Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-resource fair allocation for consolidated flash-based caching systems

Using a flash-based layer to serve the caching and buffering needs of multiple workloads has become a common practice. In such settings, resource demands will inevitably exceed available capacity sometimes. "Fair" resource allocation may offer a systematic way of partitioning resources across competing workloads during such periods of scarcity. Existing works only offer fair allocation strategies for a single resource (capacity or bandwidth) within a flash device in isolation. However, since there exist multiple critical resources that need to be partitioned within a flash device and they are correlated to each other, fair allocation of a single resource may result in a waste of other resource(s) or performance degradation of workload(s). To this end, we make a case for multi-resource fair allocation solutions for flash-based caches that consolidate multiple workloads. Furthermore, we argue that device lifetime, which depends on the behavior of running workloads, should also be considered as a first-class resource on par with capacity and bandwidth. Specifically, we build upon existing ideas related to dominant resource fairness (DRF) to devise flash-specific multi-resource fair algorithms: (i) nDRF, that jointly allocates capacity and bandwidth taking their non-linear relationship into account; (ii) ℓDRF, that explicitly considers lifetime as well in its allocation; and (iii) several variants of these. Our experimental evaluation offers important findings: (i) both nDRF and ℓDRF result in superior performance fairness compared to the state-of-the-art techniques that partition capacity in isolation; (ii) ℓDRF additionally offers improved device "wear" behavior; and (iii) our algorithms combined with reasonable demand prediction work very well in online settings with workload dynamism and uncertainty.
AI-Based Intrusion Detection Systems for In-Vehicle Networks: A Survey

The Controller Area Network (CAN) is the most widely used in-vehicle communication protocol, which still lacks the implementation of suitable security mechanisms such as message authentication and encryption. This makes the CAN bus vulnerable to numerous cyber attacks. Various Intrusion Detection Systems (IDSs) have been developed to detect these attacks. However, the high generalization capabilities of Artificial Intelligence (AI) make AI-based IDS an excellent countermeasure against automotive cyber attacks. This article surveys AI-based in-vehicle IDS from 2016 to 2022 (August) with a novel taxonomy. It reviews the detection techniques, attack types, features, and benchmark datasets. Furthermore, the article discusses the security of AI models, necessary steps to develop AI-based IDSs in the CAN bus, identifies the limitations of existing proposals, and gives recommendations for future research directions.
Adapting Static Taint Analyzers to Software Marketplaces: A Leverage Point for Mass Vulnerability Detection?

Improper input validation is still one of the most severe problem classes in web application security, although there are concepts with a good problem-solution fit, such as static taint analysis. In practice, however, existing static taint analyzers suffer from both high false positive and false negative rates, making them impractical for effective detection of new vulnerabilities. In this work, we present an approach that aims to systematically specialize existing taint analyzers toward software marketplaces to improve both recall and precision of their analyses. To validate whether our approach is suitable for finding new vulnerabilities in web applications, we applied a specialized taint-analyzer to a random sample of 1,000 plugins from the WordPress plugin store. As a result, we were able to disclose ten CVE entries, including two vulnerabilities with a high or even critical CVSS score. Our preliminary results indicate the principle feasibility of our approach and show that it may be suitable for mass vulnerability detection in software marketplaces, providing a promising foundation for future works in this domain.
On the hadronic γ-ray emission from Tycho's Supernova Remnant†

Abstract Tycho is one of nearly a dozen Galactic supernova remnants which are suggested to emit hadronic γ-ray emission. Among them, however, it is the only one in which the hadronic emission is proposed to arise from the interaction with low-density ambient medium. Based on the multi-band observations, we suggest that Tycho is encountering dense cloud at the northeastern boundary. The γ-ray emissions can be explained by hadronic process with self-consistent parameters, such as a modest energy conversion efficiency. In this SNR-cloud association scenario, the distance can be estimated as ~2.5 kpc.
First passage time distribution of stationary Markovian processes

