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Laminated substrates are used widely in the manufacture of multichip modules (MCM‐L) by the electronic packaging industry. Of late, the thrust has been towards higher density circuitry to achieve improved performance and reduced size. This has led to the use of finer lines and spacings, smaller drilled holes and buried vias in organic laminates leading to reliability issues such as electrochemical migration. One of the forms of electrochemical migration is known as conductive filament formation. Conductive filament formation is an electrochemical process. In accelerated environments of temperature and humidity, organic laminates can develop a loss of insulation resistance between conductors, eventually resulting in loss of electrical function of the circuit. The paper aims at discussing electrochemical migration in general, and conductive filament formation in particular, and its impact on the reliability of MCM‐L.

Presently gender inequality and women's nutrition are the most concerning area of any development policy. Recent empirical evidence emphasizes that gender inequality decreases over time and the on the other hand percentage of overweight (OW) and obesity for women, especially in developing countries, increases over time. However, the relationship between these two phenomena (gender inequality and obesity) has rarely been investigated. Using time series yearly data (1990–2016) from the Nutrition Landscape Information Systems (NLiS) database of World Health Organisation (WHO) for India, we apply standard time series analysis including break test, stationarity test, cointegration test, and vector error correction model (VECM) to estimate the relationship between gender inequalities and percentage of females OW and obese. Our results show that there is a long-run relationship between these variables. Moreover, we also find that a decrease in gender inequality influences the increase in the number of females under OW and obese. In conclusion, the findings of this study reveal that, while elevating the position of women in society may be an important step toward combating the epidemic of OW and obesity, strategies must also tackle unhealthy habits that promote obesity.

Conductive anodic filament (CAF) is a failure mode in printed wiring boards (PWBS), which occurs under high humility and high voltage gradient conditions. This paper aims to review the history of CAF from its identification in the 1970s to the statistical analysis of its failure mode and the factors that enhance its formation.

Charts the chronology and details the developments of CAF over the last 30 years.

CAF is a conductive copper‐containing salt created electrochemically that grows from the anode toward the cathode sub‐surface along the epoxy/glass interface. It can also grow from the anode on one layer to a cathode on another. CAF was first discovered in 1976 and was identified as a catastrophic failure mode. It is enhanced by high humidity during storage or use, by high voltage gradient between anode and cathode, by certain soldering flux ingredients, by hole drilling, multiple thermal cycles during processing, and by higher processing temperatures associated with lead‐free solders. CAF is a copper hydroxy chloride salt and is a semiconducting material.

Our analytical tools today are far superior to those of these early researchers. Early data were obtained from chart recorders and manual plotting. Today we have computers for automated data collection and analysis and the sensitivity of the scanning electron microscope has improved significantly. The researchers of the 1970s and early 1980s characterized the basic factors associated with CAF and in many ways we are just repeating what they have done.

Higher degree by research (HDR) graduates are often perceived to be overly specialised and are unable to adapt to non-academic settings (Jaeger and Rudra, 2013). Universities are under increasing pressure to embed research and transferrable skills into the candidature in a flexible and meaningful way to equip graduates with the skills to succeed in a range of careers. The paper aims to study how Flinders University has embedded the Research and Employability Skills Training (REST) Program into the HDR.

REST was established to replace the workshop-based professional development program, with a structured, compulsory, comprehensive program for HDR students, based on the Vitae Researcher Development Framework (RDF). The Program aims to provide students with the research skills they need to complete their studies and the transferrable skills employers seek, through an online, supported program that helps them identify their needs, plan and control their skills development. Such a comprehensive online candidature management system has enabled Flinders to implement the RDF and successfully and comprehensively embed REST into the HDR candidature, assisting students to articulate and demonstrate their skills with documented evidence.

The Program has been running for one year, and so far, has been successful. Students are increasingly completing the initial online Skills Needs Analysis assessment component, which helps to identify their skills gaps and recommend workshops to meet their needs. Supervisors and students are engaging with the Program through structured discussion and refection of skills at each annual milestone, thanks to the help of the Inspire online candidature management system.

REST is a valuable resource for HDR students, providing them with a range of skills to progress with their research, writing and professional development training that complements, but is separate from, their degree. Providing a structured training program which follows and supports students’ candidature, and is based around the training needs and career trajectories of the student assists the students be more equipped and supported to complete on time and are well prepared for a range of career outcomes.

A defective printed circuit board assembly that exhibited excessive current leakage was examined to determine the responsible failure mechanisms. Observation of the failure site (determined electrically) by optical and electron microscopy revealed an area in the circuit board where debonded fiber bundles bridged a plated‐through‐hole (PTH) to a copper plane. This phenomenon is highly suggestive of conductive filament formation.

