Abstract: eBPF is increasingly used around databases, but prior systems and papers often conflate goals and therefore blur the trade space: instrumentation versus control versus in-kernel state. This impedes principled comparisons and hides the kernel constraints that determine feasibility. We present a unified analysis organized into three modes of database–kernel integration via eBPF: observability (deriving DB-relevant signals from kernel and user-space hooks), policy injection (installing workload-specific cache and networking policies at kernel choke points), and kernel-resident state (providing safe transactional state semantics for eBPF programs beyond raw maps). For each mode, we characterized the hook placement, state model, and verifier/synchronization/portability constraints that shape feasibility, and then analyzed representative systems (programmable page-cache policies, XDP ingress offload, and ACID key-value with WAL export) against this framework. We show where microsecond overheads compound to core-scale costs when user-kernel crossings dominate tail latency and which integration mode fits the workload patterns. The outcome is a decision framework that guides when to measure, when to specialize the kernel policy, and when to introduce the kernel-resident state, enabling reproducible performance work without custom kernels.

Abstract: Background: The Bacillus Calmette–Guérin (BCG) vaccine against tuberculosis is the most widespread vaccine in the world. Discovered by French investigators Albert Calmette and Camille Guérin at the Pasteur Institute, it remains the only effective vaccine against tuberculosis infection. This report describes the recognition and identification of a previously unknown French handwritten laboratory notebook prepared by Drs. Calmette and Camille Guérin recording their experiments performed during the development of the BCG vaccine. Methods: The notebook was examined, translated into English, photographed and the experiments analyzed. Results: The laboratory notebook consists of 69 leaves written in 2 hands, one of which corresponds to that of Albert Calmette. This handwritten notebook contains details of experiments that were performed during the development of the BCG vaccine at the Pasteur Institute by Drs. Calmette and Guérin. These include experimental inoculations of rabbits and guinea pigs describing the pathology including skin lesions, inflammatory reactions, organ pathology and survival. The experiments describe varying inoculative dosages of the bacteria, and different routes of administration including intraperitoneal and subcutaneous injections and administration of bacilli in the ear. In those cases where the animal had died following inoculation of tubercle bacilli, necropsy was performed and the organs examined and the pathology findings described. It describes experimental animal deaths and results of necropsies. Conclusions: this previously unknown notebook is a highly organized and detailed record of investigations using tuberculosis in animal experiments and microbiological culture to produce a safe and effective vaccine, first used in humans in 1921.

Abstract: Feline immunodeficiency virus (FIV) is a lentivirus sharing significant structural and pathological similarities to human immunodeficiency virus (HIV), making it a valuable surrogate model for HIV vaccine design and development. Currently, there is no available effective vaccine could protect cats against FIV infection. This study aims to use some artificial intelligence and immunoinformatic to design a novel multi-epitope DNA vaccine targeting some conserved regions of FIV’s gag, pol, and env genes. The mapped B and T-cell epitopes across the key proteins of the FIV genomes were screened for their ability to trigger strong immune responses, while avoiding allergenic or toxic responses and were linked to the immune adjuvant PADRE. Analysis of the vaccine construct revealed a stable, soluble, and biocompatible vaccine construct with a well-folded tertiary structure capable of binding toll-like receptor 9 (TLR9) and eliciting a robust humoral and cellular immune response. These results demonstrate a promising FIV vaccine candidate with potential insight into future directions in next generation HIV vaccines. Further experimental validation is required to confirm the potential protective power of these putative vaccines in the protection of cats against FIV natural field infection.

