Abstract: Generative AI has emerged as a transformative force in cybersecurity, offering both opportunities for innovation and challenges in threat detection and mitigation. This systematic literature review and meta-analysis synthesizes existing research to evaluate the efficacy of generative AI in cybersecurity applications, focusing on detection performance, overall impact, and threat detection metrics. We conducted a comprehensive analysis of peer-reviewed studies, employing rigorous statistical methods to quantify effect sizes and their significance. The results reveal a substantial negative effect size for generative AI detection performance (d = −3.41, 95% CI [−3.42, −3.40], p < 1e−5), indicating a strong but counterintuitive trend that warrants further investigation. In contrast, the overall impact of generative AI on cybersecurity was negligible (d = −0.06, 95% CI [−0.31, 0.20], p = 0.68), suggesting a neutral net effect. However, generative AI demonstrated a statistically significant positive effect on threat detection metrics (d = 0.20, 95% CI [0.06, 0.35], p = 0.005), highlighting its potential to enhance specific security tasks. These findings underscore the dual nature of generative AI in cybersecurity, where its capabilities are context-dependent and require careful implementation. The study provides a foundational framework for future research, emphasizing the need for balanced approaches to harness generative AI’s benefits while mitigating its risks.

Abstract: Background: Surface electromyography (sEMG) and movement analysis are increasingly applied to characterize neuromuscular impairments and guide rehabilitation after stroke. Objectives: To synthesize recent literature on the application of sEMG and movement analysis in adult stroke rehabilitation, identify trends and gaps, and discuss implications for clinical practice and future research. Methods: A non-systematic scoping search was performed across PubMed, Scopus, Web of Science, and Google Scholar using combinations of “Movement analysis”, “Gait analysis”, “Electromyography”, and “Stroke.” The first 100 relevant articles (determined by title and abstract relevance) reaching data saturation were included. Data were extracted into a comparative table with fields for study descriptors, outcomes, main results, and clinical implications. Results: Publications increased from the 1990s with a concentration around 2017. Rehabilitation journals accounted for the largest share, followed by neuroscience and engineering. Motion analysis dominated study aims (62%); experimental designs were predominant (82%). Only a minority of studies used sEMG as a primary outcome measure. Most research focused on chronic stroke and lower-limb gait, though a substantial portion addressed upper-limb function. Limitations included methodological heterogeneity, underrepresentation of acute/subacute phases, and limited use of randomized designs. Conclusions: sEMG and movement analysis offer complementary, clinically relevant insights for personalized post-stroke rehabilitation, but broader, standardized adoption—particularly in acute/subacute settings and as routine outcome measures—is needed to translate advances into improved patient care.

Abstract: Downstream adaptation of a contrastively pretrained vision--language model can improve in-domain accuracy while degrading performance on unseen transfer tasks. This study examines how full fine-tuning and low-rank adaptation alter attention heatmaps under a controlled design that matches learning rate across adaptation methods. The completed matched-learning-rate matrix contains 80 runs using the OpenAI Contrastive Language--Image Pretraining model with a base 32-patch vision transformer image encoder, two datasets (EuroSAT and Oxford-IIIT Pets), four shared learning rates (1e-6, 5e-6, 1e-5, and 5e-5), and five random seeds. We measure classification-token-to-patch attention entropy, the fraction of patches required to capture 95\% of attention mass, attention concentration, head diversity, in-domain validation accuracy, and adapter-aware zero-shot accuracy on CIFAR-100. Three findings emerge. First, learning rate is a primary determinant of structural drift: on EuroSAT, full fine-tuning moves from entropy broadening at 1e-6 (+1.83%) to marked contraction at 5e-5 (-3.99%), whereas low-rank adaptation remains entropy-positive across the full matched grid (+0.68% to +1.50%). Second, low-rank adaptation preserves out-of-domain transfer substantially better than full fine-tuning at matched learning rates: averaged across the EuroSAT grid, zero-shot accuracy on CIFAR-100 is 45.13% for low-rank adaptation versus 11.28% for full fine-tuning; on Oxford-IIIT Pets, the corresponding averages are 58.01% and 8.54%. Third, Oxford-IIIT Pets exhibits a clear interaction with optimization scale: low-learning-rate low-rank adaptation underfits the in-domain task, so method-only averages can obscure the regime in which it becomes competitive. Additional rollout, patch-to-patch, centered-kernel-alignment, and backbone analyses are directionally consistent with these controlled results. Across both controlled datasets, runs with broader retained attention support also retain more zero-shot performance. Taken together, these findings support attention heatmap drift as an informative descriptive lens on model adaptation while arguing against a universal interpretation of the observed behavior as a single collapse phenomenon.

