bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Synthetic Images to Evaluate and Improve Object Detection Neural Network Performance on Aerial Image Datasets
Authors: Konen Kai , Hecking Tobias
Published: May 2022

Machine learning-based models for object detection heavily rely on large datasets of labeled images. When models trained on these datasets are applied to Unmanned Aerial Vehicle (UAV) imagery, the problem arises that the conditions under which the training images were created (lighting, altitude, angle) may be different to the UAVs applied conditions, leading to misclassifications. This problem becomes even more pressing in safety critical applications where failures can have huge negative impacts and constitute obstacles for certification of cognitive UAV components. Along a case study on car detection in low-altitude aerial imagery, we show that using, both, artificial and real images for model training has a positive effect on the performance of object detection algorithms when the trained model is applied on images from another domain. Additionally, we show that weak points from object detection neural networks trained on real-world images transfer to synthetic images and that synthetic data can be used to evaluate neural networks trained on real-world data. Since simulated images are easy to create and object labels are inherently given, the presented approaches show a promising direction for scenarios where adequate datasets are difficult to obtain, as well as for the targeted exploration of weak points of object detection algorithms.
ItemSB: Itemsets with Statistically Distinctive Backgrounds Discovered by Evolutionary Method
Authors: Shimada Kaoru , Arahira Takaaki , Matsuno Shogo
Published: May 2022

In this paper, we propose a method for discovering combinations of attributes (i.e. itemsets) against a background of statistical characteristics without obtaining frequent itemsets. The method considers a database with numerous attributes and can directly find a combination of highly correlated attributes from small populations in two consecutive variables of interest even from an incomplete database. As the proposed method determines local patterns in large-scale data, it may be used as a basis for large-scale data analysis. Evolutionary computations characterized by a network structure and a strategy to pool solutions are used throughout generations. Moreover, association rules are used to generalize the analysis method as itemsets with statistically distinctive backgrounds (ItemSBs). The class-association rules used for classification constitute a discovery method of attribute combinations, which are characteristic when the ratio of class attributes is obtained. The proposed method is an extension to statistical bivariate analysis. In addition, we determine contrast ItemSBs that are statistically different between two subgroups of data while satisfying the same conditions. Experimental results show the characteristics and effectiveness of the proposed method.
Integrating Scene Image and Conversational Text to Develop Human–Machine Dialogue
Authors: Wang Hao-Yi , Huang Jhih-Yuan , Lee Wei-Po
Published: May 2022

In recent years, it has become a trend to build social dialogue systems to achieve human–robot interaction. While current conversational systems mostly focus on the dialogue utterances, visual context also plays an important role in determining the relevance of the system responses to the dialogue. In this study, we develop an integrated approach to investigate how to achieve such a visual-language task. Our approach takes both scene images and dialogue utterances into account and trains a neural model to generate machine responses of natural language. We have conducted a series of experiments to evaluate the presented approach, and the results confirm its usefulness and effectiveness.
Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks — A Reward Curriculum Approach
Authors: Leyendecker Lars , Schmitz Markus , Zhou Hans Aoyang , Samsonov Vladimir , Rittstieg Marius , Lütticke Daniel
Published: May 2022

For years, the fully-automated robotic assembly has been a highly sought-after technology in large-scale manufacturing. Yet it still struggles to find widespread implementation in industrial environments. Traditional programming has so far proven to be insufficient in providing the required flexibility and dexterity to solve complex assembly tasks. Research in robotic control using deep reinforcement learning (DRL) advances quickly, however, the transfer to real-world applications in industrial settings is lagging behind. In this study, we apply DRL for robotic motion control to a multi-body contact automotive assembly task. Our focus lies on optimizing the final performance on the real-world setup. We propose a reward-curriculum learning approach in combination with domain randomization to obtain both force-sensitivity and generalizability of the controller’s performance. We train the agent exclusively in simulation and successfully perform the Sim-to-Real transfer. Finally, we evaluate the controller’s performance and robustness on an industrial setup and reflect its adherence to the high standards of automotive production.
In the presence of fear and refuge: Permanence, bifurcation and chaos control of a discrete-time ecological system
Authors: Banerjee Ritwick , Das Soumya , Das Pritha , Mukherjee Debasis
Published: May 2022

In this paper, we aim to study the effects of fear of predation in the presence of a competitor species and availability of refuge for the prey population. A discrete-time model of prey–predator–competitor type is formulated to study the dynamical relationship between the interacting species by deriving the conditions for local stability, permanence and existence of Neimark–Sacker bifurcation. A hybrid control technique based on state feedback strategy is implemented to control the chaos in the system. Finally, some numerical simulations are carried out to illustrate the theoretical discussions.
Diabetes mellitus prediction: An efficient pipeline of data imputation and oversampling
Authors: Rajawat Neha , Hada Bharat Singh , Lalwani Soniya , Kumar Rajesh
Published: May 2022

