bluuebunny/crossref_metadata_2025 huggingface dataset:
The Predictive role of Cognitive Factors and Academic Self-efficacy on Academic Functioning of Children at Risk for Specific Learning Disabilities
Authors: Shilshtein Evguenia , Margalit Malka
Published: August 2019

The goals of the study were to examine the predictive power of general cognitive ability, working memory, and self-efficacy in first grade for academic functioning of children at risk for learning disabilities in second grade. The study involved 82 children (age 6-7 years) from five local public elementary schools in middle-class neighborhoods in Jerusalem, including 41 children at risk for specific learning disabilities and 41 typically developing peers. In the first stage of the study, (performed at the end of first grade), general cognitive ability and working memory were assessed using subtests from the Wechsler Intelligence Scale for Children (the subtests consisted of:  Vocabulary and Block Design for general cognitive ability; Arithmetic and Digit Span for working memory). Academic self-efficacy was rated using a structural interview. At follow-up, academic functioning was assessed at the end of second grade. A serial-multiple mediation analysis revealed significant mediating roles for levels of performance in the Arithmetic subtest and for academic self-efficacy in predicting the academic functioning in second grade. The significance of the Arithmetic subtest, based on contemporary research on the structure of the intelligence was proposed. Educational implications call for sensitizing teachers to the unique role of academic self-efficacy in shaping trajectories of academic functioning development among children with RLD and in using effective strategies of promoting self-efficacy.
On Sign Pattern Matrices that Allow or Require Algebraic Positivity
Authors: Pelejo Diane Christine , Abagat Jean Leonardo
Published: August 2019

A square matrix M with real entries is algebraically positive (AP) if there exists a real polynomial p such that all entries of the matrix p(M) are positive. A square sign pattern matrix S allows algebraic positivity if there is an algebraically positive matrix M whose sign pattern is S. On the other hand, S requires algebraic positivity if matrix M, having sign pattern S, is algebraically positive. Motivated by open problems raised in a work of Kirkland, Qiao, and Zhan (2016) on AP matrices, all nonequivalent irreducible 3 by 3 sign pattern matrices are listed and classify into three groups (i) those that require AP, (ii) those that allow but not require AP, or (iii) those that do not allow AP. A necessary condition for an irreducible n by n sign pattern to allow algebraic positivity is also provided.
Maps Preserving Norms of Generalized Weighted Quasi-arithmetic Means of Invertible Positive Operators
Authors: Nagy Gergő , Szokol Patricia
Published: August 2019

In this paper, the problem of describing the structure of transformations leaving norms of generalized weighted quasi-arithmetic means of invertible positive operators invariant is discussed. In a former result of the authors, this problem was solved for weighted quasi-arithmetic means, and here the corresponding result is generalized by establishing its solution under certain mild conditions. It is proved that in a quite general setting, generalized weighted quasi-arithmetic means on self-adjoint operators are not monotone in their variables which is an interesting property. Moreover, the relation of these means with the Kubo-Ando means is investigated and it is shown that the common members of the classes of these types of means are weighted arithmetic means.
The identification of soil fungi isolated from rhizosphere in different varieties of jali (Coix lacryma-jobi) in Loa Kulu, Kutai Kartanegara, Indonesia
Authors: SOPIALENA SOPIALENA , AKHSAN N. , SURYADI A. , NURDIANA JULI
Published: August 2019

Sopialena, Akhsan N, Suryadi A, Nurdiana J. 2018. The identification of soil fungi isolated from Rhizosphere in different varieties of jali plants (Coix lacryma-jobi) in Loa Kulu, Kutai Kartanegara, Indonesia. Asian J Agric 2: 44-47. The rhizosphere effect indicated the development of active microbial population around the roots driving from the loss of organic materials. This research was intended to identify rhizosphere microbes by identifying the potential microbes four different varieties of jali (Coix lacryma-jobi L.) in Loh Sumber, Loa Kulu, Kutai Kartanegara, Indonesia, i.e., jelai beras, jelai ketan, ketan lekat, and jelai kaltara. The soil samples were collected and isolated in the area of jali plantation in Loa Kulu, Kutai Kartanegara at 45 days after planting. As many as 16 isolated samples were used, collected from four different variety of jali and 4 times of replication. The result showed that a variety of microbes at Rhizosphere could be classified as Trichoderma sp. Aspergillus sp., Pythium sp., Fusarium sp., Cunninghamelal sp., and Penicillium sp..
Short Communication: Diversity and community structure of trees in two forest types in Mt. Apo Natural Park (MANP), Philippines
Authors: SALVAÑA FLORENCE ROY P , LOPEZ CHRISTIE KAYE C , MANGAOANG CHERIE C , BRETAÑA BRYAN LLOYD P
Published: August 2019

