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The design capability, strength, and structural rigidity provided by tube hydroforming (THF) are successfully used in many applications to produce high-strength parts and assemblies with improved mechanical properties, optimized service life, and weight features. In tubular metal forming, output parameters such as branch height, distribution of tube wall material thickness, distribution of damage factor, metal flow, effective stress, and effective strain significantly affect the quality of the product after the forming process. Therefore, this paper aims to evaluate the manufacturing quality of Y-shape joints from AISI304 material steel tube through output parameters of THF process with and without counter punch force on numerical simulation base. The Finite Element Method (FEM) has become an established feature of metal forming technology. The objective of FEM is to replace costly and elaborate experimental testing with fast, low-cost computer simulation. The simulation study uses finite element method-based virtual prototyping techniques to characterize output parameters, gain insight into strain mechanics, and predict mechanical properties of shaped components. The research results are presented clearly and unambiguously through the evaluation of 7 criteria to compare the quality of the specimens hydroformed by two surveyed cases and optimize the crucial input process parameters. And these data can be applied in experiments, more efficient product and process design, calculation, and control of input parameters avoiding costly trial and error in industrial production. The findings can help technologists optimize process parameters in the hydroforming process of products with protrusion from a tubular blank

Exosomes contain biomarkers such as proteins and lipids that help in understanding normal physiology and diseases. Lipids, in particular, are infrequently studied using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) for biomarker discovery. In this study, MALDI was equipped with a high-resolution MS to investigate the exosomal lipid from human serum.Exosomal lipids were profiled by MALDI with Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Four matrices, i.e., α-cyano-4-hydroxycinnamic acid (CHCA), 2,5-dihydroxybenzoic acid (DHB), sinapinic acid (SA), and graphene oxide (GO), along with three sample preparation methods, i.e., dried droplet, thin-layer, and two-layer, were compared in terms of the number of lipid species detected and the relative abundance of each lipid from human serum and human serum exosomes.In total, 172 and 89 lipid species were identified from human serum and human serum exosomes, respectively, by all of the methods used. The greatest number of exosome lipid species, 69, was detected with the CHCA matrix, while only 8 exosome lipid species were identified with the GO matrix. Among the identified lipid species, phosphatidylcholine was identified most frequently, probably due to the use of a positive ion mode.Exosomes and human serum showed comparable lipid profiles as determined by MALDI-FTICR MS. These findings provide a new perspective on exosomal lipidomics analysis and may serve as a foundation for future lipidomics-based biomarker research using MALDI-FTICR MS.

The development of sensitive and point-of-care diagnostic tools for the serological profile of numerous Mycobacterium tuberculosis (MTB) rectifies the existing flaws in tuberculosis diagnosis. Here...

Due to the widespread emergence of COVID-19, face masks have become a common tool for reducing transmission risk between people, increasing the need for sterilization methods against mask-contaminated microorganisms. In this study, we measured the efficacy of ultraviolet (UV) laser irradiation (266 nm) as a sterilization technique against

One-dimensional hybrid nanostructures composed of a plasmonic gold nanowire core covered by a shell of magnetic oxide nanoparticles (Au@Fesubix/i/subOsubiy/i/subNWs) were synthesized by a one-pot solvothermal synthesis process. The effects of reaction temperature, time, reducing agent, and precursor as well as postsynthesis treatment were optimized to produce highly uniform NWs with a diameter of 226 ± 25 nm and a plasmonic core aspect ratio of 25 to 82. By exploiting the interaction of NWs with an external magnetic field, precise arrangements into highly periodic photonic structures were achieved, which can generate distinctive structural colors that are vividly iridescent and polarization-sensitive. Furthermore, a Bouligand-type chiral nematic film consisting of multistacked unidirectional layers of achiral NWs was fabricated using a modified layer-by-layer deposition method, which displays circular dichroism (CD) and chiral sensing capability. The addition of bovine serum albumin (BSA) as a model protein analyte induced a concentration-dependent wavelength shift of CD peaks. These intriguing properties of magnetoplasmonic anisotropic NWs and their self-assemblies could be consequently valuable for developing nature-inspired structural color imprints as well as solid-state chiral sensing devices.

The sinapinic acid (SA) matrix has frequently been used for protein analysis in matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS). However, the SA matrix does not result in the formation of distinctive multiple protein charge states, whereas the 2-nitrophloroglucinol (2-NPG) matrix is capable of this. The formation of multiple charge states in the MALDI-MS analysis of proteins is advantageous in that it results in higher accuracy. In this study, the mass spectra of several common standard proteins, namely cytochrome c, myoglobin, bovine serum albumin (BSA), and immunoglobulin G (IgG), were compared using various matrices (2,5-dihydroxybenzoic acid, α-cyano-hydroxycinnamic acid, SA, and 2-NPG). Furthermore, the mass spectra of two large standard proteins (BSA and IgG) using various acid additives (H3PO4, HNO3, H2SO4, HCl, and trifluoroacetic acid) with the 2-NPG matrix were also compared. Among the different matrices, 2-NPG provided the broadest range of multiple protein charge states, while, among the different additives, the 2-NPG matrix in combination with HCl generated the broadest multiple charge states as well as the most intense protein peaks.

