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Neonatal and pediatric mortality in kittens could be associated with bacterial infections, complications from inadequate management, congenital malformations, neonatal isoerythrolysis, parasitic diseases, and viral diseases. The complexity of causes, coupled with kittens’ physiological and immunological immaturity, complicates the diagnosis and treatment of disease, highlighting the necessity for preventive measures. This study aimed to identify the leading causes of death and the occurrence of congenital malformations in stray kittens. Necropsies were performed on 68 kittens, all aged under two months. Results indicated that respiratory lesions were the leading cause of death in the youngest group, while gastrointestinal problems were more prevalent in older groups. Infectious causes were predominant across all age groups. Congenital malformations were observed in 40% of the animals, with megaesophagus, cardiovascular anomalies, bone defects, and kidney defects being the most prevalent. The findings underscore the critical importance of hygiene in preventing infections and related complications. Promoting sterilization and sanitary control in stray cats is essential to reduce overpopulation and improve living conditions.

Background and Aim: Feline chronic gingivostomatitis (FCGS) is a frequent chronic inflammatory condition in the oral cavity with an etiopathogenesis not completely identified. This study aimed to contribute to the knowledge of FCGS by identifying the presence of feline calicivirus (FCV) antigens and natural killer (NK) cells and comparing them. Materials and Methods: Forty biopsies from the oral mucosa of cats diagnosed with chronic gingivostomatitis were subjected to immunohistochemical techniques to evaluate cells with FCV antigens and NK cells positive for CD56. Results: NK cells were identified in all samples, with an average of 725.3 ± 409.1 cells. Regarding FCV, it was identified in 18 out of 30 samples (60%), with a different number of cells with virus in between the analyzed cases. In all cases, the number of cells infected with FCV was lower than the number of NK cells present in the same samples, but there was no statistical association between them. Conclusion: This preliminary study shows that NK cells are present in gingivostomatitis lesions not exclusively caused by FCV-stimulus, as only 60% of all cases were positive for this virus, but other antigens should be considered in the etiology of FCGS.

This article presents the development of a vision system designed to enhance the autonomous navigation capabilities of robots in complex forest environments. Leveraging RGBD and thermic cameras, specifically the Intel RealSense 435i and FLIR ADK, the system integrates diverse visual sensors with advanced image processing algorithms. This integration enables robots to make real-time decisions, recognize obstacles, and dynamically adjust their trajectories during operation. The article focuses on the architectural aspects of the system, emphasizing the role of sensors and the formulation of algorithms crucial for ensuring safety during robot navigation in challenging forest terrains. Additionally, the article discusses the training of two datasets specifically tailored to forest environments, aiming to evaluate their impact on autonomous navigation. Tests conducted in real forest conditions affirm the effectiveness of the developed vision system. The results underscore the system’s pivotal contribution to the autonomous navigation of robots in forest environments.

This paper presents the integration of multimodal sensor systems for an autonomous forestry machine. The utilized technology is housed in a single enclosure which consolidates a set of components responsible for executing machine control actions and comprehending its behavior in various scenarios. This sensor box, named Sentry, will subsequently be connected to a forestry machine from MDB, model LV600 PRO. The article outlines previous work in this field and then details the integration and operation of the equipment, integrated into the forest machine, providing descriptions of the adopted architecture at both the hardware and software levels. The gathered data enables the assessment of the forestry machine’s orientation and position based on the information collected by the sensors. Finally, practical experiments are presented to demonstrate the system’s behavior and to analyze the methods to be employed for autonomous navigation, thereby assessing the performance of the established architecture. The novel aspects of this work include the physical and digital integration of a multimodal sensor system on a forestry machine, its use in a real case scenario, namely, forest vegetation removal, and the strategies adopted to improve the machine localization and navigation performance on unstructured environments.

Genomic medicine has become a growing reality; however, it is still taking its first steps in veterinary medicine. Through this approach, it will be possible to trace the genetic profile of a given individual and thus know their susceptibility to certain diseases, namely periodontal disease. This condition is one of the most frequently diagnosed in companion animal clinics, especially in dogs. Due to the limited existing information and the lack of comprehensive studies, the objective of the present study was to systematically review the existing scientific literature regarding genomic medicine in canine periodontal disease and determine which genes have already been studied and their probable potential. This study followed the recommendations of the PRISMA 2020 methodology. Canine periodontal disease allied to genomic medicine were the subjects of this systematic review. Only six articles met all of the inclusion criteria, and these were analyzed in detail. These studies described genetic variations in the following genes: interleukin-6, interleukin-10, interleukin-1, lactotransferrin, toll-like receptor 9, and receptor activator of nuclear factor-kappa B. Only in two of them, namely interleukin-1 and toll-like receptor 9 genes, may the identified genetic variations explain the susceptibility that certain individuals have to the development of periodontal disease. It is necessary to expand the studies on the existing polymorphic variations in genes and their relationship with the development of periodontal disease. Only then will it be possible to fully understand the biological mechanisms that are involved in this disease and that determine the susceptibility to its development.

