Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Fidelity Multi-Rotor Unmanned Aircraft System (UAS) Simulation Development for Trajectory Prediction Under Off-Nominal Flight Dynamics

The NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) project is conducting research to enable civilian low-altitude airspace and UAS operations. A goal of this project is to develop probabilistic methods to quantify risk during failures and off-nominal flight conditions. An important part of this effort is the reliable prediction of feasible trajectories during off-nominal events such as control failure, atmospheric upsets, or navigation anomalies that can cause large deviations from the intended flight path or extreme vehicle upsets beyond the normal flight envelope. Few examples of high-fidelity modeling and prediction of off-nominal behavior for small UAS (sUAS) vehicles exist, and modeling requirements for accurately predicting flight dynamics for out-of-envelope or failure conditions are essentially undefined. In addition, the broad range of sUAS aircraft configurations already being fielded presents a significant modeling challenge, as these vehicles are often very different from one another and are likely to possess dramatically different flight dynamics and resultant trajectories and may require different modeling approaches to capture off-nominal behavior. NASA has undertaken an extensive research effort to define sUAS flight dynamics modeling requirements and develop preliminary high-fidelity six degree-of-freedom (6-DOF) simulations capable of more closely predicting off-nominal flight dynamics and trajectories. This research has included a literature review of existing sUAS modeling and simulation work as well as development of experimental testing methods to measure and model key components of propulsion, airframe and control characteristics. The ultimate objective of these efforts is to develop tools to support UTM risk analyses and for the real-time prediction of off-nominal trajectories for use in the UTM Risk Assessment Framework (URAF). This paper focuses on modeling and simulation efforts for a generic quad-rotor configuration typical of many commercial vehicles in use today. An overview of relevant off-nominal multi-rotor behaviors will be presented to define modeling goals and to identify the prediction capability lacking in simplified models of multi-rotor performance. A description
Multiplex bead-based measurement of humoral immune responses against tumor-associated antigens in stage II melanoma patients of the EORTC18961 trial

ABSTRACT Purpose: Determine the prognostic and predictive significance of tumor associated antigen (TAA)-specific serum antibodies in melanoma patients of a large adjuvant vaccination phase III trial. Patients and methods: Serum IgG antibodies were measured against a panel of 43 antigens by a bead-based multiplex assay in 970 stage II melanoma patients of the EORTC18961 trial, evaluating adjuvant ganglioside GM2-KLH/QS-21 vaccination versus observation. Primary end point was relapse-free survival (RFS). Patients' sera at baseline, after 12 and 48 weeks of study treatment and at the last available time point (at recurrence/remission) were evaluated. Results: Prognostic clinical variables are gender, surgical confirmation of lymph node-negative status, Breslow thickness and ulceration of the primary. Prognostic spontaneous antibody responses were associated with a significant dismal (GM2, Rhod_E2, SSX2) or good prognosis (CyclinB1, SCYE1v1) for RFS, distant metastasis-free (DMFS) or overall survival (OS). Predictive spontaneous antibody responses based on significant interaction with treatment were RhodN p = 0.02, Rab38 p = 0.04 for RFS, RhodE2 p = 0.006, Recoverin p = 0.04 for DMFS and RhodE2 p = 0.003; Recoverin p = 0.04, NA17.A p = 0.04, for OS respectively. The subgroups of patients according to antibody responses for RFS were determined for RhodN sero-negative (n = 849, HR = 1.07, p = 0.6); RhodN sero-positive (n = 121,HR = 0.42, p = 0.01) and Rab38 sero-negative (n = 682, HR = 1.12, p = 0.42), Rab38 sero-positive (n = 288, HR = 0.65, p = 0.04) patients respectively. Conclusion: We identified prognostic serum antibody responses against TAA in stage II melanoma patients. A set of antibody responses correlated with a beneficial outcome for GM2 vaccination.
Synthesizing cloth wrinkles by CNN‐based geometry image superresolution

We propose a novel deep learning‐based method, called mesh superresolution, to enrich low‐resolution (LR) cloth meshes with wrinkles. A pair of low and high‐resolution (HR) meshes are simulated, with the simulation of the HR mesh tracks with that of the LR mesh. The frame data are converted into geometry images and used as a training data set. A residual network, called SR residual network, is employed to train an image synthesizer that superresolves an LR image into an HR one. Once the HR image is converted back to an HR mesh, it is abundant in wrinkles compared with its coarse counterpart. The synthesizing is very efficient and is 24× faster than a full HR simulation. We demonstrate the performances of mesh superresolution with various simulation scenes.
Stealthy Opaque Predicates in Hardware - Obfuscating Constant Expressions at Negligible Overhead

