Abstract: Against the background of severe farmland fragmentation and continuous rural labor outflow in developing countries, land consolidation through land transfer has long been regarded as the primary path to realize large-scale agricultural production. However, land transfer faces institutional and market constraints in smallholder-dominated regions. This paper takes China’s full-process agricultural production service pilot policy as a quasi-natural experiment, adopting 2006–2023 provincial panel data and staggered DID to explore how service-oriented scale reshapes cultivated land use patterns and boosts staple grain supply. We find that agricultural production services raise total grain output mainly via expanding cultivated land sown area (extensive margin) rather than lifting per-unit land yield. By popularizing mechanized operations in labor-intensive sowing and harvesting stages, the policy alleviates seasonal labor constraints, raises per capita cultivated acreage, increases multiple cropping index and optimizes grain-oriented cropping structure, thus mitigating farmland abandonment. Although the policy significantly promotes rural land transfer, the pre-existing land transfer level cannot strengthen its grain-promoting effect, which verifies that service-based scale can operate without large-scale land right consolidation. Further evidence shows the policy also improves agricultural total factor productivity, realizing coordinated optimization of land, labor and machinery factor allocation. This study supplements the land economics literature by distinguishing two scale development paths (land transfer vs service aggregation), and provides a land governance reference for smallholder economies to stabilize grain security under fragmented farmland.

Abstract: Due to the differential treatment required by non-tuberculous mycobacteria (NTM) infections, accurate identification in clinical isolates is necessary for correct management, effective treatment, and appropriate control strategies. Traditional methods, including phenotypic tests, are slow, cumbersome, and often not definitive. PCR-based methods, such as restriction fragment length polymorphism analysis, are still very time-consuming and sometimes lead to inaccurate identification because they handle fragments of different sequences but do not agree with their evolutionary origin. Sequencing is the most accurate method for species identification, with the 16S rRNA, hsp65, and rpoB genes being considered as candidates for phylogenetic and diagnostic studies. In this study, we developed a phylogenetic analysis using the 16S rRNA, hsp65, and rpoB gene sequences of Mycobacterium clinical isolates, collected between 2018 and 2022, for taxonomic categorization of Mycobacterium species, and evaluated their use for Mycobacterium species identification of clinical interest. In addition, we analyzed the genotype-phenotype correlation using characteristics such as sample origin, growth rate, and antimicrobial resistance. An alignment matrix was built (MacVector 18.5.8) based on the sequences generated in this study and sequences retrieved from NCBI, and phylogenetic analyses were performed using PAUP 4.0a. The rpoB and hsp65 markers showed phylogenetic information at the level of groups of species and subspecies, while the 16S rRNA gene was shown to be the most conserved gene, yielding a structure at the level of species complexes that can be used as a first level of identification. The clinical isolates showed phylogenetic homology with the M. abscessus, M. avium, M. fortuitum, and M. intracellulare groups. The synapomorphic characters varied between genes analyzed, showing a correlation between genotype and phenotype useful for evolutionary trends, natural classification, and molecular identification methods for clinical and treatment purposes. Keywords: taxonomy; mycobacterial classification; phylogenetics; homology; clinical isolates; molecular identification; genotypic-phenotypic correlation.

