Compositional Features Research Articles

Герб на графское Российской империи достоинство и его версии генерала от кавалерии, атамана Донского Войска графа М.И. Платова

The coat of arms and its versions of Count M.I. Platov are considered for the first time in the scientific literature, their origin, composition, symbolism, role and significance in consolidating the image of a cavalry general, a military ataman of the Don Army in the historical memory of the peoples of Russia and Europe. The highly approved coat of arms of M.I. Platov, little known to contemporaries, was distributed in independent, attributed versions, which played an important role in visualization, strengthening the authority of the “whirlwind chieftain”. It is proven that these versions are unconfirmed and are closely connected with the processes of formation of historical memory and public consciousness in Russia. The versions of the Count's coat of arms of M.I. Platov retained heraldic continuity but were complemented with new figures that revealed the pages of his military and civil service, the relations of the Don Ataman with crowned persons, the military and state elite of Russia and Europe. It is emphasized that the versions of the coats of arms are at the same time independent heraldic and artistic works. According to the authors of the unapproved coats of arms, the awards, additions and changes included in them raised and consolidated the high status of the coat of arms holders, showed their role and merits in the history of Russia. The coat of arms portraits and versions of the coat of arms of Count M.I. Platov reflected the ideas of his contemporaries about his role in the history of the country, the process of formation of the Don nobili-ty, and the state of the heraldic tradition in Russia. Independent, unapproved coats of arms were an important stage in the development of Russian heraldic studies: some are still a kind of reminder of “famous names and events”, others were used primarily to solve personal, property and social problems over the course of one generation and became historical facts in the lives of the coat of arms holders. The coat of arms engraved portrait of M.I. Platov and versions of coats of arms go back to the Don painting and coat of arms tradition of the second half of the 18th – early 19th century. They, preserving artistic and compositional features, are part of the Don and Russian military portrait, Russian heraldry.

Features of hear microelement composition in children with type 1 diabetes mellitus

Objective: Assessment of the characteristics of the microelement composition of the hair of children with type 1 diabetes mellitus (T1DM) to develop recommendations for diet correction. Material and methods. The study involved children with T1 DM (n=28) and practically healthy children from the comparison group (n=56) aged 3-5 years living in the Omsk region. The elemental composition of hair was analyzed by atomic emission and mass spectrometry with inductively coupled argon plasma. The research materials were subjected to statistical processing using nonpara-metric criteria. Results. The elemental profile of hair of children with T1 DM has been determined. Significant differences were found in the amounts of microelements in hair: lower values of beryllium (p=0.0001), chromium (p=0.003), lithium (p=0.005), vanadium (p=0.005), selenium (p=0.043), and large amounts of cuprum (p=0.025), phosphorus (p=0.001) in the hair of children with diabetes in comparison with the group of practically healthy ones. In the group of children with T1DM, there was a smaller proportion of people with insufficient magnesium (p=0.003), phosphorus (p=0.001), and cuprum (p=0.001). The severity of mineral metabolism disorders (MMD) was less in the group of children with T1DM: 53.6% of children were classified as having no MMD or having minor MMD. Conclusions. The elemental composition of the hair of children with T1DM was characterized by higher amounts of phosphorus and cuprum, lower content of chromium, selenium, beryllium, lithium and vanadium. The proportion of children with insufficient supply of magnesium, phosphorus, cuprum was higher in the comparison group. The degree of MMD in the group of children with T1 DM was generally less.

Peculiarities of Hemostasis and Proteomics in Patients With Acute Myocardial Infarction and Healthy Volunteers After SARS-CоV-2 Infection.

