The Rhythms of the Night: increase in online night activity and emotional resilience during the Spring 2020 Covid-19 lockdown

Context. The lockdown orders established in multiple countries in response to the Covid-19 pandemics are arguably one of the most widespread and deepest shock experienced by societies in recent years. Studying their impact trough the lens of social media offers an unprecedented opportunity to understand the susceptibility and the resilience of human activity patterns to large-scale exogenous shocks. Firstly, we investigate the changes that this upheaval has caused in online activity in terms of time spent online, themes and emotion shared on the platforms, and rhythms of content consumption. Secondly, we examine the resilience of certain platform characteristics, such as the daily rhythms of emotion expression. Data. Two independent datasets about the French cyberspace: a fine-grained temporal record of almost 100 thousand YouTube videos and a collection of 8 million Tweets between February 17 and April 14, 2020. Findings. In both datasets we observe a reshaping of the circadian rhythms with an increase of night activity during the lockdown. The analysis of the videos and tweets published during lockdown shows a general decrease in emotional contents and a shift from themes like work and money to themes like death and safety. However, the daily patterns of emotions remain mostly unchanged, thereby suggesting that emotional cycles are resilient to exogenous shocks.Comment: Under revie

A novel broadband forcecardiography sensor for simultaneous monitoring of respiration, infrasonic cardiac vibrations and heart sounds

The precordial mechanical vibrations generated by cardiac contractions have a rich frequency spectrum. While the lowest frequencies can be palpated, the higher infrasonic frequencies are usually captured by the seismocardiogram (SCG) signal and the audible ones correspond to heart sounds. Forcecardiography (FCG) is a non-invasive technique that measures these vibrations via force sensing resistors (FSR). This study presents a new piezoelectric sensor able to record all heart vibrations simultaneously, as well as a respiration signal. The new sensor was compared to the FSR-based one to assess its suitability for FCG. An electrocardiogram (ECG) lead and a signal from an electro-resistive respiration band (ERB) were synchronously acquired as references on six healthy volunteers (4 males, 2 females) at rest. The raw signals from the piezoelectric and the FSR-based sensors turned out to be very similar. The raw signals were divided into four components: Forcerespirogram (FRG), Low-Frequency FCG (LF-FCG), High- Frequency FCG (HF-FCG) and heart sounds (HS-FCG). A beat-by-beat comparison of FCG and ECG signals was carried out by means of regression, correlation and Bland–Altman analyses, and similarly for respiration signals (FRG and ERB). The results showed that the infrasonic FCG components are strongly related to the cardiac cycle (R2 > 0.999, null bias and Limits of Agreement (LoA) of ± 4.9 ms for HF-FCG; R2 > 0.99, null bias and LoA of ± 26.9 ms for LF-FCG) and the FRG inter-breath intervals are consistent with ERB ones (R2 > 0.99, non-significant bias and LoA of ± 0.46 s). Furthermore, the piezoelectric sensor was tested against an accelerometer and an electronic stethoscope: synchronous acquisitions were performed to quantify the similarity between the signals. ECG-triggered ensemble averages (synchronized with R-peaks) of HF-FCG and SCG showed a correlation greater than 0.81, while those of HS-FCG and PCG scored a correlation greater than 0.85. The piezoelectric sensor demonstrated superior performances as compared to the FSR, providing more accurate, beat-by-beat measurements. This is the first time that a single piezoelectric sensor demonstrated the ability to simultaneously capture respiration, heart sounds, an SCG-like signal (i.e., HF-FCG) and the LF-FCG signal, which may provide information on ventricular emptying and filling events. According to these preliminary results the novel piezoelectric FCG sensor stands as a promising device for accurate, unobtrusive, long-term monitoring of cardiorespiratory functions and paves the way for a wide range of potential applications, both in the research and clinical fields. However, these results should be confirmed by further analyses on a larger cohort of subjects, possibly including also pathological patients

New Directions in 3D Medical Modeling: 3D-Printing Anatomy and Functions in Neurosurgical Planning

