Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Improved Deep Contextual Embedding for the identification of Irony and Sarcasm

Humans use tonal stress and gestural cues to reveal negative feelings that are expressed ironically using positive or intensified positive words when communicating vocally. However, in textual data, like posts on social media, cues on sentiment valence are absent, thus making it challenging to identify the true meaning of utterances, even for the human reader. For a given post, an intelligent natural language processing system should be able to identify whether a post is ironic/sarcastic or not. Recent work confirms the difficulty of detecting sarcastic/ironic posts. To overcome challenges involved in the identification of sentiment valence, this paper presents the identification of irony and sarcasm in social media posts through transformer-based deep, intelligent contextual embedding – T-DICE – which improves noise within contexts. It solves the language ambiguities such as polysemy, semantics, syntax, and words sentiments by integrating embeddings. T-DICE is then forwarded to attention-based Bidirectional Long Short Term Memory (BiLSTM) to find out the sentiment of a post. We report the classification performance of the proposed network on benchmark datasets for #irony & #sarcasm. Results demonstrate that our approach outperforms existing state-of-the-art methods.
Working Paper No. 226 “Land and Credit: A Study of the Political Economy of Banking in the United States in the Early 20th Century”

We find that in the early 20 century, counties in the United States where the agricultural elite had disproportionately large land holdings had significantly fewer banks per capita, even correcting for state-level effects. Moreover, credit appears to have been costlier, and access to it more limited, in these counties. The evidence suggests that elites may restrict financial development in order to limit access to finance, and they may be able to do so even in countries with well-developed political institutions. JEL Classification: G20, O16, O43 The University of Chicago’s Booth School of Business and the International Monetary Fund. We thank Lakshmi Aiyar, Shawn Cole, Stijn Claessens, Oded Galor, Adair Morse, Mark Rosenzweig, Jeremy Stein, as well as participants in seminars at the IMF, the NBER Political Economy, Corporate Finance, and Growth Workshops, M.I. T. , Northwestern University, the University of Chicago, the WFA Meetings, and Yale University for comments. Rajan benefited from grants from the Stigler Center for the Study of the State and the Economy, from the Initiative on Global Markets, and from the National Science Foundation.
Star formation and supernovae in starburst galaxies

We have studied a sample of five nearby IR-luminous starburst galaxies by means of optical, near-IR and Hα imaging, optical long-slit spectroscopy and millimeter CO (1-0) imaging, performed with NOT and Onsala 20m telescopes. The star formation rate (SFR) and supernovae rate (rSN ) estimations for these galaxies are derived from the Hα imaging. The surface brightness profiles of the sample measured from KS imaging are presented, offering the spatial distribution of star formation regions. Using radio-observations together with archival X-ray data, the total mass of gas in M82 star-forming region is estimated to be Mgas ≈ 2.1 × 10 M ̄, yielding the star formation efficiency SFE ∼ 0.6. The extinction was examined in four regions near the M82 nucleus from the spectroscopic data, using the relative ratios of the Hα and Hβ lines, leading to the values 3 − 6 mag. Spectroscopic age-dating by means of Hβ line equivalent width measurement gives values of 6 − 7 Myr for studied regions. We did a comparison of the near-infrared images to older data in order to find new supernovae in our galaxies, but nothing was found. In addition, two recently discovered supernovae SN2009gf and SN2009fv were spectroscopically defined to be of type Ia.
Long-Term Discharge Estimation for the Lower Mississippi River Using Satellite Altimetry and Remote Sensing Images

