Miracle-dz/UniFAR-FTUs huggingface dataset:
Achieving trustworthy Homomorphic Encryption by combining it with a Trusted Execution Environment

Cloud database services become very appealing solutions. They offer performance and storage capabilities that client platforms do not have. However, in order to protect the users’ confidentiality and to ensure the integrity of their computations, solutions often use one of three approaches: a) Encrypting the data prior to uploading it with some symmetric encryption; b) Using a Trusted Execution Environments (TEE) such as OS containers, Virtual Machines or Intel’s Software Guard Extension (SGX); c) using Homomorphic Encryption (HE) schemes. A newer approach, which we call the ”combined model” uses a TEE to guarantee the integrity and correctness of the database code and data, while the data itself is encrypted with some HE scheme. In this paper, we explain the combined model and we show how to use it in the context of modern Multi Party Computations (MPC) schemes. In addition, we demonstrate how to construct a voting system that leverages its capabilities.
Ultrafast and nonlinear dynamics of InAs/GaAs semiconductor quantum dot lasers

Quantum dot nanostructures are one of the best practical examples of emerging nanotechnologies hence offering superior properties as compared to their quantum well counterparts. InAs/GaAs quantum dots allow producing energy- and cost-efficient devices with outstanding temperature stability, lowest threshold current, ultrafast gain dynamics, and low amplified spontaneous emission. This paper reports on the recent achievements in ultrafast and nonlinear dynamics properties of InAs/GaAs quantum dot lasers for radar systems, wireless communications and high-speed optical communications. Passive mode-locking is shown to exhibit a great potential for microwave, millimeter-wave and Terahertz signal generation with high repetition frequency tuning and jitter reduction. The optical feedback is also used to stabilize the pulse emission leading an integrated timing jitter as low as 90 fs without consuming additional power. Lastly, multimode optical feedback dynamics of InAs/GaAs QD lasers emitting on different lasing states is also studied. In particular, a chaos free operation is observed for the first time from the ground state lasing operation.
Joint design for co-existence of MIMO radar and MIMO communication system

The paper studies the scenario in which a multiple-input multiple-output (MIMO) radar coexists with a MIMO wireless communication system in the presence of clutter. The radar space-time transmit code, the radar space-time receive filter, and the communication space-time transmit covariance matrix are jointly optimized. An iterative procedure is developed to maximize the radar output signal to interference plus noise ratio (SINR) under the constraints of the communication rate, the radar waveform similarity and the power of radar and communication. Numerical results highlight the applicability of the proposed method in different scenarios.
Verification of rendering quality from measured BTFs

One of the most important, still unsolved problems in computer graphics is the generation of predictive imagery, i.e., images that represent perfect renditions of reality. Such perfect images are required in application areas like Virtual Prototyping for making reliable decisions in the costly design development of novel products like cars and airplanes. Recently, measured material properties received significant attention since they enable generation of highly accurate images that appear to be predictive at a first glance.In this work we investigate the degree of realism that can be achieved using measured bidirectional texture functions (BTFs) by comparing photographs and rendered images at two scales. To analyze the realism of rendered images at a coarse scale, we compare the light distribution resulting from standard materials to the one from measured BTFs by automatic procedures. At a fine scale, accurate reproduction of material structures is checked by a psychophysical study. Our results show that measured BTFs lead to much more accurate results than standard materials at both scales.
Data and text mining Retrieval of Enterobacteriaceae drug targets using singular value decomposition

