Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Crash-Time of Rational Speculative Bubbles of Malaysian Stock Market during the Year 2008

Rational speculative bubble can be defined as transient upward movements of stock prices above fundamental value due to speculative investors. The Generalised Johansen-LedoitSornette (GJLS) model have been developed as a flexible tool to identify the size of rational speculative bubble. This model is combines the economic theory of rational expectation bubbles with finite-time singular crash hazard rates, behavioral finance on imitation and herding of investors and traders as well as mathematical statistical physics of bifurcations and phase transitions. It has been employed successfully to a large variety of stock bubbles in many different markets. The purpose of this study is to predict crash-time, intrinsic value and size of rational speculative bubble of Malaysian stock market during global economic crisis 2008. The predicted crash-time by employing GJLS model is exactly same as empirical date of crash during 2008.
Producing on the fly anorexic plan diagrams using AniPQO

A “plan diagram” is a pictorial enumeration of the execution plan choices of a database query optimizer over the relational selectivity space. These diagrams are often remarkably complex and dense, with a large number of plans covering the selectivity space, showing that current optimizer make extremely fine-grained plan choices. However, they can often be reduced to much simpler pictures termed as “anorexic plan diagrams” with significantly fewer plans, with bounded degradation in the query processing quality. This can be achieved by applying an anorexic reduction technique to the plan diagram but the associated processing overheads may hinder the practical relevance. There is a heuristic approach, known as AniPQO, that avoids the brute force exploration of the selectivity space, and identifies a subset of plans (from plan diagram) using geometric decomposition of selectivity space. Thus, it allows us to produce an approximation to the plan diagram but does not ensure bounded degradation in query processing quality. When evaluated on the top of small home-grown Volcano based optimizer, AniPQO was found to identify anorexic set of plans, with significantly lesser overheads and without significant (not bounded) degradation in the query processing quality. This work aims to evaluate AniPQO on modern industrial-strength optimizer and to check whether it can be used as “on the fly” technique to produce anorexic plan diagrams. We have evaluated AniPQO using TPC-H and TPC-DS benchmarks on SQL Server 2008, which provides plan forcing feature. Empirical results show that AniPQO also gives anorexic set of plans on such industrial-strength optimizer and it can be used to directly produce anorexic plan diagrams. We have also visualized anorexic plan diagrams associated with AniPQO, using tool Picasso, as part of this work.
Variability in morpho-physiological parameters of fenugreek genotypes

Ten genotypes of fenugreek (Trigonella foenum-graecumL.) were evaluated for genetic variation for morphological, physiological and seed quality parameters. Significant variation was recorded in fresh weight, shoot weight, root weight and no. of branches during 30, 60 and 90 days after sowing. The study revealed different crop physiology with some like A3-31-1-17 accumulated more fresh weight during early growth stage while genotype B4-22-7-2-1 and B5-33-20 showed increased vegetative growth during 30-60 DAS. Shoot length of different genotypes was ranged between 9.4212. 42cm at 30 DAS which increased significantly at 60 DAS and 90 DAS. Root length was increased in all the genotype at 60 DAS but very less or no increase in length was noticed on 90 DAS. All the genotypes showed pod formation only after 60 DAS. Similarly Chlorophyll synthesis gradually increased in all the genotypes up to 90 DAS. All the tested genotypes showed growth in leaf area up to 90 DAS. Maximum leaf area (8.9 cm) was recorded for genotype B5-6-1 and AFg-3 while minimum (6.1) leaf area was observed in C4-2-14 genotypes. Genotypes were also differing in water potential recorded at 60 and 90 DAS. Genotype C4-2-14 and B3-77-8-10 showed to maintain water potential at 90 DAS. Maximum seed yield was recorded in AFg 3 closely followed by A3-31-1-17.
FluentPS: A Parameter Server Design with Low-frequency Synchronization for Distributed Deep Learning

