Search Results (11,807)

This manuscript presents a study on the dynamics of fiber Bragg grating formation using femtosecond radiation in the point-by-point inscription regime. By employing a multi-pass inscription technique, the dynamics of the photoinduced formation of modified regions (strokes) were investigated through an analysis of the evolution of the Bragg grating’s parameters. The results demonstrate a decrease in the average effective refractive index during the grating inscription. This study highlights the complexity of the structural transformations induced in the optical fiber core material by femtosecond laser radiation. Full article

Heart failure (HF) remains a major cause of mortality despite the advances in pharmacological treatment. Anticoagulation therapies, including Clopidogrel, Aspirin, Warfarin, and novel oral anticoagulants (NOACs) such as Apixaban, Rivaroxaban, Edoxaban, and Dabigatran, are frequently administered to HF patients to prevent thromboembolism and adverse, life-threatening outcomes (e.g., stroke and myocardial infarction). In these settings, drug resistance and variability in responsivity to therapeutic approaches are challenging issues. Recent studies suggest that non-coding RNAs, particularly microRNAs (miRs) may play a modulatory role in HF therapy context, affecting drug efficacy. Specific miRs have been associated with resistance to Clopidogrel (e.g., miR-223 and miR-26a), Aspirin (e.g., miR-19b-1-5p and miR-92a) and Warfarin (e.g., miR-133 and miR-137). Moreover, Digoxin, a cardiac glycoside acting also over bleeding risk, upregulates miR-132, which is involved in HF-associated cardiac alteration and hypertrophy. Evidence linking miR expression to NOAC pharmacodynamics, cardiac remodeling and regulation of the coagulation is growing. These findings highlight the need of deeply harnessing the potential of miRs as predictive biomarkers or therapeutic targets in HF. Improving the knowledge on the relationship between miR and anticoagulant drugs in HF patients will contribute to personalization of the anticoagulant therapies, aimed at enhancing patient responsivity and minimizing adverse effects, ultimately improving patient life quality. Full article

Generating non-standard fonts, such as running script (e.g., XingShu), poses significant challenges due to their high stroke continuity, structural flexibility, and stylistic diversity, which traditional component-based prior knowledge methods struggle to model effectively. While diffusion models excel at capturing continuous feature spaces and stroke variations through iterative denoising, they face critical limitations: (1) style leakage, where large stylistic differences lead to inconsistent outputs due to noise interference; (2) structural distortion, caused by the absence of explicit structural guidance, resulting in broken strokes or deformed glyphs; and (3) style confusion, where similar font styles are inadequately distinguished, producing ambiguous results. To address these issues, we propose a novel skeleton-guided diffusion model with three key innovations: (1) a skeleton-constrained style rendering module that enforces semantic alignment and balanced energy constraints to amplify critical skeletal features, mitigating style leakage and ensuring stylistic consistency; (2) a cross-scale skeleton preservation module that integrates multi-scale glyph skeleton information through cross-dimensional interactions, effectively modeling macro-level layouts and micro-level stroke details to prevent structural distortions; (3) a contrastive style refinement module that leverages skeleton decomposition and recombination strategies, coupled with contrastive learning on positive and negative samples, to establish robust style representations and disambiguate similar styles. Extensive experiments on diverse font datasets demonstrate that our approach significantly improves the generation quality, achieving superior style fidelity, structural integrity, and style differentiation compared to state-of-the-art diffusion-based font generation methods. Full article

Background: Stroke is a leading cause of seizures and epilepsy, both of which are linked to increased mortality, disability, and hospital readmissions. Early recognition and management of seizures in acute stroke are crucial for improving outcomes. Electroencephalogram (EEG) is not routinely used for post-stroke seizure monitoring and is typically initiated only after clinical suspicion arises, making bedside recognition essential. This scoping review aimed to map the existing literature on clinical methods used for identifying and observing early post-stroke seizures (EPSSs) at the bedside. Methods: We included literature involving adults with acute ischaemic stroke or primary intracerebral haemorrhage who were diagnosed or suspected of having inpatient EPSS. Searches were conducted in Medline, CINAHL, Embase, and the Cochrane Library for English-language publications up to April 2023. Eligible sources included primary research, case reports, systematic reviews, clinical guidelines, consensus statements, and expert opinion. Reference lists of included articles were also reviewed. Data were charted and synthesised to assess the scope, type, and gaps in the evidence. Results: Thirty papers met inclusion criteria: 17 research studies, six expert opinions, four case reports, and three clinical guidelines. Empirical evidence on clinical methods for seizure recognition and monitoring in acute stroke was limited. No studies evaluated the effectiveness of different approaches, and existing recommendations lacked detail and consensus. Conclusions: Accurate EPSS diagnosis is vital due to its impact on outcomes. This review highlights inconsistency in monitoring methods and a clear need for targeted research into effective clinical identification strategies in acute stroke care. Full article

