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This article reports on a comprehensive dataset detailing positioning errors in a 3-axis milling center machine (MCM) with computer numerical control (CNC) specifically curated for thermal error compensation. The data, which includes separate datasets for the X, Y, and Z axes, was collected through systematic measurements using an interferometric laser (IL) system under monitored thermal conditions. Each axis's acquisition was recorded with a resolution to capture dynamic variations influenced by thermal fluctuations. Temperature measurements were obtained using resistance temperature detectors (RTD) installed in the bearing housings of each axis for monitoring of thermal conditions throughout the data collection process in each axis. The dataset comprises raw positional and error data for each axis alongside metadata describing parameters such as bearing temperature, heating cycle, and machine operating conditions. This dataset can potentially be a valuable resource for researchers, enabling them to develop and validate real-time thermal error compensation algorithms, thereby enhancing CNC machining precision for each axis independently and collectively. Furthermore, the dataset's structured format facilitates comparative studies across different machine configurations and operational contexts, contributing to advancements in manufacturing technology and improvements in process parameter design and optimization.

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Medication-related osteonecrosis of the jaw (MRONJ) is a progressive condition that can cause significant bone loss and its diagnosis can be challenging. A 68-year-old man with a diagnosis of hepatocellular carcinoma, undergoing treatment with atezolizumab, bevacizumab and zoledronic acid, complained of spontaneous pain in the right lower second premolar. Oral examination revealed no dental changes and implants in the right jaw. A patient history and thorough clinical and radiographic examinations mimic endodontic disease. The implant crowns were removed, bleeding on probing, and peri-implant pockets were observed. The main hypothesis was MRONJ Stage 2, and the surgical treatment was performed. The pain ceased and signs of MRONJ were not observed within 3 months. MRONJ should be considered as a hypothesis in the case of odontalgia and a patient's history of antiresorptive and antiangiogenic therapies. Furthermore, monitoring patients with dental implants in the mandible through detailed clinical and imaging evaluation is required.

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Introduction: The Cuban population is genetically diverse, and information on the prevalence of genetic variants is still limited. As complex admixture processes have occurred, we hypothesized that the frequency of pharmacogenetic variants and drug responses may vary within the country. The aims of the study were to describe the frequency distribution of 43 single-nucleotide variants (SNVs) from 25 genes of pharmacogenetic interest within the Cuba population and in relation to other populations, while taking into consideration some descriptive variables such as place of birth and skin color. Materials and Methods: SNVs were analyzed in 357 unrelated healthy Cuban volunteers. Genotype, allele frequencies, and ancestry proportions were determined, and the pairwise fixation index (FST ) was evaluated. Results: Hardy-Weinberg equilibrium (HWE) deviations in six loci (rs11572103, rs2740574, rs776746, rs3025039, rs861539, and rs1762429) were identified. Minor allele frequencies (MAFs) ranged from 0.00 to 0.15 for variants in genes encoding xenobiotic metabolizing enzymes. They also ranged from 0.01 to 0.21 for variants in DNA repair, growth factors, methyltransferase, and methyl-binding proteins, while they ranged from 0.04 to 0.27 for variants in the O-6-methylguanine-DNA methyltransferase enzyme. Moderate genetic divergence was observed upon comparison to Africans (FST = 0.071 and SD 0.079), with 19 markers exhibiting moderate-to-large genetic differentiation. The average European, African, and Amerindian ancestry proportions were 67.8%, 27.2%, and 5.3%, respectively. Ancestry proportions differed by skin color and birthplace for both African and European components, with the exception of the European component, which showed no significant difference between individuals from Western and Eastern regions. Meanwhile, the statistical significance varied in comparisons by skin color and birthplace within the Amerindian component. Low genetic divergence was observed across geographical regions. We identified 12 variants showing moderate-to-large differentiation between White/Black individuals. Conclusion: Altogether, our results may support national strategies for the introduction of pharmacogenetic tools in clinical practice, contributing to the development of precision medicine in Cuba.

