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19 pages, 924 KiB  
Article
Determinants of Adherence to World Cancer Research Fund/American Institute for Cancer Research Recommendations in Women with Breast Cancer
by Vanessa Pachón Olmos, Marina Pollán, Nerea Fernández de Larrea-Baz, Julia Fernández-Morata, Emma Ruiz-Moreno, Javier García-Pérez, Adela Castelló, María Ángeles Sierra, Pilar Lucas, Isabel Alonso-Ledesma, Agostina Stradella, Blanca Cantos, Teresa Ramón y Cajal, Marta Santisteban, Miguel Ángel Seguí, Ana Santaballa Bertrán, Mónica Granja, Julia Camps-Herrero, Sabela Recalde, Miriam Mendez, Nuria Calvo Verges, Beatriz Pérez-Gómez, Roberto Pastor-Barriuso and Virginia Lopeadd Show full author list remove Hide full author list
Cancers 2025, 17(4), 708; https://doi.org/10.3390/cancers17040708 - 19 Feb 2025
Viewed by 1317
Abstract
Background/Objectives: The 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations benefit primary prevention and survivor outcomes. This study evaluated the adherence to these recommendations during the year prior to breast cancer diagnosis and identified related clinical and sociodemographic [...] Read more.
Background/Objectives: The 2018 World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations benefit primary prevention and survivor outcomes. This study evaluated the adherence to these recommendations during the year prior to breast cancer diagnosis and identified related clinical and sociodemographic factors. Methods: A total of 915 patients with breast cancer were recruited from eight hospitals in four regions of Spain. The participants completed an epidemiologic questionnaire and a food frequency questionnaire. The compliance with the WCRF/AICR recommendations was assessed using a standardized score based on seven recommendations. Standardized prevalences and standardized prevalence ratios (SPRs) for moderate and high adherence were calculated based on participant characteristics using binary and multinomial logistic regression models. Results: The mean adherence was 3.5 points out of 7. The recommendations with the best and worst adherence were avoiding sugar-sweetened drinks (54.4% adherence) and maintaining a fiber-rich diet (4.4% consumed ≥30 g/day). The overall adherence was better in women aged ≥60 years (SPR = 1.55; 95% CI = 1.09–2.22), and worse in those with a caloric intake ≥2000 kcal/day (SPR = 0.48; 95% CI = 0.37–0.62) or ≥2 comorbidities (SPR = 0.66; 95% CI = 0.49–0.89). The adherence to maintaining a healthy weight was worse in those with ≥2 comorbidities and stage III-IV tumors. The physical activity adherence was worse in working women and those with ≥2 comorbidities. The alcohol restriction adherence was worse in smokers. Younger women, smokers and those with a low calorie intake were less adherent to the fruit/vegetable recommendation. The consumption of fiber and limited consumption of red/processed meat adherence was poor in all the subgroups. The adherence to a limited consumption of fast food and sugary drinks was worse in younger women and high-calorie-diet consumers. Conclusions: The differences in the adherence to recommendations according to patient characteristics justify the design of personalized interventions for breast cancer patients. Full article
(This article belongs to the Section Cancer Epidemiology and Prevention)
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19 pages, 4764 KiB  
Article
Preclinical Identification of Poorly Controlled COPD: Patients with a Single Moderate Exacerbation Matter Too
by José David Maya Viejo and Fernando M. Navarro Ros
J. Clin. Med. 2025, 14(1), 22; https://doi.org/10.3390/jcm14010022 - 24 Dec 2024
Viewed by 2981
Abstract
Background and Objectives: Chronic obstructive pulmonary disease (COPD) remains a critical global health challenge, characterized by high morbidity, mortality, and healthcare costs. Current guidelines may overlook patients who present with only one moderate exacerbation or with frequent short-acting beta-agonist (SABA) use. Building on [...] Read more.
