Water-Doped Brønsted Acidic Protic Ionic Liquids for Enhanced Tributyl Citrate Synthesis in a Two-Phase Esterification System

Tributyl citrate (TBC) plays a crucial role as a plasticizer, enhancing the flexibility of polymers such as polyvinyl chloride. Its biodegradability and non-toxic nature contribute to eco-friendly appeal, making it a preferred additive in diverse industries, including food packaging, medical devices, toys, and consumer goods. Herein, a method for the synthesis of TBC using inexpensive Brønsted acidic protic ionic liquids (ILs) in a two-phase reaction system is presented. The esterification process is carried out with high yield (>99 %), selectivity (up to 98 %) and short reaction time of 2 h. The catalyst in the form of IL shows excellent performance and stability, desirable for industrial applications.

The Use of Natural Language Processing Elements for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Enterally Fed Patients with Head and Neck or Upper Gastrointestinal Tract Cancers

BACKGROUND

Psycho-oncology care has emerged as a significant concern in contemporary oncology practice, given its profound impact on patient psychological well-being. Patients undergoing treatment for head-neck or upper gastrointestinal tract cancers often experience complex emotional and psychological challenges, necessitating specialized support and intervention. Traditional approaches to psycho-oncological care may be limited in their ability to comprehensively assess and address patients' needs. Therefore, exploring innovative methodologies, such as leveraging natural language processing (NLP) elements, is crucial to enhancing the effectiveness of psycho-oncological interventions.

METHODS

In this study, we developed a method utilizing natural language processing (NLP) elements to augment psycho-oncological care for patients with head-neck or upper gastrointestinal tract cancers. The method aimed to facilitate vocabulary, sentiment, and intensity analysis of five basic emotions (happiness, sadness, anger, disgust, and fear), as well as to explore potential areas of difficulty such as body image, pain, and self-esteem. We conducted research involving 50 patients across three treatment stages.

RESULTS

Our method facilitated the identification of characteristic features at each treatment stage, aiding in the tailoring of appropriate therapies to individual patient needs. The results offer insights valuable to psychologists and psychiatrists for expedited diagnosis and intervention, potentially influencing therapy outcomes. Additionally, the data may inform treatment decisions by addressing patient-specific concerns. Furthermore, our method holds promise for optimizing the allocation of psychological care resources, particularly at the initial stages of patient contact.

LIMITATIONS

The main problem in the research was the fairly wide age range of participants, which explains the potential diversity of vocabulary.

CONCLUSION

In conclusion, our study demonstrates the potential utility of integrating natural language processing (NLP) elements into psycho-oncological care for patients with head-neck or upper gastrointestinal tract cancers. The developed method offers a novel approach to comprehensively assessing patients' emotional states and areas of difficulty, thereby facilitating tailored interventions and treatment planning. These findings underscore the importance of continued research and innovation in psycho-oncology to enhance patient care and outcomes.

The influence of UV radiation on the properties of GFRP laminates in underwater conditions

Degradation of polymer composites is a significant problem in many engineering aspects. Due to the interaction of various degradation factors during the exploitation of composites, a synergistic effect of destruction is observed. The article describes the phenomena occurring in glass fiber reinforced polyester laminates under the influence of ultraviolet radiation (UV) in an aquatic environment. The laminates were exposed to UV-A, UV-B and UV-C radiation for 1000 h in free-air and underwater conditions. During the test, the materials were immersed at stable depth of 1 mm and 10 mm, respectively. The three-point bending tests performed on the samples after being exposed to UV showed an increase in the flexural strength of the composites. Simultaneously, degradation of the outer surface layer was observed. The degradation removed the thin resin film from the surface which resulted in a direct exposure of the reinforcing fibers to the environment. The transformations taking place in the deeper layers of the composite increased the mechanical strength due to the additional cross-linking reactions excited by the energy arising from the radiation. Moreover, the formation of polymer structures from free styrene remaining after the technological process and the occurrence of free radical reactions as a result of the cage effect was also observed.

Automated detection and recognition system for chewable food items using advanced deep learning models

Identifying and recognizing the food on the basis of its eating sounds is a challenging task, as it plays an important role in avoiding allergic foods, providing dietary preferences to people who are restricted to a particular diet, showcasing its cultural significance, etc. In this research paper, the aim is to design a novel methodology that helps to identify food items by analyzing their eating sounds using various deep learning models. To achieve this objective, a system has been proposed that extracts meaningful features from food-eating sounds with the help of signal processing techniques and deep learning models for classifying them into their respective food classes. Initially, 1200 audio files for 20 food items labeled have been collected and visualized to find relationships between the sound files of different food items. Later, to extract meaningful features, various techniques such as spectrograms, spectral rolloff, spectral bandwidth, and mel-frequency cepstral coefficients are used for the cleaning of audio files as well as to capture the unique characteristics of different food items. In the next phase, various deep learning models like GRU, LSTM, InceptionResNetV2, and the customized CNN model have been trained to learn spectral and temporal patterns in audio signals. Besides this, the models have also been hybridized i.e. Bidirectional LSTM + GRU and RNN + Bidirectional LSTM, and RNN + Bidirectional GRU to analyze their performance for the same labeled data in order to associate particular patterns of sound with their corresponding class of food item. During evaluation, the highest accuracy, precision,F1 score, and recall have been obtained by GRU with 99.28%, Bidirectional LSTM + GRU with 97.7% as well as 97.3%, and RNN + Bidirectional LSTM with 97.45%, respectively. The results of this study demonstrate that deep learning models have the potential to precisely identify foods on the basis of their sound by computing the best outcomes.

Enhancing parasitic organism detection in microscopy images through deep learning and fine-tuned optimizer

Parasitic organisms pose a major global health threat, mainly in regions that lack advanced medical facilities. Early and accurate detection of parasitic organisms is vital to saving lives. Deep learning models have uplifted the medical sector by providing promising results in diagnosing, detecting, and classifying diseases. This paper explores the role of deep learning techniques in detecting and classifying various parasitic organisms. The research works on a dataset consisting of 34,298 samples of parasites such as Toxoplasma Gondii, Trypanosome, Plasmodium, Leishmania, Babesia, and Trichomonad along with host cells like red blood cells and white blood cells. These images are initially converted from RGB to grayscale followed by the computation of morphological features such as perimeter, height, area, and width. Later, Otsu thresholding and watershed techniques are applied to differentiate foreground from background and create markers on the images for the identification of regions of interest. Deep transfer learning models such as VGG19, InceptionV3, ResNet50V2, ResNet152V2, EfficientNetB3, EfficientNetB0, MobileNetV2, Xception, DenseNet169, and a hybrid model, InceptionResNetV2, are employed. The parameters of these models are fine-tuned using three optimizers: SGD, RMSprop, and Adam. Experimental results reveal that when RMSprop is applied, VGG19, InceptionV3, and EfficientNetB0 achieve the highest accuracy of 99.1% with a loss of 0.09. Similarly, using the SGD optimizer, InceptionV3 performs exceptionally well, achieving the highest accuracy of 99.91% with a loss of 0.98. Finally, applying the Adam optimizer, InceptionResNetV2 excels, achieving the highest accuracy of 99.96% with a loss of 0.13, outperforming other optimizers. The findings of this research signify that using deep learning models coupled with image processing methods generates a highly accurate and efficient way to detect and classify parasitic organisms.

