Abstract: This article presents the development and validation process of a qualitative data collection instrument aimed at analysing Natural Sciences teachers’ perceptions of practical work in lower secondary education (third cycle) in Portugal. The methodological approach combined a systematic literature review following PRISMA guidelines with an analysis of relevant curricular frameworks and legal documents. Based on the triangulation of these sources, a semi-structured interview guide was constructed, validated by a panel of five experts from four Portuguese public universities, and tested through a pilot interview. The final instrument comprises seven dimensions and fourteen subdimensions, totalling 44 items. It demonstrated methodological rigour and practical applicability for qualitative data collection and analysis. Findings indicate that the instrument enables a comprehensive exploration of teachers’ practices and perceptions regarding practical work, offering a valuable contribution to the research on didactics of science and to the professional development of teachers.

Abstract:

This paper examines the position of Makkah and Madinah in the global hospitality industry through the dual lens of Maqāṣid al-Sharīʿah and Islamic epistemology. Using empirical data drawn from official statistics (Ministry of Hajj and Umrah), policy documents (Saudi Vision 2030 reports), and critical scholarship, the study analyses how rapid commercial development has transformed the hospitality landscape of the holy cities. It shows how luxury hotel construction has displaced local communities, particularly from historic neighbourhoods surrounding the al-Masjid al-Ḥarām, relocating them to peripheral urban areas. The concept of epistemicide is employed as a critical theoretical lens, underscoring how Islamic traditions of hospitality are being overwritten by global capitalist logics. By integrating Maqāṣid al-Sharīʿah with tourism theories such as destination lifecycle, carrying capacity, and experiential tourism, this study contributes to religious tourism scholarship by offering a normative yet transferable framework for evaluating hospitality in sacred destinations. The findings highlight the need to balance capacity expansion with equity, spirituality, and sustainability in the future development of Makkah and Madinah.

Abstract: Electric-vehicle (EV) diffusion exhibits nonlinear, path-dependent dynamics shaped by interacting economic, technological, and social constraints. This paper develops a unified hybrid-systems framework that captures these complexities by integrating microfounded household choice, capacity constrained firm behavior, local network spillovers, and multi-level policy intervention within a Filippov differential-inclusion structure. Households face heterogeneous preferences, liquidity limits, and network-mediated moral and informational influences; firms invest irreversibly under learning-by-doing and profitability thresholds; and national and local governments implement distinct financial and infrastructure policies subject to budget constraints. The resulting aggregate adoption dynamics feature endogenous switching, sliding modes at economic bottlenecks, network-amplified tipping, and hysteresis arising from irreversible investment. We establish conditions for the existence of Filippov solutions, derive network-dependent tipping thresholds, characterize sliding regimes at capacity and liquidity constraints, and show how network structure magnifies hysteresis and shapes the effectiveness of local versus national policy. Optimal-control analysis further demonstrates that national subsidies follow bang--bang patterns and that network-targeted local interventions minimize the fiscal cost of achieving regional tipping. The framework provides a complex-systems perspective on sustainable mobility transitions and clarifies why identical national policies can generate asynchronous regional outcomes. These results offer theoretical foundations for designing coordinated, cost-effective, and network-aware EV transition strategies.

Abstract:

This paper advances Coherence Thermodynamics for understanding systems composed purely of information and coherence. It derives five laws of coherence thermodynamics and applies them to two case studies. Three canonical modes of coherent informational systems are developed: Standing State, Computation Crucible, and Holographic Projection. Each mode has its own dynamics and natural units, with thermodynamic coherence defined as the reciprocal of the entropy–temperature product. Within this theory, reasoning is proposed to emerge as an ordered, work‑performing process that locally resists entropy and generates coherent structure across universal features.

