bluuebunny/crossref_metadata_2025 huggingface dataset:
Fault Diagnosis Method for Imbalanced Data Based on Multi-Signal Fusion and Improved Deep Convolution Generative Adversarial Network
Authors: Deng Congying , Deng Zihao , Lu Sheng , He Mingge , Miao Jianguo , Peng Ying
Published: February 2023

The realization of accurate fault diagnosis is crucial to ensure the normal operation of machines. At present, an intelligent fault diagnosis method based on deep learning has been widely applied in mechanical areas due to its strong ability of feature extraction and accurate identification. However, it often depends on enough training samples. Generally, the model performance depends on sufficient training samples. However, the fault data are always insufficient in practical engineering as the mechanical equipment often works under normal conditions, resulting in imbalanced data. Deep learning-based models trained directly with the imbalanced data will greatly reduce the diagnosis accuracy. In this paper, a diagnosis method is proposed to address the imbalanced data problem and enhance the diagnosis accuracy. Firstly, signals from multiple sensors are processed by the wavelet transform to enhance data features, which are then squeezed and fused through pooling and splicing operations. Subsequently, improved adversarial networks are constructed to generate new samples for data augmentation. Finally, an improved residual network is constructed by introducing the convolutional block attention module for enhancing the diagnosis performance. The experiments containing two different types of bearing datasets are adopted to validate the effectiveness and superiority of the proposed method in single-class and multi-class data imbalance cases. The results show that the proposed method can generate high-quality synthetic samples and improve the diagnosis accuracy presenting great potential in imbalanced fault diagnosis.
Self-Monitoring Diabetes-Related Foot Ulcers with the MyFootCare App: A Mixed Methods Study
Authors: Ploderer Bernd , Clark Damien , Brown Ross , Harman Joel , Lazzarini Peter A. , Van Netten Jaap J.
Published: February 2023

People with diabetes-related foot ulcers (DFUs) need to perform self-care consistently over many months to promote healing and to mitigate risks of hospitalisation and amputation. However, during that time, improvement in their DFU can be hard to detect. Hence, there is a need for an accessible method to self-monitor DFUs at home. We developed a new mobile phone app, “MyFootCare”, to self-monitor DFU healing progression from photos of the foot. The aim of this study is to evaluate the engagement and perceived value of MyFootCare for people with a plantar DFU over 3 months’ duration. Data are collected through app log data and semi-structured interviews (weeks 0, 3, and 12) and analysed through descriptive statistics and thematic analysis. Ten out of 12 participants perceive MyFootCare as valuable to monitor progress and to reflect on events that affected self-care, and seven participants see it as potentially valuable to enhance consultations. Three app engagement patterns emerge: continuous, temporary, and failed engagement. These patterns highlight enablers for self-monitoring (such as having MyFootCare installed on the participant’s phone) and barriers (such as usability issues and lack of healing progress). We conclude that while many people with DFUs perceive app-based self-monitoring as valuable, actual engagement can be achieved for some but not for all people because of various facilitators and barriers. Further research should target improving usability, accuracy and sharing with healthcare professionals and test clinical outcomes when using the app.
Video Stream Recognition Using Bitstream Shape for Mobile Network QoE
Authors: Chmieliauskas Darius , Paulikas Šarūnas
Published: February 2023

Video streaming service delivery is a challenging task for mobile network operators. Knowing which services clients are using could help ensure a specific quality of service and manage the users’ experience. Additionally, mobile network operators could apply throttle, traffic prioritization, or differentiated pricing. However, due to the growth of encrypted Internet traffic, it has become difficult for network operators to recognize the type of service used by their clients. In this article, we propose and evaluate a method for recognizing video streams solely based on the shape of the bitstream on a cellular network communication channel. To classify bitstreams, we used a convolutional neural network that was trained on a dataset of download and upload bitstreams collected by the authors. We demonstrate that our proposed method achieves an accuracy of over 90% in recognizing video streams from real-world mobile network traffic data.
Landslide Susceptibility Evaluation of Machine Learning Based on Information Volume and Frequency Ratio: A Case Study of Weixin County, China
Authors: He Wancai , Chen Guoping , Zhao Junsan , Lin Yilin , Qin Bingui , Yao Wanlu , Cao Qing
Published: February 2023

A landslide is one of the most destructive natural disasters in the world. The accurate modeling and prediction of landslide hazards have been used as some of the vital tools for landslide disaster prevention and control. The purpose of this study was to explore the application of coupling models in landslide susceptibility evaluation. This paper used Weixin County as the research object. First, according to the landslide catalog database constructed, there were 345 landslides in the study area. Twelve environmental factors were selected, including terrain (elevation, slope, slope direction, plane curvature, and profile curvature), geological structure (stratigraphic lithology and distance from fault zone), meteorological hydrology (average annual rainfall and distance to rivers), and land cover (NDVI, land use, and distance to roads). Then, a single model (logistic regression, support vector machine, and random forest) and a coupled model (IV–LR, IV–SVM, IV–RF, FR–LR, FR–SVM, and FR–RF) based on information volume and frequency ratio were constructed, and the accuracy and reliability of the models were compared and analyzed. Finally, the influence of environmental factors on landslide susceptibility under the optimal model was discussed. The results showed that the prediction accuracy of the nine models ranged from 75.2% (LR model) to 94.9% (FR–RF model), and the coupling accuracy was generally higher than that of the single model. Therefore, the coupling model could improve the prediction accuracy of the model to a certain extent. The FR–RF coupling model had the highest accuracy. Under the optimal model FR–RF, distance from the road, NDVI, and land use were the three most important environmental factors, ac-counting for 20.15%, 13.37%, and 9.69%, respectively. Therefore, it was necessary for Weixin County to strengthen the monitoring of mountains near roads and areas with sparse vegetation to prevent landslides caused by human activities and rainfall.
A Novel Approach for Direction of Arrival Estimation in Co-Located MIMO Radars by Exploiting Extended Array Manifold Vectors
Authors: Akbar Sadiq , Sohail Muhammad , Zaman Fawad , Khan Muhammad Abdul Rehman , Ajavakom Nopdanai , Phanomchoeng Gridsada
Published: February 2023

