini di incertezza di misura è rappresenato dale condizioni ambientali che condizionano i dati misurati. Infatti, l’elevatà sensibilità dei sensori (termoflussimetro e termocoppie) rende quest’aspetto critic durante una campagna di test.  Durata del test: gli standard attuali richiedono almeno 72h di monnitoraggio per test sul campo. In molte condizioni non è possibile avere durate così eccessive. Per accrescere lo stato dell’arte è presentata una tecnica innovativa, basata su un approccio Soft-Sensing che combina dati misurati con un modello predittivo, con lo scopo di implementare le attuali metodologie di misura in termini di accuratezza, consume di tempo e valutazione del reale comportamento dinamico di un componente. Inoltre, la tecnica proposta è basata sull’uso di un sensore ad infrarossi che porta I seguenti vantaggi:  Sensori non a contatto rispetto agli attuali standard basati sull’uso di termocoppie e termoflussimetro;  Valurtazione “full-field” dell’intera scena inquadrata rispetto ad una valutazione puntuale ottenuta con dei sensori a contatto. I risultati ottenuti mostrano una differenza tra il valore dichiarato di trasmittanza termica e quello misurato che raggiunge al massimo il 5% nell condizioni di prova più sfavorevoli (cambiamenti di velocità dell’aria e sorgenti irradianti durante il test) ed una riduzione dei tempi nell’ordine dello sfasamento termico del materiale. Questo risultato accresce lo stato dell’arte che invece dichiarano un valore di incertezza di almeno l’8% per il test termoflussimetrico con una durata di almeno 72h.One of the main aspects in terms of energy-saving is related to the thermal performances of the building component. For this reason, more and more works can be found in the literature concerning the thermal properties assessment of the building components (conductivity, thermal transmittance, phase shift). Many works and standards describes the steady-state condition for the thermal properties evaluation but in more condition, like in-situ application, these conditions are very difficult to reproduce. For this reason, the research has been focused on the dynamic thermal behavior of a material that allows to characterize the dynamical thermal properties in more reproducible conditions. The actual methodologies for the dynamic thermal behavior assessment present many problems and difficulties:  Contact sensors: the actual standards provide a single point evaluation which is not representative of the wall thermal dynamic behavior;  Environmental conditions: one of the main aspect in terms of measurement uncertainty is represented by the environmental conditions which affect the measured data. In fact, the high sensitivity of the sensors (heat flow meter and thermocouples) makes this aspect critical in a test campaign;  Time consuming: the actual standards require at least 72h of monitoring for in-situ test. In many conditions there is not the possibility to have a so long time monitoring. In order to enhance the state-of-the-art an innovative approach is presented, based on Soft-Sensing approach that combines the measured data with a predictive model, with the ambition to improve the actual measurement methodologies in terms of accuracy, time-consuming and evaluation of the real building component behavior. Furthermore, the data are acquired with an IR sensor that gives the following advantages:  Non-contact sensor in respect to the actual standards based on the use of thermocouples and heat flow meters;  Full-field evaluation in respect to a single point evaluation obtained with a contact sensor; The results obtained show a deviation between the declared value of thermal transmittance of the building component analyzed up to 5% in more unfavorable conditions (air velocity changes and radiative external source) and a time-consuming reduction related to the thermal phase shift of the material. This result enhances the actual standard procedures that have a declared uncertainty value at least of ±8 % for the heat flow meter method with a time required for the test at least of 72h

Stationary Wavelet Transform for denoising Pulsed Thermography data: optimization of wavelet parameters for enhancing defects detection

Innovative denoising techniques based on Stationary Wavelet Transform (SWT) have started being applied to Pulsed Thermography (PT) sequences, showing marked potentialities in improving defect detection. In this contribution, a SWT-based denoising procedure is performed on high and low resolution PT sequences. Samples under test are two composite panels with known defects. The denoising procedure undergoes an optimization step. An innovative criterion for selecting the optimal decomposition level in multi-scale SWT-based denoising is proposed. The approach is based on a comparison, in the wavelet domain, of the information content in the thermal image with noise propagated. The optimal wavelet basis is selected according to two performance indexes, respectively based on the probability distribution of the information content of the denoised frame, and on the Energy-to-Shannon Entropy ratio. After the optimization step, denoising is applied on the whole thermal sequence. The approximation coefficients at the optimal level are moved to the frequency domain, then low-pass filtered. Linear Minimum Mean Square Error (LMMSE) is applied to detail coefficients at the optimal level. Finally, Pulsed Phase Thermography (PPT) is performed. The performance of the optimized denoising method in improving the defect detection capability respect to the non-denoised case is quantified using the Contrast Noise Ratio (CNR) criterion

Diagnostic accuracy of heart murmur in newborns with suspected congenital heart disease

The correlation between heart murmur and congenital heart disease (CHD) is complex and varies with observed population

Headache and recurrent abdominal pain: a controlled study by the means of the Child Behavior Checklist (CBCL).

Headache and recurrent abdominal pain (RAP) are common disorders in children and adolescents, frequently referred to paediatricians. Both disorders show similarities in trigger and comorbid factors, their burden on family and individual life, and a paroxysmal trend with risks of chronicization over time. However, very few studies have compared directly headache and RAP. The main aim of this study was to compare the psychological profile of headache and RAP patients vs. healthy controls. A total of 210 children and adolescents [99 boys, 111 girls; age range 4–18 years; mean age (m.a.) = 11.04, SD 4.05] were assessed: 70 headache patients (m.a. 12.4 years; SD 2.9; F = 35, M = 35), 70 RAP patients (m.a. 9 years; SD 3.6; F = 30, M = 40) and 70 controls (m.a. 11.7 years; SD 4.6; F = 46, M = 24). The diagnoses had been made according to international systems of classification both for headache (ICHD-II criteria) and RAP (Rome II criteria). The psychological profile had been made according to the Child Behaviour Checklist 4–18 (CBCL). ANOVA one-way analysis was used to compare CBCL scales and subscales between groups. Headache and RAP showed a very similar trend vs. control for the main scales of the CBCL, with a statistically significant tendency to show problems in the Internalizing scale (anxiety, mood and somatic complaints) and no problems in the Externalizing (behavioural) scale. Only for the Attention Problems subscale migraineurs showed a significant difference compared with RAP. In conclusion, headache and RAP show a very similar psychological profile that should be considered not only for diagnostic and therapeutic purposes, but also from the aetiological aspect