ABSTRACT Purpose Acinic cell carcinoma (ACC) of the breast is a very rare, primary salivary gland‐type breast malignancy, with ~100 reported cases in the literature. Limited information about the clinical features and outcomes of patients with ACC is available. Methods We utilized the Surveillance, Epidemiology, and End Results (SEER) database to identify ACC patients. For comparison, we also examined a cohort of invasive breast carcinomas of no special type (NST). Results Thirty ACC patients were identified among the more than 248 000 invasive breast carcinoma NST patients. ACCs were predominantly grade 3 carcinomas (44%) and were diagnosed at an earlier stage (67%). Hormone receptor (HR) and HER2 status data were available for only 13 patients, revealing molecular heterogeneity: HR−/HER2− (four patients), HR−/HER2+ (two patients), HR+/HER2− (four patients), and HR+/HER2+ (three patients). The median survival time for ACC patients was 19 months vs. 48 months for NST patients (p < 0.001). A complete‐case approach was utilized for the adjusted analyses, restricting the sample to 46 257 patients without missing data on all relevant covariates. The adjusted Kaplan–Meier analysis indicated a more pronounced decline in survival probabilities among patients with ACC compared to those with NST, with the number at risk in the ACC group diminishing to four patients by the 30‐month mark. In contrast, NST patients exhibited a more gradual decrease. In the multivariable Cox regression, which adjusted for age, TNM stage, HR/HER2, and chemotherapy, ACC histology was correlated with a 1.69‐fold increase in the hazard of death (HR: 1.69; 95% CI: 0.63–4.56), although this result was not statistically significant. Age and advanced stage continued to be strong predictors of poor survival, and the inclusion of an age–time interaction enhanced the model fit. Conclusion Acinic cell carcinoma of the breast is a very rare primary breast malignancy. Our study indicates potentially aggressive clinical behavior in mammary ACC; however, findings must be interpreted cautiously given inherent SEER limitations, especially regarding histologic and molecular subtyping accuracy. Further centralized studies are urgently needed for the accurate characterization of this rare entity.

Cutting processes, in general, and wood cutting processes in particular, are complex to explain and describe, depending on a number of influencing factors such as material characteristics, cutting tool geometry and cutting parameters. A thorough understanding of the characteristics of woodworking machining, such as cutting tool wear, cutting forces, energy consumption, and cutting tool stress, gives the opportunity to improve product quality, increase production efficiency, or improve the technological process. In this paper, some characteristic parameters of processing in flat, extensive milling of solid wood of different species are analysed in order to determine the significance of the selected parameters, as well as their mutual influences on the required cutting power.

The research aims to improve the durability and functionality of traditional wooden structures through innovative technologies, reducing the ecological footprint and enhancing the economic viability of local materials. The model benches are made from five different types of indigenous conifer wood: Norway spruce, scots pine, larch, thermally modified spruce, and spruce treated with a copper-ethanolamine based biocide. Sensors installed on the benches allow continuous monitoring of wood moisture, a key factor in determining material durability under specific climatic conditions. Collected data will enable the evaluation of optimal wood types for various climatic conditions, promoting the wider use of indigenous, environmentally renewable materials. The project also aims to connect the wood protection industry with end-users, fostering sustainable approaches to environmental preservation, cultural landscapes, and wooden heritage. The research results support the application of wood materials in sectors such as agriculture, maritime transport, and tourism, contributing to ecologically sustainable and economically efficient use of natural resources.

Fire resistance of wood materials is crucial for the safety and longevity of construction structures, with spruce wood (Picea abies spp.) being widely used due to its mechanical properties. However, its natural fire resistance is limited, which poses a challenge in the context of fire safety. This study investigates the effects of various treatments and additives on enhancing the fire resistance of spruce wood. The methodology includes testing fire resistance using the small flame test in accordance with relevant standards. The expected results could contribute to improving safety standards in the construction industry, enabling broader and safer application of spruce wood in fire-sensitive constructions. Surface roughness analysis revealed significantly smoother surfaces in treated samples (Sa = 9.03 μm) compared to untreated sawn samples (Sa = 84.54 μm), which contributed to reduced combustion intensity. In small flame tests, untreated samples exhibited visible flames with flame heights up to 13.5 cm, whereas Burn Block treated samples showed no flame development and minimal color changes. Interestingly, burning depth was greater on treated samples, reflecting surface carbonization and the formation of a protective intumescent layer that slowed heat transfer and prevented deeper structural damage.

In this paper, we will process the results of experimental and numerical analysis on the example of the boom of a machine tool - a rotary excavator. Rotary excavator SRs 1200/630 KW - 22/2, engine no. 1, field “D”, produced by “LAUHAMER” - German Democratic Republic, is intended for mining coal and tailings at the surface mine of the JP RB “KOLUBARA” Lazarevac mine. During the regular overhaul and after 35 years of operation of the rotary excavator, it was concluded that it would be necessary to assess the stress and deformation state of both the rotary excavator as a whole and its vital parts individually (primarily the excavator booms) through adequate tests. The goal is to determine the critical points on the arrow structure after the tests have been carried out and act preventively to avoid accidents and additional unnecessary costs. By comparing the experimental and numerical results, we obtained a representation of the stresses and strains on the shaft construction and defined the critical stresses and strains.

Mathematical modeling is a key tool in engineering as it enables the analysis and prediction of material behavior under specific conditions. This study focuses on material strength, which is one of the most critical aspects of engineering design and manufacturing. Understanding material strength is essential for ensuring the reliability and safety of structures and products. The structure of the paper includes a theoretical overview of the fundamentals of mathematical modeling and regression analysis, a detailed description of the experimental research, the development of a model based on collected data, and the evaluation of the obtained mathematical model. Testing was conducted using a tensile testing machine, with samples of standard dimensions in accordance with EN 10002.

In this paper, a comparison between serverless databases and conventional data storage models is discussed, with a focus placed on architectural differences, performance measures, cost-benefit analysis, and use case applicability. In cloud-native applications, the use of serverless databases, in which resources are dynamically allocated as needed, is increasingly observed. In contrast, traditional databases require manual operations for infrastructure provisioning and maintenance. Situations in which serverless databases are preferable, as well as those where traditional approaches remain suitable, are characterized in this work. A guide for selecting a database system in modern computing environments is provided, based on an evaluation of systems such as AWS Aurora Serverless, Firebase, PostgreSQL, and MongoDB.

Dynamic analysis can be used to determine dynamic displacements, time history, and the frequency content of loads. One of the analytical techniques for calculating the linear response of structures to dynamic loading is modal analysis. In modal analysis, the structural response is decomposed into several modes of oscillation. A mode is defined by its frequency and shape. Engineers refer to the mode with the lowest frequency (longest period) as the fundamental mode of oscillation. This paper presents Holzer’s approximate method for determining the modes and periods of oscillation for frame structures. The proposed approximation method, based on the relative stiffness of floors and the ground level, is also analyzed. The results obtained using the proposed approximate procedure do not significantly deviate from those obtained through more precise calculations. Therefore, it is emphasized that the method can be used both in practice and for verifying computer analyses of complex systems.