This paper presents the results of voluminous experimental investigations conducted to analyze the influence of the welding procedure on the performance of regenerated gears. Cylindrical spur gears were tested, both newly manufactured and regenerated, in two fundamentally different ways: by hard facing (surfacing) with the “hard” filler metal (DUR 600-IG) and with the “soft” filler metal (EVB2CrMo) with subsequent cementation and quenching. The regeneration procedures were defined and executed, while, subsequently, the microstructure and microhardness of the hard-faced layers were established and measured, followed by checking the durability of the hard-faced teeth flanks. Finally, techno-economic analysis was performed to establish the rationality of the conducted regenerations, i.e., the costs of regenerated and newly manufactured teeth were compared. Based on the results of the conducted investigations, it was possible to establish the influence of the welding type on the performance characteristics (primarily the service life) of the regenerated gears. For individual reparatory hard facing, the procedure with the “hard” filler metal exhibited better characteristics, while for batch reparation of numerous damaged gears, the reparation with the “soft” filler metal, followed by cementation and heat treatment, might be more convenient. The gears transfer the load through the teeth, i.e., the active parts of their flanks. The load transfer is accompanied by the relative movement of the gear and pinion teeth with mutual sliding and rolling. In this way, the stress of the surface layers, caused by the contact (Hertz) pressures, appears on the teeth flanks, while the flanks of the teeth slide at the same time. The bending stress occurs at the teeth base.Statistical data show that in the gear transmission elements, newly manufactured, most damages appear on gears, followed by failures of bearings, while failures of other parts of the power transmitters are significantly less common. That is the primary reason why many researchers paid special attention to the phenomena of the damage and destruction of gear teeth, their character, the causes for their appearance and the possibility of eliminating those causes ,2,3,4,5.The aim of this paper was to point out the numerous advantages of the regeneration process of damaged gear parts and to show how to carefully select the optimal welding technology and additional material, on a concrete example of reparation by welding. In addition, the authors pointed out the techno-economic benefits coming from application of the regeneration process through numerous parameters, such as exploitational reliability and economic justification. It is pointed out that regeneration can not only restore the function to the part but even achieve better properties than those originally possessed by the base material. This paper’s results can be useful for all the researchers and engineers dealing with these areas to opt for the regeneration of damaged parts more easily, with a detailed analysis of the gear regeneration process. In continuation of the introduction, a brief analysis of works in this field is given.Durmus et al. investigated the wear resistance of iron-based hard-faced coatings that were produced with Fe-Cr-C-B- and Fe-Cr-C-based filler metal (FM) wires, according to the ball-on-disc and dry sand/rubber wheel wear tests . Iron-baLi et al. studied the influence of a rare-earth (RE) oxide addition to the electrode coating for hard facing of a large gear and investigated the microstructures of the hard-faced specimens with and without the RE oxide . During 2O3 and d-Fe and Ce2O2S and d-Fe were increasing with the further increase in the rare-earth oxide addition.Similar to previous research, Hao et al. developed electrodes for hard facing of medium carbon steel with six additions of a rare-earth (RE) oxide . They stXing et al. prepared hard facing alloys with different amounts of Ceria by self-shielded flux-cored arc welding . The basThe purpose of the work by Gualco et al. was to study the microstructural evolution and wear resistance of a nanostructured iron-based alloy deposited by the FCAW (flux-cored arc welding) process . They evSuraj discussed different methods to evaluate the wear and corrosion resistance properties of mild steels, such as EN-8, EN-9 and EN-24, by calculating their corrosion rate . He usedCzuprynski studied the metal-mineral-type abrasive wear of a wear-resistant plate, made by a tubular electrode with a metallic core and an innovative chemical composition, using the manual metal arc hard facing process . The proJosifović and Marković laid down some theoretical considerations on gears’ regeneration in general, emphasizing advantages of hard facing as the reparation procedure, especially from the aspect of economic effectiveness ,14.Lazić et al. conducted an educated selection of hard facing technology, related to the complex procedure of checking the quality of the hard-faced layer . They coMarković, on the other hand, also considered the tribological characteristics of gears regenerated by hard facing . His resPopovic et al. executed the surface welding of rail steel with self-shielded wire, with different heat inputs, and investigated the influence of the welding heat input on the total impact energy and its components, crack growth rate and fracture mechanisms . They shArsić et al. performed an investigation to show which filler metal is the best for hard facing of parts of the construction mechanization and parts subjected to intensive abrasive wear at stone mines . Since t10 to 10 × 1010 cycles). Their samples were coated by electrolytic coatings and the effect of those coatings on the fatigue properties of the material under an ultra-high cycle was determined.Ulewicz and Novy  studied Vicen et al.  investigTrsko et al.  tested tVicen, Bronček and Novy  presenteCleaning, washing and degreasing of the gear;Identification of the type, size, character and position of the damage;Classification of the gear, based on comparison of the damage detection results and requirements from the technical documentation to correct gears intended for regeneration and for rejection (scrap);Selection of the optimal regeneration method;Defining the regeneration technological procedure;Preparation for regeneration;Executing the prescribed regeneration procedure;Machining the regenerated surfaces;Performing the strengthening procedures of the teeth working parts and other functional surfaces;Final machining—grinding;Final control and testing of the regenerated gear.Basically, the technological procedure of a gear’s regeneration consists of the following operations :CleaningPrevious research in the field of gear regeneration has shown that reparatory hard facing of the damaged working surfaces is the most reliable method for the renewal of the shapes, dimensions and working performances of the teeth. For the proper selection of an adequate method for reparatory hard facing, it is necessary to know the mechanisms of the contact surfaces’ wear. The regeneration itself is a complex process consisting of numerous technological operations, whose order of execution is particularly important and precisely defined.Material for manufacturing—steel 20MnCr5;Module m = 6 mm;Number of teeth z = 43;Base profile angle α = 20°;Tooth profile angle β = 0°;m = 0;Profile correction xf = 243.6 mm;Root circle diameter dCircular pitch 18.84 mm.The cylindrical spur gears, of the following characteristics, were used as samples for testing :MaterialThe base material, used for samples in these experiments, was steel for cementation 20MnCr5, whose marks according to different standards and chemical composition are given in Hard facing by the “hard” filler metal DUR 600-IG (according to EN14700-EFe8) ;Hard facing by the “soft” filler metal EVB2CrMo (according to EN1599-ECrMo2 B 42) with subsequent cementation and heat treatment, .Two essentially different procedures of the reparatory hard facing were used for the gear regeneration:Removal of the cemented layer from the active working surfaces by grinding to the depths of 1.2 + 0.2 and 12 mm along the tooth height;Preheating of the gears to a temperature of 230 °C and holding at that temperature for 2 h;The TIG hard facing of the prepared surfaces in the argon-protected atmosphere with the DUR 600-IG wire of diameter Ø1.2 mm;Returning of the hard-faced gear into the furnace and slow cooling with it;Grinding of the hard-faced teeth on the gear-grinding machine “Niles”.The gear regeneration through hard facing by the TIG procedure, with DUR 600-IG, consists of the following processes:Soft annealing—this operation is necessary to reduce the surface hardness of the teeth working surfaces and to enable preparation by milling. Annealing was conducted in vacuum, heating up to a temperature of 680 °C, at a rate of 10 °C/min. The gears were then held at that temperature for 4 h and then cooled at a rate of 2 °C/min.Removal of the cemented layer from the teeth active working surfaces by milling on the universal milling machine, to the depths of 1.2 + 0.2 and 12 mm along the tooth height.Preheating of the gears to a temperature of 230 °C and holding at that temperature for 2 h.Drying of electrodes at a temperature of 350 °C for 4 h.The Manual Metal Arc (MMA) hard facing of the prepared surfaces by the cored electrodes, EVB2CrMo.High annealing in the furnace.Milling to the over-dimension (with addition for grinding) on the gear milling machine Pfauter.Soft annealing.2 + CO mixture to the depth 1.0 + 0.1 mm with cooling in the pit.Cementation in the COGrinding of the hard-faced teeth to nominal size.In the case of regeneration by the “soft” filler metal EVB2CrMo, the technological procedure of regeneration is significantly different from the previously described one. It consists of the following operations:During the hard facing, the thickness of the hard-faced layer had to be increased for the size of addition predicted for subsequent surface machining.The metallographic investigations were conducted on the quantitative optical metallographic microscope POLYVAR-MET  with magnifications of 20 to 2000 times . Figure The microstructure of the surface and subsurface layers (cemented layer and the core of the newly manufactured tooth) is presented in The microstructure of the tooth hard-faced by the TIG procedure and the filler metal DUR 600-IG in the argon protective atmosphere is shown in The microstructure of the cemented layer hard-faced with the filler metal EVB2CrMo is shown in Since the exploitation characteristics of the hard-faced layer depend, to a great extent, on the size of dendrites within it, the dendritic crystals’ width was measured on the optical microscope . Those mBased on the results presented in The microhardness of the teeth, hard-faced by the TIG procedure with the filler metal DUR 600-IG, was measured in two directions, close to the top of the tooth and in the zone of the pitch circle, Besides the conducted investigations, the microhardness of the inactive tooth flanks of the regenerated teeth was measured, as well. For the sample hard-faced with the DUR 600-IG filler metal, hardness was measured in three directions, close to the tooth top (I-I), in the pitch circle zone (II-II) and at the tooth base (III-III), From the diagram in Investigation of the regenerated and newly manufactured teeth flanks’ durability was performed on a closed-circuit device shown in 6 loading cycles for the newly manufactured teeth and for the teeth hard-faced with the EVB2CrMo filler metal after 70 × 106 cycles. The longest operation prior to the appearance of the first pits was exhibited by teeth hard-faced by the TIG procedure and the DUR 600-IG