Tweet2Vec: Learning Tweet Embeddings Using Character-level CNN-LSTM Encoder-Decoder

We present Tweet2Vec, a novel method for generating general-purpose vector representation of tweets. The model learns tweet embeddings using character-level CNN-LSTM encoder-decoder. We trained our model on 3 million, randomly selected English-language tweets. The model was evaluated using two methods: tweet semantic similarity and tweet sentiment categorization, outperforming the previous state-of-the-art in both tasks. The evaluations demonstrate the power of the tweet embeddings generated by our model for various tweet categorization tasks. The vector representations generated by our model are generic, and hence can be applied to a variety of tasks. Though the model presented in this paper is trained on English-language tweets, the method presented can be used to learn tweet embeddings for different languages.Comment: SIGIR 2016, July 17-21, 2016, Pisa. Proceedings of SIGIR 2016. Pisa, Italy (2016

The influence of social network size on speech perception

Infants and adults learn new phonological varieties better when exposed to multiple rather than a single speaker. This article tests whether having a larger social network similarly facilitates phonological performance. Experiment 1 shows that people with larger social networks are better at vowel perception in noise, indicating that the benefit of laboratory exposure to multiple speakers extends to real life experience and to adults tested in their native language. Furthermore, the experiment shows that this association is not due to differences in amount of input or to cognitive differences between people with different social network sizes. Follow-up computational simulations reveal that the benefit of larger social networks is mostly due to increased input variability. Additionally, the simulations show that the boost that larger social networks provide is independent of the amount of input received but is larger if the population is more heterogeneous. Finally, a comparison of “adult” and “child” simulations reconciles previous conflicting findings by suggesting that input variability along the relevant dimension might be less useful at the earliest stages of learning. Together, this article shows when and how the size of our social network influences our speech perception. It thus shows how aspects of our lifestyle can influence our linguistic performance

Morphologic and meristic specification of some genus of Carangidae family in the Persian Gulf, Iran

Morphologic and meristic analyses were performed aided by regression charts on 96 specimens of the genus Parastromateus, 67 specimens of Caranx, 70 specimens of Alepes, 69 specimens of Scomberoides, 62 specimens of Atropus, 104 specimens of Carangoides, and 67 specimens of Trachionotus from March 2004 to February 2005. The samples were collected by using bottom trawling in the Persian Gulf. The analyses showed the complete separability of the genus while keeping their close connection with the Family. We found that Parastrometeus was specially unique in terms of keeping its relationship with the family Carangidae

Introducing genetic markers for identification and separation of 4 species of Persian Gulf and Oman Sea fishes using PCR- RFLP method

In order to introduce genetic markers of four species of fishes, 80 samples of each species, i.e. Parastromateus niger, Scomberomorus comersoniannus, Trachionotus mookalee and Caranx para were collected. DNA was extracted using phenol- chloroform method. The target gene (cytochrome b) was amplified by Thermal cycle (PCR) and the PCR product size estimated 1105 bp. In this research out of 27 DNAase enzymes which were used for PCR product enzyme digesting 8 enzymes (Bam HI, Alw 261, Rsa I, Mbo I, Alu I, Hinf I, Dpn I, Dde I) have cut side on target DNA and three enzymes of them Alu I, Hinf I and Mbo I showed polymorphism genetic differences while other enzymes displayed similar patterns. Variation of haplotypes from four species are as follows: BAA for P. niger, AAB for T. mookalee, ABA for C. para, and ACA for S. comersonianus. So it is possible to claim that each of the above Haplotypes may be used as genetic markers for each of the species

Gene 18s rRNA variation of cuttlefish population (Sepia pharaonis) in the Persian Gulf and the Oman Sea using PCR-RFLP method

We used PCR-RFLP method to identify cuttlefish (Sepia pharaonis) populations in the Persian Gulf and the Sea of Oman. Bottom trawling method was used to collect a range of 20 to 40 specimens from each 15 stations in the study area. Genomic DNA was extracted by phenol-chloroform method and one pair primer was designed for the analysis based on 1 Ss rRNA gene nucleotide sequences. A PCR product with 502 pair bases in length was obtained for all specimens and subjected to digestion by eight restriction enzymes Alui, Tacit, MO, Rsal, Hinalli, Dral, Prull and Mien DNA banding, patterns in all specimens were similar and no polymorphism was detected among them. We conclude that cuttlefish populations cannot be isolated using 18s rRNA gene extracts in the area of study

Ecophysiological indicators of stress in female Persian sturgeon, Acipenser persicus