To identify the features of plasma, platelet hemostasis, and proteomic composition of the blood plasma in patients with acute myocardial infarction (AMI) and healthy volunteers after COVID-19. The study included patients with AMI who have recently had COVID-19 (AMI-post-COVID, n=56) and patients with AMI who have not recently had COVID-19 (AMI-control, n=141). Healthy volunteers constituted the control groups and were also divided into control-post-COVID (n=32) and control-control (n=71) groups. Previous SARS-CoV-2 infection was determined by anti-N IgG in the blood serum, the level of which persists for 6-10 months after the disease. Hemostasis was evaluated by thromboelastometry (on whole blood), thrombodynamics (on platelet-poor plasma), fibrinolysis, impedance aggregometry, and proteomic analysis. The AMI-post-COVID and AMI-control groups had higher values of thrombus growth rate, size and density based on the data of thromboelastometry and thrombodynamics, as well as increased concentrations of the complement system components, proteins regulating the state of the endothelium, and a number of acute-phase and procoagulant proteins compared to the control groups. Furthermore, in the AMI-post-COVID group, compared to the AMI-control group, the thrombus density was lower, and its lysis rates were higher when measured by the thrombodynamics method on platelet-poor plasma, while the platelet aggregation induced by ADP and thrombin was higher. Also, in the control-post-COVID group, compared to the control-control group, the thrombus formation rate was lower, whereas, in contrast, the thrombus size as measured by the thrombodynamics method and the platelet aggregation induced by arachidonic acid and thrombin were higher. In addition, in the AMI-post-COVID group, compared to the AMI-control group, the concentrations of proteins involved in inflammation and hemostasis were lower. Patients with AMI who have recently had COVID-19 are characterized by a less pronounced activation of the immune response compared to patients with AMI who have not had COVID-19. This may be due to long-term chronic inflammation and depletion of components of the immune activation system after SARS-CoV-2 infection. Long-term activation of the hemostasis system in both patients with AMI and healthy volunteers after COVID-19 is primarily due to the platelet component of hemostasis.

Nd-isotope effects through factional crystallisation-assimilation (AFC) processes in the continental crust, heterogeneous in age: the example of ferrobasalts from the Ladoga Graben (Karelia, Russia)

Petrography, geochemistry and isotope geochemistry of the Mesoproterozoic volcanic rocks occurred as lava flows and the Valaam sill in the Ladoga rift, have been studied. The Ladoga rift is located in the area of thrusting of the Palaeoproterozoic Svekofennian orogenic complexes onto the Archean Karelian craton. Ferrobasites of close composition and geological position in lava flows and sill have different Nd isotopic composition, differing by 5 units εNd(t): –4…-5 in ferrobasalts of lava flows and a very low-radiogenic Nd isotopic composition in mafic rocks of the sill (εNd(t) to –11 for ferrogabbro), and identical to the isotopic composition of its acidic rocks (εNd(t) to –11 for granophyres). It is shown that in the crust, heterogeneous in age, the process of fractional crystallisation along the tholeiitic trend combined with assimilation of melt from wall rocks can be an effective mechanism for forming such “paradoxical” features of the Nd isotopic composition. The isotopic composition of sill rocks indicates the probable presence of Mesoarchean blocks in the lower crust of the Ladoga graben region.

A comprehensive study on the autochthonous microbiota, volatilome, physico-chemical, and morpho-textural features of Montenegrin Njeguški cheese

The present study aims to deepen the knowledge of the microbiota, gross composition, physico-chemical and morpho-textural features, biogenic amines content and volatilome of Njeguški cheese, one of the most popular indigenous cheeses produced in Montenegro. Cheese samples were collected in duplicate from three different batches produced by three Montenegrin artisan producers. For the first time, the microbiota of Njeguški cheese was investigated using both culture-dependent techniques and metagenomic analysis. Coagulase positive staphylococci viable counts were below the detection limit of the analysis (<1 log cfu g−1). Salmonella spp., Listeria monocytogenes and staphylococcal enterotoxins were absent. However, relatively high viable counts of Enterobacteriaceae, Escherichia coli, Pseudomonadaceae and eumycetes were detected. Metataxonomic analysis revealed a core microbiome composed of Lactococcus lactis, Streptococcus thermophilus, Debaryomyces hansenii, and Kluyveromyces marxianus. Furthermore, the detection of opportunistic pathogenic yeasts such as Magnusiomyces capitatus and Wickerhamiella pararugosa, along with the variable content of biogenic amines, suggests the need for increased attention to hygienic conditions during Njeguški cheese production. Significant variability was observed in humidity (ranging from 38.37 to 45.58 %), salt content (ranging from 0.70 to 1.78 %), proteins content (ranging from 21.42 to 25.08 %), ash content (ranging from 2.97 to 4.05 %), hardness, springiness, and color among samples from different producers. Gas chromatography-mass spectrometry analysis showed a well-defined and complex volatilome profile of the Njeguški cheese, with alcohols (ethanol, isoamyl alcohol, phenetyl alcol), esters and acetates (ethyl acetate, ethyl butanoate, isoamyl acetate), ketones (acetoin, 2-butanone), and acids (acetic, butanoic, hexanoic acids) being the main chemical groups involved in aroma formation. This research will provide new insights into the still poorly explored identity of Njeguški cheese, thus serving as a first baseline for future studies aimed at protecting its tradition.

