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The purpose of this paper is to provide evidence on the importance of cross-border cooperation in the quality assurance of transnational education (TNE) by offering a comparative overview of how TNE is quality assured by both sending and receiving countries. Through this comparative analysis, it will be possible to appreciate the diversity of approaches to TNE. The paper also shows that for the foreseeable future, progress towards effective and effiicient quality assurance of TNE cannot rest on the hope of developing an internationally agreed framework, but it must rest on strengthening cooperation between quality assurance agencies operating within different national frameworks.

This paper looks at four key sending countries of TNE, the UK, Australia, the USA and Germany, considering the main drivers for out-going TNE, its main features and how it is quality assured. It then considers the same aspects from the perspective of receiving countries of TNE, looking at four key receiving locations, China, Dubai, Singapore and Hong Kong. It also offers an overview of some recent international initiatives aimed at fostering cross-border cooperation in the quality assurance of TNE.

In the backdrop of this overview of different approaches to TNE, this paper will conclude that for the foreseeable future it is not possible to develop an internationally agreed view and approach to TNE and its quality assurance. This conclusion allows the author to focus on the importance of cross-border cooperation amongst quality assurance agencies in sending and receiving countries for the effective and efficient quality assurance of TNE.

This is the first comparative study of different countries’ approaches to TNE and its quality assurance, taking into account both sending and receiving countries. It allows pointing to the key different features in different countries’ approaches and illustrates how these often relate to the underlining national strategic priorities and drivers for TNE (either in-bound or out-bound). It also allows the international community to realise that in the absence of a viable shared and agreed international framework for the regulation and quality assurance of TNE, it is of paramount importance to focus efforts on inter-agency cross-border cooperation in order to ensure that TNE continues to be of good quality and relevant to the respective communities.

An individual’s driving style significantly affects overall traffic safety. However, driving style is difficult to identify due to temporal and spatial differences and scene heterogeneity of driving behavior data. As such, the study of real-time driving-style identification methods is of great significance for formulating personalized driving strategies, improving traffic safety and reducing fuel consumption. This study aims to establish a driving style recognition framework based on longitudinal driving operation conditions (DOCs) using a machine learning model and natural driving data collected by a vehicle equipped with an advanced driving assistance system (ADAS).

Specifically, a driving style recognition framework based on longitudinal DOCs was established. To train the model, a real-world driving experiment was conducted. First, the driving styles of 44 drivers were preliminarily identified through natural driving data and video data; drivers were categorized through a subjective evaluation as conservative, moderate or aggressive. Then, based on the ADAS driving data, a criterion for extracting longitudinal DOCs was developed. Third, taking the ADAS data from 47 Kms of the two test expressways as the research object, six DOCs were calibrated and the characteristic data sets of the different DOCs were extracted and constructed. Finally, four machine learning classification (MLC) models were used to classify and predict driving style based on the natural driving data.

The results showed that six longitudinal DOCs were calibrated according to the proposed calibration criterion. Cautious drivers undertook the largest proportion of the free cruise condition (FCC), while aggressive drivers primarily undertook the FCC, following steady condition and relative approximation condition. Compared with cautious and moderate drivers, aggressive drivers adopted a smaller time headway (THW) and distance headway (DHW). THW, time-to-collision (TTC) and DHW showed highly significant differences in driving style identification, while longitudinal acceleration (LA) showed no significant difference in driving style identification. Speed and TTC showed no significant difference between moderate and aggressive drivers. In consideration of the cross-validation results and model prediction results, the overall hierarchical prediction performance ranking of the four studied machine learning models under the current sample data set was extreme gradient boosting > multi-layer perceptron > logistic regression > support vector machine.

The contribution of this research is to propose a criterion and solution for using longitudinal driving behavior data to label longitudinal DOCs and rapidly identify driving styles based on those DOCs and MLC models. This study provides a reference for real-time online driving style identification in vehicles equipped with onboard data acquisition equipment, such as ADAS.

The paper aims to disentangle the physiological credit risk from the credit risk coming from the inefficient screening and monitoring management process. The analysis is conducted on a sample of 338 Italian banks–56 joint-stock banks (SpA), 23 cooperative banks (Popolari) and 259 mutual banks (BCCs)–over the time period 2006–2017.

The authors use the maximum likelihood method to estimate the efficient frontier, as a set of best management credit practices, which minimises the credit risk defined on the basis of the level of loans granted, the technical structure of the loan portfolio (such as credit lines, mortgages, consumer loans and other technical loan categories) and the interest rate charges.