filler metal, where the destructive pitting started after 74 × 106 loading cycles. After 98 × 106 loading cycles, the full duration of tests, for newly manufactured teeth, 18% of the most endangered tooth surface was covered with pitting; for the tooth hard-faced with the EVB2CrMo filler metal, the attacked area was about 50 %; and for the tooth hard-faced by the TIG procedure, this was only about 12 %. Analyzing the operation time until the first appearance of the destructive pitting of the regenerated and newly manufactured teeth produced the diagram shown in The appearance of the destructive wear, namely, the first pitting pits, was noticed after 69 × 10The size of the pitted surface of the tooth was determined by the visual method. The template was made of opaque foil, the opening of which was as long as the tooth’s height (about 17.5 [mm]) and 10 [mm] wide. Then, the teeth portions were examined with the magnifying glass (magnification 5×). The assessment was made according to the most worn teeth and their parts with the most pits. Those tests were performed in the phase of destructive pitting, namely, after noticing the initial pits with the naked eye.Economic analysis of the applied regeneration procedures assumes a comparison of costs of the regenerated and newly manufactured gears. The regeneration price includes material and labor costs, as well as overheads. The comparison results are presented in ek)—represents the relative price of the regenerated gear (rC) with respect to price of the new gear (nC) and is determined according to expression: Indicator of economic justification of regeneration (rt) was determined from the diagram shown in nt = 1510 h. Assuming that 5% of the teeth working surfaces being affected by pitting are a criterion for interruption of the gears’ working capacity , the operating time of the gears regenerated by the appropriate welding method (epk)—represents the ratio of the regenerated and new gear service lives:Coefficient of the exploitational reliability (β)—takes into account both the regeneration price and the service life of regenerated teeth until the limit wear appearance. It is calculated according toCondition for economic rationality of regeneration , it would be more convenient to apply the “soft” filler metals with subsequent cementation and heat treatment.


A rare and valuable Palaeolithic wooden point, presumably belonging to a hunting weapon, was found in the Ljubljanica River in Slovenia in 2008. In order to prevent complete decay, the waterlogged wooden artefact had to undergo conservation treatment, which usually involves some expected deformations of structure and shape. To investigate these changes, a series of surface-based 3D models of the artefact were created before, during and after the conservation process. Unfortunately, the surface-based 3D models were not sufficient to understand the internal processes inside the wooden artefact . Since some of the surface-based 3D models were taken with a microtomographic scanner, we decided to create a volumetric 3D model from the available 2D tomographic images. In order to have complete control and greater flexibility in creating the volumetric 3D model than is the case with commercial software, we decided to implement our own algorithm. In fact, two algorithms were implemented for the construction of surface-based 3D models and for the construction of volumetric 3D models, using (1) unsegmented 2D images CT and (2) segmented 2D images CT. The results were positive in comparison with commercial software and new information was obtained about the actual state and causes of the deformation of the artefact. Such models could be a valuable aid in the selection of appropriate conservation and restoration methods and techniques in cultural heritage research. Our interest in reconstructing 3D solid models using computed tomography was piqued when we were confronted with the deformation changes of a Palaeolithic wooden point  Figure . The 40,Additional laboratory investigations of the artefact  were carried out. Radiometric analysis (AMS14C) places the point in the Palaeolithic period. Two datings have been made. The first (Miami–USA) showed yew wood (Taxus sp.) to be older than 43,970 years (Beta-252943), and a re-dating in Oxford gave a maximum age of 38,490 ± 330 BP (OxA-19866).Since the discovery, special attention and care have been taken to ensure conditions for the permanent preservation of the point in its natural environment. Underwater archaeologists suggested sinking the point in a special capsule in the deeper sediments of the site in the riverbed of the Ljubljanica. In this way, the point would be optimally protected from the danger of rapid decay. The 3D model and the virtual replica would be presented to the public. However, a different view prevailed. This envisaged the conservation and public presentation of the Palaeolithic remains as a valuable museum exhibit. The lace was kept for five years under artificial conditions (in distilled and regularly changing water). In 2013, the lace was sent to the Römisch–Germanisches Zentralmuseum in Mainz (Germany), which carried out the conservation with melamine resin (C3 H6 N6) in the years 2013–2015. The conservation was completed in 2017. In 2018, the artefact was returned to the Ljubljana City Museum, where it is kept. The wooden point is now one of only eight Palaeolithic wooden artefacts in Europe. However, no other artefact was made in such a beautiful leaf-like shape.A visual inspection of the point after conservation revealed that it had changed. The point was smaller, lighter in colour and more clearly curved in the area of the planting. A computerised volumetric and geometric deformation analysis of the point cloud of five 3D models (CloudCompare computer software) confirmed this finding. Significant deterioration and deformation was found during the conservation phase. In 2018, we conducted a comparison of five 3D surface models of the Palaeolithic wooden point . The artBased on computer volumetric analysis of the five 3D surface models recorded in different years ,7, it waA comparative study of 3D surface models of the Palaeolithic wooden point has shown  that theA comparison of the amount of information contained in point clouds or triangulation meshes of 3D surface models acquired with optical scanners and tomographs illustrates the qualitative advantage of tomographs . This alDepending on the 3D scanner, the technique for reconstructing the 3D model is also different. In the traditional 3D surface model, we reconstruct the model by combining surface images  in three-dimensional space. In the volumetric 3D model, we reconstruct a 3D model from the greyscale values (HU or RGB) of 2D tomography images. Such models are more accurate, of higher quality and with less noise compared to conventional computer vision models. They also provide optimal conditions for objective evaluation of the scanned object—volumetric analysis, qualitative analysis of the material, deformation analysis, etc.The Palaeolithic wooden point, which we have been studying since 2008, was scanned with a microtomographic scanner (Micro XCT 400) in 2018 and 2019. This provided 2D tomographic images that allowed us to look inside the artefact to better understand the reasons for the various deformations that occurred, especially after the conservation process. Analysing and understanding the changes in a waterlogged artefact over a period of 10 years is very valuable knowledge for scientists and conservators. Therefore, we decided to reconstruct surface-based and volumetric 3D models from the available 2D tomography slices. In this way, we were able to investigate the internal cracks, fractures, pores, inclusions and deformations of the wooden point. Since we wanted to have complete control over the tomographic reconstruction of the 3D model from CT sections, we decided to design and implement our own algorithm.Reconstructing 3D models from CT images is a particular challenge for further research in computer vision, where rendering 3D models with open-source algorithms from images captured by DSLR cameras, structured light scanners, laser and other scanners is widely used for surface and remote sensing. This technique still belongs to the field of computer graphics. A number of segmentation algorithms are adapted to the specific objectives of the users. It is no coincidence that the primary application of noninvasive computed tomography is not the reconstruction of 3D models in the sense of computer vision. The focus is on the interest in noninvasive graphical insights, visualisations and analyses of 2D, 3D or 4D information in a three-dimensional coordinate system for the purpose of visual support in medical diagnostics, measurement technology, analysis and quality control of materials in industry and science.Most algorithms for processing and reconstructing CT images have not received special attention from computer vision in general or its application in cultural studies due to the emphasis on commercialisation, closed code, specialisation (medicine or industry), radiation risk and intellectual property protection. With this novelty, i.e., the 3D anatomical model and the proposed algorithmic solution, we wanted to present a new challenge to traditional research and applied work in the field of computer vision in heritage sciences. The 3D anatomical model not only enriches the digitised cultural heritage and knowledge about the artefacts, but at the same time expands the possibilities for their analytical treatment, holistic visualisation and augmentation.Since the background of our research team is in 3D computer vision  and we eTo reconstruct the 3D model from 2D images CT, we selectively used some time-limited open-source and commercial software tools  for 3D rendering and visualisation of tomographic images during the preparatory phase. However, we were not satisfied with the initial results. Our research objective was a comprehensive volumetric reconstruction of the internal  structure of a 3D and 4D model of a selected archaeological object. Commercial 3D image processing programmes usually use special segmentation algorithms to process specific 2D image file formats and are designed for specific work and research goals in medicine or industry. However, they are not suitable for use in cultural studies. We often faced limited use of converted files, additional procedures, inaccurate volumetric data and substitution of 3D graphics for 2D graphics in analytical procedures. These circumstances were the reason why we decided to develop a special segmentation algorithm for reconstructing a 3D model from microtomographic images. The algorithm was adapted to the work requirements of archaeological and conservation treatment of smaller archaeological objects.Archaeologists and conservators occasionally come across CT images of artefacts in their work, but they do not have the appropriate software tools and solutions for noninvasive reconstruction and analysis of 3D models. Since working with expensive hardware and commercial algorithms is not designed for the goals, interests, needs and problems of archaeological or conservation research, the vast amount of data and information contained in 3D anatomical models remains unused and undocumented. At the same time, the use of a customised segmentation algorithm also pointed to new challenges and opportunities in the reconstruction of 3D models in computer vision, where work is still based on more affordable hardware for reconstructions of only surface 3D models. Conventional 3D models of computer vision, compared to 3D models reconstructed from 2D images CT, are of lower quality, highly noisy, volumetrically unreliable