In manual maintenance inspections of large-scaled photovoltaic (PV) or rooftop PV systems, several days are required to survey the entire PV field. To improve reliability and shorten the amount of time involved, this study proposes an electrical examination based method for locating multiple faults in the PV array. The maximum power point tracking (MPPT) algorithm is used to estimate the maximum power of each PV panel; this is then compared with metering the output power of PV array. Power degradation indexes are parameterized to quantify the degradation between maximum power and metered output power. Bidirectional hetero-associative memory (BHAM) networks are then used to locate multiple faults within the entire PV field. For a rooftop PV system with two strings, as seen in Figure 1, experimental results demonstrate that the proposed model has computational efficiency for real-time applications and that its algorithm is easily implemented in a mobile intelligent vehicle.

Our environment has been impacted by man-made pollutants mainly industries make substantial use of synthetic dyes which exhibit cytotoxicity and have significant environmental consequences. Effective photocatalyst-based approaches for degrading synthetic dyes into less toxic chemical are of great interest. Synthesizing NPs using biological approaches, particularly plant-based approaches offer advantages, decreasing the risk of NPs losing biocompatibility during synthesis, cost-effectiveness, and eco-friendliness. In this study, we employed a green synthesis method to produce manganese oxide nanoparticles (MnO NPs) utilizing leaf extract from the Lathyrus Aphaca plant. The synthesized MnOx NPs were characterized through various techniques; X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), and UV–visible spectroscopy. XRD analysis showed distinct peaks, indicated the presence crystallographic planes within the MnO₂ nanoparticles, thus confirming their crystalline structure. SEM study highlighted closely packed configurations with average size of approximately ≥ 50-70 nm, with well-defined boundaries. EDX analysis showed the presence of elemental manganese (Mn) in the samples, with peaks corresponding to Mn detected at lower energy levels, predominantly represented by MnO. FTIR, showed the presence of the O-O stretching mode at a frequency of 719 cm^-1, the presence of MnO₆ oxides of manganese, and peak at 548 cm^-1 corresponded to the Mn-O stretching mode. Furthermore, the green-synthesized manganese oxide nanoparticles exhibited promising photocatalytic and adsorption capabilities against Methylene Blue (MB) dye, leading to approximately 93.21% degradation of MB when treated with the green-synthesized MnO nanoparticles derived from plant extract. This highlights the efficacy and potential of these nanoparticles in environmental remediation applications, particularly in the degradation of methylene blue contaminants.

Ti-aluminosilicate gels were used as supports for immobilization of Fe, Co and Ni oxides (5%) by impregnation, and synthesis of efficient photocatalysts in degradation of β-lactam antibiotic from water. Titanium oxide (1 and 2%) was incorporated into zeolite network by modifying the gel during the zeolitation process. The formation of the zeolite Y structure and its microporous structure were evidenced by X-ray diffraction and N2 physisorption. The structure, composition, reduction and optical properties were studied by X-ray difraction, H2-TPR, XPS, Raman, photoluminiscence and UV-Vis spectroscopy. The obtained results indicated a zeolite Y structure for all photocatalysts with tetra-coordinate Ti4+ sites. The immobilized metals from group VIII are both in the form of metal oxides such as Fe2O3, Fe3O4, CoO, Co3O4 , NiO and also in the me-tallic state (Fe0, Co0, and Ni0). A red shift of the absorption edge was observed in UV-Vis spectra of photocatalysts upon addition of Fe, Co or Ni species. The photocatalytic performances were evaluated in degradation of cefuroxime from water under visible light irradiation. The best results were obtained for iron immobilized photocatalysts. Scavenger experiments explained the photocatalytic results and their mechanisms. A different contribution of the active species to the photocatalytic reactions was evidenced.

