Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential Identification of Mine Openings Using Remote Sensing Topographic LiDAR, Montague Gold District (NTS 11D/12), Halifax Regional Municipality

Nova Scotia has a long history of gold mining dating back to the 1800s. Most gold mines operated prior to modern environmental standards, which often resulted in unsecured abandoned mine openings and tailings that were not reclaimed following recovery of gold from ore. These vestiges may be a hazard to the local environment or to visitors to the sites. A critical component for evaluation of hazardous conditions is having an accurate location of these features.
EVOLUTION OF RADIO SERVICES IN THE ERA OF VOICE-CONTROLLED DIGITAL ASSISTANTS

The paper evaluates the impact of voice-controlled digital assistants on the evolution of radio services, proposing to apply radio personalization, recommendation and content atomization techniques to the conversational interface. The paper introduces the relevance of smart speakers for radio, and then technically describes a prototype based on voice-controlled digital assistants providing a set of personalized audio services, like keyword-based Audio-On-Demand (AoD) search, semantic similarity search and content-based audio recommendations. A first analysis of the impact of semantically coherent audio segments with metadata, or audio atoms, is also included, leveraging on a subset of the available AoD archive. The developed prototype service is then tested and assessed with a user evaluation with the purpose to measure the listener's reaction and propensity to access flexible radio services using a voice interfaces.
Critical review of analytical models for the in-plane and out-of-plane assessment of URM buildings

The seismic assessment of URM buildings requires proper methods of analysis and verification procedures, which consider both out-of-plane and in-plane behavior within the ambit of the displacement-based approach. In addition to numerical models, which are able to analyze also complex structures, analytical mechanically-based models can be derived from standards and are effective to support risk mitigation policies. The facade of a two-storey URM building has been considered as simple case study, and the results in terms of %NBS provided by different standards of methods from literature are compared. Regarding the out-of-plane behavior, some possible collapse mechanisms have been considered, in order to check the different methods of evaluation of the displacement demand and definition of the ultimate capacity. For the in-plane behavior, first of all a discussion on the different failure criteria for piers and spandrels is presented, and then the response of one single pier and the adjacent spandrels is investigated, in order to check the mutual interaction. Some comments on critical issues in present standards and proposals for a new release of NZSEE are also presented.
tpprof: A Network Traffic Pattern Profiler

When designing, understanding, or optimizing a computer network, it is often useful to identify and rank common patterns in its usage over time. Often referred to as a network trafﬁc pattern, identifying the patterns in which the network spends most of its time can help ease network operators’ tasks considerably. Despite this, extracting trafﬁc patterns from a network is, unfortunately, a difﬁcult and highly manual process. In this paper, we introduce tpprof , a proﬁler for network trafﬁc patterns. tpprof is built around two novel abstractions: (1) network states, which capture an approximate snap-shot of network link utilization and (2) trafﬁc pattern sub-sequences,which represent a ﬁnite-state automaton over a sequence of network states. Around these abstractions, we introduce novel techniques to extract these abstractions, a robust tool to analyze them, and a system for alerting operators of their presence in a running network.
Rural Telemental Health and Adolescents: Try a Little Shakespeare

ABSTRACT Twenty-five percent of Americans live in rural areas, almost all of which are designated as mental health service shortage areas. This designation represents serious problems for adolescents needing help with predictable developmental problems. The project described serves communities without mental health professionals; uses telemental health technology, co-located in rural primary care clinics; and emphasizes communication and coordination among professionals and clients. An example of addressing identity formation in an adolescent experiencing significant family and relational stress is explored, including the resolution of an ongoing friendship problem by using a school assignment, an analysis of Shakespeare’s Sonnet 48. Discussion includes safety, immediacy, and using bibliotherapy in telemental health with adolescents, as well as the appropriateness of telemental health for individual and parent-child sessions.
Adapting public transport policies to behavioral heterogeneity-An application to value of time

Understanding heterogeneity in behaviors is a challenge to build appropriate economic models. It is also important to design public policies adapted to the heterogeneous behaviors observed in the population. Discrete choice models are a suitable tool to address behavioral heterogeneity. In particular, the increasing popular integrated choice latent variables model offers an opportunity to study behavioral heterogeneity in great depth thanks to the inclusion of latent variables into discrete choice models. In this paper, we address heterogeneity in value of time in public transport, regarding how it varies depending on objective and perceived measures of comfort. Indeed, travel time is no longer considered as a complete waste of time but as an occasion to perform activities (working, rest, meet people.), all the more so when travel environment is comfortable. Based on a choice experiment conducted in the Rhône-Alpes Region and the estimation of six models, our results underscore that seat availability and people’s latent attitudes about comfort in public transport impact value of time. In particular, positive feelings and perceived time while traveling with coach and train increase the probability to choose a public transport mode and lower value of time. From these results, we derive public policy implications in terms of infrastructures and communication campaigns.
Likelihood Ratio Test for Order Restrictions against all Alternatives in Multivariate Normal Distribution