With pursuing high accuracy on big datasets, current research prefers designing complex neural networks, which need to maximize data parallelism for short training time. Many distributed deep learning systems, such as MXNet and Petuum, widely use parameter server framework with relaxed synchronization models. Although these models could cost less on each synchronization, its frequency is still high among many workers, e.g., the soft barrier introduced by Stale Synchronous Parallel (SSP) model. In this paper, we introduce our parameter server design, namely FluentPS, which can reduce frequent synchronization and optimize communication overhead in a large-scale cluster. Different from using a single scheduler to manage all parameters’ synchronization in some previous designs, our system allows each server to independently adjust schemes for synchronizing its parameter shard and overlaps the push and pull processes of different servers. We also explore two methods to improve the SSP model: (1) lazy execution of buffered pull requests to reduce the synchronization frequency and (2) a probability-based strategy to pause the fast worker at a probability under SSP condition, which avoids unnecessary waiting of fast workers. We evaluate ResNet-56 with the same large batch size at different cluster scales. While guaranteeing robust convergence, FluentPS gains up to 6× speedup and reduce 93.7% communication time costs than PS-Lite. The raw SSP model causes up to 131× delayed pull requests than our improved synchronization model, which can provide fine-tuned staleness controls and achieve higher accuracy.
Radio Channel Characterization of Mid-band 5 G Service Delivery for Low Altitude Aerial Base Stations

This paper presents a study which evaluated the potential for using low altitude, unmanned aerial vehicles to deliver 5 Generation cellular connectivity, particularly into areas requiring short-term enhancement in coverage. Such short-term enhancement requirements may include large gatherings of people or during disaster scenarios where there may be service outages or a need for increased bandwidth. An evaluation of this approach was conducted with empirically generated results regarding signal quality and cellular coverage – illustrating the potential of using unmanned low altitude aerial vehicles to deliver 5G cellular mobile services. Specifically, channel gain, mean time delay of the received signals (mean), and the Root Mean Square spread of the delay (RMS) were investigated for two distinct user modes at three different drone heights for three selected environments; an open area (field), a tree-lined environment, and an enclosed area. Maximum likelihood estimates for the various drone heights, user modes, and operational environments were found to be Rician distributed for received signal strength measurements, whereas mean and RMS for the open and tree-lined environments were Weibull distributed with the enclosed area tests being lognormally distributed. The paper also investigates how the channel gain may be affected when operating in each of the various global bands allocated for mid-5G communications; namely Europe, China, Japan, Korea, and Northern America. These regional mid-5G band allocations were found to yield minimal variance for all the environments considered. INDEX TERMS 5G, 5 Generation, Personalized Networks, Propagation, Signal Delay, Signal Reliability, UAV.
Evaluating the Goodness of Fit of a SEM Model

This paper will focus on the basics of path analysis, how to run path models in Proc CALIS, and how to use SAS to test for multivariate normality. Two estimation methods for path analysis: ML (Maximum Likelihood) and FIML (Full Information Maximum Likelihood) will be explained and compared. The results from Proc CALIS will also be compared with the SPSS AMOS module and the Mplus software. Further, SAS can be used to check data for the MAR (Missing At Random) assumption and to estimate a path model after imputing missing data. Power calculations for structural equation models can be done with Proc IML. The concepts behind SEM power calculation will be explained and an IML program to perform SEM power calculations will be presented. The data used for the analysis in this presentation is from the REACH-Detroit project, a culturally tailored Diabetes intervention for African American and Latino/a persons in inner city Detroit. Outline Introduction to Path Analysis. Pages 1-2 Evaluating the Goodness of Fit of a SEM Model. Page 3 Degrees of Freedom and Power. Pages 3-4 Description of the REACH Detroit Project and Hypothesized Path Model. Pages 4-5 Multivariate Normality. Pages 6-8 Missing Data. Pages 8-10 Results of Fitting a Path Model to the REACH Detroit Data. Pages 10-14 Comparison Between SAS Proc CALIS, SPSS/AMOS, and Mplus. Page 15 Conclusions Page 15 References Page 16-17 Appendix: SAS Code for Multivariate Normality, Missing Data Analysis, Path Model for REACH Pages 18-19 Introduction to Path Analysis A Path Analysis model is a multivariate linear model based on a diagram that specifies the relationships between the variables, such as Figure 1 below. Path Analysis is the sub-model of SEM (Structural Equation Model), in which all variables (except error terms) are manifest, meaning observable. Whereas, SEM allows for both manifest and latent variables. Let n be the size of a random sample, where X1 to Xp are the independent variables and Y1 to Yq are the dependent variables. In general, p and q do not have to be equal. Each of X1 to Xp and Y1 to Yq are n  1 vectors. Figure 1: Example of a Path Diagram With Equations, p = 3, q = 2.  Y1 = X1γY1X1 + X2γY1X2 + Y2βY1Y2 + δ1.  Y2 = X2γY2X2 + X3γY2X3 + δ2.
Cysteine-mediated decyanation of vitamin B 12 by the predicted membrane transporter

