Laterality of Stance during Optic Flow Stimulation in Male and Female Young Adults

During self-motion, the spatial and temporal properties of the optic flow input directly influence the body sway. Men and women have anatomical and biomechanical differences that influence the postural control during visual stimulation. Given that recent findings suggest a peculiar role of each leg in the postural control of the two genders, we investigated whether the body sway during optic flow perturbances is lateralized and whether anteroposterior and mediolateral components of specific center of pressure (COP) parameters of the right and left legs differ, reexamining a previous experiment (Raffi et al. (2014)) performed with two, side-by-side, force plates. Experiments were performed on 24 right-handed and right-footed young subjects. We analyzed five measures related to the COP of each foot and global data: anteroposterior and mediolateral range of oscillation, anteroposterior and mediolateral COP velocity, and sway area. Results showed that men consistently had larger COP parameters than women. The values of the COP parameters were correlated between the two feet only in the mediolateral axis of women. These findings suggest that optic flow stimulation causes asymmetry in postural balance and different lateralization of postural controls in men and women

Food waste as a (negative) measure of social capital. A study across Italian Provinces

Household food waste is a crucial problem in developed countries. Food waste behaviour is the result of complex interactions among economic factors, deeply rooted habits, and social norms. It can thus be considered a measure of the social capital characterizing a community. We test this hypothesis using a national-level dataset on household food-related behaviours and opinions in Italy gathered in 2016. This country is an ideal test bed for a comparative analysis on social capital. We find household food waste measures to be negatively related with the local level of social capital. This relationship is mediated by family income, as it becomes weaker for better-off families. Furthermore, we find that behaviours and opinions eliciting status concerns with respect to food, as well as lack of organisational abilities, generate increased food waste. In turn, these behaviours and opinions are more prevalent in areas with low social capital. Our results, captured by a simple model where food waste decisions are considered in the context of a modified public good game, allow to derive several policy implications for the reduction of food waste

BAT2 and BAT3 polymorphisms as novel genetic risk factors for rejection after HLA-related SCT.

The genetic background of donor and recipient is an important factor determining the outcome of allogeneic hematopoietic SCT (allo-HSCT). We applied whole-genome analysis to investigate genetic variants - other than HLA class I and II - associated with negative outcome after HLA-identical sibling allo-HSCT in a cohort of 110 β-Thalassemic patients. We identified two single-nucleotide polymorphisms (SNPs) in BAT2 (A/G) and BAT3 (T/C) genes, SNP rs11538264 and SNP rs10484558, both located in the HLA class III region, in strong linkage disequilibrium between each other (R2 =0.92). When considered as single SNP, none of them reached a significant association with graft rejection (nominal P<0.00001 for BAT2 SNP rs11538264, and P<0.0001 for BAT3 SNP rs10484558), whereas the BAT2/BAT3 A/C haplotype was present at significantly higher frequency in patients who rejected as compared to those with functional graft (30.0% vs 2.6%, nominal P=1.15 × 10-8; and adjusted P=0.0071). The BAT2/BAT3 polymorphisms and specifically the A/C haplotype may represent a novel immunogenetic factor associated with graft rejection in patients undergoing allo-HSCT

GNSS Positioning using Android Smartphone

The possibility to manage pseudorange and carrier-phase measurements from the Global Navigation Satellite System (GNSS) chipset installed on smartphones and tablets with an Android operating system has changed the concept of precise positioning with portable devices. The goal of this work is to compare the positioning performances obtained with a smartphone and an external mass-market GNSS receiver both in real-time and post-processing. The attention is also focused not only on the accuracy and precision, but also on the possibility to determine the phase ambiguity values as integer (fixed positioning) that it is still a challenging aspect for mass-market devices: if the mass-market receiver provides good results under all points of view both for real-time and post-processing solutions (with precisions and accuracies of about 5 cm and 1 cm, respectively), the smartphone has a bad behaviour (order of magnitude of some meters) due to the noise of its measurements

Silver nanoparticles from orange peel extract: Colorimetric detection of Pb2+ and Cd2+ ions with a chemometric approach

Green silver nanoparticles (AgNPs@OPE) were obtained by using orange (citrus sinensis) peel water extract (OPE) that acts as a reducing and capping agent. This procedure permits the valorisation of waste as orange peel, and lowers the environmental impact of the process, with respect to the conventional synthetic procedure. The OPE extract reduced Ag(I) to Ag(0) in alkaline conditions, and stabilised the produced nanoparticles as a capping agent. The AgNPs@OPE were deeply characterized by UV–Vis spectroscopy, FT-IR, SEM analysis and DLS analysis and successively used as colorimetric sensors for different metals in aqueous solution. The colourimetric assay showed that AgNPs@OPE were able to detect Pb2+ and Cd2+, as demonstrated by the splits of surface plasmon resonance (SPR) band accompanied by the formation of a second new band; these spectral modification resulted in a colour change, from pristine nanoparticles’ yellow to brown, due to the aggregation process. For the quantification of each of the two target cations, a calibration was performed by using the univariate linear regression, within the linearity ranges, exploiting the absorbance ratio between the main SPR band and the new band relative to the aggregate formation. Then a multivariate approach was followed to perform both Cd2+ and Pb2+ quantification by means of Partial Least Square regression (PLS) and target cations distinction by Linear Discriminant Analysis (LDA) applied on Principal Components Analysis (PCA) outputs, in both cases using the entire UV–Vis spectra (350–800 nm) as input data. Finally, the ability to quantify and distinguish between Cd2+ and Pb2+ was tested in tap water samples spiked with the two cations in order to confirm the application of the AgNPs@OPE as selective sensor in real samples

From social interactions to private environmental behaviours: The case of consumer food waste

