bluuebunny/crossref_metadata_2025 huggingface dataset:
Dam Safety Evaluation Method after Extreme Load Condition Based on Health Monitoring and Deep Learning
Authors: Song Jintao , Liu Yunhe , Yang Jie
Published: May 2023

The safety operation of dams after extreme load is an important frontier research topic in the field of dam engineering. The dam health monitoring provides a reliable data basis for a safety evaluation after extreme loads. This study proposes a novel data-driven fusion model for a dam safety evaluation after extreme load based on monitoring data derived by sensors. First, the relationship between dam environmental quantity and effect quantity is deeply excavated based on bidirectional long short-term memory (BiLSTM) network, which is a deeply improved LSTM model. Aiming at the parameter optimization problem of BiLSTM model, sparrow search algorithm (SSA), which is an advanced optimization algorithm, is integrated. Second, conducting the constructed SSA-BiLSTM model to estimate the change law of dam effect quantity after the extreme load. Finally, the Mann–Whitney U-test theory is introduced to establish the evaluation criterion of the dam safety state. Project case shows that the multiple quantitative prediction accuracy evaluation indicators of the proposed method are significantly superior to the comparison method, with mean absolute percentage error (MAPE) and mean absolute error (MAE) values decreasing by 30.5% and 27.8%, respectively, on average. The proposed model can accurately diagnose the dam safety state after the extreme load compared with on-site inspection results of the engineering department, which provides a new method for dam safety evaluation.
Peak Tibiofemoral Contact Forces Estimated Using IMU-Based Approaches Are Not Significantly Different from Motion Capture-Based Estimations in Patients with Knee Osteoarthritis
Authors: Di Raimondo Giacomo , Willems Miel , Killen Bryce Adrian , Havashinezhadian Sara , Turcot Katia , Vanwanseele Benedicte , Jonkers Ilse
Published: May 2023

Altered tibiofemoral contact forces represent a risk factor for osteoarthritis onset and progression, making optimization of the knee force distribution a target of treatment strategies. Musculoskeletal model-based simulations are a state-of-the-art method to estimate joint contact forces, but they typically require laboratory-based input and skilled operators. To overcome these limitations, ambulatory methods, relying on inertial measurement units, have been proposed to estimated ground reaction forces and, consequently, knee contact forces out-of-the-lab. This study proposes the use of a full inertial-capture-based musculoskeletal modelling workflow with an underlying probabilistic principal component analysis model trained on 1787 gait cycles in patients with knee osteoarthritis. As validation, five patients with knee osteoarthritis were instrumented with 17 inertial measurement units and 76 opto-reflective markers. Participants performed multiple overground walking trials while motion and inertial capture methods were synchronously recorded. Moderate to strong correlations were found for the inertial capture-based knee contact forces compared to motion capture with root mean square error between 0.15 and 0.40 of body weight. The results show that our workflow can inform and potentially assist clinical practitioners to monitor knee joint loading in physical therapy sessions and eventually assess long-term therapeutic effects in a clinical context.
Atomic Force Microscopy Probing and Analysis of Polyimide Supramolecular Systems for Sensor Devices
Authors: Stoica Iuliana , Barzic Andreea Irina , Ursu Cristian , Stoian George , Hitruc Elena Gabriela , Sava Ion
Published: May 2023

A series of polyimide supramolecular systems containing different amounts of azochromophore were tested as flexible supports that can be used in the fabrication of certain devices, such as sensors for monitoring the temperature changes, by coating them with conductive metals. That is why it is required to have good interfacial compatibility between the flexible substrate and the inorganic layer. The interface of the sensor elements must be designed in such a way as to improve the sensitivity, accuracy, and response time of the device. Laser irradiation is one of the commonly employed techniques used for surface adaptation by patterning polyimides to increase contact and enhance device reliability and signal transmission. In this context, this work highlights unreported aspects arising from the azo-polyimide morphology, local nanomechanical properties and wettability, which are impacting the compatibility with silver. The texture parameters indicate an improvement of the modulations’ quality arising after laser irradiation through the phase mask, increasing the bearing capacity, fluid retention, and surface anisotropy when the amount of the azochromophore increases. The force curve spectroscopy and wettability studies indicated that the modification of the polymer morphology and surface chemistry lead to a better interfacial interaction with the metal lines when the azo component and the polyamidic acid are in equimolar quantities.
Speaker Counting Based on a Novel Hive Shaped Nested Microphone Array by WPT and 2D Adaptive SRP Algorithms in Near-Field Scenarios
Authors: Dehghan Firoozabadi Ali , Adasme Pablo , Zabala-Blanco David , Palacios Játiva Pablo , Azurdia-Meza Cesar
Published: May 2023

