Miracle-dz/UniFAR-FTUs huggingface dataset:
Surface Integral Methods in Jet Aeroacoustics: Refraction Corrections

One of the major challenges in computational jet aeroacousties is the accurate modeling and prediction of acoustic fields to reduce and control the jet noise. Surface integral methods (e.g., the Kirchhoff method and Ffowcs Williams-Hawkings method) can be used in computational aeroacoustics to extend the near-field computational fluid dynamics results to far field. The surface integral methods can efficiently and accurately predict aerodynamically generated noise provided the control surface surrounds the entire source region. However, for jet noise prediction, shear mean flow exists outside the control surface that causes refraction. Mean flow refraction corrections for the surface integral methods have been done in the past using simple geometric acoustics. A more rigorous method based on Lilley's equation is investigated here due to its more realistic assumption of the acoustic propagation. Jet noise computational results based on large-eddy simulation for the near field of an isothermal jet at Reynolds number 400,000 are used for the evaluation of the solution on the Ffowcs Williams-Hawkings control surface. The proposed methodology for prediction of far-field sound pressure level shows that the acoustic field within the zone of silence is consistent with the measured data.
Quality of Life in Pediatric Patients with Minimal Change Disease

Objectives: This study was conducted to assess the quality of life (QOL) in children between 2 and 18 years of age with Minimal Change Disease (MCD) as the commonest variant of primary idiopathic nephrotic syndrome (NS) using validated arabic version of Pediatric Quality of Life Inventory (PedsQLTM 4.0 Generic Core Scales). Subjects: This cross-sectional comparative study was conducted in Tanta University Hospital (TUH), Pediatric nephrology inpatient unit or outpatient clinic between October 2016 and October 2017. In this questionnaire-based study, 100 children with primary idiopathic NS and an equal number of age-matched controls with other chronic diseases were included. Their clinical and demographic details were recorded and QOL was assessed using PedsQLTM 4.0 Generic Core Scales. Conclusions: The present study shows that the overall QOL in children with MCD was better than in children with other chronic illnesses.
Phrase-Level Metaphor Identification Using Distributed Representations of Word Meaning

Metaphor is an essential element of human cognition which is often used to express ideas and emotions that might be difficult to express using literal language. Processing metaphoric language is a challenging task for a wide range of applications ranging from text simplification to psychotherapy. Despite the variety of approaches that are trying to process metaphor, there is still a need for better models that mimic the human cognition while exploiting fewer resources. In this paper, we present an approach based on distributional semantics to identify metaphors on the phrase-level. We investigated the use of different word embeddings models to identify verb-noun pairs where the verb is used metaphorically. Several experiments are conducted to show the performance of the proposed approach on benchmark datasets.
Corrigendum to : Sentiment Lexica from Paired Comparisons

The sentiment scores presented by Dalitz & Bednarek in “Sentiment lexica from paired comparisons” at the ICDM Sentire workshop (2016) were based on an approximation formula by Elo that was grossly inaccurate in that particular use case. This corrigendum describes how the scores should be estimated instead and shows that these new scores are indeed a good fit to the probabilistic sentiment score model. The conclusions in the Sentire paper about the quality of the corpus based sentiment lexica SentiWS and SenticNet 3 still hold, however, because the scores obtained with the inaccurate approximation formula are similar to the correctly estimated scores when scaled with a factor, which means that the correlation is not that much affected by the error. Nevertheless, the approximate solution presented in the Sentire paper should not be used and be replaced by a numerical non-linear least squares or maximum likelihood optimization.
Integrating natural language and formal analysis for legal documents

Although much research has gone into natural language legal document analysis, practical solutions to support legal document drafting and reasoning are still limited in functionality. However given the textual basis of law there is much potential for NLP techniques to aid in the context of drafting legal documents, especially contracts. Furthermore, there is a body of work focusing on the formal semantics of norms and legal notions which has direct applications in analysis of such documents. In this paper we present our attempt to use several off-the-shelf NLP techniques to provide a more intelligent contract editing tool to lawyers. We exploit these techniques to extract information from contract clauses to allow intelligent browsing of the contract. We use this surface analysis to bridge the gap between the English text of a contract and its formal representation, which is then amenable to automated deduction, specifically it allows us to identify conflicts in the contract.
To switch or not to switch? – Understanding German consumers’ willingness to pay for green electricity tariff attributes

