Abstract: We present a strengthened collider-facing extension of the uploaded Quantum Information Copy Time (QICT) program to compressed Higgsino searches at \( \sqrt{s}=13 \) TeV. The underlying QICT manuscript identifies its theorem-level core as a copy-time definition \( \tau_\text{copy} \), a Liouvillian-squared susceptibility \( \chi^{(2)}_Q \), and a conserved-charge speed-limit bound; the infrared and phenomenological sections are explicitly conditional closures. We therefore do not claim a theorem-level Higgsino prediction. Instead, we construct a fully explicit QICT-to-collider closure map, validate a detector-level surrogate against public CMS and ATLAS compressed-Higgsino reach anchors, perform a quantitative public-contour recast, propagate dominant surrogate uncertainties, and isolate a new branch-transition observable \( B_{\ell t} = N_{\ell t} / (N_{\ell t} + N_{\text{track}}) \). Within this strengthened framework, the residual post-public-limit search prior remains two-branched: an ultra-compressed branch near \( m_{\tilde{\chi}_1^\pm} \approx 200-240 \) GeV with \( \Delta m^\pm \sim 0.35-0.9 \) GeV, and a few-GeV branch near \( m_{\tilde{\chi}_1^\pm} \simeq 150-220 \) GeV with \( \Delta m \simeq 2-6 \) GeV. The manuscript is deliberately modest about logical status, but it is now quantitative, reproducible, and falsifiable.

Abstract: The study continues the authors' previous research on The Impact of CO₂ Laser Treatment on Kevlar^® KM2+ Fibres Fabric Surface Morphology, using direct laser surface texturing of polymers. SEM and Confocal microscopy image analysis of Kevlar^® KM2+ 440D and 600 are performed to analyze the results. In the course of the study, the surface topography of Kevlar^® KM2+ fabric is optimized by adjusting the continuous wave (CW) CO2 laser parameters so that it increases the surface roughness before graphene coating and resistance to yarn pulling out of the fabric without destroying the unique structure of Kevlar® KM2+ fibres. Experimental study measurement data indicate an increase in surface roughness by 50%, and a set of laser parameter variants has been obtained that allows increasing the yarn pulling out force of KM2+ woven fabric from the fabric in the range from 50% to 99%, compared to untreated fabric. The results obtained are potentially applicable for the production of composite materials against projectile fragmentation.

Abstract: Open-vocabulary 3D object detection (OV-3DOD) is crucial for real-world perception, yet existing monocular methods are often limited by predefined categories or heavy reliance on external 2D detectors. In this paper, we propose CLIP-Mono3D, an end-to-end one-stage transformer framework that directly integrates vision-language semantics into monocular 3D detection. By leveraging CLIP-derived semantic priors and grounding object queries in semantically salient regions, our model achieves robust zero-shot generalization to novel categories without requiring auxiliary 2D detectors. Furthermore, we introduce OV-KITTI, a large-scale benchmark extending KITTI with 40 new categories and over 7,000 annotated 3D bounding boxes. Extensive experiments on OV-KITTI, KITTI, and Argoverse demonstrate that CLIP-Mono3D achieves competitive performance in open-vocabulary scenarios.

Abstract: This work investigates the performance improvement of a four-probe ballistic rectifier on bilayer graphene (BLG) through the formation of an energy gap under a perpendicular electric field. For this purpose, exfoliated BLG was deposited on oxidized p+-Si and structured into an asymmetric cross junction with 90 nm wide channels. The junction consists of a straight voltage stem (contacts U,L) and slanted current injectors (contacts 1,2). The differential conductance of the stem, g_UL, as a function of back-gate bias, V_BG, reveals clear indications of energy gap formation and lateral depletion zones at the edges of the channel. The _DC characteristic of the ballistic rectifier, V_UL(I₁₂), shows an increase of the output voltage VUL with increasing V_BG. We attribute this to reduced diffuse scattering at the rough edges when the lateral depletion zones form smooth barriers.

