Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Framework for Simulating Computing Infrastructure and Network Data Flows Targeted on Cloud Computing

Understanding how computing infrastructure decisions influence overall performance and cost can be very difficult. Simulation techniques are an important tool to help analyse and evaluate different infrastructure configurations and deployment scenarios. As diversity of cloud computing resources is growing, the space of possible infrastructure configurations becomes larger and finding the best solution becomes harder. In our previous paper, we presented a framework to benchmark cloud resources to obtain objective and comparable results. Based on those results, our simulation framework allows to model applications and to estimate their performance. Compared to other infrastructure or cloud simulation tools our framework excels when it comes to the simulation of network data flows.
Robust Scale-Free Synthesis for Frequency Control in Power Systems

The ac frequency in electrical power systems is conventionally regulated by synchronous machines. The gradual replacement of these machines by asynchronous renewable-based generation, which provides little or no frequency control, increases system uncertainty and the risk of instability. This imposes hard limits on the proportion of renewables that can be integrated into the system. In this paper, we address this issue by developing a framework for performing frequency control in power systems with arbitrary mixes of conventional and renewable generation. Our approach is based on a robust stability criterion that can be used to guarantee the stability of a full power system model on the basis of a set of decentralized tests, one for each component in the system. It can be applied even when using detailed heterogeneous component models, and can be verified using several standard frequency response, state-space, and circuit theoretic analysis tools. Furthermore, the stability guarantees hold independently of the operating point, and remain valid even as components are added to and removed from the grid. By designing decentralized controllers for individual components to meet these decentralized tests, every component can contribute to the regulation of the system frequency in a simple and provable manner. Notably, our framework certifies the stability of several existing (nonpassive) power system control schemes and models, and allows for the study of robustness with respect to delays.
Imaging CSEM data in the presence of electrical anisotropy - eScholarship

IMAGING CSEM DATA IN THE PRESENCE OF ELECTRICAL ANISOTROPY Gregory A. Newman * , Michael Commer * and James J. Carazzone + Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley California ExxonMobil Upstream Research Company, Houston Texas Email: ganewman@lbl.gov ABSTRACT Formation anisotropy should be incorporated into the analysis of controlled source electromagnetic (CSEM) data because failure to do so can produce serious artifacts in the resulting resistivity images for certain data configurations of interest. This finding is demonstrated in model and case studies. Sensitivity to horizontal resistivity will be strongest in the broadside electric field data where detectors are offset from the tow line. Sensitivity to the vertical resistivity is strongest for over flight data where the transmitting antenna passes directly over the detecting antenna. Consequently, consistent treatment of both over flight and broadside electric field measurements requires an anisotropic modeling assumption. To produce a consistent resistivity model for such data we develop and employ a 3D CSEM imaging algorithm that treats transverse anisotropy. The algorithm is based upon non-linear conjugate gradients and full wave equation modeling. It exploits parallel computing systems to effectively treat 3D imaging problems and CSEM data volumes of industrial size. Here we use it to demonstrate the anisotropic imaging process on model and field data sets from the North Sea and offshore Brazil. We also verify that isotropic imaging of over flight data alone produces an image generally consistent with the vertical resistivity. However, superior data fits are obtained when the same over flight data are analyzed assuming an anisotropic resistivity model.
Lending Without Creditor Rights, Collateral, or Reputation: The “Trusted Assistant” Loan in 19th Century China

This paper considers lending to finance projects in a setting where repayment enforcement appears impossible. The loan was illegal and thus legally unenforceable. Creditors were incapable of applying private coercion to force repayment. Borrowers lacked both collateral and reputation capital. Project cash flows were unobservable. The projects were the acquisition of Imperial administrative posts by scholars in nineteenth century Qing China. The lending mechanism was the “trusted-assistant loan. ” Our model of trusted-assistant lending shows that it is a renegotiation-proof implementation of efficient state dependent financing. Empirical analysis of officials’ diaries and bank records shows that the employment of trusted-assistant lending and the performance of trusted-assistant loans conforms roughly with the model’s predictions.
Embedding of Egocentric Action Videos in Semantic-Visual Graph

