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The purpose of this paper is to clarify the method of using RF impedance changes as an early indicator of degradation of solder joint. It proposes the mode of crack propagation in solder joint and outlines why RF impedance analysis can be capable of detecting small cracks. The study aims to show the potential of RF impedance analysis as a prognostic tool that can provide advanced warning of impending failures of solder joint.

In this paper, the mode of crack propagation in solder joint was studied to show why RF impedance analysis could be capable of detecting small cracks. A real simple impedance‐controlled test vehicle was developed to allow RF impedance and DC resistance measurements to monitor solder joint degradation. The influence of crack length on RF impedance was evaluated by high frequency structure simulator (HFSS) simulation for the first time.

The paper demonstrates that RF resistance can respond to an open state of a solder joint as well as DC resistance. Furthermore, RF impedance can monitor partial degradation of solder joints, while the DC resistance cannot do it. In addition, time‐domain reflection coefficient is found to be more useful than RF impedance in detecting solder joint degradation. The HFSS simulation results show that even very slight physical degradation of solder joints can be detected using RF impedance analysis.

In this paper, HFSS simulation is used for the first time to evaluate the influence of crack length on RF impedance.

This chapter provides an in-depth analysis of the cleanup and closing of the nuclear weapons facility at Rocky Flats (RF), Colorado, United States, which was completed 60 years ahead of schedule and $30 billion under budget. We demonstrate how the events leading to the successful completion of the project was an instance of generativity made possible by the Appreciative Intelligence of the project leaders and participants. At the end of the Cold War, production at RF was terminated and experts considered cleaning up of the dangerous facility technically impossible, risky, and impractical. Yet, working in collaboration with contractors, local officials, and community leaders, the RF team achieved extraordinary results. After the unprecedented cleanup, 4,000 acres were transferred to the U.S. Fish and Wildlife Service and became a national wildlife refuge. Generativity is an approach to life that directs our actions toward positive outcomes. For generativity to happen, stakeholders in the RF project had to care about the environment around them for innovative solutions to emerge. Instead of stagnation or blind acceptance of circumstances, they chose to reframe and find new ways to perceive situations facing them. This case study shows that individuals with high Appreciative Intelligent acknowledge present circumstances, choose to reframe, see possibilities for the future, and take the necessary actions to achieve them. They also expand their Appreciative Intelligence beyond their personal lives. At RF, despite the imminent closing of the plant, stakeholders generated socially responsible solutions and transformed a public liability into a community asset.

This study aims to explore the essential factors of the reason for (RF) and reason against (RA) and their impact on tourist attitudes and intentions to use e-bike sharing services by using a novel approach based on behavioral reasoning theory (BRT).

A quantitative method was used to collect data from 292 tourists and analyze the data using the partial least squares structural equation modeling (PLS-SEM) technique.

The outcomes indicate that both “RF” and “RA” are crucial in affecting tourist attitudes and intentions to use e-bike-sharing services. In addition, factors such as convenience, price saving and time saving were identified as “RF” while “RA” weather conditions, safety concerns and image barriers were identified that affect tourist attitudes and intention to use e-bike sharing services. These findings also indicate that tourists’ values of openness to change significantly influence “RF” and have no impact on “RA” and attitude toward e-bike-sharing services.

This study provides valuable insights that complement the existing literature on electric bike sharing and BRT in the context of promoting sustainable and eco-friendly consumption.

This research takes a significant step forward in investigating the tourist attitudes and intentions toward using e-bike sharing services in a tourist destination growing economy by using the BRT theory and proposing a model that considers both the “RF” and “RA” using e-bikes for urban transportation.

