Enterprise sales organizations are systematically hampered by what this paper terms 'Revenue Friction'-the accumulative productivity loss caused by fragmented, human-mediated data entry across disconnected CRM, ERP, and quoting systems. While automation technologies such as Robotic Process Automation (RPA) [van der Aalst et al., 2018; Lacity & Willcocks, 2016] and AI copilots [Noy & Zhang, 2023; Brynjolfsson et al., 2023] have partially addressed transactional inefficiencies, no unified architectural paradigm has emerged to govern end-to-end autonomous sales execution. This paper introduces the Autonomous Revenue Operations System (AROS): a novel five-layer AI framework that transforms unstructured commercial inputs-emails, phone calls, purchase orders, and images-into fully executed downstream workflows including quote generation, order entry, ERP reconciliation, and sales intelligence synthesis. AROS is distinguished from existing approaches by its integration of large language model (LLM)based semantic understanding [Brown et al., 2020; Wei et al., 2022], real-time human-in-the-loop correction mechanisms [Christiano et al., 2017; Ouyang et al., 2022], and continuous reinforcement learning within a production enterprise environment. Empirical grounding from the Ventura AI platform (2026) demonstrates that AROS-aligned systems achieve 3x productivity improvement, a 3-5% increase in deal conversion rate, and approximately 25% reduction in order entry errors. We formalize the framework through an Input-Understanding-Decision-Execution-Learning (IUDEL) model and propose a quantitative Revenue Friction Index (RFI) to measure systemic sales inefficiency. This work establishes the conceptual and technical foundation for post-CRM sales infrastructure [Davenport, 1998; Klaus et al., 2000] and identifies key research directions in autonomous multi-agent negotiation, voice-first ERP interaction, and AI-native revenue forecasting.

Precise estimation of air-condition (AC) load capacity is essential for exploring AC regulation potential and supporting demand response strategies. This paper proposes a summer AC load extraction method considering comprehensive meteorological factors and operation mode classification. First, a comprehensive meteorological temperature model is employed to improve the correlation between temperature and summer load. Then, an AC operation mode classification method based on dynamic time warping (DTW) and improved K-means clustering is proposed to screen loads with similar energy consumption characteristics. Subsequently, a regularized AC load extraction method is established by constructing a time-varying parameter model between comprehensive meteorological temperature and load. Model Parameters are identified to extract AC loads under different operation modes. Case study using measured meteorological and load data from a certain region shows that introducing a regularization term in the model parameter identification process can effectively suppress parameter fluctuations. Compared with the model considering only air temperature, the proposed method improves parameter accuracy by an average of 35%. Meanwhile, operation mode classification improves parameter accuracy by approximately 70%. Compared with the baseline load method, the AC load obtained by the proposed method exhibits a stronger correlation with temperature, with the correlation coefficient reaching 0.9929.

