Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymmetric Causality between Unemployment Rate and House Prices in each State of the U.S

The Great Recession of 2008 in the U.S. was mostly attributed to the U.S. housing market bubble that came to an end in 2007. In this paper, we provide empirical evidence on the above conjecture by detecting the asymmetric causality between house prices and unemployment rate in each state of the U.S. We find that indeed, decreases in house prices cause unemployment in 39 states. There is evidence in only 19 states that an increase in house prices causes unemployment. Since an asymmetric analysis requires the use of nonlinear models, we use nonlinear models and find evidence of asymmetric cointegration between the two variables in all states.
Risk Aversion and the Financial Accelerator *

We extend the Bernanke, Gertler and Gilchrist (1999) financial accelerator model with risk-neutral entrepreneurs to entrepreneurs with CRRA preferences. The optimal contract is identical to debt when there is no default, while when there is default entrepreneurs retain a part of their assets. In partial equilibrium, leverage becomes more sensitive to fluctuations in expected returns to capital when entrepreneurs are risk averse. In general equilibrium, this higher sensitivity tends to stabilize business cycle fluctuations . The response of output to “risk shocks” — shocks to the variance of unobserved idiosyncratic productivity — or shocks to the wealth distribution between households and entrepreneurs is 60 to 70 percent smaller when entrepreneurs are risk averse than when they are risk neutral. However, technology and monetary shocks have quantitatively similar effects on key macro variables, although about 20 percent smaller with risk aversion.
Surface-Enhanced Raman Spectroscopy of the Endothelial Cell Membrane

We applied surface-enhanced Raman spectroscopy (SERS) to cationic gold-labeled endothelial cells to derive SERS-enhanced spectra of the bimolecular makeup of the plasma membrane. A two-step protocol with cationic charged gold nanoparticles followed by silver-intensification to generate silver nanoparticles on the cell surface was employed. This protocol of post-labelling silver-intensification facilitates the collection of SERS-enhanced spectra from the cell membrane without contribution from conjugated antibodies or other molecules. This approach generated a 100-fold SERS-enhancement of the spectral signal. The SERS spectra exhibited many vibrational peaks that can be assigned to components of the cell membrane. We were able to carry out spectral mapping using some of the enhanced wavenumbers. Significantly, the spectral maps suggest the distribution of some membrane components are was not evenly distributed over the cells plasma membrane. These results provide some possible evidence for the existence of lipid rafts in the plasma membrane and show that SERS has great potential for the study and characterization of cell surfaces.
Relaying energy allocation in training-based amplify and forward relay communications

We consider relay-assisted communication in a training-based transmission scheme. Each transmission block consists of a training phase and a data transmission phase. The relay node employs the amplify-and-forward protocol during all transmissions. We focus on the relay signaling design and investigate the benefit of allowing for different relaying power during the training phase and the data transmission phase. Specifically, the relaying energy allocation between the two phases is optimized for maximizing the average received signal-to-noise ratio at the destination node. We study this optimization problem for both single-antenna relay and multi-antenna relay and derive a simple closed-form relaying energy allocation strategy that achieves near-optimal performance. This closed-form strategy depends only on the length of the data transmission phase but not on other system parameters such as the relaying energy budget, the number of antennas at the relay, and the distances between the source, relay and destination nodes.
Extractive Speech Summarization Using Shallow Rhetorical Structure Modeling