Motivation: The identification of potential drug target proteins in bacteria is important in pharmaceutical research for the development of new antibiotics to combat bacterial agents that cause diseases. Results: A new model that combines the singular value decomposition (SVD) technique with biological filters composed of a set of protein properties associated with bacterial drug targets and similarity to protein-coding essential genes of Escherichia coli (strain K12) has been created to predict potential antibiotic drug targets in the Enterobacteriaceae family. This model identified 99 potential drug target proteins in the studied family, which exhibit eight different functions and are proteincoding essential genes or similar to protein-coding essential genes of E.coli (strain K12), indicating that the disruption of the activities of these proteins is critical for cells. Proteins from bacteria with described drug resistance were found among the retrieved candidates. These candidates have no similarity to the human proteome, therefore exhibiting the advantage of causing no adverse effects or at least no known adverse effects on humans. Contact: rita_silverio@hotmail.com. Supplementary information: Supplementary data are available at Bioinformatics online.
Characterizing Blood-Stage Antimalarial Drug MIC Values In Vivo Using Reinfection Patterns

ABSTRACT The MIC is an essential quantitative measure of the asexual blood-stage effect of an antimalarial drug. In areas of high malaria transmission, and thus frequent individual infection, patients who are treated with slowly eliminated antimalarials become reinfected as drug concentrations decline. In the frequent relapse forms of Plasmodium vivax and in Plasmodium ovale malaria, recurrent infection occurs from relapses which begin to emerge from the liver approximately 2 weeks after the primary illness. An important determinant of the interval from starting treatment of a symptomatic infection to the patency of these recurrent infections is the in vivo concentration-response relationship and thus the in vivo MIC. Using mechanistic knowledge of parasite asexual replication and the pharmacokinetic and pharmacodynamic properties of the antimalarial drugs, a generative statistical model was derived which relates the concentration-response relationship to time of reinfection patency. This model was used to estimate the in vivo MIC of chloroquine in the treatment of Plasmodium vivax malaria.
Towards Solving the Problem of Virtual Machine Placement in Cloud Computing: A Job Classification Approach

Cloud Computing is a paradigm that delivers services by providing an access to wide range of shared resources which are hosted in cloud data centers. One of the recent challenges in this paradigm is to enhance the energy efficiency in these data centers. In this study, a model that identifies common patterns for the jobs submitted to the cloud is proposed. This model is able to predict the type of the job submitted and accordingly, the set of users’ jobs is classified into four subsets. Each subset contains jobs that have similar requirements. In addition to the jobs’ common pattern and requirements, the users’ history is considered in the jobs’ type prediction model. The goal of job classification is to find a way to propose useful strategy that helps to improve power efficiency. Based on the process of jobs’ classification, the best fit virtual machine is allocated to each job. Then, the virtual machines are placed on the physical machines according to a novel strategy, called Mixed Type Placement strategy. The core idea of the proposed strategy is to place virtual machines of the jobs of different types in the same physical machine whenever possible. The placement process is based on Multi Choice Knapsack Problem which is a generalization of the classical Knapsack Problem. This is because different types of jobs do not intensively use the same compute or storage resources in the physical machine. This strategy minimizes the number of active physical machines which, in turn, leads to major reduction in the total energy consumption in the data center. The total execution time and the cost of executing the jobs submitted are considered in the placement process. To evaluate the performance of the proposed strategy, the CloudSim simulator is used with a real workload trace to simulate the cloud computing environment. The results show that the proposed strategy outperform both Genetic Algorithm and Round Robin from energy efficiency perspective.
Information Mining from Health Protection Data Against Mosquitoes

West Nile Virus (WNV) first time appeared in 2012 in the Regional District of Xanthi in Greece in Northern Eastern Greece and in total 63 cases were reported between 2012-2014. The Region of Eastern Macedonia and Thrace (EMTh) conducted a mosquito and vector control program. In this study, we apply three different data mining techniques to data about 314 households and concerned 2014. They were analyzed using the classification algorithm PART, the clustering algorithm k-means and the association rule mining algorithm, Apriori from the WEKA data mining package. The results indicate that the infected persons have some common characteristics. Hopefully, this aims to generate detailed knowledge of household use of insecticide consumer products to kill mosquitoes, the factors that affect the use of these products. The findings indicate that there is room for improvement towards the self protection methods against mosquitoes.
Baicalein disturbs the morphological plasticity and motility of breast adenocarcinoma cells depending on the tumor microenvironment

