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Collecting real-time infant feeding and support experience: co-participatory pilot study of mobile health methodology
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The quantitative dataset supporting the conclusions of this article is available in the OSF project https://osf.io/yqsnd/ [https://doi.org/10.17605/OSF.IO/YQSND].Supplementary Information is available online at: https://internationalbreastfeedingjournal.biomedcentral.com/articles/10.1186/s13006-025-00707-7#Sec31 .Background:
Breastfeeding rates in the UK have remained stubbornly low despite long-term intervention efforts. Social support is a key, theoretically grounded intervention method, yet social support has been inconsistently related to improved breastfeeding. Understanding of the dynamics between infant feeding and social support is currently limited by retrospective collection of quantitative data, which prohibits causal inferences, and by unrepresentative sampling of mothers. In this paper, we present a case-study presenting the development of a data collection methodology designed to address these challenges.
Methods:
In April–May 2022 we co-produced and piloted a mobile health (mHealth) data collection methodology linked to a pre-existing pregnancy and parenting app in the UK (Baby Buddy), prioritising real-time daily data collection about women's postnatal experiences. To explore the potential of mHealth in-app surveys, here we report the iterative design process and the results from a mixed-method (explorative data analysis of usage data and content analysis of interview data) four-week pilot.
Results:
Participants (n = 14) appreciated the feature’s simplicity and its easy integration into their daily routines, particularly valuing the reflective aspect akin to journaling. As a result, participants used the feature regularly and looked forward to doing so. We find no evidence that key sociodemographic metrics were associated with women’s enjoyment or engagement. Based on participant feedback, important next steps are to design in-feature feedback and tracking systems to help maintain motivation.
Conclusions:
Reflecting on future opportunities, this case-study underscores that mHealth in-app surveys may be an effective way to collect prospective real-time data on complex infant feeding behaviours and experiences during the postnatal period, with important implications for public health and social science research.We acknowledge the funding by the BA/Wellcome Trust small grants for supporting this project (reference SRG2021/210128)
UK Live Comedy Sector Survey Report 2024
Get PDFThe UK Live Comedy Sector Survey 2024 was jointly conducted by the Centre for Comedy Studies Research at
Brunel University, the Live Comedy Association, and British Comedy Guide. The UK Live Comedy Sector Survey was administered by Brunel University of London and ethical approval to conduct the survey was received from the College of Business, Arts and Social Sciences Research Ethics Committee at Brunel University of London.This report outlines the main findings of the UK Live Comedy Sector Survey 2024 conducted by the Centre for Comedy Studies Research (CCSR), the Live Comedy Association (LCA) and British Comedy Guide (BCG). Until now very little was known about the size, scale and impact of the UK live comedy sector. The survey provides detailed insights about the economics of the live comedy sector including its size and its longevity, numbers of shows and ticket sales, and turnover. It also provides insights into regional variations, venues used and performance types supported, and reveals inequalities and inequities prevalent in the sector. The survey serves to support and advocate live comedy in the UK politically, economically and socially.
366 people working in UK live comedy completed the survey. 67% of respondents were comedians.
33% of respondents were people working as comedy promoters, producers, venue managers, festival
organisers or agentsLive Comedy Association; Brunel University of London. Centre for Comedy Studies Research (CCSR); British Comedy Guide
An Impulsive Approach to State Estimation for Multirate Singularly Perturbed Complex Networks Under Bit Rate Constraints
Get PDFIn this article, the problem of ultimately bounded state estimation is investigated for discrete-time multirate singularly perturbed complex networks under the bit rate constraints, where the sensor sampling period is allowed to differ from the updating period of the networks. The facilitation of communication between sensors and the remote estimator through wireless networks, which are subject to bit rate constraints, involves the use of a coding-decoding mechanism. For efficient estimation in the presence of periodic measurements, a specialized impulsive estimation method is developed, which aims to carry out impulsive corrections precisely at the instants when the measurement signal is received by the estimator. By employing the iteration analysis method under the impulsive mechanism, a sufficient condition is established that ensures the exponential boundedness of the estimation error dynamics. Furthermore, an optimization algorithm is introduced for addressing the challenges related to bit rate allocation and the design of desired estimator gains. Within the presented theoretical framework, the correlation between estimation performance and bit rate allocation is elucidated. Finally, a simulation example is provided to demonstrate the validity of the proposed estimation approach.10.13039/501100019033-Key Area Research and Development Program of Guangdong Province (Grant Number: 2021B0101410005);
10.13039/501100003453-Natural Science Foundation of Guangdong Province of China (Grant Number: 2021A1515011634 and 2021B1515420008);
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: U22A2044 and 62206063);
Local Innovative and Research Teams Project of Guangdong Special Support Program of China (Grant Number: 2019BT02X353);
10.13039/501100004543-China Scholarship Council (Grant Number: 202208440312)
