19684 research outputs found
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Formulation and characterisation of resveratrol-loaded nanostructured lipid carriers for use in combination with scalp cooling therapy to mitigate chemotherapy-induced follicular cytotoxicity and hair loss
No full textHair loss represents a highly traumatic side-effect of chemotherapy treatment, it significantly affects psychological well-being, self-esteem and quality-of-life, with the fear of alopecia causing severe anxiety for cancer patients. While effective in eliminating cancer cells, chemotherapy drugs collaterally damage hair follicles resulting in chemotherapy-induced alopecia (CIA). Scalp cooling is a breakthrough treatment for patients, being the only clinically proven method to prevent CIA, with 50-65% of patients experiencing low grade alopecia (thus negating use of head covers and/or wigs during treatment).Our recent biological studies showed that optimal cooling effectively protects cells in human hair follicles from chemotherapy drug-mediated damage, whereas suboptimal cooling is less effective. However, combining cooling with an antioxidant that blocks reactive oxygen species (ROS) restores this protective effect against chemotherapy-induced hair follicle damage.In this study we focused on encapsulating the antioxidant resveratrol (RV) in nanostructured lipid carriers (NLCs) to optimise follicular targeting as a precursor to scalp cooling. We aimed for a particle size above 200 nm to limit systemic absorption and found that the nanoparticles had the desired properties when formulated with propylene glycol dicaprylate as the liquid lipid. RV-loaded NLCs remained stable at 4°C for > 6 months, with less than 10% variation in their size, polydispersity index (PDI), and zeta potential (ZP). Transmission electron microscopy (TEM) confirmed formation of Type I NLCs, featuring imperfect crystals that suggest a disordered lattice, facilitating RV's presence as disordered crystals or amorphous clusters within the matrix. Skin deposition studies demonstrated that RV-loaded NLCs reach the follicular reservoir within 6 hours, confirming their potential for co-application with scalp cooing for combating CIA
Long time series prediction of milling force via a hybrid multi neuro-network-based algorithm
No full textThe application of machine learning and deep learning has significantly improved the accuracy and efficiency of cutting force prediction in machining processes. However, challenges such as short prediction period, degradation in accuracy over time, and the risk of overfitting remains. These limitations collectively hinder the reliability and generalizability of artificial intelligence-based force prediction models. To address these issues, this study proposed a novel hybrid multi-neural-network algorithm that integrates convolutional neural networks, long short-time memory, and residual networks to enhance both the accuracy and duration of cutting force prediction. Prior to model training, raw force signals are pre-processed using particle swarm optimization-based variational mode decomposition to effectively eliminate noise and reduce uncertainty. The training and testing datasets are derived from milling experiments conducted under varying cutting parameters, tool types, and sensor configurations to better emulate real-world industrial conditions. Experimental results demonstrate that the hybrid model model can accurately predict cutting forces over a duration exceeding 1 s. The model's higher mean absolute error under varying test conditions suggests good robustness. The proposed data pre-processing phase contributes to a 6.38 % improvement in prediction accuracy. Furthermore, increasing the hyperparameter “timestep” helps mitigate overfitting, with only a minor trade-off in accuracy (less than 5 %). These findings demonstrate the effectiveness of the hybrid algorithm in addressing key limitations of existing models and highlight its potential for robust and generalizable prediction using AI in manufacturing applications
A metamaterials-augmented drone monitor for acoustics-based remote fault detection and diagnosis
No full textDrone Acoustic Remote Sensing Technology (DARST) holds significant potential in the approach to promote condition monitoring performance and efficiency. However, due to high aerodynamic noises from the drone itself, DARST has to be equipped with large scale microphone arrays and embedded with complex algorithms in order to improve the signal-to-noise ratio (SNR). This complicated construction along with high costs, makes DARST systems hard to be deployed in industrial applications. To address this challenge, this paper proposes a compact acoustic metamaterial structure-based system to augment the drone acoustic sensing, which is shortened to Metamaterials-augmented Drone Monitor (MADM) approach for the sake of simplicity. The design and performance of the proposed MADM method were explored through numerical simulations and experiments, demonstrating superior acoustic signal enhancement, frequency-selective behaviour and directional sensitivity characteristics. Subsequently, a series of experiments with machinery fault signals under different SNRs were conducted, comprehensively assessing the fault detection capabilities of the proposed MADM in monitoring and diagnosing a machinery transmission system. The results show that the MADM method can efficiently suppress drone-induced noise and robustly extract diagnostic features from bearing and gear faults, even under strong noise influence at SNR as low as −20 dB, and the average SNR improvement surpasses 140 %. The simple structured system needs only a single-channel acoustic signal with commonly used FFT-based algorithms, which occupies merely 22 % of the drone’s total payload capacity, offering a new cost-efficient approach for DARST in online inspection and fault diagnosis of industrial machinery