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesThis paper illustrates the feasibility and utility of combining cranial anatomy and brain function on the same 3D-printed model, as evidenced by a neurosurgical planning case study of a 29-year-old female patient with a low-grade frontal-lobe glioma. We herein report the rapid prototyping methodology utilized in conjunction with surgical navigation to prepare and plan a complex neurosurgery. The method introduced here combines CT and MRI images with DTI tractography, while using various image segmentation protocols to 3D model the skull base, tumor, and five eloquent fiber tracts. This 3D model is rapid-prototyped and coregistered with patient images and a reported surgical navigation system, establishing a clear link between the printed model and surgical navigation. This methodology highlights the potential for advanced neurosurgical preparation, which can begin before the patient enters the operation theatre. Moreover, the work presented here demonstrates the workflow developed at the National University Hospital of Iceland, Landspitali, focusing on the processes of anatomy segmentation, fiber tract extrapolation, MRI/CT registration, and 3D printing. Furthermore, we present a qualitative and quantitative assessment for fiber tract generation in a case study where these processes are applied in the preparation of brain tumor resection surgery.Icelandic Innovation Fund RANNIS company Ossur University Hospital Landspital

Genetic diversity and origin of the rare, narrow endemic Asperula crassifolia (Rubiaceae)

We examined the patterns of genetic variation in the narrow endemic Asperula crassifolia (Campania, southern Italy), taking into account the schizoendemic distribution of the Mediterranean members of Asperula sect. Cynanchicae. We obtained plastid DNA sequences of the rps16 intron and the trnC-petN intergenic spacer for several members of A. sect. Cynanchicae, for three living populations (48 individuals) and ten herbarium specimens of A. crassifolia. We also analysed nSSR data for A. crassifolia, to infer population diversity and differentiation. Our results suggest that the centre of diversity of A. crassifolia is the island of Capri, where A. crassifolia harbours four different ptDNA haplotypes, two of which are shared with other species of sect. Cynanchicae. Microsatellite analyses revealed low levels of genetic diversity for the mainland population (Nerano, Sorrentine Peninsula) and the neighbouring Sirenusae islets. Diversity in A. crassifolia is mainly explained by ancestral variation and recent divergence. Rarity in A. crassifolia is a natural condition; however, we express concern for the small census population size as it might trigger further rarefaction

CT and MRI assessment and characterization using segmentation and 3D modeling techniques: applications to muscle, bone and brain

This paper reviews the novel use of CT and MRI data and image processing tools to segment and reconstruct tissue images in 3D to determine characteristics of muscle, bone and brain.This to study and simulate the structural changes occurring in healthy and pathological conditions as well as in response to clinical treatments. Here we report the application of this methodology to evaluate and quantify: 1. progression of atrophy in human muscle subsequent to permanent lower motor neuron (LMN) denervation, 2. muscle recovery as induced by functional electrical stimulation (FES), 3. bone quality in patients undergoing total hip replacement and 4. to model the electrical activity of the brain. Study 1: CT data and segmentation techniques were used to quantify changes in muscle density and composition by associating the Hounsfield unit values of muscle, adipose and fibrous connective tissue with different colors. This method was employed to monitor patients who have permanent muscle LMN denervation in the lower extremities under two different conditions: permanent LMN denervated not electrically stimulated and stimulated. Study 2: CT data and segmentation techniques were employed, however, in this work we assessed bone and muscle conditions in the pre-operative CT scans of patients scheduled to undergo total hip replacement. In this work, the overall anatomical structure, the bone mineral density (BMD) and compactness of quadriceps muscles and proximal femoral was computed to provide a more complete view for surgeons when deciding which implant technology to use. Further, a Finite element analysis provided a map of the strains around the proximal femur socket when solicited by typical stresses caused by an implant press fitting. Study 3 describes a method to model the electrical behavior of human brain using segmented MR images. The aim of the work is to use these models to predict the electrical activity of the human brain under normal and pathological conditions by developing detailed 3D representations of major tissue surfaces within the head, with over 12 different tissues segmented. In addition, computational tools in Matlab were developed for calculating normal vectors on the brain surface and for associating this information with the equivalent electrical dipole sources as an input into the model