Background In order to achieve an environmentally friendly and sustainable energy supply, it is necessary that this goal is supported by society. In different countries worldwide it has been shown that one way consumers want to support the energy transition is by purchasing green electricity. However, few people make the leap from their intention to a buying decision. This study explores parameters that influence whether German consumers decide to switch to a green electricity tariff. Methods We conducted a quota-representative online survey including a discrete choice experiment with 371 private households in Germany in 2016. For the econometric analysis, a generalized multinomial logit model in willingness to pay space was employed, enabling the estimation of WTP values to be as realistic as possible. Results The results show that consumers’ decision regarding whether or not to make the switch to green energy is mainly influenced by the source of green energy, whether a person can outsource the switching process, and a person’s attitude towards the renewable energy sources levy that currently exists in Germany. Conclusions As our findings indicate politics should focus on supporting wind and solar energy as German consumers prefer this sources over biogas. As suggested by our results, the EEG levy is a reason why consumers have lower WTP for a switch to a green tariff. Therefore a switching bonus with a specifically “framed” bonus in the amount of the current EEG levy could be a promising strategy for the increase of green energy tariff acceptance. Furthermore, attention should be given to psychological and behavioral aspects, as our results indicate that these factors influence the consumer’s choice for a green electricity tariff.
Effect of Activation of the Ca2+-Permeable Acid-Sensing Ion Channel 1a on Acid-Induced Vascular Endothelial Cell Injury of Henoch-Schönlein Purpura Children

Acidosis in local environment plays a critical role in cell injury. One key mediator of acidosis-induced cell injury is the acid-sensing ion channels (ASICs), particularly ASIC1a. Herein, we investigated the role of ASIC1a in acid-induced vascular endothelial cell injury of Henoch-Schonlein purpura (HSP) children. Acid-induced ASIC1a, Calpain and Calcineurin expression in vascular endothelial cells pretreated with IgA1 isolated from HSP were detected by real time quantitative polymerase chain reaction and western blot methods, respectively. Cell cytotoxicity was measured by interleukin-8 and nitric oxide production with ELISA. The results showed acid-induced ASIC1a, Calpain and Calcineurin expression in cells increased, especially at PH6.5. The cytotoxicity of vascular endothelial cells was increased by extracellular acidosis. Moreover non-specific or specific blockers of ASIC1a, Amiloride and PcTX-1 could remarkably decrease these parameters. These findings show that increased [Ca2+]i, mediated via ASIC1a, might contribute to acid-induced vascular endothelial cell injury of HSP.
Managing uncertainties in urban runoff quality models: A benchmarking methodology

In this paper we present a benchmarking methodology, which aims at comparing urban runoff quality models, based on the Bayesian theory. After choosing the different configurations of models to be tested, this methodology uses the Metropolis algorithm, a general MCMC sampling method, to estimate the posterior distributions of the models' parameters. The analysis of these posterior distributions allows a quantitative assessment of the parameters' uncertainties and their interaction structure, and provides information about the sensitivity of the probability distribution of the model output to parameters. The effectiveness and efficiency of this methodology are illustrated in the context of 4 configurations of pollutants' accumulation/erosion models, tested on 4 street subcatchments. Calibration results demonstrate that the Metropolis algorithm produces reliable inferences of parameters thus, helping on the improvement of the mathematical concept of model equations.
Pre-feeding embryos of antarctic and temperate echinoderms use dissolved organic material for growth and metabolic needs

The energy reserves of eggs of marine invertebrates have been assumed to supply the metabolic needs of development unhl feeding on particles commences. This view is challenged by recent laboratory studies which show that marine invertebrate embryos of some nonarthropodan phyla are able to transport and use dissolved organic material (DOM, e.g. amino acids and fatty acids) in seawater as a source of material (energy) for metabolic needs and growth. Here we present results of experiments conducted in situ (in Antarctica and N. Pacific) and in the laboratory, which show that embryos could, in some cases, meet the metabolic costs of embryonic development and increase in organic weight (biomass) prior to being able to feed on particles. Increases in biomass of embryos of temperate species correlated with the timing of spring phytoplankton blooms. In contrast, the biomass of embryos (of temperate species) reared during periods of low primary productivity decreased, or remained constant. Phytoplankters exude DOM into seawater and these exudates are shown here to enhance embryonic growth. In most cases, there was no net use of endogenous reserves during prefeeding development; growth and energy needs were apparently met through consumption of DOM in seawater. We suggest that DOM is an important food source for embryos of soft-bodied marine invertebrates in polar and temperate oceans.
Evaluation of Continuous Membrane Chromatography Concepts with an Enhanced Process Simulation Approach

