Different Types Of Components Research Articles

Nonparametric Predictive Inference for Discrete Lifetime Data

This paper presents nonparametric predictive inference for discrete lifetime data. While lifetimes are mostly treated as continuous random variables in statistics, there are scenarios where time observations are recorded as discrete values, for example, in actuary, where lifetimes are often recorded as integers in years. The presented method provides lower and upper probabilities for a variety of events of interest involving discrete lifetimes, with examples provided for illustration. Furthermore, the discrete-time situation is considered for inference of the reliability of systems, with discrete-time data for components of different types and using the survival signature to combine inference on components’ reliability to quantify the overall system reliability.

A Probabilistic Approach for Threshold Reliability Structures with Three Different Types of Components

In the present work, we study threshold reliability systems consisting of three different kinds of independent components. Within these structures, the components belonging to the same type, share a common reliability and the same weight. The reliability attributes of the aforementioned systems are investigated in some detail. Explicit expressions for calculating their reliability function, the mean time to failure and the corresponding Birnbaum’s importance measures are established. For illustration purposes, several numerical results are presented, while some concluding remarks about the impact of the design parameters of the underlying structures are delivered. A short discussion for potential future work is also developed.

UV-Curable Polymer Nanocomposites: Material Selection, Formulations, and Recent Advances

This study addresses the development of UV-curable polymer nanocomposites (PNCs), mainly based on acrylate, emphasizing material selection and formulation strategies that achieve efficient dispersion of the nanofillers (NFs). We begin by exploring various types of UV-curing coatings and delve deeper into their key components: monomers, oligomers, photoinitiators, fillers, and additives. Different types of components and examples are presented. Furthermore, this study delves into the critical importance of modifying NFs to tune the physical properties of the composite. It provides an overview of commonly used NFs and underscores the importance of surface modification (chemical and physical) as a pivotal technique for producing high-performance UV-curable PNCs. Additionally, various additives such as adhesion promoters, anti-foaming agents, and wetting and dispersing agents are discussed, emphasizing their functions within the formulation process. Different dispersion and blending methods are also discussed. The paper concludes by summarizing and presenting recent advancements in the formulation of UV-curable PNCs. This overview offers valuable insights to researchers and engineers working on the development of advanced materials.

RGS Proteins in Sympathetic Nervous System Regulation: Focus on Adrenal RGS4.

The sympathetic nervous system (SNS) consists largely of two different types of components: neurons that release the neurotransmitter norepinephrine (NE, noradrenaline) to modulate homeostasis of the innevrvated effector organ or tissue and adrenal chromaffin cells, which synthesize and secrete the hormone epinephrine (Epi, adrenaline) and some NE into the blood circulation to act at distant organs and tissues that are not directly innervated by the SNS. Like almost every physiological process in the human body, G protein-coupled receptors (GPCRs) tightly modulate both NE release from sympathetic neuronal terminals and catecholamine (CA) secretion from the adrenal medulla. Regulator of G protein Signaling (RGS) proteins, acting as guanosine triphosphatase (GTPase)-activating proteins (GAPs) for the Gα subunits of heterotrimeric guanine nucleotide-binding proteins (G proteins), play a central role in silencing G protein signaling from a plethora of GPCRs. Certain RGS proteins and, in particular, RGS4, have been implicated in regulation of SNS activity and of adrenal chromaffin cell CA secretion. More specifically, recent studies have implicated RGS4 in regulation of NE release from cardiac sympathetic neurons by means of terminating free fatty acid receptor (FFAR)-3 calcium signaling and in regulation of NE and Epi secretion from the adrenal medulla by means of terminating cholinergic calcium signaling in adrenal chromaffin cells. Thus, in this review, we provide an overview of the current literature on the involvement of RGS proteins, with a particular focus on RGS4, in these two processes, i.e., NE release from sympathetic nerve terminals & CA secretion from adrenal chromaffin cells. We also highlight the therapeutic potential of RGS4 pharmacological manipulation for diseases characterized by sympathetic dysfunction or SNS hyperactivity, such as heart failure and hypertension.