Opaque predicates are a well-established fundamental building block for software obfuscation. Simplified, an opaque predicate implements an expression that provides constant Boolean output, but appears to have dynamic behavior for static analysis. Even though there has been extensive research regarding opaque predicates in software, techniques for opaque predicates in hardware are barely explored. In this work, we propose a novel technique to instantiate opaque predicates in hardware, such that they (1) are resource-efficient, and (2) are challenging to reverse engineer even with dynamic analysis capabilities. We demonstrate the applicability of opaque predicates in hardware for both, protection of intellectual property and obfuscation of cryptographic hardware Trojans. Our results show that we are able to implement stealthy opaque predicates in hardware with minimal overhead in area and no impact on latency.
Asymmetry Helps: Improved Private Information Retrieval Protocols for Distributed Storage

We consider private information retrieval (PIR) for distributed storage systems (DSSs) with noncolluding nodes where data is stored using a non maximum distance separable (MDS) linear code. It was recently shown that if data is stored using a particular class of non-MDS linear codes, the MDS-PIR capacity, i.e., the maximum possible PIR rate for MDS-coded DSSs, can be achieved. For this class of codes, we prove that the PIR capacity is indeed equal to the MDS-PIR capacity, giving the first family of non-MDS codes for which the PIR capacity is known. For other codes, we provide asymmetric PIR protocols that achieve a strictly larger PIR rate compared to existing symmetric PIR protocols.
Morphology, Nucleation, and Isothermal Crystallization Kinetics of Poly(Butylene Succinate) Mixed with a Polycarbonate/MWCNT Masterbatch

In this study, nanocomposites were prepared by melt blending poly(butylene succinate) (PBS) with a polycarbonate (PC)/multi-wall carbon nanotubes (MWCNTs) masterbatch, in a twin-screw extruder. The nanocomposites contained 0.5, 1.0, 2.0, and 4.0 wt% MWCNTs. Differential scanning calorimetry (DSC), small angle X-ray scattering (SAXS) and wide angle X-ray scattering (WAXS) results indicate that the blends are partially miscible, hence they form two phases (i.e., PC-rich and PBS-rich phases). The PC-rich phase contained a small amount of PBS chains that acted as a plasticizer and enabled crystallization of the PC component. In the PBS-rich phase, the amount of the PC chains present gave rise to increases in the glass transition temperature of the PBS phase. The presence of two phases was supported by scanning electron microscopy (SEM) and atomic force microscopy (AFM) analysis, where most MWCNTs aggregated in the PC-rich phase (especially at the high MWCNTs content of 4 wt%) and a small amount of MWCNTs were able to diffuse to the PBS-rich phase. Standard DSC scans showed that the MWCNTs nucleation effects saturated at 0.5 wt% MWCNT content on the PBS-rich phase, above this content a negative nucleation effect was observed. Isothermal crystallization results indicated that with 0.5 wt% MWCNTs the crystallization rate was accelerated, but further increases in MWCNTs loading (and also in PC content) resulted in progressive decreases in crystallization rate. The results are explained by increased MWCNTs aggregation and reduced diffusion rates of PBS chains, as the masterbatch content in the blends increased.
How Glycerol and Water Contents Affect the Structural and Functional Properties of Starch-Based Edible Films

As starch is an inexpensive, filmogenic, easily processable and a widely available material, it is a material that can be utilized in the creation of biodegradable films and containers, presenting as a viable alternative to polymers derived from petrol. Moreover, starch could also be used to create edible coatings for fresh foods in order to extend shelf life. As such, wheat starch films with two glycerol contents were formulated to mimic the effects of compounds currently used to coat fruit. Their structural and functional properties were characterized. This study found that the transfer properties of starch films containing 33% of plasticizer was less effective than film comprised of 50% glycerol. Water diffusivity, oxygen permeability, and water vapor permeability at two different humidity gradients, surface tension, works of surface adhesion and cohesion, and moisture sorption were tested. Glycerol content does not play a significant role on the color or mechanical properties. This work shows that glycerol can strongly affect the functional properties of starch-based coatings and films.
Pathophysiology and Diagnosis of Pulmonary Hypertension Due to Left Heart Disease

Pulmonary hypertension due to left heart disease (PH-LHD) is the most common type of pulmonary hypertension, although an accurate prevalence is challenging. PH-LHD includes PH due to systolic or diastolic left ventricular dysfunction, mitral or aortic valve disease and congenital left heart disease. In recent years a new and distinct phenotype of “combined post-capillary and pre-capillary PH,” based on diastolic pulmonary gradient and pulmonary vascular resistance, has been recognized. The roles of right ventricular dysfunction and pulmonary vascular compliance in PH-LHD have also been elucidated recently and they appear to have significant clinical implications. Echocardiography continues to play a seminal role in diagnosis of PH-LHD and heart failure with preserved LV ejection fraction, as it can identify valve disease and help to distinguish PH-LHD from pre-capillary PH. Right, and occasionally left heart catheterization, remains the gold-standard for diagnosis and phenotyping of PH-LHD, although Cardiac Magnetic Resonance Imaging is emerging as a useful alternative tool in non-invasive diagnostic and prognostic assessment of PH-LHD. In this review, the latest evidence for more recent advances will be discussed, including the role of fluid challenge and exercise during cardiac catheterization to unravel occult post-capillary and the role of vasoreactivity testing. The use of many or all of these diagnostic techniques will undoubtedly provide key information about sub-groups of patients with PH-LHD that might benefit from medical therapy previously considered to be only suitable for pulmonary arterial hypertension.
A Systematic Mapping Study on Security in Agile Requirements Engineering