Abstract: Background: Major depressive disorder (MDD) is increasingly viewed through a neuroplasticity lens, with developmental synaptic pruning emerging as a potential core liability. Genetic evidence implicates pruning pathways, while rapid-acting antidepressants like ketamine promote synaptogenesis, suggesting that excessive early elimination leaves circuits vulnerable to later stress. Few computational models, however, capture the specific MDD pattern of latent fragility collapsing under perturbation, followed by recovery via limited plasticity enhancement.Methods: An overparameterized feed-forward neural network (∼396,000 parameters) was trained on a noisy four-class Gaussian cluster task to represent dense early connectivity. Excessive pruning (95% magnitude-based weight removal, per-layer) simulated adolescent over-elimination. Fragility was assessed under input perturbations and internal neural noise (post-activation Gaussian injections at varying intensities) modeling neuromodulatory disruption. Recovery involved gradient-guided regrowth (50% of pruned connections, prioritized by loss-reduction potential) followed by fine-tuning. Comparisons included random regrowth and a sparsity sweep to identify thresholds.Results: The intact network showed robust performance across conditions. Pruning induced sharp collapse (clean accuracy ∼51%, standard noisy ∼43%), with pronounced sensitivity to internal noise (moderate stress accuracy ∼31%) exceeding input noise effects. Gradient-guided regrowth plus fine-tuning restored near-baseline accuracy (clean/standard ∼100%) and robustness (combined stress ∼97%) despite ∼47% persistent sparsity. Targeted regrowth slightly outperformed random under high stress. A critical threshold emerged around 93% sparsity, beyond which combined-stress performance dropped abruptly (>44 percentage points).Conclusions: Excessive pruning generates threshold-like intrinsic fragility consistent with stress-triggered MDD relapse, while targeted, limited synaptogenesis efficiently compensates without full density restoration. These findings support a pruning-mediated plasticity deficit as a mechanistic framework for MDD vulnerability and highlight the therapeutic potential of activity-dependent plasticity enhancement. The model provides a testable scaffold for linking polygenic pruning risk to circuit-level decompensation and rapid treatment response.

Abstract: Movement disorders frequently arise as secondary manifestations of systemic, metabolic, toxic, infectious, vascular, autoimmune, and iatrogenic conditions, yet they remain underrecognized in clinical practice. This narrative review aims to provide a comprehensive and clinically oriented overview of secondary movement disorders, emphasizing common and uncommon etiologies, underlying pathophysiological mechanisms, diagnostic challenges, and management considerations. A broad literature review was conducted using PubMed, Scopus, and Google Scholar, focusing on movement disorders associated with medications, stroke, infections, metabolic abnormalities, demyelinating and autoimmune diseases, neurodegenerative conditions, and systemic illnesses. Secondary movement disorders encompass a wide spectrum of hyperkinetic and hypokinetic phenomenologies, including tremor, dystonia, chorea, myoclonus, parkinsonism, ataxia, and mixed syndromes, often reflecting disruption of basal ganglia–thalamo–cortical and cerebellothalamic networks. Drugs—particularly antipsychotics, antiseizure medications, antidepressants, and antiemetics—represent the most frequent cause, while vascular lesions, infections, and metabolic disturbances constitute important and potentially reversible contributors. Neuroimaging and ancillary testing play a pivotal role in identifying secondary etiologies and distinguishing them from primary neurodegenerative or functional disorders. Recognition of secondary movement disorders is essential, as prompt identification and treatment of the underlying cause may lead to symptom resolution or significant improvement. This review highlights the importance of systematic evaluation, interdisciplinary collaboration, and individualized management strategies, reinforcing the concept that movement disorders often reflect multisystem disease rather than isolated motor pathology.