Climate-driven environmental filtering determines hump-shaped elevational pattern of seed plant beta diversity in the central Himalayas

Understanding how and why assemblage dissimilarity changes along spatial gradient is a great challenge in ecology, because answers to these questions depend on the analytical types, dimensions, and components of beta diversity we concerned. To obtain a comprehensive understanding of assemblage dissimilarity and its implications for biodiversity conservation in the Himalayas, we explored the elevational patterns and determinants of beta diversity and its turnover and nestedness components of pairwise and multiple types and taxonomic and phylogenetic dimensions simultaneously. Patterns of beta diversity and their components of different types and dimensions were calculated based on 96 sampling quadrats along an 1800−5400 m elevational gradient. We examined whether and how these patterns differed from random expectations using null models. Furthermore, we used random forest methods to quantify the role of environmental variables representing climate, topography, and human disturbance in determining these patterns. We found that beta diversity and its turnover component, regardless of its types and dimensions, shown a hump-shaped elevational patterns. Both pairwise and multiple phylogenetic beta diversity were remarkably lower than their taxonomic counterpart. These patterns were significantly less than random expectation and were mostly associated with climate variables. In summary, our results suggested that assemblage dissimilarity of seed plants was mostly originate from the replacement of closely related species determined by climate-driven environmental filtering. Accordingly, conservation efforts should better cover elevations with different climate types to maximalize biodiversity conservation, rather than only focus on elevations with highest species richness. Our study demonstrated that comparisons of beta diversity of different types, dimensions, and components could be conductive to consensus on the origin and mechanism of assemblage dissimilarity.

Automatically optimized component model computation for power system simulation on GPU

This work provides an approach that automatically optimizes the component computations on graphics processing unit (GPU) devices from different vendors. The approach consists of a two-level optimization, where the first level considers the linear part of the computation for vectorization and applies mixed matrix formats to increase computational throughput further. Then, the second optimization level treats the combination of linear and non-linear parts as a black box and searches for the optimal configuration of parameters such as the degree of vectorization, the combination of matrix formats, and the group (of threads) sizes during parallel execution on GPU. Moreover, we also introduce constraints that reduce the optimization procedure’s execution time. Finally, we select three different types of components that could be representative to computational tasks in power system and perform our optimization approach on these kernels. The computational performance is compared with unoptimized baseline and sparse linear algebra library based implementations, result shows that our optimization leads to better performance and more efficient memory utilization.

The presence of microplastics in personal care and cosmetic products (PCCPs) commonly used in Ho Chi Minh City

Microplastics pollution poses a global environmental challenge due to its well-documented effects on marine ecosystems and the food chain for humans. Personal care and cosmetic products (PCCPs), have the potential to be a source of microplastics, which directly contribute to aquatic microplastics pollution. This study investigated the presence of microplastics in widely used PCCPs in Ho Chi Minh City. The microplastics concentration in 21 samples of toothpaste, exfoliating products, facial cleansers, shower gels, and hand sanitizers were examined. The PCCPs samples were dissolved in boiling water and then filtered to separate microplastics. The chemical composition of polymers of extracted microplastics was determined using a Fourier-transform infrared spectroscopy (FTIR) with ATR. We found that 14 PCCPs samples contained microplastics as an ingredient. Granular form microplastics were predominant in PCCPs. The largest size of microplastics was found in an exfoliating product (40-2,085μm), while the smallest size was observed in toothpaste (10-380μm). Acrylates copolymers were a common ingredient in the 14 PCCPs samples. Carbomer, polyethylene, and polyethylene glycol were only found in toothpaste samples. The research aims to regulate the components in different types of PCCPs in Vietnam to minimize microplastics discharge into the environment.