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Effective pest population monitoring is crucial in precision agriculture, which integrates various technologies and data analysis techniques for enhanced decision-making. This study introduces a novel approach for monitoring lures in traps targeting the Mediterranean fruit fly, utilizing air quality sensors to detect total volatile organic compounds (TVOC) and equivalent carbon dioxide (eCO2). Our results indicate that air quality sensors, specifically the SGP30 and ENS160 models, can reliably detect the presence of lures, reducing the need for frequent physical trap inspections and associated maintenance costs. The ENS160 sensor demonstrated superior performance, with stable detection capabilities at a predefined distance from the lure, suggesting its potential for integration into smart trap designs. This is the first study to apply TVOC and eCO2 sensors in this context, paving the way for more efficient and cost-effective pest monitoring solutions in smart agriculture environments.

Assuntos

Tephritidae , Compostos Orgânicos Voláteis , Compostos Orgânicos Voláteis/análise , Animais , Tephritidae/fisiologia , Dióxido de Carbono/análise , Controle de Insetos/métodos , Controle de Insetos/instrumentação

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Recent research has demonstrated the effectiveness of convolutional neural networks (CNN) in assessing the health status of bee colonies by classifying acoustic patterns. However, developing a monitoring system using CNNs compared to conventional machine learning models can result in higher computation costs, greater energy demand, and longer inference times. This study examines the potential of CNN architectures in developing a monitoring system based on constrained hardware. The experimentation involved testing ten CNN architectures from the PyTorch and Torchvision libraries on single-board computers: an Nvidia Jetson Nano (NJN), a Raspberry Pi 5 (RPi5), and an Orange Pi 5 (OPi5). The CNN architectures were trained using four datasets containing spectrograms of acoustic samples of different durations (30, 10, 5, or 1 s) to analyze their impact on performance. The hyperparameter search was conducted using the Optuna framework, and the CNN models were validated using k-fold cross-validation. The inference time and power consumption were measured to compare the performance of the CNN models and the SBCs. The aim is to provide a basis for developing a monitoring system for precision applications in apiculture based on constrained devices and CNNs.

Assuntos

Acústica , Redes Neurais de Computação , Animais , Abelhas/fisiologia , Aprendizado de Máquina , Algoritmos

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BACKGROUND: Pathophysiological changes post-liver transplantation impact the pharmacokinetics and pharmacodynamics of antibiotics. Piperacillin, often used in combination with tazobactam, is a key antibiotic after transplantation to its broad-spectrum activity, but there is a lack of specific pharmacokinetic data in this population. This study aims to describe the pharmacokinetic parameters and target attainment of piperacillin in pediatric liver transplant recipients. METHODS: Patients with preserved renal function (estimated glomerular filtration rate > 50 mL/min/1.73 m2) receiving intravenous piperacillin-tazobactam at 112.5 mg/kg every 8 h (100 mg piperacillin/12.5 mg tazobactam), with a rapid infusion (0.5-1 h), were included. Two blood samples per child were collected during the same interval within 48 h of starting therapy. A Bayesian approach was applied to estimate individual pharmacokinetic parameters and perform dosing recommendations against Enterococcus spp., Enterobacterales and Pseudomonas aeruginosa. RESULTS: Eight patients with median age of 8 months were included. Median piperacillin clearance and central volume of distribution for the cohort were 11.11 L/h/70 kg and 9.80 L/70 kg, respectively. Seven patients (87.5%) presented with concentrations below the target of 100% fT > MIC. Simulations suggested that these patients required more frequent dosing and extended duration of infusion to ensure target attainment. One patient (12.5%) had trough concentrations that exceed 16 mg/L and could receive a lower daily dose. CONCLUSIONS: This case series highlights the importance of personalized therapy in pediatric liver transplant recipients due to the unpredictable and highly variable piperacillin pharmacokinetics in this population.