Co2P/CoP embedded in N, P, S triply-doped hollow carbon towards enhanced oxygen electrocatalysis

Simultaneously dispersing phosphide crystallites and multiple heteroatoms in hollow carbon is a significant yet challenging task for achieving high-performance oxygen electrocatalysts of zinc-air batteries. Herein, a simple wrapping-pyrolysis strategy is proposed to prepare Co2P/CoP embedded in N, P, S triply-doped hollow carbon (Co2P/CoP@NPS-HC). Co2P/CoP@NPS-HC composite features hollow polyhedral structure populated with numerous catalytically active Co2P/CoP nanoparticles and N, P, S heteroatoms. This optimized catalyst exhibits excellent activity for oxygen reduction reaction, with a half-wave potential of 0.82 V vs. RHE, and impressive enhancement for oxygen evolution reaction, indicated by an overpotential of 400 mV at 10 mA cm−2. Moreover, Co2P/CoP@NPS-HC catalyst exhibits greater durability and superior methanol tolerance compared to commercial Pt/C. The excellent bifunctional electrocatalytic performance of Co2P/CoP@NPS-HC catalyst is attributed to the synergistic effect of uniformly dispersed Co2P/CoP nanoparticles and N, P, S triply-doped hollow carbon structure. The former provides abundant catalytically active sites, while the latter offers a high accessible specific surface area, as well as enhances catalytic activity and electronic conductivity due to its altered charge distribution.

Integrating multi-spectral imaging and Raman spectroscopy for in vivo endoscopic assessment of rat intestinal tract

An integrated system for in vivo multi-spectral imaging (MSI) and Raman spectroscopy was developed to understand the external morphology and internal molecular information of biological tissues. The achieved MSI images were reconstructed by eighteen separated images from 400 nm to 760 nm, whose illumination bands were selected with six tri-channel band filters. Based on the spectral analysis algorithms, the spatial distribution patterns of blood volume, blood oxygen content and tissue scatterer volume fraction were visualized. In vivo Raman spectral measurements were executed by inserting specially designed optical probe into instrumental channel of endoscope. By this way, the molecular composition at selected sampling points could be identified with its fingerprint spectral information under the guidance of molecular imaging modality. Therefore, both structural and compositional features of intestinal membrane could be addressed without labeling and continuously. The achieved results testified that our presented methodology reveals insights not easily extracted from either MSI or Raman spectroscopy individually, which brings the enrichment of biological and chemical meanings for future in vivo studies.

Compositional and dramaturgical analysis of Mykola Lysenko’s Concert polonaises Op. 5 and Op. 7 and specificity of their performing interpretation