Background and Objectives: Chronic obstructive pulmonary disease (COPD) remains a critical global health challenge, characterized by high morbidity, mortality, and healthcare costs. Current guidelines may overlook patients who present with only one moderate exacerbation or with frequent short-acting beta-agonist (SABA) use. Building on findings from the Seleida study, this research refines the criteria for poor COPD control to include these patients, aiming to improve early identification of high-risk cases in primary care. Methods: A retrospectiveand multicenter study is conducted using data from 110 COPD patients in Spain. Poor control is redefined as having at least one moderate exacerbation or as using three or more SABA inhalers annually. Key predictors, such as SABA/short-acting muscarinic antagonist (SAMA) inhalers and antibiotic prescriptions, are identified using logistic regression and LASSO regularization to enhance predictive accuracy. Results: The model achieves a good predictive performance, with an AUC-ROC of 0.978, sensitivity of 92.86%, and specificity of 87.50%. Key predictors reliably identify high-risk patients, enabling timely interventions. This study demonstrates a statistically significant association between once-daily inhaler therapies and better COPD control compared to multiple daily doses, supported by chi-square analysis (p = 0.008) and binary logistic regression (p = 0.018). Nevertheless, the variable ‘daily inhalation frequency’ (1 vs. >1 inhalation/day) was excluded from the final model to prevent overfitting. Conclusions: By refining the criteria for COPD control to include patients with at least one moderate exacerbation or frequent SABA use, this model provides a practical tool for early risk stratification in primary care, particularly in resource-limited settings. Early identification of high-risk patients can reduce hospitalizations and healthcare costs, supporting a proactive approach to COPD management. Further validation in larger cohorts is essential to confirm its broader applicability. Full article
(This article belongs to the Section Respiratory Medicine)
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17 pages, 557 KiB  
Review
Heart Rate Variability in Basketball: The Golden Nugget of Holistic Adaptation?
by Rubén Portes Sánchez, Enrique Alonso-Pérez-Chao, Julio Calleja-González and Sergio L. Jiménez Sáiz
Appl. Sci. 2024, 14(21), 10013; https://doi.org/10.3390/app142110013 - 2 Nov 2024
Cited by 4 | Viewed by 3436
Abstract
The main aim of this narrative review is to assess the existing body of scientific literature on heart rate variability (HRV) in relation to basketball, focusing on its use as a measure of internal load and vagal nerve responses. Monitoring HRV offers insights [...] Read more.
The main aim of this narrative review is to assess the existing body of scientific literature on heart rate variability (HRV) in relation to basketball, focusing on its use as a measure of internal load and vagal nerve responses. Monitoring HRV offers insights into the autonomic function and training-induced adaptations of basketball players. Various HRV measurement protocols, ranging from short-term to longer durations, can be conducted in different positions and conditions, such as rest, training, and sleep, to determine this key metric. Consistency and individualization in measurement protocols, responding to the athlete’s specific characteristics, is crucial for reliable HRV data and their interpretation. Studies on HRV in basketball have explored psychological adaptation, training effects, individual differences, recovery, and sleep quality. Biofeedback techniques show positive effects on HRV and anxiety reduction, potentially enhancing performance and stress management. The scientific literature on HRV in basketball could benefit from studies involving longer monitoring periods to identify significant trends and results related to training and recovery. Longitudinal HRV monitoring in teams with intense travel schedules could reveal the impact on athletes of all levels and ages, and, in this regard, individualized interpretation, considering the subjective recovery and fitness levels of athletes, is recommended to optimize training programs and performance. HRV provides insights into training and competitive loads, aiding in determining exercise intensities and training status. Additionally, HRV is linked to recovery and sleep quality, offering valuable information for optimizing player performance and well-being. Overall, HRV is a reliable tool for adjusting training programs to meet the specific needs of basketball players. Full article
(This article belongs to the Special Issue Exercise Physiology and Biomechanics in Human Health)
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13 pages, 2059 KiB  
Article
A New Licensed Quadrivalent Antileptospiral Canine Vaccine Prevents Mortality, Clinical Signs, Infection, Bacterial Excretion, Renal Carriage and Renal Lesions Caused by Leptospira Australis Experimental Challenge
by Jérôme Bouvet, Carine Segouffin Cariou, Frantz Oberli, Anne-Laure Guiot and Lionel Cupillard
Vaccines 2024, 12(10), 1104; https://doi.org/10.3390/vaccines12101104 - 26 Sep 2024
Cited by 1 | Viewed by 1893
Abstract
Background: L. Australis is one of the most prevalent Leptospira strains infecting dogs, leading, in natural conditions, to severe life-threatening cases. Objective: The objective was to evaluate the onset and duration of immunity (OOI and DOI) induced by a new licensed quadrivalent antileptospiral [...] Read more.
