Comparison of environmental impacts of individual meals - Does it really make a difference to choose plant-based meals instead of meat-based ones?

More than one third of global greenhouse gas emissions (GHG) can be attributed to our food system. Limiting global warming to 1.5° or 2 °C will not be possible without reducing GHG emissions from the food system. Dietary change at the meal level is of great importance as day-to-day consumption patterns drive the global food production system. The aim of this paper was to assess the life cycle environmental impact of a sample of meals from different cuisines (chilli, lasagne, curry and teriyaki meals) and their meat-based, vegetarian, vegan, and whole-food vegan recipe variations. The environmental impacts (global warming, freshwater eutrophication, terrestrial acidification and water depletion potential) of 13 meals, made with 33 different ingredients, were estimated from cradle to plate using Life Cycle Assessment (LCA). Results showed that irrespective of the type of cuisine, the plant-based version of meals (vegan and whole-food vegan) had substantially lower environmental impacts across all impact categories than their vegetarian and meat-based versions. On average, meat-based meals had 14 times higher environmental impact, while vegetarian meals had 3 times higher environmental impact than vegan meals. Substantial reductions in the environmental impacts of meals can be achieved when animal-based ingredients (e.g., beef, cheese, pork, chicken) are replaced with whole or minimally processed plant-based ingredients (i.e., vegetables, legumes) in recipes. Swapping animal-based meals for plant-based versions, and preferably transitioning to plant-based diets, present important opportunities for mitigating climate change and safeguarding environmental sustainability

Nearly-linear monotone paths in edge-ordered graphs

How long a monotone path can one always find in any edge-ordering of the complete graph Kn? This appealing question was first asked by Chv´atal and Koml´os in 1971, and has since attracted the attention of many researchers, inspiring a variety of related problems. The prevailing conjecture is that one can always find a monotone path of linear length, but until now the best known lower bound was n 2/3−o(1). In this paper we almost close this gap, proving that any edge-ordering of the complete graph contains a monotone path of length n 1−o(1

Sentiment Classification of Customer Reviews about Automobiles in Roman Urdu

Text mining is a broad field having sentiment mining as its important constituent in which we try to deduce the behavior of people towards a specific item, merchandise, politics, sports, social media comments, review sites etc. Out of many issues in sentiment mining, analysis and classification, one major issue is that the reviews and comments can be in different languages like English, Arabic, Urdu etc. Handling each language according to its rules is a difficult task. A lot of research work has been done in English Language for sentiment analysis and classification but limited sentiment analysis work is being carried out on other regional languages like Arabic, Urdu and Hindi. In this paper, Waikato Environment for Knowledge Analysis (WEKA) is used as a platform to execute different classification models for text classification of Roman Urdu text. Reviews dataset has been scrapped from different automobiles sites. These extracted Roman Urdu reviews, containing 1000 positive and 1000 negative reviews, are then saved in WEKA attribute-relation file format (arff) as labeled examples. Training is done on 80% of this data and rest of it is used for testing purpose which is done using different models and results are analyzed in each case. The results show that Multinomial Naive Bayes outperformed Bagging, Deep Neural Network, Decision Tree, Random Forest, AdaBoost, k-NN and SVM Classifiers in terms of more accuracy, precision, recall and F-measure.Comment: This is a pre-print of a contribution published in Advances in Intelligent Systems and Computing (editors: Kohei Arai, Supriya Kapoor and Rahul Bhatia) published by Springer, Cham. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-03405-4_4

Rindler Particles and Classical Radiation

We describe the quantum and classical radiation by a uniformly accelerating point source in terms of the elementary processes of absorption and emission of Rindler scalar photons of the Fulling-Davies-Unruh bath observed by a co-accelerating observer.To this end we compute the emission rate by a DeWitt detector of a Minkowski scalar particle with defined transverse momentum per unit of proper time of the source and we show that it corresponds to the induced absorption or spontaneous and induced emission of Rindler photons from the thermal bath. We then take what could be called the inert limit of the DeWitt detector by considering the limit of zero gap energy. As suggested by DeWitt, we identify in this limit the detector with a classical point source and verify the consistency of our computation with the classical result. Finally, we study the behavior of the emission rate in D space-time dimensions in connection with the so called apparent statistics inversion.Comment: 8 pages, 2 figure

Feature selection for chemical sensor arrays using mutual information

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays

Leading-effect vs. Risk-taking in Dynamic Tournaments: Evidence from a Real-life Randomized Experiment

