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Three-dimensional complex permittivity prediction from spatio-temporal electric field distributions
No full textQuantitative imaging is a critical task in various applications, including medical diagnostics, non-destructive evaluation and material characterisation. This work addresses the problem of three-dimensional (3D) permittivity profile reconstruction of a region of interest (RoI) by leveraging a deep learning model. This is performed by training the model to establish a mapping between the spatio-temporal electric field data and the corresponding permittivity profile of the RoI. The deep learning model is designed to handle the time-varying electric field data efficiently, using a combination of convolutional layers to extract spatial features and Long Short-Term Memory (LSTM) networks, to model temporal dependencies. The effectiveness of this approach is demonstrated through comprehensive validations in different scenarios, offering a powerful tool for quantitative permittivity prediction in a wide range of applications.<br/
Optimization of end-fire realized gain and side lobe levels in active and parasitic antenna arrays
No full textThis work presents a comprehensive optimization strategy for both active and parasitic antenna arrays, focusing on maximizing the overall efficiency and realized gain (RG). Using a differential evolution (DE) algorithm, we optimize key parameters such as element spacing, excitation currents, and load values. By removing predefined constraints on excitation vectors, this approach achieves greater flexibility and higher RG for all the array configurations, which is validated through full-wave simulations. Using the proposed DE-based optimization technique, we show a five-element parasitic array, achieving a maximum RG of 11.42 dB. Then, the optimization is extended to include side lobe level (SLL) minimization, balancing RG and low SLLs to improve the end-fire radiation performance. The parasitic five-element array achieves a RG of 10.32 dB with a SLL of −20 dB. This approach offers promising results for 5G and beyond wireless communication systems requiring compact, high-efficiency arrays with controlled interference.<br/
Geospatial mapping of drug-resistant tuberculosis prevalence in Africa at national and sub-national levels
No full textObjectiveTo map subnational and local prevalence of drug-resistant tuberculosis (DR-TB) across Africa.MethodsWe assembled a geolocated dataset from 173 sources across 31 African countries, comprising drug susceptibility test results and covariate data from publicly available databases. We used Bayesian model-based geostatistical framework with multivariate Bayesian logistic regression model to estimate DR-TB prevalence at lower administrative levels.ResultsWe estimated 148,239 DR-TB cases (95% Uncertainty Interval [UI]: 17,499- 313,683) in Africa, showing significant variation by country. Eswatini and South Africa had highest case numbers, while Algeria and Egypt had the lowest. The highest DR-TB prevalence was estimated in Eswatini (53.26; 95%UI 13.13-66.12), Morocco, Tunisia, and South Africa, while the lowest prevalence was found in Gabon, the Republic of Congo, Sierra Leone, and Mali. Marked subnational variation in DR-TB prevalence was noted, where 91 subnational areas across 12 countries had prevalence rates higher than their respective national averages. Factors such as mean temperature (β=2.01; 95% CrI: 1.21, 3.42), population density (β=0.41; 95% CrI: 0.19, 0.95), and fine particulate matter (β=0.66; 95% CrI: 0.20, 0.80) were positively associated with DR-TB prevalence.ConclusionThe study highlights substantial national and subnational variability in DR-TB prevalence across Africa, aiding policymakers in designing localized TB control interventions
A green deal and financing sustainable transport in Europe: a target costing analysis
No full textThis study investigates how Europe financed an efficient and environmentally friendly transport system and supported clean shipping investments from 2012 to 2021. Grounded in target costing theory, which aims to maximize a product's future success, this paper evaluates several green European financing pools and their effectiveness in facilitating the Green Deal transformation of the transport system. Utilizing a unique dataset from the Clean Shipping Project Platform, the results of this study indicate that Europe's environmental and financial support primarily stemmed from the European Investment Bank (EIB) which began backing green investments in 2010. The findings reveal a cautious yet significant contribution of the EIB towards climate protection in the shipping industry and identify challenges in financing smaller firms and innovative technologies thus emphasizing the need for strategic fund allocation to align with the EU's climate goals. These insights have critical policy implications for EU-based financing of European environmental policies prior to the proclamation of the Green Deal, which preceded the 2021-2028 budget period, as well as for the available climate funding mechanisms aimed at achieving the COP26 targets