[Background] The rapidly changing business environments in which many companies operate is challenging traditional Requirements Engineering (RE) approaches. This gave rise to agile approaches for RE. Security, at the same time, is an essential non-functional requirement that still tends to be difficult to address in agile development contexts. Given the fuzzy notion of "agile" in context of RE and the difficulties of appropriately handling security requirements, the overall understanding of how to handle security requirements in agile RE is still vague. [Objective] Our goal is to characterize the publication landscape of approaches that handle security requirements in agile software projects. [Method] We conducted a systematic mapping to outline relevant work and contemporary gaps for future research. [Results] In total, we identified 21 studies that met our inclusion criteria, dated from 2005 to 2017. We found that the approaches typically involve modifying agile methods, introducing new artifacts (e.g., extending the concept of user story to abuser story), or introducing guidelines to handle security issues. We also identified limitations of using these approaches related to environment, people, effort and resources. [Conclusion] Our analysis suggests that more effort needs to be invested into empirically evaluating the existing approaches and that there is an avenue for future research in the direction of mitigating the identified limitations.
On the Evolution of Technical Lag in the npm Package Dependency Network

Software packages developed and distributed through package managers extensively depend on other packages. These dependencies are regularly updated, for example to add new features, resolve bugs or fix security issues. In order to take full advantage of the benefits of this type of reuse, developers should keep their dependencies up to date by relying on the latest releases. In practice, however, this is not always possible, and packages lag behind with respect to the latest version of their dependencies. This phenomenon is described as technical lag in the literature. In this paper, we perform an empirical study of technical lag in the npm dependency network by investigating its evolution for over 1.4M releases of 120K packages and 8M dependencies between these releases. We explore how technical lag increases over time, taking into account the release type and the use of package dependency constraints. We also discuss how technical lag can be reduced by relying on the semantic versioning policy.
Algal Colonization of Young Arctic Sea Ice in Spring

The importance of newly formed sea ice in spring is likely to increase with formation of leads in a more dynamic Arctic icescape. We followed the ice algal species succession in young ice (≤0.27 m) in spring at high temporal resolution (sampling every second day for one month in May–June 2015) in the Arctic Ocean north of Svalbard. We document the early development of the ice algal community based on species abundance and chemotaxonomic marker pigments, and relate the young-ice algal community to the communities in the under-ice water column and the surrounding older ice. The seeding source seemed to vary between algal groups. Dinoflagellates were concluded to originate from the water column and diatoms from the surrounding older ice, which emphasizes the importance of older ice as a seeding source over deep oceanic regions and in early spring when algal abundance in the water column is low. In total, 120 taxa (80 identified to species or genus level) were recorded in the young ice. The protist community developed over the study period from a ciliate, flagellate and dinoflagellate dominated community to one dominated by pennate diatoms. Environmental variables such as light were not a strong driver for the community composition, based on statistical analysis and comparison to the surrounding thicker ice with low light transmission. The photoprotective carotenoids to Chl a ratio increased over time to levels found in other high-light habitats, which shows that the algae were able to acclimate to the light levels of the thin ice. The development into a pennate diatom-dominated community, similar to the older ice, suggests that successional patterns tend towards ice-associated algae fairly independent of environmental conditions like light availability, season or ice type, and that biological traits, including morphological and physiological specialization to the sea ice habitat, play an important role in colonization of the sea ice environment. However, recruitment of ice-associated algae could be negatively affected by the ongoing loss of older ice, which acts as a seeding repository.
Programming: Further Factors that Influence Success