The Relevance of Reperfusion Stroke Therapy for miR-9-3p and miR-9-5p Expression in Acute Stroke-A Preliminary Study

Reperfusion stroke therapy is a modern treatment that involves thrombolysis and the mechanical removal of thrombus from the extracranial and/or cerebral arteries, thereby increasing penumbra reperfusion. After reperfusion therapy, 46% of patients are able to live independently 3 months after stroke onset. MicroRNAs (miRNAs) are essential regulators in the development of cerebral ischemia/reperfusion injury and the efficacy of the applied treatment. The first aim of this study was to examine the change in serum miRNA levels via next-generation sequencing (NGS) 10 days after the onset of acute stroke and reperfusion treatment. Next, the predictive values of the bioinformatics analysis of miRNA gene targets for the assessment of brain ischemic response to reperfusion treatment were explored. Human serum samples were collected from patients on days 1 and 10 after stroke onset and reperfusion treatment. The samples were subjected to NGS and then validated using qRT-PCR. Differentially expressed miRNAs (DEmiRNAs) were used for enrichment analysis. Hsa-miR-9-3p and hsa-miR-9-5p expression were downregulated on day 10 compared to reperfusion treatment on day 1 after stroke. The functional analysis of miRNA target genes revealed a strong association between the identified miRNA and stroke-related biological processes related to neuroregeneration signaling pathways. Hsa-miR-9-3p and hsa-miR-9-5p are potential candidates for the further exploration of reperfusion treatment efficacy in stroke patients.

Synthesis and Primary Activity Assay of Novel Benitrobenrazide and Benserazide Derivatives

Schiff bases attract research interest due to their applications in chemical synthesis and medicinal chemistry. In recent years, benitrobenrazide and benserazide containing imine moiety have been synthesized and characterized as promising inhibitors of hexokinase 2 (HK2), an enzyme overexpressed in most cancer cells. Benserazide and benitrobenrazide possess a common structural fragment, a 2,3,4-trihydroxybenzaldehyde moiety connected through a hydrazone or hydrazine linker acylated on an N' nitrogen atom by serine or a 4-nitrobenzoic acid fragment. To avoid the presence of a toxicophoric nitro group in the benitrobenrazide molecule, we introduced common pharmacophores such as 4-fluorophenyl or 4-aminophenyl substituents. Modification of benserazide requires the introduction of other endogenous amino acids instead of serine. Herein, we report the synthesis of benitrobenrazide and benserazide analogues and preliminary results of inhibitory activity against HK2 evoked by these structural changes. The derivatives contain a fluorine atom or amino group instead of a nitro group in BNB and exhibit the most potent inhibitory effects against HK2 at a concentration of 1 µM, with HK2 inhibition rates of 60% and 54%, respectively.

Raw and Pre-Treated Styrene Butadiene Rubber (SBR) Dust as a Partial Replacement for Natural Sand in Mortars

The circular economy (CE) is widely known for its emphasis on reducing waste and maximizing the use of resources by reusing, recycling, and repurposing materials to create a sustainable and efficient system. The CE is based on 3R-reuse, reduce, and recycle. The aim of this article is to use styrene butadiene rubber dust (SBR) in building material, constituting secondary waste in the production of SBR, which is currently disposed of as landfill. SBR is partly intended to replace the natural raw material sand. The purpose of the final material is to use it for its light weight, insulating properties, or ability to absorb vibrations and sounds. Various shares of SBR dust in mortars were tested. Some of the mortars used SBR thermal pre-treatment at temperatures of 200, 275, and 350 °C. The strength and SEM results are presented. The best pre-treatment for SBR dust is thermal treatment at 275 °C. The maximum usage of rubber dust with thermal treatment is 60% as a sand substitute. The novel finding of this study is the possibility to use more than 30% rubber dust (as a substitute for sand) thanks to pre-treatment, whereby 30% is a common maximum ratio in mortars.

Assessment of refining efficiency during the refining cycle in a foundry degassing unit in industrial conditions

The article focuses on the issue of improving the efficiency of a Foundry Degassing Unit (FDU) via operational testing of aluminium alloys during casting at MOTOR JIKOV Slévárna a.s.. As part of the research, the efficiency of the refining process in the FDU was assessed. The main emphasis was placed on determining the moment of the greatest decrease in the hydrogen content in the melt and whether it is possible to shorten the refining cycle. The values of the Dichte Index were determined, on the basis of which the degassing curve was plotted and the progress of the melt degassing was assessed. To ensure the required quality of castings, the maximum allowable value of the Dichte Index ranged from 3 to 4%. During the process, the temperature drop during the refining cycle was also determined. The total temperature drop from pouring the melt into the ladle to the end of refining ranged from 26 to 32 °C, which is within the acceptable limits of the foundry. Based on the knowledge resulting from the operational experiments, recommendations were formulated to optimize the refining technology at the FDU for the MOTOR JIKOV Slévárna a.s. foundry.

Chemical Modification of Dental Dimethacrylate Copolymer with Tetramethylxylylene Diisocyanate-Based Quaternary Ammonium Urethane-Dimethacrylates-Physicochemical, Mechanical, and Antibacterial Properties

In this study, two novel quaternary ammonium urethane-dimethacrylates (QAUDMAs) were designed for potential use as comonomers in antibacterial dental composite restorative materials. QAUDMAs were synthesized via the reaction of 1,3-bis(1-isocyanato-1-methylethyl)benzene with 2-(methacryloyloxy)ethyl-2-decylhydroxyethylmethylammonium bromide (QA10+TMXDI) and 2-(methacryloyloxy)ethyl-2-dodecylhydroxyethylmethylammonium bromide (QA12+TMXDI). Their compositions with common dental dimethacrylates comprising QAUDMA 20 wt.%, urethane-dimethacrylate monomer (UDMA) 20 wt.%, bisphenol A glycerolate dimethacrylate (Bis-GMA) 40 wt.%, and triethylene glycol dimethacrylate (TEGDMA) 20 wt.%, were photocured. The achieved copolymers were characterized for their physicochemical and mechanical properties, including their degree of conversion (DC), glass transition temperature (Tg), polymerization shrinkage (S), water contact angle (WCA), flexural modulus (E), flexural strength (FS), hardness (HB), water sorption (WS), and water leachability (WL). The antibacterial activity of the copolymers was characterized by the minimum bactericidal concentration (MBC) and minimum inhibitory concentration (MIC) against Staphylococcus aureus and Escherichia coli. The achieved results were compared to the properties of a typical dental copolymer comprising UDMA 40 wt.%, Bis-GMA 40 wt.%, and TEGDMA 20 wt.%. The introduction of QAUDMAs did not deteriorate physicochemical and mechanical properties. The WS and WL increased; however, they were still satisfactory. The copolymer comprising QA10+TMXDI showed a higher antibacterial effect than that comprising QA12+TMXDI and that of the reference copolymer.

Correlation dimension and entropy in the assessment of sex differences based on human gait data

Introduction

It is proved that there are differences between gait performed by females and males, which appear in movements of selected body parts. Despite numerous state-of-the-art studies related to the discriminative analysis of motion capture data, the question of whether measures of signal complexity and uncertainty can extract valuable features for the problem of sex distinction still remains open. It is the subject of the paper.

Methods

Correlation dimension, as well as approximate and sample entropies, are selected to describe motion data. In the numerical experiments, the collected dataset with 884 samples of 25 females and 30 males was used. The measurements took place in the Human Motion Laboratory (HML), equipped with a highly precise motion capture system. Two variants of data representation were investigated-time series that contain joint rotations of taken skeleton model as well as positions of the markers attached to the human body. Finally, a comparative analysis between the populations of females and males using descriptive statistics, non-parametric estimation, and statistical hypotheses verification was carried out.

Results

There are statistically significant sex differences extracted by the taken measures. In general, the movements of lower limbs result in greater values of correlation dimension and entropies for females, while selected upper body parts play a similar role for males. The dissimilarities are mainly observed in hip, ankle, shoulder, and head movements.

Discussion

Correlation dimension and entropy measures provide robust and explainable features of motion capture data with a valuable description of the human locomotion system. Thus, beyond the importance of discovered differences between females and males, their interpretation and understanding are also known.