Background: L. Australis is one of the most prevalent Leptospira strains infecting dogs, leading, in natural conditions, to severe life-threatening cases. Objective: The objective was to evaluate the onset and duration of immunity (OOI and DOI) induced by a new licensed quadrivalent antileptospiral vaccine (EURICAN® L4) including four Leptospira components (Canicola, Icterohaemorrhagiae, Grippotyphosa and Australis) against L. Australis. To this end, a severe L. Australis challenge model was developed, using a canine strain recently isolated from the field. Material and Methods: Seven- to ten-week-old puppies received two doses of the vaccine four weeks apart and were challenged with an L. Australis isolate two weeks (OOI) and 12 months (DOI) later. Mortality, clinical signs, leptospiremia, leptospiruria, renal carriage, and renal lesions were assessed after challenge. Results: The challenge induced multiple severe clinical signs in controls, leading to the death or euthanasia of 83% of puppies and 57% of adults. In controls, leptospiremia was detected in all dogs, leptospiruria in 67% of puppies and 86% of adults, kidneys tested positive for Leptospira in 83% of puppies and 71% of adults, and kidney lesions were observed in 100% of puppies and 86% of adults. In addition, thrombocytopenia associated with increased concentrations of urea, creatinine, and aspartate aminotransferase was recorded in controls displaying severe clinical signs. In both OOI and DOI studies, none of the vaccinates had clinical signs, no Leptospira was detected in blood, urine, and kidney samples, and no kidney lesions were observed in vaccinates. No significant changes in hematological and biochemical parameters in vaccinates were recorded. Conclusion: EURICAN® L4 was shown to induce quick and long-lasting protection against a severe L. Australis infectious challenge, preventing mortality, clinical signs, infection, bacterial excretion, renal lesions, and renal carriage. Full article
(This article belongs to the Special Issue Updates on Veterinary Vaccines and Vaccinology)
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18 pages, 2672 KiB  
Article
Preclinical Evaluation of Electronic Health Records (EHRs) to Predict Poor Control of Chronic Respiratory Diseases in Primary Care: A Novel Approach to Focus Our Efforts
by Fernando M. Navarro Ros and José David Maya Viejo
J. Clin. Med. 2024, 13(18), 5609; https://doi.org/10.3390/jcm13185609 - 21 Sep 2024
Cited by 5 | Viewed by 4747
Abstract
Background/Objectives: Managing chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD) within the Spanish Sistema Nacional de Salud (SNS) presents significant challenges, particularly due to their high prevalence and poor disease control rates—approximately 45.1% for asthma and 63.2% for COPD. [...] Read more.
Background/Objectives: Managing chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD) within the Spanish Sistema Nacional de Salud (SNS) presents significant challenges, particularly due to their high prevalence and poor disease control rates—approximately 45.1% for asthma and 63.2% for COPD. This study aims to develop a novel predictive model using electronic health records (EHRs) to estimate the likelihood of poor disease control in these patients, thereby enabling more efficient management in primary care settings. Methods: The Seleida project employed a bioinformatics approach to identify significant clinical variables from EHR data in primary care centers in Seville and Valencia. Statistically significant variables were incorporated into a logistic regression model to predict poor disease control in patients with asthma and COPD patients. Key variables included the number of short-acting β-agonist (SABA) and short-acting muscarinic antagonist (SAMA) canisters, prednisone courses, and antibiotic courses over the past year. Results: The developed model demonstrated high accuracy, sensitivity, and specificity in predicting poorly controlled disease in both asthma and COPD patients. These findings suggest that the model could serve as a valuable tool for the early identification of at-risk patients, allowing healthcare providers to prioritize and optimize resource allocation in primary care settings. Conclusions: Integrating this predictive model into primary care practice could enhance the proactive management of asthma and COPD, potentially improving patient outcomes and reducing the burden on healthcare systems. Further validation in diverse clinical settings is warranted to confirm the model’s efficacy and generalizability. Full article
(This article belongs to the Section Respiratory Medicine)
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15 pages, 1784 KiB  
Article
Acoustic Detection of Vaccine Reactions in Hens for Assessing Anti-Inflammatory Product Efficacy
by Gerardo José Ginovart-Panisello, Ignasi Iriondo, Tesa Panisello Monjo, Silvia Riva, Jordi Casadó Cancer and Rosa Ma Alsina-Pagès
Appl. Sci. 2024, 14(5), 2156; https://doi.org/10.3390/app14052156 - 5 Mar 2024
Cited by 4 | Viewed by 1673
Abstract
Acoustic studies on poultry show that chicken vocalizations can be a real-time indicator of the health conditions of the birds and can improve animal welfare and farm management. In this study, hens vaccinated against infectious laryngotracheitis (ILT) were acoustically recorded for 3 days [...] Read more.
