Range Of Applications Research Articles

SUPER-COUGH: A Super Learner-based ensemble machine learning method for detecting disease on cough acoustic signals

Sound classification has obtained considerable attention in recent years due to its wide range of applications in various fields, such as speech recognition, sound surveillance, music analysis, and environmental monitoring. Because of its success, audio classification can also be employed in medical applications. Coughing is the most common disease symptom, and cough sounds might be used to diagnose them. This research focuses on identifying observable features of cough and classifying them into positive, negative, or symptomatic categories. A novel ensemble learning model based on the super learner (SL) is proposed to diagnose the disease using cough sounds utilizing various audio features such as Frequency Distribution, Time Domain Features, Spectral Features, and Time–Frequency Features. The SL method is a cross-validated approach to stacked generalization, and it can select an optimal learner from a set of learners and improve performance by selecting and merging models using cross-validation. The proposed SL model comprises DT, RF, LR, SVM, ET, and k-NN algorithms. We use the public Coughvid dataset, and the proposed model achieves a correct classification rate for symptomatic cases, which was 90.90%, and the positive predictive value for COVID-19 cases was 84.50%. The SL3 model attains 72%, 78%, 73%, 74.4%, and 78.85% precision, recall, f1-score, accuracy, and average AUC values, respectively. The numerical results show that the proposed model might be implemented to diagnose various other diseases that can be determined from respiratory sounds.

Utilizing AI-Enhanced Multi-Omics Integration for Predictive Modeling of Disease Susceptibility in Functional Phenotypes

With the continuous development of machine learning technology, the scientific research of biomedical materials is gradually shifting to a data-driven direction. The rise of this trend stems from the widespread use of Bio sequencing technology, which provides entirely new methods and insights for testing and evaluating the biological function of biomedical materials. The performance and performance of biomedical materials have a wide range of applications in medical applications, drug delivery, biosensors and other fields, so it is important to further optimize them. However, with the accumulation and increasing complexity of data, there is a need for more intelligent and efficient ways to process and analyze this heterogeneous scientific data. Therefore, the establishment of an open, shared infrastructure for storing heterogeneous scientific data from different research fields will be the cornerstone of cross-disciplinary joint analysis. This infrastructure will not only accelerate the collection and integration of data, but will also provide opportunities for collaboration and innovation across disciplines. This paper highlights a new trend in biomedical materials research, namely a data-driven approach, and the key role of Bio sequencing technology in this process. At the same time, we call for the establishment of an open data storage and sharing platform to promote multidisciplinary cooperation, accelerate the optimization and innovation of biomedical materials, and open up broader prospects for future biomedical applications. This effort is expected to push scientific research in the medical field to new heights, providing safer and more effective treatments and medical programs for patients.

Investigation of the composition and morphology of raw materials from the Aral Sea region

Abstract Clay and clay-based minerals have attracted research attention because of their unique properties and a vast range of applications in industry. In order to assess the potential applications, four different processed local kaolin-based raw minerals were collected from the Aral Sea region of Uzbekistan, and the total mineralogical properties have been explored. The results reveal that the structural, vibrational and electronic properties of metakaolinites only slightly differ from those of kaoline. The presence of corundum, quartz and kaolinite structural phase in minerals was determined by XRD analysis. FTIR and Raman studies expose the primary peaks which are associated with the functional groups of Al–OH, Al–O and Si–O in higher-frequency stretching and lower-frequency bending modes. The elemental and chemical compositional (XRF and XPS) analysis demonstrates the presence of major elements (Al, Si, Na, Fe, Ti) in the raw mineral and other metal contaminations (Mg, Ca, S, Cr, Zr). The SEM analysis demonstrates the morphological nature of kaolin-based raw minerals that can be exploited for industrial purposes.

Upconversion Nanoparticles Based Sensing: From Design to Point-of-Care Testing.