Two-Stage Leaching of PCBs Using Sulfuric and Nitric Acid with the Addition of Hydrogen Peroxide and Ozone

The paper presents the possibility of recovering metals from printed circuit boards (PCBs) of spent mobile phones using the hydrometallurgical method. Two-stage leaching of Cu(II), Fe(III), Sn(IV), Zn(II), Ni(II) and Pb(II) with H2SO4 (2 and 5 M) and HNO3 (2 M) with the addition of H2O2 (10 and 30%) and O3 (9 or 15 g/h) was conducted at various process conditions (temperature-313, 333 and 353 K, time-60, 120, 240, 300 min, type and concentration of leaching agent, type and concentration of oxidant, solid-liquid ratio (S/L)), allowing for a high or total metals leaching rate. The use of two leaching stages allows for the preservation of selectivity, separation and recovery of metals: in the first stage of Fe(III), Sn(IV) and in the second stage of the remaining tested metal ions, i.e., Cu(II), Zn(II), Ni(II) and Pb(II). Removing Fe from the tested PCBs' material at the beginning of the process eliminates the need to use magnetic methods, the purpose of which is to separate magnetic metal particles (ferrous) from non-magnetic (non-ferrous) particles; these procedures involve high operating costs. Since the leaching of Cu(II) ions with sulfuric(VI) acid practically does not occur (less than 1%), this allows for almost complete transfer of these ions into the solution in the second stage of leaching. Moreover, to speed up the process and not generate too many waste solutions, oxidants in the form of hydrogen peroxide and ozone were used. The best degree of leaching of all tested metal ions was obtained when 2 M sulfuric(VI) acid at 353 K was used in the 1st research stage, and 2 M nitric(V) acid and 9 g/h O3 at 298 K in the 2nd stage of leaching, which allowed it to be totally leached 100% of Fe(III), Cu(II), Sn(IV), Zn(II), Ni(II) and 90% Pb(II).

Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies

Radiomics is an emerging approach to support the diagnosis of pulmonary nodules detected via low-dose computed tomography lung cancer screening. Serum metabolome is a promising source of auxiliary biomarkers that could help enhance the precision of lung cancer diagnosis in CT-based screening. Thus, we aimed to verify whether the combination of these two techniques, which provides local/morphological and systemic/molecular features of disease at the same time, increases the performance of lung cancer classification models. The collected cohort consists of 1086 patients with radiomic and 246 patients with serum metabolomic evaluations. Different machine learning techniques, i.e., random forest and logistic regression were applied for each omics. Next, model predictions were combined with various integration methods to create a final model. The best single omics models were characterized by an AUC of 83% in radiomics and 60% in serum metabolomics. The model integration only slightly increased the performance of the combined model (AUC equal to 85%), which was not statistically significant. We concluded that radiomics itself has a good ability to discriminate lung cancer from benign lesions. However, additional research is needed to test whether its combination with other molecular assessments would further improve the diagnosis of screening-detected lung nodules.

Shape-Controlled Iron-Paraffin Composites as γ- and X-ray Shielding Materials Formable by Warmth-of-Hands-Derived Plasticity

The design of shielding materials against ionizing radiation while simultaneously displaying enhanced multifunctional characteristics remains challenging. Here, for the first time, we present moldable paraffin-based iron nano- and microcomposites attenuating γ- and X-radiation. The moldability was gained by the warmth-of-hands-driven plasticity, which allowed for obtaining a specific shape of the composites at room temperature. The manufactured composites contained iron particles of various sizes, ranging from 22 nm to 63 μm. The target materials were widely characterized using XRD, NMR, Raman, TGA, SEM, and EDX. In the case of microcomposites, the shielding properties were developed at two concentrations: 10 and 50 wt %. The statistically significant results indicate that the iron particle size has a negligible effect on the shielding properties of the nano- and microcomposites. On the other hand, the higher iron particle contents significantly affected the attenuating ability, which emerged even as superior to the elemental aluminum in the X-ray range: at a 70 kV anode voltage, the half value layer was 6.689, 1.882, and 0.462 cm for aluminum, paraffin + 10 wt % Fe 3.5-6.5 μm, and paraffin + 50 wt % Fe 3.5-6.5 μm microcomposites, respectively. Importantly, the elaborated methodology-in situ cross-verified in the hospital studies recording real-life sampling-opens the pathway to high-performance, eco-friendly, lightweight, and recyclable shields manufactured via fully reproducible and scalable protocols.

Recycle Option for Municipal Solid Waste Incineration Fly Ash (MSWIFA) as a Partial Replacement for Cement in Mortars Containing Calcium Sulfoaluminate Cement (CSA) and Portland Cement to Save the Environment and Natural Resources

Reduction of emissions, energy consumption, and use of substitutes for natural resources is an element of sustainable development and the circular economy. Cement production is a process with a high carbon footprint; therefore, minimizing the use of this material has a significant impact on reducing environmental costs. A substitute for cement is municipal solid waste incineration fly ash (MSWIFA). The article presents a method of making an eco-concrete with the use of municipal solid waste incineration hazardous fly ash. The use of secondary waste for the production of building materials additionally contributes to achieving climate neutrality established by the European Union and China. The article analyzes the physicochemical properties of various MSWIFAs, the amount and leachability of heavy metals, and selected elements from MSWIFA and concrete properties. The technical properties of mortars containing MSWIFA were investigated. Consistency is not affected by MSWIFA content, although the workability time is prolonged. Air entraining admixture efficiency is lowered, but the effect lasts longer. The initial setting time is prolonged, and the flexural and compressive strengths are decreased in early terms because of the zinc presence in MSWIFA. MSWIFA does not influence the water demand, volume stability of mortars, or microstructure of cement's hydration products.

Eco-Conscious Approach to Thermoresponsive Star-Comb and Mikto-Arm Polymers via Enzymatically Assisted Atom Transfer Radical Polymerization Followed by Ring-Opening Polymerization

This study explores the synthesis, characterization, and application of a heterofunctional initiator derived from 2-hydroxypropyl cyclodextrin (HP-β-CD), having eight bromoester groups and thirteen hydroxyl groups allowing the synthesis of mikto-arm star-shaped polymers. The bromoesterification of HP-β-CD was achieved using α-bromoisobutyryl bromide as the acylation reagent, modifying the cyclodextrin (CD) molecule as confirmed by electrospray ionization mass spectrometry (ESI-MS), nuclear magnetic resonance (NMR), attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy analysis, and differential scanning calorimetry (DSC) thermograms. The initiator's effectiveness was further demonstrated by obtaining star-comb and mikto-arm polymers via an enzymatically assisted atom transfer radical polymerization (ATRP) method and subsequent ring-opening polymerization (ROP). The ATR polymerization quality and control depended on the type of monomer and was optimized by the way of introducing the initiator into the reaction mixture. In the case of ATRP, high conversion rates for poly(ethylene oxide) methyl ether methacrylate (OEOMA), with molecular weights (Mn) of 500 g/mol and 300 g/mol, were achieved. The molecular weight distribution of the obtained polymers remained in the range of 1.23-1.75. The obtained star-comb polymers were characterized by different arm lengths. Unreacted hydroxyl groups in the core of exemplary star-comb polymers were utilized in the ROP of ε-caprolactone (CL) to obtain a hydrophilic mikto-arm polymer. Cloud point temperature (TCP) values of the synthesized polymers increased with arm length, indicating the polymers' reduced hydrophobicity and enhanced solvation by water. Atomic force microscopy (AFM) analysis revealed the ability of the star-comb polymers to create fractals. The study elucidates advancements in the synthesis and utilization of hydrophilic sugar-based initiators for enzymatically assisted ATRP in an aqueous solution for obtaining complex star-comb polymers in a controlled manner.

1-Hydroxyalkylphosphonium Salts-Synthesis and Properties

An efficient and convenient method for the synthesis of 1-hydroxyalkylphosphonium salts is described. Reactions were carried out at room temperature, in a short time, and without chromatography for product isolation. The properties of the obtained phosphonium salts were examined and discussed. In this paper, primary attention was paid to the stability of phosphonium salts, depending on the structure of the aldehydes used as substrates in their preparation. Other conditions such as the type of solvent, temperature, and molar ratio of the substrates were also investigated. Finally, the high reactivity of 1-hydroxyalkylphosphonium salts was demonstrated in reactions with amide-type substrates and (hetero)aromatic compounds. The developed step-by-step procedure (with the isolation of 1-hydroxyphosphonium salts) was compared to the one-pot protocol (in situ formation of such phosphonium salts).