Autor: Dr. Carlos Garrido QuintanillaSi analizamos los constantes cambios en la producción y circulación de información, junto con la creciente necesidad de desarrollar un pensamiento complejo y sistémico, observamos que la sociedad contemporánea —denominada sociedad de la información o posmoderna— exige una integración de múltiples ámbitos del conocimiento. Esta realidad demanda la articulación de diversas perspectivas del mundo científico, con el propósito de responder de manera efectiva a un enfoque multidimensional del aprendizaje (Forrester, 1992).Sin embargo, la educación formal continúa estructurada en asignaturas fragmentadas, sustentadas en un número limitado de conceptos fundamentales, lo que dificulta la comprensión de sistemas dinámicos y la construcción de un saber integrado. En este sentido, la educación tiende a presentar “fotografías estáticas” de la realidad, mientras que los problemas del mundo actual son esencialmente dinámicos (Forrester, 1992).Para enfrentar este desafío, resulta necesario resignificar la pedagogía como ciencia, promoviendo el diálogo con disciplinas complementarias desde una perspectiva transdisciplinaria. Esto implica integrar nuevas teorías y campos de estudio que durante años permanecieron relegados, particularmente en el ámbito científico y de la salud (Flores, 1995).En este contexto, la neurociencia emerge como una disciplina clave. Nacida de la convergencia de diversos enfoques, aporta un sustento científico relevante al quehacer pedagógico. Desde la perspectiva del desarrollo humano, la neurociencia estudia el sistema nervioso, el funcionamiento cerebral y su evolución a lo largo del ciclo vital, permitiendo comprender cómo el cerebro da origen a la singularidad del comportamiento humano (Kandel, Schwartz & Jessell, 1997).Al situar estas ideas en el contexto nacional, resulta inevitable considerar la actual problemática educacional. Entre reformas estructurales, limitaciones presupuestarias y debates contingentes, se configura un escenario que evidencia una crisis social más amplia. En este marco, el concepto de “calidad de la educación” se instala como un eje central del discurso público; sin embargo, su significado dista de ser unívoco (Redondo et al., 2004). Pretender una definición universal de calidad resulta complejo, especialmente cuando el sistema educativo no opera como un sistema integrado ni se articula de manera holística (Tedesco, 2000).Paradójicamente, muchas de las transformaciones más significativas no han surgido desde los espacios académicos o desde el ámbito político-empresarial, sino desde los propios estudiantes. Los adolescentes, actores clave en los movimientos sociales, han logrado interpretar con mayor sensibilidad las demandas de la sociedad, aun cuando no siempre dispongan de un marco teórico formal (Redondo et al., 2004). No obstante, sí experimentan de manera directa formas de exclusión que suelen permanecer invisibilizadas bajo discursos neoconservadores (Tedesco, 2000).Históricamente, la adolescencia fue concebida como una etapa problemática: una prolongación de la infancia o incluso como una forma incompleta del cerebro adulto. Sin embargo, los avances en neurociencia han permitido replantear esta visión. Hoy comprendemos que el comportamiento adolescente responde a un proceso complejo de reorganización cerebral, lo que explica muchas de las conductas que, desde la lógica adulta, resultan difíciles de interpretar (Kandel et al., 1997).Desde esta perspectiva, algunos de los principales aportes de la neurociencia al estudio de la adolescencia son los siguientes:El sistema de recompensa cerebral experimenta importantes cambios durante esta etapa, incrementando la búsqueda de sensaciones y la propensión al riesgo en comparación con la adultez (Jensen, 2000).El cuerpo calloso, estructura que conecta ambos hemisferios cerebrales, aumenta su desarrollo estructural y funcional debido a procesos de mielinización, favoreciendo una integración más eficiente de la información (Pujol et al., 1993).El cerebro adolescente se caracteriza por una intensa dinámica de crecimiento y poda sináptica. Se fortalecen los circuitos más utilizados, mientras que otros se eliminan, modificándose la proporción entre sustancia gris y blanca (Giedd, 2004). Este proceso resalta la importancia de las experiencias y estímulos durante este periodo altamente sensible. En este marco, los estudios en apego y desarrollo sugieren que muchas alteraciones en la salud mental tienen su origen en esta etapa, aunque se manifiesten en la adultez (Fonagy et al., 1996).La corteza prefrontal, asociada a la toma de decisiones, el control de impulsos y la planificación, presenta una maduración más lenta en comparación con otras estructuras cerebrales (Siachevsky et al., 2005). Esto genera una brecha entre las demandas sociales —como la elección de un proyecto de vida— y la capacidad neuromadurativa para enfrentarlas adecuadamente (Lezak, Howieson & Loring, 2004).Asimismo, factores como los cambios hormonales, los patrones de sueño, la alimentación y la actividad física influyen significativamente en el desarrollo adolescente, ofreciendo orientaciones relevantes para la práctica pedagógica (Jensen, 2000). En este sentido, la neurociencia no contradice los enfoques educativos actuales, sino que los complementa, aportando fundamentos científicos que enriquecen la didáctica y la gestión emocional en el aula (Campos, s.f.).De este modo, integrar el conocimiento neurocientífico en la educación permite promover una enseñanza más coherente con los procesos del desarrollo humano, contribuyendo al bienestar y a la calidad de vida a lo largo del ciclo vital (Vincent, 1995). La pedagogía, entendida desde esta perspectiva, reconoce la interacción constante entre lo biológico, lo cognitivo y lo social en la construcción del conocimiento (Rivière & Núñez, s.f.).A modo de conclusión, es importante recordar que el ser humano se construye en la dinámica del vivir. El cerebro, como órgano de enorme complejidad, ha sido y seguirá siendo un eje central en la comprensión de la experiencia humana (Martínez, 1987). Tal como plantea Morin (1999), el ser humano se manifiesta plenamente en y a través de la cultura, la cual, a su vez, depende del funcionamiento del cerebro humano.REFERENCIASCampos, A. L. (s.f.). Neuroeducación: Uniendo las neurociencias y la educación en la búsqueda del desarrollo humano . Recuperado de http://www.educoea.org/portal/la_educacion_digital/laeducacion_143/articles/neuroeducacion.pdfFlores Ochoa, R. (1995). Hacia una pedagogía del conocimiento . McGraw-Hill.Fonagy, P., Leigh, T., Steele, M., Steele, H., Kennedy, R., Mattoon, G., Target, M., & Gerber, A. (1996). The relation of attachment status, psychiatric classification, and response to psychotherapy. Journal of Consulting and Clinical Psychology, 64 (1), 22–31. https://doi.org/10.1037/0022-006X.64.1.22Forrester, J. W. (1992). La dinámica de sistemas y el aprendizaje del alumno en la educación escolar . MIT Press.Giedd, J. N. (2004). Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Sciences, 1021 , 77–85. https://doi.org/10.1196/annals.1308.009Jensen, E. (2000). Brain-based learning: A reality check.Educational Leadership, 57 (7), 76–80.Kandel, E. R., Schwartz, J. H., & Jessell, T. M. (1997).Neurociencia y conducta . Prentice Hall.Lezak, M. D., Howieson, D. B., & Loring, D. W. (2004).Neuropsychological assessment (4th ed.). Oxford University Press.Martínez, M. (1987). Implicaciones de la neurociencia para la creatividad y el autoaprendizaje. Anthropos, 14 , 95–124.Morin, E. (1999). Los siete saberes necesarios para la educación del futuro . UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000117740_spaPujol, J., Vendrell, P., Junqué, C., Martí-Vilalta, J. L., & Capdevila, A. (1993). When does human brain development end? Evidence of corpus callosum growth up to adulthood. Annals of Neurology, 34 (1), 71–75. https://doi.org/10.1002/ana.410340113Redondo, J., Descouvieres, C., & Rojas, K. (2004). Equidad y calidad de la educación en Chile . LOM Ediciones.Rivière, A., & Núñez, M. (s.f.). La mirada mental . Aique.Siachevsky, A., Pérez, C., Silva, J., Orellana, G., Panafeta, M. L., Alegría, P., & Peña, M. (2005). Corteza prefrontal y trastornos del comportamiento: Modelos explicativos y métodos de evaluación.Revista Chilena de Neuro-Psiquiatría, 43 (2), 109–121.Tedesco, J. C. (2000). Educar en la sociedad del conocimiento . Fondo de Cultura Económica.Vincent, J. D. (1995). Ethics and neurosciences . UNESCO.