To show how the use of conductor spacings below 4 mil in printed wiring boards (PWBs) can introduce an unanticipated failure mechanism, leading to current leakage and short circuit failure.

The tests in this study were conducted in accordance with IPC‐TM‐650 2.6.25, using boards designed with conductor spacings between plated through holes (PTHs) ranging from 6 to 3 mil and from 8 to 3 mil between PTHs and ground planes. The board types and conductor spacings were selected to include current and future printed circuit board fabrication technology.

For PWBs that may be used in harsh environments where the relative humidity and temperature may approach those of the test environments, even for relatively short periods of time, spacings of 4 mil or less in the materials tested may not be appropriate. However, it is unlikely that the 85°C and 85 percent RH conditions are the minimum conditions to induce this failure mechanism. More tests at lower temperatures and relative humidity combinations should be conducted to evaluate conditions at which this type of failure begins.

The value of the paper lies in that the tests show that the IPC industry standard for conductive filament formation (CFF) testing of PTH‐PTH conductor spacings of 4 mil or less, at 85°C/85 percent RH can introduce a CFF variant failure mechanism, and therefore, may need to be modified to ensure that the test conditions accelerate the CFF mechanism and not other low resistance paths.

Increasing board densities, decreasing spacing between holes and features and the growing requirement for printed circuit boards to perform in high temperature/high humidity environments have led to renewed concerns about possible reliability problems caused by the growth of Conductive Anodic Filaments (CAF). To date, there has been a lack of information on standardized test procedures and failure analysis methods for various types of prepregs and laminates.This paper introduces a standard test vehicle design and discusses suitable testing, failure analysis and board manufacturing methods. It also includes the requirements for CAF resistance and there is a discussion of material benchmarking tests with some preliminary results from this testing. These methods should be applicable to boards used in all market segments, including high density interconnect, and automotive applications.

Denial-of-service (DoS) attacks develop unauthorized entry to various network services and user information by building traffic that creates multiple requests simultaneously making the system unavailable to users. Protection of internet services requires effective DoS attack detection to keep an eye on traffic passing across protected networks, freeing the protected internet servers from surveillance threats and ensuring they can focus on offering high-quality services with the fewest response times possible.

This paper aims to develop a hybrid optimization-based deep learning model to precisely detect DoS attacks.

The designed Aquila deer hunting optimization-enabled deep belief network technique achieved improved performance with an accuracy of 92.8%, a true positive rate of 92.8% and a true negative rate of 93.6.

The introduced detection approach effectively detects DoS attacks available on the internet.

The paper aims to comprehensively use the knowledge of tourist spatial behaviour to improve World Heritage Site (WHS) management. Efficient heritage management can be achieved if critical aspects such as tourist spatial activities were better and comprehensively understood, primarily at the micro-level. Inaccurate information on these essential aspects will potentially cause problems in managing a WHS and compromises its Outstanding Universal Value. This study aims to extend the knowledge of tourist spatial behaviour by including the non-spatial and spatial characteristics of the tourists to better manage a WHS.

This study uses a trip diary and a GPS tracking app with 384 free independent tourists as the study respondents. Melaka WHS was chosen as the study area. The data were complemented by an aggregative analysis method to extract different discrete patterns based on individual itineraries.

This paper indicates a noticeable relationship between individuals’ non-spatial and spatial characteristics. It suggests that integrating these two characteristics can provide more comprehensive knowledge of tourist behaviour.

This paper provides a different perspective to improving WHS management by determining the operative tools to develop an effective visitor management plan.

Fake news in cyberspace has greatly interfered with national governance, economic development and cultural communication, which has greatly increased the demand for fake news detection and intervention. At present, the recognition methods based on news content all lose part of the information to varying degrees. This paper proposes a lightweight content-based detection method to achieve early identification of false information with low computation costs.

The authors' research proposes a lightweight fake news detection framework for English text, including a new textual feature extraction method, specifically mapping English text and symbols to 0–255 using American Standard Code for Information Interchange (ASCII) codes, treating the completed sequence of numbers as the values of picture pixel points and using a computer vision model to detect them. The authors also compare the authors' framework with traditional word2vec, Glove, bidirectional encoder representations from transformers (BERT) and other methods.

The authors conduct experiments on the lightweight neural networks Ghostnet and Shufflenet, and the experimental results show that the authors' proposed framework outperforms the baseline in accuracy on both lightweight networks.

The authors' method does not rely on additional information from text data and can efficiently perform the fake news detection task with less computational resource consumption. In addition, the feature extraction method of this framework is relatively new and enlightening for text content-based classification detection, which can detect fake news in time at the early stage of fake news propagation.