Despite increasing interest in monitoring the global water cycle, the availability of in situ gauging and discharge time series is decreasing. However, this lack of ground data can partly be compensated for by using remote sensing techniques to observe river stages and discharge. In this paper, a new approach for estimating discharge by combining water levels from multi-mission satellite altimetry and surface area extents from optical imagery with physical flow equations at a single cross-section is presented and tested at the Lower Mississippi River. The datasets are combined by fitting a hypsometric curve, which is then used to derive the water level for each acquisition epoch of the long-term multi-spectral remote sensing missions. In this way, the chance of detecting water level extremes is increased and a bathymetry can be estimated from water surface extent observations. Below the minimum hypsometric water level, the river bed elevation is estimated using an empirical width-to-depth relationship in order to determine the final cross-sectional geometry. The required flow gradient is derived from the differences between virtual station elevations, which are computed in a least square adjustment from the height differences of all multi-mission satellite altimetry data that are close in time. Using the virtual station elevations, satellite altimetry data from multiple virtual stations and missions are combined to one long-term water level time series. All required parameters are estimated purely based on remote sensing data, without using any ground data or calibration. The validation at three gauging stations of the Lower Mississippi River shows large deviations primarily caused by the below average width of the predefined cross-sections. At 13 additional cross-sections situated in wide, uniform, and straight river sections nearby the gauges the Normalized Root Mean Square Error (NRMSE) varies between 10.95% and 28.43%. The Nash-Sutcliffe Efficiency (NSE) for these targets is in a range from 0.658 to 0.946.
TWO-PASS 3 D MIGRATION AND LINEARIZED INVERSION IN THE ( x , t )-DOMAIN 1

JAKUBOWICZ, H. and MILLER, D. 1989. Two-pass 3D migration and linearized inversion in the (x, t)-domain. Geophysical Prospecting 37, 143-148. 3D Kirchhoff migration and acoustic Born inversion of zero-offset seismic data in a constant-velocity medium can be uniformly factored as a cascade of two 2D diffraction inte­ grals. The formal argument is based on a straightforward implementation of the original time-domain approach of Gibson, Lamer and Levin. The factorization differs from the factor­ ization described by Jakubowicz and Levin in omitting all time-dependent filters from the 2D operators in favour of ID filtrations performed as a preprocess and a postprocess. INTRODUCTION Gibson, Larner and Levin (1983) introduced an efficient approach to 3D migration by means of a simple heuristic argument showing that the Kirchhoff-summation method could be accomplished by successive applications of the standard 2D tech­ nique. In a companion paper, which has been the subject of some further discussion (Stolt 1984; Fokkema, Lortzer and Ziolkowski 1986; Jakubowicz and Levin 1986), Jakubowicz and Levin (1983) argued that 3D wave-equation migration could be precisely factored as a cascade of two 2tD wave-equation migrations by considering migration in both the (x, w) and (k, w) domains. They declined to treat the (x, t) domain on the grounds that the half-derivative in 2tD Kirchhoff migration ren­ dered the analysis intractable. In this note we sidestep the issue of the half-derivative and observe that the 3D wave-equation migration can be handled precisely by the original time-domain algorithm provided both the input data and output image are modified by the appli­ cation of suitable 1D filters. This is both computationally efficient and natural with respect to the original heuristic. Furthermore, since Kirchhoff migration based on exploding reflectors differs from multidimensional inversion based on the Born 1 Received July 1987, revision accepted May 1988. 2 Formerly GECO UK; current address: Texaco Ltd, 1 Knightsbridge Green, London SWIX 7QJ, U.K. 3 Schlumberger-Dol1 Research, P.O. Box 307, Ridgefield, CT 06877, U.SA
INTEGRATION OF INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) INTO CEMENT DEEP MIXING METHOD

: In the deep mixing improvement method, soil-cement columns are installed in to an invisible ground, therefore it is impossible to visually confirm the circumstance of the constructions process. As the results, the inadequacy of construction data management and quality control of the constructed soil-cement columns may happen following re-construction of the columns, and structures failures/damages in some cases. By incorporating the Information and Communication Technology (ICT), authors have invented and developed a system to visualize the construction process of the deep mixing work in real-time, namely “3D Pile Viewer”. This system consists of two functions that are the positioning guidance and the visualization of the construction information. The former has been developed by using the combination of the Global Navigation Satellite System (GNSS) or the Total Station (TS), and the tilt sensor. The latter is to create three-dimensional model of all information during construction such as depth, electrical current value, amount of slurry, rotation speeds, etc., then sharing via internet. By introducing the newly developed system to various actual construction sites Japan and oversea, the practical performance of the system and its advantages have been confirmed.
Robust non-negative matrix factorization for subspace learning