Speech processing algorithms, especially sound source localization (SSL), speech enhancement, and speaker tracking are considered to be the main fields in this application. Most speech processing algorithms require knowing the number of speakers for real implementation. In this article, a novel method for estimating the number of speakers is proposed based on the hive shaped nested microphone array (HNMA) by wavelet packet transform (WPT) and 2D sub-band adaptive steered response power (SB-2DASRP) with phase transform (PHAT) and maximum likelihood (ML) filters, and, finally, the agglomerative classification and elbow criteria for obtaining the number of speakers in near-field scenarios. The proposed HNMA is presented for aliasing and imaging elimination and preparing the proper signals for the speaker counting method. In the following, the Blackman–Tukey spectral estimation method is selected for detecting the proper frequency components of the recorded signal. The WPT is considered for smart sub-band processing by focusing on the frequency bins of the speech signal. In addition, the SRP method is implemented in 2D format and adaptively by ML and PHAT filters on the sub-band signals. The SB-2DASRP peak positions are extracted on various time frames based on the standard deviation (SD) criteria, and the final number of speakers is estimated by unsupervised agglomerative clustering and elbow criteria. The proposed HNMA-SB-2DASRP method is compared with the frequency-domain magnitude squared coherence (FD-MSC), i-vector probabilistic linear discriminant analysis (i-vector PLDA), ambisonics features of the correlational recurrent neural network (AF-CRNN), and speaker counting by density-based classification and clustering decision (SC-DCCD) algorithms on noisy and reverberant environments, which represents the superiority of the proposed method for real implementation.
Effect of Etifoxine on Locomotor Activity and Passive Learning in Rats with Diazepam-Induced Cognitive Deficit
Authors: Kokova Vesela , Apostolova Elisaveta
Published: May 2023

Etifoxine is an anxiolytic drug with a dual mechanism of action. In contrast to conventional benzodiazepine anxiolytics, which induce cognitive dysfunction and myorelaxation, no memory impairment nor a decrease in motor activity is observed with etifoxine. This study aims to evaluate the effects of etifoxine on locomotor activity and passive learning in rats with diazepam-induced memory deficit. Male Wistar rats were treated intraperitoneally for 7 days with: (1) saline; (2) diazepam 2.5 mg/kg bw or (3) diazepam 2.5 mg/kg bw and etifoxine in a dose of 50 mg/kg bw. Activity cage test was used for evaluation of locomotor activity, and step-through and step-down tests were performed to study the passive learning. Etifoxine increased the number of horizontal movements on the 7th and 14th days of the experiment. The drug exhibits anti-amnesic effect in a model of diazepam-induced anterograde amnesia by enhancing long-term memory in passive learning tests. The data obtained suggest that etifoxine can reduce the benzodiazepine-induced cognitive deficit. Moreover, such a combination can alleviate the negative influence of benzodiazepines on locomotor activity. However, additional studies are necessary to translate these results into clinical practice.
Comparative Study of Conventional, Microwave-Assisted and Supercritical Fluid Extraction of Bioactive Compounds from Microalgae: The Case of Scenedesmus obliquus
Authors: Georgiopoulou Ioulia , Louli Vasiliki , Magoulas Kostis
Published: May 2023

The recovery of bioactive products with green processes is a critical topic for the research and industry fields. In this work, the application of solid–liquid (SLE), microwave-assisted extraction (MAE) with aq. ethanol 90% v/v and supercritical fluid extraction (SFE) with CO2 for the recovery of biocomponents from Scenedesmus obliquus is studied. The effects examined were temperature (30–60 °C), time (6–24 h), and solvent-to-biomass ratio (20–90 mLsolv/gbiom) for SLE, temperature (40–60 °C), time (5–25 min), solvent-to-biomass ratio (20–90 mLsolv/gbiom), and microwave power (300–800 W) for MAE, and temperature (40–60 °C), pressure (110–250 bar), solvent flow rate (20–40 gsolv/min), and cosolvent presence (0, 10% w/w ethanol) for SFE in relation to the extract’s yield, phenolic, chlorophyll, carotenoid content, and antioxidant activity. The optimum extraction conditions determined were 30 °C, 24 h, and 90 mLsolv/gbiom for SLE, 60 °C, 5 min, 90 mLsolv/gbiom, and 300 W for MAE, and 60 °C, 250 bar, and 40 gsolv/min for SFE. Additionally, a kinetic SFE study was conducted and the obtained results were satisfactorily correlated using Sovová’s model. The comparison between the methods proved MAE’s efficiency in all terms compared to SLE. Moreover, SFE was accompanied with the lowest yield and chlorophyll content, yet led to an increased carotenoid content and improved antioxidant activity. Finally, the cosolvent addition significantly improved SFE’s yield and led to the most superior extract.
Simultaneous Quantification of Some Fluoroquinolone Residues in Real Wastewater Effluents Using CZE
Authors: Abdel-Gawad Sherif A. , Altharawi Ali
Published: May 2023

Since active pharmaceutical ingredients (APIs) are directly related to human health, monitoring and quantifying them in the environment is a crucial and challenging issue. Using capillary-zone electrophoresis (CZE), four frequently used fluoroquinolones (FQs), ciprofloxacin, sparfloxacin, moxifloxacin, and gatifloxacin, were efficiently isolated and measured in pharmaceutical industrial wastewater. Solid-phase extraction (SPE) was developed and used as an efficient sample pretreatment procedure. The capillary electrophoretic procedure’s various parameters were tuned to produce the optimal separation pattern for the drugs under consideration. All of the drugs under study were quantified in a concentration range of 0.5 to 50 µg/mL. After full assay validation in compliance with ICH-Q2B criteria, real wastewater samples were subjected to effective SPE, and the proposed assay was successfully used to determine the examined FQs in real wastewater samples.
Sex Differentiation from Human Scent Chemical Analysis
Authors: Pojmanová Petra , Ladislavová Nikola , Škeříková Veronika , Kukal Jaromír , Urban Štěpán
Published: May 2023