Multiple-input multiple-output (MIMO) radars enable better estimation accuracy with improved resolution in contrast to traditional radar systems; thus, this field has attracted attention in recent years from researchers, funding agencies, and practitioners. The objective of this work is to estimate the direction of arrival of targets for co-located MIMO radars by proposing a novel approach called flower pollination. This approach is simple in concept, easy to implement and has the capability of solving complex optimization problems. The received data from the far field located targets are initially passed through the matched filter to enhance the signal-to-noise ratio, and then the fitness function is optimized by incorporating the concept of virtual or extended array manifold vectors of the system. The proposed approach outperforms other algorithms mentioned in the literature by utilizing statistical tools for fitness, root mean square error, cumulative distribution function, histograms, and box plots.
Automatic Code Review by Learning the Structure Information of Code Graph
Authors: Yin Ying , Zhao Yuhai , Sun Yiming , Chen Chen
Published: February 2023

At present, the explosive growth of software code volume and quantity makes the code review process very labor-intensive and time-consuming. An automated code review model can assist in improving the efficiency of the process. Tufano et al., designed two automated tasks to help improve the efficiency of code review based on the deep learning approach, from two different perspectives, namely, the developer submitting the code and the code reviewer. However, they only used code sequence information and did not explore the logical structure information with a richer meaning of the code. To improve the learning of code structure information, a program dependency graph serialization algorithm PDG2Seq algorithm is proposed, which converts the program dependency graph into a unique graph code sequence in a lossless manner, while retaining the program structure information and semantic information. We then designed an automated code review model based on the pre-trained model CodeBERT architecture, which strengthens the learning of code information by fusing program structure information and code sequence information, and then fine-tuned the model according to the code review activity scene to complete the automatic modification of the code. To verify the efficiency of the algorithm, the two tasks in the experiment were compared with the best Algorithm 1-encoder/2-encoder. The experimental results show that the model we proposed has a significant improvement under the BLEU, Lewinshtein distance and ROUGE-L metrics.
Optimization of the Outlet Shape of an Air Circulation System for Reduction of Indoor Temperature Difference
Authors: Park Jin-Young , Yoo Young-Jun , Kim Young-Choon
Published: February 2023

This study proposes an air circulation system that can forcibly circulate the lowest cold air to the top of indoor smart farms, and it has a width, length, and height of 6, 12, and 2.5 m, respectively, to reduce the effect of temperature differences between the upper and lower parts on the growth rate of plants in winter. This study also aimed to reduce the temperature deviation generated between the upper and lower parts of the target indoor space by optimizing the shape of the manufactured outlet of the air circulation system. A table of L9 orthogonal arrays, which is a design of experiment methodology, was used, and it presented three levels of the following design variables: blade angle, blade number, output height, and flow radius. Flow analysis was performed for the experiments on the nine models to minimize the high time and cost requirements. Based on the derived analysis results, an optimized prototype was manufactured by applying the Taguchi method, and experiments were conducted by installing 54 temperature points in an indoor space to identify the temperature difference between the upper and lower parts over time for the performance experiment. Under natural convection, the minimum temperature deviation was 2.2 °C and the temperature difference between the upper and lower parts did not decrease. For a model without an outlet shape, such as a vertical fan, the minimum temperature deviation was 0.8 °C and at least 530 s were required to reach a difference of less than 2 °C. When air was circulated in the air circulation system with the proposed outlet shape, the minimum temperature deviation was 0.6 °C and the time required to reach a difference of less than 2 °C was 440 s. Using the proposed air circulation system, cooling and heating costs are expected to be reduced in summer and winter because the arrival time and temperature difference between the upper and lower parts can be reduced using the outlet shape compared with the case without the outlet shape.
Design Principle and Proofing of a New Smart Textile Material That Acts as a Sensor for Immobility in Severe Bed-Confined Patients
Authors: Iliescu Bogdan Florin , Mancasi Vlad Niki , Ilie Ionut Dumitru , Mancasi Iulian , Costachescu Bogdan , Rotariu Daniel Ilie
Published: February 2023

