bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Genetic Algorithms to Design an Optimized Keyboard Layout for Brazilian Portuguese
Authors: Pacheco Gustavo , Palmeira Eduardo , Yamanaka Keiji
Published: November 2020

Currently, keyboards are the most common means of communicating with computers. Despite being the most commonly used keyboard layout, QWERTY has had various issues raised concerning its effectiveness, as it is not efficient in English (target language) or in fact other languages. Therefore, this paper presents the development process of a Genetic Algorithm with the intention of generating a more adequate and coherent layout proposal for Brazilian Portuguese, which has its focus on ergonomics and user productivity. Using five ergonomic criteria and a statistical analysis of the characters and sequences of most frequently used pairs in Brazilian Portuguese, a layout approximately 53% better than QWERTY was obtained.
Uma Linguagem de Consulta para Visualização de Agrupamentos
Authors: Sodré Ana , Floriano Luis , Pozo Aurora , Hara Carmem
Published: November 2020

A utilização de técnicas de aprendizado de máquina popularizou-se nos últimos anos nas mais diversas áreas e aplicações. No entanto, a aplicação de tais técnicas ainda depende de um profissional especializado, que execute a sequência de tarefas necessárias para sua execução. Na área de banco de dados, o SQL democratizou a utilização de sistemas gerenciadores de bancos de dados (SGBD) para o usuário final através de uma linguagem declarativa simples, que se assemelha à linguagem natural. Neste artigo, é proposta a linguagem Clustering Visualization Query Language (CVQL), que estende o SQL para a realização de agrupamentos e visualização destes resultados. Agrupamento é uma técnica utilizada para dividir os dados em grupos que compartilham características similares. A visualização destes agrupamentos em diferentes formas é uma funcionalidade essencial para o usuário final analisar os grupos gerados. O CVQL foi implementado utilizando o SGBD mySQL e a biblioteca scikit-learn. Para apresentar o sistema, é adotado um exemplo de consulta com apenas 8 linhas sobre uma base de dados real de casos de Covid-19 nos EUA. Para o processamento da sequência de tarefas executadas pela consulta seriam necessárias 140 linhas de código na linguagem Python, que demonstra a utilidade do sistema.
Evaluation of Texture Maps as Input to Extract Deep Features in Glaucoma Diagnosis
Authors: Silva Daniel , Silva Romuere
Published: November 2020

Glaucoma is a significant cause of blindness in the world. Doctors use computerized images to detect these diseases. Early detection of the disease increases the chances of treatment, reducing the adverse effects. This work proposes an evaluation of texture maps combinations as input to Convolutional Neural Networks for glaucoma classification in retinal images. In our experiments, we used three textures maps, three CNN architectures, and three classifiers. We achieve a Kappa =0.708±0.054 and a Accuracy = 0.859±0.021. We conclude that using the combination of texture maps can improve the automatic detection of glaucoma compared to single-channel inputs, and could be used by state-of-the-art methods to improve their classification rates.
Automated Emergency Room Triage: Helping Patients Get the Best Treatment
Authors: Inoue Alexandre , Prado Marcus , Cozman Fábio
Published: November 2020

We describe an intelligent triage system for emergency rooms; the system interacts with patients and classifies them by priority level and with respect to medical specialty. The system consists of a conversational interface, coupled with sensors and a physical robot-like platform, and classifiers that operate on symptoms and measurements so as to select a medical specialty and to output a priority level. Tests with human subjects demonstrated that our Healthbot system was well received and in fact preferred to alternatives by most people. Tests have also shown that the classifiers reached accuracy consistent with a doctor's output.
Computational Mining on IBICT BDTD’s Thesis and Dissertation Metadata for Supporting Social Science Research
Authors: R. Filho Rodrigo , Oliveira Elismênnia , Nunes Jordão , Inuzuka Marcelo , Do Nascimento Hugo
Published: November 2020

The Brazilian Digital Library of Thesis and Dissertations (BDTD) provides essential data to support many social sciences investigations. Nevertheless, there is still a lack of computation tools tailored for helping extract and analyze the necessary information from the BDTD library. In this paper, we discuss the development of computational solutions to answer questions from a particular social sciences research using metadata from BDTD. The solutions involve the integration of data processing and presentation techniques, such as string-processing algorithms, knowledge graphs and information visualizations. All programming codes implemented at the scope of the project are available for helping other researchers. The paper also highlights the importance of having researchers from Social Science and Computer Science working together, what motivates future collaborations in these areas.
Brain Tissue Classification to Detect Focal Cortical Dysplasia in Magnetic Resonance Imaging
Authors: Simozo Fabricio , Oliveira Marcos , Murta-Junior Luiz
Published: November 2020

Focal cortical dysplasia (FCD) is a local malformation of the cortex, the main cause of refractory epilepsy in childhood and one of the most common causes in adults. The surgery decision and planning depend on the FCD localization. Although recent studies have successfully detected FCD through artificial intelligence, no study investigates the relevance and prevalence of cortical features on FCD identification and the performance of different machine learning techniques. In this study, the proposed method constructed a voxel-based set of features, e.g., texture measure, border definition, cortical thickness.
Descoberta de Conhecimento em Dados de Scout do Campeonato Brasileiro de Futebol
Authors: Ortolan Luís , Silva Diego
Published: November 2020