Diabetes is a chronic disease which indicates the high level of body glucose level. As per the World Health Organization (WHO), 422 million people were diabetic until 2014. This paper develops an accurate classification machine learning model and an efficient usage of data pre-processing pipeline to improve overall accuracy. For the purpose, six algorithms: Support Vector Machine with Linear kernel (Linear-SVM), Support Vector Machine with RBF kernel (RBF-SVM), K-Nearest Neighbor (KNN), Artificial Neural Network (ANN), Decision Tree and Random Forest are used for classification purpose and their comparative accuracy is analyzed. Data Imputation, Oversampling and Feature scaling techniques are the constituents of Data preprocessing pipeline. Experiments are performed on a well-known dataset of National Institute of Diabetes and Digestive and Kidney Diseases, the PIMA diabetes dataset. The data preprocessing techniques, data imputation and Synthetic Minority Oversample Technique (SMOTE) analysis improved classification accuracy from 77% on raw data, to 88.12% (on Random Forest Classifier) and 91% (on ANN Classifier), respectively. Furthermore, a new feature generation approach is applied and performance is analyzed using the SVM model. Original data attributes BMI and Insulin are replaced with new features BMI_NORMAL and INSULIN_NORMAL, respectively. The significant improvement by proposed technique is confirmed by statistical testing followed by post-hoc analysis.
Construction of Real Estate Debt Crisis Early Warning Model Based on RBF Neural Network
Authors: Jianyu Gui , Wenzhi Peng , Mingqing Jiao , Dong Zhou
Published: May 2022

The current market economic environment is constantly changing, and real estate companies are constantly facing various risks in the course of their operations, which have created some obstacles to real estate companies’ normal financial activities, and the occurrence of a debt crisis may reduce the company’s expected benefits. If real estate companies can identify debt risks early on and take effective steps to avoid them, they will have a better chance of avoiding debt problems. Therefore, this study introduces RBF neural network technology to construct a new real estate debt crisis early warning model. This study selects 20 indicators, constructs the financial early warning index system of listed companies, collects the financial data of 86 real estate listed companies from 2016 to 2020, uses the principal component analysis method to reduce the dimension of the collected financial data, and uses the reduced dimension data to construct the real estate debt crisis early warning model of RBF neural network to realize the real estate debt crisis early warning. The empirical results show that the early warning model constructed in this study can effectively warn the real estate debt crisis, effectively analyze the development trend of real estate companies, help to better prevent the debt crisis of real estate enterprises, and improve the comprehensive benefits of real estate enterprises.
Superresolution Reconstruction Method of Software Remote Sensing Image Based on Convolutional Neural Network
Authors: Wang Yani , Dong Jinfang , Wang Bo , Khanna Shaweta , Singh Anupam , Hussain Syed Abid
Published: May 2022

In order to solve the problem of long training time for remote sensing image super-resolution reconstruction algorithm, a method for remote sensing image superresolution reconstruction based on convolutional neural network is proposed, which combines dense convolutional network, parallel CNN structure, and subpixel convolution. The features of low-resolution images are extracted using dense convolutional networks, parallel CNNs are used to reduce network parameters, and subpixel convolutions are used to complete feature reconstruction. The results show that the final PSNR value of the black curve with the number of iterations of the three methods in the training process is the highest 27.3, followed by the middle curve, and the worst curve is 27.0. It is proved that the method extracts more features, retains more image details, and improves the reconstruction effect of the image; it greatly reduces the parameters in the network and avoids the phenomenon of overfitting in the deep network.
Convolutional Neural Network-Based Algorithm for Predicting the Gross Marine Product in Fujian Province
Authors: Liu Tao , Shan Juan
Published: May 2022

Ocean economy is the sum of various industrial activities for developing, utilizing, and protecting the ocean, as well as the activities associated with it. As the globe gradually pays more attention to ocean economic growth, China, as a significant maritime country, has begun to pay attention to the sector and put up ocean economic development policies. The marine economy has great potential, and the development of the marine economy is of great significance to the economic development of China. The Fujian Province is located at the junction of the Belt and Road and the Yangtze River Economic Belt, with a unique geographical location and natural resource advantages. Analyzing the state of the ocean economy in the Fujian Province, identifying challenges, and developing ocean economic development strategies to promote the long-term growth of the ocean economy in the Fujian Province has become a pressing issue that must be addressed. Because there is currently limited research on ocean economic systems and a paucity of ocean economic data, this paper uses a deep neural network to forecast the ocean production output value of the Fujian Province. The experimental results show that the model proposed in this paper can predict the ocean invention value of the Fujian Province well, which confirms the effectiveness of the model.
An Empirical Study on the Impact of Customer Purchase Intention Based on Factor Analysis and Structural Equation Model
Authors: Huang Shiwang
Published: May 2022

Consumer purchasing choices are being more influenced by online reviews, and bad online reviews have a greater effect on customers than favourable online reviews. In order to investigate the mechanism by which negative online reviews influence consumer purchase decisions, this paper focuses on two key indicators of negative online reviews: the quality of negative reviews and the quantity of negative reviews. It also introduces consumer product involvement and perceived risk as intermediary variables. SPSS 20.0 and AMOS 23.0 analytic software is used for descriptive, validity, reliability, correlation, and regression analyses of data. The empirical approach is used to verify and update a model or hypothesis. Detrimental Internet reviews had a negative impact on customers' purchase intentions, as well as the perceived risk and product engagement of the recipient's psychological representations, according to this research.
Research on Tourism Route Recommendation Strategy Based on Convolutional Neural Network and Collaborative Filtering Algorithm
Authors: He Shan
Published: May 2022