Rare earth-doped upconversion nanoparticles (UCNPs) have achieved a wide range of applications in the sensing field due to their unique anti-Stokes luminescence property, minimized background interference, excellent biocompatibility, and stable physicochemical properties. However, UCNPs-based sensing platforms still face several challenges, including inherent limitations from UCNPs such as low quantum yields and narrow absorption cross-sections, as well as constraints related to energy transfer efficiencies in sensing systems. Therefore, the construction of high-performance UCNPs-based sensing platforms is an important cornerstone for conducting relevant research. This work begins by providing a brief overview of the upconversion luminescence mechanism in UCNPs. Subsequently, it offers a comprehensive summary of the sensors' types, design principles, and optimized design strategies for UCNPs sensing platforms. More cost-effective and promising point-of-care testing applications implemented based on UCNPs sensing systems are also summarized. Finally, this work addresses the future challenges and prospects for UCNPs-based sensing platforms.

Soret and Dufour Effects on MHD Fluid Flow Through a Collapssible Tube Using Spectral Based Collocation Method

This paper examine numerical study for soret and dufour effects on unsteady Newtonian MHD fluid flow with mass and heat transfer in a collapsible elastic tube using Spectral Collocation technique. The objective of the study is to determine the velocity, temperature and concentration profiles together with heat and mass transfer rates. The governing equations are continuity, momentum, energy and concentration equation. The system of nonlinear partial differential equations governing the flow solved numerically by applying collocation method and implemented in MATLAB. The numerical solution of the profiles displayed both by graphically and numerically for different values of the physical parameters. The effects of varying various parameters such as Reynolds number, Hartmann number, Soret number, Dufour number and Prandtl number on velocity, temperature and concentration profiles also the rates of heat and mass transfer are discussed. The findings of this study are important due to its wide range of application including but not limited to medical fields, biological sciences and other physical sciences where collapsible tubes are applied.

Preparation and characterization of multipurpose polypropylene composite with outstanding flame retardancy and antistatic property

AbstractTo enhance the safety grade and broaden the application scope of polypropylene in coal mines, the calcium alginate@ammonium polyphosphate@graphite microsheet (CA@APP@GM) had been synthesized and introduced into the polypropylene (PP) material to endow excellent flame retardancy, antistatic characteristics, thermostability, combustion behavior, and mechanical performance. Physical characterizations on the chemical composition and microstructure of both the gaseous and condensed phase products indicated that the phosphorus‐containing compounds were found in the char residue which were beneficial to accelerate the charring reaction to terminate the mass and heat transfer process. Hence, the CA@APP@GM executed the condensed‐phase flame‐retardant mechanism to enhance the fire resistance of PP matrix. Consequently, it is believed that the CA@APP@GM, with its remarkable flame retardancy and antistatic properties, has the potential to significantly expand the range of applications for PP materials in coal mines.

Microbially Inspired Calcium Carbonate Precipitation Pathway Integrated Polyelectrolyte Capsules (MICPC) for Biomolecules Release.

Complexation between oppositely charged polyelectrolytes offers a facile single-step strategy for assembling functional micro-nano carriers for efficient drug and vaccine delivery. However, the stability of the delivery system within the physiological environment is compromised due to the swelling of the polyelectrolyte complex, driven by the charge shielding effect, and consequently leads to uncontrollable burst release, thereby limiting its potential applications. In a pioneering approach, cellular pathway-inspired calcium carbonate precipitation pathways are developed that are integrated into polyelectrolyte capsules (MICPC). These innovative capsules are fabricated at the interface of all-aqueous microfluidic droplets, resulting in a precisely controllable and sustained release profile in physiological conditions. Unlike single-step polyelectrolyte assembly capsules which always perform rapid burst release, the MICPC exhibits a sustainable and tunable release pattern, releasing biomolecules at an average rate of 3-10% per day. Remarkably, the degree of control over MICPC's release kinetics can be finely tuned by adjusting the quantity of synthesized calcium carbonate particles within the polyelectrolyte complex. This groundbreaking work not only deepens the insights into polyelectrolyte complexation but also significantly enhances the overall stability of these complexes, opening up new avenues for expanding the range of applications involving polyelectrolyte complex-related materials.