A análise de dados esportivos, conhecida como scout, tem ganhado grande atenção graças aos resultados positivos de sua aplicação em uma grande variedade de esportes. Devido à popularidade do futebol, há diversos trabalhos que buscam aplicar o Aprendizado de Máquina em dados de scout nesse esporte. Esses dados compreendem contagem de eventos, como passes e finalizações, e podem auxiliar o processo de tomada de decisão por parte de equipes técnicas. No entanto, esses esforços se concentram no futebol europeu. Neste trabalho, investigamos a obtenção de conhecimento por algoritmos de Aprendizado de Máquina em dados de scout obtidos no futebol brasileiro. Com isso, mostramos o potencial e as limitações atuais dessa abordagem.
Otimização de Florestas Aleatórias através de ponderação de folhas em árvore de regressão
Authors: Ponte Caio , Caminha Carlos , Furtado Vasco
Published: November 2020

Floresta Aleatória é um algoritmo popular e efetivo na resolução de problemas de classificação e regressão. As predições de uma Floresta Aleatória são feitas considerando que cada árvore possui igual contribuição no resultado final. Este trabalho propõe um novo método de ponderação de árvores de regressão com o objetivo de melhorar o poder de predição do modelo. Nossa estratégia é motivada em utilizar medidas de dispersão estatística, como desvio padrão ou erro padrão da média, como indicadores de qualidade da predição na folha. A estratégia de ponderação proposta foi comparada com outros métodos de ponderação. Nessa comparação observou-se que a mesma reduziu o Erro Absoluto Médio em cerca de 30% dos conjuntos de dados estudados.
Sensor Validation for Indoor Air Quality using Machine Learning
Authors: Seibert Vagner , Araújo Ricardo , McElligott Richard
Published: November 2020

To guarantee a high indoor air quality is an increasingly important task. Sensors measure pollutants in the air and allow for monitoring and controlling air quality. However, all sensors are susceptible to failures, either permanent or transitory, that can yield incorrect readings. Automatically detecting such faulty readings is therefore crucial to guarantee sensors' reliability. In this paper we evaluate three Machine Learning algorithms applied to the task of classifying a single reading from a sensor as faulty or not, comparing them to standard statistical approaches. We show that all tested machine learning methods -- Multi-layer Perceptron, K-Nearest Neighbor and Random Forest -- outperform their statistical counterparts, both by allowing better separation boundaries and by allowing for the use of contextual information. We further show that this result does not depend on the amount of data, but ML methods are able to continue to improve as more data is made available.
Improving automatic data extraction from financial statements with clustering analysis
Authors: Ferraz Victor , Olivato Gabriel , Magollo Igor , Naldi Murilo
Published: November 2020

The financial statement analysis is a fundamental part of the credit risk attribution process, producing documents that are valuable sources of information about companies’ economic and financial wealth. Large volumes of that type of document demand automatic data extraction, and locators drive the tools for that task. However, due to the lack of regulation, there is not a standard layout for such documents, which originates a variety of document structures. Such variety burdens the feature extraction tools, reducing their performance. Clustering analysis overcomes such burden by finding the best document clusters, allowing the development of fine-tuned locators for each cluster based on their main characteristics, which is the main objective of this work. We applied state-of-the-art clustering techniques, RNG-HDBSCAN*, FOSC and MustaCHE, over financial statements documents to assess their clusters and main structures, separate outliers, and analyze their main features. The result allows the specialists to define proper locators for each cluster, increasing the performance of the data extraction tools.
Extreme Events Characterization on Time Series
Authors: Rodrigues Marcos Wander , Zárate Luis Enrique
Published: November 2020

The use of sensors in environments where they require constant monitoring has been increasing in recent years. The main goal is to guarantee the effectiveness, safety, and smooth functioning of the system. To identify the occurrence of abnormal events, we propose a methodology that aims to detect patterns that can lead to abrupt changes in the behavior of the sensor signals. To achieve this objective, we provide a strategy to characterize the time series, and we use a clustering technique to analyze the temporal evolution of the sensor system. To validate our methodology, we propose the clusters’ stability index by windowing. Also, we have developed a parameterizable time series generator, which allows us to represent different operational scenarios for a sensor system where extreme anomalies may arise.
Spending Segmentation and Outlier Detection in Brazilian Elections
Authors: Simoes Leandro G. C. , Verri Filipe A. N. , Yoneyama Takashi
Published: November 2020

