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They are ready to fight and must fight on the war’ – The Manchester Liberal Party’s Response to the South African War
No full textEffect of Noise on Bornean Orangutans’ Glucocorticoid Metabolite (GCM) Levels
Get PDFZoos are increasingly hosting out-of-hours events such as ‘Music Nights’ to increase visitation, raising potential animal welfare concerns due to anthropogenic noise pollution. This study examined the physiological stress response, measured through faecal glucocorticoid metabolite (FGCM), of Bornean orangutans (Pongo pygmaeus; n = 6) at Twycross Zoo during four consecutive weekends of live music events. Faecal samples were collected over these weekends and compared with a comprehensive 24 h acoustic analysis of the enclosure. The acoustic data indicated that the environment was dominated by noise from the ventilation system, which masked the sound from the live music. Comparisons of acoustic metrics between Event and Non-Event periods showed that LAeq, LA10, and LA90 were significantly higher during event hours or open zoo periods. In contrast, daily means did not differ. Group-averaged FGCM concentrations were higher on Event days (mean ± SE: Event = 826 ± 99 ng/g; No Event = 701 ± 44 ng/g), but comparisons for each individual showed no significant differences (Batu: t = 0.577, p = 0.596; Maliku: t = 1.475, p = 0.212; Molly: t = 0.290, p = 0.786; Kibriah: t = 0.771, p = 0.506). In contrast, FGCM concentrations increased significantly with increasing acoustic levels (LAeq) across individuals, with Batu and Maliku generally showing higher FGCM levels in response to louder days. These findings suggest that the constant background noise may have caused partial habituation. At the same time, individual variation highlights the importance of assessing physiological responses at the individual level, as relying on group-level data may overlook adverse welfare effects on sensitive individuals
Eating Well When Living With an Intellectual Disability—Exploring the Carer: Client Relationship in Residential Settings
Get PDFExecutive Summary: Carers face challenges in balancing the promotion of healthy eating whilst respecting residents' autonomy, especially when residents have cognitive impairments or are on psychotropic medications. Strategies like rapport‐building and individualised care are used but vary in effectiveness. The findings highlight the critical need for tailored nutritional education and support to enhance the health outcomes of individuals with intellectual disabilities while respecting their autonomy and preferences. The study highlights the importance of integrating comprehensive nutritional training for carers and involving nutritionists and dietitians in care planning. This could improve dietary practices in residential settings, ultimately contributing to better health outcomes for this vulnerable population
Utilizing Wadi Rum Silica Sands for Solar Thermal Energy and Heat Storage: A Sustainable Solution for Domestic Use
Get PDFThis research offers a hands-on examination of using Jordan’s naturally abundant, high-purity Wadi Rum silica sand (SiO2 > 99%) as an affordable material for thermal energy storage (TES) in concentrated solar power (CSP) systems aimed at home-scale applications. During the 3 days of continuous testing, the setup achieved a peak heat transfer rate of 18.7 kW, heating water by 27°C, reaching a top outlet temperature of 54.9°C. The silica sand proved to be an effective thermal reservoir, attaining internal temperatures between 67°C and 69°C. On average, the system produced 11.2 kWh of thermal energy per day, with an overall efficiency of 50.2%, while cutting daily CO2 emissions by about 2.07 kg. The economic assessment showed a payback time of just 1.49 years, which reduced to 1.04 years with a 30% subsidy. Altogether, the findings confirm that Wadi Rum silica sand offers a practical, sustainable, and financially attractive pathway for thermal storage, directly advancing Jordan’s drive toward a cleaner and more self-reliant energy future
Thermo-Magnetic Peristaltic Casson Flow in a Microchannel containing a Darcy- Brinkman porous medium with thermal radiation and heat source effects
