Improved motion-correction for MRI with markerless face-tracking

Motion artifacts are a well-known problem in MRI. They can extensively reduce image sharpness and resolution, as well as obscure pathologic conditions, which will make the images not suitable for clinical or research purposes. Over the years, multiple motion correction methods have been proposed to compensate for motion artifacts in different MRI applications. In this thesis, we investigate methods to maximize the image quality of brain MR images at different motion regimes, with the goal of obtaining high-quality images in the case of large and continuous motion profiles as might be expected in some children or patients with movement disorders. We describe a new autofocusing algorithm to correct for in-plane translations and rotations without any previous information coming from motion tracking sources. Preliminary results show good motion compensation for 2D translations. However, we show how rotations cannot be accurately estimated at the present stage, which should be investigated in future studies. We analyse the extent of the motion parameters estimation accuracy of a navigator-based motion correction method using simulated data. The navigator relies on GRAPPA reconstruction of the highly accelerated navigator fat-volumes to estimate the motion parameters. Our results suggest that the fat-navigator is capable of compensating for large range of motion, as well as for fast and slow changes in the head position. Better correction is expected if GRAPPA weights are updated throughout the entire duration of the scan. The fat-navigator is then compared with another tracking technique based on structured light to track the subject’s head movements. We present the results obtained from different motion types as well as a method to improve the motion estimation accuracy of the navigator-based technique in the presence of extensive pitch-wise motion using a skull masking approach. Finally, we introduce a method to quickly develop and test motion-robust pulse sequences using an open-source framework to acquire MR images producing low acoustic noise levels, which make them suitable for paediatric/infant age group, where research scans are typically conducted while the subject is sleeping

Robust retrospective motion correction of head motion using navigator-based and markerless motion tracking techniques

Purpose This study investigated the artifacts arising from different types of head motion in brain MR images and how well these artifacts can be compensated using retrospective correction based on two different motion-tracking techniques. Methods MPRAGE images were acquired using a 3 T MR scanner on a cohort of nine healthy participants. Subjects moved their head to generate circular motion (4 or 6 cycles/min), stepwise motion (small and large) and “simulated realistic” motion (nodding and slow diagonal motion), based on visual instructions. One MPRAGE scan without deliberate motion was always acquired as a “no motion” reference. Three dimensional fat-navigator (FatNavs) and a Tracoline markerless device (TracInnovations) were used to obtain motion estimates and images were separately reconstructed retrospectively from the raw data based on these different motion estimates. Results Image quality was recovered from both motion tracking techniques in our stepwise and slow diagonal motion scenarios in almost all cases, with the apparent visual image quality comparable to the no-motion case. FatNav-based motion correction was further improved in the case of stepwise motion using a skull masking procedure to exclude non-rigid motion of the neck from the co-registration step. In the case of circular motion, both methods struggled to correct for all motion artifacts. Conclusion High image quality could be recovered in cases of stepwise and slow diagonal motion using both motion estimation techniques. The circular motion scenario led to more severe image artifacts that could not be fully compensated by the retrospective motion correction techniques used

Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns

Maps represent powerful tools to show the spatial variation of a variable in a straightforward manner. A crucial aspect in map rendering for its interpretation by users is the gamut of colours used for displaying data. One part of this problem is linked to the proportion of the human population that is colour blind and, therefore, highly sensitive to colour palette selection. The aim of this paper is to present the cblindplot R package and its founding function - cblind.plot() - which enables colour blind people to just enter an image in a coding workflow, simply set their colour blind deficiency type, and immediately get as output a colour blind friendly plot. We will first describe in detail colour blind problems, and then show a step by step example of the function being proposed. While examples exist to provide colour blind people with proper colour palettes, in such cases (i) the workflow include a separate import of the image and the application of a set of colour ramp palettes and (ii) albeit being well documented, there are many steps to be done before plotting an image with a colour blind friendly ramp palette. The function described in this paper, on the contrary, allows to (i) automatically call the image inside the function without any initial import step and (ii) explicitly refer to the colour blind deficiency type being experienced, to further automatically apply the proper colour ramp palette

Impacts of exhaust gas cleaning systems (EGCS) discharge waters on planktonic biological indicators

Exhaust Gas Cleaning Systems (EGCS), operating in open-loop mode, continuously release acidic effluents (scrubber waters) to marine waters. Furthermore, scrubber waters contain high concentrations of metals, polycyclic aromatic hydrocarbons (PAHs), and alkylated PAHs, potentially affecting the plankton in the receiving waters. Toxicity tests evidenced significant impairments in planktonic indicators after acute, early-life stage, and long-term exposures to scrubber water produced by a vessel operating with high sulphur fuel. Acute effects on bacterial bioluminescence (Aliivibrio fischeri), algal growth (Phaeodactylum tricornutum, Dunaliella tertiolecta), and copepod survival (Acartia tonsa) were evident at 10 % and 20 % scrubber water, while larval development in mussels (Mytilus galloprovincialis) showed a 50 % reduction at ∼5 % scrubber water. Conversely, larval development and reproductive success of A. tonsa were severely affected at scrubber water concentrations ≤1.1 %, indicating the risk of severe impacts on copepod populations which in turn may result in impairment of the whole food web