Low-amplitude craniofacial EMG power spectral density and 3D muscle reconstruction from MRI

Improving EEG signal interpretation, specificity, and sensitivity is a primary focus of many current investigations, and the successful application of EEG signal processing methods requires a detailed knowledge of both the topography and frequency spectra of low-amplitude, high-frequency craniofacial EMG. This information remains limited in clinical research, and as such, there is no known reliable technique for the removal of these artifacts from EEG data. The results presented herein outline a preliminary investigation of craniofacial EMG high-frequency spectra and 3D MRI segmentation that offers insight into the development of an anatomically-realistic model for characterizing these effects. The data presented highlights the potential for confounding signal contribution from around 60 to 200 Hz, when observed in frequency space, from both low and high-amplitude EMG signals. This range directly overlaps that of both low γ (30-50 Hz) and high γ (50-80 Hz) waves, as defined traditionally in standatrd EEG measurements, and mainly with waves presented in dense-array EEG recordings. Likewise, average EMG amplitude comparisons from each condition highlights the similarities in signal contribution of low-activity muscular movements and resting, control conditions. In addition to the FFT analysis performed, 3D segmentation and reconstruction of the craniofacial muscles whose EMG signals were measured was successful. This recapitulation of the relevant EMG morphology is a crucial first step in developing an anatomical model for the isolation and removal of confounding low-amplitude craniofacial EMG signals from EEG data. Such a model may be eventually applied in a clinical setting to ultimately help to extend the use of EEG in various clinical roles

Medical image analysis and 3-d modeling to quantify changes and functional restoration in denervated muscle undergoing electrical stimulation treatment

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On the power spectrum of motor unit action potential trains synchronized with mechanical vibration

Objective: Provide a definitive analysis of the spectrum of a motor unit action potential train elicited by mechanical vibratory stimulation via a detailed and concise mathematical formulation. Experimental studies demonstrated that motor unit action potentials are not exactly synchronized with the vibratory stimulus but show a variable latency jitter, whose effects have not been investigated yet. Methods: Synchronized action potential train was represented as a quasi-periodic sequence of a given motor unit waveform. The latency jitter of action potentials was modeled as a Gaussian stochastic process, in accordance to previous experimental studies. Results: A mathematical expression for power spectrum of a synchronized motor unit action potential train has been derived. The spectrum comprises a significant continuous component and discrete components at the vibratory frequency and its harmonics. Their relevance is correlated to the level of synchronization: the weaker the synchronization, the more relevant the continuous spectrum. EMG rectification enhances the discrete components. Conclusion: The derived equations have general validity and well describe the power spectrum of actual EMG recordings during vibratory stimulation. Results are obtained by appropriately setting the level of synchronization and vibration frequency. Significance: This study definitively clarifies the nature of changes in spectrum of raw EMG recordings from muscles undergoing vibratory stimulation. Results confirm the need of motion artifact filtering for raw EMG recordings during stimulation and strongly suggests to avoid EMG rectification that significantly alters the spectrum characteristics

THz spectroscopy on graphene-like materials for bio-compatible devices

Graphene-like (GL) layers and eumelanin-based graphene-like (EUGL) hybrids have been investigated through THz time domain spectroscopy. The interest in these materials lies on their peculiar chemical-physical properties: the former are conductive water stable materials, whereas the latter are biocompatible materials with good conductive and adhesive properties. Both exhibit promising optoelectronic and bioelectronic applications. We measured mixtures of GL layers or EUGL hybrids with KBr, shaped in pellets with uniform thickness, in order to circumvent problems related to sample inhomogeneity and roughness. A mean field theory was applied to extract direct information on permittivity and conductivity. Data have been carefully fitted through the Drude-Smith theory, confirming the conductive nature of the hybrid materials. The results show that EUGL hybrid-based devices can be promising for the next generation of printable bio-circuits