Abstract: The chemical agents, the injection modes and displacement characteristics of chemical compound flooding, consisting of plugging agent, oil displacement agent, and viscosity reducer, were investigated by laboratory experiments for the target heavy oil reservoirs after multiple cycles of huff and puff. The performance of oil displacement agent, viscosity reducer and plugging agent were evaluated and the formulation and concentration were optimized. The oil displacement effects and displacement characteristics of different injection modes were studied by two-pipe models. The experiment results showed that the alternating injection of oil displacement agent and viscosity reducer yielded better results than their mixed injection, and small segments alternating injection achieved the highest recovery, which playing a role in gradual adjustment of the profile and its seepage resistance was greater. The dosage of the plugging agent should be no less than 0.5 pore volume (0.5 PV). There was a balance between the viscosity increase of polymer and the reduction of interfacial tension of viscosity reducer. The larger the dosage of the oil displacement agent, the higher the capacity to expand the swept volume and to adjust the profile enhanced, the larger the maximum liquid production ratio between high and low permeability layer, but the shorter of the liquid production reverse duration. The larger the dosage of the viscosity reducer, the greater the water cut decrease, but the smaller of maximum liquid production ratio. For chemical compound flooding in the Zhong'er block in Gudao oilfield, the recommended injection mode was 0.1 PV plugging agent + 2000mg/L oil displacement agent + 0.5wt% viscosity reducer, with small segments of oil displacement agent followed by viscosity reducer at an injection slug ratio of 6:4, which providing an efficient and economical chemical compound flooding technology solution for field application.

Abstract: Multidrug resistance (MDR) remains a major pathophysiological barrier to effective anthracycline-based chemotherapy, including daunorubicin (DNR), in the treatment of leukemia. However, population-level measurements of drug uptake do not resolve variability in uptake kinetics among individual leukemia cells, which may influence intracellular drug accumulation and therapeutic response. In this study, real-time DNR uptake was quantified at the single-cell level using a microfluidic biochip that enabled long-term cellular retention and continuous monitoring. Both wild-type drug-sensitive leukemia cells and a multidrug-resistant mutant overexpressing the P-glycoprotein (P-gp) efflux pump were examined. Kinetic analysis revealed that DNR uptake in drug-sensitive cells was well described by a single dominant uptake process, whereas uptake in MDR cells required a model incorporating two kinetically distinct processes. In both cell populations, pronounced cell-to-cell variation was observed in uptake rates and intracellular drug retention, indicating substantial functional heterogeneity within phenotypically similar cells. This variability persisted following treatment with an MDR inhibitor and obscured differences between inhibitor-treated and untreated cells when uptake was compared across different single cells. To overcome this limitation, a same-single-cell analysis (SASCA) approach was employed, enabling direct comparison of DNR uptake in the same individual cell before and after inhibitor exposure, thereby revealing enhanced intracellular DNR retention and accelerated uptake kinetics following inhibition. Together, these results demonstrate that real-time single-cell kinetic analysis reveals functionally relevant heterogeneity in multidrug-resistant leukemia cells and provides insight into the pathophysiology of MDR that cannot be obtained from population-averaged measurements.

Abstract: Livestock grazing strongly influences terrestrial ecosystems and plays a critical role in carbon dynamics, with outcomes highly dependent on grazing management. High-frequency rotation (HFR) grazing has been proposed to reduce the uneven spatial grazing distribution commonly associated with low-frequency rotation (LFR) grazing, potentially altering forage production and soil organic carbon (SOC). However, most ecosystem models used to assess SOC dynamics do not explicitly represent uneven grazing distribution, limiting their ability to evaluate management effects. To address this limitation, we enhanced the MEMS ecosystem model by incorporating a spatially explicit grazing distribution through the introduction of discrete spatial units and key environmental drivers, including forage availability and quality, and distance to water. Using remote sensing-derived enhanced vegetation index (EVI), we verified the simulated grazing distribution using an experimental rangeland site in Oklahoma. We tested the model’s sensitivity to grazing frequency under different management (stocking rate, timing, and duration) and climate (typical, dry, and wet) scenarios. Our results indicate that uneven grazing distribution leads to distinct spatial patterns of forage production and SOC. Notably, significant differences in field-average production and SOC between HFR and LFR emerged under heavy intensity grazing, where HFR sustained higher SOC stocks and productivity than LFR. These findings highlight the importance of spatially explicit modeling in understanding grazing distributions, suggesting that HFR grazing may be beneficial mostly under heavy intensity grazing. Our study offers actionable guidance for designing future grazing management experiments to address this critical knowledge gap and advance carbon management strategies.

