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L’articolo offre una visione d’insieme della vita e dell’opera di Diego de Pantoja (1571-1618), uno dei pionieri della missione gesuitica in Cina. Seguendo la strada aperta da Francesco Saverio, Diego de Pantoja raggiunse Pechino al seguito di Matteo Ricci, entrando in contatto con i letterati cinesi attivi nella corte imperiale e riuscendo così a dare alla missione la necessaria stabilità. Partendo dagli anni di formazione giovanile per giungere, attraverso l’epoca di attività missionaria svolta a Pechino come collaboratore prima e successore poi del padre Matteo Ricci, sino alla persecuzione di Nanchino, l’esilio e la morte avvenuta a Macao, il testo prende in esame i principali contributi offerti da Diego di Pantoja alla causa missionaria, tra cui la stesura della Relación de la entrada de algunos padres de la Compañia de Jesús en la China e de Le sette vittorie sui sette peccati capitali (Qikedaquan) e la riforma del calendario.

Ground-penetrating radar (GPR) started as a radio echo sounding technology during the second half of the last century, but it is now a well-established and widely adopted technology for producing high-resolution images of subsurface [...]

Abstract Mild cognitive impairment (MCI) is a heterogeneous syndrome with two main clinical subtypes, amnestic (aMCI) and non-amnestic (naMCI). The analysis of heart rate variability (HRV) is a tool to assess autonomic function. Cognitive and autonomic processes are linked via the central autonomic network. Autonomic dysfunction entails several adverse outcomes. However, very few studies have investigated autonomic function in MCI and none have considered MCI subtypes or the relationship of HRV indices with different cognitive domains and structural brain damage. We assessed autonomic function during an active orthostatic challenge in 253 oupatients aged ≥ 65, [n = 82 aMCI, n = 93 naMCI, n = 78 cognitively normal (CN), neuropsychologically tested] with power spectral analysis of HRV. We used visual rating scales to grade cerebrovascular burden and hippocampal/insular atrophy (HA/IA) on neuroimaging. Only aMCI showed a blunted response to orthostasis. Postural changes in normalised low frequency (LF) power and in the LF to high frequency ratio correlated with a memory test (positively) and HA/IA (negatively) in aMCI, and with attention/executive function tests (negatively) and cerebrovascular burden (positively) in naMCI. These results substantiate the view that the ANS is differentially impaired in aMCI and naMCI, consistently with the neuroanatomic substrate of Alzheimer's and small-vessel subcortical ischaemic disease.

The United Nations 2030 Agenda for Sustainable Development highlighted the importance of adopting sustainable agricultural practices to mitigate the threat posed by climate change to food systems around the world, to provide wise water management and to restore degraded lands. At the same time, it suggested the benefits and advantages brought by the use of near-surface geophysical measurements to assist precision farming, in particular providing information on soil variability at both vertical and horizontal scales. Among such survey methodologies, Ground Penetrating Radar has demonstrated its effectiveness in soil characterisation as a consequence of its sensitivity to variations in soil electrical properties and of its additional capability of investigating subsurface stratification. The aim of this contribution is to provide a comprehensive review of the current use of the GPR technique within the domain of precision irrigation, and specifically of its capacity to provide detailed information on the within-field spatial variability of the textural, structural and hydrological soil properties, which are needed to optimize irrigation management, adopting a variable-rate approach to preserve water resources while maintaining or improving crop yields and their quality. For each soil property, the review analyses the commonly adopted operational and data processing approaches, highlighting advantages and limitations.

Atrial flutter (AFL) is a common atrial arrhythmia typically characterized by electrical activity propagating around specific anatomical regions. It is usually treated with catheter ablation. However, the identification of rotational activities is not straightforward, and requires an intense effort during the first phase of the electrophysiological (EP) study, i.e., the mapping phase, in which an anatomical 3D model is built and electrograms (EGMs) are recorded. In this study, we modeled the electrical propagation pattern of AFL (measured during mapping) using network theory (NT), a well-known field of research from the computer science domain. The main advantage of NT is the large number of available algorithms that can efficiently analyze the network. Using directed network mapping, we employed a cycle-finding algorithm to detect all cycles in the network, resembling the main propagation pattern of AFL. The method was tested on two subjects in sinus rhythm, six in an experimental model of in-silico simulations, and 10 subjects diagnosed with AFL who underwent a catheter ablation. The algorithm correctly detected the electrical propagation of both sinus rhythm cases and in-silico simulations. Regarding the AFL cases, arrhythmia mechanisms were either totally or partially identified in most of the cases (8 out of 10), i.e., cycles around the mitral valve, tricuspid valve and figure-of-eight reentries. The other two cases presented a poor mapping quality or a major complexity related to previous ablations, large areas of fibrotic tissue, etc. Directed network mapping represents an innovative tool that showed promising results in identifying AFL mechanisms in an automatic fashion. Further investigations are needed to assess the reliability of the method in different clinical scenarios.