Abstract: Background/Objectives: Obstetric spinal anaesthesia practice changes with evidence, drug availability, and quality-improvement priorities, but longitudinal African data remain limited. This study described temporal changes in spinal anaesthesia practice for caesarean delivery in Windhoek, Namibia, and examined associated postoperative re-covery outcomes. Methods: We conducted a retrospective time-trend analysis of 400 routinely collected anaesthesia records for caesarean deliveries from 2017 to 2025. Calendar time was grouped as 2017-2019, 2020, 2021, and 2022-2025. Practice variables included intrathecal regimen, vasopressor type, spinal needle gauge, documented spinal level, infusion time, and spinal attempts. Outcomes included pain, headache, nausea, shortness of breath, blood pressure drop, backache, symptom count, and motor recovery grade. Results: Anaesthesia practice changed substantially. Phenylephrine use increased from 0.0% in 2017-2019 to 70.6% in 2020, 96.8% in 2021, and 100.0% in 2022-2025. Use of 27G spinal needles increased from 0.0% in 2017-2020 to 95.2% in 2021 and 76.3% in 2022-2025. Any postoperative symptom was documented in 74.5% of records, predominantly backache. After adjustment for age, body mass index, and intrathecal regimen, calendar period remained associated with postoperative symptom burden. Conclusions: Obstetric spinal anaesthesia practice evolved in this Windhoek cohort, with substantial changes in vasopressor selection, spinal needle gauge, spinal level, and in-fusion time. Routine anaesthesia data can support local quality-improvement protocols for haemodynamic management and patient-centred recovery after caesarean spinal an-aesthesia.

Abstract: Human herpesvirus 8 (HHV-8), also known as Kaposi sarcoma–associated herpesvirus (KSHV), is a gamma-2 herpesvirus implicated in a distinctive group of lymphoproliferative disorders (LPD) and lymphomas, in several of which the neoplastic cells are concurrently infected with Epstein–Barr virus (EBV), a gamma-1 herpesvirus. This review summarizes the spectrum of HHV-8/EBV co-positive lymphoproliferations. We first outline the biology of both viruses—their latent and lytic life cycles and the viral gene products (including LANA, vFLIP and v-cyclin for HHV-8 and EBNA-1 and LMP-1 for EBV) through which they deregulate the cell cycle, inhibit apoptosis, and evade immune recognition and may create conditions permissive for B-cell transformation. We then place the principal KSHV/HHV8-associated entities—primary effusion lymphoma and its extracavitary presentation, KSHV/HHV8-positive germinotropic lymphoproliferative disorder, KSHV/HHV8-associated multicentric Castleman disease, and KSHV/HHV8-positive diffuse large B-cell lymphoma—within the current WHO-HAEM5 and ICC frameworks. PEL is frequently EBV-positive, and GLPD is characteristically dual-positive, whereas the KSHV/HHV8-positive lesional cells of MCD and KSHV/HHV8-positive DLBCL are usually EBV-negative. For the purposes of this review, dual positivity denotes demonstration of LANA and EBER within the same morphologically defined lesional cell population and is distinguished from concurrent viral positivity in separate or insufficiently characterized cell populations. Particular attention is given to rare atypical lesions with overlapping features. These cases suggest possible biological relationships among KSHV/HHV8-associated proliferations but do not yet establish a single continuous disease spectrum or a uniform mechanism of viral cooperation.

Abstract: Introduction: Yellow fever re-emerged as a major public health threat in the Americas during 2024–2025, with increasing numbers of cases and deaths, predominantly among unvaccinated individuals. Although the live-attenuated 17D yellow fever vaccine is highly effective, adults aged ≥60 years have an increased risk of serious adverse events following immunization (AEFIs). We assessed the safety profile of yellow fever vaccination in Colombia, with particular emphasis on older adults, and contextualized the observed risks within an epidemic setting characterized by active transmission and high mortality. Methods: We conducted an observational, descriptive study using secondary data from Colombia’s Expanded Program on Immunization and the national VigiFlow pharmacovigilance system. Individuals vaccinated against yellow fever between October 1, 2024, and July 31, 2025, were included. Reported AEFIs were analyzed by severity, sex, and age group. Rates were calculated per 100,000 vaccinated individuals, with 95% confidence intervals, and compared between adults aged ≥60 years and younger individuals. Older adults were further stratified into five-year age groups. Results: Among 3,915,966 vaccinated individuals, 425 AEFIs were reported in 233 unique cases. The overall AEFI rate was 10.85 per 100,000 vaccinated individuals, and the severe AEFI rate was 2.94 per 100,000. Adults aged ≥60 years had substantially higher rates of overall AEFIs than those aged <60 years (54.05 versus approximately 6.1 per 100,000, respectively), corresponding to a rate ratio of 8.8. Severe AEFI rates were 11.90 per 100,000 among adults aged ≥60 years and approximately 2.0 per 100,000 among younger individuals, corresponding to a rate ratio of 6.1. The highest severe-event rate was observed among adults aged 80–84 years, at 49.82 per 100,000. Nine fatal outcomes were reported; following causality assessment, none was considered attributable to the vaccine. Conclusions: Reported AEFIs following yellow fever vaccination were more frequent among adults aged ≥60 years, with a particularly marked increase in the oldest age groups. Nevertheless, the absolute rate of severe events remained low, at approximately 1.2 per 10,000 vaccinated older adults, and no reviewed fatal outcomes were attributed to vaccination. In settings of active yellow fever transmission, vaccination decisions for older adults should therefore be guided by individualized benefit–risk assessment rather than age alone, accompanied by careful screening, active pharmacovigilance, and clear risk communication. Vaccination remains the principal intervention for preventing yellow fever-related deaths.