The ubiquitin proteasome system (UPS) utilizes an orchestrated enzymatic cascade of E1, E2, and E3 ligases to add single or multiple ubiquitin-like molecules as post-translational modification (PTM) to proteins. Ubiquitination can alter protein functions and/ or marks ubiquitinated proteins for proteasomal degradation but deubiquitinases (DUBs) can reverse protein ubiquitination. While the importance of DUBs as regulatory factors in the UPS is undisputed, many questions remain on DUB selectivity for protein targeting, their mechanism of action, and the impact of DUBs on the regulation of diverse biological processes. Furthermore, little is known about the expression and role of DUBs in tumors of the human central nervous system (CNS). In this comprehensive review, we have used publicly available transcriptional datasets to determine the gene expression profiles of 99 deubiquitinases (DUBs) from five major DUB families in seven primary pediatric and adult CNS tumor entities. Our analysis identified selected DUBs as potential new functional players and biomarkers with prognostic value in specific subtypes of primary CNS tumors. Collectively, our analysis highlights an emerging role for DUBs in regulating CNS tumor cell biology and offers a rationale for future therapeutic targeting of DUBs in CNS tumors.

Forest degradation is known to be widespread in the tropics, but is currently very poorly mapped, in part because there is little quantitative data on which satellite sensor characteristics and analysis methods are best at detecting it. To improve this, we used data from the Tropical Forest Degradation Experiment (FODEX) plots in the southern Peruvian Amazon, where different numbers of trees had been removed from four 1 ha forest plots, carefully inventoried by hand and Terrestrial Laser Scanning before and after the logging to give a range of biomass change (ΔAGB) values. We conducted a comparative study of six multispectral optical satellite sensors (WorldView-3, SkySat, SPOT-7, PlanetScope, Sentinel-2 and Landsat 8) at 0.3 – 30 m spatial resolution, to find the best combination of sensor and remote sensing indicator for change detection. Spectral reflectance, the Normalized Difference Vegetation Index (NDVI) and texture parameters were extracted after radiometric calibration and image preprocessing. The strength of the relationships between the change in these values and field-measured ΔAGB (computed in % ha−1) was analysed. The results demonstrate that: (a) texture measures correlates more with ΔAGB than simple spectral parameters; (b) the strongest correlations are achieved for those sensors with spatial resolutions in the intermediate range (1.5 - 10 m), with finer or coarser resolutions producing worse results, and (c) when texture is computed using a moving square window ranging between 9 - 14 m in length. Maps predicting ΔAGB showed very promising results using a NIR-derived texture parameter for 3 m resolution PlanetScope (R2 = 0.97 and RMSE = 1.80 % ha−1), followed by 1.5 m SPOT-7 (R2 = 0.74 and RMSE = 5.25 % ha−1) and 10 m Sentinel-2 (R2 = 0.71 and RMSE = 5.55 % ha−1). Texture models derived from 0.3 m WorldView-3 improved with increasing window size, with highest R2 of 0.62 and RMSE = 6.35 % ha−1 for a window of 14 m in length. The degradation in our field plots is invisible to the 30 m resolution Landsat data. Our findings imply that, at least for lowland Peru, low-medium intensity disturbance can be detected best in optical wavelengths using a texture measure derived from 3 m PlanetScope data. That such data are being collected daily, and currently released free as monthly mosaics over tropical forests as part of the Norway’s International Climate and Forest Initiative (NICFI), is excellent news for monitoring such degradation.

The objective of this work is to identify the mechanism of dropwise condensation on a smooth solid surface. We investigate the stable dropwise condensation that occurs at a droplet growth rate of 1 µm/s in diameter on a gold-coated glass surface. Additionally, we present our observations on unstable dropwise condensation, i.e., degradation of dropwise condensation of steam on a gold surface. The Surface Plasmon Resonance Imaging (SPRi) approach used in this study has lateral resolutions of 4-10 µm, thickness resolutions of 0.1-1 nm, and temporal resolutions of 200-10,000 frames per second (FPS). SPRi is used to evaluate the existence and structure of thin films and occurrence of initial nuclei during condensation. Visualization of the onset of stable dropwise condensation suggests droplets form at heterogeneous nucleation sites and that no film greater than a monolayer exists on the surface before the formation of droplets. Observation of the unstable dropwise condensation of steam shows the existence of water films that are several nanometers thick between droplets. This work shows that neither the nucleation theory or film rupture theory can individually explain the physics of dropwise condensation. Therefore, there is a need for a more comprehensive theory that can explain the mechanism of dropwise condensation.

