The review is devoted to the physical, chemical and technological aspects of the breath-figures self-assembly process. Main stages of the process and the impact of the polymer architecture and physical parameters of the breath-figures self-assembly on the eventual pattern are covered. The review is focused on the hierarchy of spatial and temporal scales inherent for the breath-figures self-assembly. Multi-scale patterns arising from the process are addressed. The characteristic spatial lateral scales of patterns vary from nanometers to dozens of micrometers. The temporal scales of the process span from micro-seconds to seconds. The qualitative analysis performed in the paper demonstrates that the process is mainly governed by the interfacial phenomena, whereas the impact of inertia and gravity is negligible. Characterization and applications of polymer films manufactured with breath-figures self-assembly are discussed.

Hierarchical honeycomb patterns were manufactured with the breath-figures self-assembly by drop-casting on the silicone-oil lubricated glass substrates. Silicone oil promoted spreading of the polymer solutions. The process was carried out with the industrial grade polystyrene and polystyrene with the molecular weight Mw=35.000. Both of polymers gave rise to the patterns, built from micro- and nano-scaled pores. Ordering of the pores was quantified with the Voronoi tessellations and calculating the Voronoi entropy. Measurement of the apparent contact angles evidenced the Cassie - Baxter wetting regime of the porous films.

Volatile compounds, abundant in breath, can be used to accurately diagnose and monitor a range of medical conditions. This offers a non-invasive, low-cost approach with screening applications; however, uptake of this diagnostic approach has been limited by conflicting published outcomes. Most published reports rely on large scale screening of the public, at single time points and without reference to ambient air. Here, we present a novel approach to volatile sampling from cellular headspace and mouse breath that incorporates multi-time point analysis and ambient air subtraction revealing compound flux as an effective proxy of active metabolism. This approach to investigating breath volatiles offers a new avenue for disease biomarker discovery and diagnosis. Using gas chromatography mass spectrometry (GC/MS), we focus on low molecular weight, metabolic substrate/by-product compounds and demonstrate that this non-invasive technique is sensitive (reproducible at ~1 µg cellular protein, or ~500,000 cells) and capable of precisely determining cell type, status and treatment. Isolated cellular models represent components of larger mammalian systems and we show that stress- and pathology-indicative compounds are detectable in mice, supporting further investigation using this methodology as a tool to identify volatile targets in human patients.

The present article seeks to study whether there is any relationship between the equation of the rhythmic figures (Lugos Abarca, 2023) and cardiac auscultation using Field's method, which consists of representing cardiac sounds by means of musical notation (Field, 2010). A new meaning is given to the equation, concluding a mathematical equality between the equation of the rhythmic figures and the formula for calculating the RR Interval.

With recent developments in fusion engineering, interest has sparked in development of fusion devices for deterrent. Enormous amount of energy generated by combining two light nuclei could be contained and manipulated at will to trigger and accelerate micro explosions (from shock wave, x-rays or ion beam focusing) which finally result in full scale blast. Materials required to make such device are critical. They must possess high strength, high hardness, ductility, formability, drawability, and anisotropic properties. High entropy alloys (HEA) are new class of materials which nicely fulfils this requirement. Essentially, they are solid solutions of multi principal elements (usually > 5) eliminating the need of base metal as in conventional alloys. This gives them many unique properties which may be tailored at will (heat treatment, cold rolling, precipitation, irradiation). They also exhibit excellent directional properties with formation of distinct bands along certain preferred crystallographic planes even in hexagonal close packed structures. These anisotropic properties are strong function of rolling, working, or forging (swaging) direction and can be utilized to benefit. This study encompasses making outer shell of a typical fusion device selected on the basis of the weight, which is a function of area of pay load bay of carrier aircraft.

This work aimed to characterize a DBD plasma equipment through optical and electrical measurements, seeking to obtain a greater knowledge of the plasma production process and how it behaves through the adopted parameters, such as frequency and voltage applied between electrodes, at a fixed distance of 1.7 mm. In order to measure them, three different characterization techniques were applied. The first method was the Lissajous figures, a technique quite effective for a complete electrical characterization of DBD equipment. The second technique used was the Optical Emission Spectroscopy, a tool used for the diagnosis of plasma, being it possible to identify the excited species produced in filamentary and diffuse discharge in the plasma. And finally, the triple Langmuir probe technique was used to obtain the electron temperature and electron density. Based on this study, it was possible to identify the equipment efficiency in different regimes. The electron temperature measurement for both systems analyzed were 27.96 eV and 20.69 eV to the filamentary and diffuse regimes, respectively. The density of electrons number to these regimes were 1.09 × 10²¹ m⁻³ and 1.56 × 10²¹ m⁻³.