Protocollo per il campionamento dei parametri chimico-fisici a sostegno degli elementi biologici in ambiente lacustre

Abstract not availableIl protocollo sul campionamento delle acque lacustri integra completandole le metodologie di campionamento ed analisi del fitoplancton, delle macrofite acquatiche e della fauna a macroinvertebrati in ambiente lacustre riportati nei capitoli successivi di questo Manuale. Anche questo protocollo come i precedenti segue le indicazioni della Direttiva 60/2000/CE (Water Framework Directive, WFD) e del Regolamento per la progettazione del programma di monitoraggio emanato dal Ministero dell?Ambiente e della Tutela del Territorio e del Mare

Scale mismatches between predictor and response variables in species distribution modelling: A review of practices for appropriate grain selection

There is a lack of guidance on the choice of the spatial grain of predictor and response variables in species distribution models (SDM). This review summarizes the current state of the art with regard to the following points: (i) the effects of changing the resolution of predictor and response variables on model performance; (ii) the effect of conducting multi-grain versus single-grain analysis on model performance; and (iii) the role of land cover type and spatial autocorrelation in selecting the appropriate grain size. In the reviewed literature, we found that coarsening the resolution of the response variable typically leads to declining model performance. Therefore, we recommend aiming for finer resolutions unless there is a reason to do otherwise (e.g. expert knowledge of the ecological scale). We also found that so far, the improvements in model performance reported for multi-grain models have been relatively low and that useful predictions can be generated even from single-scale models. In addition, the use of high-resolution predictors improves model performance; however, there is only limited evidence on whether this applies to models with coarser-resolution response variables (e.g. 100 km2 and coarser). Low-resolution predictors are usually sufficient for species associated with fairly common environmental conditions but not for species associated with less common ones (e.g. common vs rare land cover category). This is because coarsening the resolution reduces variability within heterogeneous predictors and leads to underrepresentation of rare environments, which can lead to a decrease in model performance. Thus, assessing the spatial autocorrelation of the predictors at multiple grains can provide insights into the impacts of coarsening their resolution on model performance. Overall, we observed a lack of studies examining the simultaneous manipulation of the resolution of predictor and response variables. We stress the need to explicitly report the resolution of all predictor and response variables.Peer reviewe

From zero to infinity: Minimum to maximum diversity of the planet by spatio-parametric Rao's quadratic entropy

Aim: The majority of work done to gather information on the Earth's biodiversity has been carried out using in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannon’s information theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Rao’s quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, that is they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Rao’s quadratic entropy by proposing its parameterization for the first time.
 Innovation: The parametric Rao’s quadratic entropy, coded in R, (a) allows the representation of the whole continuum of potential diversity indices in one formula, and (b) starting from the Rao’s quadratic entropy, allows the explicit use of distances among pixel reflectance values, together with relative abundances.
 Main conclusions: The proposed unifying measure is an integration between abundance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale. Being part of the rasterdiv R package, the proposed method is expected to ensure high robustness and reproducibility

Indici per la valutazione della qualit? ecologica dei laghi

Collection of methods to evaluate lake quality using biological element

How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Assessment of phenolic herbicide toxicity and mode of action by different assays

A phytotoxicity assay based on seed germination/root elongation has been optimized and used to evaluate the toxic effects of some phenolic herbicides. The method has been improved by investigating the influence of experimental conditions. Lepidium sativum was chosen as the most suitable species, showing high germinability, good repeatability of root length measurements, and low sensitivity to seed pretreatment. DMSO was the most appropriate solvent carrier for less water-soluble compounds. Three dinitrophenols and three hydroxybenzonitriles were tested: dinoterb, DNOC, 2,4-dinitrophenol, chloroxynil, bromoxynil, and ioxynil. Toxicity was also determined using the Vibrio fischeri MicrotoxA (R) test, and a highly significant correlation was found between EC50 values obtained by the two assays. Dinoterb was the most toxic compound. The toxicity of hydroxybenzonitriles followed the order: ioxynil > bromoxynil > chloroxynil; L. sativum exhibited a slightly higher sensitivity than V. fischeri to these compounds. A QSAR analysis highlighted the importance of hydrophobic, electronic, and hydrogen-bonding interactions, in accordance with a mechanism of toxic action based on protonophoric uncoupling of oxidative phosphorylation. The results suggest that the seed germination/root elongation assay with L. sativum is a valid tool for the assessment of xenobiotic toxicity and can be recommended as part of a test battery