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This paper shares the reflections of a small group of graduate students and faculty members in the United Arab Emirates (UAE) on the challenges and affordances of using large language model (LLM) tools to assist with academic writing in an English Medium Education (EME) context. The influence of interpretive grounded theory afforded the authors the opportunity to engage with emerging data from a focus group interview. Ethical issues including academic integrity and maturity formed a major theme of this study, as well as the future-thinking affordances of LLMs in facilitating and democratizing academic writing for all, including those in EME programs. Considering that LLMs are here to stay and will be used by students and faculty alike, the authors consider that the nature of assessment is likely to change and indeed will require higher education institutions to consider the types of assessments in place, with a view to potentially modifying them in light of these technological advances. We recommend the use of deeply personalized, critically reflective writing assignments where students demonstrate how the topic has meaning in their individual context and personal life story, that will ensure academic integrity and maturity while still embracing these new technologies to widen the scope of academic writing.

ABSTRACT: The advent of immunological therapies has revolutionized the treatment of solid and haematological cancers over the last decade. Licensed therapies which activate the immune system to target cancer cells can be broadly divided into two classes. The first class are antibodies that inhibit immune checkpoint signalling, known as immune checkpoint inhibitors (ICIs). The second class are cell‐based immune therapies including chimeric antigen receptor T lymphocyte (CAR‐T) cell therapies, natural killer (NK) cell therapies, and tumour infiltrating lymphocyte (TIL) therapies. The clinical efficacy of all these treatments generally outweighs the risks, but there is a high rate of immune‐related adverse events (irAEs), which are often unpredictable in timing with clinical sequalae ranging from mild (e.g. rash) to severe or even fatal (e.g. myocarditis, cytokine release syndrome) and reversible to permanent (e.g. endocrinopathies).The mechanisms underpinning irAE pathology vary across different irAE complications and syndromes, reflecting the broad clinical phenotypes observed and the variability of different individual immune responses, and are poorly understood overall. Immune‐related cardiovascular toxicities have emerged, and our understanding has evolved from focussing initially on rare but fatal ICI‐related myocarditis with cardiogenic shock to more common complications including less severe ICI‐related myocarditis, pericarditis, arrhythmias, including conduction system disease and heart block, non‐inflammatory heart failure, takotsubo syndrome and coronary artery disease. In this scientific statement on the cardiovascular toxicities of immune therapies for cancer, we summarize the pathophysiology, epidemiology, diagnosis, and management of ICI, CAR‐T, NK, and TIL therapies. We also highlight gaps in the literature and where future research should focus.

Abstract Through experimental tests, this paper investigated the effectiveness of microwave healing on asphalt mixtures containing iron powder (IP) filler to improve durability and enhance mechanical properties. The moisture sensitivity of the asphalt mixes with varying iron powder filler contents was measured using the modified Lottman test. For evaluating the asphalt mixture healing ability, two complementary methods were used: the fatigue-based method, derived from the ability of microwave healing of asphalt mixture samples damaged up to 50% level of indirect tensile fatigue (ITF), and the fracture-based method, obtained from the strength recovery rate of broken semi-circular samples by applying consecutive breaking-healing cycles. The results showed that the greater the quantity of iron powder filler in the asphalt sample, the greater the sample’s indirect tensile strength and TSR ratio, indicating that IP had a positive effect on moisture sensitivity. The findings also indicated that utilizing iron powder as a filler positively strengthens the fatigue life, increases the toughness, and increases the microwave healing indices (both fatigue and failure approaches). Finally, according to the study results, substituting 70% iron powder as the filler is the most suitable option for improving the mechanical and self-healing characteristics of asphalt mixes.

Abstract Aims The use of loop diuretics in pulmonary arterial hypertension (PAH) is less frequent compared with heart failure. The clinical and prognostic characteristics of PAH patients according to loop diuretic use remain unexplored. In this study, we retrospectively analysed the characteristics and survival of PAH patients requiring different doses of loop diuretics. Methods and results Patients diagnosed with PAH between 2001 and 2022 at seven European centres for the management of PAH. According to the median equivalent dose of furosemide in the overall cohort, patients were divided into two subgroups: no/low‐dose loop diuretic and high‐dose loop diuretic. Primary outcome was 5 year all‐cause mortality. Among the 397 patients included, 227 (57%) were treated with loop diuretics. Median daily furosemide equivalent dose was 25 mg, and accordingly patients were divided in no/low dose (i.e. ≤25 mg, n = 257, 65%) vs. high dose (i.e. >25 mg, n = 140, 35%). Patients in the high‐dose group were older, more likely to have comorbidities, and had a more severe disease according to the ESC/ERS risk category. Crude 5 year survival was significantly shorter in patients in the high‐dose group, but after adjustment for age, sex, and risk category, high loop diuretic dose was not significantly associated with the primary outcome. Conclusions Use of high dose of loop diuretics in PAH is associated with a higher burden of comorbidities, more severe disease, and worse survival. However, in PAH, the need of high loop diuretic dose is a marker of disease severity and not an independent prognostic factor.