Abstract—The static and fatigue analysis of plates with holes, made of 2D woven roving composites, is conducted. The parametrization of convex holes is proposed. Experimental results of specimens without holes and with different shapes of notches are discussed. The fatigue behaviour is considered with the use of the low cycle fatigue method. The analysis is supplemented by the numerical finite element modeling. The present work is an extension of the results discussed in the literature. The finite element modeling of plates with holes is presented in details in Ref [1-3] including also the problems of the accuracy. The experimental results and the form of specimens are shown in Ref [4]. Two parametrical description of static and fatigue behaviour of plates with holes characterizes the goal and the novelty of the paper. The fuzzy approach is employed to reduce the number of experimental data [5].

In addition to nucleic acids, various viral proteins are involved in the assembly of virion. If it is possible to create a biologically active agent that leads to the degradation of one of the key proteins for virus assembly and/or destroys the viral factory, then this agent will effectively cope with virus replication. One of these key proteins for the SARS-CoV-2 virus is the nucleocapsid protein (N-protein). As such a bioactive agent, we offer a modular nanotransporter (MNT) developed by us, which, in addition to an antibody mimetic to the N-protein, contains an amino acid sequence for the attraction of the Keap1 E3 ubiquitin ligase. This should lead to the subsequent degradation of the N-protein. We have shown that functional properties of modules within the MNT permit its internalization into target cells, endosome escape into the cytosol, and binding to the N-protein. Using flow cytometry and Western blot, it was demonstrated that significant degradation of N-protein is observed when A549 and A431 cells transformed with N-protein are incubated with the developed MNTs. The proposed MNTs open up a new approach for the treatment of viral diseases.

Current satellite remote sensing methods struggle to detect and map forest degradation, a critical issue as it is likely a major and growing source of carbon emissions and biodiveristy loss. TanDEM-X InSAR phase height (hϕ) is a promising variable for measuring forest disturbances, as it is closely related to mean canopy height, and thus should decrease if canopy trees are removed. However, previous research has focused on relatively flat terrain, despite the fact that much of the worlds’ remaining tropical forests are found in hilly areas, and this inevitably introduces artifacts in sideways imaging systems. In this paper, we find a relationship between hϕ and aboveground biomass change in four selectively logged plots in a hilly region of central Gabon. We show that minimising the level of multilooking in the interferometric processing chain strengthens this relationship, and that degradation estimates across steep slopes in the surrounding region are improved by selecting data from the most appropriate pass directions on a pixel-by-pixel basis. This shows that TanDEM-X InSAR can measure the magnitude of degradation, and that topographic effects can be mitigated if data from multiple SAR viewing geometries are available.

In China, the production of crop straw has been estimated to be approximately 800 Million tons yearly of which about 40% was burned. Corn stover is one of the main agricultural wastes in China. It has shown that lignin in corn stover could be effectively removed byMyrothecium verrucaria. The effects of the pretreatment of corn strover by Myrothecium verrucaria on compost were studied. The results showed that corn stover pretreatment by Myrothecium verrucaria, the Cellulose, Hemicellulose, and lignin were degraded and the results were 33.43%, 11.53% and 18.70% respectively. Scanning electron microscope (SEM) analysis showed that the surface structure of corn stover was changed. Fourier transform infrared spectroscopy (FTIR) analysis showed that the degradation products of lignin were increased. The exposed area of cellulose and hemicellulose was increased. Compared with the control group, the pH value was stable and the temperature was higher. The content of nitrogen in the material decreased, while the contents of total phosphorus and total potassium increased.The C/N ratio of materials decreased after composting.The results showed that the pretreatment of Myrothecium verrucaria improve the degradation of lignocelluloses, a great contribution was made to reduce the causes loss of plant nutrient and to fight against environmental pollution.