Abstract: Electric vehicles (EVs) have fundamentally changed the noise, vibration, and harshness (NVH) landscape of automotive powertrains. In the absence of masking inter-nal-combustion-engine noise, harmonic components such as gear whine, electric-motor orders, and inverter-related tones become more perceptible and more critical to vehicle re-finement. This review synthesizes the current state of the art in harmonic NVH engineer-ing for electric drivetrains, focusing on the interactions between gear geometry, manufac-turing variability, electromechanical coupling, structural transfer, and human sound per-ception. Classical mechanisms of gear-mesh excitation are revisited together with emerg-ing EV-specific challenges, including long-wavelength flank deviations, ghost orders, lightweight housing dynamics, and psychoacoustic sound-quality requirements. The re-view further examines recent progress in predictive and data-driven approaches, includ-ing machine-learning-based gear-noise modeling, digital-twin concepts, and virtual NVH assessment workflows. Overall, the literature shows that harmonic NVH engineering in EVs is evolving from a conventional gear-noise problem into a multidisciplinary sys-tem-level task integrating gear dynamics, manufacturing science, structural acoustics, electric-drive control, psychoacoustics, and data-driven optimization. This review pro-vides a structured synthesis of these developments and identifies key research gaps and future directions for the next generation of refined electric drivetrains.

Abstract: Monkey pox virus has caused two major outbreaks in the past 4 years. Transmission of the virus is via close person-to-person contact, which suggests that the virus is of high virulence and pathogenicity. This work reports evidence gleaned from an in-house MATLAB open reading frame finder applied to the GenBank assembled genome of monkey pox virus. Using the data in the output file of the software that includes gene sequence, gene length, gene molecular weight, amino acid sequence of gene, protein molecular weight, and isoelectric point of protein, two significant results were observed. Firstly, profiling for genes of length more than 60 base pair reveal a total of 255 candidate genes, of which more than 200 are of protein length between 20 to 80 plus amino acids. Secondly, plotting the protein isoelectric point and molecular weight in a theoretical 2D protein gel plot shows that there are clusters of viral proteins of different molecular weight at different pH values from pH 4 to 12. In particular, there is a large cluster of proteins between pH 8 and 10, which suggests that alkaline blood pH may promote monkey pox virus virulence. However, absence of many proteins in the pH range of around 5, points to a potential therapeutic window where modulation and control of blood pH at 5, may provide symptomatic relief for the patient, while awaiting the patient’s immune response to degrade the viral particles in the blood.

Abstract: Massera and Schaffer [\textit{Ann. Math. (2), 1958}] derived a breakthrough upper bound for the Clarkson angle between two nonzero vectors in a normed linear space, which was later improved by Maligranda [\textit{Am. Math. Mon., 2006}]. Pecaric and Rajic [\textit{Math. Inequal. Appl., 2007}] extended Maligranda's inequality to finitely many nonzero vectors. We derive a non-Archimedean version of Massera-Schaffer-Maligranda-Pecaric-Rajic inequality.

Abstract: The digital age has expanded social media and online forums, allowing free expression for nearly 45% of the global population. Yet, it has also fueled online harassment, bullying, and harmful behaviors like hate speech and toxic comments across social networks, messaging apps, and gaming communities. Studies show 65% of parents notice hostile online behavior, and one-third of adolescents in mobile games experience bullying. A substantial volume of abusive content is generated and shared daily, not only on the surface web but also within dark web forums. Creators of abusive comments often employ specific words or coded phrases to evade detection and conceal their intentions. To address these challenges, we propose a hybrid deep learning model that integrates BERT, CNN, and LSTM architectures with a ReLU activation function to detect abusive language across multiple online platforms, including YouTube comments, online forum discussions, and dark web posts. The model demonstrates strong performance on a diverse and imbalanced dataset containing 77,620 abusive and 272,214 non-abusive text samples (ratio 1:3.5), achieving approximately 99% across evaluation metrics such as Precision, Recall, Accuracy, F1-score, and AUC. This approach effectively captures semantic, contextual, and sequential patterns in text, enabling robust detection of abusive content even in highly skewed datasets, as encountered in real-world scenarios.