Abstract: Background: A group of patients with untreated unilateral vestibular schwannoma (UVS) was observed in previous clinical trials, and the results indicated a reduction in the vestibulo-ocular reflex (VOR) on the side of lesion. However, in a subset of patients, a loss of VOR gain was also observed on the contralateral (non-tumor) side, which may indicate the presence of contralateral neural crosstalk. Methods: To understand our previous clinical findings, the present study has expanded its population to investigate whether these unexpected findings are recognized in a significantly larger population of patients with UVS (n=640). Retrospectively, mean VOR gains of all semicircular canals (SCC) were obtained using video head impulse tests (vHIT) and compared between ipsi- and contralateral side of lesion. To eliminate any potential bias resulting from procedural effects, vHIT data was also obtained from a control group of 72 healthy subjects. Results: As expected, a VOR gain reduction was identified on the side of lesion in a substantial proportion of patients with UVS, varying ranging from 19.4% (anterior SCC) to 39.7% (posterior SCC). More interesting was the observation of a significant proportion of patients (21.9%) exhibiting a significant VOR reduction in posterior semicircular canal on the contralateral side, with a strong correlation with the ipsilateral side (r = 0.70). In relation to this phenomenon, our data further demonstrates that possible crosstalk of the superior branch of the vestibular nerve is of less influence on the contralateral side VOR gains compared to that of the inferior branch. Conclusion: Firstly, a reduced VOR gain in the contralateral posterior semicircular canals was found. Secondly, correlations between the inferior vestibular branches in UVS patients were comparable to the control group. These results may support the interactions such as bilateral commissural connectivity between vestibular nuclei.

Abstract: Black Soldier Fly (BSF) larvae are gaining attention for their high feed conversion efficien-cy, transforming organic matter into nutrients. As interest in insects as food ingredients grows, quality control becomes essential. This study evaluates the potential of near-infrared spectroscopy (NIRS) using benchtop and portable equipment to simultane-ously determine crude proteins and lipids in BSF larvae flour. Larvae were reared on agro-industrial waste, processed into flour, and analyzed using reference methods. NIRS data were examined with PCA for sample grouping and PLS regression for quantification. The benchtop method NIRS showed superior accuracy, with RMSECV of 1.24% and R²CV of 0.946 for lipids, and 0.59% and 0.989 for proteins. The portable device, though less pre-cise, effectively identified nutritional patterns. This green analytical approach eliminates toxic reagents, reduces environmental impact, and ensures rapid, precise analysis. It supports sustainable insect production, fostering food security, and eco-friendly agro-industrial practices.

Abstract: The Stueckelberg wave equation is solved for unitary solutions, which links the eigenvalues of the Hamiltonian directly to the oscillation frequency. As it has been showed previously that this PDE relates to the Dirac operator, and on the other hand it is a linearized Hamilton-Jacobi-Bellman PDE, from which the Schrödinger equation can be deduced in a nonrelativistic limit, it is clear that it is the key equation in relativistic quantum mechanics. We give a stationary solution for the quantum telegraph equation and a Bayesian interpretation for the measurement problem. The stationary solution is understood as a maximum entropy prior distribution and measurement is understood as Bayesian update. We discuss the interpretation of the single electron experiments in the light of finite speed propagation of the transition probability field and how it relates the interpretation of quantum mechanics more broadly.

Abstract: Preserving critical data, preventing unauthorized access, securing communication are aspects of information security. To implement them as hardware is more reliable than software. There are various hardware solutions that suggest using a separate computational unit which is capable of providing various security enhancements. This article describes a heterogeneous security architecture with a tightly coupled security core to the CPU. A security interface that allows direct control and monitory of the security core over the CPU is proposed. In the article analysis of how the interface interacts with the controlled and monitored CPU is done. This analysis explains the benefits and why for certain aspects control is implemented seeking performance while for others - using less logic.

Abstract: Few-shot object detection focuses on accurately identifying and locating novel categories with just a small set of annotated examples. However, accurate object detection in remote sensing images still faces challenges such as scale variations, small objects, and complex background interferences. To alleviate these issues, we propose DAFSDet, a dual attention guided few-shot object detection framework, to effectively mine discriminative key features. Specifically, we propose a Content-Aware Strip Pyramid (CASP) module that uses content-aware upsampling for spatial attention and bidirectional strip convolution for long-range context, forming a joint spatial–semantic attention mechanism. CASP produces robust multi-scale features, highlighting key regions while preserving semantic and contextual information for few-shot detection. Subsequently, we design a Deformable Attention Region Proposal Network (DA-RPN) to produce high-quality candidate regions from the enhanced features. Through the collaborative optimization of CASP and DA-RPN, our method significantly improves the accuracy and robustness of few-shot object detection in remote sensing images, particularly in complex scenarios with large number of small objects and messy backgrounds. Experimental results on two large-scale datasets, DIOR and NWPU VHR-10, demonstrate that the proposed model achieves strong performance and clear advantages.