The immobility of patients confined to continuous bed rest continues to raise a couple of very serious challenges for modern medicine. In particular, the overlooking of sudden onset immobility (as in acute stroke) and the delay in addressing the underlying conditions are of utmost importance for the patient and, in the long term, for the medical and social systems. This paper describes the design principles and concrete implementation of a new smart textile material that can form the substrate of intensive care bedding, that acts as a mobility/immobility sensor in itself. The textile sheet acts as a multi-point pressure-sensitive surface that sends continuous capacitance readings through a connector box to a computer running a dedicated software. The design of the capacitance circuit ensures enough individual points to provide an accurate description of the overlying shape and weight. We describe the textile composition and circuit design as well as the preliminary data collected during testing to demonstrate the validity of the complete solution. These results suggest that the smart textile sheet is a very sensitive pressure sensor and can provide continuous discriminatory information to allow for the very sensitive, real-time detection of immobility.
Fiber Residual Stress Effects on Modal Gain Equalization of Few-Mode Fiber Amplifier
Authors: Pei Li , Chang Yanbiao , Wang Jianshuai , Zheng Jingjing , Ning Tigang , Li Jing , Bai Bing , Shen Lei , Zhong Li
Published: February 2023

The modal gain equalization (MGE) of few-mode fiber amplifiers (FMFAs) ensures the stability of signal transmission. MGE mainly relies on the multi-step refractive index (RI) and doping profile of few-mode erbium-doped fibers (FM-EDFs). However, complex RI and doping profiles lead to uncontrollable residual stress variations in fiber fabrication. Variable residual stress apparently affects MGE due to its impacts on the RI. So, this paper focuses on the residual stress effects on MGE. The residual stress distributions of passive and active FMFs were measured using a self-constructed residual stress test configuration. As the erbium doping concentration increased, the residual stress of the fiber core decreased, and the residual stress of the active fibers was two orders of magnitude lower than that of the passive fiber. Compared with the passive FMF and the FM-EDFs, the residual stress of the fiber core completely transformed from tensile stress to compressive stress. This transformation led to an obvious smooth RI curve variation. The measurement values were analyzed with FMFA theory, and the results show that the differential modal gain of the FMFA increased from 0.96 to 1.67 dB as the residual stress decreased from 4.86 to 0.01 MPa.
An Online Hashing Algorithm for Image Retrieval Based on Optical-Sensor Network
Authors: Chen Xiao , Li Yanlong , Chen Chen
Published: February 2023

Online hashing is a valid storage and online retrieval scheme, which is meeting the rapid increase in data in the optical-sensor network and the real-time processing needs of users in the era of big data. Existing online-hashing algorithms rely on data tags excessively to construct the hash function, and ignore the mining of the structural features of the data itself, resulting in a serious loss of the image-streaming features and the reduction in retrieval accuracy. In this paper, an online hashing model that fuses global and local dual semantics is proposed. First, to preserve the local features of the streaming data, an anchor hash model, which is based on the idea of manifold learning, is constructed. Second, a global similarity matrix, which is used to constrain hash codes is built by the balanced similarity between the newly arrived data and previous data, which makes hash codes retain global data features as much as possible. Then, under a unified framework, an online hash model that integrates global and local dual semantics is learned, and an effective discrete binary-optimization solution is proposed. A large number of experiments on three datasets, including CIFAR10, MNIST and Places205, show that our proposed algorithm improves the efficiency of image retrieval effectively, compared with several existing advanced online-hashing algorithms.
Improving BLE-Based Passive Human Sensing with Deep Learning
Authors: Iannizzotto Giancarlo , Lo Bello Lucia , Nucita Andrea
Published: February 2023

Passive Human Sensing (PHS) is an approach to collecting data on human presence, motion or activities that does not require the sensed human to carry devices or participate actively in the sensing process. In the literature, PHS is generally performed by exploiting the Channel State Information variations of dedicated WiFi, affected by human bodies obstructing the WiFi signal propagation path. However, the adoption of WiFi for PHS has some drawbacks, related to power consumption, large-scale deployment costs and interference with other networks in nearby areas. Bluetooth technology and, in particular, its low-energy version Bluetooth Low Energy (BLE), represents a valid candidate solution to the drawbacks of WiFi, thanks to its Adaptive Frequency Hopping (AFH) mechanism. This work proposes the application of a Deep Convolutional Neural Network (DNN) to improve the analysis and classification of the BLE signal deformations for PHS using commercial standard BLE devices. The proposed approach was applied to reliably detect the presence of human occupants in a large and articulated room with only a few transmitters and receivers and in conditions where the occupants do not directly occlude the Line of Sight between transmitters and receivers. This paper shows that the proposed approach significantly outperforms the most accurate technique found in the literature when applied to the same experimental data.
Modeling of Rapid Pam Systems Based on Electrothermal Micromirror for High-Resolution Facial Angiography
Authors: Xia Yuanlin , Wang Yujie , Liang Tianxiang , Peng Zhen , He Liang , Wang Zhuqing
Published: February 2023

In this paper, a portable photoacoustic microscopy (PAM) system is proposed based on a large stroke electrothermal micromirror to achieve high resolution and fast imaging. The crucial micromirror in the system realizes a precise and efficient 2-axis control. Two different designs of electrothermal actuators with “O” and “Z” shape are evenly located around the four directions of mirror plate. With a symmetrical structure, the actuator realized single direction drive only. The finite element modelling of both two proposed micromirror has realized a large displacement over 550 μm and the scan angle over ±30.43° at 0–10 V DC excitation. In addition, the steady-state and transient-state response show a high linearity and quick response respectively, which can contribute to a fast and stable imaging. Using the Linescan model, the system achieves an effective imaging area of 1 mm × 3 mm in 14 s and 1 mm × 4 mm in 12 s for the “O” and “Z” types, respectively. The proposed PAM systems have advantages in image resolution and control accuracy, indicating a significant potential in the field of facial angiography.
State-Space Model for Arrival Time Simulations and Methodology for Offline Blade Tip-Timing Software Characterization
Authors: Tocci Tommaso , Capponi Lorenzo , Rossi Gianluca , Marsili Roberto , Marrazzo Marco
Published: February 2023