Compensative Resistance to Erastin-Induced Ferroptosis in GPX4 Knock-Out Mutants in HCT116 Cell Lines

Ferroptosis results from the accumulation of oxidized and damaged lipids which then leads to programmed cell death. This programmed process is iron-dependent, and as a fundamental biological process, plays a crucial role in tissue homeostasis. The ferroptosis molecular pathway depends on self-regulatory genes: GPX4; TFRC; ACSL4; FSP1; SLC7A11, and PROM2. Some of them were considered here as ferro-sensitive or ferro-resistance markers. We examined the impact of GPX4 gene knock-out, using the CRISPR/Cas-9 technique, on ferroptosis induction in the HCT116 colorectal cancer cell line. The results confirmed that cells lacking the GPX4 gene (GPX4 KO) should be more susceptible to ferroptosis after erastin treatment. However, the decrease in cell viability was not as significant as we initially assumed. Based on the lipid peroxidation markers profile and RT-qPCR gene expression analysis, we revealed the activation of an alternative antioxidant system supporting GPX4 KO cells, mostly for cellular ferroptotic death avoidance. Increased expression of FSP1 and PRDX1 genes in knock-out mutants was associated with their function-recognized here as ferroptosis suppressors. For such reasons, studies on the role of GPX4 and other crucial genes from the ferroptotic pathway should be explored. Despite promising prospects, the utilization of ferroptosis mechanisms in cancer therapy remains at the stage of experimental and in vitro preclinical studies.

Structural characterization of newly-developed Al79Ni5Fe5Y11 and Al79Ni11Fe5Y5 alloys with amorphous matrixes

The low glass-forming ability of aluminium-based metallic glasses significantly limits their development and preparation. This paper updates the current state of knowledge by presenting the results of structural studies of two newly-developed Al79Ni5Fe5Y11 and Al79Ni11Fe5Y5 alloys with a reduced aluminium content (< 80 at.%). The alloys were produced by conventional casting (ingots) and melt-spinning (ribbons). Structural characterization was carried out for bulk ingots first, and then for the melt-spun ribbons. The ingots possessed a multiphase crystalline structure, as confirmed by X-ray diffraction and scanning electron microscopy observations. The amorphous structure of the melt-spun ribbons was determined by X-ray diffraction and transmission electron microscopy. SEM observations and EDX element maps of the cross-section of melt-spun ribbons indicated a homogeneous elemental composition. Neutron diffraction revealed the presence of nanocrystals in the amorphous matrix of the melt-spun ribbons. DSC data of the melt-spun ribbons showed exothermic events corresponding to the first crystallization at temperatures of 408 °C and 387 °C for Al79Ni5Fe5Y11 and Al79Ni11Fe5Y5, respectively.

On the reduction of mixed Gaussian and impulsive noise in heavily corrupted color images

In this paper, a novel approach to the mixed Gaussian and impulsive noise reduction in color images is proposed. The described denoising framework is based on the Non-Local Means (NLM) technique, which proved to efficiently suppress only the Gaussian noise. To circumvent the incapacity of the NLM filter to cope with impulsive distortions, a robust similarity measure between image patches, which is insensitive to the impact of impulsive corruption, was elaborated. To increase the effectiveness of the proposed approach, the blockwise NLM implementation was applied. However, instead of generating a stack of output images that are finally averaged, an aggregation strategy combining all weights assigned to pixels from the processing block was developed and proved to be more efficient. Based on the results of comparisons with the existing denoising schemes, it can be concluded that the novel filter yields satisfactory results when suppressing high-intensity mixed noise in color images. Using the proposed filter the image edges are well preserved and the details are retained, while impulsive noise is efficiently removed. Additionally, the computational burden is not significantly increased, compared with the classic NLM, which makes the proposed modification applicative for practical image denoising tasks.

Shaping the Structure and Properties of TiO2-ZnO Oxide Coatings Produced by Plasma Electrolytic Oxidation on Titanium Substrate

The paper presents the results of preliminary research on the possibility of synthesizing ZnO-TiO2 mixed coatings by plasma electrochemical oxidation (PEO). The aim of the work was to synthesize TiO2-ZnO mixed coatings on a titanium substrate from an electrolyte containing ZnO nanoparticles (NPs) and to assess the parameters of PEO on the structure, chemical composition, and properties of the obtained oxide coatings. The PEO process was carried out under various current-voltage conditions using different signals: DC, DC pulse, and AC. In this work, optimal conditions for the PEO process were determined to obtain well-adhering oxide coatings with the highest possible content of ZnO. The structure and morphology of the resulting oxide coatings were investigated, and their chemical and phase composition was comprehensively examined (EDX, XRD, XPS, and GD-OES). In addition, their basic optical properties were assessed. It has been shown that in the PEO DC pulse process, it is possible to obtain oxide coatings characterized by a high degree of structure order, high ZnO content in the oxide coating (3.6 at.%, XPS), and prospective applications for photocatalytic purposes (3.12 eV).

Radix-4 CORDIC algorithm based low-latency and hardware efficient VLSI architecture for Nth root and Nth power computations

In this article, a low-complexity VLSI architecture based on a radix-4 hyperbolic COordinate Rotion DIgital Computer (CORDIC) is proposed to compute the [Formula: see text] root and [Formula: see text] power of a fixed-point number. The most recent techniques use the radix-2 CORDIC algorithm to compute the root and power. The high computation latency of radix-2 CORDIC is the primary concern for the designers. [Formula: see text] root and [Formula: see text] power computations are divided into three phases, and each phase is performed by a different class of the proposed modified radix-4 CORDIC algorithms in the proposed architecture. Although radix-4 CORDIC can converge faster with fewer recurrences, it demands more hardware resources and computational steps due to its intricate angle selection logic and variable scale factor. We have employed the modified radix-4 hyperbolic vectoring (R4HV) CORDIC to compute logarithms, radix-4 linear vectoring (R4LV) to perform division, and the modified scaling-free radix-4 hyperbolic rotation (R4HR) CORDIC to compute exponential. The criteria to select the amount of rotation in R4HV CORDIC is complicated and depends on the coordinates [Formula: see text] and [Formula: see text] of the rotating vector. In the proposed modified R4HV CORDIC, we have derived the simple selection criteria based on the fact that the inputs to R4HV CORDIC are related. The proposed criteria only depend on the coordinate [Formula: see text] that reduces the hardware complexity of the R4HV CORDIC. The R4HR CORDIC shows the complex scale factor, and compensation of such scale factor necessitates the complex hardware. The complexity of R4HR CORDIC is reduced by pre-computing the scale factor for initial iterations and by employing scaling-free rotations for later iterations. Quantitative hardware analysis suggests better hardware utilization than the recent approaches. The proposed architecture is implemented on a Virtex-6 FPGA, and FPGA implementation demonstrates [Formula: see text] less hardware utilization with better error performance than the approach with the radix-2 CORDIC algorithm.

Effects of Multi-Walled Carbon Nanotube Dosages and Sonication Time on Hydration Heat Evolution in Cementitious Composites

This study aimed to investigate the heat generated during the hydration process in cementitious composites containing multi-walled carbon nanotubes (MWCNTs). The cumulative heat release and heat flow of these cementitious composites were measured over a period of 168 h using isothermal calorimetry. Three different MWCNT dosages, 0.05 wt%, 0.1 wt%, and 0.2 wt%, along with two different sonication times for the solution, which were 20 min and 60 min, were applied in the experimental program. The results reveal that the incorporation of MWCNTs and the use of a naphthalene-based superplasticizer to disperse the nanotubes generally led to a reduction in heat emission during the early stages of hydration, a lower first peak value in the initial stage of hydration, and a significant delay in the acceleration period compared with the reference sample lacking this superplasticizer. Furthermore, the results demonstrate that both the dosage of multi-walled carbon nanotubes (MWCNTs) and the sonication time have an impact on the heat emission and hydration process since the same amount of superplasticizer was applied to all pastes. An increase in the MWCNT dosage led to a decrease in the rate of hydration heat at the main peak for all pastes. Additionally, longer sonication times resulted in lower values of heat generated, reduced main peak values in the heat rate evolution, and generally extended delays in the occurrence of the main peak.