We propose an extractive summarization approach with a novel shallow rhetorical structure learning framework for speech summarization. One of the most under-utilized features in extractive summarization is hierarchical structure information-semantically cohesive units that are hidden in spoken documents. We first present empirical evidence that rhetorical structure is the underlying semantic information, which is rendered in linguistic and acoustic/prosodic forms in lecture speech. A segmental summarization method, where the document is partitioned into rhetorical units by K-means clustering, is first proposed to test this hypothesis. We show that this system produces summaries at 67.36% ROUGE-L F-measure, a 4.29% absolute increase in performance compared with that of the baseline system. We then propose Rhetorical-State Hidden Markov Models (RSHMMs) to automatically decode the underlying hierarchical rhetorical structure in speech. Tenfold cross validation experiments are carried out on conference speeches. We show that system based on RSHMMs gives a 71.31% ROUGE-L F-measure, a 8.24% absolute increase in lecture speech summarization performance compared with the baseline system without using RSHMM. Our method equally outperforms the baseline with a conventional discourse feature. We also present a thorough investigation of the relative contribution of different features and show that, for lecture speech, speaker-normalized acoustic features give the most contribution at 68.5% ROUGE-L F-measure, compared to 62.9% ROUGE-L F-measure for linguistic features, and 59.2% ROUGE-L F-measure for un-normalized acoustic features. This shows that the individual speaking style of each speaker is highly relevant to the summarization.
NICT’s Participation in WAT 2018: Approaches Using Multilingualism and Recurrently Stacked Layers

In this paper we describe all our NMT systems for the following translation tasks we participated in: ASPEC (all tasks), Indic Languages (multilingual tasks) and the Myanmar-English task. Our team,“NICT-5”, focused on the utility of bidirectional, recurrently stacked layered and multilingual models for AS-PEC, simple domain adaptation approaches for Myanmar-English and multilingual models for Indic Languages. In the case of AS-PEC translation, we noted that a single multilingual/bidirectional model (without ensem-bling) has the potential to achieve (near) state-of-the-art results for all the language pairs. We also noted that models that use recurrently stacking layers do not experience a large loss in translation quality despite having signiﬁcantly fewer parameters compared to the vanilla NMT models. An interesting observation is that systems with the best BLEU might not be the best in terms of human evaluation.
Information Systems Use Of Funds To The Government Of The Transparent

Kudus received a substantial village fund allocation, the allocation of funds transferred to the village government in Kudus Regency, Central Java, to support village development in 2017 reached Rp 219.89 billion. Problems that can arise in their use include: Administration of financial statements: Reduction of Village Fund allocations, Can not be held accountable for the use, misappropriation of village assets, Rental of Village Treasury Land (TKD) which is not his right. These problems can be overcome by presenting good and transparent information, for this purpose an information system for using village funds (SIMDANDES) is needed for village fund management received by Gondangmanis village, Kab. Kudus District with Information Retrieval System, System (SIMDANDES) Algorithm very useful for monitoring village fund use and uptake carried out in each village in real time, as well as information for village heads and policy makers in Kudus District to establish a policy.
PECTINOID BIVALVES OF THE PERMIAN-TRIASSIC CRISIS

5 Introduction . 5 General . 5 Collections . 5 Pectinoids . 6 The Greatest Mass Extinction . 7 Is There a Precise Permian-Triassic Boundary? 7 Acknowledgments . 11 General Abbreviations . 12 Abbreviations in Tables . 12 Descriptive Terms . 13 Morphology. 14 Shell Preservation and Microstructure . 16 Pectinoid Adaptations. 19 Form and Ornamentation . 20 Classification and Phylogeny . 22 Classification Adopted . 23 Systematics. 25 Order Pectinoida (from Pectenina Waller, 1978) . 25 Superfamily Pterinopectinacea Newell, 1938 . 25 Family Pterinopectinidae Newell, 1938 . 25 Genus Claraia Bittner, 1901 . 25 Claraia clarae (von Hauer), 1851 . 27 Claraia stachei Bittner, 1901 . 27 Genus Denguiria Boyd and Newell, 1979 . 28 Denguiria azzouzorum Boyd and Newell, 1979 . 29 Genus Pterinopectinella Newell, 1938 . 29 Pterinopectinella spinifera Newell and Boyd, new species . 29 Superfamily Aviculopectinacea Meek and Hayden, 1864 . 29 Family Cassianoididae Newell and Boyd, new family . 32 Genus Cassianoides Newell and Boyd, new genus . 32 Cassianoides kingorum Newell and Boyd, new species . 33 Family Etheripectinidae Waterhouse, 1982 . 33 Genus Heteropecten Kegel and Costa, 1951 . 34 Heteropecten vanvleeti (Beede), 1902 . 36 Genus Eumorphotis Bittner, 1901 . 37 Eumorphotis multiformis (Bittner), 1899 . 39 Genus Spyridopecten Campbell and McKelvey, 1972 . 39 Spyridopecten sp. 39 Genus Undopecten Waterhouse, 1982 . 41 Genus Girtypecten Newell, 1938 . 41 Girtypecten sublaqueatus (Girty), 1908 . 41 Genus Vnigripecten Muromtseva, 1984 . 44 Vnigripecten phosphaticus (Girty), 1910 . 44 Family Acanthopectinidae Newell and Boyd, new family . 45 Genus Acanthopecten Girty, 1903 . 45 Acanthopecten coloradoensis (Newberry), 1861 . 45 Family Euchondriidae Newell, 1938 . 47 Genus Euchondria Meek, 1874 . 48 Euchondria cooperi Newell and Boyd, new species . 48
Vibration Model of the Mobile Platform with Serial Industrial Manipulator for the Purpose of Suspension Design