With improving people’s living standards, tourism has become essential leisure and entertainment. At present, it has begun to shift from a quantity-oriented tourism method to a quality-oriented tourism method. It is difficult for passengers to choose the route that suits them from the numerous routes. Given the above problems, this study proposes a travel route recommendation algorithm that combines a convolutional neural network and collaborative filtering. The algorithm uses a convolutional neural network to extract the latent features in the customer and travel itinerary data and then uses the matrix factorization method based on collaborative filtering to perform score prediction. The experimental results show that the algorithm can meet the travel requirements of different customers. At the same time, the recommendation accuracy of the tourist route is improved, and technology and method are provided for realizing the personalized recommendation service of the tourist route.
Research on Precision Teaching Model of Ideology Course Based on Collaborative Filtering Algorithm
Authors: Li Jinshan
Published: May 2022

The ideological and political course should not only keep the academic rationality and political nature of the course itself, but also take into account the characteristics of colleges and universities and students’ growth and development needs. At present, there are some problems in the curriculum of ideology, such as mechanical rigidity, weak pertinence, lack of synergy, and inability to form a personalized collaborative and precise education mechanism. Aiming at related problems, this article constructs an accurate teaching model of ideological and political course based on collaborative filtering algorithm. First, the public test set of recommended fields is used to test and verify the effectiveness and practicability of the algorithm. For the data sparseness and cold start of collaborative filtering algorithm, the course feature attributes and attribute value preference matrix are used to solve the problem, and the similarity is calculated offline, so as to realize the real-time recommendation and accurate teaching of the course. In order to verify the effectiveness of this method for precise teaching, we conducted a test. The test results show that the precise teaching model has a positive effect on the improvement in students’ academic performance. The method proposed in this article realizes the identity transformation of students from passive acceptance to active construction, and the teaching effectiveness of ideological and political course is effectively improved.
Production Optimization and Biochemical Characterization of Cellulase from Geobacillus sp. KP43 Isolated from Hot Spring Water of Nepal
Authors: Khadka Subash , Khadka Deegendra , Poudel Ram Chandra , Bhandari Mukund , Baidya Purnima , Sijapati Jaishree , Maharjan Jyoti
Published: May 2022

This study is aimed at isolating and identifying a thermophilic cellulolytic bacterium from hot spring water and characterizing thermostable cellulase produced by the isolate. Enrichment and culture of water sample was used for isolation of bacterial strains and an isolate with highest cellulase activity was chosen for the production, partial purification, and biochemical characterization of the enzyme. Different staining techniques, enzymatic tests, and 16s ribosomal DNA (16s rDNA) gene sequencing were used for the identification of the isolate. The cellulase producing isolate was Gram positive, motile, and sporulated rod‐shaped bacterium growing optimally between 55°C and 65°C. Based on partial 16s rDNA sequence analysis, the isolate was identified as Geobacillus sp. and was designated as Geobacillus sp. KP43. The cellulase enzyme production condition was optimized, and the product was partially purified and biochemically characterized. Optimum cellulase production was observed in 1% carboxymethyl cellulose (CMC) at 55°C. The molecular weight of the enzyme was found to be approximately 66 kDa on 12% SDS‐PAGE analysis. Biochemical characterization of partially purified enzyme revealed the temperature optimum of 70°C and activity over a wide pH range. Further, cellulase activity was markedly stimulated by metal ion Fe2+. Apart from cellulases, the isolate also depicted good xylanase, cellobiase, and amylase activities. Thermophilic growth with a variety of extracellular enzyme activities at elevated temperature as well as in a wide pH range showed that the isolated bacteria, Geobacillus sp. KP43, can withstand the harsh environmental condition, which makes this organism suitable for enzyme production for various biotechnological and industrial applications.
[Retracted] Toxicological Effects of Sewage Water on Chick Embryonic Development
Authors: Khan Sana , Baqa Hafiz Muhammad Noman , Mahmood Hamas , Farooq Muhammad , Samiullah Khizar , Yasin Riffat , Bashir Muhammad Amjad , Rahman Abdur , Mehmood Tahir , Atta Sagheer , Alkhuriji Afrah Fahad
Published: May 2022