Assuntos

Antibacterianos , Transplante de Fígado , Combinação Piperacilina e Tazobactam , Piperacilina , Humanos , Masculino , Antibacterianos/administração & dosagem , Antibacterianos/farmacocinética , Antibacterianos/uso terapêutico , Feminino , Lactente , Piperacilina/administração & dosagem , Piperacilina/farmacocinética , Piperacilina/uso terapêutico , Combinação Piperacilina e Tazobactam/administração & dosagem , Combinação Piperacilina e Tazobactam/uso terapêutico , Combinação Piperacilina e Tazobactam/farmacocinética , Pré-Escolar , Teorema de Bayes , Criança

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BACKGROUND: Comprehensive genomic profiling (CGP) identifies genetic alterations and patterns that are crucial for therapy selection and precise treatment development. In Colombia, limited access to CGP tests underscores the necessity of documenting the prevalence of treatable genetic alterations. This study aimed to describe the somatic genetic profile of specific cancer types in Colombian patients and assess its impact on treatment selection. METHODS: A retrospective cohort study was conducted at Clínica Colsanitas S.A. from March 2023 to June 2024. Sequencing was performed on the NextSeq2000 platform with the TruSight Oncology 500 (TSO500) assay, which simultaneously evaluates 523 genes for DNA analysis and 55 for RNA; additionally, analyses were performed with the SOPHiA DDM software. The tumor mutational burden (TMB), microsatellite instability (MSI), and programmed cell death ligand 1 (PDL1) were assessed. RESULTS: Among 111 patients, 103 were evaluated, with gastrointestinal (27.93%), respiratory (13.51%), and central nervous system cancers (10.81%) being the most prevalent. TP53 (37%), KMT2C (28%), and KRAS (21%) were frequent mutations. Actionable findings were detected in 76.7% of cases, notably in digestive (20 patients) and lung cancers (8 patients). MSI was stable at 82.52% and high at 2.91%, whilst TMB was predominantly low (91.26%). CONCLUSIONS: The test has facilitated access to targeted therapies, improving clinical outcomes in Colombian patients. This profiling test is expected to increase opportunities for personalized medicine in Colombia.

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Spectral signatures allow the characterization of a surface from the reflected or emitted energy along the electromagnetic spectrum. This type of measurement has several potential applications in precision agriculture. However, capturing the spectral signatures of plants requires specialized instruments, either in the field or the laboratory. The cost of these instruments is high, so their incorporation in crop monitoring tasks is not massive, given the low investment in agricultural technology. This paper presents a low-cost clamp to capture spectral leaf signatures in the laboratory and the field. The clamp can be 3D printed using PLA (polylactic acid); it allows the connection of 2 optical fibers: one for a spectrometer and one for a light source. It is designed for ease of use and holds a leave firmly without causing damage, allowing data to be collected with less disturbance. The article compares signatures captured directly using a fiber and the proposed clamp; noise reduction across the spectrum is achieved with the clamp.

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This study focuses on semantic segmentation in crop Opuntia spp. orthomosaics; this is a significant challenge due to the inherent variability in the captured images. Manual measurement of Opuntia spp. vegetation areas can be slow and inefficient, highlighting the need for more advanced and accurate methods. For this reason, we propose to use deep learning techniques to provide a more precise and efficient measurement of the vegetation area. Our research focuses on the unique difficulties posed by segmenting high-resolution images exceeding 2000 pixels, a common problem in generating orthomosaics for agricultural monitoring. The research was carried out on a Opuntia spp. cultivation located in the agricultural region of Tulancingo, Hidalgo, Mexico. The images used in this study were obtained by drones and processed using advanced semantic segmentation architectures, including DeepLabV3+, UNet, and UNet Style Xception. The results offer a comparative analysis of the performance of these architectures in the semantic segmentation of Opuntia spp., thus contributing to the development and improvement of crop analysis techniques based on deep learning. This work sets a precedent for future research applying deep learning techniques in agriculture.

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Identifying mutations in cancer-associated genes to guide patient treatments is essential for precision medicine. Circulating tumor DNA (ctDNA) offers valuable insights for early cancer detection, treatment assessment, and surveillance. However, a key issue in ctDNA analysis from the bloodstream is the choice of a technique with adequate sensitivity to identify low frequent molecular changes. Next-generation sequencing (NGS) technology, evolving from parallel to long-read capabilities, enhances ctDNA mutation analysis. In the present review, we describe different NGS approaches for identifying ctDNA mutation, discussing challenges to standardized methodologies, cost, specificity, clinical context, and bioinformatics expertise for optimal NGS application.