Machine learning identification of risk factors for heart failure in patients with diabetes mellitus with metabolic dysfunction associated steatotic liver disease (MASLD): the Silesia Diabetes-Heart Project

BACKGROUND

Diabetes mellitus (DM), heart failure (HF) and metabolic dysfunction associated steatotic liver disease (MASLD) are overlapping diseases of increasing prevalence. Because there are still high numbers of patients with HF who are undiagnosed and untreated, there is a need for improving efforts to better identify HF in patients with DM with or without MASLD. This study aims to develop machine learning (ML) models for assessing the risk of the HF occurrence in patients with DM with and without MASLD.

RESEARCH DESIGN AND METHODS

In the Silesia Diabetes-Heart Project (NCT05626413), patients with DM with and without MASLD were analyzed to identify the most important HF risk factors with the use of a ML approach. The multiple logistic regression (MLR) classifier exploiting the most discriminative patient's parameters selected by the χ2 test following the Monte Carlo strategy was implemented. The classification capabilities of the ML models were quantified using sensitivity, specificity, and the percentage of correctly classified (CC) high- and low-risk patients.

RESULTS

We studied 2000 patients with DM (mean age 58.85 ± SD 17.37 years; 48% women). In the feature selection process, we identified 5 parameters: age, type of DM, atrial fibrillation (AF), hyperuricemia and estimated glomerular filtration rate (eGFR). In the case of MASLD( +) patients, the same criterion was met by 3 features: AF, hyperuricemia and eGFR, and for MASLD(-) patients, by 2 features: age and eGFR. Amongst all patients, sensitivity and specificity were 0.81 and 0.70, respectively, with the area under the receiver operating curve (AUC) of 0.84 (95% CI 0.82-0.86).

CONCLUSION

A ML approach demonstrated high performance in identifying HF in patients with DM independently of their MASLD status, as well as both in patients with and without MASLD based on easy-to-obtain patient parameters.

Application of Sunflower Husk Pellet as a Reducer in Metallurgical Processes

In relation to the climate policy being introduced, the search for a replacement for solid fossil fuels with renewable raw materials is ongoing. In this study, a potential biomass (sunflower husk pellet) application in the process of copper slag reduction was assessed. For the purpose of raw material characterisation, thermogravimetric tests were carried out and characteristic temperature points were determined with the use of a high-temperature microscope. The slag reduction tests led to the recovery of 97% of copper and a decrease in this metal content in the slag to less than 0.5% Cu, which enables safe storage or use in other industrial branches.

Research on the impact of rotor wear on the effectiveness of the aluminium refining process

Physical modelling is successfully used to understand mechanisms involved in the aluminium refining process by injecting inert gas into the liquid metal through rotors. Two types of industrial impellers, which are extremely different in construction, were tested in the research. The aim of the research was to determine the effectiveness of their operation depending on their degree of wear. This type of research has not been tested on water models so far. During the process, the parameters were changed, such as the gas flow rate from 13 to 19 L/min, the rotor speed from 325 to 400 rpm and the height of the rotor from the bottom of the refining reactor. Tests were carried out for new and worn rotors. Oxygen removal rate curves were prepared on the basis of tests determining changes in oxygen content in the model liquid as a function of time for changing rotor speed values. It was found that the efficiency of hydrogen removal from the model liquid was higher when worn impellers were used in the model. In order to verify results of model tests, a metallographic analysis of samples obtained in industrial conditions and using the analysed process parameters was carried out.

The effect of quaternary ammonium polyethylenimine nanoparticles on bacterial adherence, cytotoxicity, and physical and mechanical properties of experimental dental composites

A significant problem related to the functioning of resin-based composites for dental fillings is secondary or recurrent caries, which is the reason for the need for repeated treatment. The cross-linked quaternary ammonium polyethylenimine nanoparticles (QA-PEI-NPs) have been shown to be a promising antibacterial agent against different bacteria, including cariogenic ones. However, little is known about the properties of dental dimethacrylate polymer-based composites enriched with QA-PEI-NPs. This research was carried out on experimental composites based on bis-GMA/UDMA/TEGDMA matrix enriched with 0.5, 1, 1.5, 2 and 3 (wt%) QA-PEI-NPs and reinforced with two glass fillers. The cured composites were tested for their adherence of Streptococcus Mutans bacteria, cell viability (MTT assay) with 48 h and 10-days extracts , degree of conversion (DC), water sorption (WSO), and solubility (WSL), water contact angle (CA), flexural modulus (E), flexural strength (FS), compressive strength (CS), and Vickers microhardness (HV). The investigated materials have shown a complete reduction in bacteria adherence and satisfactory biocompatibility. The QA-PEI-NPs additive has no effect on the DC, VH, and E values. QA-PEI-NPs increased the CA (a favorable change), the WSO and WSL (unfavorable changes) and decreased flexural strength, and compressive strength (unfavorable changes). The changes mentioned were insignificant and acceptable for most composites, excluding the highest antibacterial filler content. Probably the reason for the deterioration of some properties was low compatibility between filler particles and the matrix; therefore, it is worth extending the research by surface modification of QA-PEI-NPs to achieve the optimum performance characteristics.

Metabolic profiling to evaluate the impact of amantadine and rimantadine on the secondary metabolism of a model organism

Metabolic profiling offers huge potential to highlight markers and mechanisms in support of toxicology and pathology investigations during drug development. The main objective was to modify therapy with adamantane derivatives: amantadine and rimantadine, to increase their bioavailability and evaluate the influence of such therapy on drug metabolism using Saccharomyces cerevisiae as the model organism. In this study, the profile of endogenous metabolites of a model organism was measured and interpreted to provide an opportunity to investigate changes induced by treatment with amantadine and rimantadine. It was found that resveratrol supplementation synergistically enhanced the effects of amantadine treatment and increased rimantadine metabolism, potentially reducing side effects. The fingerprinting strategy was used as an efficient technique for qualitatively evaluating and monitoring changes in the profiles of endogenous components and their contents in a model organism. Chemometric tools were employed to find marker compounds that can be defined as characteristic indicators of a pharmacological response to a therapeutic intervention. An improved understanding of the mechanisms involved in drug effect and an increased ability to predict individual variations in the drug response of organisms will improve the treatment process and the development of new therapies.

Flexible, Transparent, and Cytocompatible Nanostructured Indium Tin Oxide Thin Films for Bio-optoelectronic Applications

Electrical stimulation has been used successfully for several decades for the treatment of neurodegenerative disorders, including motor disorders, pain, and psychiatric disorders. These technologies typically rely on the modulation of neural activity through the focused delivery of electrical pulses. Recent research, however, has shown that electrically triggered neuromodulation can be further enhanced when coupled with optical stimulation, an approach that can benefit from the development of novel electrode materials that combine transparency with excellent electrochemical and biological performance. In this study, we describe an electrochemically modified, nanostructured indium tin oxide/poly(ethylene terephthalate) (ITO/PET) surface as a flexible, transparent, and cytocompatible electrode material. Electrochemical oxidation and reduction of ITO/PET electrodes in the presence of an ionic liquid based on d-glucopyranoside and bistriflamide units were performed, and the electrochemical behavior, conductivity, capacitance, charge transport processes, surface morphology, optical properties, and cytocompatibility were assessed in vitro. It has been shown that under selected conditions, electrochemically modified ITO/PET films remained transparent and highly conductive and were able to enhance neural cell survival and neurite outgrowth. Consequently, electrochemical modification of ITO/PET electrodes in the presence of an ionic liquid is introduced as an effective approach for tailoring the properties of ITO for advanced bio-optoelectronic applications.

