26207 research outputs found
Sort by
Mathematical modelling approach to understanding the effect of Mg-rich synthetic gypsum used as fertilizer on growth of Hevea brasiliensis in acid soils
Get PDFKnowledge of plant growth dynamics is essential where constraints such as COVID-19 lockdown restrictions have limited its field establishment. Thus, modeling can be used to predict plant performance where field planting/monitoring cannot be achieved. This study was conducted on the growth dynamics of rubber planted on two acid soils treated with either dolomitic limestone (GML), kieserite or Mg-rich synthetic gypsum (MRSG) to supply the Mg required by rubber seedlings. To understand the effect of applied treatments on the changes in rubber growth, data on plant height, stem diameter and biomass were regressed against months after transplanting (MAT) using the equation y = A/ (1+be-ct), and its derivative dydt=Abce−ct(1+be−ct)z was utilized for estimating the growth rate of the parameters. The dynamics in plant height, stem girth and plant biomass were modelled using an exponential function of y = Aebt and their rate of change was derived using dx/dy = Abebt. The experiment indicated that the logistic growth curve model expressed as y = A/ (1+be-ct), closely described the growth in terms of each parameter against months after transplanting. A high probability level (a = 0.0001) was recorded in the model for all the treatments in the study. The growth of rubber seedlings in the glasshouse was improved by MRSG treatment in the two studied soils (Ultisol and Oxisol), giving comparable results to other Mg fertilizer treatments. The plant performed better on the Ultisol compared to the Oxisol. The results indicate the potential of using MRSG to replace conventional Mg-fertilizers to sustain rubber seedling growth
A comic-based body image intervention for adolescents in semi-rural Indian schools: A randomised controlled trial
No full textAdolescents in India experience body dissatisfaction and its associated adverse impacts on physical and mental health and gender equality. However, evidence-based interventions are scarce. Mental health interventions worldwide have traditionally relied upon delivery by expert providers. However, this prevents scalability, particularly in rural settings, where resources are often lacking. Therefore, this study evaluated the efficacy of a low-resource teacher-delivered mixed-gender comic-based body image intervention among adolescents in semi-rural Indian schools. A randomised controlled trial was conducted among 2631 students (50 % girls; classes 6 to 8; Mage = 12.03 years, SD = 1.22) across 41 schools around the Jaipur district in Rajasthan. Each school was randomly allocated to receive six comic-based intervention sessions (n = 1347) or lessons-as-usual (n = 1284; control). The primary outcome of body esteem and related secondary and exploratory outcomes assessing mental health and gender stereotyping were assessed at baseline, 1 week-post-intervention, and 3-months follow-up (ClinicalTrials.gov, NCT04317755). Linear Mixed Model analyses revealed that compared to the control group, intervention students reported significantly higher body esteem and skin shade satisfaction, and significantly lower eating pathology, internalisation of appearance ideals, and gender stereotyping, with all effects maintained at follow-up. Compared to control group, boys in the intervention group also demonstrated significantly higher body image-related life engagement and body hair satisfaction at follow-up. Both students and teachers indicated high intervention acceptability via quantitative and qualitative findings. These findings present the first effective teacher-delivered school-based body image intervention in India, which can be implemented at scale using minimal resources, and thus indicates promise regarding broader dissemination across urban and rural settings
Static and dynamic malware analysis using CycleGAN data augmentation and deep learning techniques
No full textThe increasing sophistication of malware and the use of evasive techniques such as obfuscation pose significant challenges to traditional detection methods. This paper presents a deep convolutional neural network (CNN) framework that integrates static and dynamic analysis for malware classification using RGB image representations. Binary and memory dump files are transformed into images to capture structural and behavioural patterns often missed in raw formats. The proposed system comprises two tailored CNN architectures: a static model with four convolutional blocks designed for binary-derived images and a dynamic model with three blocks optimised for noisy memory dump data. To enhance generalisation, we employed Cycle-Consistent Generative Adversarial Networks (CycleGANs) for cross-domain image augmentation, expanding the dataset to over 74,000 RGB images sourced from benchmark repositories (MaleVis and Dumpware10). The static model achieved 99.45% accuracy and perfect recall, demonstrating high sensitivity with minimal false positives. The dynamic model achieved 99.21% accuracy. Experimental results demonstrate that the fused approach effectively detects malware variants by learning discriminative visual patterns from both structural and runtime perspectives. This research contributes to a scalable and robust solution for malware classification unlike a single approach
