Search Results (206,565)

This study develops a kinetic model that captures poly-ether-ether-ketone (PEEK) crystallization over a temperature $T$ window from glass transition ($T_g$) to melting ($T_m$) temperature, and across cooling rates from 5 to ~10³ °C/min. The framework is a parallel dual-Nakamura formulation whose isokinetic parameters {$k_i\left(T\right),n_i,w_i\left(T\right)$} are obtained from a bi-level non-linear regression of isothermal crystallization tests conducted using a flash-differential scanning calorimeter (FSC). The weight $w_i\left(T\right)$ partitions the faster primary and slower secondary crystallization and is represented by a physics-based analytical function that captures its dome-shaped temperature dependence. A maximum isothermally achievable enthalpy function is introduced so that the model predicts enthalpy $\Delta H\left(t\right)$ natively under arbitrary thermal profiles. To extend this isothermal backbone to non-isothermal conditions, two explicit cooling-rate-dependent scalars are introduced, $\omega \left(\dot{T}\right)$ and $\chi \left(\dot{T}\right)$, which shift $w_i\left(T\right)$ and limit attainable crystallinity at high cooling rates respectively. Finally, a rate-dependent induction time relation is added to adjust the onset of crystallization. Calibrating these rate functions against non-isothermal experiments, while keeping the isokinetic parameters fixed, yields a single isothermal–non-isothermal model that predicts $\Delta H\left(t\right)$ under arbitrary $T\left(t\right)$ profiles. Model performance is validated using an interrupted FSC experiment with a multi-segment cooling program that mimics a local transient thermal history of PEEK during additive manufacturing. The sample is cooled through successive constant-rate segments with intermittent quench–remelt cycles to probe the accumulated crystallinity along the path. Without additional fitting, the model predicts the measured enthalpy evolution with R² ≈ 0.95. The framework thus provides a practical route for predicting polymer crystallinity under processing-relevant thermal histories. Full article

Livestock production systems are considered some of the most environmentally degrading due to greenhouse gas (GHG) emissions and their contribution to poor air, soil and water quality, amongst other impacts. Advanced manure treatment technologies are required in response to intensification of dairy production worldwide, and the considerably greater volumes of manure generated that require collection and management. Similarly, in Australian dairy systems cows spend more time off pasture, with increased collection of larger manure volumes from a range of contained housing facilities. Adoption of advanced treatment is required to capture nutrients at risk of loss, and ideally to valorise manure to support uptake of these technologies. This review describes the generation of manure and the manure sources found in commercial Australian systems, including grazing-based and intensive dairy farms, supporting zero grazing. The review draws on manure data from pasture-based industries elsewhere and summarises their properties for comparison with Australian systems. Manure treatments that recover and retain nutrients, water and energy are reviewed. These include additives, mechanical/chemical/membrane separation, thermochemical and biological treatments which produce organic and inorganic soil amendments, clarified or potable water, gases (N₂, H₂), biofuels and energy. The review describes the technical and operational details of the technologies, and where there are opportunities for the Australian dairy industry. Treatment technologies need to be validated for Australian systems based on the collated data of local manure properties, as differences with international manure data have been observed. The relative costs, technological maturity, and the benefits and challenges associated with adoption are discussed. Many advanced technologies are ready for adoption, but others are experimental or at pilot stage and relative costs range from low to very high. However, to accurately assess feasibility of manure treatments, environmental, and production benefits should be balanced against capital and operating expenses and account for costs associated with current management. For large intensive farms, implementing advanced manure technologies may be required to ensure approval to operate/expand and to meet regulatory compliance. Future research for the Australian industry should investigate nutrient retention and further develop separation treatments incorporating chemical and mechanical technologies. Bioconversion of manure through insect composting as well as investigating co-digestion opportunities to enhance biogas production would support famers currently using these systems. Full article