Abstract: Nowadays, most water meters are mechanical and intended to be installed on pipes completely filled with water. But the pipelines of a water supply network may contain air, which poses a metrological problem: if this air flows through the domestic intakes, it can propel the moving part of meters, resulting in an overestimation of water consumption. Of how much? There is a surprising lack of field data on this topic. So, the case of one house is reported: it is located at the top of a steep and sparsely occupied street, with water typically supplied for a few hours per day. The house's meter (multi-jet) was estimating a huge and erratic consumption: several times more than what would be normally expected on average, and with some daily peaks exceeding the built storage capacity (underground cistern plus roof tank). After one year of monitoring, including the installation of a few devices, it is concluded that: (1) the house's meter was affected by air in the water supply network (most likely for different reasons, of which three are discussed); (2) a small air-release valve installed just upstream from the meter did not solve the problem; (3) another mechanical meter (single-jet) installed just downstream was also affected by air (although to a lesser extent), and (4) reliable estimates of water consumption were finally obtained with an ultrasonic meter installed at the domestic intake (and with a mechanical meter installed at the roof tank's outlet). Thus, the case reported emphasizes the need to study more how air in pipelines affects mechanical water meters, and to sometimes consider alternatives for measuring domestic water consumption.

Abstract: Intra-articular injection of autologous Platelet Rich-Platelet Plasma (PRP) is commonly employed as a non-surgical option for treating early-stage knee osteoarthritis (OA). Placebo-controlled clinical trials show sustained improvements in knee pain and function in most, but not all patients. Although several hypotheses have been put forward, the reasons for inconsistent responses remain unclear. Exosomes, a class of lipid membrane-bound extracellular otherwise known as small extracellular vesicles (sEVs), are a prominent component of PRP. sEVs are thought to mediate many of PRP’s therapeutic effects by carrying complex molecular cargos that regulate gene expression when taken up by cells in osteoarthritic joints. We hypothesized that patient-to-patient variations in sEV protein content correlate with patient responses to PRP. To test this, we compared the proteomes of PRP-derived sEVs from 3 patients who reported significant improvement in symptoms from baseline to 12 weeks post-injection (responders) versus 3 who did not (non-responders). 48 proteins identified by mass spectrometry were significantly different between Responders and Non-Responders. Taken together, these findings indicate that a patient’s responsiveness to PRP treatment could be associated with EV protein cargo composition.

Abstract: Fused Deposition Modeling (FDM) components require accurate identification of printing parameters to support reliable quality assessment and scalable reverse‑engineering workflows. This study evaluates whether mechanical response curves can be used to infer critical manufacturing parameters—specifically build direction, layer thickness, and infill density. Force–displacement and stress–strain data obtained from tensile tests were converted into image‑based representations and classified using individual and ensemble machine learning models. The influence of applying a moving‑average filter to smooth the curve‑derived images was also examined. Ensemble approaches, particularly AdaBoost, achieved higher accuracy and robustness across the evaluated variables, with the best results obtained from unfiltered stress–strain images. Under limited‑data conditions, ensemble models generally outperformed individual classifiers, while Multilayer Perceptron and Support Vector Machine models showed more stable but less accurate behavior. Overall, the findings demonstrate the feasibility of predicting FDM printing parameters directly from mechanical‑curve‑derived images, enabling a non‑destructive approach suitable for scalable reverse‑engineering and improved traceability within additive manufacturing processes.