During tumor invasion, cancer cells change their morphology and mode of migration based on communication with the surrounding environment. Numerous studies have indicated that paracrine interactions from non‐neoplastic cells impact the migratory and invasive properties of cancer cells. Thus, these interactions are potential targets for anticancer therapies. In this study, we showed that the flavones member baicalein suppresses the motility of breast cancer cells that is promoted by paracrine interactions. First, we identified laminin‐332 (LN‐332) as a principle paracrine factor in conditioned medium from mammary epithelium‐derived MCF10A cells that regulates the morphology and motility of breast adenocarcinoma MDA‐MB‐231 cells. Then, we carried out a morphology‐based screen for small compounds, which showed that baicalein suppressed the morphological changes and migratory activity of MDA‐MB‐231 cells that were induced by conditioned medium from MCF10A cells and LN‐332. We also found that baicalein caused narrower and incomplete lamellipodia formation in conditioned medium‐treated MDA‐MB‐231 cells, although actin dynamics downstream of Rho family small GTPases were unaffected. These results suggest the importance of mammary epithelial cells in the cancer microenvironment promoting the migratory activity of breast adenocarcinoma cells and show a novel mechanism through which baicalein inhibits cancer cell motility.
Intact first- and second-order false belief reasoning in a patient with severely impaired grammar

Abstract The retention of first-order theory of mind (ToM) despite severe loss of grammar has been reported in two patients with left hemisphere brain damage (Varley & Siegal, 2000; Varley, Siegal, & Want, 2001). We report a third, and more detailed, case study. Patient PH shows significant general language impairment, and severe grammatical impairment similar to that reported in previous studies. In addition we were able to show that PH's impairment extends to grammatical constructions most closely related to ToM in studies of children (embedded complement clauses and relative clauses). Despite this, PH performed almost perfectly on first-order false belief tasks and on a novel nonverbal second-order false belief task. PH was also successful on a novel test of “ToM semantics” that required evaluation of the certainty implied by different mental state terms. The data strongly suggest that grammar is not a necessary source of structure for explicit ToM reasoning in adults, but do not rule out a critical role for “ToM semantics. ” In turn this suggests that the relationship observed between grammar and ToM in studies of children is the result of an exclusively developmental process.
The Antecedents and Consequences of Health Literacy in an Ecological Perspective: Results from an Experimental Analysis

This study analyses the relationship between the antecedents and consequences of health literacy (HL) at the ecological level among the nations involved in the European Health Literacy Survey (HLS-EU). The antecedents and consequences were investigated by means of proxy indicators. The HL was measured using the 47-item HLS-EU questionnaire (HLS-EUQ47) and the Newest Vital Sign (NVS). The two measures stood in significant correlation to the outcomes of the sub-discipline of the Euro Health Consumer Index (r = 0.790 for HLS-EUQ47; r = 0.789 for NVS). The HLS-EUQ47 also stood in correlation to the percentage of population with post-secondary education (r = 0.810), the reading performance for 15-year-old students (r = 0.905), the presence of a national screening program for breast (r = 0.732) or cervical cancer (r = 0.873). The NVS stood in correlation with the unemployment rate (r = −0.778), the Gross Domestic Product (r = 0.719), the Gini coefficient (r = −0.743), the rank of the Euro Patient Empowerment Index (r = −0.826), the expenditure on social protection (r = 0.814), the Consumer Empowerment Index (r = 0.898), the percentage of adults using the internet for seeking health information (r = 0.759), the prevalence of overweight individuals (r = −0.843), the health expenditure (r = 0.766), as well as the percentage of individuals using the internet for interacting with public authorities (r = 0.755). This study provides some preliminary considerations regarding alternative means by which to study HL and proposes new methods for experimentation. The methods and the results could offer a means by which the relationship between society and overall healthcare protection could be strengthened.
Using 1-Hz GPS Data to Measure Deformations Caused by the Denali Fault Earthquake