The political campaigns in Brazilian elections are mostly financed by public money. Every candidate has to provide detailed accountability reports to the legal authorities, which must be analyzed in a short time frame in search of eventual fraud or suspicious transactions. In this work we have compiled a real data set from 2016 Brazilian elections for all city councils in the São Paulo state and used it to propose a framework of data segmentation analysis and validation. An exploratory data analysis is performed to determine the features distribution and to define the required feature pre-processing tasks. A clustering analysis using DBSCAN method is applied to a subset of the original data, focused on segmenting the spending data regarding contracts with car fuel providers and detecting potential outliers. Three clusters were identified and a ridge regression model was used to evaluate the most important features on cluster definition. One cluster was related to candidates that received zero votes and the remaining two discriminated suppliers if they had or not contracts almost exclusively related to candidate spending on car fuel. The hyperparameters from the clustering analysis were validated using a bootstrap method and a null hypothesis of data set structure randomness was rejected using a Monte Carlo approach.
Machine Learning to Assist in Pneumonia Decision Making: A Systematic Review of the Literature
Authors: Silva Victor , Ramos Novo Amanda Days , Souza Damires , Rêgo Alex
Published: November 2020

Clinical decision support systems is a research area in which Machine Learning (ML) techniques can be applied. Nevertheless, specifically in assisting pneumonia decision making, the use of ML has not been so expressive. To help matters, this work aims to contribute to the evolution of the intersection of such areas by presenting a Systematic Review of the Literature. It provides results which may help to identify, interpret and evaluate how ML techniques have been applied and some research enhancements yet to be done.
Mini-Addenbrooke’s Cognitive Examination (MACE): a Useful Cognitive Screening Instrument in Older People?
Authors: Larner A.J.
Published: November 2020

Background

The Mini-Addenbrooke’s Cognitive Examination (MACE) is a recently described brief cognitive screening instrument.

Objective

To examine the test accuracy of MACE for the identification of dementia and mild cognitive impairment (MCI) in a cohort of older patients assessed in a neurology-led dedicated cognitive disorders clinic.

Methods

Cross-sectional assessment of consecutive patients with MACE was performed independent of the reference standard diagnosis based on clinical interview of patient and, where possible, informant and structural brain imaging, and applying standard clinical diagnostic criteria for dementia and MCI. Various test accuracy metrics were examined at two MACE cut-offs ( ≤ 25/30 and ≤ 21/30), comparing the whole patient cohort with those aged ≥ 65 or ≥ 75 years, hence at different disease prevalences.

Results

Dependent upon the chosen cut-off, MACE was either very sensitive or very specific for the identification of any cognitive impairment in the older patient cohorts with increased disease prevalence. However, at both cut-offs the positive predictive values and post-test odds increased in the older patient cohorts. At the more sensitive cut-off, improvements in some new unitary test metrics were also seen.

Conclusion

MACE is a valid instrument for identification of cognitive impairment in older people. Test accuracy metrics may differ with disease prevalence.
Comparison of the Effects of Deep Brain Stimulation of the Prelimbic Cortex and Basolateral Amygdala for Facilitation of Extinction Process of Conditioned Fear
Authors: Mokhtari Hashtjini Mina , Pirzad Jahromi Gila , Sadr Seyed Shahabeddin , Khaleghi Ali , Hatef Boshra , Meftahi Gholam Hossein
Published: November 2020

Background: The study of the biological basis of fear in animal models has progressed considerably because of the energy and space that the brain devotes to this basic emotion. Electrical stimulation targets several structures of the brain to examine its behavioral effects and to understand the role of different regions in underlying mechanisms of fear processing and anxiety in preclinical models. Objectives: In this study, the effects of high-frequency deep brain stimulation (DBS) of the basolateral amygdala (BLA) and prelimbic (PL) sub-region of the prefrontal cortex were evaluated on the extinction process of conditioned fear. Methods: This study was performed on 35 male Wistar rats in the weight range of 220 – 250 g. After selecting the animals, they were separated into five groups. Then, we did stereotactic surgery on rats for electrode implantation. After recovery, some rats were conditioned, followed by a 10-day treatment schedule via high-frequency DBS in the BLA or PL. Next, freezing behavior was measured as a predicted response dedicated to extinction, without shock (re-exposure). In addition, we used ELISA and Western blot to estimate blood serum corticosterone levels and c-Fos protein expression. Results: The mean freezing time recorded for the PL group was significantly lower than that of both the BLA group and the PC group (P < 0.01). The BLA group and PC group were also significantly different (P < 0.001). Corticosterone results indicated that the PL group had significantly higher serum corticosterone levels compared with both the BLA group and the PC group (P < 0.01). In addition, the BLA group revealed a significant reduction in c-Fos expression compared with the PC (P < 0.001). Conclusions: This study provides further evidence for the contribution of the prelimbic cortex and amygdala both in acquisition and extinction processes during contextual fear conditioning. However, the PL stimulation by high-frequency DBS might be more involved in the extinction process and play a more important role as an enhancer.
Comparison of Care Outcomes Between Two Methods of Drug Injection Through Ports and Peripheral Veins in Patients Undergoing Chemotherapy
Authors: Mosavi Seied Hashem , Elahi Nasrin , Asadizaker Marziyeh , Ahmadzadeh Deilami Ahmad
Published: November 2020