Modern biopharmaceutical products strive for small-scale, low-cost production. Continuous chromatography has shown to be a promising technology because it assures high-capacity utilization, purity and yield increases, and lower facility footprint. Membrane chromatography is a fully disposable low-cost alternative to bead-based chromatography with minor drawbacks in terms of capacity. Hence, continuous membrane chromatography should have a high potential. The evaluation of continuous processes goes often along with process modeling. Only few experiments with small feed demand need to be conducted to estimate the model parameters. Afterwards, a variety of different process setups and working points can be analyzed in a very short time, making the approach very efficient. Since the available modeling approaches for membrane chromatography modules did not fit the used design, a new modeling approach is shown. This combines the general rate model with an advanced fluid dynamic distribution. Model parameter determination and model validation were done with industrial cell cultures containing Immunoglobulin G (IgG). The validated model was used to evaluate the feasibility of the integrated Counter Current Chromatography (iCCC) concept and the sequential chromatography concept for membrane adsorber modules, starting with a laboratory-type module used for sample preparation. A case study representing a fed-batch reactor with a capacity from 20 to 2000 L was performed. Compared to batch runs, a 71% higher capacity, 48.5% higher productivity, and 38% lower eluent consumption could be achieved.
Adding integrations, saturated controls, and stabilization for feedforward systems

Our study relates to systems whose dynamics generalize x/spl dot/=h(y,u), y/spl dot/=f(y,u), where the state components x integrate functions of the other components y and the inputs u. We give sufficient conditions under which global asymptotic stabilizability of the y subsystem (respectively, by saturated control) implies global asymptotic stabilizability of the overall system (respectively, by saturated control). It is obtained by constructing explicitly a control Lyapunov function and provides feedback laws with several degrees of freedom which can be exploited to tackle design constraints. Also, we study how appropriate changes of coordinates allow us to extend its domain of application. Finally, we show how the proposed approach serves as a basic tool to be used, in a recursive design, to deal with more complex systems. In particular the stabilization problem of the so-called feedforward systems is solved this way.
Interactive Segmentation of Medical Images: A Survey

Image segmentation is a fundamental process in most systems that support medical diagnosis, surgical planning and treatments. Generally this process is done manually by clinicians, which may be time-consuming and tedious. To alleviate the problem, a number of interactive segmentation methods have been proposed in the literature. These techniques take advantage of automatic segmentation and allow users to intervene the segmentation process by incorporating prior-knowledge, validating results and correcting errors, thus potentially lead to accurate segmentation results. In this paper, we present a survey of interactive segmentation techniques popular for medical image analysis.
A Practical Approach to Measuring and Improving the Functional Veriﬁcation of Embedded Software

We propose in this paper to apply functional qualiﬁcation - based on the theory of mutation analysis - to ﬁrmware co-veriﬁcation environments, by integrating the GNU Project Debugger ( gdb ) remote serial protocol (RSP) with the functional qualiﬁcation engine. More speciﬁcally, the Certitude functional qualiﬁcation tool is applied to the veriﬁcation of an STMicroelectronics video IP. In this system, the hardware part is generated by High Level Synthesis ﬂow tools mainly implementing the data-ﬂow part, while the ﬁrmware part, written in C, is running on an STMicroelectronics embedded processor model devoted to the control part. Both hardware and ﬁrmware parts are simulated on a Transaction Level Modeling (TLM) platform with RSP access, modeling a virtual system-on-chip. In this particular context, the embedded software is only accessible through the RSP. We describe how our functional qualiﬁcation tool is extended to work in this environment. We present how the use of this technique allowed dead code in the ﬁrmware to be identiﬁed and to point out critical weaknesses in the veriﬁcation environment. We show that ﬁxing these issues led to reducing the memory consumption of the ﬁrmware and to ﬁnding critical bugs in the hardware/ﬁrmware. The standard nature of the RSP means that this could be a global technique to apply mutation analysis to embedded software.
YOU CAN’T MEASURE IT BUT YOU CAN KNOW IT: PRECISELY SYNTHESISING ACOUSTIC FLOW

Typical acoustic currents are usually far too small to be measurable with any precision. This paper presents a technique that uses an impedance head to generate with precision a desired, acoustic current waveform, usually periodic. An impedance head with multiple microphones, after a suitable calibration procedure, allows calculation of the acoustic pressure and current waveforms at the appropriate reference plane. The current waveform injected by such a device is a complicated function of the waveform supplied to the transducer driving the impedance head, the acoustic properties of the impedance head itself, the frequency responses of the transducer and microphones, and the frequency responses of the electronic circuitry involved. It is possible however, using an iterative technique, to adjust the waveform driving the input transducer so that the waveform of the current injected into the device under study has the desired waveform. In this fashion an impedance head can be used to synthesise and to inject a precisely known acoustic flow waveform. As an application we report that the synthesis of a model glottal flow waveform which is then input to a rigid, unvarying physical model of the vocal tract. This allows, for the first time, the rigorous evaluation of the various techniques that are used to determine the acoustical properties of the vocal tract and the glottal waveform under a wide range of conditions.
F1 Query: Declarative Querying at Scale