For toxicity research, a total of 100 fertilized nonincubated eggs were used for this study. There were two trials in this experiment which were further divided into 2 phases based on a different days of sewage water treatment and observation days. In each trial, 50 eggs were used and divided into 5 groups. Group A, B, and C were treated with three different concentrations of pure and diluted sewage water (100%, 70%, and 30%), respectively. Control group D was given 0.3 ml saline solution (0.9% NaCl) and group E was uninjected. Different parameters such as the embryo’s body weight, body length, forelimb length, hindlimb length, and head diameter were determined. In trial 1, eggs were treated with sewage water on 7th day of incubation and opened on 8th day (phase I) and 9th day (phase II). When the trial 1 (phase I) findings were compared to the control groups, it was observed that body weight, body length, forelimb length, and hindlimb length were highly statistically significant differences (p < 0.01), but the head diameter was not significant (p > 0.05). Phase II result showed embryo’s head diameter was a highly statistically significant difference (p < 0.01), whereas forelimb length was significant (p < 0.05), and body weight, body length, and hindlimb length were nonsignificant (p > 0.05). In trial 2, eggs were treated with sewage water on 14th day of incubation and opened on 15th day (phase I) and 16th day (phase II). Results of 15th day showed a highly statistically significant (p < 0.01) difference in hindlimb length, while body weight, body length, forelimb length, and head diameter were nonsignificant (p > 0.05). Phase II of trial 2 showed that on 16th day, body weight, body length, forelimb length, hindlimb length, and head diameter showed a nonsignificant (p > 0.05) difference between experimental and control groups. Embryos were observed to be deforming on the 9th day (after 48 hours of exposure to sewage water). Other phases showed no signs of deformation. Except on 8th day of incubation, dose‐related mortalities were present in experimental groups, while the control group showed no mortality.
Computational English Online Teaching Monitoring System Based on Deep Learning Algorithm
Authors: Feng Julin , Michalak Wazid
Published: May 2022

In order to improve the monitoring effect of English online teaching, this paper combines the deep learning algorithm to construct the English online teaching monitoring system and conduct real-time supervision of the English online teaching process. Furthermore, by altering the original DCGAN, this research seeks to apply the approach of constructing a deep convolutional adversarial network to tackle the issue of small-sample target recognition in a given scene and develop an appropriate learning model. According to the results of the experimental research, the English online teaching monitoring system proposed in this paper, which is based on the deep learning algorithm, can play an important role in online English teaching monitoring and effectively improve the efficiency of online English management.
Long Noncoding RNA MALAT1 Promotes Laryngocarcinoma Development by Targeting miR‐708‐5p/BRD4 Axis to Regulate YAP1‐Mediated Epithelial‐Mesenchymal Transition
Authors: Wu Xiaoqin , Tan Yenong , Tang Xuxia
Published: May 2022

Objective. The objective of this study was to investigate whether long noncoding RNA Metastasis‐Associated Lung Adenocarcinoma Transcript 1 (MALAT1) contributes to laryngocarcinoma development via regulating the Yes‐associated protein 1‐ (YAP1‐) mediated epithelial‐mesenchymal transition (EMT) and the underlying mechanism. Methods. The effects of MALAT1 suppression and BET inhibitor JQ1 on the malignant phenotypes and cancer stem cell‐ (CSC‐) like properties of laryngocarcinoma cells as well as the expression of bromodomain‐containing protein 4 (BRD4), YAP1, and EMT markers were investigated. Moreover, the relationships between MALAT1 and miR‐708‐5p as well as between miR‐708‐5p and BRD4 were explored. Furthermore, whether MALAT1 regulated the malignant phenotypes of laryngocarcinoma cells via sponging miR‐708‐5p to target BRD4 was revealed by both in vitro and in vivo experiments. Results. MALAT1 suppression inhibited the malignant phenotypes of laryngocarcinoma cells, such as decreased proliferation, promoted apoptosis, suppressed migration, and inhibited the CSC properties. Suppression of MALAT1 increased miR‐708‐5p expression and decreased the expression of BRD4 and YAP1 and inhibited EMT. Moreover, there were target relationships between MALAT1 and miR‐708‐5p as well as between miR‐708‐5p and BRD4. miR‐708‐5p overexpression and MALAT1 suppression had synergistic inhibitory effects on the malignant phenotypes of laryngocarcinoma cells and the expression of BRD4, YAP1, and EMT. Furthermore, in vivo experiments confirmed that MALAT1/miR‐708‐5p regulated tumorigenicity by regulating BRD4 and YAP1‐mediated EMT. Conclusions. Our results indicate that suppression of MALAT1 may inhibit laryngocarcinoma development by sponging miR‐708‐5p/BRD4 to regulate YAP1‐mediated EMT. Targeting MALAT1/miR‐708‐5p/BRD4 axis may provide a promising therapeutic strategy for laryngocarcinoma.
An Evaluation Method of English Teaching Ability Based on Deep Learning
Authors: Song Chunyan
Published: May 2022

The traditional English teaching ability assessment algorithm has some problems, such as low accuracy and poor effect. Therefore, this paper proposes an English teaching ability assessment algorithm based on deep learning. According to the proposed method, it analyzes the characteristics of the input layer, convolution layer, pooling layer, and fully connected layer in the deep learning technology. And then, it also help to determine the dimensions of the convolution kernel matrix and derive the weight parameters through back propagation. Finally, it introduces the open-minded computing for deep learning assessment of English teaching ability, calculate the best standard data and best vector data ratio, and establish a deep learning model to realize English teaching ability assessment. The experimental results show that this method can improve the accuracy of English teaching ability assessment.
Economic Forecasting Model Based on Chaos Simulated Annealing Neural Network
Authors: Zhang Qing , Mu Yuning
Published: May 2022