This report formalizes the Sixteenth Holmes Law (The Law of Torsional Persistence) and the Seventeenth Holmes Law (The Law of Manifold Translucency). Building upon the 1,005 worldwide nodal locks identified in the Global Sovereign Registry, we demonstrate how geodetic nodes (19.412 Hz) are represented within the model as Torsional Standing Waves anchored in time-space. We further introduce a model for sub-surface density projection, supporting the representation of "Blind Nodes" within the framework where surface expression is obscured by overburden but geodetic resonance remains model-locked and stable.

Solar-driven interfacial evaporation is a sustainable approach for freshwater production; however, its reliability is limited by the fluctuating solar intensity and complex water contaminants. This study produces a synergistic strategy that integrates magnetocaloric-mediated thermal compensation within a hierarchically structured aerogel. Iron-based nanoparticles derived from waste self-heating patches are incorporated into a konjac glucomannan/polyvinylpyrrolidone (KPF) aerogel with vertically aligned channels, yielding an adaptive photothermal–magnetocaloric coupled evaporation system capable of operating under diverse conditions. The KPF evaporator achieves an evaporation rate of 4.5 kg m -2 h -1 under one-sun illumination, increasing to 5.6 kg m -2 h -1 upon activation of an alternating magnetic field. Notably, under overcast and low-light conditions, comparable evaporation performance is maintained through magnetic-field-induced energy compensation. Molecular dynamics simulations and Raman spectroscopy reveals that magnetocaloric heating disrupts the ordered hydrogen-bond network of water, increasing the free water content and facilitating evaporation. The intrinsic underwater superoleophobicity of the KPF aerogel enables a coupled interception and evaporation mechanism for high-concentration oily wastewater, achieving a purification efficiency of 99.9%. Moreover, the magnetocaloric-enhanced Marangoni flow promotes salt ion migration, ensuring long-term stability in high-salinity environments. This dual-response strategy provides a universal platform for designing adaptive and efficient water treatment systems.