Abstract: Folate is an essential vitamin associated with protein and DNA synthesis in the body. Compared with synthetic folic acid, 6S-5-methyltetrahydrofolate calcium salt crystal form C (MTHF CAC) is safer and has a higher bioavailability. In this study, a nanofiber membrane (MT-GE) was prepared from fish gelatin and MTHF CAC in the aqueous system via electrospinning. The differential scanning calorimetry results show the higher thermal stability of MT-GE than GE. The weight loss curve of MT-GE detected by thermogravimetric analysis was higher than that of GE. X-ray diffraction indicated the slightly higher crystalline strength of MT-GE than GE. Therefore, the inclusion of MTHF CAC improved the physical characteristics of GE nanofibers. High-performance liquid chromatography analysis revealed that the retention of MTHF CAC in MT-GE reached 85.57%, which suggests that electrospinning caused no effect on the properties of MTHF CAC. The MT-GE membrane supported cell proliferation, and the Cell Counting Kit-8 results indicate that the cell proliferation rate exceeded 100%, with the MT-GE solution demonstrating more than double the proliferation rate of the control group. Therefore, MT-GE has great potential for use as medical biomaterial.

Abstract: Benzofuran and indole are structurally similar compounds, but they show different reactivity patterns. Benzofuran can undergo electrophilic substitution at either the  or  position depending on the electrophile, whereas indole reacts preferentially at the  position. Density functional theory (DFT) calculations of the Wheland intermediates in the Vilsmeier-Haack formylation and nitration reactions are consistent with the experimental results for formylation, but cannot explain the regioselectivity observed in the nitration of of benzofuran. A frontier orbital approach successfully explains the regiochemistry of Vilsmeier-Haack reaction: electron density favors substitution at the  position in benzofuran and at the  position in indole. In contrast, nitration at the  position in both benzofuran and indole can be explained by assuming charge control as the dominant factor governing the reaction.

Abstract: Orthographic depth varies across alphabetic writing systems and plays a central role in spelling acquisition. In immersion education, a second language (L2) is used as a language of instruction for part of the curriculum, such that learners are primarily confronted with its writing system during the initial stages of literacy development. This early exposure may shape the spelling strategies subsequently deployed in the first language (L1), which also corresponds to the dominant language of the surrounding community. This article provides a structured review of key mechanisms involved in spelling acquisition, orthographic depth, and cross-linguistic influence in bilingual and immersion contexts. On this basis, it proposes a conceptual and predictive framework specifying how the orthographic depth of the instructional language modulates spelling strategies and spelling error profiles in L1. Focusing on French-speaking pupils enrolled in immersion programmes with L2s characterised by either predominantly phonemic or opaque orthographies, the framework integrates strategy-based models of orthographic development. The model distinguishes phonological, lexical, and morphographic components of orthographic knowledge and predicts that immersion in phonemic-dominant orthographies favours phonographic dominance and regularisation patterns, whereas immersion in opaque orthographies promotes greater reliance on lexical-orthographic strategies, resulting in distinct and systematic spelling error profiles in French.