As a vital component of the terrestrial ecosystem, grassland accounts for one-third of the global vegetation system. Grassland degradation has been exacerbated due to extreme overgrazing in China's Inner Mongolia Autonomous Region (IMAR). While conservation was carried out as the Ecological Subsidy and Award Program (ESAP) to mitigate grassland degradation, little is known about its effectiveness in improving the biophysical conditions of grassland. This paper integrates the conceptual frameworks of total socio-environmental systems to assess how ecological systems respond to ESAP, investigate spatial heterogeneity of ESAP, and explore the meddling effects of socio-environmental interactions on ESAP. We integrate ecological, climate, and socioeconomic data and developed several hierarchical linear mixed models (HLMM) to investigate how these factors interact with ESAP in IMAR. Our findings prove that the above-ground biomass between 2011 and 2015 responds significantly to variations in socioeconomic conditions and ecological communities. Available land resources, hospital and medical facilities, and net farmer and herdsman income are the most critical factors contributing to grassland productivity. Primary industries like mining, total consumer retail value, farming, forestry, animal husbandry, fishery productions, and GDP are the most damaging factors affecting biomass. Our study recommends a regionally or locally tailored ecological recovery policy, instead of a generalized one, in the future effort to conserve grassland.

We propose a deep learning algorithm that directly compensates for luminance degradation owing to the deterioration of organic light emitting diode (OLED) devices to address the burn-in phenomenon of OLED displays. Conventional compensation circuits are encumbered by a high cost of development and manufacturing processes owing to their complexity. However, given that deep learning algorithms are typically mounted on a system on chip (SoC), the complexity of the circuit design is reduced, and the circuit can be reused by re-learning only the changed characteristics of the new pixel device. The proposed approach comprises deep feature generation and multi-stream self-attention, which decipher the importance of the variables, and the correlation between burn-in-related variables. It also utilizes a deep neural network that identifies the nonlinear relationship between the extracted features and luminance degradation. Thereafter, the luminance degradation is estimated from the burn-in-related variables, and the burn-in phenomenon can be addressed by compensating for the luminance degradation. The experimental results revealed that compensation was successfully achieved within an error range of 4.56%, and demonstrate the potential of a new approach that can mitigate the burn-in phenomenon by directly compensating for pixel-level luminance deviation.

Targeted Protein Silencing (TPS) is an elegant approach to investigate protein function and its role in the cellular landscape, overcoming limitations of genetic perturbation strategies. In contrast to CRISPR/Cas9 and RNA interference, these systems act in a reversible manner and reduce off-target effects. Several TPS have been developed and wisely improved, including compartment delocalization tools and protein degradation systems. In this review, we focus on Anchor-Away, deGradFP, auxin inducible degron (AID) and dTAG technologies, and discuss their recent applications and advances. Finally, we propose Nano-Grad, a novel nanobody-based protein degradation tool to specifically proteolyze endogenous tag-free target protein.

The steel damper column is an energy-dissipating member that is suitable for reinforced concrete (RC) buildings, and those used for multistory housing in particular. However, the effectiveness of steel damper columns may be affected by the behavior of surrounding members, and this effect can be severe in the case of seismic sequences. This article investigates the nonlinear response of building models having an RC moment-resisting frame (MRF) with and without steel damper columns under seismic sequences. The applicability of the concept of the momentary energy input to the prediction of the peak response of RC MRFs with damper columns under seismic sequences is also investigated. The main findings of the study are summarized as follows. (1) The peak response of RC MRFs with damper columns subjected to sequential accelerations is similar to the peak response obtained considering only the mainshock, whereas the cumulative strain energy of RC MRFs accumulates more for sequential accelerations. (2) The steel damper column is effective in reducing the peak and cumulative responses of RC MRFs in the case of sequential seismic input. (3) The relation of the hysteretic dissipated energy during a half cycle of the structural response and the peak displacement of the first modal response can be properly evaluated using the simple model proposed in this study.