No full textAbstact: The objective of this article is to study mathematically the magnetohydrodynamic (MHD) unsteady non-Newtonian oscillatory blood flow and heat transfer in micro-channels containing a Darcy-Brinkman porous medium. The Casson fluid model is deployed. Additionally the effects of heat source, nonlinear thermal radiation and Hall current are included. Convective heating and slip at the internal boundaries of the microchannel are also examined. Utilizing a set of non-dimensional variables the governing partial differential equations and associated boundary conditions are transformed into non-dimensional form. By solving the transformed model, exact solutions are obtained. Graphical representations depict the influence of different physical characteristics on the velocity and temperature patterns. In addition, this study incorporated a parametric analysis to demonstrate the impacts of key parameters on Nusselt number and wall shear stress. Increased values of thermal radiation and the Casson rheological parameter produce intensify velocity fields. Blood flow is also controlled by modulating the intensity of the external magnetic field, and the regulation of the blood temperature is achieved via modifying its thermal conductivity. With an increment in thermal Biot number (Bh) (stronger convective heating at the micro-channel walls) there is a uniform increase in temperatures. With elevation in Hall parameter, more complex streamline patterns are generated and there is an increased in the magnitude of trapped boluses. An increment in Grashof number (Gr) i.e. stronger thermal buoyancy force, accelerates the flow. Elevation in Nusselt number is produced with a stronger heat source (S). With greater frequency (), the blood flow is more strongly modified by periodic fluctuations in the driving pressure and this produces an elevated amplitude of velocity oscillations, thereby increasing the average velocity of the blood. Increasing slip (í µí»¾) generates significant flow deceleration in the micro-channel.This work, which focuses on thermal radiation in the blood flow, will significantly influence therapeutic strategies for hyperthermia. Specifically, the analysis provides a good foundation for more sophisticated computational fluid dynamics (CFD) studies and will enhance our understanding and management of blood flow and heat transfer in for example arterial hemodynamics
A review and meta-analysis of the efficacy of arbuscular mycorrhizal fungi in remediating toxic metals in mine-affected soils
Get PDFMines are natural reservoirs of various minerals, metals, and metalloids. Several heavy metals (HMs), such as Pb, Cd, Cr, Cu, and Ni, are major anthropogenic pollutants that cause severe environmental pollution. The accumulation of these toxic HMs in soils has raised several concerns for crop growth, food safety, and marketing. Physiological and biochemical processes in plants are severely impacted by HMs, disrupting normal metabolic activities and reducing biomass production. Phytoremediation plays a pivotal role in addressing HM contamination by offering an eco-friendly, economical, and holistic solution. Similarly, arbuscular mycorrhizal fungi (AMF) play a significant role by forming a symbiotic relationship with plant roots. In this association, plants provide root exudates, while AMF enhance plant growth under heavy metal stress by supplying essential nutrients, minerals, and water. These fungi also improve nutrient status, soil quality, and ecosystem stability. The present review and meta-analysis encompass an examination of the global distribution of toxic HMs in mining-affected areas. Furthermore, the study highlights the role of various plant species and microbes, particularly AMF, in mitigating HM stress and its impact on plant growth and nutrition. The meta-analysis also evaluates the efficacy of AMF as a remediation strategy for HM-impacted mine soils
Response to the Health and Social Care Committee call for evidence "Adult Social Care Reform The Cost of Inaction"
Get PDFThis response to the inquiry focuses on the following areas:-How much is inaction on Adult Social Care reform costing the NHS and local authorities, and what impact does this have on the adults who receive social care and the public?- Where in the system is the cost of inaction on Adult Social Care reform being borne the most
CGF-Deep-CNN: A Novel Computationally Enhanced Multiclass Cyber Attacks Detection Model for Low Powered IoT Ecosystem