In this study, cottonseed oil biodiesel and waste lard biodiesel were produced through a transesterification process and blended with conventional diesel at different ratios (B10 and B20). The performance and emission characteristics of these fuels were systematically evaluated in a single-cylinder, four-stroke, water-cooled diesel engine operating at speeds of 1000–1800 rpm under a constant 50% load. The physicochemical properties of the fuels were analyzed, and engine parameters including brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), and emissions of carbon monoxide (CO), hydrocarbon (HC), carbon dioxide (CO₂), and nitrogen oxides (NOx) were measured. The results demonstrated that, compared with diesel, biodiesel blends significantly reduced CO, HC, and CO₂ emissions. At 1800 rpm, the LB20 blend showed reductions of 31.03% in CO, 47.06% in HCs, and 19.14% in CO₂ relative to diesel. These reductions are mainly attributed to the higher oxygen content and lower hydrogen-to-carbon ratio of biodiesel, which promote more complete combustion. However, all biodiesel blends exhibited higher NOx emissions than diesel, with the increase being more pronounced at higher blend ratios. At 1800 rpm, the LB20 blend recorded the highest NOx emissions, which were 20.63% higher than those of diesel under the same condition. In terms of performance, biodiesel blends showed higher BSFC and lower BTE compared with diesel, mainly due to their lower calorific value and higher viscosity. The lowest BTE and the highest BSFC were both observed with the LB20 blend, at 22.64% and 358.11 g/kWh, respectively. Full article

Hemiparesis is a disabling consequence of stroke, causing abnormal gait patterns with biomechanical asymmetries. Gait mechanics for stroke survivors appear resistant to conventional rehabilitation. Auditory rhythmical cueing (ARC) represents an emerging intervention option. To determine effective gait interventions, objective measures of gait collected from real-world environments may be required in addition to standard clinical outcomes to aid understanding of gait mechanics. This study reports on the ability of wearable activity monitors to quantify an ARC intervention for fifty-nine stroke survivors randomised into an ARC gait and balance training programme or an equivalent training programme without ARC. Gait assessments were undertaken at baseline and at 6 weeks for 4-metre walks and continuously for 7 days following each home assessment using a wearable activity monitor. The success rates of data collection using the wearable activity monitors ranged from 64 to 95%. Forty-eight Digital Mobility Outcomes representing a broad range of gait mechanics were calculated. Visualisation of all DMOs using radar plots indicated changes from baseline in both groups, with individual data indicating large variability in response to the intervention and control programme. Including wearable activity monitors to evaluate gait interventions for stroke survivors provides additional value to traditional methods and aids understanding of individual responses; as such, they should be used for future intervention-based research. Full article

This study aims to investigate whether a combined action observation–motor imagery practice may enhance the effects of conventional physical rehabilitation in a stroke survivor population. A total of 8 (7 male, 1 female) post-stroke patients with upper limb hemiparesis were enrolled into a single-blinded, randomised, study. Five times per week for three weeks, four patients experienced 60’ conventional physical therapy, while the other 4 experienced 30’ conventional physical therapy and 30’ action observation–motor imagery practice. The Fugl-Meyer Assessment-Upper Extremity and the Wolf Motor Function Test scores from the baseline and post-physiotherapy were used to evaluate upper extremity motor function. Patients who received the AO + MI alongside conventional physical rehabilitation benefitted more than those who received only conventional physical rehabilitation. However, the sample size was very small (only eight participants), which reduces both the statistical power and the ability to generalise the results. Moreover, there was no follow-up; therefore, it is unclear whether the observed improvements lasted over time. Finally, some potentially confounding factors, such as stroke type or lesion site, were not statistically controlled. Notwithstanding these limitations, our findings may serve as a basis for future large-scale, well-controlled studies on AO + MI in stroke rehabilitation. Full article

Atrial fibrillation (AF) is a prevalent heart arrhythmia, characterized by an irregularly irregular rhythm and the absence of identifiable P waves on ECG. Given the loss of effective atrial contraction, AF carries a risk of serious complications. If untreated, AF can promote thrombogenesis, leading to stroke, systemic embolism (e.g., limb or organ ischemia), and myocardial infarction. These serious complications highlight the importance of understanding AF and assessing stroke risk to guide optimal management of this chronic arrhythmia. Congruent with recent technological developments, advanced imaging has emerged as a modality to better understand AF. This review highlights advanced imaging techniques and their advantages, with a focus on 4D flow MRI, a novel modality that enables visualization of blood flow patterns in three dimensions and provides unique insights into cardiac hemodynamics. It also synthesizes the current literature on key hemodynamic markers identified by 4D flow MRI, including blood flow stasis, wall shear stress, and vorticity. Quantifying these markers has improved predictive accuracy of future stroke risk in AF patients, allowing clinicians to risk stratifying their patients and optimize management. Finally, the review discusses potential future markers that may further refine our understanding of AF and inform patient care. Full article