The relevance of the article. Mykola Lysenko’s creativity attracts the attention of the world music community. This is confirmed by the availability of CD albums with the composer’s music created by Ukrainian and foreign musicians. The composer’s piano opuses are of considerable interest, but among them there are pieces that, despite their artistic value, are performed relatively infrequent. The purpose of the article is to identify the compositional and dramaturgical features of two Concert polonaises Op. 5 and Op. 7 by M. Lysenko and analyze their performance versions. Taken in combination, this will allow us to better understand the specifics of the composer’s interpretation of the polonaise genre and identify approaches to the interpretation of these works that are common in contemporary piano performance practice. The methodology is based on an integrative approach, and involves the use of systematic, analytical, structural-functional, inductive and comparative methods. The results. In his two Concert polonaises, M. Lysenko presents different approaches to the understanding of the genre, which is manifested at the level of their composition, musical dramaturgy, and the embodiment of the virtuoso-concert principle. In addition, the study examines the performing versions of polonaises created by contemporary Ukrainian pianists, which helped to identify trends in their performing interpretation. Conclusions. The compositional structure of the first Concert polonaise is proportional, while in the second Concert polonaise the composer does not keep the symmetry of the form of the sections, expanding the middle section and shortening the reprise. The musical dramaturgy of the first Concert polonaise is marked by the contrast of musical images, while the second Concert polonaise is dominated by lyrical imagery. These pieces embody opposite aspects of virtuosity, which is manifested at the level of texture and dynamic palette. Interpreting these Concert polonaises by M. Lysenko, the pianists reveal different aspects of their musical and figurative sphere: lyricism or poetry, bright dancing or heroics. An interesting trend in the performing interpretation of the works is the reduction of the middle section (episode), which is possible due to the repetition of the thematic material. The practical significance. The material of the article can be used in the further study of the specifics of the performance interpretation of M. Lysenko’s music, as well as in the study of the artist’s work in a special piano class, courses “The analysis of musical forms”, “The history of music”.

Application of scalable sensor-assisted multi-scale computational methods in the simulation of micro mechanical behavior of composite materials

Micro mechanics involves the examination of the mechanical behavior of heterogeneous materials, taking into account inhomogeneities such as voids, fractures, and inclusions, and building on mathematical models developed. Composites bring engineering design barriers despite their strengths. Composite manufacturing and processing need specialized equipment, strategies, and labor, ensuring they are challenging and expensive. Mechanical behavior deals with how a composite material performs if faced with mechanical effects and action. Scalable sensor-assisted multi-scale computational Methods (SS-MSCM) are used to investigate topics ranging from the molecular basis of soot production in combustion to how molecule-level flaws influence macroscopic mechanical qualities. Carbon fiber reinforced polymers (CFRP) are generated by mixing graphene fiber with a resin, like vinyl ester and epoxy, to render a composite material with superior performance to the component ingredients. Hence, SS-MSCM-CFRP has Improved mechanical qualities achieved by incorporating nano-reinforcements, including carbon nanofibers and graphene nanoplates, into the CFRP matrix: enhanced flexural and compressive strengths, energy absorption upon impact, toughness to fracture, and interlaminar bonding. Composite materials feature excellent mechanical qualities like high strength and stiffness, fatigue resistance, and durability. It is possible to insert scalable sensors throughout the manufacturing process, which enables real-time monitoring of structural health, strain, and other factors. Scalable sensor-assisted multi-scale computational methods offer enhanced accuracy, real-time monitoring, and cost-effectiveness by integrating sensor data with computational models, improving predictions and failure mechanism insights. However, they face limitations like sensor dependency, computational complexity, data integration challenges, and high implementation costs, leading to potential discrepancies between simulation and experimental results. Important qualities include corrosion resistance, thermal conductivity, and electrical conductivity. As the composite materials develop to satisfy the established mechanical stress and temperature conditions, they offer high durability and strength.

A novel method for rice identification: Coupling Raman spectroscopy with Fourier spectrum and analyzing with deep learning

The development of detection methods for food adulteration is of great significance for promoting innovation and development in food safety supervision technology. In this study, we proposed a novel model: Raman-Fourier-BiLSTM-CNN (RFBC), which combines Raman spectroscopy with deep learning to achieve precise identification of seven brands of japonica rice in the northeastern region of China. This model focuses on revealing the worth of the Fourier spectrum of Raman spectra. The raw Raman spectra and their Fourier spectra are cleverly coupled through a Bi-directional Long Short-Term Memory (BiLSTM) connection structure, and the resulting composite features are deeply analyzed by a Convolutional Neural Network (CNN). Compared to traditional algorithms, RFBC exhibits superior feature extraction capabilities. To further evaluate the recognition performance of RFBC, this study compared it with the RFBC model containing only the original Raman spectrum branch, as well as with machine learning models based on Principal Component Analysis (PCA), including Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbor (KNN), and eXtreme Gradient Boosting (XGBoost). The results show that, compared with the other five models, RFBC can accurately identify different brands of japonica rice, with significant advantages in accuracy, precision, recall, and other aspects. RFBC achieves a classification accuracy of 97.1 %, macro precision of 97.2 %, macro recall of 97.1 %, and macro F1-score of 97.2 %. The system proposed in this study can more accurately identify brands of japonica rice, providing strong technical support for combating counterfeit japonica rice products.