In view of the prototype of the traditional chaotic network model, a neural network model with continuously updated chaotic noise is innovatively improved. This model has the advantages of two network models. On this basis, a logic graph is proposed, which can replace the chaotic noise generated by the running process of the model function. Models with these advantages can innovatively solve problems such as constrained optimization with dimensions larger than three, high discreteness, and weak linear relationship between convex and concave. Simulation results can be confirmed that the algorithm of this model is very close to the predicted value. This neural network model is an improved model with strong applicability and can be applied to optimization problems of economic systems or other industrial systems. In order to effectively alleviate the predictive control problem of nonlinear research objects, we propose a control method based on chaotic neural network in this study. Taking the economic model as the nonlinear object, establishing the basic structure of the chaotic neural network model, reconstructing the time and space structure, and obtaining the optimal solution of time continuation and embedding dimension through information entropy and pseudonearest neighbor, then the chaotic properties of nonlinear objects and the topology of chaotic neural networks are determined. In the simulation, test samples and experimental samples are established, and the predicted and true values are compared. The prediction results of the model established by this method in this study prove the effectiveness of the method. The training time of the chaotic neural network will not fall into a local minimum, thereby reducing the training time and ensuring the accuracy of the prediction.
A New Joint Approach with Temporal and Profile Information for Social Bot Detection
Authors: Yang Zhou , Chen Xingshu , Wang Haizhou , Wang Wenxian , Miao Zhenxiong , Jiang Tao
Published: May 2022

With the increasing popularity of online social networks (OSNs), a huge number of social bots have emerged. Social bots are involved in various cybercrimes like cyberbullying and rumor dissemination, which have seriously affected the normal order of OSNs. Nowadays, existing studies in this field almost focus on English OSNs like Twitter and Facebook. However, it is difficult to directly apply these detection technologies to Sina Weibo, which is one of the largest Chinese microblogging services in the world. In addition, social bots are evolving rapidly and time-consuming feature engineering may not perform well in detecting newly emerging social bots. In this paper, we propose a new joint approach with Temporal and Profile information for social bot detection (TPBot). The approach includes data collection module, feature extraction module, and detection module. To begin with, data collection module uses a web crawler to obtain user data from Sina Weibo. Next, the feature extraction module regards the user posts as temporal data to extract temporal-semantic and temporal-metadata features. Furthermore, this module extracts features based on users’ profile. Finally, a detection model based on BiGRU and attention mechanism is designed in the detection module. The results show that TPBot performs better than baselines with the F1-score of 0.9837 on the Sina Weibo dataset. Moreover, we have also conducted an experiment on the two datasets collected from Twitter to evaluate the generalization ability of TPBot. It is found that TPBot outperforms baselines on the new datasets and has good generalization ability.
Dimensions of Internet of Things: Technological Taxonomy Architecture Applications and Open Challenges—A Systematic Review
Authors: Kumar Krishna , Kumar Aman , Kumar Narendra , Mohammed Mazin Abed , Al-Waisy Alaa S. , Jaber Mustafa Musa , Shah Rachna , Al-Andoli Mohammed Nasser
Published: May 2022

We are traversing the growing emerging technology paradigms in today’s advanced technological world. In this present era, the Internet of Things (IoT) is extensively used in all sectors. IoT is the ecosystem of smart devices which contains sensors, smart objects, networking, and processing units. These integrated devices provide better services to the end user. IoT is impacting our environment and is becoming one of the most popular technologies. The leading use of IoT in human life is to track activities anywhere at any time. The utmost utilities achieved by IoT applications are decision-making and monitoring for efficient and effective management. In this paper, an extensive literature review on IoT has been done using the systematic literature review (SLR) technique. The main focus areas include commercial, environmental, healthcare, industrial, and smart cities. The issues related to the IoT are also discussed in detail. The purpose of this review is to identify the major areas of applications, different popular architectures, and their challenges. The various IoT applications are compared in accordance with technical features such as quality of service and environmental evaluation. This study can be utilized by the researchers to understand the concept of IoT and provides a roadmap to develop strategies for their future research work.
Experimental Investigation to Utilize Adsorption and Absorption Technique to Reduce CO2 Emissions in Diesel Engine Exhaust Using Amine Solutions
Authors: Muthiya Solomon Jenoris , Natrayan L. , Kaliappan S. , Patil Pravin P. , Naveena B. E. , Dhanraj Joshuva Arockia , Subramaniam Mohankumar , Paramasivam Prabhu
Published: May 2022

Due to the increased demand for global transportation needs, a long-range diesel engine is considered an important prime mover to fulfill the transportation demand. The major problem addressed by the diesel engines is it liberates harmful emissions and it also increases global warming. CO2 is considered an important greenhouse gas and it has to be controlled by diesel engines. In this research, extensive experimental work is done to identify a suitable solution to control CO2 emissions. For five different mole concentrations (0.1 to 0.5), three types of amino solutions (L-alanine, L-aspartic acid, and L-arginine) were prepared. By passing diesel exhaust through each solution, CO2 absorption is investigated. For CO2 absorption, an appropriate CO2 control system is built and tested. The tests were carried out in a diesel engine which is a naturally aspirated single-cylinder engine with a water-cooled system. It was possible to obtain an effective CO2 reduction of up to 90%, as well as a simultaneous reduction in HC and CO.
Management of Acute Adrenal Insufficiency-Related Adverse Events in Children with Congenital Adrenal Hyperplasia: Results of an International Survey of Specialist Centres
Authors: Ali Salma Rashid , Bryce Jillian , Krone Nils P. , Claahsen-van der Grinten Hedi L. , Ahmed S.Faisal
Published: May 2022