Consumer food waste, like many environmental behaviours, takes place in private, and is not directly subject to social monitoring. Nevertheless, social interactions can affect private opinions and behaviours. This paper builds an agent-based model of interactions between consumers heterogeneous in their sociability, their initial opinions and behaviours related to food waste, and their willingness to consider different opinions, in order to assess how social interactions can affect private behaviours. Compared to existing models of opinion dynamics, we innovate by including a range of “cognitive dissonance” between stated opinions and actual behaviours that consumers are willing to accept before changing one of the two. We calibrate the model using questionnaire data on household food waste in Italy. We find that a limited degree of mixing between different socio-demographic groups, namely adult and young consumers, is enough to trigger change, but a certain openness of mind is required from more wasteful individuals. Equally, a small group of environmentally committed consumers can attract a sizeable share of the population towards low-waste behaviours if they show a certain variability of opinions and are willing to compromise with individuals in their close neighbourhood in terms of opinions. These findings can help design effective interventions to promote pro-environmental behaviours, taking advantage of the beneficial network effects while anticipating negative externalities

Food waste reduction in supply chains through innovations: a review

Purpose: Agri-food supply chains are facing a number of challenges, which cause inefficiencies resulting in the waste of natural and economic resources, and in negative environmental and social impacts. Food waste (FW) is a result of such inefficiencies and supply chain actors search for economically viable innovations to prevent and reduce it. This study aims to analyse the drivers and the barriers that affect the decision of supply chain operators to adopt innovations (technological – TI, organisational – OI and marketing – MI) to reduce FW. Design/methodology/approach: The analysis was carried out using a four-step approach that included: a literature review to identify factors affecting the decision to adopt innovations; analysis of FW drivers and reduction possibilities along agri-food supply chains through innovations; mapping the results of Steps 1 and 2 and deriving conclusions regarding the factors affecting the adoption of innovations to reduce and prevent FW. Findings: Results show that different types of innovations have a high potential in reducing and preventing FW along the supply chain; however, they still must be economically feasible to be adopted by decision makers in the food supply chain. TI, OI and MI are often interrelated and can trigger each other. When it comes to a combination of different types of innovation to reduce and prevent FW, a good example of combining TI, OI and MI may be observed in the retail sector in Europe. Here, innovative smartphone apps (TI) to promote the sale of products nearing their expiration dates (OI in terms of organising the sales differently and MI in terms of marketing it differently) were developed and adopted via different retailing channels, leading to the creation of a new business model. Practical implications: This study analyses the drivers of FW generation together with the factors affecting the decision to adopt innovations to reduce it and provides solutions to supply chain operators to prevent and reduce FW through different types of innovations. Originality/value: Literature has not systematically addressed innovations aiming at the reduction of FW yet. This paper provides a comprehensive literature review of the determinants of innovation adoption and offers a novel view on the problem of FW reduction by means of innovation, by linking factors affecting the decision to innovate with FW drivers

Energy and Exergy Analyses on Seasonal Comparative Evaluation of Water Flow Cooling for Improving the Performance of Monocrystalline PV Module in Hot-Arid Climate

Solar irradiation in hot-arid climatic countries results in increased temperatures, which is one of the major factors affecting the power generation efficiency of monocrystalline photovoltaic (PV) systems, posing performance and degradation challenges. In this paper, the efficiency of a water-flow cooling system to increase the output of a monocrystalline PV module with a rated capacity of 80 W is studied from both energy and exergy perspectives. The energy and exergy tests are performed for each season of the year, with and without cooling. The energy and exergy efficiencies, as well as the commodity exergy values, are used to compare the photovoltaic device with and without cooling. The findings are based on the experimental data that were collected in Tehran, Iran as an investigated case study in a country with a hot-arid climate. The findings show that when water-flow cooling is used, the values of the three efficiency metrics change significantly. In various seasons, improvements in regular average energy efficiency vary from 7.3% to 12.4%. Furthermore, the achieved increase in exergy efficiency is in the 13.0% to 19.6% range. Using water flow cooling also results in a 12.1% to 18.4% rise in product exergy

Methodology framework for prioritisation of renewable energy sources in port areas

Ports play a crucial role in increasing the decarbonisation of urban environments to mitigate the environmental impacts of maritime transport and promote sustainable intermodal mobility. Various efforts have been made to increase energy self-sufficiency using renewable energy sources (RESs) in different ports worldwide. However, the ports played an essential role in the pollution process of the nearest cities due to the short distance and merging with urban areas. In this case, solar and wind were measured using the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data of four Lazio province ports. Each RES was evaluated using 10 years of monthly data for mapping and 1 year of hourly data for potential assessment and energy converters installation. Furthermore, the time series method has been considered to design and develop better management of RESs for decision making monitoring the energy needs of ports. This time series method has been applied to the generated energy source based on various parameters of the RESs used in port

Explainable Machine Learning Exploiting News and Domain-Specific Lexicon for Stock Market Forecasting

In this manuscript, we propose a Machine Learning approach to tackle a binary classification problem whose goal is to predict the magnitude (high or low) of future stock price variations for individual companies of the SP 500 index. Sets of lexicons are generated from globally published articles with the goal of identifying the most impactful words on the market in a specific time interval and within a certain business sector. A feature engineering process is then performed out of the generated lexicons, and the obtained features are fed to a Decision Tree classifier. The predicted label (high or low) represents the underlying company's stock price variation on the next day, being either higher or lower than a certain threshold. The performance evaluation we have carried out through a walk-forward strategy, and against a set of solid baselines, shows that our approach clearly outperforms the competitors. Moreover, the devised Artificial Intelligence (AI) approach is explainable, in the sense that we analyze the white-box behind the classifier and provide a set of explanations on the obtained results