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The Kirkendall void had been a well-known issue for long-term reliability of semiconductor interconnects; while even the KVs exist at the interfaces of Cu and Sn, it may still be able to pass the condition of unbias long-term reliability testing, especially for 2,000 cycles of temperature cycling test and 2,000 h of high temperature storage. A large number of KVs were observed after 200 cycles of temperature cycling test at the intermetallic Cu₃Sn layer which locate between the intermetallic Cu₆Sn₅ and Cu layers. These kinds of voids will grow proportional with the aging time at the initial stage. This paper aims to compare various IMC thickness as a function of stress test, the Cu₃Sn and Cu₆Sn₅ do affected seriously by heat, but Ni₃Sn₄ is not affected by heat or moisture.

The package is the design in the flip chip-chip scale package with bumping process and assembly. The package was put in reliability stress test that followed AEC-Q100 automotive criteria and recorded the IMC growing morphology.

The Cu₆Sn₅ intermetallic compound is the most sensitive to continuous heat which grows from 3 to 10 µm at high temperature storage 2,000 h testing, and the second is Cu₃Sn IMC. Cu₆Sn₅ IMC will convert to Cu₃Sn IMC at initial stage, and then Kirkendall void will be found at the interface of Cu and Cu₃Sn IMC, which has quality concerning issue if the void’s density grows up. The first phase to form and grow into observable thickness for Ni and lead-free interface is Ni₃Sn₄ IMC, and the thickness has little relationship to the environmental stress, as no IMC thickness variation between TCT, uHAST and HTSL stress test. The more the Sn exists, the thicker Ni₃Sn₄ IMC will be derived from this experimental finding compare the Cu/Ni/SnAg cell and Ni/SnAg cell.

The research found that FCCSP can pass automotive criteria that follow AEC-Q100, which give the confidence for upgrading the package type with higher efficiency and complexities of the pin design.

This result will impact to the future automotive package, how to choose the best package methodology and what is the way to do the package. The authors can understand the tolerance for the kind of flip chip package, and the bump structure is then applied for high-end technology.

The overall three kinds of bump structures, Cu/Ni/SnAg, Cu/SnAg and Ni/SnAg, were taken into consideration, and the IMC growing morphology had been recorded. Also, the IMC had changed during the environmental stress, and KV formation was reserved.

The purpose of this paper is to present the result of calculations that were performed to estimate the structural weight of the passenger aircraft using novel technological solution. Mass penalty resulting from the installation of the fuselage boundary layer ingestion device was needed in the CENTRELINE project to be able to estimate the real benefits of the applied technology.

This paper focusses on the finite element analysis (FEA) of the fuselage and wing primary load-carrying structures. Masses obtained in these analyses were used as an input for the total structural mass calculation based on semi-empirical equations.

Combining FEA with semi-empirical equations makes it possible to estimate the mass of structures at an early technology readiness level and gives the possibility of obtaining more accurate results than those obtained using only empirical formulas. The applied methodology allows estimating the mass in case of using unusual structural solutions, which are not covered by formulas available in the literature.

Accurate structural mass estimation is possible at an earlier design stage of the project based on the presented methodology, which allows for easier and less costly changes in designed aircrafts.

The presented methodology is an original method of mass estimation based on a two-track approach. The analytical formulas available in the literature have worked well for aeroplanes of conventional design, but thanks to the connection with FEA presented in this paper, it is possible to estimate the structure mass of aeroplanes using unconventional technological solutions.

This study aims to show a case study of ecosystem-based adaptation (EbA) measures to increase coastal system’s resilience to extreme weather events and sea-level rise (SLR) implemented at Kiyú (Uruguayan coast of the Rio de la Plata river estuary).

A participatory process involving the community and institutional stakeholders was carried out to select and prioritise adaptation measures to reduce the erosion of sandy beaches, dunes and bluffs due to extreme wind storm surge and rainfall, SLR and mismanagement practices. The recovery of coastal ecosystems was implemented through soft measures (green infrastructure) such as revegetation with native species, dune regeneration, sustainable drainage systems and the reduction of use pressures.

Main achievements of this case study include capacity building of municipal staff and stakeholders, knowledge exchanges with national-level decision makers and scientists and the incorporation of EbA approaches by subnational-level coastal governments. To consolidate EbA, the local government introduced innovations in the coastal management institutional structure.