Uptake of vitamin B12 is essential for many prokaryotes, but in most cases the membrane proteins involved are yet to be identified. We present the biochemical characterization and high-resolution crystal structure of BtuM, a predicted bacterial vitamin B12 uptake system. BtuM binds vitamin B12 in its base-off conformation, with a cysteine residue as axial ligand of the corrin cobalt ion. Spectroscopic analysis indicates that the unusual thiolate coordination allows for decyanation of vitamin B12. Chemical modification of the substrate is a property other characterized vitamin B12-transport proteins do not exhibit.
Pure User Mode Deterministic Replay on Windows

The ability to record and replay program executions has many interesting applications such as debugging in the backwards direction, discovering and fixing the source of non-deterministic bugs and data races and retracing the steps of a system intrusion. Unfortunately, the power of deterministic replay tools is underutilized by the general public as the tools are either too difficult to deploy or unable to fulfill the performance and log size requirements of the user. As it happens, the majority of the research has been aimed at implementing such tools for Linux, and other platforms, including Windows, have mostly been neglected. In this thesis we look at whether it is possible to implement a deterministic replay tool for the Windows platform that is easily deployable (user mode only without operating system support – this entails no OS modifications or drivers), can record all system calls and their side-effects (even if unknown), works on large programs (1 GB+ RAM), and has a high recording performance (≈2x slowdown). We found that the challenges deterministic replay tools are facing in user mode are exacerbated on Windows due to a lack of documentation and a more restrictive API. Despite this we came up with a design proposal that solves all the problems necessary to implement a deterministic replay tool that satisfies all our requirements for the Windows platform. We present novel techniques to record thread scheduling and non-deterministic instructions. We also describe in detail how to recreate the address space of a recorded program in which code can be executed and access resources directly without instrumentation or modifications just like in the original program. An alternative novel approach to this technique is also suggested. None of the methods rely on operating system support. Although the design proposal remains theoretical we have implemented two partial prototypes that were used to experiment on a small dummy program. Our findings show that it is reasonable to expect a recording slowdown on real programs in the range of 1-5x that will stay consistent even on programs with high memory usage. Regardless, the results are not conclusive and should be taken with a grain of salt.
Investigating the Potential to Estimate Insar Penetration Depth Over Ice Sheets from Pol-Insar Data

Digital elevation models generated with SAR interferometry (InSAR) are an important information source for glacier and ice sheet mass balance. However, the measured elevations suffer from a penetration bias due to the interferometric phase center being up to several tens of meters below the surface. The penetration of the microwave signals depends on SAR parameters (e.g. frequency) and snow and ice conditions. There is potential to estimate this penetration bias directly from the data by means of polarimetric InSAR models. Existing models fail to describe the data across different test sites and ice conditions and phase centers were found to be deeper than predicted by these models. SAR tomography is employed to assess the vertical distribution of backscattering in the data from an airborne campaign. The data are compared to refined models in order to find better representations of the vertical backscattering distribution, while the model complexity is purposely kept simple to make a phase center estimation possible. Additionally, recent work showed the importance of strong subsurface layers which influence phase center depth. Combining the refined subsurface structure models and dominant subsurface layers allows simulating a variety of ice sheet subsurface scenarios and can be used to assess the potential to estimate the InSAR phase center depth directly from the data.
Gold-standard evaluation of a folksonomy-based ontology learning model

Folksonomy, as one result of collaborative tagging process, has been acknowledged for its potential in improving categorization and searching of web resources. However, folksonomy contains ambiguities such as synonymy and polysemy as well as different abstractions or generality problem. To maximize its potential, some methods for associating tags of folksonomy with semantics and structural relationships have been proposed such as using ontology learning method. This paper evaluates our previous work in ontology learning according to gold-standard evaluation approach in comparison to a notable state-of-the-art work and several baselines. The results show that our method is comparable to the state-of the art work which further validate our approach as has been previously validated using task-based evaluation approach.
1 RETAIL CHAINS : MARKET POSITION AND EXPLOITATION