Solar energy is one of the renewable and clean energy sources. Accurate solar radiation (SR) estimates are therefore needed in solar energy applications. Firstly, two deep learning models, including gated recurrent unit (GRU) and long short-term memory (LSTM), were developed in this study. Next, a data pre-processing technique named multivariate variational mode decomposition (MVMD) was used to construct the MVMD-GRU and MVMD-LSTM hybrid models. To better test the performance of proposed simple and hybrid models, four stations located in the Illinois State of the USA (i.e., Dixon Springs, Fairfield, Rend Lake, and Carbondale) were considered as the study sites. Whole the simple and hybrid models were established under two different strategies, i.e., local and external. In the local strategy, SR of each location was estimated using the minimum and maximum air temperatures from the same station. While, minimum and maximum air temperatures as well as SR data from the nearby station were utilized in external strategy to estimate SR time series of any target site. Root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) metrics were used when evaluating the models performances. The overall results revealed that the proposed MVMD-GRU and MVMD-LSTM hybrid models illustrated better SR estimates compared to the simple GRU and LSTM in both the local and external strategies. The values of error metrics obtained for the superior hybrid models (i.e., MVMD-LSTM) during the testing period were as: RMSE = 2.532 MJ/m2.day, MAE = 1.921 MJ/m2.day, R2 = 0.916 at Dixon Springs; RMSE = 2.476 MJ/m2.day, MAE = 1.878 MJ/m2.day, R2 = 0.921 at Fairfield; RMSE = 2.359 MJ/m2.day, MAE = 1.780 MJ/m2.day, R2 = 0.924 at Rend Lake; RMSE = 2.576 MJ/m2.day, MAE = 1.941 MJ/m2.day, R2 = 0.914 at Carbondale. Therefore, the coupled models proposed in this study can be possibly recommended as suitable alternatives to the simple deep learning models with a reliable precision in estimating SR time series.

Abstract Recently electronic tattoo sensors have attracted immense interest for health monitoring mainly due to their higher sensing performance than conventional dry sensors, owing to the ultra-low thickness which results in their conformability to the skin. However, their performance is worse than wet sensors. Further, these electronic tattoo sensors are not durable and reusable when free-standing because of their low thickness and being too delicate. Here, we report a remarkably high-performance freestanding, reusable, ultrathin and ultra-soft electronic tattoo sensor made of parylene-hydrogel double layer system with high water retention over extended periods that can be used for the extended period of 6 months. The hydrogel electronic tattoo (HET) sensors consist of electrically conductive self-adhesive hydrogel with a thickness of 20 µm and Young’s modulus of only 31 kPa at 37 °C, allowing for ultra-conformal contact to the skin microscopic features. Our HET sensors are fabricated using a scalable cost-effective method on ordinary tattoo papers and are laminated on the skin like temporary tattoos and were used for electrophysiological signals recording such as electrocardiography (ECG), electromyography (EMG), and skin hydration, temperature sensing. The HET sensors, for the first time, show 234% lower sensor-skin interface impedance (SSII) and significantly lower susceptibility to motion than gold standard medical grade silver/silver chloride wet gel electrodes which are known to have the lowest SSII and susceptibility to motion. Further, the low HET-skin interface impedance leads to a considerably larger signal amplitude and signal-to-noise ratio (SNR) of the electrophysiological signals recorded using HET sensors in comparison with those obtained using gold standard medical grade silver/silver chloride wet gel electrodes. The SNR of some types of electrophysiological signals such as EMG recorded using HET is up to 19 dB higher than gold standard medical grade electrodes due to higher signal amplitude, significantly lower susceptibility of HET to motion and lower motion artifacts. Also, the HET sensor is the first free-standing ultrathin tattoo sensor that can be transferred from the skin to tattoo paper and vice versa many times and the electrophysiological sensing quality remained high during repeated use for over 6 months.