Abstract— The content of the article develops the vibration model of mobile platform with serial manipulator mounted. Two main sources of vibration in mobile platform manipulation systems are the ground uncertainties and manipulator motors stiffness. Vibration can affect the behavior of the manipulator control system and decrease its dynamic properties. One of effective solutions to decrease vibration is to design vibration isolation system. To design isolators it is strictly important to perform frequency analysis of the system “mobile platform-manipulator” and to estimate its natural frequencies. Developed vibration model is based on the Denavit-Hartenberg convention. Platform and manipulator are assumed as one kinematic chain. This allows to decrease the number of system’s degrees of freedom. Motors in manipulator joints are modeled by their stiffness and damping. Simulation and frequency analysis is performed. Based on simulation results, the model of the platform with vibration isolators (modeled by their stiffness and damping) is developed.
ROAD: A New Spatial Object Search Framework for Road Networks

In this paper, we present a new system framework called ROAD for spatial object search on road networks. ROAD is extensible to diverse object types and efficient for processing various location-dependent spatial queries (LDSQs), as it maintains objects separately from a given network and adopts an effective search space pruning technique. Based on our analysis on the two essential operations for LDSQ processing, namely, network traversal and object lookup, ROAD organizes a large road network as a hierarchy of interconnected regional subnetworks (called Rnets). Each Rnet is augmented with 1) shortcuts and 2) object abstracts to accelerate network traversals and provide quick object lookups, respectively. To manage those shortcuts and object abstracts, two cooperating indices, namely, Route Overlay and Association Directory are devised. In detail, we present 1) the Rnet hierarchy and several properties useful in constructing and maintaining the Rnet hierarchy, 2) the design and implementation of the ROAD framework, and 3) a suite of efficient search algorithms for single-source LDSQs and multisource LDSQs. We conduct a theoretical performance analysis and carry out a comprehensive empirical study to evaluate ROAD. The analysis and experiment results show the superiority of ROAD over the state-of-the-art approaches.
Effect of Triglyceride Structure on Fecal Excretion of 13C-Labeled Triglycerides