The 3 November 2002 moment magnitude 7.9 Denali fault earthquake generated large, permanent surface displacements in Alaska and large-amplitude surface waves throughout western North America. We find good agreement between strong ground-motion records integrated to displacement and 1-hertz Global Positioning System (GPS) position estimates collected ∼140 kilometers from the earthquake epicenter. One-hertz GPS receivers also detected seismic surface waves 750 to 3800 kilometers from the epicenter, whereas these waves saturated many of the seismicinstruments in the same region. High-frequency GPS increases the dynamic range and frequency bandwidth of ground-motion observations, providing another tool for studying earthquake processes.
RobLoP: Towards Robust Privacy Preserving Against Location Dependent Attacks in Continuous LBS Queries

With the increasing popularity of location-based services (LBS), how to preserve one’s location privacy has become a key issue to be concerned. The commonly used approach $k$ -anonymity, originally designed for protecting a user’s snapshot location privacy, inherently fails to preserve the user from location-dependent attacks (LDA) that include the maximum movement boundary (MMB) attacks and maximum arrival boundary (MAB) attacks, when the user continuously requests LBS. This paper presents RobLoP, a robust location privacy preserving algorithm against LDA in continuous LBS queries. The key insight of RobLoP is to theoretically derive the constraints of both MMB and MAB in a uniform way. It provides a necessary condition of the pairwise user to be safely cloaked against LDA. On top of that, RobLoP first identifies those candidate users who can be cloaked with the requesting user. RobLoP then searches for a so-called strict point set including the candidate set and other auxiliary points, as a sufficient condition under which RobLoP can finally generate the cloaked region successfully. To the best of our knowledge, RobLoP is the first work that can preserve location privacy against LDA thoroughly and closely with a theoretical guarantee. The effectiveness and superiority of RobLoP to state-of-the-art studies are validated via extensive simulations on the real trucks data, the synthetic data, as well as the measured data collected by ourselves.
Improving Character-Based Decoding Using Target-Side Morphological Information for Neural Machine Translation

Recently, neural machine translation (NMT) has emerged as a powerful alternative to conventional statistical approaches. However, its performance drops considerably in the presence of morphologically rich languages (MRLs). Neural engines usually fail to tackle the large vocabulary and high out-of-vocabulary (OOV) word rate of MRLs. Therefore, it is not suitable to exploit existing word-based models to translate this set of languages. In this paper, we propose an extension to the state-of-the-art model of Chung et al. (2016), which works at the character level and boosts the decoder with target-side morphological information. In our architecture, an additional morphology table is plugged into the model. Each time the decoder samples from a target vocabulary, the table sends auxiliary signals from the most relevant affixes in order to enrich the decoder’s current state and constrain it to provide better predictions. We evaluated our model to translate English into German, Russian, and Turkish as three MRLs and observed significant improvements.
Three dimensional carbon-bubble foams with hierarchical pores for ultra-long cycling life supercapacitors

Design and synthesis of integrated, interconnected porous structures are critical to the development of high-performance supercapacitors. We develop a novel and facile synthesis technic to construct three-dimensional carbon-bubble foams with hierarchical pores geometry. The carbon-bubble foams are fabricated by conformally coating, via catalytic decomposition of ethanol, a layer of carbon coating onto the surfaces of pre-formed ZnO foams and then the removal of the ZnO template by a reduction-evaporation process. Both the wall thickness and the pore size can be well tuned by adjusting the catalytic decomposition time and temperature. The as-synthesized carbon-bubble foams electrode retains 90.3% of the initial capacitance even after 70 000 continuous cycles under a high current density of 20 A g−1, demonstrating excellent long-time electrochemical and cycling stability. The symmetric device displays rate capability retention of 81.8% with the current density increasing from 0.4 to 20 A g−1. These achieved electrochemical performances originate from the unique structural design of the carbon-bubble foams, which provide not only abundant transport channels for electron and ion but also high active surface area accessible by the electrolyte ions.
Distinct Patterns of Reduced Prefrontal and Limbic Gray Matter Volume in Childhood General and Internalizing Psychopathology

