Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphological Parsing by Foveal Split: Evidence from Anaglyphs

We investigated the early moments of visual word recognition, when the retinal information—by hypothesis split vertically along the fovea—is divided into two visual pathways, projecting the right visual field into the left hemisphere (LH), and the left visual field into the right hemisphere (RH). Wearing red/blue anaglyph glasses, participants performed a lexical decision task to compounds (FOOTBALL) and monomorphemic words that were either pseudo-compounds (CARPET) or unsegmentable (JINGLE). The stimuli were presented (masked, 60 ms exposure) in three color combinations: all black, red/blue (ipsilateral visual pathways), and blue/red (contralateral pathways). For the red/blue and blue/red conditions, the colors were split either at the morpheme boundary (legal split) or at a character to the left or to the right of the split (illegal split). We found an advantage (RT and accuracy) of compounds over non-compounds, independent of pathway, and an advantage of legal vs. illegal constituent split. Results suggest that the visual word recognition system performs parsing analyses that are in consonant with the morphological objects of the language. The advantage of pseudo-compounds over unsegmentables suggests that at an early—pre-lexical—stage the system is partially insensitive to the semantic properties of the whole word.
Students’ attitudes towards distance education: A comparative study between Sino-foreign cooperative universities and typical universities in China

The global pandemic in Spring 2010 catapulted hundreds of universities worldwide into the realm of online education. Technological advancements over the last two decades had made online education viable but it was still a relatively small part of higher education. For most students the move to online education was not a choice or an option but a necessity and their reactions will play an important part in strategic decisions made in higher education for years to come. It is important to understand their perception’s and attitudes towards online education. The implications for Western universities with campuses in China are significant due to the vast differences in delivering US accredited course content online vs in person in China. Sino-foreign cooperative universities deliver Western curriculum courses in English thereby providing students with a different academic experience than typical Chinese universities. An exploration of whether the attitude of Sino-foreign cooperative university students and Chinese university students towards distance education is different is relevant at this time. Data was collected by an online survey completed by both students of typical Chinese universities and of Sino-foreign universities. The results suggest that students had a generally positive attitude towards distance education and that there were no significant differences in students’ attitudes towards distance education as a function of the type of university they attend. The findings are of interest because if Chinese students prove receptive to online education in general, the type of opportunities for SinoChinese Universities are significantly changed.
EFFECT OF SUPPLEMENTATION BROILER DIETS WITH DIFFERENT LEVELS OF POLYUNSATURATED FATTY ACIDS ON PRODUCTIVE AND SOME BIOCHEMICAL TRAITS

The study aimed to evaluate of adding multiple sources of polyunsaturated fatty acids (PUFA’s) to diets and their effects on productive performance and some biochemical traits of broiler. The study was conducted at the poultry farm belong to department of animal production/College of Agriculture-University of Anbar from 26/12/2017 to 6/2/2018 (42 day). A total of 210, One-day old unsexed Ross (308) chicks with average weight 40 gm. , were randomly distributed to seven treatments with three replicates per treatment (10 chicks/ replicate). Birds in T1 were fed a basal diet used as control, T2 included addition of Conjugated Linoleic Acid (CLA) with (3 gm/kg feed), T3 included addition of Flaxseed Oil (FXO) with (3 gm/kg feed), T4 included addition of Fish Oil (FO) with (3 gm/kg feed), T5 included addition of (CLA) and (FXO) with (1.5+1.5 gm/kg feed)respectively, T6 included addition of (CLA) and (FO) with (1.5+1.5 gm/kg feed)respectively, T7 included addition of (CLA), (FXO) and (FO) with (1+1+1 gm/kg feed)respectively. All diets were formulated to meet the same requirements. Broiler were fed with water and feed ad libitum. The data of Body Weight Gain (BWG), Feed Consumption (FC) and Feed Conversion Ratio (FCR) were recorded weekly. The results of supplementation CLA, FXO and FO with (1+1+1 gm/kg feed) respectively (T7) had significant increase (P<0.05) in live body weight, Body weight gain accumulative and relative growth rate as compared with T2 addition of (CLA) with (3 gm/kg feed) and T1 (Control). Also results revealed significant improvement in Accumulative feed conversion ratio of birds in T2, T3, T4, T5, T6 and T7 comparison with T1 (Control). No significant differences recorded between treatments in Feed consumption and Blood biochemical traits included: Globulin, Albumin, Glucose, High density lipoprotein (HDL), Low density lipoprotein (LDL), Very low density lipoprotein (VLDL), Triglycerides (T.G) and Cholesterol (T.Chol.) at 42 days of age.
Amphiphilic polymers in disperse systems