Conventional non-negative matrix factorization methods fail to clusetring due to many noisy data. Therefore, this paper proposes a novel non-negative matrix factorization method to learn a robust subspace from the noisy space. Considering matrix completion and non-negative matrix factorization, the proposed method can recover the contaminated data and learn a low-dimensional eﬀective subspace. Experiments on the ORL face dataset with Salt & Pepper noise show that our proposed method is eﬀective and robust.
Serving Their Needs: A Qualitative Examination of Nutrition Policy Implementation in the Early Care and Education Setting

Background: ​Childhood obesity is a growing problem in the United States and results in increased risk for chronic diseases such as diabetes, heart disease, and hypertension. Thirteen percent of youth in Georgia are obese. Identifying strategies to assist children in establishing healthy habits is essential to reduce the risk of childhood obesity. The Early Care and Education (ECE) setting is ideal for the implementation of obesity prevention practices. However, there are barriers present for implementing nutrition policies in this setting. This report explores the implementation of food and beverage best practices in the ECE setting and highlights barriers to and facilitators for adopting these policies. Methods: ​We conducted 24 interviews and 6 focus groups with ECE program directors and teachers in 6 regions in Georgia. The statewide sample included directors from child care learning centers, family child care homes, and license-exempt programs. A trained qualitative researcher facilitated focus groups and interviews. Data were audio recorded and transcribed verbatim. Qualitative data analysis software, NVivo 10, was used to code data and identify emergent themes. Results: ​Several key themes related to barriers to food and beverage policy implementation emerged including the need for: 1) enhanced parent communication, 2) resources to limit juice consumption, and 3) financial support to decrease food costs. Facilitators of nutrition policy implementation included: 1) ease of access to water, 2) children’s preferences for fruits and vegetables, and 3) availability of existing nutrition resources. Findings will inform the development of resources to support nutrition policy implementation as well as policy training for ECE teachers in Georgia. Conclusions: ​Study themes may provide insight about how to improve current resources and develop new solutions to improve adoption and implementation of nutrition policies in the ECE setting in the future.
Semianalytical Solution for Large Deformation of Salt Cavern with Strain-Softening Behavior

A semianalytical solution of stress and displacement in the strain-softening and plastic flow zones of a salt cavern is presented. The solution is derived by adopting the large deformation theory, considering the nonlinear Hoek–Brown (H-B) strength criterion. The Romberg method is used to carry out numerical calculation, and then, the large deformation law of displacement is analyzed. The results are compared with those obtained by former numerical methods, and the solutions are validated. The results indicate that the displacement of the plastic zone decreases with the increase in distance away from the salt cavern. Similarly, it decreases with an increase in the geological strength index or running pressure, with the running pressure having a more significant effect on the displacement. It increases with the dilation angle, and the impact degree gradually increases. Compared with the softening parameter, , of the plastic zone, the flow parameter, , has little impact on the displacement. The displacement of the plastic zone obviously increased when considering the strain-softening of salt rock. When considering the shear dilation and softening behaviors of salt rock, the analytical solution obtained by employing the experiential regression Hoek–Brown (H-B) criterion, which considers many factors such as the structural characteristics of the salt formation and the rock mass quality, is safer and closer to the actual situation. This study can provide reference for many applications, including but not confined to analyzing the deformation of the surrounding rock of an underground salt cavern storage facility during construction.
Liquefaction Evaluation of Aveiro Sands from SCPTU and SDMT Tests