Abstract: As industries increasingly transition manufacturing and production systems toward enabled smart factories, governments and policymakers assume a critical role in establishing regulatory frameworks that enable emerging Industry 4.0 ecosystems to develop and remain competitive. While existing scholarship has devoted substantial attention to technological capabilities and innovation potential, comparatively limited emphasis has been placed on the policy, regulatory, and governance structures that shape organizational readiness and workforce transformation in this digital industrial era. This study examines how institutional arrangements—encompassing public policy, regulatory regimes, and governance mechanisms—influence organizations’ capacity to adopt Industry 4.0 technologies and to effectively transform their workforce. Grounded in institutional theory and sociotechnical perspectives, the research adopts a multilevel analytical approach to explore the interactions between macro-level policy and regulatory environments, meso-level organizational readiness, and micro-level workforce outcomes. The study used the systematic literature review SLR to investigate 80 scholarly studies on key dimensions of organizational readiness, including digital maturity, leadership commitment, IT–OT integration, and change management capabilities, and analyzes how these factors mediate the relationship between external governance frameworks and Industry 4.0 implementation. In parallel, the research examines workforce transformation processes, with particular attention to reskilling and upskilling initiatives, job redesign, human–machine collaboration, and employee acceptance of AI-driven systems. Drawing on a comprehensive review of existing literature, supplemented by insights from organizational leaders and technical professionals operating within Industry 4.0 environments, the study evaluates the impact of policy and regulatory oversight on organizational readiness. The findings highlight the importance and impact of the organizational framework as an essential ingredient to organizational readiness and workforce transformation in Industry 4.0, spanning policy to governance practices, regulatory compliance challenges, and the human-centered implications of automation. Additionally, the study addresses ethical, social, and labor-related considerations, including data governance, algorithmic accountability, and workforce inclusion. The analysis reveals a consistent emphasis on workforce reskilling across national Industry 4.0 strategies, although significant variation exists in policy implementation approaches. Overall, the findings demonstrate that organizational readiness for Industry 4.0 is strongly associated with organizations' internal architecture, with leadership commitment and workforce digital literacy, underscoring the central role of governance and human-centered capabilities in enabling sustainable digital industrial transformation.

Abstract: A non-sinusoidal regime is commonly found in power grids and affects the nominal operation and performance of industrial equipment supplied by the electrical network. The non-sinusoidal regime is mainly caused by nonlinear circuit elements, especially power-electronic devices. In real industrial cases, the harmonic content of voltage and current varies; consequently, the RMS values can change significantly, influencing both power flow and power quality. To determine these variations, this article proposes a method for analyzing the dependence between the harmonic weights of voltage and current and the sensitivities of reactive and apparent powers. After introducing dependency relationships between real, reactive, and apparent powers and harmonic weights, the method uses these relationships to calculate sensitivities when one or more parameters are modified. A numerical algorithm is implemented in MATLAB/Simulink to determine the sensitivities in a real case. The values obtained are compared with those directly calculated from measured data, and the small errors demonstrate the accuracy of the proposed method.