Abstract: Fostering teachers’ professional agency is central to promoting relevant chemistry learning, as it enables future teachers to design accurate, evidence-informed and meaningful learning in a rapidly changing scientific landscape. This article summarises 25 years of evidence-based chemistry teacher education (EBTE) within the LUMA co design ecosystem. Situated in the Department of Chemistry, the Chemistry Teacher Education Unit collaborates closely with scientists and co designs pedagogical content knowledge (PCK) and Technological Pedagogical Content Knowledge (TPASK) courses that are both scientifically up to date and pedagogically effective. Developing strong PCK grounded in chemistry research, chemistry education research and classroom practice, strengthens scientific literacy, enabling teachers to translate often complex chemical ideas into accessible and relevant forms for learners. The EBTE model connects theory and practice, supports cross boundary collaboration and prepares research-oriented designer teachers for the demands of modern science, sustainability, digitalisation and AI. Co design within the co-design-based research (CoDBR) framework enhances teachers’ professional, relational and epistemic agency by enabling research informed development and fostering close collaboration with chemists and societal partners through LUMAlab Gadolin. Agency driven co design within the LUMA ecosystem can build the capacity of student teachers, practising teachers and students to engage confidently with contemporary chemistry, and contribute to a scientifically literate and sustainable future.

Abstract: Introduction: Propofol is one of the most commonly used intravenous anesthetics worldwide and is considered safe for all age groups. However, there have been reports that propofol can induce severe atrioventricular block in humans, and several studies have shown that propofol hinders or prevents the inducibility of arrhythmias during electrophysiological studies (EPS) and radiofrequency (RF) ablation. Objectives: Verify whether propofol prevents or hinders the inducibility of arrhythmias during EPS and RF ablation procedures in children with Wolff-Parkinson-White Syndrome. Methods:We conducted a retrospective observational cohort study including 45 pediatric patients aged 0–18 years. Patients were identified through a review and analysis of a database of individuals with Wolff–Parkinson–White syndrome who were referred for electrophysiological study and/or radiofrequency ablation at the Electrophysiology Laboratory of the Institute of Cardiology (IC/FUC) in Porto Alegre over the past five years (2019-2024). Patients with prior ablation, structural heart disease, or ongoing antiarrhythmic therapy were excluded. The patients were divided into two groups and designated as group S (who received sedation) or group G (who received general anesthesia). Sedation (group S) was performed with midazolam (0.08–0.2 mg/kg), fentanyl (0.1–0.2 μcg/kg), and propofol 50–60 µg/kg/min in continuous infusion. General anesthesia (group G), in turn, was performed with sevoflurane at an average dose of 2% (1 MAC according to age). Results: From 4,874 invasive electrophysiology procedures performed during the study period, 45 involved pediatric patients with WPW. The sedation group (n=29) had significantly older patients (14.6±2.5 vs 10.3±2.8 years, p<0.001) with higher weight (65.9±16.3 vs 41.2±7.8 kg, p<0.001) compared to the general anesthesia group (n=16). Arrhythmia was successfully induced in 15/29 (51.7%) patients in the sedation group compared to 13/16 (81.2%) in the general anesthesia group (p=0.062, Fisher's exact test). Although this difference did not reach statistical significance, it represents a clinically relevant 29.5% lower induction rate in the sedation group. Post-hoc power analysis revealed the study was underpowered (49.8%), suggesting a possible Type II error. Analysis of the "procedure room time" revealed a longer duration in the general anesthesia group (97.8±36.7 vs 67.8±24.4 minutes), and this difference was statistically significant (p = 0.002). Conclusions: This study compared propofol-based sedation with sevoflurane-based general anesthesia in pediatric WPW patients. While sedation with propofol did not show a statistically significant reduction in arrhythmia inducibility, there was a concerning trend toward lower induction rates (29.5% difference) that may be clinically relevant. The study's limited statistical power (49.8%) suggests these findings should be interpreted cautiously, and larger prospective studies are needed to definitively establish whether propofol affects arrhythmia inducibility in this population. Propofol remains a viable option for these procedures, but clinicians should be aware of the potential for reduced inducibility, particularly in cases where arrhythmia induction is critical for diagnosis and treatment.

