The efficient use of municipal waste is becoming increasingly important for sustainable environmental quality. An integral part of the process of recycling waste material is its quality sorting. Nowadays, both manual and automated sorting methods, especially optical sorting, are used worldwide for sorting mixed waste. This article presents the application of the NIR/VIS optical sorting system through a description of this processing equipment integrated into a specific plastic waste processing line. The aim of the article was to select the optimal mode of operation generally applicable to mixed waste, and, specifically, to compare the quality of sorting of plastic waste in automated and manual sorting modes. In order to compare the efficiency of the sorting system, significant parameters of the sorting process were proposed. The measurement of the plastic waste sorting purity parameter was based on data obtained by weighing selected control samples, and the evaluation of the results of these measurements showed, in particular, the dependence of the concerned parameter not only on the sorting mode, i.e., automated and manual, but also on the conveyor belt speed/waste material flow, on the pre-sorting methods and, in the case of manual sorting, on the operating shift. The subsequent economic assessment of both sorting processes clearly declared the investment in automated sorting systems in the optical system operation mode not only as profitable, but also as extremely advantageous both for the production economy and the environment.

Polyamide 12 (PA 22000) is a well-known material and one of the most biocompatible materials tested and used to manufacture customized medical implants by selective laser sintering technology. To optimize the implants, several research activities were considered, starting with the design and manufacture of test samples made of PA 2200 by selective laser sintering (SLS) technology, with different processing parameters and part orientations. The obtained samples were subjected to compression tests and later to SEM analyses of the fractured zones, in which we determined the microstructural properties of the analyzed samples. Finally, an evaluation of the surface roughness of the material and the possibility of improving the surface roughness of the realized parts using finite element analysis to determine the optimum contact pressure between the component made of PA 2200 by SLS and the component made of TiAl6V4 by SLM was performed.

Composite materials reinforced with recycled fibers gather a great deal of interest with regards to construction applications. A novel polymer concrete composite was proposed, comprised of a surface layer and a structural composite reinforced with recycled glass fibers. The novel multi-material composite included a large amount of glass-fiber-reinforced polymer (GFRP) waste (30%), which is expected to help protect the environment. Large panels comprised of this polymer concrete composite, which reproduce the appearance of natural stone, were manufactured. A new methodology for porosity analysis of a large panel comprised of a multi-material composite was proposed, utilizing three-dimensional (3D) X-ray computed tomography (CT). The volume of pores was distributed between the constituent composite materials and then statistically analyzed. Homogeneous distribution of the pores within the novel multi-material composite was found. The observed mean porosities of the composite panel were 0.146% for the surface layer material and 31.3% for the structural composite material. The mean density of the panel, determined by the CT density method, was 1.73 g/cm³. The composite materials porosity provides a favorable effect for achieving lightweight structures. Using scanning electron microscopy (SEM) analysis, it was observed that a good connection interface between the constituent composite materials existed.

Surging electricity demand, its limited supply, and the pandemic crisis are just some of the key factors that resulted in changes in electricity prices on the power exchanges. This topic brings about a notable economic influence on both producers and consumers. The main purpose of this paper is to explore power price volatility during the four-year period from 1 January 2018 to 31 December 2021, in 28 power exchanges in Europe, measured using daily velocity data. In addition, based on the fixed and chain base index numbers, as well as their relative merits, this paper was designed to measure the gap and convergence in trends. Considering that the price volatility varies depending on the observation period, this paper performs a comparative analysis of electricity price volatility on a daily, monthly, quarterly, and annual level for all examined countries. The obtained results indicate that electricity price volatility is higher on a daily basis. Related to this, convergent trends are demonstrated on all 28 observed markets, and there is a growing trend of hourly spot prices in the analyzed four-year period. The results of this paper also confirm a higher power price volatility during the pandemic period in 2020 and 2021 compared to the prepandemic period during 2018 and 2019.

Mechanical behavior and characteristics of two different types of materials: cast iron with lamellar graphite EN-GJL-250 and cast iron with spheroidal graphite EN-GJS-400-15 which were cast in ceramic molds using gravitational casting method has considered in this research. The ceramic molds were obtained by 3D printing method. First, a finite element analysis was developed to determine Tresca and von Mises stresses and the deformations of the ceramic molds under an applied pressure of 25 MPa. Samples were produced by gravitational casting using two types of cast iron materials. Mechanical tests were made using samples produced from these two types of materials and microstructure analysis evaluation of fractured zones was realized by scanning electron microscopy. Obtained results were finally used for designing, developing, and producing of one ‘hydraulic block’ of a railway installation by the Benninger Guss company of Switzerland.

Patient-specific 3D models of the human mandible are finding increasing utility in medical fields such as oral and maxillofacial surgery, orthodontics, dentistry, and forensic sciences. The efficient creation of personalized 3D bone models poses a key challenge in these applications. Existing solutions often rely on 3D statistical models of human bone, offering advantages in rapid bone geometry adaptation and flexibility by capturing a range of anatomical variations, but also a disadvantage in terms of reduced precision in representing specific shapes. Considering this, the proposed parametric model allows for precise manipulation using morphometric parameters acquired from medical images. This paper highlights the significance of employing the parametric model in the creation of a personalized bone model, exemplified through a case study targeting mandibular prognathism reconstruction. A personalized model is described as 3D point cloud determined through the utilization of series of parametric functions, determined by the application of geometrical morphometrics, morphology properties, and artificial neural networks in the input dataset of human mandible samples. With 95.05% of the personalized model’s surface area displaying deviations within −1.00–1.00 mm relative to the input polygonal model, and a maximum deviation of 2.52 mm, this research accentuates the benefits of the parametric approach, particularly in the preoperative planning of mandibular deformity surgeries.