Effects of carboxylated styrene‐butadiene latex nanoparticles on channeling leakage and pore structure of oil well cement

AbstractThe exploitation efficiency of oil and gas resources depends on the cementing quality. In cementing engineering, interlayer migration occurs in the underground gas layer with cement hole as the main channel, which seriously threatens the sealing integrity of cement casing and leads to the failure of cementing operation. To improve the gas migration control ability of oil well cement (OWC), two carboxylated styrene‐butadiene latex nanomaterials styrene butadiene latex containing itaconic acid and sodium p‐styrene sulfonate (SBSI) and styrene‐butadiene latex containing methacrylic acid and sodium p‐styrene sulfonate (SBSM) were synthesized. The effects of SBSI and SBSM with different carboxyl structures on the gas migration control ability and pore structure of cement were investigated. The results show that the latex is densely packed on the cement matrix through the dissociation and adsorption behavior of carboxyl groups, and the smaller particle size and lower adsorption are more conducive to the formation of the film. The introduction of latex effectively shortened the transition time of cement gel state and significantly reduced the permeability of interlayer material migration. Compared with OWC, the transition time of cement containing SBSI and SBSM latex (SBSI/OWC and SBSM/OWC) decreased from 28 to 18 and 17 min, respectively, and the filter loss decreased from 60 to 40 and 36 mL, respectively. The isolation effect of the latex film on the interlayer gas and the provision of mechanical support have greatly improved the gas migration control ability of the cement and ensured the cementing quality. In addition, the refinement of cement pore structure caused by latex brings better rheological and mechanical properties to cement. This study clarified the change of latex in the gel transition stage of OWC from liquid to solid and revealed the mechanism of latex on the internal structure change of cement. It broadens the application range of latex nanomaterials in the field of OWC and provides a new possibility for the use of OWC in high temperature and high salt environment.

Scalable Moment Propagation and Analysis of Variational Distributions for Practical Bayesian Deep Learning.

Bayesian deep learning is one of the key frameworks employed in handling predictive uncertainty. Variational inference (VI), an extensively used inference method, derives the predictive distributions by Monte Carlo (MC) sampling. The drawback of MC sampling is its extremely high computational cost compared to that of ordinary deep learning. In contrast, the moment propagation (MP)-based approach propagates the output moments of each layer to derive predictive distributions instead of MC sampling. Because of this computational property, it is expected to realize faster inference than MC-based approaches. However, the applicability of the MP-based method in deep models has not been explored sufficiently, even though some studies have demonstrated the effectiveness of MP only in small toy models. One of the reasons is that it is difficult to train deep models by MP because of the large variance in activations. To realize MP in deep models, some normalization layers are required but have not yet been studied. In addition, it is still difficult to design well-calibrated MP-based models, because the effectiveness of MP-based methods under various variational distributions has also not been investigated. In this study, we propose a fast and reliable MP-based Bayesian deep-learning method. First, to train deep-learning models using MP, we introduce a batch normalization layer extended to random variables to prevent increases in the variance of activations. Second, to identify the appropriate variational distribution in MP, we investigate the treatment of moments of several variational distributions and evaluate their uncertainty quality of predictions. Experiments with regression tasks demonstrate that the MP-based method provides qualitatively and quantitatively equivalent predictive performance to MC-based methods regardless of variational distributions. In the classification tasks, we show that we can train MP-based deep models by extended batch normalization. We also show that the MP-based approach realizes 2.0-2.8 times faster inference than the MC-based approach while maintaining the predictive performance. The results of this study can help realize a fast and well-calibrated uncertainty estimation method that can be deployed in a wider range of reliability-aware applications.

Acoustic shadow zone of the guided wave in a variable thickness plate

This paper calculates the acoustic shadow zone of the guided wave in a variable thickness plate. The variable thickness plate has a wide range of applications in bridges, ships, etc., and the guided wave is often used for its nondestructive testing. The velocity gradient induced by thickness variations will deflect the guided wave towards lower phase velocities. Both frequency and thickness variation play crucial roles in determining the extent of path bending. In particular, the guided wave can undergo reverse propagation at the non-boundary of the plate. This curved propagation path results in an acoustic shadow zone, inaccessible to direct waves. This article calculates and experimentally verifies the curved propagation path of dispersive guided waves. Experiments show that the degree of propagation path bending increases with the increase of frequency in a certain frequency range. On the path that varies along the thickness, the experiment observes an acoustic shadow zone that accounts for nearly 25% of the total path. Additionally, a practical case study involving a guided wave with a curved path is presented. Consideration of the curved path improves the positioning accuracy, offering insights into damage location in variable thickness plates. This research on the propagation path and acoustic shadow zone contributes to advancing the understanding of guided wave propagation characteristics and enhancing their application in nondestructive testing for variable thickness structures.

