Reviewerly/exHarmony huggingface dataset:
EZInterviewer: To Improve Job Interview Performance with Mock Interview Generator

Interview has been regarded as one of the most crucial step for recruitment. To fully prepare for the interview with the recruiters, job seekers usually practice with mock interviews between each other. However, such a mock interview with peers is generally far away from the real interview experience: the mock interviewers are not guaranteed to be professional and are not likely to behave like a real interviewer. Due to the rapid growth of online recruitment in recent years, recruiters tend to have online interviews, which make it possible to collect real interview data from real interviewers. In this paper, we propose a novel application named EZInterviewer, which aims to learn from the online interview data and provides mock interview services to the job seekers. The task is challenging in two ways: (1) the interview data are now available but still of low-resource; (2) to generate meaningful and relevant interview dialogs requires thorough understanding of both resumes and job descriptions. To address the low-resource challenge, EZInterviewer is trained on a very small set of interview dialogs. The key idea is to reduce the number of parameters that rely on interview dialogs by disentangling the knowledge selector and dialog generator so that most parameters can be trained with ungrounded dialogs as well as the resume data that are not low-resource. Specifically, to keep the dialog on track for professional interviews, we pre-train a knowledge selector module to extract information from resume in the job-resume matching. A dialog generator is also pre-trained with ungrounded dialogs, learning to generate fluent responses. Then, a decoding manager is finetuned to combine information from the two pre-trained modules to generate the interview question. Evaluation results on a real-world job interview dialog dataset indicate that we achieve promising results to generate mock interviews. With the help of EZInterviewer, we hope to make mock interview practice become easier for job seekers.
After the Complaint

editorial Free Access Share on After the Complaint: What Should ACM Disclose? Authors: Marty J. Wolf View Profile , Joseph A. Konstan View Profile , Helena Mentis View Profile , Jane Prey View Profile , Harald Störrle View Profile Authors Info & Claims Communications of the ACMVolume 66Issue 3March 2023pp 6–11https://doi.org/10.1145/3581640Published:22 February 2023Publication History 0citation8,981DownloadsMetricsTotal Citations0Total Downloads8,981Last 12 Months8,981Last 6 weeks120 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteView all FormatsPDF
The analysis of the Castelsaraceno microearthquake sequence (southern Italy) through a semi-automated template matching and machine-learning approach reveals an anti-apenninic fault

The accurate characterization of microearthquake sequences allows seismologists to shed light on the physical processes involved in earthquake nucleation, the deformation processes underlying rupture activation and propagation, and to image faults geometry at depth.&amp;#160;The current methodologies used for this purpose first need the event detection and the phase-picking - usually manual-based - and earthquake locations, which require plenty of work even by expert analysts particularly in the case of microearthquake signals, commonly noise contaminated. Thus, improving standard procedures through semi-automatic or fully-automatic workflows would be an essential step forward towards the more efficient analysis of seismic sequences.Here we show the results of a semi-automated template matching and machine-learning based workflow applied for the characterization of the foreshock-mainshock-aftershock microearthquake sequence occurred close to Castelsaraceno village (High Agri Valley, Southern Apennines, Italy) in August 2020. The analyses were performed on seismic data mainly recorded by a local seismic network belonging to the High Agri Valley geophysical Observatory (HAVO) deployed in the study area and located at a maximum epicentral distance of ~20 km from the seismicity cluster.The application of the semi-automated single-station template matching technique to the continuous data-streams of the two nearest stations of the HAVO network (from 28th July to 12th October 2020) allowed us to detect more than twice the number of microearthquakes previously identified by standard manual detections. The phase-picking was automatically performed through a deep-learning algorithm (Phasenet) on the 202 ultimate detected microearthquakes. Finally, an automatic multi-step absolute and relative earthquake location procedure was carried out.A total of 76 events were identified as belonging to the Castelsaraceno sequence, which occurred in a short time span (7-12 August) and in a limited range of depths (10 -12 km). Both the Ml 2.1 foreshock doublet and the Ml 2.9 mainshock occurred on 7 August ruptured the same seismogenic patch, thus suggesting the presence of a persistent asperity. The integrated analysis of the aftershocks distribution, the focal mechanism of the mainshock, and the geological framework of the study area, allowed revealing the seismogenic fault, not currently mapped in literature: a NE-SW striking (225&amp;#176;), high-angle (55&amp;#176;) fault with a left-lateral transtensional (rake -30&amp;#176;) kinematic. We also hypothesize that the seismic sequence occurred at depth in a brittle layer of the crystalline basement confined between two regions with more ductile rheology; futhermore, the estimated b-value (0.73&amp;#177;0.04) indicates the occurrence of the sequence in a relatively low-heterogeneity material and suggests the unimportant effect of pore-fluid pressure in driving its evolution.&amp;#160;
Bayesian networks with examples in R