The goal of this study is to analyze trends in clinical utilization of CT brain perfusion (CTP) across the past 10 years, during which there have been substantial changes in neuro-interventional and neuroimaging guidelines related to emergent stroke therapy, particularly intra-arterial mechanical thrombectomy. The Cosmos platform, a multi-institutional data aggregation tool containing health record data from billions of encounters, was used to retrospectively identify millions of patients with active clinical encounters during the study period (2015–2024). For each calendar quarter, numbers and proportions of active patients undergoing mechanical thrombectomy or brain CTP were obtained using billing code queries. CTP utilization per 100,000 active patients grew slowly from Q1-2015 to Q3-2017, ranging from 4.32 to 9.45, but beginning in Q4-2017, coinciding with the publication of landmark stroke trials, CTP utilization began to increase more rapidly, almost 4-fold higher as determined through segmented linear regression, reaching 61.24 per 100,000 in Q4-2024. Although causation cannot be proven in this study, the observed increases in CTP utilization likely reflect rapid adoption of evidence-based adjustments to stroke triage guidelines after eligibility for mechanical neurointervention had been widened to 24 h from symptom onset. Full article

Differentiating genuine hemiplegic gait (HG) in stroke survivors from hemiplegic-like gait voluntarily imitated by healthy adults (MHG) is essential for reliable assessment and intervention planning. Treadmill-based gait data were obtained from 79 participants—39 stroke patients (HG) and 40 healthy adults—instructed to mimic HG (MHG). Forty-eight spatiotemporal and force-related variables were extracted. Random Forest, support vector machine (SVM), and logistic regression classifiers were trained with (i) the full feature set and (ii) the 10 most important features selected via Random Forest Gini importance. Performance was assessed with 5-fold stratified cross-validation and an 80/20 hold-out test, using accuracy, F1-score, and the area under the receiver operating characteristic curve (AUC). All models achieved high discrimination (AUC > 0.93). The SVM attained perfect discrimination (AUC = 1.000, test set) with the full feature set and maintained excellent accuracy (AUC = 0.983) with only the top 10 features. Temporal asymmetries, delayed vertical ground reaction force peaks, and mediolateral spatial instability ranked highest in importance. Reduced-feature models showed negligible performance loss, highlighting their parsimony and interpretability. Supervised machine learning algorithms can accurately distinguish true hemiplegic gait from mimicked patterns using a compact subset of gait features. The findings support data-driven, time-efficient gait assessments for clinical neurorehabilitation and for validating experimental protocols that rely on gait imitation. Full article

Background/Objectives: The associations between plasma homocysteine and pre-stroke antithrombotic medication and the effects these have on clinical outcomes of patients undergoing ischemic stroke remains unclear. This study aimed to evaluate the combined effect of plasma homocysteine levels and the use of pre-stroke antithrombotic medication on the clinical outcomes of patients experiencing first-ever and recurrent ischemic strokes. Methods: Anonymized data from consecutive patients who experienced ischemic stroke and had their plasma homocysteine levels evaluated were retrospectively analyzed. Pre-stroke antithrombotic medication status, clinical variables potentially influencing homocysteine concentrations, and stroke recurrence data were collected. Clinical outcomes were assessed using the modified Rankin Scale 3 months after stroke onset. The association between hyperhomocysteinemia and clinical outcomes was evaluated using logistic regression models. Results: Hyperhomocysteinemia was significantly associated with unfavorable clinical outcomes (adjusted odds ratio [aOR], 1.32; 95% confidence interval, 1.04–1.69) in the 2767 patients who were analyzed. The absence of pre-stroke antithrombotic medication use was associated with unfavorable outcomes (aOR range, 1.29–1.56), specifically in patients with first-ever stroke (aOR range, 1.45–1.64) but not in patients with recurrent strokes (aOR range, 0.70–1.04). Conclusions: Hyperhomocysteinemia and non-use of pre-stroke antithrombotic medication were significantly related to unfavorable outcomes in patients experiencing their first-ever stroke. These findings might provide prognostic insights into stroke management and patient stratification. Full article

The paper presents an innovative theoretical concept of a bio-inspired soft gripper system with two parallel jaws, a fixed and a mobile one. It is conceived for gripping fragile or soft objects with complex, irregular shapes that are easily deformable. This novel gripper is designed for handling small objects of masses up to 0.5 kg. The maximum gripping stroke of the mobile jaw is 13.5 mm. The driving motor is a pneumatic muscle, an actuator with inherently compliant, spring-like behavior. Compliance is the feature responsible for the soft character of the gripper system, ensuring its passive adaptability to the nature of the object to be gripped. The paper presents the structural, kinematic, static, and dynamic models of the novel gripper system and describes the compliant behavior of the entire assembly. The results of the dynamic simulation of the gripper have confirmed the attaining of the imposed motion-related performance. Full article