The study on the ecophysiological impacts of stress in female Persian sturgeon broodfishes revealed that the average cortisol level varried in all broodfish caught at the Sefidrud River (163.38±21.2ng mL-1), Sefidrud River estuary (260.27±19.7ng mL-1) and Gorganrud River estuary (179.38±20.8ng mL-1). The variations in serum glucose levels were 140.65±12.05mg dL-1, 144.44±5.9mg dL-1 and 126.24±11mg dL-1, respectively. The maximum level of cortisol (781 ng mL-1) and serum glucose (281 mg dL-1) were observed during the transport of broodfish from the capture stations to the hatcheries and the minimum level of cortisol (25.2 ng mL-1) and serum glucose (33 mg dL-1) were observed during the confinement of broodfishes in the breeding ponds. The rhythmic and significant variations of cortisol level during capture, handling, transport and confinement of female Persian sturgeon broodfish in all three regions can be regarded as a valuable indicator of stres

A comparative survey of abundance and biomass of Caspian Sea macrobenthos in coastal waters of Mazandaran Province

Caspian Sea macrobenthos was surveyed every two months from December 2007 to October 2008, in the west, east and central parts of Mazandaran province waters. Each area was sampled with 3 replicates at 2 depths of 5 and 10m by Van Veen grab. Five different classes were recognized, including Polychaeta (52.7%), Oligochaeta (27.8%), Bivalvia (12%), Cnistacea (7.5%) and Insects (0.07%). Total mean (LSD) abundance and biomass were 2727± 1303 individual/m2 and 88.9±22.93, respectively. The Polychaeta demonstrated the highest abundance and Bivalvia had the highest biomass. The highest abundance of macrobenthos was found in eastern and the highest biomass in western coasts of Mazandaran. In August 2008, macrobenthos abundance showed higher values. In October, remarkable difference was observed between the abundance of Polychaeta and other macrobenthos organisms. According to Kniskal-Wallis test, abundance and biomass of the entire macrobenthos classes except Insects, showed a significant difference between sampling months (P<0.05). Macrobenthos biomass had no significant difference among the three areas whereas abundance demonstrated a significant difference within these areas (P< 0.05)

Reproduction characteristics of the Vimba vimba persa (Pallas, 1811), in coastal waters of the Caspian Sea

Some reproduction characteristics of the Caspian Vimba, Vimba vimba persa, were studied from Oct. 2008 to Sep. 2009 in coastal waters of the Caspian Sea (Mazandaran province). 994 specimens were monthly collected from 6 fish landing sites of Ramsar, Tonekabon, Chalus, Mahmood Abad, Sari and Behshahr. The fecundity was measured using 92 specimens. This species was found to have more abundance in spring (especially April and May). The samples composed of 397(42.6%) male, 537(57.4%) female; the sex ratio was M:F = 1:1.35. The advanced stages of maturity (4th & 5th) were found in April and May. The highest Gonadosomatic Index in females was in May and the lowest one was in July. The average of absolute and relative fecundities was 17198±7710 and 171.85±48.8, respectively

A novel, eco-friendly and green synthesis of PPAC-ZnO and PPAC-nZVI nanocomposite using pomegranate peel: Cephalexin adsorption experiments, mechanisms, isotherms and kinetics

In the present work, powdered activated carbon coated by nanoparticles ZnO and nZVI was derived from pomegranate peel extracts and finally applied for removal of cephalexin (CEX (from aqueous solutions. This experimental research was conducted discontinuously. The effects of pH of solution, reaction time, PPAC-nZVI and PPAC-ZnO composites dose, and initial concentration of cephalexin and composite recovery on process efficiency were investigated. The removal efficiency in optimal conditions for cephalexin with PPAC-nZVI and PPAC-ZnO (CEX = 50 mg L�1, composite dose = 1.25 g L�1, reaction time = 45 min and pH = 5) was obtained 96.06 and 94.17, respectively. The results of the study of isotherm and absorption kinetics for both composites showed that the absorption process follows Langmuir isotherm and pseudo second-order kinetics. The present study showed that the composites could be used as an effective and bio-friendly absorbent to remove cephalexin from aqueous solutions. © 2020 The Society of Powder Technology Japa

Fake News Detection on Twitter Using Propagation Structures

The growth of social media has revolutionized the way people access information. Although platforms like Facebook and Twitter allow for a quicker, wider and less restricted access to information, they also consist of a breeding ground for the dissemination of fake news. Most of the existing literature on fake news detection on social media proposes user-based or content-based approaches. However, recent research revealed that real and fake news also propagate significantly differently on Twitter. Nonetheless, only a few articles so far have explored the use of propagation features in their detection. Additionally, most of them have based their analysis on a narrow tweet retrieval methodology that only considers tweets to be propagating a news piece if they explicitly contain an URL link to an online news article. By basing our analysis on a broader tweet retrieval methodology that also allows tweets without an URL link to be considered as propagating a news piece, we contribute to fill this research gap and further confirm the potential of using propagation features to detect fake news on Twitter. We firstly show that real news are significantly bigger in size, are spread by users with more followers and less followings, and are actively spread on Twitter for a longer period of time than fake news. Secondly, we achieve an 87% accuracy using a Random Forest Classifier solely trained on propagation features. Lastly, we design a Geometric Deep Learning approach to the problem by building a graph neural network that directly learns on the propagation graphs and achieve an accuracy of 73.3%