Introduction An egocentric camera captures rich and varied information of how the wearer interacts with their environment. The challenge for the visual understanding of this information is currently significant and not only limited by the enormous variety of such interactions but also by limitations in the current visual description (e.g. those rooted in motion or appearance) for distinguishing interactions. Supervised training, provided by labelled examples, alleviates some of these ambiguities by including information about the object being used (e.g. ‘click-mouse’ vs ‘pick-up phone’), or perhaps less interestingly, by limiting the study to interactions that can be distinguished from one another (e.g. open vs drink). Several datasets [6, 5, 3, 2] and methods [5, 8, 7] have attempted supervised object interaction recognition from egocentric videos. While these works differ in the features used and classification techniques adopted, they all assume a semantically distinct set of pre-selected verbs or verb-noun combinations in the ground-truth. Annotators are expected to assign a video segment to one of these preselected labels. When free annotations were used, from audio scripts [1] or textual annotations [2], a majority vote is used to select a single verb for each action class. Other annotations are treated as outliers, even when they represent a meaningful and correct annotation of a video segment. In this ongoing work, we treat each free annotation as a valid description of an object interaction. For example, for one interaction such as lifting an object from a workspace,
On The Computational Complexity Of Bi-Clustering

In this work we formalize a new natural objective (or cost) function for biclustering Monochromatic bi-clustering. Our objective function is suitable for detecting meaningful homogenous clusters based on categorical valued input matrices. Such problems have arisen recently in systems biology where researchers have inferred functional classifications of biological agents based on their pairwise interactions. We analyze the computational complexity of the resulting optimization problems. We show that finding optimal solutions is NP-hard and complement this result by introducing a polynomial time approximation algorithm for this bi-clustering task. This is the first positive approximation guarantee for bi-clustering algorithms. We also show that bi-clustering with our objective function can be viewed as a generalization of correlation clustering.
Knowledge, attitude and practice of nursing students Dezful university of medical sciences towards evidence-based nursing in the second semester of the academic year 2017-2018

Introduction: Nowadays The health care systems around the world face many challenges and in many cases, health care is accompanied by many question Therefore, evidence-based practice, as an essential factor for improving health care is more emphasis. This study aimed to investigate the knowledge and attitude of nursing students of Dezful university of medical sciences toward evidence-based nursing. Method: This descriptive-analytical study was conducted in the second semester of the academic year of 2017-2018 at the Faculty of Nursing and Midwifery of Dezful university of medical sciences. The data collection tool was a standard questionnaire "Knowledge, attitude and practice of undergraduate nursing students about evidence-based practice". Data were analyzed using descriptive and analytical statistics in SPSS software. Results: The results showed that knowledge and attitude toward evidence-based practice with access to medical evidence from the Internet (p = 0/001, r = 0/273) and journal clubs (p = 0/000, r = 0 / 306) and the use of reference books and referring to them (p = 0/000, r = 0/401), there is a statistically significant relationship (p=0/01, r=0/277). This means that the mean scores of knowledge and attitudes among students most in search of scientific evidence in various ways (internet and journal clubs and reference books), as well as easier access to evidence, were significantly higher than other students. Conclusion: Evidence-based nursing is a process that is Emphasis on the latest findings will take the best decisions in order to raise the quality of care. Therefore, it is better for students to become fully acquainted with this concept and learn it. although The students' attitudes toward evidence-based practice was moderate; But with proper planning educational reforms in the education of nursing students, can be an important step in the development and promotion of evidence-based practice picked up.
Food Expenditure, Food Preparation Time and Household Economies of Scale

This paper is concerned with the effect of household size on the allocation of household money and time to food consumption. A broad literature has examined household economies of scale. Since food is a private good, it might be expected that larger households, which could economize on shared goods such as housing, would spend more per equivalent household member on food. However, recent studies have found the opposite result: for households with similar total expenditures, larger families spend less per capita on food. This paper examines household time inputs and shows that economies of scale in preparing food can explain this result. I introduce economies of scale into a household production model. The size of the household changes both the relative price of a unit of food and the time required to prepare it, affecting household demand for both inputs to food production. Larger households can achieve the same level of consumption at lower expenditure by substituting cheaper production time for more expensive ingredients. Using household expenditure and time-use survey data from Russia, I estimate the effect of changing household size on food expenditures and food-related time. The estimates indicate that doubling the size of household reduces per capita food expenditure by over 30% and per capita preparation time by about 75% in households with two and more people. A married man from a two adult household spends three times less time preparing food than a single man living alone. For a woman, a transition from a single to a two-person households results in more modest time saving of 45% in case such transition is not a result of a marriage. A married woman enjoys no time savings at all, while a woman with children spends more time in food-related activities than her single counterparts. I also find that the time intensity of meals increases with household size, but that the quality of meals is unaffected by changes in household size.
Listening is Seeing : Effects of Auditory Load on Inattentional Blindness

