The mass accretion rate of galaxy clusters: a measurable quantity

We explore the possibility of measuring the mass accretion rate (MAR) of galaxy clusters from their mass profiles beyond the virial radius $R_{200}$. We derive the accretion rate from the mass of a spherical shell whose inner radius is $2R_{200}$, whose thickness changes with redshift, and whose infall velocity is assumed to be equal to the mean infall velocity of the spherical shells of dark matter halos extracted from $N$-body simulations. This approximation is rather crude in hierarchical clustering scenarios where both smooth accretion and aggregation of smaller dark matter halos contribute to the mass accretion of clusters.Nevertheless, in the redshift range $z=[0,2]$, our prescription returns an average MAR within $20-40 \%$ of the average rate derived from the merger trees of dark matter halos extracted from $N$-body simulations. The MAR of galaxy clusters has been the topic of numerous detailed numerical and theoretical investigations, but so far it has remained inaccessible to measurements in the real universe. Since the measurement of the mass profile of clusters beyond their virial radius can be performed with the caustic technique applied to dense redshift surveys of the cluster outer regions, our result suggests that measuring the mean MAR of a sample of galaxy clusters is actually feasible. We thus provide a new potential observational test of the cosmological and structure formation models.Comment: 11 pages, 7 figures, 5 tables, minor text modifications to match the published version, typos correcte

Synthetic character fidelity through non-verbal behaviour in computer games

Artificial Intelligence in games has historically focused on providing a challenging opponent for a player and narrative development. Scope exists to increase the fidelity of synthetic characters throughout the game to create a more immersive game play experience. This requires both visual and behavioural fidelity, and while graphics are nearing photorealism, synthetic characters' behaviour is still unrealistic. Non-verbal behaviour of synthetic characters has to date received little attention and so the scope and participants of non-verbal behaviour requires identification. We review the range of spatial and task scenarios relevant in a game context, then identify categories of non-verbal behaviour and go on tot summarise their role in communication and propose their incorporation in the design of non-player characters. Finally we review how non-verbal behaviour of synthetic agents might increase immersion for a player and identify interaction techniques that might facilitate non-verbal communication with players and non-players characters alike

IoT and Biosensors: A Smart PortablePotentiostat With AdvancedCloud-Enabled Features

Recent advances in Internet-of-Things technology have opened the doors to new scenariosfor biosensor applications. Flexibility, portability, and remote control and access are of utmost importanceto move these devices to people’s homes or in a Point-of-Care context and rapidly share the results withusers and their physicians. In this paper, an innovative portable device for both quantitative and semi-quantitative electrochemical analysis is presented. This device can operate autonomously without the needof relying on other devices (e.g., PC, tablets, or smartphones) thanks to built-in Wi-Fi connectivity. Thedeveloped hardware is integrated into a cloud-based platform, exploiting the cloud computational powerto perform innovative algorithms for calibration (e.g., Machine Learning tools). Results and configurationscan be accessed through a web page without the installation of dedicated APPs or software. The electricalinput/output characteristic was measured with a dummy cell as a load, achieving excellent linearity.Furthermore, the device response to five different concentrations of potassium ferri/ferrocyanide redox probewas compared with a bench-top laboratory instrument. No difference in analytical sensitivity was found.Also, some examples of application-specific tests were set up to demonstrate the use in real-case scenarios.In addition, Support Vector Machine algorithm was applied to semi-quantitative analyses to classify theinput samples into four classes, achieving an average accuracy of 98.23%. Finally, COVID-19 related testsare presented and discussed (PDF) IoT and Biosensors: A Smart Portable Potentiostat With Advanced Cloud-Enabled Features. Available from: https://www.researchgate.net/publication/355214115_IoT_and_Biosensors_A_Smart_Portable_Potentiostat_With_Advanced_Cloud-Enabled_Features [accessed Oct 25 2021]