Large constellations of multi-national superand hypermarket chains dispose a significant share of the total volume of seafood products demanded in the European market. These chains have a considerably market position, allowing them to control their suppliers. This paper is based on two research questions; (i) how do the retailers exploit their market position, and (ii) what are the resulting logistical consequences for their suppliers. An interview survey has been carried out among supermarket chains in Norway, Spain, Portugal and United Kingdom in order to address these questions. The topics covered in the interviews were purchase strategy regarding species and products, quality, logistics, suppliers and type of cooperation, market development and future trends. This paper presents the results from the survey, and discusses the retailers’ supplier strategies and the corresponding consequences. The information has been analyzed in order to address mutual and geographical variations among the chains and their markets. One of the significant results is that the majority of retailers, independent of nationality, prefer to invest in a close and long term relationship with a limited number of suppliers. However, the agreements are often considered as an authorisation to do business rather than committing contracts. Hence, the retailers prefer to form a relationship based on the security and benefits of a relational contract, but with the flexibility and competitive elements of a discrete market based relationship. This might give high risks for the suppliers.
hemical composition and seasonal variability of the essential oils of eaves and morphological analysis of Hyptis carpinifolia tone

Hyptis carpinifolia Benth. , Lamiaceae, is a species known popularly as “rosmaninho” and “mata-pasto”, and leaves are employed in Brazilian folk medicine to treat colds, flu, and rheumatism. The aim of this study was to perform a morphological description of H. carpinifolia and to evaluate the seasonal chemical variability of the leaf essential oils during 12 months. Macroscopic characterization of H. carpinifolia was carried out with the naked eye and with a stereoscopic microscope. Essential oils were isolated from leaves by hydrodistillation in Clevenger apparatus and analyzed by gas chromatography/mass spectrometry. esquiterpenes ssential oil composition ,8-Cineole Major compounds were found to be 1,8-cineole (39.6–61.8%), trans-cadina-1(6),4-diene (2.8–17.5%), caryophyllene (4.4–10.0%), prenopsan-8-ol (4.2–9.6%) and -pinene (2.9–5.3%). Results of essential oils compositions were processed by cluster analysis and principal component analysis. Data showed high variability in the concentration of the components. Besides, there was a seasonal variability of chemical composition, probably related mainly to the rainfall regime. © 2016 Sociedade Brasileira de Farmacognosia. Published by Elsevier Editora Ltda. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Mining Large-scale News Articles For Predicting Forced Migration

Many people are being displaced every day from all around the globe. Many of them are forced to leave their homes because of socio-political conflicts, human-made or natural disasters. In order to develop an early warning system for forced migration in the context of humanitarian crisis, it is essential to study the factors that cause forced migration, and build a model to predict the future number of displaced people. In this research, we focus on studying forced migration due to socio-political conflicts for which violence is the main reason. In particular, we investigate whether the degree of violence in a specific region can be detected from news articles related to that region and whether the detected violence scores can be used to improve the prediction accuracy. We investigate three techniques to extract the degree of violence from a corpus of news articles: ED-FE, TD-FE and SWSW. SWSW measures the semantic similarity between documents and a set of seed-words representing violence. ED-FE extracts violent events from news articles, which are the incidents related to attacks or the ones resulting in casualties. TD-FE uses topic modeling techniques to reduce the size of the information for easier analysis and filtering the violent incidents. Experiments indicate that ED-FE and TD-FE provide accurate violence scores which are very effective features for making forced displacement forecasts and using them in prediction models improves the prediction accuracy.
Slip Effects on Unsteady MHD and Heat Transfer Flow over A Stretching Sheet Embedded with Suction in A Porous Medium Filled With A Jeffrey Fluid

The effects of slip on unsteady MHD flow and heat transfer of a Jeffrey fluid flow over a stretching sheet embedded through porous medium in the presence of suction are examined. The unsteady flow problems is reduced to ordinary differential equations using similarity transformations and are solved numerically using Runge-Kutta fourth order in association with shooting technique in MATLAB. Based on the solution of these equations an extensive analysis is performed to investigate the effects. The effects of non-dimensional parameters such as suction parameter, Jeffrey parameter, magnetic parameter, permeability parameter, Prandtl number, thermal radiation parameter, heat source or sink parameter and Eckert number on velocity and temperature profiles are presented graphically moreover, the numerical values of the skin friction coefficient and the local Nusselt number are calculated and shown in tabular form. It is found that present result has been good agreement with the existed studies under some special cases.