This paper presents a novel method for determining parameters and uncertainty bands of nonlinear functions fitted to data obtained from measurements. In this procedure, one or two new variables are implemented to linearize this function for using the linear regression method. The best parameters of the straight-line in new variables are adjusted to the transformed coordinates of tested points according to the weighted total mean square criterion WTLS, or WTLS-C of data points are also correlated. Uncertainties of measured points are found according to the rules of the GUM Guide. The parameters and the uncertainty band of the nonlinear function result from the parameters of this straight line and of its uncertainty band. A few examples determining the parameters and uncertainty bands of different types of nonlinear functions are presented. There are also examples of measurements using the presented method and conclusions.

The paper looks into the turbulent history of the ancient town of Akrai/Acrae in a mountainous part of southeastern Sicily, encapsulated in the assemblage of finds from a domestic cistern, which was remodeled and adapted in the course of its use. The cistern is considered as an architectural feature against the background of the ancient town, and the assemblage recovered from it is exmined thoroughly category by category, giving insight into the life of the ancient inhabitants of this island in the Mediterranean.

In the article we present the current state of research on triglycine sulfate (TGS) – one of the flagship materials used in active thermal detectors of infrared radiation (IR). A description of the second-order phase transition in TGS is provided. The methods for measuring the relevant electrical parameters of IR sensors based on TGS are presented, focusing on their application in thermal detection of IR radiation. The article is based on available literature and the results of our own research.

The sensor described here enables measurement of temperature avoiding semiconductor-fiber coupling losses as we have in conventional fiberoptic temperature sensor. Response time of the sensor increases and it is rugged and inexpensive.

Dynamic mechanical analysis is widely used to characterize viscoelastic materials, yet the physical origin of the measured phase shift remains only partially understood for structurally extended specimens. Its standard interpretation typically assumes a single, effective phase shift between applied stress and strain. In this work, we investigate the temperature-dependent viscoelastic response of medical- grade acrylonitrile butadiene styrene (ABS) fabricated by fused filament fabrication and injection molding, combining DMA measurements, fractographic analysis, and analytical modeling. Rectangular beam specimens were subjected to three-point bending DMA over a tempera- ture range spanning the glass transition region. The storage modulus, loss modulus, and phase shift were determined as functions of tem- perature and compared between manufacturing routes. While both materials exhibit nearly identical glass transition temperatures, the 3D- printed samples exhibit a modest reduction in storage modulus, reflecting microstructural heterogeneity introduced by the layer-wise fabri- cation process. Fractographic observations reveal characteristic interlayer features and microvoids that correlate with the observed mechan- ical response. To interpret the temperature-dependent phase shift, we develop a theoretical model of a damped vibrating beam in which each eigenmode contributes with its own phase shift. By introducing a temperature-dependent effective damping coefficient, the model’s mode-averaged phase shift reproduces the experimental DMA data with high accuracy. By linking DMA phase measurements to the mode dynamics of the tested structure, the proposed framework establishes DMA as a structure-sensitive dynamical probe and is applicable to a broad class of polymer, composite, and additively manufactured materials.

Przedstawiono nowy algorytm do badania porowatości włóknin. Algorytm zawiera przetwarzanie obrazu podświetlanej włókniny. Na obrazie są zaznaczone jasne obszary, co oznacza rozrzedzoną dystrybucję włókien. Ponieważ włókniny są używane między innymi jako materiały medyczne i filtracyjne, ich struktura ma znaczący wpływ na ich właściwości fizyczne. Zadaniem oprogramowania jest przede wszystkim określenie porowatości materiału. The new algorithm to study the properties of nonwoven fabrics is presented in the paper. The algorithm consists in image processing of the image of the highlighted nonwoven fabric. From the image there are selected the bright areas, which means sparse distributions of the fibers. Because nonwoven fabrics are used, among others, as medical and filtration materials their structure has significant impact on their ownership. The software task is primarily determine the porosity of the material.