This article proposes application of a new mathematical model of spots for solving inverse problems using a learning method, which is similar to using the deep learning. In general, the spots represent vague figures in abstract “information spaces” or crisp figures with lack of in-formation about their shapes and are adequate for representation human mental images and reasoning in Artificial Intelligence (AI). However, crisp figures are regarded as a special and limiting case of spots. A basic mathematical apparatus, basing on L4 numbers, has been developed for the representation and processing of qualitative information of elementary spatial relations between spots. Also, we defined L4 vectors, L4 matrices, and mathematical operations on them. Developed apparatus can be used in AI, in particular, for knowledge representation and for modeling qualitative reasoning and learning. Another application area is the solution of inverse problems by learning. For example, this can be applied to image reconstruction using ultrasound, X-ray, magnetic resonance, or radar scan data. The introduced apparatus was verified by solving problems of reconstruction of images, utilizing only qualitative data of its elementary relations with some scanning figures. This article also demonstrates application of spot-based inverse Radon algorithm for binary image reconstruction.

Existing approaches to identifying predictive T-cell epitopes have traditionally utilized either 2-digit HLA super-families or more commonly autologous HLA alleles to facilitate the predictions, but frequently they may not consider their representation within a population. Here we propose a modification to this concept whereby subsets of individuals are selected for their specific HLA allele profiles and the representation they provide within a given population. Using this targeted approach to HLA selection and the linkages to specific individuals may enable the design of restricted experimental strategies.

The brain, rather than being homogeneous, displays an almost infinite topological genus, because is punctured with a very high number of topological vortexes, i.e., .e., nesting, non-concentric brain signal cycles resulting from inhibitory neurons devoid of excitatory oscillations. Starting from this observation, we show that the occurrence of topological vortexes is constrained by random walks taking place during self-organized brain activity. We introduce a visual model, based on the Pascal’s triangle and linear and nonlinear arithmetic octahedrons, that describes three-dimensional random walks of excitatory spike activity propagating throughout the brain tissue. In case of nonlinear 3D paths, the trajectories in brains crossed by spiking oscillations can be depicted as the operation of filling the numbers of the octahedrons in the form of “islands of numbers”: this leads to excitatory neuronal assemblies, spaced out by empty area of inhibitory neuronal assemblies. These procedures allow us to describe the topology of a brain of infinite genus, to assess inhibitory neurons in terms of Betti numbers, and to highlight how non-linear random walks cause spike diffusion in neural tissues when tiny groups of excitatory neurons start to fire.

The Universe, rather than being homogeneous, displays an almost infinite topological genus, because it is punctured with a countless number of gravitational vortexes, i.e., black holes. Starting from this view, we aim to show that the occurrence of black holes is constrained by geometric random walks taking place during cosmic inflationary expansion. At first, we introduce a visual model, based on the Pascal’s triangle and linear and nonlinear arithmetic octahedrons, which describes three-dimensional cosmic random walks. In case of nonlinear 3D paths, trajectories in an expanding Universe can be depicted as the operation of filling the numbers of the octahedrons in the form of “islands of numbers”: this leads to separate cosmic structures (standing for matter/energy), spaced out by empty areas (constituted by black holes and dark matter). These procedures allow us to describe the topology of an universe of infinite genus, to assess black hole formation in terms of infinite Betti numbers, to highlight how non-linear random walks might provoke gravitational effects also in absence of mass/energy, and to propose a novel interpretation of Beckenstein-Hawking entropy: it is proportional to the surface, rather than the volume, of a black hole, because the latter does not contain information.