The amphiphilic polymers have a lot of particular physical and chemical properties such as; the aggregation shape and size, the hydrophilic and the lipophilic segments, etc. The researchers on amphiphilic polymers focus on polymers material field. The important theories and signification in using amphiphilic polymers are known to all with its good performances in many fields. In this work initially, the Giesekus model was used to study the rheology of the amphiphilic polymers solution. The Giesekus model includes three parameters that describe any used polymer, and the parameters were selected from the literature data. A mathlab code was created to simulate the Giesekus model. The obtained results showed shear thinning at the shear rate range. Finally, the Hydrophilic-Lipophilic Amphiphilic polymers in disperse systemsــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ ـ University Bulletin – ISSUE No.17Vol. (2) – August2015. 6 Deviation (HLD) and Net-Average Curvature (NAC) model was presented. The HLD_NAC model was used to predict the phase behavior of microemulsion and the properties of microemulsion. Depending on microemulsion morphology, some models from literature were presented to predict the microemulsion rheology. The predicted microemulsion morphology and viscosity may be useful in the design of formulations for enhanced oil recovery.
Payable Management on Corporate Profitability of Brewery Manufacturing Companies in Nigeria

This study examines the effect of the management of accounts payable on the profitability of Brewery companies in Nigeria. The variables include, Accounts payable, Debt ratio and sales growth rate. Secondary sources of data were used for the period 2000-2011. The hypotheses were tested using multiple regression analytical tools. The results show that accounts payable had negative but non significant relationship with profitability ratio of the companies under Brewery manufacturing companies in Nigeria. Debt ratio had positive and significant relationship, while sales growth rate was negative and significant with the profitability ratio of Brewery companies in Nigeria.
A LSH-based Method for Similarity Queries on Binary Hybrid Data

Locality Sensitive Hashing (LSH) has been widely used in high-dimensional data and large-scale datasets for nearest neighbor queries, but LSH is mostly applied for data with a single data type, so this paper attempts to adapt LSH to binary hybrid data, such as data with image and text, data with location and text, etc. On the one hand, an effective index is difficult to be built on binary hybrid data, which are normally high-dimensional data consisting of different datastructures. On the other hand, for different data types, distance functions are different. Such as Euclidean distance function for numeric data, Jaccard distance function for character data, etc., soflexible similarity queries are difficult to efficiently processed on binary hybrid data, which should consider similarity of two data types simultaneously. To this end, this paper proposes a generalized LSH 网络出版时间:2017-02-24 14:34:00 网络出版地址:http://kns.cnki. net/kcms/detail/11.1826. TP.20170224. 1434.012. html
A disproof of representationalism

A definition of representationalism I am here concerned with representationalism as a basic belief about meaning. A ‘representation’ I take to be a linguistic formulation in the mind that is believed to be actually or potentially true or false. ‘Representationalism’ is thus the belief that language takes its meaning from an actual or potential relationship with states of affairs. This includes the truth-correspondent theory of meaning, but also subsumes a Wittgensteinian variant that makes the meaning of language dependent on a relationship with social states of affairs (such as the expectations of the language-users). Representationalism in this sense should not be confused with the senses in which it is sometimes used in epistemology (where it is equivalent to indirect realism) or in aesthetics. My goal here is not to refute representations in the mind in order to argue for a direct account of perception, but rather to disprove representationalism in meaning, which is a belief that both direct and indirect realists are likely to share, along with the vast majority of philosophers in the analytic tradition. Direct realists are just as much representationalists on my account, because even if they believe that perception is of actual objects, they must also concede that language represents those objects in a form different from perception.
Jaaru: Efﬁciently Model Checking Persistent Memory Programs Extended Abstract