Abstract: The Unified Evolution Equation (UEE) provides a common analytical framework that unifies reversible quantum dynamics (unitary evolution), dissipative dynamics of open systems (GKLS), and transport effects induced by boundaries and resonances (zero-area resonance kernels) as a single notion of time evolution of states. The purpose of this paper (UEE_01) is to define the UEE as a mathematically consistent analytical foundation and to establish its well-posedness, including existence, uniqueness, and invariance of states.We formulate the theory by taking the observable algebra as a von Neumann algebra and the state space as its predual, and by characterizing physically admissible time evolutions as preduals of normal, unital, completely positive maps. The UEE is formally expressed as a sum of reversible, dissipative, and resonance-transport generators. Rigorously, solutions are defined in the mild sense as trajectories generated by a strongly continuous completely positive and trace-preserving (CPTP) semigroup.Given the analytical data of the UEE, we construct the reversible, dissipative, and resonance-transport components separately as CPTP group or semigroup evolutions. Using a Chernoff/Trotter-type product formula, we prove that the composite limit evolution exists, forms a CPTP semigroup, and that its generator coincides with the closure of the sum of the individual generators. As a consequence, invariance of the set of normal states and the well-posedness of the UEE are rigorously established.This work provides a solid analytical foundation for the unified GKLS+$R$ representation employed in subsequent papers, ensuring consistency between physical modeling and operator-theoretic dynamics.

Abstract:

Ti alloys are widely used in several fields, such as aerospace and biomedical, due to their high mechanical properties under severe loading conditions. Recently, the interest in these materials produced by additive manufacturing process has increased, but intensive research should be done to better characterise their properties. This work aims to study and compare the effect of surface properties, internal defects, microstructure, hardness and Hot Isostatic Pressing (HIP) treatment or in-Vacuum Heat Treatment (VHT) on fatigue properties of a Ti6Al4V produced by Selective Laser Melting (SLM) and Electron Beam Melting (EBM) additive manufacturing technologies. The samples were fully characterised using a wide range of techniques, in terms of microstructure (optical microscopy and SEM), mechanical properties (hardness mapping) and surface texture (confocal microscopy). The internal defects were evaluated using an image-based analysis approach. The uniaxial fatigue endurance limit properties were determined by a Dixon-Mood staircase approach and the failed samples near the fatigue limit were characterised by fracture surface and defect area analysis. A study of the applied load on the flaw areas was carried out to unveil the root causes of fatigue failure. The results showed that the fatigue properties of the as-printed samples were mainly determined by the surface roughness, whereas in the machined samples the internal defect dimension ruled the fatigue resistance of the material. The HIP used as a post-printing treatment is effective in substantially reducing the presence of internal pores, although local microstructural changes can take place only in the case of smooth surface. In conclusion, when properly developed in their melted parameters, both EBM and SLM technologies produce similar mechanical performance on comparable roughness levels, thus finding shared fields of application and fully eligible for the production of structural components.

Abstract:

The predominant forms of inflammatory bowel disease (IBD) are Crohn's disease and ulcerative colitis, which occur in approximately 0.5-1% of the World population. Alterations in the microbial flora (dysbiosis) are considered the primary precipitating factor in IBD. Because antibiotics are major disruptors of the microbiome, it was hypothesized that different antibiotic classes might induce distinct alterations in gut flora, reflected in positive or negative associations with IBD incidence at the population level. Average yearly consumption was calculated from ECDC reports (2004-2023) for the major antibiotic classes, which cover 99.87% of total antibiotic consumption across 30 European countries. Data were compared with age-stratified IBD incidence (15–39 years) estimated for 2021. Ordinal logistic regression modeled the association between antibiotic class proportions and IBD-incidence categories, entering each antibiotic class separately as a continuous predictor. Pearson correlation analyses were conducted to assess linear associations, and Kruskal-Wallis tests were applied to compare incidence categories. Statistical significance was set at p < 0.05. Tetracyclines (J01A), narrow-spectrum penicillin (J01CE, J01CF), and sulfonamides (J01E) showed a significant positive association with IBD incidence, indicating that higher consumption was associated with higher national incidence. In contrast, cephalosporins, macrolides, aminoglycosides, and quinolones showed significant negative associations, suggesting links to lower national incidence levels. Different antibiotic consumption patterns across 30 European countries may be associated with the IBD incidence.