and limited both graphically and in terms of data. We have successfully overcome these shortcomings with new, simple and undemanding segmentation algorithms for reconstructing a 3D model from 2D images CT.The rest of the article is structured as follows: The London Charter  and the 3D models reconstructed with traditional computer vision algorithms have become permanent digital carriers of artefact information that archaeologists can later examine, evaluate, compare and analyse without damaging or destroying the original objects. However, 3D surface models only contain information about the surface properties of artefacts. This information limitation can be improved by developing and using specialised algorithms to reconstruct volumetric 3D models of archaeological objects from image recordings of deep scanners  to reveal their internal structure or anatomy as well.The use of volumetric 3D models represents a qualitative advance in the integration of increasingly affordable computer technologies and software solutions into the regular professional and research work of archaeologists and conservators. The AGORA 3D Heritage Project has also been working towards this  ,13Surface-based and volumetric 3D models would greatly enrich archaeological documentation, improve work in archaeological laboratories and enable conservation science to deal comprehensively with cultural heritage remains. However, volumetric 3D models can provide conservators and restorers with additional useful information for planning the use of appropriate methods and techniques to protect critical cultural heritage remains.The number of scientific papers dealing with the use of computed tomography (CT) is very extensive in the international research environment. The number of bibliographic units has increased in recent years. This is due to the fact that investment in the development and use of CT technologies is increasing year by year and is becoming one of the most important areas of Industry 4.0 . At the A review of published sources shows that the use of nondestructive CT or µCT technology in archaeology has so far focused mainly on the study of very delicate objects from the Palaeolithic and early civilisations. For example, CT scanners have been used to examine mummies , Ötzi 2 and The After 2019, industrial µCT scanners and specialised commercial software will be increasingly used in archaeological studies . The firCurrent research interests in the noninvasive use, reconstruction, visualisation and processing of 2D µCT images include: analysis of all types of materials , analysiThe current importance and applicability of computed microtomography in analytical archeology is confirmed by the microtomographic treatment of the Venus from Willendorf by the Department of Evolutionary Anthropology and the Core Facility for Micro-Computed Tomography, University of Vienna, which researched and microtomographically processed the approx. 30,000 year old figurine made out of oolitic limestone using commercial computer software Amira. The research offered important new insights into the origins and methods of making this valuable archaeological artifact .The original dilemma of algorithms for processing 2D images for CT at “low-level” was solved decades ago in the framework of Marr’s “high-level” paradigm , althougThe use of computed tomography and tomographic sensors is increasingly expanding the field of robotic surgery ,43,44, aalgorithms for the reconstruction of 2D tomographic images from tomographic projections andalgorithms for the reconstruction of volumetric 3D models from 2D tomographic images. For the reconstruction of 3D models from CT images, the terms “volume rendering” and “surface rendering” are often used synonymously in computer graphics ,50.In computed tomography we distinguish two types of algorithms, depending on the type of reconstruction. However, the use of both terms requires some caution as they are often used uncritically and indiscriminately in professional articles, even in cases that do not involve reconstruction of 3D surface or volumetric models from CT, MRI or PET images and are based on attenuations or RGB matrices of grey values. The term “volumetric imaging” has not yet gained acceptance in computer vision methods and techniques for reconstructing 3D models. However, it is accepted in computer graphics methods and techniques for 3D visualisation of tomographic images .While in the first case, the algorithms are adapted and specialised for processing image signals based on attenuation values or HU numbers, in the second case various specialised algorithms are used to represent the 3D surface model. These include algorithms from computer vision and computer graphics ,53, suchThe reconstruction of CT images in three-dimensional space is of particular importance in modern medicine and industry. Especially in robotic surgery, prosthetics and orthopaedics as well as in the analysis of material quality. This is not only about real-time visualisation and improving accuracy in the detection and treatment of diseases, such as in robotic surgery, but also about achieving higher quality products in industry. In both medicine and industry, methods for reconstructing and visualising 2D tomography images are on the rise. Algorithms for target rendering are also being adapted and developed accordingly. For example, Microsoft Visual Studio  has deveIn recent years, there has been increasing interest in the use of machine learning and deep learning algorithms, convolutional neural networks (CNN) or other artificial intelligence algorithms in industrial computed tomography. Occasionally, adapted or modified algorithms are used that have already been used in the reconstruction of 2D tomography images, such as Fourier volume rendering, Monte Carlo volume rendering , the addAlgorithms for imaging or reconstructing 3D volumetric models can be divided into four groups: Ray Casting Algorithms, Splatting Algorithms, Cell Projection Algorithms and Multi-Pass Resampling Algorithms. However, in the practice of 3D visualisation and modelling from tomographic images, three techniques for volumetric image projections in computed tomography stand out: maximum intensity projection (MIP), minimum intensity projection (MiniIP) and three-dimensional volume rendering (3DVR)  or direcAn optimised 2D tomographic image is a key factor for the quality of all further procedures from visualisation to reconstruction of 3D models and addition. Therefore, most research efforts in computed tomography have been and still are focused on the improvement of algorithms for 2D image reconstruction and not on the reconstruction of 3D models. In computed tomography, computer graphics algorithms have become the most popular. Chris Shaw  mentionsFundamentals of computerised tomography: image reconstruction from projections [A transparent contribution to the understanding and open questions of computerised tomography and the algorithms used for reconstruction was presented by G.T. Herman in his most cited work in the field of computerised tomography, his book jections . Herman 3D Segmentation Algorithms for Computerised Tomographic Imaging: a Systematic Literature Review [A second review of the features, capabilities and shortcomings of segmentation and reconstruction algorithms in computed tomography can be found in e Review . The arte Review . There iIn tomographic image reconstruction in medicine, additive manufacturing, materials analysis and industrial control, the filtered backprojection (FBP) algorithm has been standardised for some time. In recent years, somewhat forgotten iterative reconstruction algorithms have resurfaced in industrial tomography ,63,64,65The development so far shows a multitude of specialised reconstruction algorithms. The number and variety of algorithms is due to the fact that each selected algorithm and segmentation method or technique is adapted to specific research questions of 2D tomography image reconstruction in medical or industrial diagnostic imaging or analytical practise.Computed tomography algorithm developers are still mainly focused on optimising algorithms for segmentation, recovery and 3D reconstruction of CT images ,59 and oTraditional radiology after 1889 and computed tomography after 1975 have been present in archaeology since its beginnings. The use of algorithms for the reconstruction of 2D images (for example: Inverse Fourier Transform or the filtered back projection commonly used today) is considered a noninvasive technique for the anatomical study of delicate, unstable and valuable artefacts  such as Only rarely do we find examples of the reconstruction of archaeological 3D models from tomographic images. This is partly due to the development of a relatively autonomous field of computed tomography, which is primarily developed as an imaging technique in medical diagnostics and as a measurement and control technique in industry. The algorithms for reconstructing the X-ray signal into a 2D image and 3D visualisation from CT images are also geared towards these goals. Isolated attempts at 3D modelling from CT images are also the result of the high financial cost of using CT scanners and the still insufficiently exposed need to use 3D anatomical models in additive manufacturing.The reconstruction of 3D models of archaeological artefacts has so far been mainly limited to 3D surface-based modelling in archaeology. 3D surface-based models have in most cases been created using affordable photogrammetry, laser scanners and structured light scanners. Various computer vision algorithms have been used for reconstructing 3D surface models, such as: intuitive algorithms for computing similarity or distance , SIFT—ScThe reconstruction of anatomical 3D models from tomographic images is not yet the subject of interest of heritage sciences for a comprehensive documentation of archaeological objects. The use of computed tomography algorithms in archaeology still primarily adapts to the possibilities of arbitrary use of medical and industrial hardware. It is only since 2015 that we have seen greater interest from archaeologists and conservators in the use of computed tomography in the processes of conservation, restoration and visualisation of archaeological objects ,86,87,88According to studies published in 2020 and 2021, archaeologists and conservators continue to use commercially tested material and composite analysis software tools to reconstruct or visualise 3D archaeological models, such as VGStudio MAX, Amira Avizo 9.0, Simpleware—Synopsys, Inc. and Dragonfly Pro—Carl Zeiss. We also recommend the possibility of online 3D visualisation of 2D images CT, with  interactThis is also the reason why, given the still financially inaccessible hardware, no specific computed tomography hardware or algorithms have been developed for the needs of heritage conservation, suitable for documentation and research science. Such initiatives have been presented in the past. For example, the Belgian project AGORA3D was launched in 2008. In recent years there have been efforts in this direction, for example by researchers at the University of Bologna and the Conservazione e Restauro “La Venaria Reale”—CCR of the University of Turin. An important innovation in the use of computed tomography for the conservation of valuable remains of cultural heritage are interdisciplinary projects of some French  ,88, BritThe basic research objective was to select, improve and evaluate an algorithm for high-quality reconstruction of 3D surface and 3D volume models from tomographic images for the needs of preservation, conservation and evaluation of archaeological heritage remains. With the new approach in computer vision, mainly using algorithms