Early diagnosis of Alzheimer's Disease based on multi-attention mechanism.

Alzheimer's Disease is a neurodegenerative disorder, and one of its common and prominent early symptoms is language impairment. Therefore, early diagnosis of Alzheimer's Disease through speech and text information is of significant importance. However, the multimodal data is often complex and inconsistent, which leads to inadequate feature extraction. To address the problem, We propose a model for early diagnosis of Alzheimer's Disease based on multimodal attention(EDAMM). Specifically, we first evaluate and select three optimal feature extraction methods, Wav2Vec2.0, TF-IDF and Word2Vec, to extract acoustic and linguistic features. Next, by leveraging self-attention mechanism and cross-modal attention mechanisms, we generate fused features to enhance and capture the inter-modal correlation information. Finally, we concatenate the multimodal features into a composite feature vector and employ a Neural Network(NN) classifier to diagnose Alzheimer's Disease. To evaluate EDAMM, we perform experiments on two public datasets, i.e., NCMMSC2021 and ADReSSo. The results show that EDAMM improves the performance of Alzheimer's Disease diagnosis over state-of-the-art baseline approaches on both datasets.

Multi-scale ceramic self-extinguishing fire retardant coating based on scale armor layer

Currently, designing an efficient and broadly applicable (suitable for foams, wood, steel, plastic) fire-retardant coating remains a significant challenge. This work introduces a multi-scale micro-nanostructured hybrid fireproof coating. The composite features basic fillers that include ceramic glass microspheres, while its interior comprises an inorganic aerogel made from nano black phosphorus and silicon dioxide nanofibers for reinforcement, with a phosphorus-containing acrylic polymer serving as the base. Upon exposure to elevated temperatures, the coating’s surface transforms into a solid char layer resembling scale armor, effectively functioning as a robust fire barrier to protect the underlying substrate. The coating treated rigid polyurethane foam achieved an exceptionally high Limiting Oxygen Index of 45 %, outperforming comparable products. In terms of flame retardancy and smoke suppression, this innovative coating significantly reduces Peak Heat Release Rate (50.3 %) and Total Smoke Production (54.9 %). Notably, it exhibits rapid self-extinguishing capabilities within seconds during butane flame tests at temperatures exceeding 1100 °C, demonstrating remarkable resistance to high-temperature flames. This research offers a straightforward methodology for developing high-performance fireproof coatings, with promising applications across various industrial settings.

Synchronously Consolidating Li, Se, S, and C for Robust Li-SeS Batteries.

S-redox involving solvated polysulfides is accompanied by volumetric change and structural decay of the S-based cathodes. Here, we propose a synchronous construction strategy for consolidating Li, Se, S, and C elements within a composite cathode via a paradigm reaction of 8Li+2Se+CS2 = 2Li4SeS+C. The obtained composite features crystalline Li4SeS encapsulated in a carbon nanocage (Li4SeS@C), exhibiting ultrahigh electrical conductivity, ultralow activation barrier, and excellent structural integrity, accordingly enabling large specific capacity (615 mAh g-1) and high capacity retention (87.3% after 350 cycles) at 10 A g-1. TOF-SIMS demonstrates its superior volumetric efficiency to a similar derivative SeS@C (2Se+CS2 = 2SeS+C), and DFT reveals its lower activation barrier than Li2S@C and Li2Se@C. This consolidation design significantly improves the electrochemical performance of S-based cathodes, and the paradigm reaction guarantees structural diversity and flexibility. Moreover, employing a synchronous construction mechanism to maximize the synergistic effect between element consolidation and carbon encapsulation opens up a new approach for developing robust S or chalcogenide cathodes.