Acoustic studies on poultry show that chicken vocalizations can be a real-time indicator of the health conditions of the birds and can improve animal welfare and farm management. In this study, hens vaccinated against infectious laryngotracheitis (ILT) were acoustically recorded for 3 days before vaccine administration (pre-reaction period) and also from vaccination onwards, with the first 5 days being identified as the “reaction period” and the 5 following days as “post reaction”. The raw audio was pre-processed to isolate hen calls and the 13 Mel-frequency cepstral coefficients; then, the spectral centroid and the number of vocalizations were extracted to build the acoustic dataset. The experiment was carried out on the same farm but in two different houses. The hens from one house were assigned to the control group, without administration of the anti-inflammatory product, and the other formed the treatment group. Both acoustic data sets were recorded and processed in the same way. The control group was used to acoustically model the animal reaction to the vaccine and we automatically detected the hens’ vaccine reactions and side effects through acoustics. From Scikit-Learn algorithms, Gaussian Naive Bayes was the best performing model, with a balanced accuracy of 80% for modeling the reactions and non-reactions caused by ILT in the control group. Furthermore, the importance of algorithm permutation highlighted that the centroid and MFCC4 were the most important features in acoustically detecting the ILT vaccine reaction. The fitted Gaussian Naive Bayes model allowed us to evaluate the treatment group to determine if the vocalizations after vaccine administration were detected as non-reactions, due to the anti-inflammatory product’s effectiveness. Of the sample, 99% of vocalizations were classified as non-reactions, due to the anti-inflammatory properties of the product, which reduced vaccine reactions and side effects. The non-invasive detection of hens’ responses to vaccination to prevent respiratory problems in hens described in this paper is an innovative method of measuring and detecting avian welfare. Full article
(This article belongs to the Special Issue The Analysis and Interpretation of Animal Vocalisations)
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23 pages, 1449 KiB  
Article
Challenges That Need to Be Addressed before Starting New Emergency Remote Teaching at HEIs and Proposed Solutions
by Simona Šinko, Joan Navarro, Xavier Solé-Beteta, Agustín Zaballos and Brigita Gajšek
Sustainability 2024, 16(3), 1144; https://doi.org/10.3390/su16031144 - 29 Jan 2024
Cited by 3 | Viewed by 1438
Abstract
Emergency Remote Teaching (ERT) aims to swiftly adapt conventional face-to-face educational methods to alternative (typically virtual) formats during crises. The recent COVID-19 pandemic accentuated the vulnerability of traditional educational systems, revealing limitations in their ability to effectively withstand such unprecedented events, thereby exposing [...] Read more.