Abstract: Resonant transfer and excitation (RTE) is a correlated two-electron process mediated by the two-center electron-electron interaction: A projectile electron is excited while a target electron is captured, forming doubly excited states. These decay via X-ray (RTEX) or Auger (RTEA) emission. For fast enough collisions with light targets, RTE becomes analogous to dielectronic capture (DC)—a key plasma process—and is described by the impulse approximation (IA). Early (1983–1992) RTEX and the more stringent, state-selective RTEA measurements at accelerator facilities provided indirectly, essential DC cross section information before direct electron-ion DC measurements became available. The 1992 review [1], focusing on zero-degree Auger projectile spectroscopy (ZAPS) of state-selective KLL D states, validated the IA for low-Z_p ions (Z_p ≤ 9). However, a puzzling systematic discrepancy was revealed: IA cross sections were consistently larger than experiment, with the disagreement increasing as projectile atomic number Z_p decreased. This review updates RTEA progress since 1992: Refinements to IA calculations include the use of more accurate Auger rates, considerations of Auger anisotropic emission, novel target binding corrections and even an exact IA formulation. Experimental ZAPS improvements feature a hemispherical spectrograph and a proven in situ more accurate standardized absolute cross section calibration using binary encounter electrons. A methodical analysis demonstrates impressive agreement across all measurements spanning both pre- and post-1992 eras including measurements presented here for the first time, eliminating systematic discrepancies. IA validity is confirmed down to boron ions, with He⁺ ions as the sole clear exception together with some borderline Li-like ion cases. Recently, a rigorous ion-atom collision treatment has also emerged: Nonperturbative close-coupling calculations of transfer excitation of He-like ions in collisions with He confirms RTE dominance via two-center electron-electron interactions at large impact parameters, while providing unexpected insights into many-body collision dynamics at the lowest collision energies.

Abstract: The contemporary breeding of Cannabis sativa L. has shifted toward exotic chemovars defined by fruity, floral, and sweet aromas, traits driven by minor volatile esters rather than quantitatively dominant terpenes. Despite their economic importance, the enzymatic machinery governing the synthesis of these high-value volatile esters remains uncharacterized. This study presents a genome-wide identification and tissue-specific expression landscape of the CsBAHD acyltransferase superfamily, the metabolic drivers of ester biosynthesis. Using a custom hidden Markov model (HMM), 108 high-confidence CsBAHD genes were identified in the cs10 reference genome. Physical mapping reveals a non-uniform distribution characterized by dense telomeric gene clusters on chromosomes 1, 2, 4, 5, and 8. While these dynamic regions facilitate rapid chemical diversification via chromosomal recombination, their hyper-variability contributes to linkage drag and the phenotypic instability of exotic traits observed during hybridization. Integration with multi-tissue transcriptomic datasets identified distinct transcripts for the putative enzymes governing ester biosynthesis in the glandular trichome. CsBAHD45 is a constitutively expressed high-abundance transcript (mean: 1953 TPM), whereas chemotypic diversity is generated by a subset of hyper-variable genes, including CsBAHD19 and CsBAHD16, which exhibit extreme presence/absence variation across the plants. It is proposed that this strain-specific repertoire drives the accumulation of high-value odorants, including sulfur-containing esters responsible for tropical passionfruit notes, phenethyl esters driving honey and fruit nuances, and acetylated terpenes analogous to the floral profiles of lavender and rose. Structural validation via physicochemical fingerprinting and deep modeling with the ESM-2 protein language model confirmed a striking topological consensus with functionally reviewed reference enzymes. Beyond the floral sink, distinct vegetative gene clusters were identified that govern root zone defense, stem fiber lignification, and seed coat maturation. Phylotranscriptomic analysis suggests that the aerial floral biosynthetic capacity evolved via the neofunctionalization of these ancestral core-fiber and root-defense genes. Finally, this study proposes a physicochemical sequestration model, hypothesizing that ancestral CsBAHDs catalyzed the formation of cannabinoid esters to stabilize volatile defensive terpenes as persistent contact insecticides. Consequently, the modern high-potency chemotype may be the product of anthropogenic selection, where the selection for free THC drove the loss of this ester-based defence system. Collectively, these findings provide a high-resolution genomic blueprint for the de-orphaning of the CsBAHD superfamily, establishing molecular targets for the marker-assisted breeding of premium aromatic chemovars, optimized industrial fiber properties, and robust root-zone defense systems.