Blade tip-timing is an extensively used technique for measuring blade vibrations in turbine and compressor stages; it is one of the preferred techniques used for characterizing their dynamic behaviors using non-contact probes. Typically, arrival time signals are acquired and processed by a dedicated measurement system. Performing a sensitivity analysis on the data processing parameters is essential for the proper design of tip-timing test campaigns. This study proposes a mathematical model for generating synthetic tip-timing signals, descriptive of specific test conditions. The generated signals were used as the controlled input for a thorough characterization of post-processing software for tip-timing analysis. This work represents the first step in quantifying the uncertainty introduced by tip-timing analysis software into user measurements. The proposed methodology can also offer essential information for further sensitivity studies on parameters that influence the accuracy of data analysis during testing.
Pred-SF: A Precipitation Prediction Model Based on Deep Neural Networks
Authors: Tang Rongnian , Zhang Pu , Wu Jingjin , Chen Youlong , Dong Lingyu , Tang Song , Li Chuang
Published: February 2023

How to predict precipitation accurately and efficiently is the key and difficult problem in the field of weather forecasting. At present, we can obtain accurate meteorological data through many high-precision weather sensors and use them to forecast precipitation. However, the common numerical weather forecasting methods and radar echo extrapolation methods have insurmountable defects. Based on some common characteristics of meteorological data, this paper proposes a Pred-SF model for precipitation prediction in target areas. The model focuses on the combination of multiple meteorological modal data to carry out self-cyclic prediction and a step-by-step prediction structure. The model divides the precipitation prediction into two steps. In the first step, the spatial encoding structure and PredRNN-V2 network are used to construct the autoregressive spatio-temporal prediction network for the multi-modal data, and the preliminary predicted value of the multi-modal data is generated frame by frame. In the second step, the spatial information fusion network is used to further extract and fuse the spatial characteristics of the preliminary predicted value and, finally, output the predicted precipitation value of the target region. In this paper, ERA5 multi-meteorological mode data and GPM precipitation measurement data are used for testing to predict the continuous precipitation of a specific area for 4 h. The experimental results show that Pred-SF has strong precipitation prediction ability. Some comparative experiments were also set up for comparison to demonstrate the advantages of the combined prediction method of multi-modal data and the stepwise prediction method of Pred-SF.
Development and Analysis of a CNN- and Transfer-Learning-Based Classification Model for Automated Dairy Cow Feeding Behavior Recognition from Accelerometer Data
Authors: Bloch Victor , Frondelius Lilli , Arcidiacono Claudia , Mancino Massimo , Pastell Matti
Published: February 2023

Due to technological developments, wearable sensors for monitoring the behavior of farm animals have become cheaper, have a longer lifespan and are more accessible for small farms and researchers. In addition, advancements in deep machine learning methods provide new opportunities for behavior recognition. However, the combination of the new electronics and algorithms are rarely used in PLF, and their possibilities and limitations are not well-studied. In this study, a CNN-based model for the feeding behavior classification of dairy cows was trained, and the training process was analyzed considering a training dataset and the use of transfer learning. Commercial acceleration measuring tags, which were connected by BLE, were fitted to cow collars in a research barn. Based on a dataset including 33.7 cow × days (21 cows recorded during 1–3 days) of labeled data and an additional free-access dataset with similar acceleration data, a classifier with F1 = 93.9% was developed. The optimal classification window size was 90 s. In addition, the influence of the training dataset size on the classifier accuracy was analyzed for different neural networks using the transfer learning technique. While the size of the training dataset was being increased, the rate of the accuracy improvement decreased. Beginning from a specific point, the use of additional training data can be impractical. A relatively high accuracy was achieved with few training data when the classifier was trained using randomly initialized model weights, and a higher accuracy was achieved when transfer learning was used. These findings can be used for the estimation of the necessary dataset size for training neural network classifiers intended for other environments and conditions.
Remediation of Sb-Contaminated Soil by Low Molecular Weight Organic Acids Washing: Efficiencies and Mechanisms
Authors: Li Sicheng , Pan Weibin , Tong Lizhi , Hu Yuanyuan , Zou Yulin , Huang Xiaojia
Published: February 2023

Low molecular weight organic acids (LMWOAs) are promising agents in the remediation of heavy metal contaminated soil with strong complexing ability and less environmental impact. However, the application of LMWOAs for washing the Sb-contaminated soil still faces great challenges, such as the selection of suitable washing agents, optimal washing parameters, and the unclear Sb removal mechanism. In this study, five suitable LMWOAs were screened from ten common washing agents and their optimum washing parameters were determined. The results showed that oxalic acid (OA) and HEDP were the top two outstanding agents, and the removal efficiencies of Sb were 68.79% and 49.73%, respectively, under optimal parameters (OA at 0.5 mol/L, HEDP at 0.2 mol/L, washing for 480 min, and the liquid-to-solid ratio of 15). The soil was analyzed for chemical speciation, morphology, functional groups, and mineralogy before and after washing. The results indicated that Fe/Al minerals in the soil are the main reason for the adsorption of Sb, and the possible mechanisms of Sb removal by LMWOAs included the dissolution of minerals, complexation reaction, and ligand exchange. Our findings highlight the potential application of LMWOAs as efficient washing agents to remove Sb from contaminated soils.
Architecture, Engineering and Building Science: The Contemporary Relevance of Vitruvius’s De Architectura
Authors: Bianco Lino
Published: February 2023