Critical distance: On illustrating news events from afar
Get PDFPowerful images depicting the horror and devastation of geopolitical events and heinous abuses of power have an indisputable role to play in our society. This article however challenges the role of the eye witness as the sole conduit to valuable insights within news and media discourse. The authors propose that image-making practices (such as illustration) that operate at a distance from events allow for equally valid insights. Using three case studies of imagery produced at a remove from the news events it thematises, they argue that it is precisely the distance from the news event that enables the work to draw out aspects that are usually outside the frame of visibility. An analysis of Daniel Heyman’s portraits of Abu Ghraib detainees, Tings Chak’s schematic representations of migrant detention centres, and Catherine Anyango Grunewald’s animated film concerning the death of black teenager Michael Brown demonstrates that working at a remove can enable illustrators, artists and activists to reveal overlooked systems of power and control, restore dignity to dehumanised subjects, and reveal the limits of visual evidence. The article concludes with a reflection on the possibilities and limitations of the visual as a form of evidence
Developing a clinical decision tool to support paramedics when assessing and managing children with minor head injury
Get PDFBackground: Head-injured children are commonly transported to the Emergency Department (ED) by ambulance. However, most of those conveyed are deemed non-serious and are discharged at triage. Hospital clinicians use clinical decision tools to support their assessment of head-injured children; however, this is generally to determine whether a computed tomography (CT) scan is indicated. Currently, there is no pre-hospital clinical decision tool designed to support paramedics when assessing and managing head-injured children at scene. The aim of this study was to determine consensus amongst experts and stakeholders to inform the development of a new tool to support paramedics in safely assessing and managing children with minor head injury. Methods: A consultation process using a modified online Delphi technique comprising two rounds and a consensus meeting was completed between September 2023 and January 2024. A 5-point Likert scale was used to assess consensus, set a-priori at 67%. Free text survey responses arising from the Delphi were studied and concepts were developed. Data were analysed anonymously, and feedback was given after each round. Results: An expert stakeholder group comprising 36 participants took part in Round One, and 34 participants in Round Two of the online Delphi. The participants included parents/grandparents/caregivers, paramedics, primary care clinicians, ED doctors, ED nurses and Paediatricians. Consensus was reached in 36 statements following Rounds One and Two. The remaining eight statements were discussed at a consensus meeting, which was attended by 12 stakeholders. Seven of the eight statements reached agreement. Conclusion: This Delphi study has established consensus amongst a group of experts and stakeholders on the content and format of a pre-hospital paediatric head injury clinical decision tool, designed for use by paramedics: PATCH (Pre-hospital Assessment Tool for Children with Head injury). Future research should include an evaluation of the acceptability and usability of PATCH by paramedics. Clinical trial number: Not applicable
Internet Of Things—An Engineering Approach (From Principles To Practice)
No full textInternet of Things—An Engineering Approach: From Principles to Practice provides clear engineering practice guides on developing intelligent sensor/actuator nodes and then forming an Internet of Things (IoT) system including communication protocols to connect the sensor node to Internet and a software framework enabling Internet users to access the IoT nodes. IoT will be widely used in smart homes, smart cities, digital health, and by digital manufacturers. However, the development of an IoT system can be complicated since it combines technologies in networking and security, wireless communication/wireless sensor networks/broadband cellular networks, sensors and actuators, data acquisition and real-time embedded systems, edge computing with artificial intelligence, and low-power electronics technologies.All engineering practice topics come with examples, mostly from the first-hand materials of the author’s research projects, e.g., digital telephone switching and ISDN (integrated services digital network), text-independent speaker identification using neural networks, Internet-based distance experiments on embedded systems, powering indoor IoT sensor nodes by photovoltaic energy harvesting, low-power electronics for implantable neural recording for blowflies, surface acoustic wave (SAW)-based zero-power passive sensing for wearable applications, MEMs capacitor for ultrasound imaging/digital speakers, contactless electrodes for physiological measurements, electrical impedance tomography (EIT) for respiration indexing in intensive care, and electrooculography (EoG)-based gaze tracking for augmented reality. Therefore, this book can be used for teaching or be used as a reference for relevant research