We investigate how the correlation properties of a stationary Markovian stochastic process affect its First Passage Time Distribution (FPTD). With explicit examples, in this paper we show that the tail of the first passage time distribution crucially depends on the correlation properties of the process and it is independent of its stationary distribution. When the process includes an infinite set of time-scales bounded from above, the FPTD shows tails modulated by some exponential decay. In the case when the process is power-law correlated the FPTD shows power-law tails 1/tν and therefore the moments ⟨tn⟩ of the FPTD are finite only when n<ν−1. The existence of an infinite and unbounded set of time-scales is a necessary but not sufficient condition in order to observe power-law tails in the FPTD. Finally, we give a general result connecting the FPTD of an additive stochastic processes x(t) to the FPTD of a generic process y(t) related by a coordinate transformation y=f(x) to the first one.
Reconfigurable System-on-Chip Architectures for Robust Visual SLAM on Humanoid Robots

Visual Simultaneous Localization and Mapping (vSLAM) is the method of employing an optical sensor to map the robot’s observable surroundings while also identifying the robot’s pose in relation to that map. The accuracy and speed of vSLAM calculations can have a very significant impact on the performance and effectiveness of subsequent tasks that need to be executed by the robot, making it a key building component for current robotic designs. The application of vSLAM in the area of humanoid robotics is particularly difficult due to the robot’s unsteady locomotion. This paper introduces a pose graph optimization module based on RGB (ORB) features, as an extension of the KinectFusion pipeline (a well-known vSLAM algorithm), to assist in recovering the robot’s stance during unstable gait patterns when the KinectFusion tracking system fails. We develop and test a wide range of embedded MPSoC FPGA designs, and we investigate numerous architectural improvements, both precise and approximation, to study their impact on performance and accuracy. Extensive design space exploration reveals that properly designed approximations, which exploit domain knowledge and efficient management of CPU and FPGA fabric resources, enable real-time vSLAM at more than 30 fps in humanoid robots with high energy-efficiency and without compromising robot tracking and map construction. This is the first FPGA design to achieve robust, real-time dense SLAM operation targeting specifically humanoid robots. An open source release of our implementations and data can be found in [1].
Path-Planning for Unmanned Aerial Vehicles with Environment Complexity Considerations: A Survey

Unmanned aerial vehicles (UAVs) have the potential to make a significant impact in a range of scenarios where it is too risky or too costly to rely on human labour. Fleets of autonomous UAVs, which complete tasks collaboratively while managing their basic flight and related tasks independently, present further opportunities along with research and regulatory challenges. Improvements in UAV construction and components, along with developments in embedded computing hardware, communication mechanisms and sensors which may be mounted on-board a UAV, are nearing the point where commercial deployment of fleets of autonomous UAVs will be technically possible. To fulfil this potential, UAVs will need to operate safely and reliably in complex and potentially dynamically changing environments with path-planning, obstacle sensing and collision avoidance paramount. This survey presents an original environment complexity classification and critically analyses the current state of the art in relation to UAV path-planning approaches. Moreover, it highlights the existing challenges in environment complexity modelling and representation, as well as path-planning approaches, and outlines open research questions together with future directions.
A seer knows best: optimized object storage shuffling for serverless analytics

Serverless platforms offer high resource elasticity and pay-as-you-go billing, making them a compelling choice for data analytics. To craft a "pure" serverless solution, the common practice is to transfer intermediate data between serverless functions via serverless object storage (IBM COS; AWS S3). However, prior works have led to inconclusive results about the performance of object storage, since they have left large margin for optimization. To verify that object storage has been underrated, we design a novel shuffle manager for serverless data analytics termed Seer. Specifically, Seer dynamically chooses between two shuffle algorithms to maximize performance. The algorithm choice is based on some predictive models, and very importantly, without users having to specify intermediate data sizes at the time of the job submission. We integrate Seer with PyWren-IBM [31], a serverless analytics framework, and evaluate it against both serverful (e.g., Spark) and serverless systems (e.g., Google BigQuery). Our results certify that our new shuffle manager can deliver performance improvements over them.
A Ranked Bandit Approach for Multi-stakeholder Recommender Systems