Abstract. Salvaña FRP, Lopez CKC, Mangaoang CC, Bretaña BLP. 2019. Short Communication: Diversity and community structure of trees in two forest types in Mt. Apo Natural Park (MANP), Philippines. Biodiversitas 20: 1794-1801. A forest ecosystem is the basic ecological unit that exists as a habitat for a community of both native and introduced organisms. It is the limited number of reliable information on the diversity and community structure of tree species in one of the Philippines’ protected landscape, Mt. Apo Natural Park (MANP), that initiates this study. The present study was carried out to determine species diversity and community structure including seedlings, saplings and large trees of two forest types, namely tropical lowland evergreen rainforest and tropical lower montane rainforest. Two one-kilometer transects were established in each forest types. Each transect was divided into five sampling points. A total of 67 tree species belonging to 29 families were identified from both forest types. Species richness was higher in tropical lowland evergreen rainforest compared to tropical lower montane rainforest. Relative abundance showed that among the identified families, Dipterocarpaceae and Moraceae have the highest abundance which is mostly present in the two forest types. This was followed by Meliaceae and Myrtaceae. The two forest types were satisfactory at community level having large number of seedlings compared to saplings and trees. Based on this, the two forest types, dominated by seedlings, are actively regenerating.
Screening for potential antidiabetes and antioxidant activities of selected plants from East Kalimantan, Indonesia
Authors: RAMADHAN RICO , KRISTANTI ALFINDA NOVI , AMIRTA RUDIANTO , KUSUMA IRAWAN WIJAYA , PHUWAPRAISIRISAN PREECHA , HAQIQI MUHAMMAD TAUFIQ , SAPARWADI SAPARWADI
Published: August 2019

Abstract. Ramadhan R, Kristanti AN, Amirta R, Kusuma IW, Phuwapraisirisan P, Haqiqi MT, Saparwadi. 2019. Screening for potential antidiabetes and antioxidant activities of selected plants from East Kalimantan, Indonesia. Biodiversitas 20: 1820-1826. Ten selected plants in this study have been used traditionally in West Kutai, East Kalimantan as medicinal plants. This study aimed to screen and evaluate the in vitro antidiabetic and antioxidant activity of methanol extracts of selected plants from East Kalimantan. The antidiabetic activity was carried out by α-glucosidase inhibitory activity with maltose and sucrose as substrates while antioxidant activity was determined by free radicals scavenging activity against DPPH, ABTS and Nitric Oxide (NO). The results showed that Garcinia riedeliana extract had strong inhibitory activity with an IC50 value of 0.04 mg/mL followed by  Shorea laevis, Pternandra azurea and Bridelia tomentosa with IC50 values of 0.12; 0.15 and 0.16 mg/mL in maltose respectively, while quercetin as positive control had an IC50 value of 0.08 mg/mL. G.riedeliana extract also showed good α-glucosidase inhibitory activity with an IC50 value of 0.23 mg/mL in sucrose as substrate. The results on antioxidant activity showed that all extracts have IC50 value against free radicals DPPH, ABTS, and nitric oxide. The most active extract as α-glucosidase inhibitory activity and antioxidant activity was G. riedeliana extract. These findings provide the scientific evidence that one species of medicinal plants from East Kalimantan might be potential as an antioxidant and α-glucosidase inhibitor.
The potential of yeasts from the oil-contaminated soil and mangrove rhizosphere for degrading crude oil
Authors: ALAMI NUR HIDAYATUL , MAULIDIYA LUTHFI LAILATUL , KUSWYTASARI N D , ZULAIKA ENNY , SHOVITRI MAYA
Published: August 2019

Abstract. Alami NH, Maulidiya LL, Kuswytasari ND, Zulaika E, Shovitri M. 2019. The potential of yeasts from the oil-contaminated soil and mangrove rhizosphere for degrading crude oil. Biodiversitas 20: 1833-1838. Bioremediation of crude oil contaminated soil eventually depends on the activities of microorganisms to degrade contaminants. Bioaugmentation, through the addition of microbial culture to contaminated soil, can be used to enhance degradation rates. This research aimed to determine the effect of yeast formulations isolated from the oil-contaminated soil and mangrove rhizosphere to degrade crude oil and evaluate the most effective yeast formulation and incubation timefor crude oil degradation. This research was conducted by subculturing yeast in the slant agar medium, screening hydrocarbonoclastic yeast in crude oil- Bushnell Hass Mineral Salt (BHMS) medium, biodegradation test, measuring the total cell number with Total Plate Count (TPC), Total Petroleum Hydrocarbon (TPH) test with the gravimetric method, and measuring soil moisture content. The design of the research was Completely Randomized Factorial Design with 3 replications. Data were analyzed quantitatively by using statistical tests for TPC and TPH, while a descriptive qualitative test analyzed soil moisture. The result showed that yeast formulation and incubation time affected crude oil degradation. An effective yeast consortium for oil degradation is T20 consortium with an incubation period of 30 days, which result in 72.26 % oil degradation.
Mammalian diversity in West Java, Indonesia
Authors: HUSODO TEGUH , SHANIDA SYA SYA , FEBRIANTO PUPUT , PUJIANTO M PAHLA , MEGANTARA ERRI N
Published: August 2019