When it comes to forest management and protection, knowledge is key. Therefore, forest mapping is crucial to obtain the required knowledge towards profitable resource exploitation and increased resilience against wildfires. Within this context, this paper presents a literature review on tree classification and segmentation using data acquired by unmanned aerial vehicles, with special focus on the last decade (2013–2023). The latest research trends in this field are presented and analyzed in two main vectors, namely: (1) data, where used sensors and data structures are resumed; and (2) methods, where remote sensing and data analysis methods are described, with particular focus on machine learning approaches. The study and review methodology filtered 979 papers, which were then screened, resulting in the 144 works included in this paper. These are systematically analyzed and organized by year, keywords, purpose, sensors, and methods used, easily allowing the readers to have a wide, but at the same time detailed, view of the latest trends in automatic tree classification and segmentation using unmanned aerial vehicles. This review shows that image processing and machine learning techniques applied to forestry and segmentation and classification tasks are focused on improving the accuracy and interpretability of the results by using multi-modal data, 3D information, and AI methods. Most works use RGB or multispectral cameras, or LiDAR scanners, individually. Classification is mostly carried out using supervised methods, while segmentation mostly uses unsupervised machine learning techniques.

The tooth is made up of three mineralized tissues, enamel, dentin, and cementum, which surround a non-mineralized tissue called the dental pulp. Micro-computed tomography (mCT) is an imaging technology based on X-rays that allows non-invasive visualization of objects at a microscopic scale, according to their radiopacity and in three dimensions (3D). Likewise, it allows the subsequent execution of morphological and quantitative analysis of the objects, such as, for example, the determination of the relative mineral density (MD). The present work aimed to describe the MD of feline teeth using mCT. The studied sample consisted of four European Shorthair cats, from which nine canine teeth were extracted per medical indication. These teeth were evaluated through dental radiography before and after their extraction. Using mCT and the CTAn software, the values of the relative mineral density of the root of each tooth and of specific segments corresponding to the coronal, middle, and apical thirds of the root were determined. Mean MD of root tissues was 1.374 ± 0040 g·cm−3, and of hard root, tissues was 1.402 ± 0.035 g·cm−3. Through mCT, it was possible to determine the mean MD values of feline canine teeth. The study of MD could become an ancillary method for the diagnosis and characterization of dental pathology.

Este estudo buscou revisar a literatura sobre o método de custeio Time-Driven Activity-Based Costing, de modo a verificar o estado da arte da temática, analisando seu desenvolvimento ao longo dos 16 anos após a primeira publicação de Kaplan e Anderson, que ocorreu em 2004. O enquadramento metodológico desta pesquisa é qualiquantitativo, com objetivo descritivo, e foi adotado o procedimento de Revisão Sistemática da Literatura. Os estudos-alvo da revisão foram obtidos por meio das bases de dados Web of Science e Scopus. Após terem sido aplicados os critérios de filtragem, pormenorizados na seção do método, obteve-se uma amostra contendo 102 artigos, distribuídos em 75 periódicos científicos. Os resultados apontaram uma expressiva vantagem quantitativa das publicações voltadas à área da saúde e à carência por pesquisas em outros setores prestadores de serviços e indústrias de modo geral. Ao longo das análises, são discutidas oportunidades para estudos futuros, entre os quais o aprofundamento teórico necessário à temática, cuja produção científica tem se concentrado em pesquisas de caráter empírico. Nesse sentido, destaca-se o campo das Ciências Contábeis como bem posicionado para o adequado endereçamento das carências teóricas que foram referidas na literatura consultada.

O estudo investiga a assimetria de custos nas empresas brasileiras do agronegócio. Mediante análise de regressão múltipla, a pesquisa tem por objetivo analisar a relação dos custos de mão de obra e a oferta de crédito com a assimetria dos custos dessas empresas. A pesquisa caracteriza-se como quantitativa, descritiva e documental. Sua amostra é composta por 8 empresas listadas na bolsa de valores e que constam no segmento Carnes e Derivados ou no segmento Agricultura. Os resultados apontaram para um comportamento anti-sticky nos custos das empresas. Além disso, verificou-se que a variável mão de obra é um componente importante para explicar a assimetria de custos das empresas, diferentemente da variável de oferta de crédito, a qual não se mostrou significante. Como contribuição o estudo auxilia na tomada de decisão das empresas, em razão de que evidencia a forte redução dos custos com a diminuição da capacidade produtiva.