The paper analyses the results of the liquefaction potential evaluation at the harbour of Aveiro (Portugal) from distinct in situ testing approaches. The study was based on the results of CPTu/SCPTu tests and DMT/SDMT tests, including the measurement of shear wave velocity (VS), taking into account the grain size distribution curves. The analysis was performed to estimate the cyclic resistance ratio (CRR) from in situ tests, and to compare the CRR with the cyclic stress ratio (CSR), with the seismic action evaluated according to Portuguese National Annex of the Eurocode 8. These two parameters were used to assess the liquefaction safety factor (FS) and the liquefaction potential index (LPI). In addition, the liquefaction severity number (LSN) was also used to quantify the effects of liquefaction and consequent land damage by estimating the volumetric strains. The estimate of the cyclic resistance ratio CRR from DMT appears to be interesting since the horizontal stress index KD is sensitive to a factors which are known to increase liquefaction resistance.
Counting generalized Schr\"oder paths

A Schroder path is a lattice path from $(0,0)$ to $(2n,0)$ with steps $(1,1)$, $(1,-1)$ and $(2,0)$ that never goes below the $x-$axis. A small Schroder path is a Schroder path with no $(2,0)$ steps on the $x-$axis. In this paper, a 3-variable generating function $R_L(x,y,z)$ is given for Schroder paths and small Schroder paths respectively. As corollaries, we obtain the generating functions for several kinds of generalized Schroder paths counted according to the order in a unified way.
Subspace Methods for 1 Nonlinear Optimization

Subspace techniques such as Krylov subspace methods have been well known and extensively used in 7 numerical linear algebra. They are also ubiquitous and becoming indispensable tools in nonlinear opti8 mization due to their ability to handle large scale problems. There are generally two types of principals: i) 9 the decision variable is updated in a lower dimensional subspace; ii) the objective function or constraints 10 are approximated in a certain smaller functional subspace. The key ingredients are the constructions of 11 suitable subspaces and subproblems according to the specific structures of the variables and functions 12 such that either the exact or inexact solutions of subproblems are readily available and the corresponding 13 computational cost is significantly reduced. A few relevant techniques include but not limited to direct 14 combinations, block coordinate descent, active sets, limited-memory, Anderson acceleration, subspace 15 correction, sampling and sketching. This paper gives a comprehensive survey on the subspace meth16 ods and their recipes in unconstrained and constrained optimization, nonlinear least squares problem, 17 sparse and low rank optimization, linear and nonlinear eigenvalue computation, semidefinite program18 ming, stochastic optimization and etc. In order to provide helpful guidelines, we emphasize on high level 19 concepts for the development and implementation of practical algorithms from the subspace framework. 20
The conﬁned primal integral A measure to benchmark heuristic MINLP solvers against global MINLP solvers

It is a challenging task to fairly compare local solvers and heuristics against each other and against global solvers. How does one weigh a faster termination time against a better quality of the found solution? In this paper, we introduce the conﬁned primal integral, a new performance measure that rewards a balance of speed and solution quality. It emphasizes the early part of the solution process by using an exponential decay. Thereby, it avoids that the order of solvers can be inverted by choosing an arbitrarily large time limit. We provide a closed analytic formula to compute the conﬁned primal integral a posteriori and an incremental update formula to compute it during the run of an algorithm. For the latter, we show that we can drop one of the main assumptions of the primal integral, namely the knowledge of a ﬁxed reference solution to compare against. Furthermore, we prove that the conﬁned primal integral is a transitive measure when comparing local solves with diﬀerent ﬁnal solution values. Finally, we present a computational experiment where we compare a local MINLP solver that uses certain classes of cutting planes against a solver that does not. Both versions show very diﬀerent tendencies w.r. t. average running time and solution quality, and we use the conﬁned primal integral to argue which of the two is the preferred setting.
Community-responsive adaptation to flooding in Kibera, Kenya