Integrated approach to determining the identity of the pollution of adjacent territories with oil products

The methodology of arranging laboratory studies of oil-contaminated soils, soils and bottom sediments to determine the source and composition of hydrocarbon contamination is described. The complex approach to laboratory analysis of samples of oil-contaminated soils, soils and bottom sediments is proposed, which allows a highly reliable identification of the potential source of contamination and/or making conclusions about the identity of the contamination of adjacent territories. The proposed complex of analytical methods includes infrared spectrometry, gas chromatography with mass-selective detection, thin-layer chromatography with flame ionization detection and elemental analysis (C, H, N, S, O). Application of the proposed integrated approach allows highly reliable determination of the nature of oil contamination of soils, estimation of the total gross content of oil products and their hydrocarbon composition, and identification of the potential source of pollution. Possible errors in the interpretation of the results of determining the identity of contamination of territories and the importance of using an integrated approach in drawing conclusions about the source (culprit) of pollution are shown using real soil samples taken from oil-contaminated objects and adjacent territories. The importance of taking into account the losses of volatile oil products at the stage of sample preparation for soil contamination with light oil fractions is demonstrated. The use of standard methods of sample preparation (drying of the samples under study) leads to errors in assessing the level of contamination of territories with volatile hydrocarbons and in the choice of methods of remediation of contaminated territories. To minimize losses of volatile hydrocarbons (petrol and naphtha fractions) at the stage of soil sampling and transportation the use of sorbent is proposed. Addition of a sorbent to the soil contaminated with oil products can reduce losses of volatile hydrocarbons by 15 – 20% in the analyzed samples. Application of the developed complex approach makes it possible to determine the features of the individual hydrocarbon composition, group and elemental composition of petroleum products and identify hydrocarbon indicators (markers) inherent only to a certain type of petroleum product.

A Simple Methodology to Gain Insights into the Physical and Compositional Features of Ternary and Quaternary Compounds Based on the Weight Percentages of Their Constituent Elements: A Proof of Principle Using Conventional EDX Characterizations

A Simple Methodology to Gain Insights into the Physical and Compositional Features of Ternary and Quaternary Compounds Based on the Weight Percentages of Their Constituent Elements: A Proof of Principle Using Conventional EDX Characterizations

Application of group decomposition and 1.5-dimensional spectra to acoustic composite fault diagnosis of rolling bearings

Abstract Under the background of strong noise and mutual interference coupling of each fault, the acoustic compound fault diagnosis of rolling bearing is very challenging。 For the composite fault features which are difficult to be extracted due to strong noise interference and uneven distribution of fault intensity, put forward the optimization of swarm decomposition combined with 1.5-dimensional(1.5-d) spectrum method of acoustic composite rolling bearing fault feature separation. The method firstly uses the composite index to iteratively search for the optimal group decomposition threshold value, the adaptive group decomposition of composite fault acoustic signals is realized by optimal parameter group disassembly, and then selects the sensitive components for the decomposed components, and then further analyzes the envelope signal of the sensitive components to reduce the redundancy components and the noise interference, and selects the 1.5-d spectrum to further analyze the envelope signal, thus realizes the effective separation of the composite faults of the rolling bearings acoustic faults. Rolling bearing simulations and experimental acoustic signals verify the validity of the proposed method, and this work gives a new tool for composite fault diagnosis of revolving machinery.

Development and Application of a Liquid Sampling Device with Timing, Quantitative and Depth Determination

This thesis describes the development process of a liquid sampling device that can be timed, quantitative, and deep. The structural composition, working principle, and innovative features of the liquid sampling device are introduced, and the application prospects are analyzed. The device has the function of controllable and adjustable sampling point depth and sampling volume, and adopts quantitative collection and collection methods without contact with accessories. The device has a silent function in the sample body, which can realize pre-booking of collection time points and multi-point synchronous collection. Wireless remote control automatic mode is adopted for sending and stopping collection instructions, which can be sent one-to-one or one-to-many at the same time. It provides automation links for water quality monitoring projects and meets the requirements of modern scientific and technological development.