for 3D surface-based modelling in the processing of 2D image records, we wanted to highlight the suitability and applicability as well as the analytical and documentary importance of 3D volumetric models in computer vision and heritage science. At the same time, we wanted to answer some open questions about the observed changes in 3D surface-based models of Palaeolithic wooden point from its discovery to the completion of conservation ,5,7.As open-source algorithms are used for observing 3D surface models obtained from image acquisitions from DSLR cameras, structured light scanners, lasers and other surface and remote sensing devices, reconstruction of 2D images from CT, MRI and other depth sensors also requires appropriate observational techniques. Most algorithms for processing and reconstructing CT images have not received special attention from computer vision in heritage science due to a focus on commercialisation, closed source, specialisation , radiation risks and intellectual property protection. With new methods for reconstructing surface and volumetric 3D models from CT images, we aim to challenge the traditional research and application field of computer vision in heritage science.With the new experiences, we aim to expand the research interest of computer vision  from the already-established traditional 3D surface models to the reconstruction of surface models and 3D volumetric models from tomographic images. We anticipate that the price of 3D depth detection scanners will become more affordable for cultural scientists on the threshold of the fourth industrial revolution.A particular research and development goal was to develop a simple algorithm for reconstructing volumetric 3D models from CT images of archaeological objects. The algorithm should not require highly specialised computer and mathematical knowledge from the user. We were guided by the idea that the algorithm should be simple, robust and adaptable to the specific needs of archaeologists and conservators. After all, they occasionally come across CT images of artefacts in their work, but they do not have the appropriate algorithms, customised software tools and solutions for reconstructing and analysing 3D models. Therefore, they are usually forced to use commercial software tools developed and adapted for other purposes, namely diagnostic work in medicine and industry. Since working with them is not tailored to the goals, interests, needs and problems of archaeological or conservation research, the huge amount of data and information contained in surface-based and volumetric 3D models remains unused. This leads to an impoverishment of the digital documentation of cultural objects. Developing a simple computer algorithm suitable for working with cultural heritage remains was our ultimate motivating goal, which would provide an incentive for further research in computer vision and cultural heritage science.After studying the literature and initially testing various computed tomography, computer graphics and computer vision algorithms for reconstructing 3D models from 2D images CT, we were faced with the need to develop a new iterative algorithm. The tested solutions did not meet our expectations to reconstruct a surface-based and volumetric 3D model that would answer the open questions about the identified changes in the five surface-based 3D models of the Palaeolithic wooden point accurately, volumetrically precise and graphically clear enough. The test with commercial software also showed that the built-in algorithms reconstruct the 3D model, but only the outer surface edge points of the cloud. Volumetrically, it reliably and accurately reconstructs only the 3D surface model of the scanned object.2D image CT in the format TIFF  consisting of a grey HU or RGB matrix in which each point (pixel) of the matrix has a grey x/y value;z-coordinate value of each voxel of the 3D layer in Cartesian three-dimensional space;the thickness of the X-ray beam corresponding to the an edge-detection technique that segments selected greyscale RGB values of each boundary point (pixel) of a 2D image.The workflow of the new algorithm is based on a preliminary analysis of the properties of the 2D CT image slices and the projection of the output file of the 3D model (an OBJ file) based on the following parameters of the reconstruction of the surface-based and volumetric 3D model:The algorithm must be adapted to the purpose of the archaeologist or conservator to reconstruct the 3D surface and 3D volume model of the artefact under investigation. In the selected test case this will be: detection of dislocations, inclusions, pores, cracks, openings, damage, deformations and fractures in the anatomical structure of the object.The design of the algorithm should focus on the specific research objective of reconstructing the 3D surface and 3D volume model in the initial phase of development. Based on the available data contained in the greyscale values of the images from CT, we found that the reconstruction of the 3D spatial and 3D surface model can, on the one hand, use the full set of attenuation or RGB values and, on the other hand, develop an algorithm that can detect features in the anatomical structure of the object that are aligned with a specific archaeological or conservation goal.dAR3D converts 2D images from CT directly and without additional segmentation into 3D slices CT , registers them in a three-dimensional coordinate system as a collection file and then reconstructs them into a volumetric and surface-based 3D model, andthe algorithm with the working code name sAR3D, which first limits the number and values of features in the 2D image CT by segmentation. It then converts the segmented 2D images CT with a z-coordinate value into a 3D scalar field of voxels (3D CT slices), registers them in a three-dimensional volume coordinate system as a collection file, and then reconstructs them into a 3D volume and 3D surface model using the aggregation and alignment method. The segmentation algorithm is intended for specific analysis or research goals in the archaeological, conservation or restoration treatment of an archaeological object. It is faster than the dAR3D and can be implemented on personal computers without memory limitations. It can also be used in other fields or in cases where we decide to segment features in a 2D CT (MRI etc.) image.the algorithm with the working code name Methodologically, two iterative algorithms were developed that differ in terms of the degree of robustness, the research purpose and the temporal dynamics of the implementation:The algorithms are limited to the process of reconstructing the 3D surface model and the 3D volume model from 2D images CT .dR3D is slower (due to the large amount of information contained and consequently the size of the output file). Reconstructing a 3D model takes about 7 times longer than reconstructing a 3D model from segmented CT images. Due to the large amount of information, additional computer storage capacity or cloud processing is required. This algorithm is useful:in the initial nonselective and noninvasive examination of the anatomical structure of the artefact to obtain initial information about the artefact and for the subsequent selection of target features for archaeological, analytical or conservation processing;for a comprehensive archaeological 3D documentation, and;to produce a 3D additive as a perfect replica of the original.The direct algorithm sAR3D, which was the subject of our special development refinement due to its robustness, simplicity and efficiency, is adapted to the research goals of the direct user. It is intended for the working purposes of archaeological, conservation or restoration treatment. It is faster in time and can be realised on noncommercial personal computers without memory limitations. It is user-friendly, robust and simple. No special knowledge  is required to achieve the user’s research goals of reconstructing a 3D model from CT images.The segmentation algorithm The workflow of the two algorithms is shown in Code the algorithms for direct and segmented reconstruction of 3D models from 2D µCT  in four steps. The individual steps and specifics of the code record structure are shown in the tabular overview , which lIn the mathematical and logical design of the code of both algorithms, we used a numerical analysis software package, MATLAB. The chosen fourth-generation programming language is sufficiently effective for performing mathematical operations. However, the segmentation process is only one form of mathematical algorithm. In addition, the programming language can quickly work with tables to quickly convert segmentation data into a 3D coordinate table.The code of both algorithms is the same in the first step (selecting and registering 2D images CT for 3D reconstruction), in the phase of converting 2D images into 3D layers and in the phase of writing a 3D model in OBJ format. The codes of the two algorithms differ only in the fourth step, where we use the outer and inner edge detection technique to segment individual 3D layers.The code uses the auxiliary algorithm of the NATSORTFILES function (built into MATLAB SORT), which classifies an array of cells with filenames or paths. It takes into account all numeric values in the array . It is a “natural sort type” or an “alphanumeric type”. NATSORTFILES (74) does not mean sorting by natural order, but separates file names and their extensions. This has the effect that shorter file and directory names are always placed before longer names, thus ensuring the correct order of names in the directory. For the same reason, file paths are divided into each path delimiter and each directory level is sorted separately.A special feature of the code of both algorithms is the input of “z-values” or “z-coordinates”. This procedure is crucial for the correct volumetric arrangement of the 3D model. If we want to reconstruct a surface and volumetric 3D model from CT images that allows accurate volumetric analysis and comparison, it is not enough to simply fold 2D images into a virtual 3D model. To achieve a volumetric match with the original, each 3D layer must be inserted into a Cartesian coordinate model of the space with precise voxel dimension data . Only in this way can we obtain a volumetrically accurate 3D anatomical model that is volumetrically identical to the original. If we simply glue the images of CT together, we will obtain the correct values for the width (x) and thickness (y) of the object, but the length (z-coordinate) will be completely distorted, unrealistic and useless for volumetric analysis and final reconstruction.The fundamental difference between the two algorithms lies in the introduction of the segmentation procedure, which in our case is based on the technique of detecting edges on the surface and in the anatomical structure of the studied object. The segmentation procedure removes insignificant grey values of edges from the image CT and determines the edge values that will be the subject of the user’s examination. The segmentation procedure allows us to highlight the selected target features of the anatomical structure of the original more clearly in the reconstruction of the 3D model than with the dAR3D algorithm. In this way, we simplify and shorten the reconstruction and extract the features highlighted in the 3D anatomical model while preserving all volumetric values and information.In our case, segmentation is considered as a form of mathematical algorithm. This was also the reason why we chose a numerical analysis software package (MatLab) to write the code. This programming language is suitable for working with tables and can effectively convert segmented data into a