Abstract: The development of cutting-edge vehicle communication technology targeted at enhancing road safety, traffic efficiency, and autonomous mobility has been expedited by the emergence of intelligent transportation systems. Direct wireless connection between vehicles is made possible via vehicle-to-vehicle (V2V) communication, which speeds up the exchange of vital safety data like speed, trajectory, braking status, and road conditions. By incorporating Artificial Intelligence (AI) into V2V networks, predictive skills are improved, enabling cars to foresee possible risks and react proactively as opposed to reactively.With an emphasis on its operational architecture, supporting technologies, recent research advancements, and future network paradigms, this study provides a thorough scientific overview of V2V communication. The report demonstrates how next-generation wireless technologies, edge computing, and AI-driven analytics are converting vehicle networks into intelligent safety ecosystems. Important issues are also looked at, such as interoperability, scalability, cyber security hazards, and latency limitations. The study comes to the conclusion that AI-enabled V2V communication will be a key component of completely autonomous and accident-free transportation systems.

Abstract: Chemotherapy- and/or radiotherapy-induced oral mucositis (CRIOM) is a common and debilitating complication in patients with head and neck cancer, driven largely by excessive proinflammatory cytokine signalling and treatment-associated bacterial dysbiosis. This review synthesizes current mechanistic evidence on cytokine toxicity and microbial imbalance in pathogenesis of CRIOM and to summarize emerging therapeutic strategies targeting these pathways. A structured PubMed search identified preclinical and clinical studies evaluating cytokine-mediated inflammation, microbiome alterations, and interventions with anti-inflammatory or microbiota-modulating effects. The reviewed evidence demonstrates that elevated IL-1β, IL-6, TNF-α, iNOS, and nitric oxide amplify tissue injury and ulceration, while disruption of oral and gut microbial communities, characterized by loss of beneficial commensals and enrichment of pathogenic taxa, further exacerbates mucosal inflammation. Anti-inflammatory agents, including pentoxifylline, atorvastatin, trans-caryophyllene, azilsartan, recombinant human IL-11, and low-level laser therapy reduced cytokine levels and improved mucosal healing. Additionally, microbiome-targeted approaches such as oral microbiota transplantation and a multi-strain probiotic cocktail restored microbial balance and attenuated CRIOM severity. Overall, current findings highlight cytokine toxicity and dysbiosis as synergistic drivers of CRIOM and support anti-inflammatory and microbiome-modulating therapies as promising adjunctive strategies; however, further studies incorporating patient-specific factors is needed to guide optimized clinical application.

Abstract: The MADS-box transcription factor (TF) family constitutes a critical class of transcriptional regulators in plants, playing pivotal roles in diverse developmental processes. MIKC-type proteins represent Type II MADS-box TFs that widely function in regulating floral organ development and reproductive growth in plants. In this study, a total of 38 MIKC-type MADS TFs were identified from the sorghum genome, distributed across nine chromosomes. Based on sequence alignments and phylogenetic analysis, these 38 SbMIKC genes (SbMIKCs) were further classified into 10 distinct subfamilies. The expression profiles of these SbMIKCs across multiple tissues revealed five major patterns, among which SbMIKC17 exhibited relatively abundant transcript levels during grain development in sorghum. Further assays confirmed that the protein encoded by SbMIKC17 localizes to the nucleus without self-transactivation activity in yeast. Integrated results from DAP-seq, dual-luciferase assays, and yeast one-hybrid experiments demonstrated that SbMIKC17 binds to and activates the promoter of SbAGPS1, as well as enhancing the promoter activities of SbBt1, SbGBSSI, SbSSIIa, and SbISA1 simultaneously. Collectively, these findings suggest that the MIKC-type MADS gene SbMIKC17 may play a crucial role in starch biosynthesis in sorghum.