Inattentional blindness (IB) is the failure to notice an unexpected, yet obvious, visual stimulus due to focused attention on another task. This study sought to examine the effects of auditory load on IB and if IB increases in concordance with cognitive load between medium and high auditory load conditions. Participants were asked to view an IB video showing cards being dealt that had been paired with either music or music with embedded tones. They were asked to count the number of cards and report if they saw anything unusual in the video. The results indicate that as auditory load increases, IB increases. These results seem to indicate that there is a limit to attentional abilities, at which point unexpected events go unnoticed and that a trend of increasing IB can be seen in conformity with increasing cognitive load.
Stirring and transport enhancement in a continuously modulated free-surface flow

The transport of fluid from a recirculation region adjacent to a free surface is studied using a numerical method validated with experimental flow visualization. The flow is an example of a liquid film coating process, and consists of two counter-rotating rolls placed side-by-side and half-submerged in a bath of fluid. In the gap between the rolls a recirculation zone exists just below the free surface, around which the flow splits into two films. Fluid recirculating for long periods has been identified as a source of coating defects, so this paper considers a possible method of inducing stirring. The flow is modulated by driving one of the rolls through a Hooke's joint, which delivers a well-characterized periodic perturbation to the roll speed. In response to this speed modulation, the free surface undergoes a periodic change in position and shape which drives an exchange of fluid between the recirculation region and the surrounding flow. The amplitude of the free-surface motion is strongly dependent on modulation frequency. The dynamics of the free surface preclude a quasi-steady approach, even in the small-frequency limit, and so a fully time-dependent analysis based on the finite element method is employed. Trigonometric temporal interpolation of the finite element data is used to make passive tracer advection calculations more efficient, and excellent agreement is seen between simulation and experiment. Computations of the stable and unstable invariant manifolds associated with periodic points on the free surface reveal that the exchange of fluid is governed by a self-intersecting turnstile mechanism, by which most fluid entrained during a modulation cycle is ejected later in the same cycle. Transport over several cycles is explored by observation of the evacuation of passive tracers initially distributed uniformly in the recirculation zone. Results demonstrate the persistence of unmixed cores whose size is dependent on the modulation frequency. By considering the percentage of tracers remaining after a fixed number of cycles, contours in frequency–amplitude space show that for each modulation amplitude there is a frequency which produces the most effective transport, with up to 80 % of tracers removed by a modulation which produces only a 5 % change in film thickness. Finally it is shown how modulation of both rolls at slightly different phases can reduce the film thickness variation to about 1 % while maintaining the level of transport.
Spin-resolved photoemission of a ferromagnetic Mn5Ge3(0001) epilayer on Ge(111)

Here we present a study of the electronic structure of epitaxial ferromagnetic Mn5Ge3(0001) films on Ge(111) by means of x-ray absorption spectroscopy, x-ray photoelectron spectroscopy, and spin-resolved photoelectron spectroscopy. Spin-polarization (P) value of +(15±5)% at the Fermi energy (EF) is measured with a photon energy of hν=21.2 eV. Our findings are in contrast to recent band structure calculations, predicting P=−41% at EF for the ferromagnetic bulk Mn5Ge3.
To Follow the Targets , Follow the Reward : A Reinforcement Learning Approach to Multi-Target Tracking with a Multi-Function Radar

Two key concepts in radar systems that make them effective in air and missile defense are multi-target tracking and multi-function radar, in which a radar allocates some of its resources to detecting new targets (”scan”) while also placing beams to follow already-acquired targets (”track”). Over the past half-century, various disjointed approaches have been developed separately for the resource allocation problem between track vs. scan, for the data-association problem (i.e. how to accurately assign detections to the correct track), where to schedule beams for the multi-target tracking, and how to deconflict those scheduling priorities. This project will propose a Reinforcement Learning approach to the joint problem of resource allocation and data association, given specified long-term objectives. The advantage of an RL approach is that it does not need to be targetdynamics or environment-specific, like some of the traditional methods: it could learn on-line if the reward function is appropriately designed to be interpretable from a real-world environment without a global reference truth. Our focus will be the formulation of an MDP and one or more PartiallyObservable Markov Decision Process (POMDP) to capture the problem that can be solved with an on-policy learning methods for MDP and modified for POMDPs. The aim will be fourfold:
Remote Sensing of Cloud Droplet Radius Profiles using solar
reflectance from cloud sides. Part I: Retrieval development and
characterization