Thanks to its non-destructive, high-resolution imaging possibilities and its sensitivity to both conductive and dielectric subsurface structures, Ground-Penetrating Radar (GPR) has become a widely recognized near-surface geophysical tool, routinely adopted in a wide variety of disciplines. Since its first development almost 100 years ago, the domain in which the methodology has been successfully deployed has significantly expanded from ice sounding and environmental studies to precision agriculture and infrastructure monitoring. While such expansion has been clearly supported by the evolution of technology and electronics, the operating principles have always secured GPR a predominant position among alternative inspection approaches. The aim of this contribution is to provide a large-scale survey of the current areas where GPR has emerged as a valuable prospection methodology, highlighting the reasons for such prominence and, at the same time, to suggest where and how it could be enhanced even more.

Abstract Background To date the TGF-β1 activation mediated by integrin ανβ5 during fibrosis is well-known. This process has been shown also in the heart, where cardiac fibroblasts (CF) differentiate into α-smooth muscle actin (α-SMA)-positive myofibroblasts (MyoFB). Here, we studied the effects on CF, isolated by spontaneously hypertensive rats (SHR), of integrin ανβ5 inhibition in MyoFB differentiation. Methods Staining and immunohistochemistry were performed on rat cardiac tissue. CF were isolated by enzymatic digestion from SHR (SHR-CF) and normotensive WKY (WKY-CF) rat hearts and then treated for in vitro evaluation. Results SHR heart tissues revealed a higher TGF-β1 expression vs. WKY samples. SHR-CF showed an enhanced SMAD2/3 activation and an up-regulated expression of α-SMA, a typical MyoFB marker, especially after TGF-β1 treatment. Immunostaining on cardiac tissues revealed a higher expression of integrin ανβ5 in SHR vs. WKY rat hearts. In vitro results confirmed the up-regulation of integrin ανβ5 expression in SHR-CF at basal condition and after TGF-β1 treatment, in comparison with WKY-CF. Inhibition of integrin ανβ5 by cilengitide treatment led a decreased expression of ανβ5, collagen I, and α-SMA in SHR-CF vs. WKY-CF, resulting in a diminished differentiation of CF into MyoFB. Taking together, results suggested that SHR-CF are more susceptible to TGF-β1, showing an up-regulated activation of SMAD2/3 signaling, and an increased ανβ5, α-SMA, and collagen I expression. Hypertension stimulus promoted an up-regulation of integrin ανβ5 on SHR cardiac tissue and its in vitro inhibition reverted pro-fibrotic events of SHR-CF. Conclusion Inhibition of integrin ανβ5 exerted by cilengitide strongly diminished SHR-CF differentiation into detrimental MyoFB. So, integrin ανβ5 might be considered a novel therapeutic target and cilengitide an effective pharmacological tool to limit the progression of hypertension-induced cardiac fibrosis.

Self-driving cars and autonomous vehicles are revolutionizing the automotive sector, shaping the future of mobility altogether. Although the integration of novel technologies such as Artificial Intelligence (AI) and Cloud/Edge computing provides golden opportunities to improve autonomous driving applications, there is the need to modernize accordingly the whole prototyping and deployment cycle of AI components. This paper proposes a novel framework for developing so-called AI Inference Engines for autonomous driving applications based on deep learning modules, where training tasks are deployed elastically over both Cloud and Edge resources, with the purpose of reducing the required network bandwidth, as well as mitigating privacy issues. Based on our proposed data driven V-Model, we introduce a simple yet elegant solution for the AI components development cycle, where prototyping takes place in the cloud according to the Software-in-the-Loop (SiL) paradigm, while deployment and evaluation on the target ECUs (Electronic Control Units) is performed as Hardware-in-the-Loop (HiL) testing. The effectiveness of the proposed framework is demonstrated using two real-world use-cases of AI inference engines for autonomous vehicles, that is environment perception and most probable path prediction.

Among all the forensic applications in which it has become an important exploration tool, ground penetrating radar (GPR) methodology is being increasingly adopted for buried landmine localisation, a framework in which it is expected to improve the operations efficiency, given the high resolution imaging capability and the possibility of detecting both metallic and non-metallic landmines. In this context, this study presents landmine detection equipment based on multi-polarisation: a ground coupled GPR platform, which ensures suitable penetration/resolution performance without affecting the safety of surveys, thanks to the inclusion of a flexible ballistic shielding for supporting eventual blasts. The experimental results have shown that not only can the blanket absorb blast-induced flying fragments impacts, but that it also allows for the acquisition of data with the accuracy required to generate a correct 3D reconstruction of the subsurface. The produced GPR volume is then processed through an automated learning scheme based on a Convolutional Neural Network (CNN) capable of detecting buried objects with a high degree of accuracy.