A Wi-Fi cloud-based portable potentiostat for electrochemical biosensors

The measurement of the analyte concentration in electrochemical biosensors traditionally requires costly laboratory equipment to obtain accurate results. Innovative portable solutions have recently been proposed, but usually, they lean on personal computers (PCs) or smartphones for data elaboration and they exhibit poor resolution or portability and proprietary software. This paper presents a low-cost portable system, assembling an ad hoc -designed analog front end (AFE) and a development board equipped with a system on chip integrating a microcontroller and a Wi-Fi network processor. The wireless module enables the transmission of measurements directly to a cloud service for sharing device outcome with users (physicians, caregivers, and so on). In doing so, the system does not require neither the customized software nor other devices involved in data acquisition. Furthermore, when any Internet connection is lost, the data are stored on board for subsequent transmission when a Wi-Fi connection is available. The noise output voltage spectrum has been characterized. Since the designed device is intended to be battery-powered to enhance portability, investigations about battery lifetime were carried out. Finally, data acquired with a conventional benchtop Autolab PGSTAT-204 electrochemical workstation are compared with the outcome of our developed device to validate the effectiveness of our proposal. To this end, we selected ferri/ferrocyanide as redox probe, obtaining the calibration curves for both the platforms. The final outcomes are shown to be feasible, accurate, and repeatable

A self-calibrating IoT portable electrochemical immunosensor for serum human epididymis protein 4 as a tumor biomarker for ovarian cancer

Nowadays analytical techniques are moving towards the development of smart biosensing strategies for point-of-care accurate screening of disease biomarkers, such as human epididymis protein 4 (HE4), a recently discovered serum markers for early ovarian cancer diagnosis. In this context, the present work represents the first implementation of a competitive enzyme-labelled magneto-immunoassay exploiting a homemade IoT Wi-Fi cloud-based portable potentiostat for differential pulse voltammetry readout. The electrochemical device was specifically designed capable of autonomous calibration and data processing, switching between calibration and measurement modes: in particular, firstly a baseline estimation algorithm is applied for correct peak computation, then calibration function is built by interpolating data with a four-parameter logistic function. The calibration function parameters are stored on the cloud for inverse prediction to determine the concentration of unknown samples. Interpolation function calibration and concentration evaluation are performed directly on-board, reducing the power consumption. The analytical device was validated in human serum, demonstrating good sensing performance for analysis of HE4 with detection and quantitation limits in human serum of 3.5 and 29.2 pM, respectively, reaching the sensitivity required for diagnostic purposes, with high potential for applications as portable and smart diagnostic tool for point-of-care testing

Rapid Quantification of SARS-Cov-2 Spike Protein Enhanced with a Machine Learning Technique Integrated in a Smart and Portable Immunosensor

An IoT-WiFi smart and portable electrochemical immunosensor for the quantification of SARS-CoV-2 spike protein integrated with machine learning features was developed. The immunoenzymatic sensor is based on the immobilization of monoclonal antibodies directed to SARS-CoV-2 S1 subunit on Screen-Printed Electrodes functionalized with gold nanoparticles, the analytical protocol involving a single-step sample incubation. Immunosensor performance was assessed by validation carried out in viral transfer medium, which is commonly used for de-sorption of nasopharyngeal swabs. Remarkable specificity of the response was demonstrated by testing H1N1 Hemagglutinin from swine-origin influenza A virus and Spike Protein S1 from Middle East respiratory syndrome coronavirus. Machine learning was successfully used for data processing and analysis: different support vector machine classifiers were evaluated proving that algorithms affect the classifier accuracy. The test accuracy of the best classification model in terms of true positive/true negative sample classification was 97.3%. In addition, ML algorithm can be easily integrated into the developed cloud-based portable Wi-Fi device. Finally, the immunosensor was successfully tested using a third generation replicating incompetent lentiviral vector pseudotyped with SARS-CoV-2 spike glycoprotein, thus proving the applicability of the immunosensor to whole virus detection

Femtosecond Two-Photon Absorption Spectroscopy Of Copper Indium Sulfide Quantum Dots: A Structure-Optical Properties Relationship