This paper deals with the prediction of surface roughness in manufacturing polycarbonate (PC) by applying Bayesian optimization for machine learning models. The input variables of ultraprecision turning—namely, feed rate, depth of cut, spindle speed, and vibration of the X-, Y-, and Z-axis—are the main factors affecting surface quality. In this research, six machine learning- (ML-) based models—artificial neural network (ANN), Cat Boost Regression (CAT), Support Vector Machine (SVR), Gradient Boosting Regression (GBR), Decision Tree Regression (DTR), and Extreme Gradient Boosting Regression (XGB)—were applied to predict the surface roughness (Ra). The predictive performance of the baseline models was quantitatively assessed through error metrics: root means square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). The overall results indicate that the XGB and CAT models predict Ra with the greatest accuracy. In improving baseline models such as XGB and CAT, the Bayesian optimization (BO) is next used to determine their best hyperparameters, and the results indicate that XGB is the best model according to the evaluation metrics. Results have shown that the performance of the models has been improved significantly with BO. For example, the values of RMSE and MAE of XGB have decreased from 0.0076 to 0.0047 and from 0.0063 to 0.0027, respectively, for the training dataset. Using the testing dataset, the values of RMSE and MAE of XGB have decreased from 0.4033 to 0.2512 and from 0.2845 to 0.2225, respectively. Moreover, the vibrations of the X, Y, and Z axes and feed rate are the most significant feature in predicting the results, which is in high accordance with the literature. We find that, in a specified value domain, the vibration of the axes has a greater influence on the surface quality than does the cutting condition.

Analysis and management of surface water quality is a need for many economic and production fields, but requires much time and forces. Multivariate statistical algorithms are applied to the dataset, which made up from 19 water quality criteria collected from 10 sampling sites across waterways from Sai Gon river basin. PCA-X (PCA – Principle Component Analysis) model of the dataset provides grouping by geographical location and flow direction, with explanation of the first 2 principal components are 62.4 and 25.2 %, respectively, which overviews the quality of water of these sampling sites, and allows determination of unexpected pollution sources from the system. These results are the basis of developing a method for delimiting and securing local pollution sites, assisting water quality monitoring and environmental management.

We study a special class of non-convex quadratic programs subject to two (possibly indefinite) quadratic constraints when the level sets of the constraint functions are {\it not} arranged {\it alternatively.} It is shown in the paper that this class of problems admit strong duality following a tight SDP relaxation, without assuming primal or dual Slater conditions. Our results cover Ye and Zhang's development in 2003 and the generalized trust region subproblems (GTRS) as special cases. Through the novel geometric view and some simple examples, we can explain why the problem becomes very hard when the level sets of the constraints are indeed arranged alternatively.

Given \begin{document}$ n\times n $\end{document} symmetric matrices \begin{document}$ A $\end{document} and \begin{document}$ B, $\end{document} Dines in 1941 proved that the joint range set \begin{document}$ \{(x^TAx, x^TBx)|\; x\in\mathbb{R}^n\} $\end{document} is always convex. Our paper is concerned with non-homogeneous extension of the Dines theorem for the range set \begin{document}$ \mathbf{R}(f, g) = \{\left(f(x), g(x)\right)|\; x \in \mathbb{R}^n \}, $\end{document} \begin{document}$ f(x) = x^T A x + 2a^T x + a_0 $\end{document} and \begin{document}$ g(x) = x^T B x + 2b^T x + b_0. $\end{document} We show that \begin{document}$ \mathbf{R}(f, g) $\end{document} is convex if, and only if, any pair of level sets, \begin{document}$ \{x\in\mathbb{R}^n|f(x) = \alpha\} $\end{document} and \begin{document}$ \{x\in\mathbb{R}^n|g(x) = \beta\} $\end{document}, do not separate each other. With the novel geometric concept about separation, we provide a polynomial-time procedure to practically check whether a given \begin{document}$ \mathbf{R}(f, g) $\end{document} is convex or not.

In this paper, we study some fundamental geometrical properties related to the $${\mathcal {S}}$$ -procedure. Given a pair of quadratic functions (g, f), it asks when “ $$g(x)=0 \Longrightarrow ~ f(x)\ge 0$$ ” can imply “( $$\exists \lambda \in {\mathbb {R}}$$ ) ( $$\forall x\in {\mathbb {R}}^n$$ ) $$f(x) + \lambda g(x)\ge 0.$$ ” Although the question has been answered by Xia et al. (Math Program 156:513–547, 2016), we propose a neat geometric proof for it (see Theorem 2): the $${\mathcal {S}}$$ -procedure holds when, and only when, the level set $$\{g=0\}$$ cannot separate the sublevel set $$\{f

Disaccharides are sugars composed of two monosaccharides joined by a glycosidic linkage. The specific properties of a disaccharide depend on the type of the glycosidic linkage and the identity of the two component monosaccharides. In this work, seven disaccharide isomers (gentiobiose, isomaltose, melibiose, lactose, maltose, cellobiose, and sucrose) were analyzed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) using a graphene oxide matrix. Each disaccharide was identified by its unique cleavage pattern. To determine the feasibility of quantitative analyses based on specific fragment patterns, mixtures of sucrose with cellobiose or maltose were prepared at different ratios and analyzed by MALDI-MS, where a strong linear correlation was observed between the relative peak intensity of the sucrose fragment peak at m/z 185 and the amount of sucrose in the mixture. The calibration curve was successfully applied to obtain the relative amount of maltose and sucrose in four different honey samples.