Conferences worldwide focus on a range of disciplines relating to the construction of the built environment. They tend to emphasize either the art or the science of building, the former focusing on architectural theory and design while the latter targets a range of topics from civil and/or building engineering to building physics. Vitruvius’s De Architectura Libri Decem is a seminal treatise more than two millennia old which addresses these themes in a holistic manner. This text remains valid today for students and professionals engaged in architecture and building engineering. Translated as Ten Books on Architecture, it not only presents an overall view of the disciplines of town planning, architecture and civil engineering, along with the qualifications required to practice them, but also addresses building materials, civil-engineering structures and the science influencing buildings. Although grounded in the practice and technology of Ancient Rome, the principles put forward in this treatise are still valid nowadays for effective, sustainable architectural-engineering design based on rigorous education and good knowledge of building materials and construction. Vitruvius’s definition of architecture—the one still customarily used—is an inclusive philosophical statement on the essence of building for humanity to house humanity. It recalls the symbiotic relation between architecture and building engineering that is often forgotten in the contemporary emphasis on specialization.
The Source and Distribution of Tetracycline Antibiotics in China: A Review
Authors: Chang Donghao , Mao Yizhi , Qiu Wei , Wu Yunshu , Cai Baiyan
Published: February 2023

In recent years, antibiotics have been listed as a new class of environmental pollutants. Tetracycline antibiotics (TCs) used in human medical treatment, animal husbandry and agricultural production are the most widely used antibiotics. Due to their wide range of activities and low cost, their annual consumption is increasing. TCs cannot be completely metabolized by humans and animals. They can be abused or overused, causing the continuous accumulation of TCs in the ecological environment and potential negative effects on non-target organisms. These TCs may spread into the food chain and pose a serious threat to human health and the ecology. Based on the Chinese environment, the residues of TCs in feces, sewage, sludge, soil and water were comprehensively summarized, as well as the potential transmission capacity of air. This paper collected the concentrations of TCs in different media in the Chinese environment, contributing to the collection of a TC pollutant database in China, and facilitating the monitoring and treatment of pollutants in the future.
Pancreas–Liver–Adipose Axis: Target of Environmental Cadmium Exposure Linked to Metabolic Diseases
Authors: Moroni-González Diana , Sarmiento-Ortega Victor Enrique , Diaz Alfonso , Brambila Eduardo , Treviño Samuel
Published: February 2023

Cadmium has been well recognized as a critical toxic agent in acute and chronic poisoning cases in occupational and nonoccupational settings and environmental exposure situations. Cadmium is released into the environment after natural and anthropogenic activities, particularly in contaminated and industrial areas, causing food pollution. In the body, cadmium has no biological activity, but it accumulates primarily in the liver and kidney, which are considered the main targets of its toxicity, through oxidative stress and inflammation. However, in the last few years, this metal has been linked to metabolic diseases. The pancreas–liver–adipose axis is largely affected by cadmium accumulation. Therefore, this review aims to collect bibliographic information that establishes the basis for understanding the molecular and cellular mechanisms linked to cadmium with carbohydrate, lipids, and endocrine impairments that contribute to developing insulin resistance, metabolic syndrome, prediabetes, and diabetes.
Treatment of Animal Tungiasis: What’s New?
Authors: dos Santos Katharine Costa , Brandão Guedes Paula Elisa , Teixeira Jamille Bispo de Carvalho , Harvey Tatiani Vitor , Carlos Renata Santiago Alberto
Published: February 2023

In tropical and subtropical countries, particularly in disadvantaged communities, tungiasis is a severe public health problem, which is often neglected by the authorities. The sand fleas Tunga penetrans, predominant in endemic areas, and Tunga trimamillata, whose cases in humans are less frequent, are the cause of this zoonosis. Domestic animals are potential reservoirs and disseminators of tungiasis, so controlling their infection would significantly advance the prevention of human cases. This literature review compiles the most recent studies and innovations in treating animal tungiasis. Studies of approaches to the treatment of animal tungiasis, as well as disease control and prevention, are described. Isoxazolines are highlighted as promising drugs to treat animal tungiasis, with high efficacy and pharmacological protection. The positive impacts of this discovery on public health are also discussed, since dogs are an essential risk factor for human tungiasis.
Developing Marsha and Marian’s Neighbors: A Shared Housing Intervention to Address Homelessness among LGBTQ+ and Pregnant/Parenting Youth
Authors: Gattis Maurice N. , Wagaman M. Alex , Kemmerer Aaron
Published: February 2023

