Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing the Internet Research Agency’s Social Media Operations During the 2016 U.S. Presidential Election using Linguistic Analyses

Converging investigations on the part of multiple agencies/agents have provided overwhelming evidence for Russian interference in the 2016 U.S. presidential election. As a part (and consequence) of recent reports, multiple datasets that capture actions taken by actors of the Internet Research Agency (IRA), have been released to the public. In the cur-rent paper, we present and abridged report of several preliminary forensic analyses of Facebook ad data and Twitter troll accounts that were run by the IRA during the election cycle. Through the use of language analysis, we characterize the evolution of IRA content over the course of the election cycle, providing a basis for understanding how left- and right-leaning ideologies were differentially targeted to spread enmity among the American electorate. Additionally, through an analysis of syntactic constructions, we find that the content produced by the IRA on Twitter was linguistically unique from a control sample of English-speaking Twitter accounts. Altogether, our findings suggest that the IRA’s operations were largely unsophisticated and “low-budget” in nature, with no serious attempts at point-of-origin obfuscation being taken.
Faster Convergence to Realized Volatility with Microstructure Noise

The volatility of asset return plays a critical role for high-frequency trading. However, the microstructure noise could bias the estimated realized volatility. Zhang et al. (2005) propose a batch estimator for the realized volatility of highfrequency data in the presence of microstructure noise. It gives the estimates after all the data arrive. This paper proposes a recursive version of their estimator that outputs volatility estimates as the data arrive. Our estimator gives excellent estimates well before all the data arrive. Both real high-frequency futures data and simulation data confirm the performance of the recursive estimator.
HR Transactional Services : Four Associated Factors for Successful Operation

This paper presents a case study on HR transactional services in a leading financial services association in the UK. The study has identified four associated factors for a successful delivery of HR transactional services and assessed how these factors are practised in two separate HR divisions of Transactional Shared Services and Strategic HR Teams. Based on six in-depth semi-structured interviews, our findings suggest that in order to effectively deliver HR shared services, the proposed four associated factors must be flexible to business change and fluid in practice.
Edible Oil Quality Adding Value to OKLAHOMA

Introduction Majority of the edible oils used for cooking, frying and food formulations are derived from plant sources, specifically from oilseeds such as soybean, canola, sunflower seeds, cottonseed and peanuts. Edible vegetable oils are liquid at room temperature and comprised of mainly triacylglycerides that are made up of three fatty acids attached to a glycerol molecule through ester bonds (see fact sheet FAPC-196 Lipid Glossary). Physical, chemical and nutritional properties of vegetable oils vary significantly depending on the type of fatty acids present in the oil. Unsaturated fatty acid content of vegetable oils is significantly higher than that of animal fats. Although high unsaturated fatty acid content makes the oil healthier, highly unsaturated oils are prone to fast oxidation and quality deterioration during processing, handling and storage. Vegetable oils also contain other compounds in minor amounts that affect their quality and nutritional value. Phytosterols, tocopherols, waxes are some of the minor components of vegetable oils (less than 1 percent of the oil). These compounds are not regularly analyzed for oil quality evaluation purposes partly due to the complexity of the analytical protocols and the need for expensive instruments for testing. Oil quality deteriorates by hydrolysis, oxidation and polymerization of the oil. Hydrolysis increases the amount of free fatty acids (FFA), monoand diacylglycerols and glycerols in oils. Oxidation produces hydroperoxides and low molecular weight volatile compounds such as aldehydes, ketones, carboxylic acids, and short chain alkanes and alkenes. Dimers and polymers also are formed when oil is exposed to high temperatures during cooking and frying. Monitoring and maintaining edible oil quality are paramount importance to ensure safety of the product for consumption. Although there is no official standard set for evaluating edible oil quality, FFA content, peroxide value (PV) and p-anisidine value (AV) are commonly used in industry to report edible oil quality. This fact sheet summarizes edible oil quality parameters used in industry and for research purposes.
Economic Returns from Social and Political Globalization: Does Signaling Help Developing and Transition Countries to Attract Foreign Direct Investment?