The cross-correlation-based analysis to digest the conformational dynamics of the mitoBK channels in terms of their modulation by flavonoids

The activity of mitochondrial large-conductance voltage- and [Formula: see text]-activated [Formula: see text] channels (mitoBK) is regulated by a number of biochemical factors, including flavonoids. In particular, naringenin (Nar) and quercetin (Que) reached reasonable scientific attention due to their well-pronounced channel-activating effects. The open-reinforcing outcomes of Nar and Que on the mitoBK channel gating have been already reported. Nevertheless, the molecular picture of the corresponding channel-ligand interactions remains still to be revealed. In this work, we investigate the effects of the Nar and Que on the conformational dynamics of the mitoBK channel. In this aim, the cross-correlation-based analysis of the single-channel signals recorded by the patch-clamp method is performed. The obtained results in the form of phase space diagrams enable us to visually monitor the effects exerted by the considered flavonoids at the level of temporal characteristics of repetitive sequences of channel conformations. It turns out that the mitoBK channel activation by naringenin and quercetin does not lead to the change in the number of clusters within the phase space diagrams, which can be related to the constant number of available channel macroconformations regardless of the flavonoid administration. The localization and occupancy of the clusters of cross-correlated sequences suggest that mitoBK channel stimulation by flavonoids affects the relative stability of channel conformations and the kinetics of switching between them. For most clusters, greater net effects are observed in terms of quercetin administration in comparison with naringenin. It indicates stronger channel interaction with Que than Nar.

GMM-Based Expanded Feature Space as a Way to Extract Useful Information for Rare Cell Subtypes Identification in Single-Cell Mass Cytometry

Cell subtype identification from mass cytometry data presents a persisting challenge, particularly when dealing with millions of cells. Current solutions are consistently under development, however, their accuracy and sensitivity remain limited, particularly in rare cell-type detection due to frequent downsampling. Additionally, they often lack the capability to analyze large data sets. To overcome these limitations, a new method was suggested to define an extended feature space. When combined with the robust clustering algorithm for big data, it results in more efficient cell clustering. Each marker's intensity distribution is presented as a mixture of normal distributions (Gaussian Mixture Model, GMM), and the expanded space is created by spanning over all obtained GMM components. The projection of the initial flow cytometry marker domain into the expanded space employs GMM-based membership functions. An evaluation conducted on three established cellular identification algorithms (FlowSOM, ClusterX, and PARC) utilizing the most substantial publicly available annotated dataset by Samusik et al. demonstrated the superior performance of the suggested approach in comparison to the standard. Although our approach identified 20 cell clusters instead of the expected 24, their intra-cluster homogeneity and inter-cluster differences were superior to the 24-cluster FlowSOM-based solution.

Comparsion of Catalyst Effectiveness in Different Chemical Depolymerization Methods of Poly(ethylene terephthalate)

This paper presents an overview of the chemical recycling methods of polyethylene terephthalate (PET) described in the scientific literature in recent years. The review focused on methods of chemical recycling of PET including hydrolysis and broadly understood alcoholysis of polymer ester bonds including methanolysis, ethanolysis, glycolysis and reactions with higher alcohols. The depolymerization methods used in the literature are described, with particular emphasis on the use of homogeneous and heterogeneous catalysts and ionic liquids, as well as auxiliary substances such as solvents and cosolvents. Important process parameters such as temperature, reaction time, and pressure are compared. Detailed experimental results are presented focusing on reaction yields to allow for easy comparison of applied catalysts and for determination of the most favorable reaction conditions and methods.

Effect of Time on the Properties of Bio-Nanocomposite Films Based on Chitosan with Bio-Based Plasticizer Reinforced with Nanofiber Cellulose

The deterioration of the performance of polysaccharide-based films over time, particularly their hydrophilicity and mechanical properties, is one of the main problems limiting their applications in the packaging industry. In the present study, we proposed to improve the performance of chitosan-based films through the use of: (1) nanocellulose as an additive to reduce their hydrophilic nature; (2) bio-based plasticizer to improve their mechanical properties; and (3) chestnut extract as an antimicrobial agent. To evaluate their stability over time, the properties of as-formed films (mechanical, hydrophilic, barrier and antibacterial) were studied immediately after preparation and after 7, 14 and 30 days. In addition, the morphological properties of the films were characterized by scanning electron microscopy, their structure by FTIR, their transparency by UV-Vis and their thermal properties by TGA. The films showed a hydrophobic character (contact angle above 100°), barrier properties to oxygen and carbon dioxide and strong antibacterial activity against Gram-negative (E. coli) and Gram-positive (S. aureus) bacteria. Moreover, the use of nanofillers did not deteriorate the elongation at breaks or the thermal properties of the films, but their addition reduced the transparency. In addition, the results showed that the greatest change in film properties occurred within the first 7 days after sample preparation, after which the properties were found to stabilize.

Machine learning profiles of cardiovascular risk in patients with diabetes mellitus: the Silesia Diabetes-Heart Project

AIMS

As cardiovascular disease (CVD) is a leading cause of death for patients with diabetes mellitus (DM), we aimed to find important factors that predict cardiovascular (CV) risk using a machine learning (ML) approach.

METHODS AND RESULTS

We performed a single center, observational study in a cohort of 238 DM patients (mean age ± SD 52.15 ± 17.27 years, 54% female) as a part of the Silesia Diabetes-Heart Project. Having gathered patients' medical history, demographic data, laboratory test results, results from the Michigan Neuropathy Screening Instrument (assessing diabetic peripheral neuropathy) and Ewing's battery examination (determining the presence of cardiovascular autonomic neuropathy), we managed use a ML approach to predict the occurrence of overt CVD on the basis of five most discriminative predictors with the area under the receiver operating characteristic curve of 0.86 (95% CI 0.80-0.91). Those features included the presence of past or current foot ulceration, age, the treatment with beta-blocker (BB) and angiotensin converting enzyme inhibitor (ACEi). On the basis of the aforementioned parameters, unsupervised clustering identified different CV risk groups. The highest CV risk was determined for the eldest patients treated in large extent with ACEi but not BB and having current foot ulceration, and for slightly younger individuals treated extensively with both above-mentioned drugs, with relatively small percentage of diabetic ulceration.

CONCLUSIONS

Using a ML approach in a prospective cohort of patients with DM, we identified important factors that predicted CV risk. If a patient was treated with ACEi or BB, is older and has/had a foot ulcer, this strongly predicts that he/she is at high risk of having overt CVD.

Efficient Synthesis of 2-Ethylhexanoic Acid via N-Hydroxyphthalimide Catalyzed Oxidation of 2-Ethylhexanal with Oxygen

An efficient method for the synthesis of 2-ethylhexanoic acid has been reported. The method involves the 2-ethylhexanal oxidation using oxygen or air in the presence of N-hydroxyphthalimide in isobutanol as a solvent under mild conditions. A high selectivity of >99% for 2-ethylhexanoic acid was achieved. The influence of catalyst amount, solvent type and quantity, temperature, and reaction time on the product composition was studied. The developed method is in line with the global trends aimed at developing green oxidation processes as well as having potential for implementation in industry due to its high selectivity, cost-effective oxidizing agent, and mild reaction conditions. The use of isobutanol as a solvent is of crucial importance providing an opportunity for potential producers of 2-EHAL from butanal to employ the less valuable alcohol.

Pyrotechnic Delay Compositions Based on BaO2: Not as "Green" as Expected

The aims of this study were to investigate the potential of using barium peroxide as an environmentally friendly oxidising agent, to evaluate the composition of the combustion products of the developed pyrotechnic delay compositions (PDCs) and to provide information about the impact of the utilised metallic fuel (Mg, Al, Fe or Cu) on the properties of those PDCs. The PDCs exhibited acceptable friction and impact sensitivity values. This allowed conducting further experiments, e.g., determining the linear combustion velocity of the PDCs as a function of oxygen balance (OB). Based on the composition of the post-combustion residues, determined by Raman spectroscopy and SEM-EDS, an initial mechanism for the combustion of the developed PDCs was proposed.