Abstract: Denoising-based CT reconstruction methods can suppress high-frequency textures that are relevant for subtle lesion visibility. Motivated by hybrid convolution–attention designs such as CTLformer, this paper proposes a frequency-constrained denoising framework that preserves diagnostically relevant textures while reducing noise. The method introduces a dual-domain loss combining spatial fidelity with frequency-band constraints computed using discrete cosine transform representations. Evaluations on 52,000 paired slices from two low-dose CT datasets show that, relative to CNN-only and attention-only baselines, the proposed approach increases PSNR by 0.7–1.1 dB while maintaining higher high-frequency energy consistency. Reader-oriented texture metrics also improve by 8%–14% in regions with fine structural patterns.

Abstract: Accurate and rapid determination of moisture content in waste sludge is essential for optimizing dewatering processes, reducing disposal costs, and minimizing environmental impact. This study investigates the use of Fourier Transform Near-Infrared (FT-NIR) spectroscopy combined with Partial Least Squares Regression (PLS-R) for predicting the moisture content of dewatered sludge. A total of 96 sludge samples, with dry matter contents ranging from 12.4% to 24.6%, were collected from two treatment plants. FT-NIR spectra were acquired over the 800–2500 nm range, and chemometric models were developed to correlate spectral information with gravimetrically determined moisture content. The optimized PLS-R model demonstrated strong predictive performance, achieving a cross-validated coefficient of determination (R²CV) of 0.87, a root mean square error of cross-validation (RMSECV) of 0.92%, and a residual predictive deviation (RPD) of 2.73. Independent test set validation confirmed the robustness of the model (R²test = 0.88, RMSEP = 0.88%, RPD = 2.92), supported by strong calibration results (R² = 0.95, RMSEE = 0.60%, RPD = 4.46). Principal component analysis indicated that spectral variability observed in sludge samples was primarily associated with WWTP-specific characteristics, reflecting moisture–organic matter interactions. These results demonstrate that FT-NIR spectroscopy is a promising tool for sludge moisture prediction.

Abstract: Studying how people manage and use their time not only deepens our understanding of individual routines but also highlights the roles they play within their household and society. The Survey of Health, Ageing, and Retirement in Europe (SHARE) Wave 8 developed a novel time expenditure module enabling cross-national, longitudinal analysis of daily activities among adults aged 50 and over. This paper presents the module’s design and initial findings. We provide methodological guidance essential for accurate data interpretation and present descriptive results by country, gender, age, and education. Our findings reveal substantial cross-national variation in time allocation patterns. While sleep (7-8.5 hours) and leisure activities (3.5-5.5 hours) dominate daily schedules across all countries, women spend approximately an hour more per day on household chores than men, with even greater gaps of 78 to 109 minutes in Southern Europe. Gender differences in care work are negligible, with the notable exception of Israel where women provide substantially more care. In contrast, men spend more time in paid work and leisure. Educational gradients are most pronounced for paid work: tertiary-educated older adults spend nearly three times as long in employment (119 minutes) compared to those with below-secondary education (44 minutes). Time use shifts substantially with age: paid work drops from 207 to 18 minutes between ages 50-64 and 65-79, while leisure and sleep increase. Contrary to stereotypes of older adults’ lives, these patterns reveal both continuity and change. With subsequent waves, this module will illuminate whether these patterns represent stable features of later life or transitional states that evolve with health, partnership status, and proximity to end of life.

Abstract: Demodex mites are common commensals of mammalian skin, but under certain conditions, they can cause severe skin diseases. This study analyzed the presence, diversity, and phylogenetic relationships of Demodex species in two wolf subspecies from southern Europe to determine whether species-level differences exist between wild and domestic canids after thousands of years of divergence. A total of 1,400 hair samples from 140 wolves were analyzed using qPCR targeting mitochondrial 16S rRNA and nuclear 18S rRNA genes. Overall, 37% of wolves were positive for Demodex DNA, with a higher prevalence in Italian (46%) than in Iberian (36%) wolves. The lip and chin areas were the most reliable sampling sites. Four Demodex species were identified in wolves: D. injai and D. canis (associated with dogs), and D. folliculorum and D. brevis (associated with humans). Co-infestations involving multiple Demodex species were recorded for the first time in wild canids. These results challenge the long-held belief of strict host specificity in Demodex mites. The discovery of Demodex species associated with both humans and dogs in wolves supports the idea that host-switching and ecological interactions have occurred throughout the evolution of canids and humans. Such cross-species transfers may have taken place during the early domestication of dogs. However, given the isolated history of the two southern wolf populations, it is more probable that these findings result from recent interspecific transmission events, likely facilitated by ecological overlap with domestic animals and human environments. Future genomic studies will be essential for clarifying the evolutionary relationships within the genus Demodex and its host associations.