Objective: The aim of this work was to determine the effects of specific changes in the structure of 13C-labeled triglyceride (TG*) on its fecal excretion relative to total stool fat excretion determined simultaneously in patients with reduced exocrine pancreatic function. Methods: A series of 47 studies were conducted in 26 young cystic fibrosis (CF) patients and 11 adult patients with chronic pancreatitis over a five year period. Each test consisted of ingesting a single high fat test meal containing both 13C-labeled triglyceride (TG*) and dysprosium chloride (DyCl3) a nonabsorbable marker of intestinal transit; in most studies the food colorant brilliant blue (FD&C blue #1) was administered along with the DyCl3. The TG*s tested were: P*P*P* = TRIPALMITIN-1,1,1-13C3; SO*S = 2-OCTANOYL-1,3-DISTEARIN-2-octanoyl-1,2-13C2; and P*LP* = 2-LAURYL-1,3-DIPALMITIN-dipalmitoyl-1,1,2,2-13C4. Ingestion of the test meal was followed by collection of individual stools for at least 72 hours. Stools were analyzed for 13C-Excess (13C*), total fat, and Dy. Results: Excretion of P*LP* showed a high degree of linear correlation with stool fat (r2 = 0.924) over a wide-range of fecal fat values. Excretion of SO*S was also significantly correlated with stool fat, but its excretion was less than 10% at all levels of steatorrhea and the slope of the regression line relating TG* excretion to stool fat was some four to five times smaller than observed for P*LP*. Fecal excretion of P*P*P* was highly correlated with stool fat (r2 = 0.941) in patients with moderate steatorrhea (<25 g fat/24 hours) and the slope of the regression line (3.20) was considerably greater than for P*LP*. Only results from those studies in which stool collections were complete (Dy excretion >90%) were utilized in the statistical comparisons (36 of 47 studies). Conclusions: The observed highly significant linear correlation between P*LP* and stool fat over the entire range of steatorrhea suggests that P*LP* excretion may be a suitable surrogate for fecal fat in patients with reduced exocrine pancreatic function. Because fecal excretion of TG* administered as described can be accurately determined by sampling only two visually marked stools, development of a noninvasive test to replace the current 72-hour stool fat test using this approach is possible. Use of other engineered TG*s and/or labeled fatty acids, may provide a method for non-invasive in vivo assessment of the specific defect(s) leading to steatorrhea in other patient groups.
Estimating the Determinants of Foreign Direct Investment Inflows: How Important are Sampling and Omitted Variable Biases?

This paper investigates the importance of factor endowment vis-a-vis institutions in explaining the locational choice of foreign investors during the 1990s.Using dynamic panel estimation on data for transition economies, we find that low labour costs, bureaucratic efficiency ("institutions"), agglomeration economies and natural resource abundance are key factors explaining foreign investors' decisions.However, sampling proves fundamental as these overall determinants mask deep and, so far empirically unexplored, differences between groups of recipient countries.For example, for the former Soviet Union economies we estimate that labour costs are no longer crucial, but abundance of natural resources and (interestingly) lower levels of human capital are.For Eastern Europe, we find that external liberalisation (one aspect of economic reform) is crucial in foreign investor's decisions.The main message is that minimising sampling biases and accounting for previously omitted variables yields a different, much richer picture than previously available. JEL classification: F21, O16, C33, P27 Keywords: Foreign direct investment, dynamic panel estimation, transition economies
Coming to Play or Coming to Win: Participation and Success at the Olympic Games

This paper investigates the post-War Summer Olympic Games in order to determine the economic and political determinants of national participation, and of female participation in particular. Success at the Games (i.e., medal counts) is then analyzed in two ways, from the individual level and the national level, showing similar results. Female participation is rising over time, augmented primarily by larger nations. There is a significant and measurable advantage to larger nations (both in GDP per capita and in population) in terms of participation and success at the Games. Furthermore, there are undeniable advantages to being the hosting nation, and to being a neighbor to the host. Equally striking is the fact that while there is no evidence of a bias of Communist and single-party governments to send more athletes to the Games, once there, the athletes of these nations perform exceptionally well. There is support for the hypothesis that colonial links make a difference, imparting a mixed blessing from the past. Predictions for participation and gold, silver and bronze medal counts by nation for the 2000 Sydney Games conclude the paper.
An image-based texture mapping technique for apparel products exhibition and interior design

In this paper, we propose an image-based texture mapping technique for textile products exhibition that does not require geometric representation of 3D models. Under this technique, a texture grid is built interactively for a target area in an original image. This grid acts as the intermediate space between planar space and texture space. The texture coordinate for each pixel in the target area can be calculated based on this grid, and the 3D effect can be successfully realized by further fine adjustment of the grid. This technique can be applied in apparel products exhibition and interior design. q 2004 Elsevier B.V. All rights reserved.
Deep Learning-aided Resource Orchestration for Vehicular Safety Communication