Alcoholic liver disease (ALD) and nonalcoholic fatty liver disease (NAFLD) are typically asymptomatic and slow-progressing but potentially fatal diseases that are common causes of liver cirrhosis and related complications. Exosomes are nano-sized extracellular vesicles that have been linked to various intercellular communication processes and can carry biological materials reflecting the state and severity of disease. In this study, shotgun proteomic analysis of the protein expression profiles of extracellular vesicles, including exosomes and microvesicles, enriched from human serum samples of 24 patients diagnosed with various fatty liver diseases was performed using liquid chromatography tandem mass spectrometry (LC-MS/MS) followed by protein identification and label-free quantification using the MaxQuant platform. A total of 329 proteins, including 190 previously reported exosome-specific proteins, were identified from four types of liver disease, where significant differences in protein expression were found in apolipoproteins, immunoglobulins, and other previously reported markers of liver disease. Principal component analysis of 61 proteins identified from MaxQuant analysis of the LC-MS/MS data provided a confident differentiation between ALD and NAFLD. SIGNIFICANCE: The current investigation revealed the difference among various types of liver disease using LC-MS/MS of exosomes enriched from human serum samples of 24 patients where the most significantly up-regulation proteins were alpha-2-macroglobulin for alcoholic hepatitis and apolipoprotein C3 for nonalcoholic fatty liver disease.

Decontamination of organophosphorus chemical warfare nerve agents (CWNAs) is gaining importance for human security. Herein, we have employed a dry-photodecontamination method for CWNA model molecules of dimethyl methylphosphonate, dimethyl phosphite, diethyl methylphosphonate, and diethyl phosphite contaminated on aluminum (Al) and oxidized Al foils. For understanding their photo-degradation pathways, the photo-decomposition secondary chemical products generated as a result of UVC-decontamination were fully examined for the contaminated Al and oxidized Al target areas in a closed reactor system by gas chromatography and mass spectrometry. Solid residues were also fully examined by X-ray photoelectron spectroscopy and Fourier-transform infrared spectroscopy. Density functional theory at the B3LYP/6–31 G level was used for geometric optimization, and the electronic energy state calculation was conducted on the level of TD-SCF/B3LYP/6–31 G. The new results further deepen the photo-decomposition mechanism of CWNAs, the development of dry UV light photo-decontamination methods, and the treatment of secondary by-products.

Exosomes are nanosized vesicles commonly found in biological fluids as a result of a secretion process involving endosomes and multivesicular bodies. The isolation and analysis of exosomes can be useful for noninvasive clinical diagnosis of a variety of human diseases. We investigated the utility of analyzing exosomal proteins, using matrix-assisted laser desorption/ionization combined with Fourier-transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS), as a means of determining the presence of exosomes. MALDI-FTICR-MS analyses of exosomes enriched from human serum via centrifugation in a mass range of

We present a new S-lemma with two quadratic equalities and use it to minimize a special type of polynomials of degree 4. As a result, by the Dinkelbach approach with 2 SDP’s (semidefinite programming), the minimum value and the minimum solution to the Tikhonov regularization of the total least squares problem with \(L=I\) can be nicely obtained.

Ultraviolet (UV) laser irradiation was applied to decontaminate chemical warfare agent simulants chloroethyl phenyl sulfide (CEPS) and malathion, with results obtained from gas chromatography–mass spectrometry analysis. Exposure of CEPS to a 266 nm laser exhibited feasible decontamination by dominantly producing the byproduct diphenyl disulfide. However, decontamination in the cases with 355 and 532 nm exposure on CEPS as well as 266 nm exposure on malathion were relatively inefficient. Results also show a strong correlation between decontamination efficiency and absorption probability, which indicates the importance of selecting proper laser wavelengths and supports the photochemical mechanism of UV laser decontamination.

Issues related to global energy and environment as well as health crisis are currently some of the greatest challenges faced by humanity, which compel us to develop new pollution-free and sustainable energy sources, as well as next-generation biodiagnostic solutions. Optical functional nanostructures that manipulate and confine light on a nanometer scale have recently emerged as leading candidates for a wide range of applications in solar energy conversion and biosensing. In this review, recent research progress in the development of photonic and plasmonic nanostructures for various applications in solar energy conversion, such as photovoltaics, photothermal conversion, and photocatalysis, is highlighted. Furthermore, the combination of photonic and plasmonic nanostructures for developing high-efficiency solar energy conversion systems is explored and discussed. We also discuss recent applications of photonic–plasmonic-based biosensors in the rapid management of infectious diseases at point-of-care as well as terahertz biosensing and imaging for improving global health. Finally, we discuss the current challenges and future prospects associated with the existing solar energy conversion and biosensing systems.