Abstract: Background/Objectives Atrial fibrillation/flutter (AF) and liver cirrhosis both present a large disease burden internationally, with millions of adults afflicted. There is evidence of a link between these two diseases; however, the prevalence and impact of liver cirrhosis in patients with and without AF have not been extensively detailed. With the utilization of a large national database, we examined the relationship between liver cirrhosis and AF and the effects on hospital outcomes. Methods We conducted a nationwide review from 2016 to 2020 utilizing the Nationwide Inpatient Sample (NIS) database. Patients ≥ 18 years old with newly diagnosed atrial fibrillation or atrial flutter were identified. They were then further stratified into patients with and without liver cirrhosis. Characteristics and comorbidities were identified, evaluating in-hospital mortality as the primary outcome. Results A total of 3,866,486 patients with a primary diagnosis of AF were included. Patients with liver cirrhosis were younger in age (mean age 68.32 vs 74.36 years old), the majority were White (74.1%), followed by Black (10.2%), and Hispanic (10.5%). They had more comorbidities, such as diabetes (45.1% vs 37.3%, p<0.001), hypertension (78.5% vs 83.6%, p<0.01), and chronic kidney disease (22.1% vs 19.5%, p<0.001) when compared to patients without liver cirrhosis. Patients with liver cirrhosis had a higher risk of in-hospital mortality (OR=1.84, p<0.001), hypovolemic shock (OR=2.17, p<0.001), gastrointestinal bleed (OR=2.42, p<0.001), requiring blood transfusions (OR=1.84, p<0.001), and requiring ICU-level of care with intubation (OR=1.214, p<0.001), central line (OR=1.33, p<0.001), arterial line (OR=1.32, p<0.001) and vasopressors (OR=1.61, p<0.001). Moreover, patients with liver cirrhosis had a lower risk of having an acute cerebrovascular accident (OR=0.431), transient ischemic attack (OR=0.475), or pulmonary embolism (OR=0.68) while hospitalized (p<0.001). Conclusion Our results have demonstrated a remarkable relationship between AF and liver cirrhosis, with significantly increased morbidity and mortality reported in individuals with both conditions compared to AF without liver cirrhosis.

Abstract: Dielectric engineered plasmonic nano-hole arrays (NHAs) provide an effective approach for controlling subwavelength light confinement. Here, we investigate wavelength compression in aluminum NHAs filled with three different dielectric materials such as Al₂O₃, MoO₃, and TiO₂ under illumination by a 1.5 µm lightwave. The hole radius varies from 300 nm to 500 nm to analyze the combined effects of geometry and dielectric environment on the plasmonic response. The NHAs filled with Al₂O₃ exhibit a pronounced and monotonic increase of the compressed wavelength with decreasing hole radius, indicating strong geometric tunability of the dominant plasmonic mode. Meanwhile, the structures filled with MoO₃ or TiO₂ show weak wavelength variations over the same radius range. Spatially resolved analysis at these nano-holes reveals nearly position-independent wavelength squeezing for Al₂O₃, whereas noticeable spatial variations appear for MoO₃ and TiO₂ at hole radii of 450 nm and 400 nm, respectively. The observed wavelength compression is attributed to hybrid plasmonic modes originating from the interplay between in-hole–like compressed cavity modes and localized surface plasmon polaritons. Our findings demonstrate how dielectric composition tunes wavelength compression in plasmonic NHAs, offering practical guidelines for designing the near-infrared plasmonic devices.