Evaluation of weathering resistance of cross-laminated timber blocks surface-treated with TiO2 nanoparticles by liquid-precursor flame spray pyrolysis

Wood is a versatile and renewable resource utilized in a wide range of applications, including tools, furniture, construction, and advanced engineering structures. However, certain inherent properties of wood, such as moisture and ultraviolet (UV) degradation, impose limitations on its long-term durability and dimensional stability for outdoor applications. This research investigates the weathering durability of cross-laminated timber (CLT) blocks surface-treated with titanium dioxide (TiO2) nanoparticles synthesized via liquid-precursor flame spray pyrolysis (FSP), directly deposited onto the surface of CLT blocks, and thereby resulting in a porous TiO2 coating. This coating endows the CLT surface with superhydrophobic properties evidenced by a water contact angle of ≥150°. Results from scanning electron microscopy and X-ray diffraction show the coating to be comprised of crystalline, sub-100 nm individual and aggregated TiO2 particles with significant porosity. Even after an 8-week accelerated weathering test, a portion of the crystalline TiO2 particles remains on the CLT surface. The TiO2-treated CLT demonstrates enhanced resistance to discoloration and gloss change over 8-weeks of accelerated weathering conditions, which are evidenced by a total color difference (ΔE) that is 3–4 times lower than that of the untreated CLT in the initial two weeks, and 58% lower after 8 weeks of weathering. Furthermore, the TiO2-treated CLT exhibits fewer weathering defects, such as splits and cracks, than the untreated CLT. The enhanced weathering durability of the TiO2-treated CLT is attributed to reduced lignin degradation, which is supported by the Fourier-transform infrared spectroscopy analysis. The findings of this study suggest that the TiO2 coating by FSP offers a viable and cost-effective method for modifying engineered wood products for improving hydrophobicity and protecting against the deteriorating effects of UV irradiation and moisture exposure.

Ab initio study of quantized conduction mechanism in trilayered heterostructure for scaled down memory device applications

Interface of the layered heterostructure revealing the quantized conductance phenomena which cannot be achieved with either semiconducting layer alone in absence of externally applied electric field has wide range of applications in electronic industry of RRAM devices. A comprehensive analysis of electronic properties of CeO2/Ta2O5/CeO2 trilayered heterostructure has been carried out using first principle calculation employing VASP to explore the state of art of RRAM including barrier height, barrier width, conducting filament width and shape. For better understanding of conduction mechanism involved in RS, the influence of crystalline and amorphous phase of Ta2O5 sandwiched between CeO2 layers is analyzed by potential energy lineups, DOS, isosurface and integrated charge density plots. Origin of quantized states formed near the Fermi level in DOS is provided physically by growth of charge conducting filaments in isosurface charge density plots, and charge redistribution from Bader charge analysis. Outcomes of this study confirmed that with more quantized charge, crystalline Ta2O5 is better for interfacial RRAM devices. Apart from previously available findings, results of this study will provide new route to the potential application of this layered material in electronics especially storage devices.

Low-Thrust Nonlinear Orbit Control for Very Low Lunar Orbits

In the next decades, both space agencies and private competitors are targeting the lunar environment as a scientific and technological resource for future space missions. In particular, the confirmed existence of water-ice deposits in the vicinity of the poles (predominantly the south pole) makes polar or near-polar low lunar orbits attractive for the purpose of designing space missions that could search for suitable Lunar base sites. However, traveling very-low-altitude orbits is very challenging, as they are strongly perturbed by the Moon’s gravity field as well as third- and fourth-body effects due to the Earth and the Sun. Several studies demonstrate that these orbits are expected to impact the lunar surface in a few months. Therefore, the definition and implementation of an effective station-keeping strategy represents a crucial issue in order to extend satellites’ lifetime. In this paper, a feedback nonlinear control law is employed in order to perform corrective maneuvers aimed at keeping the state of the satellite within acceptable margins. The satellite is assumed to be equipped with a steerable and throttleable low-thrust propulsion system. The control law is based on the Lyapunov stability theory and does not require any reference path to track, with a considerable decrease in the computational cost. The proposed real-time control law includes control saturation, related to the maximum available thrust magnitude, and is developed employing modified equinoctial elements, in order to avoid singularities and extend its range of application. Finally, the strategy at hand is tested in the presence of all the relevant perturbations (i.e., harmonics of the selenopotential, third- and fourth-body effects) in order to show its effectiveness and efficiency.