Introduction: There is wide variation in reported rates of acute adrenal insufficiency (AI)-related adverse events (sick day episodes and adrenal crises) between centres. This study aimed to evaluate the level of consensus on criteria considered essential for defining and managing these events in children with Congenital Adrenal Hyperplasia. Methods: Active users of the International Congenital Adrenal Hyperplasia and International Disorders of Sex Development (I-CAH/I-DSD) Registries (n = 66), non-active users of I-CAH/I-DSD (n = 35), and the EuRRECa e-Reporting Registry (n = 10) were approached to complete an online survey. Results: Fifty-six centres from 27 countries responded to the survey; the response rates for the three groups were 42 (65%), 11 (31%), and 3 (30%), respectively. Steroid management plans, one to one patient education, and contact details of health care staff were provided by over 90% of centres in high-income countries. All 56 centres advised glucocorticoid stress dosing in the event of fever. Less common indications for sick day dosing included vaccination and mild afebrile intercurrent illness, recommended by 17 (30%) and 9 (16%) centres, respectively. The most frequently reported stress dosing regimens were tripling the total daily dose of hydrocortisone and administering 3 times daily and doubling or tripling the largest daily hydrocortisone dose depending on the nature of the trigger and administering 3 times daily, recommended by 24 (43%) and 21 (38%) centres, respectively. Vomiting was the most common indication for intramuscular hydrocortisone injection, reported by 34 (61%) centres. Over 50% of respondents indicated that essential clinical criteria for adrenal crisis should include fatigue and nausea or vomiting and over 60% indicated that hypotension, hyponatraemia, hyperkalaemia, and clinical improvement following parenteral glucocorticoids were essential criteria. In the event of an adrenal crisis, 47 (84%) reported that the majority of patients were admitted to hospital. For the management of an adrenal crisis, a bolus parenteral injection of hydrocortisone was the most frequently administered medication, reported by 50 (89%) centres. Conclusion: Although there is variation in the definition and management of AI-related adverse events in children amongst centres, there is also a good level of consensus on specific aspects that can lead to greater benchmarking of care.
Do conceito de “variante” nos estudos do léxico de perspectiva histórico-variacional
Authors: Machado Filho Américo Venâncio Lopes
Published: May 2022

Embora plenamente assentado nos estudos sociolinguísticos contemporâneos, o conceito de variante linguística demanda uma revisão teórica, se observado a partir da ótica dos estudos do léxico, sobretudo quando este estiver relacionado a pesquisas de viés histórico-variacional. Neste trabalho, apresentam-se considerações sobre os possíveis limites de identificação e caracterização da unidade de variação lexical, quando consideradas alterações formais em outros níveis de análise, especialmente os de verve fonética. Utilizam-se, como suporte para a reflexões sobre o tema, considerações sobre o processo de constituição do léxico do português e, em especial, os resultados de fenômenos de convergência e divergência etimológicas registrados na história da língua.
Português Almoxarife, São Tomé: sentenças relativas com relativizadores ku e com
Authors: Figueiredo Carlos Filipe Guimarães
Published: May 2022

O presente trabalho analisa a elaboração de sentenças relativas com recurso aos relativizadores “ku” e “com” no português da comunidades bilingue (português e santome) de Almoxarife, São Tomé, procurando determinar as motivações que subjazem a essas construções.
Discursos da imprensa brasileira sobre a voz de Lula
Authors: Piovezani Carlos
Published: May 2022

Desde o anúncio do câncer de laringe de Lula em outubro de 2011, vimos surgir um amplo e disperso conjunto de textos sobre os riscos que a doença representava para a voz do ex-presidente do Brasil. Fundamentados na Análise do discurso, derivada de Michel Pêcheux, nossa proposta consiste em interpretar alguns dos enunciados da mídia brasileira que trataram da voz de Lula, na tentativa de interpretar suas distintas posições e seus diferentes sentidos. Buscamos ainda empreender uma reflexão sobre certos aspectos da memória e da história brasileira conservados na voz de uma de suas personagens mais importantes, no intuito de aventar possíveis respostas às seguintes questões: por que se falou tanto de sua voz? Quais são as posições e os sentidos dessas falas sobre a voz de Lula? Qual o papel que ela desempenhou em suas falas públicas, na composição de seu carisma e em seu sucesso político?
A teoria da argumentação na língua e sua relação com Platão, Saussure e Benveniste: breve discussão epistemológica
Authors: Dall'Cortivo-Lebler Cristiane
Published: May 2022

A Teoria da Argumentação na Língua, desenvolvida por Oswald Ducrot, Jean-Claude Anscombre e Marion Carel experimentou, ao longo de seu desenvolvimento, diferentes fases e formas, através das quais seus autores buscaram constantemente um alinhamento ente aquilo que seu principal desenvolvedor, Oswald Ducrot, denominou hipóteses externas e hipóteses internas. O presente trabalho discute a presença de Teorias Linguísticas e da Filosofia na obra de Ducrot, através de conceitos de Platão, Ferdinand de Saussure e Émile Benveniste, que constituem suas hipóteses externas. Tal presença culminou na criação de diferentes conceitos que compõem a Semântica Linguística, bem como lhe conferiram um olhar específico sobre a linguagem, que valoriza as relações da língua com a própria língua, bem como entende que a fala é fruto da atividade linguística de um eu que fala para um tu.
Atenuação e cortesia em intervenções metaenunciativas na conversa
Authors: Hilgert José Gaston
Published: May 2022