Research on healthy ageing shows that lifespan reductions are often caused by mitochondrial dysfunction. Thus, it is very interesting that the deletion of mitochondrial matrix peptidase LonP1 was observed to abolish embryogenesis, while deletion of the mitochondrial matrix peptidase ClpP prolonged survival. To unveil the targets of each enzyme, we documented the global proteome of LonP1^+/- mouse embryonal fibroblasts (MEF), for comparison with ClpP^-/- depletion. Proteomic profiles of LonP1^+/- MEF generated by label-free mass spectrometry were further processed with the STRING webserver Heidelberg for protein interactions. ClpP was previously reported to degrade Eral1 as a chaperone involved in mitoribosome assembly, so ClpP deficiency triggers accumulation of mitoribosomal subunits and inefficient translation. LonP1^+/- MEF also showed Eral1 accumulation, but no systematic effect on mitoribosomal subunits. In contrast to ClpP^-/- profiles, several components of the respiratory complex I membrane arm were accumulated, whereas the upregulation of numerous innate immune defense components was similar. Overall, LonP1 as opposed to ClpP appears to have no effect on translational machinery, instead it shows enhanced respiratory dysfunction; this agrees with reports on the human CODAS syndrome caused by LonP1 mutations.

Artificial intelligence systems are increasingly becoming a component of security-critical applications. The protection of such systems from various types of destructive influences is thus a relevant area of research. The vast majority of previously published works are aimed at reducing vulnerability to certain types of disturbances or implementing certain resilience properties. At the same time, the authors either do not consider the concept of resilience as such, or their understanding varies greatly. This work presents a formalized definition of resilience and its characteristics for artificial intelligence systems from a systemic point of view. It systematizes ideas and approaches to building resilience to various types of disturbances. Taxonomy of resilience of artificial intelligence systems to destructive disturbances is proposed. Approaches and technologies for complex protection of intelligent systems, issues of their resource efficiency and other open research issues are considered. Approaches of resilience assessment for artificial intelligence system are also analyzed and recommendations are provided for their implementation.

Free volume is an extremely important intrinsic defect in polymers. Structurally, the free volume is the randomly distributed holes in the polymer molecular chain segments. From the perspective of molecular movement, it is also the space needed for the movement of molecular segments. In proton exchange membrane fuel cells, the free volume is also the space needed for the directional conduction of protons. Irradiation grafting sulfonated polyvinylidene fluoride (PVDF) is one of the methods to produce proton exchange membrane with good proton channel rate. Using the LYS-1 program, based on the linear absorption coefficient and backscatter coefficient models, the percentage of annihilated positrons in PVDF in the two-layer model and the three-layer model was studied, and comparing the two fitting results it is determined that the model closest to the positron annihilation percentage required by the PALS experiment is the two-layer model, which allows the percentage of positrons that are annihilated in PVDF films with a thickness of 100 μm to reach 46% using the high energy positron source ⁴⁴Ti without using the positron moderator. Using positron annihilation lifetime spectrum (PALS) analysis methods, based on Eldrup's classical model of free volume, the influence of absorbed doses of α particles on the free volume and crystallinity of PVDF was investigated, respectively. Based on the two test results the model of cross-linking and degradation of polyvinylidene fluoride irradiated by α particles was determined. Afterwards, X-ray diffraction (XRD) methods was used to study the change of PVDF crystal area before and after irradiation. The XRD results are consistent with the results measured by PALS.

Organosilicate glass (OSG) films are a vital component in modern electronic devices, with their electrical properties playing a crucial role in device performance. This comprehensive review systematically examines the influence of chemical composition, vacuum ultraviolet (VUV) irradiation, and plasma treatment on the electrical properties of OSG films. Through an extensive survey of literature and experimental findings, we elucidate the intricate interplay between these factors and the resultant alterations in electrical conductivity, dielectric constant, and breakdown strength of OSG films. Key focus areas include the impact of diverse organic moieties incorporated into the silica matrix, the effects of VUV irradiation on film properties, and the modifications induced by various plasma treatment techniques. Furthermore, we discuss the underlying mechanisms governing these phenomena, shedding light on the intricate molecular interactions and structural rearrangements occurring within OSG films under different environmental conditions. This review not only consolidates existing knowledge but also identifies gaps in understanding and suggests avenues for future research, thereby advancing our comprehension of OSG film behavior and paving the way for enhanced performance in next-generation electronic and photonic devices.

