Auto-sapiens autonomous driving vehicle

This paper presents the Auto-Sapiens project, an autonomous driving car developed by the Mechatronics and Vehicle Dynamics Lab, at Sapienza University of Rome. Auto-Sapiens is a technological platform to test and improve innovative control algorithms. The car platform is a standard car (Smart ForTwo) equipped with throttle, brake, steering actuators and different sensors for attitude identification and environment reconstruction. The first experiments of the Auto-Sapiens car test a new obstacle avoidance. The vehicle, controlled by an optimal variational feedback control, recently developed by the authors, includes the nonlinearities inherent in the car dynamics for better performances. Results show the effectiveness of the system in terms of safety and robustness of the avoidance maneuvers

Traumatic and non-traumatic spinal cord lesions: an Italian comparison of neurological and functional outcomes

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Solar particle effects on minor components of the Polar atmosphere

Abstract. Solar activity can influence the Earth's environment, and in particular the ozone layer, by direct modulation of the e.m. radiation or through variability of the incoming cosmic ray flux (solar and galactic particles). In particular, solar energetic particles (SEPs) provide additional external energy to the terrestrial environment; they are able to interact with the minor constituents of the atmospheric layer and produce ionizations, dissociations, dissociative ionizations and excitations. This paper highlights the SEP effects on the chemistry of the upper atmosphere by analysing some SEP events recorded during 2005 in the descending phase of the current solar cycle. It is shown that these events can lead to short- (hours) and medium- (days) term ozone variations through catalytic cycles (e.g. HOx and NOx increases). We focus attention on the relationship between ozone and OH data (retrieved from MLS EOS AURA) for four SEP events: 17 and 20 January, 15 May and 8 September. We confirm that SEP effects are different on the night and day hemispheres at high latitudes.</p

Analisis Abnormal Return Saham pada Peristiwa Merger dan Akuisisi di Indonesia

This study aims to obtain empirical evidence related to market reactions indicated by abnormal returns around the time of the 2016-2019 merger and acquisition announcement. The population in this study are companies listed on the Indonesia Stock Exchange that have conducted mergers and acquisitions. The sampling technique uses purposive sampling, the data obtained by 12 companies, namely 3 companies do mergers and 9 companies make acquisitions. Data analysis techniques in this study were one sample test method Kolmogorv-Smirnov test, paired sample t-test test, and one sample t-test using SPSS application version 25. The results of this study showed: During the 11 days study period, there were average abnormal return negative that insignificant for 7 days and average abnormal return positive that also insignificant for 4 days around the announcement time of the company’s mergers and acquisitions. These insignificant test results prove that the market was not approved during the period before and after mergers and acquisitions

A technique for short‐term warning of solar energetic particle events based on flare location, flare size, and evidence of particle escape

We have developed a technique to provide short‐term warnings of solar energetic proton (SEP) events that meet or exceed the Space Weather Prediction Center threshold of J (>10 MeV) = 10 pr cm−2 s−1 sr−1. The method is based on flare location, flare size, and evidence of particle acceleration/escape as parameterized by flare longitude, time‐integrated soft X‐ray intensity, and time‐integrated intensity of type III radio emission at ∼1 MHz, respectively. In this technique, warnings are issued 10 min after the maximum of ≥M2 soft X‐ray flares. For the solar cycle 23 (1995–2005) data on which it was developed, the method has a probability of detection of 63% (47/75), a false alarm rate of 42% (34/81), and a median warning time of ∼55 min for the 19 events successfully predicted by our technique for which SEP event onset times were provided by Posner (2007). These measures meet or exceed verification results for competing automated SEP warning techniques but, at the present stage of space weather forecasting, fall well short of those achieved with a human (aided by techniques such as ours) making the ultimate yes/no SEP event prediction. We give some suggestions as to how our method could be improved and provide our flare and SEP event database in the auxiliary material to facilitate quantitative comparisons with techniques developed in the future

Valorization of cigarette butts for synthesis of levulinic acid as top value-added chemicals

Unprecedented in the literature, levulinic acid (LA), one of the top value-added intermediates of chemical industry, is obtained from cigarette butts as cellulose feedstock by means of a one-pot hydrothermal process carried out at 200&nbsp;°C for 2&nbsp;h and catalysed by phosphoric acid. The protocol avoids the use of more aggressive and toxic H2SO4 and HCl, that are generally employed on several cellulose sources (e.g. sludge paper), thus minimizing corrosion phenomena of plants. Neither chemical pre-treatment of butts nor specific purification procedure of LA are required. Notably, by simply modifying acid catalyst (e.g. using CH3COOH), another top value-added fine chemical such as 5-hydroxymethylfuraldehyde (HMF) is obtained, thus widening the scope of the method. Being cigarette filters a waste available in quantities of megatonnes per year, they represent an unlimited at no cost source of cellulose, thus enabling the up-scale to an industrial level of LA production

Forecasting solar proton events by using the ESPERTA model

The ESPERTA (Empirical model for Solar Proton Event Real Time Alert) forecast tool has a Probability of Detection (POD) of 63% for all >10 MeV events with proton peak intensity ≥10 pfu (i.e., ≥S1 events, S1 referring to minor storms on the NOAA Solar Radiation Storms scale), from 1995 to 2014 with a false alarm rate (FAR) of 38% and a median (minimum) warning time (WT) of ∼4.8 (∼0.4) hr. The ESPERTA model modified to predict ≥S2 (i.e., ≥100 pfu) has a POD of 75% and a FAR of 24% for the 1995 - 2014 interval with a median (minimum) WT of ∼1.7 (∼0.2) hr based on predictions made at the time of the S1 threshold crossing. Here, both versions of the ESPERTA model have been applied to forecast recent solar proton events from 2015 to 2017, yielding results consistent with model performance for the 1995 to 2014 interval