Recommender systems traditionally find the most relevant products or services for users tailored to their needs or interests but they ignore the interests of the other sides of the market (aka stakeholders). In this paper, we propose to use a Ranked Bandit approach for an online multi-stakeholder recommender system that sequentially selects top 𝑘 items according to the relevance and priority of all the involved stakeholders. We presented three different criteria to consider the priority of each stakeholder when evaluating our approach. Our extensive experimental results on a movie dataset showed that the contextual multi-armed bandits with a relevance function make a higher level of satisfaction for all involved stakeholders in the long term.
Characteristic velocities of stripped-envelope core-collapse supernova cores*

The velocity of the inner ejecta of stripped-envelope core-collapse supernovae (CC-SNe) is studied by means of an analysis of their nebular spectra. Stripped-envelope CC-SNe are the result of the explosion of bare cores of massive stars (≥8 M ⊙ ), and their late-time spectra are typically dominated by a strong [OI] λλ6300, 6363 emission line produced by the innermost, slow-moving ejecta which are not visible at earlier times as they are located below the photosphere. A characteristic velocity of the inner ejecta is obtained for a sample of 56 stripped-envelope CC-SNe of different spectral types (IIb, Ib, Ic) using direct measurements of the linewidth as well as spectral fitting. For most SNe, this value shows a small scatter around 4500 km s -1 . Observations (< 100 d) of stripped-envelope CC-SNe have revealed a subclass of very energetic SNe, termed broad-lined SNe (BL-SNe) or hypernovae, which are characterized by broad absorption lines in the early-time spectra, indicative of outer ejecta moving at very high velocity (v ≥ 0.1c). SNe identified as BL in the early phase show large variations of core velocities at late phases, with some having much higher and some having similar velocities with respect to regular CC-SNe. This might indicate asphericity of the inner ejecta of BL-SNe, a possibility we investigate using synthetic three-dimensional nebular spectra.
Quantum tomography meets dynamical systems and bifurcations theory

A powerful tool for studying geometrical problems in Hilbert spaces is developed. We demonstrate the convergence and robustness of our method in every dimension by considering dynamical systems theory. This method provides numerical solutions to hard problems involving many coupled nonlinear equations in low and high dimensions (e.g., quantum tomography problem, existence and classification of Pauli partners, mutually unbiased bases, complex Hadamard matrices, equiangular tight frames, etc.). Additionally, this tool can be used to find analytical solutions and also to implicitly prove the existence of solutions. Here, we develop the theory for the quantum pure state tomography problem in finite dimensions but this approach is straightforwardly extended to the rest of the problems. We prove that solutions are always attractive fixed points of a nonlinear operator explicitly given. As an application, we show that the statistics collected from three random orthonormal bases is enough to reconstruct pure states from experimental (noisy) data in every dimension d ⩽ 32.
Stress Relaxation in Porous GaN Prepared by UV Assisted Electrochemical Etching

This study describes the stress relaxation in porous GaN grown on Al2O3 substrates. The results indicate that the stress relaxation has taken place in the samples which increases by increasing the etching current. As compared to the as-grown GaN films, porous GaN exhibits substantial photoluminescence (PL) intensity enhancement with red-shifted band-edge peaks associated with the relaxation of the compressive stress. The red shifted phonon energy peak (E2) in the Raman spectra of the porous GaN films confirms further such a stress relaxation. Scanning electron microscopy (SEM) demonstrates that, the current density has significant effect on the size and shape of the pores.
UvA-DARE How leaders' emotional displays shape followers' organizational citizenship behavior