This paper investigates the effects that rain drop erosion has on the integrity of wind turbine materials. This research involves analysis of impact models and theoretical equations to simulate the impact phenomena when a raindrop collides with a wind turbine blade at high speed. Impact phenomena that occur when a raindrop impacts with a wind turbine blade were evaluated. Additionally, the use of various types of software was considered to simulate this impact event. The model results of the raindrop impact with respect to a comparison of the governing equations and impact behaviour are addressed. Future work is outlined including adding variables to the erosion modelling algorithms.

A reduced order model is developed to monitor aeroengines condition (defining their degradation from a baseline state) in real-time, by using data collected in specific sensors. This reduced model is constructed by applying higher order singular value decomposition plus interpolation to appropriate data, organized in tensor form. Such data are obtained using a detailed engine model that takes the engine physics into account. Thus, the method synergically combines the advantages of data-driven (fast online operation) and model-based (the engine physics is accounted for) condition monitoring methods. Using this reduced order model as surrogate of the engine model, two gradient-like condition monitoring tools are constructed. The first tool is extremely fast and able to precisely compute `on the fly’ the turbine inlet temperature, which is a paramount parameter for the engine performance, operation, and maintenance, and can only be roughly estimated by the engine instrumentation in civil aviation. The second tool is not so fast (but still reasonably inexpensive) and precisely computes both, the engine degradation and the turbine inlet temperature at which sensors data have been acquired. These tools are robust in connection with random noise added to the sensors data and can be straight forwardly applied to other mechanical systems.

The good management of the building maintenance should be based on the regular maintenance work. Repair works are often not carried out or there are shifts in time, which causes degradation of the building. The article presents a method of planning renovation works of a MUBAR (maintenance Management in an Un-renovated Building with Abandoning Renovation) based on the consequences in case of their lack. No renovation work on individual elements in a building can cause a threat to the stability of the building structure, risking the lives of users, continuing damage to the building by damaging further elements, or even a building disaster. The method can also be applied to historic buildings. Often, due to abandonment of repairs caused most often by lack of the owner, improper manager or irresponsible users, degradation of these objects occurs. The consequences of neglected renovation of buildings lead to irreversible processes of their destruction. The aim of the article is to present the developed method of planning renovation works based on the consequences of lack of renovation works.

Alzheimer’s disease (AD) and the therapies of AD with anti-amyloid1-42 (Aβ) monoclonal antibodies are associated with the vascular complications of brain edema, hemorrhage, and cerebral amyloid angiopathy (CAA) termed amyloid-related imaging abnormalities (ARIAs). The neuropathology of normal and AD brains demonstrates that monocyte/macrophages (MMs) are critical in successful brain clearance in healthy brain by up-loading, transporting, and degrading Aβ but fail degradation and clearance in AD patients by releasing Aβ into vessels at the blood-brain barrier, causing vasculitis and ARIAs. The naturally-formed epoxides (EpFAs) of polyunsaturated fatty acids (PUFA’s), including arachidonic, docosahexaenoic, and eicosapentaenoic fatty acids, may repair degradation of Aβ by regulating Aβ-degrading enzymes, inflammatory cytokines, and unfolded protein response (UPR) to endoplasmic reticulum stress in a homeostatic fashion. EpFAs are, however, degraded by the soluble epoxide hydrolase enzyme (sEH) but are protected by the sEH inhibitor (sEHI) TPPU. In the cultures of AD patients’ macrophages, TPPU with the epoxide EEQ, and the cGAS/STING inhibitor H-151 increased uptake of Aβ at 2 hours and degradation of Aβ at 24 hours. In conclusion, the soluble epoxide hydrolase inhibitor TPPU with omega-3 fatty acids and the cGAS/STING inhibitor H-151 increase Aβ uptake and degradation in macrophages of AD patients, and potentially enhancing Aβ clearance in the AD brain.