Emergency Remote Teaching (ERT) aims to swiftly adapt conventional face-to-face educational methods to alternative (typically virtual) formats during crises. The recent COVID-19 pandemic accentuated the vulnerability of traditional educational systems, revealing limitations in their ability to effectively withstand such unprecedented events, thereby exposing shortcomings in the adopted ERT strategies. The goal of this study is to discuss the establishment of resilient, sustainable, and healthy educational systems in non-crisis times, which will enable teachers and students to make a smoother and less stressful transition to Emergency Remote Teaching (ERT) when necessary. A comprehensive hybrid approach, combining quantitative (interviews) and qualitative (online survey) methods has obtained data from 276 professors in 29 countries. These data have been used to identify a range of challenges related to ERT and their perceived level of difficulty. The methodological and social challenges (overshadowed by technical issues at the beginning of the crisis) identified in this research—such as the lack of personal contact or poor feedback from students—have been found to be the most demanding. From the collected insights regarding the perceived level of difficulty associated with the identified challenges, the present study aims to contribute to making higher education systems more robust in non-crisis times. Full article
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12 pages, 674 KiB  
Article
Impact of SARS-CoV-2 Infection on Unvaccinated Pregnant Women: Non-Reassuring Fetal Heart Rate Tracing Because of Placentitis
by Alexandra Claudet, Daniele De Luca, Elie Mosnino, Jérémie Mattern, Olivier Picone, Jeanne Sibiude, Estelle Wafo, Vassilis Tsatsaris, Emilie Giral, Irène Grefenstette, Julie Carrara, Dominique A. Badr, Marie-Hélène Saint-Frison, Sophie Prevot, Alexandra Benachi and Alexandre J. Vivanti
Viruses 2023, 15(5), 1069; https://doi.org/10.3390/v15051069 - 27 Apr 2023
Cited by 1 | Viewed by 2232
Abstract
In 2020, a new coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in China. SARS-CoV-2 infection has been shown to be highly morbid in pregnant women, being a risk factor for several obstetric conditions leading to increased maternal and neonatal mortality. [...] Read more.
In 2020, a new coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in China. SARS-CoV-2 infection has been shown to be highly morbid in pregnant women, being a risk factor for several obstetric conditions leading to increased maternal and neonatal mortality. A few studies since 2020 have shown SARS-CoV-2 maternal–fetal transmission and noted placental abnormalities grouped under the term placentitis. We hypothesized that these placental lesions could be responsible for abnormalities in placental exchange and therefore abnormalities in cardiotocographic monitoring, leading to premature fetal extraction. The objective is to identify the clinical, biochemical, and histological determinants associated with the occurrence of non-reassuring fetal heart rate (NRFHR) outside labor in fetuses of SARS-CoV-2-infected mothers. We conducted a retrospective multicenter case series of the natural history of maternal SARS-CoV-2 infections resulting in fetal delivery outside labor due to NRFHR. Collaboration was sought with the maternity hospitals in the CEGORIF, the APHP and Brussels hospitals. The investigators were contacted by e-mail on three successive occasions over a period of one year. Data from 17 mothers and 17 fetuses were analyzed. Most women had a mild SARS-CoV-2 infection; only two women presented severe infection. No woman was vaccinated. We found a substantial proportion of maternal coagulopathy at birth: elevation of APTT ratio (62%), thrombocytopenia (41%) and liver cytolysis (58.3%). Iatrogenic prematurity was noted in 15 of 17 fetuses, and 100% were born by cesarean delivery due to emergency criteria. One male neonate died on the day of birth due to peripartum asphyxia. Three cases of maternal–fetal transmission were recorded following WHO criteria. Placental analysis in 15 cases revealed eight cases of SARS-CoV-2 placentitis, causing placental insufficiency. In total, 100% of the placentas analyzed showed at least one lesion suggestive of placentitis. SARS-CoV-2 maternal infection during pregnancy is likely to generate neonatal morbidity in relation to placental damage resulting in placental insufficiency. This morbidity may be the consequence of induced prematurity as well as acidosis in the most severe situations. Placental damage occurred in unvaccinated women and in women with no identified risk factor, in contrast to severe maternal clinical forms. Full article
(This article belongs to the Section Viral Immunology, Vaccines, and Antivirals)
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25 pages, 8987 KiB  
Article
A Quasi-Affine Transformation Evolutionary Algorithm Enhanced by Hybrid Taguchi Strategy and Its Application in Fault Detection of Wireless Sensor Network
by Jeng-Shyang Pan, Ru-Yu Wang, Shu-Chuan Chu, Kuo-Kun Tseng and Fang Fan
Symmetry 2023, 15(4), 795; https://doi.org/10.3390/sym15040795 - 24 Mar 2023
Cited by 8 | Viewed by 2115
Abstract
A quasi-affine transformation evolutionary algorithm improved by the Taguchi strategy, levy flight and the restart mechanism (TLR-QUATRE) is proposed in this paper. This algorithm chooses the specific optimization route according to a certain probability, and the Taguchi strategy helps the algorithm achieve more [...] Read more.