本研究旨在利用基于 BRT 的新方法, 探讨使用电动自行车共享服务的支持原因（RF）和反对原因（RA）的基本因素及其对游客使用电动自行车共享服务的态度和意图的影响。

采用定量方法收集 292 名游客的数据, 并使用 PLS-SEM 技术分析数据。

结果表明“RF”和“RA”对于影响游客使用电动自行车共享服务的态度和意图至关重要。此外, 方便、节省价格和节省时间等因素被确定为“RF”, 而“RA”则被确定为影响游客态度和使用电动自行车共享服务意愿的天气条件、安全问题和形象障碍。这些发现还表明, 游客对变革的开放价值观显着影响“RF”, 但对“RA”和对电动自行车共享服务的态度没有影响。

这项研究提供了宝贵的见解, 在促进可持续和环保消费的背景下补充了有关电动自行车共享和 BRT 的现有文献。

本研究利用 BRT 理论, 在调查经济增长的旅游目的地中游客对使用电动自行车共享服务的态度和意图方面迈出了重要一步, 并提出了一个同时考虑“RF”和“RA”的模型用于城市交通的电动自行车。”

Este estudio pretende explorar los factores esenciales de las razones a favor (RF) y en contra (RA) y su impacto en las actitudes e intenciones de los turistas de utilizar los servicios de bicicletas eléctricas compartidas (e-bike sharing) utilizando un enfoque novedoso basado en la BRT.

Se utilizó un método cuantitativo para recopilar datos de 292 turistas y analizarlos mediante la técnica PLS-SEM.

Los resultados indican que tanto la “RF” como la “RA” son cruciales para afectar a las actitudes e intenciones de los turistas de utilizar los servicios de e-bike-sharing. Además, se identificaron como “RF” factores como la comodidad, el ahorro de precio y el ahorro de tiempo, mientras que como “RA” se identificaron las condiciones meteorológicas, las preocupaciones por la seguridad y las barreras de imagen que afectan a las actitudes de los turistas y a su intención de utilizar los servicios de e-bike sharing. Estos resultados también indican que los valores de apertura al cambio de los turistas influyen significativamente en “RF” y no tienen ningún impacto en “RA” ni en la actitud hacia los servicios de e-bike sharing.

Este estudio aporta valiosas ideas que complementan la bibliografía existente sobre el uso compartido de bicicletas eléctricas (e-bike sharing) y el BRT en el contexto de la promoción de un consumo sostenible y respetuoso con el medio ambiente.”

Esta investigación da un importante paso adelante en la investigación de las actitudes e intenciones de los turistas hacia la utilización de los servicios de e-bike sharing en un destino turístico de economía en crecimiento utilizando la teoría del BRT y proponiendo un modelo que tiene en cuenta tanto la “RF” como la “RA” que utilizan las e-bikes para el transporte urbano.”

To improve the frequency of adoption of mobile health services (MHSs) by users (consumers), it is critical to understand users' MHS adoption behaviors. However, the literature primarily focuses on MHS adoption-related factors and lacks consideration of the joint impacts of reasons for (RF) and reasons against (RA) on users' attitudes and adoption behaviors regarding MHSs. To fill this gap, this study integrates behavioral reasoning theory (BRT) and protective motivation theory (PMT) to develop a research model by uncovering the reasoning process of personal values, RF and RA, adoption attitudes and behavior toward MHSs. In particular, health consciousness (HC) is selected as the value. Comparative advantage, compatibility and perceived threat severity are considered the RF subconstructs; value barriers, risk barriers and tradition and norm barriers are deemed the RA subconstructs.

A total of 281 responses were collected to examine the model with the partial least squares structural equation modeling (PLS-SEM) method.

The results show that HC positively affects attitude through RA and RF. Additionally, RF partially mediates the relationship between HC and adoption behavior. This study contributes to a deeper understanding of user adoption behavior in MHS and provides practical guidance for the health services industry.

This study contributes to the existing MHS literature by understanding the joint influences of personal values, RF and RA on user attitude, which eventually determines users' adoption decisions regarding MHSs.