Abstract. Husodo T, Shanida SS, Febrianto P, Pujianto MP, Megantara EN. 2019. Mammalian diversity in West Java, Indonesia. Biodiversitas 20: 1846-1858. Protected forests in West Java are wider than conservation forests, whereas mammalian diversity in protected forests is as high as mammalian diversity in conservation forests. Mammals in protected forests are not protected by regional protection regulations, while anthropogenic factors in Java are quite high. This is possible that mammals who have high conservation status will experience local extinction. This study aims to determine (i) the composition of mammalian species and (ii) the species that are always found in studies of mammalian diversity in West Java. The study was conducted through a qualitative approach by combining several methods such as interview, camera trapping, sign survey, observation and transect, and collapsible traps. Mammalia in West Java found 54 species, 21 families, and nine orders with details of three species of Artiodactyla, 12 species of Carnivores, seven species of Chiroptera, one species of Dermoptera, one species of Euphotyphla, one species of Pholidota, five species of Primates, 21 species of Rodentia, and three species of Scandentia. The species that are always found in all study locations are nine species, including wild boar, Javan leopard, leopard cat, Javan mongoose, oriental small-clawed otter, Asian palm civet, grizzled leaf monkey, Javan langur, and Javan tree shrew. The results presented here may facilitate improvements in the mammalian diversity database, especially in the non-conservation area.
Optimization of manganese bioleaching activity and molecular characterization of indigenous heterotrophic bacteria isolated from the sulfuric area
Authors: PRASIDYA DENAYA ANDRYA , WILOPO WAHYU , WARMADA I WAYAN , RETNANINGRUM ENDAH
Published: August 2019

Abstract. Prasidya DA, Wilopo W, Warmada IW, Retnaningrum E. 2019. Optimization of manganese bioleaching activity and molecular characterization of indigenous heterotrophic bacteria isolated from the sulfuric area. Biodiversitas 20: 1904-1909.  The present research evaluated the manganese bioleaching potency of a heterotrophic bacteria KB3B1. This bacterial strain has been isolated from sulfuric area located at Ungaran, Middle of Java, Indonesia using modified 9K medium by adding of several organic nutrients. The manganese bioleaching activities of the strain was analysed by applying of varying glycine concentrations (0, 5, 10, 15 mg mL-1) with pyrolusite pulp densities of 0.02 g cm-3 on a rotary shaker at 180 rpm for 18 days incubation. Several parameters, including the growth of bacteria, pH values, the concentration of soluble manganese and cyanide, were investigated at the interval of 3 days. Molecular characteristics of the strain were further analyzed based on 16S rDNA gene sequences. After 15 days, the maximum yield of manganese 16.6% was achieved under the addition of 10 mg mL-1 glycine. This maximum extract obtained was followed by the maximum bacterial growth, pH, and cyanide product of the strain. Phylogenetic analysis showed that the strain was closely related with Bacillus niacini EP89. Besides, the average frequencies of guanine and cytosine (G+C) of the strain was in same range as that of the reference bacteria in the GenBank and Bergey's Manual Systematics of Bacteria.
EDUCAÇÃO GEOMÉTRICA E ARTE VISUAL DE LEONARDO DA VINCI: UMA EXPERIÊNCIA PELA A ANÁLISE GEOMETRIA DO QUADRO DA MONA LISA
Authors: Dutra Jorge Luiz Prudencio
Published: August 2019

O objetivo desse trabalho foi educar estudantes do Colégio Estadual Senhor do Bonfim (CESB) pela Modelagem Matemática e a Geometria nos desenhos e pintura de Mona Lisa de Leonardo da Vinci e aproximar do futuro lugar da profissão. O procedimento dessa experiência de extensão, teve origem na pesquisa sobre temas sobre Geometria, a organização de um plano de intervenção e a realização da extensão universitária do componente Laboratório do Ensino da Matemática II do curso de Licenciatura em Matemática lotado no Campus VII da Universidade do Estado da Bahia. Os métodos operados foram o estudo bibliográfico, a Modelagem Matemática e o expositivo com a finalidade de ensinar os pensamentos geométricos e suas representações nos desenhos e na pintura da Mona Lisa. A Educação Básica foi o foco da intervenção, em especial estudantes do CESB. Organizamos a intervenção em forma de feira livre intitulada: I Feira de Aprendizagem do Laboratório do Ensino da Matemática (I FALEM). Pela Educação Geométrica, podemos demonstrar pensamentos e expressões geométricas nas formas, linhas, sombra, movimento, vários atributos e atribuições nos gráfico-visuais de Mona Lisa aos e às estudantes do CESB e provocar a emoção de aprender novos sentidos e significados da Geometria na Arte Visual.
Método de Valoração da Água Subterrânea Impactada por Atividades Contaminantes no Estado de São Paulo
Authors: Bertolo Reginaldo Antonio , Hirata Ricardo , Aly Junior Osvaldo
Published: August 2019

As águas subterrâneas apresentam uma notável importância para os ecossistemas, atuando na perenidade de rios e na sustentação da vida aquática, assim como no atendimento de vários tipos de necessidades humanas. Estas águas vêm sendo deterioradas nas últimas décadas, em especial nas áreas urbanas, colocando em risco suas funções e serviços ecossistêmicos. No Estado de São Paulo, a aplicação dos procedimentos de gerenciamento de áreas contaminadas (GAC), previstos na Lei Estadual 13577/2009 e demais instrumentos, contribuem para a melhoria das condições ambientais e propiciam condições seguras de uso do solo. Por outro lado, reconhece-se que as ações previstas no GAC não resultam na extração total de contaminantes do meio contaminado, em especial nas águas subterrâneas, o que propicia a criação de não conformidades com leis federais mais amplas, que exigem do responsável a reparação integral de um dano ambiental. Este trabalho objetiva apresentar um método de valoração dos serviços ecossistêmicos prestados pelas águas subterrâneas e aquíferos, servindo como parâmetro para a quantificação da reparação integral do dano ambiental. O método implica na realização do cálculo dos volumes de água subterrânea associados ao problema ambiental, multiplicados por um valor de custo unitário da água subterrânea. As equações utilizadas para a quantificação dos volumes de água são apresentadas, assim como uma discussão sobre a utilização dos valores unitários. O resultado final deste trabalho, avalia-se, é a criação de conformidades entre as legislações Estadual e Federal que tratam do tema.
Artistic Concerns in Preservation
Authors: Albuquerque Beatriz
Published: August 2019