"Bayesian networks with examples in R." Journal of Quality Technology, ahead-of-print(ahead-of-print), pp. 1–2
Technology Science and Its Overall Process

There are many research practices and working styles. Not all are equally effective, and some are not recommendable. In this chapter, we describe the overall process of technology science on which we base the rest of the book. This process is later refined and specialized. Reading and writing are essential ingredients in all scientific research. This chapter outlines the roles of reading and writing in the abovementioned process.
Simple Meter

Abstract This unit presents dotted-note combinations that occur when the sounds on the beat are grouped into two uneven sounds: a long sound followed by a short sound or a short sound followed by a long sound. It offers numerous exercises in a variety of keys, as well as assessment tools.
The journey towards FAIR: A story from the marine domain

The marine subdomain consists of a diverse data landscape, with several Research Infrastructures (RIs) involved. In the ENVRI-FAIR project the marine domain is represented by Euro-ARGO, ICOS (Marine), EMSO, and LifeWatch (Marine) as RIs as listed on the ESFRI roadmap, and SeaDataNet as European marine data management infrastructure. The overarching goal of ENVRI-FAIR is that all participating research infrastructures (RIs) will improve their level of FAIRness and become ready for connecting their data repositories and services to the European Open Science Cloud (EOSC).To achieve this goal, the marine domain partners have first analysed and assessed the FAIRNess level of each participating RI and identified the necessary actions to improve their individual FAIRness. They then created a roadmap and implementation plan that led to the development of an Essential Ocean Variable (EOV) demonstrator, highlighting the FAIRness achievements.&amp;#160;&amp;#160;&amp;#160;In this presentation we will discuss in more detail the RI FAIR assessment and analysis process and show how it evolved alongside the evolution of the FAIR assessment tools themselves and the harmonisation required to be meaningful and useful. We will then walk you through the analysis of this assessment that led to a list of strengths and weaknesses per RI, and the solutions to overcome the weaknesses for each individual of the FAIR principle. Finally, we will present the outcomes of the required upgrades, adoptions of standards, improvements, developments and services that were developed as part of the implementation plan and led to the construction of the EOV demonstrator product.
Spatiotemporal and hydrogeological assessment of groundwater supported by soft computing modeling of heavy metal in Al-Hassa, Eastern Province, Saudi Arabia

As one of the vulnerable arid regions, Saudi Arabia suffered from an optimal water crisis. Rapid population, industrialization, and urbanization mandated the water stress and agricultural water balance in the region; as such, there is a need for integrated water resources planning and management. To meet sustainable development goal six (SDGs-6), the ground and surface water need to be within the required quality and quantity. Hence there is a need for both the physical, chemical and hydrogeological assessment of groundwater in the Eastern part of Saudi Arabia. This study proposed three scenarios to assess the hydrogeological groundwater quality, namely, experimental laboratory based on fieldwork, geospatial mapping of the parameters (EC, pH, CaCO3, Turbidity, NA, k, Mg, Ca, F, Cl, Br, Li, B, Al, V, Cr, Fe, Mn, Ni, Co, Cu, Zn, As, Se, Sr, Mo, and Ba), and intelligent computational analysis using machine learning (ML). This research is motivated toward intelligent prediction of some heavy metals using neural network (NN), and adaptive neuro-fuzzy inference system (ANFIS). The evaluation criteria of the predictive results were analyzed based on mean absolute percentage error (MAPE), correlation coefficient (CC), and determination coefficient (DC). The outcomes proved the satisfactory ability of the NFIS model over the NN approach, despite its predictive credit.&amp;#160;
Using Apriori Algorithm to Find the Number of Frequent Heat Wave Days Affecting Cities in Europe Over the Future Period

