Experimental Realization of Optimal Noise Estimation for a General Pauli Channel

We present the experimental realization of the optimal estimation protocol for a Pauli noisy channel. The method is based on the generation of 2-qubit Bell states and the introduction of quantum noise in a controlled way on one of the state subsystems. The efficiency of the optimal estimation, achieved by a Bell measurement, is shown to outperform quantum process tomography

Feature Selection Based on a Genetic Algorithm for Optimizing Weaning Success

Finding the right time for weaning from ventilator is a difficult clinical decision. Several systems based on machine or deep learning are reported in literature. However, the results of these applications are not completely satisfactory and may be improved. An important aspect is represented by the features used as input of these systems. In this paper we present the results of the application of genetic algorithms to perform feature selection on a dataset containing 13688 patients under mechanical ventilation characterizing by 58 variables, extracted from the MIMIC III database. The results show that all features are important, but four of them are essential: 'Sedation_days', 'Mean_Airway_Pressure', 'PaO2', and 'Chloride'. This is only the initial step to obtain a tool to be added to the other clinical indices for minimize the risk of extubation failure

Photometric Redshift of X-Ray Sources in the Chandra Deep Field South

Based on the photometry of 10 near-UV, optical, and near-infrared bands of the Chandra Deep Field South, we estimate the photometric redshifts for 342 X-ray sources, which constitute ~99% of all the detected X-ray sources in the field. The models of spectral energy distribution are based on galaxies and a combination of power-law continuum and emission lines. Color information is useful for source classifications: Type-I AGN show non-thermal spectral features that are distinctive from galaxies and Type-II AGN. The hardness ratio in X-ray and the X-ray-to-optical flux ratio are also useful discriminators. Using rudimentary color separation techniques, we are able to further refine our photometric redshift estimations. Among these sources, 137 have reliable spectroscopic redshifts, which we use to verify the accuracy of photometric redshifts and to modify the model inputs. The average relative dispersion in redshift distribution is ~8%, among the most accurate for photometric surveys. The high reliability of our results is attributable to the high quality and broad coverage of data as well as the applications of several independent methods and a careful evaluation of every source. We apply our redshift estimations to study the effect of redshift on broadband colors and to study the redshift distribution of AGN. Our results show that both the hardness ratio and U-K color decline with redshift, which may be the result of a K-correction. The number of Type-II AGN declines significantly at z>2 and that of galaxies declines at z>1. However, the distribution of Type-I AGN exhibits less redshift dependence. As well, we observe a significant peak in the redshift distribution at z=0.6. We demonstrate that our photometric redshift estimation produces a reliable database for the study of X-ray luminosity of galaxies and AGN.Comment: 40 pages, 11 figures. Accepted for publication in the Astrophysical Journa

Asymmetry index in muscle activations

Gait asymmetry is typically evaluated using spatio-temporal or joint kinematics parameters. Only a few studies addressed the problem of defining an asymmetry index directly based on muscle activity, extracting parameters from surface electromyography (sEMG) signals. Moreover, no studies used the extraction of the muscle principal activations (activations that are necessary for accomplishing a specific motor task) as the base to construct an asymmetry index, less affected by the variability of sEMG patterns. The aim of this study is to define a robust index to quantitative assess the asymmetry of muscle activations during locomotion, based on the extraction of the principal activations. SEMG signals were analyzed combining Statistical Gait Analysis (SGA) and a clustering algorithm that allows for obtaining the muscle principal activations. We evaluated the asymmetry levels of four lower limb muscles in: (1) healthy subjects of different ages (children, adults, and elderly); (2) different populations of orthopedic patients (adults with megaprosthesis of the knee after bone tumor resection, elderly subjects after total knee arthroplasty and elderly subjects after total hip arthroplasty); and (3) neurological patients (children with hemiplegic cerebral palsy and elderly subjects affected by idiopathic Normal Pressure Hydrocephalus). The asymmetry index obtained for each pathological population was then compared to that of age-matched controls. We found asymmetry levels consistent with the expected impact of the different pathologies on muscle activation during gait. This suggests that the proposed index can be successfully used in clinics for an objective assessment of the muscle activation asymmetry during locomotion

Caracteres epidérmicos foliares de latifoliadas herbáceas del chaco occidental, San Luis

The leaf epidermis of the following forbs from the Westem Chaco region (San Luis Province, Argentina) are analized and lIIustrated: Conyza bonariensis, Schkuria pinnata, Xanthium spinosum, Cryptantha mendocina, Evolvulus seticeus, Cucurbitella asperata, Ibicella parodii, Clematis denticulata, Solanum juvenale y Tribulus terrestris. The characteres used for taxonomíc determination are those useful for the identification of small fragments such as: cell walls, trichomas, stomata and cuticular omamentatlon. A key for the identification of these species is presented.Se analiza e ilustra la epidermis foliar de las siguientes latifoliadas herbáceas de la región Chaquena Occidental, San Luis, Argentina: Conyza bonariensis, Schkuria pinnata, Xanthium spinosum, Cryptantha mendocina, Evolvulus sericeus, Cucurbitella asperata, Ibicella parodii, Clematis denticulata, Solanum juvenale y Tribulus terrestris. Los caracteres considerados de valor diagnóstico en la determinación de estas especies son aquellos útiles para la identificación de fragmentos pequeños tales como: las formas de la pared anticlinal de las células epld6rmicas propiamente dichas, los tricomas, los complejos estomáticos y la ornamentación cuticular. Se presenta una clave para la identificación de estas especies

NEPA (netupitant/palonosetron) for the antiemetic prophylaxis of nausea and vomiting induced by chemotherapy (CINV) with Folfirinox and Folfoxiri even during the COVID-19 pandemic: A real-life study