Abstract: Background/Aim: Hepatitis D virus (HDV) infection is the most severe form of viral hepatitis but is under-recognized. We evaluated HDV screening frequency and clinical characteristics of HDV-positive patients in our liver center in the United States. Method: Patients with chronic hepatitis B (CHB) evaluated between January 2021 and December 2023 were included. For those tested anti-HDV(+), HDV RNA was performed and clinical data were recorded. Results: Among 1,337 (M=716, F=621) CHB patients, 93.3% were foreign-born. The cohort included 74.9% Asians, 12.3% Blacks, 9.1% Whites and 1.3% Hispanics. HDV screening significantly increased after 2011 reflecting an increase in HDV awareness. Patients aged 18-40 years had the highest screening rate of 58%. Overall, 13 (1.95%) were tested HDV positive and 11 were repeatedly HDV RNA(+). PWID was noted in 5 of 11. Despite low HBV DNA levels, all had ≥stage 2 fibrosis, and 7 had advanced stage 3-4 disease. After a median follow-up of 8.75 years, 8 (73%) developed hepatic decompensation and 4 had hepatocellular carcinoma. Conclusion: HDV screening reached 51.3% among our predominantly foreign-born CHB patients. The high prevalence of advanced fibrosis at diagnosis underscores the importance of HDV screening. Early diagnosis and effective therapy are urgently needed for this challenging disease.

Abstract: Background/Objectives: Autism spectrum disorder (ASD) is biologically heterogeneous, and immune-linked variation may coincide with differences in tryptophan–kynurenine pathway (KP) metabolism. Here, we report a targeted urinary profile of KP metabolites, NAD (nicotinamide adenine dinucleotide), and neopterin in a Bulgarian pediatric ASD cohort to describe within-cohort patterns and associations. Methods: Second-morning, acid-stabilized spot urine was collected from 73 children with ASD in Bulgaria (3–13 years; 57 males; 16 females). No contemporaneous neurotypical control group was enrolled; therefore, laboratory-provided reference limits are reported only as contextual benchmarks and are not interpreted as ASD-specific abnormalities. Tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), quinolinic acid (QUIN), NAD, and neopterin were quantified and derived indices were computed (KYN/TRP × 1000; QUIN/KYNA). Non-parametric statistics, Benjamini–Hochberg false discovery rate (FDR) correction, and Spearman correlation analyses were applied. Results: Neopterin was strongly associated with QUIN and KYN in creatinine-normalized data (QUIN: ρ = 0.59, q36 = 2.64 × 10-7; KYN: ρ = 0.54, q36 = 3.69 × 10-6); these associations persisted when reconstructed as absolute concentrations (e.g., QUIN_abs: ρ = 0.68, q36 = 2.69 × 10-10) and after partial Spearman correlation controlling for spot creatinine (partial ρ = 0.46, q = 2.52 × 10-4). One NAD value was &lt;LOQ and was imputed as ½LOQ; sensitivity analyses did not materially change inference. Conclusions: In this ASD-only cross-sectional dataset, urinary neopterin levels co-varied with urinary KYN and QUIN and with KP indices. Clinical interpretation and causal inference require controlled and longitudinal studies with richer covariate capture.

Abstract: Objective collapse models are often implemented so that collapse acts only on the fermionic (matter) sector, while bosonic fields do not undergo fundamental collapse. In generalized trace dynamics (GTD), spontaneous localization is expected to arise when the trace Hamiltonian has a significant anti-self-adjoint component. In this note we show, starting from the STM-atom (spacetime-matter atom) trace Lagrangian written in terms of two inequivalent matrix velocities Q̇₁ and Q̇₂, that the purely bosonic subsector admits a self-adjoint Hamiltonian, whereas the fermionic sector carries an intrinsic anti-self-adjoint contribution. The key structural input is that making the trace Lagrangian bosonic requires insertion of two unequal odd-grade Grassmann elements β₁ ≠ β₂. Assuming natural adjoint properties for these elements, we compute the trace Hamiltonian explicitly via trace-derivative canonical momenta (with bosonic and fermionic variations treated separately) and isolate the resulting anti-self-adjoint term. This provides a first-principles mechanism, within GTD, for why only fermionic degrees of freedom act as collapse channels.

