Unforgeable Noise-Tolerant Quantum Tokens

The realization of devices which harness the laws of quantum mechanics represents an exciting challenge at the interface of modern technology and fundamental science. An exemplary paragon of the power of such quantum primitives is the concept of "quantum money". A dishonest holder of a quantum bank-note will invariably fail in any forging attempts; indeed, under assumptions of ideal measurements and decoherence-free memories such security is guaranteed by the no-cloning theorem. In any practical situation, however, noise, decoherence and operational imperfections abound. Thus, the development of secure "quantum money"-type primitives capable of tolerating realistic infidelities is of both practical and fundamental importance. Here, we propose a novel class of such protocols and demonstrate their tolerance to noise; moreover, we prove their rigorous security by determining tight fidelity thresholds. Our proposed protocols require only the ability to prepare, store and measure single qubit quantum memories, making their experimental realization accessible with current technologies.Comment: 18 pages, 5 figure

Developing a spatiotemporal model to integrate landslide susceptibility and critical rainfall conditions. A practical model applied to Rio de Janeiro municipality

Despite being a landscape evolution element, landslides pose a significant threat to infrastructure, property, and human life around the globe. In Brazil, this has been a major source of concern for many years. Over the last decades, especially in the humid areas of Brazil, landslide occurrences have become more frequent and catastrophic (Pelech et al., 2019). Especially in large and medium-sized cities, poorly-regulated living conditions and a progressing global warming scenario will likely increase the frequency, magnitude, and possibly damagecaused by landslides (Marengo et al., 2021). On the other hand, despite the efforts of local authorities to forecast and mitigate the phenomena, not enough is currently being done in terms of preparedness for future events, especially concerning research (Dias et al., 2021).Due to the geomorphological and climatic settings, the municipality of Rio de Janeiro (~1,200 km²) is often affected by landslides (Coelho Netto et al., 2007; 2009). According to the Brazilian Institute of Geography and Statistics (IBGE, 2021), the municipality has 6.7 million inhabitants, of which circa 20-25% lives in the favelas. These communities, usually located on hill slopes, face diverse challenges such as poor basic infrastructure, lack of sanitation systems, and high criminality, which tend to diminish the inhabitants’ awareness of potential landslide hazards. On the other hand, the municipality of Rio de Janeiro has systematically tracked rainfall data for the last decades. Such data comprises 33 stations, recording measurements every 15 minutes. Rainfall data is availablefor a few decades and comprise 33 stations recording measurements every 15 minutes. Also, the availability of high-resolution DTM and DEM (obtained through LiDAR with a 15 cm resolution), orthoimagery updated quasiyearly, and a suitable landslide inventory, turns Rio de Janeiro into a promising real-life laboratory for suggesting and enhancing modeling solutions that may provide valuable tools for landslide emergency preparedness, management, and response.Building upon the findings of Steger et al, 2022, the present research represents a joint effort to suggest a methodological framework to develop a dynamic landslide model that integrates static predisposing factors with dynamic rainfall conditions. Data-driven methods (e.g., Generalized Additive Models) will be used to establish statistical relationships between the static factors, the dynamic rainfall conditions prior to a potential landslide, and the landslide occurrence in space and time. The outcomes may be used by stakeholders to strategically prepare for potential rainfall events leading to landslides and possibly to improve early warning systems. Data collection and preparation are currently happening, and the analysis will follow. Partial results will be presented at the 6th World Landslide Forum

Ensuring confidence in predictions: A scheme to assess the scientific validity of in silico models

The use of in silico tools within the drug development process to predict a wide range of properties including absorption, distribution, metabolism, elimination and toxicity has become increasingly important due to changes in legislation and both ethical and economic drivers to reduce animal testing. Whilst in silico tools have been used for decades there remains reluctance to accept predictions based on these methods particularly in regulatory settings. This apprehension arises in part due to lack of confidence in the reliability, robustness and applicability of the models. To address this issue we propose a scheme for the verification of in silico models that enables end users and modellers to assess the scientific validity of models in accordance with the principles of good computer modelling practice. We report here the implementation of the scheme within the Innovative Medicines Initiative project “eTOX” (electronic toxicity) and its application to the in silico models developed within the frame of this project

Validation of the Subtle and Blatant Racism Scale for Asian American College Students (SABR-A 2 )

This investigation describes the validation of a measure of perceived racism developed to assess racial experiences of Asian American college students. In three studies across two different regions of the United States, there was strong evidence for the validation of the 8-item Subtle and Blatant Racism Scale for Asian American College Students (SABR-A 2 ). The subtle racism subscale refers to instances of discrimination attributable implicitly to racial bias or stereotype, whereas the blatant racism subscale refers to instances of discrimination attributable explicitly to racial bias or stereotype. The two-subscale structure of the SABR-A 2 was supported by exploratory and confirmatory factor analyses and demonstrated discriminant, convergent, and incremental validity, as well as internal reliability and stability over 2 weeks