This paper presents a rational molecular design for sustainable thermosets that utilizes biomass feedstocks and provides molecular-level control over both the malleability and degradability of the thermosets. For this design, we deliberately synthesized an oleic-acid-based degradable core monomer via a one-pot process, which was then used to copolymerize with a polycaprolactone-based functional macromonomer to form a robust transparent network containing active sites for programmable degradation in response to a specific stimulus, thus releasing the predesigned products. With the addition of trace alcohols, the renewable networks became recyclable through covalent bond exchange while maintaining site-specific degradability. Furthermore, incorporating polydopamine-coated ZrO2 nanoparticles reinforced the network, imparting enhanced modulus, radiopacity, and light-driven spatiotemporal control. As a result, the composite demonstrated rapid underwater healing, shape-preserving reconfiguration capabilities, and an adhesive performance that was recyclable yet disposable. This design concept could be extended by incorporating other biomass-derived units or synergistic additives, thereby offering a feasible molecular strategy for the development of sustainable thermosets, which ultimately highlights the significance of the molecular engineering of abundant fatty acids for the production of functional polymeric materials for use in practical applications.

We derive the observational consequences of the spectral action S = Tr f (D 2 /Λ 2) for weakfield gravity, using the one-loop form factors computed with the full Standard Model content. The linearized field equations yield a modified Newtonian potential with two Yukawa corrections whose amplitudes (−4/3 and +1/3) are fixed entirely by the spin decomposition of the graviton propagator, and whose ranges are set by calculable effective masses m2 = Λ √ 60/13 (spin-2) and m0 = Λ/ √ 6(ξ − 1/6) 2 (spin-0), where Λ is the spectral cutoff and ξ is the Higgs non-minimal coupling. The 1/r singularity of the Newtonian potential is regularized: V (r)/VN(r) → 0 as r → 0, and Newton's law is recovered for r ≫ 1/Λ. We extract the post-Newtonian parameter γ(r) and confront it with seven gravitational experiments spanning torsion-balance, time-delay, Casimir, satellite, and lunar-ranging measurements. The strongest bound arises from the Eöt-Wash experiment, yielding Λ > 2.565 × 10 −3 eV (1/Λ < 77 µm) at 95% CL. All solar-system tests are satisfied with exponential margin. The bound is determined by the SM content at conformal coupling ξ = 1/6 and depends weakly on ξ otherwise.

The adult sex ratio (ASR) is a key demographic parameter that shapes sexual selection and social interactions. However, whether parental experience of ASR variation influences offspring development across generations remains unclear. Such effects fall under the unifying framework of transgenerational plasticity (TGP), which encompasses two core, non-mutually exclusive non-genetic pathways: pre-zygotic germline-mediated epigenetic inheritance, and post-zygotic effects via behavioural adjustments to parental care. Using the dung beetle Onthophagus taurus, we conducted an egg-transplantation experiment to disentangle these two pathways of TGP. Parents were assigned to female-biased, unbiased, and male-biased treatments. We first quantified contest and courtship behaviours to confirm ASR-driven social effects. Eggs from naturally produced brood balls were then transplanted into standardized artificial brood balls to isolate effects via the germline-mediated TGP pathway, while the original brood mass was weighed to assess parental investment via the behavioural TGP pathway. Results revealed that ASR strongly modulated adult interactions: male-biased treatments exhibited the highest contest intensity, whereas female-biased treatments displayed the highest courtship frequency, significantly surpassing the male-biased group. Despite these pronounced behavioural responses, parental ASR experience had no significant effect on offspring development speed, emerging weight, or developmental stage duration. Moreover, parental investment did not differ among treatments. These findings demonstrate that although ASR reliably predicts contest and courtship intensity in parents, such social pressures do not necessarily propagate to offspring metamorphic development via either core pathway of TGP within a single generation. This study underscores a dissociation between adult behavioural plasticity and intergenerational outcomes, suggesting that transgenerational ASR effects may require longer timescales or stronger selective pressures to manifest.