Abstract:

Plant chemodiversity is generally evaluated through metabolite richness, relative abundance, compositional dissimilarity, and biosynthetic organization. However, these descriptors characterize chemical states without explicitly identifying which metabolites, chemical classes, or biosynthetic pathways gain or lose relative representation during transitions between states. Here, we introduce Chemical Game Theory, an operational framework in which metabolites are treated as elementary chemical strategies, biosynthetic pathways constitute higher-order strategies, and normalized chromatographic abundances define their frequencies within a mixture. Replicator-based equations are used to calculate realized chemical payoffs, which quantify the relative advantage or disadvantage of each strategy during compositional transitions. Shannon diversity describes metabolite-level coexistence, whereas the General Biosynthetic Diversity Index, GBDI, characterizes pathway allocation and intrapathway branching. The framework was applied to previously published GC-MS and GC-FID profiles of essential oils from leaves and four developmental stages of the reproductive organ of Piper mollicomum Kunth, sampled over five months. Leaves exhibited the greatest overall metabolite diversity and biosynthetic architectural complexity, while the reproductive stages followed distinct and temporally variable chemical trajectories. Replicator analysis identified stage-dependent changes in the relative performance of terpenoid, mixed, shikimate-derived, and other biosynthetic strategies. The terpenoid route was consistently favored during specific reproductive-stage transitions, whereas the mixed pathway showed recurrent relative decline. Chemical dominance, Shannon diversity, GBDI, and realized payoff therefore captured distinct but complementary dimensions of chemical organization. Chemical Game Theory provides a quantitative language for interpreting the redistribution of chemical investment across plant compartments and developmental states. In phytochemical and bioprospecting studies, the framework may support the rational selection of plant organs, developmental stages, and collection periods associated with high target-metabolite abundance, emerging chemical strategies, or expanded biosynthetic and structural space.

Abstract: Flood-risk index classification asks a narrower question than operational flood forecasting: given a vector of composite risk indicators describing a place, can a classifier tell high-risk from low-risk locations, and does that ability survive contact with real geography? This study answers the question in three successive steps, each building on the result of the one before it. The starting point is a synthetic benchmark of 1,117,957 records distributed through Kaggle and referred to here, following the reviewer’s correction, as Resurrectum Diluvium: twenty ordinal composite indices with no verifiable link to any real place. Six classifiers — Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, LightGBM, and CatBoost — were benchmarked on this dataset, and Logistic Regression won decisively (AUC-ROC = 0.9256), a result later traced to the linear, additive way the synthetic indices were themselves generated rather than to any property of composite indices in general. To test that explanation against real evidence, the identical pipeline was applied to the FEMA National Risk Index at county resolution (n = 3140U.S. counties), with the target rebuilt from a loss-per-exposure rate rather than raw dollar losses after the latter was found to correlate with population size (r = 0.63) almost as strongly as with hazard. On this first real dataset the ranking inverted: Random Forest reached AUC = 0.7855 against 0.6680 for Logistic Regression, and a leave-one-region-out cross-validation across the four U.S. Census regions collapsed every model toward chance (mean AUC 0.52–0.55), a result a stratified random split alone would never have revealed. Because one confirmation is an anecdote and two are a pattern, the same pipeline was run a third time at census-tract resolution (n = 84,034 tracts, roughly twenty-seven times the county sample), using an independently downloaded and merged extract to rule out a one-off artifact. The tract-level results repeat the county-level story point for point: Random Forest again leads under random splitting (AUC = 0.8507) and again loses the most ground under spatial cross-validation (mean AUC = 0.590), while Logistic Regression, the weakest model under random splitting at both real-world scales, is consistently the one that generalizes best across untrained regions (mean spatial AUC = 0.638). Taken across all three stages and roughly 1.2 million observations, the evidence points to a specific and testable conclusion rather than a general claim about algorithms: a classifier’s apparent superiority on pooled, randomly split data says little about whether it has learned anything that holds outside the region it was trained on, and this gap remains invisible unless geography is deliberately excluded from at least one evaluation fold.