This work investigates the physicochemical characteristics of waste tire pyrolysis char (WTP-char) produced at 500 °C in an industrial-scale auger reactor. The study uniquely combines material profiling with environmental safety assessment, specifically targeting organic contaminants and polymer stabilizers, evaluating WTP-char’s potential for circular economy applications. The samples underwent comprehensive analysis, including GC-MS, TGA, SEM-EDS, TXRF, and BET surface area measurements. The results revealed a high volatile matter content (13 wt.%), attributed to the thermal inertia typical of industrial-scale units. The organic fraction was dominated by n-alkanes (48.3%) and a significant concentration (6.97%) of the stabilizer Tris(2,4-di-tert-butylphenyl) phosphate (bDtBPP), posing potential environmental risks due to its cytotoxicity. Polycyclic aromatic hydrocarbon (PAH) analysis showed a prevalence of high-molecular-weight (HMW) compounds (79.7%), indicating high chemical stability. Although the specific surface area was low (28.9 m²/g), suggesting the need for activation, the material exhibits potential as a low-cost semi-reinforcing filler or solid fuel. By moving beyond laboratory-scale experiments to real industrial production, this study establishes a practical framework for evaluating both the performance and environmental safety of waste tire pyrolysis char. Full article

Ashwagandha, a revered herb in Ayurvedic medicine for over 3000 years, is recognized for its potential benefits in regulating sleep and supporting overall vitality. This study evaluated the comparative effects of Ashwagandha root extract (ARE) and melatonin (MLT) on sleep quality in adults. In this prospective, randomized, double-blind, placebo-controlled trial, 200 men and women aged 18–50 years were randomized to receive ARE (300 mg twice daily; n = 50), MLT (3 mg/day; n = 50), a combination of ARE (600 mg/day) and MLT (3 mg/day; n = 50), or placebo (n = 50) for eight weeks. The primary outcome was the change in sleep onset latency (SOL) from baseline to week eight, measured by actigraphy. Secondary outcomes included actigraphy-based changes in total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE), as well as subjective measures such as the Pittsburgh Sleep Quality Index (PSQI) and the Hamilton Anxiety Scale (HAM-A). At week eight, SOL was significantly reduced across treatment groups, with the ARE–MLT (p < 0.0001) combination showing the greatest improvement. The combination group also demonstrated significant improvements in TST (p < 0.0001), WASO (p < 0.0001), and SE (p < 0.0001), whereas ARE and MLT monotherapy produced moderate but comparable benefits. Inferential analyses confirmed statistically significant improvements in objective and subjective sleep measures (p < 0.0001). Safety analyses indicated that mild adverse events occurred across all groups, with no clinically significant between-group differences. Overall, both Ashwagandha and melatonin improved sleep disturbances in adults, with combination therapy producing the most consistent and pronounced benefits. Full article

School-based mental health screening typically relies on single-time-point assessments, which assume that students’ emotional well-being is sufficiently stable for classification based on a single measurement. The present study examined this assumption by evaluating the stability of emotional well-being classifications under repeated mood monitoring. Students from two secondary schools (United Kingdom, n = 413; Australia, n = 354) completed the Brief Emotional Experience Scale weekly across six to seven weeks. Emotional well-being classifications were examined relative to a predefined low well-being threshold to assess stability across time, and a post-monitoring survey examined students’ self-reported perceptions of the monitoring experience. Most students (78%) showed consistently above-threshold classifications across monitoring occasions, while a small proportion (5%) showed persistently low classifications. However, 17% of students fluctuated above and below the low well-being threshold across weeks, indicating that classification status for this group was sensitive to assessment timing. When monitoring data were aggregated using different decision rules, the proportion of students flagged as low well-being varied substantially, ranging from approximately 5% under a conservative stability-based criterion to around 12% when classifications were based on averaged monitoring scores. Classifications derived from averaged monitoring scores showed high agreement with single-time-point classifications, while identifying a partially different subset of students as low well-being, underscoring the sensitivity of threshold-based decisions to classification approach. Student feedback provided preliminary contextual insight into the acceptability of repeated monitoring under routine school conditions, with over half of respondents reporting that the process supported their emotional understanding. A substantial minority also reported greater inclination to talk with others about their well-being. Overall, the findings indicate that single-time-point screening may provide an incomplete basis for emotional well-being classification for some students, and that repeated assessment offers additional temporal context for interpreting threshold-based screening decisions. Full article

