Spacecraft rendezvous by differential drag under uncertainties

At low Earth orbits, differentials in the drag forces between spacecraft can be used for controlling their relative motion in the orbital plane. Current methods for determining the drag force may result in errors due to inaccuracies in the density models and drag coefficients. In this work, a methodology for relative maneuvering of spacecraft based on differential drag, accounting for uncertainties in the drag model, is proposed. A dynamical model composed of the mean semimajor axis and the argument of latitude is used for describing long-range maneuvers. For this model, a linear quadratic regulator is implemented, accounting for the uncertainties in the drag force. The actuation is the pitch angle of the satellites, considering saturation. The control scheme guarantees asymptotic stability of the system up to a certain magnitude of the state vector, which is determined by the uncertainties. Numerical simulations show that the method exhibits consistent robustness to accomplish the maneuvers, even in the presence of realistic modeling of density fields, drag coefficients, the corotation of the atmosphere, and zonal harmonics up to J(8)

Spacecraft Proximity Navigation and Autonomous Assembly based on Augmented State Estimation: Analysis and Experiments

AIAA Guidance, Navigation, and Control Conference 2 - 5 August 2010, Toronto, Ontario CanadaThis paper presents a spacecraft relative navigation scheme based on a tracking technique. The augmented state estimation technique is a variable-dimension filtering approach, originally introduced by Bar-Shalom and Birmiwal [1]. In this technique, the state model for a target spacecraft is augmented by introducing, as extra state components, the target's control inputs. The maneuver, modeled as accelerations, is estimated recursively along with the other states associated with position and velocity, while a target maneuvers. By using the proposed navigation method, a chaser spacecraft can estimate the relative position, the attitude and the control inputs of a target spacecraft, flying in its proximity. It is assumed that the chaser spacecraft is equipped with on-board sensors able to measure the relative position and relative attitude of the target spacecraft. The available sensors would provide a measurement update sample time of the order of one second and be subject to random measurement interruption longer than one second. As preliminary analysis, this work introduces the technique applied to the planar, three-degree-of-freedom, spacecraft relative motion. The proposed approach is validated via hardware-in-the-loop experimentation, using four autonomous three-degree-of-freedom robotic spacecraft simulators, floating on a flat floor. The proposed navigation method is proved to be more robust than a standard Kalman Filter estimating relative position and attitude only

The Primacy of High b-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer

Predicting clinically significant prostate cancer (csPCa) is crucial in PCa management. 3T-magnetic resonance (MR) systems may have a novel role in quantitative imaging and early csPCa prediction, accordingly. In this study, we develop a radiomic model for predicting csPCa based solely on native b2000 diffusion weighted imaging (DWIb2000) and debate the effectiveness of apparent diffusion coefficient (ADC) in the same task. In total, 105 patients were retrospectively enrolled between January–November 2020, with confirmed csPCa or ncsPCa based on biopsy. DWIb2000 and ADC images acquired with a 3T-MRI were analyzed by computing 84 local first-order radiomic features (RFs). Two predictive models were built based on DWIb2000 and ADC, separately. Relevant RFs were selected through LASSO, a support vector machine (SVM) classifier was trained using repeated 3-fold cross validation (CV) and validated on a holdout set. The SVM models rely on a single couple of uncorrelated RFs (ρ < 0.15) selected through Wilcoxon rank-sum test (p ≤ 0.05) with Holm–Bonferroni correction. On the holdout set, while the ADC model yielded AUC = 0.76 (95% CI, 0.63–0.96), the DWIb2000 model reached AUC = 0.84 (95% CI, 0.63–0.90), with specificity = 75%, sensitivity = 90%, and informedness = 0.65. This study establishes the primary role of 3T-DWIb2000 in PCa quantitative analyses, whilst ADC can remain the leading sequence for detection

A 64-Channel 965-μW Neural Recording SoC with UWB Wireless Transmission in 130-nm CMOS

This brief presents a 64-channel neural recording system-on-chip (SoC) with a 20-Mb/s wireless telemetry. Each channel of the analog front end consists of a low-noise bandpass amplifier, featuring a noise efficiency factor of 3.11 with an input-referred noise of 5.6 μVrms in a 0.001- to 10-kHz band and a 31.25-kSps 6-fJ/conversion-step 10-bit SAR analog-to-digital converter. The recorded signals are multiplexed in the digital domain and transmitted via an 11.7% efficiency pulse-position modulation ultrawideband transmitter, reaching a transmission range in excess of 7.5 m. The chip has been fabricated in a 130-nm CMOS process, measures 25 mm2, and dissipates 965 μW from a 0.5-V supply. This SoC features the lowest power per channel (15 μW) and the lowest energy per bit (48.2 pJ) among state-of-the-art wireless neural recording systems with a number of channels larger than 32. The proposed circuit is able to transmit the raw neural signal in a large bandwidth (up to 10 kHz) without performing any data compression or losing vital information, such as local field potentials