Background: The aim of this paper is to describe the development of a shared housing model intervention that was designed to serve youth experiencing homelessness who are LGBTQ+ and/or pregnant/parenting. The intervention is built around two guiding philosophies: housing first and restorative justice. Methods: We engaged in a year-long planning process with an advisory group from 1 July 2021 through 30 June 2022. The advisory group is a partnership between Virginia Commonwealth University School of Social Work, seven young people with lived experience expertise, and members from four partner organizations, including local organizations serving LGBTQ+ youth. Results: Marsha and Marian’s Neighbors is designed to provide safe, comfortable housing for 12 months for 20 young people and their children if they have any. Participants will live in apartments where rent and utilities are paid for by the program for all participants. The program also provides money for arrears that may prevent the participants from being able to secure a lease, mental health appointments, legal consultations, and doula services provided by partners recruited by the planning team. Services are provided by staff and partners that are LGBTQ+ affirming and pregnant and parenting affirming. Conclusion: One of the most important lessons that we learned is the power of developing shared values in a novel intervention for LGBTQ+ youth. One focused intervention that supports both pregnant and parenting youth who identify as LGBTQ+ remains necessary. Paradoxically, LGBTQ+ people, particularly bisexual, lesbian, and queer cisgender women, are at an equal or greater risk of unplanned pregnancy. Both groups are vulnerable to housing instability independently, and those who live at the intersection of being LGBTQ+ and pregnant/parenting face an elevated risk for housing instability.
Eticidad e intersubjetividad en las biografías educativas de un grupo de profesores
Authors: Sadio-Ramos Fernando José
Published: February 2023

El texto presentado a continuación contiene la fundamentación y la estructura de la Tesis Doctoral titulada Determinación del rol de la intersubjetividad y de la eticidad en las biografías educativas de un grupo de profesores/ Determinação do papel da intersubjectividade e da eticidade nas biografías educativas de um grupo de profesores (Ramos, 2014) leída en la Universidad de Granada, a finales del año pasado. Se complementa esa fundamentación con la presentación de una de las biografías educativas reconstituidas en la investigación, que tomamos como ejemplo del proceso de reflexión sobre los temas de la eticidad y de la intersubjetividad conducido por una de nuestras colaboradoras.
Multipolaridade, metaconstitucionalismo e a perspectiva kantiana
Authors: Furtado Érika Rigotti
Published: February 2023

O projeto de paz perpétua de Immanuel Kant, uma vez fundado na racionalidade, apresenta o Direito como ferramenta primordial à obtenção da pacificação mundial. Na atualidade, as ideias de multipolaridade e metaconstitucionalismo trazem implícita a proposta da paz kantiana, máxime quanto à universalização de valores centrados no resguardo da dignidade humana. Neste sentido, o presente trabalho discute o alcance das questões humanitárias no âmbito da dinâmica de poder presente na disputa entre a governança global liberal e a governança global cosmopolita, traçando uma abordagem a partir da perspectiva kantiana da paz perpétua. Para tanto, o estudo considera que quanto maior a proximidade entre os valores ético-normativos observados nas constituições estatais, maiores as oportunidades para a expansão da proteção da dignidade humana, por meio do processo de interação normativa inerente ao metaconstitucionalismo.
Aplicação da robótica educacional como estratégia para formar jovens autônomos e capazes de atuar ativamente na sociedade
Authors: Matos Debora Ferreira , Vieira Andressa Viana , De Assis Paulo Érik Silva , Vieira Rebeca Soares , Nascimento Sandriel Lima , Lima Vinicius de Sousa , Dos Santos Jéssica Almeida
Published: February 2023

Considerando que as metodologias aplicadas nas redes de ensino regular têm foco em transmitir conteúdos, ao invés de contextualizar e tornar o aprendizado significativo para o aluno, o presente projeto de extensão surge com o objetivo de aproximar o processo de aprendizagem visando à formação integral dos participantes, através da aplicação da Robótica Educacional, na instituição do município de Açailândia-MA. A escolha da escola para implementação do projeto de extensão foi feita baseada em análises dos resultados de índices como IDEB e ENEM do ano de 2019, sendo selecionada a escola Mary Dalva Castro. A metodologia aplicada proporcionando a superação de barreiras epistemológicas, fixação dos conceitos físicos, além de serem encorajados a buscarem os conceitos e a importância da ciência em suas vidas.
Autonomia, participação e gestão financeira dos recursos do PDE-Escola nas escolas da rede estadual do Maranhão
Authors: Lima Maria Eliana Alves
Published: February 2023

O objetivo é relacionar a transferência dos recursos federais para as escolas públicas no Maranhão e a participação da comunidade na gestão financeira. Argumenta-se sobre os condicionantes políticos imbricados nos processos de gestão democrática das escolas públicas. A perspectiva metodológica qualitativa analisa a participação da comunidade escolar na aplicação dos recursos do Programa PDE Escola entre os anos de 2011 a 2013 em quinze escolas da rede estadual. Verificou-se que os princípios da gestão financeira não são compreendidos pelos membros da escola, que aplica os recursos conforme prioridade da gestão.
As reformas educativas no Brasil dos anos 1990: repercussão histórica para o modelo de gestão escolar democrática
Authors: Lima Maria Eliana Alves
Published: February 2023