The outcomes of the article include, besides the increase in the resilience of social-ecological systems, the strengthening of socio-institutional behaviour, structure and sustainability. This experience provides insights for developing a strategy for both Integrated Coastal Management and climate adaptation at the national scale.

One of the greatest challenges faced by the 1994 post-apartheid government in South Africa is the housing problem that has persisted for almost 30 years into democracy. Innovation in research and practice is required to address this problem. This paper aims to discuss the aforementioned objective.

This paper presents an argument for housing knowledge management as one part of a much larger system of housing provision and critically compares information variations on one hypothetical, low-cost housing unit adapted for varying climatic regions. It aims to enquire if there is an overlap in information.

The findings do confirm a noteworthy overlap in the information of the varying units. Therefore, knowledge management of the information would prove effective and may contribute in part to housing provision.

The study is limited to assessing the information changes made to the contract documentation of the housing unit.

The paper argues that knowledge management of this overlapping information could impact housing provision by providing knowledge power to those affected by the housing problem.

The findings are a unique perspective presented through a knowledge management lens. In addition, the said knowledge management lens provides a platform to raise additional questions. When seeking answers to these questions, it is expected that research sub-themes would be identified focussing further research studies towards finding answers.

Heavy rainfall is one of the main causes of the degradation of historic rammed Earth architecture. For this reason, ensuring the conservation thereof entails understanding the factors involved in these risk situations. The purpose of this study is to research three past events in which rainfall caused damage and collapse to historic rammed Earth fortifications in Andalusia in order to analyse whether it is possible to prevent similar situations from occurring in the future.

The three case studies analysed are located in the south of Spain and occurred between 2017 and 2021. The hazard presented by rainfall within this context has been obtained from Art-Risk 3.0 (Registration No. 201999906530090). The vulnerability of the structures has been assessed with the Art-Risk 1 model. To characterise the strength, duration, and intensity of precipitation events, a workflow for the statistical use of GPM and GSMaP satellite resources has been designed, validated, and tested. The strength of the winds has been evaluated from data from ground-based weather stations.

GSMaP precipitation data is very similar to data from ground-based weather stations. Regarding the three risk events analysed, although they occurred in areas with a torrential rainfall hazard, the damage was caused by non-intense rainfall that did not exceed 5 mm/hour. The continuation of the rainfall for several days and the poor state of conservation of the walls seem to be the factors that triggered the collapses that fundamentally affected the restoration mortars.

A workflow applied to vulnerability and hazard analysis is presented, which validates the large-scale use of satellite images for past and present monitoring of heritage structure risk situations due to rain.

This study aims to investigate the relationships between firms’ strategic planning (SP), leadership and technology transfer competence (TTC) by specifically incorporating the mediating role of strategic quality management (SQM).

This study performs structural equation modeling using AMOS on survey data collected from 200 Turkish firms operating in multiple industries and sectors.

This study finds that leadership in Turkish firms operating in multiple sectors is positively associated with SQM. This study further finds that SQM positively influences Turkish firms’ TTC and mediates the roles of SP and leadership in TTC.

A key research implication from this study relates to the mediating role of SQM in TTC in an emerging economy context. This study highlights that SP and leadership can play an essential role in TTC through the mediating mechanism of SQM. Consequently, SQM emerges as a crucial linking pin in conveying the impact of quality management practices on technology transfer in emerging markets.

An essential managerial implication of this study relates to the critical roles of leadership, SP and SQM in TTC. For the managers of firms operating in a relatively uncertain emerging context such as Turkey, it is essential to adopt a supportive and empowering leadership style, where open communication and innovative activities are viewed positively and SQM is adopted holistically. Also, SP should be streamlined throughout the firm and followed by SQM to support TTC.

This paper links the technology (and knowledge) management and the strategy and leadership literature streams by focusing on the mechanisms of technology transfer and delving into the linkages between SQM, leadership, SP and TTC. It specifically presents SP and leadership as precursors to SQM in their joint influence on TTC. Accordingly, this research bridges technology, strategy and leadership research and provides a broader picture of technology transfer that encompasses the joint role of different processes in firms’ TTC.

The aim of this study was to measure the readiness of science and mathematics supervisors to utilize technology and online learning platforms for teachers' plans and professional development, during and after the period of the COVID-19 pandemic.

To achieve this aim, the researchers developed a questionnaire comprising of 55 items based on the instruments used in pertinent studies. A mixed-methods research design was employed, whereby a quantitative online survey was supplemented by focus group discussions with selected supervisors. Survey data were subjected to one-way analysis of variance and t-test, while information obtained via focus groups was coded to identify common themes related to the obstacles and challenges supervisors face.