Training Latency Minimization for Model-Splitting Allowed Federated Edge Learning
Get PDFTo alleviate the shortage of computing power faced by clients in training deep neural networks (DNNs) using federated learning (FL), we leverage the edge computing and split learning to propose a model-splitting allowed FL (SFL) framework, with the aim to minimize the training latency without loss of test accuracy. Under the synchronized global update setting, the latency to complete a round of global training is determined by the maximum latency for the clients to complete a local training session. Therefore, the training latency minimization problem (TLMP) is modelled as a minimizing-maximum problem. To solve this mixed integer nonlinear programming problem, we first propose a regression method to fit the quantitative-relationship between the cut-layer and other parameters of an AI-model, and thus, transform the TLMP into a continuous problem. Considering that the two subproblems involved in the TLMP, namely, the cut-layer selection problem for the clients and the computing resource allocation problem for the parameter-server are relative independence, an alternate-optimization-based algorithm with polynomial time complexity is developed to obtain a high-quality solution to the TLMP. Extensive experiments are performed on a popular DNN-model EfficientNetV2 using dataset MNIST, and the results verify the validity and improved performance of the proposed SFL framework.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62132004);
Jiangsu Major Project on Basic Researches (Grant Number: BK20243059)
Neural Combinatorial Optimization for Multiobjective Task Offloading in Mobile Edge Computing
Get PDFTask offloading is crucial in supporting resource-intensive applications in mobile edge computing. This paper explores multiobjective task offloading, aiming to minimize energy consumption and latency simultaneously. Although learning-based algorithms have been used to address this problem, they train a model based on one a priori preference to make the offloading decision. When the preference changes, the trained model may not perform well and needs to be retrained. To address this issue, we propose a neural combinatorial optimization method that combines an encoder-decoder model with reinforcement learning. The encoder captures task relationships, while the decoder, equipped with a preference-based attention mechanism, determines offloading decisions for various preferences. Additionally, reinforcement learning is employed to train the encoder-decoder model. Since the proposed method can infer the offloading decision for each preference, it eliminates the need to retrain the model when the preference changes, thus improving real-time performance. Experimental studies demonstrate the effectiveness of the proposed method by comparison with three algorithms on instances of different scales.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: U23A20347);
Royal Society International Exchange (Grant Number: IEC-NSFC-211264)
Unlocking Business Success: How Networking and Branding Capabilities Drive Performance Through Product Innovativeness
Get PDFData Availability Statement:
The data that support the findings of this study are available from the corresponding author upon reasonable request.In today's fast-paced market, developing innovative products with significant advantages over existing alternatives is essential for a strong market presence. This study, based on the resource-based and dynamic capability view, examines how market and technological innovativeness contribute to differentiation advantage and improved business performance. It also investigates the roles of complementary capabilities in enhancing these relationships. Primary data were collected through an on-site questionnaire survey of Iranian research and development-intensive manufacturing firms. Using 125 valid responses from senior managers, partial least squares structural equation modeling tested the proposed model. Findings indicate that networking and branding capabilities enhance technological and market innovativeness, respectively, thereby strengthening differentiation advantage. Moreover, differentiation advantage is a crucial mechanism for translating innovativeness into improved business performance. These results provide theoretical insights and practical guidance for developing effective product innovativeness strategies to augment international competitiveness and performance
Incorporating acute HIV infection screening, same‐day diagnosis and antiretroviral treatment into routine services for key populations at sexual health clinics in Indonesia: a baseline analysis of the INTERACT prospective study
Get PDFData Availability Statement:
Data are available upon reasonable request. Requests for data sharing can be made by submission of a study concept to the INTERACT Study Group for evaluation of the scientific value, relevance, design, feasibility and overlap with existing projects.Introduction:
Indonesia has an escalated HIV epidemic concentrated among key populations. To strengthen the care cascade, we implemented a care pathway for the screening of individuals for acute HIV infection (AHI), to achieve prompt diagnosis and antiretroviral treatment (ART) initiation, at three non-governmental sexual health clinics in Jakarta and Bali. We assessed the AHI testing uptake, yield and prevalence, and the care cascade.
Methods:
This is a cross-sectional baseline analysis of individuals (≥16 years) who presented for HIV testing and were consecutively enrolled (May 2023−November 2024). We used an AHI risk-score self-assessment and test algorithm comprising a fourth-generation antibody/p24 antigen rapid diagnostic test (4gRDT; Abbott Determine HIV Early Detect) and, if negative/discordant, followed by HIV-PCR (Cepheid Xpert) (either individual or pooled-sample testing). AHI was pragmatically defined as having negative/discordant RDT results with positive HIV-PCR (ISRCTN41396071).