F1 Query is a stand-alone, federated query processing platform that executes SQL queries against data stored in different file-based formats as well as different storage systems at Google (e.g., Bigtable, Spanner, Google Spreadsheets, etc.). F1 Query eliminates the need to maintain the traditional distinction between different types of data processing workloads by simultaneously supporting: (i) OLTP-style point queries that affect only a few records; (ii) low-latency OLAP querying of large amounts of data; and (iii) large ETL pipelines. F1 Query has also significantly reduced the need for developing hard-coded data processing pipelines by enabling declarative queries integrated with custom business logic. F1 Query satisfies key requirements that are highly desirable within Google: (i) it provides a unified view over data that is fragmented and distributed over multiple data sources; (ii) it leverages datacenter resources for performant query processing with high throughput and low latency; (iii) it provides high scalability for large data sizes by increasing computational parallelism; and (iv) it is extensible and uses innovative approaches to integrate complex business logic in declarative query processing. This paper presents the end-to-end design of F1 Query. Evolved out of F1, the distributed database originally built to manage Google's advertising data, F1 Query has been in production for multiple years at Google and serves the querying needs of a large number of users and systems.
Creating Risk-Scores in Very Imbalanced Datasets: Predicting Extremely Violent Crime among Criminal Offenders Following Release from Prison

In this chapter, we will discuss the many benefits of the Area under the Curve metric (AUC), not only as a performance measure, but also as a tool for optimizing models on very imbalanced datasets. We first introduce the measure formally and then discuss a few modeling techniques that can be used specifically for imbalanced datasets. Then we will include techniques that optimize the AUC directly. We will discuss how to choose suitable cut-points on an AUC optimized score and present a case study on predicting violent felony offenses (VFO) on a parole population.
Quantile-Regret Minimisation in Infinitely Many-Armed Bandits

The stochastic multi-armed bandit is a well-studied abstraction of decision making in the face of uncertainty. We consider the setting in which the number of bandit arms is much larger than the possible number of pulls, and can even be inﬁnite. With the aim of minimising regret with respect to an optimal arm, existing methods for this setting either assume some structure over the set of arms (Kleinberg et al., 2008, Ray Chowdhury and Gopalan, 2017), or some property of the reward distribution (Wang et al., 2008). Invariably, the validity of such assumptions—and therefore the performance of the corresponding methods— depends on instance-speciﬁc parameters, which might not be known beforehand. We propose a conceptually simple, parameter-free, and practically effective alternative. Speciﬁcally we introduce a notion of regret with respect to the top quantile of a probability distribution over the expected reward of randomly drawn arms. Our main contribution is an algorithm that achieves sublinear “quantile-regret”, both (1) when it is speciﬁed a quantile, and (2) when the quantile can be any (unknown) positive value. The algorithm needs no side information about the arms or about the structure of their reward distributions: it relies on random sampling to reach arms in the top quantile. Experiments show that our algorithm outperforms several previous methods (in terms of conventional regret) when the latter are not tuned well, and often even when they are.
Plate Interactions , Evolving Magmatic Styles , and Inheritance of Structural Paths : Development of the GoldRich , Miocene

Ore deposits constitute singularities in the Earth crust, and form in response to a combination in time and space of a variety of geological processes. We here explore the complex setting that led to formation of an outstanding belt of precious-metal epithermal deposits in northern Chile, including the world class Au-Cu-As El Indio deposit. We discuss the formation of the El Indio belt in terms of Oligocene–Miocene plate tectonic and magmatic evolution of the Nazca–South America margin. The analysis of Landsat images allows recognition of a highly fractured domain involving a major Oligocene NW-SE–trending fault zone, with associated R1-R2–type structures. We suggest that a set of time-coincidental factors that occurred between ~10 and 6 Ma may have led to formation of the Late Miocene El Indio belt. Late Miocene subduction of the Juan Fernández Ridge (JFR) coincided with a substancial shift in magmatic emplacement style, linked to a compositional change from andesitic to dacitic, which resulted in the passage from stratovolcanoes to dome and dike complexes. It is not the composition alone, but the style that may be the crucial element here to understand why mineralization developed. Although stratovolcanoes easily vent volatiles and metals (via violent eruptions and quiescent outgassing), intrusions tend to retain these, and therefore, can generate volatile-, metal-rich hydrothermal solutions. We further propose that subduction of the JFR may have involved increased plate coupling, and the reactivation of older NNE trending R2 type shears (inherited structural corridors), along which the belt would have formed preferentially.
Automatic Design Method of Probabilistic Finite State Machine Using PSO for Swarm Robots Aggregation

This paper proposes to use evolutionary computations to design probabilistic finite state machine for the controller on an aggregation problem of swarm robotics. This problem formulated as an optimization problem was solved by the PSOs. Several computer simulations were conducted to investigate the validity of the proposed method. The results obtained in this paper show to us that the proposed method is useful for the aggregation problem and the best optimized controllers are interpretable. This would be transferable to real swarm robots problems.