The empirical results show that the increase in non-performing loans (NPLs) is related both to the severe and protracted recession in Italy, which significantly reduced borrowers' capacity to service their debt, and to other factors, such as banks' lending monitoring policies with limited capacity to work-out defaulted loans.

The authors propose a new approach to the study of the performance of the credit process. With the stochastic frontier, the physiological credit risk, assumed by the bank according to its lending activity and management choices, is separated from the credit risk resulting from an inefficient management of the screening and monitoring process. In addition, the authors analyse the determinants of the excess of NPLs. This aspect is considered particularly original because the scientific contributions which consider the causes of NPLs have largely focused on the level of NPLs not considering the physiological part, linked to the structure of the bank's loan portfolio and its operational strategy and therefore not compressible and in any case not attributable to mismanagement or moral hazard.

Based on DNase I and reduced graphene oxide (rGO)-magnetic silicon microspheres (MNPS), a highly sensitive and selective fluorescent probe for the detection of PD-L1 was developed.

Here °C we present a feasibility of biosensor to detection of PD-L1 in lung tumors plasma. In the absence of PD-L1°C the PD-L1 aptamer is absorbed on the surface of graphene oxide modified magnetic nanoparticles °8rGO-MNPS°9 and leading to effective fluorescence quenching. Upon adding PD-L1°C the aptamer sequences could be specifically recognized by PD-L1 and the aptamer/PD-L1 complex is formed°C resulting in the recovery of quenched fluorescence.

This sensor can detect PD-L1 with a linear range from 100 pg mL⁻¹ to 100 ng mL⁻¹, and a detection limit of 10 pg•m⁻¹ was achieved.

This method provides an easy and sensitive method for the detection of PD-L1 and will be beneficial to the early diagnosis and prognosis of tumors.

The Joint United Nations Programme on HIV/AIDS (UNAIDS) goal to end the acquired immunodeficiency syndrome (AIDS) epidemic as a public health threat by 2030 emphasises the importance of leaving no one behind. To determine progress towards the elimination goal in Ghana, an in-depth understanding of human immunodeficiency virus (HIV) care from the perspective of vulnerable populations such as persons living with HIV in incarceration is necessary. This study aims to explore the experiences of incarcerated individuals living with HIV (ILHIV) and on antiretroviral therapy (ART) in selected Ghanaian prisons to help inform policy.

The study adopted a qualitative approach involving in-depth interviews with 16 purposively selected ILHIV on ART from purposively selected prisons. Interviews were conducted between October and December 2022. Thematic analysis was performed using the ATLAS.Ti software.

Three themes were generated from the analysis: waking up to a positive HIV status; living with HIV a day at a time; and being my brother’s keeper: preventing HIV transmission. All participants underwent HIV screening at the various prisons. ILHIV also had access to ART although those on remand had challenges with refills. Stigma perpetuated by incarcerated individuals against those with HIV existed, and experiences of inadequate nutrition among incarcerated individuals on ART were reported. Opportunities to improve the experiences of the ILHIV are required to improve care and reduce morbidity and mortality.

Through first-hand experiences from ILHIV in prisons, this study provides the perception of incarcerated individuals on HIV care in prisons. The insights gained from this study can contribute to the development of targeted interventions and strategies to improve HIV care and support for incarcerated individuals.

The review aims to facilitate a broader understanding of platform opening and cooperation and points out potential research directions for scholars.

This study searches Web of Science (WOS) database for relevant literature published between 2010 and 2021 and selects 86 papers for this review. The selected literature is categorized according to three dimensions: the strategic choice of platform opening and cooperation (before opening), the construction of an open platform (during opening) and the impact of platform opening and cooperation (after opening). Through comparative analysis, the authors identify research gaps and propose four future research agendas.

The study finds that the current studies are fragmented, and a research system with a theoretical foundation has not yet formed. In addition, with the development of platform operations, new topics such as platform ecosystems and open platform governance have emerged. In short, there is an urgent need for scholars to conduct exploratory research. To this end, the study proposes four future research agendas: strengthen basic research on platform opening and cooperation, deeply explore the dynamic evolution and cutting-edge models of platform opening and cooperation, analyze potential crises and impacts of platform openness and strengthen research on open platform governance.