Abstract. Convective clouds play an essential role for Earth's climate as well as for regional weather events since they have a large influence on the radiation budget and the water cycle. In particular, cloud albedo and the formation of precipitation are influenced by aerosol particles within clouds. In order to improve the understanding of processes from aerosol activation, over cloud droplet growth to changes in cloud radiative properties, remote sensing techniques become more and more important. While passive retrievals for spaceborne observations have become sophisticated and commonplace to infer cloud optical thickness and droplet size from cloud tops, profiles of droplet size have remained largely uncharted territory for passive remote sensing. In principle they could be derived from observations of cloud sides, but faced with with the small-scale structure of cloud sides, classical passive remote sensing techniques are rendered inappropriate. In this work the feasibility is demonstrated to gain new insights into the vertical evolution of cloud droplet effective radius by using reflected solar radiation from cloud sides. Central aspect of this work on its path to a working cloud side retrieval is the analysis of the impact unknown cloud surface geometry has on effective radius retrievals. Using extensive 3D radiative transfer calculations on the basis of realistic droplet size resolving cloud simulations, the sensitivity of reflected solar radiation to cloud droplet size is examined. Sensitivity is enhanced by considering the pixel surrounding to resolve ambiguities caused by illumination and cloud geometry. Based on these findings, a statistical approach is used to provide an effective radius retrieval. An in-depth sensitivity study of the presented approach on the basis of a wide range of radiative transfer test cases demonstrates the feasibility to retrieve cloud particle size profiles from cloud sides.
Effects of Swirl Bubble Injection on Mass Transfer and Hydrodynamics for Bubbly Flow Reactors: A Concept Paper

Bubble flow reactors (BFR) are commonly used for various industrial processes in the field of oil and gas production, pharmaceutical industries, biochemical and environmental engineering etc. The operation and performance of these reactors rely heavily on a range of hydrodynamic parameters; prominent among them are geometric configurations including gas injection geometry, operating conditions, mass transfer etc. A huge body of literature is available to describe the optimum design and performance of bubbly flow reactors with conventional bubble injection. Attempts were made to modify gas injection for improved efficiency of BFR's. However, here instead of modifying the geometry of the gas injection, an attempt has been made to generate swirl bubbles for gaining larger mass transfer between gas and liquid. Here an exceptionally well thought strategies have been used in our numerical simulations towards the design of swirl injection mechanism, whose paramount aspect is to inhibit the rotary liquid motion but facilitates the swirl movement for bubbles in nearly stationary liquid. Our comprehension here is that the swirl motion can strongly affect the performance of bubbly reactor by identifying the changes in hydrodynamic parameters as compared to the conventional bubbly flows. In order to achieve this bubbly flow, an experimental setup has been designed as well as computational fluid dynamic (CFD) code was used with to highlight a provision of swirl bubble injection by rotating the sparger plate.
Variations of transcript profiles between sea otters Enhydra lutris from Prince William Sound, Alaska, and clinically normal reference otters

Development of blood leukocyte gene transcript profiles has the potential to expand condition assessments beyond those currently available to evaluate wildlife health, including sea otters Enhydra lutris, both individually and as populations. The 10 genes targeted in our study represent multiple physiological systems that play a role in immuno-modulation, inflammation, cell protection, tumor suppression, cellular stress-response, xenobiotic metabolizing enzymes, and antioxidant enzymes. These genes can be modified by biological, physical, or anthropogenic impacts and consequently provide information on the general type of stressors present in a given environment. We compared gene transcript profiles of sea otters sampled in 2008 among areas within Prince William Sound impacted to varying degrees by the 1989 ‘Exxon Valdez’ oil spill with those of captive and wild reference sea otters. Profiles of sea otters from Prince William Sound showed elevated transcription in genes associated with tumor formation, cell death, organic exposure, inflammation, and viral exposure when compared to the reference sea otter group, indicating possible recent and chronic exposure to organic contaminants. Sea otters from historically designated oiled areas within Prince William Sound 19 yr after the oil spill had higher transcription of genes associated with tumor formation, cell death, heat shock, and inflammation than those from areas designated as less impacted by the spill.