The rise of new technologies in the twenty-first century is accompanied by challenges in arts preservation that underscore the need to constantly adapt to new ways of approaching preservation issues. This article investigates the problems in preserving digitally-born cultural heritage and explores the connections between digital cultural heritage and preservation of digitally-born artwork. At the core of this study is the question of how to deal with and preserve digital cultural heritage in the changing world of technology, following a case study model with an emphasis on practical research. The results suggest that while the importance of preventing damage is crucial, further investigations are needed in order to fully treat issues concerning the accurate representation of the artist's intention.
THE SPATIAL COMPOSITION OF ALUN-ALUN ON JAVA ISLAND TODAY
Authors: Kohori Takako , Hadi Akhmad Arifin , Furuya Katsunori
Published: August 2019

This study focuses on alun-alun, the open spaces in Indonesia that have a long cultural history. Alun-alun mostly located in the center of cities; they influence the pattern of cities and become a mental map for inhabitants. In this study, we investigated the distribution of alun-alun throughout Java Island. The research consisted of three parts. First, we identified Alun-alun from the colonial era using the old maps from Leiden University There were 15 locations of alun-alun in 13 cities identified from the old maps with characteristics as follows; 1) rectangular land, 2) located adjacent to the city mosque, and 3) located adjacent to the Regent’s office or Palace. In the second part, from those definitions, we confirmed 90 locations of alun-alun in 87 cities that have existed from the colonial period to the present across Java Island. The third part, we clarified the current province of alun-alun from two perspectives: area and spatial composition. We found that the present alun-alun show regional tendencies. Alun-alun in cities of Banten and West Java province was mostly in a small-scale area without Ficus benjamina trees. These points overlap with features described in the colonial era. Alun-alun in cities of Central Java and Yogyakarta province was relatively in a large-scale area and characterized by Ficus benjaminaas the main tree. Alun-alun in cities of East Java province was also in a large-scale area, but space mostly divided by planted areas, open area, structures, and others.
RAINWATER HARVESTING AS AN ALTERNATIVE SOURCE OF DOMESTIC WATER IN LAMPUNG PROVINCE - INDONESIA
Authors: Susilo Gatot Eko , Prayogo Tri Budi
Published: August 2019

Urban areas in Indonesia will experience water crisis in the future due to the rapid population growth. Local water companies will face big problems to meet the water needs of these cities in the future, due to limited water resources and environmental degradation. Efforts to find new alternative water sources are important to undertake in order to ensure the availability of clean and fresh water in the future. This paper aims to investigate the effectiveness of rainwater harvesting facility and the potential benefits of rainwater harvesting applications in urban areas in Indonesia. The cities that are the object of research are Bandar Lampung, Pringsewu, and Metro City. These three cities are the fastest growing cities in Lampung Province. Simulation to find supporting capacity of RWH is applied for house type 45, which has an effective rooftop area of 30 m2. The maximum capacity of the tanks being tested is 1 m3 and 2 m3, and the number of occupants is 5 to 7 people. Research shows that RWH has great potential to meet domestic water demand in major cities in Indonesia. From some analysis and simulation of this research, it is known that the supporting capacity of RWH for domestic water supply in the cities studied is 40% to 50% on average. Research also shows that reservoir size 2 m3 is the most recommended dimension in RWH implementation in Lampung Province cities.
Emotion Regulation in Context: Social Connectedness Moderates Concurrent and Prospective Associations With Depressive Symptoms
Authors: Marroquín Brett , De Rutte Jennifer , May Casey L. , Wisco Blair E.
Published: August 2019

Introduction: Emotion regulation in healthy functioning and in depression is typically examined as an intrapersonal phenomenon, but growing evidence suggests social factors affect individuals' strategy use and effectiveness. We examined whether the role of emotion regulation in depression—concurrently and over four weeks—depends on social connectedness, predicting that higher social connectedness would dilute effects of one's own strategy use regardless of specific strategy.

Methods: Young adult participants (n = 187) completed measures of perceived social connectedness, depressive symptoms, two avoidant emotion regulation strategies (ruminative brooding and experiential avoidance), and two approach-oriented strategies (positive reappraisal and planning), and depressive symptoms again four weeks later (n = 166).

Results: Cross-sectional associations of emotion regulation with symptoms were moderated by social connectedness: effects of both avoidant and approach strategies were weaker among more connected individuals. Prospectively, social connectedness moderated effects of approach strategies, but not avoidant strategies. Among more socially connected individuals, using approach strategies—which are typically adaptive—was associated with higher symptoms over time.