Do you know who you’re talking to? Methodological reflections on maintaining inclusivity and research integrity when responding to inauthentic encounters in online qualitative research
Get PDFThere is an ongoing debate around how to design online synchronous qualitative research studies, and respond in the moment, when researchers suspect that they are engaging with ‘impostor’ or ‘fraudulent’ participants. Initial literature framed ineligible participants as a threat to data quality and the integrity of the research itself, calling for reactionary approaches to potential participants. This paper contributes to the growing literature cautioning that strict screening approaches may negatively harm genuine participants and undermine inclusion efforts. This paper explores the concept of ‘knowing’ research participants in qualitative research, focusing on methods that enhance how we genuinely come to know the participants we seek to include, particularly in reclaiming interactions that may have become curtailed during online research. Through consideration of researchers’ ethical responsibilities in relation to what is presumed or learned, we offer methodological reflections on how researchers’ skilful attention to the research encounter may be all that is required to ensure continued research integrity within the context of inauthentic participants. Taking actions to better know participants upholds our ethical responsibilities to them and also has the effect of identifying inauthentic participants who intentionally falsify their accounts
Pasture heterogeneity improves donkey welfare: Effects of structural variation, species diversity, and sward height on herd emotional states
Get PDFGrazing environment plays a key role in the welfare of domestic herbivores. In the UK, donkeys are typically kept on species-poor, agriculturally improved grasslands that offer limited dietary and behavioural opportunities. Obesity, driven by low exercise levels and unsuitable diet, remains a primary welfare concern in this species. This study examined whether field habitat heterogeneity, measured as structural variation, botanical diversity, and sward height, affects donkey welfare. Over a six-month grazing season, three donkey herds rotationally grazed 10 fields that differed in their level of habitat heterogeneity. Animal herd welfare was assessed using Qualitative Behaviour Assessment (QBA) of 194 videos, each scored independently by three trained enumerators. Habitat heterogeneity had a highly significant influence on donkey herd emotional states. Fields with greater structural variation were associated with more energetic behavioural expressions, while taller swards were linked to calmer, more relaxed states. Taller grass may have reduced competition for resources, leading to a more relaxed herd, while structural variation created environmental differences that encouraged more energetic expressions. These findings demonstrate that increasing field habitat heterogeneity can promote positive welfare states in donkeys, highlighting the importance of integrating environmental or semi-natural habitat features into grazing management practices
Surface functionalization of TiO 2 with an albumin–teicoplanin complex to prevent implant‐associated infections
Get PDFPostoperative infection and aseptic loosening are leading causes of orthopedic implant failure, often necessitating complex and costly revision surgeries. Teicoplanin (TP), a glycopeptide antibiotic effective against methicillin‐resistant Staphylococcus aureus (MRSA), and albumin (AB), a biocompatible carrier protein, present a promising strategy for implant surface functionalization. However, previous approaches using intermediate adhesive layers have demonstrated limited antibiotic retention following physiological conditioning. This study investigates the direct functionalization of titanium dioxide (TiO2) powder with an AB‐TP complex to develop a stable antibacterial surface coating capable of retaining efficacy after phosphate exposure. The AB‐TP complex was prepared and immobilized onto TiO2 powder. AB attachment kinetics and stability were assessed using the bicinchoninic acid (BCA) assay after short‐term incubation, serial buffer washes, and extended conditioning. In vitro, antibacterial efficacy was evaluated against S. aureus using viable count assays and disk diffusion. Additional tests assessed TP leaching following sample conditioning. The biological response of osteoblast‐like MG63 cells to AB‐TP was examined to evaluate cytocompatibility and pro‐osteogenic potential. AB demonstrated rapid and irreversible binding to TiO2, with negligible protein loss following 10 washes or 7‐day physiological buffer incubation. AB‐TP‐TiO2 completely inhibited bacterial growth (6.18‐log reduction). Following phosphate conditioning, AB‐TP‐TiO2 retained antibacterial activity, with log reductions of 3.3. Disk diffusion confirmed no TP leaching from AB‐TP‐TiO2, in contrast to TP‐TiO2, which exhibited significant antibiotic release and complete loss of antibacterial function post‐conditioning. Treatment of MG63 with the AB‐TP supported significant cell growth and increased alkaline phosphatase activity. Direct functionalization of TiO2 with the AB‐TP complex yields a stable, durable, and antibacterial surface capable of withstanding physiological conditions. This approach bypasses the limitations of adhesive layers and demonstrates potential for application in orthopedic implant coatings