A quasi-affine transformation evolutionary algorithm improved by the Taguchi strategy, levy flight and the restart mechanism (TLR-QUATRE) is proposed in this paper. This algorithm chooses the specific optimization route according to a certain probability, and the Taguchi strategy helps the algorithm achieve more detailed local exploitation. The latter two strategies help particles move at random steps of different sizes, enhancing the global exploration ability. To explore the new algorithm’s performance, we make a detailed analysis in seven aspects through comparative experiments on CEC2017 suite. The experimental results show that the new algorithm has strong optimization ability, outstanding high-dimensional exploration ability and excellent convergence. In addition, this paper pays attention to the demonstration of the process, which makes the experimental results credible, reliable and explainable. The new algorithm is applied to fault detection in wireless sensor networks, in which TLR-QUATRE is combined with back-propagation neural network (BPNN). This study uses the symmetry of generation and feedback for network training. We compare it with other optimization structures through eight public datasets and one actual landing dataset. Five classical machine learning indicators and ROC curves are used for visualization. Finally, the robust adaptability of TLR-QUATRE on this issue is confirmed. Full article
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15 pages, 8754 KiB  
Article
Separation of Ambient Radio Noise and Radio Signals Received via Ionospheric Propagation
by Ben A. Witvliet, Rosa M. Alsina-Pagès, David Altadill, Erik van Maanen and Geert Jan Laanstra
Atmosphere 2023, 14(3), 529; https://doi.org/10.3390/atmos14030529 - 9 Mar 2023
Cited by 7 | Viewed by 3110
Abstract
Systems for atmospheric research and wireless communication use the High Frequency (HF) radio spectrum. At these frequencies, typically up to 20 MHz, the ambient electromagnetic noise is stronger than the noise generated by the receiver itself, thereby limiting the sensitivity of the instruments. [...] Read more.
Systems for atmospheric research and wireless communication use the High Frequency (HF) radio spectrum. At these frequencies, typically up to 20 MHz, the ambient electromagnetic noise is stronger than the noise generated by the receiver itself, thereby limiting the sensitivity of the instruments. Especially in urban areas, the noise level is high. In remote rural environments, where artificial noise sources are absent, a much lower noise level is observed. It has been shown that this noise arrives via ionospheric propagation and consists of impulsive noise from lightning and a background component that resembles additive white Gaussian noise. To establish the absolute field strength of this background noise component, a direction- and polarization-agnostic antenna is realized by adding the power of two orthogonal antenna elements in the digital domain. To suppress radio signals arriving via ionospheric propagation—of which the spectral and temporal aspects are not known a priori—a novel adaptive filter is demonstrated that separates the background noise from the radio signals in the joint frequency-time domain. This method is demonstrated using measurements from a polarimetric experiment on 7 MHz in a remote rural area in Catalonia. The results are submitted to the International Telecommunication Union for the validation of ambient noise models. Full article
(This article belongs to the Special Issue Ionospheric Science and Ionosonde Applications)
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6 pages, 6215 KiB  
Proceeding Paper
Conscious Walk Methodology Design for Acoustic, Air Quality and Biodiversity Evaluation in Urban Environments
by Marc Arnela, Mariona Ferrandiz-Rovira, Marc Freixes, Danielly Garcia, Carme Martínez-Suquía, Ma Eulàlia Parés, Oriol Serra, Ester Vidaña-Vila and Rosa Ma Alsina-Pagès
Eng. Proc. 2022, 27(1), 75; https://doi.org/10.3390/ecsa-9-13336 - 1 Nov 2022
Cited by 2 | Viewed by 1595
Abstract
Environmental noise and air pollution, as well as poor green infrastructure quality, are major concerns for the European population due to their impacts on citizens’ health, especially for those citizens living in urban environments, which materializes in a rising number of complaints to [...] Read more.