Non-volatile memory technologies such as Intel Optane DC memory have recently become available. These technologies provide both near DRAM performance and the persistency of disks. Persistent memory presents an interface much like DRAM — programs perform normal load and store instructions to access persistent storage, bypassing the operating system to achieve higher performance — and provides a way for developers to redesign how programs manage data. For example, persistent memory makes it possible to use a single copy of a data structure for both a working in-memory copy of the data structure and as a persistent store for the data. This eliminates the overheads of serialization and deserialization and may simplify working with large data sets. Ensuring crash consistency for persistent memory data structures is extremely challenging. Stores to persistent memory do not immediately become persistent — they are first written to the volatile cache and do not become persistent until their cache line is flushed to persistent memory. As this can take an arbitrary amount of time to happen due to cache capacity constraints, later stores can be made persistent before earlier stores. To enforce ordering properties as well as that stores are made persistent in a timely manner, it is necessary to use special instructions to explicitly flush cache lines, such as clflush and clflushopt. Writing correct data structures for persistent memory in the presence of failures requires developers to carefully reason about the subtle ordering and persistency properties their code relies upon and to ensure that they enforce those properties with the appropriate use of flush and fence instructions. Our experience with persistent memory benchmarks suggests that it is very easy to make a mistake (e.g., forget to add the necessary flush instructions). Testing persistent memory programs is particularly challenging. Missing cache flush instructions would not become apparent unless the machine suffers from a failure at a very specific interval in the execution. Moreover, trying to test data structures by abruptly cutting power to a machine creates numerous practical challenges including the risk of corrupting other programs on the machine. This paper presents a novel model checker, named Jaaru, to find bugs in persistent memory programs. Jaaru exhaustively explores the space of executions from non-determinism due to cache line persistency without needing any user annotations. Jaaru is also efficient due to (1) a constraint refinement based approach for partial order reduction that drastically reduces the state space to be explored and (2) an effective leverage of commit stores – a common programming pattern – that can reduce the number of steps taken from exponential in the length of a program execution to quadratic.
Strongly Connected Components Based Efficient PPR Algorithms

Personalized PageRank(PPR)is usualy employed to rank the nodes of graphs.Due to the ever increasing volume of graph,how to improve the efficiency of PPR computations has become a research focus.Thus the purpose of this paper is to improve the efficiency of PPR computations.The existing optimization algorithms can be generaly classified into two categories: distributed algorithm and serial algorithm,and the general approach of them is mainly through partitioning the computations on the big graph into computations on multiple smaler sub-graphs, but the communication between sub-graphs usualy involve a large amount of data and is of a high frequency.The SCC(Strongly Connected Component)based algorithms proposed in this paper can resolve these problems effectively.The main computation steps of them is:first identify and remove volumes of unrelated nodes and edges quickly before PPR computation,then transform the PPR computations on big graph into that on multiple SCC sub-graphs,which make the multiple data communications between sub-graphs turn into one time communication.The SCC based algorithm in this paper can reduce not only the communication amount between SCCs but also the storage I/O frequency,while keeping high algorithm accuracy.The experiments demonstrate that the algorithms proposed in this paper can make obvious improvements for the PPR computation efficiency.
Is Inflation Bias Beneficial? Evidence from a Typical Discretionary Monetary Policy Strategy