Soil morphology plays a fundamental role in the vertical and lateral movements of solutes and water transport, providing knowledge regarding spatial distribution of its textural properties and subsurface dynamics. In this framework, the measured values of electrical conductivity are able to reveal the heterogeneity of soil that is present in a particular agricultural field and they are affected by more than one important physical characteristic: soil texture, organic matter, moisture content, and the depth of the clay pan. In the microwave region, these dynamics are known to exhibit a frequency dependent behaviour. This study explores the application of a Step Frequency Continuous Wave Ground Penetrating Radar (SFCW GPR) to shed light on the practical impact that these dependencies have on the imaging results, not only regarding the electrical characterisation of the subsurface morphology, but also in its correct interpretation. This information is of notable importance for determining water-use efficiency and planning precision-agriculture programs. The results clearly show visible and significant fluctuations of the amplitude levels, depending on the considered central frequency, demonstrating that the frequency dependence of electromagnetic properties of heterogeneous soil are significant and cannot be ignored if the aim is to properly define the subsurface attributes. The measurements also suggest that correlating the delineated variations might help in the identification of extended features and the classification of areas that possess similar properties in order to increase the confidence in monitoring soil resources.

Ground Penetrating Radar (GPR) images are affected, to some degree, by the relative orientation of antennas and subsurface targets. This is particularly true not only for targets that show a significant directivity, but also for inclined planes, such as fractures and faults. Depending on the relative geometry between the antennas and the orientation of the target, radar waves can be preferentially scattered, which causes changes in the reflected signal amplitude. Therefore, traditional single polarization and single azimuth surveys may produce inadequate results. The work presented here examines the use of a multi-azimuth GPR survey to increase the imaging performance of inclined fractures, showing the shortcomings of single-profile surveying and highlighting the benefits that such a strategy has on detection and characterization.

Heart failure is a chronic disease with high morbidity and mortality, which represents a growing challenge in medicine. A major risk factor for heart failure with reduced ejection fraction is a history of myocardial infarction. The expansion of a large infarct scar and subsequent regional ventricular dilatation can cause postinfarct remodelling, leading to significant enlargement of the left ventricular chamber. It has a negative prognostic value, because it precedes the clinical manifestations of heart failure. The characteristics of the infarcted myocardium predicting postinfarct remodelling can be studied with cardiac magnetic resonance and experimental imaging modalities such as diffusion tensor imaging can identify the changes in the architecture of myocardial fibers. This review discusses all the aspects related to postinfarct left ventricular remodelling: definition, pathogenesis, diagnosis, consequences, and available therapies, together with experimental interventions that show promising results against postinfarct remodelling and heart failure.

Background: To evaluate the changes in autonomic neural control mechanisms before malignant ventricular arrhythmias, we measured heart rate variability (HRV) and heart rate turbulence (HRT) in patients with ventricular tachycardia or fibrillation (Group I; n=6), non sustained ventricular tachycardia (Group II; n=32), frequent premature ventricular beats (Group III; n=26) and with ICD implantation (Group IV; n=11). Methods: Time domain parameters of HRV and turbulence onset (TO) and slope (TS) were calculated on 24 hour Holter recordings. Normal values were: SDNN > 70 msec for HRV, TO 2.5 msec/RR-I for HRT. Results: Whereas SDNN was within normal range and similar in all study groups, HRT parameters were significantly different in patients who experienced VT/VF during Holter recording. Abnormal TO and/or TS were present in 100% of Group I patients and only in about 50% of Group II and IV. On the contrary, normal HRT parameters were present in 40-70% of Group II, III and IV patients and none of Group I. Conclusions: These data suggest that HRT analysis is more suitable than HRV to detect those transient alterations in autonomic control mechanisms that are likely to play a major trigger role in the genesis of malignant cardiac arrhythmias. (Heart International 2007; 3: 51-7)

Background Animal study results point to oxidative stress as a key mechanism triggering postoperative atrial fibrillation (PoAF), yet the extent to which specific biomarkers of oxidative stress might relate to PoAF risk in humans remains speculative. Methods and Results We assessed the association of validated, fatty acid–derived oxidative stress biomarkers (F2‐isoprostanes, isofurans, and F3‐isoprostanes) in plasma and urine, with incident PoAF among 551 cardiac surgery patients. Biomarkers were measured at enrollment, the end of surgery, and postoperative day 2. PoAF lasting ≥30 seconds was confirmed with rhythm strip or electrocardiography and centrally adjudicated. Outcomes were assessed until hospital discharge or postoperative day 10, whichever occurred first. Urine level of each oxidative stress biomarker rose at the end of surgery (2‐ to 3‐fold over baseline, P