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Sensors used in precision agriculture for the detection of heavy metals in irrigation water are generally expensive and sometimes their deployment and maintenance represent a permanent investment to keep them in operation, leaving a lasting polluting footprint in the environment at the end of their lifespan. This represents an area of opportunity to design new biological devices that can replace part, or all of the sensors currently used. In this article, a novel workflow is proposed to fully carry out the complete process of design, modeling, and simulation of reprogrammable microorganisms in silico. As a proof-of-concept, the workflow has been used to design three whole-cell biosensors for the detection of heavy metals in irrigation water, namely arsenic, mercury and lead. These biosensors are in compliance with the concentration limits established by the World Health Organization (WHO). The proposed workflow allows the design of a wide variety of completely in silico biodevices, which aids in solving problems that cannot be easily addressed with classical computing. The workflow is based on two technologies typical of synthetic biology: the design of synthetic genetic circuits, and in silico synthetic engineering, which allows us to address the design of reprogrammable microorganisms using software and hardware to develop theoretical models. These models enable the behavior prediction of complex biological systems. The output of the workflow is then exported in the form of complete genomes in SBOL, GenBank and FASTA formats, enabling their subsequent in vivo implementation in a laboratory. The present proposal enables professionals in the area of computer science to collaborate in biotechnological processes from a theoretical perspective previously or complementary to a design process carried out directly in the laboratory by molecular biologists. Therefore, key results pertaining to this work include the fully in silico workflow that leads to designs that can be tested in the lab in vitro or in vivo, and a proof-of-concept of how the workflow generates synthetic circuits in the form of three whole-cell heavy metal biosensors that were designed, modeled and simulated using the workflow. The simulations carried out show realistic spatial distributions of biosensors reacting to different concentrations (zero, low and threshold level) of heavy metal presence and at different growth phases (stationary and exponential) that are backed up by the whole design and modeling phases of the workflow.

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Cancer is the leading cause of disease-related death among children. Vincristine (VCR), a key component of childhood cancer treatment protocols, is associated with the risk of peripheral neuropathy (PN), a condition that may be reversible upon drug discontinuation but can also leave lasting sequelae. Single nucleotide polymorphism (SNP) in genes involved in VCR pharmacokinetics and pharmacodynamics have been investigated in relation to an increased risk of PN. However, the results of these studies have been inconsistent. A retrospective cohort study was conducted to investigate the potential association of drug transporter genes from the ATP-binding cassette (ABC) family and the centrosomal protein 72 (CEP72) gene with the development of PN in 88 Caucasian children diagnosed with cancer and treated with VCR. Genotyping was performed using real-time PCR techniques for the following SNPs: ABCB1 rs1128503, ABCC1 rs246240, ABCC2 rs717620, and CEP72 rs924607. The results indicated that age at diagnosis (OR = 1.33; 95% CI = 1.07-1.75) and the ABCC1 rs246240 G allele (OR = 12.48; 95% CI = 2.26-100.42) were associated with vincristine-induced peripheral neuropathy (VIPN). No association was found between this toxicity and CEP72 rs924607. Our study provides insights that may contribute to optimizing childhood cancer therapy in the future by predicting the risk of VIPN.