Background: One of the common treatments for cancer is chemotherapy that is usually done by intravenous injection. Central catheters and portholes are used for the intravenous administration of chemotherapy drugs through peripheral vessels. Objectives: This study aimed to compare the caring outcomes of the two methods of drug injection through the peripheral vessels and ports in patients undergoing chemotherapy. Methods: In this descriptive study, 68 cancer patients admitted to the Hematology and Oncology Wards of Shahid Baghaei Hospital 2 in Ahwaz during three months were evaluated in two groups of 34 patients receiving chemotherapy (one group via ports and one group via peripheral blood vessels). Data were collected by a questionnaire consisting of two parts: demographic information (sex, age, and type of disease) and information about the patient's condition (drug injection method, serum, and catheter number), and an observational checklist including inflammation rate, drug extravasation, limitation of patient movement, medical expenses, and patient satisfaction. Data were analyzed using SPSS version 24 software. Results: According to the results of the study, the two groups were compared in terms of inflammation (P = 0.0001, T = 4.908), drug extravasation (P = 0.0001, T = 3.872), movement limitation P = 0.000, T = 4.922) the cost of treatment (P = 0.0001, χ2 = 56.973, P = 0.000, and patient satisfaction (P = 0.0001, T = -23.66). Conclusions: Performing chemotherapy through the port has fewer side effects and brings more comfort to the patients.
Potential productivity realization of common winter wheat plants under drought
Authors: Zhuk O. I.
Published: November 2020

Aim. The goal of this work was to study the effect of soil drought on the reproductive ability of common winter wheat plants (Triticum aestivum L.). Methods. Wheat plants of cultivars Kujalnik and Ladijinka were grown under optimal nutrition and well-water conditions to the earing-flowering phase, after that the experimental plants were transferred to drought regime for 8 days, after that the optimal water supply was restored to the end of vegetation. During the experiment, the stem and ear length were measured. Ripened plants were analyzed according to the structure of the yield. Results. It is established that the effect of drought in the critical phase of ontogenesis the earing-flowering led to the decreasing the stem and ear length, the mass of the ear and grains, number of grains on plant. Conclusions. Water deficit in the soil in the critical phase of earing-flowering led to a decrease in the productive of winter wheat plants due to the inhibition of growth of stem and ear, decreasing grain number and the mass of ear and grains.

Keywords: Triticum aestivum L, stem, ear, productivity, drought.
Research progress of tin oxide-based thin films and thin-film transistors prepared by sol-gel method
Authors: Liu Xian-Zhe , Zhang Xu , Tao Hong , Huang Jian-Lang , Huang Jiang-Xia , Chen Yi-Tao , Yuan Wei-Jian , Yao Ri-Hui , Ning Hong-Long , Peng Jun-Biao ,   Institute of Polymer Optoelectronic Materials and Devices, State Key Laboratory of Luminescence Materials and Devices, South China University of Technology, Guangzhou 510641, China,   New Vision Opto-Electronic Technology Co., Ltd, Guangzhou 510530, China
Published: November 2020

Transparent conductive oxide (TCO) films and transparent oxide semiconductor (TOS) films have been widely adopted in solar cells, flat panel displays, smart windows, and transparent flexible electronic devices due to their advantages of high transparency and good conductivity and so on. Most of TCO and TOS films are mainly derived from indium oxide, zinc oxide and tin oxide. Among these materials, the In element is toxic, rare and expensive for indium oxide film, which will cause environmental pollution; zinc oxide film is sensitive to acid or alkali etchants, resulting in a poor formation of film patterning; tin oxide film is not only non-toxic, eco-friendly, and cheap but also has good electrical properties and strong chemical stability. Thus, tin oxide has a great potential for developing the TCO and TOS films. At present, the film is prepared mainly by the vacuum deposition technique. The drawbacks of this technique are complex and expensive equipment system, high energy consumption, complicated process and high-cost production. However, compared with the vacuum deposition technique, the sol-gel method has attracted extensive attention because of its virtues such as simple process and low cost. In this paper, we review the development status and trend of TCO and TOS films. First, the structural characteristics, conductive mechanism, element doping theory and carrier scattering mechanism of tin oxide thin films are introduced. Then the principle of sol-gel method and correlative film fabrication techniques are illustrated. Subsequently, the application and development of tin oxide-based thin films prepared by sol-gel method in n-type transparent conductive films, thin-film transistors and p-type semiconductor films in recent years are described. Finally, current problems and future research directions are also pointed out.
SHARPGrads: Development and Assessment of a Research Skills Workshop Program for Graduate Students at the University of South Carolina
Authors: Winchester Stacy L , Freeman Amie Dillard
Published: November 2020