The problem of testing the isotonic of several p -variate normal mean vectors against all alternatives is considered. This is a multivariate extension of Robertson and Wegrnan (1978). In the present paper, two cases are considered. First, it is assumed that the covariance matices are known and second that they have an unknown scale factor. For both cases, we propose the test statistic, critical values and estimate the power of tests. The p -values are obtained by simulation study.
Bayesian calibration of the Peng-Robinson fluid model for siloxane MDM vapor flows in the non-ideal regime

Non-Ideal Compressible-Fluid Dynamics (NICFD) investigates the gas dynamics of a special class of fluids, typically (but not limited to) vapors of molecular complex compounds, characterized by a thermodynamic state space containing a non-ideal region. In the non-ideal regime, the fluid no longer behaves as an ideal gas with state equation Pv = RT (whereas P is the gas pressure, v the specific volume, R the gas constant and T the temperature) and more complex fluid models are required. Currently, the community is racing to develop reliable and predictive tools to investigate the non-ideal dynamics and to ultimately improve the design of devices involving NICFD flows. A global perspective including experiments, computations, and theory is needed in order to develop sophisticated physical models as well as a systematic and comprehensive treatment of calibration and validation procedures. This work focuses on the calibration of the polytropic Peng-Robinson (PR) fluid model [Peng and Robinson, 1976] for siloxane MDM (Octamethyltrisiloxane, C8H24O2Si3) vapor flows in the non-ideal regime. Specifically, the goal is to calibrate the material-dependent parameters appearing in the equations of state by combining experimental NICFD flows measurements with numerical simulations. The calibration process relies on a standard Bayesian inference framework and it takes advantage of the first-ever experiments on non-ideal expanding flows of siloxane MDM vapor [Spinelli et al., 2018]. The Bayesian framework to infer the polytropic PR model parameters accounts for uncertainties in the test-rig operating conditions (treated as nuisance parameters). Specifically, the inference considers the total pressure Pt and total temperature Tt at the inlet of the test section (uncertain operating conditions) and the fluid critical pressure Pcr, ∗giulio.gori@inria.fr, DeFI Team, CMAP Lab (Ecole Polytechnique, Inria Saclay Ile de France), 1 rue Estienne d’Orves, 91120 Palaiseau, France †LIMSI, CNRS, Université Paris-Saclay, Bât. 508, rue John von Neumann, Campus Universitaire, F-91405 Orsay, France ‡DeFI Team, CMAP Lab (Ecole Polytechnique, Inria Saclay Ile de France), 1 rue Estienne d’Orves, 91120 Palaiseau, France
Fatigue crack detection based on changes of the structure vibration characteristics

Abstract In order to implement a technique for detecting fatigue cracks in vibrating structures, a test bench was built in the laboratory and an experimental investigation was conducted. The case of this study is a simplistic representation of a bucket wheel excavator from mining industries, designed to have a fragile structural member acting as a mechanical fuse. No artificial excitation is used. The structural member is naturally damaged during operation and its vibration is monitored over time, until the crack occurs. This paper deals with spectral and transmissibility matrices, by means of which two measurements are compared about changes in the frequency content. The emphasis is not on the modal parameters themselves, but on comparing the spectral waveforms by means of two metrics, the relative error and the likelihood metric from a statistical test. The performance of each feature to detect the changes caused by the presence of cracks in the test-bench is illustrated.
Automatic Gale Warning Proposals for Swiss Lakes and Regional Aerodromes

Switzerland counts over 50 lakes and aerodromes for which warnings must be issued in case of high probability for wind gusts exceeding 25 knots. As these gale warnings are not automated, forecasters are required to permanently monitor the local weather evolution at these numerous specific locations, beside their main duties. Not surprisingly, quality assessments demonstrate low efficiency, with storm events frequently missed. In order to support the forecasters in their ongoing weather surveillance, an automatic warning system (GaleWarn) is developed which delivers precursory proposals for gale warnings. Working with a predictor list containing relevant measurements and short-term forecasts of the numerical weather prediction model COSMO-2, and later COSMO-1, GaleWarn delivers a storm probability for each warning object (lakes and aerodromes) every 10 minutes. Initially, a genetic programming method is developed and tested to forecast the storm probability. Nevertheless, the obtained results do not outperform the quality of logistic regression which is finally chosen for the operative system. GaleWarn has a high hit rate (75% on average) combined with a high false alarm ratio (68% on average). The performance is better in winter than in summer and the variation of quality among the warning objects is relatively large. Compared to the manual warnings, GaleWarn shows a significantly higher hit rate and a relatively higher false alarm ratio. Hence, the automatic warning proposals will help the forecaster to detect more storm events by reacting sufficiently early, but the numerous false alarms will have to be filtered. The warning proposals will appear on the platform the forecasters commonly use for the weather analysis and warning edition (NinJo). Several measures have been taken in order to reduce the number of warning proposals to the minimum required. We can deduce that, combined with the forecaster’s expertise, the utilization of GaleWarn should lead to a general improvement of the gale warning quality.
Disentangling the causal effects of air pollutants on health: when the numerous characteristics of the planetary boundary layer can help