A escola pública no Brasil partir dos anos de 1990 sofreu profundas influências nos padrões de organização e gestão, ocasionadas por intervenções estatais resultantes dos desdobramentos assumidos pelas relações capitalistas, consubstanciadas pelo neoliberalismo. A emergência de novos modelos de gestão escolar demandou das políticas públicas novas relações entre o Estado e as políticas educacionais, revelando prioridades e compromissos na elaboração e implementação de programas e projetos educativos. A descentralização como princípio da reforma educacional encontra-se legitimada na Lei de Diretrizes e Bases da Educação Nacional – LDBEN n.º 9394/96 que orienta para o redimensionamento do sistema de ensino, através de novos referenciais de gerenciamento, com o objetivo de aumentar a produtividade e democratizar a educação formal. A orientação básica para a gestão educacional, a partir da LDB de 1996, é a ampliação da autonomia da escola nas dimensões pedagógica, administrativa e financeira, fortalecendo sua gestão.
Fatores de risco modificáveis para o Acidente Vascular Encefálico Isquêmico: revisão integrativa da literatura
Authors: Miranda Janaína Almeida Galvão , Matos Rodrigo Almeida , Rosa Vanessa Tsunemitsu Fernandes , De Matos Luciana Wietzikoski Otoni , Leitão Luciana Pereira Colares
Published: February 2023

A detecção precoce e controle dos fatores de riscos para o Acidente Vascular Encefálico (AVE) isquêmico é fundamental, pois reduzem sua incidência e sua recidiva, visto que a taxa de mortalidade gira em torno de 14% a 26%. Sendo de suma importância que tais fatores sejam identificados, a fim de serem abordados na atenção primária à saúde, visando a prevenção e promoção desse agravo. Objetivo:  Analisar os fatores de risco modificáveis que aumentam a probabilidade do desenvolvimento de um AVE isquêmico. Metodologia:  Trata-se de um estudo de revisão integrativa da literatura, nas bases de dados LILACS, MEDLINE, SciELO, nos últimos 5 anos em inglês, espanhol e português. Resultados: pode-se evidenciar que 100% dos estudos identificados nessa RIL foram produzidos e publicados em cenário internacional, em língua inglesa, sendo 90% advindos da base de dados PubMed. O país que mais publicou sobre a temática foi a China, com 50% das publicações. Ressalta-se que 30% das pesquisas foram decorrentes do estudo CSPPT. O ano com maior número de publicações foi o de 2019 (40%). A revista Journal of stroke and cerebrovascular diseases: the official journal of National Stroke Association foi a detentora de maior número de publicações (30%). Conclusão: Conclui-se que o presente estudo alcançou o seu objetivo, sendo identificado que os fatores mais prevalentes foram a hipertensão, hiperglicemia, IMC elevado, FA, hipercolesterolemia, maus hábitos alimentares, tabagismo e sedentarismo. Além disso, espera-se incentivar a elaboração de mais estudos sobre a temática no país, visto que a amostra se constitui de estudos internacionais.
Avaliação da viabilidade da exploração sustentável do Shale gas na região sudeste do Brasil, com base em aspectos geológicos
Authors: Capistrano Gabriel Godinho , Tassinari Colombo Celso Gaeta , Cañas Stephanie San Martín , Rocha Haline de Vasconcellos
Published: February 2023

O gás de folhelho é um dos recursos não convencionais em destaque nas últimas décadas. A Bacia do Paraná (porção sul do Brasil), principalmente a Formação Irati, é um prospecto bastante interessante para gás de folhelho. Na área estabelecida para este estudo, composta pelos estados de São Paulo, Mato Grosso do Sul e Paraná foram pesquisados 143 trabalhos científicos, que compuseram uma revisão bibliográfica com a finalidade de obter informações acerca de seus principais parâmetros geoquímicos, onde foi possível determinar um bom potencial para a exploração dos folhelhos. Com o método analógico foi calculado um valor estimado de reservas de 225 TCF. Existem alguns problemas com o processo de exploração desse recurso no Brasil, como a sua proximidade com o Sistema Aquífero Guarani (SAG em inglês) e o uso de faturamento hidráulico. Uma solução interessante visando uma melhor aceitação do público geral/ambientalista seria de substituir a água no processo de faturamento por dióxido de carbono (CO2) e a combinação da produção de gás natural não convencional com a acumulação geológica de CO2, uma das mais eficientes formas de aprisionar carbono da atmosfera e reduzir as emissões de gás carbônico.
Analisis Kelas Massa Batuan Terhadap kestabilan Lereng Bendungan Lolak Menggunakan Metode Rock Mass Rating
Authors: Muarif Fahmy Idris , Maryati Sri , Hutagalung Ronal
Published: February 2023

The process of displacement or movement of slope stability constituent materials followed by the sedimentation process of the deposited material is a landslide event. The negative impact of the landslide if it occurs in residential areas, can cause material and infrastructure losses, or economic losses in the affected area if the landslide products can cover the road access. The purpose of this study was to determine the level of rock mass and its effect on slope stability, and to determine the rock mass quality of the study area. The research area is located in Lolak Dam. Based on the results of the analysis carried out, the conclusion is that the observations starting from station 1, station 2, station 3, and station 4 show moderate-good rock strength. The condition of the discontinuity shows continuity of less than 1 meter, the aperture of discontinuity are open to a bit wide, with varying roughness, namely coarse, and slightly coarse, with the infilling material calcite veins. The level of weathering starts from weathered to very weathered. Groundwater conditions are dominated by discontinuities that have a dry level. Based on the discontinuity characteristic, station 1 has good rock mass class, station 2 has medium rock mass class, station 3 has medium rock mass class, and station 4 has good rock mass class. this value can be used as a reference value for the next stage of decision making regarding the strengthening of the slopes in the study area.
Interpretasi Lapisan Bawah Permukaan Sebagai Perencanaan Tempat Penyimpanan Sampah Di Desa Talumelito, Kabupaten Gorontalo
Authors: K Badaun Nur Azizah , Zainuri Ahmad , Akase Noviar , Aris Ayub Pratama
Published: February 2023