Heatwave episodes have severe consequences in the forms of excess mortality in many regions around the world, shortage of agricultural products, drastic changes in ecosystem function and health risks. Due to the global mean temperature rising, the acceleration of extreme temperature disturbing highly at the local scale level, particularly in urban areas. From an economic growth point of view, Major cities are contributing in terms of GDP more. Heatwaves have impacted European GDP significantly in recent years. Our work is to find the number of frequent heat wave days affecting cities which are contributing to the growth of the economy in terms of GDP and density of population wise in Europe over the near future, mid future and long future using the Apriori algorithm. The features of the heat wave and their attributes have been defined according to the criteria explained in ETCCDI. The dataset that contains heat wave days in Europe derived from EURO-CORDEX climate projections is used in this work.ReferencesCopernicus Climate Change Service (C3S): Heat waves and cold spells in Europe derived from climate projections, Climate Change Service Climate Data Store (CDS),&amp;#160;&amp;#160;DOI:10.24381/cds.9e7ca677 David Garc&amp;#237;a-Le&amp;#243;n.et.al, Current and projected regional economic impacts of heatwaves in Europe, Nature Communications, https://doi.org/10.1038/s41467-021-26050-z Christophe Lavaysse.et.al, Towards a monitoring system of temperature extremes in Europe, Nat. Hazards Earth Syst. Sci,doi:10.5194/nhess-2017-181, 2017 Chlo&amp;#233; Prodhomme. et.al, Seasonal prediction of European summer heatwaves,https://doi.org/10.1007/s00382-021-05828-3 S. E. Perkins and L.V.Alexander, On the Measurement of Heat Waves, DOI: https://doi.org/10.1175/JCLI-D-12-00383.1 S. E. Perkins-Kirkpatrick.et.al, Changes in regional heatwave characteristics as a function increasing global temperature, DOI:10.1038/s41598-017-12520-2 Agrawal, R. and Srikant, Fast Algorithms for Mining Association Rules in Large Databases. Proceedings of the 20th International Conference on Very Large Data Bases, VLDB, Santiago de Chile, 12-15 September 1994, 487-499.
Il genere linguistico come fenomeno grammaticale e semantico-referenziale. Considerazioni preliminari sull’esempio dell’italiano e del polacco

The article addresses the relation between the grammatical gender and the linguistic encoding of sex distinction (natural gender).Our goal is to problematize the category of gender as a multipart and multifunctional linguistic phenomenon operating in diverse dimensions of a language.The analysis of Italian and Polish languages illustrates that grammatical gender -whose main function is to signal syntactic relations between text constituents -and natural gender -whose main function is to encode information about the sex of a referent -are in principle autonomous and independent linguistic phenomena which are however strongly interrelated in a linguistic system through a morphological and syntactic interface.
A Bayesian deep learning method for credit card fraud detection with uncertainty quantification

With the changes of people’s consuming attitudes and the popularization of mobile payment, credit card seems increasingly indispensable in life. However, as the number of issued credit cards and credit lines is increasing, there emerges more and more fraud cases involving credit cards. Due to the rapid development of the Internet industry, the channels for capital flow have become unprecedentedly smooth, making it very difficult to prevent credit card fraud cases. If that continues, the development of banks and other financial institutions in the credit card field would be restricted, which might affect people's daily consumption and even the normal running of the society. The Bayesian Deep Learning method is used to quantify the uncertainty of credit card fraud prediction in this essay. Through experimental analysis, the accuracy of the model is over 99%. Compared with conventional classification models, this model has superior performance.
Temporal and spatial evolution of radiated energy to seismic moment scaling during the preparatory phase of the Mw 6.1, 2009 L’Aquila earthquake (Italy) and the 2016 Central Italy Seismic Sequence.