In recent years, the research on the Iranian Chrysididae has been extremely prolific, thanks to the efforts of different teams. After the first checklist published by Rosa et al. (2013), more than one hundred taxa of cuckoo wasps have been recorded as new for Iran, including nine taxa described as new for science. Moreover, major modifications impacted the taxonomy of the family with two genera revaluated (Chrysellampus Semenov-Tian-Shanskij, 1932 and Colpopyga Semenov-Tian-Shanskij, 1954), Pseudochrysis Semenow, 1891 reintroduced for Pseudospinolia Linsenmaier, 1951; the description of the genus Morphochrysis Rosa & Pavesi, 2023 and several taxonomical changes to species level which were published and that deeply changed the first checklist, namely. As a consequence of all these fragmented changes, we propose a new, updated checklist of the Iranian species, to summarize all the new findings published in the last years. We describe eleven new species for science, Chrysis amerii Rosa & Farhad, sp. nov., C. chamrosh Rosa, sp. nov., C. crenulata Rosa, sp. nov., C. edentata Rosa & Baiocchi, sp. nov., C. peri Rosa & Baiocchi, sp. nov. and C. titanica Rosa, sp. nov. (succincta group), C. mediasignata Rosa, sp. nov. (leachii group), C. heimi Rosa, sp. nov. (maculicornis group), C. simurgh Rosa, sp. nov. (subsinuata group), Chrysura filidichroa Rosa, sp. nov. (dichroa group) and Hedychridium personatum Rosa, sp. nov. with its own new species-group. We report twenty-six new records of Chrysidinae for Iran: Chrysidea disclusa (Linsenmaier, 1959); Chrysis afghanica Linsenmaier, 1968; C. cylindrica Eversmann, 1858; C. echidna Semenov-Tian-Shanskij, 1967; C. grohmanni bolivari Mercet, 1902; C. klio Balthasar, 1953; C. laetula Semenov-Tian-Shanskij & Nikol'skaya, 1954; C. leuconoe Semenov-Tian-Shanskij, 1967; C. maracandensis Radoszkowski, 1877; C. mirabilis Radoszkovsky, 1877; C. mossulensis Abeille de Perrin-du Buysson, 1887; C. pseudobrevitarsis Linsenmaier, 1951; C. robertsi Rosa, 2020; C. rutilans Olivier, 1791; C. turcomana Semenov-Tian-Shanskij & Nikol'skaya, 1954; Chrysura laodamia laodamia (du Buysson, 1900); Euchroeus pellucidus (Radoszkowski, 1877); Hedychridium bytinskii Linsenmaier, 1959; H. mochii Strumia, 1994; H. plagiatum (Mocsáry, 1883); Hedychrum concinnum (Mocsáry, 1909); H. semicyaneum Mocsáry, 1889; Spinolia stchurovskyi (Radoszkowski, 1877); Spintharina extrema (Semenov-Tian-Shanskij & Nikol’skaya, 1954), and S. houskai (Balthasar, 1953). The current number of known taxa has therefore increased from 185 (179 species and 6 subspecies) to 315 (306 species + 9 subspecies). Hedychrum persicum Mocsáry, 1914 stat. nov. is upgraded to species rank. Chrysis chrysophora Semenow, 1892 and Hedychrum cyaneum Brullé, 1846 are considered nomina dubia and the latter as incertae sedis. Chrysis dawahi Strumia, 2012 is considered nomen nudum. The majority of chrysidid species in Iran (77.64%) are found exclusively in the Western Palearctic region. Among these, 21% are restricted to the Western Palaearctic. A thorough discussion is also provided on unreliable and doubtful species records.

Since asphalt pavement bleeding and raveling are significant threats to road safety, comfort, and service life, timely and accurate detection of them is desirable and cost-effective to develop pavement maintenance programs. Moreover, due to the fact that both of these distresses (i.e., raveling and bleeding) affect the texture of pavements, simultaneous classification of these distresses can provoke challenges. Thus, this study explores efficient texture analysis of 2D images for bleeding and raveling detection using tree-based ensemble methods. To this end, two scenarios of feature extraction are taken into account using Histogram Equalization (HE), Local Binary Pattern (LBP), and Gray-Level Co-occurrence Matrix (GLCM) techniques. Based on these two feature sets, four tree-based ensemble methods were evaluated for classifying the three classes of Bleeding, Raveling, and No-Bleeding & No-Raveling. The results confirmed that Feature Set B which derived from the integration of HE-GLCM and LBP-GLCM feature extraction provided the most favorable outcome, and gained the high performance of F1-Score ≅ 97 %. Finally, Convolutional Neural Network (CNN) models were constructed using the collected dataset and compared to the proposed method.