Abstract: The hypothesis that antibiotics evolved from or co-opted bacterial intercellular signaling molecules predicts that signaling-active compounds should exhibit physicochemical properties favorable for drug development. We explored this prediction through a comparative cheminformatics analysis of 74 bacterial signaling molecules — comprising 48 small-molecule diffusible signals, 17 peptide autoinducers and intracellular messengers, and 9 antibiotics with documented signaling activity — against 71 randomly selected drug-like molecules. Small-molecule signaling molecules showed significantly higher Lipinski Rule-of-5 compliance than random drugs (95.8% vs. 73.2%; Odds Ratio = 8.40, 95% CI: 1.86–38.1, p = 0.001; Bonferroni-adjusted p = 0.009), while peptide autoinducers and intracellular messengers showed near-zero compliance (5.9%), confirming that the enrichment is specific to small-molecule diffusible signals. Predicted membrane permeability was over 2-fold higher for small-molecule signals (72.9% vs. 32.4% classified as “Good”), and enrichment was observed across six of seven drug-likeness filters (Enrichment Factors 1.12–1.31). We identified 10 signaling-active molecules with favorable profiles whose direct antibiotic activity has not been systematically tested; six are free of PAINS alerts. This analysis was conducted with substantial AI assistance, molecular properties were compiled from databases rather than computed de novo, and results require independent verification with validated cheminformatics tools. We present these findings as a hypothesis-generating study to stimulate experimental testing of the signaling-first triage concept for antibiotic discovery. For all abbreviations and acronyms used throughout this manuscript, please refer to the Glossary section.

Abstract: Hypnosis and hypnotherapy have emerged as powerful, evidence-based therapeutic modalities with demonstrated efficacy across a broad spectrum of mental and somatic health conditions. This comprehensive review synthesizes the latest research from 2018 to 2026, examining the neurobiological mechanisms, clinical applications, and therapeutic outcomes of hypnotic interventions. Recent meta-analytic evidence reveals effect sizes ranging from medium to large (d = 0.5 to 2.72) for various conditions, with particularly robust evidence for chronic pain management, depression, anxiety disorders, and perioperative care. Neuroimaging studies have elucidated the neural substrates of hypnotic analgesia and emotional regulation, demonstrating modulation of the anterior cingulate cortex, default mode network, and pain matrix. Randomized controlled trials consistently show that hypnotherapy achieves outcomes comparable to or exceeding cognitive behavioral therapy for depression, with sustained benefits extending up to 3.5 years post-treatment. Importantly, hypnotic interventions demonstrate excellent safety profiles with no significant adverse events reported across studies. This review establishes hypnosis as a credible, hope-inspiring healing modality that warrants broader integration into mainstream clinical practice for patients seeking effective, non-pharmacological treatment options.

Abstract:

Background: Lassa fever remains a major public health challenge in West Africa, particularly in Nigeria where recurrent outbreaks continue to place pressure on health systems. Facility-based analyses are important for understanding morbidity and mortality trends in endemic regions. Objective: To assess morbidity and mortality trends of Lassa fever among patients managed at Irrua Specialist Teaching Hospital over a five-year period. Methods: A retrospective hospital-based cross-sectional study was conducted at Irrua Specialist Teaching Hospital, Edo State, Nigeria. Case records of all patients with confirmed Lassa fever managed between January 2018 and August 2022 were reviewed. Data were extracted using a structured checklist and analysed using SPSS version 23. Descriptive statistics were used to summarise socio-demographic, clinical and outcome variables. Results: A total of 191 Lassa fever case records met the eligibility criteria. The estimated mean age was 26.0 ± 18.8 years, with most patients younger than 30 years. There was a slight male predominance (52.4%). Admissions peaked in 2018 (47.1%) and declined thereafter. Most patients presented within five days of symptom onset (46.1%), although 17.8% presented after more than 11 days. The most common symptoms were fever (91.1%), vomiting (50.3%), headache (46.6%), and anorexia (46.1%), while haemorrhagic manifestations were uncommon (4.7%). The overall case fatality rate was 13.6%. Most hospital admissions lasted 6–15 days. Conclusion: Lassa fever remains an important cause of hospital admission and mortality in Edo State. Although mortality in this cohort was within previously reported hospital-based ranges, delayed presentation and non-specific clinical features remain challenges for early diagnosis. Strengthening surveillance systems, improving early detection, and enhancing infection prevention practices are essential to reducing Lassa fever morbidity and mortality in endemic settings.