We examined the effects of happy and angry expressions of leaders on followers' organizational citizenship behavior (OCB). OCB involves behaviors that bene ﬁ t an organization, but fall outside of formal job requirements and reward structures (Bateman & Organ, 1983). We show that leaders'emotionaldisplaysplayaroleinencouragingordiscouragingOCB.Incontrasttoprevious evidencethatangerdisplayscanincreasefollowermotivationandin-roleperformance,Study1(a scenario study among employees of various companies) revealed a decrease in willingness to perform OCB after a leader expressed anger rather than happiness. In Study 2 (a lab experiment involving university students), participants expended less effort working overtime after being confronted with an angry rather than a happy leader. In both studies, the detrimental effects of anger were stronger when the anger was perceived as inappropriate. We conclude that anger may decrease OCB, especially when the target considers it inappropriate. © 2015 All reserved. ANOVA perceived appropriateness showed a signi ﬁ cant main effect of the leader's . 001, ɳ . 39. Participants the leader's more appropriate in the compared to the this effect was quali ﬁ ed by an When than This might enthusiastic as extra polite when they performed subpar.
The novel oligopeptide utilizing species Anaeropeptidivorans aminofermentans M3/9T, its role in anaerobic digestion and occurrence as deduced from large-scale fragment recruitment analyses

Research on biogas-producing microbial communities aims at elucidation of correlations and dependencies between the anaerobic digestion (AD) process and the corresponding microbiome composition in order to optimize the performance of the process and the biogas output. Previously, Lachnospiraceae species were frequently detected in mesophilic to moderately thermophilic biogas reactors. To analyze adaptive genome features of a representative Lachnospiraceae strain, Anaeropeptidivorans aminofermentans M3/9T was isolated from a mesophilic laboratory-scale biogas plant and its genome was sequenced and analyzed in detail. Strain M3/9T possesses a number of genes encoding enzymes for degradation of proteins, oligo- and dipeptides. Moreover, genes encoding enzymes participating in fermentation of amino acids released from peptide hydrolysis were also identified. Based on further findings obtained from metabolic pathway reconstruction, M3/9T was predicted to participate in acidogenesis within the AD process. To understand the genomic diversity between the biogas isolate M3/9T and closely related Anaerotignum type strains, genome sequence comparisons were performed. M3/9T harbors 1,693 strain-specific genes among others encoding different peptidases, a phosphotransferase system (PTS) for sugar uptake, but also proteins involved in extracellular solute binding and import, sporulation and flagellar biosynthesis. In order to determine the occurrence of M3/9T in other environments, large-scale fragment recruitments with the M3/9T genome as a template and publicly available metagenomes representing different environments was performed. The strain was detected in the intestine of mammals, being most abundant in goat feces, occasionally used as a substrate for biogas production.
Predictors of sustainment of two distinct nutrition and physical activity programs in early care and education