N-acetylcysteine (NAC) is a glutathione precursor with established antioxidant and anti-inflammatory properties that has been investigated as a neuroprotective agent across multiple neurological conditions. This systematic review systematically mapped the clinical evidence for NAC across seven neurological disorders. PubMed and Cochrane Library were searched for studies published between 1 January 1995 and 31 December 2025. Twenty-three studies were included: traumatic brain injury (TBI, n = 6), Alzheimer’s disease (AD, n = 5), Parkinson’s disease (PD, n = 5), multiple sclerosis (n = 4), amyotrophic lateral sclerosis (n = 2), and migraine (n = 1); no eligible epilepsy studies were identified. The strongest evidence emerged for acute mild TBI, where early NAC administration significantly improved symptom resolution, and for PD, where combined intravenous/oral NAC improved dopamine transporter binding. In AD, nutraceutical formulations including NAC and other active compounds showed trends toward cognitive stabilization. Most included studies had a high or serious risk of bias, and only eight of 23 assessed oxidative stress biomarkers. NAC demonstrated a favorable safety profile across all conditions. Despite fragmented and heterogeneous evidence, the encouraging signals identified warrant large-scale randomized controlled trials with a standardized biomarker assessment. Full article

Background: The phase of electroencephalogram (EEG) signals critically influences cortical reactivity to external inputs. Phase-dependent effects and their sensitivity to stimulation intensity have been observed at suprathreshold levels, while subthreshold transcranial magnetic stimulation (TMS) cannot induce motor evoked potentials (MEPs), resulting in limited research on phase-dependent responses under subthreshold stimulation. In this study, we used a combined transcranial magnetic stimulation and electroencephalography (TMS–EEG) approach to examine how the ongoing EEG phase influences cortical responses at subthreshold intensity and to characterize these responses in terms of temporal, spatial, and spectral features. Methods: Thirty-four healthy adults received subthreshold single-pulse TMS at the motor hotspot during 64-channel EEG recording. The mu-phase at the time of TMS delivery was estimated using autoregression-based forward prediction and categorized into four bins (0°, 90°, 180°, and 270°). The cortical responses were assessed using inter-trial phase coherence (ITPC), TMS-evoked potentials (TEPs), global mean field power (GMFP), and event-related spectral perturbation (ERSP). Results: Phase estimation reliably distinguished four mu-phase bins. Subthreshold TMS–EEG responses showed clear phase dependence: early ITPC and several TEP components (N15, P30, N45, P60, and N100) differed significantly across phases, with 180° and 270° often eliciting stronger responses. GMFP revealed robust phase effects at mid-latency components, and TMS-induced mu-rhythms were the greatest at 180°. Conclusions: Our results showed that the EEG phase significantly modulates cortical reactivity at subthreshold stimulation levels, supporting mu-phase-based closed-loop TMS as a promising strategy for precise neuromodulation. Full article

