Miracle-dz/UniFAR-FTUs huggingface dataset:
A Genetic Programming Model for S&P 500 Stock Market Prediction

The stock market is considered one of the most standard investments due to its high revenues. Stock market investment can be risky due to its unpredictable activities. That is why, there is an urgent need to develop intelligent models to predict the for stock market index to help managing the economic activities. In the literature, several models have been proposed to give either shortterm or long-term prediction, but what makes these models supersede the others is the accuracy of their prediction. In this paper, a prediction model for the Standards & Poors 500 (S&P500) index is proposed based Genetic Programming (GP). The experiments and analysis conducted in this research show some unique advantages of using GP over other soft computing techniques in stock market modeling. Such advantages include generating mathematical models, which are simple to evaluate and having powerful variable selection mechanism that identifies significant variables.
The new eye of smart city: Novel citizen Sentiment Analysis in Twitter

Governments across the world are trying to move closer to their citizens for better smart city monitoring and governance. Twitter Sentiment Analysis is opening new opportunities to achieve it. In this paper, a methodological framework to collect, pre-process, analyse and map citizen sentiment from Twitter in helping the Governments monitor their citizens' moods is proposed based on the prior works. Multinomial Naïve Bayes classifier is used to build a sentiment classifier, which employs a variety of features including a specific microblogging feature - emoji. Our proposed sentiment model outperforms the top system in the task of Sentiment Analysis in Twitter in SemEval-2013 in terms of averaged F scores. The novel feature emoji has proved to be useful for Sentiment Analysis in Twitter data in this work. We also apply our model to real-world tweets and present how Government agencies can track the fluctuation of citizens' moods using mapping techniques.
Prediction of the eigenvectors for spatial multiplexing MIMO systems in time-varying channels

In mobile communications, time varying channels make the available channel information out of date. Timely updating the channel state is an obvious solution to improve the system performance in a time varying channel. However, a better knowledge of the channel comes at the cost of a decrease in the system throughput. Thus, predicting the future channel conditions can improve not only the performance but also the throughput of many types of wireless systems. This is especially true for a wireless system where multiple antennas are applied at both link ends. In this paper we propose and evaluate the performance of a prediction scheme for multiple input multiple output (MIMO) systems that apply spatial multiplexing. We aim at predicting the future precoder/decoder directly without going through the prediction of the channel matrix. The results show that in a slowly time varying channel an increase in the system performance by a factor of two is possible
Upregulation of Twist in oesophageal squamous cell carcinoma is associated with neoplastic transformation and distant metastasis

Background: The antiapoptotic and epithelial–mesenchymal transition activities of Twist have been implicated in the neoplastic transformation and the development of metastasis, respectively. Upregulation of Twist, described in several types of human cancer, also acts as a prognostic marker of poor outcome. Aim: To investigate Twist expression in oesophageal squamous cell carcinoma (SCC) and its prognostic value in a Chinese cohort of patients with oesophageal SCC. Methods: Twist expression in primary oesophageal SCC of 87 Chinese patients was investigated by immunohistochemical staining. Twist protein level in one immortalised normal oesophageal epithelial cell line and six oesophageal SCC cell lines was measured by western blot analysis. Twist mRNA level in 30 pairs of frozen specimens of primary oesophageal SCC and non-neoplastic oesophageal epithelium from the upper resection margin of corresponding oesophagectomy specimen was also determined by semiquantitative reverse transcription-PCR. Results: It was found that Twist was upregulated in oesophageal SCC cell lines, and its mRNA and protein levels were both increased in oesophageal SCC and the non-neoplastic oesophageal epithelium (p<0.001). In addition, a high level of Twist expression in oesophageal SCC was significantly associated with a greater risk for the patient of developing distant metastasis within 1 year of oesophagectomy (OR 3.462, 95% CI 1.201 to 9.978; p = 0.022). Conclusions: Our results suggest that upregulation of Twist plays a role in the neoplastic transformation to oesophageal SCC and subsequent development of distant metastasis. Twist may serve as a useful prognostic marker for predicting the development of distant metastasis in oesophageal SCC.
Extraction of translation equivalents from non-parallel corpora

This paper presents a widely applicable method for extracting bilingual expressions from non-parallel corpora. The algorithm first collects word sequences as candidates for translation equivalents that match given patterns of word sequences from each corpus. Then, translation equivalents are selected from these candidates by aligning component words from within word sequences. We show the results of acquiring Japanese and English compound nouns from unrelated financial newspapers. We also demonstrate that the method can collect pairs that do not appear in terminological dictionaries.
Treatment of experimental erosive arthritis in rats by injection of the muralytic enzyme mutanolysin