Human scent traces are often the only pieces of evidence providing information about individuals that were present at a crime scene. In this study, the possibility of sex differentiation using detailed chemical analyses of human scent samples for forensic purposes is discussed. The human scent samples were analyzed through the use of headspace-gas chromatography/mass spectrometry (HS-GC/MS). The results of these chemical analyses were evaluated using several data processing approaches (Linear Support Vector Machine, Quadratic Discriminant Analysis, and Ridge Regression), which were applied to distinguish between sexes from the human scent samples obtained from the palms of six volunteers for twelve weeks. This study indicates that sex differentiation based on the chemical analysis of human scent samples using HS-GC/MS is possible. The best results were obtained using the Ridge Regression with thresholding providing accuracy and a critical sensitivity of the sex differentiation of better than 91%.
Generalizability of Machine Learning to Categorize Various Mental Illness Using Social Media Activity Patterns
Authors: Ang Chee Siang , Venkatachala Ranjith
Published: May 2023

Mental illness has recently become a global health issue, causing significant suffering in people’s lives and having a negative impact on productivity. In this study, we analyzed the generalization capacity of machine learning to classify various mental illnesses across multiple social media platforms (Twitter and Reddit). Language samples were gathered from Reddit and Twitter postings in discussion forums devoted to various forms of mental illness (anxiety, autism, schizophrenia, depression, bipolar disorder, and BPD). Following this process, information from 606,208 posts (Reddit) created by a total of 248,537 people and from 23,102,773 tweets was used for the analysis. We initially trained and tested machine learning models (CNN and Word2vec) using labeled Twitter datasets, and then we utilized the dataset from Reddit to assess the effectiveness of our trained models and vice versa. According to the experimental findings, the suggested method successfully classified mental illness in social media texts even when training datasets did not include keywords or when unrelated datasets were utilized for testing.
Characteristics of Carbon Emission Transfer under Carbon Neutrality and Carbon Peaking Background and the Impact of Environmental Policies and Regulations on It
Authors: Yang Xiaowan , Guo Xiaoyu , Wang Yanan
Published: May 2023

In recent years, with the increase in global carbon dioxide content, the negative impact of the greenhouse effect has become increasingly significant. Moreover, countries have gradually recognized the importance and urgency of carbon emission (CE) reduction. Under the dual-carbon background, CE transfer has received increasing attention. The study of its characteristics can help carry out CE reduction. Therefore, the study analyzes the characteristics of CE transfer, hoping to reduce carbon dioxide emissions. In addition, environmental policies and regulations have a significant impact on CE transfer. CE transfer under different environmental policies and regulations varies greatly. The relationship between environmental policies and regulations and CE transfer needs to be specifically analyzed. Therefore, a theoretical model is built based on environmental policies and regulations and CE transfer. This model is used to analyze the impact of different environmental policies and regulations on CE transfer. The measurement is tested via numerical simulation. The results show that good environmental policies and regulations can effectively reduce global CE. This study also compares and analyzes the relationship between differences in environmental policies and regulations and carbon leakage (CL). The results show that positive environmental policies and regulations can reduce CL, thus achieving the goal of carbon emission reduction. The above results show that in the context of dual carbon, appropriate environmental policies and regulations can reasonably regulate CE transfer and CL level. This can reduce the global emissions of carbon dioxide and the negative impact of the greenhouse effect on the world.
Models and Methods for Quantifying the Environmental, Economic, and Social Benefits and Challenges of Green Infrastructure: A Critical Review
Authors: Jezzini Yasser , Assaf Ghiwa , Assaad Rayan H.
Published: May 2023

With growing urbanization and increasing climate change-related concerns, green infrastructures (GIs) are recognized as promising solutions for mitigating various challenges and promoting sustainable development. Despite the important role of GIs, a comprehensive synthesis of the quantification of their full range of benefits and challenges is lacking in the current literature. To address this gap, a systematic literature review was conducted on the quantifiable environmental, economic, and social benefits and challenges of GIs. This paper followed the Preferred Reporting Items for Systematic Review (PRISMA) methodology, where 75 relevant articles were reviewed to present the various models and methods that could be used to quantify and assess the impacts of different GI types. The study further investigated existing knowledge trends and patterns, identified research gaps, and suggested future research directions. The results revealed that while existing research studies offer great insights into the impacts of GIs, a more holistic approach is necessary to balance the benefits and challenges of GIs. The findings also offered a comprehensive understanding of a wide range of environmental, economic, and social considerations of both natural and engineered GIs. Ultimately, the performed literature review serves as a comprehensive guide for researchers and practitioners and could be used in estimating and evaluating the benefits and challenges of GI plans and programs as well as in making informed decisions about GI projects.
Deep Learning Optimisation of Static Malware Detection with Grid Search and Covering Arrays
Authors: ALGorain Fahad T. , Alnaeem Abdulrahman S.
Published: May 2023