IEEE 802.11p based V2X communication uses stochastic medium access control, which cannot prevent broadcast packet collision, in particular during high channel load. Wireless congestion control has been designed to keep the channel load at an optimal point. However, vehicles’ lack of precise and granular knowledge about true channel activity, in time and space, makes it impossible to fully avoid packet collisions. In this paper, we propose a machine learning approach using deep neural network for learning vehicles’ transmit patterns, and as such predicting future channel activity in space and time. We evaluate the performance of our proposal via simulation considering multiple safety-related V2X services involving heterogeneous transmit patterns. Our results show that predicting channel activity, and transmitting accordingly, reduces collisions and significantly improves communication performance.
Exactly Solved Economies with Heterogeneity

We propose a novel modeling approach for general equilibrium economies with persistent heterogeneity that yields exact solutions. This is an important advancement relative to previous approaches where approximations are necessary, either by summarizing the distributional state space with a fixed number of moments or, alternatively, by perturbing the problem around a given fixed point for which the solution is known. As our approach does not impose any restriction on the shape of the state variable distribution, it can also be used to evaluate the conditions under which previous solution methods are likely to succeed.
Title : An Adaptive Pitch Axis Autopilot Design For An Unstable

An adaptive pitch axis autopilot design procedure is presented. The design procedure is applicable to both stable and unstable pitch axis models and to those having nonminimum phase. The design approach assumes the adaptive autopilot is activated after achieving level flight. It is shown a rate-feedback compensator can be designed to ensure stable level flight pitch axis operation for the entire desired flight regime. The adaptive control loop design utilizes a pole-placement algorithm. The closed-loop characteristic polynomial is designed to have dominant poles of that of an ideal second order system to obtain the desired transient response. The identification of the system uses a modified least-squares algorithm with a variable forgetting factor. The nonlinear pitch axis model is used in simulations to evaluate the design. Command response tests include the step response and the ramp command response.
Entrepreneurship, e-finance and mobile banking

This paper focuses on the role of entrepreneurship and e-finance in determining a person's intention to adopt mobile banking. The approach utilised in this paper is to develop a conceptual framework that includes a number of propositions that are developed and justified by the literature. The main findings of this paper are that people's entrepreneurial inclination and learning tendency will determine how they respond to marketing and knowledge about mobile banking. The practical implications are that financial institutions involved in e-finance can focus their marketing efforts at increasing people's exposure to mobile banking.
Causal discovery using clusters from observational data

Many methods have been proposed over the years for distinguishing causes from effects using observational data only, and new ones are continuously being developed – deducing causal relationships is difficult enough that we do not hope to ever get the perfect one. Instead, we progress by creating powerful heuristics, capable of capturing more and more of the hints that are present in real data. One type of such hints, quite surprisingly rarely explicitly addressed by existing methods, is inhomogeneities in the data. Clusters are a very typical occurrence that should be taken into account, and exploited, in the process of identifying causes and effects. In this paper, we discuss the potential benefits, and explore the hints that clusters in the data can provide for causal discovery. We propose a new method, and show, using both artificial and real data, that accounting for clusters in the data leads to more accurate learning of causal structures.
Identification of Lys49-PLA2 from crude venom of Crotalus atrox as a human neutrophil-calcium modulating protein

We fortuitously observed a human neutrophil intracellular free-calcium concentration ([Ca2+]i) increasing activity in the commercially available phosphodiesterase I (PDE I), which is actually dried crude venom of Crotalus atrox. As this activity was not observed with another commercially available pure PDE I, we tried to find out the causative molecule(s) present in 'crude' PDE, and identified Lys49-phospholipase A2 (Lys49-PLA2 or K49-PLA2), a catalytically inactive protein which belongs to the phospholipase A2 family, by activity-driven three HPLC (reverse phase, size exclusion, reverse phase) steps followed by SDS-PAGE and LC-MS/MS. K49-PLA2 induced Ca2+ infl ux in human neutrophils without any cytotoxic eff ect. Two calcium channel inhibitors, 2-aminoetoxydiphenyl borate (2-APB) (30 µM) and SKF-96365 (20 µM) signifi cantly inhibited K49-PLA2-induced [Ca2+]i increase. These results suggest that K49-PLA2 modulates [Ca2+]i in human neutrophils via 2-APB- and SKF-96365-sensitive calcium channels without causing membrane disruption.