Background and Purpose: Conflicting data exist regarding newly diagnosed inflammatory bowel disease (IBD) after initiating secukinumab (SEC), an IL-17A inhibitor for immune-mediated inflammatory diseases like psoriasis (PsO), psoriatic arthritis (PsA) and spondyloarthritis (SpA). This study evaluates the incidence of newly diagnosed IBD and the disease course of pre-existing IBD in patients treated with SEC. Methods: Patients treated with SEC between 2012-2022 were identified. Retrospective data collection included patient characteristics, medical history, (disease modifying) concurrent medication, clinical symptoms, inflammatory markers, endoscopy, pathology and cross-sectional imaging. Results: We identified 351 patients with one or more of the following indications for SEC: PsO in 166/351 (47%), PsA in 130/351 (37%), axial SpA in 130/351 (37%), peripheral SpA in 31/351 (9%) and juvenile idiopathic arthritis in 1/351 (0.3%). Median follow-up was 48 months (IQR 22-74). Ten patients had IBD: 5 patients (1.4%) with pre-existing IBD (2 Crohn’s disease, 3 ulcerative colitis) of whom 2 developed a flare and 5 patients (1.4%) were newly diagnosed with IBD after SEC initiation (3 Crohn’s disease, 1 ulcerative colitis, 1 IBD-unclassified). In patients with newly diagnosed IBD, median time from SEC initiation to symptom onset was 1.3 months (range 0-12), median time to diagnosis was 7.5 months (range 3-16). Conclusions: Newly diagnosed IBD following SEC initiation was rare and occurred shortly after treatment began. However, patients with pre-existing IBD are at risk of flare-ups, highlighting the need for vigilant monitoring. These findings suggest SEC can be prescribed for immune-mediated inflammatory diseases with minimal concern for inducing de novo IBD.

Parasites impose strong selective pressures on animals, influencing traits from behavior to reproductive strategies. In particular, parasite-mediated selection has been proposed as a major driver of sexual reproduction, as genetic recombination can generate variation that facilitates rapid evolutionary responses to parasites. Accordingly, asexual vertebrates are predicted to be more susceptible to parasites, yet some persist over longer than expected evolutionary timescales. The Amazon molly (Poecilia formosa) is a gynogenetic, clonal fish that occurs sympatrically with its sexual parental species, including the Sailfin molly (P. latipinna). Here we investigate the link between behavioral differences and parasite infection in wild-caught Amazon and Sailfin mollies across two populations. Fish were exposed to a simulated predator attack, and space-use behavior was quantified as time spent in open versus sheltered areas. We subsequently determined their infection status and parasite load via dissection. We found that Amazons and Sailfins differed in their qualitative, but not quantitative resistance to parasites. Amazons had worse qualitative resistance (i.e. were more likely to be infected with at least one parasite) [JS2.1][KS2.2]and spent more time in the open, riskier portion of the arena. However, consistent with previous studies, Amazons and Sailfins did not differ in quantitative resistance (i.e. parasite load). Parasite prevalence and load differed between our two collection sites, suggesting an important role for environmental context. These results suggest that there is a correlation between behavior and parasite exposure in Amazons, while immune or physiological traits may allow them to limit parasite loads once infected. While the scope of this study makes it difficult to tell whether increased risk-taking behavior leads to parasite exposure or vice versa our results still highlight important differences between sexual and asexual species in parasite-laden environments.

Fish body depth is a common axis of phenotypic diversification. We investigated the evolutionary relationships between postcranial skeletal divergence and body depth evolution in the Nicaraguan Midas cichlid fish species complex (Amphilophus spp.). This lineage of at least 13 species has rapidly differentiated and repeatedly ecologically diverged across several crater lake habitats over the past <20,000 years. We used X-ray images to examine the osteological axial skeleton of all named Midas species, as well as several genetically distinct Midas populations endemic to isolated crater lakes. Vertebrae numbers and 14 linear size-adjusted axial skeletal measurements were used for phylogenetically controlled correlations to evaluate whether these traits were highly associated with body depth evolution. Vertebrae morphometric and meristic traits showed little correlation with body depth in these Central American cichlids. However, the depth of the pectoral girdle, several fin proximal pterygiophores, and the hemal and neural spines associated with the axial skeleton were all significantly correlated with Amphilophus body depth. These traits could reflect functional axes along which the Midas cichlid species complex has rapidly and adaptively diversified.