This paper revisits five previous studies spanning a decade, which were used in the development and validation of a computational model named PreSS (Predict Student Success) to predict student success in an introductory programming module with 80% accuracy. PreSS was initially developed over three studies from 2004 – 2006, recording data from 240 students across multiple institutions incorporating three studies. These studies examined 25 factors and six machine learning algorithms, resulting in a model that used only three factors and the naïve Bayes machine learning algorithm (coupled with multiple other statistical techniques) called PreSS. The authors completed two subsequent independent studies over the academic years 20132015 that were used to investigate if the PreSS model was still valid on a modern data set while also collecting new data (factors) that were not considered during the initial development of PreSS. These two studies successfully validated PreSS, even with a decade separating the student profiles and landscapes. This paper has two main objectives; the first objective is an investigation on factors gathered during the initial development of PreSS that were not used in the final model. This is important as several factors were found to be significant at the time but were excluded as their associated sample size was small and the goal was to develop the most generalizable model possible. PreSS is arguably a universal model for two reasons. 1) PreSS is independent of the programming language used. PreSS has been so far been exposed to 6 different programming languages that include: Java, C#, Processing, Python, Visual Basic and C++ and still maintained the same high level of accuracy. 2) PreSS is also independent of any specifics of the cohort sampled such as gender bias, institution bias, age bias etc. The second objective of this paper is an examination of additional data collected in two recent independent studies, to determine if incorporating some or all of these new factors could improve the accuracy of PreSS. This paper reports on 90 experiments using data from all five previous studies, examining 126 possible factors. The work successfully identified 16 factors that when used in combination with the original PreSS factors either produced significant increases in prediction accuracy or exhibited noteworthy findings. Some of the 16 factors produced substantial gains in accuracy (in some cases in excess of 8%) or when integrated into the PreSS model, revealed interesting substitutions of factors.
TS-NET: Combining Modality Specific and Common Features for Multimodal Patch Matching

Multimodal patch matching addresses the problem of finding the correspondences between image patches from two different modalities, e.g. RGB vs sketch or RGB vs near-infrared. The comparison of patches of different modalities can be done by discovering the information common to both modalities (Siamese like approaches) or the modality-specific information (Pseudo-Siamese like approaches). We observed that none of these two scenarios is optimal. This motivates us to propose a three-stream architecture, dubbed as TS-Net, combining the benefits of the two. In addition, we show that adding extra constraints in the intermediate layers of such networks further boosts the performance. Experimentations on three multimodal datasets show significant performance gains in comparison with Siamese and Pseudo-Siamese networks† †Codes and resources available at http://github.com/ensv/TS-Net.
Completely Independent Spanning Trees in k-Th Power of Graphs

Abstract Let T1, T2, . , Tk be spanning trees of a graph G. For any two vertices u, v of G, if the paths from u to v in these k trees are pairwise openly disjoint, then we say that T1, T2, . , Tk are completely independent. Araki showed that the square of a 2-connected graph G on n vertices with n ≥ 4 has two completely independent spanning trees. In this paper, we prove that the k-th power of a k-connected graph G on n vertices with n ≥ 2k has k completely independent spanning trees. In fact, we prove a stronger result: if G is a connected graph on n vertices with δ(G) ≥ k and n ≥ 2k, then the k-th power Gk of G has k completely independent spanning trees.
Boredom-Driven Curious Learning by Homeo-Heterostatic Value Gradients

This paper presents the Homeo-Heterostatic Value Gradients (HHVG) algorithm as a formal account on the constructive interplay between boredom and curiosity which gives rise to effective exploration and superior forward model learning. We offer an instrumental view of action selection, in which an action serves to disclose outcomes that have intrinsic meaningfulness to an agent itself. This motivated two central algorithmic ingredients: devaluation and devaluation progress, both underpin agent's cognition concerning intrinsically generated rewards. The two serve as an instantiation of homeostatic and heterostatic intrinsic motivation. A key insight from our algorithm is that the two seemingly opposite motivations can be reconciled—without which exploration and information-gathering cannot be effectively carried out. We supported this claim with empirical evidence, showing that boredom-enabled agents consistently outperformed other curious or explorative agent variants in model building benchmarks based on self-assisted experience accumulation.
Mitochondria and Mood: Mitochondrial Dysfunction as a Key Player in the Manifestation of Depression

Human and animal studies suggest an intriguing link between mitochondrial diseases and depression. Although depression has historically been linked to alterations in monoaminergic pharmacology and adult hippocampal neurogenesis, new data increasingly implicate broader forms of dampened plasticity, including plasticity within the cell. Mitochondria are the cellular powerhouse of eukaryotic cells, and they also regulate brain function through oxidative stress and apoptosis. In this paper, we make the case that mitochondrial dysfunction could play an important role in the pathophysiology of depression. Alterations in mitochondrial functions such as oxidative phosphorylation (OXPHOS) and membrane polarity, which increase oxidative stress and apoptosis, may precede the development of depressive symptoms. However, the data in relation to antidepressant drug effects are contradictory: some studies reveal they have no effect on mitochondrial function or even potentiate dysfunction, whereas other studies show more beneficial effects. Overall, the data suggest an intriguing link between mitochondrial function and depression that warrants further investigation. Mitochondria could be targeted in the development of novel antidepressant drugs, and specific forms of mitochondrial dysfunction could be identified as biomarkers to personalize treatment and aid in early diagnosis by differentiating between disorders with overlapping symptoms.