Much of the world’s existing and future population will live in slums, where the twin trajectories of rapid urbanisation and increased flooding driven by climate change collide. Few spatial planning policies currently address this issue in practice. Poorly planned relocation from slum areas has caused conflict and insecurity, while large-scale infrastructural solutions for reducing flood risk are prohibitively expensive. There is a need to consider how local adaptation measures for increasing resilience to flooding can complement other structural and policy measures. This paper describes and evaluates autonomous, market-based and public-policy-driven structural and non-structural adaptation approaches to flooding in Kibera, the largest informal settlement in Nairobi, Kenya. The analysis employs a novel survey data set from 963 households in Kibera and extensive community and institutional stakeholder consultation. Results of the consultation demonstrate how autonomous adaptation at the household level is disincentivised by insecure housing tenure, while public-policy-driven approaches are constrained by the lack of effective community engagement. Combining the lessons from this analysis with 10 years of experience in developing public space and infrastructure projects in Kibera, the paper builds the case for an approach to ‘community-responsive adaptation’ to urban flooding that negotiates these limitations.
A Comparison between Pixel Intensity and Texture Analysis based Damage Detection Techniques

Imaging based damage detection techniques are increasingly being uti lized alongside traditional visual inspection methods to provide owners/operators of infrastructure with an efficient source of quantitative information for ensuring their continued safe a nd economic operation. However, choosing a suitable damage detection technique that will provide a high level of quantitative information is often a timely and challenging prospect as there exists a wide array of algorithms currently available. These algor ithms may be partitioned into one of two groups; pixel intensity based methods and texture analysis base d methods . The algorithms in e ach group are naturally suited to different applications, depending largely on whether the damaged region under considerat ion is more separable from the background based on colour or on texture . This paper compares two algorithms, one from each category, which have previously been proposed in the domain of Infrastructure Maintenance Management (IMM). The algorithms are applie d to a range of scenes featuring various forms of damage and their performance is investigated for best detection on the basis of per ormance coordinates in the Receiver Operating Characteristic (ROC) space . The general superiority of the pixel intensity b ased approach over the texture analysis based approach is demonstrated, in particular when considering High Dynamic Range (HDR) imagery.
The status of the leech fauna (Annelida, Hirudinea) at the eastern region of Azerbaijan

This study was carried out between May 2017 and December 2019 to determine leech species in some wetlands in the Eastern region of Azerbaijan. In the research, the leech samples were collected from a total of 21 locations from six wetlands in the eastern part of Azerbaijan. As a result of field and laboratory studies, five species of leeches were determined (Dina stschegolewi, Erpobdella sp., Haemopis sanguisuga, Hirudo orientalis, and Placobdella costata). In this research, Erpobdellid leech Erpobdella sp. are the first records from different three wetlands of Azerbaijan. In the freshwaters of Azerbaijan has been recorded 14 species of leeches. However, there are not detailed researches that these leech species are found in Azerbaijan. The freshwater leech fauna for the eastern region of Azerbaijan is determined for the first time in ith this research. P. costata and H. sanguisuga in two different, Erpobdella sp. in three various wetlands were found. However, D. stschegolewi and H. orientalis were determined only in one wetland. While Erpobdella sp coexists with P. costata in two water sources, it was observed that lives with H. orientalis in one wetland. H. sanguisuga and D. stschegolewi could not be detected with different leech species in water sources.
Effect of Architecture in Recurrent Neural Network Applied on the Prediction of Stock Price

—The recurrent neural network is generally utilized in an assortment of areas, such as pattern recognition, natural language processing and computational learning. Time series prediction is one of the most challenging topics for many years due to its application in ﬁnance and decision making. This article centers chieﬂy on the methods and techniques of forecasting future prices of two stocks: IAM.PA and ORA.PA. An experimental investigation is grounded on two years of historical information. Furthermore, the statistics of the stocks and the predictions are made for 22 days in advance. The prediction performance compares three approaches of the recurrent neural network: Elman recurrent neural network in the ﬁrst stage, Long Short-Term Memory recurrent neural network for the next phase, and Gated Recurrent Unit in the third phase. The article aims to accommodate a comparative analysis among these three models based on mean square error, time per step, memory and the number of hidden nodes required for excellent accuracy.