Reliability Testing of Recycled SMD Components Reused in E-Textiles after Ageing by Washing Cycles

This paper presents a method for recycling and reusing SMD chip components in e-textiles using a special contacting technique. The method involves using a UV-curable, non-conductive acrylic adhesive to connect SMD components onto electrically conductive textile stretchable ribbons. At the end of the product’s life-cycle, the components are removed from the ribbon and reused to manufacture new products. The recycling procedure involves several steps, including disassembly, inspection, cleaning, repair, and reassembly of components. The results of an experiment testing the electrical resistance of new and reused components after washing and drying cycles showed that electrical resistance of reused joints did not significantly deteriorate compared to new joints. The reused components maintain their functionality and performance, suffering no significant impairment. They perform comparably to new components, even after repeated washing and drying cycles. The method offers several benefits, including conservation of raw materials, minimization of waste, and reduction of production costs. It can also help mitigate component shortages. However, it is found that the suitability of this remanufacturing method varies with different types of components. Certain component types may be more susceptible to damage or even unsuitable for this method. The method is particularly beneficial for higher-value or components experiencing market shortages, demonstrating its potential to address urgent industry challenges while contributing to environmental sustainability.

Reliability Prediction of Radiation Induced Failures in Semiconductor Packages

The growth and usage of semiconductor components has risen greatly due to evolution of applications in industries such as aerospace, defense, and automotive, in both the commercial and government sectors. Among the different types of components that make their way into such applications, digital logic and memory-based devices are of prime importance due to the ever-demanding need to store and compute vast amounts of data. This brings to the forefront the reliability of such components, especially in demanding applications in aerospace and defense where components are exposed to extremely harsh environments where high performance is critical. This is where we find that reliability is largely dependent on the susceptibility of semiconductor components to radiation induced effects - total ionizing dose (TID) and single event effects (SEE). Optimization in design, process, and packaging could make microelectronics more reliable to the radiation effects. Packaging material and thickness affect the incident flux of radiation on microelectronics and can help mitigate both dose and SEE effects in electronics. Additionally, packaging materials should not generate a high flux of secondary particles when exposed to environmental radiation (an example is alpha emissions from impurities in package mold compound or underfill). In this paper, the behavior of semiconductors at the component level due to radiation effects is evaluated. A reduced order model approach is presented where the analysis is performed at the functional block level then aggregated into component. The behavioral model can be used to predict the behavior across different operating, design, and process conditions.

Effects of trigonelline, diosgenin, and Cistanche deserticola polysaccharide on the culture of female germline stem cells in vitro

Female germline stem cells (FGSCs) are renewable sources of oocytes that play an indispensable role in re-establishing mammal fertility. Here, we have established FGSCs from neonatal mice, which exhibit characteristics of germline stem cells. We show that compared with monomeric trigonelline and diosgenin, macromolecular compounds Cistanche deserticola polysaccharides (CDPs) in Chinese herbal medicine can enhance the ability of FGSCs to differentiate into oocytes at appropriate concentrations while maintaining self-renewal in vitro. In contrast, trigonelline and diosgenin inhibited the expression of germ cell-specific genes while reducing cell proliferation activity. In summary, CDPs could induce the differentiation and self-renewal of FGSCs in vitro. The comparison of the effects of the active components of different types of Chinese medicine will provide a reference for the development of clinical drugs in the future, and help to elucidate the development process of FGSCs.

Integrated network pharmacology, metabolomics, transcriptomics and microbiome strategies to reveal the mechanism of Sang Ju Yin on the treatment of acute lung injury on the gut-microbiota-lung axis