This paper investigates the impact of several hyperparameters on static malware detection using deep learning, including the number of epochs, batch size, number of layers and neurons, optimisation method, dropout rate, type of activation function, and learning rate. We employed the cAgen tool and grid search optimisation from the scikit-learn Python library to identify the best hyperparameters for our Keras deep learning model. Our experiments reveal that cAgen is more efficient than grid search in finding the optimal parameters, and we find that the selection of hyperparameter values has a significant impact on the model’s accuracy. Specifically, our approach leads to significant improvements in the neural network model’s accuracy for static malware detection on the Ember dataset (from 81.2% to 95.7%) and the Kaggle dataset (from 94% to 98.6%). These results demonstrate the effectiveness of our proposed approach, and have important implications for the field of static malware detection.
Structural renovation of the Secondary standard of the electric power unit for the industrial frequency range
Authors: Shevkun Serhii , Dobroliubova Maryna , Statsenko Oleksii
Published: May 2023

The article reveals ways for structural renovation of the composition of the Secondary standard of the electrical power unit for the industrial frequency range with the aim of restoring the technical resource of its constituent parts, improving metrological characteristics in terms of increasing output power, as well as increasing productivity and reducing the cost of work due to their automation.

Based on the results of the metrological characteristics’ analysis of electrical energy and power measuring equipment modern nomenclature and the existing standard base, it is proposed to make a structural renovation of the standard by including additional equipment to its composition, namely: the precision three-phase standard electricity meter compatible with the high-precision three-phase power source. The structural scheme of the renovation standard has been developed.

The renovation of the standard allows turning the standard into a single hardware and software complex that provides calibration and testing of wide nomenclature of electric power and electric energy meters in the full range of values in high-performance automated mode.
Healthcare utilisation and mortality in people with osteoarthritis in the UK: findings from a national primary care database
Authors: Swain Subhashisa , Coupland Carol , Sarmanova Aliya , Kuo Chang Fu , Mallen Christian , Doherty Michael , Zhang Weiya
Published: May 2023

Background

The burden of osteoarthritis (OA) in UK primary care has not been investigated thoroughly.

Aim

To estimate healthcare use and mortality in people with OA (overall and joint specific).

Design and setting

A matched cohort study of adults with an incident diagnosis of OA in primary care were selected for the study using UK national Clinical Practice Research Datalink (CPRD) electronic records.

Method

Healthcare utilisation was measured as the annual average number of primary care consultations and admissions to hospital after the index date for any cause and all-cause mortality data in 221 807 people with OA and an equal number of controls (with no OA diagnosis) who were matched to the case patients by age (standard deviation 2 years), sex, practice, and year of registration. The associations between OA and healthcare utilisation and all-cause mortality were estimated using multinomial logistic regression and Cox regression, respectively, adjusting for covariates.

Results

The mean age of the study population was 61 years and 58% were female. In the OA group, the median number of primary care consultations per year after the index date was 10.91 compared with 9.43 in the non-OA control group (P= 0.001) OA was associated with an increased risk of GP consultation and admission to hospital. The adjusted hazard ratio for all-cause mortality was 1.89 (95% confidence interval [CI] = 1.85 to 1.93) for any OA, 2.09 (95% CI = 2.01 to 2.19) for knee OA, 2.08 (95% CI = 1.95 to 2.21) for hip OA, and 1.80 (95% CI = 1.58 to 2.06) for wrist/hand OA, compared with the respective non-OA control group.

Conclusion

People with OA had increased rates of GP consultations, admissions to hospital, and all-cause mortality that varied across joint sites.
Progression of stroke risk in patients aged <65 years diagnosed with atrial fibrillation: a cohort study in general practice
Authors: Mendonça Silvia C , Edwards Duncan A , Lund Jenny , Saunders Catherine L , Mant Jonathan
Published: May 2023

Background

As a result of new technologies, atrial fibrillation (AF) is more likely to be diagnosed in people aged <65 years.

Aim

To investigate the risk of someone diagnosed with AF aged <65 years developing an indication for anticoagulation before they reach 65 years.

Design and setting

Population-based cohort study of patients from English practices using the Clinical Practice Research Datalink, a primary care database of electronic medical records.

Method

The study included patients aged <65 years newly diagnosed with AF. The CHA2DS2-VASc score was derived at time of diagnosis based on patients’ medical records. Patients not eligible for anticoagulation were followed up until they became eligible or turned 65 years old. The primary outcome of interest was development of a risk factor for stroke in AF.

Results

Among 18 178 patients aged <65 years diagnosed with AF, 9188 (50.5%) were eligible for anticoagulation at the time of diagnosis. Among the 8990 patients not eligible for anticoagulation, 1688 (18.8%) developed a risk factor during follow-up before reaching 65 years of age or leaving the cohort for other reasons, at a rate of 6.1 per 100 patient-years. Hypertension and heart failure were the most common risk factors to occur, with rates of 2.65 (95% CI = 2.47 to 2.84) and 1.58 (95% CI = 1.45 to 1.72) per 100 patient-years, respectively. The rate of new diabetes was 0.95 (95% CI = 0.85 to 1.06) per 100 patient-years.

Conclusion

People aged <65 years with AF are at higher risk of developing hypertension, heart failure, and diabetes than the general population, so may warrant regular review to identify new occurrence of such risk factors.
Management of asthma in primary care in the changing context of the COVID-19 pandemic: a qualitative longitudinal study with patients
Authors: Santillo Marta , Tonkin-Crine Sarah , Wang Kay , Butler Christopher C , Wanat Marta
Published: May 2023

Background

The COVID-19 pandemic dramatically affected asthma monitoring in primary care, but exploration of patients’ views and their experiences of managing their asthma and seeking help from primary care during the pandemic has been limited.