This is the first systematic review on platform opening and cooperation. Through categorizing literature into three dimensions, this article clearly shows the research status and provides future research avenues.

The cardiomegaly can be determined by the cardiothoracic ratio (CTR) which can be measured in a chest x-ray image. It is calculated based on a relationship between a size of heart and a transverse dimension of chest. The cardiomegaly is identified when the ratio is larger than a cut-off threshold. This paper aims to propose a solution to calculate the ratio for classifying the cardiomegaly in chest x-ray images.

The proposed method begins with constructing lung and heart segmentation models based on U-Net architecture using the publicly available datasets with the groundtruth of heart and lung masks. The ratio is then calculated using the sizes of segmented lung and heart areas. In addition, Progressive Growing of GANs (PGAN) is adopted here for constructing the new dataset containing chest x-ray images of three classes including male normal, female normal and cardiomegaly classes. This dataset is then used for evaluating the proposed solution. Also, the proposed solution is used to evaluate the quality of chest x-ray images generated from PGAN.

In the experiments, the trained models are applied to segment regions of heart and lung in chest x-ray images on the self-collected dataset. The calculated CTR values are compared with the values that are manually measured by human experts. The average error is 3.08%. Then, the models are also applied to segment regions of heart and lung for the CTR calculation, on the dataset computed by PGAN. Then, the cardiomegaly is determined using various attempts of different cut-off threshold values. With the standard cut-off at 0.50, the proposed method achieves 94.61% accuracy, 88.31% sensitivity and 94.20% specificity.

The proposed solution is demonstrated to be robust across unseen datasets for the segmentation, CTR calculation and cardiomegaly classification, including the dataset generated from PGAN. The cut-off value can be adjusted to be lower than 0.50 for increasing the sensitivity. For example, the sensitivity of 97.04% can be achieved at the cut-off of 0.45. However, the specificity is decreased from 94.20% to 79.78%.

Lactose intolerance is lactose digestive disorder due to lactase enzyme deficiency. This can affect the quality of life by restricting the intake of certain foods. The aim of this study is to show the lactose intolerance to the restriction in food intake and quality of life.

This study was conducted with adults aged 18–60 years. A survey was used to gather information on the demographic characteristics of the patients and their symptoms related to lactose intolerance. In addition, the Visual Analog Scale was administered to identify common symptoms and the World Health Organization Quality of Life (WHOQOL)-Bref Quality of Life Scale to determine their quality of life.

The average quality of life subscale scores was 56.25 ± 14.06 for physical, 58.29 ± 11.72 for mental, 63.28 ± 21.35 for social and 62.36 ± 16.37 for environmental. When VAS scores obtained for the common digestive system symptoms in lactose intolerance were compared with Quality of Life scores; it was found that physical life quality scores decreased (r = −0.239, p = 0.030) as the complaints of diarrhea increased and physical and environmental life quality decreased (r = −0.316, p = 0.004/r = −0.277, p = 0.012, respectively) as abdominal pain increased.

People reduce dairy consumption due to digestive system complaints. Therefore, it is important to inform the people about the effects of lactose intolerance because discomfort caused by intolerance can affect nutrient intake and lower the quality of life.

Despite the potential for co-operatives to improve smallholder farmers' livelihoods, membership in the co-operatives is low. This study examines factors that influence smallholder farmers' decisions to join agricultural co-operatives.

This study involved a survey of 1,274 smallholder chicken farmers. The data were analysed through a two-sample t-test of association, Pearson's Chi-square test and binary probit regression model.

The results suggest that farming as the main source of income, owning a chicken house, education attainment, attending training or accessing information, vaccination of goats and keeping a larger herd of goats are the key factors which significantly influence co-operative membership. However, gender, age, household size, distance to the nearest agrovet, vaccinating chicken and the number of chickens kept do not influence co-operative membership.

The survey did not capture data on some variables which have been shown to influence co-operative membership. Nevertheless, the results show key explanatory variables which influence membership in co-operatives.

These findings have implications for development agencies that seek to use co-operatives for agricultural development and improvement of smallholder farmers' livelihoods. The agencies can use the results to initiate interventions relevant for different types of smallholder farmers through co-operatives.

This study highlights the influence of smallholder farmers' financial investments in farming and the extent of commercialisation on co-operative membership. Due to low membership in co-operatives, recognising the heterogeneity of smallholder farmers is the key in agricultural development interventions through co-operative membership.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2022-0165.