table with 3D coordinates. The code written in this programming language is generally robust, easy to understand and use, optimal for processing image files  and does not require additional and intermediate procedures.The right choice of edge-detection techniques is crucial for efficient segmentation. The edge of a CT image can be defined as an abrupt change in intensity. The edge is nothing more than the boundary of a particular region. In a CT image, the edge can be defined as a break in brightness or a change in the grey values of the HU or RGB matrix. When the light intensity or the grey value changes, this is called an edge. Edge perception is important for describing the shape and anatomical structure of an object. Edge detection identifies boundaries in a 2D image CT. The features can be common or separate. The main goal of edge detection in the segmentation algorithm is to obtain the volume and surface features of the object. Before selecting the segmentation code, we investigated and evaluated different edge detection techniques  and seleWe have investigated, compared and tested different techniques  for edge detection in the image CT of the Palaeolithic wooden point and some other artefacts . We chosarchaeological or conservation treatment of the artefact using the segmentation sAR3D. Segmentation in our case is a technique for determining, selecting and limiting the grey RGB values in CT images. This also allows us to reconstruct the 3D surface and 3D volume model. It is a rarely used 3D modelling technique, even when it comes to the commercial reconstruction of a 3D model from CT images. However, CT image segmentation is different from the prevailing 3D modelling techniques in computer vision, where segmentation is based on other paradigms, such as: light sources, contrast, colour shading, generalisation of geometric shapes, etc.The process of reconstructing the 3D surface model and the 3D volume model from CT sections was adapted to the specific research objectives of the In our particular case, segmentation was used to determine and mark the edges of the non-oody x–y–z coordinate points (voxels) in each 3D layer. This marked the features in the anatomical structure of the 3D layer . We selected those features in the 3D layer which, in accordance with the aim of the study, we believed could successfully answer the question about the nonwoody features of the artefact and the factors that might influence the observed surface deformation of the object. In our case, these were openings, pores, fractures, inclusions, cracks, etc. By determining the outer edge handles, we have set the stage for the reconstruction of the 3D surface model, while the 3D anatomical model will volumetrically mark and represent selected features that were the subject of research interest and observation.The visualisation of the 3D model, which was reconstructed from 2D images CT, is done with the graphical open-source software tools CloudCompare and MeshLab, which enable high-quality and accurate visualisation of 3D models, their volumetric analysis and comparison.Step 1: the point cloud of the 3D model in the selected format  is entered using the “Open” function in the CC software;Step 2: The tool CROSS SECTION removes unwanted or disturbing sections in the point cloud and then exports the selected section as a new point cloud to CC;Step 3: The calculation of NORMAL with the surface approximation method follows ;Step 4: The calculated normals are aligned to the normals using an orientation algorithm or a numerical Fast Marching method ;Step 5: Poisson Surface Reconstruction is used to convert a point cloud into a 3D model with triangulation mesh.Depending on the exposed research objectives and the planned treatment of the 3D model and the objectives of its visualisation, follows.Step 6: x, y, z) of critical points in the anatomical structure of the Palaeolithic point.For further processing and clearer visualisation, various filters, stereogram analyses and other tools are available for multilevel volumetric, statistical and analytical treatment of the point cloud . In our case, we opted for anatomical or volumetric 3D visualisation and volumetric detection  of the selected 3D models.Algorithms for reconstructing 3D models from CT images were tested on a 40,000-year-old Palaeolithic wooden hunting weapon found in the Ljubljanica River (Slovenia) in 2008  and threVolume and deformation analyses with the software CloudCompare were carried out for 3D volumetric models of the Palaeolithic wooden point.dAR3D—direct algorithm for 3D model reconstruction;sAR3D—segmentation algorithm for 3D model reconstruction.Algorithms used for reconstruction of 3D models from CT Images:Input data : reconstOutput data : 3D modePROCESSOR: INTEL (R) Core (TM) i7-8850 U @ 1.80 GHz;RAM: 8 GB;GPU: NVIDIA GeForce RTX 1050;OS: Windows 10 (64-bit).The algorithms were systematically developed, tested and evaluated on a commercially available portable computer (a laptop) with the following configuration:MatLab  was used to develop the algorithms.Open source applications for graphical, statistical and volumetric processing MeshLab and CloudCompare were used to process image data, compare and reconstruct the 3D model.The reconstruction of the 3D models of the Palaeolithic wooden point was carried out using both developed algorithms . Based odAR3D), we reconstructed the 3D surface-based model and the 3D volumetric model directly from the entire set of 2D images CT of the Palaeolithic wooden point , the surface-based 3D model is extremely accurate and even surpasses the photo of the original in certain parameters . The difference in contrast and accuracy between the reconstructed 3D model and the original photo is due to the limitations of the DSLR camera such as colour gradations, the influence and direction of light on the artefact and other circumstances of the photo. The difference in contrast between the reconstructed dAR3D model and the model displayed with the commercial Avizo Fire (FEI) tool is due to the use of different 2D image resolutions in the TIFF format. In our case, the image resolution used to reconstruct the 3D model was significantly higher (2690 × 2731) than the image resolution (1012 × 1024) used by the commercial tool to display the 3D model. This is also the reason why our model is more accurate and the point cloud also contains a much larger set of stored information.sAR3D, we first marked only the grey RGB values  in the 2D images CT for the reconstruction of the 3D surface model and the 3D volume model, as well as regions that indicated nonwood features or values in the images. With this intervention, we limited the segmentation to selected features in the anatomical structure of the point , only the segmented values in the anatomical structure were highlighted in the 3D volumetric model . The comparison  was performed using the ICP algorithm and the CloudCompare graphical software tool. The comparison showed slight discrepancies between the two models. From this comparison it can be concluded that the quality of the reconstructed 3D model depends mainly on the quality of the input data. This fact also became clear when comparing two models that were created at different resolutions. Here the differences were in the contrast and texture details of the surface-based 3D model and not in its volumetric deviations.To determine the efficiency of the algorithm and the quality of the reconstructed 3D surface-based model, we compared the 3D model of the wooden point reconstructed with the algorithms sAR3D. During segmentation, we paid attention to dislocations, inclusions, pores, cracks, openings, damages, crisps, deformations and fractures. We located critical areas, identified damage and changes that were previously not readable from the 3D surface-based model.In the volumetric computer analysis of the anatomical structure of the volumetric 3D models, we restricted ourselves to a model reconstructed with a segmentation algorithm The critical points of the artefact’s internal structure were determined volumetrically and marked on the model . Three pA comparison was made between models of the Palaeolithic point reconstructed in 2018 and 2019 using a CT scanner . CompareA comparison of the anatomical changes of the artefact after one year shows a tendency towards greater contraction of the tip . This prThe deformation changes seen in Experimental tests of 3D model reconstruction with our algorithms were conducted on four smaller archaeological objects made of bone and clay and two other materials (concrete and fabric) to determine the robustness and quality of the algorithms for 3D model reconstruction of surfaces and volumes .dAR3D and sAR3D, they do not differ in any way from the quality of the models reconstructed with commercial software tools. It is significant that the segmentation algorithm . With reconstructed 3D models, it provides the user with a large amount of data and information and enriches archaeological documentation. The image data and information can be processed with already-available software tools for processing 3D network data. However, it is true that this makes the reconstruction of 3D models more expensive than traditional computer vision algorithms. With the financial availability of CT hardware, it is also becoming interesting for use in the heritage sciences. This is confirmed by the growing number of research projects and published professional contributions in all fields and not only in heritage studies.With the developed segmentation algorithm we used in our specific archaeological case, the process of segmenting features in 2D images using the Roberts Edge detector, after reconstructing the 3D model (from any plane section) we obtain a depth image of the object in the case of a dynamic 3D visualisation or a printed 2.5-D image simulating the holographic method of recording 3D dimensional information about an archaeological object.Our simplification of the preprocessing of 2D image files or 3D slices eliminates the need to use additional philtres  for the segmentation process. It is also not necessary to use the translucent visualisation technique (Gaboutchian) of the 3D anatomical model. The depth view .With the reconstructed 3D models, we were able to accurately identify, examine and document the internal structure of the artefact. Deformations  are clearly visible and volumetrically localised. The 3D anatomical model successfully complemented the knowledge of the features and specificities of the alterations and revised the erroneous and not fact-based assessment of the alterations that was solely based on the surface-based 3D models.The chosen hardware and software proved to be suitable to realise the set development and assessment goals of the study. It can form a basis for a possible standardisation of hardware and software for the reconstruction of computed tomography images into a 3D model.The advantage of both algorithms is their ease of use. The user can reconstruct the 3D model according to his research objectives, with the appropriate hardware and open-source software configuration of the computer system, without any special mathematical or computer knowledge and without additional professional and technical support from a radiologist, computer scientist or physicist.the selected number of CT images in the appropriate format ;data and information from the radiologist about the thickness of the layer (information about the possible inclination (in degrees) of the object mounted in the CT reader, and;information from the radiologist about the limits of the object (length – width – thickness) that can be detected by the selected CT reader with a single X-ray (scan).To implement the