Abstract:

Background and Objectives: The thoracolumbar fascia (TLF) has been implicated in low back pain, but imaging-based characterization in specific degenerative lumbar pathologies—particularly in surgical cohorts—remains limited. To evaluate TLF thickness on Magnetic resonance imaging (MRI) and Ultrasound (US) across common lumbar pathologies, examine associations with age, body mass index, disability, and assess MRI–US agreement for TLF thickness. Materials and Methods: In this prospective single-centre cohort, adults scheduled for elective lumbar surgery underwent preoperative US (short- and long-axis at L3) and review of routine lumbar MRI (axial and sagittal T1-weighted measurements at L3) using standardized protocols. Disability was assessed using the Oswestry Disability Index (ODI). Group comparisons, correlation analyses, and intraclass correlation coefficients were used to evaluate between-diagnosis differences, patient-factor associations, and MRI–US agreement. Results: Thirty-seven patients were eligible (15 lumbar spinal stenosis, 5 discs herniations, 4 spondylolisthesis, 2 scoliosis, 9 revision surgeries, 2 trauma comparators). Median TLF thickness was 0.86 mm (0.16–1.40) on axial MRI, 1.12 mm (0.47–2.33) on sagittal MRI, 2.38 mm (1.01–5.91) on US short-axis, and 2.87 mm (1.12–5.74) on US long-axis. Axial MRI thickness differed across groups (p=0.010), driven by thinner measurements in trauma versus disc herniation (p=0.031); no significant group effects were observed on sagittal MRI or US. Age correlated positively with axial MRI thickness (p=0.021). No significant correlations were detected between ODI and TLF thickness on MRI or US. MRI–US agreement was poor, indicating the modalities are not interchangeable for TLF thickness measurement. Conclusions: TLF thickness measured on MRI and US did not consistently differentiate diagnostic groups and was not associated with disability. Thickness estimates differed substantially by modality, with poor MRI–US agreement. Larger studies with standardized acquisition and reliability testing are needed to clarify the clinical and mechanistic relevance of TLF imaging in degenerative lumbar disease and to determine whether it can support phenotype-based stratification within degenerative spine disease.

Abstract: Emergency evacuation in complex and dynamic building environments requires robust and adaptive routing strategies capable of responding to evolving hazards, blocked passages, and changing crowd behaviour. Most existing evacuation planners rely on static geometric representations and lack semantic awareness of the environment, limiting their ability to perform informed re-planning and backtracking when routes become unsafe. This paper proposes a neuro-symbolic evacuation planning framework that integrates Lifelong Planning A* (LPA*) with ontology-driven semantic reasoning and a Bidirectional Long Short-Term Memory (BiLSTM) prediction model. The building’s spatial and semantic knowledge is represented using the Web Ontology Language (OWL) and Resource Description Framework (RDF), enabling automated inference of implicit connections and enforcement of safety policies. The BiLSTM model learns temporal patterns from ontology-consistent evacuation trajectories and provides guidance for remaining-cost estimation and early prediction of routes likely to require backtracking, which is combined with a bounded semantic heuristic to preserve admissibility and optimality guarantees. Simulation results in a multi-floor academic building show that the proposed BiLSTM-guided semantic LPA* framework reduces average evacuation time by up to 9.6%, decreases node expansions by up to 32%, and increases evacuation success rates to 96.2% compared with a purely semantic baseline. The BiLSTM model also achieves strong predictive performance, with a test AUC of 0.92 for backtracking prediction and a next-state accuracy of 87.1%. The proposed framework provides a scalable, explainable, and real-time solution for personalised and policy-compliant evacuation guidance under rapidly evolving emergency conditions.