A single intravenous injection into rats of 0.4 mg of the muralytic enzyme mutanolysin, given as long as 3 d after an arthropathic dose of peptidoglycan-polysaccharide polymers derived from group A streptococci (PG-APS), resulted in a complete resolution of acute arthritis and the prevention of chronic joint disease. When administration of mutanolysin was delayed until 14 d after the injection of PG-APS, a great reduction in the severity of chronic inflammation was still observed. Quantitation of the amount of PG-APS present in the limbs, spleen, and liver by a solid phase enzyme-linked immunoassay indicated that the tissues of mutanolysin-treated rats contained as much PG-APS as tissues of PBS-treated control rats. In addition, rats treated with mutanolysin immediately after receiving an intraperitoneal injection of PG-APS developed a transient limb edema similar to that seen in rats after the injection of PG-APS digested to a small fragment size in vitro with mutanolysin. We hypothesize that mutanolysin acts in vivo by degrading PG-APS to small fragments that persist but are no longer arthropathic.
Data Structures for Efficient Tree Mining with Soft Embedding Constraints

XML is playing an increasing role in data exchanges and the volume of available resources is thus growing dramatically. As they are heterogeneous, these resources must be translated into a mediator schema to be queried. For this purpose, automatic tools are required. These tools must allow the extraction of common data structures from the tree-like XML data. In this paper, we present a novel approach based on a low memory-consuming representation which can be improved by considering a binary representation. We show that these representations have many properties to enhance subtree mining algorithms, especially when considering soft tree embedding constraints. Experiments highlight the interest of our proposition.
Data fusion of FLIR and LADAR in autonomous weapons systems

We use data fusion in our automatic target recognition (ATR) system to identify and track airbourne objects. The fusion process allows for a much more robust conclusion to be drawn from what may well be incomplete data. The method we use for the fusion process is twofold. The Transferable belief model (TBM), which is derived from Dempster Shafer Theory (DST) is used for matching type and Kalman Filters are used for matching pose. We are not aware of the TBM being used within such a real world sce- nario. We also present model based matching algorithms for both 20 and 30 data obtained from disparate sensors. Results for a typical scenario are presented showing the benefits of fusing the results using the TBM and Kalman Filter:
Low Vital Capacity and Electrocardiographic ST-T Abnormalities in Asymptomatic Adults

Studies have shown that low forced vital capacity (LFVC) is associated with atherosclerosis. However, it is unclear whether LFVC is associated with resting electrocardiographic ST-T abnormalities, a common finding that is prognostic for cardiovascular events. Therefore, pulmonary functions, ST-T abnormalities defined with Minnesota Code, and cardiometabolic risk factors were examined in a cross-sectional study of 1,653 asymptomatic adults without past history of coronary heart diseases. The prevalence of diabetes, metabolic syndrome, and ST-T abnormalities significantly increased with decreasing percent of predicted forced vital capacity (%PFVC). ST-T abnormalities were observed in 73 subjects (4.4% in total). Multiple logistic regression analysis showed that, compared with the highest quartile of %PFVC (≥99.7%), the lowest quartile of %PFVC (≤84.2%) was persistently associated with ST-T abnormalities even after further adjustment for diabetes or metabolic syndrome (odds ratio (95%CI): 2.44 (1.16–5.14) and 2.42 (1.15–5.10), resp. ). Similar trends were observed when subjects were divided into quartiles according to percent of predicted forced expiratory volume in 1 second (FEV1), but not the ratio of FEV1/FVC. In conclusion, LFVC may be associated with ST-T abnormalities independent of metabolic abnormalities in asymptomatic adults, suggesting a plausible link between impaired pulmonary defects and cardiovascular diseases.
Effect of Gedunin on Acute Articular Inflammation and Hypernociception in Mice

Gedunin, a natural limonoid from Meliaceae species, has been previously described as an antiinflammatory compound in experimental models of allergic inflammation. Here, we report the antiinflammatory and antinociceptive effects of gedunin in an acute model of articular inflammation induced by zymosan (500 μg/cavity; intra-articular) in C57BL/6 mice. Intraperitoneal (i.p.) pretreatment with gedunin (0.005–5 mg/kg) impaired zymosan-induced edema formation, neutrophil accumulation and hypernociception in mouse knee joints, due to decreased expression of preproET-1 mRNA and production of LTB4, PGE2, TNF-α and IL-6. Mouse post-treatment with gedunin (0.05 mg/kg; i.p.) 1 and 6 h after stimulation also impaired articular inflammation, by reverting edema formation, neutrophil accumulation and the production of lipid mediators, cytokines and endothelin. In addition, gedunin directly modulated the functions of neutrophils and macrophages in vitro. The pre-incubation of neutrophil with gedunin (100 µM) impaired shape change, adhesion to endothelial cells, chemotaxis and lipid body formation triggered by different stimuli. Macrophage pretreatment with gedunin impaired intracellular calcium mobilization, nitric oxide production, inducible nitric oxide synthase expression and induced the expression of the antiinflammatory chaperone heat shock protein 70. Our results demonstrate that gedunin presents remarkable antiinflammatory and anti-nociceptive effects on zymosan-induced inflamed knee joints, modulating different cell populations.
Courtship signals and mate choice of the flies of inbred Drosophila montana strains

