Light absorbing aerosols (LAA) absorb sunlight and heat the atmosphere. This work presents a novel methodology to experimentally quantify the heating rate (HR) induced by LAA into an atmospheric ...layer. Multiwavelength aerosol absorption measurements were coupled with spectral measurements of the direct, diffuse and surface reflected radiation to obtain highly time-resolved measurements of HR apportioned in the context of LAA species (black carbon, BC; brown carbon, BrC; dust), sources (fossil fuel, FF; biomass burning, BB), and as a function of cloudiness. One year of continuous and time-resolved measurements (5 min) of HR were performed in the Po Valley. We experimentally determined (1) the seasonal behavior of HR (winter 1.83 ± 0.02 K day–1; summer 1.04 ± 0.01 K day–1); (2) the daily cycle of HR (asymmetric, with higher values in the morning than in the afternoon); (3) the HR in different sky conditions (from 1.75 ± 0.03 K day–1 in clear sky to 0.43 ± 0.01 K day–1 in complete overcast); (4) the apportionment to different sources: HRFF (0.74 ± 0.01 K day–1) and HRBB (0.46 ± 0.01 K day–1); and (4) the HR of BrC (HRBrC: 0.15 ± 0.01 K day–1, 12.5 ± 0.6% of the total) and that of BC (HRBC: 1.05 ± 0.02 K day–1; 87.5 ± 0.6% of the total).
The amount of reflected energy by snow and ice plays a fundamental role in their melting processes. Different non-ice materials (carbonaceous particles, mineral dust (MD), microorganisms, algae, ...etc.) can decrease the reflectance of snow and ice promoting the melt. The object of this paper is to assess the capability of field and satellite (EO-1 Hyperion) hyperspectral data to characterize the impact of light-absorbing impurities (LAIs) on the surface reflectance of ice and snow of the Vadret da Morteratsch, a large valley glacier in the Swiss Alps. The spatial distribution of both narrow-band and broad-band indices derived from Hyperion was analyzed in relation to ice and snow impurities. In situ and laboratory reflectance spectra were acquired to characterize the optical properties of ice and cryoconite samples. The concentrations of elemental carbon (EC), organic carbon (OC) and levoglucosan were also determined to characterize the impurities found in cryoconite. Multi-wavelength absorbance spectra were measured to compare the optical properties of cryoconite samples and local moraine sediments. In situ reflectance spectra showed that the presence of impurities reduced ice reflectance in visible wavelengths by 80–90 %. Satellite data also showed the outcropping of dust during the melting season in the upper parts of the glacier, revealing that seasonal input of atmospheric dust can decrease the reflectance also in the accumulation zone of the glacier. The presence of EC and OC in cryoconite samples suggests a relevant role of carbonaceous and organic material in the darkening of the ablation zone. This darkening effect is added to that caused by fine debris from lateral moraines, which is assumed to represent a large fraction of cryoconite. Possible input of anthropogenic activity cannot be excluded and further research is needed to assess the role of human activities in the darkening process of glaciers observed in recent years.
The continuous and automated monitoring of canopy phenology is of increasing scientific interest for the multiple implications of vegetation dynamics on ecosystem carbon and energy fluxes. For this ...purpose we evaluated the applicability of digital camera imagery for monitoring and modeling phenology and physiology of a subalpine grassland over the 2009 and 2010 growing seasons. We tested the relationships between color indices (i.e. the algebraic combinations of RGB brightness levels) tracking canopy greenness extracted from repeated digital images against field measurements of green and total biomass, leaf area index (LAI), greenness visual estimation, vegetation indices computed from continuous spectroradiometric measurements and CO₂ fluxes observed with the eddy covariance technique. A strong relationship was found between canopy greenness and (i) structural parameters (i.e., LAI) and (ii) canopy photosynthesis (i.e. Gross Primary Production; GPP). Color indices were also well correlated with vegetation indices typically used for monitoring landscape phenology from satellite, suggesting that digital repeat photography provides high-quality ground data for evaluation of satellite phenology products. We demonstrate that by using canopy greenness we can refine phenological models (Growing Season Index, GSI) by describing canopy development and considering the role of ecological factors (e.g., snow, temperature and photoperiod) controlling grassland phenology. Moreover, we show that canopy greenness combined with radiation use efficiency (RUE) obtained from spectral indices related to photochemistry (i.e., scaled Photochemical Reflectance Index) or meteorology (i.e., MOD17 RUE) can be used to predict daily GPP. Building on previous work that has demonstrated that seasonal variation in the structure and function of plant canopies can be quantified using digital camera imagery, we have highlighted the potential use of these data for the development and parameterization of phenological and RUE models, and thus point toward an extension of the proposed methodologies to the dataset collected within PhenoCam Network.