Aim

To investigate patients’ experiences of asthma management in the community during the COVID-19 pandemic.

Design and setting

A qualitative longitudinal study using semi-structured interviews with patients from four GP practices across diverse regions including Thames Valley, Greater Manchester, Yorkshire, and North West Coast.

Method

Interviews were undertaken with patients with asthma, who were usually managed in primary care. The interviews were audiorecorded, transcribed, and analysed using inductive temporal thematic analysis and a trajectory approach.

Results

Forty-six interviews were conducted with 18 patients over an 8-month period that covered contrasting stages of the COVID-19 pandemic. Patients felt less vulnerable as the pandemic subsided, but the process of making sense of risk was dynamic and influenced by multiple factors. Patients relied on self-management strategies, but felt that routine asthma reviews should still have been conducted during the pandemic and highlighted that they had limited opportunities to discuss their asthma with health professionals. Patients with well-controlled symptoms felt that remote reviews were largely satisfactory, but still thought face-to-face reviews were necessary for certain aspects, such as physical examination and patient-led discussions of sensitive or broader issues associated with asthma, including mental health.

Conclusion

The dynamic nature of patients’ perception of risk throughout the pandemic highlighted the need for greater clarity regarding personal risk. Having an opportunity to discuss their asthma is important to patients, even when access to face-to-face consultations in primary care is more restricted than usual.
Implementation and impact of a social prescribing intervention: an ethnographic exploration
Authors: Pollard Tessa , Gibson Kate , Griffith Bethan , Jeffries Jayne , Moffatt Suzanne
Published: May 2023

Background

Social prescribing involves referral of patients from primary care to link workers, who work with them to access appropriate local voluntary and community sector services.

Aim

To explore how a social prescribing intervention was delivered by link workers and the experiences of those referred to the intervention.

Design and setting

The study used ethnographic methods to conduct a process evaluation of a social prescribing intervention delivered to support those living with long-term conditions in an economically deprived urban area of the North of England.

Method

Participant observation, shadowing, interviews, and focus groups were used to examine the experiences and practices of 20 link workers and 19 clients over a period of 19 months.

Results

Social prescribing provided significant help for some people living with long-term health conditions. However, link workers experienced challenges in embedding social prescribing in an established primary care and voluntary sector landscape. The organisations providing social prescribing drew on broader social discourses emphasising personal responsibility for health, which encouraged a drift towards an approach that emphasised empowerment for lifestyle change more than intensive support. Pressures to complete assessments, required for funding, also encouraged a drift to this lighter-touch approach. A focus on individual responsibility was helpful for some clients but had limited capacity to improve the circumstances or health of those living in the most disadvantaged circumstances.

Conclusion

Careful consideration of how social prescribing is implemented within primary care is required if it is to provide the support needed by those living in disadvantaged circumstances.
Desarrollo de la conciencia ambiental desde la perspectiva docente
Authors: Rubina Ticlla Maria Elena , Alva Rodriguez Carmen Laura , Díaz Torres Betzabeth , Benavente Ayquipa Rosa María
Published: May 2023

A través del uso de la tecnología, la escolarización se aceleró como resultado a la pandemia del COVID-19. El objetivo del estudio fue interpretar el desarrollo de la conciencia ambiental desde la mirada docente. El estudio se construyó bajo el enfoque cualitativo con diseño hermenéutico a nivel interpretativo. Se utilizó una guía de entrevistas semiestructurada, que se aplicó a seis docentes que cumplían con los requisitos previos para el estudio. Los hallazgos incluyeron proporcionar a la comunidad educativa información para contribuir al desarrollo de la conciencia ambiental, tener un conocimiento completo sobre la conciencia ambiental y utilizar técnicas para fomentar un sentido de valor y amor por el planeta tierra. A modo de cierre, es necesario fomentar la conciencia ambiental ya que es un proceso que requiere la comprensión y el dominio de una variedad de ideas, así como de componentes estratégicos, buen comportamiento y responsabilidad ambiental.
Competencias digitales y gestión directiva en la profesionalidad docente
Authors: Huapaya Pevez De Tejada Nanci Alicia , Vera Rojas Haydeé Liliana , Castillo Olsson Sara Edith , Llerena Delgado Lilian Magdalena
Published: May 2023

A raíz del COVID-19, las Competencias Digitales (CD) y la Gestión Directiva (GD) han adquirido una gran relevancia en el ámbito educativo; por tal motivo, el objetivo fue determinar la influencia de las CD y la GD en el Desempeño Docente (DD). La metodología fue cuantitativa, de diseño causal correlacional, de corte transaccional y con una muestra de 101 educadores. La aplicación de la encuesta permitió la recolección de datos que, al procesarse estadísticamente, arrojaron un valor de significancia de 0,008 < 0,05 y un coeficiente de Nagelkerke de 17,8%, lo que permitió concluir que, las CD y la GD influyen positiva y significativamente en el DD; así como en todas sus dimensiones (preparación para el aprendizaje, enseñanza para el aprendizaje, participación en la gestión de la escuela articulada a la comunidad y el desarrollo de la profesionalidad y la identidad docente.
TIC y aprendizaje de negocios internacionales
Authors: Panduro Ramírez Jeidy Gisell , Alanya Beltrán Joel Elvys , Vargas Tumaya Jady Luz , Valderrama Zapata Carlos Alberto
Published: May 2023