Introduction The goal of the present study was to investigate factors associated with sustainment of two evidence-based programs for nutrition promotion in early care and education (ECE) settings – Food Friends (FF) and Together, We Inspire Smart Eating (WISE). Materials and methods In a cross-sectional study design, ECE directors (N = 55) from centers that had previously been trained in WISE or FF completed a survey. Program-specific measures included Steckler's Perception of Innovations, the Program Sustainability Assessment Tool (PSAT), and the Organizational Readiness for Change Assessment (ORCA). For our primary outcomes, two measures of sustainment were examined: Nutrition Continued Practice (i.e., the use of or general focus on nutrition programs) and Program Fidelity (i.e., how well centers used specific evidence-based practices of WISE or FF). Multiple regression was used to determine the association of these outcomes with program, years since last implementation, and overall scores on predictors. Follow-up correlation analyses were used to investigate outcome relationships with context submeasures due to high intercorrelations between predictor submeasures. Results Nutrition Continued Practice was significantly predicted by program and overall PSAT score. WISE programs had significantly higher Nutrition Continued Practice scores than FF program (p = 0.03). All subscales of the PSAT (e.g., environmental support, funding stability, organizational capacity, program adaptation, communications, and strategic planning) were significantly correlated with Nutrition Continued Practice (all rs > 0.30, all ps < 0.03). Program Fidelity was significantly predicted by PSAT and Steckler Perception of Innovation scores. All subscales of the PSAT were strongly positively correlated with Program Fidelity (all rs > 0.48, all ps < 0.001); relative advantage (r = 0.54, p < 0.001) and level of institutionalization (r = 0.61, p < 0.001) were positively correlated with Program Fidelity. Conclusion This study suggests that factors associated with the continued practice of program principles are partially distinct from those that are associated with the sustainment of specific practices driving program fidelity. Results suggest capacity building strategies may be important for both continued attention to nutrition and physical activity as well as sustaining fidelity to specific evidence-based practices.
4 days in dry immersion increases arterial wall response to ultrasound wave as measured using radio-frequency signal, comparison with spaceflight data

Recent studies have reported a significant increase in common carotid artery (CCA) intima media thickness, wall stiffness and reflectivity to ultrasound, in astronauts, after six months of spaceflight. The hypothesis was that 4 days in dry immersion (subjects under bags of water) will be sufficient to change the CCA wall reflectivity to ultrasound similar to what observed after spaceflight. Such response would be quantified using the amplitude of the ultrasound signal returned to the probe by the target concerned. [coefficient of signal return (Rs)]. The Rs for anterior and posterior CCA wall, sternocleidomastoid muscle, intima layer and CCA lumen were calculated from the ultrasound radio frequency (RF) data displayed along each echographic line. After four days of DI, Rs increased in the CCA posterior wall (+15% +/- 10 from pre DI, p < 0.05), while no significant change was observed in the other targets. The observed increase in Rs with DI was approximately half compared to what was observed after six months of space flight (+34% +/- 14). This difference may be explained by dose response (dry immersion only four days in duration). As a marker of tissue-level physical changes, Rs provide complimentary information alongside previously observed CCA wall thickness and stiffness.
Self-consistent atmosphere modeling with cloud formation for low-mass stars and exoplanets

Context: Low-mass stars and extrasolar planets have ultra-cool atmospheres where a rich chemistry occurs and clouds form. The increasing amount of spectroscopic observations for extrasolar planets requires self-consistent model atmosphere simulations to consistently include the formation processes that determine cloud formation and their feedback onto the atmosphere. Aims: Complement the MARCS model atmosphere suit with simulations applicable to low-mass stars and exoplanets in preparation of E-ELT, JWST, PLATO and other upcoming facilities. Methods: The MARCS code calculates stellar atmosphere models, providing self-consistent solutions of the radiative transfer and the atmospheric structure and chemistry. We combine MARCS with DRIFT, a kinetic model that describes cloud formation in ultra-cool atmospheres (seed formation, growth/ evaporation, gravitational settling, convective mixing, element depletion). Results: We present a small grid of self-consistently calculated atmosphere models for $T_ \text{eff} = 2000 - 3000$ K with solar initial abundances and $\log(g) = 4.5$. Cloud formation in stellar and sub-stellar atmospheres appears for $T_\text{eff} < 2700$ K and has a significant effect on the structure and the spectrum of the atmosphere for $T_\text{eff} < 2400$ K. We have compared the synthetic spectra of our models with observed spectra and found that they fit the spectra of mid to late type M-dwarfs and early type L-dwarfs well. We also test DRIFT-MARCS for an example exoplanet and demonstrate that our simulations reproduce the Spitzer observations for WASP-19b rather well for $T_{\rm eff}=2600$ K, $\log(g)=3.2$ and solar abundances. Our model points at an exoplanet with a deep cloud-free atmosphere with a substantial day-night energy transport and no temperature inversion.