Predicting post-lung transplant survival in systemic sclerosis using CT-derived features from preoperative chest CT scans.

The current understanding of survival prediction of lung transplant (LTx) patients with systemic sclerosis (SSc) is limited. This study aims to identify novel image features from preoperative chest CT scans associated with post-LTx survival in SSc patients and integrate them into comprehensive prediction models. We conducted a retrospective study based on a cohort of SSc patients with demographic information, clinical data, and preoperative chest CT scans who underwent LTx between 2004 and 2020. This cohort consists of 102 patients (mean age, 50 years ± 10, 61% (62/102) females). Five CT-derived body composition features (bone, skeletal muscle, visceral, subcutaneous, and intramuscular adipose tissues) and three CT-derived cardiopulmonary features (heart, arteries, and veins) were automatically computed using 3-D convolutional neural networks. Cox regression was used to identify post-LTx survival factors, generate composite prediction models, and stratify patients based on mortality risk. Model performance was assessed using the area under the receiver operating characteristics curve (ROC-AUC). Muscle mass ratio, bone density, artery-vein volume ratio, muscle volume, and heart volume ratio computed from CT images were significantly associated with post-LTx survival. Models using only CT-derived features outperformed all state-of-the-art clinical models in predicting post-LTx survival. The addition of CT-derived features improved the performance of traditional models at 1-year, 3-year, and 5-year survival prediction with maximum AUC scores of 0.77 (0.67-0.86), 0.85 (0.77-0.93), and 0.90 (95% CI: 0.83-0.97), respectively. The integration of CT-derived features with demographic and clinical features can significantly improve t post-LTx survival prediction and identify high-risk SSc patients. Question What CT features can predict post-lung-transplant survival for SSc patients? Finding CT body composition features such as muscle mass, bone density, and cardiopulmonary volumes significantly predict survival. Clinical relevance Our individualized risk assessment tool can better guide clinicians in choosing and managing patients requiring lung transplant for systemic sclerosis.

Reexploring the conception of heat-health risk: From the perspectives of dimensionality and spatiality.

Extreme heat events are more frequent and intense as a result of global climate change, thus posing tremendous threats to public health. However, extant literature exploring the multidimensional features of heat-health risks from a spatial perspective is limited. This study revisits extreme heat-health risk and decomposes this concept by integrating multi-sourced datasets, identifying compositional features, examining spatial patterns, and comparing classified characteristics based on local conditions. Using Maryland as the focal point, we found that the components of heat-health risk are different from traditional risk dimensions (i.e., vulnerability, hazards, and exposure). Through a local-level clustering analysis, heat-health risks were compared with areas having similar features, and among those with different features. The findings suggest a new perspective for understanding the socio-environmental and socio-spatial features of heat-health risks. They also offer an apt example of applying cross-disciplinary methods and tools for investigating an ever-changing phenomenon. Moreover, the spatial classification mechanism provides insights about the underlying causes of heat-health risk disparities and offers reference points for decision-makers regarding identification of vulnerable areas, resource allocation, and causal inferences when planning for and managing extreme heat disasters.

Changes to Structural and Compositional Features of Water-Soluble Arabinoxylans in Sourdough Bread.

This research investigates the influence of milling methods and starter cultures on the structural characteristics of water-extractable arabinoxylans (WE-AX) in stone-milled whole-grain flour and sourdough bread. Stone milling was conducted to generate six different whole wheat flour samples, from which sourdough bread was produced using wheat and rye starter cultures. The study found that both milling parameters and the type of starter culture significantly impacted the fine structural details of WE-AX, including sugar composition, arabinoxylan (AX) content, and the arabinose-to-xylose (A/X) ratio values. These differences were statistically significant (p < 0.05). Furthermore, transforming flour into sourdough bread resulted in the molecular degradation of AX, significantly reducing its molecular weight and leading to a more heterogeneous fine structure. This detailed characterization of AX's alterations during food processing provides insights into evaluating its potential health benefits in whole-grain products.