algorithm directly, the user needs:The information and data provided are important for the accurate volumetric treatment of the object and its match to the original. Algorithms otherwise adapted for the use of computed tomography and 3D model reconstruction from CT images of small archaeological objects for archaeological documentation and for planning conservation and restoration procedures can also be robustly used in other cases . The limit for the choice of the algorithm’s intended use depends on the technical possibilities of the chosen CT reader.The algorithms are useful in the reconstruction of 3D models from 2D microtomographic or tomographic images acquired with all types of CT or µCT readers, as well as with other depth imaging readers . The segmentation algorithm can be fully adapted to the needs of different users and workspaces. It is simple and straightforward and does not require in-depth mathematical and computer knowledge of the direct user.The quality of the reconstructed anatomical (3D volumetric) and surface-based 3D models from 2D µCT images is not significantly different from the quality of 3D models created with more expensive commercial software. The evaluation of the algorithms confirmed that the quality of the 3D model depends mainly on the quality of the input 2D CT or µCT images.dAR3D algorithm is significantly slower than the sAR3D in reconstructing the 3D model. The shorter reconstruction time of the 3D model with the sAR3D algorithm is due to the smaller amount of information in the segmented 2DµCT images. The difference between the two algorithms also lies in the size of the output file of the 3D model. The dAR3D file is significantly larger  with high resolution (3000 × 3000 or more) and a high density of greyscale values of the HU or RGB matrix, the reconstruction process with a direct algorithm can be very time consuming. These circumstances significantly extend the time limits for effective reconstruction of 3D models, but they can be overcome with the help of cloud processing (4th data processing paradigm—op. Cit.) ,95,96.Advantages, disadvantages and limitations of both algorithms are summarised in The reconstruction of surface-based and volumetric 3D models of an archaeological object with both algorithms confirmed the extraordinary informative value of the model for an objective assessment of the current state of the artefact. The additional information about the condition of the artefact obtained in this way can also be of great help to conservators in selecting the most appropriate methods and techniques for conservation and protection.Professional work in the field of cultural heritage conservation, archaeology, conservation and museology cannot be imagined without the use of new scientific methods and techniques originating in the natural sciences, or without the use of new computer and information technologies, artificial intelligence, collections of 3D models, multimedia, robotics, computer analysis of deformations and other modern technologies . Indeed, 3D surface-based models and volumetric 3D models , volumetric 3D analyses and CT have become indispensable for documentation for the permanent, integrated conservation and presentation of tangible cultural heritage today and in the future.The importance of 3D surface-based and volumetric 3D models and 3D computer visualisations enriches the standards for archaeological and cultural heritage recommended by the London Charter , the SevAt the same time, computed tomography and the reconstruction of 3D volumetric  models and 3D surface-based models from tomographic or microtomographic images can effectively contribute to the implementation of Rule 4 of the Amendments to the UNESCO Convention for the Protection of the Underwater Cultural Heritage, which recommends that state authorities and institutions apply nondestructive methods to cultural heritage remains .It would be appropriate for the archaeological and conservation professions to use noninvasive computed tomography more frequently than in the past and to model successful practises as standard methods and techniques for dealing with fragile and rapidly degradable cultural heritage remains.Both the algorithms for reconstructing 3D surface-based and 3D volumetric models from CT images can be upgraded with new methods from the fields of computer vision, deep learning and artificial intelligence. By upgrading algorithms to reconstruct 3D models, we could complement or even replace the autonomous analytical function of humans in the treatment and evaluation of cultural heritage remains. Experiences with algorithms such as Deep Learning already represent a significant advance in the automatic recognition and processing of 2D images from computed tomography. Methods and techniques ranging from convolutional neural networks (CNNs) to variational auto-encoders (VAEs) are being used. These artificial intelligence methods are already delivering successful results in the automatic recognition of complex patterns in computed tomographic image data, particularly in the faster and more efficient segmentation of features and the automatic diagnosis of X-ray image conditions .


Water with the necessary quality is indispensable to the functioning of most of the known life forms, being essential to human health, social and economic development, and ecosystems functioning. However, only 2.5% of all water on Earth is freshwater, and less than 1% is accessible, its availability being actually affected by climate change and direct human impacts. Furthermore, population growth and industry expansion have been leading to the continuous degradation of freshwater quality around the world. Under these circumstances, ensuring sufficient and safe water supplies for everyone is one of the Sustainable Development Goals (SDGs) set by the United Nations General Assembly in 2015 for the year 2030. For this goal to be achieved, the development and implementation of appropriate and efficient wastewater treatments is a major challenge.The application of polymers and polymeric materials in wastewater treatment is a research field that has greatly developed from the end of the last century. The very nature, structure, and versatility of polymers make them useful for many applications, including wastewater treatment processes. Conventional and novel approaches have been elaborated or refined by researchers from different areas, who have demonstrated that polymers and polymeric materials may have an important role not only in the removal of pollutants of different origin and nature from wastewater but also in the recycling of materials and the improvement of wastewater efficiency and economy.In view of the relevant contribution of polymers and polymeric materials to the conservation of the aquatic environment, namely by their application in wastewater treatment, this Special Issue (SI) was launched for the publication of original research or review papers within this topic. The aim was to bring forth the challenges and discuss current trends and perspectives in the utilization of polymers and polymeric materials—either synthetic or natural—for the treatment or purification of wastewater.Eleven research works ,9,10,11 N,N-dimethylacetamide) by the sputtering technique. They demonstrated the efficiency of this technique to load AgNPs, which provided membranes with biocidal properties resistant to biofouling and made them proficient for water disinfection treatments.Abdulsalam et al.  develope2O2 concentration, initial dye concentration, temperature, and presence of electrolytes . Aiming at the catalytic removal of Rhodamine B (RB) dye, Ansari et al. [3O4 nanoparticles (NPs) and sodium dodecyl sulfate (SDS) coated Fe3O4 NPs (SDS@Fe3O4) by the co-precipitation method. RB degradation was tested in presence of H2O2, H2O2 and Fe3O4 NPs, and H2O2 and SDS@Fe3O4 NPs, the latter providing an increased catalytic removal, as the SDS coating avoided the aggregation of Fe3O4 and the associated efficiency reduction.Mia et al.  loaded i2 and pyrolysis at 600 °C. The adsorption of Cr (VI) by the produced SLACM was shown to be favored by decreasing pH (within pH 2 and 9) and increasing temperature (within 20 and 40 °C). Hoshima et al. [In the field of adsorptive treatments, Khan et al.  investig3O4 magnetic nanocomposite (P(St-b-AAc)/Fe3O4)) and tested it for the adsorption of antibiotic ciprofloxacin from synthetic wastewater. This work included the optimization of operational parameters, namely antibiotic concentration, pH, nanocomposite mass, and contact time, and showed that P(St-b-AAc)/Fe3O4 was efficient in the adsorptive removal of ciprofloxacin. Aiming at the adsorption of selective serotonin reuptake inhibitor (SSRI) antidepressants and their metabolites from water, Gornik et al. [3O4 by an in situ one-step procedure, which was loaded onto yeast cells to obtain MY. Then, MY was used as core for the polymerization of MIPs using SMX as template to produce MY@MIPs. The authors compared MY@MIPs with MY and non-imprinted MY@NIPs (synthesized in the same way as MY@MIPs but in the absence of template) and evidenced the superior SMX adsorption capacity of MY@MIPs. Furthermore, besides the selectivity of MY@MIPs towards SMX in the presence of other pharmaceuticals and in real wastewater, the reutilization capability of this material was also proved, pointing to its possible application as an alternative adsorbent for SMX selective removal from wastewater.Four papers in the SI dealt with the adsorptive removal of pharmaceuticals ,7,9,10. Membrane filtration and catalytic applications together with the utilization of polymeric materials for the adsorptive removal of pollutants were discussed in this SI. Furthermore, it is worth highlighting the attention given to the adsorptive removal of pharmaceuticals from wastewater. Since the 1990s, a growing scientific concern about pharmaceuticals may be inferred from the number of related publications, and this SI was no exception. Such a concern is mainly related to (i) the analytic development that has made possible their detection at trace levels and the confirmation of their ubiquity in environment; and (ii) the ecological risks related to their potential to cause physiological responses in non-target individuals, including endocrine disruption and antibiotic resistance. An important benefit of pharmaceuticals removal by adsorption is that such a treatment does not result into the formation of by-products, which in some cases can be more hazardous than the parent compounds. Polymers have been used for long in conventional wastewater treatment for the flocculation/coagulation of solids, so that they may be easily separated from water. However, the SI hereby presented makes evident that polymers and polymeric materials may have many new and varied applications in wastewater treatment. Most published works take advantage of polymers’ versatility and capacity to be combined or modified to produce advanced materials with relevant features for water treatment. In fact, polymer modification is presently a hot topic, since it allows for the development of specific and even smart materials for target applications in different sectors, including wastewater treatment. Owing to the efforts of polymer engineers and scientists, many alternative and advanced polymeric materials are continuously developed. In the specific case of wastewater treatment, polymer applications have become very important due to the increased pollutant removal efficiencies that they offer, so this is a research field in great expansion. The progress in the last years and the successful applications of polymer and polymeric materials are reflected by the high quality works published within this SI.