A major limitation of near-infrared spectroscopy (NIRS) is its high sensitivity to the scalp and low sensitivity to the brain of adult humans. In the present work we use multi-distance hyperspectral NIRS (hNIRS) to investigate the optimal source-detector distances, range of wavelengths, and analysis techniques to separate cerebral responses to 30-s breath holds (BHs) from the responses in the superficial tissue layer in healthy adult humans. We observed significant responses to BHs in the scalp hemodynamics. Cerebral responses to BHs were detected in the cytochrome C oxidase redox (rCCO) at 4 cm without using data from the short-distance channel. Using the data from the 1 cm channel in the two-layer regression algorithm showed that hemodynamic and rCCO responses also occurred at 3cm. We found that the waveband 700-900 nm was optimal for the detection of cerebral responses to BHs in adults.

The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection which detects the patient's exhaled VOCs combined with sensor arrays of Convolutional Neural Network (CNN) algorithms as a new lung cancer detection is attracting more researchers' attention. However, due to low accuracy, high complexity computation and large number of parameters make the CNN algorithms difficult transplant to the embedded system of POCT devices. A lightweight neural network (LTNet) in this work is proposed to deal with this problem, and meanwhile, achieve high-precision classification of acetone and ethanol gases, which are respiratory markers for lung cancer patients. Compared to currently popular lightweight CNN models such as EfficientNet, LTNet has fewer parameters (32K) and its training weight size is only 0.155 MB. LTNet achieved an overall classification accuracy of 99.06% and 99.14% in the own mixed gas dataset and the University of California (UCI) dataset, which are both higher than that of the five existing models’, and it also offers the shortest training (844.38s and 584.67s) and inference time (23s and 14s) in the same validation set. Compared to the existing CNN models, LTNet is more suitable for resource-limited POCT devices.

Exhaled breath condensate (EBC) sample analysis is an entirely non-invasive novel sample collection method that is fast, easy to perform, and effort-appeared independent. EBC samples can be very useful in identifying the biomarkers of many diseases. This review provides an updated overview of EBC pH disturbances in different disorders as well as physiological levels among healthy individuals since 2012. Our meta-analysis addresses some of the key questions related to sample processing before pH measurement and discusses various methods of condensate standardization that can be employed prior to conducting a pH assay. Given the recent widespread interest in research into the use of EBC to identify biomarkers, it is necessary to establish a pathway leading from analytical methods for biomarker evaluation using EBC pH to clinical applications of this technology. This review fills a gap in the literature and attempts to connect theory to practical analytical approaches to analyzing EBC samples and making critical treatment-related decisions next to the patient's bed.

Halloysite and kaolinite are dioctahedral TO phyllosilicates that drive the interest of scientists for formulating environmental friendly materials, and consequently in the field of ceramics. The main scope of this study was the understanding of the texture evolution upon the dehydroxylation reaction and the influence of the presence of halloysite. In situ synchrotron (002) and (111) poles figures were recorded on the DiffAbs beamline at SOLEIL Synchrotron, from room temperature to 1000°C, on kaolinite and/or halloysite-rich samples shaped by tape casting. Commercial kaolins and halloysite provided by Imerys company were used. The samples were labeled KRG100, KCS100, H100, KRG50H50 and KRG59H50 in relation with the wt. % of kaolin (KRG, KCS) or halloysite (H) clays. In samples KCS100 and KRG100, a strong texture was observed until in situ annealing at 700°C, with respect to the c-axis of kaolinite. One the contrary, the texture with respect to the c-axis of halloysite for the sample H100 was weak whatever the temperature was. Moreover, this weak texture disappeared before the complete dehydroxylation of halloysite. This is due to the opening of some halloysite tubes. When considering the samples KRG50H50 and KCS50H50, a significant texture was observed with the c-axis preferentially oriented perpendicular to the sample surface . The presence of kaolinite platelets predominated onto the alignment of halloysites tubes. Furthermore, it was noted that the halloysite influenced the (002) diffracted intensity into the temperature range 20 °C and 400 °C. Above 400°C, the behavior obtained for the (002) reflection in samples KRG50H50 and KCS50H50 was similar to the behavior noticed for pure kaolins KRG100 and KCS100 respectively. The dehydroxylation temperature range appeared to be relevant with combined effect of kaolinite and halloysite transformations arising from KRG100 or KCS100 and H100 samples. Therefore, the onset point of dehydroxylation is 550 °C ± 25 °C for KRG100, KCS100 KRG50H50 and KCS50H50. For the pure halloysite H100 sample, the dehydroxylation starts at lower temperature 475°C. It was also noted that during the dehydroxylation of kaolinite, the characteristic portion of ring related to the diffracted intensity of the (111) reflection located at χ = 45 ° tended to disappear above 550 °C and led to the formation of a new transitory phase with a (111) reflection with perpendicular alignment to the c-axis. Indeed, an epitaxial relationship with the (111) kaolinite reflection could be assumed. Further X-ray scattering experiments allowed highlighting the effective offset temperature of the dehydroxylation, which was identified as close to 720 °C. The metakaolinite obtained undergone structural transformation to another transitory phase at 1000°C.