Background/Objectives: Stroke often results in lasting upper limb deficits. Mirror visual feedback (MVF) supports motor recovery, and electromyography-triggered electrical stimulation (ES) could enhance engagement. However, the effects in healthy older adults, age-matched to typical patient cohorts, remain insufficiently understood. We tested MVF and MVF + ES using functional near-infrared spectroscopy. Methods: Seventeen right-handed older adults performed left-wrist flexion under three visual conditions: circle fixation, viewing the right hand at rest, and mirror viewing, with/without electrical stimulation to the right-wrist flexors time-locked to left-forearm electromyography. Oxygenated hemoglobin (oxy-Hb) was recorded over the bilateral inferior frontal gyrus (IFG), precentral gyrus (PrG), postcentral gyrus (PoG), supramarginal gyrus (SMG), superior parietal lobule (SPL), and supplementary motor area. Effects were assessed with linear mixed-effects models (stimulation × visual condition); pairwise comparisons of estimated marginal means used Fisher’s least significant difference. Left-forearm electromyography verified comparable effort across conditions. Results: Linear mixed-effects models revealed left-lateralized increases in oxy-Hb, most prominently under mirror viewing with stimulation. Post hoc tests showed high oxy-Hb in the left IFG, PrG, PoG, SMG, and SMA. The left EMG did not differ. Conclusions: In healthy older adults, MVF paired with EMG-triggered ES enhances frontoparietal–motor engagement beyond MVF alone, with recruitment shaped by visuo–proprioceptive congruence. These findings support mechanistic plausibility and motivate dose–response optimization and patient-focused trials testing behavioral transfer in stroke. Full article

This paper investigates the effects of using 10% v/v (E10) and 30% v/v (E30) ethanol–gasoline blends on spark ignition (SI) engine fuel consumption, brake-specific fuel consumption, brake thermal efficiency, combustion parameters and exhaust gas temperature. The 30% v/v ethanol–gasoline blend was designed not to exceed the octane number (RON and MON) of the regular commercially available reference fuel (E10); therefore, the knock resistance of the reference and research fuel does not differ significantly. The tests were conducted on an AVL internal combustion engine test cell using a four-stroke, four-cylinder, turbocharged SI engine with direct injection and a compression ratio of 12.2:1. The engine was manufactured in 2022, and it is the latest commercially available version currently in production. Engine tests were conducted under stoichiometric conditions (when possible) at loads ranging from 2–20 bar brake mean effective pressure and engine speeds ranging from 1000–6000 rpm, and the fuel consumption, brake-specific fuel consumption, combustion parameters, exhaust gas temperature and brake thermal efficiency were measured using the two different ethanol–gasoline blends. Test results showed that the higher concentration ethanol–gasoline blend—due to its lower density, lower heating value and higher latent heat of vaporization—had increased fuel consumption, brake-specific fuel consumption and decreased brake thermal efficiency, while exhaust gas temperature also decreased (at 2500 rpm 12 bar BMEP, the differences were 11%, 6.6%, −0.78% and −3.7%, respectively). Peak combustion pressures were identical under the same operating conditions, but the peak combustion temperature of E30 was on average 3% lower. Full article

Background/Objectives: In view of demographic change and the increase in chronic illnesses, home care poses a considerable challenge. Telemedical technologies offer considerable potential for improving the quality of care and relieving the burden on family caregivers. With this study, we aim to develop appropriate training strategies for the use of telemedical applications in home care, focusing on the specific requirements of patients with dementia, heart failure, diabetes mellitus, chronic obstructive pulmonary disease, and stroke. Methods: A comprehensive survey was conducted among 31 family caregivers to record their experience with digital technologies and to analyze caregiver acceptance of these technologies and barriers to their use. The survey comprised 29 questions, including a mix of multiple-choice, Likert scale, and open-ended questions. The internal consistency of the questionnaire was high (Cronbach’s alpha = 0.8876). Results: The results show that although 32% of respondents already use digital technologies, there is a significant need for training and support. Key barriers identified include a lack of technical skills (cited by 45% of respondents), limited access to suitable devices (38%), and privacy concerns (35%). In addition, 90% of respondents expressed a willingness to participate in training programs. Conclusions: Based on the survey results, evidence-based recommendations are provided for the design of training programs tailored to the individual needs of family caregivers. Through a targeted combination of e-learning modules, webinars, and practical exercises, family caregivers can be empowered to take full advantage of telemedical technologies and thus significantly improve the quality of care at home. The results underscore the importance of overcoming technical barriers and providing comprehensive training to ensure the effective use of telemedicine in home care. Full article