No desdobramento de uma conversa chama particular atenção a recorrente remissão do falante ao ato da formulação linguística em si, ora comentando e avaliando o próprio dizer ou negociando a palavra certa com o interlocutor, ora explicitando o trabalho de busca da formulação adequada ou qualificando o sentido das escolhas feitas. Nesse processo, o falante, de certa forma, suspende o curso do conteúdo da conversa e se volta a algum aspecto relativo ao modo de dizer esse conteúdo. Em outras palavras, instala-se no desdobramento da enunciação um dizer sobre o dizer, uma enunciação sobre a enunciação, em suma, uma metaenunciação. Entre as diferentes manifestações metaenunciativas distingue-se uma por sua natureza destacadamente interativa. Nela o enunciador, explícita ou implicitamente, encena um diálogo com o seu interlocutor sobre a propriedade ou conveniência do que foi ou vai ser dito no curso da interação. Nesse sentido, o enunciador pode se desculpar ou pedir permissão para usar determinadas palavras ou expressões, tratar de determinados assuntos, fazer alusão a outros, ou ainda justificar certos procedimentos discursivos. Pode ele também chamar atenção do interlocutor sobre o que e como vai dizer, destacando, assim, a seu ponto de vista em relação ao de seu parceiro de interação. A análise das atividades metaenunciativas desse tipo, em razão de seu caráter explicitamente interacional, revela que elas se caracterizam, predominantemente, por uma formulação marcada por traços de atenuação, configurando-se, por isso, em atos de cortesia. O objetivo deste artigo é, justamente, o de identificar e descrever recursos linguísticos de atenuação inerentes a essas intervenções metaenunciativas e, dessa forma, dar evidência à relação de cortesia que elas estabelecem entre os participantes da interação.
O gênero tutorial e a terminologia das redes sociais
Authors: Santiago Márcio Sales , Krieger Maria da Graça , Araújo Júlio
Published: May 2022

Neste artigo, analisa-se a terminologia presente em tutoriais de redes sociais da internet. Por sua vez, entende-se o tutorial como um texto especializado, repleto de termos, cujo objetivo é instruir um indivíduo ou um conjunto de indivíduos que necessitam de determinadas orientações para operacionalizar uma ferramenta informatizada, como uma rede social. Em consequência, importa aos estudos terminológicos a identificação das características dos termos nesse gênero textual digital. Assim, é descrita e exemplificada uma terminologia das redes sociais. Os resultados da análise mostram que é possível se referir a duas especificidades terminológicas nos tutoriais, as quais contribuem para determinar o perfil terminológico do domínio temático abordado, especificamente sob o ponto de vista da denominação.
A adaptação de palavras do português para o papiamentu
Authors: Freitas Shirley , Bandeira Manuele , Araujo Gabriel Antunes de
Published: May 2022

Este estudo investiga a nativização/adaptação de palavras do português para o papiamentu, tendo dois objetivos: (i) discutir uma etimologia portuguesa para alguns empréstimos; (ii) e tratar dos processos fonológicos e morfológicos ocorridos nos processos de adaptação. A definição da língua lexificadora deste crioulo (português ou espanhol) permanece controversa, havendo defensores de pelo menos quatro hipóteses. O corpus foi constituído pelo trabalho de Maduro (1953), autor que defende uma base espanhola para o papiamentu. A análise dos dados mostrou que as reflexões etimológicas de Maduro apresentavam imperfeições, e algumas etimologias foram revistas, considerando-se tanto o português como o espanhol como étimos. No caso das palavras terminadas em -mentu, em sua maioria, foi estabelecido um étimo português, havendo ainda casos em que a palavra foi formada no próprio papiamentu, sendo o -mentu um sufixo. Assim sendo, este trabalhou mostra que a presença do português no papiamentu é maior do que aquela assumida por Maduro (1953). Ademais, de fato, a nativização se dá a partir dos padrões fonológicos da língua receptora.
Cartas do Coronel Francisco Gomes Vieira: notícias de um acervo familiar
Authors: Toledo Neto Sílvio de Almeida , Oliveira Monteiro Amanda Valéria
Published: May 2022

O objetivo deste trabalho é dar notícia da constituição de um valioso acervo de cartas pessoais, da família Gomes Vieira, recentemente doado ao Arquivo Histórico de Taubaté. A partir da transcrição de três cartas datadas da segunda metade do século XIX, descrevem-se algumas de suas características filológicas.
O modelo de “letramentos acadêmicos”: teoria e aplicações
Authors: Komesu Fabiana Cristina , Fischer Adriana
Published: May 2022