Abstract: The global food supply chain (FSC) wastes nearly one-third of all food produced—over 2 billion tonnes annually—highlighting the need for technologies to reduce food loss and waste (FLW). Simultaneously, existing solutions are often evaluated in isolation, limiting cross-comparison and informed decision-making. This research develops an explainable decision support system (XDSS) that combines the Best–Worst Method (BWM) and Stochastic Multi-criteria Acceptability Analysis for Group Decision-Making (SMAA-2), providing probabilistic rankings that incorporate preference uncertainty. The framework assesses 100 technology-based strategies for reducing FLW across five criteria: geographic fit, product category, FSC stage, stakeholder role, and technology used. Each scenario undergoes 50,000 Monte Carlo simulations with a fixed seed of 12345 to enable reproducibility. Trade-offs are formalised through penalty functions and weight vectors, while hit-and-run sampling explores feasible weight regions. Example user queries demonstrate how qualitative preferences translate into rank-acceptability profiles: Query 1's maximum rank-1 acceptability is 62%, and Query 2's is 74%. The XDSS provides transparent, robust, and context-sensitive recommendations that support evidence-based technology adoption by SMEs and local authorities. By enabling reproducible and explainable prioritisation, the system advances UN’s Sustainable Development Goal (SDG) 12.3, which aims to reduce FLW along the FSC.

Abstract: First described in the 1980s, mentorship has evolved from an emerging idea to a well-established culture. As such, a concomitant understanding of "mentor", "mentee", and "mentorship" is indicated—something currently lacking. In response, this work examines the author's fourteen types of mentoring relationships, over 39 years, regarding outcomes of peer-reviewed publications. The results demonstrate that mentors are most effective when they possess applicable experience compared to their mentees, experience considered by the mentees as having the potential to aid in their ability to solve a problem. In this respect, mentees require a particular self-awareness to identify that they have a solvable problem, anticipate a solution, and can effectively utilize the mentor's experience. Therefore, mentees are not equivalent to protégés, who, with their mentor, develop their careers and psychosocial competencies. The basis of mentorship is problem-solving for mentees, in contrast. Consequently, most productively, mentees choose their mentors, rather than having them assigned. Therefore, much of the effort in organizing matches for advancing the mentorship culture can be misguided and unproductive. In contrast, effective mentorship matching aids a relevant self-awareness in mentees and provides them with options for selecting mentors who are willing and able to share their pertinent problem-solving knowledge.

Abstract: Background: Obesity is a risk factor for increased blood pressure, in which the relation-ship is mediated by the action of various pro-inflammatory mediators such as myelop-eroxidase (MPO), xanthine oxidase (XO), and oxidized low-density lipoprotein (Ox-LDL). The objective of this research is to evaluate the contribution serum MPO, xanthine oxidase XO, and Ox-LDL as determinants of blood pressure in adults with abdominal obesity. Methods: A cross-sectional study was conducted involving 86 adults with abdominal obesity. Waist circumference (WC), fasting serum glucose (FSG), MPO, XO, and serum Ox-LDL were measured. The contributions of these parameters to systolic blood pressure (SBP) and diastolic blood pressure (DBP) were then assessed. Results: Multivariate analy-sis showed that the determinants of SBP were WC, FSG, MPO, and XO (Beta = 0.418, 0.328, 0.282, 0.248 respectively, all p< 0.05; adjusted R2 = 41.5%), while the determinants of DBP were FSG, WC, and MPO (Beta = 0.310, 0.284, 0.274, respectively, all p< 0.05; adjusted R2 = 24.8%). Conclusions: MPO has a role as a determining factor for SBP and DBP, XO has a role as a determining factor for SBP, while Ox-LDL does not have a significant role in blood pressure.