RF transceiver module is considered a vital part of any wireless communication system. This module consists of two important parts the RF transceiver and analog-to-digital converter (ADC). Usually, both these parts – RF transceiver and ADC – are used to enhance the perspective of size and power. The data processing in 4G communication makes hurdles and need research attention to make it faster and smaller in size. Accuracy and fast processing are the critical challenges in the modern communication system.

After theoretical and practical investigations, this research work proposes key new techniques for the RF transceiver module. These techniques will make RF transceiver small, power-efficient and on the other hand, make dual SAR-ADC more effective as well. The proposed design has no intermediate frequency where the RF transceiver is reduced its major blocks from five to four, which includes crystal oscillator, phase lock loop, power amplifier and low noise amplifier. Moreover, the shared circuitry is introduced in the architecture of the SAR-ADC for the production of dual outputs, specifically in bootstrapped switch and comparator.

The miniaturized RF transceiver and SAR-ADC are well tested separately before the plantation on the printed circuit board (PCB). The operating voltage and frequency of the RF transceiver module are 1.2 V and 5.8 GHz, where the sampling rate, bandwidth and output power are 25 MHz, 200 MHz and 5 dBm, respectively. The core area of the PCB is 58.13 mm². The bandwidth efficiency is 93% using surface acoustic wave less transmitter. The circuit is based on the library of 90 nm CMOS technology.

The entire circuit is highly synchronized with the input and reference clocks to avoid self-interference.

This study examines the motives and enabling factors regarding reverse factoring (RF) adoption in the automobile industry's supply chain.

This is a qualitative case study based on in-depth interviews with financial institutions in two countries having different statuses within the automobile industry global value chain: Mexico as a peripheral and Spain as a semi-peripheral country.

The RF is more widely deployed in Spain than in Mexico. The differences in the adoption of RF between the two countries stem from the availability of programs for suppliers at different supply levels, their efficient implementation and a robust regulatory framework, but especially from the cooperative approach adopted. The motives and enablers of RF adoption in the automobile industry can be explained under a framework of different supply chain management models. The RF programs driven by self-interest financial motives are characterized by an asymmetric distribution of benefits among supply chain participants. The RF programs that combine self-interest with cooperative motives are partially characterized by balanced benefits. In addition, they favor involvement practices and strengthen long-term relationships among supply chain participants. In this cooperative approach, trust, transparency and especially sharing information are considered relevant enablers. Finally, the specific automobile industry's features that determine RF adoption are linked to the structure and governance mode of the supply chain. The structure in terms of length – multiple supply levels – conditions the design of RF programs based on the buyer's position in the supply chain. The governance mode, particularly how the relationships are established, conditions the factors and requisites for efficient adoption of the RF programs.

This research analyzes the RF framed in the dynamics of buyer–supplier relationships and different models of supply chain management, allowing us to identify cooperation motives and their impact on RF adoption, beyond the traditional economic and financial motives highlighted by previous literature.

Generally, iterative methods which have some instability solutions in complex structural and non-linear mechanical problems are used to compute reliability index. The purpose of this paper is to establish a non-linear conjugate gradient (NCG) optimization algorithm to overcome instability solution of the Hasofer-Lind and Rackwitz-Fiessler (HL-RF) method in first-order reliability analysis. The NCG algorithms such as the Conjugate-Descent (CD) and the Liu-Storey (LS) are used for determining the safety index. An algorithm is found based on the new line search in the reliability analysis.

In the proposed line search for calculating the safety index, search direction is computed by using the conjugate gradient approach and the HL-RF method based on the new and pervious gradient vector of the reliability function. A simple step size is presented for the line search in the proposed algorithm, which is formulated by the Wolfe conditions based on the new and previous safety index results in the reliability analysis.

From the current work, it is concluded that the proposed NCG algorithm has more efficient, robust and appropriate convergence in comparison with the HL-RF method. The proposed methods can eliminate numerical instabilities of the HL-RF iterative algorithm in highly non-linear performance function and complicated structural limit state function. The NGC optimization is applicable to reliability analysis and it is correctly converged on the reliability index. In the NCG method, the CD algorithm is slightly more efficient than the LS algorithm.