Acute lung injury (ALI) is a clinically prevalent inflammatory disorder that still needs to be developed with more accurate diagnostic biomarkers and more satisfactory therapies. This study intended to explore the therapeutic material basis and molecular mechanisms of a classical traditional Chinese medicinal prescription, Sang Ju Yin (SJY), against ALI, focusing on the chemical components of formula composition, the disturbance of host genes/metabolites and the dysbiosis of intestinal flora. First, based on liquid chromatography-mass spectrometry (LC-MS) component analysis, 212 in vitro and 44 in vivo compounds were identified respectively in SJY. Then, network pharmacology was adopted to calculate potential anti-ALI compounds in SJY and predict that CXCR2, PI3K-Akt signaling and arachidonic acid (AA) metabolism could be potential targets. Subsequently, integrative multi-omics techniques were employed to elaborate deeper systematic molecular mechanisms. Metabolomic data combining both 1H NMR and LC-MS techniques illustrated that 146 pulmonary and 75 fecal biomarkers, associated with AA and other metabolisms, were recuperated by SJY’s intervention. Transcriptomic analyses suggested that SJY could significantly regulate genes and signaling pathways involved with inflammation and apoptosis, such as PI3K-Akt. Further the obtained key targets (IL-10, LCAT, CXCR2 and C5) were verified by qRT-PCR and their relative compound-target interaction were validated by molecular docking. Notably, the disturbance of intestinal microbial community (such as the abundance of Lactobacillus, etc.) was detected through 16S rRNA gene sequencing, that could be effectively reshaped by SJY. Collectively, our integrated work showed SJY could regulate the crosstalk of metabolite-target-pathway-microflora along the gut-microbiota-lung axis on the whole. Noteworthy, our study provided fundamental and new insights into how molecular networks connected different types of components, genes, metabolites, microbes and potential pathways to map an endogenous functional landscape for clinical ALI diagnosis and SJY application.

FAILURE MODEL OF NON-RESTORABLE COMPLEX TECHNICAL OBJECT OF MILITARY EQUIPMENT

Maintenance (MT) is a necessary component the process of operating a complex technical object of military equipment, intended for long-term operation in wartime and harsh operating conditions. The volume, content and timing of maintenance must be completely determined by the reliability properties of the object, conditions and modes of its use. Effective implementation of any maintenance operation is possible only if the design of the object provides special means for this purpose (for measuring the defining parameters) and ensures the accessibility and convenience of performing the operation. Complex technical objects in modern society are extremely important. Such objects belong to the class of restored objects long-term repeated use. They are usually expensive and require significant operating costs. To ensure the required level of failure-free operation during their operation, maintenance is usually carried out, the essence of which is the timely preventive replacement of elements that are in a pre-failure state, which is very important for military equipment. A characteristic feature of complex technical objects for special purposes (military equipment) is the presence in their composition of a large number (tens, hundreds of thousands) different types of components that have different levels of reliability, different patterns of their wear and aging processes. This feature requires a more subtle approach to organizing and planning maintenance during operation (of military equipment). The above statements fully justify the conclusion about need to determine the main characteristics of the maintenance system in early stages of its design, when it is still possible to make changes to design of the object. In this work, a model of failure-free operation non-repairable complex technical object of military equipment is developed. The work also confirms the general idea that data obtained fully confirm the assumption that a maintenance strategy that is not restored is more preferable in the case of unreliable (inaccurate) information about the reliability indicators of elements of a military equipment object.

Reliability-Related Interpretations of Algebraic Inequalities

New results related to maximizing the reliability of common systems with interchangeable redundancies at a component level have been obtained by using the method of algebraic inequalities. It is shown that for systems with independently working components with interchangeable redundancies, the system reliability corresponding to a symmetric arrangement of the redundant components is always inferior to the system reliability corresponding to an asymmetric arrangement of the redundant components, irrespective of the probabilities of failure of the different types of components. It is also shown that for series–parallel systems, the system reliability is maximized by arranging the main components in ascending order of their probabilities of failure, whereas the redundant components are arranged in descending order of their probabilities of failure. Finally, this article derives rigorously the highly counterintuitive result that if two components must be selected from <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> batches containing reliable and faulty components with unknown proportions, the likelihood that both components will be reliable is maximized by selecting both components from a randomly selected batch.