Abstract: Efficiently adapting large language models (LLMs) to specialized domains remains challenging due to substantial computational and memory requirements. In this work, we introduce CoDES (Context-efficient Domain Ensemble System), a framework designed to enhance small language models through context-efficient domain adaptation and weighted parameter ensembling. CoDES integrates context-specific fine-tuning, parameter-efficient adaptation using Low-Rank Adaptation (LoRA), and completion-only supervision to focus training on answer tokens while preserving pretrained capabilities and reducing computational cost. To further improve performance and robustness, the framework combines multiple fine-tuned models through weighted parameter ensembling. We evaluate CoDES on biomedical multiple-choice question answering using the MedMCQA benchmark. Experimental results show that the ensemble of tuned small models achieves 74.8% accuracy, approaching the performance of a much larger 72B-parameter model (77.1%). While requiring substantially fewer computational resources. The proposed framework offers several practical advantages, including achieving comparable performance, lower energy consumption, faster inference, and flexible adaptation to specialized domains. By reducing the reliance on extremely large models, CoDES provides a scalable and resource-efficient pathway for deploying high-performing language model systems in knowledge-intensive environments where models must be frequently updated with evolving domain information.

Abstract: Contemporary philosophy of mind is beginning to rehabilitate Arthur Schopenhauer as a proto-phenomenologist whose metaphysics of the will—once divested of its ontological commitments—provides thick descriptions of embodied agency, self-structure, and intersubjective resonance. This article validates this thesis through a four-stage naturalized reconstruction: (1) Schopenhauer’s "world-knot" and the unity of body and will are interpreted as phenomenal facets of minimal self-models within the framework of the Free Energy Principle (Friston, 2010). (2) His fragmented theory of the self is situated within Gallagher’s Pattern Theory of Self (2013). (3) His ethics of compassion is framed as a precursor to a Pattern Theory of Compassion. (4) Finally, affective criticality is employed to explain Schopenhauer's diagnosis of pessimism as a form of predictive dysregulation. Methodologically, the paper circumvents the pitfall of superficial analogies by adopting a weak methodological naturalism, utilizing cognitive models as a functional grammar for phenomenal material without reductively truncating the metaphysical deep structure.

Abstract: Objective: To assess the psychometric properties of the Academic Motivation Scale (AMS) in a sample of university students from Ecuador Method: This instrumental research examines the construct validity through confirmatory factor analysis and the reliability of the AMS. Sample: 1007 subjects (n=403 women, 39.9%) from the Salesian Polytechnic University of Ecuador. Results: Regarding the construct validity of the AMS, confirmatory factor analysis indicated that the model demonstrated a good fit to the data, with CMIN or χ2(303) = 1171.948, p ¡ 0.001, CFI = 0.987 (robust), RMSEA = 0.053 (confidence interval between 0.050 and 0.057), and SRMR = 0.047. The Cronbach’s Alpha (α) and McDonald’s Omega (ω) reliability coefficients were ≥0.80. Conclusion: Given the psychometric properties presented, the use of the AMS-E is recommended for evaluating factors of academic motivation in the Ecuadorian population.

Abstract: This study analyzes four Indonesian presidential elections (2009-2024) as a time series analysis within the event study framework on IHSG volatility. We examine the influence of macroeconomic, trading activity, and VIX channels, as well as whether their impact differs between pre-election and post-election periods. The methodology employs Principal Component Analysis (PCA) to construct channel variables and multiple linear regression with interaction terms on a baseline 5-month window before and after election month. The results consistently show that global risk sentiment (VIX) is the only significant positive driver of volatility. There is no significant interaction effects were found in either the 5-month, indicating that the influence of these channels is not statistically different between the pre-election and post-election periods. We conclude that Indonesian stock market volatility around presidential elections is predominantly driven by global risk sentiment, which overshadows domestic political transitions and associated local market dynamics.