I examine whether a developing or transition country’s political and social engagement in the international system – labeled as a country’s political and social globalization – has a positive influence on its ability to attract foreign direct investments (FDI), and hence, on the amount of FDI that it receives. My research is motivated by insights from signaling theory, which posits that actors provide information about themselves through signals in situations where the underlying quality or nature of such actors is less than perfectly discernible. A high degree of political and social globalization can potentially serve as a positive signal to foreign investors that a country is “invested” in the international system, global society, and in the larger global political economy, thereby lowering the perceived risk of investing in this country. As part of the empirical analysis, I undertake multivariate regressions using panel data on more than 100 developing and transition countries. The results show that both political and social globalization lower the perceived country risk in terms of attracting FDI. While social globalization helps attract FDI through both strategic and non-strategic signaling, the same is true for political globalization only with strategic signaling and not with non-strategic signaling. Given the importance of FDI to growth and development, the findings of this study can particularly inform policymakers in developing and transition countries.
Robust Fault Detection for a Class of Uncertain NonlinearSystems Based on Multiobjective Optimization

A robust fault detection scheme for a class of nonlinear systems with uncertainty is proposed. The proposed approach utilizes robust control theory and parameter optimization algorithm to design the gain matrix of fault tracking approximator (FTA) for fault detection. The gain matrix of FTA is designed to minimize the effects of system uncertainty on residual signals while maximizing the effects of system faults on residual signals. The design of the gain matrix of FTA takes into account the robustness of residual signals to system uncertainty and sensitivity of residual signals to system faults simultaneously, which leads to a multiobjective optimization problem. Then, the detectability of system faults is rigorously analyzed by investigating the threshold of residual signals. Finally, simulation results are provided to show the validity and applicability of the proposed approach.
Optimization design and motion simulation of multi-link mechanism based on mechanical press

Multi-link mechanism of mechanical press has gradually become an important technology for the development of machinery industry in the current era. However, there are still many shortcomings in the theory and operation of this technology. The theory of multilink mechanism of mechanical press in China was summarized and compared with the traditional presses. Mechanical horses were taken as examples, and the relevant major influencing factors were identified and optimized. The results show that the optimized mechanical horse is more stable. The purpose of this study is to provide scientific support for the improvement of the theory of multi-link mechanism of mechanical press in China and to provide a positive impact on the development of machinery industry in China.
Uncovering markers for downy mildew resistance in grapevine through mass spectrometry-based metabolomics

O mildio e uma ameaca importante a industria vitivinicola e o desenvolvimento de hibridos entre Vitis vinifera e Vitis spp. selvagens, resistentes a doenca, e uma estrategia promissora no combate a esta doenca. A descoberta de marcadores metabolicos e essencial. Neste trabalho pretendemos acelerar o processo de selecao das caracteristicas de resistencia ao mildio utilizando metabolomica baseada em espectrometria de massa de elevada resolucao para a descoberta de marcadores de resistencia. Comparamos a cultivar suscetivel ‘Trincadeira’ com a mais resistente ‘Regent’. Ambas foram facilmente discriminadas com base no seu perfil metabolico, tendo sido encontrados varios picos exclusivos de cada cultivar.
PaSTRI : A Novel Data Compression Algorithm for Two-Electron Integrals inQuantum Chemistry ∗ Extended Abstract

Integral computations for two-electron repulsion energies are very frequently used applications in quantum chemistry. Computational complexity, energy consumption and the size of the output data generated by these computations scales with O(N4), where N is the number of atoms simulated in the system. In many applications, the same integrals are required to be calculated multiple times. Storing these values and reusing them requires impractical amounts of storage space; whereas recalculating them requires a lot of computations. On the other hand, generated data typically requires much less precision than the built-in floating point data types. We propose PaSTRI (Pattern Scaling for Two-electron Repulsion Integrals), a fast novel compression algorithm which makes it possible to calculate these integrals only once, store them, and reuse them at much smaller computational cost then recalculation. PaSTRI is lossy compared to floating point numbers, but still maintains the precision level required by the integral computations. PaSTRI is an extension to SZ[1] compressor package as a part of ECP-EZ. We have evaluated our compressor using GAMESS[4] dataset, and achieved 17.5:1 compression ratio whereas compression ratios for original SZ was 8.0:1 and ZFP[3] was 7.1:1.
Modelling of Sequential Casting Procedure of Foundation Slabs

Abstract In this paper, we present computer simulation results of foundation concrete slab behaviour in an early stage. The Künzel and Kiessl`s model was used to analyze heat and moisture fields and was extended by a set of climatic conditions and by a model of hydration heat evolution in concrete. The isotropic damage model was used together with the B3 model for description of concrete mechanical behaviour. The problem was solved using program SIFEL. The code was extended by the implementation of the sequential construction using time controlled switching on/off of particular degrees of freedom. This extension affected results significantly.
A Complete Bengali OCR: A Novel Hybrid Approach to Handwritten Bengali Character Recognition

A complete Bengali OCR is presented incorporating a novel hybrid approach to handwritten Bengali character recognition. The idea is to combine structural analysis and template matching techniques in order to recognise the handwritten Bengali characters. Handwritten Bengali characters are inherently cursive and there is an absence of well-defined strokes. In this approach, the character set has been separated into different distinct sub-classes based one some distinguishable structural features. Details of several approaches to detect these structural features are presented. Structural and syntactic features have been generated from the training samples to generate distinct character signatures. A match dictionary has been devised based on these character signatures, that helps in collecting multiple prototypes from the training samples. A revised form of continuity analysis is applied to match the test characters to the characters in the match dictionary. This complete OCR has been thoroughly implemented and tested and very promising results have been achieved in this direction.
Bulk-bin-packing based migration management of reserved virtual machine requests for green cloud computing