Materials and Methods. All patients recruited from October 2018 to July 2019 were treated in OncoFort Hospital, Bucharest, with nivolumab or pembrolizumab. We investigated T lymphocyte CD3+, CD4+, CD8+, and CD4/CD8 cells by flow cytometry in patients before and after receiving treatment with anti-PD-1 agents. Results. We found that the responder group showed higher expression on CD4+ cells than the nonresponder group after the first cycle of immunotherapy. The prediction of the immunotherapeutic effect revealed that the elevation of T lymphocytes CD8+ and CD4+ after the first cycle of immunotherapy was followed by a decrease in their expression after the second cycle and was followed by a return almost to that one after the first administration. Conclusion. Our work indicates that the evaluation of the cells of the immune system in relation to the tumor and immunotherapy may lead to a better understanding of the pathogenic mechanisms and the identification of prognostic and predictive factors that will more effectively model the therapeutic approach.Immunotherapy using immune checkpoint inhibitors has revolutionized the treatment, and many types of cancer show a response rate of 20–40% and a significant increase in five-year survival. However, immunotherapy is expensive and may cause serious adverse events. Therefore, a predictive method allowing identification of responding patients before starting the treatment would be very useful. In this study, we aimed to identify and implement other individual prognosis factors, factors that could lead to an improved clinical decision made in regard to the patient to establish an individualized treatment.  Cancer has been the second leading cause of mortality after cardiovascular disease for several years, and, in some countries, it has become the leading cause of death recently. Immunotherapy, using immune checkpoint inhibitors, has revolutionized the treatment, and many types of cancer show a response rate of 20–40% and a significant increase in five-year survival. However, immunotherapy is expensive and may cause serious adverse events , 2. TherOver 83,000 new cases of cancer were recorded in Romania in 2018, and 50,900 Romanians died because of this disease in 2017, according to data from the Global Cancer Observatory . AcOne of the main tools in the arsenal of the immune system is a group of specialized cells known as lymphocytes. Lymphocytes are divided into three main populations, different in terms of function and surface markers: T lymphocytes, B lymphocytes, and “natural killer” (NK) lymphocytes. The specific surface markers for T, B, and NK cells are CD3, CD19, and CD16+56, respectively. CD3 is expressed in 60–80% of normal lymphocytes in peripheral blood and 65–85% in thymocytes. T lymphocytes perform complex functions—both as an effector of the cell-mediated and regulatory immune response—through humoral factors they secrete, called lymphokines. They perform the following functions: regulation of the immune response, control the cells that express non-self-molecules on their surface, and, last but not least, mediation of the reactions of delayed hypersensitivity . CD4+ lyCurrently, the anticheckpoints that are used in oncology target inhibitory receptors are CTLA4 (cytotoxic T-lymphocyte-associated antigen 4) and PD-1 (programmed cell death protein 1) and its PD-L1 ligand. CTLA4 and PD-1 are two such checkpoints, which are expressed on activated T cells and attenuate the effector T cell response. The first generation of anticheckpoints targets CTLA4. CTLA4 is expressed in T cells, cytotoxic CD8+, and also at the level of CD4+ auxiliary T and regulatory T (TReg) cells. It intervenes early in T cell activation in the secondary lymphoid organs, during the presentation of the tumor antigen by the naive T lymphocyte dendritic cells, by inhibiting lymphocyte activation in T effectors. CTLA4 molecules are present inside intracellular vesicles and are only transported to the surface of the lymphocyte only when the TCR-specific antigen is recognized. It is an early modulator of lymphocyte activation: if the stimulation via the TCR is stronger, more CTLA4 is produced in large quantities. CTLA4, which is an inhibitory coreceptor, has the same ligands as the CD28 activator coreceptor: CD80 and CD86. As CTLA4 has a stronger affinity for these ligands than CD28, it counteracts the activating effect of the CD28 and results in lymphocyte inhibition. The second generation of anticheckpoints targets the PD-1 coinhibitor receptor or one of its PD-L1 receivers. The way of the programmed cell death protein 1 (PD-1) is another negative feedback that has the peculiarity of acting later in the process of lymphocyte activation at the level of peripheral tissues and the tumor microenvironment. While CTLA4 regulates the early activation of the naive T lymphocyte in the lymph node, the PD-1 receptor acts on the activation of the T lymphocyte during its effector phase on contact with the tumor –15.There has been extensive research on novel biological markers that are specific to the mechanism of action of immune checkpoint inhibitors that may predict response to therapy, and these markers have been recently and extensively reviewed.In this study, we included 20 patients, all of which were hospitalized and diagnosed with advanced renal cancer, lung cancer and melanoma (stage IV) regardless of the status of programmed death ligand 1 (PD-L1). The patients were all treated with immunotherapy using nivolumab (240 mg) or pembrolizumab (200 mg) alone. Each cycle is of 14 days and starts from the day the patient received nivolumab and of 21 days starting from the day the patient received pembrolizumab. We assessed the state of illness every cycle by checking the blood tests and radiological test after 8–12 weeks from the first day of treatment. All patients were evaluated by imaging according to the criteria of RECIST 1.1 and according to the protocol of nivolumab and pembrolizumab administration. Each patient received at least 3 doses of pembrolizumab and 4–6 doses of nivolumab. The age range was from 40 to 77 years . Informed consent was obtained from all patients, and all procedures performed in the study involving human participants were in accordance with the ethical standards. If patients had brain metastases at study entry, they were initially stabilized by radiation therapy.Peripheral blood samples (5 mL) were collected from 20 patients in every cycle before treatment with anti-PD-1 antibodies. We collected three blood samples in total from each patient. The second sample was taken 14 or 21 days after the first cycle of PD-1 antibody treatment. The study complied with the Declaration of Helsinki and was approved by the Institutional Review Board Ethics Committee of OncoFort Hospital, Bucharest, Romania, no. 6133/02.09.2018.We used flow cytometry technique for analyzing the modifications of different subsets of lymphocytes in relation to the response to immunotherapy.The principle of the method is as follows.Flow cytometry is a technique that allows the measurement of the properties of suspended biological particles running through a flow system. The term consists of three other basic terms , and the suspension represents the state in which the particles are dispersed in a fluid. The marked samples are purchased from the flow cytometer. During the acquisition of the sample, the cells move one by one through a laser beam scattering the incident light . At the same time, fluorochrome-labeled cells emit fluorescence generated by fixing labeled reagents. These scattering and fluorescence signals, detected by the instrument, provide information about the cell size (FSC), its internal complexity (SSC), and the relative fluorescence intensity. Three distinct stages of processing the scattered light and fluorescence emitted by the analyzed particles can be described. In the first stage , the light coming from the cells is collected by means of optical devices, being then selected by filtering certain wavelengths that are directed to the detectors. In the second stage , at the level of the detectors, an electrical signal is generated proportional to the intensity of the captured optical signal. In the third stage , the electrical impulses produced by the detectors are amplified. The electrical signals are then converted into digital values that can be processed, stored, and displayed by the computer attached to the system. The cells appear graphically as agglomerations of dots forming distinct cell populations , and the device records the values in the form of percentages of sets and subsets of the tested cell populations .P < 0.05.The data are shown as median values, with error bars representing the range from the minimum value (lower bar) to the maximum value (upper bar). The results were analyzed using the Kruskal–Wallis nonparametric test (ANOVA). Statistical analysis and graphing were performed using GraphPad Prism, version 5.0 . Results were considered statistically significant at In this study, we included 20 patients diagnosed with advanced malignant renal, lung, and melanoma tumors (stage IV) with a mean age of 60 (extreme: 40–77 years). Gender distribution was equal, that is, 10 female patients and 10 male patients were included .Of the total number of patients, there were 2 women and 6 men with lung cancer group, 8 women and 2 men with melanoma, and only two male patients with kidney cancer .The median age of the patients diagnosed with