Abstract: The investigation into the effects of wind and radiation pressures emitted by OB-type stars on star-forming molecular clouds constitutes a crucial area of research within astrophysics. As OB stars expel mass and release radiative energy, they exert pressure on nearby molecular clouds. This paper explores the impact of both wind and radiation pressure from OB stars on molecular clouds, examining how these forces influence the critical mass of the clouds in question. The approach taken involves a theoretical or mathematical framework, complemented by numerical analysis that utilizes a range of parameters associated with OB stars and molecular clouds. The findings indicate that an increase in wind and radiation pressure from OB stars leads to a reduction in the critical mass of the molecular cloud. This suggests that these pressures can have a dual effect, either dispersing or compressing the molecular cloud they affect. Furthermore, it was determined that the combined influence of wind and radiation pressure is more pronounced than the effects of either force acting independently, with radiation pressure demonstrating a somewhat greater impact than wind pressure based on the results obtained.

Abstract: Baja California is the second-highest state in Mexico for hospital discharges attributed to coccidioidomycosis (CM), yet epidemiological information on population-level exposure remains limited. To estimate exposure to Coccidioides and assess its association with environmental factors, we conducted intradermal coccidioidin skin testing among 416 residents across nine regions of Baja California. We analyzed 24 environmental variables, including bioclimatic, topographic, and land use indicators. Overall, 31.9% of participants tested positive. Higher odds of exposure were observed in Valle de las Palmas and La Morita. Differences between high- and low-positivity localities were observed in annual precipitation, precipitation during the wettest month, and elevation. High-positivity areas were characterized by annual precipitation ranging from 243 to 311 mm, wettest-month precipitation from 55 to 79 mm, and elevations between 125 and 276 meters above sea level. These findings indicate heterogeneous exposure to Coccidioides across Baja California and highlight the role of environmental factors in shaping transmission risk, supporting the need for strengthened epidemiologic surveillance in high-positivity areas.

Abstract: Dissolved oxygen (DO) management is a primary challenge in intensive aquaculture, where conventional aeration often suffers from high energy costs and low efficiency in decentralized systems. Oxygen transfer kinetics were investigated under oxygen-depleted conditions (initial DO = 2.4 mg L⁻¹) using the dynamic method. The system's performance was characterized through the volumetric mass transfer coefficient (kLa), Specific Oxygen Transfer Efficiency (SOTE), and dimensionless analysis (Reynolds, Schmidt, and Sherwood numbers). After 1 hour of operation, the DO concentration increased to 6.2 mg L⁻¹, achieving a net oxygen transfer of 9.55 ± 0.46 g. The system yielded a kLa of 1.44 h⁻¹ (R² = 0.97) and a SOTE of 76.4 ± 7.8 gO₂ kWh⁻¹. Dimensionless analysis (Re ≈ 2 x 10⁴, Sc ≈ 500, Sh ≈ 682) confirms that oxygen transfer is governed by hydrodynamic-induced interfacial area generation rather than molecular diffusion. Biological validation demonstrated that fish (catfish) grown under nanobubble-assisted conditions achieved a 43% higher growth rate over 17 days compared to non-assisted groups. These findings demonstrate that hydrodynamically controlled nanobubble spray systems provide an energy-efficient and scalable solution for decentralized aquaculture aeration.

Abstract: Epiderm is composed by specific layers, functions and implications in the life The purpose of the study is to analyse and to identify structural characteristics reffering to melanocytic nevi, in youth patients. Congenital melanocytic nevi are pigmented lesions that are usually present a birth. They are generally benign, but a small percentage (especially the larger ones) can potentially transform into malignant melanoma. Using both optical and electronic microscope, could be possible a better describtion related specificity in melanocytic nevi characteristics. Future trends, are important key points in management, including preventive and prophylactic methods.