Abstract: This paper critiques the established loss of simultaneity in special relativity which comes from Minkowski spacetime, and proposes a return to simultaneity through Lorentz transformation. Einstein's original thought experiment with a train (observer M’), an embankment (observer M) and lightning is shown, at first, to be inadequate for a test on simultaneity, and a new scenario is proposed. The new scenario posits that both observers M and M’ should be in the middle when the waves arrive (when waves leave is the original scenario). Despite time dilation and length contraction, simultaneity can be observed, suggesting that motion does not preclude simultaneity. But there is more; by using Lorentz invariance (therefore pure calculation), the conclusion of simultaneity will be reached with both the original and the new scenarios for both observers. This paper argues that Minkowski's oblique coordinates are probably unnecessary. Lorentz transformation maintains a consistent scale between observers, suggesting a shared background that supports simultaneity.

Abstract: Gully erosion is a significant threat to the sustainability of soil in Mediterranean basins. Despite its impact, there is a lack of research providing accurate regional-scale cartography of complete gully network. This study aims to automatically map the gully network in the olive-growing landscapes of the Guadalquivir basin (Spain) using Machine Learning (ML) algorithms: Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR). We integrated these models with 17 predictive variables (including hydrotopographic, climatic, and edaphic factors) and the Gully Head Initiation (GHI) index. RF was the most suitable model, achieving an Area Under the Curve (AUC) of 0.91 and an F1-score of 0.83 and enabled the delineation of a gully network totalling 8439.05 km. Variable importance analysis revealed that flow accumulation (17.33 %) and the GHI index (nearly 30%) were the primary predictors, with the Rainy Day Normal (RDN)-based formulation outperforming the maximum daily precipitation (Pmax)-based one. Spatially, countryside hills landscapes exhibited the highest gully densities (42.50 m/ha). The results demonstrate the effectiveness of combining ML with physically-based indices to generate high-resolution gully cartography for soil conservation planning in Mediterranean olive groves.

Abstract: Agricultural Commercialization Clusters (ACC) play a vital role in Ethiopia's agricultural and rural development initiatives, aimed at promoting sustainable livelihoods. This study examines the impacts of ACC practices on the livelihood diversification of rural households in South Ethiopia. Data was collected from 355 households, comprising 177 participants in Agricultural Commercialization Clusters (ACC) and 178 non-participants, using household surveys and qualitative insights from interviews and focus group discussions. Descriptive statistics and econometric modeling, including the Endogenous Switching Regression (ESR) approach, were used to assess the effects of Agricultural Commercialization Clusters (ACC) on livelihood diversification in South Ethiopia. The probit model identified critical determinants of agricultural commercialization cluster, such as education level, total land size, access to irrigation, and proximity to roads and markets. The ESR full information maximum likelihood (FIML) results showed that livelihood diversification was positively influenced by farmland size, access to agricultural extension services, and credit availability. For non-ACC participant households, engaging in ACC practices resulted in an 18.9% increase in livelihood diversification. The results suggest that ACC practices significantly enhance livelihood diversification in the region. In South Ethiopia, achievements of agricultural commercialization clusters significantly contribute to combating unemployment and are directly linked to the Sustainable Development Goals (SDGs), specifically SDG 1, 2, and 3. The study recommends that policymakers and development practitioners enhance access to extension services, credit, markets, roads, and irrigation infrastructure to strengthen livelihood diversification through ACC in South Ethiopia.