Abstract: Polarizers and polarization optics technology has been widely used in various application fields. Although there is a wealth of independent research on polarizers, thin films and polarization spectroscopy, there is a lack of a systematic review that combines "polarizers" with "polarization spectroscopy measurement methodology". In this paper, polarizers and polarization spectroscopy has been discussed revolving the development, fabrication and characterization of related materials, which include Polyvinyl Alcohol (PVA)-I2 polarizers, two-dimensional (2D) functional polarizers and grid wire polarizers. The summarized methodology based on Mueller-Stokes polarimetry and Poincaré sphere, which bridges the gap between optimal structural design and performance improvement. Furthermore, this study presents characterization techniques, mechanistic insights, and potential applications of polarizers and polarization spectroscopy. These findings offer a comprehensive strategy for designing novel structures and inspire future research on next-generation functional thin films for optical displays, molecular structural analysis, polarization imaging and polarization photodetectors.

Abstract: The remarkable evolution of incretin-based therapeutics from selective glucagon-like peptide-1 receptor agonists to dual, triple and emerging polyagonists has fundamentally expanded our understanding of metabolic regulation. Clinical trials have consistently demonstrated coordinated improvements in glycaemic control, hepatic steatosis, body composition, insulin sensitivity, cardiovascular and renal outcomes, inflammatory activity, mitochondrial metabolism and energy expenditure that extend well beyond the expected physiological effects of individual receptor activation. These observations suggest that the therapeutic efficacy of contemporary polyagonists cannot be adequately explained by isolated hormonal mechanisms but instead reflects modulation of an integrated physiological regulatory system. We propose the existence of an Entero–Pancreatico–Hepatico–Systemic Polyhormonal Metabolic Homeostasis Network (EPHS-PMHN), a dynamic endocrine, neural, immune and metabolic communication network in which gastrointestinal nutrient sensing initiates coordinated signaling through the enteroendocrine system, pancreatic islets, liver, central nervous system, adipose tissue, skeletal muscle, kidneys, cardiovascular system, immune system and peripheral mitochondria. Although incretin hormones constitute the principal initiating signals within this network, physiological regulation is ultimately achieved through integrated actions of both incretin and non-incretin mediators including insulin, glucagon, amylin, fibroblast growth factor-21, bile acid signaling pathways, adipokines, hepatokines, myokines, autonomic neural pathways, inflammatory mediators, circadian regulators and intracellular nutrient-sensing mechanisms. Within this framework, physiological variables traditionally regarded as independently regulated — including fasting and postprandial glycaemia, hepatic fat content, insulin-glucagon balance, hepatic gluconeogenesis, lipid oxidation, triglyceride synthesis, resting energy expenditure, metabolic flexibility, mitochondrial function and inflammatory tone — are interpreted as emergent properties of coordinated network behaviour rather than isolated homeostatic endpoints. Furthermore, neurobehavioral determinants including psychological stress, sleep architecture, cognitive function, emotional state, personality traits and environmental influences continuously modulate network activity, thereby contributing to the unique metabolic phenotype observed in each individual. Accordingly, obesity, type 2 diabetes mellitus, metabolic dysfunction-associated steatotic liver disease, dyslipidaemia, sarcopenic obesity and cardio-renal-metabolic syndrome are viewed not as isolated disorders but as diverse clinical expressions of differential dysregulation within the same integrated metabolic network. This framework provides a mechanistic explanation for the superior efficacy of polyagonist therapies as network-restorative interventions rather than hormone replacement strategies and establishes a conceptual foundation for precision metabolic medicine based on characterization of network function instead of isolated biochemical abnormalities.