Background and Methods: In order to study fractal HR dynamics in Chagas disease, we performed detrended fluctuation analysis (DFA)—along with analysis of power‐law β slope (β index) and standard deviation of N–N intervals (SDNN)—in edited and unedited (with ventricular premature beats — VPBs, only in DFA analysis) series of R‐R intervals from Holter monitoring of healthy controls (Group 0, n = 27) and Chagas disease patients with left ventricular (LV) ejection fraction >50% (Group 1, n = 137) and with LV ejection fraction

Mild cognitive impairment (MCI) is set to become a major health problem with the exponential ageing of the world's population. The association between MCI and autonomic dysfunction, supported by indirect evidence and rich with clinical implications in terms of progression to dementia and increased risk of mortality and falls, has never been specifically demonstrated.To conduct a comprehensive assessment of autonomic function in subjects with MCI by means of power spectral analysis (PSA) of heart rate variability (HRV) at rest and during provocative manoeuvres.This cross-sectional study involved 80 older outpatients (aged ≥ 65) consecutively referred to a geriatric unit and diagnosed with MCI or normal cognition (controls) based on neuropsychological testing. PSA was performed on 5-minute electrocardiographic recordings under three conditions--supine rest with free breathing (baseline), supine rest with paced breathing at 12 breaths/minute (parasympathetic stimulation), and active standing (orthosympathetic stimulation)--with particular focus on the changes from baseline to stimulation of indices of sympathovagal balance: normalized low frequency (LFn) and high frequency (HFn) powers and the LF/HF ratio. Blood pressure (BP) was measured at baseline and during standing. Given its exploratory nature in a clinical population the study included subjects on medications with a potential to affect HRV.There were no significant differences in HRV indices between the two groups at baseline. MCI subjects exhibited smaller physiological changes in all three HRV indices during active standing, consistently with a dysfunction of the orthosympathetic system. Systolic BP after 10 minutes of standing was lower in MCI subjects, suggesting dysautonomia-related orthostatic BP dysregulation.Our study is novel in providing evidence of autonomic dysfunction in MCI. This is associated with orthostatic BP dysregulation and the ongoing follow-up of the study population will determine its prognostic relevance as a predictor of adverse health outcomes.

Arrhythmic death remains one of the most important causes of mortality after an acute myocardial infarction also in the revascularization era. As a consequence, identification of patients at risk should be performed before discharge. Unfortunately, in the clinical practice, this evaluation is mainly based on detection of a depressed left ventricular ejection. This approach, however, cannot adequately distinguish arrhythmic versus non-arrhythmic risk. This issue is of critical relevance when considering that arrhythmic death can be significantly reduced by appropriate interventions of implantable cardioverter defibrillator. Available evidence, however, indicates that in the first month after myocardial infarction, device implantation does not significantly reduce cardiac mortality: it seems that the reduction of arrhythmic death is counterbalanced by an increase in rate of death from non arrhythmic cause. It is therefore to be hoped that, in the future, arrhythmic risk evaluation will be based not only on the extent of left ventricular dysfunction but also on the analysis of other risk markers such as those reflecting autonomic dysfunction, cardiac electrical instability and presence of subclinical inflammation.

Objective: Undiagnosed atrial fibrillation (AF) patients are at high risk of cardioembolic stroke or other complications. The aim of this study was to analyze the blood volume pulse (BVP) signals obtained from a wristband device and develop an algorithm for discriminating AF from normal sinus rhythm (NSR) or from other arrhythmias (ARR). Approach: Thirty patients with AF, 9 with ARR and 31 in NSR were included in the study. The recordings were obtained at rest from Empatica E4 wristband device and lasted 10 min. The analysis, on a 2 min segment, included spectral, variability and irregularity analysis performed on the inter-diastolic interval series, and similarity analysis performed on the BVP signal. Main results and Significance: Variability parameters were the highest in AF, the lowest in NSR and intermediate for ARR, as an example pNN50 values were, respectively, , , (p  <  0.05). The similarity parameters were the highest in NSR, the lowest in AF and intermediate for ARR, as an example using a threshold for assessing similarity of : , , , all p  <  0.05. The rhythm classification was preceded by over-sampling (using synthetic minority over-sampling technique) the class of ARR, being it the smallest class. Then, the features selection was performed (using the sequential forward floating search algorithm) which identified two variability parameters (pNN70 and pNN40) as the best selection. The classification by the k-nearest neighbor classifier reached an accuracy of about 0.9 for NSR and AF, and 0.8 for ARR. Using pNN70 and pNN40, the specificity for the three rhythms was Spnsr  =  0.928, Spaf  =  0.963, Sparr  =  0.768, while the sensitivity was Spnsr  =  0.773, Spaf  =  0.754, Sparr  =  0.758. [ABSTRACT FROM AUTHOR]