Quasi-experimental evidence increasingly support the air pollution detrimental effect on health, but the question of which air pollutants impact which pathology remains largely open. In this paper, we exploit a novel sets of instruments: altitude weather conditions, and more specifically the characteristics of the planetary boundary layer (PBL). Numerous physical characteristics may influence differently the air pollutants’ concentrations. By selecting optimal instruments from a large set of PBL characteristics with a IV Lasso procedure, we disentangle the impact of six air pollutants. We find that at least three air pollutants, ozone, sulfur dioxide and carbon monoxide, have a strong effect on respiratory diseases, independently of each other, even when controlling for the other pollutants in presence. Children are mostly affected. As for cardiovascular diseases and the mortality rate, our results point out to respectively carbon monoxide and particulate matters.
Intrusion detection model using naive bayes and deep learning technique

The increase of security threats and hacking the computer networks are one of the most dangerous issues should treat in these days. Intrusion Detection Systems (IDSs), are the most appropriate methods to prevent and detect the attacks of networks and computer systems. This study presents several techniques to discover network anomalies using data mining tasks, Machine learning technology and dependence of artificial intelligence techniques. In this research, the smart hybrid model was developed to explore any penetrations inside the network. The model divides into two basic stages. The first stage includes the Genetic Algorithm (GA) in selecting the characteristics with depends on a process of extracting, Discretize And dimensionality reduction through Proportional K-Interval Discretization (PKID) and Fisher Linear Discriminant Analysis (FLDA) on respectively. At the end of the first stage combining Naïve Bayes classifier (NB) and Decision Table (DT) using NSL-KDD data set divided into two separate groups for training and testing. The second stage completely depends on the first stage outputs (predicted class) and reclassified with multilayer perceptrons using Deep Learning4J (DL) and the use of algorithm Stochastic Gradient Descent (SGD). In order to improve the performance in terms of the accuracy in classification of penetrations, raising the average of discovering and reducing the false alarms. The comparison of the proposed model and conventional models show the superiority of the proposed model and the previous conventional hybrid models. The result of the proposed model is 99.9325 of classification accuracy, the rate of detection is 99.9738 and 0.00093 of false alarms
Estimation of groundwater contribution to crop water usein Kulavat irrigation command area in Khorezm, Uzbekistan

*Corresponding Author E-mail: kenjabaev@yahoo.com Due to arid climate of Uzbekistan, water scarcity threatens the sustainable development of irrigated agriculture. In future, accounting all nonconventional water resources to mitigate water scarcity and to increase insitu crop water use become main topic for most researches. In this context, groundwater evaporation (Egw) can be considered as one of the sources to meet crop-water use where the water table is shallow and groundwater salinity is low.In this study, soil texture, groundwater table depth and salinity maps are developed in geographical information system based on analyzing long-term archive data. These data then employed to estimate and map Egw through a semi-empirical approach. The results suggest that surface irrigation may be reduced considering Egw contribution ranging from 205240 mm (e.g. light soils) to 305-360 mm (e.g. medium to heavy soils). The approach can be recommended to adjust the soil water balance in the root zone and optimize irrigation schedule.
Fawkes: Faster Mobile Page Loads via App-Inspired Static Templating

Despite the rapid increase in mobile web trafﬁc, page loads still fall short of user performance expectations. State-of-the-art web accelerators optimize computation or network fetches that occur after a page’s HTML has been fetched. However, clients still suffer multiple round trips and server processing delays to fetch that HTML; during that time, a browser cannot display any visual content, frustrating users. This problem persists in warm cache settings since HTML is most often marked as uncacheable because it usually embeds a mixture of static and dynamic content. Inspired by mobile apps, where static content (e.g., lay-out templates) is cached and immediately rendered while dynamic content (e.g., news headlines) is fetched, we built Fawkes. Fawkes leverages our measurement study ﬁnding that 75% of HTML content remains unchanged across page loads spread 1 week apart. With Fawkes, web servers extract static, cacheable HTML templates for their pages ofﬂine, and online they generate dynamic patches which express the updates required to transform those templates into the latest page versions. Fawkes works on unmodiﬁed browsers, using a JavaScript library inside each template to asynchronously apply updates while ensuring that JavaScript code only sees the state that it would have in a default page load despite downstream content having already been loaded. Across a wide range of pages, phones, and live wireless networks, Fawkes improves interactivity metrics such as Speed Index and Time-to-ﬁrst-paint by 46% and 64% at the median in warm cache settings; results are 24% and 62% in cold cache settings. Further, Fawkes outperforms recent server push and proxy systems on these metrics by 10%-24% and 69%-73%.
Eating Attitudes and Behaviors of a Sample of Sexual Minority Men