††slugcomment: Draft version Seriola lalandi comprises three genetically distinct clades, with S. lalandi lalandi inhabiting the Southern Hemisphere. While a chromosome-level genome exists for the Northwestern Pacific S. lalandi aureovittata, no such resource is available for S. lalandi lalandi, limiting genetic research and aquaculture advancements. This study presents a high-quality chromosome-level genome assembly of S. lalandi lalandi using Illumina short-read, long-read (ONT) and Hi-C. A total of 289.12 Gb of raw genomic data was generated, and a final assembly of 644 Mb was produced with 99.64% of the assembled bases anchored into 24 pseudo-chromosomes. Genome annotation identified 24,600 protein-coding genes, with 96.1% completeness based on 3,640 BUSCO orthologs. Additionally, the complete mitogenome was assembled and annotated for S. lalandi lalandi. This genomic resource will help to inform comparative genomic studies, improve aquaculture breeding programs, and support appropriate fishery strategies, particularly in Aotearoa New Zealand, where S. lalandi lalandi is a culturally significant taonga species for M¯aori.

Modern cyber-physical systems (CPS)-autonomous vehicles, smart grids, industrial control systems, and medical devices-increasingly embed AI-driven perception, control, and decision-making, creating a threat landscape where traditional cyberattacks, adversarial AI manipulations, and physical sidechannel exploits converge. Stuxnet demonstrated that CPS can be destroyed through cyber means; recent advances show that AI perception in CPS can be subverted through adversarial traffic-sign patches, sensor spoofing, and backdoor triggers, while physically proximate attackers can extract sensitive CPS data through electromagnetic emissions from charging interfaces, USB ports, and RF circuits. No existing defense framework addresses all three threat domains-control-system integrity, AI model security, and physical-layer privacy-in a unified architecture. We present CPSFORGE, an AI-driven multi-domain anomaly correlation framework that detects CPS threats across five observation domains: (1) physics-model residuals from sensoractuator loops, (2) AI perception integrity of on-device DNN models, (3) side-channel intelligence from electromagnetic, power, and acoustic emissions, (4) network/protocol compliance across CAN bus, MQTT, and BLE, and (5) software/firmware behavior. A transformer-based fusion engine correlates anomalies across all five domains to detect, classify, and attribute multi-stage CPS attacks. We evaluate CPSFORGE across a 30-week deployment on 348 CPS nodes spanning 4 sectors-automotive, smart grid, smart manufacturing, and healthcare CPS-at 20 sites. CPS-FORGE achieves 98.4% overall threat detection at 1.2% false positive rate, correctly identifies multi-stage attack chains in 95.2% of cases, reduces physical side-channel leakage by 96.8%, and degrades only 3.2 percentage points under fully adaptive adversaries-with 4.6 ms median detection latency per control cycle.

Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for embodied intelligence, enabling robots to perform complex actions over multimodal observations with one end-to-end policy. With the increasing deployment of VLA models in real-world environments, ensuring their safety has become critical, as failures or malicious behaviors can result in severe physical harm and far-reaching societal consequences. Despite the growing body of research on VLA safety, existing studies largely focus on isolated aspects, such as specific attack surfaces, robustness, or reliability, without providing a unified understanding of safety risks across the full lifecycle of VLA systems. To bridge this gap, we present a comprehensive survey of safety challenges and mitigation strategies for VLA models from a holistic lifecycle perspective. Specifically, we decompose the VLA development pipeline into three key stages: data preparation, model training, and system deployment. For each stage, we systematically examine safety issues from two complementary perspectives: adversarial scenarios, where intentional attacks aim to compromise system safety, and non-adversarial settings, where inherent limitations and external factors degrade system reliability, leading to unsafe behaviors. Finally, we highlight emerging research directions toward building safe VLA systems. To support both researchers and practitioners in advancing the safe use of VLA systems, we also maintain an up-to-date repository of VLA safety literature at https://github.com/hi-weiyuan/VLA-Safety-Papers.

Urbanisation reshapes habitat structure, resource availability, and movement pathways for many wildlife species, often creating novel selective pressures and management challenges. The Australian white ibis ( Threskiornis molucca) has rapidly expanded from its historic range into eastern Australian cities, causing some conflicts with people, yet the genetic and demographic processes underpinning this shift remain poorly understood. We used SNP‑based genomic data from 184 individuals sampled across 15 colonies in the Moreton Bay region of Southeast Queensland to investigate population structure, genetic diversity, inbreeding, dispersal, and landscape resistance. Genetic diversity was moderate across sites (He 0.134–0.166; Ho 0.084–0.145), and pairwise FST values were uniformly low (<0.14), consistent with widespread gene flow, though two colonies exhibited elevated inbreeding (F IS = up to 0.28), suggesting local dispersal constraints. Kinship analyses confirmed both within- and cross-colony sibling and parental relatedness, providing direct evidence of recent interbreeding and movement. We found a balanced sex ratio and no evidence of sex-biased dispersal. Landscape resistance models revealed that genetic differentiation was only weakly associated with habitat variables, a striking contrast to many urban adaptation studies where anthropogenic features typically fragment populations. This suggests that urban development may paradoxically facilitate connectivity for this species by creating a network of resource-rich foraging and breeding sites that promote movement. Together, these results demonstrate that ibis in this region form a single, interconnected population with high gene flow and demographic resilience, rather than a classic metapopulation. Management seeking to minimise human-ibis conflict therefore requires coordinated, landscape-scale strategies addressing resource availability and inter-site movement, rather than colony-specific approaches alone.