The dynamic consolidation of Virtual Machines (VMs) into a minimum number of Physical Machines (PMs) is a key energy-efficient practice in a cloud data centre, to reduce the running PMs and save electricity costs. We proposed a migration based VM consolidation approach for reserved requests. Real Dataset EC2 was used in the simulation experiments. The proposed BBPMM has demonstrated the elastic capability of adjusting the running PMs and it reduced 38% of running PMs in a reservation transition period.
Formalizing Constructive Cryptography using CryptHOL

Computer-aided cryptography increases the rigour of cryptographic proofs by mechanizing their verification. Existing tools focus mainly on game-based proofs, and efforts to formalize composable frameworks such as Universal Composability have met with limited success. In this paper, we formalize an instance of Constructive Cryptography, a generic theory allowing for clean, composable cryptographic security statements. Namely, we extend CryptHOL, a framework for game-based proofs, with an abstract model of Random Systems and provide proof rules for their equality and composition. We formalize security as a special kind of system construction in which a complex system is built from simpler ones. As a simple case study, we formalize the construction of an information-theoretically secure channel from a key, a random function, and an insecure channel.
A study on factors influencing compressive strength of CO 2-cured concrete

CO2 curing of concrete is an effective process to cure concrete products and utilize CO2. To improve the CO2 curing efficiency and strength of CO2-cured concrete blocks, factors influencing the compressive strength of CO2-cured concrete, such as specimen molding pressure, procuring relative humidity, pre-curing time, effective water to cement ratio, the degree of vacuum in curing chamber, CO2 pressure and concentration, were experimentally investigated. The results indicated that the strength of concrete specimens after CO2 curing correlated well with the CO2 curing degree. The suitable conditions, which could not only improve the curing efficiency, but also improved the strength of cured concrete products, include: molding pressure of 15 ~ 25MPa, pre-curing of three hours at relative humidity between 60-70%, effective water to cement ratio between 0.15 and 0.25, the degree of vacuum in curing chamber at -0.06 ~-0.09MPa, CO2 pressure and concentration at 0.20 ~ 0.40MPa and 60% respectively.
ALLELIC COMPOSITION AT GLU GENES IN A COLLECTION OF SPRING WHEAT GERMPLASM

For HMW-GS, a total of 16 different subunits and 30 allelic haplotypes were identified. The expression of HMW-GS ranged from 3 to 5 per genotype instead of 6 per genotype, revealing the phenomenon of gene silencing. The 2* was the most frequent subunit for Glu-A1 locus and was found in 52.45% lines. Eight subunits were identified for Glu-B1 locus. Five subunit pairs i.e. 6+8, 7+8, 7+9, 13+16 and 17+18 were present in the germplasm. Some single subunits i.e. 6, 7, 8 and 20 were also found. Subunit pair 17+18 was the most frequent with a partial frequency of 32.17%. For Glu-D1, four subunit pairs i.e. 2+12, 5+10, 2+11 and 5+11 were observed. The 5+10 was the most frequent subunit for Glu-D1 and was present in 65.03% lines. The 2+12 subunit pair was identified in 34.97% lines. For Glu3 loci 18 LMW subunits were identified. For Glu-A3, five subunits i.e. b, c, d, e and g were identified. Eight subunits i.e. b, c, d, f, g, h, i and j were identified for Glu-B3 locus. Four subunits i.e. a, b, c and l were identified for Glu-D3 locus.
A Method of Hyponym Acquisition Based on “isa” Pattern

The research on hyponymic relations acquisition is a basic and crucial problem in the field of knowledge ac- quisition of text.For the hyponym acquisition in hyponymic relation acquisition based on pattern,combined with our research work,we introduce a method of hyponym acquisition based on“isa”pattern.Firstly,we make use of the dic- tionary and sentence patterns that have been semi-automatically obtained to analyze“isa”pattern.Then we obtain hyp- onyms of different quantity according to different rules.In the experiment analysis,we got a good result by using the method.
Automatic Creation of Artistic Chinese Calligraphy

We present an approach to creating Chinese calligraphy with particular style from learning author’s written works automatically. Our first contribution is a method to represent Chinese character topology via fuzzy relative position. Our second contribution is an algorithm to take topological features as features fed into the evaluation model, which is a decision tree algorithm. Our third contribution is an algorithm of heuristic search in the optimization glyph phase. To improve the converge speed, we introduce hypothesis testing and the decay function of transformation amplitude. The experiments demonstrate our algorithm can obtain the similar style Chinese calligraphy with training samples.
Flame Prediction Based on Harmful Expression Judgement Using Distributed Representation