Abstract: This paper presents an open, anonymized dataset of academic service requests collected before and after an administrative process redesign in a multi-campus university in Ecuador. The dataset was extracted from the Sistema Nacional Académico and covers two consecutive six-month periods: PERIOD_1, representing the original processes, and PERIOD_2, representing the redesigned processes. It contains 432 aggregated records corresponding to 97,809 requests across three anonymized campuses, 25 request types, and 13 workflow states. Each record combines period, campus, request type, current state, and the aggregated request count, while preserving privacy through aggregation and removal of identifiers. Descriptive analyses show that request volume increased by 14.03%, approved requests increased by 24.27%, and the combined rate of four institutionally defined undesirable states decreased from 5.20% to 4.46%. The dataset, documentation, and reproducible analysis code are publicly available through Figshare and GitHub, supporting research on higher education administration, workflow analysis, institutional analytics, and process improvement.

Abstract: Molten salt-based thermal energy storage (TES) systems are widely deployed for large-scale energy storage; however, they currently utilize only sensible heat, limiting their energy density and overall efficiency. The utilization of latent heat in molten salts has the potential to significantly increase the extractable energy, but its practical implementation remains largely unexplored due to challenges related to solidification control, thermal stresses, and structural integrity. Addressing this gap is essential for improving the performance and economic viability of TES systems in renewable energy applications. This work presents the first combined experimental and numerical study demonstrating the safe and controlled utilization of latent heat in a molten salt TES system at semi-industrial scale. A vertical shell-and-tube heat exchanger integrated into a salt tank was investigated experimentally, enabling controlled melting and solidification of solar salt under realistic operating conditions. High-resolution spatial and temporal measurements of temperature and heat flux were used to establish detailed energy balances and characterize the thermal response during phase change. In addition, a validated three-dimensional CFD model was developed and validated against the measured temperature histories to predict the corresponding crystallization behaviour and support system optimization and scale-up. The combined experimental–numerical analysis provides new insights into molten salt solidification. While the thermal response was validated experimentally, the spatial distribution and temporal evolution of the solid phase were inferred from the validated CFD simulations. It is shown that complete solidification can increase the thermal energy yield by approximately 10%. However, an optimal operating strategy is identified at about 60% solidification, corresponding to an energy storage capacity of approximately 1300 kJ/kg within a temperature range of 550°C to 200°C. Beyond this point, heat transfer is significantly reduced due to the formation of insulating solid layers, and thermal stresses may compromise structural integrity. These findings demonstrate the technical feasibility of controlled latent heat utilization in the investigated molten salt TES configuration and provide new insight into the mechanisms governing frozen-layer growth and discharge performance under high-temperature operating conditions.

Abstract: This paper discusses the world of zero-day cyberattacks, which exploit unknown vulnerabilities that often slip past traditional defenses that rely on signatures. This situation has led to a push for behavioral detection methods that can adapt to new attack patterns. However, many intrusion detection systems that use machine learning are still tested on data that's been shuffled over time, which can lead to misleading results and a failure to account for changes in real-world traffic. To address these issues, we introduce a drift-aware continual generative behavioral-detection framework. This framework does three key things: it maintains an up-to-date baseline of normal behavior, uses generative techniques to maintain visibility into rare but significant patterns even when conditions change, and provides risk scores that are ready for Security Information and Event Management (SIEM) systems to support triage and correlation in security operations. To ensure our methods are robust, we have developed a reproducible evaluation protocol that relies on strict time-ordered data splits, stress tests focused on drift, and reporting that emphasizes practical aspects like latency, update frequency, and auditability. Our framework is designed to work with publicly available network traffic data and encourages transparent studies and sharing of findings for independent verification. By merging ongoing adaptation with careful evaluation and practical alerting, our approach aims to fill critical gaps that often hinder the reliability and readiness of cybersecurity research in high-stakes environments.