A novel cytoplasmic dye decolorizing peroxidase from Dictyostelium discoideum was investigated that oxidizes anthraquinone dyes, lignin model compounds and general peroxidase substrates like ABTS efficiently. Unlike related enzymes, an aspartate residue replaces the first glycine of the conserved GXXDG motif in Dictyostelium DyPA. In solution, Dictyostelium DyPA exists as a stable dimer with the side chain of Asp146 contributing to the stabilization of the dimer interface by extending the hydrogen bond network connecting two monomers. To gain mechanistic insights, we solved the Dictyostelium DyPA structures in the absence of substrate as well as in the presence of potassium cyanide and veratryl alcohol to 1.7, 1.85, and 1.6 Å resolution, respectively. The active site of Dictyostelium DyPA has a hexa-coordinated heme iron with a histidine residue at the proximal axial position and either an activated oxygen or CN^- molecule at the distal axial position. Asp149 is in an optimal conformation to accept a proton from H₂O₂ during the formation of compound I. Two potential distal solvent channels and a conserved shallow pocket leading to the heme molecule were found in Dictyostelium DyPA. Further, we identified two substrate-binding pockets per monomer in Dictyostelium DyPA at the dimer interface. Long-range electron transfer pathways associated with a hydrogen-bonding network that connects the substrate-binding sites with the heme moiety are described.

(1) Teeth, represent in humans the most resilient tissues. However, exposure to concentrated acids might lead to their obliteration, thus making human identification difficult. Teeth often contain dental restorations from materials that are even more resilient to acid impact. This paper introduces novel method of 3D reconstruction of dental patterns as a crucial step for digital identification with dental records.; (2) With combination of modern methods of Micro-Computer Tomography, Cone Beam Computer Tomography, Attenuated Total Reflection in conjunction with Fourier-Transform Infrared Spectroscopy and Artificial Intelligence Convolutional Neural Network algorithms, the paper presents the way of 3D dental pattern reconstruction and human remains identification. Research studies morphology of teeth, bone, and dental materials (Amalgam, Composite, Glass-ionomer cement) under different periods of exposure to 75% sulfuric acid; (3) Results reveal significant volume loss in bone, enamel, dentine, and as well glass-ionomer cement. Results also reveal significant resistance of composite and amalgam dental materials to sulfuric acid impact, thus serving as strong parts in the dental pattern mosaic. Paper also introduces probably first successful artificial intelligence application in automated forensic CBCT segmentation.; (4) Interdisciplinary cooperation utilizing mentioned technologies can solve problem of human remains identification with 3D reconstruction of dental patterns and their 2D projections over existing ante-mortem records.

B-cell lymphoid malignancies is a heterogeneous group of hematologic cancers, where Bruton's tyrosine kinase (BTK) inhibitors have received FDA approval for several subtypes. The first-in-class covalent BTK inhibitor, ibrutinib, binds to the C481 amino acid residue to block the BTK enzyme and prevent the downstream signaling. Resistance to covalent BTK inhibitors can occur through mutations at the BTK binding site (C481S) but also other BTK sites and the phospholipase C gamma 2 (PLCγ2) resulting in downstream signaling. To bypass the C481S mutation, non-covalent BTK inhibitors, such as pirtobrutinib, were developed and are active against both wild-type and the C481S mutation. In this review, we discuss the molecular and genetic mechanisms which contribute to acquisition of resistance to covalent and non-covalent BTK inhibitors. In addition, we discuss the new emerging class of BTK degraders, which utilize the evolution of proteolysis-targeting chimeras (PROTACs) to degrade the BTK protein and constitute an important avenue of overcoming resistance. The moving landscape of resistance to BTK inhibitors and the development of new therapeutic strategies highlight the ongoing advances, that are being made towards the pursue of cure of B-cell lymphoid malignancies.