INTRODUCTION Academic libraries are placing increasing emphasis on the provision of instruction for graduate students in non-traditional research skills and competencies such as scholarly communication concepts, data management and visualization, and text mining. Since proficiency in these concepts is often expected of graduate students but training may not be offered in the classroom, the library is a natural home for such instruction. DESCRIPTION OF PROGRAM Librarians at the University of South Carolina created a two-day workshop series for graduate students called SHARPGrads. This paper describes the planning process, survey method used to develop and assess the program, and findings obtained from attendance and survey responses. A successful collaboration with the university’s Graduate School led to higher than expected registration. Post-assessment feedback demonstrates that targeting training to graduate students early in their program of study is advantageous. Furthermore, students in social sciences and humanities disciplines reported that SHARPGrads met their expectations to a higher degree than students in the sciences and health sciences. Although a number of survey respondents reported that the training program was too short, participant retention during day two of the program dropped significantly. NEXT STEPS An evaluation of the range of second day training opportunities is considered for the next iteration of the program. Results taken from this study and recommendations for future programs will be useful for librarians involved in the development and implementation of workshops for graduate students.
Deep artificial neural network based on environmental sound data for the generation of a children activity classification model
Authors: García-Domínguez Antonio , Galvan-Tejada Carlos E. , Zanella-Calzada Laura A. , Gamboa Hamurabi , Galván-Tejada Jorge I. , Celaya Padilla José María , Luna-García Huizilopoztli , Arceo-Olague Jose G. , Magallanes-Quintanar Rafael
Published: November 2020

Children activity recognition (CAR) is a subject for which numerous works have been developed in recent years, most of them focused on monitoring and safety. Commonly, these works use as data source different types of sensors that can interfere with the natural behavior of children, since these sensors are embedded in their clothes. This article proposes the use of environmental sound data for the creation of a children activity classification model, through the development of a deep artificial neural network (ANN). Initially, the ANN architecture is proposed, specifying its parameters and defining the necessary values for the creation of the classification model. The ANN is trained and tested in two ways: using a 70–30 approach (70% of the data for training and 30% for testing) and with a k-fold cross-validation approach. According to the results obtained in the two validation processes (70–30 splitting and k-fold cross validation), the ANN with the proposed architecture achieves an accuracy of 94.51% and 94.19%, respectively, which allows to conclude that the developed model using the ANN and its proposed architecture achieves significant accuracy in the children activity classification by analyzing environmental sound.
Integrated analysis of lncRNA and mRNA reveals novel insights into cashmere fineness in Tibetan cashmere goats
Authors: Fu Xuefeng , Zhao Bingru , Tian Kechuan , Wu Yujiang , Suo Langda , Ba Gui , Ciren Deji , De Ji , Awang Cuoji , Gun Shuangbao , Yang Bohui
Published: November 2020

Tibetan cashmere goats are famous for producing the finest, softest and lightest cashmere fiber in China. The growth and development of skin are closely related to fineness and are the key factors affecting the quality of cashmere. To investigate the specific role of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in regulating cashmere fineness of Tibetan Cashmere goats in the anagen phase, we conducted high-throughput RNA sequencing of fine-type and coarse-type skin tissues. We identified 2,059 lncRNA candidates (1,589 lncRNAs annotated, 470 lncRNAs novel), and 80 differentially expressed (DE) lncRNAs and their potential targets were predicted. We also identified 384 DE messenger RNAs (mRNAs) out of 29,119 mRNAs. Several key genes in KRT26, KRT28, KRT39, IFT88, JAK3, NOTCH2 and NOTCH3 and a series of lncRNAs, including ENSCHIT00000009853, MSTRG.16794.17, MSTRG.17532.2, were shown to be potentially important for regulating cashmere fineness. GO and KEGG enrichment analyses of DE mRNAs and DE lncRNAs targets significantly enriched in positive regulation of the canonical Wnt signaling pathway, regulation of protein processing and metabolism processes. The mRNA-mRNA and lncRNA-mRNA regulatory networks further revealed potential transcripts involved in cashmere fineness. We further validated the expression patterns of DE mRNAs and DE lncRNAs by quantitative real-time PCR (qRT-PCR), and the results were consistent with the sequencing data. This study will shed new light on selective cashmere goat breeding, and these lncRNAs and mRNAs that were found to be enriched in Capra hircus RNA database.
The genetic diversity and population structure of two endemic Amazonian quillwort (Isoetes L.) species
Authors: Santos Mirella Pupo , Araujo João V.S. Rabelo , Lopes Arthur V. Sant’anna , Vettorazzi Julio Cesar Fiorio , Boechat Marcela Santana Bastos , Arêdes Fernanda AbreuSantana , Campos Naiara Viana , Calderon Emiliano Nicolas , Santos Fernando M. Gomes , Fernandes Tais Nogueira , da Fonseca Rodrigo Nunes , Pereira Messias Gonzaga , Oliveira Guilherme , Zandonadi Daniel Basilio , Martins RodrigoLemes , Esteves Francisco de Assis
Published: November 2020

Background

Two endemic lycophyte species Isoetes cangae and Isoetes serracarajensis have been recently described in the State of Pará in the Amazon forest located in northern Brazil. Isoetes L. has survived through three mass extinctions. Plants are considered small-sized, heterosporous, and can display a great diversity of physiological adaptations to different environments. Thus, the current study aimed to estimate the genetic variation of the populations of I. cangae and I. serracarajensis to generate information about their different mechanisms for survival at the same geographical location that could point to different reproductive, adaptative and dispersal strategies and should be considered for effective conservation strategies.