Assuntos

Proteína 2 Associada à Farmacorresistência Múltipla , Proteínas Associadas à Resistência a Múltiplos Medicamentos , Neoplasias , Doenças do Sistema Nervoso Periférico , Polimorfismo de Nucleotídeo Único , Medicina de Precisão , Vincristina , Humanos , Vincristina/efeitos adversos , Vincristina/uso terapêutico , Doenças do Sistema Nervoso Periférico/induzido quimicamente , Doenças do Sistema Nervoso Periférico/genética , Criança , Feminino , Masculino , Proteínas Associadas à Resistência a Múltiplos Medicamentos/genética , Pré-Escolar , Medicina de Precisão/métodos , Neoplasias/tratamento farmacológico , Neoplasias/genética , Adolescente , Estudos Retrospectivos , Proteínas de Ciclo Celular/genética , Lactente , Antineoplásicos Fitogênicos/efeitos adversos , Antineoplásicos Fitogênicos/uso terapêutico , Predisposição Genética para Doença , Genótipo , Alelos , Subfamília B de Transportador de Cassetes de Ligação de ATP/genética , Proteínas Associadas aos Microtúbulos

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SUMMARY: In forensic anthropology, the radius bone has been shown to determine the sex of human remains in a number of different populations. The dry mass and growth of long bones, including the radius, are associated with sex hormone levels; however, the use of bone weight to determine sex has not been sufficiently investigated. The aim of this study was to apply bone morphometric parameters, including maximum length of radius (MLR), circumference at the midshaft of radius (CMR), and weight of radius (WR), to 400 sample radii from a Northeastern Thai population. Univariate and multivariate discriminant functions of all parameters were systemically applied. Equations for calculating sex classification were also determined. Descriptive data analysis showed significant sexual dimorphism in all variables (p < 0.05). The canonical correlation was highest in CMR (0.772) and the ratio of weight to length (0.747). Multivariate discriminant function analysis showed that the measured indices of the right radius were slightly greater than those of the left radius. The parameters demonstrating the highest values of the standardized canonical discriminant function coefficients were CMR (Rt. = 0.496, Lt. 0.431) and WR (Rt. = 0.681, Lt. = 0.715). Moreover, the results of the multivariable (stepwise method) indicated that the best accuracy rates for using combinations of CMR and WR were 94 % (right side) and 92 % (left side). In conclusion, the weight of the radius (rather than the length) is an effective parameter in determining sex.

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En antropología forense, se ha demostrado que el hueso radio determina el sexo de los restos humanos en varias poblaciones diferentes. La masa seca y el crecimiento de los huesos largos, incluido el radio, están asociados con los niveles de hormonas sexuales; sin embargo, el uso del peso de los huesos para determinar el sexo no se ha investigado suficientemente. El objetivo de este estudio fue aplicar parámetros morfométricos óseos, incluida la longitud máxima del radio (LMR), la circunferencia en la mitad del radio (CMR) y el peso del radio (PR), a 400 radios de muestra de una población del noreste de Tailandia. Se aplicaron sistémicamente funciones discriminantes univariadas y multivariadas de todos los parámetros. También se determinaron ecuaciones para calcular la clasificación por sexo. El análisis descriptivo de los datos mostró un dimorfismo sexual significativo en todas las variables (p < 0,05). La correlación canónica fue mayor en CMR (0,772) y la relación peso-longitud (0,747). El análisis de función discriminante multivariante mostró que los índices del radio derecho eran ligeramente mayores que los del radio izquierdo. Los parámetros que demostraron los valores más altos de los coeficientes de la función discriminante canónica estandarizada fueron CMR (Rt. = 0,496, Lt. 0,431) y PR (Rt. = 0,681, Lt. = 0,715). Además, los resultados del método multivariable (método paso a paso) indicaron que las mejores tasas de precisión al usar combinaciones de CMR y PR fueron del 94 % (lado derecho) y del 92 % (lado izquierdo). En conclusión, el peso del radio (más que la longitud) es un parámetro eficaz para determinar el sexo.