Cryobiopsy increases the EGFR detection rate in non-small cell lung cancer

Objectives: Detection of activating epidermal growth factor receptor (EGFR) mutation is crucial for individualized treatment of advanced non-small-cell lung cancer (NSCLC). However little is known about how biopsy technique affects the detection rate of EGFR mutations. This retrospective, single center study evaluated the detection rate of EGFR mutations in tissue obtained by bronchoscopic cryobiopsy and compared this to other standard tissue sampling techniques. Materials and methods: We retrospectively analyzed 414 patients with histologically confirmed NSCLC and known EGFR mutation status between 3/2008-7/2014. Tumor specimens obtained by tissue preserving bronchoscopic cryobiopsy were compared to those obtained by other techniques. Results and conclusion: Analysis of bronchoscopic cryobiopsy tissue detected 29 activating EGFR mutations in 27 (21.6 ) out of 125 patients, while analysis of tissue obtained by non-cryobiopsy techniques (bronchoscopic forceps biopsies, fine needle aspiration, imaging guided transthoracical and surgical procedures) detected 42 EGFR mutations in 40 (13.8 ) out of 298 patients (p < 0.05). Cryobiopsy increased detection rate of EGFR mutations in central tumors compared with forceps biopsy (19.6 versus 6.5 , p < 0.05), while an insignificant trend was detected also for peripheral tumors (33.3 versus 26.9 ). Bronchosopic cryobiopsy increases the detection rate of activating EGFR mutations in NSCLC in comparison to other tissue sampling techniques. This will help to optimize individualized treatment of patients with advanced tumors. Because of the retrospective nature of this analysis, a prospective trial is mandatory for final assessment. © 2020 The Author(s

Top Radiative Corrections in Non-minimal Standard Models

We derive the one-loop effective action induced by a heavy top in models with an extended Higgs sector. We use the effective action to analyze the top corrections to the $\rho$ parameter and to the Higgs-gauge boson couplings. We show that in models with $\rho\not=1$ at tree-level, one does not lose generally the bound on $m_t$ from the $\rho$ parameter.Comment: 9 pages, phyzzx file, UPR-0603T. (a new reference has been added

Meaning in life is associated with the psychopathology of eating disorders: differences depending on the diagnosis.

Previous studies indicated that meaning in life was inversely associated with eating behaviors and a negative attitude toward food, body satisfaction, and borderline symptoms. However, research on the association between meaning in life and eating disorder psychopathology is scarce, and there are no studies on the association between meaning in life and the eating disorder psychopathology depending on the diagnosis. The aim of the present study is to verify whether meaning in life is differentially associated with a broad range of psychopathology symptoms commonly observed in people with ED, depending on the diagnosis, in a sample of 240 ED patients. We found that meaning in life was negatively associated with eating behaviors and a negative attitude toward food, body satisfaction, borderline symptoms, and hopelessness in all types of eating disorders, regardless of the specific diagnosis. Moreover, the association with meaning in life was different depending on the type of eating disorders. Specifically in the participants with Anorexia Nervosa Restrictive, meaning in life had a higher percentage of explained variance in the eating disorders psychopathology (between 30%-65%). Therefore, these results seem to indicate that, although meaning in life is an important variable in all the eating disorders subtypes, it is especially relevant in participants with the Anorexia Nervosa Restrictive subtype

Numerical aerodynamic simulation of the space shuttle ascent environment

After the STS 51-L accident, an extensive review of the Space Shuttle Orbiter's ascent aerodynamic loads uncovered several questionable areas that required further analysis. The insight gained by comparing the Shuttle ascent CFD numerical simulations, obtained by the NASA Ames Space Shuttle Flow Simulation Group, to the current IVBC-3 aerodynamic loads database was instrumental in resolving uncertainties on the Orbiter payload bay doors and fuselage. Initial confidence in the numerical simulations was gained by comparing them with the limited flight data that had been obtained during the Orbiter Flight Test (OFT) program. Current CFD results exist for Mach numbers 0.6, 0.9, 1.05, 1.55, 2.0, and 2.5. Since the pre STS-1 wind tunnel test program (IA-105) often yields considerable differences when compared to STS-5 flight data, the M(sub infinity) = 1.05 transonic case is the most investigated. The IA308 mated-vehicle hot gas plume wind tunnel test, recently completed at AEDC 16T (transonic) and Lewis (hypersonic), is also used to compare with the computation where applicable

MaxDIA enables library-based and library-free data-independent acquisition proteomics

MaxDIA is a software platform for analyzing data-independent acquisition (DIA) proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves deep proteome coverage with substantially better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate (FDR) estimates on both library-to-DIA match and protein levels, including when using whole-proteome predicted spectral libraries. This is the foundation of discovery DIA-hypothesis-free analysis of DIA samples without library and with reliable FDR control. MaxDIA performs three- or four-dimensional feature detection of fragment data, and scoring of matches is augmented by machine learning on the features of an identification. MaxDIA's bootstrap DIA workflow performs multiple rounds of matching with increasing quality of recalibration and stringency of matching to the library. Combining MaxDIA with two new technologies-BoxCar acquisition and trapped ion mobility spectrometry-both lead to deep and accurate proteome quantification. The software platform MaxDIA streamlines analysis of data-independent acquisition proteomics