Tetracycline antibiotics are widely used in cattle to treat and prevent bacterial infections, including enteric and systemic diseases. They are also used to treat bovine mastitis, which affects milk quality and productivity. Improper or excessive use can leave antibiotic residues in animal products, posing a public health risk and promoting antimicrobial resistance. In this study, we examined oxytetracycline (OTC) residues in raw cow’s milk from the semi-arid region of Alagoas, Northeastern Brazil. We used a paper-based microdevice (μPAD) with copper nanoparticles (CuNPs). Milk samples were collected from all four teats of 30 randomly selected Girolando cows across different rural properties. The method performed well, showing a linear response from 1 to 25 μg mL⁻1 and a high correlation coefficient (R2 = 0.99946). The recovery rate was 94.70
Manual testing, in which testers follow natural language instructions to validate system behavior, remains essential for uncovering issues that are difficult to capture with automation. However, manual test cases often contain test smells, quality issues such as ambiguity, redundancy, or missing checks that reduce reliability, maintainability, and reproducibility. Existing detection approaches largely depend on manually engineered rules and thus struggle to generalize and scale across heterogeneous test suites. In our previous work, we assessed the feasibility of using Small Language Models (SLMs) for test smell detection by evaluating GEMMA-3-4B, LLAMA-3.2-3B, and PHI-4-14B on test steps from 143 real-world Ubuntu test cases, covering seven smell types. PHI-4-14B achieved the best performance. In this article, we investigate whether a contemporary Large Language Model (GEMINI-3-PRO-PREVIEW) available at the time of the study can identify test smells in natural language manual test cases using a prompt-based, whole-test-case analysis strategy. Unlike approaches that analyze individual test steps in isolation, our approach evaluates complete test cases, enabling the model to consider relationships and dependencies among test steps. We evaluate the approach on 100 Ubuntu test cases covering seven test smell types and compare its performance against previously evaluated SLMs, including GEMMA-3-4B, LLAMA-3.2-3B, and PHI-4-14B. Our results show that GEMINI-3-PRO-PREVIEW outperforms the SLMs, while producing actionable explanations that can help practitioners revise manual test cases for greater clarity and consistency. We also find that test smells are pervasive in practice, with nearly one detected test smell per step on average, highlighting the need for scalable and automated quality support for manual testing artifacts.
Soil aggregation is a fundamental process that influences various soil properties, including structure, porosity, water infiltration, and resistance to erosion. In the Caatinga biome, preserving the soil's physical quality is crucial to the development of sustainable agriculture. In this biome, soil aggregation is critical due to the susceptibility of the semi-arid area to erosion and degradation. This study aims to evaluate the impact of converting native vegetation (NV; dense Caatinga) into two grasslands and two integrated livestock-forestry (ILF) systems on soil organic carbon (SOC) content and soil physical quality through water-stable aggregate (WSA) classes (macroaggregates, mesoaggregates, and microaggregates) and aggregation indices (mean weight diameter (MWD), geometric mean diameter (GMD), and aggregate stability index (ASI)). Soil samples were collected at 0–10, 10–20, 20–30, 30–50, 50–70, and 70–100cm layers in Nossa Senhora da Glória Municipality, Sergipe State, Brazil. The land use systems analyzed in this study included NV, an ILF system with Gliricidia (Gliricidia sepium (Jacq.) Kunth ex Walp.)+Urochloa (Urochloa decumbens (Stapf) R.D. Webster) under no-tillage (ILFug), another ILF system with Gliricidia+forage cactus (Opuntia cochenillifera (Linnaeus) Miller) under convention tillage (ILFcg), improved pasture (ImpP), and degraded pasture (DegP). Almost all parameters studied were significantly correlated with SOC content, demonstrating that soil organic matter (SOM) is a primary agent in binding soil particles together, influencing the variation in WSA and aggregation indices. The ImpP and DegP exhibited similar SOC content; however, the ImpP showed a higher ASI and increased amount of macroaggregates (particle diameter>2.000mm). The highest SOC content was found in the ILFug system across the soil profile. There was a predominance of macroaggregates in topsoil (0–10cm layer) regardless of land use, with the highest proportion found in NV (78.7%); while the lowest was observed in the ILFcg system (59.0%). The ILFug system also showed the greatest ASI at almost all soil layers; the exception was the 0–10 and 50–70cm layers, where the NV had the highest values of 89.1% and 90.5%, respectively. This study demonstrates that implementing integrated systems under no-tillage as a nature-based solution can enhance SOC content and stability of soil aggregates in semi-arid environments.
The low solubility of propolis in water and its limited bioavailability reduce the effectiveness of bioactive compounds, demonstrating the necessity of techniques that can overcome these limitations. Spray-drying is a promising approach to overcoming these challenges. In this study, microparticulate systems containing greenish-brown propolis extract were produced and characterised. The following analyses were performed: antioxidant activity; total phenol and flavonoid content; UV–Vis and FTIR spectroscopy; thermal analysis; scanning electron microscopy (SEM); and in vitro dissolution tests. The extracts and microparticles exhibited a total flavonoid content of 5.15
The development of behavioral control studies for Thyrinteina arnobia (Stoll, 1782) (Lepidoptera: Geometridae) involves the elucidation of the chemical ecology, which begins with the observation of the calling sexual behavior through the exposure of females abdominal gland. After the pheromone release, the perception of chemical substances is carried out in the sensilla of male antennae, whose characterization can be carried out using scanning electron microscopy (SEM). Thus, this research aimed to ultrastructurally characterize the antennal sensilla of males and females of T. arnobia. For the characterization of the structural morphology of the sensilla in the antennae of females and males of T. arnobia, scanning electron microscopy was used. In total, six types of sensilla were identified, and characterized in trichoid, squamiform, caetic, basiconic, celoconic and styloconic. The antennae of female and male T. arnobia have different structural morphology of sensilla. The trichoid sensilla are the most abundant, mainly in the antennae of males, indicating that they can respond to stimuli from chemical substances, since these sensilla are recognized for their sex pheromone receptor function. The present study allows a better understanding of the sexual dimorphism between female and male T. arnobia.