Abstract: Search is undergoing a structural shift from ranked retrieval and static retrieval-augmented generation (RAG) to agentic information seeking. Large language models (LLMs) now plan queries, browse pages, inspect evidence, maintain state, and synthesize answers or reports whose credibility depends on traceable external support. The resulting literature is fast-growing but difficult to compare. Web agents, search agents, agentic RAG systems, deep research agents, and multimodal browsing agents often reuse similar planners, retrievers, memories, verifiers, and writers, yet operate under different task regimes, evidence environments, output artifacts, tool budgets, and judging protocols. This survey argues that LLM-based search agents should be compared through a Search-Agent Comparison Contract that jointly specifies the task regime, evidence environment, evidence unit, control policy, output artifact, and evaluation contract. Using this lens, we delimit the field against traditional information retrieval, static RAG, generic LLM agents, and graphical user interface (GUI) agents. We then organize representative systems through comparison fields and executable workflow components, synthesize learning recipes from prompting and trajectory distillation to reinforcement learning, process rewards, verifier-guided search, test-time scaling, and multimodal orchestration, and consolidate benchmarks spanning BrowseComp-style browsing, GAIA/HLE-style assistant and frontier-reasoning tasks, long-form deep research, multimodal evidence-grounded search, and domain-specific settings. The central thesis is that progress should be measured not only by final-answer accuracy, but also by evidence quality, citation faithfulness, live-versus-frozen reproducibility, leakage control, cost, and artifact reporting. By synthesizing more than 400 works, this survey provides a reference map and a methodological foundation for building trustworthy search agents as accountable evidence-acquisition infrastructure.

Abstract:

Medicinal plants are important sources of bioactive phytochemicals and essential mineral elements with therapeutic potential. This study investigated the effects of extraction solvent polarity on the total phenolic content (TPC), total flavonoid content (TFC), and elemental composition of Nerium oleander, Bulbine frutescens, and Cotyledon orbiculata. Phenolic and flavonoid contents were determined spectrophotometrically, while elemental nutrients in N. oleander extracts were analyzed using inductively coupled plasma-optical emission spectroscopy. N. oleander exhibited the highest phenolic and flavonoid contents among the three species. Dichloromethane extracts yielded the highest TPC (6.936 ± 0.613 mg GAE/100 mg), whereas hexane extracts produced the highest TFC (8.793 ± 0.020 mg QE/100 mg). Extraction solvent significantly affected phenolic recovery (p < 0.05), with a significant interaction between solvent and plant species. Essential macroelements (Ca, Mg, Na and K) and micronutrients (Al, Mn, Zn and Fe) were detected, while Cr, Cu, Ni and Pb were absent or below detectable limits. These findings demonstrate the importance of solvent selection and highlight N. oleander as a promising source of phytochemicals and mineral nutrients for phytomedicinal and nutraceutical applications.

Abstract: A single paragraph of about 200 words maximum. Ecotourism has the potential to support biodiversity conservation and community development, particularly in biologically rich regions such as the Amazon. The Área de Conservación Regional Comunal Tamshiyacu Tahuayo (ACRCTT), located in the Loreto region of Peru, provides a case study in which local communities collaborate with ecotourism initiatives and researchers to protect biodiversity. This study examined whether varying levels of community involvement in ecotourism were associated with differences in conservation attitudes, knowledge, and self-reported conservation behavior. Semi-structured interviews were conducted with one adult from nearly every household in three adjacent villages within the ACRCTT between November and December 2019. The villages differed in ecotourism participation, allowing comparative analysis within a shared environmental and governance context. Findings indicated that villages with greater ecotourism involvement demonstrated significantly higher levels of self-reported conservation-oriented behavior. Employment in ecotourism was also positively associated with greater conservation awareness and knowledge, although conservation knowledge was more strongly associated with formal education. Qualitative responses suggested that residents perceived ecotourism as an alternative to hunting, logging, and other extractive activities. While the study design does not allow causal inference, the findings suggest that community-based ecotourism may contribute to conservation-oriented attitudes and behaviors by increasing environmental awareness and diversifying local livelihoods.