Smart Attendance System using Face Recognition


 Face recognition offers a wide range of valuable applications in social media, security, and surveillance contexts. The software used for building facial recognition algorithms is Python and OpenCV. "Attendance using Face Recognition" is a method for tracking and managing attendance that makes use of facial recognition technology. By seamlessly integrating the 'Face Recognition' module, a native Python feature, and the OpenCV library, our system excels in accuracy and dependability. The system then stores attendance records in a database and provides real-time reports. In this article, we demonstrate how to create a face recognition system in Python utilizing the built-in "Face Recognition" module and the OpenCV library. Our results show that our system achieves high accuracy and robustness while being efficient and scalable, catering to a wide spectrum of educational institutions, organizations, and enterprises.

Supercritical fluid decontamination (SCFD) of poly(vinylidene fluoride) (PVDF) and further upcycling into highly porous aerogels with a well defined microstructure

Per- and polyfluoroalkyl substances (PFAS) like polyvinylidene fluoride (PVDF) have a wide range of applications due to their high stability and persistency, but their production is increasingly being restricted because the mentioned outstanding properties simultaneously impose drawbacks in terms of poor (bio)degradability. The lack of appropriate and industrially established solutions for handling and reuse of PVDF after fulfilling its first purpose aggravates this environmental issue. The presented work outlines a novel approach for the upcycling of PVDF waste material by supercritical fluid decontamination of used PVDF and subsequent conversion into a value-added, highly porous PVDF-based material with an open-cell structure, a so-called aerogel, containing a well-defined pore morphology on the microscale. The work further shows that the synthesis of an aerogel from used PVDF tolerates impurities to a certain extent, for which the previous treatment does not necessarily have to render a material 100 % free of contaminations. As a result, a proof-of-concept is given for an industrially feasible process that is capable of upcycling a valuable high-performance polymer into a sophisticated porous material, thereby avoiding the release of potentially toxic fluorine compounds and opening a path towards a circular economy for contaminated PVDF.

Using Auricular Cartilage-fascia Composite Tissue Free Grafting Technique to Improve Cartilage Survival Outcomes.

Auricular cartilage graft has a wide range of applications in plastic and reconstructive surgery. However, there is still a risk of absorption of the grafts over time. Intrinsic postauricular fascia (IPF) with a rich vascular network may play an important role in the nutrition and repair of auricular cartilage. This study aimed to investigate the effect of IPF on the survival viability of free auricular cartilage grafts. 24 auricular cartilages were obtained from 6 New Zealand white rabbits which were divided into the cartilage-fascia composite graft group (FC group, n=12) and the cartilage without fascia group (C group, n=12). Two groups of cartilage were implanted into each side of the subcutaneous pocket of the rabbit's dorsum. The rabbits were sacrificed after 3 months and all cartilage grafts were obtained. Macroscopic observation, histopathological staining, and biomechanical testing were performed on all specimens. There were significant differences between the 2 groups regarding proliferating chondrocytes, apoptotic chondrocytes, vascularization, and matrix collagen. Compared to the auricular cartilage grafts without fascia, the auricular cartilage-fascia composite grafts had more neovascularization, proliferative chondrocytes, and type II collagen, with a homogeneous cartilage matrix and no obvious areas of heterogeneous staining. Young's modulus and ultimate tensile strength of cartilage were reduced in both groups compared to pretransplantation, but the composite graft group was superior to the fascia-free group. Auricular cartilage-fascial composite tissue free graft could improve cartilage survival outcomes with higher viability and mechanical properties.