Feline oral squamous cell carcinoma (FOSCC) is the most common oral neoplasia in cats. This malignant tumor is locally invasive, has a high mortality rate, and its etiology is not yet known. In humans, head and neck squamous cell carcinoma is associated with tobacco smoke, alcohol consumption, and human papillomavirus infection. Herein, a critical review about the potential etiologic factors of FOSCC was performed, considering publications between 2000 and 2022, aiming to synthesize all available scientific evidence regarding this issue. Recommendations of the PRISMA statement and the Cochrane Collaboration were followed and the PubMed database searched by using the MeSH terms MeSH terms “oral”, “mouth”, “lingual”, “labial”, “gingiva”, “carcinoma”, “squamous”, and “feline”. The selection process for eligible studies was based on specific inclusion and exclusion criteria and the quality of the studies assessed. The initial search resulted in 553 publications, with only 26 of these being included in the review. Sixteen studies were related to viral etiology and nine related to environmental factors such as exposure to tobacco smoke, ectoparasitic products, and the presence of oral comorbidities. When evaluated, feline papillomavirus was detected in 16.2% of samples of FOSCC. In the three studies focused on exposure to tobacco smoke, 35.2% (30/85) of cats with FOSCC had a history of this exposure. The consumption of canned food and the use of deworming collars were associated, in only one publication, with a risk of neoplasia increased by 4.7 and 5.3 times, respectively. Among 485 cats with FOSCC, 6.4% had dental and oral pathology (i.e., periodontal disease or feline chronic gingivostomatitis). The present study demonstrates that the available evidence on the etiology of FOSCC is still limited, however, there has been an increasing interest on this topic. To better understand the role of the possible etiological factors of this aggressive disease, and model for its human counterpart, large, prospective multi-institutional studies are needed.

Vegetation mapping requires accurate information to allow its use in applications such as sustainable forest management against the effects of climate change and the threat of wildfires. Remote sensing provides a powerful resource of fundamental data at different spatial resolutions and spectral regions, making it an essential tool for vegetation mapping and biomass management. Due to the ever-increasing availability of free data and software, satellites have been predominantly used to map, analyze, and monitor natural resources for conservation purposes. This study aimed to map vegetation from Sentinel-2 (S2) data in a complex and mixed vegetation cover of the Lousã district in Portugal. We used ten multispectral bands with a spatial resolution of 10 m, and four vegetation indices, including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Enhanced Vegetation Index (EVI), and Soil Adjusted Vegetation Index (SAVI). After applying principal component analysis (PCA) on the 10 S2A bands, four texture features, including mean (ME), homogeneity (HO), correlation (CO), and entropy (EN), were derived for the first three principal components. Textures were obtained using the Gray-Level Co-Occurrence Matrix (GLCM). As a result, 26 independent variables were extracted from S2. After defining the land use classes using an object-based approach, the Random Forest (RF) classifier was applied. The map accuracy was evaluated by the confusion matrix, using the metrics of overall accuracy (OA), producer accuracy (PA), user accuracy (UA), and kappa coefficient (Kappa). The described classification methodology showed a high OA of 90.5% and kappa of 89% for vegetation mapping. Using GLCM texture features and vegetation indices increased the accuracy by up to 2%; however, classification using GLCM texture features and spectral bands achieved the highest OA (92%), indicating the texture features′ capability in detecting the variability of forest species at stand level. The ME and CO showed the highest contribution to the classification accuracy among the GLCM textures. GNDVI outperformed other vegetation indices in variable importance. Moreover, using only S2A spectral bands, especially bands 11, 12, and 2, showed a high potential to classify the map with an OA of 88%. This study showed that adding at least one GLCM texture feature and at least one vegetation index into the S2A spectral bands may effectively increase the accuracy metrics and tree species discrimination.

A 3-to-4-year-old roe deer (Capreolus capreolus L.) was admitted to the Veterinary Hospital. Although it showed well-developed antlers with retained velvet, an external female appearance and genitalia were evident. External biometrical measurements were taken for the antlers, and a computed tomography was performed. Molecular studies targeting the SRY gene were performed, and a PIS (polled intersex syndrome) mutation diagnosis was implemented. The gonads consisted of a right testicle paired with a left ovotestis. Histologically, the ovary-like structures in the ovotestis were functional, but the testis, as the testis-like structure in the ovotestis, did not show active spermatogenesis. No evidence of SRY gene was detected by PCR, suggesting an XX-chromosome constitution. Additionally, polled intersex syndrome (PIS) deletion was not detected in the case under study. The clinical and histopathological findings confirmed the DSD with the presence of a testicle and a contralateral ovotestis.