Background: Difficulties in recruiting patients for clinical trials increase costs and delay the implementation of new therapies. A better understanding of participants’ motivations and barriers can help with developing effective recruitment strategies. The aim of the study was to identify the factors influencing the decisions of adult Poles to participate in clinical trials. Methods: The survey was conducted among Polish adults aged 18 years and older by the independent research company Ariadna between January and February 2023. The questionnaire consisted of 22 questions, nine of which related to the determinants of participation in clinical trials. 1079 people took part in the survey. Results: The study population included 568 women (52.6%) and 511 men (47.4%). The mean age of respondents was 44.96 years (SD = 16.30). 49.9% of respondents (n = 538) declared their willingness to participate in clinical trials in the future. Among those who were reluctant (n = 158, 14.6%), the main barriers were: safety concerns (n = 59, 5.5%), lack of trust (n = 43, 4.0%), and insufficient knowledge (n = 33, 3.1%). The strongest motivation was the desire to improve health (n = 869, 80.5%), and the most frequently indicated reason for participation was cancer (n = 740, 68.6%). The least frequently indicated were diseases of the urinary and reproductive systems (n = 125; 11.6%). Conclusions: The results highlight key aspects important to patients when deciding whether to participate in clinical trials. Such findings may prove useful for researchers in getting to know their patients better and in developing effective strategies to recruit and retain participants in clinical trials. Full article

Background/Objectives: The peroneus longus tendon (PLT) is increasingly used as an autograft for anterior cruciate ligament reconstruction (ACLR). However, during PLT harvest, the necessity of distal peroneus longus-to-peroneus brevis (PL-to-PB) tenodesis for the potential preservation of donor ankle function and medial longitudinal arch alignment remains unclear. This study compared ankle function, donor-site morbidity, complications, and weight-bearing radiographic foot alignment after PLT harvest with and without distal tenodesis. Methods: Between January 2020 and December 2024, 92 primary ACLR cases using an ipsilateral PLT autograft were retrospectively screened; 60 patients with available bilateral weight-bearing comparative foot radiographs were included and categorized into a tenodesis group (n = 30) or a non-tenodesis group (n = 30). Ankle outcomes included American Orthopedic Foot and Ankle Society (AOFAS) Ankle–Hindfoot and Foot and Ankle Disability Index (FADI) scores, ankle range of motion (ROM), and donor-site complications. Radiographic alignment was assessed using Meary’s angle and calcaneal pitch angle on bilateral weight-bearing lateral foot radiographs, including side-to-side differences. Results: Follow-up duration was comparable between groups (18.5 ± 4.4 vs. 16.8 ± 3.4 months, p = 0.113). No patient demonstrated clinically relevant loss of ankle range of motion or strength at final follow-up. AOFAS (97.3 ± 4.9 vs. 95.0 ± 5.5, p = 0.078) and FADI (96.8 ± 5.2 vs. 95.3 ± 5.5, p = 0.091) scores were similarly high in the tenodesis and non-tenodesis groups, respectively. Sural nerve sensory disturbance occurred in 6/30 (20.0%) versus 5/30 (16.7%) patients (p = 0.739), and no harvest-site infection was observed. On weight-bearing radiographs, Meary’s angle and calcaneal pitch angle did not differ significantly between groups on the operated side (Meary: 7.99 ± 6.76 vs. 4.76 ± 6.32°, p = 0.061; calcaneal pitch: 23.19 ± 5.94 vs. 21.41 ± 4.64°, p = 0.201) or intact side (Meary: 7.05 ± 6.89 vs. 5.36 ± 6.11°, p = 0.320; calcaneal pitch: 23.33 ± 5.43 vs. 22.00 ± 4.48°, p = 0.305). Side-to-side differences were small and comparable (Δ Meary: 0.94 ± 3.97 vs. −0.60 ± 3.58°, p = 0.120; Δ calcaneal pitch: −0.14 ± 3.35 vs. −0.59 ± 3.29°, p = 0.603). Conclusions: Distal PL-to-PB tenodesis did not appear to provide measurable advantages in donor-ankle patient-reported outcomes or weight-bearing radiographic foot alignment compared with no tenodesis after PLT harvest for ACLR. Full article

