Reflectometric System for Continuous and Automated Monitoring of Irrigation in Agriculture

In this work, a time domain reflectometry (TDR)-based system for continuous and diffused monitoring of soil water content in agriculture is presented. The proposed TDR-based system employs elongate sensing elements (SEs). In practical application, each wire-like SE is buried along the cultivation row to be monitored, and through a single TDR measurement it is possible to retrieve the water content profile of the cultivation along the length of the SE. By connecting the TDR-based monitoring system to the irrigation machines, it would be possible to automatically start/stop irrigation based on the actual water requirement of the cultivations, thus favoring precision agriculture and enhancing irrigation efficiency. To demonstrate the feasibility of the proposed monitoring solution, a dedicated hardware+software platform was developed and the TDR-based system was experimented in open-field cultivations

Uncovering the Correlation between COVID-19 and Neurodegenerative Processes: Toward a New Approach Based on EEG Entropic Analysis

COVID-19 is an ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although it primarily attacks the respiratory tract, inflammation can also affect the central nervous system (CNS), leading to chemo-sensory deficits such as anosmia and serious cognitive problems. Recent studies have shown a connection between COVID-19 and neurodegenerative diseases, particularly Alzheimer’s disease (AD). In fact, AD appears to exhibit neurological mechanisms of protein interactions similar to those that occur during COVID-19. Starting from these considerations, this perspective paper outlines a new approach based on the analysis of the complexity of brain signals to identify and quantify common features between COVID-19 and neurodegenerative disorders. Considering the relation between olfactory deficits, AD, and COVID-19, we present an experimental design involving olfactory tasks using multiscale fuzzy entropy (MFE) for electroencephalographic (EEG) signal analysis. Additionally, we present the open challenges and future perspectives. More specifically, the challenges are related to the lack of clinical standards regarding EEG signal entropy and public data that can be exploited in the experimental phase. Furthermore, the integration of EEG analysis with machine learning still requires further investigatio

Microwave reflectometric systems and monitoring apparatus for diffused-sensing applications

Most sensing networks rely on punctual/local sensors; they thus lack the ability to spatially resolve the quantity to be monitored (e.g. a temperature or humidity profile) without relying on the deployment of numerous inline sensors. Currently, most quasi-distributed or distributed sensing technologies rely on the use of optical fibre systems. However, these are generally expensive, which limits their large-scale adoption. Recently, elongated sensing elements have been successfully used with time-domain reflectometry (TDR) to implement diffused monitoring solutions. The advantage of TDR is that it is a relatively low-cost technology, with adequate measurement accuracy and the potential to be customised to suit the specific needs of different application contexts in the 4.0 era. Based on these considerations, this paper addresses the design, implementation and experimental validation of a novel generation of elongated sensing element networks, which can be permanently installed in the systems that need to be monitored and used for obtaining the diffused profile of the quantity to be monitored. Three applications are considered as case studies: monitoring the irrigation process in agriculture, leak detection in underground pipes and the monitoring of building structures

Combined Punctual and Diffused Monitoring of Concrete Structures Based on Dielectric Measurements

This work presents a microwave reflectometry-based system for monitoring large concretestructures (during the curing process and also while the structure is in use), through the combineduse of punctual and diffused sensing elements. In particular, the adoption of punctual probes ona reference concrete specimen allows the development of an innovative and accurate calibrationprocedure, useful to obtain the value of the water content on a larger structure made of the samematerial. Additionally, a wire-like diffused sensing element can be permanently embedded inbuildings and used to monitor the structure along the entire length of the sensing element. Theadopted diffused sensing element can be used not only to detect dielectric variation during the curingprocess, but also throughout the service life of the structure. The combined use of punctual anddiffused sensing elements represents an important innovation from a procedural point of view, ableto provide detailed and quantitative information on the health status of the structure both duringand after construction

Assessment and Scientific Progresses in the Analysis of Olfactory Evoked Potentials

The human sense of smell is important for many vital functions, but with the current state of the art, there is a lack of objective and non-invasive methods for smell disorder diagnostics. In recent years, increasing attention is being paid to olfactory event-related potentials (OERPs) of the brain, as a viable tool for the objective assessment of olfactory dysfunctions. The aim of this review is to describe the main features of OERPs signals, the most widely used recording and processing techniques, and the scientific progress and relevance in the use of OERPs in many important application fields. In particular, the innovative role of OERPs is exploited in olfactory disorders that can influence emotions and personality or can be potential indicators of the onset or progression of neurological disorders. For all these reasons, this review presents and analyzes the latest scientific results and future challenges in the use of OERPs signals as an attractive solution for the objective monitoring technique of olfactory disorder

A Method for Optimizing the Artifact Subspace Reconstruction Performance in Low-Density EEG

— Electroencephalogram (EEG) plays a significant role in the analysis of cerebral activity, although the recorded electrical brain signals are always contaminated with artifacts. This represents the major issue limiting the use of EEG in daily life applications, as artifact removal process still remains a challenging task. Among the available methodologies, Artifact Subspace Reconstruction (ASR) is a promising tool that can effectively remove transient or large-amplitude artifacts. However, the effectiveness of ASR and the optimal choice of its parameters have been validated only for high-density EEG acquisitions. In this regard, the present study proposes an enhanced procedure for the optimal individuation of ASR parameters, in order to successfully remove artifact in lowdensity EEG acquisitions (down to four channels). The proposed method starts from the analysis of real EEG data, to generate a large semi-simulated dataset with similar characteristics. Through a finetuning procedure on this semi-simulated data, the proposed method identifies the optimal parameters to be used for artifact removal on real data. The results show that the algorithm achieves an efficient removal of artifacts preserving brain signal information, also in low-density EEG signals, thus favoring the adoption of EEG also for more portable and/or daily-life applications