This paper usefully shows how the HL-RF algorithm and the NCG scheme are formulated in first-order reliability analysis. The proposed algorithm is validated from six numerical and structural examples taken from the literature. The HL-RF method is not converged on several non-linear mathematic and complex structural examples, while the two proposed conjugate gradient methods are appropriately converged for all examples. The CD algorithm is converged about twice faster than the LS algorithm in most of the problems. Therefore, application of the NCG method is possible in reliability analysis.

The purpose of this paper is to present a new class of printed circuit board (PCB)‐based, radio frequency micro‐electro‐mechanical systems (RF‐MEMS) switches and to describe the packaging method and evaluate performance.

Traditional PCB materials and processes were combined with photolithographic high‐density interconnect (HDI) and MEMS to form 3D high‐performance RF switches.

A new type of MEMS RF switch has been developed on a PCB platform. Using processes analogous to those used for silicon MEMS, PCB, and HDI technologies were utilized to fabricate these 3D structures. The PCB‐based microstructures are “mil‐scale” rather than the “micro‐scale” of silicon MEMs. A co‐fabrication packaging method for the MEMS RF switch was also developed. The PCB‐based MEMS switches have demonstrated excellent RF performance and “hot‐switching” RF power‐handling capability. PCB‐based MEMS RF switches have the advantages of low cost and amenability to scale‐up for a high degree of integration.

Further development on photo imageable dielectric materials will enable this technology to improve yield and processability.

The paper describes the development of PCB‐based MEMS RF switches. These elements will enable new applications and enhance the functionality of PCBs. They are also more amenable to system integration compared with silicon MEMS.

The purpose of this paper is to empirically investigate the joint effects of lead time, information sharing and the accounts receivable period on reverse factoring (RF) adoption from the suppliers’ perspective.

Supported by one of the largest commercial banks in China, survey data are collected from 424 Chinese manufacturing firms and analyzed using regression methods.

The results suggest that lead time positively affects suppliers’ RF adoption directly and indirectly through the accounts receivable period. Meanwhile, information sharing has a positive, direct and a negative, indirect influence on suppliers’ RF adoption.

The findings give suppliers and financial institutions a better understanding of how to leverage the benefits of RF.

For repairable systems (RSs), reliability estimation is generally performed using virtual age models. Virtual age models consider the effect of maintenance actions by reducing system age using restoration factor (RF). RF is generally estimated from system failure data using various statistical methods. However, RSs such as railway systems experience various types of maintenance actions at different times during their life cycle. To consider all these different types of actions, we need multiple RFs in the virtual age model. As failure data are limited, the estimation of so many parameters becomes a complex problem and it can lead to erroneous inferences. These RFs are representative of effects of maintenance activities on the system. Therefore, these can be predicted from the information about the maintenance actions performed on the system. The paper aims to discuss these issues.

The paper considers different types of maintenance actions to predict RF of the system. These maintenance actions involve the replacement of components at some level of assembly. Each component in an assembly has its own impact on assembly restoration. RF for assembly/systems can be obtained by aggregating effects of multiple component replacement using analytical hierarchy process . The RF values obtained for different types of maintenance actions are then used to calculate the virtual age of the system at different failure points. Using these virtual age failure points, suitable distribution is fitted and parameters are estimated. The distribution and parameters provide information about reliability of the system at any point of time.

This paper provides an easier approach that gives different RFs for different types of PM and CM. To calculate RFs, it considers the impact of maintenance actions performed as well as the impact of the component on which they are performed. It is simpler and gives more consistent results than other approaches, which estimate RF using different statistical methods.

This paper provides an alternative approach to predict RF parameters instead of estimating these parameters using statistical methods. Estimation of parameters using different statistical methods is complex in nature and gives erroneous and inconsistent results. The approach given in this paper is simpler and gives more reliable results. This approach can be useful in estimating parameters for RSs when failure data are limited.