Get PDFRecently, heavy network traffic and significant data accumulation have been observed in smart energy-efficient wireless sensor-based applications. These power-aware sensors devices form low-power Internet of Things (IoT) ecosystem. In such applications, IoT nodes gather and analyze private data, which becomes a natural target for cyber-attacks. Many intrusion detection systems (IDSs) are designed to address this issue, but the majority of these systems are computationally expensive with high latency and fail to accurately identify subcategories of cyber-attacks. Attribute selection would help in reducing the data required for attack identification, thereby decreasing delays and memory usage for data storage, while also enhancing detection performance. In this paper, an advanced and optimized IDS model for IoT applications was proposed, utilizing a novel hybrid attribute selection method called credit gain function (CGF). This method incorporates correlation feature selection (CFS) and gain ratio. The proposed attribute selector is used to optimize the dataset through CGF, resulting in a memory-constrained dataset. By employing the proposed CFS method, a novel IDS model based on the Deep-CNN technique is recommended for detecting and classifying cyber-attacks and their sub-categories within an IoT environment. Performance analysis of the presented framework was conducted using four public datasets—IoTID20, UNSW-nb15, NSL-KDD, and KDD—under various metrics, employing different parameters for binary, multi-class, and sub-category classification. The evaluation demonstrated that the proposed IDS model is highly capable, achieving a high accuracy, precision, recall, and F-measure of 98.1%, 96.7%, 96.3%, and 96.8%, respectively. The optimal performance was attained when implementing two convolutional layers and three dense layers of the CNN model with a batch size of 64. Additionally, the presented framework was evaluated to be efficient, with a mean response delay of 2.8 seconds and a low false positive rate of 0.002%. Consequently, the proposed intrusion detection model offers a constructive solution for assessing different cyber-attacks in an IoT ecosystem
Healthy forests safeguard traditional wild meat food systems in Amazonia
Get PDFAmazonia is the largest and the most species-rich tropical forest region on Earth , where hundreds of Indigenous cultures and thousands of animal species have interacted over millennia . Although Amazonia offers a unique context to appraise the value of wildlife as a source of food to millions of rural inhabitants, the diversity, geographic extent, volumes and nutritional value of harvested wild meat are unknown. Here, leveraging a dataset comprising 447,438 animals hunted across 625 rural localities, we estimate an annual extraction of 0.57 Mt of undressed animal biomass across Amazonia, equivalent to 0.34 Mt of edible wild meat. Just 20 out of 174 taxa account for 72% of all animals hunted and 84% of the overall biomass extracted. We show that this amount of wild meat can meet nearly half of protein and iron dietary requirements for rural peoples, along with a substantial portion of their needs for B vitamins (18-126%) and zinc (23%). However, wild meat productivity is likely to have decreased by 67% in nearly 500,000 km² of highly deforested areas of Amazonia. Furthermore, the availability of wild meat per capita decreases significantly in areas with higher human population, greater proximity to cities, and more extensive deforestation. These findings highlight the urgent need to preserve the forest to safeguard biodiversity and traditional wild meat food systems, which will be essential for ensuring Amazonian peoples' well-being and achieving several of the United Nations Sustainable Development Goals . [Abstract copyright: © 2025. The Author(s).
Optimization of passive acoustic bird surveys: a global assessment of BirdNET settings
No full textBirdNET is a popular machine learning tool for automated recognition of bird sounds. However, evidence on how to optimize its settings for accurate bird monitoring remains limited. Here, we evaluate how BirdNET settings influence model performance in identifying bird vocalizations and characterizing bird communities, using 4224 1-min recordings from 67 recording locations worldwide. Giving equal importance to recall and precision, a low confidence score threshold (0.1–0.3) appears optimal for detecting bird vocalizations, whereas higher thresholds (around 0.5) are more suitable for characterizing bird communities. Based on our findings, we recommend increasing the Overlap parameter from its default value of 0 to 2 s, as this consistently improves BirdNET performance in detecting both bird vocalizations and species presence. The effect of the Sensitivity parameter varied across regions. However, a value of 0.5 maximizes global performance for community-level analyses across all confidence thresholds, and a value of 1.5 generally yields better results for vocalization-level studies, particularly at low confidence thresholds. Our findings offer practical guidance for selecting BirdNET settings in passive acoustic bird surveys, enhancing both the identification of bird vocalizations and the characterization of bird communities
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