Modelling and analysis of the vibro-acoustic coupling behaviours of the cylinder liner-water jacket system towards cavitation prediction
No full textCylinder liner cavitation has a profound effect on performance, efficiency, and reliability, posing a major challenge to the advancement of diesel engine technology. Cavitation generation involves complex energy transfer and the interaction of multiple physical fields, particularly the strong coupling effect between the cylinder liner and water jacket. This study proposes a novel cavitation prediction method that integrates piston tribo-dynamics, cylinder liner dynamics, and water jacket acoustics. The vibro-acoustic coupling behaviour of a cylinder liner-water jacket system under piston slaps was investigated. The coupling relationship between the liner vibration and coolant pressure was revealed. The variation laws of vibration and cavitation risk factor with the acoustic parameters were systematically analysed. The results indicate that the added mass and damping effects of the fluid can significantly affect the dynamic characteristics of the cylinder liner. The high negative pressure in the water jacket resulted from the superposition of vibration-generated radiated waves and boundary-reflected acoustic waves. The dynamic behaviour of the cylinder liner-water jacket system is closely related to the coupled modes and acoustic boundaries. These results provide a valuable reference for the coupled optimisation of vibration and cavitation inhibition in diesel engines.</p
Effect of N-Acetylcysteine on mortality in COVID-19 patients:A systematic review and meta-analysis of randomized controlled trials
No full textIntroduction: The coronavirus disease 2019 (COVID-19) pandemic has prompted global interest in potential adjunctive therapies. N-acetylcysteine (NAC), a mucolytic agent that enhances intracellular glutathione synthesis, has antioxidant properties and may indirectly modulate inflammation through redox regulation. While preclinical and observational data suggest potential mortality benefits, findings from randomized controlled trials (RCTs) have been inconsistent. Objective: To systematically review and synthesize the evidence from RCTs evaluating the effect of NAC on mortality in patients with COVID-19. Methods: This systematic review and meta-analysis was conducted according to PRISMA guidelines. Six databases were searched from inception to March 21, 2025. Eligible studies were RCTs comparing NAC to placebo or standard care in adult COVID-19 patients, with mortality as a reported outcome. Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Cochrane RoB 2 tool. Statistical analyses were performed with a random-effects model to estimate pooled odds ratios (ORs) and 95% confidence intervals (CIs). Results: Ten RCTs comprising 1,424 patients were included. NAC regimens varied by dose and route. The pooled OR for mortality was 0.49 (95% CI: 0.25–0.94; I2 = 67%), indicating a 51% reduction in the odds of death among patients receiving NAC. Seven studies had low risk of bias; three had some concerns, primarily due to open-label designs. Conclusion: NAC may reduce mortality in COVID-19 patients, particularly when administered at higher doses or via non-oral routes. Further large-scale RCTs are needed to confirm these findings and establish optimal dosing and administration strategies.</p
Motivations and barriers in Huddersfield’s community gardens:exploring experiential social capital and community resilience
No full textThis study scrutinises the motivations and barriers to participation in community gardens (CGs) in Huddersfield, a town in West Yorkshire, UK, through the lens of experiential social capital. It presents a theoretical framework that integrates bonding, bridging, and linking social capital, while emphasising the importance of shared sensory experiences in strengthening social bonds and emotional connections. Using qualitative methods, the study draws on 16 semi-structured interviews with community members. The findings identify key motivations for participation, including social interaction, mental well-being, and skill development. Reported barriers include declining volunteer numbers, physical workload, limited institutional support, and accessibility challenges. The study highlights CGs as valuable spaces for fostering social cohesion and enhancing community resilience. It concludes with practical recommendations for garden managers, designers, and policymakers to improve engagement and support the long-term sustainability of these initiatives
Towards a Sociology of Intersex
No full textIntersex people and those with variations of sex characteristics are born with a combination of sex characteristics (chromosomal, gonadal and/or anatomical) that do not fit the typical definitions of male or female. The sociology of intersex and variations of sex characteristics is very underdeveloped, reflecting the social erasure, stigmatisation and discrimination that intersex people face. Intersex minors continue to be subjected to irreversible non-consensual and medically unnecessary medical interventions designed to make them fit normative notions of sexed and gendered embodiment. Feminisms have largely overlooked the existence of variations of sex characteristics, and epistemological violence is a problem in this field more broadly. This chapter provides a brief overview of key issues, aiming to introduce key concepts and terminology, and to fuel development of the field