Automated Identification of Hidden Corrosion Based on the D-Sight Technique: A Case Study on a Military Helicopter

Hidden corrosion remains a significant problem during aircraft service, primarily because of difficulties in its detection and assessment. The non-destructive D-Sight testing technique is characterized by high sensitivity to this type of damage and is an effective sensing tool for qualitative assessments of hidden corrosion in aircraft structures used by numerous ground service entities. In this paper, the authors demonstrated a new approach to the automatic quantification of hidden corrosion based on image processing D-Sight images during periodic inspections. The performance of the developed processing algorithm was demonstrated based on the results of the inspection of a Mi family military helicopter. The nondimensional quantitative measurement introduced in this study confirmed the effectiveness of this evaluation of corrosion progression, which was in agreement with the results of qualitative analysis of D-Sight images made by inspectors. This allows for the automation of the inspection process and supports inspectors in evaluating the extent and progression of hidden corrosion.

Catalyst Design through Grafting of Diazonium Salts-A Critical Review on Catalyst Stability

In the pursuit of designing a reusable catalyst with enhanced catalytic activity, recent studies indicate that electrochemical grafting of diazonium salts is an efficient method of forming heterogeneous catalysts. The aim of this review is to assess the industrial applicability of diazonium-based catalysts with particular emphasis on their mechanical, chemical, and thermal stability. To this end, different approaches to catalyst production via diazonium salt chemistry have been compared, including the immobilization of catalysts by a chemical reaction with a diazonium moiety, the direct use of diazonium salts and nanoparticles as catalysts, the use of diazonium layers to modulate wettability of a carrier, as well as the possibility of transforming the catalyst into the corresponding diazonium salt. After providing descriptions of the most suitable carriers, the most common deactivation routes of catalysts have been discussed. Although diazonium-based catalysts are expected to exhibit good stability owing to the covalent bond created between a catalyst and a post-diazonium layer, this review indicates the paucity of studies that experimentally verify this hypothesis. Therefore, use of diazonium salts appears a promising approach in catalysts formation if more research efforts can focus on assessing their stability and long-term catalytic performance.

Following the Decomposition of Hydrogen Peroxide in On-Site Mixture Explosives: Study of the Effect of the Auxiliary Oxidising Agent and Binder

The issues of safety and its impact on both human health and the environment are on-going challenges in the field of explosives (EXs). Consequently, environmentally-friendly EXs have attracted significant interest. Our previous work, dedicated to on-site mixed (OSM) EXs utilising concentrated hydrogen peroxide (HTP) as an oxidising agent, revealed that the gradual decomposition of HTP may be harnessed as an additional safety measure, e.g., protection from theft. The rate of HTP decomposition is dependent on the OSM components, but this dependence is not straightforward. Relevant information about the decomposition of HTP in such complex mixtures is unavailable in literature. Consequently, in this work, we present a more detailed picture of the factors influencing the dynamics of HTP decomposition in EXformulations. The relevant measurement and validation methodology is laid out and the most relevant factors for determining the rate of HTP decomposition are highlighted. Among these, the choice of auxiliary oxidising agent is of particular relevance and it can be seen that the choice to use ammonium nitrate (AN), made in previous works dealing with HTP-based EXs, is sub-optimal in terms of maintaining the stability of HTP. Another important finding is that glass microspheres are not as inert to HTP as would be expected, as replacing them with polymer microspheres significantly slowed the decomposition of HTP in the investigated OSM samples.

Aluminium Matrix Composite Materials Reinforced by 3D-Printed Ceramic Preforms

This article employed the fused deposition modelling (FDM) method and gas-pressure infiltration to manufacture alumina/AlSi12 composites. Porous ceramic skeletons were prepared by FDM 3D printing of two different alumina powder-filed filaments. The organic component was removed using a combination of solvent and heat debinding, and the materials were then sintered at 1500 °C to complete the process. Thermogravimetric tests and DTA analysis were performed to develop an appropriate degradation and sintering program. Manufactured skeletons were subjected to microstructure analysis, porosity analysis, and bending test. The sintering process produced porous alumina ceramic samples with no residual carbon content. Open porosity could occur due to the binder's degradation. Liquid metal was infiltrated into the ceramic, efficiently filling any open pores and forming a three-dimensional network of the aluminium phase. The microstructure and characteristics of the fabricated materials were investigated using high-resolution scanning electron microscopy, computer tomography, hardness testing, and bending strength testing. The developed composite materials are characterized by the required structure-low porosity and homogenous distribution of the reinforcing phase, better mechanical properties than their matrix and more than twice as high hardness. Hence, the developed innovative technology of their manufacturing can be used in practice.

Traditional vs. Energetic and Perchlorate vs. "Green": A Comparative Study of the Choice of Binders and Oxidising Agents

The aim of this article is to compare rocket propellants containing a traditional binder (hydroxyl-terminated polybutadiene) and an energetic binder (glycidyl azide polymer), as well as a perchlorate oxidising agent and a "green" one, i.e., ammonium perchlorate and phase-stabilised ammonium nitrate. We have outlined the effects of individual substances on the sensitivity parameters and decomposition temperature of the produced solid propellants. The linear combustion velocity was determined using electrical methods. Heats of combustion for the propellant samples and the thermal decomposition features of the utilised binders were investigated via differential scanning calorimetry (DSC). Activation energy values for the energetic decomposition of the propellants were determined via the Kissinger method, based on DSC measurements at varied heating rates.

On the Development of a Digital Twin for Underwater UXO Detection Using Magnetometer-Based Data in Application for the Training Set Generation for Machine Learning Models

Scanning underwater areas using magnetometers in search of unexploded ordnance is a difficult challenge, where machine learning methods can find a significant application. However, this requires the creation of a dataset enabling the training of prediction models. Such a task is difficult and costly due to the limited availability of relevant data. To address this challenge in the article, we propose the use of numerical modeling to solve this task. The conducted experiments allow us to conclude that it is possible to obtain high compliance with the numerical model based on the finite element method with the results of physical tests. Additionally, the paper discusses the methodology of simplifying the computational model, allowing for an almost three times reduction in the calculation time without affecting model quality. The article also presents and discusses the methodology for generating a dataset for the discrimination of UXO/non-UXO objects. According to that methodology, a dataset is generated and described in detail including assumptions on objects considered as UXO and nonUXO.

Study of the Combustion Mechanism of Zn/KMnO4 Pyrotechnic Composition

This work aims to investigate the combustion mechanism for a pyrotechnic delay composition (PDC), consisting of zinc powder as a fuel and KMnO4 as an oxidising agent. For this purpose, the compositions were thermally conditioned at several set temperatures, chosen based on our previous work. Tests were also performed for post-combustion residues obtained via combustion of the PDCs in a manometric bomb. The samples were examined by scanning electron microscopy (SEM), Raman spectroscopy and X-ray diffractometry (XRD). Furthermore, the obtained results were correlated with previous studies by the authors and compared with data available in the literature. On the basis of tests carried out for thermally conditioned samples, a combustion mechanism was determined for Zn/KMnO4 as a function of temperature. The results show that the combustion process dynamics are independent of equilibrium ratio and limited mainly by diffusion of liquid fuel into the solid oxidising agent. Moreover, it has been revealed that Raman spectroscopy can be effectively used to determine combustion mechanisms for pyrotechnic compositions.

Towards "Green" ANFO: Study of Perchlorates and Inorganic Peroxides as Potential Additives

Ammonium nitrate-fuel oil (ANFO) explosives are inexpensive and readily produced, but are highly prone to misfires, with the remaining explosive being a significant risk and environmental contaminant. In this work, studies on various additives, such as selected perchlorates and inorganic peroxides, which are intended to lower the susceptibility of ANFO to misfires by increasing its sensitivity to shock, have been conducted. These studies showed the viability of using these additives in ANFO, allowing for conducting shock wave sensitivity tests for bulk charges in the future. We investigated the effects of introducing these additives into ANFO (on its sensitivity), as well as thermal and energetic properties. We observed minor increases in friction and impact sensitivity, as well as a moderate reduction in the decomposition temperature of the additive-supplemented ANFO in comparison to unmodified ANFO.