Environmental noise and air pollution, as well as poor green infrastructure quality, are major concerns for the European population due to their impacts on citizens’ health, especially for those citizens living in urban environments, which materializes in a rising number of complaints to public administration. This issue is further stressed for urban areas located close to aggressive sources of such pollutants, such as airports, railways, highways, or leisure areas. To attend to this situation from the viewpoint of citizens’ everyday lives, this paper proposes a hybrid methodology in the form of a collective campaign in which citizens, especially those from environments that have a stronger impact, cooperate with scientists to collect high quality acoustic, chemical, and biodiversity data. The campaign consists of a conscious walk that considers acoustic measurements conducted by both experts and citizens, coupled with air quality measurements and biodiversity descriptions. The final goal of the method is to obtain subjective and objective data on the soundscape, air quality, and biodiversity in order to evaluate a pre-designed route in an urban location, namely, in the surroundings of Parc de la Ciutadella, Barcelona, Spain. Full article
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14 pages, 10918 KiB  
Article
Trend and Representativeness of Acoustic Features of Broiler Chicken Vocalisations Related to CO2
by Gerardo José Ginovart-Panisello, Ignasi Iriondo Sanz, Tesa Panisello Monjo, Silvia Riva, Tomas Garriga Dicuzzo, Eva Abancens Escuer and Rosa Ma Alsina-Pagès
Appl. Sci. 2022, 12(20), 10480; https://doi.org/10.3390/app122010480 - 17 Oct 2022
Cited by 7 | Viewed by 2036
Abstract
The concentration of CO2 is relatively large in poultry farms and high accumulations of this gas reduce animal welfare. Good control of its concentration is crucial for the health of the animals. The vocalizations of the chickens can show their level of [...] Read more.
The concentration of CO2 is relatively large in poultry farms and high accumulations of this gas reduce animal welfare. Good control of its concentration is crucial for the health of the animals. The vocalizations of the chickens can show their level of well-being linked to the presence of carbon dioxide. An audio recording system was implemented and audio raw data was processed to extract acoustical features from four cycles of forty days, three of them from the same farm. This research aims to find the most relevant acoustic features extracted from the broiler’s calls that are related to the CO2 concentration and that could help to automate procedures. The results are encouraging since MFCC 6, 9, 4 and 3 are the most important features that relate the vocalizations of the chickens to the gas concentration, furthermore there is a clear and more similar representativeness trend during birds’ life period from day 15 to day 40. Full article
(This article belongs to the Special Issue The Analysis and Interpretation of Animal Vocalisations)
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17 pages, 4715 KiB  
Article
Application of Improved Quasi-Affine Transformation Evolutionary Algorithm in Power System Stabilizer Optimization
by Jing Huang, Jiajing Liu, Cheng Zhang, Yu Kuang and Shaowei Weng
Electronics 2022, 11(17), 2785; https://doi.org/10.3390/electronics11172785 - 4 Sep 2022
Cited by 3 | Viewed by 1698
Abstract
This paper proposes a parameter coordination optimization design of a power system stabilizer (PSS) based on an improved quasi-affine transformation evolutionary (QUATRE) algorithm to suppress low-frequency oscillation and improve the dynamic stability of power systems. To begin, the simulated annealing (SA) algorithm randomly [...] Read more.