Embora o termo “letramentos acadêmicos” tenha sido originalmente desenvolvido visando ao estudo de letramentos em nível superior, o conceito também se aplica ao período da pré-escola ao ensino médio. Uma perspectiva dos letramentos acadêmicos concebe leitura e escrita como práticas sociais que variam segundo contexto, cultura e gênero (Barton; Hamilton, 1998; Street, 1984, 1985). As práticas de letramento de disciplinas acadêmicas podem ser entendidas como práticas sociais variadas associadas a diferentes comunidades. Além disso, uma perspectiva dos letramentos acadêmicos também leva em consideração letramentos não diretamente relacionados a temas e disciplinas, mas a discursos institucionais mais amplos e a gêneros. Do ponto de vista do estudante, um traço dominante das práticas de letramento acadêmico é a exigência de mudança de estilo de escrita e gênero segundo contexto. O objetivo é dispor de modo conjunto de práticas de letramento apropriadas a cada cenário e lidar com sentidos sociais e identidades que cada prática evoca.
À margem da luz do lampião: travestis, bonecas e bichas loucas no Lampião da Esquina (1978-1981)
Authors: Simionato Gabriel Donizetti Ferreira
Published: May 2022

Este artigo busca analisar as relações estabelecidas entre as comunidades transgêneras e o movimento homossexual brasileiro e a comunidade gay, por meio do periódico da imprensa alternativa Lampião da Esquina (1978-1981). Para tanto, analisou-se três cartas de leitores e uma reportagem que abarcavam o tema da transgeneridade. Os conceitos de gênero, conforme Butler (2019), Lauretis (2019) e Scott (2019), e de representação, conforme Chartier (1991; 2011), foram fundamentais para a análise. Também foram utilizados os textos de Cruz e Peixoto (2007) e de Luca (2008) quanto ao uso da imprensa como fonte histórica. Percebe-se a cis-heteronormatividade vigente na comunidade e no movimento gay do período, a manutenção de um discurso patologizante e estereotipado, assim como a marginalização e repulsão das comunidades transgêneras nesses coletivos (comunidade gay no periódico Lampião da Esquina).
Homoerotismo e masculinidades: abordagens sobre o HIV/Aids na revista Spartacus (1987-1990)
Authors: Pereira Victor Melo
Published: May 2022

A epidemia do HIV/Aids teve grandes efeitos na população homossexual, impactando o movimento de luta por direitos e gerando uma segunda onda de reivindicações. No que diz respeito à imprensa voltada a esse público, ocorreu ainda uma multiplicidade de veículos considerados como “homoeróticos”, os quais procuraram informar a respeito da doença de modo a não estigmatizar as relações sexuais entre homens. Neste contexto, foi publicada a revista Spartacus, que circulou entre 1987 e 1990 e publicou uma coluna chamada “O médico responde”, que tirava dúvidas dos leitores sobre questões de saúde e sexualidade. O objetivo deste artigo é discutir o modo como o periódico abordou esses temas em seus textos e sua relação com o contexto social da época, o qual foi marcado por uma estigmatização da homossexualidade, sobretudo masculina. Neste cenário, a grande mídia e o governo federal veicularam chamadas “alarmistas” a respeito da doença, sem muitos dados sobre prevenção e conscientização. Busca-se, portanto, compreender de que modo Spartacus se posicionou neste contexto, uma vez que tinha como público-alvo uma população diretamente afetada pela epidemia. Para esta pesquisa, parte-se de pressupostos da História da Imprensa, História das Relações de Gênero e Sexualidade e História do Tempo Presente
Sem memória, sem democracia: perspectivas sobre a ascensão fascista no Brasil neoliberal
Authors: Silveira Felipe Lazzari da
Published: May 2022

O presente artigo tem como escopo problematizar a ausência de memória social do passado autoritário e sua relação com o avanço do fascismo na sociedade brasileira no contexto contemporâneo. Tal esforço, consistente em um ensaio de caráter teórico e historiográfico, foi procedido mediante revisão de bibliografia sobre os temas pertinentes e os resultados da investigação estão estruturados em três tópicos, nos quais são analisados, respectivamente, o fascismo além de seu formato histórico, sua compatibilidade com neoliberalismo e o papel desempenhado pela ausência de memória do passado ditatorial no processo de intensificação das pulsões antidemocráticas.
O marxismo e a questão penal: entre o realismo de esquerda e os abolicionismos penais
Authors: Silva Gustavo Carneiro da
Published: May 2022

Com o objetivo de apontar alguns caminhos possíveis para a análise marxista da questão penal, o trabalho se debruça sobre as contribuições de duas vertentes comumente contrapostas: o realismo criminológico de esquerda, de autores como Jock Young e Roger Matthews, e os abolicionismos penais, de autores como Thomas Mathiesen e Angela Davis. Para tanto, realiza uma revisão bibliográfica com o fim de expor as principais teses de cada abordagem, relacionando-as às contribuições pertinentes elaboradas pela teoria social marxista. Posteriormente, busca delinear as contribuições que cada uma das perspectivas trouxe para o modo como a teoria marxista compreende os fenômenos envolvendo a punição e a questão penal. Do realismo criminológico de esquerda, destaca-se a contribuição para o destaque da importância que a ideologia possui na sustentação do sistema penal. Dos abolicionismos penais, são ressaltados a abordagem profundamente histórica do problema e o modo como deriva um programa político voltado para a atuação prática de suas análises. Por fim, o trabalho faz um breve apontamento sobre a ausência da crítica marxista.