When completing the survey, the supervisors approached proficiency using technology; however, focus group discussions revealed misconceptions related to e-leaning and limitations in their abilities to use technology in schools, as well as obstacles imposed by the structure and management of the educational system. T

These findings indicate that supervisors need support in acquiring the competencies required for integrating technology in education, and that their support to teacher community needs to be grounded in clear and systematic approaches and best educational practices.

These findings indicate that supervisors need support in acquiring the competencies required for integrating technology in education, and that their support to teacher community needs to be grounded in clear and systematic approaches and best educational practices.

Metropolitan areas suffer from frequent road traffic congestion not only during peak hours but also during off-peak periods. Different machine learning methods have been used in travel time prediction, however, such machine learning methods practically face the problem of overfitting. Tree-based ensembles have been applied in various prediction fields, and such approaches usually produce high prediction accuracy by aggregating and averaging individual decision trees. The inherent advantages of these approaches not only get better prediction results but also have a good bias-variance trade-off which can help to avoid overfitting. However, the reality is that the application of tree-based integration algorithms in traffic prediction is still limited. This study aims to improve the accuracy and interpretability of the models by using random forest (RF) to analyze and model the travel time on freeways.

As the traffic conditions often greatly change, the prediction results are often unsatisfactory. To improve the accuracy of short-term travel time prediction in the freeway network, a practically feasible and computationally efficient RF prediction method for real-world freeways by using probe traffic data was generated. In addition, the variables’ relative importance was ranked, which provides an investigation platform to gain a better understanding of how different contributing factors might affect travel time on freeways.

The parameters of the RF model were estimated by using the training sample set. After the parameter tuning process was completed, the proposed RF model was developed. The features’ relative importance showed that the variables (travel time 15 min before) and time of day (TOD) contribute the most to the predicted travel time result. The model performance was also evaluated and compared against the extreme gradient boosting method and the results indicated that the RF always produces more accurate travel time predictions.

This research developed an RF method to predict the freeway travel time by using the probe vehicle-based traffic data and weather data. Detailed information about the input variables and data pre-processing were presented. To measure the effectiveness of proposed travel time prediction algorithms, the mean absolute percentage errors were computed for different observation segments combined with different prediction horizons ranging from 15 to 60 min.

This research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income inequality.

Municipal data from the Annual Social Information Report, the National Electric Energy Agency and the National Institute of Meteorology spanning 2002 to 2020 are utilized. The Synthetic Difference-in-Differences methodology is employed for empirical analysis, and robustness checks are conducted using the Doubly Robust Difference in Differences and the Double/Debiased Machine Learning methods.

The findings reveal that biomass plant installations lead to an average annual increase of approximately R$688.00 in formal workers' wages and reduce formal income inequality, with notable benefits observed for workers in the industry and agriculture sectors. The robustness tests support and validate the primary results, highlighting the positive implications of renewable energy integration on economic development in the studied municipalities.

This article represents a groundbreaking contribution to the existing literature as it pioneers the identification of the impact of biomass plant installation on formal employment income and local economic development in Brazil. To the best of our knowledge, this study is the first to uncover such effects. Moreover, the authors comprehensively examine sectoral implications and formal income inequality.

Unlike conventional aircraft, birds can glide without a vertical tail. The purpose of this paper is to analyse the influence of dihedral angle spanwise distribution on lateral-directional dynamic stability by the simulation, calculation in the development of the bird-inspired aircraft and the flight testing.

The gliding magnificent frigatebird (Fregata magnificens) was selected as the study object. The geometric and mass model of the study object were developed. Stability derivatives and moments of inertia were obtained. The lateral-directional stability was assessed under different spanwise distributions of dihedral angle. A bird-inspired aircraft was developed, and a flight test was carried out to verify the analysed results.

The results show that spanwise distribution changing of dihedral angle has influence on the lateral-directional mode stability. All of the analysed configurations have convergent Dutch roll mode and rolling mode. The key role of dihedral angle changing is to achieve a convergent spiral mode. Flight test results show that the bird-inspired aircraft has a well-convergent Dutch roll mode.

The theory that birds can achieve its lateral-directional stability by changing its dihedral angle spanwise distribution may explain the stability mechanism of gliding birds.

This paper helps to improve the understanding of bird gliding stability mechanism and provides bio-inspired solutions in aircraft designing.