Discussion: Results partially replicate previous research and support the role of social factors as important contexts of intraper-sonal emotion regulation and dysregulation in depression. Findings suggest that social resources can dilute intrapersonal effects regardless of strategy type—more in the shorter term than in the longer term—and can even lead seemingly adaptive strategies to backfire over time. Implications for research integrating emotion regulation, relationships, and depressive psychopathology are discussed.
Knock-In Rat Lines with Cre Recombinase at the Dopamine D1 and Adenosine 2a Receptor Loci
Authors: Pettibone Jeffrey R. , Yu Jai Y. , Derman Rifka C. , Faust Thomas W. , Hughes Elizabeth D. , Filipiak Wanda E. , Saunders Thomas L. , Ferrario Carrie R. , Berke Joshua D.
Published: August 2019

Genetically modified mice have become standard tools in neuroscience research. Our understanding of the basal ganglia in particular has been greatly assisted by BAC mutants with selective transgene expression in striatal neurons forming the direct or indirect pathways. However, for more sophisticated behavioral tasks and larger intracranial implants, rat models are preferred. Furthermore, BAC lines can show variable expression patterns depending upon genomic insertion site. We therefore used CRISPR/Cas9 to generate two novel knock-in rat lines specifically encoding Cre recombinase immediately after the dopamine D1 receptor (Drd1a) or adenosine 2a receptor (Adora2a) loci. Here, we validate these lines usingin situhybridization and viral vector mediated transfection to demonstrate selective, functional Cre expression in the striatal direct and indirect pathways, respectively. We used whole-genome sequencing to confirm the lack of off-target effects and established that both rat lines have normal locomotor activity and learning in simple instrumental and Pavlovian tasks. We expect these new D1-Cre and A2a-Cre rat lines will be widely used to study both normal brain functions and neurological and psychiatric pathophysiology.
Caracterización técnica, productiva y comercial de las MIPYMES lácteas caprinas en Costa Rica
Authors: Chacón-Villalobos Alejandro , Mora-Valverde David
Published: August 2019

Este estudio fue realizado entre los años 2017 y 2018. Se buscó establecer las características técnicas y productivas del sector industrializador costarricense de la leche caprina, por medio del estudio de 10 emprendimientos en todo el país. Se utilizó una herramienta de diagnóstico que consideró la sociografía de los productores, el origen y manejo de la leche, las condiciones operativas de las instalaciones, buenas prácticas de manufactura, productos lácteos manufacturados y su comercialización, así como las percepciones de los productores hacia el sector. Se documentaron aspectos como las características socioeconómicas de los productores, la experiencia en el sector, el rol de la actividad caprina dentro de su economía, la infraestructura de sus plantas de producción, los productos manufacturados y las prácticas de gestión administrativa. Se estableció que los emprendimientos industrializadores necesitan implementar acciones de mejora en diferentes áreas técnicas, administrativas y de gestión de la calidad. Muchas de sus problemáticas derivan del pequeño tamaño de los emprendimientos, y de la limitada cadena de comercialización existente. Posibles derroteros futuros y mejoras para el sector se discuten en este trabajo.
Document Informed Neural Autoregressive Topic Models with Distributional Prior
Authors: Gupta Pankaj , Chaudhary Yatin , Buettner Florian , Schütze Hinrich
Published: August 2019

We address two challenges in topic models: (1) Context information around words helps in determining their actual meaning, e.g., “networks” used in the contexts artificial neural networks vs. biological neuron networks. Generative topic models infer topic-word distributions, taking no or only little context into account. Here, we extend a neural autoregressive topic model to exploit the full context information around words in a document in a language modeling fashion. The proposed model is named as iDocNADE. (2) Due to the small number of word occurrences (i.e., lack of context) in short text and data sparsity in a corpus of few documents, the application of topic models is challenging on such texts. Therefore, we propose a simple and efficient way of incorporating external knowledge into neural autoregressive topic models: we use embeddings as a distributional prior. The proposed variants are named as DocNADEe and iDocNADEe. We present novel neural autoregressive topic model variants that consistently outperform state-of-the-art generative topic models in terms of generalization, interpretability (topic coherence) and applicability (retrieval and classification) over 7 long-text and 8 short-text datasets from diverse domains.
Neural Relation Extraction within and across Sentence Boundaries
Authors: Gupta Pankaj , Rajaram Subburam , Schütze Hinrich , Runkler Thomas
Published: August 2019

Past work in relation extraction mostly focuses on binary relation between entity pairs within single sentence. Recently, the NLP community has gained interest in relation extraction in entity pairs spanning multiple sentences. In this paper, we propose a novel architecture for this task: inter-sentential dependency-based neural networks (iDepNN). iDepNN models the shortest and augmented dependency paths via recurrent and recursive neural networks to extract relationships within (intra-) and across (inter-) sentence boundaries. Compared to SVM and neural network baselines, iDepNN is more robust to false positives in relationships spanning sentences. We evaluate our models on four datasets from newswire (MUC6) and medical (BioNLP shared task) domains that achieve state-of-the-art performance and show a better balance in precision and recall for inter-sentential relationships. We perform better than 11 teams participating in the BioNLP shared task 2016 and achieve a gain of 5.2% (0.587 vs 0.558) in F1 over the winning team. We also release the crosssentence annotations for MUC6.
Recurrent Poisson Process Unit for Speech Recognition
Authors: Huang Hengguan , Wang Hao , Mak Brian
Published: August 2019