Abstract: This study examines the impact of regrinding on the interfacial properties of sulfide minerals and the flotation performance of weathered copper-porphyry tailings. The feed material is characterized by a low copper grade (0.17%) and a high proportion of oxidized species (53.84%), which contributes to its inherent chemical stability and poor flotation kinetics. The findings indicate that regrinding serves a dual role: facilitating the liberation of mineral intergrowths and inducing mechanical surface renewal. This renewal is characterized by a significant decrease in the oxidation-reduction potential (ORP) and an intensification of the surface reactivity. Experimental results identify an optimal grinding fineness of 77-81% passing -0.045 mm, yielding a copper recovery of 16.26% in the absence of a sulfidizing agent. The integration of sodium sulfide (400 g/t) with regrinding significantly enhances recovery to 36.37%, driven by the establishment of a reducing environment (ORP ≈ -150 mV) and the chemisorption-mediated activation of mineral surfaces. While ultrafine grinding (90-100% passing -0.045 mm) further increases recovery to 51.47%, it is accompanied by deleterious sliming effects and a subsequent loss of process selectivity. The study confirms that mechanical surface rejuvenation and the optimization of electrochemical conditions are critical for improving the processing efficiency of anthropogenic resources, providing a theoretical framework for establishing rational beneficiation regimes.

Abstract: Contemporary leadership theories have largely emphasized performance optimization, decision-making efficiency, and structural coordination. While these approaches have contributed to organizational effectiveness, they insufficiently account for the role of human perception in shaping sustainable leadership outcomes. This limitation becomes increasingly significant in complex, diverse, and technologically mediated environments, where differences in interpretation directly influence coordination, trust, and decision quality. This paper introduces the Saudi School of Conscious Leadership, a perception-centered framework that reconceptualizes leadership as a dynamic process of maintaining perceptual balance across three interdependent dimensions: the individual, societal systems, and temporal transformation. Rather than positioning leadership as a function of authority or control, the framework defines it as the alignment of meaning, trust, justice, and collective awareness within a coherent interpretive system. The model is informed by long-term civilizational principles emphasizing continuity, balance, and relational coherence, and integrates key constructs including perceptual alignment, perceptual integrity, and meaning-based coordination into a unified explanatory structure. It proposes that leadership effectiveness emerges from the capacity to align diverse perceptual frameworks, thereby transforming cognitive differences into integrative outcomes rather than fragmentation. By shifting the analytical focus from external performance metrics to internal coherence, this study advances leadership theory in three ways: it introduces perception as a central analytical dimension, provides a mechanism-based explanation for the dual effects of diversity, and generates testable propositions for future empirical research. The framework offers both a conceptual foundation and a practical lens for understanding how leadership systems can sustain human meaning and organizational adaptability in increasingly complex environments.

Abstract: This study investigates hybrid brake-pad composites made by adding different percentages of silicon carbide (15% and 20% SiC) and zinc oxide (10%, 15%, and 20% ZnO). The goal was to find a composite that improves brake working efficiency. Wear and hardness tests were carried out according to ASTM standards. The experimental results were analyzed using Design of Experiments method to study how wear changes over time under different loads. Time-series trend analysis visualizes how the specific wear rate developed. The results showed that sample A5 had the best wear resistance and certified A5 as the optimum structural stability over time composite sample. The hardest samples were A2 and A5. The best composite was selected for a static structural analysis using ANSYS 2022-R1 to evaluate stress, strain, deformation, and elastic energy. The thermal analysis examined heat distribution, heat generation, and heat flux in the hybrid composite material. The numerical results showed that stress levels are lower at outer surfaces compared to the inner regions. The outer surfaces exhibit a uniform distribution heat flux. Directional heat flux showed a slight increase near the inner radius, the disk protrusions and edges. These findings clarified how the optimal composite behaves under braking conditions.

Abstract: While skeletal imagery appears across various ancient Andean traditions, the Wari Empire (c. 600–1000 CE) developed a uniquely standardized and widespread skull motif—the uma tullu—distributed throughout its former territory. Through an analysis of 63 artifacts spanning ceramic, textile, and metal media, this study identifies key diagnostic markers of the motif: the representation of the metopic suture and the application of red pigment. By cross-referencing these stylistic features with bioarchaeological data, the research posits that the uma tullu served as a central communicative device. In the absence of a formal script, this motif encoded imperial values and ancestral cult practices, facilitating ideological expansion and state identity. Ultimately, this work demonstrates how standardized iconography functioned as a system of graphic communication and ideological cohesion in the Middle Horizon Andes.