A discretionary central banker accepts excess inflation (inflation bias) either to stabilize real growth or spur it beyond the natural rate of economy. The paper posits that empirical investigation of the extent of effectiveness of inflation bias per se in achieving these objectives is important in (i) defining the scope of monetary policy as an inflation and growth-stabilizer and (ii) assessing if discretion should be preferred over commitment for achievement of such dual objectives. Since, no inflation bias indicators exist to carry out appropriate empirical analysis, this paper proposes a framework to generate new inflation bias indicators for a typical example of the discretionary monetary policy strategy of Pakistan. Autoregressive distributed lag (ARDL) bounds testing and estimation strategy is used not only to account for optimal dynamics but to avoid spurious regression and endogeneity problems. The findings of the paper, based on stable and robust results suggest that inflationstabilization should be the prime objective of monetary policy. To avoid long-term real growth losses, a commitment based monetary policy should be preferred to discretion as the latter produces inflation bias, which is significantly detrimental to real growth in the long-run. Jel Code: E52, E58, E5,E32, C32, E31
Mixotrophy among Dinoflagellates’

Mixotrophy, used herein for the combination of phototrophy and phagotrophy, is widespread among dinoflagellates. It occurs among most, perhaps all, of the extant orders, including the Prorocentrales, Dinophysiales, Gymnodiniales, Noctilucales, Gonyaulacales, Peridiniales, Blastodiniales, Phytodiniales, and Dinamoebales. Many cases of mixotrophy among dinoflagellates are probably undocumented. Primarily photosynthetic dinoflagellates with their “own” plastids can often supplement their nutrition by preying on other cells. Some primarily phagotrophic species are photosynthetic due to the presence of kleptochloroplasts or algal endosymbionts. Some parasitic dinoflagellates have plastids and are probably mixotrophic. For most mixotrophic dinoflagellates, the relative importance of photosynthesis, uptake of dissolved inorganic nutrients, and feeding are unknown. However, it is apparent that mixotrophy has different functions in different physiological types of dinoflagellates. Data on the simultaneous regulation of photosynthesis, assimilation of dissolved inorganic and organic nutrients, and phagotophy by environmental parameters (irradiance, availablity of dissolved nutrients, availability of prey) and by life history events are needed in order to understand the diverse roles of mixotrophy in dinoflagellates.
Data Mining & Machine Learning Algorithms for Air Pollutant Prediction

Air pollution can be defined as existence or initiation of a liquid, solid, and gases in the environment which have noxious effects on human health’s and animals and environment. Now a day’s fresh air of environment is getting polluted due to harmful substances like biological molecules, noxious substances and harmful gases. The focus of this paper is to study about the data mining and machine learning techniques used for prediction of air pollution and the mainly focus is on the prediction of PM2.5 on the basis of all the other air pollutants and temperature and humidity. For implementing such type of model different types of classification and prediction algorithms are used.
Coupled QM/MM Molecular Dynamics Simulations of HCl Interacting with Ice Surfaces and Water Clusters − Evidence of Rapid Ionization

We present the results of coupled quantum mechanics and molecular mechanics (QM/MM) classical molecular dynamics simulations for HCl sticking to the (0001) basal plane of ice Ih. Interatomic forces and energies of hydrogen chloride and up to 24 water molecules in the top ice bilayer were obtained from semiempirical molecular orbital calculations based on the PM3 method. A few PM3 parameters were adjusted so that structural and energetic properties of small neutral and ionic systems match available ab initio and experimental data. This QM region was coupled to the remainder of the ice surface (the MM region), which was treated using the analytic TIP4P force field. The surface temperature was between 0 and 180 K, and the dynamics was followed for 100 ps. On surface impact, HCl binds to a dangling (free) H2O oxygen via a ClH−OH2 hydrogen bond. If the Cl is solvated by one dangling H2O hydrogen, HCl adsorbs molecularly. If two dangling hydrogens are available in a surface hexagon, HCl dissociates to a Cl-−H3O.
Weakly Supervised Part-of-Speech (POS) Tagging without Disambiguation