Orientation-dependent plastic flow in nanoscratching of copper surfaces

The characterization of frictional behavior in ductile metals is a crucial aspect of materials science, as it relates to the plastic deformation of the material. However, due to the intricate dislocation evolution at the submicron/nanometer scale, the isolation of the basic plastic mechanisms remains challenging. In this study, nanoscratching technology is employed to investigate submicron/nanometer-level plastic deformation in individual grains of polycrystalline copper. To achieve this, a crystal plastic constitutive model for copper materials is developed by incorporating geometrically necessary dislocation effects. The calibration of the constitutive model is conducted with great precision and specificity, leveraging mechanical responses, surface accumulation morphology, and indentation size effects from nanoindentation experiments of 110-oriented single crystal copper. Through the combination of crystal plastic finite element simulation and nanoscratching experiments, the plastic flow of the material is thoroughly analyzed. The results demonstrate that the anisotropic scratching behavior is influenced by different orientations of individual grains, taking into account both statistical storage dislocations and geometrically necessary dislocations. The insights gleaned from this study offer a valuable contribution to our understanding of the plastic mechanisms of metals at a small scale, enhancing the design and performance of advanced materials for a wide range of applications.

The Development and Progress of Engineering Economics: A Retrospect and Prospect Based on Visual Analysis

Engineering economics is a cross subject with a wide range of applications, and it has taken on different characteristics with the changing times. The aim of this paper is to depict a sufficiently elaborate and vivid knowledge map of this field, with further discussion and outlook on the hotspots presented therein. Based on the principles and methods of bibliometrics, we use several visualization tools, mainly Vosviewer, to present the characteristics of the published literature within the field of engineering economics from multiple perspectives. Specifically, we collect 624 engineering economics documents published in the Web of Science core collection database between 1915 and 2021, and quantitatively analyze them in the following three aspects: (1) basic data characteristics, including annual publications, annual citations, research directions, and highly cited publications; (2) outstanding performers and cooperations in the four levels of country/region, institution, source and author, including co-authorship, bibliographic coupling, co-citation and co-occurrence analyses; and (3) keyword analyses, including co-occurrence analyses, burst detection analyses, and high-frequency word clouds. In addition, we further explore important topics within the field represented by intelligent and green transformation.

Advanced Magnetic Actuation: Harnessing the Dynamics of Sm2Fe17-xCuxN3 Composites.

Recently, there has been an escalating demand for advanced materials with superior magnetic properties, especially in the actuator domain. High coercivity (Hci), an essential magnetic property, is pivotal for programmable shape changes in magnetic actuators and profoundly affects their performance. In this study, a new Sm2Fe17-xCuxN3 magnet with a high Hci was achieved by modifying the temperature of the reduction-diffusion process─lowering it from 900 to 700 °C through the introduction of Cu and finer control over the structure and morphology of the Sm2Fe17-xCuxN3 magnetic component within the actuator composite. Consequently, the Sm2Fe17-xCuxN3 magnet demonstrated a remarkable Hci of 11.5 kOe, eclipsing the value of 6.9 kOe attained by unalloyed Sm2Fe17N3 at reduced temperatures. By capitalizing on the enhanced magnetic properties of the Sm2Fe17-xCuxN3 composite and incorporating poly(ethylene glycol) into the elastomer matrix, we successfully fabricated a robust actuator. This innovative approach harnesses the strengths of hard magnets as actuators, offering stability under high-temperature conditions, precision control, longevity, wireless functionality, and energy efficiency, highlighting the vast potential of hard magnets for a range of applications.

Chemical Recycling and Physical Tuning of Necklace-Shaped Polydimethylsiloxanes Bearing Anthracene Dimer Units.

The problem of plastic waste in the environment calls for the development of new polymeric materials designed specifically for easy recycling at the end of their life cycle. Herein, a green polymer system comprising a series of necklace-shaped polydimethylsiloxanes bearing anthracene dimer units is developed. The polymers have low environmental impact and are easily recycled. Further, their flexibility and glass transition temperatures are easy to control. These necklace-shaped inorganic polymers are synthesized by photopolymerizing (dimerizing) anthracene-terminated oligo-dimethylsiloxane monomers. A key achievement of the present work is the successful chemical recovery of the monomers from the polymers through thermal depolymerization, enabling monomer-polymer recycling. By applying equilibrium polymerization with base catalysts, monomers with a controlled distributed chain length are synthesized from monomers with a constant chain length. The necklace-shaped polymers synthesized from these randomized monomers have amorphous structures and readily form transparent films. It is possible to modulate the thermal and mechanical properties of the polymers by controlling the average chain length of the polydimethylsiloxane between the anthracene dimers. This investigation presents a method for the synthesis and cyclic utilization of polymer materials with a wide range of applications, including plastics and elastomers.