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The Fourth Industrial Revolution (4IR) is an era of enormous technical progress that has impacted professionals across industries, including Chartered Accountants (CAs). This study explored how CAs view the impact of the 4IR on their profession, focusing on the shifting roles, competencies, and challenges they face during this transitional period. The research adopted a qualitative approach to data collecting, including 14 semi-structured interviews with participants from various CA backgrounds. This research provides a thorough knowledge of the 4IR’s consequences for the profession and the perceptions of CA’s of the 4IR. Rapid task automation via technologies such as AI is posing a challenge to traditional CA roles, forcing a change towards more analytical thinking and strategic insight. CAs need to develop critical thinking abilities and data analysis ability. Older generations might need support to adapt to the technological changes. Despite fears about job loss due to technology, members were largely optimistic about the 4IR’s professional development potential. Conclusions are drawn and recommendations are given.

Introduction There is an ongoing scientific discussion, that anti-cancer effects induced by radiofrequency (RF)-hyperthermia might not be solely attributable to subsequent temperature elevations at the tumor site but also to non-temperature-induced effects. The exact molecular mechanisms behind said potential non-thermal RF effects remain largely elusive, however, limiting their therapeutical targetability.Objective Therefore, we aim to provide an overview of the current literature on potential non-temperature-induced molecular effects within cancer cells in response to RF-electromagnetic fields (RF-EMF).Material and Methods This literature review was conducted following the PRISMA guidelines. For this purpose, a MeSH-term-defined literature search on MEDLINE (PubMed) and Scopus (Elsevier) was conducted on March 23rd, 2024. Essential criteria herein included the continuous wave RF-EMF nature (3 kHz − 300 GHz) of the source, the securing of temperature-controlled circumstances within the trials, and the preclinical nature of the trials.Results Analysis of the data processed in this review suggests that RF-EMF radiation of various frequencies seems to be able to induce significant non-temperature-induced anti-cancer effects. These effects span from mitotic arrest and growth inhibition to cancer cell death in the form of autophagy and apoptosis and appear to be mostly exclusive to cancer cells. Several cellular mechanisms were identified through which RF-EMF radiation potentially imposes its anti-cancer effects. Among those, by reviewing the included publications, we identified RF-EMF-induced ion channel activation, altered gene expression, altered membrane potentials, membrane oscillations, and blebbing, as well as changes in cytoskeletal structure and cell morphology.Conclusion The existent literature points toward a yet untapped therapeutic potential of RF-EMF treatment, which might aid in damaging cancer cells through bio-electrical and electro-mechanical molecular mechanisms while minimizing adverse effects on healthy tissue cells. Further research is imperative to definitively confirm non-thermal EMF effects as well as to determine optimal cancer-type-specific RF-EMF frequencies, field intensities, and exposure intervals.

AbstractIntroduction Hyperthermia (HT) induces various cellular biological processes, such as repair impairment and direct HT cell killing. In this context, in-silico biophysical models that translate deviations in the treatment conditions into clinical outcome variations may be used to study the extent of such processes and their influence on combined hyperthermia plus radiotherapy (HT + RT) treatments under varying conditions.Methods An extended linear-quadratic model calibrated for SiHa and HeLa cell lines (cervical cancer) was used to theoretically study the impact of varying HT treatment conditions on radiosensitization and direct HT cell killing effect. Simulated patients were generated to compute the Tumor Control Probability (TCP) under different HT conditions (number of HT sessions, temperature and time interval), which were randomly selected within margins based on reported patient data.Results Under the studied conditions, model-based simulations suggested a treatment improvement with a total CEM43 thermal dose of approximately 10 min. Additionally, for a given thermal dose, TCP increased with the number of HT sessions. Furthermore, in the simulations, we showed that the TCP dependence on the temperature/time interval is more correlated with the mean value than with the minimum/maximum value and that comparing the treatment outcome with the mean temperature can be an excellent strategy for studying the time interval effect.Conclusion The use of thermoradiobiological models allows us to theoretically study the impact of varying thermal conditions on HT + RT treatment outcomes. This approach can be used to optimize HT treatments, design clinical trials, and interpret patient data.