We have interpreted the two-photon absorption spectrum of water-soluble copper indium sulfide (CIS) QDs with stoichiometry 0.18 (Cu), 0.42 (In), and 2 (S) and an average diameter of approximately 2.6 nm. For that, we employed the wavelength-tunable femtosecond Z-scan technique and the parabolic effective-mass approximation model, in which the excitonic transition energies were phenomenologically corrected due to the stoichiometry of the nanocrystal. This model considers a conduction band and three valence sub-bands allowing excitonic transitions via centrosymmetric (Δl = ±1, where l is the angular momentum of the absorbing state) and non-centrosymmetric (Δl = 0) channels. In such case, this became relevant because the CIS QDs with chalcopyrite crystalline structure is a non-centrosymmetric semiconductor. Thus, our experimental results pointed out two 2 PA allowed bands located at 715 nm (2hv = 3.47 eV) and 625 nm (2hv = 3.97 eV) with cross sections of (6.3 ± 1.0) x 102 GM and (4.5 ± 0.7) x 102 GM, respectively. According to the theoretical model, these 2 PA bands can be ascribed to the 1P1/2(h3) → 1S3/2(e) (lower energy band) and 1P1/2(hheavy) → 1S3/2(e) (90%)/(10%)1P1/2(hsplit-off) → 1P3/2(e) (higher energy band) excitonic transitions. A good agreement (magnitude and spectral position) between the experimental and theoretical data were obtained. However, our experimental data suggest that the higher-energy 2 PA band may have other contributions due to the mixing between the heavy- and the light-hole bands, which the effective mass model does not take into consideration

Il fenomeno delle dipendenze nella ASL della Provincia di Lecco. Dati anno 2009

---Il Report analizza il fenomeno delle dipendenze nella ASL della provincia di Lecco. La descrizione del fenomeno si sviluppa intorno all\u27analisi degli indicatori individuati dall\u27Osservatorio Europeo delle Dipendenze di Lisbona (OEDT): 1-uso di sostanze nella popolazione generale (questo indicatore va a rilevare i comportamenti nei confronti di alcol e sostanze psicoattive da parte della popolazione generale); 2-prevalenza d\u27uso problematico delle sostanze psicoattive; 3-domanda di trattamento degli utilizzatori di sostanze; 4-mortalit? degli utilizzatori di sostanze; 5-malattie infettive. Altri due importanti indicatori che si stanno sviluppando, e che vengono qui illustrati, sono l\u27analisi delle Schede di Dimissione Ospedaliera (SDO) e gli indicatori relativi alle conseguenza sociali dell\u27uso di droghe (criminalit? droga correlata). Inoltre sono state applicate diverse metodologie standard di stima sia per quantificare la quota parte sconosciuta di utilizzatori di sostanze che non afferiscono ai servizi, sia per identificarne alcune caratteristiche

Serologic evidence of occupational exposure to avian influenza viruses at the wildfowl/poultry/human interface

Ecological interactions between wild aquatic birds and outdoor-housed poultry can enhance spillover events of avian influenza viruses (AIVs) from wild reservoirs to domestic birds, thus increasing the related zoonotic risk to occupationally exposed workers. To assess serological evidence of AIV infection in workers operating in Northern Italy at the wildfowl/poultry interface or directly exposed to wildfowl, serum samples were collected between April 2005 and November 2006 from 57 bird-exposed workers (BEWs) and from 7 unexposed controls (Cs), planning three sample collec-tions from each individual. Concurrently, AIV surveillance of 3587 reared birds identified 4 AIVs belonging to H10N7, H4N6 and H2N2 subtypes while serological analysis by hemagglutination inhibition (HI) assay showed recent infections caused by H1, H2, H4, H6, H10, H11, H12, and H13 subtypes. Human sera were analyzed for specific antibodies against AIVs belonging to antigenic subtypes from H1 to H14 by using HI and virus microneutralization (MN) assays as a screening and a confirmatory test, respectively. Overall, antibodies specific to AIV-H3, AIV-H6, AIV-H8, and AIV-H9 were found in three poultry workers (PWs) and seropositivity to AIV-11, AIV-H13—still detectable in October 2017—in one wildlife professional (WP). Furthermore, seropositivity to AIV-H2, accounting for previous exposure to the “extinct” H2N2 human influenza viruses, was found in both BEWs and Cs groups. These data further emphasize the occupational risk posed by zoonotic AIV strains and show the possible occurrence of long-lived antibody-based immunity following AIV infections in humans