Methods

The genetic diversity and population structure of I. cangae and I. serracarajensis were investigated using Inter Simple Sequence Repeat (ISSR) molecular markers. Total genomic DNA was isolated, and the genetic diversity parameters were calculated.

Results

The sixteen primers produced 115 reproducible bands, 87% of which were polymorphic. A high level of polymorphic loci (81.74% and 68.48%) and a high Shannon index (Sh = 0.376 and 0.289) were observed for I. cangae and I. serracarajensis, respectively. The coefficient of genetic differentiation between population areas (GST) showed a higher value in I. serracarajensis (0.5440). Gene flow was higher in I. cangae (1.715) and lower in I. serracarajensis populations (0.419). Overall, the results further show that I. serracarajensis and I. cangae are two species with considerable genetic variation and that these differences may reflect their habitats and modes of reproduction. These results should be considered in the development of effective conservation strategies for both species.
Language and Archeology
Authors: Ricquier Birgit
Published: November 2020

Languages inform us about early ancestors, past contact situations, and innovations. Through language classification, it is possible to trace proto‐speech communities in time and in space. The “Words‐and‐Things” approach allows for insights into the material and sociocultural life of these proto‐speech communities. In order to investigate the causes of language dispersals, linguistic results are usually linked to data from other disciplines, such as archaeology. Methods used to relate results from multiple disciplines include correlation, direct association, and the search for common regional processes. Such multidisciplinary narratives are sometimes criticized for having circular reasoning or not being independently verifiable. A possible solution is the supplemental approach, which recognizes the differences between the data and methodologies of either discipline but proposes that they supplement each other. This, in turn, leads to better hypotheses on those parts of history for which no written texts exist.
Audience (and Audience Design)
Authors: Avineri Netta
Published: November 2020

The role of “audience” in interaction has been an area of interest within linguistic anthropology for decades. Various scholars have conceptualized the discursive and intersubjective relationships between interlocutors and the importance of audience/recipients/addressees to the ongoing negotiation of talk‐in‐interaction. Whereas earlier conceptualizations of language prioritized the role of the speaker, writer, or performer, a focus on audience has reshaped the field with its recognition of the ongoing, public, collaborative nature of interactions across contexts. These foci have moved “audience” from being seen as a passive recipient role to one that is foregrounded as an integral part of interactions. This entry will highlight how notions of audience have been theorized by a number of scholars, including Netta Avineri and Bernard C. Perley; Allan Bell; Alessandro Duranti; Norman Fairclough; Nelson Flores and Jonathan Rosa; Howard Giles, Donald M. Taylor, and Richard Bourhis; Erving Goffman, Charles Goodwin, John Heritage, Edwin Hutchins, Elinor Ochs and Lisa Capps; and Harvey Sacks, Emanuel A. Schegloff, and Gail Jefferson. This entry focuses on the role of audience in spoken, written, and multimodal communication across the lifecycle and across institutions (e.g. media, legal settings, policing, health contexts, family). In monolingual and multilingual contexts, the way that audience is conceptualized is shaped by interlocutors' identities (e.g. race, gender, sexuality) and epistemics. Language use (e.g. syntax, semantics, phonology, phonetics, morphology, pragmatics) can also undergo processes of styling depending on the relationships between speakers/users and audience. “Audience” has been examined through methods including participant‐observation and ethnography in global contexts. More recent scholarship on the topic has demonstrated how “audience” is intimately connected to power dynamics and the pursuit of social justice, to ensure that all audiences are seen and heard.
Babbling and Baby Talk
Authors: Davis Barbara L.
Published: November 2020

Canonical babbling marks the onset of speech‐like behavior in human infants. It is characterized by rhythmic syllabic vocalizations that contain alternations between consonants and vowels. These vocalizations sound like speech, but do not convey meanings to the listener. These syllables emerge from the developing biological capacities of the infant production and perception systems. They are deployed in social settings and enable functional connections between the infant and caregivers before language emerges.
Benedict, Ruth
Authors: Stanlaw James
Published: November 2020

Ruth Benedict (1887–1948) is one of the most famous anthropologists of the mid‐twentieth century. She is recognized as a founder of the “culture and personality” school of American anthropology, which was largely predicated upon, and influenced by, linguistics.
Bernstein, Basil
Authors: Stanlaw James
Published: November 2020

Basil Bernstein (1924–2000) was one of the founders of the field of sociolinguistics and was especially noted for his ideas about how economics and social class – and their corresponding manners of speech – have critical educational consequences.
Birdwhistell, Ray
Authors: Stanlaw James
Published: November 2020

The American anthropologist Ray Birdwhistell (1918–1992) was a key the founder of the field of kinesics, the study of facial expressions, posture, gestures, and body language. He argued that that as much as 70% of all information in a social interaction is conveyed nonverbally.
Child Language
Authors: Avineri Netta
Published: November 2020

