An Effective Semiclassical Approach to IR Spectroscopy

We present a novel approach to calculate molecular IR spectra based on semiclassical molecular dynamics. The main advance from a previous semiclassical method [M. Micciarelli, R. Conte, J. Suarez, M. Ceotto J. Chem. Phys. 149, 064115 (2018)] consists in the possibility to avoid state-to-state calculations making applications to systems characterized by sizable densities of vibrational states feasible. Furthermore, this new method accounts not only for positions and intensities of the several absorption bands which make up the IR spectrum, but also for their shapes. We show that accurate semiclassical IR spectra including quantum effects and anharmonicities for both frequencies and intensities can be obtained starting from semiclassical power spectra. The approach is first tested against the water molecule, and then applied to the 10-atom glycine aminoacid

Assessing the Impact of Real-Time Machine Translation on Multilingual Meetings in Global Software Projects

Communication in global software development is hindered by language differences in countries with a lack of English speaking professionals. Machine translation is a technology that uses software to translate from one natural language to another. The progress of machine translation systems has been steady in the last decade. As for now, machine translation technology is particularly appealing because it might be used, in the form of cross-language chat services, in countries that are entering into global software projects. However, despite the recent progress of the technology, we still lack a thorough understanding of how real-time machine translation affects communication. In this paper, we present a set of empirical studies with the goal of assessing to what extent real-time machine translation can be used in distributed, multilingual requirements meetings instead of English. Results suggest that, despite far from 100% accurate, real-time machine translation is not disruptive of the conversation flow and, therefore, is accepted with favor by participants. However, stronger effects can be expected to emerge when language barriers are more critical. Our findings add to the evidence about the recent advances of machine translation technology and provide some guidance to global software engineering practitioners in regarding the losses and gains of using English as a lingua franca in multilingual group communication, as in the case of computer-mediated requirements meetings

An Efficiency-Based Power Management Strategy for an Isolated Microgrid Project

The microgrids design for remote locations represents one of the most important and critical applications of the microgrid concept. It requires the correct sizing and the proper utilization of the different sources to guarantee the economical feasibility and the reliability of the supply. This study illustrates an efficiency-based power management strategy, designed for an undergoing microgrid project, where the sizing process of the resources (diesel generators, battery energy storage system, and PV plant) is obtained using a mixed-integer optimization algorithm. The proposed power management strategy guarantees the efficient exploitation of the power sources, which is one of the key elements of the optimal sizing process, being naturally included in the definition of the energy cost functions. The effectiveness of the power control strategy is validated by means of quasi-dynamic simulations on the complete microgrid model, where sources are defined by the optimal problem solution, while the cabling (size and length) and the main switchboards location reflect the expected system layout. Results obtained from the simulation of the microgrid electrical system include losses, and allow to verify and to highlight the desired quantities, such as the quality of supply at each busbar (voltage magnitude), and the state of charge of the energy storage system

Anticipating New Treatments for Cystic Fibrosis: A Global Survey of Researchers

Cystic fibrosis is a life-threatening disease that affects at least 100,000 people worldwide. It is caused by a defect in the cystic fibrosis transmembrane regulator (CFTR) gene and presently, 360 CFTR-causing mutations have been identified. Since the discovery of the CFTR gene, the expectation of developing treatments that can substantially increase the quality of life or even cure cystic fibrosis patients is growing. Yet, it is still uncertain today which developing treatments will be successful against cystic fibrosis. This study addresses this gap by assessing the opinions of over 524 cystic fibrosis researchers who participated in a global web-based survey. For most respondents, CFTR modulator therapies are the most likely to succeed in treating cystic fibrosis in the next 15 years, especially through the use of CFTR modulator combinations. Most respondents also believe that fixing or replacing the CFTR gene will lead to a cure for cystic fibrosis within 15 years, with CRISPR-Cas9 being the most likely genetic tool for this purpose

Optimal Management of a Smart Port with Shore-Connection and Hydrogen Supplying by Stochastic Model Predictive Control

The paper proposes an optimal management strategy for a Smart Port equipped with renewable generation and composed by an electrified quay, operating Cold-Ironing, and a Hydrogen-based quay, supplying Zero-Emission Ships. One Battery Energy Storage System and one Hydrogen Energy Storage System are used to manage renewable energy sources and to supply electric and hydrogen-fueled ships. A model predictive control based algorithm is designed to define the best economic strategy to be followed during operations. The control algorithm takes into account the uncertainties of renewable energy generation using stochastic optimization. The performance of the approach is tested on a potential future Smart Port equipped with wind and photovoltaic generation

A comprehensive approach to dark matter studies: exploration of simplified top-philic models