In this article, we present a new concept for predicting satellite-derived land surface temperature (LST) under cloudy skies over vegetated areas in the Alps. Although many different reconstruction ...methods have been developed, they require rarely available inputs, or they restore missing pixels from clear-sky observations with low spatial resolution (1-5 km), which makes them unreliable in heterogenous ecosystems. Given these limitations, we propose a station-based procedure to predict cloud-covered grids from 1-km Terra MODIS LST at 250 m spatial resolution. First, we explored correlations between ground-measured LST and air temperature in conjunction with other geo-biophysical variables under cloudy-sky conditions derived from ESRA clear-sky radiation model. Considering a high site dependency driven by different landcovers, in-situ data were aggregated into three groups (forest, permanent crops, grassland) and then, models were established. Next, the regressions were applied to 250-m gridded predictors to estimate cloud-covered LST pixels for six Terra MODIS LST images in 2014. While for permanent crops and forest group linear modelling was the most efficient, neural networks achieved the best performance for grasslands. The reconstructions showed reasonable LST distribution considering landscape heterogeneity of the region. The results were validated against timeseries of ground-measured LST in 2014. The models achieved reliable performance with an average R 2 of 0.84 and root-mean-square error of 2.12 °C. Despite some limitations, mainly due to diversified character of cloudy-sky conditions and high heterogeneity of gridded predictors, the method can effectively reconstruct overcast MODIS data at subpixel level, which shows great potential for producing cloud-free LSTs in complex ecosystems
Traditional assessment of a stroke subject's motor ability, carried out by a therapist who observes and rates the subject's motor behavior using ordinal measurements scales, is subjective, time ...consuming and lacks sensitivity. Rehabilitation robots, which have been the subject of intense inquiry over the last decade, are equipped with sensors that are used to develop objective measures of motor behaviors in a semiautomated way during therapy. This article reviews the current contributions of robot-assisted motor assessment of the upper limb. It summarizes the various measures related to movement performance, the models of motor recovery in stroke subjects and the relationship of robotic measures to standard clinical measures. It analyses the possibilities offered by current robotic assessment techniques and the aspects to address to make robotic assessment a mainstream motor assessment method.
There is growing evidence that pesticides may be among the causes of worldwide bee declines, which has resulted in repeated calls for their increased scrutiny in regulatory assessments. One recurring ...concern is that the current frameworks may be biased towards assessing risks to the honey bee. This paradigm requires extrapolating toxicity information across bee species. Most research effort has therefore focused on quantifying differences in sensitivity across species. However, our understanding of how responses to pesticides may vary within a species is still very poor. Here we take the first steps towards filling this knowledge gap by comparing acute, lethal hazards in sexes and castes of the eusocial bee Bombus terrestris and in sexes of the solitary bee Osmia bicornis after oral and contact exposure to the pesticides sulfoxaflor, Amistar (azoxystrobin) and glyphosate. We show that sensitivity towards pesticides varies significantly both within and across species. Bee weight was a meaningful predictor of pesticide susceptibility. However, weight could not fully explain the observed differences, which suggests the existence of unexplored mechanisms regulating pesticide sensitivity across bee sexes and castes. Our data show that intra-specific responses are an overlooked yet important aspect of the risk assessment of pesticides in bees.
In this paper, we made use of PRISMA imaging spectroscopy data for retrieving surface snow properties in the Nansen Ice Shelf (East Antarctica). PRISMA satellite mission has been launched in 2019 and ...it features 239 spectral bands covering the 400-2500 nm interval. These data are promising for cryospheric applications, since several snow and ice parameters can be derived from reflectance in the Visible Near InfraRed - Short Wave InfraRed (VNIR-SWIR) wavelength interval. Here we analyze, for the first time, PRISMA data collected in Antarctica. Our scene was acquired on December 2020 over the Nansen Ice Shelf (NIS). Using PRISMA data we estimated various snow parameters (effective grain diameter, snow specific surface area, snow spectral and broadband albedo, bottom of atmosphere snow reflectance, type of impurities in snow and their concentration), and we compared them with data presented in the scientific literature.