OBJECTIVE: The outbreak of coronavirus disease 2019 (COVID-19) has affected the treatment of cancer patients, with particular regard to the management of both chemotherapy and side effects. Chemotherapy-induced nausea and vomiting (CINV) are amongst the most troublesome side effects that impair patients’ adherence to treatments and their quality of life (QoL). NEPA (Akynzeo®), is an oral fixed-dose combination of netupitant [a neurokinin-1 receptor antagonist (NK1RA), 300 mg] and palonosetron [(5-hydroxytryptamine (serotonin or 5HT) type3 receptor antagonist (5HT3RA), 0.5 mg] which has been shown to be effective in preventing CINV. PATIENTS AND METHODS: This prospective study started before the outbreak of COVID-19 and was carried out during the pandemic period. The aim was to evaluate the efficacy and safety of a single oral dose NEPA plus 12 mg of dexamethasone (DEX) in patients treated with Folfoxiri plus Bevacizumab and Folfirinox. The patients were diagnosed with advanced colorectal cancer (CRC) or advanced pancreatic ductal adenocarcinoma (PDAC). They were divided into two groups: naïve patients and patients previously treated with serotonin receptor antagonists (5HT3-RA) and neurokin-1 receptor antagonists (NK1-RA). RESULTS: During the overall phase, the complete response (CR) rate was 96.8% in naïve patients treated with Folfoxiri plus Bevacizumab, and 94.6% in patients treated with Folfirinox. During the acute and delayed phases, the CR rate was 92.8% and 94.2%, with Folfoxiri and Bevacizumab, as well as 96.2% and 94.6%, with Folfirinox. There was no adequate control of CINV events in patients on antiemetic prophylaxis with 5HT3-RA or NK1-RA associated with cortisone. During the overall phase, the CR rate was 74.6% with Folfoxiri plus Bevacizumab and 75.8% with Folfirinox. During the acute and delayed phases, the CR rate was 72.5% and 74.8% with Folfoxiri plus Bevacizumab, as well as 75.2% and 74.6% with Folfirinox. CONCLUSIONS: This study has shown the therapeutic benefits of NEPA in the management and prophylaxis of CINV events, both in naive patients and patients previously treated with 5HT3-RA and NK1-RA. In addition, NEPA has been shown to be safe, both before and during the COVID-19 pandemic

The Red Sequence of High-Redshift Clusters: a Comparison with Cosmological Galaxy Formation Models

We compare the results from a semi-analytic model of galaxy formation with spectro-photometric observations of distant galaxy clusters observed in the range 0.8< z< 1.3. We investigate the properties of their red sequence (RS) galaxies and compare them with those of the field at the same redshift. In our model we find that i) a well-defined, narrow RS is obtained already by z= 1.2; this is found to be more populated than the field RS, analogously to what observed and predicted at z=0; ii) the predicted U-V rest-frame colors and scatter of the cluster RS at z=1.2 have average values of 1 and 0.15 respectively, with a cluster-to-cluster variance of 0.2 and 0.06, respectively. The scatter of the RS of cluster galaxies is around 5 times smaller than the corresponding field value; iii) when the RS galaxies are considered, the mass growth histories of field and cluster galaxies at z=1.2 are similar, with 90 % of the stellar mass of RS galaxies at z=1.2 already formed at cosmic times t=2.5 Gyr, and 50 % at t=1 Gyr; v) the predicted distribution of stellar ages of RS galaxies at z=1.2 peaks at 3.7 Gyr for both cluster and field populations; however, for the latter the distribution is significantly skewed toward lower ages. When compared with observations, the above findings show an overall consistency, although the average value 0.07 of the observed cluster RS scatter (U-V colors) at z=1.2 is smaller than the corresponding model central value. We discuss the physical origin and the significance of the above results in the framework of cosmological galaxy formation.Comment: 14 pages, accepted for publication in ApJ. Updated one referenc

A Puzzling X-Ray Source Found in the chandra Deep Field South

In this letter we report the detection of an extremely strong X-ray emission line in the 940ks chandra ACIS-I spectrum of CXO CDFS J033225.3-274219. The source was identified as a Type1 AGN at redshift of z = 1.617, with 2.0 -- 10.0 keV rest frame X-ray luminosity of ~ 10^44 ergs s^-1. The emission line was detected at 6.2^{+0.2}_{-0.1} keV, with an equivalent width (EW) of 4.4^{+3.2}_{-1.4} keV, both quantities referring to the observed frame. In the rest frame, the line is at 16.2^{+0.4}_{-0.3} keV with an EW of 11.5^{+8.3}_{-3.7} keV. An X-ray emission line at similar energy (~ 17 keV, rest frame) in QSO PKS 2149-306 was discovered before using ASCA data. We reject the possibility that the line is due to a statistical or instrumental artifact. The line is most likely due to blueshifted Fe-K emission from an relativistic outflow, probably an inner X-ray jet, with velocities of the order of ~ 0.6-0.7c. Other possible explanations are also discussed

Radiomics to predict response to neoadjuvant chemotherapy in rectal cancer: influence of simultaneous feature selection and classifier optimization

According to the guidelines, patients with locally advanced colorectal cancer undergo neoadjuvant chemotherapy. However, response to therapy is reached only up to 30% of cases. Therefore, it would be important to predict response to therapy before treatment. In this study, we demonstrated that the simultaneous optimization of feature subset and classifier parameters on different imaging datasets (T2w, DWI and PET) could improve classification performance. On a dataset of 51 patients (21 responders, 30 non responders), we obtained an accuracy of 90%, 84% and 76% using three optimized SVM classifiers fed with selected features from PET, T2w and ADC images, respectively