Fedratinib combined with ropeginterferon alfa-2b in patients with myelofibrosis (FEDORA): study protocol for a multicentre, open-label, Bayesian phase II trial
No full textBACKGROUND: Myelofibrosis (MF) is a clonal haematopoietic disease, with median overall survival for patients with primary MF only 6.5 years. The most frequent gene mutation found in patients is JAK2 V617F, causing constitutive activation of the kinase and activation of downstream signalling. Fedratinib is an oral selective JAK2 inhibitor. It has shown activity in MF and is well-tolerated, but combination with other therapies is likely needed to achieve clonal remission. Combining a JAK2 inhibitor with an interferon may be synergistic, as haematopoietic cells are activated from quiescence (a typical kinase resistance mechanism) rendering them more sensitive to inhibition. Ropeginterferon alfa-2b is a next generation pegylated interferon-α-2b with high tolerability and clinical activity in patients with MF, however, evidence of tolerability and activity in combination with fedratinib is lacking in this setting. The aim of the FEDORA trial is to assess tolerability, safety, and activity of fedratinib with ropeginterferon alfa-2b in patients with MF who require treatment to justify further investigation in a phase III trial. METHODS: FEDORA is a single arm, multicentre, open-label, Bayesian phase II trial to assess tolerability, safety, and activity of fedratinib with ropeginterferon alfa-2b aiming to recruit 30 patients. Patients with JAK2 V617F positive primary or secondary MF, who are aged ≥ 18 years, have intermediate-1 with palpable splenomegaly of > 5cm, intermediate-2, or high-risk disease according to the Dynamic International Prognostic Scoring System (DIPSS), and who require treatment are eligible. The primary outcome is tolerability, whereby the combination is deemed intolerable in a patient if drug-related toxicities in the first four months of treatment lead to: either drug being discontinued; delays in treatment exceeding 28 consecutive days; or death. FEDORA uses a within-patient dose escalation regimen to ensure each patient reaches a personalised dose combination that is acceptable. DISCUSSION: FEDORA is using a Bayesian trial design and aims to provide evidence of the tolerability, safety, and activity of combining fedratinib with ropeginterferon alfa-2b upon which the decision as to whether a phase III trial is warranted will be based.TRIAL REGISTRATION: EudraCT number: 2021-004056-42.ISRCTN: 88,102,629.</p
Emerging trends in long-acting sustained drug delivery for glaucoma management
No full textGlaucoma is an optic neuropathy in which progressive degeneration of retinal ganglion cells and the optic nerve leads to irreversible visual loss. Glaucoma is one of the leading causes of blindness. The pathogenesis of glaucoma is determined by different pathogenetic mechanisms, including increased intraocular pressure, mechanical stress, excitotoxicity, resistance to aqueous drainage and oxidative stress. Topical formulations are often used in glaucoma treatment, whereas surgical measures are used in acute glaucoma cases. For most patients, long-term glaucoma treatments are given. Poor patient compliance and low bioavailability are often associated with topical therapy, which suggests that sustained-release, long-acting drug delivery systems could be beneficial in managing glaucoma. This review summarizes the eye’s physiology, the pathogenesis of glaucoma, current treatments, including both pharmacological and nonpharmacological interventions, and recent advances in long-acting drug delivery systems for the treatment of glaucoma.<br/
Automated precision weighing: leveraging 2D video feature analysis and machine learning for live body weight estimation of broiler chickens
No full textThe measurement of bird live weight during the production cycle is an important management practice in commercial broiler farming. However, the accuracy and practicalities of current weighing methods are limited. This paper proposes a non-invasive system that uses low-cost, overhead conventional cameras combined with computer vision and AI techniques to automatically weigh broiler chickens. The main objectives were to: (i) evaluate 2D video feature descriptors, together with regression modelling, to predict the live weight of broilers; (ii) establish the impact of posture (i.e. sitting/standing) and bird age on the accuracy of weight estimation; (iii) assess the feasibility of the camera-weighing system to monitor weight at different bird ages. In the first experiment, a video feature analysis was performed to evaluate the accuracy of 2D feature descriptors (ellipse axes, ellipse area, bounding box width, bounding box height) to predict the weight of broilers. Individual birds were manually weighed to establish a reference weight. The relationship between the feature sets and the reference weight was evaluated using six multivariate regression models. The approach was tested on two groups of broilers aged 23 (n=21 broilers) and 35 (n=23 broilers) days old, weighing between 570 to 2980g. In experiment 2, the best performing feature set and linear regression modelling from experiment 1 were applied to a larger number of birds across a greater age range (5 to 35 days old, n=222 broilers). To be more representative of the intended application of this technology, footage was recorded from the feeding area of a commercial broiler house and an automated chicken detector and tracking method was applied. The model was retrained using reference weights from experiment 2 (ranging from 100 to 3085g) to refine model performance. In experiment 1, the posture feature did not improve weight estimation whilst age improved the performance of all models. The accuracy of body weight estimation was greatest when bird age and the minor ellipse axis (x,y endpoints of the maximum points that are perpendicular to the longest line that can be drawn through an object) were used as model features. In experiment 2, the model showed the poorest performance in 5-day old birds with a mean relative error of 12.1 ± 7.9%. Overall, however, the model could estimate the weight of a broiler chicken with a mean relative error of 7.0 ± 5.8%. The results indicate that the analysis of 2D image features using video analytics and regression modelling is a promising method of obtaining rapid, cost-effective and accurate estimates of broiler live weight
Mycotoxin exposure through the consumption of processed cereal food for children (< 5 years old) from rural households of Oshana, a region of Namibia
No full textMycotoxin exposure from contaminated food is a significant global health issue, particularly among vulnerable children. Given limited data on mycotoxin exposure among Namibian children, this study investigated mycotoxin types and levels in foods, evaluated dietary mycotoxin exposure from processed cereal foods in children under age five from rural households in Oshana region, Namibia. Mycotoxins in cereal-based food samples (n = 162) (mahangu flour (n = 35), sorghum flour (n = 13), mahangu thin/thick porridge (n = 54), oshikundu (n = 56), and omungome (n = 4)) were determined by liquid chromatography-tandem mass spectrometry. Aflatoxin B1 (AFB1, 35.8%), zearalenone (27.2%), fumonisin B1 (FB1, 24.1%), citrinin (CIT, 12.4%) and deoxynivalenol (10.5%) were the major mycotoxins quantified. Food samples (35.8% (n = 58) and 6.2% (n = 10)) exceeded the 0.1 µg/kg AFB1 and 200 µg/kg FB1 EU limit for children’s food, respectively. Several emerging mycotoxins including the neurotoxic 3-nitropropionic acid, moniliformin (MON), and tenuazonic acid were quantified in over 50% of all samples. Co-occurrence of AFB1, CIT, and FB1 detected in 4.9% (n = 8) samples, which could heighten food safety concerns. Regarding exposure assessment and risk characterization, average probable dietary intake for AFB1 from all ready-to-eat-foods was 0.036 µg/kg bw/day, which resulted in margin of exposures (MOE) of 11 and 0.65 risk cancer cases/year/100,000 people, indicating a risk of chronic aflatoxicosis. High tolerable daily intake values for FB1, and MOE for beauvericin and MON exceeded reference values. Consumption of a diversified diet and interventions including timely planting and harvesting, best grain storage, and other standard postharvest food handling practices are needed to mitigate mycotoxin exposure through contaminated cereal foods and to safeguard the health of the rural children in Namibia
Book review: Rémy Ambühl and Andy King (eds), Documenting Warfare: Records of the Hundred Years War, Edited and Translated in Honour of Anne Curry (Woodbridge: Boydell and Brewer, 2024)
No full textCode-review-as-an-educational-service: a tool for Java code review in programming education
No full textHigh-quality source code is the foundation of successful and sustainable software development, while code review plays a crucial role in ensuring code quality. We place a special emphasis on the educational application of code review, aiming to assist novice students who are entry-level programmers establish industry-standard programming practices while reducing the likelihood of vulnerabilities and technical debt. Given that existing code review tools often require complex setups and are designed for large-scale, enterprise-level software projects, we advocate for the development of an easy-to-use, zero-configuration, and lightweight tool that is specifically tailored to the needs of educational environments. This paper reports our development of such a cloud-native code review tool as an educational service. Although still at the proof-of-concept stage, our internal and preliminary assessment has confirmed the promising usability and usefulness of this tool both for students (e.g., self-reviewing an individual exercise) and for educators (e.g., examining cohort exercises and prioritising teaching materials). By integrating this tool into our innovative project Automating Programming Education in Java, we believe that such an educational service would be able to make contributions to faster maturation of programming skills in students.<br/