Abstract: This paper introduces the concept of Existential Resistance Literature as an emerging interdisciplinary framework positioned at the intersection of philosophy, leadership theory, and socio-technical systems. The study responds to accelerating technological developments that increasingly frame human behavior through algorithmic, predictive, and data-driven models. While such systems enhance efficiency and coordination, they simultaneously risk reducing human agency, meaning, and interpretive depth.Building on a perception-centered perspective, the paper proposes that contemporary systems face a fundamental challenge: not merely optimization, but the preservation of human coherence. In response, Existential Resistance Literature is conceptualized as a human-centered intellectual and narrative approach that resists reductionist interpretations of human identity. Central to this framework is the concept of perceptual integrity, which explains how individuals and systems maintain meaning, trust, and continuity under conditions of complexity and technological mediation.The study integrates recent research on cognitive diversity, collective intelligence, and human–AI interaction to demonstrate that sustainable systems depend not only on structural efficiency but on interpretive alignment. By reframing resistance as a constructive process of preserving meaning rather than opposing technology, the paper advances a novel paradigm for understanding the relationship between human systems and algorithmic environments.

Abstract: The challenge of context-free validity arises from the common belief that rigorous methodology ensures research credibility in various contexts, despite variations in epistemic foundations, institutional capacity, cultural norms, and operational conditions. This assumption is clear in Global South contexts, where research tools and evaluation frameworks from other regions are applied without proper adaptation, highlighting the limitations of claims to universal validity. The challenge is especially evident in socioeconomic research, where tools and frameworks are often applied across contexts without accounting for institutional capacity, cultural norms, or resource limitations. This paper presents the Contextual Research Validity Index (CRVI), a framework for evaluating how well a research design fits the epistemic, institutional, cultural, and operational aspects of its intended context. The CRVI views contextual validity as a form of legitimacy, emphasising that a method’s credibility relies not only on technical precision but also on how well its assumptions align with the realities of the environment. The framework includes four dimensions—epistemic alignment, institutional fit, cultural resonance, and operational feasibility—combined into a composite index for systematic assessment. By focusing on contextual alignment, the CRVI addresses shortcomings in existing validity frameworks and provides researchers, evaluators, and practitioners with a tool to anticipate misfits, adapt designs, and enhance interpretive robustness. By redefining validity as a relational outcome and treating contextual coherence as a quantifiable aspect of rigour, the CRVI provides a systematic framework for assessing the legitimacy of research across diverse contexts.

Abstract: Fatigue is a frequent, disabling and difficult to treat symptom of multiple sclerosis (MS). Low grade inflammation and energetic dysfunction have been proposed as mechanisms underlying the pathogenesis of this symptom. Owing to its anti-inflammatory and metabolic properties, there is a rational for ketogenic diet (KD) application in this setting. We conducted a single arm open label interventional study on a strictly selected group of 16 non-obese patients with multiple sclerosis who were prescribed KD for three months. With respect to baseline, at 3 months we observed a significant reduction of fatigue severity scale (5.18 ± 1.02 vs. 4.16 ± 0.98; p = 0.042), Epworth Sleepiness Scale (5.64 ± 2.46 vs. 8.46 ± 3.05; p < 0.001), Pittsburgh Sleep Quality Index (5.64 ± 3.53 vs. 7.62 ± 2.59; p = 0.009), Depression Anxiety Stress Scales-21 depression (3.18 ± 2.93 vs. 6.15 ± 3.81; p = 0.036) and anxiety (5.15 ± 4.10 vs. 1.55 ± 1.92; p = 0.019) sub-scales, and an improvement in energy sub-scale of Multiple Sclerosis Quality of Life-54 (52.49 ± 12.83 vs. 37.43 ± 14.26; p = 0.042). These findings suggest that KD might be useful for the treatment of fatigue and they raise the interest for the use of KD in the treatment of other symptoms frequently encountered in multiple sclerosis.