Over the past few years, there has been a resurgence of interest in using recurrent neural network-hidden Markov model (RNN-HMM) for automatic speech recognition (ASR). Some modern recurrent network models, such as long shortterm memory (LSTM) and simple recurrent unit (SRU), have demonstrated promising results on this task. Recently, several scientific perspectives in the fields of neuroethology and speech production suggest that human speech signals may be represented in discrete point patterns involving acoustic events in the speech signal. Based on this hypothesis, it may pose some challenges for RNN-HMM acoustic modeling: firstly, it arbitrarily discretizes the continuous input into the interval features at a fixed frame rate, which may introduce discretization errors; secondly, the occurrences of such acoustic events are unknown. Furthermore, the training targets of RNN-HMM are obtained from other (inferior) models, giving rise to misalignments. In this paper, we propose a recurrent Poisson process (RPP) which can be seen as a collection of Poisson processes at a series of time intervals in which the intensity evolves according to the RNN hidden states that encode the history of the acoustic signal. It aims at allocating the latent acoustic events in continuous time. Such events are efficiently drawn from the RPP using a sampling-free solution in an analytic form. The speech signal containing latent acoustic events is reconstructed/sampled dynamically from the discretized acoustic features using linear interpolation, in which the weight parameters are estimated from the onset of these events. The above processes are further integrated into an SRU, forming our final model, called recurrent Poisson process unit (RPPU). Experimental evaluations on ASR tasks including ChiME-2, WSJ0 and WSJ0&1 demonstrate the effectiveness and benefits of the RPPU. For example, it achieves a relative WER reduction of 10.7% over state-of-the-art models on WSJ0.
Dictionary-Guided Editing Networks for Paraphrase Generation
Authors: Huang Shaohan , Wu Yu , Wei Furu , Luan Zhongzhi
Published: August 2019

An intuitive way for a human to write paraphrase sentences is to replace words or phrases in the original sentence with their corresponding synonyms and make necessary changes to ensure the new sentences are fluent and grammatically correct. We propose a novel approach to modeling the process with dictionary-guided editing networks which effectively conduct rewriting on the source sentence to generate paraphrase sentences. It jointly learns the selection of the appropriate word level and phrase level paraphrase pairs in the context of the original sentence from an off-the-shelf dictionary as well as the generation of fluent natural language sentences. Specifically, the system retrieves a set of word level and phrase level paraphrase pairs derived from the Paraphrase Database (PPDB) for the original sentence, which is used to guide the decision of which the words might be deleted or inserted with the soft attention mechanism under the sequence-to-sequence framework. We conduct experiments on two benchmark datasets for paraphrase generation, namely the MSCOCO and Quora dataset. The automatic evaluation results demonstrate that our dictionary-guided editing networks outperforms the baseline methods. On human evaluation, results indicate that the generated paraphrases are grammatically correct and relevant to the input sentence.
Domain Agnostic Real-Valued Specificity Prediction
Authors: Ko Wei-Jen , Durrett Greg , Li Junyi Jessy
Published: August 2019

Sentence specificity quantifies the level of detail in a sentence, characterizing the organization of information in discourse. While this information is useful for many downstream applications, specificity prediction systems predict very coarse labels (binary or ternary) and are trained on and tailored toward specific domains (e.g., news). The goal of this work is to generalize specificity prediction to domains where no labeled data is available and output more nuanced realvalued specificity ratings.We present an unsupervised domain adaptation system for sentence specificity prediction, specifically designed to output real-valued estimates from binary training labels. To calibrate the values of these predictions appropriately, we regularize the posterior distribution of the labels towards a reference distribution. We show that our framework generalizes well to three different domains with 50%-68% mean absolute error reduction than the current state-of-the-art system trained for news sentence specificity. We also demonstrate the potential of our work in improving the quality and informativeness of dialogue generation systems.
Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation
Authors: Kong Xiang , Xie Qizhe , Dai Zihang , Hovy Eduard
Published: August 2019

Mixture of Softmaxes (MoS) has been shown to be effective at addressing the expressiveness limitation of Softmax-based models. Despite the known advantage, MoS is practically sealed by its large consumption of memory and computational time due to the need of computing multiple Softmaxes. In this work, we set out to unleash the power of MoS in practical applications by investigating improved word coding schemes, which could effectively reduce the vocabulary size and hence relieve the memory and computation burden. We show both BPE and our proposed Hybrid-LightRNN lead to improved encoding mechanisms that can halve the time and memory consumption of MoS without performance losses. With MoS, we achieve an improvement of 1.5 BLEU scores on IWSLT 2014 German-to-English corpus and an improvement of 0.76 CIDEr score on image captioning. Moreover, on the larger WMT 2014 machine translation dataset, our MoSboosted Transformer yields 29.6 BLEU score for English-toGerman and 42.1 BLEU score for English-to-French, outperforming the single-Softmax Transformer by 0.9 and 0.4 BLEU scores respectively and achieving the state-of-the-art result on WMT 2014 English-to-German task.
What Should I Learn First: Introducing LectureBank for NLP Education and Prerequisite Chain Learning
Authors: Li Irene , Fabbri Alexander R. , Tung Robert R. , Radev Dragomir R.
Published: August 2019