Assuntos

Humanos , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Idoso , Adulto Jovem , Rádio (Anatomia)/anatomia & histologia , Determinação do Sexo pelo Esqueleto , Tailândia , Análise Discriminante , Antropologia Forense , Confiabilidade dos Dados

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Rheumatoid arthritis (RA) is a multifactorial autoimmune inflammatory disease that mainly affects the joints, on reducing functional capacity and impacting quality of life. Cytokines such as tumor necrosis factor (TNF) and interleukin 6 (IL-6) are crucial in the pathogenesis and treatment of this disease. Some patients using TNF inhibitors (TNFi) do not respond or lose their response to these medications. Clinical, sociodemographic, and genetic data were used to evaluate the associations of single nucleotide polymorphisms (SNP) in TNF, TNFRSF1A, and TNFRSF1B genes with the diagnosis of RA, standardized score results, laboratory tests, and response to TNFi. In one subsample, TNF and IL-6 serum levels cytokines were performed. A total of 654 subjects (360 healthy controls and 294 diagnosed with RA) were included in the analysis. Higher levels of TNF have been found in individuals diagnosed with RA. IL-6 levels were higher in individuals who did not respond to TNFi treatment, while responders had levels comparable to those without the disease. No associations were found between the SNPs studied and the diagnosis of RA; however, rs767455-C seems to play a role in the response to golimumab treatment, being related to better therapeutic response and lower mean serum leukocyte levels. In addition, rs1061622-G was associated with poorer functional capacity and rs1800629-A was associated with higher leukocyte values and serum transaminase levels. The rs1061622-G and rs767455-C may play a role in the response to TNFi treatment, especially for patients using golimumab, although they do not seem to be associated with the diagnosis of RA. Polymosphisms in the TNF pathway may impact baseline levels of immune cells and markers of renal and hepatic function in RA patients. Our results highlight the importance of evaluating the impact of these polymorphisms on TNFi response and safety, particularly in larger-scale studies.

Assuntos

Artrite Reumatoide , Interleucina-6 , Polimorfismo de Nucleotídeo Único , Receptores Tipo II do Fator de Necrose Tumoral , Inibidores do Fator de Necrose Tumoral , Fator de Necrose Tumoral alfa , Humanos , Artrite Reumatoide/genética , Artrite Reumatoide/tratamento farmacológico , Feminino , Masculino , Pessoa de Meia-Idade , Fator de Necrose Tumoral alfa/genética , Interleucina-6/genética , Interleucina-6/sangue , Receptores Tipo II do Fator de Necrose Tumoral/genética , Inibidores do Fator de Necrose Tumoral/uso terapêutico , Adulto , Receptores Tipo I de Fatores de Necrose Tumoral/genética , Idoso , Estudos de Casos e Controles , Antirreumáticos/uso terapêutico

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Endometrial cancer (EC) is a heterogeneous disease with a rising incidence worldwide. The understanding of its molecular pathways has evolved substantially since The Cancer Genome Atlas (TCGA) stratified endometrial cancer into four subgroups regarding molecular features: POLE ultra-mutated, microsatellite instability (MSI) hypermutated, copy-number high with TP53 mutations, and copy-number low with microsatellite stability, also known as nonspecific molecular subtype (NSMP). More recently, the International Federation of Gynecology and Obstetrics (FIGO) updated their staging classification to include information about POLE mutation and p53 status, as the prognosis differs according to these characteristics. Other biomarkers are being identified and their prognostic and predictive role in response to therapies are being evaluated. However, the incorporation of molecular aspects into treatment decision-making is challenging. This review explores the available data and future directions on tailoring treatment based on molecular subtypes, alongside the challenges associated with their testing.

Assuntos

Biomarcadores Tumorais , Neoplasias do Endométrio , Instabilidade de Microssatélites , Humanos , Neoplasias do Endométrio/genética , Neoplasias do Endométrio/patologia , Neoplasias do Endométrio/terapia , Neoplasias do Endométrio/metabolismo , Feminino , Biomarcadores Tumorais/genética , Mutação , Patologia Molecular , Prognóstico , Proteína Supressora de Tumor p53/genética , Proteína Supressora de Tumor p53/metabolismo

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Colorectal cancer is one of the most common cancers worldwide. Lymph node metastasis is an important marker of colorectal cancer progression and plays a key role in the evaluation of patient prognosis. Accurate preoperative assessment of lymph node metastasis is crucial for devising appropriate treatment plans. However, current clinical imaging methods have limitations in many aspects. Therefore, the discovery of a method for accurately predicting lymph node metastasis is crucial clinical decision-making. DNA methylation is a common epigenetic modification that can regulate gene expression, which also has an important impact on the development of colorectal cancer. It is considered to be a promising biomarker with good specificity and stability and has promising application in predicting lymph node metastasis in patients with colorectal cancer. This article reviews the characteristics and limitations of currently available methods for predicting lymph node metastasis in patients with colorectal cancer and discusses the role of DNA methylation as a biomarker.