Results:
Three thousand seven hundred and ninety-seven (44.0%) of 8665 individuals were screened for study eligibility, and 3689 (97.2%) were enrolled. Median age was 28 years, and 78.2% were male. Men who have sex with men (MSM) accounted for 53.3%, clients of sex workers 19.2%, persons having a sex partner living with HIV 8.9% and sex workers 4.1%. We diagnosed 229 (6.3%; 229/3662) persons with RDT-positive (chronic) HIV, and we additionally identified 13 persons with AHI—that is a diagnostic yield of 5.6% (95% CI 3.1−9.5; 13/229) overall, and 6.1% (95% CI 3.2−10.3; 12/198) among MSM. AHI prevalence was 0.38% (95% CI 0.20−0.65; 13/3429) overall, and 0.72% (95% CI 0.37−1.2; 12/1677) among MSM. The number of persons needed to test to identify one person with AHI was 264 (3429/13) overall and 140 (1677/12) among MSM. The 4gRDT's performance to detect AHI was poor (2/13). Most participants received their HIV-PCR results on the same day (84.8%, 2907/3429) or within 24 hours (92.8%, 3182/3429). Of the 242 newly HIV-diagnosed individuals, 236 (97.5%) started ART, of whom 158 (67.0%) on the same day and 215 (91.1%) within 1 week.
Conclusions:
We successfully implemented prompt AHI diagnosis and treatment, and identified a high AHI prevalence among Indonesian MSM. Prioritizing access to AHI testing can create opportunities for enhanced interventions to curb the HIV epidemic among key populations.Wellcome Africa Asia Programme Vietnam;
UK Medical Research Council (MRC) and the Foreign Commonwealth and Development Office (FCDO)
Dual beam and dual circular polarized multiplexing reflectarray for Ku band satellite communication
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All data generated or analysed during this study are included in this published article.In this letter, a broadband low-profile dual circularly polarized reflectarray (dual-CP RA) for Ku-band satellite communications is proposed. A novel single-layer metasurface unit cell consisting of a functional layer, an air layer and a metal plate is investigated first. The functional layer is a metal structure printed on the F4B substrate. The air layer can effectively extend the bandwidth, and the overall profile is only 0.12λ0, where λ0 represents the wavelength at 11.725 GHz. To independently control the phase of left-handed circularly polarized (LHCP) and right-handed circularly polarized (RHCP) waves, Dynamic phase and Berry phase methods are employed by either changing the size of microstrip lines or the rotating of the cells. Finally, a dual-CP RA with 1600 cells is designed to realize two beams at 20° for LHCP wave and − 20° for RHCP wave at 11.725 GHz. The measured gain for LHCP wave is 29.1 dB with the aperture efficiency (AE) of 47% and 1-dB gain bandwidth of 37.4%, while the gain, AE, and bandwidth for RHCP wave are 29.22 dB, 48.3% and 37% respectively.This work was supported by the Key Research and Development Program of Shaanxi under Grant 2024GX-ZDCYL-01-29 and in part by the Science and Technology Project of Xi’an City under Grant 24KPZT0010
Valorising excavated low-grade waste clay in limestone calcined clay cement system for 3D printing applications
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Data will be made available on request.Limestone calcined clay cement (LC3) presents a suitable low-carbon cementitious material for large-scale 3D printing due to its long open time. This study investigates the impact of substituting up to 100 % natural aggregate with recycled brick aggregates (BA) on the engineering properties, durability and printing properties of LC3. BA's rough surface and irregular shape reduced the workability of the LC3 mixtures even though the water absorption of BA was compensated for by adding extra water. The mechanical strength increased significantly in the presence of BA of around 36 %–62 %. Moreover, incorporating BA was found to boost the hydration and allowed it continue due to the presence of additional water in its microstructure. The water absorptions of LC3 prepared with up to 70 % replacement level of aggregates with BA were comparable to the reference mix, while a 100 % replacement level increased the water absorption by around 9 %. In contrast, incorporating BA improved the freeze-thaw resistivity by up to 25 %. Moreover, it was found that incorporating BA improved the layer quality of 3D-printed filaments. The results of this study present a breakthrough in the recycling of brick aggregates in LC3 systems for both cast and 3D printing applications, which will help develop a more environmentally friendly mixture with high engineering performance
Bridging the pulse: Exploring inequalities in diabetes and hypertension medication prescriptions in Spain's immigrant and native communities
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The authors do not have permission to share data.JEL classification:
F22; I12; I14; J15.Migrants often face barriers in accessing high quality healthcare, leading to unequal treatment. This research investigates the disparities in medication utilization for cardiovascular risk factors between immigrant and native-born populations in Spain. The study specifically examines differences in drug prescriptions for managing diabetes and hypertension, two key contributors to cardiovascular disease. We analyze administrative healthcare records to examine the probability of patients receiving prescriptions for antidiabetic and antihypertensive medications. Additionally, we assess the likelihood of patients undergoing tests to measure glycated hemoglobin levels and blood pressure, two crucial indicators for monitoring diabetes and hypertension management.The analysis is stratified across different levels of medical needs, by also controlling for individual socioeconomic status, physician diagnoses, biometric data and primary care centers fixed effects. The findings reveal that all immigrant groups have lower probabilities of being prescribed medications for diabetes and hypertension and this is especially true for people with higher levels of healthcare needs. These findings underscore the importance of addressing healthcare disparities to achieve more equitable outcomes for immigrant communities.Nicodemo has received funding from the Economic and Social Research Council (grant number ES/T008415/1)
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