The Talumelito waste storage area is located in Talumelito Village, Telaga Biru District, Gorontalo Regency which accommodates waste from various human activities. Organic and inorganic waste will become a breeding ground for diseases that are very dangerous for society and the environment. The purpose of this study was to determine the subsurface layer as an interpretation of the planning for the construction of a waste storage area and determine whether it is feasible or not. The resistivity geoelectric method of the Schlumberger configuration is one of the geophysical methods that is easy, inexpensive and efficient and does not damage the environment. The geoelectric method is a geophysical method used to identify the properties and physical conditions of the subsurface based on the resistivity values of the rock. This method utilizes variations in the resistivity values of the subsurface rocks to detect geological structures or subsurface rock formations. Based on an analysis of resistivity and geological electrical properties, the location of the planning for the construction of a waste storage area is at VES 2, VES 3, and VES 5 points. Where from the interpretation results the three VES points have bedrock rock layers with granite rock types. Meanwhile, at VES 1 and VES 4, there is a layer of sandstone under the top soil layer. VES 2, VES 3 and VES 5 points are suitable for waste storage because there are layers of waterproof rock. Whereas at VES 1 and VES 4 points it is not suitable for waste storage because the sandstone layer is a layer that has good permeability, so if there is liquid waste from garbage, the waste will contaminate groundwater.
İnfeksiyöz Deve (Camelus dromedarius) Keratokonjonktivitis Olgularında Moraxella bovoculi'nin İdentifikasyonu ve Antimikrobiyal Duyarlılıklarının Belirlenmesi
Authors: ÖZAVCI Volkan , SEFEROĞLU Yiğit
Published: February 2023

İnfeksiyöz keratokonjonktivit (İKC) sığır ve koyunlarda ekonomik kayıplara neden olan bir göz hastalığıdır. Hastalık etkenleri genel olarak Moraxella bovis ve M. ovis olarak bilinirken 2007'de IKC'den de sorumlu türler arasına M. bovoculi’de tanımlanmıştır. Bu çalışmanın amacı konjonktival hiperemi, oküler ağrı, fotofobi ve lakrimasyon semptomları gösteren develerde Moraxella spp. varlığının saptanması ve antimikrobiyal duyarlılık profillerindeki farklılıkları belirlemektir. Aydın yöresinde 30 adet deve’ye (Camelus dromedarius) ait sağ ve sol gözlerden bilateral (n= 60 örnek) konjonktival svap örnekleri nazikçe toplandı. Moraxella spp. (6/60; %10) suşları sürüntü örneklerinden fenotipik ve genotipik yöntemlerle izole edildi. Biyokimyasal olarak ilk değerlendirme nitrat redüksiyon ve jelatinaz sonuç negatif olması yönünden M. ovis ve M. bovoculi (M. bovis negatif) ile uyumluluk gösterdi. Ayrıca, 357F ve 1492R evrensel primerleri kullanarak 16S rRNA PCR gerçekleştirildi ve nükleotit sekansı yapıldı. Sanger sekanslama ile izolatların Moraxella bovoculi (Moraxella bovoculi suşu 3709'a %98-99 benzerlik Access. No: GU181221.1) olduğu doğrulandı. İzolatlarda eritromisin (%100), amoksisilin-klavulanik asit, penisilin, siprofloksasin ve tetrasiklin (%67) gibi yaygın antibiyotiklere direnç, sefotaksim, gentamisin ve imipenem’e (%100) duyarlılık tespit edildi. M. bovoculi suşu develerin göz infeksiyonlarında ülkemizde daha önce rapor edilmemiştir. Bu nedenle çalışmamız develerin göz infeksiyonlarında M. bovoculi'nin varlığını doğrulamaktadır ve develerin göz infeksiyonlarından izole edilebileceğine vurgu yapmaktadır.
Tolwaka ornata, nuevo género y especie de Salpingidae (Coleoptera) de Chile
Authors: Solervicens Jaime
Published: February 2023

Se propone Tolwaka gen. nov. para acoger a T. ornata sp. nov. Se describen ambos taxones y se proporcionan imágenes del adulto y de diversas estructuras diferenciales de la especie. Se discuten las afinidades y diferencias de Tolwaka con los géneros Oncosalpingus Blair, 1919 y Chileosalpingus Solervicens, 2022.
Update distribution of the mud-dauber wasp Sceliphron fistularium (Dahlbom, 1843) (Hymenoptera: Sphecidae) in South America with new records
Authors: Ceccolini Filippo
Published: February 2023

New records of the mud-dauber wasp Sceliphron fistularium (Dahlbom, 1843) for South America are reported. First record for Upper Demerara-Berbice (Guyana), Miranda (Venezuela), Vaupés (Colombia), Azuay, Orellana, Manabí, and Napo (Ecuador), Ayacucho and Cusco (Peru), Alagoas and Distrito Federal (Brazil), Amambay and Central (Paraguay), Canelones and Cerro Largo (Uruguay), and Santa Fe (Argentina) are given. The detailed distribution for each country of the continent is shown.