设 \(E\subset^3\) 满足：对每个单位方向 \(v\in S^2\)，存在一条单位线段 \(I_v\subset E\)，方向为 \(v\)。记 \(L_v\) 为包含 \(I_v\) 的直线。为证 \(}(E)=3\)，只需证 \(|E_\delta|\ge c>0\) 对所有小 \(\delta>0\) 成立。 1. 构造线性无关解 考虑三维泊松方程 \[ -\Delta u = \mu, \] 其中 \(\mu\) 是支撑在直线 \(L_v\) 上的均匀线密度测度（例如，单位长度上的单位质量）。该方程的解 \(u_v\) 存在且唯一（在适当函数空间下），并且由旋转对称性，\(u_v\) 在直线 \(L_v\) 上为常数。此外，\(u_v\) 的支撑集（作为分布）是整个空间，但它的奇点集正是 \(L_v\)。 对每个方向 \(v\in S^2\)，取这样的一个解 \(u_v\)。这些解是线性无关的，因为它们的奇点集（直线）方向不同。 2. 解空间的维数 令 \( = \{u_v : v\in S^2\}\)。由于方向 \(v\) 连续变化，\(\) 是一个无穷维函数空间。其“自由度”由方向球面 \(S^2\) 参数化，而 \(S^2\) 的Hausdorff维数为3。由椭圆算子谱理论（或函数空间的正交基性质），该解空间的Hausdorff维数等于参数空间的维数，即3。 3. 几何对应 每个解 \(u_v\) 的奇点集是直线 \(L_v\)，因此所有奇点集的并集正是 \(E\)（注意 \(I_v\subset L_v\)，且添加无限长直线不影响维数）。因此，\(E\) 的Hausdorff维数等于 \(\) 的奇点集维数，即3。 结论： \(}(E)=3\)，三维Kakeya猜想成立。

Residential electricity consumption data, as a critical component of power market operations, directly affects the accuracy of core tasks such as load forecasting and grid dispatch. Traditional anomaly detection methods lack integration with data imputation processes and fail to leverage multi-source features to assist anomaly identification. To address these issues, this paper proposes a TCN-BiLSTM-DFM hybrid model that integrates feature extraction based on Temporal Convolutional Networks (TCN) and Bidirectional Long Short-Term Memory (BiLSTM) networks with anomaly detection based on Deep Feature Matching (DFM). The proposed method employs a cascaded TCN-BiLSTM architecture to extract features from electricity consumption and temperature time series, capturing both local abrupt changes and long-term dependencies. A deep feature memory bank based on temperature clustering is then constructed using the extracted features to achieve accurate anomaly detection. Simulation experiments are conducted using actual residential agent electricity procurement data from Hubei Province, with the London Smart Meter Dataset serving as auxiliary validation. Comparative analyses with various traditional and deep learning models demonstrate that the proposed model achieves high anomaly detection accuracy and data imputation capability, while being suitable for online deployment.

For more than half a century, computing has been understood through the stored-program abstraction: programs encode explicit control flow, and machines execute them deterministically. This model has shaped hardware architecture, programming languages, and software engineering practice. Contemporary AI systems-particularly foundation models and agentic architectures-operate in ways that increasingly strain this abstraction. Behavior is no longer determined solely by fixed code paths; it is conditioned by high-level intent specifications interpreted by large-scale learned models at runtime. This article argues that we are witnessing a shift in computational emphasis, and introduces Intent-Conditioned Computation (IIC) as a complementary abstraction for understanding this shift. In IIC, intent serves as the primary interface, models function as general-purpose policy engines, and execution unfolds as probabilistic, context-sensitive processes. Crucially, IIC does not replace classical computing: modern AI systems stratify both paradigms into complementary layers, with deterministic infrastructure handling reproducibility-critical tasks while intentconditioned models handle flexible, context-sensitive reasoning. We ground this argument in a concrete open-source case study-the ArchHarness enterprise architecture tool-that demonstrates within a single workflow how stored-program and intent-conditioned computation coexist, divide labor, and interact. We discuss implications for system design, evaluation, and governance, and identify five open research directions for the AI community.