Lost in the Middle: How Language Models Use Long Contexts

While recent language models have the ability to take long contexts as input, relatively little is known about how well the language models use longer context. We analyze language model performance on two tasks that require identifying relevant information within their input contexts: multi-document question answering and key-value retrieval. We find that performance is often highest when relevant information occurs at the beginning or end of the input context, and significantly degrades when models must access relevant information in the middle of long contexts. Furthermore, performance substantially decreases as the input context grows longer, even for explicitly long-context models. Our analysis provides a better understanding of how language models use their input context and provides new evaluation protocols for future long-context models.Comment: 15 pages, 17 figure

Stigma toward schizophrenia : do all psychiatrists behave the same? Latent profile analysis of a national sample of psychiatrists in Brazil

Background: An important issue concerning the worldwide fight against stigma is the evaluation of psychiatrists’ beliefs and attitudes toward schizophrenia and mental illness in general. However, there is as yet no consensus on this matter in the literature, and results vary according to the stigma dimension assessed and to the cultural background of the sample. The aim of this investigation was to search for profiles of stigmatizing beliefs related to schizophrenia in a national sample of psychiatrists in Brazil. Methods: A sample of 1414 psychiatrists were recruited from among those attending the 2009 Brazilian Congress of Psychiatry. A questionnaire was applied in face-to-face interviews. The questionnaire addressed four stigma dimensions, all in reference to individuals with schizophrenia: stereotypes, restrictions, perceived prejudice and social distance. Stigma item scores were included in latent profile analyses; the resulting profiles were entered into multinomial logistic regression models with sociodemographics, in order to identify significant correlates. Results: Three profiles were identified. The “no stigma” subjects (n = 337) characterized individuals with schizophrenia in a positive light, disagreed with restrictions, and displayed a low level of social distance. The “unobtrusive stigma” subjects (n = 471) were significantly younger and displayed the lowest level of social distance, although most of them agreed with involuntary admission and demonstrated a high level of perceived prejudice. The “great stigma” subjects (n = 606) negatively stereotyped individuals with schizophrenia, agreed with restrictions and scored the highest on the perceived prejudice and social distance dimensions. In comparison with the first two profiles, this last profile comprised a significantly larger number of individuals who were in frequent contact with a family member suffering from a psychiatric disorder, as well as comprising more individuals who had no such family member. Conclusions: Our study not only provides additional data related to an under-researched area but also reveals that psychiatrists are a heterogeneous group regarding stigma toward schizophrenia. The presence of different stigma profiles should be evaluated in further studies; this could enable anti-stigma initiatives to be specifically designed to effectively target the stigmatizing group

Automation of one-loop QCD corrections

We present the complete automation of the computation of one-loop QCD corrections, including UV renormalization, to an arbitrary scattering process in the Standard Model. This is achieved by embedding the OPP integrand reduction technique, as implemented in CutTools, into the MadGraph framework. By interfacing the tool so constructed, which we dub MadLoop, with MadFKS, the fully automatic computation of any infrared-safe observable at the next-to-leading order in QCD is attained. We demonstrate the flexibility and the reach of our method by calculating the production rates for a variety of processes at the 7 TeV LHC.Comment: 64 pages, 12 figures. Corrected the value of m_Z in table 1. In table 2, corrected the values of cross sections in a.4 and a.5 (previously computed with mu=mtop/2 rather than mu=mtop/4). In table 2, corrected the values of NLO cross sections in b.3, b.6, c.3, and e.7 (the symmetry factor for a few virtual channels was incorrect). In sect. A.4.3, the labeling of the four-momenta was incorrec

Geographic distance, water circulation and environmental conditions shape the biodiversity of Mediterranean rocky coasts

11 páginas, 2 tablas, 3 figuras.Ecological connectivity is important for effective marine planning and biodiversity conservation. Our aim was to identify factors important in influencing variation in benthic community structure on shallow rocky reefs in 2 regions of the Mediterranean Sea with contrasting oceanographic regimes. We assessed beta (β) diversity at 146 sites in the littoral and shallow sublittoral from the Adriatic/Ionian Seas (eastern region) and Ligurian/Tyrrhenian Seas (western region) using a null modelling approach to account for variation in species richness. The distance decay relationship between species turnover within each region and geographic distance by sea was determined using generalised linear models. Mantel tests were used to examine correlations between β diversity and connectivity by ocean currents, estimated from Lagrangian dispersal simulations. Variation in β diversity between sites was partitioned according to environmental and spatial components using a distance-based redundancy approach. Species turnover along a gradient of geographic distance was greater by a factor of 3 to 5 in the western region than the eastern region, suggesting lower connectivity between sites. β diversity was correlated with connectivity by ocean currents at both depths in the eastern region but not in the western region. The influOPEN ACCESS ence of spatial and environmental predictors of β diversity varied considerably between regions, but was similar between depths. Our results highlight the interaction of oceanographic, spatial and environmental processes influencing benthic marine β diversity. Persistent currents in the eastern region may be responsible for lower observed β diversity compared to the western region, where patterns of water circulation are more variable.This work was supported by the European Community’s 7th Framework Programme (FP7/ 2007−2013) under Grant Agreement No. 287844 for the project ‘Towards COast to COast NETworks of marine protected areas (from the shore to the high and deep sea), coupled with sea-based wind energy potential (CoCoNet)’.Peer reviewe