Manufacturing of Corrosion-Resistant Surface Layers by Coating Non-Alloy Steels with a Polymer-Powder Slurry and Sintering

This paper describes the combination of surface engineering and powder metallurgy to create a coating with improved corrosion resistance and wear properties. A new method has been developed to manufacture corrosion-resistant surface layers on steel substrate with additional carbide reinforcement by employing a polymer-powder slurry forming and sintering. The proposed technology is an innovative alternative to anti-corrosion coatings applied by galvanic, welding or thermal spraying techniques. Two different stainless-steel powders were used in the research. Austenitic 316 L and 430 L ferritic steel powders were selected for comparison. In addition, to improve resistance to abrasive wear, coatings containing an additional mixture of tetra carbides (WC, TaC, TiC, NbC) were applied. The study investigates the effects of using multicomponent polymeric binders, sintering temperature, and atmosphere in the sintering process, as well as the presence of reinforcing precipitation, microstructure and selected surface layer properties. Various techniques such as SEM, EDS, hardness and tensile tests and corrosion resistance analysis are employed to evaluate the characteristics of the developed materials. It has been proven that residual carbon content and nitrogen atmosphere cause the release of hard precipitations and thus affect the higher mechanical properties of the obtained coatings. The tensile test shows that both steels have higher strength after sintering in a nitrogen-rich atmosphere. Nitrogen contributes over 50% more to the tensile strength than an argon-containing atmosphere.

Zinc Evaporation from Brass Scraps in the Atmosphere of Inert Gas

A description of the process of metal evaporation from liquid alloys at an atmospheric pressure has a practical value for both the smelting and remelting of their scraps. The quantities of volatile components that are eliminated in these processes depend on many factors of which the type of melting device, the method and conditions of the process performance, the alloy composition and the kind of applied atmosphere are of the greatest importance. In this paper, the results of the research on zinc evaporation from brass scraps containing 10.53 wt% Zn are presented. The experiments were conducted using the thermogravimetric method at 1080 ÷ 1240 °C in a helium atmosphere. In the research, the levels of zinc removal from copper ranged between 82% and 99%. The values of the overall mass transfer coefficient for zinc k_Zn, determined based on the experimental data, ranged from 4.74 to 8.46 × 10^-5 ms^-1. The kinetic analysis showed that the rate of the analysed process was determined by mass transfer in the gas phase.

Research on the Flow Parameters of Waste Motion in a Rotary Kiln with the Use of the Tracer Method

The motion of input material in a rotary kiln is an important aspect of its operation. This can be observed especially in the case of the implementation of the hazardous waste incineration process in this device. The values of the flow parameters, mainly the residence time and the degree of mixing, can determine the proper and safe treatment of waste. The relationships that occur in the layer of solid material in a rotary kiln have not been completely recognized. This article presents a research method that involves an experiment on a laboratory stand simulating a rotary kiln in association with a dedicated algorithm. Multi-criteria tests were carried out. The adopted research method was the tracer method. It used a tracer which, subject to the same transport conditions as other material particles, provided information on the characteristic of the motion of tested materials in the rotating cylinder. The application based on the residence time distribution (RTD) algorithm returned information about the characteristics of the motion of the material in the rotary cylinder in terms of residence time distribution and the degree of mixing. This tracer method, together with stimulus impulses on the grate and a dedicated RTD algorithm, was used here as a sensor method to examine the characteristics of material motion on various grate systems. The data obtained as a result of this research may include, among others, the boundary conditions for numerical simulations of processes carried out in a rotary kiln.

From Corrective to Predictive Maintenance-A Review of Maintenance Approaches for the Power Industry

Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead to high costs and substantial economic losses not only for the power plant but for consumers and the larger society. Therefore, the power production industry relies on a variety of approaches to maintenance tasks, ranging from traditional solutions and engineering know-how to smart, AI-based analytics to avoid potential downtimes. This review shows the evolution of maintenance approaches to support maintenance planning, equipment monitoring and supervision. We present older techniques traditionally used in maintenance tasks and those that rely on IT analytics to automate tasks and perform the inference process for failure detection. We analyze prognostics and health-management techniques in detail, including their requirements, advantages and limitations. The review focuses on the power-generation sector. However, some of the issues addressed are common to other industries. The article also presents concepts and solutions that utilize emerging technologies related to Industry 4.0, touching on prescriptive analysis, Big Data and the Internet of Things. The primary motivation and purpose of the article are to present the existing practices and classic methods used by engineers, as well as modern approaches drawing from Artificial Intelligence and the concept of Industry 4.0. The summary of existing practices and the state of the art in the area of predictive maintenance provides two benefits. On the one hand, it leads to improving processes by matching existing tools and methods. On the other hand, it shows researchers potential directions for further analysis and new developments.

A Simulation Model for the Inductor of Electromagnetic Levitation Melting and Its Validation

This article presents a numerical model of electromagnetic levitation melting and its experimental validation. Levitation melting uses the phenomenon of magnetic induction to float a melted, usually metallic, conductor in an electromagnetic field. With the appropriate configuration of the coil (the source of the alternating magnetic field), the eddy currents induced in the molten batch interact with the coil magnetic field, which causes the melted metal to float without direct contact with any element of the heating system. Such a contactless process is very beneficial for melting very reactive metals (e.g., titanium) or metals with a high melting point (e.g., tungsten). The main disadvantage of levitation melting is the low efficiency of the process. The goal of the authors is to develop, by means of a numerical simulation and optimization tools, a system for levitation melting with acceptable efficiency. To achieve this, it is necessary to develop a reliable and representative computational model. The proposed model includes an analysis of the electromagnetic field, with innovative modeling of the convective heat transport. Experimental validation of the model was performed using aluminum alloy, due to the lack of the need to use a protective atmosphere and the ease of measurements. The measurements included electrical values, the melted batch positions during levitation, the melting time, and the temperature distribution in its area. The verification showed that the compliance between the computational model and the simulation for the position of the batch was accurate to 2 mm (6.25%), and the consistency of the batch melting time was accurate to 5 s (5.49%). The studies confirmed the good representativeness of the developed numerical model, which makes it a useful tool for the future optimization of the levitation melting system.

Identification of Control-Related Signal Path for Semi-Active Vehicle Suspension with Magnetorheological Dampers

This paper presents a method for the identification of control-related signal paths dedicated to a semi-active suspension with MR (magnetorheological) dampers, which are installed in place of standard shock absorbers. The main challenge comes from the fact that the semi-active suspension needs to be simultaneously subjected to road-induced excitation and electric currents supplied to the suspension MR dampers, while a response signal needs to be decomposed into road-related and control-related components. During experiments, the front wheels of an all-terrain vehicle were subjected to sinusoidal vibration excitation at a frequency equal to 12 Hz using a dedicated diagnostic station and specialised mechanical exciters. The harmonic type of road-related excitation allowed for its straightforward filtering from identification signals. Additionally, front suspension MR dampers were controlled using a wideband random signal with a 25 Hz bandwidth, different realisations, and several configurations, which differed in the average values and deviations of control currents. The simultaneous control of the right and left suspension MR dampers made it necessary to decompose the vehicle vibration response, i.e., the front vehicle body acceleration signal, into components related to the forces generated by different MR dampers. Measurement signals used for identification were taken from numerous sensors available in the vehicle, e.g., accelerometers, suspension force and deflection sensors, and sensors of electric currents, which control the instantaneous damping parameters of MR dampers. The final identification was carried out for control-related models evaluated in the frequency domain and revealed several resonances of the vehicle response and their dependence on the configurations of control currents. In addition, the parameters of the vehicle model with MR dampers and the diagnostic station were estimated based on the identification results. The analysis of the simulation results of the implemented vehicle model carried out in the frequency domain showed the influence of the vehicle load on the absolute values and phase shifts of control-related signal paths. The potential future application of the identified models lies in the synthesis and implementation of adaptive suspension control algorithms such as FxLMS (filtered-x least mean square). Adaptive vehicle suspensions are especially preferred for their ability to quickly adapt to varying road conditions and vehicle parameters.