Los estudiantes universitarios presentan dificultades para aprender temas relacionados con los Negocios Internacionales (NI). Por eso, es importante apoyar el empleo de las TIC en mejora del aprendizaje significativo. El objetivo fue determinar el nivel de relación entre la utilidad de las TIC y la adquisición de aprendizajes en estudiantes de NI en tiempos de virtualidad. El estudio fue cuantitativo de corte transversal y metodología hipotética deductiva, la técnica fue la encuesta y los instrumentos utilizados fueron dos cuestionarios validados por expertos. La población estuvo comprendida por estudiantes del cuarto ciclo de una institución educativa superior. Los resultados determinaron que sí existe una correlación directa, significativa y alta. Las conclusiones determinaron que las TIC son importantes en la construcción de aprendizajes significativos, éstos a su vez, aunados a recursos digitales acorde a las necesidades e intereses del estudiantado, fortalecen una sólida formación profesional y empleabilidad en el futuro.
Evgeni Pachukanis e a caracterização do fascismo
Authors: Alvares de Farias João Guilherme
Published: May 2023

O objetivo deste artigo consiste em recuperar das reflexões de Evgeni Pachukanis (1891-1937) os componentes básicos caracterizadores do fascismo, empregando a esses componentes certa sistematicidade até certo ponto ausente na exposição do texto pachukaniano. Também abordaremos aquilo que nos parece ser um limite relativo presente em sua reflexão. Em seguida, pretendemos colocar suas posições em diálogo com algumas das clássicas contribuições que integram a tradição marxista, tais como aquelas elaboradas por Clara Zetkin, Palmiro Togliatti e Nicos Poulantzas. Inspirados pelos últimos textos de conjuntura do cientista político Armando Boito Jr. (2019; 2020; 2021), acreditamos que essa recuperação permite extrair do texto pachukaniano os principais elementos caracterizadores do fascismo, principalmente, no que diz respeito à formulação de um conceito teórico geral e sintético.
Bastidores e repercussões de La Distinction de Pierre Bourdieu
Authors: Pulici Carolina
Published: May 2023

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Disfagia na fase aguda do AVC isquêmico em pacientes com e sem trombólise
Authors: Coradi Guarnieri Paola , Biorchi da Silva Haliesca , Mattos Mezzalira Ronan , Savoldi Angélica
Published: May 2023

Introdução. O Acidente Vascular Cerebral (AVC) é uma condição que pode resultar em prejuízos neurológicos e levar à incapacidade funcional. A disfagia é uma alteração na biomecânica da deglutição e frequentemente pode estar presente em indivíduos acometidos por AVC. A trombólise endovenosa é o tratamento mais indicado e eficaz quando administrado no momento certo, restabelecendo o fluxo sanguíneo na área afetada. Objetivo. Comparar a incidência e o grau de severidade da disfagia e a necessidade de via alternativa de alimentação em pacientes trombolisados e não trombolisados acometidos por AVC isquêmico. Método. Estudo retrospectivo, quantitativo, comparativo, de análise de 331 prontuários de pacientes em fase aguda de AVCi, onde 98 realizaram tratamento trombolítico (G1) e 233 não realizaram o tratamento (G2). Os dados coletados em prontuário eletrônico foram: idade, sexo, realização ou não da trombólise, motivo da não trombólise, grau de disfagia, nível de dieta e AVC prévio. Foram realizadas análises descritivas e comparativas através do teste Quiquadrado de Pearson. Resultados. A incidência de disfagia nos dois grupos foi proporcional (G1=48% e G2=54,5%), entretanto, destacou-se a severidade da disfagia no G2 (48,8% disfagia severa) e a necessidade de via alternativa de alimentação (82,2%) em relação ao G1. Conclusão. Os indivíduos sem trombólise apresentam maior tendência a ocorrência de disfagia na fase aguda do AVCi, bem como pior grau de severidade em relação aos pacientes que realizaram a terapia trombolítica.
Thermo-energetic simulation in openmodelica and energyplus: Test case from standard VDI 2078
Authors: Schramm Marcelo , Rodrigues Leticia Jenisch , Braatz Diandra Garcia
Published: May 2023

In this work, the test case 1 of german standard VDI 2078 is used to compare the softwares OpenModelica and EnergyPlus. The mentioned standard provides calculation methods of thermal load and temperature and test cases for validation of thermal zones’ models. This case’s behavior was evaluated in both softwares, keeping the reference values provided by the standard. Pearson’s correlation coefficient calculated between the values obtained by OpenModelica and EnergyPlus for zone air temperature, operative temperature and thermal load for the thermal zone type M are, respectively, 0,98 (very strong correlation), 0,87 (strong correlation) and 0,99 (very strong correlation). Among the reasons for deviations in results from both programs are the calculation method of thermal resistances and capacitances and of radiative coefficient, as well as the treatment of zone’s internal mass.
Conforto ambiental, cidades e ergonomia: uma análise nas ruas do bairro Butantã
Authors: Isaac Solimar Mendes , Ferreira Lucas Rafael , Viana Kárita Ressiguier Chagas , Morita Gabriela Katie Silva , Silva Marcus Vinicius Rodrigues
Published: May 2023