Research on the failure mechanism and characteristic evolution of lithium-ion battery under different operation temperatures and extrusion deformation
No full textLithium-ion batteries (LIBs) are essential for energy storage and electric vehicle applications due to their high energy density and long cycle life. However, safety and reliability concerns persist, particularly under varying operational conditions. This study investigates the morphology, mechanical, electrical, and thermal evolution of LiFePO4 batteries under different temperatures, extrusion deformation, and states of charge (SOC). The primary goal was to examine the combined effects of these factors on battery performance, with a focus on improving battery management systems and safety. The results demonstrate that temperature, SOC, and deformation significantly impact the electrochemical impedance spectroscopy (EIS) of the batteries, with temperature having the most substantial effect. Notably, at low temperatures, the EIS amplitude in the mid-frequency region at −20 °C was about twice that at −10 °C, and the temperature effect diminished as the temperature exceeded 0 °C. Extrusion deformation also increased the EIS amplitude, particularly in the low-frequency region. Furthermore, deformation, SOC, and temperature significantly influenced stress–strain behavior, open-circuit voltage (OCV), and thermal performance. Internal morphological analysis revealed that severe extrusion deformation caused particle fragmentation, reduced porosity, and induced cracks in both the anode and cathode materials. These findings provide critical insights into the failure mechanisms of LIBs under complex stress conditions, which is crucial for enhancing battery safety and reliability.</p
Efficacy and safety of GLP-1 receptor agonists in the management of obstructive sleep apnea in individuals without diabetes:A systematic review and meta-analysis of randomized, placebo-controlled trials
No full textIntroduction: Obstructive sleep apnea (OSA) is a common sleep disorder that disrupts breathing during sleep. While continuous positive airway pressure therapy is the standard treatment, poor adherence has led to exploration of alternative treatments. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have been shown to reduce body weight and may help manage OSA. This systematic review and meta-analysis evaluated the efficacy and safety of GLP-1 RAs in individuals with OSA and elevated body weight who are without diabetes. Methods: A systematic search was conducted in September 2024 across multiple databases. Randomized controlled trials (RCTs) evaluating GLP-1 RAs for OSA in adults with a body mass index (BMI) ≥30 kg/m2 were included. The primary outcomes were changes in the apnea-hypopnea index (AHI) and overall adverse events. Meta-analyses were performed using a random-effects model. Results: Three RCTs were included in the analysis. Pooled results showed that GLP-1 RA treatment significantly reduced AHI compared to placebo, with a weighted mean difference (WMD) of −16.6 events per hour (95 % confidence interval [CI]: −27.9 to −5.3). However, GLP-1 RAs were associated with a higher frequency of adverse events, with an odds ratio (OR) of 1.62 (95 % CI: 1.16 to 2.24) compared to placebo. Conclusion: GLP-1 RAs effectively reduce OSA severity, offering a promising alternative for individuals with OSA and elevated body weight. However, the increased risk of side effects must be considered. Further long-term studies are needed to confirm the sustained benefits and safety of GLP-1 RAs in OSA management.</p
Fast Eserogram:A novel adaptive spectrum segmentation method for rolling bearing fault diagnosis
Full text linkEarly fault diagnosis of rolling bearings remains a critical challenge in industrial applications due to weak fault features and strong background noise interference. While the Fast Kurtogram (FK), as a classic fault diagnosis method, has been widely employed for fault detection in rotating machinery, its fixed frequency-band segmentation strategy may discard fault-related components, and conventional statistical indices often lack robustness under strong noise interferences. To overcome these challenges, a novel Fast Eserogram method for early fault detection is proposed in this paper. First, the Fourier model-fitting method is employed to extract spectral trends. Second, the local minima points of the spectral trend are integrated with a 1/3-binary tree filter bank to construct an adaptive filter group, maximizing the preservation of fault-related frequency bands. Subsequently, a robust statistical index—the Envelope Spectrum Energy Ratio (ESER) is established to evaluate the fault information richness in narrowband signals, enabling the selection of the optimal demodulation frequency band (ODFB). Finally, fault diagnosis is achieved through envelope spectrum analysis of the selected ODFB. The Fast Eserogram method exhibits superior performance to FK, Autogram, Accurgram, RCCgram and Log-cycligram in detecting early rolling bearing faults, as evidenced by experimental results.</p
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