Abstract:

In-vitro dissolution study is crucial for quality assurance and stability, serving as a surrogate test for evaluating in-vivo performance of a drug. The dissolution procedure should be designed using an appropriate validated approach, depending on the type of dosage form. Dissolution testing is crucial to regulatory decision-making in a number of aspects. Conventional formulations have validated regulatory-compliant dissolution methods, conversely novel drug formulations like nanoparticles and microparticles lack standard validated procedures for the same. The present article provides information about the various compendial and non-compendial methods available for in-vitro dissolution testing of nano-formulations including the selection of dissolution media, different factors affecting the release, advancements in the dissolution procedures and also included the recently developed marketed nano-formulations.

Abstract: Background: Despite highly efficacious long-acting injectable pre-exposure prophylaxis (LAI-PrEP) achieving >99% efficacy in clinical trials, people who inject drugs (PWID) experience near-zero population-level HIV prevention effectiveness. We hypothesized that nested structural barriers, not pharmacological limitations, explain this disparity. Methods: We developed a Monte Carlo simulation modeling an 8-step LAI-PrEP cascade for PWID under current U.S. policy conditions (n=100,000 per scenario). We decomposed barriers into three layers: pathogen biology, HIV testing gaps, and architectural barriers (policy, stigma, infrastructure, research exclusion, algorithmic deprioritization). We compared PWID outcomes to men who have sex with men (MSM) receiving identical pharmacological interventions and modeled stochastic avoidance failure using network density dynamics. Results: Under current policy, PWID achieved P(R0=0) = 0.003% (95% CI: 0.000-0.006%) compared to 16.3% for MSM—a 5,433-fold disparity. Architectural barriers accounted for 93.2% of cascade failure (policy 38.4%, infrastructure 21.9%, stigma 20.5%, algorithmic bias 8.2%, research exclusion 4.1%), while HIV testing gaps contributed 6.8%. Even theoretical maximum intervention achieved only 19.7% effectiveness. Stochastic avoidance modeling predicted 73.8% probability of major outbreak within 5 years (median: 3.0 years). Conclusions: Current HIV prevention for PWID relies on probability rather than intervention. Structural barriers—particularly criminalization and MSM-centric infrastructure—create conditions where effective prevention is mathematically impossible regardless of drug efficacy. Policy reform addressing these architectural barriers is essential to prevent predictable outbreaks.

Abstract: Taking the recent widespread controversy surrounding Yan Xuejing's live-streamed remarks as a case study, this paper analyses how public figures' discourse within commercial communication spheres is amplified by algorithms through digital expression and metaphorical labelling, thereby triggering class perception fractures and group emotional polarisation. Employing Xi Jinping's key directives on literary and artistic endeavours (‘centring on the people’ and ‘seriously considering social impact’) alongside the ‘integrity and artistic excellence’ standard as normative benchmarks, the article distinguishes between legal liability and ethical responsibility in the arts. It contends that the issue lies not in ‘discussing money’ per se, but in the absence of empathy within the mode of expression and the imbalance in public exemplification. This paper contends that such discourse has already produced foreseeable social consequences of value misalignment at the communication level. While not necessarily equivalent to ‘incitement of group hostility’ in legal terms, it warrants serious reflection and correction in terms of artistic ethics and social responsibility.

Abstract: The rising uncertainties in electric load behaviour owing to human, technological and so-cio-economic events present a need to improve the accuracy and efficiency of current short-term load prediction (STLP) models. This paper compares the performance of four hybrid models for short-term Amp load prediction: Adaptive Neuro-Fuzzy Inference Sys-tem (ANFIS) integrated with Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO), and Convolutional Neural Network (CNN) integrated with Long Short-Term Memory (LSTM) network and Extreme Gradient Boosting (XGB) machine. The models were trained and tested using historical data comprising hourly electrical Amp load ob-tained from a power utility substation in Kenya, and the corresponding weather data (temperature, wind speed, humidity) from January 2023 to June 2024. From the model testing results, both ANFIS-PSO and ANFIS-GA hybrid models show superior predictive accuracies with MAPE values of 4.519 and 4.636; RMSE of 0.3901 and 0.4024, and R2 scores of 0.9425 and 0.9391 respectively compared to CNN-LSTM and CNN-XGB models. The prediction across all models improved when the load data was pre-processed using Variational Mode Decomposition (VMD) technique. Nonetheless the hybrid ANFIS mod-els exhibited superior prediction accuracy, which is owed to their inherent adaptability to irregular data that enables them to capture the complex temporal patterns and non-linearities of Amp load well, thus making them more suitable for short-term load prediction problems.

