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Abstract An alkaline earth boro-aluminosilicate glass (Eagle XG), a soda-lime glass, and a light-weight polyethylene-terephthalate (PET) foil, used as typical substrates for photovoltaics, were treated by an energetic proton beam (3 MeV, dose 106–107 Gy) corresponding to approx. 30 years of operation at low Earth orbit. Properties of the irradiated substrates were characterized by atomic force microscopy, optical absorption, optical diffuse reflectance, Raman spectroscopy, X-ray photoelectron spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and terahertz (THz) spectroscopy. Minimal changes of optical and morphological properties are detected on the bare Eagle XG glass, whereas the bare PET foil exhibits pronounced increase in optical absorption, generation of photoluminescence, as well as mechanical bending. On the other hand, the identical substrates coated with Indium-tin-oxide (ITO), which is a typical material for transparent electrodes in photovoltaics, exhibit significantly higher resistance to the modifications by protons while ITO structural and electronic properties remain unchanged. The experimental results are discussed considering a potential application of these materials for missions in space.

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.

Abstract The present paper evaluates the feasibility of a process flowsheet for butanol bioproduction, as pure compound or as a blend with the biodiesel used as the liquid-liquid extraction (LLEx) solvent. In order to evidence this aspect, a modeling and simulation study was performed using Aspen Hysys commercial simulator. Process simulation results evidenced specific (per ton of butanol separated) power consumption of 22.5 kW/t and hot and cold utility specific consumptions were in power equivalences of 3.4 MW and 2.6 MW respectively. In order to achieve a feasible extraction process of biobutanol from the fermentative broth, a specific quantity of 1.125 t/t biodiesel (recovered as a blend) was required.

The space-time geometry exterior to a new four-dimensional, spherically symmetric and charged black hole solution that, through a coupling of general relativity with a non-linear electrodynamics, is non-singular everywhere, for small r it behaves as a de Sitter metric, and asymptotically it behaves as the Reissner-Nordström metric, is considered in order to study energy-momentum localization. For the calculation of the energy and momentum distributions, the Einstein, Landau-Lifshitz, Weinberg and Møller energy-momentum complexes were applied. The results obtained show that in all prescriptions the energy depends on the mass M of the black hole, the charge q, two parameters a ∈ Z + and γ ∈ R + , and on the radial coordinate r. The calculations performed in each prescription show that all the momenta vanish. Additionally, some limiting and particular cases for r and q are studied, and a possible connection with strong gravitational lensing and microlensing is attempted.

The overall purpose of the research is to develop a method to compute ecological flows in line with the EU Water Framework Directive (Directive 2000/60/EC) for the whole Romanian territory, for a variety of hydrological, morphological and ecological conditions. The method has three components: a Quantity component, a Dynamic component, and a Real-time operation component. The Quantity component is a hydrological method with elements of the aquatic fauna habitat indirectly linked to biological organisms based on the current Romanian knowledge on the linkages between hydrology and aquatic biology. The Dynamic and Real-time operation components are related to the hydrological forecast. The method is practical, robust and easy to apply. The concept and the ideas use the hydrological forecast to ensure the water dynamics required by the Water Framework Directive, and to develop the quantitative component, keeping in mind that putting it into practice might have importance for a broader audience. In order to better highlight the concept, the paper shows three practical examples of the RoEflow method’s application.

A p-NiO/n-KNbO3 heterojunction photocatalyst was synthesized via a photodeposition method and for the first time applied in photocatalytic N2 fixation under simulated sunlight.

This work intended to explore some motivations that influence people’s eating habits towards sustainability. This was an observational, cross-sectional study, carried out by questionnaire survey on a non-probabilistic sample of 10,067 participants from 13 countries (Argentina, Brazil, Croatia, Greece, Hungary, Latvia, Lithuania, Poland, Portugal, Serbia, Slovenia, Romania and United States). Results indicated that people prefer fresh local foods from the season, being important because it allows transportation and storage to be reduced, which in many cases implies refrigeration systems and consequent energy expenditure. Although people avoid food waste at home, the awareness for the waste at restaurants still needs to be improved. Consumers seem to prefer foods that have been produced and packed in sustainable ways but still give importance to the package—understandable for food products. The results also indicated significant differences in the food choice motivations between groups for all sociodemographic variables tested (age, sex, marital status, education, professional area, living environment and country), but the association was high only for variable country. Additionally, a tree classification analysis allowed to identify the relative importance of the influential variables on the sustainable food choices, with country being the most important, followed by age and sex. Additionally, discriminant function analysis allowed establishing a model for the relation between country and six variables accounting for preservation of biodiversity, respect for life, save natural resources, save energy, reduce industrial pollution and minimal packaging. Although with some limitations, this study brings valuable insight into some aspects linked with sustainable food choices on a number of countries and how people shape their food choices according to some sustainability issues.

In this work, the feasibility of texture parameters extracted from B-Mode images were explored in quantifying medium temperature variation. The goal is to understand how parameters obtained from the gray-level content can be used to improve the actual state-of-the-art methods for non-invasive temperature estimation (NITE). B-Mode images were collected from a tissue mimic phantom heated in a water bath. The phantom is a mixture of water, glycerin, agar-agar and graphite powder. This mixture aims to have similar acoustical properties to in vivo muscle. Images from the phantom were collected using an ultrasound system that has a mechanical sector transducer working at 3.5 MHz. Three temperature curves were collected, and variations between 27 and 44 degrees C during 60 min were allowed. Two parameters (correlation and entropy) were determined from Grey-Level Co-occurrence Matrix (GLCM) extracted from image, and then assessed for non-invasive temperature estimation. Entropy values were capable of identifying variations of 2.0 degrees C. Besides, it was possible to quantify variations from normal human body temperature (37 degrees C) to critical values, as 41 degrees C. In contrast, despite correlation parameter values (obtained from GLCM) presented a correlation coefficient of 0.84 with temperature variation, the high dispersion of values limited the temperature assessment.