Breath volatile organic compound analysis is a non-invasive tool for assessing health status; the compositional profile of these compounds in the breath of patients with chronic kidney disease is believed to change with decreasing renal function. We aimed to identify breath volatile organic compounds for recognizing patients with chronic kidney disease. Using thermal desorption-gas chromatography-mass spectrometry, untargeted analysis of breath markers was performed using breath samples of healthy controls (n=18) versus non-dialysis (n=21) and hemodialysis (n=12) patients with chronic kidney disease in this cross-sectional study. A total of 303 volatile organic compounds alongside 12 clinical variables were used to determine the breath volatile organic compound profile. Metabolomic analysis revealed that age, systolic blood pressure, and fifty-eight breath volatile organic compounds differed significantly between the chronic kidney disease group (non-dialysis + hemodialysis) and healthy controls. Thirty-six volatile organic compounds and two clinical variables that showed significant associations with chronic kidney disease in the univariate analysis were further analyzed. Different spectras of breath volatile organic compounds between the control and chronic kidney disease groups were obtained. Multivariate model incorporating age, 2-methyl-pentane, and cyclohexanone showed high performance (accuracy, 86%) in identifying patients with chronic kidney disease, with odds ratios (95% confidence interval) P-values of 0.18 (0.07-2.49) 0.013; 2.10 (0.94-2.24) 0.025; and 2.31 (0.88–2.64) 0.008, respectively. Hence, renal dysfunction-associated characteristic profiles of breath volatile organic substances can be used as non-invasive markers to screen for chronic kidney disease.

Yogic and meditative traditions have long held that the fluctuations of the breath and the mind are intimately related. While respiratory modulation of cortical activity and attentional switching are established, the extent to which electrophysiological markers of attention exhibit synchronization with respiration is unknown. To this end, we examined 1) frontal midline theta-beta ratio, an indicator of attentional control state known to correlate with mind wandering episodes and functional connectivity of the executive control network; 2) pupil diameter (PD), a known proxy measure of locus coeruleus (LC) noradrenergic activity; and 3) respiration for evidence of phase synchronization and information transfer (multivariate Granger causality) during quiet restful breathing. Our results indicate that both TBR and PD are simultaneously synchronized with the breath, suggesting an underlying oscillation of an attentionally relevant electrophysiological index that is phase-locked to the respiratory cycle which could have the potential to bias the attentional system into switching states. We highlight the LC’s pivotal role as a coupling mechanism between respiration and TBR, and elaborate on its dual functions as both a chemosensitive respiratory nucleus and a pacemaker of the attentional system. We further suggest that an appreciation of the dynamics of this weakly coupled oscillatory system could help deepen our understanding of the traditional claim of a relationship between breathing and attention.

Many patients with Coronavirus disease 2019 (COVID-19) suffer from shortness of breath and severe chest pain. Here we report successful therapy of a patient with diagnosis of COVID-19, severe chest pain and significant shortness of breath, using radial extracorporeal shock wave therapy (rESWT). The latter started seven days after beginning of symptoms and drug therapy without success, and involved daily application of 15.000 to 20.000 radial extracorporeal shock waves over the intercostal muscles as well as the paravertebral muscles of the thoracic and lumbar spine, diaphragm and flanks. Immediately after the first rESWT session the patient experienced significant pain relief and improvement of breathing. Four days later the pain had completely subsided and breathing was largely normalized. This type of noninvasive, non-pharmacologic treatment could help many COVID-19 patients or patients who still suffer from breathing problems weeks after having been infected with SARS-CoV-2, giving them back quality of life.