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Through enviromics, precision breeding leverages innovative geotechnologies to customize crop varieties to specific environments, potentially improving both crop yield and genetic selection gains. In Brazil's four southernmost states, data from 183 distinct geographic field trials (also accounting for 2017-2021) covered information on 164 genotypes: 79 phenotyped maize hybrid genotypes for grain yield and their 85 nonphenotyped parents. Additionally, 1342 envirotypic covariates from weather, soil, sensor-based, and satellite sources were collected to engineer 10 K synthetic enviromic markers via machine learning. Soil, radiation light, and surface temperature variations remarkably affect differential genotype yield, hinting at ecophysiological adjustments including evapotranspiration and photosynthesis. The enviromic ensemble-based random regression model showcases superior predictive performance and efficiency compared to the baseline and kernel models, matching the best genotypes to specific geographic coordinates. Clustering analysis has identified regions that minimize genotype-environment (G × E) interactions. These findings underscore the potential of enviromics in crafting specific parental combinations to breed new, higher-yielding hybrid crops. The adequate use of envirotypic information can enhance the precision and efficiency of maize breeding by providing important inputs about the environmental factors that affect the average crop performance. Generating enviromic markers associated with grain yield can enable a better selection of hybrids for specific environments.

RESUMO

Behavior analysis is a widely used non-invasive tool in the practical production routine, as the animal acts as a biosensor capable of reflecting its degree of adaptation and discomfort to some environmental challenge. Conventional statistics use occurrence data for behavioral evaluation and well-being estimation, disregarding the temporal sequence of events. The Generalized Sequential Pattern (GSP) algorithm is a data mining method that identifies recurrent sequences that exceed a user-specified support threshold, the potential of which has not yet been investigated for broiler chickens in enriched environments. Enrichment aims to increase environmental complexity with promising effects on animal welfare, stimulating priority behaviors and potentially reducing the deleterious effects of heat stress. The objective here was to validate the application of the GSP algorithm to identify temporal correlations between heat stress and the behavior of broiler chickens in enriched environments through a proof of concept. Video image collection was carried out automatically for 48 continuous hours, analyzing a continuous period of seven hours, from 12:00 PM to 6:00 PM, during two consecutive days of tests for chickens housed in enriched and non-enriched environments under comfort and stress temperatures. Chickens at the comfort temperature showed high motivation to perform the behaviors of preening (P), foraging (F), lying down (Ld), eating (E), and walking (W); the sequences <{Ld,P}>; <{Ld,F}>; <{P,F,P}>; <{Ld,P,F}>; and <{E,W,F}> were the only ones observed in both treatments. All other sequential patterns (comfort and stress) were distinct, suggesting that environmental enrichment alters the behavioral pattern of broiler chickens. Heat stress drastically reduced the sequential patterns found at the 20% threshold level in the tested environments. The behavior of lying laterally "Ll" is a strong indicator of heat stress in broilers and was only frequent in the non-enriched environment, which may suggest that environmental enrichment provides the animal with better opportunities to adapt to stress-inducing challenges, such as heat.

RESUMO

Jataí is a pollinator of some crops; therefore, its sustainable management guarantees quality in the ecosystem services provided and implementation in precision agriculture. We acquired videos of natural and artificial hives in urban and rural environments with a camera positioned at the hive entrance. In this way, we obtained videos of the entrance of several colonies for multiple bee tracking and removed images from the videos for bee detectors. This data, their respective labels, and metadata make up the dataset. The dataset displays potential for utilization in computer vision tasks such as comparative studies of deep learning models. They can also integrate intelligent monitoring systems for natural and artificial hives.