Weakly supervised part-of-speech (POS) tagging aims to predict the POS tag for a given word in context by making use of partially annotated data instead of fully tagged corpora. As POS tagging is crucial for downstream natural language processing (NLP) tasks such as named entity recognition and information extraction, weakly supervised POS tagging is speciﬁcally attractive in languages where tagged corpora are mostly unavailable. In this paper, we propose a novel framework for weakly supervised POS tagging where no annotate corpora are available and the only supervision information comes from a dictionary of words where each of them is associated with a list of possible POS tags. Our approach is built upon error-correcting output codes (ECOC) is which each POS tag is assigned with a unique L -bit binary vector. For a total of O POS tags, we therefore have a coding matrix M of size O × L with value { 1 , − 1 } . Each column of the coding matrix M speciﬁes a dichotomy over the tag space to learn a binary classiﬁer. For each binary classiﬁer, its training data is generated in the following way: a word will be considered as a positive training example only if the whole set of its possible tags falls into the positive dichotomy speciﬁed by the column coding; and similarly for negative training examples. Given a word, its POS tag is predicted by concatenating the predictive outputs of the L binary classiﬁers and choosing the one with the closest distance according to some measure. By incorporating the ECOC strategy, the set of all possible tags for each word is treated as an entirety without the need of performing disambiguation. Moreover, instead of manual feature engineering employed in most previous POS tagging approaches, features for training and testing in the proposed framework are automatically generated using neural language modeling. The proposed framework has been evaluated on three corpora for English, Italian and Malagasy POS tagging, achieving accuracies of 93.21%, 90.9% and 84.5% respectively, which shows a signiﬁcant improvement compared to the state-of-the-art approaches.
Semantic Grid Map based LiDAR Localization in Highly Dynamic Urban Scenarios

—Change-over-time objects such as pedestrians and vehicles remain challenging for scan-to-map pose estimation using 3D LiDAR in the ﬁeld of autonomous driving because they lead to incorrect data association and structural occlusion. This paper proposes a novel semantic grid map (SGM) and corresponding algorithms to estimate the pose of observed scans in such scenarios to improve robustness and accuracy. The algorithms consist of a Gaussian mixture model (GMM) to initialize the pose, and a grid probability model to keep estimating the pose in real-time. We evaluate our algorithm thoroughly in two scenarios. The ﬁrst scenario is an express road with heavy trafﬁc to prove the performance towards dynamic interferences. The second scenario is a factory to conﬁrm the compatibility. Experimental results show that the proposed method achieves higher accuracy and smoothness than mainstream methods, and is compatible with static environments.
Ownership Structure and Firm Growth: Evidence from Vietnam

This study aims to investigate the relationship between ownership structure and firm growth in the context of an emerging economy by employing a sample of more than 2,000 firm-year observations of listed companies in the period 2013–2017. Using the randomand fixed-effects specifications for panel data, we find that the state ownership has a negative effect on the growth of firms, while there is no statistical significance between foreign ownership and firm growth. This paper contributes to the literature byproviding some novel insight into the influence of ownership structure on firm growth. The paper provides some policy recommendation to support the growth of Vietnamese enterprises.
Sentiment Analysis on Nepali Movie Reviews using Machine Learning

—This research article presents machine learning methods for detecting the sentiment expressed by movie reviews. The semantic orientation of a review can be positive or negative. Analysis of opinion for particular product, news or document could be beneﬁcial to many companies, institutions and individuals for marketing, advertising, question answering, product selection and so on. We have created a Nepali movie review dataset with total 500 samples having 250 samples per each positive and negative class of sentiment from various online sources. Sentiment analysis system implements various natural language processing techniques for document preprocessing and feature extraction. Naive Bayes based machine learning technique is used for the classiﬁcation of the sentiment. Empirical results shows, classiﬁcation accuracies are, 79 . 23% of precision, 78 . 57% of recall and 78 . 90% of F-score.