Two 'order effects' may emerge in dynamic tournaments with information feedback. First, participants adjust effort across stages, which could advantage the leading participant who faces a larger 'effective prize' after an initial victory (leading-effect). Second, participants lagging behind may increase risk at the final stage as they have 'nothing to lose' (risk-taking). We use a randomized natural experiment in professional two-game soccer tournaments where the treatment (order of a stage-specific advantage) and team characteristics, e.g. ability, are independent. We develop an identification strategy to test for leading-effects controlling for risk-taking. We find no evidence of leading-effects and negligible risk-taking effects

Vat polymerization 3D printing of composite acrylate photopolymer-based coated glass beads

Vat photopolymerization-based three-dimensional (3D) printing techniques have been used as an efficient method for complex and special geometries in various applications. Composites are also a group of polymer materials that are obtained by adding a reinforcing component such as filler, fibres with different origins. Therefore, the development of 3D printable composites is paramount due to their high precision and speed of production. Glass beads (GBs) have been favorites as economical reinforcement agents for their chemical stability, water resistance in acidic environments, dimensional stability, and eco-friendly properties. In this study, 3D printable composites based on coated glass beads (CGBs) have been prepared. First, the beads are coated with ultraviolet (UV) curable resins to improve the interface with the polymer matrix. Then, CGBs are mixed with 3D printing resin and formulated for digital light processing (DLP) printing. The coating process is checked by scanning electron microscopy (SEM), and the mechanical properties of the 3D-printed composite structures have been evaluated by bending and compression tests. Also, the fracture behavior of cured resin has been checked with SEM. Mechanical property investigations have shown the success of the 3D printing of the CGBs into a photopolymer resin (PR) composite with behavior modification and compatibility of the interface with the matrix in practice

Mechanisms of Cognitive Impairment in Cerebral Small Vessel Disease: Multimodal MRI Results from the St George's Cognition and Neuroimaging in Stroke (SCANS) Study.

Cerebral small vessel disease (SVD) is a common cause of vascular cognitive impairment. A number of disease features can be assessed on MRI including lacunar infarcts, T2 lesion volume, brain atrophy, and cerebral microbleeds. In addition, diffusion tensor imaging (DTI) is sensitive to disruption of white matter ultrastructure, and recently it has been suggested that additional information on the pattern of damage may be obtained from axial diffusivity, a proposed marker of axonal damage, and radial diffusivity, an indicator of demyelination. We determined the contribution of these whole brain MRI markers to cognitive impairment in SVD. Consecutive patients with lacunar stroke and confluent leukoaraiosis were recruited into the ongoing SCANS study of cognitive impairment in SVD (n = 115), and underwent neuropsychological assessment and multimodal MRI. SVD subjects displayed poor performance on tests of executive function and processing speed. In the SVD group brain volume was lower, white matter hyperintensity volume higher and all diffusion characteristics differed significantly from control subjects (n = 50). On multi-predictor analysis independent predictors of executive function in SVD were lacunar infarct count and diffusivity of normal appearing white matter on DTI. Independent predictors of processing speed were lacunar infarct count and brain atrophy. Radial diffusivity was a stronger DTI predictor than axial diffusivity, suggesting ischaemic demyelination, seen neuropathologically in SVD, may be an important predictor of cognitive impairment in SVD. Our study provides information on the mechanism of cognitive impairment in SVD

An eclipsing binary distance to the Large Magellanic Cloud accurate to 2 per cent

In the era of precision cosmology it is essential to determine the Hubble Constant with an accuracy of 3% or better. Currently, its uncertainty is dominated by the uncertainty in the distance to the Large Magellanic Cloud (LMC) which as the second nearest galaxy serves as the best anchor point of the cosmic distance scale. Observations of eclipsing binaries offer a unique opportunity to precisely and accurately measure stellar parameters and distances. The eclipsing binary method was previously applied to the LMC but the accuracy of the distance results was hampered by the need to model the bright, early-type systems used in these studies. Here, we present distance determinations to eight long-period, late- type eclipsing systems in the LMC composed of cool giant stars. For such systems we can accurately measure both the linear and angular sizes of their components and avoid the most important problems related to the hot early-type systems. Our LMC distance derived from these systems is demonstrably accurate to 2.2 % (49.97 +/- 0.19 (statistical) +/- 1.11 (systematic) kpc) providing a firm base for a 3 % determination of the Hubble Constant, with prospects for improvement to 2 % in the future.Comment: 34 pages, 5 figures, 13 tables, published in the Nature, a part of our data comes from new unpublished OGLE-IV photometric dat