Abstract: It is shown that the off-shell renormalization schemes for subtraction of ultraviolet divergences in Quantum Field Theory produce zero for sums of perturbative corrections to physical quantities when all perturbation orders are taken into account. That is the off-shell renor malization schemes are in this sense unphysical. In this connection it is desirable to develop on-shell renormalization schemes for different quantum theories.

Abstract: A flexible paper base SERS substrate with hydrophobic surface was fabricated through a simple route. The Ag nanoparticle was modified on filter paper through in situ growth method. After optimizing the condition during the growth and surface modification process, the hydrophobic filter paper-Ag was prepared via soaking in 10-8 g/ml of 1-Dodecanethiol with 12 h growth time. The flexible SERS substrate exhibit excellent hydrophobic properties, the contact angle of water could achieve 130.2 °. When the solution of analyte was dropped onto the SERS substrate, the diffusion effect was limited. After evaporation, the target analyte was concentrated within a fixed area. The hydrophobic SERS substrate could simultaneously improve the SERS signal and fluorescence of the analyte. The paper base SERS substrate with hydrophobic surface was used for detecting thiram from edible oil, and the sensitivity was down to 10-7 M. We proposed a flexible, economical and green hydrophobic SERS substrate for the detection of harmful ingredient from hydrophobic phase.

Abstract: We provide a referee-grade closure of the Quantum Information Copy Time (QICT) program by identifying a single information-theoretic quantity that simultaneously (i) controls operational certifiability times and (ii) sources semiclassical gravitational dynamics. The central identification is that the same localized relative entropy (equivalently, a modular-energy deficit) that upper-bounds restricted trace-distance distinguishability also enters entanglement-equilibrium arguments yielding the Einstein equation in small causal diamonds. Within an explicit axiomatic layer, we (1) remove the observer from the fundamental time scale by postulating a universal update time \tau_0 and proving \tau_{\mathrm{copy}}^{(\mathrm{op})}\ge \tau_0 for any admissible channel family \mathfrak{F}; (2) show that ’t Hooft’s deterministic cellular automaton (DCA) sector arises as the \tau_{\mathrm{copy}}^{(\mathrm{op})}\to \tau_0 limit of reversible local update rules, with the associated Hilbert-space lift given by a permutation unitary; and (3) derive the gravitational field equation from an information action via induced-gravity/heat-kernel methods, with the effective matter source fixed by relative-entropy stationarity (entanglement equilibrium). All figures and tables are reproducible from the accompanying code.

Abstract: In this work, we demonstrate how an effective spacetime description and an Einstein--Friedmann structure can emerge naturally from the geometry of a universal wavefunction, without postulating gravitational field equations or introducing matter fields explicitly. By treating the flux hypersurface associated with a conserved wavefunction current as an embedded Lorentzian manifold, we show that its induced geometry is necessarily of Friedmann--Robertson--Walker type under minimal assumptions of homogeneity and isotropy. We show that the intrinsic curvature of the induced metric is fully determined by the embedding geometry itself. In particular, de Sitter spacetime arises as a special, maximally symmetric case corresponding to a constant-curvature hyperboloid in the ambient space. More generally, for physically relevant and normalisable classes of wavefunction envelopes, the embedding geometry remains hyperboloid in character but exhibits a time-dependent curvature scale. In this regime, the effective vacuum curvature term is approximately constant at early times, giving rise to de Sitter behaviour, and subsequently decays as the hypersurface evolves, leading asymptotically to a linear expansion law. By identifying a conserved, potential-like geometric invariant inherited from the universal wavefunction, we recover an effective Einstein--Friedmann structure on the hypersurface without invoking gravitational dynamics. This invariant fixes the scaling of the dominant contribution to the effective energy density and determines the value of the effective gravitational coupling. For closed slicing, this contribution cancels identically against the spatial curvature term in the Friedmann equation, leaving the late-time expansion governed solely by the residual vacuum-like sector. These results position general relativity as an emergent effective theory arising from a deeper wavefunction-based geometric structure.