We consider approximately 23,000 microearthquakes occurred between 2005 and 2016 in central Italy to investigate the crustal strength before and after the three largest earthquakes of the 2016 seismic sequence (i.e., the Mw 6.2, 24 August 2016 Amatrice, the Mw 6.1, 26 October 2016 Visso, and the Mw 6.5, 30 October 2016 Norcia earthquakes). We monitor the spatio-temporal deviations of the observed radiated energy, ES, with respect to theoretical values, ESt, derived from a scaling model between ES and M0 calibrated for background seismicity in central Italy. These deviations, defined here as Energy Index (EI), allow us to identify the onset of the activation phase one week before the mainshock. We show that foreshocks are characterized by a progressive increase in slip per unit stress, in agreement with the diffusion of highly pressurized fluids before the L&amp;#8217;Aquila earthquake proposed by previous studies. Our results suggest that the largest events occur where EI is highest, in agreement with the existing link between EI and the mean loading stress. Furthermore, our results show a progressive evolution of the dynamic properties of microearthquakes in the years following the Mw 6.1, 2009 L&amp;#8217;Aquila earthquake, and the existence of high EI patches close to the Amatrice earthquake hypocenter. We show the existence of a crustal volume with high EI even before the Mw 6.5 Norcia earthquake. Our results agree with the previously suggested hypothesis that the Norcia earthquake nucleated at the boundary of a large patch, highly stressed by the two previous mainshocks of the sequence. We highlight the mainshocks interaction both in terms of EI and of the mean loading shear stress associated to microearthquakes occurring within the crustal volumes comprising the mainshock hypocenters. Our study shows that the dynamic characteristics of microearthquakes can be seen as beacons of stress change in the crust, and, thus, be exploited to monitor the seismic hazard of a region and help to intercept the preparation phase of large earthquakes.
Preliminary results of a thermal maturity modelling study as a tool for understanding a structural setting – the case of the Fold and Thrust Belt of Western Greece.

The Hellenides Fold and Thrust Belt (HFTB) is an arcuate shaped belt whose rocks were deposited in a series of platforms and basins that formed the southern rifted margin of the Apulian microcontinent. Despite a renew interest in the last years due to an international licensing round for the exploration and production of hydrocarbons in Greece, still little is published about its geometry, thermal maturity and hydrocarbon generation timing of the main source rocks hosted in the Mesozoic section. The External-most exposed part of the HFTB consists of the pre-Apulian and the Ionian geotectonic zones from West to East. Being part of the southern passive margin of Tethys from Triassic to Late Cretaceous, the Ionian zone represents a sedimentary basin which was differentiated from the adjacent platforms during the Jurassic rifting and consists of Triassic evaporites, Triassic-Eocene carbonates, and Oligocene-Early Miocene turbidites. The Pre-Apulian zone, as part of the slope of the Apulian platform to the Ionian basin, is made up of Triassic evaporites and up to Miocene carbonates. Organic rich layers are found across the Pre-Apulian and Ionian zones, and chiefly within Mesozoic. Present-day geometries have resulted from the mainly thin-skinned Miocene compressional deformation developed after the collision of the Apulian and Eurasian continental paleomargins. To understand the amount of overburden thickness across the chain, we performed Rock-Eval 6 pyrolysis, Gas Chromatography-Mass Spectrometry, MicroRaman spectroscopy and transmitted light petrography on Mesozoic-Cenozoic source rocks across an ENE-WSW transect in Western Greece where westward migrating intra-Ionian imbricate thrusts are evident. Overall, the data suggest that Cenozoic samples are immature, while Lower Cretaceous and Mid-Upper Jurassic thermal maturity reaches the onset of the oil window and further increases in Lower Jurassic and Triassic successions. Maturity data were used as input parameters to 1D thermal maturity modelling of wells and pseudo-wells across this transect. Model calibration by using present-day heat flow values and a Mesozoic rifting model, suggests that the eroded thickness at each studied location exceeds 1.5km. These erosion estimates better constrain our understanding of the geometry of the belt and the timing of maximum burial.
Implications for Possible Fault Zones Deduced from Lithogeochemical Characterization of Reservoir Levels of a Geothermal Field: Edremit Example