The language of children and youth has been an area of interest within linguistic anthropology and related fields for decades. The earliest stages of language development among infants and toddlers, young children, and youth/teenagers are a critical site for socialization into both linguistic and cultural norms and practices. Scholarly foci have ranged from understanding how language works to biological perspectives on brain development to cultural learning. Child language can be examined through a number of lenses, including formal categories and features of language (e.g. syntax, semantics, phonology, phonetics, morphology, pragmatics), contexts (e.g. school, home, community), and interlocutors (e.g. family, peers, teachers, community members). The cases in this entry highlight diverse language practices among children and youth, including narrative, argument, routinized/formulaic language, code‐switching, language brokering, use of new technologies, and slang. Here, child language‐in‐context is central, based on in‐depth ethnographic studies that foreground the complexities of interactions, interlocutors, identities, practices, and ideologies.
Communication, Animal
Authors: Hurn Samantha
Published: November 2020

Communication between humans and nonhuman animals has been complicated by traditional assumptions that human language is preeminent. While some anthropologists have explored communication in nonhuman primates to inform our understanding of the evolution of human language, there has been reluctance within sociocultural anthropology to consider the communicative competencies of other species as intrinsically valuable. However, spoken language is just one of many communicative forms. Other animals also possess complex systems of communication, some displaying social aspects of human discourse such as turn‐taking, and some with such requisite criteria for language as a shared system of representational signs. Nonverbal communication is another feature of human and nonhuman social life, facilitating trans‐species empathy, while in systems of communication which utilize capacities humans lack, the precise meanings and mechanisms currently elude human understanding. This entry presents some representative examples of nonhuman and of human–nonhuman communication systems in relation to assumptions about human language.
Context and Contextualization
Authors: Kuipers Joel
Published: November 2020

While the notion of context has been in use for centuries, it has undergone remarkable conceptual refinement in the past 50 years. Once viewed in experimental psychology as a “nuisance variable,” among linguistic anthropologists it is associated with actor‐oriented meaning‐centered approaches to the description of communicative practice. The active process by which participants make relevant, cancel, or revise the interpretive process in conversation can then be viewed ascontextualization. More recently, linguistic anthropologists have turned their attention to the process by which structured, text‐like features of social interaction come to “gel” as “no longer in play,” and thus become “decontextualized.” How those discursive “texts” become “recontextualized” are among the most central practices within cultural orders, integral to the institutional authority of legal, medical, educational, and artistic systems.
Conversation Analysis (CA)
Authors: Rossi Giovanni
Published: November 2020

Conversation analysis (CA) is an approach to the study of language and social interaction that puts at center stage its sequential development. The chain of initiating and responding actions that characterizes any interaction is a source of internal evidence for the meaning of social behavior as it exposes the understandings that participants themselves give of what one another is doing. Such an analysis requires the close and repeated inspection of audio and video recordings of naturally occurring interaction, supported by transcripts and other forms of annotation. Distributional regularities are complemented by a demonstration of participants' orientation to deviant behavior. CA has long maintained a constructive dialogue and reciprocal influence with linguistic anthropology. This includes a recent convergence on the cross‐linguistic and cross‐cultural study of social interaction.
Definiteness, Grammatical
Authors: Khor Su Yin
Published: November 2020

Definiteness refers to the identifiability and non‐identifiability of referents in a particular context, i.e. the level of specificity of the referent can be established with a determiner. In English, this is most commonly expressed using determiners, such as
a/an
and
any
to mark indefiniteness, whereas determiners like
the
,
this
, and
that
mark definiteness. In some other languages, such as Swedish, affixes are used. The grammatical information encoded in the determiners or the affixes are not only limited to the referent's identifiability: some languages encode grammatical gender and number.
Evolution of the Human Body with Respect to Language Evolution
Authors: Putt Shelby S.J.
Published: November 2020

Language has left telltale signs of its evolution on the human body. By comparing the anatomy and genomes of humans with other apes, anthropologists have identified key areas of the human body that have evolved in response to the evolution of language and speech, including the vocal tract, ear, and brain. Because many of these structures are composed of soft tissues that do not fossilize, determining exactly when these changes occurred remains a challenge. This entry provides a broad overview of the different methods and tools that anthropologists have employed to interpret the language abilities of fossil hominins, the scientific critiques that have been leveled against some of these approaches, and the current status of the field.
Gumperz, John J.
Authors: Khor Su Yin
Published: November 2020

John J. Gumperz (1922–2013) was an American linguist whose work on speech and social groups greatly influenced sociolinguistics, linguistic anthropology, and discourse analysis. After returning from fieldwork in India, he joined the faculty at the University of California, Berkeley where he remained until his death.

With Dell Hymes, he developed a discourse analytic method drawing on ethnography for analyzing communication that considers the communicative form and function within a given cultural context or speech community. Gumperz's own contribution to linguistics includes a refined method for the analysis of social interactions, known as interactional sociolinguistics, underscoring the meaning making process between language users in social interactions.