Abstract: In cluster-merger analyses, the dominant gravitating component is often modeled as effectively history-independent after several dynamical times, even if the gas retains thermodynamic signatures of past perturbations. Recent weak-lensing work by HyeongHan et al. (2025) complicates that expectation for the Perseus Cluster by reporting a massive sub-halo, centered on NGC 1264, and a connecting mass bridge in a cool-core system long treated as a benchmark relaxed cluster. Perseus is already known from X-ray studies to host large-scale sloshing and an ancient cold front that preserve evidence of past perturbation on Gyr (gigayear) timescales. Taken together, these results motivate a re-examination of how merger history can remain observationally relevant in nominally relaxed clusters. This paper advances a deliberately modest claim. Rather than treating Perseus as a standalone falsification of ΛCDM or of conventional hydrodynamical explanations, this paper treats it as an especially informative case in which a remnant stress-energy interpretation becomes interesting enough to warrant further study. In this interpretation, long-lived gravitational structure is represented phenomenologically by a coarse-grained remnant stress-energy TμνRem, motivated by a covariant closure construction. The principal contribution of the paper is a falsifiable observational program rather than a claim of proof. After controlling for instantaneous merger parameters, residual lensing-gas centroid offsets in nominally relaxed clusters should correlate with independent merger-history proxies if such remnants are physically relevant. Existing lensing and X-ray archives already permit a pilot test, while upcoming wide-field surveys can extend the sample.

Abstract: Ordinary differential equations are fundamental tools for modeling dynamic systems in science, engineering, and applied mathematics. Solving these equations accurately and efficiently is crucial, particularly in cases where analytical solutions are challenging or impossible to obtain. This paper presents a method for solving inhomogeneous linear ordinary differential equations using an artificial neural network. The network is composed of a single input layer with one neuron, one hidden layer with three neurons, and a single output layer with one neuron. A multiple regression model is employed to determine the weights from the input layer to the hidden layer, while radial basis functions are used to compute the weights from the hidden layer to the output layer. The bias values are chosen within the range of -1 to 1 to optimize learning behavior. A trial solution is constructed as a sum of two parts. One part satisfies the initial condition, and the other part is the output of the network to approximate the function. The neural network is trained to minimize the mean squared error of the residuals obtained by doing the substitution of the trial solution into the given ordinary differential equation. The methodology is tested on first-order and second-order ordinary differential equations to evaluate its accuracy, stability and how its capability can be generalized. The results show that the method can approximate the exact solutions of these ordinary differential equations with high accuracy.

Abstract: Background/Objectives: WHO has identified Carbapenem-Resistant Acinetobacter baumannii (CRAb) and carbapenem-producing Enterobacterales (CPE) as the “critical priority” group of MDR organisms for which new therapeutic strategies are urgently needed. Here, we evaluated in vitro synergistic activity of eugenol, cinnamaldehyde and carvacrol in combination with β-lactams, gentamicin, or colistin against multidrug-resistant (MDR) Gram-negative bacteria (GNB). Methods: We selected seven MDR-GNB clinical isolates inclining CRAb, ESBL-producing and CPE clinical isolates displaying different antimicrobial susceptibility profiles. The genomes of clinical isolates were characterized by whole-genome sequencing and synergy testing was performed with checkerboard assay. Results: Our results demonstrated that eugenol, cinnamaldehyde and carvacrol in combination with colistin exhibited high synergistic activity against MDR-GNB clinical isolates (37.5-50%), while the effect was almost indifferent in combination with different β-lactam molecules or gentamicin (87.5-100%). Synergistic interaction of eugenol, cinnamaldehyde and carvacrol with colistin induced a statistically significant reduction (p<0.05) of the MIC values compared with the molecules tested alone. Conclusions: Our data demonstrated showed that this synergistic interaction was not affected by different antimicrobial resistance genes and/or different antimicrobial susceptibility profiles. In conclusion, our results suggest that eugenol, cinnamaldehyde and carvacrol in combination with colistin represents a potential strategy for treatment of MDR-GNB pathogens and limit their diffusion.