Este estudo teve a finalidade de elucidar a importância do conforto térmico, conforto acústico e da ergonomia defronte à qualidade de vida e mobilidade nas ruas e avenidas da cidade de São Paulo. Como estudo de caso, foram escolhidas 03 tipologias de vias com características distintas, porém localizadas no mesmo bairro e nas mesmas imediações, com distâncias de no máximo 500 metros entre si. As vias escolhidas foram: Rua Coronel Palimércio de Rezende, Avenida Vital Brasil e Avenida Caxingui, todas localizadas no bairro Butantã, na cidade de São Paulo. Por meio de abordagens práticas, foram coletados dados das áreas escolhidas relacionados à ergonomia, conforto térmico e acústico, tais como: temperatura do ambiente externo, umidade do ar, pressão sonora, velocidade do vento, amplitude térmica das superfícies, aspectos da calçada, estacionamento na via, presença de vegetação, de mobiliário urbano, de sinalização viária, a diversidade de uso do solo e contagem de pedestres e veículos. As análises dos dados coletados foram organizadas em forma de tabelas e gráficos, possibilitando uma análise comparativa dos resultados obtidos entre as tipologias das vias. Após o diagnótsico, foi possível aferir que em uma cidade complexa e diversa como São Paulo, existem tipos de vias com diferentes morfologias urbanas e distintas condições de ergonomia, conforto térmico e acústico em um mesmo bairro, e tais variações intervêm diretamente na caminhabilidade e na percepção de conforto do usuário, de forma que há uma interferência palpável em seu modo de vivenciar e utilizar o espaço público.
Anestesia em canino submetido a laparotomia exploratória para retirada de gossipiboma abdominal
Authors: Da Silva Luis Fernando , De Souza Patrícia Rocha , Castillo Raquel Martina Rodrigues , Trein Thomas Alexander , Gorczak Rochelle
Published: May 2023

A anestesia parcialmente intravenosa (PIVA), é a associação de anestesia inalatória com administração de fármacos por meio de infusão contínua. Suas vantagens estão associadas à analgesia somática e a redução na depressão respiratória. Este artigo tem como objetivo retratar a utilização da PIVA no procedimento de laparatomia exploratória para retirada de gossipiboma em um canino. Foi atendido uma canina, fêmea, SRD e 26kg, três anos. Ao ultrassom abdominal foi visualizado área hiperecogenica de 10 cm, circular, em região hipogástrica, peristaltismo reduzido e líquido livre. O animal foi encaminhado para a laparatomia emergencial. Recebeu medicação pré-anestésica, seguido de indução anestésica e sendo então intubado, mantendo o mesmo no isofluorano, ao efeito em volatilização baixa. Associado a infusão continua de cetamina (10 µg/kg/min) e cloridrato de remifentanil (5 µg/kg/h) intravenosos. No trans-operatório não observou-se nenhuma alteração significativa considerando sinais vitais, estabilidade cirúrgica e sedação. No pós operatório imediato apresentou algia e foi necessário mantê-la em infusão contínua de cetamina por 12 horas, o paciente ficou internado no primeiro dia pós-operatório recebendo analgesia com opioides, antibioticoterapia e fluidoterapia. Sendo assim, para o animal em questão, o protocolo anestésico balanceado juntamente com a modalidade PIVA, teve efeito satisfatório, observou-se estabilidade na cirurgia, nos sinais vitais e no trans-operatório.
La visualización en geometría actividades heurísticas con las figuras
Authors: Retamal Ismenia Guzmán
Published: May 2023

La geometría es un dominio que exige la articulación cognitiva de dos registros de representación, la visualización de formas para representar el espacio y el lenguaje para enunciar propiedades y deducir nuevas. La manera de ver las figuras depende de la manera en que ella se pone en juego, hay una manera de ver icónica y otra muy diferente que es la manera no icónica. La visualización no icónica implica deconstrucción de las formas visualmente ya conocidas. Se distinguen la deconstrucción de formas, la deconstrucción dimensional de figuras y la deconstrucción heurística (puzles). La deconstrucción dimensional es el proceso cognitivo central de la manera de ver en Geometría.
Predicting Food Safety Violations via Social Media to Improve Public Health Surveillance
Authors: Lee Carmen Kar Hang
Published: May 2023