One third of fatal car accidents and so much tragedies are due to alcohol abuse. These sad numbers could be mitigated if everyone had access to a breathalyzer anytime and anywhere. Having a breathalyzer built into a phone or a wearable could be the way to get around the reluctance to carry a separate device. Towards this goal, we propose an inexpensive breathalyzer that could be integrated in the screen of mobile devices. Our technology is based on the evaporation rate of the fog produced by the breath on the phone screen, which increases as a function of the breath alcohol content. The device simply uses a photodiode placed on the side of the screen to measure the signature of the scattered light intensity from the phone display that is guided through the stress layer of the Gorilla glass screen. A part of the display light is coupled to the stress layer via the evanescent field induced at the edge of the breath microdroplets. We demonstrate that the intensity signature measured at the detector can be linked to the blood alcohol content. We fabricated a prototype in a smartphone case powered by the phone’s battery, controlled by an application software installed in the smartphone and tested it in real-world environments. Limitations and future work toward a fully operational device are discussed.

In the present work a novel, portable and innovative eNose composed of a surface acoustic wave (SAW) sensor array based ZIF-8, and ZIF-67 nanocrystals (pure and combined with gold nanoparticles) as sensitive layers has been tested as a non-invasive system to detect and differentiate disease markers, such as acetone, ethanol and ammonia, related with early diagnosis of diabetes mellitus through exhaled breath. The sensors have been prepared by spin coating, achieving continuous and homogenous sensitive layers. Low concentrations (5 ppm, 10 ppm and 25ppm) of the marker analytes were measured, obtaining high sensitivities, good reproducibility, short time response and fast signal recovery.

Abstract: Fanconi anemia (FA), a chromosomal instability syndrome, is caused by inherited pathogenic variants in any of 22 FANC genes, that cooperate in the FA/BRCA pathway. This pathway regulates the repair of DNA interstrand crosslinks (ICLs) through homologous recombination. In FA proper repair of ICLs is impaired, and accumulation of toxic DNA double strand breaks occurs. In order to repair this type of DNA damage, FA cells activate alternative error-prone DNA repair pathways, that may lead to the formation of gross structural chromosome aberrations of which radial figures are the hallmark of FA and their segregation during cell division are the origin of subsequent aberrations like translocations, dicentrics and acentric fragments. The deficiency in DNA repair has pleiotropic consequences in the phenotype of patients with FA, including developmental alterations, bone marrow failure and an extreme risk to develop cancer. The mechanisms leading to the physical abnormalities during embryonic development have not been clearly elucidated, however FA has features of premature aging with chronic inflammation mediated by pro-inflammatory cytokines, that results in tissue attrition, selection of malignant clones and cancer onset. Moreover, the effect of the FA/BRCA pathway in germinal cells, evidenced by infertility in patients with FA attests of chromosomal instability and cell death also occurring in the germinal compartment.

The wavelet spectral characteristics of three respiratory muscle signals (Scalenus (SC), Parasternal intercostal (IC) and Rectus abdominis (RA)) and one locomotor muscle Brachioradialis (BR) were analyzed in the time-frequency (T-F) domain during breath-holding (BH). Study was performed for an end-expiratory BH maneuver on twelve healthy, physically active, naive apneists (6 professional athletes; 6 recreational athletes, two in the post-COVID-19 period) using surface electromyography (sEMG). We observe individual effects dependent on muscle oxygenation and person’s fitness, consistent with the mechanism of motor unit (MU) recruitment and the transition of slow-twitch oxidative (type 1) to fast-twitch (oxidative) glycolytic (type 2) muscle fibers. Professional athletes had longer BH duration (BHD) and strong hypercapnic response on expiratory RA, which is activated abruptly at higher BHDs in a person-specific range below 250 Hz and dependent on BHD. This is in contrast with recreational athletes, who had strong hypoxic response on inspiratory IC, which is activated faster and gradually in the frequency range of 250-450 Hz (independent of the apneist and BHD). This pilot study preliminarily indicates that it is possible to non-invasively assess the physiological characteristics of skeletal muscles, especially oxygenation, and improve physical fitness tests by determining T-F features of elevated myoelectric IC and RA activity during BH.