In addition to the methodological import of his work, he contributed to the understanding of speech communities, especially language and power. For instance, he made a distinction between a so‐called standard variety and their speakers, seen as the more prestigious form of a language, contrasted with diglossic speakers who were users of marginalized varieties in addition to the more prestigious standard variety.
Imitation
Authors: Weidman Amanda
Published: November 2020

Imitation occurs at different levels of language, ranging from sound symbolism and other forms of iconicity at the word level, to formal resemblances and echoes at the level of the poetics of language, to larger‐scale, discourse‐level phenomena such as mimicry, stylization, and reported speech. This entry provides a broad perspective on the phenomenon of imitation in language and its utility as a theoretical concept in linguistic anthropology.
Kinship Terms and Kinship Systems
Authors: Heath Jeffrey
Published: November 2020

Kinship terminology has been studied in three distinct but overlapping ways. In one, kin terms are mapped onto genealogical grids consisting of kintypes, both consanguineal like cousin {MoBrCh, MoSiCh, FaBrCh, FaSiCh, …} and affinal like brother‐in‐law (SiHu, BrWi). The goal is to identify the principles underlying the full set of mappings in a given system. Correlations with social practices and cultural models may follow. The second approach focuses on how native speakers talk about kinship, how kin terms function in discourse, and how kin‐term systems can be decomposed into multiple subsystems. The third approach tackles the evolution over time of kin‐term systems, using historical documents or reconstruction. This terminological evolution may then be correlated with changing social‐structural practices.
Language and Creativity: Improvisation
Authors: Duranti Alessandro , McCoy Matthew
Published: November 2020

Improvisation is a ubiquitous aspect of both everyday and ritualized interactions. When composing utterances, speakers draw from a vast repertoire of expressions and patterns that allows for spontaneous invention across a range of situations and contexts. This entry explains how one's ability to improvise varies along a continuum and is made possible, in part, by socialization practices that include routine activities and frequent repetition while also allowing for some variation and individual invention. Past and current research suggests that repeated exposure to the conventions of particular speech genres and exchange systems, combined with an expansive stock of idiomatic, formulaic, or semi‐formulaic speech provides the building blocks out of which both planned discourse (e.g. in a scripted public speech) and improvised oral discourse (e.g. in informal conversation or in an unplanned public speech) are born.
Language and Creativity: Slang
Authors: Roth‐Gordon Jennifer
Published: November 2020

Any linguistic term identified as slang signals to listeners (and embeds speakers in) the negotiation of stance, style, and stigma. A speaker may intend to align with friends or with a trend in society, but a listener or overhearer may tap into more negative associations that frequently surround slang speaking. A thorough investigation of slang must include attention to larger social contexts in which lexical or discourse features come to be associated with non‐standard speech and a particular persona or trend. Attention to real‐world instances of language use contextualizes not only which words, phrases, or discourse patterns are considered slang, but also what the consequences and social outcomes are for different users of this marked speech style. Linguistically speaking, slang may feel like a moving target in part because it relies on social contexts that are themselves constantly changing. But slang remains incredibly stable as a linguistic label for speech that is placed in sharp contrast to the “standard language” and to any register that conveys formality and respect. As such, the study of slang offers deep insight into the identities, cultural and linguistic ideologies, and power relations within and between social groups.
Language and Social Class
Authors: Block David
Published: November 2020

This entry takes on the task of discussing linguistic anthropology research on language and class in education. After briefly clarifying what we might mean by class, it focuses on three foundational figures who have either directly or indirectly influenced later research. It then discusses four key studies carried out between the 1970s and the 2000s, before moving to a brief consideration of research on English in the world carried out during the first two decades of the twenty‐first century.
Language Emergence
Authors: Kegl Judy Anne
Published: November 2020

The emergence of language involves the creation of language from non‐language and contributes to the wider study of language acquisition that includes canonical cases of first‐language acquisition, second‐language acquisition, language evolution, and creolization. Language emergence provides strong evidence for the poverty of the stimulus argument that accounts for universals of language and makes a case for the biological bases of language and the impact of critical period on language acquisition. The process of language emergence is examined in the context of the emergence of Nicaraguan Sign Language – the first case of language emergence to be documented and studied as the process was underway. Although distinct from creolization in its lack of language input, this case of emergence is explored using models of creolization. Communication accountability and periodicity in the signal are argued to serve as major triggers to language emergence.
Language Families
Authors: Haugen Jason D.
Published: November 2020

Languages that descend from a common ancestor can be grouped together intolanguage families. This entry discusses the major issues involved in establishing suchlinguistic geneticrelations, including subdividing language families into subgroups and connecting established language families to larger macro‐families (also known as phyla or stocks). The major methods used by historical linguists to relate languages are assessed, as are the uses of lexical reconstruction to locate the homelands of and date non‐written ancestor languages (proto‐languages). Finally, some of the major language families from around the world are presented and overviewed.