Wildfires are complex natural events that cause significant environmental and property damage, as well as human losses, every year throughout the world. In order to aid in their management and mitigate their impact, efforts have been directed towards developing decision support systems that can predict wildfire propagation. Most of the available tools for wildfire spread prediction are based on the Rothermel model that, apart from being relatively complex and computing demanding, depends on several input parameters concerning the local fuels, wind or topography, which are difficult to obtain with a minimum resolution and degree of accuracy. These factors are leading causes for the deviations between the predicted fire propagation and the real fire propagation. In this sense, this paper conducts a literature review on optimization methodologies for wildfire spread prediction based on the use of evolutionary algorithms for input parameter set calibration. In the present literature review, it was observed that the current literature on wildfire spread prediction calibration is mostly focused on methodologies based on genetic algorithms (GAs). Inline with this trend, this paper presents an application of genetic algorithms for the calibration of a set of the Rothermel model’s input parameters, namely: surface-area-to-volume ratio, fuel bed depth, fuel moisture, and midflame wind speed. The GA was validated on 37 real datasets obtained through experimental prescribed fires in controlled conditions.

Collagenated porcine-derived bone graft materials exhibit osteoconductive properties and the development of different formulations intends to enhance bone regeneration. This study aims to evaluate bone healing in a rabbit cancellous bone defect in response to grafting with different physicochemical forms of heterologous porcine bone. Twenty-six adult male New Zealand White rabbits received two critical size femoral bone defects per animal (n = 52), each randomly assigned to one of the five tested materials (Apatos, Gen-Os, mp3, Putty, and Gel 40). Animals were sacrificed at 15- and 30-days post-surgery. Qualitative and quantitative (new bone, particle and connective tissue percentages) histological analyses were performed. Histomorphometry showed statistically significant differences in all evaluated parameters between mp3 and both Putty and Gel 40 groups, regardless of the timepoint (p < 0.05). Moreover, statistical differences were observed between Apatos and both Putty (p = 0.014) and Gel 40 (p = 0.007) groups, at 30 days, in regard to particle percentage. Within each group, regarding new bone formation, mp3 showed significant differences (p = 0.028) between 15 (40.93 ± 3.49%) and 30 (52.49 ± 11.04%) days. Additionally, intragroup analysis concerning the percentage of particles revealed a significant reduction in particle occupied area from 15 to 30 days in mp3 and Gen-Os groups (p = 0.009). All mp3, Gen-Os and Apatos exhibited promising results in terms of new bone formation, thus presenting suitable alternatives to be used in bone regeneration.

Every year, wildfires strike the Portuguese territory and are a concern for public entities and the population. To prevent a wildfire progression and minimize its impact, Fuel Management Zones (FMZs) have been stipulated, by law, around buildings, settlements, along national roads, and other infrastructures. FMZs require monitoring of the vegetation condition to promptly proceed with the maintenance and cleaning of these zones. To improve FMZ monitoring, this paper proposes the use of satellite images, such as the Sentinel-1 and Sentinel-2, along with vegetation indices and extracted temporal characteristics (max, min, mean and standard deviation) associated with the vegetation within and outside the FMZs and to determine if they were treated. These characteristics feed machine-learning algorithms, such as XGBoost, Support Vector Machines, K-nearest neighbors and Random Forest. The results show that it is possible to detect an intervention in an FMZ with high accuracy, namely with an F1-score ranging from 90% up to 94% and a Kappa ranging from 0.80 up to 0.89.

This study aimed at studying the influence of the quantitative variation of the autologous spongy bone graft on its osteogenic properties by virtue of the fact that its attainment has inconveniences of significant morbidity at local donor level and the limited quantity of grafting able to be obtained. Recourse was made to an osteotomy model for this purpose with the removal of a small 4 mm segment at the mid-diaphysis of the left tibia of twenty one sheep, stabilised by an osteosynthesis plate on which different quantities of autografting spongy bone were applied so that the referred bone defect (1) would not to be completely filled (1.5 g), (2) would be filled without any compression (3 g) and (3) would be filled with an excessive quantity (5 g) (n=5/each group). (4) A control osteotomy (n=6) was also carried out where the bone defect remained empty. Comparison of the evolution of bone regeneration during the postoperative period of 12 weeks was carried out by means of conventional radiographic exams and optical densitometry analysis and by radiological bone densitometry (DEXA--Dual-Energy X-ray Absorptiometry), bone histomorphometry and histological analysis after the animals' euthanasia. Optical density was significantly affected (p