Life cycle assessment of fuel ethanol from sugarcane in Argentina

10.1007/s11367-013-0584-2Purpose The production of bioethanol in Argentina is based on the sugarcane plantation system, with extensive use of agricultural land, scarce use of fertilizers, pesticides, and artificial irrigation, and burning of sugarcane prior to harvesting. The objective of this paper is to develop a life cycle assessment (LCA) of the fuel ethanol from sugarcane in Tucumán (Argentina), assessing the environmental impact potentials to identify which of them cause the main impacts. Methods Our approach innovatively combined knowledge about the main impact pathways of bioethanol production with LCA which covers the typical emission-related impact categories at the midpoint life cycle impact assessment. Real data from the Argentinean industry subsystems have been used to perform the study: S1¿sugarcane production, S2¿milling process, S3¿sugar production, and S4¿ethanol production from molasses, honey, or sugarcane juice. Results and discussion The results are shown in the three alternative pathways to produce bioethanol. Different impact categories are assessed, with global warming potential (GWP) having the highest impact. So, the production of 1 kg of ethanol from molasses emitted 22.5 kg CO2 (pathway 1), 19.2 kg CO2 from honey (pathway 2), and 15.0 kg CO2 from sugarcane juice (pathway 3). Several sensitivity analyses to study the variability of the GWP according to the different cases studied have been performed (changing the agricultural yield, including economic and calorific allocation in sugar production, and modifying the sugar price). Conclusions Agriculture is the subsystem which shows the highest impact in almost all the categories due to fossil fuel consumption. When an economic and calorific allocation is considered to assess the environmental impact, the value is lowe

Wafer-level assembly and sealing of a MEMS nanoreactor for in situ microscopy

This paper presents a new process for the fabrication of MEMS-based nanoreactors for in situ atomic-scale imaging of nanoparticles under relevant industrial conditions. The fabrication of the device is completed fully at wafer level in an ISO 5 clean room and it is based on silicon fusion bonding and thin film encapsulation for sealed lateral electrical feedthroughs. The fabrication process considerably improves the performances of previous nanoreactors. The wafer-level assembly allows faster preparation of devices, hydrocarbon contamination is no longer observed and the control of the channel height leads to a better flow reproducibility. The channel is shown to be sufficiently hermetic to work in the vacuum of a transmission electron microscope while a pressure of 100 kPa is maintained inside the nanoreactor. The transparency is demonstrated by the atomic scale imaging of YBCO nanoparticles, with a line spacing resolution of 0.19 nm.DIMES-ECTMElectrical Engineering, Mathematics and Computer Scienc

Beneficial Effect of Methylprednisolone on Cardiac Myocytes in a Rat Model of Severe Brain Injury

Cardiac injury, occurred after traumatic brain injury (TBI), has been recognized for more than a century. Bcl-2 is a key regulatory component of the mitochondrial cell death pathway, and its overexpression is cytoprotective in many cell types. The therapeutic agents, which induce the expression of bcl-2 protein, might provide a new therapy to prevent cardiac myocyte damage following TBI. In this study, we investigated whether methylprednisolone I sodium succinate (MPSS) influences the expression of bcl-2 in the heart. Wistar-Albino female rats underwent TBI (300 g/cm) generated by the weight-drop method, and were left untreated (n = 6) or treated with either MPSS (30 mg/kg) (n = 6) or vehicle (albumin solution) (n = 6). The heart was isolated from each animal with TBI. For comparison, the hearts were isolated from sham-operated (n = 6) and control rats (n = 6). The relative expression of bcl-2 mRNA in the heart was quantitated by real-time polymerase chain reaction. We also assessed lipid peroxidation in the heart tissue by determining the concentration of thiobarbituric acid-reactive substances (TBARs) as an indicator of tissue damage. The bcl-2 expression level was significantly higher in the hearts of MPSS-treated rats compared to that of other TBI groups (p < 0.0001). Moreover, TBI increased the lipid peroxidation in the heart, which was significantly reduced by the treatment with MPSS (p < 0.0001). These findings provide evidence for the efficacy of MPSS in protection of cardiac myocytes to achieve optimal heart donation after TBI in heart transplantation. (c) 2005 Tohoku University Medical Press.WoSScopu

Jets and QCD: A Historical Review of the Discovery of the Quark and Gluon Jets and its Impact on QCD

The observation of quark and gluon jets has played a crucial role in establishing Quantum Chromodynamics [QCD] as the theory of the strong interactions within the Standard Model of particle physics. The jets, narrowly collimated bundles of hadrons, reflect configurations of quarks and gluons at short distances. Thus, by analysing energy and angular distributions of the jets experimentally, the properties of the basic constituents of matter and the strong forces acting between them can be explored. In this review, which is primarily a description of the discovery of the quark and gluon jets and the impact of their observation on Quantum Chromodynamics, we elaborate, in particular, the role of the gluons as the carriers of the strong force. Focusing on these basic points, jets in e+e− collisions will be in the foreground of the discussion and we will concentrate on the theory that was contemporary with the relevant experiments at the electron-positron colliders. In addition we will delineate the role of jets as tools for exploring other particle aspects in ep and \hbox{$pp/p\bar{p}$} collisions  −  quark and gluon densities in protons, measurements of the QCD coupling, fundamental 2-2 quark/gluon scattering processes, but also the impact of jet decays of top quarks, and W ± , Z bosons on the electroweak sector. The presentation to a large extent is formulated in a non-technical language with the intent to recall the significant steps historically and convey the significance of this field also to communities beyond high energy physics

Search for multimessenger sources of gravitational waves and high-energy neutrinos with Advanced LIGO during its first observing run, ANTARES, and IceCube

Astrophysical sources of gravitational waves, such as binary neutron star and black hole mergers or core-collapse supernovae, can drive relativistic outflows, giving rise to non-thermal high-energy emission. High-energy neutrinos are signatures of such outflows. The detection of gravitational waves and high-energy neutrinos from common sources could help establish the connection between the dynamics of the progenitor and the properties of the outflow. We searched for associated emission of gravitational waves and high-energy neutrinos from astrophysical transients with minimal assumptions using data from Advanced LIGO from its first observing run O1, and data from the Antares and IceCube neutrino observatories from the same time period. We focused on candidate events whose astrophysical origins could not be determined from a single messenger. We found no significant coincident candidate, which we used to constrain the rate density of astrophysical sources dependent on their gravitational-wave and neutrino emission processes

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients. © The Author(s) 2024