This paper proposes a parameter coordination optimization design of a power system stabilizer (PSS) based on an improved quasi-affine transformation evolutionary (QUATRE) algorithm to suppress low-frequency oscillation and improve the dynamic stability of power systems. To begin, the simulated annealing (SA) algorithm randomly updates the globally optimal solution of each QUATRE iteration and matches the inferior solution with a certain probability to escape the local extreme point. This new algorithm is first applied to the power system. Since the damping ratio is one of the criteria with which to measure the dynamic stability of the power system, this paper sets the objective function according to the principle of maximization of the damping coefficient of the electromechanical mode, and uses SA-QUATRE to search a group of global optimal PSS parameter combinations to improve the safety factor of the system as much as possible. Finally, the method’s rationality and validity were validated by applying it to the simulation examples of the IEEE 4-machine 2-area system with different operation states. The comparison with the traditional optimization algorithm shows that the proposed method has more advantages for multi-machine PSS parameter coordination optimization, can restrain the low-frequency oscillation of the power system more effectively and can enhance the system’s stability. Full article
(This article belongs to the Special Issue Machine Learning in the Industrial Internet of Things)
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17 pages, 4275 KiB  
Article
Balancing Data through Data Augmentation Improves the Generality of Transfer Learning for Diabetic Retinopathy Classification
by Zahra Mungloo-Dilmohamud, Maleika Heenaye-Mamode Khan, Khadiime Jhumka, Balkrish N. Beedassy, Noorshad Z. Mungloo and Carlos Peña-Reyes
Appl. Sci. 2022, 12(11), 5363; https://doi.org/10.3390/app12115363 - 25 May 2022
Cited by 26 | Viewed by 4455
Abstract
The incidence of diabetes in Mauritius is amongst the highest in the world. Diabetic retinopathy (DR), a complication resulting from the disease, can lead to blindness if not detected early. The aim of this work was to investigate the use of transfer learning [...] Read more.
The incidence of diabetes in Mauritius is amongst the highest in the world. Diabetic retinopathy (DR), a complication resulting from the disease, can lead to blindness if not detected early. The aim of this work was to investigate the use of transfer learning and data augmentation for the classification of fundus images into five different stages of diabetic retinopathy. The five stages are No DR, Mild nonproliferative DR, Moderate nonproliferative DR, Severe nonproliferative DR and Proliferative. To this end, deep transfer learning and three pre-trained models, VGG16, ResNet50 and DenseNet169, were used to classify the APTOS dataset. The preliminary experiments resulted in low training and validation accuracies, and hence, the APTOS dataset was augmented while ensuring a balance between the five classes. This dataset was then used to train the three models, and the best three models were used to classify a blind Mauritian test datum. We found that the ResNet50 model produced the best results out of the three models and also achieved very good accuracies for the five classes. The classification of class-4 Mauritian fundus images, severe cases, produced some unexpected results, with some images being classified as mild, and therefore needs to be further investigated. Full article
(This article belongs to the Special Issue Deep Neural Networks in Medical Imaging)
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27 pages, 1622 KiB  
Article
A Data-Driven Approach to Quantify and Measure Students’ Engagement in Synchronous Virtual Learning Environments
by Xavier Solé-Beteta, Joan Navarro, Brigita Gajšek, Alessandro Guadagni and Agustín Zaballos
Sensors 2022, 22(9), 3294; https://doi.org/10.3390/s22093294 - 25 Apr 2022
Cited by 21 | Viewed by 4667
Abstract
In face-to-face learning environments, instructors (sub)consciously measure student engagement to obtain immediate feedback regarding the training they are leading. This constant monitoring process enables instructors to dynamically adapt the training activities according to the perceived student reactions, which aims to keep them engaged [...] Read more.
In face-to-face learning environments, instructors (sub)consciously measure student engagement to obtain immediate feedback regarding the training they are leading. This constant monitoring process enables instructors to dynamically adapt the training activities according to the perceived student reactions, which aims to keep them engaged in the learning process. However, when shifting from face-to-face to synchronous virtual learning environments (VLEs), assessing to what extent students are engaged to the training process during the lecture has become a challenging and arduous task. Typical indicators such as students’ faces, gestural poses, or even hearing their voice can be easily masked by the intrinsic nature of the virtual domain (e.g., cameras and microphones can be turned off). The purpose of this paper is to propose a methodology and its associated model to measure student engagement in VLEs that can be obtained from the systematic analysis of more than 30 types of digital interactions and events during a synchronous lesson. To validate the feasibility of this approach, a software prototype has been implemented to measure student engagement in two different learning activities in a synchronous learning session: a masterclass and a hands-on session. The obtained results aim to help those instructors who feel that the connection with their students has weakened due to the virtuality of the learning environment. Full article
(This article belongs to the Special Issue From Sensor Data to Educational Insights)
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