Foodborne illness outbreaks originating in food service establishments (FSEs) are a serious public health concern. There are multiple ways that FSEs can contribute to the propagation of foodborne illnesses. However, not all these risks can be detected by health authorities during official inspections for two reasons. First, health authorities have limited resources, meaning not every FSE can be inspected as often and expediently as necessary. Second, because the food safety and hygiene standards of FSEs are dynamic, the inspection results might represent a snapshot that fails to resemble the current FSE situation. Consequently, it would be helpful to have an early warning system that can allow health authorities to predict the risk levels of FSEs and proactively intervene by demanding that high-risk FSEs take appropriate countermeasures. Considering that customers who feel sick after visiting an FSE may not report their experience to health authorities but instead disclose this information by posting online reviews on social media platforms, this study leverages social media data to predict food safety violations by FSEs. The empirical data for this study derive from two sources: the FSE inspection results from the Department of Health and Mental Hygiene in New York City, which labeled each FSE according to whether it violated food safety regulations, and textual reviews posted by FSE customers on Yelp. Machine learning algorithms were employed to extract textual features from the reviews and construct predictive models. Our results demonstrate that customer reviews posted on social media platforms are valuable for predicting FSE food safety violations. Health authorities can leverage social media data to construct predictive models and deploy them to optimize resource allocation and prioritize interventions to prevent foodborne illness outbreaks originating in FSEs, improving public health. FSE managers can also deploy the models to improve their hygiene standards in response to alerts raised. By taking appropriate countermeasures earlier, they can reduce their risk of financial loss due to negative inspection results.
Studying the Influence of Toxicity and Emotion Features for Stress Detection on Social Media
Authors: Alghamdi Zeyad , Kumarage Tharindu , Karami Mansooreh , Alatawi Faisal , Mosallanezhad Ahmadreza , Liu Huan
Published: May 2023

It is crucial to detect and manage stress as early as possible before it becomes a severe mental and physical health problem. Some authors even introduce stress as a “silent killer” to emphasize the significance of early stress management. Traumatic global events such as COVID-19 have amplified stress throughout online communities and it is quite common to see that social media users often vent about their problems or situations online. The ability to detect a person's stress from their posts on social media platforms like Reddit or Twitter in a timely manner can help early stress management and consequently counters mental health conditions. In order to detect stress from social media posts, we must obtain the characteristics that signal a user's stress. Which motivates us to study how salient features influence stress detection. On social media, text-based methods of communication predominantly overtake verbal forms, which makes these platforms a convenient rich medium with an extensive amount of text content to analyze a user's thoughts and emotions. We present a novel approach that helps improve stress detection on social media textual content with sentiment, emotion, and toxicity features. We design our framework based on multiple Transformer-based state-of-the-art sentiment, emotion, and toxicity analysis tools and models for feature extraction and discuss the stress detection tasks’ interpretability via inspecting multiple dimensions. For the evaluation, we use publicly available and high-quality datasets where the social media posts are real, carefully selected and labeled. Our experiments show the influence of the proposed new feature dimensions on stress detection by comparing the state-of-the-art baselines and suggesting future directions in stress detection on social media. Furthermore, our extensive feature correlation analysis highlights different aspects, such as 1) Positive and Negative sentiment, 2) Joy, Sadness, and Fear emotions, and 3) Obscene and Insult toxicity as governing factors in improving stress detection performance.
#VoyYVuelvo: Performances of Chilean identity and cultural memory on Instagram after Nicanor Parra's death
Authors: Guzmán María Victoria
Published: May 2023

This paper examines an analysis carried out of the mediations and remediations of Nicanor Parra’s image and poetry online, focusing on how digital methods can be used for qualitative analysis, their relevance for current research, as well as some ethical considerations. Nicanor Parra was a revolutionary Chilean poet, a national icon whose death in 2018 represented a significant memory site where contemporary understandings of Chilean identity can be studied. Through digital qualitative methods, I traced the use of the hashtag #nicanorparra after his death. The data was analysed using discourse analysis, both textual and visual, to properly weigh the mix of images and captions that Instagram posts offer and interpret how these ‘media of memory’ articulate discourses around Chilean identity and memory today. The posts constructed a figure of Parra akin to a modern prophet, whose message of “anti-ness” called on users to act on issues such as economic inequality and the impact of industrial development on the country's environment. Through Parra's poetry, digitally expressed through vernacular creativity, a collective mnemonic imagination sketches expectations for Chile, which are particularly crucial after the massive protests demanding profound political and economic change of 2019.
Maximising Social Media Platforms to Enhance Sexuality Education in Rural Schools
Authors: Adekola Ayobami Precious
Published: May 2023

Sexuality education is central to the South African government's strategy to promote adolescents' sexual and reproductive health, reduce student pregnancy, and prevent sexually transmitted infections, including HIV. The school-based sexuality education program aims to reduce young people’s vulnerability, enhance their decision-making skills, and improve their self-efficacy. The rising incidence of sexually transmitted infections and student pregnancy in some rural schools in King Cetshwayo district may indicate that their sexuality education programs are ineffective as a result of multiple contextual factors. In light of this, the author conducted a study that explored students' lived experiences with the sexuality education programs available in their schools. This phenomenological study was conducted in 2020. Nine schools were chosen, and 84 purposively sampled secondary school students participated in focus group interviews. The collected data were analysed using an interpretative phenomenological analysis framework. Study findings revealed that social media platforms could be utilised to improve the effectiveness of school-based sexuality education in the research setting. The study identified untapped opportunities to spread sexuality education messages to all stakeholders, including students, teachers, parents, and various community actors. Furthermore, the findings showed that using social media platforms could increase the spread and accessibility of sexuality education messages outside of the four walls of classrooms. In addition, it emerged that social media could be used to create platforms for confidential, private, and non-judgemental engagements on sensitive aspects of sexuality education. Based on the findings of the study, the author recommends that policymakers initiate and implement policies that will integrate the use of multiple social media platforms to advance the messages of sexuality education to all stakeholders. In addition, such platforms could be used for capacity building and support for both teachers and students, as well as a medium for multi-stakeholder engagement.