Introduction Cell repair dynamics are crucial in optimizing anti-cancer therapies. Various assays (eg, comet assay and γ-H2AX) assess post-radiation repair kinetics, but interpreting such data is challenging and model-based data analyses are required. However, ambiguities in parameter calibration remain an unsolved challenge. To address this, we propose combining survival dose-rate effects with computer simulations to gain knowledge about repair kinetics. Methods After a literature review, theoretical discriminators based on common fractionation/dose-rate-related effects were defined to discard unrealistic model dynamics. The Multi-Hit Repair (MHR) model was calibrated with canine osteosarcoma Abrams cell line data to study the discriminators’ efficacy in scenarios with limited survival data. Additionally, survival dose-rate-dependent data from the human SiHa cervical cancer cell line were used to illustrate the survival behavior at diverse dose-rates and the capability of the MHR to model these data. Results SiHa data confirmed the validity of the proposed discriminators. The discriminators filtered 99% of parameter sets, improving the calibration of Abrams cells data. Furthermore, results from both cell lines may hint universal aspects of cellular repair. Conclusions Dose-rate theoretical discrimination criteria are an effective method to understand repair kinetics and improve radiobiological model calibration. Moreover, this methodology may be used to analyze diverse biological data using dynamic models in-silico .

Over the past decade, ecological connectivity has entered the political agenda, especially within the European transnational context. This evolution has driven the development of structural ecological connectivity and landscape permeability methodologies, such as the Continuum Suitability Index (CSI) presented here, which considers a range of anthropogenic factors that impact ecosystems. Numerous international and national projects have adopted the CSI to assess terrestrial landscape permeability on the macro-regional scale and prioritize areas for the implementation of ecological conservation and restoration measures. Although the CSI methodology has been applied several times, its sensitivity to individual factors, plausibility and ability to maintain consistency and robustness across different data sources and levels of spatial data precision have remained largely unexplored. Here, we presented the conceptual aspects of the CSI methodology, incorporating the outcomes from a literature review and expert workshops, and examined the CSI results for three projects spanning the Alps and Dinaric Mountains. Five key factors—namely, land use, population pressure, landscape fragmentation, environmental protection and topography—were identified as pivotal for analyzing landscape permeability and thus ecological connectivity. Notably, among these factors, population pressure exhibited the highest sensitivity, while fragmentation exerted the least influence on CSI outcomes. When comparing the CSI factors with data on the presence of red-listed species, the environmental protection indicator emerged as the most influential factor. Furthermore, our investigation comparing the different projects indicated that the chosen level of detail and data sources had minimal impact on the CSI results. Collectively, these analyses highlight CSI's adaptability and considerable potential as a versatile and straightforward applicable tool for an initial assessment of ecological connectivity at the macro-regional scale.

IntroductionWe report brigatinib long-term efficacy and safety from phase 1/2 and phase 2 (ALTA) trials in ALK-rearrangement positive (ALK+) NSCLC.MethodsThe phase 1/2 study evaluated brigatinib 30 to 300 mg/d in patients with advanced malignancies. ALTA randomized patients with crizotinib-refractory ALK+ NSCLC to brigatinib 90 mg once daily (arm A) or 180 mg once daily (7-d lead-in at 90 mg; arm B).ResultsIn the phase 1/2 study, 79 of 137 brigatinib-treated patients had ALK+ NSCLC; 71 were crizotinib pretreated. ALTA randomized 222 patients (n = 112 in arm A; n = 110 in arm B). Median follow-up at phase 1/2 study end (≈5.6 y after last patient enrolled) was 27.7 months; at ALTA study end (≈4.4 y after last patient enrolled), 19.6 months (A) and 28.3 months (B). Among patients with ALK+ NSCLC in the phase 1/2 study, median investigator-assessed progression-free survival (PFS) was 14.5 months (95% confidence interval [CI]: 10.8-21.2); median overall survival was 47.6 months (28.6-not reached). In ALTA, median investigator-assessed PFS was 9.2 months (7.4-11.1) in arm A and 15.6 months (11.1-18.5) in arm B; median independent review committee (IRC)-assessed PFS was 9.9 (7.4-12.8) and 16.7 (11.6-21.4) months, respectively; median overall survival was 25.9 (18.2-45.8) and 40.6 (32.5-not reached) months, respectively. Median intracranial PFS for patients with any brain metastases was 12.8 (9.2-18.4) months in arm A and 18.4 (12.6-23.9) months in arm B. No new safety signals were identified versus previous analyses.ConclusionsBrigatinib exhibited sustained long-term activity and PFS with manageable safety in patients with crizotinib-refractory ALK+ NSCLC.