Abstract: Melanogenesis is a highly complex process regulated by multiple signaling pathways that control melanin synthesis in melanocytes and its subsequent transfer to keratinocytes. This process is further influenced by an intricate network of interactions among various skin cell populations, including inflammatory cells, which release paracrine factors in response to internal and external stimuli, such as UV radiation. The aim of this study was to evaluate effectiveness a new cosmetic formulation Skin Glow Complex designed for the topical treatment of skin dyschromia. We investigated the potential benefits of the for-mulation in two major resident skin cell types, keratinocytes and fibroblasts subjected to UV irradiation. Additionally, its effects were tested in 3D human melanocyte spheroid model, that better mimics the skin's environment. Treatment with the new formulation prevented UV-induced reactive oxygen species (ROS) formation in keratinocytes. In dermal fibroblasts, the formulation decreased the expression of matrix metalloproteinases while simultaneously promoting cell proliferation and collagen synthesis. Finally, results obtained from the melanocyte spheroid model confirmed the formulation’s ability to reduce melanin production, reinforcing its potential use in the treatment of skin dyschromia. Overall, these findings indicate that the new product represents a promising natural option to support skin repair and counteract aging and UV-induced damage.

Abstract: This paper presents a Load-Dependent Multimodal Vibration Signal Enhancement and Fusion Framework (LD-MVSEFF) for load-specific condition monitoring, building on the Customised Load Adaptive Framework (CLAF). The proposed approach enhances the classification of CLAF load-dependent fault subclasses namely Healthy, Mild, Moderate, and Severe by integrating complementary information from raw vibration signals and signal-encoded representations. Three input channels are employed, combining time–frequency domain features with Continuous Wavelet Transform (CWT) and Gramian Angular Difference Field (GADF) image encodings, with each channel independently trained and evaluated to identify its most effective classifiers. To address the reduced separability of the Mild and Moderate fault subclasses under varying load conditions, a weighted decision fusion strategy is introduced, assigning classifier contributions according to their class-specific strengths. Experimental evaluation over five runs demonstrates high and stable performance, with the best configuration achieving an overall accuracy of 99.04% ± 0.22% and an average training time of 18 min and 30 s. The results confirm the effectiveness of LD-MVSEFF as a robust multimodal methodology for load-specific condition monitoring.

Abstract: Objective Although the baseline Prognostic Nutritional Index (PNI) is a well known prognostic factor in lung cancer, the clinical significance of its fluctuation during treatment remains unclear. This study aimed to evaluate the prognostic value of dynamic changes in PNI and to determine whether improvement in nutritional-immune status correlates with survival outcomes. Methods A total of 478 patients diagnosed with lung cancer were retrospectively analyzed. PNI was calculated based on serum albumin and total lymphocyte counts. The baseline value was defined as PNI1, and the post treatment value as PNI2. The dynamic change in PNIΔ was categorized as increased, stable, or decreased. The relationship between these dynamic parameters and Overall Survival. and Progression Free Survival was assessed using Kaplan Meier and Cox regression analyses. Results The median follow up was 19.9 months. Patients with higher PNI1 and PNI2 scores exhibited significantly longer OS and PFS. Notably, patients who demonstrated an increase in PNIΔ during the treatment course had significantly longer overall survival compared to those with stable or decreased scores (p=0.023). In multivariate analysis, while cancer type and post treatment PNI (PNI2) were identified as independent prognostic factors (p=0.007 for PNI2), the dynamic improvement in PNI emerged as a critical indicator of better clinical trajectory in univariate analysis. Conclusion This study demonstrates that PNI is not merely a static baseline marker but a dynamic biomarker that reflects the host's response to treatment and disease. An increase in PNI values during treatment is associated with improved survival, suggesting that dynamic monitoring of nutritional and immune status provides valuable prognostic information for patient management in lung cancer.