Influence of extraction methods on the composition of essential oils of Achillea millefolium L. from Lithuania

In this study, flowering aerial parts of Achillea millefolium were used as a matrix for supercritical CO2 extraction (SFE) of volatile oil. The collected extracts were analyzed by GC-FID and GC-MS methods and their composition were compared with that of the essential oil isolated by hydrodistillation (HD). The composition of the essential oil obtained by hydrodistillation and SFE methods is widely different. Indeed, the SFE volatile oil had a pale yellow color whereas the HD oil had a blue color due to the presence of chamazulene (48.0% vs. 4.3%). Other important constituents of HD oil were (E)- caryophyllene (19.5 %) and γ-muurolene (13.1%). The CO2 supercritical extract was dominated by (E)-caryophyllene (26.0%), γ-muurolene (22.0%), and caryophyllene oxide (8.1%)

Cerebellar structural variations in subjects with different hypnotizability

Hypnotizability-the proneness to accept suggestions and behave accordingly-has a number of physiological and behavioral correlates (postural, visuomotor, and pain control) which suggest a possible involvement of cerebellar function and/or structure. The present study was aimed at investigating the association between cerebellar macro- or micro-structural variations (analyzed through a voxel-based morphometry and a diffusion tensor imaging approach) and hypnotic susceptibility. We also estimated morphometric variations of cerebral gray matter structures, to support current evidence of hypnotizability-related differences in some cerebral areas. High (highs, N = 12), and low (lows, N = 37) hypnotizable healthy participants (according to the Stanford Hypnotic Susceptibility Scale, form A) were submitted to a high field (3 T) magnetic resonance imaging protocol. In comparison to lows, highs showed smaller gray matter volumes in left cerebellar lobules IV/V and VI at uncorrected level, with the results in left lobule IV/V maintained also at corrected level. Highs showed also gray matter volumes smaller than lows in right inferior temporal gyrus, middle and superior orbitofrontal cortex, parahippocampal gyrus, and supramarginal parietal gyrus, as well as in left gyrus rectus, insula, and middle temporal cortex at uncorrected level. Results of right inferior temporal gyrus survived also at corrected level. Analyses on micro-structural data failed to reveal any significant association. The here found morphological variations allow to extend the traditional cortico-centric view of hypnotizability to the cerebellar regions, suggesting that cerebellar peculiarities may sustain hypnotizability-related differences in sensorimotor integration and emotional contro

SPECIFIC ALPINE ENVIRONMENT LAND COVER CLASSIFICATION METHODOLOGY: GOOGLE EARTH ENGINE PROCESSING FOR SENTINEL-2 DATA

Abstract. Land Cover (LC) plays a key role in many disciplines and its classification from optical imagery is one of the prevalent applications of remote sensing. Besides years of researches and innovation on LC, the classification of some areas of the World is still challenging due to environmental and climatic constraints, such as the one of the mountainous chains. In this contribution, we propose a specific methodology for the classification of the Land Cover in mountainous areas using Sentinel 2, 1C-level imagery. The classification considers some specific high-altitude mountainous classes: clustered bare soils that are particularly prone to erosion, glaciers, and solid-rocky areas. It consists of a pixel-based multi-epochs classification using random forest algorithm performed in Google Earth Engine (GEE). The study area is located in the western Alps between Italy and France and the analyzed dataset refers to 2017–2019 imagery captured in the summertime only. The dataset was pre-processed, enriched of derivative features (radiometric, histogram-based and textural). A workflow for the reduction of the computational effort for the classification, which includes correlation and importance analysis of input features, was developed. Each image of the dataset was separately classified using random forest classification algorithm and then aggregated each other by the most frequent pixel value. The results show the high impact of textural features in the separation of the mountainous-specific classes the overall accuracy of the final classification achieves 0.945

Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security.

Requirements elicitation, analysis and modeling are critical activities for software success. However, software systems are increasingly complex, harder to develop due to an ever-growing number of requirements from numerous and heterogeneous stakeholders, concerning dozens of requirements types, from functional to qualitative, including adaptation, security and privacy, ethical, acceptance and more. In such settings, requirements engineers need support concerning such increasingly complex activities, and Requirements Engineering (RE) modeling tools have been developed for this. However, such tools, although effective, are complex, time-consuming and requiring steep learning curves. The consequent lack of acceptance and abandonment in using such tools, by engineers, paves the way to the application of RE techniques in a more error-prone, low-quality way, increasing the possibility to have failures in software systems delivered. In this paper, we identify main areas of lack of acceptance, affecting RE engineers, for such tools, and propose an approach for making modeling tools more effective in engaging the engineer in performing RE in a tool-based way, receiving adequate feedback and staying motivated to use modeling tools. This is accomplished by performing acceptance requirements analysis (through the Agon Framework) and using gamification to increase the engagement of engineers during the usage of RE modeling tools. Towards this end, we performed a case study, within the VisiOn European Project, for enhancing a tool for modeling privacy and security requirements. Our case study provides preliminary evidence that our approach supports in making RE modeling tools more engaging from the engineer perspective