Abstract: Background: Post-stroke upper-limb spasticity can cause pain, hinder passive care, and lead to secondary musculoskeletal complications. Current minimally invasive treatments have important limitations. Cryoneurolysis, which creates a controlled cold lesion of peripheral nerves, may offer a partially reversible focal denervation alternative. Methods: We conducted a feasibility case series in the outpatient department of a rehabilitation center. Three adults with chronic post-stroke hemi-paresis and a non-functional spastic upper limb underwent ultrasound- and nerve stimula-tion-guided cryoneurolysis of the musculocutaneous, median, and/or ulnar nerves. All had demonstrated a positive response to diagnostic nerve blocks beforehand. Feasibility outcomes in-cluded completion of planned nerve targets, tolerability under local anesthesia, absence of serious adverse events, and completion of 6-month follow-up. Secondary outcomes were Modified Ash-worth Scale (MAS), qualitatively assessed passive joint mobility (video-documented), pain meas-ured by visual analogue scale, sensory testing, and electroneuromyography (ENMG). Results: All procedures were completed as planned. Treatment was well tolerated under local anesthesia, and no serious adverse events occurred. MAS decreased by at least 2 points in targeted patterns, with immediate improvement in passive mobility; these effects persisted at 6 months. Pain remained unchanged in two participants and improved in one. Sensory testing at 6 weeks was stable. ENMG findings were heterogeneous, including reduced ulnar sensory action potential amplitude and biceps denervation activity in one participant. Conclusions: In this small series, cryoneurolysis for post-stroke upper-limb spasticity was feasible and associated with sustained tone reduction and improved passive mobility. Larger controlled studies are required to better define safety, optimize targeting strategies, and assess patient-centered outcomes.

Abstract: This study investigates the structural performance of a redesigned AAR Type E knuckle coupler using finite element analysis (FEA). The modified knuckle incorporates geometric reinforcement in critical load-bearing regions together with a hollow internal structure aimed at reducing component weight while maintaining structural integrity. Two numerical models were developed: a component level model, in which the knuckle was analyzed independently, and an assembly-level model that integrates the knuckle with the coupler body to capture realistic load transfer through contact interactions. Both models were subjected to a tensile draft load of 650,000 lbs (2670 kN) in accordance with Association of American Railroads (AAR) standards. The component-level analysis predicted peak von Mises stresses of approximately 1050 MPa, primarily concentrated near the pivot pin hole and curved pulling face regions. When contact interactions between the knuckle and coupler body were included in the assembly model, the representative peak stress decreased to approximately 950 MPa, corresponding to a stress reduction of about 10% due to load redistribution across the assembly interfaces. Highly localized stress peaks at sharp geometric edges were identified as numerical stress singularities and were excluded from engineering interpretation. The results demonstrate that assembly-level finite element modeling provides a more realistic representation of load transfer mechanisms in railway coupler systems and is essential for accurately predicting stress distribution and identifying critical fatigue-prone regions. These findings provide valuable insights for improving the structural reliability and design optimization of freight rail coupler components.

Abstract: The paper presents the cutting tool-life of uncoated and DLC-coated inserts used for machining of aluminum-lithium components used in the structure of Airbus A350 aircraft. Based on the collected data, a feed-forward artificial neural network with two hidden layers was created, trained using the Bayesian Regularization (trainbr) algorithm in MATLAB. The obtained results indicate a high performance of the model, with a low mean square error (MSE) and a correlation coefficient R &gt; 0.98, which reflects an excellent generalization capacity and a close correlation between the actual and estimated values. The regression plot and error analysis confirmed the accuracy of the predictions made by the network. The internal parameters of the algorithm, such as the gradient and μ, provided additional information regarding the optimization process.