The introduction of technology-assisted rehabilitation (TAR) uncovers promising challenges for the treatment of motor disorders, particularly if combined with exergaming. Patients with neurological ...diseases have proved to benefit from TAR, improving their performance in several activities. However, the subjective perception of the device has never been fully addressed, being a conditioning factor for its use. The aims of the study were: (a) to develop a questionnaire on patients' personal experience with TAR and exergames in a real-world clinical setting; (b) to administer the questionnaire to a pilot group of neurologic patients to assess its feasibility and statistical properties.
A self-administrable and close-ended questionnaire, Technology Assisted Rehabilitation Patient Perception Questionnaire (TARPP-Q), designed by a multidisciplinary team, was developed in Italian through a Delphi procedure. An English translation has been developed with consensus, for understandability purposes. The ultimate version of the questionnaire was constituted of 10 questions (5 with multiple answers), totalling 29 items, exploring the patient's performance and personal experience with TAR with Augmented Performance Feedback. TARPP-Q was then administered pre-post training in an observational, feasible, multi-centric study. The study involved in-patients aged between 18 and 85 with neurological diseases, admitted for rehabilitation with TAR (upper limb or gait). FIM scale was run to control functional performance.
Forty-four patients were included in the study. All patients answered the TARPP-Q autonomously. There were no unaccounted answers. Exploratory factor analyses identified 4 factors: Positive attitude, Usability, Hindrance perception, and Distress. Internal consistency was measured at T0. The values of Cronbach's alpha ranged from 0.72 (Distress) to 0.92 (Positive attitude). Functional Independence Measure (FIM®) scores and all TARPP-Q factors (Positive attitude, Usability, Hindrance perception, except for Distress (p = 0.11), significantly improved at the end of the treatment. A significant positive correlation between Positive attitude and Usability was also recorded.
The TARPP-Q highlights the importance of patients' personal experience with TAR and exergaming. Large-scale applications of this questionnaire may clarify the role of patients' perception of training effectiveness, helping to customize devices and interventions.
Myotonic dystrophy type 1 (DM1) and type 2 (DM2) are autosomal dominant multisystemic disorders caused by expansion of microsatellite repeats. In both forms, the mutant transcripts accumulate in ...nuclear foci altering the function of alternative splicing regulators which are necessary for the physiological mRNA processing. Missplicing of insulin receptor (IR) gene (INSR) has been associated with insulin resistance, however, it cannot be excluded that post-receptor signalling abnormalities could also contribute to this feature in DM. We have analysed the insulin pathway in skeletal muscle biopsies and in myotube cultures from DM patients to assess whether downstream metabolism might be dysregulated and to better characterize the mechanism inducing insulin resistance. DM skeletal muscle exhibits alterations of basal phosphorylation levels of Akt/PKB, p70S6K, GSK3β and ERK1/2, suggesting that these changes might be accompanied by a lack of further insulin stimulation. Alterations of insulin pathway have been confirmed on control and DM myotubes expressing fetal INSR isoform (INSR-A). The results indicate that insulin action appears to be lower in DM than in control myotubes in terms of protein activation and glucose uptake. Our data indicate that post-receptor signalling abnormalities might contribute to DM insulin resistance regardless the alteration of INSR splicing.
Retrieval of Sun-Induced Chlorophyll Fluorescence (F) spectrum is one of the challenging perspectives for further advancing F studies towards a better characterization of vegetation structure and ...functioning. In this study, a simplified Spectral Fitting retrieval algorithm suitable for retrieving the F spectrum with a limited number of parameters is proposed (two parameters for F). The novel algorithm is developed and tested on a set of radiative transfer simulations obtained by coupling SCOPE and MODTRAN5 codes, considering different chlorophyll content, leaf area index and noise levels to produce a large variability in fluorescence and reflectance spectra. The retrieval accuracy is quantified based on several metrics derived from the F spectrum (i.e., red and far-red peaks, O2 bands and spectrally-integrated values). Further, the algorithm is employed to process experimental field spectroscopy measurements collected over different crops during a long-lasting field campaign. The reliability of the retrieval algorithm on experimental measurements is evaluated by cross-comparison with F values computed by an independent retrieval method (i.e., SFM at O2 bands). For the first time, the evolution of the F spectrum along the entire growing season for a forage crop is analyzed and three diverse F spectra are identified at different growing stages. The results show that red F is larger for young canopy; while red and far-red F have similar intensity in an intermediate stage; finally, far-red F is significantly larger for the rest of the season.
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