We studied genetic variation in fly mating signals and mate choice in crosses within and between inbred strains of Drosophila montana. Male songs and the cuticular hydrocarbons of both sexes as well as some of the flies’ behavioural traits differed significantly between strains. This did not, however, cause sexual isolation between strains. In fact, courtship was shorter if the female was courted by a male of a foreign strain than when courted by their own male. Heterosis was found for courtship duration and the carrier frequency of male song. Diallel analysis of male song revealed additive genetic variation in four out of the five traits studied. Two traits showed dominance variation and one of these, carrier frequency, expressed unidirectional dominance with alleles for higher carrier frequency being dominant. Direction of dominance in carrier frequency was the same as the direction of sexual selection exercised by D. montana females on this trait, which suggests that sexual selection could be a driving force in the evolution of song towards a higher carrier frequency.
The Cytokine Network of Wallerian Degeneration: Tumor Necrosis Factor-α, Interleukin-1α, and Interleukin-1β

Wallerian degeneration (WD) is the inflammatory response of the nervous system to axonal injury, primarily attributable to the production of cytokines, the mediator molecules of inflammation. We presently document the involvement of the inflammatory cytokines TNFα, interleukin (IL)-1α, and IL-1β in peripheral nerve (PNS) injury in C57/BL/6NHSD (C57/BL) mice that display the normal rapid progression of WD (rapid-WD) and C57/BL/6-WLD/OLA/NHSD mice that display abnormal slow progression of WD (slow-WD). TNFα and IL-1α mRNAs were expressed, whereas TNFα but not IL-1α protein was synthesized in intact PNS of C57/BL mice. TNFα and IL-1α protein synthesis and secretion were rapidly upregulated during rapid-WD in Schwann cells. IL-1β mRNA expression and protein synthesis and secretion were induced sequentially in Schwann cells with a delay after injury. Thereafter, recruited macrophages contributed to the production of TNFα, IL-1α, and IL-1β, which in turn augmented myelin phagocytosis by macrophages. Observations suggest that TNFα and IL-1α are the first cytokines with protein production that is upregulated during rapid-WD. TNFα and IL-1α may initiate, therefore, molecular and cellular events in rapid-WD (e.g., the production of additional cytokines and NGF). TNFα, IL-1α, and IL-1β may further regulate, indirectly, macrophage recruitment, myelin removal, regeneration, and neuropathic pain. In contrast to rapid-WD, the production of TNFα, IL-1α, and IL-1β protein was deficient in slow-WD, although their mRNAs were expressed. mRNA expression and protein production of TNFα, IL-1α, and IL-1β were differentially regulated during rapid-WD and slow-WD, suggesting that mRNA expression, by itself, is no indication of the functional involvement of cytokines in WD.
Improved adaptive stereo matching using double dynamic programming with correlation of row and column

In a variety of stereo matching algorithms using dynamic programming algorithm can effectively improve the speed and accuracy with good real-time performance and easy realization. In this paper, with advantages of dynamic programming, we presents a stereo matching algorithm using double dynamic programming with correlation of row and column, which uses improved adaptive support-weight approach and energy minimization model to solve the optimization problem. In the solving process, different constructed values of data items given based on characters of variation in the column direction using row dynamic programming and the values of smoothness item in the column direction, to reduce apparent defective stripes, are used to get the final result using column dynamic programming. Experimental results used Middlebury database show that the proposed algorithm can reduce the overall matching error rates and apparent defective stripes and get a better stereo matching effect.
Long-Term Clock Synchronization in wireless sensor networks with arbitrary delay distributions

Clock synchronization is a crucial issue in the operation of wireless sensor networks. Although the existing synchronization algorithms under linear clock model assumptions perform well for short periods, they will become problematic for applications with long-term requirements. In this paper, we consider a more realistic and flexible relationship model for two clocks and exploit a Taylor expansion to approximate the relationship. Based on this model and a two-way time message exchange procedure, an estimation algorithm is proposed to recover the relationship and then achieve the synchronization. Finally, simulation results demonstrate that the proposed algorithm improves the accuracy of synchronization as compared to existing algorithms in many scenarios, and is also robust to different distributions of random delays.
Face recognition using a fourier polar based approach