The goal of the present study was to learn more about eating disorder behaviors in a sample of sexual minority men across different stages of gay identity development in order to provide evidence-based recommendations for clinicians and researchers. Participants were recruited via a university GLBT/LGBT listserv, resulting in 142 eligible participants. Significant differences were found on the Mizes Anorexic Cognitions Questionnaire-Revised (Mizes et al., 2000) scale. The group representing Stages 3 (Identity Tolerance) and 4 (Identity Acceptance) of Cass’s (1979) model had the highest eating disordered scores. Discussion of the findings is accompanied by recommendations for practice and research.
EARLY LEAD EXPOSURE AND ITS EFFECTS ON ACADEMIC ACHIEVEMENT AND EARNINGS: EVIDENCE FROM AN ENVIRONMENTAL NEGLIGENCE

May 16, 2012 Abstract Between 1984 and 1989 more than 20,000 tons of toxic chemicals containing high concentrations of lead were brought to the city of Arica (in northern Chile). Initially, the chemical waste was located several kilometers from the city. The rapid expansion of Arica in the early 1990s, which included the construction of social housing projects meters away from the waste deposit, put a large number of families at risk. For more than a decade, individuals living in the vicinity of the contaminated areas were exposed to critical levels of lead. The medical literature suggests that even minimum lead exposure might have long-term effects on individual’s behavior and cognitive ability. However, there is little evidence showing direct effects on academic achievement and (fortunately) the literature rarely examines cases in which large numbers of individuals have been affected by lead exposure. In this paper we examine the effects of lead exposure on academic achievement in the case of Arica. We analyze longitudinal data from a large population of individuals living and attending primary and secondary schools in Arica between 2004 and 2008. Our data include longitudinal information on proximity to the polluted areas (from individual’s place of residence), levels of lead exposure, comprehensive sets of controls, and multiple nationally representative academic test scores. Our findings indicate significant and negative effects of household proximity to contaminated areas on student academic performance. We also estimate the effect of blood lead levels on student academic performance, finding significantly negative effects. Finally, combining these estimates with those obtained from regressions of annual earnings on student’s academic performance, we provide an estimate of the effect of lead exposure on life-time earnings.
Are Pro-Worker Judges Detrimental to Firm Survival and Employment?

In European countries, recent reforms of employment protection legislation aimed at reducing the supposedly differentiated treatment by judges of compensations for wrongful dismissal, supposed to be detrimental to employment and to the survival of small firms. However, there is only anecdotal evidence on this issue. To fill this gap, this paper provides new information about 55,000 Appeal Court decisions merged with administrative firm-level records covering all the universe of French firms. The quasi-random assignment of judges to cases reveals that judges bias has statistically significant effects on the survival, employment and hires of small low performing firms. Such results are consistent with the standard effect of the level of firing compensation on worker flows. We go one step further and provide novel insights about the effects of the variability of compensations: setting all judges biases at the mean i.e. eliminating any judge-related dispersion would decrease the liquidation probability of small low performing firms within 3 years after the judgment by 5% (i.e. 0.3 percentage point) and would increase their employment growth by 14% (i.e. 2.2 percentage points).
This paper is included in the Proceedings of the 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’20)

Serverless containers and functions are widely used for deploying and managing software in the cloud. Their popularity is due to reduced cost of operations, improved utilization of hardware, and faster scaling than traditional deployment meth-ods. The economics and scale of serverless applications demand that workloads from multiple customers run on the same hardware with minimal overhead, while preserving strong security and performance isolation. The traditional view is that there is a choice between virtualization with strong security and high overhead, and container technologies with weaker security and minimal overhead. This tradeoff is unacceptable to public infrastructure providers, who need both strong security and minimal overhead. To meet this need, we developed Fire-cracker, a new open source Virtual Machine Monitor (VMM) specialized for serverless workloads, but generally useful for containers, functions and other compute workloads within a reasonable set of constraints. We have deployed Firecracker in two publically-available serverless compute services at Amazon Web Services (Lambda and Fargate), where it supports millions of production workloads, and trillions of requests per month. We describe how specializing for serverless informed the design of Firecracker, and what we learned from seamlessly migrating Lambda customers to Firecracker.