Brain connectomics' modification to clarify motor and nonmotor features of myotonic dystrophy type 1

The adult form of myotonic dystrophy type 1 (DM1) presents with paradoxical inconsistencies between severity of brain damage, relative preservation of cognition, and failure in everyday life. This study, based on the assessment of brain connectivity and mechanisms of plasticity, aimed at reconciling these conflicting issues. Resting-state functional MRI and graph theoretical methods of analysis were used to assess brain topological features in a large cohort of patients with DM1. Patients, compared to controls, revealed reduced connectivity in a large frontoparietal network that correlated with their isolated impairment in visuospatial reasoning. Despite a global preservation of the topological properties, peculiar patterns of frontal disconnection and increased parietal-cerebellar connectivity were also identified in patients' brains. The balance between loss of connectivity and compensatory mechanisms in different brain networks might explain the paradoxical mismatch between structural brain damage and minimal cognitive deficits observed in these patients. This study provides a comprehensive assessment of brain abnormalities that fit well with both motor and nonmotor clinical features experienced by patients in their everyday life. The current findings suggest that measures of functional connectivity may offer the possibility of characterizing individual patients with the potential to become a clinical tool

SARS-CoV-2 infection in pregnancy. Clues and proof of adverse outcomes

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) represents one of the most threatening viral infections in the last decade. Amongst susceptible individuals, infected pregnant women might be predisposed to severe complications. Despite the extensive interest in SARS-CoV-2 research, the clinical course of maternal infection, the vertical transmission and the neonatal outcomes have not been completely understood yet. The aim of our study was to investigate the association between SARS-CoV-2 infection, obstetric outcomes and vertical transmission. Methods: A prospective observational study was performed, enrolling unvaccinated pregnant patients positive for SARS-CoV-2 (cases) and matched with uninfected pregnant women (controls). Maternal and neonatal nasopharyngeal swabs, maternal and cord blood, amniotic fluid and placenta tissue samples were collected; blood samples were tested for anti-S and anti-N antibodies, and histologic examination of placental tissues was performed. Results: The cases showed a significant association with the development of some obstetric complications, such as intrauterine growth restriction and pregnancy-associated hypothyroidism and diabetes, as compared to controls; their newborns were more likely to have a low birth weight and an arterial umbilical pH less than 7. The viral genome was detected in maternal and cord blood and placental samples in six cases. Conclusions: Pregnant women positive for SARS-CoV-2 infection are more likely to develop severe obstetric outcomes; their newborns could have a low birth weight and arterial pH. Vertical transmission seems a rare event, and further investigation is strongly needed

Psychological treatments and psychotherapies in the neurorehabilitation of pain. Evidences and recommendations from the italian consensus conference on pain in neurorehabilitation

BACKGROUND: It is increasingly recognized that treating pain is crucial for effective care within neurological rehabilitation in the setting of the neurological rehabilitation. The Italian Consensus Conference on Pain in Neurorehabilitation was constituted with the purpose identifying best practices for us in this context. Along with drug therapies and physical interventions, psychological treatments have been proven to be some of the most valuable tools that can be used within a multidisciplinary approach for fostering a reduction in pain intensity. However, there is a need to elucidate what forms of psychotherapy could be effectively matched with the specific pathologies that are typically addressed by neurorehabilitation teams. OBJECTIVES: To extensively assess the available evidence which supports the use of psychological therapies for pain reduction in neurological diseases. METHODS: A systematic review of the studies evaluating the effect of psychotherapies on pain intensity in neurological disorders was performed through an electronic search using PUBMED, EMBASE, and the Cochrane Database of Systematic Reviews. Based on the level of evidence of the included studies, recommendations were outlined separately for the different conditions. RESULTS: The literature search yielded 2352 results and the final database included 400 articles. The overall strength of the recommendations was medium/low. The different forms of psychological interventions, including Cognitive-Behavioral Therapy, cognitive or behavioral techniques, Mindfulness, hypnosis, Acceptance and Commitment Therapy (ACT), Brief Interpersonal Therapy, virtual reality interventions, various forms of biofeedback and mirror therapy were found to be effective for pain reduction in pathologies such as musculoskeletal pain, fibromyalgia, Complex Regional Pain Syndrome, Central Post-Stroke pain, Phantom Limb Pain, pain secondary to Spinal Cord Injury, multiple sclerosis and other debilitating syndromes, diabetic neuropathy, Medically Unexplained Symptoms, migraine and headache. CONCLUSIONS: Psychological interventions and psychotherapies are safe and effective treatments that can be used within an integrated approach for patients undergoing neurological rehabilitation for pain. The different interventions can be specifically selected depending on the disease being treated. A table of evidence and recommendations from the Italian Consensus Conference on Pain in Neurorehabilitation is also provided in the final part of the pape