In this work, a face recognition approach for human identification is proposed. It is based on the Discrete Fourier Transform of the original spatial image and on the polar mapping of the spectrum of the latter image. While the first step eliminates the translation's effect between faces, the second step minimizes the effect of any face's rotation. The approach is evaluated by studying its performance with other existing techniques using a correlation coefficient as a similarity measure for comparison purposes. Besides, the effect of the number of images used in the training procedure is studied. The results show that the proposed technique outperforms the other techniques and a recognition of 100 percent is possible as the number of training images is increased.
Identification of an RNA binding region within the N-terminal third of the influenza A virus nucleoprotein

The influenza A virus nucleoprotein (NP) has been examined with regard to its RNA-binding characteristics. NP, purified from virions and devoid of RNA, bound synthetic RNAs in vitro and interacted with the ribonucleotide homopolymers poly(A), poly(G), poly(U), and poly(C) in a salt-dependent manner, showing higher binding affinity for polypyrimidine homopolymers. To map the NP regions involved in RNA binding, a series of deleted forms of the NP were prepared, and these truncated polypeptides were tested for their ability to bind poly(U) and poly(C) homopolymers linked to agarose beads. Proteins containing deletions at the N terminus of the NP molecule showed reduced RNA-binding activity, indicating that this part of the protein was required to bind RNA. To identify the NP region or regions which directly interact with RNA, proteins having the maltose-binding protein fused with various NP fragments were obtained and tested for binding to radioactively labeled RNAs in three different assays: (i) nitrocellulose filter binding assays, (ii) gel shift assays, and (iii) UV light-induced cross-linking experiments. A maltose-binding protein fusion containing the N-terminal 180 amino acids of NP behaved as an RNA-binding protein in the three assays, demonstrating that the N terminus of NP can directly interact with RNA. This NP region could be further subdivided into two smaller regions (amino acids 1 to 77 and 79 to 180) that also retained RNA-binding activity.
Adjusting the EM algorithm for design of experiments with missing data

The analysis of designed experiment with missing observation has been dealt by the use of the EM algorithm even before the fundamental paper by Dempster, Laird and Rubin (1977). The direct application of the EM algorithm to a data set following designed experiments such as randomized block designs, or factorial experiments, with missing observations may lead to the estimation of parametric functions that are not estimable. In this paper we present an adjustment of the EM algorithm for additive classification models that prevents the user from obtaining results, which are not reliable. The adjustment consists in applying the R-process introduced by Birkes, Dodge and Seely (1976), that determines which are the estimable parametric functions. The observations and the parameters are then partitioned in a suitable way, and the maximum likelihood estimates for the estimable parametric functions are derived applying EM to each partition. The proposed algorithm is called REM; several numerical examples and one application are presented
ChronoView: A Space-Efficient Method for Visualizing Temporal Patterns

Numerous events occur daily, of which many kinds are recorded as log data. A temporal pattern is a set of timestamps that accompany events. Temporal patterns include many kinds of valuable information and suggest tendencies of human activities, occurrences of accidents, etc. Therefore, it is important to identify remarkable features of temporal patterns in event data. There are many methods for representing time-oriented data. However, it is difficult to observe many temporal patterns because most naive methods require a certain area to visualize a temporal pattern. This paper presents a space-efficient technique for visualizing temporal patterns that facilitates simultaneous visualization of many event groups and comparisons of their occurrence patterns.
GtRNAdb: a database of transfer RNA genes detected in genomic sequence

Transfer RNAs (tRNAs) represent the single largest, best-understood class of non-protein coding RNA genes found in all living organisms. By far, the major source of new tRNAs is computational identification of genes within newly sequenced genomes. To organize the rapidly growing collection and enable systematic analyses, we created the Genomic tRNA Database (GtRNAdb), currently including over 74 000 tRNA genes predicted from 740 species. The web resource provides overview statistics of tRNA genes within each analyzed genome, including information by isotype and genetic locus, easily downloadable primary sequences, graphical secondary structures and multiple sequence alignments. Direct links for each gene to UCSC eukaryotic and microbial genome browsers provide graphical display of tRNA genes in the context of all other local genetic information. The database can be searched by primary sequence similarity, tRNA characteristics or phylogenetic group. The database is publicly available at http://gtrnadb.ucsc. edu.
Additional doses of Constraint Induced Language Therapy (CILT) can improve outcomes in aphasia1

Esther S. Kim1 & Kayla Paterson2 1Department of Communication Sciences and Disorders, University of Alberta, Edmonton, Alberta, Canada; 2Specialized Rehabilitation Outpatient Program, Glenrose Rehabilitation Hospital, Edmonton, Alberta, Canada . Q (1) Does Constraint Induced Language Therapy (CILT) improve verbal production of trained and untrained stimuli after one and two treatment periods (treatment period = 30 hrs over 2 weeks)? (2) Are treatment effects maintained at 8-weeks following treatment completion? (3)What is the influence of aphasia severity on treatment accuracy, maintenance, and generalization to discourse and untrained materials?