Recent years have witnessed the rising popularity of Natural Language Processing (NLP) and related fields such as Artificial Intelligence (AI) and Machine Learning (ML). Many online courses and resources are available even for those without a strong background in the field. Often the student is curious about a specific topic but does not quite know where to begin studying. To answer the question of “what should one learn first,”we apply an embedding-based method to learn prerequisite relations for course concepts in the domain of NLP. We introduce LectureBank, a dataset containing 1,352 English lecture files collected from university courses which are each classified according to an existing taxonomy as well as 208 manually-labeled prerequisite relation topics, which is publicly available 1. The dataset will be useful for educational purposes such as lecture preparation and organization as well as applications such as reading list generation. Additionally, we experiment with neural graph-based networks and non-neural classifiers to learn these prerequisite relations from our dataset.
Insufficient Data Can Also Rock! Learning to Converse Using Smaller Data with Augmentation
Authors: Li Juntao , Qiu Lisong , Tang Bo , Chen Dongmin , Zhao Dongyan , Yan Rui
Published: August 2019

Recent successes of open-domain dialogue generation mainly rely on the advances of deep neural networks. The effectiveness of deep neural network models depends on the amount of training data. As it is laboursome and expensive to acquire a huge amount of data in most scenarios, how to effectively utilize existing data is the crux of this issue. In this paper, we use data augmentation techniques to improve the performance of neural dialogue models on the condition of insufficient data. Specifically, we propose a novel generative model to augment existing data, where the conditional variational autoencoder (CVAE) is employed as the generator to output more training data with diversified expressions. To improve the correlation of each augmented training pair, we design a discriminator with adversarial training to supervise the augmentation process. Moreover, we thoroughly investigate various data augmentation schemes for neural dialogue system with generative models, both GAN and CVAE. Experimental results on two open corpora, Weibo and Twitter, demonstrate the superiority of our proposed data augmentation model.
Leveraging Web Semantic Knowledge in Word Representation Learning
Authors: Liu Haoyan , Fang Lei , Lou Jian-Guang , Li Zhoujun
Published: August 2019

Much recent work focuses on leveraging semantic lexicons like WordNet to enhance word representation learning (WRL) and achieves promising performance on many NLP tasks. However, most existing methods might have limitations because they require high-quality, manually created, semantic lexicons or linguistic structures. In this paper, we propose to leverage semantic knowledge automatically mined from web structured data to enhance WRL. We first construct a semantic similarity graph, which is referred as semantic knowledge, based on a large collection of semantic lists extracted from the web using several pre-defined HTML tag patterns. Then we introduce an efficient joint word representation learning model to capture semantics from both semantic knowledge and text corpora. Compared with recent work on improving WRL with semantic resources, our approach is more general, and can be easily scaled with no additional effort. Extensive experimental results show that our approach outperforms the state-of-the-art methods on word similarity, word sense disambiguation, text classification and textual similarity tasks.
Contextualized Non-Local Neural Networks for Sequence Learning
Authors: Liu Pengfei , Chang Shuaichen , Huang Xuanjing , Tang Jian , Cheung Jackie Chi Kit
Published: August 2019

Recently, a large number of neural mechanisms and models have been proposed for sequence learning, of which selfattention, as exemplified by the Transformer model, and graph neural networks (GNNs) have attracted much attention. In this paper, we propose an approach that combines and draws on the complementary strengths of these two methods. Specifically, we propose contextualized non-local neural networks (CN3), which can both dynamically construct a task-specific structure of a sentence and leverage rich local dependencies within a particular neighbourhood.Experimental results on ten NLP tasks in text classification, semantic matching, and sequence labelling show that our proposed model outperforms competitive baselines and discovers task-specific dependency structures, thus providing better interpretability to users.
FANDA: A Novel Approach to Perform Follow-Up Query Analysis
Authors: Liu Qian , Chen Bei , Lou Jian-Guang , Jin Ge , Zhang Dongmei
Published: August 2019

Recent work on Natural Language Interfaces to Databases (NLIDB) has attracted considerable attention. NLIDB allow users to search databases using natural language instead of SQL-like query languages. While saving the users from having to learn query languages, multi-turn interaction with NLIDB usually involves multiple queries where contextual information is vital to understand the users’ query intents. In this paper, we address a typical contextual understanding problem, termed as follow-up query analysis. In spite of its ubiquity, follow-up query analysis has not been well studied due to two primary obstacles: the multifarious nature of follow-up query scenarios and the lack of high-quality datasets. Our work summarizes typical follow-up query scenarios and provides a new FollowUp dataset with 1000 query triples on 120 tables. Moreover, we propose a novel approach FANDA, which takes into account the structures of queries and employs a ranking model with weakly supervised max-margin learning. The experimental results on FollowUp demonstrate the superiority of FANDA over multiple baselines across multiple metrics.
Preparation And Characterization Of Novel Iron (III) HydroxidePaper Mill Sludge Composite Adsorbent For Chromium Removal
Authors: YARAŞ Ali , ARSLANOĞLU Hasan
Published: August 2019