Development of an Adaptive Efficient Thermal/Electric Skipping Control Strategy Applied to a Parallel Plug-in Hybrid Electric Vehicle

In recent years automobile manufacturers focused on an increasing degree of electrification of the powertrains with the aim to reduce pollutants and CO2 emissions. Despite more complex design processes and control strategies, these powertrains offer improved fuel exploitation compared to conventional vehicles thanks to intelligent energy management. A simulation study is here presented aiming at developing a new control strategy for a P3 parallel plug-in hybrid electric vehicle. The simulation model is implemented using vehicle modeling and simulation toolboxes in MATLAB/Simulink. The proposed control strategy is based on an alternative utilization of the electric motor and thermal engine to satisfy the vehicle power demand at the wheels (Efficient Thermal/Electric Skipping Strategy-ETESS). The choice between the two units is realized through a comparison between two equivalent fuel rates, one related to the thermal engine and the other related to the electric consumption. An adaptive function is introduced to develop a charge-blended control strategy. The novel adaptive control strategy (A-ETESS) is applied to estimate fuel consumption along different driving cycles. The control algorithm is implemented on a dedicated microcontroller unit performing a Processor-In-the-Loop (PIL) simulation. To demonstrate the reliability and effectiveness of the A-ETESS, the same adaptive function is built on the Equivalent Consumption Minimization Strategy (ECMS). The PIL results showed that the proposed strategy ensures a fuel economy similar to ECMS (worse of about 2% on average) and a computational effort reduced by 99% on average. This last feature reveals the potential for real-time on-vehicle applications

Sorting of multiple molecular species on cell membranes

Eukaryotic cells maintain their inner order by a hectic process of distillation of molecular factors taking place on the surface of their lipid membranes. To understand the properties of this molecular sorting process, a physical model of the process has been recently proposed [arXiv:1811.06760], based on (a) the phase separation of a single, initially dispersed molecular species into spatially localized sorting domains on the lipid membrane, and (b) domain-induced membrane bending leading to the nucleation of submicrometric lipid vesicles, naturally enriched in the molecules of the engulfed sorting domain. The analysis of the model has shown the existence of an optimal region of the parameter space where sorting is most efficient. Here, the model is extended to account for the simultaneous distillation of a pool of distinct molecular species. We find that the mean time spent by sorted molecules on the membrane increases with the heterogeneity of the pool (i.e., the number of distinct molecular species sorted) according to a simple scaling law, and that a large number of distinct molecular species can in principle be sorted in parallel on a typical cell membrane region without significantly interfering with each other. Moreover, sorting is found to be most efficient when the distinct molecular species have comparable homotypic affinities. We also consider how valence (i.e., the average number of interacting neighbors of a molecule in a sorting domain) affects the sorting process, finding that higher-valence molecules can be sorted with greater efficiency than lower-valence molecules

Distributed hydrologic modeling of a sparsely monitored basin in Sardinia, Italy, through hydrometeorological downscaling

The water resources and hydrologic extremes in Mediterranean basins are heavily influenced by climate variability. Modeling these watersheds is difficult due to the complex nature of the hydrologic response as well as the sparseness of hydrometeorological observations. In this work, we present a strategy to calibrate a distributed hydrologic model, known as TIN-based Real-time Integrated Basin Simulator (tRIBS), in the Rio Mannu basin (RMB), a medium-sized watershed (472.5 km2) located in an agricultural area in Sardinia, Italy. In the RMB, precipitation, streamflow and meteorological data were collected within different historical periods and at diverse temporal resolutions. We designed two statistical tools for downscaling precipitation and potential evapotranspiration data to create the hourly, high-resolution forcing for the hydrologic model from daily records. Despite the presence of several sources of uncertainty in the observations and model parameterization, the use of the disaggregated forcing led to good calibration and validation performances for the tRIBS model, when daily discharge observations were available. The methodology proposed here can be also used to disaggregate outputs of climate models and conduct high-resolution hydrologic simulations with the goal of quantifying the impacts of climate change on water resources and the frequency of hydrologic extremes within medium-sized basins

A comparison of 0.375% ropivacaine psoas compartment block and 2% prilocaine spinal anaesthesia in dogs undergoing tibial plateau levelling osteotomy