Background/Objectives: Complementary medicines (CMs) are widely used in Australia, yet consumer beliefs about their safety and effectiveness often diverge from the scientific evidence. Contemporary statewide data from Victoria, particularly about these perceptions and underlying perception profiles, are limited. We therefore aimed to characterise CM use patterns and perceptions of it among Victorian adults and identify the demographic and use-related belief patterns. Methods: A cross-sectional survey was conducted in metropolitan and regional Victoria (November 2024–August 2025) among adults (≥18 years) who had used complementary medicines in the previous 12 months (N = 447). The questionnaire assessed CM use patterns, perceived effectiveness, safety, quality, perceived risk relative to prescription medicines, adverse events, and demographics. The analyses included descriptive statistics, χ² tests with multiple-comparison control, Spearman correlations, and a multivariable regression. An exploratory factor analysis (EFA) and latent class analysis (LCA) were used to identify the perception dimensions and distinct consumer profiles. Results: CM use was frequent (62.2% daily; 19.2% weekly) and often long term (>1 year, 55.0%). The most commonly used products were vitamin D (53.0%), multivitamins (39.8%), magnesium (34.5%), iron (33.8%), and vitamin C (30.0%). The perceptions were favourable: 77.3% rated CMs as effective, 90.4% as safe, and 60.3% as high quality; 78.5% perceived CMs to have lower side-effect risks than prescription medicines. Adverse events were reported by 12.3%. In the adjusted models, adults ≥ 65 years and monthly/occasional users were less likely to endorse “lower risk than prescription medicines” (aOR: 0.18; 95% CI: 0.06–0.51; aOR: 0.36, 0.18–0.72). East Asian respondents had lower odds of endorsing CM effectiveness than Caucasian/White respondents (aOR: 0.28, 0.11–0.72). Their perceived quality was higher among men (aOR: 1.73, 1.09–2.74) and adults aged 55–65 years (aOR: 3.81, 1.39–10.48). Conclusions: In this contemporary statewide Victorian sample, CM use was common and generally viewed positively, yet the comparative risk may be underestimated. Profiling perception patterns and identifying belief patterns by age, culture, and use intensity provides actionable targets for clinician/pharmacist counselling and culturally tailored education to support safer, evidence-aligned CM use. Full article

Social media platforms contain rich but noisy narratives of psychological distress, creating opportunities for early mental health risk detection. However, existing datasets capture heterogeneous constructs such as suicide risk severity, depression diagnosis, and DSM-5 symptom presence, and most prior models are trained and evaluated on a single corpus, limiting their clinical alignment and cross-dataset generalizability. In this study, we fine-tune a domain-specific long-document transformer, AIMH/Mental-Longformer-base-4096, for binary mental health risk detection (risk vs. no risk) using two clinically aligned Reddit datasets: the C-SSRS Reddit corpus and the eRisk 2025 depression dataset. To handle long user histories, we introduce an LLM-based summarization pipeline that compresses posts exceeding 2000 tokens while preserving mental health-relevant information. We also conduct a seven-configuration ablation study across combinations of three corpora (C-SSRS, eRisk, and ReDSM5) to examine how dataset semantics influence model performance. On a held-out C-SSRS + eRisk test set (n = 279), the proposed model achieves a mean balanced accuracy of 0.89 ± 0.01 across five random seeds, with a best run of 0.90 and a 5.74 percentage point improvement over the strongest baseline (TF-IDF + Random Forest). The model also shows strong cross-platform generalization, achieving BA = 0.78 on the depression-reddit-cleaned dataset (n = 7731) and BA = 0.85 (ROC-AUC = 0.92) on a Twitter suicidal-intention dataset (n = 9119) without additional fine-tuning. The ablation analysis shows that although a three-dataset configuration (C-SSRS + eRisk + ReDSM5) maximizes aggregate performance, the ReDSM5 labels encode symptom presence rather than clinical risk, creating a semantic mismatch. This finding highlights the importance of label compatibility when combining heterogeneous mental health corpora. Explainability analysis using Integrated Gradients and attention visualization shows that the model focuses on clinically meaningful expressions such as therapy references, diagnosis, and hopelessness rather than isolated keywords. These results demonstrate that clinically aligned long-context transformers can provide accurate and interpretable mental health risk detection from social media while emphasizing the critical role of dataset semantics in multi-corpus training. Full article