This work deals with
the removal of Cr (III) and Cr (VI) from synthetic solutions via a novel
composite adsorbent prepared by precipitating iron (III) hydroxide on paper
mill sludge (PMS). To obtain Fe(OH)3 loaded PMS, -8+16 mesh fraction
of PMS was saponified with NaOH solution, then iron (III) chloride was
impregnated, hydrolyzed in NaOH solution and dried. The influences of pH, time,
initial concentration and temperature on removal of Cr (III) and Cr (VI) were
examined and it was determined that Cr (VI) removal occurs simultaneously with
a reduction reaction. Maximum removal yields for Cr (III) and Cr (VI) occurred
at approximately pH = 5 and the adsorption achieved equilibrium in 90 min. Cr
(VI) adsorption ratio decreases while Cr (III) removal percentage increases
with raising in temperature. Experimental results are consistent with Langmuir
isotherm. Adsorption capacities of Cr (III) and Cr (VI) were calculated as
8.49, 10.14, 12.62 mg/g and 7.64, 5.39 and 4.17 mg/g for 25, 40 and 55 °C,
respectively. Enthalpy changes for Cr (III) and Cr (VI) were calculated as
24.67 kJ/mol and -12.46 kJ/mol, respectively. These results demonstrated that
the adsorption phenomenon of Cr (III) and Cr (VI) are endothermic and
exothermic.
Feature Selection with Sequential Forward Selection Algorithm from Emotion Estimation based on EEG Signals
Authors: ALAKUŞ Talha Burak , TÜRKOĞLU İbrahim
Published: August 2019

In this study, we conducted EEG-based emotion recognition on arousal-valence emotion model. We collected our own EEG data with mobile EEG device Emotiv Epoc+ 14 channel by applying visual-aural stimulus. After collection we performed information measurement techniques, statistical methods and time-frequency attributes to obtain key features and created feature space. We wanted to observe the effect of features thus, we performed Sequential Forward Selection algorithm to reduce the feature space and compared the performance of accuracies for both all features and diminished features. In the last part, we applied QSVM (Quadratic Support Vector Machines) to classify the features and contrasted the accuracies. We observed that diminishing the feature space increased our average performance accuracy for arousal-valence dimension from 55% to 65%.
Rock Burst and Actually Effective Bolting for Rock Burst Prevention
Authors: Nguyen Ngoc Minh , Pham Duc Thang
Published: August 2019

Rock burst represents a very dangerous phenomenon in deep underground mining, as well as for underground structures in unfavourable conditions (great depth, high horizontal stress, proximity of major tectonic structures, etc.). The rock burst problem relates to the natural and mining conditions of the rock mass. The evaluation of rock burst is becoming increasingly important as mining activities reach greater depths. In the literature, rock burst assessment challenge was tackled by many researchers using various methods. However, no study providing review and comparison of different rock burst assessment methods is available. In this paper, rock burst classification is briefly summarized. This includes a classification based on rock burst type, and another classification based on rock burst severity. As an important method for rock burst prevention, some novel energy-absorbing bolts were developed. These bolts demonstrate constant resistance under both static and shock loads and large elongation ability enabling them to withstand large deformations of rock masses under rock burst-prone conditions. Among the novel energy absorbing bolts, Modified Cone Bolt (MCB) and Constant Resistance at Large Deformation (CRLD) Bolt are selected to be presented in this paper.
Selection of Material for Facing Drive Drum of Belt Conveyor
Authors: Hrydziushka D. V. , Brуzhevich A. V. , Piskun E. V.
Published: August 2019

It is known that conveyor operates in chemically aggressive and abrasive environments; for this reason the drive drum of belt conveyor wears out rather rapidly. It is noted that the lining of the conveyor drum increases coefficient of friction between the conveyor drum and the conveyor belt, reduces the belt wear rate, and also protects against corrosion and abrasive wear. The plot of the PU-60 polyurethane wear rate as function of load when rolling on steel is presented. It is noted that increasing the load increases the strength of adhesive junction between steel and polyurethane rollers; friction wear causes fatigue failure of surface layers of the materials. Besides, the plot of the PU-80 polyurethane wear rate as function of load when rolling on steel is presented. The plot of the polyurethanes wear rate as function of hardness of polyurethane is presented, which shows that the lowest wear rate is demonstrated by the hardest polyurethane, PU-80. The bar chart of static friction coefficient for PU-60 and PU-80 polyurethanes demonstrates that the optimal material for lining the drive drum of a conveyor belt is PU-80. The plot of the rubber wear rate as function of load at a speed of 1 m/s is presented. The plot shows that the wear rate increases with increasing the load. This is due to the effect of two factors: growing contact deformations of the surface layer of the rubber and increasing the contact area of mating parts. It is noted that IRP-1347 rubber is less susceptible to wear than "REMAGRIP" rubber. This allows using IRP-1347 rubber in aggressive environments. The bar chart of static friction coefficient for the rubber presented in the paper shows that the investigated IRP-1347 and REMAGRIP rubber grades have the required value of static friction coefficient for use as lining material for the drive drum. The plot of the wear rate as function of the rubber hardness and as function of the polyurethane hardness is presented. In practice, it is proved that the best material for lining the drive drum is PU-80.