A Comprehensive Model for Efficient Design Space Exploration of Imprecise Computational Blocks

After almost a decade of research, development of more efficient imprecise computational blocks is still a major concern in imprecise computing domain. There are many instances of the introduced imprecise components of different types, while their main difference is that they propose different precision-cost-performance trade-offs. In this paper, a novel comprehensive model for the imprecise components is introduced, which can be exploited to cover a wide range of precision-cost-performance trade-offs, for different types of imprecise components. The model helps to find the suitable imprecise component based on any desired error criterion. Therefore, the most significant advantage of the proposed model is that it can be simply exploited for design space exploration of different imprecise components to extract the suitable components, with the desired precision-cost-performance trade-off for any specific application. To demonstrate the efficiency of the proposed model, two novel families of Lowest-cost Imprecise Adders (LIAs) and Lowest-cost Imprecise Multipliers (LIMs) are introduced in the paper, which are systematically extracted based on exploration of the design space provided by the proposed model. A wide range of simulation and synthesis results are also presented in the paper to prove the comparable efficiency of the systematically extracted LIA/LIM structures with respect to the most efficient existing human-made imprecise components both individually and in a Multiply-Accumulate application.

Comparisons of coherent systems with two types of heterogeneous components having proportional reversed hazard rates

AbstractThe comparison of coherent systems in terms of stochastic orders is vital in reliability theory. While there is a considerable amount of literature devoted to comparing systems with homogeneous and independent components, real‐world systems often consist of heterogeneous components. Hence, this article aims to investigate systems with heterogeneous and independent components, as well as, those with heterogeneous and dependent components. For this purpose, we consider systems comprise of three components, which are of two different types of components, namely two components of type A and one component of type B. The system's lifetime distribution is represented using the failure signature when the components are independent, which is a function of the component's life distribution. However, when the components are dependent, the system's lifetime distribution is represented using copula and diagonal sections. Additionally, distorted distributions are utilized to enable distribution‐free stochastic comparisons. Using these representations, we compare systems with components having proportional reversed hazard rates, in three scenarios: (i) when components are heterogeneous and independent; (ii) when components are heterogeneous and dependent; and finally, (iii) comparing systems with homogeneous and independent components with those that have heterogeneous components. To illustrate the applicability of these results, we provide some examples and applications.

Research Status and Development Trend of Piezoelectric Accelerometer

Piezoelectric accelerometers have been widely used because of their large range, simple structure, stable performance, and other advantages. With the improvement of science and technology, the application field is expanding, but there are still some problems in high-temperature environments and low-frequency vibration conditions. Under high-temperature environments, the piezoelectric material will undergo depolarization or resistance change, resulting in sensor failure. Aerospace instruments, water conservancy platforms, and other fields require high-precision instruments with vibration amplitudes of the order of a few microns in the range of 0.01–1 Hz, which require low-frequency and ultra-low-frequency sensors for the measurements. Therefore, how to increase the operating temperature and reduce the noise of piezoelectric accelerometers has become a problem that needs to be solved. This paper reviews the structure, principle, application range, and material selection of piezoelectric components of different types of piezoelectric accelerometers and summarizes the current problems and future research priorities.

Remaining useful life prediction of weighted k-out-of-n systems based on dynamic random weights of importance

With the increasing complexity of various industrial systems, the reliability assessment and remaining useful life prediction of weighted k-out-of-n systems considering stochastic correlation have become a concern in the field of reliability. The components’ varying locations and operating environments result in fluctuating reliability and different impacts on normal system operation. In this study, the Birnbaum importance of components is modeled for a weighted k-out-of-n continuous degradation system consisting of different types of components with stochastic correlation. Furthermore, a reliability model and a remaining useful life prediction model based on kernel diffeomorphism estimation with dynamic random weights of Birnbaum importance are developed for weighted k-out-of-n systems. First, the component state reliability model is established by a nonparametric method of adaptive kernel diffeomorphism estimation. Second, the multivariate copula function is used to characterize the stochastic correlation of different types of component degradation. In addition, the Birnbaum importance model with stochastic correlation of components was developed using Akaike Information Criterion for copula function preference. A remaining useful life prediction model for the weighted k-out-of-n continuous degradation system is established considering the dynamic random weights of Birnbaum importance measures. Finally, the validity and accuracy of the proposed weighted k-out-of-n system remaining useful life model are verified using a cluster of plant protection unmanned aerial vehicles.