Surgery remains an essential element of the multimodality radical treatment of patients with early-stage nonsmall cell lung cancer. In addition, thoracic surgery is one of the key specialties involved in the lung cancer tumour board. The importance of the surgeon in the setting of a multidisciplinary panel is ever-increasing in light of the crucial concept of resectability, which is at the base of patient selection for neoadjuvant/adjuvant treatments within trials and in real-world practice. This review covers some of the topics which are relevant in the daily practice of a thoracic oncological surgeon and should also be known by the nonsurgical members of the tumour board. It covers the following topics: the pre-operative selection of the surgical candidate in terms of fitness in light of the ever-improving nonsurgical treatment alternatives unfit patients may benefit from; the definition of resectability, which is so important to include patients into trials and to select the most appropriate radical treatment; the impact of surgical access and surgical extension with the evolving role of minimally invasive surgery, sublobar resections and parenchymal-sparing sleeve resections to avoid pneumonectomy.

Orientation: The general goal of the professional industrial and organisational psychology (IOP) master’s coursework and internship programmes is to enable the qualifying student to contribute to organisational strategic and operational human resource practices and people behavioural dynamics, assessment, and intervention design. Research purpose: The study explored the perceived effectiveness of the professional IOP master’s coursework and internship programmes in qualifying intern psychologists as employable industrial and organisational psychologists (IOPs). Motivation for the study: Internships are a practical way for intern psychologists to operationalise their professional purpose, acquire key occupation-related skills and practise their professional capability in real-world work settings. Research approach/design and method: The sample involved South African intern psychologists specialising in IOP (n = 17). Qualitative research methods with thematic data analysis were employed. Main findings: Guided by self-determination theory, the findings suggested that the IOP master’s coursework and internship programmes promote holistic development and embed confidence in practical and theoretical competence on both a personal and a professional level. Intrinsic and autonomous motivation regarding the IOP’s role and identity are also crystallised while the importance of continuous personal and professional growth, as well as a good support network, are acknowledged. Practical/managerial implications: Understanding the intern IOPs experience and required competencies for employment may help to improve the design and development of the professional IOP master’s coursework and internship programmes. Contribution/value-add: The study especially emphasised the need to enhance the effectiveness and support offered within the professional IOP master’s coursework and internship programmes by incorporating the principles of self-determination theory.

Orientation: An understanding of career adaptability and organisational commitment has become a thought-provoking phenomenon facing many contemporary organisations in the investment sector. Research purpose: This study aimed to investigate the relationship between career adaptability and organisational commitment among employees in the investment sector. Motivation for the study: There is an increasing need to understand employees’ capability to successfully manage changes that occur in the work context and how these impact their commitment to the organisation. Research approach: study adopted a quantitative research approach. A biographical questionnaire, Career Adapt-Abilities Scale, and Organisational Commitment Questionnaire, were administered among 200 permanent employees in the investment sector. Descriptive statistics, correlations, independent t-tests, and regressions were used to analyse the data. Main findings: The results showed a significant positive correlation between career adaptability and organisational commitment of employees who work in the investment sector. These results supported a predictive relationship between some demographic variables, career adaptability, and organisational commitment. Practical implications: Organisations should consider agile approaches to career adaptability given the constantly changing work environment in the Fourth Industrial Revolution and aim to achieve organisational commitment through the alignment of individual and organisational values and goals. Contribution: The findings provided valuable insight and knowledge about career adaptability and organisational commitment particularly for employees in the investment sector.