lung cancer was 64 years; for melanoma, it was 59 years for women and 55 years for males; and it was 55 years for kidney cancer. Based on the clinical evaluation, 12 patients had stable disease, 6 patients had progressive disease, and 2 dead.We aimed to quantify the extent of lymphodepletion or increase of T lymphocytes following immunotherapy. We found a mean decrease of CD4/CD8 ratio and low values of T lymphocytes in two patients before and after the first administration of immunotherapy, which was associated with a poor prognosis.The two patients included in the study who died after a first administration of immunotherapy presented the following values of T lymphocytes: 19.14% CD3+, 8.11% CD4+, and 9.30% CD8+.Interesting is the case of the second patient, who died after 2 immunotherapy administrations and who presented instead the low CD4/CD8 ratio of 0.45 before the first administration and 0.43 after the second administration.We dynamically tested the expression of immune biomarkers by flow cytometry before the first administration and after the other administrations of immunotherapy for all patients.We analyzed the variation in trends of each biomarker. Some of the biomarkers on circulating T cells showed a difference between groups at the before treatment time point, and we believe the reason for this is that these patients were diagnosed with different types of cancer and had previously received different chemotherapeutic agents in lung and renal cancer and target therapy for BRAF mutation in melanoma, which influenced the initial state of their immune systems. No variants of dynamic evaluations were observed depending on the tumor type or gender.Immune checkpoint inhibitors have not been associated with severe immune-related adverse events (ir AEs) such as rashes, diarrhea, colitis, hypophysis disorder, hepatotoxicity, and hypothyroidism.From the total number of patients, we extracted 2 patients who performed a number of 11 immunotherapy administrations so that we could show the dynamics of T lymphocytes during the treatment, which is exemplified in Tables A 77-year-old female patient with metastatic melanoma, without BRAF mutation and previous treatment, is the first case presented and treated with nivolumab (240 mg) as a first line at an interval of 14 days.The second patient is a 58-year-old male diagnosed with advanced lung cancer. Nivolumab was given as a second-line treatment, and cytotoxic chemotherapy was given as the first-line treatment.We subsequently subtracted the individual expression values from the mean of the appropriate time point and drew a trend curve to assess changes in expression, which can be seen in the figures above.In graphical representation, it is observed that the CD3+, CD4+, and CD8+ counts followed the same trend initially downward then upward.We evaluated the absolute numbers of the above-mentioned immune cell subsets to confirm their impact on OS and response to treatment. In agreement with the data shown in Figures The change in the CD4/CD8 ratio before and after one course of immunotherapy is shown in These results  reveal tImmune checkpoints are essential for the maintenance of immune self-tolerance. Tumor cells can escape from these immune-regulatory mechanisms, allowing cancer to continue to grow and metastasize.In this research, we have focused on 3 types of cancer—renal cancer, lung cancer, and melanoma—with impact on the population. In this study, we obtained a blood-based immune signature on circulating T cells before and early during immunotherapy. Lung cancer is the most commonly occurring cancer in men and the third most commonly occurring cancer in women. There were 2 million new cases in 2018 . MelanomThe evaluation of the immune system is difficult to perform due to the multitude of factors involved in patients diagnosed with cancer . At presThe prognostic importance of the expression of PD-1 on tumor-infiltrating lymphocytes and circulating T cells is demonstrated in a number of studies –28. ZhenOur study is the first to describe the variation tendency of biomarker expression during the cycles of immunotherapy in different localizations of the primary tumor, and we constructed a simple model to predict the therapeutic effect of immunotherapy.By analyzing the cells of the immune system, we will be able to determine if the patient responds to the treatment or not. Another novelty of this study is that we are in the peak period of immunotherapy and no markers have been found to track the response to treatment, the doctor stops treatment only on the basis of imaging investigations, and the evaluation of the cells of the immune system is useful.Evaluation of T lymphocytes in the blood and their correlation with the percentage of T lymphocytes in the tumor lymphocyte infiltrate will show us how the immune system responds to the disease and what we can develop to get a better response.Previous studies have shown that the ratio of CD4/CD8 T cells reflects the status of the immune system and can independently predict mortality from all causes. Shah et al. , in his The present study showed a statistically significant association between the change in the CD4/CD8 ratio before and after one course of immunotherapy and the downward tendency of the CD4/CD8 ratio during one course of immunotherapy, suggesting an active immunological response against cancer invasion.There are conflicting literature data on the decrease in the proportion of CD4+T lymphocytes in the blood as a result of tumor invasion, causing CD4+ cells to migrate from the blood to the tumor site. There are studies that claim that tumor eradication is associated with a low number of CD4+ T lymphocytes and studies that claim that an increased percentage of CD4+ T lymphocytes are associated with the response to treatment and eradication of the tumor , 34.There is also evidence that CD8+ T lymphocytes represent the class of lymphocytes that correlate best with favorable overall clinical outcomes, usually infiltrating breast lesions to the greatest extent . It has In a previous study involving 678 patients treated with autologous activated lymphocyte immunotherapy, the CD4+ T cell numbers were maintained at almost the same level compared with the levels before immunotherapy, whereas the CD8 T cell number increased significantly the result obtained in our study .There are several different kinds of immunotherapy using different phenotypic proportions of CD4 and CD8 T cells and differing CD4/CD8 ratios. A study which involved 100 patients with metastatic breast cancer who had received direct subcutaneous injection of low-dose IL-2 and administration of oral retinoic acid to prevent tumoricidal activity and were followed up for 3 years showed that the lymphocyte count, NK cell numbers, and the CD4/CD8 ratio were found to increase significantly .One limitation in this study is the impossibility to evaluate PD-L1 expression for patients with melanoma and kidney cancer.It would be interesting to correlate the imaging data evaluation of peritumoral TILS with the values of the T lymphocytes in the blood.In general, the decrease in the immunoreactive threshold in the neoplastic patient affects the numerical balance of lymphoid cells in the peripheral circulation, deviating from the normal percentage values of different cell sets and subsets, especially total T lymphocytes (CD3+), “helper” T lymphocytes (helper CD4+), and cytolytic and “suppressor” T lymphocytes (CD8+). Therefore, the determination of the proportions of CD3+, CD4+, and CD8+ cells is useful in the evaluation of monitoring patients with immune status affected by cancer. The values of the obtained parameters can be correlated either with the immunosuppressive state given by the tumor, its stage of expansion, and consistency of the immunoreactive means of the body, or with the immune status resulting from the application of immunosuppressive treatments .The evaluation of the cells of the immune system in relation to the tumor and immunotherapy may lead to a better understanding of the pathogenic mechanisms and the identification of prognostic and predictive factors that will more effectively model the therapeutic approach.


After 2 months, on the 6th of May 2021 she was brought to the hospital in Sawangi, with complaints of pain over the right side of the face which was sudden in onset, continuous, dull aching, radiating to forehead on the right side with the history of associated swelling over the right side of the face which was initially small in size and gradually increased to present size of 3 x 2 cm approx, with history of difficulty in mastication, deglutition and speech were altered, nasal stiffness over the right side since 15 days. She is a known case of hypothyroidism for 20 years, diabetes mellitus and hypertension for 10 years with chronic kidney disease. On extraoral examination patient's face was asymmetrical due to fungal infection and diffused swelling over the right side of the face and opthalmoplegia, blurring of vision, ptosis, chemosis and restricted eye movements. Intraoral examination reveals mouth opening of 25mm with diffuse gingival swelling seen in the upper right maxillary alveolar region extending anteroposteriorly from 11 to 26 regions. Magnetic resonance imaging brain and orbit reveals invasive fungal sinusitis with the cutaneous collection and intracranial extension of mucormycosis.We are presenting the case of a 75-year-old female who tested positive for COVID-19 in the 2