Applications of Linear Scanning Magnetostrictive Transducers (MST) for Finding Hard-to-Detect Anomalies in Structural Components

Guided wave testing is now a widely accepted method for detection of structural damage in many different types of components, from pipelines to pressure vessels to tanks. Torsional wave modes (T modes) in pipes and shear horizontal (SH) mode guided waves in plates are good candidates for finding areas with generalized corrosion, due to the absence of fluid coupling effects and their lack of dispersion. However, from our field test experience, certain types of defects are difficult to detect with conventional T mode or SH mode guided wave probes. Gradual wall thinning is one such type of defect; another is crack-like defects in or close to welds or penetrations in the pipe. Recently, Southwest Research Institute (SwRI) has developed a new sensor configuration and scanning system that overcomes these limitations. We have recently developed a linear scanning magnetostrictive transducer (MsT) probe system, in which a FeCo strip wound with radio frequency (RF) coils is attached to the structure under test with shear wave couplant, and a moving permanent magnet driven by a motor is used to excite SH guided waves at predefined positions along this strip. The probe is designed to operate over a wide frequency range (20 – 500 kHz) and can be used to generate dispersive shear wave mode (SH1) in addition to the nondispersive SH0 mode. The use of different modes with the sensor at multiple positions allows detection of a range of defect types. In this paper, the performance of linear scanning MsTs is presented, including experimental evaluation of detection of gradual wall thinning patches of different depths and locations on a steel pipe and plate mockups. Another set of experiments evaluates detection of notches in seam welds. Indications from real-time B-scan and SAFT (synthetic aperture focusing technique) processing will be presented.

Modeling and Implementation of a Joint Airborne Ground Penetrating Radar and Magnetometer System for Landmine Detection

We modeled and implemented a joint airborne system integrating ground penetrating radar (GPR) and magnetometer (MAG) models specifically for landmine detection applications. We conducted both simulations and experimental analyses of the joint airborne GPR and MAG models, with a focus on detecting the metallic components of different types of landmines, including antitank (AT) M15 metallic, antipersonnel (AP) M16 metallic, and AT M19 plastic (minimum-metal) landmines. The GPR model employed the finite-difference time-domain (FDTD) method and was evaluated using a singular value decomposition (SVD) and Kirchhoff migration (KM) with matched filtering (MF). These advanced techniques enabled the automatic identification and precise focusing of the reflected hyperbolic signals emitted by the landmines while considering cross-range resolution. Additionally, the MAGs were utilized based on the magnetic dipole model with a de-trend and a spatial median filtering method to estimate the magnetic anomaly of the landmines while considering various data spatial intervals. The joint airborne GPR and MAG system was implemented by combining and integrating the GPR and MAG models for experimental validation. Through this comprehensive approach, which included experiments, simulations, and data processing, the design parameters of the final system were obtained. These design parameters can be used in the development and application of landmine detection systems based on airborne GPR and MAG technology.

On reliability assessment of weighted k-out-of-n systems with multiple types of components

ABSTRACT This paper studies the reliability function of a weighted k -out-of- n system with multiple types of components. A weighted system with M different types of components is considered and two real-life scenarios for the operation of the system are defined. In the first one, it is assumed that the system operates if the accumulated weight of all active components is more than a predetermined threshold k , otherwise the system fails. In the second scenario, the system is assumed to operate if the total weight of the operating components of type i is more than or equal to the corresponding threshold k i , for at least m types of components, m ≤ M . Our approaches in assessing the reliability function of the system lifetime rely on the notion of survival signature corresponding to multi-type weighted k -out-of- n system. The formulas for the proposed survival signature are presented and the corresponding computational algorithms are also given. To examine the theoretical results, the reliability function and other aging characteristics of a wind farm (system) consisting of three plants located in three different regions are assessed numerically and graphically. Finally, an allocation problem to determine the best choice for the distribution of each type in the weighted k -out-of- n systems is studied.