Studies of dark matter lie at the interface of collider physics, astrophysics and cosmology. Constraining models featuring dark matter candidates entails the capability to provide accurate predictions for large sets of observables and compare them to a wide spectrum of data. We present a framework which, starting from a model lagrangian, allows one to consistently and systematically make predictions, as well as to confront those predictions with a multitude of experimental results. As an application, we consider a class of simplified dark matter models where a scalar mediator couples only to the top quark and a fermionic dark sector (i.e. the simplified top-philic dark matter model). We study in detail the complementarity of relic density, direct/indirect detection and collider searches in constraining the multi-dimensional model parameter space, and efficiently identify regions where individual approaches to dark matter detection provide the most stringent bounds. In the context of collider studies of dark matter, we point out the complementarity of LHC searches in probing different regions of the model parameter space with final states involving top quarks, photons, jets and/or missing energy. Our study of dark matter production at the LHC goes beyond the tree-level approximation and we show examples of how higher-order corrections to dark matter production processes can affect the interpretation of the experimental results.Comment: 52 pages, 23 figure

Pain treatment with high-dose, controlled-release oxycodone: an Italian perspective

To investigate the possible role and tolerability of high-dose (>160 mg/day) oxycodone controlled release (CR) for the treatment of cancer and non-cancer pain. 227 patients with cancer or non-cancer pain were enrolled in an open-label, multi-center, Italian study in order to assess the adequacy of their existing pain management (using a numerical rating scale [NRS]) and the possible benefit high-dose oxycodone CR may offer patients experiencing uncontrolled pain. Results: Pain was poorly controlled at baseline, with only 18.1% of patients reporting adequate pain relief (NRS <3.5). All other patients reported uncontrolled pain, with an average NRS of 7.81. At baseline assessment, 47.89% of patients had been in pain for up to 3 months, 32.82% for 3–6 months, and 19.19% for more than 6 months. After baseline assessment, patients were switched to oxycodone CR monotherapy. The starting dose was individualized to each patient and titrated up over a 3- to 4-day period until effective pain management was achieved. Treatment was continued for an average of 37.24 days during the study. Pain control (final mean NRS of 2.85) was attained with an average dose of oxycodone CR 221.84 mg/day. Standard adverse events (including constipations, nausea, and vomiting) were recorded in 39.64% of patients receiving high-dose oxycodone CR monotherapy. Side-effects tended to subside after the initial week of treatment and did not result in any participants leaving the study. High-dose oxycodone CR can achieve rapid and effective management of moderate to severe cancer and non-cancer pain with minimum side-effects

Amyotrophic lateral sclerosis phenotypes significantly differ in terms of magnetic susceptibility properties of the precentral cortex

The aim of our study was to investigate whether the magnetic susceptibility varies according to the amyotrophic lateral sclerosis (ALS) phenotypes based on the predominance of upper motor neuron (UMN)/lower motor neuron (LMN) impairment. We retrospectively collected imaging and clinical data of 47 ALS patients (12 with UMN predominance (UMN-ALS), 16 with LMN predominance (LMN-ALS), and 19 with no clinically defined predominance (Np-ALS)). We further enrolled 23 healthy controls (HC) and 15 ALS mimics (ALS-Mim). These participants underwent brain 3-T magnetic resonance imaging (3-T MRI) with T1-weighted and gradient-echo multi-echo sequences. Automatic segmentation and quantitative susceptibility mapping (QSM) were performed. The skewness of the susceptibility values in the precentral cortex (SuscSKEW) was automatically computed, compared among the groups, and correlated to the clinical variables. The Kruskal-Wallis test showed significant differences in terms of SuscSKEW among groups (χ2(3) = 24.2, p < 0.001), and pairwise tests showed that SuscSKEW was higher in UMN-ALS compared to those in LMN-ALS (p < 0.001), HC (p < 0.001), Np-ALS (p = 0.012), and ALS-Mim (p < 0.001). SuscSKEW was highly correlated with the Penn UMN score (Spearman's rho 0.612, p < 0.001). This study demonstrates that the clinical ALS phenotypes based on UMN/LMN sign predominance significantly differ in terms of magnetic susceptibility properties of the precentral cortex. Combined MRI-histopathology investigations are strongly encouraged to confirm whether this evidence is due to iron overload in UMN-ALS, unlike in LMN-ALS. • Magnetic susceptibility in the precentral cortex reflects the prevalence of UMN/LMN impairment in the clinical ALS phenotypes. • The degree of UMN/LMN impairment might be well described by the automatically derived measure of SuscSKEW in the precentral cortex. • Increased SuscSKEW in the precentral cortex is more relevant in UMN-ALS patients compared to those in Np-ALS and LMN-ALS patients

MARS Bulletin Vol 17 No 1

The annexed document is the template for the bulletin that will be issued on the 10th March. This bulletin covers meteorological analysis and crop yield forecasts for the period 21 November 2008 - 28 February 2009 (since the day after the last covered period, to the last day of the decade before)JRC.G.3-Monitoring agricultural resource