BACKGROUND: In dogs undergoing routine elective orthopaedic surgeries carried out as same-day surgeries regional anaesthetic techniques (RATs) should aim to produce analgesia but minimising the postoperative motor dysfunction. Our objective was to compare the perioperative analgesic effects and the time to motor recovery between spinal anaesthesia (SA) with hyperbaric solution of prilocaine 2% (mg = 4 x [0.3 × BW (kg) + 0.05 × SCL (cm)]) and morphine (0.03 mg/kg) and combined ultrasound (US) and electro stimulator-guided psoas compartment and ischiatic nerve block (PB) with ropivacaine 0.375% (0.45 mL/kg). Dogs undergoing tibial plateau levelling osteotomy (TPLO) were randomly assigned to receive either SA or PB. Procedural failure, perioperative rescue analgesia, motor block recovery and complications were recorded. RESULTS: Procedural failure rate (PFR) was 19% (7 out of 36) for SA and 9% (3 out of 32) for PB (p = 0.31). Intraoperative rescue analgesia was administered to 6/29 (21%) SA group dogs and in 15/29 (52%) PB group dogs, respectively (p = 0.03). At 3 h after RAT, percentage of dogs with complete block recovery was 25/29 (86%) and 25/29 (86%) in group SA and PB, respectively (p = 1). Two cases of pruritus and one case of urinary retention were recorded in the SA group. Residual ischiatic nerve block was noted at 12 h after RAT in 2/15 (13%) of dogs in group PB; it completely resolved 24 h after RAT. CONCLUSIONS: SA with prilocaine 2% and PB with ropivacaine 0.37% were found suitable for dogs undergoing same-day TPLO surgery. Pruritus and urinary retention in SA and residual block in both groups might occasionally delay the time of discharge. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12917-022-03277-6

Investigating parameter transferability across models and events for a Semiarid Mediterranean Catchment

Physically based distributed hydrologic models (DHMs) simulate watershed processes by applying physical equations with a variety of simplifying assumptions and discretization approaches. These equations depend on parameters that, in most cases, can be measured and, theoretically, transferred across different types of DHMs. The aim of this study is to test the potential of parameter transferability in a real catchment for two contrasting periods among three DHMs of varying complexity. The case study chosen is a small Mediterranean catchment where the TIN-based Real-time Integrated Basin Simulator (tRIBS) model was previously calibrated and tested. The same datasets and parameters are used here to apply two other DHMs-the TOPographic Kinematic Approximation and Integration model (TOPKAPI) and CATchment HYdrology (CATHY) models. Model performance was measured against observed discharge at the basin outlet for a one-year period (1930) corresponding to average wetness conditions for the region, and for a much drier two-year period (1931-1932). The three DHMs performed comparably for the 1930 period but showed more significant differences (the CATHY model in particular for the dry period. In order to improve the performance of CATHY for this latter period, an hypothesis of soil crusting was introduced, assigning a lower saturated hydraulic conductivity to the top soil layer. It is concluded that, while the physical basis for the three models allowed transfer of parameters in a broad sense, transferability can break down when simulation conditions are greatly altered

Patient Involvement in Shared Decision-Making: Do Patients Rate Physicians and Nurses Differently?

Background. Shared decision-making implies that patients and healthcare professionals make decisions together about clinical exams, available treatments, choice of options, and the benefit or downside of every choice. Patients involved in the shared decision-making process are more compliant with treatments and have a reduced risk of complications related to the pathology. In Italy, patient involvement in caring processes is still barely investigated. Aim. To investigate patients’ perceptions about shared decision-making with physicians and nurses, respectively, and to examine the relationship between shared decision-making and patient satisfaction and perceived quality of care/treatment. Methods. The study was performed between March and June 2019 in two wards of one Italian hospital. A questionnaire was administered to inpatients at the time of admission and again at discharge, including demographic information and measurement scales regarding patient involvement in shared decision-making, patient satisfaction, and perceived quality of treatment/care. Results. A total of 151 out of 301 patients completed questionnaires at both admission and discharge. Patients’ scores for shared decision-making (information, patient needs, treatment planning) were significantly different for physicians and nurses. At both admission and discharge, patients rated shared decision-making significantly higher for physicians compared to nurses, while there were no differences in their satisfaction ratings. Patient ratings of physicians did not change from admission (information: mean (M) = 3.50, standard deviation (SD) = 0.81; patient need: M = 3.05, SD = 1.05; treatment planning: M = 2.75, SD = 1.23) to discharge (information: M = 3.50, SD = 0.79; patient need: M = 3.17, SD = 1.02; treatment planning: M = 2.66, SD = 1.23) (p = 0.924, p = 0.098, p = 0.293, respectively), but patients’ ratings of nurses’ behavior increased significantly from admission (information: M = 2.44, SD = 1.23; patient need: M = 2.27, SD = 1.17; treatment planning: M = 2.12, SD = 1.19) to discharge (information: M = 2.62, SD = 1.22; patient need: M = 2.53, SD = 1.24; treatment planning: M = 2.35, SD = 1.21) (p = 0.019, p = 0.001, p = 0.003, respectively). Attention to patients’ needs was the key determinant of both satisfaction with nurses (OR = 3.65, 95% CI = 1.31–10.14, p = 0.013) and perceived quality of care (OR = 3.97, 95% CI = 1.49–10.55, p = 0.006). Providing appropriate information about disease progress and treatments was a key determinant of both satisfaction with physicians (OR = 19.75, 95% CI = 7.29–53.55, p < 0.001) and perceived quality of treatment (OR = 8.03, 95% CI = 3.25–19.81, p < 0.001). Discussion. Nurses should be sensitized to involving patients in the decision-making process, especially upon hospital admission. Specific training about effective communication techniques can be implemented to manage relationships with patients in different caring situations. Practical implications and future directions are discussed