Abstract: Generative artificial intelligence has reduced the technical cost of producing scientific text, but increased output does not by itself produce cumulative knowledge, conceptual novelty, or epistemic progress. This article develops the Reinforcement Learning Contour (RLC) as a conceptual and architectural framework for converting AI-assisted scientific work from repeated document generation into governed recursive learning. The framework distinguishes an epistemic contour, Cₜ, from the governed transformation operator, Φₜ, through which a research episode may produce a successor contour. The contour records the time-indexed configuration of knowledge, ontology, relations, retrieval, evaluative criteria, inquiry policy, provenance, memory, tools, and governance constraints. The operator organizes evidence retrieval, source verification, adversarial evaluation, human approval, and reintegration. Changes in the answer-producing function within a contour are analytically separated from changes to the transformation operator itself; the latter are treated as Learning III-like events that cannot be autonomously committed and require an explicit human meta-decision. The central proposition is a differentiation principle: the value of a research cycle is proportional not to the quantity of text it produces but to the beneficial, traceable differentiation it creates between the preceding contour and the contours governing subsequent perception, interpretation, decision, and action. The framework is positioned relative to Popperian criticism, Lakatosian research programmes, Bateson’s orders of learning, double-loop learning, socially situated objectivity, provenance, temporal knowledge representation, and agentic science. It specifies a role-based architecture in which generation authority is strictly weaker than human acceptance authority; a twelve-step governed research cycle; a Structured Epistemic Change Record that documents change without collapsing quality into a scalar reward; novelty and anti-recursion controls; failure modes; seven falsifiable hypotheses; and a comparative pilot design. The proposal is explicitly unvalidated. Its claim is not that automation guarantees scientific progress, but that claims of recursive learning can be made more inspectable, contestable, and governable.

Abstract: Background and Clinical Significance: Cholangiocarcinoma (CCA) is molecularly heterogeneous, and the expanding number of actionable alterations has made comprehensive molecular profiling central to the management of advanced disease. This report presents two rare fusion-positive cases and reviews the molecular landscape, biomarker-directed therapies, resistance mechanisms, and clinically applicable sequencing strategies in CCA. Case Presentation: The first patient was a 63-year-old woman with metastatic biliary tract adenocarcinoma who experienced progression after multiple systemic therapies. Next-generation sequencing identified an NTRK1 fusion, and larotrectinib produced rapid metabolic regression, improvement in Eastern Cooperative Oncology Group performance status from 2 to 0, and durable disease control through June 2025. The second patient was a 29-year-old man with intrahepatic cholangiocarcinoma and primary resistance to gemcitabine–cisplatin. Detection of a RET fusion enabled treatment with selpercatinib, resulting in complete metabolic response and 19 months of disease control. At hepatic oligoprogression, thermal ablation permitted continuation of selpercatinib before subsequent progression. Conclusions: These cases demonstrate that rare NTRK1 and RET fusions can be clinically decisive in CCA. Routine DNA- and RNA-based molecular profiling, longitudinal reassessment, and multidisciplinary management may expand therapeutic opportunities and support individualized treatment beyond conventional histology-based pathways.

Abstract: Shot peen forming and creep age forming are the principal industrial routes for generating contour in metallic aircraft wing covers. Although the mechanics of both are well documented, neither has been examined with the patent record as the unit of analysis. This study assembles comparative corpora of 157 patent families spanning 1951 to 2026, by classification-anchored retrieval and systematic citation-network tracing, coding every family by claim type and determining its jurisdictional breadth and grant outcome. The two processes exhibit measurably different bottlenecks. Creep age forming devotes 40% of its corpus to tooling against 15% for shot peen forming, whereas shot peen forming devotes 24% to control and compensation against 8% for creep age forming. The binding constraint has been geometry transfer for the former and process control for the latter, so the two routes require different de-risking strategies. Three further results follow. The foundational era of shot peen forming is tri-national rather than exclusively American. Apparent Chinese dominance of the recent record survives neither normalisation against background filing nor a breadth measure, 96% of Chinese families being filed at a single office. Citation tracing rather than classification search is required to observe such a landscape.