In recent years, flaming-that is, hostile or insulting interaction-on social media has been a problem. To avoid or minimize flaming, enabling the system to automatically check messages before posting to determine whether they include expressions that are likely to trigger flaming can be helpful. We target two types of harmful expressions: insulting expressions and expressions that are likely to cause a quarrel. We first constructed an original harmful expressions dictionary. To minimize the cost of collecting the expressions, we built our dictionary semi-automatically by using word distributed representations. The method used distributed representations of harmful expressions and general expressions as features, and constructed a classifier of harmful/general expressions based on these features. An evaluation experiment found that the proposed method was able to extract harmful expressions with an accuracy of approximately 70%. The proposed method was also able to extract unknown expressions; however, it tended to wrongly extract non-harmful expressions. The method is able to determine unknown harmful expressions not included in the basic dictionary and can identify semantic relationships among harmful expressions. Although the method cannot presently be applied directly to multi-word expressions, it should be possible to add such a capability by introducing time-series learning.
Utterance Embedding Knowledge Attention Self-Attention Context Attention Feed-Forward Target Embedding Self-Attention Context Attention Utterance Attention Feed-Forward Target Embedding Self-Attention Knowledge Attention First-Pass Attention Feed-Forward Document / Utterance Embedding Feed-Forward S

Document Grounded Conversations is a task to generate dialogue responses when chatting about the content of a given document. Obviously, document knowledge plays a critical role in Document Grounded Conversations, while existing dialogue models do not exploit this kind of knowledge effectively enough. In this paper, we propose a novel Transformerbased architecture for multi-turn document grounded conversations. In particular, we devise an Incremental Transformer to encode multi-turn utterances along with knowledge in related documents. Motivated by the human cognitive process, we design a two-pass decoder (Deliberation Decoder) to improve context coherence and knowledge correctness. Our empirical study on a real-world Document Grounded Dataset proves that responses generated by our model significantly outperform competitive baselines on both context coherence and knowledge relevance.
An over view of climate change in the southwestern part of Bangladesh in Jessore and Sathkhira districts and rice Yield response ; an analysis of aggregate level data

This study examines the association between the yield of three main rice crops (e.g., Aus, Aman and Boro) and three main climate variables (e.g., extreme temperature, least temperature and rainfall) for Bangladesh especially Jessore and Sathkhira districts. We use time series data for the 1972–2009 period at an aggregate level to evaluate the association between climate variables and rice harvest using both the normal least rectangles and median (quartile) regression approaches. The findings of this study approve that climate variables have had important belongings on rice yields but that these properties vary among three rice crops. Extreme temperature is statistically important for all rice crops with optimistic belongings on Aus and Aman rice and contrary belongings on Boro rice. Lowest temperature has a statistically important bad effect on Aman rice and a significantly confident effect on Boro rice. Finally, rainwater has a statistically important result on Aus and Aman rice. However, the effects of extreme temperature and least temperature are more distinct compared with that of rainfall. Given these special effects of temperature on rice crops and swelling climate change susceptibilities, policy makers should fund the study and progress of temperature lenient rice varieties, mainly for Aman and Boro rice.
An Alternative Approach to RSVP-aware MBone Applications

QoS guarantee is one of the most critical issues for deploying multicast-style applications. However, the complexity of communication between applications and QoS mechanism decreases the utility of QoS provisioning. In this paper, we will propose an alternative approach to RSVP-aware MBone applications. This approach adopts RLR (RSVP Library Redirection), which can transform legacy Internet applications into RSVP-aware without modifying their source codes. We will extend the ability of RLR to support UDP (User Datagram Protocol), multicast-style MBone applications and use Vic as an example to illustrate how to transform legacy applications into RSVP-aware. We also deploy a user interface for users to adjust their reservation requirement.
A Computationally Efficient and Temporally Scalable Dynamic Traffic Simulation and Assignment System – Dynamic Urban Systems in Transportation ( DynusT )

The dynamic traffic simulation and assignment model DynusT (Dynamic Urban Systems in Transportation) is a model system that is designed and implemented to perform simulationbased dynamic traffic assignment (DTA) analysis. Due to its unique algorithmic structure and software implementation, it is capable of performing DTA on regional-level networks with long simulation period. This makes DynusT particularly well-suited for regional level modeling such as regional transportation planning, corridor studies, integration with activity-based models and mass evacuation modeling. The purpose of this paper is to present an overview of the theoretical and algorithmic innovation in DynusT.