Reduced gray matter volume (GMV) is widely implicated in psychopathology, but scholars have found mostly overlapping areas of GMV reduction across disorders rather than unique neural signatures, potentially due to pervasive comorbidity. GMV reductions may be associated with broader psychopathology dimensions rather than specific disorders. We used an empirically supported bifactor model consisting of common psychopathology and internalizing- and externalizing-specific factors to evaluate whether latent psychopathology dimensions yield a clearer, more parsimonious pattern of GMV reduction in prefrontal and limbic/paralimbic areas implicated in individual disorders. A community sample of children (N = 254, ages 6–10) was used to evaluate whether GMV reductions could constitute early neural risk factors. The common psychopathology factor was associated with reduced GMV in prefrontal areas (dorsal, orbitofrontal, ventrolateral). The internalizing-specific factor was related to reduced GMV in limbic/paralimbic areas (hippocampus, amygdala, insula). No significant associations were found between GMV and the externalizing-specific factor after accounting for common psychopathology.
Obesity suppresses tumor attributable PSA, affecting risk categorization.

Obesity is linked with more aggressive prostate cancer and higher rates of disease recurrence post treatment. It is unclear if this is due to specific tumor-promoting effects of obesity or diagnostic bias. Patients undergoing prostatectomy were categorized according to their body mass index (BMI). Expected prostate-specific antigen (PSA) levels were calculated for each patient based on tumor characteristics. The effect of obesity on the accuracy of pre-treatment risk categorization was determined, and mediation analysis was used to identify the contribution of biologic vs non-biologic mechanisms to the observed increased risk of biochemical recurrence. Residual tumor-promoting effects were estimated in a survival model controlling for diagnostic error. The following results were obtained. The analysis included 1587 patients. Despite similar rates of adverse pathological features at prostatectomy, biochemical recurrence rates were significantly higher in very obese patients, which persisted after adjustment for stage, grade and PSA. Tumor volume however correlated significantly with BMI (P = 0.004), and the difference in predicted and observed 'tumor-attributable' PSA (Delta-PSA) in very obese patients was greater than three times higher than that of healthy patients (P = 0.0067). Regression analysis indicated that the effect of BMI on tumor volume was fully mediated indirectly by its effect on PSA. Inclusion of this diagnostic error as a covariate in the survival analysis attenuated the effect of BMI on recurrence. In conclusion, being very obese suppresses tumor-associated PSA resulting in a diagnostic bias that is responsible for errors in risk classification, and potentially contributes to a delay in initial presentation.
Spanish Night : Attitudinal Analysis From a Short-Term STEM Intervention Targeting the Hispanic / Latino Community

Over the past two decades, many sources have pointed to the growing divide between the science, technology, engineering, and mathematics (STEM) infrastructure and the corresponding labor force arising from the educational apparatus of the United States (Jackson, 2002; Porter & Stern, 1999; President’s Council of Advisors on Science and Technology (PCAST), 2012). Given the ever-increasing technological nature of human society, producing scholars and practitioners of STEM fields is important for geo-political stability, progress, and the environmental health of the planet. Said simply, what was once Jackson’s (2002) “quiet crisis” has now become a center stage issue in the American dialogue: schools are doubling down on STEM majors, alternative educational pipelines are cropping up (e.g., App Academy in San Francisco), and national initiatives are working to get more young people excited about programming (e.g., Code.org’s “Hour of Code”). Together, these initiatives are working to ‘disquiet’ and allay the STEM crisis in America – to close the ‘million scientist shortfall’ mentioned in the 2012 President’s Council of Advisors on Science and Technology (PCAST) report.