Many individuals are wearing face masks improperly at ‘half mask’ and potentially breathing out microbes that can contaminate the air as well as anything below the nose. This note provides the first report that bacteria and fungi breathed out during nasal air exhalation are able to be cultured after landing on blood agar plates. The CFU’s are higher after both 10 breaths and extremely significant for 20 breaths compared to the control plates exposed to the air. Implications of this finding are that going ‘nose commando’ may be able to continue the spread of respiratory diseases such as COVID-19.

The paper proves the existence of a family of axisymmetric equilibrium figures as solutions of a stationary problem with unknown boundaries for the Navier–Stokes equations corresponding to the slow rotation of a viscous compressible two-layer liquid mass about some axis. It is assumed that the liquids are barotropic, capillary and have different viscosities, the internal fluid being bounded by a closed surface. This interface does not intersect with the external boundary of the cloud. The proof is based on implicit function theorem and carried out in the Hölder spaces.

Diabetes mellitus is a widespread chronic metabolic disorder demanding regular blood glucose level surveillance (BGLs). Current invasive techniques, such as finger-prick tests, often result in discomfort for patients, leading to infrequent monitoring and potential health complications. The primary objective of this study was to design a novel, portable, non-invasive system for diabetes detection using breath samples, named as DiabeticSense, an affordable digital health device for early detection, encouraging immediate intervention. The device employed MOSFET-based electrochemical sensors to assess volatile organic compounds in breath samples, whose concentrations differ between diabetic and non-diabetic individuals. The system merged body vital signs with sensor voltages obtained by processing breath sample data to predict diabetic conditions. Our research used readings from 100 patients at a nationally recognised hospital to form the dataset. Data was then processed 10 using a Gradient Boosting Classifier model, and performance was cross-validated. The proposed system attained a promising accuracy of 86.6%, marking an improvement of 20.72% over an existing regression technique. The developed device introduces a non-invasive, cost-effective, and user-friendly solution for preliminary diabetes detection. It has the potential to increase patient adherence to regular monitoring.

We conducted many model simulations to understand the causes of the damages of coronavirus to lung tissues and constructed a diagram showing viral development, immune response and damage accumulation curves. We found that main causes are (1) the phase lag between the viral reproduction process and a belayed immune response, (2) the direct viral damages and massive collateral damages which are mainly caused by belated immune responses, and (3) further tissue damages triggered by accumulated wastes in lungs. We deduced from those causes that the key strategies for preventing lung damages include avoiding direct lung infection, altering host-virus interactions, promoting immune responses, diluting virus concentrations in lung tissues by promoting viral migration to the rest of the body, maintaining waste removal balance, protecting heart function and renal function, avoiding other infections, reducing allergic reactions and other inflammation, etc. We finally discussed how to use dietary, medical, emotional, lifestyle, environmental, mechanical factors, etc. to alter disease outcomes. We show why true benefits of those factors cannot be determined by randomized controlled trials, and why the multiple-factor optimization approach can be highly effective by examining organ usable capacity in the cause of death. This treatment protocol using water, air, salt, sound, temperature, emotion, exercise, etc. can be the most powerful cures for viral and non-viral lung infections because they do not depend on molecular specificity and are freely available to anyone.

The reliable online analysis of volatile compounds in exhaled breath remains a challenge as a plethora of molecules occur in different concentration ranges (i.e. ppt to %), and need to be detected against an extremely complex background matrix. While this complexity is commonly addressed by hyphenating a specific analytical technique with appropriate preconcentration and/or preseparation strategies prior to detection, we herein propose the combination of three analytical tools based on truly orthogonal measurement principles as an alternative solution: field-asymmetric ion mobility spectrometry (FAIMS), Fourier-transform infrared (FTIR) spectroscopy-based sensors utilizing substrate-integrated hollow waveguides (iHWG), and luminescence sensing (LS). These three tools have been integrated into a single compact analytical platform suitable for online exhaled breath analysis. The analytical performance of this prototype system was tested via artificial breath samples containing nitrogen (N2), oxygen (O2), carbon dioxide (CO2) and acetone as a model volatile organic compound (VOC) commonly present and detected in breath. Functionality of the combined system was demonstrated by detecting these analytes in their respectively breath-relevant concentration range and mutually independent of each other generating orthogonal yet correlated analytical signals. Finally, adaptation of the system towards the analysis of real breath samples during future studies is discussed.