Abstract: This paper presents a web-based learning platform built on a Retrieval-Augmented Generation (RAG) architecture, designed to support dialogical learning. Rather than treating learner questions as isolated inputs, the platform views learning as an ongoing dialogue, preserving context across interactions and grounding responses in curated and validated educational materials. The system uses a modular web-based design that clearly separates content management, retrieval and generation, and dialogue handling. This modularity enables the integration of various generative models – both open-source and commercial – and supports deployment in real e-learning environments without requiring local installation. A representative use case demonstrates how the platform can support learning at the university level. Overall, the study shows how dialogically grounded RAG-based systems can improve transparency, contextual coherence, and pedagogical value in AI-supported e-learning.

Abstract: Every company conducts evaluations to ensure the quality of its product and services. One useful tool is the control chart. Multivariate simultaneous control charts, such as Max-Mchart, Max-Half-Mchart, Max-MEWMA, and Max-MCUSUM, are used to monitor the mean and variability simultaneously. The Max-Half-Mchart is advantageous because it can detect both small and large shifts in the mean and covariance matrix. However, outliers can cause the chi-square cumulative distribution function to approach one, leading the inverse standard normal cumulative distribution toward infinity and triggering masking and swamping effects. To overcome this, robust estimators of the mean and covariance matrix are required. Fast-MCD and Det-MCD are fast robust estimators based on the C-step algorithm. The results of the outlier detection show that the robust Max-Half-Mchart based on Det-MCD performs best for a small number of outliers, while the robust Max-Half-Mchart based on Fast-MCD and Det-MCD performs best for a large number of outliers. In terms of process shift detection, both robust Max-Half-Mchart based on Fast-MCD and Det-MCD can detect shifts effectively. Applications to OPC cement quality data and synthetic data indicate that the robust Max-Half-Mchart based on Det-MCD is the most sensitive to outliers.

Abstract: We introduce the Informational Coherence Index (Icoer), a bounded metric for quantifying the degree of integration and alignment among interconnected artificial intelligence (AI) models. The index combines four interpretable components: normalized processing capacity, a Gaussian informational coupling function that decays with inter-model distance, an entropy-based weight reflecting output uncertainty, and a Lorentzian resonance factor capturing synchronicity. We prove that Icoer ∈ [0, 1] and is monotonically decreasing in both informational distance and entropy. We derive closed-form gradients for optimizing network coherence via gradient ascent and demonstrate convergence on networks of up to 100 models. A pairwise extension of the index is also proposed for settings where inter-model distances are defined over embedding spaces. Simulation experiments confirm that the metric exhibits proportional sensitivity to parameter variations, correctly identifies informational bottlenecks, and scales to large networks. We discuss the relationship between Icoer and established measures such as agreement rate and mutual information, and outline directions for empirical validation on real AI systems.

Abstract: Terrestrial Gross Primary Productivity (GPP) is pivotal to the global carbon cycle, and its response to climate change is strongly regulated by topographic conditions through complex, non-linear mechanisms that remain poorly quantified at macro scales. Integrating multi-source remote sensing data with structural equation modeling (SEM), geographical detectors, and generalized additive models (GAM), this study investigated the spatiotemporal dynamics of GPP and its non-linear responses to coupled climate-topography gradients across China from 2001 to 2020. Results revealed a significant increasing trend in GPP across nearly 80% of China, with precipitation identified as the dominant driver, surpassing temperature and radiation. Topography significantly modulated climate sensitivity by redistributing hydrothermal resources. A distinct transition in dominant limiting factors was observed along the altitudinal gradient, shifting from water-limited (<2000 m) to energy-limited (>3000 m) regimes. Notably, mid-altitude regions (1000–2000 m) exhibited the highest sensitivity to precipitation, representing an ecological "sweet spot". Furthermore, we quantified critical ecological thresholds for climatic drivers, identified saturation points for temperature (~17.4°C) and precipitation (~1974 mm), and an inhibition threshold for solar radiation (>101 W/m²). These findings elucidate the transition mechanisms of climatic constraints and non-linear thresholds in complex terrain, providing robust scientific evidence for region-specific ecosystem and carbon management.