Investigation of the reservoir lithology of Edremit geothermal field from western Anatolia is performed using the drill cuttings that belong to the reservoir levels. The samples are analysed in an attempt to determine the mineralogical and petrographical features, mineral compositions and whole rock geochemistry. The examinations include macroscopic and microscopic analyses, followed by the techniques of X-Ray Diffraction (XRD), Confocal Raman Spectroscopy (CRS), Electron Probe Micro Analysis (EPMA) and X-Ray Fluorescence (XRF). Dominant rock fragments and mineral phases are identified as granitic rocks and quartz, feldspars, micas, carbonates and amphiboles, respectively. Textural characteristics of the samples display the effects of cataclasm and alteration, indicating faulting and hydrothermal fluid activity. The changes in major and trace element concentrations along the well bore reveal three different concentration levels at depth intervals of 900-928 m, 930-974 m and 976-1038 m as well as an inverse relationship between SiO2 and CaO. These three distinctive zones correlate well with the variations in grains sizes (coarse to fine) and textural features (cataclastic to mylonitic) with depth. Taking into account the reported water leakage zone around 930 m depth and the evidences for hydrothermal fluid effect (such as pyrite abundance, alterations, sulphur presence) observed along the well bore, possible fault zone and as a result, the likely pathway for the hydrothermal fluid is inferred to be in the middle section (930-974 m) of the identified three zones. It is also deduced from the lithogeochemical results that the fluid is potentially Si-rich in this zone and Ca-rich in deeper levels which are in line with the previously investigated hydrogeochemistry of the system. This study points out that mineralogical-petrographical studies integrated with geochemical analyses can potentially serve as significant indicators in determination of lithological variations that can be correlated with fault zones of deep systems for prospective exploration sites.&amp;#160;This study has been published in Applied Geochemistry in 2022 and complete work can be accessed from https://doi.org/10.1016/j.apgeochem.2022.105388
Morphometric signatures of neotectonic activity in Kotdwar region, northwestern Himalaya, India.

Tectonics plays a crucial role in shaping a landscape, especially in young mountain chains like the Himalayas, where thrusts and faults govern the landform features. This study uses morphometric analysis to assess the tectonic evolution in the Haridwar-Kotdwar foothills. The region is bound by the E-W trending Main Boundary Thrust (MBT) and Himalayan Frontal Thrust (HFT) in the north and south, respectively. N-S trending faults divide the region into three segments or blocks with distinct tectonic and stratigraphic setups. The results of the morphometric analysis reveal that the E-W trending Boksar Thrust (BT) and Haldu Paro Thrust (HPT) in segment 2 are neotectonically active. The high values of Ksn and Chi-Ksn reveal signatures of neotectonic activity along BT and HPT in segment 2, whereas no such signatures are observed along these thrusts in segment 3. There is an increased incision in segment 2, which can also be ramifications of tectonic activity along BT and HPT. The Gradient Length Anomalies (GLA) show negative anomalies along BT, HPT and MBT, which is evidence of upliftment along these thrusts. The values of the hypsometric index also show an increasing trend with an increase in the area, also ascertaining the signatures of tectonic activity in segment 2. Similar signatures of neotectonic activity are not seen in the morphometry results of segments 1 and 3, making segment 2 the most active block in the region. Therefore, this study helps understand the tectonic evolution of the Haridwar-Kotdwar region and the seismic hazard in this region.