Machine learning and quantum computing are both areas with considerable progress in recent years. The combination of these disciplines holds great promise for both research and practical applications. Recently there have also been many theoretical contributions of quantum machine learning algorithms with experiments performed on quantum simulators. However, most questions concerning the potential of machine learning on quantum computers are still unanswered such as How well do current quantum machine learning algorithms work in practice? How do they compare with classical approaches? Moreover, most experiments use different datasets and hence it is currently not possible to systematically compare different approaches. In this paper we analyze how quantum machine learning can be used for solving small, yet practical problems. In particular, we perform an experimental analysis of kernel-based quantum support vector machines and quantum neural networks. We evaluate these algorithm on 5 different datasets using different combinations of quantum feature maps. Our experimental results show that quantum support vector machines outperform their classical counterparts on average by 3 to 4% in accuracy both on a quantum simulator as well as on a real quantum computer. Moreover, quantum neural networks executed on a quantum computer further outperform quantum support vector machines on average by up to 5% and classical neural networks by 7%.

The Fourth Industrial Revolution (4IR) rapidly advanced at the beginning of the 21st century. Leaders within organisations need to adjust their visions, plans, organisational structures, and management with regard to the demands, challenges and opportunities of this development. This is in particular the case in higher educational institutions (HEIs), which have to adjust to the rapid changes and new demands of skills of university graduates. Leaders in HEIs must therefore be aware of the related challenges and opportunities and might have to adjust the learning and teaching environment, the skills development of students, graduates, and faculty, as well as the technological requirements to create advanced skill sets. This article is based on a qualitative research study which was conducted at a university in South Africa. In-depth, semi-structured interviews were used to explore the views of higher-education leaders at the selected university. Data were analysed through thematic analysis. It was found that leaders in HEIs need to be aware of their leadership and preferences in times of transition toward a more technologised learning environment, as well as the needs, demands, challenges and opportunities of the new workplaces, and new skill sets needed in the 4IR. The researchers made some recommendations.“Education is the key that unlocks the golden door to freedom.” George Washington Carver.

Burnout is described as emotional and physical exhaustion, reduced accomplishment, together with an outlook of inadequacy and cynicism related to job stress. It has a harmful impact globally, especially in developing countries, such as South Africa. This study is a phenomenological collective case study focusing on burnout experience in a sample of female medical doctors working in a South African public hospital. Based on ongoing explorations of burnout themes, empirically based intervention strategies are needed to be developed and presented for the South African public health sector to prevent stress-related burnout. The findings support the trend in literature that burnout is an overwhelming experience for female medical doctors in South Africa. The study presents voices of female medical doctors, their concerns, the causes for burnout and their coping mechanisms. It provides a strong contribution to exploring and presenting women’s experiences in working in the medical field in South Africa from a positive psychology perspective. The findings indicate the struggles and the coping mechanisms of female medical doctors working in the field.

Abstract Increasing evidence suggests that remotely sensed spectral diversity is linked to plant species richness. However, a conflicting spectral diversity–biodiversity relationship in grasslands has been found in previous studies. In particular, it remains unclear how well the spectral diversity–biodiversity relationship holds in naturally assembled species‐rich grasslands. To address the linkage between spectral diversity and plant species richness in a species‐rich alpine grassland ecosystem, we investigated (i) the trade‐off between spectral and spatial resolution in remote sensing data; (ii) the suitability of three different spectral metrics to describe spectral diversity (coefficient of variation, convex hull volume and spectral species richness) and (iii) the importance of confounding effects of live plant biomass, dead plant biomass and plant life forms on the spectral diversity–biodiversity relationship. We addressed these questions using remote sensing data collected with consumer‐grade cameras with four spectral bands and 10 cm spatial resolution on an unmanned aerial vehicle (UAV), airborne imaging spectrometer data (AVIRIS‐NG) with 372 bands and 2.5 m spatial resolution, and a fused data product of both datasets. Our findings suggest that a fused dataset can cope with the requirement of both high spatial‐ and spectral resolution to remotely measure biodiversity. However, in contrast to several previous studies, we found a negative correlation between plant species richness and spectral metrics based on the spectral information content (i.e. spectral complexity). The spectral diversity calculated based on the spectral complexity was sensitive to live and dead plant biomass. Overall, our results suggest that remote sensing of plant species diversity requires a high spatial resolution, the use of classification‐based spectral metrics, such as spectral species richness, and awareness of confounding factors (e.g. plant biomass), which may be ecosystem specific.