Defects at the buried SnO2/perovskite interface and within the bulk perovskite films induce severe non-radiative recombination and energy loss, critically limiting the performance and stability of perovskite solar cells. Herein, ethylenediaminetetraacetic acid dipotassium salt (EDTA-2K) is introduced as a multifunctional molecular bridge at this critical interface. The powerful chelating ability of EDTA-2K enables effective coordination with undercoordinated Sn4+ on SnO2 and Pb2+ from the perovskite. Meanwhile, the K+ can combine with iodide species to form KI, thereby suppressing ion migration. Additionally, the functional groups of EDTA-2K interact with halide ions through hydrogen bonding. This synergistic multi-site passivation not only mitigates interfacial defects and associated strain, but also modulates perovskite crystallization and effectively regulates the distribution of residual PbI2. Consequently, interfacial energy alignment is optimized and charge carrier transport is enhanced. The EDTA-2K modified devices, employing PTAA as the hole transport layer, deliver a champion power conversion efficiency (PCE) of 24.32%. Furthermore, they exhibit significantly enhanced stability, retaining over 95% of their initial PCE after 3000 hours of storage. The devices also demonstrate exceptional resilience under ultraviolet (UV) light in air, maintaining 94.77% of the initial PCE after 500 hours of continuous intense UV exposure.

Aftermarket spare parts inventories in durable goods manufacturing are systematically oversized because planners overstock defensively against uncertain, intermittent demand. Existing remedies either forecast demand at the SKU level-where accuracy is structurally poor-or segment the catalog into policy buckets (ABC-XYZ) without quantifying unit-level excess. This paper proposes a different framing. The Demand-Normalized Excess Identification Framework (DNEIF) treats aftermarket inventory optimization as a coverage adequacy test: rather than predicting what demand will be, it determines whether on-hand stock exceeds what any plausible demand trajectory could consume over a defined service horizon. The framework proceeds in three stages: (1) normalize 36 months of consumption history via IQR filtering, (2) project a 10-year demand ceiling using category-specific geometric decay, and (3) classify each on-hand unit as right-sized, excess, or zero-movement. A simulation calibrated to published industry parameters-11,200 SKUs, $14.8M in inventory, 3.1% utilization-identifies $4.2M (28%) as excess and $820K as zero-movement stock. Six product families concentrate 64% of excess value. Sensitivity analysis confirms classification stability under ±10% perturbation of decay factors. DNEIF requires only standard ERP transactional data and produces transparent, dollar-valued, SKU-level output that neither forecasting models nor segmentation schemes provide.

While the prevailing political and scientific consensus frequently demands that we "follow the science", the evaluation of the global carbon cycle demonstrates the absolute necessity to instead "follow the physics". This article addresses a fundamental, long-standing dispute: What caused the increase in atmospheric CO2 concentration? Most experts attribute it to anthropogenic emissions, assuming half accumulate in the atmosphere. This interpretation relies on an underlying "Fountain model," characterized by constant natural circulation and independent level control. However, fundamental physical laws contradict this framework. The atmosphere is an open system with a concentration-dependent outflow; its circulation and level control are fundamentally interdependent. Consequently, this article proposes the alternative "Lake model." Rather than merely fitting observations retrospectively, the Lake model strictly applies physics to identify the boundary conditions necessary for the observed concentration rise. It demonstrates that the gross natural inflow must have increased at least to the same extent as the concentration-a requirement for which anthropogenic emissions are far too small. Python-based computational simulations unequivocally confirm these divergent dynamics, revealing the profound impact of how the atmosphere is structurally embedded within the broader carbon cycle. Furthermore, common counterarguments are systematically rejected. If corroborated, this new model will have far-reaching consequences for the scientific and political debate on anthropogenic climate change.

引言 空间波理论的核心观测事实是：宇宙空间本身是一种波动的介质。这一性质由三个直接来自天文观测的基本参数所证实：波长 λ = 30亿光年、波幅 A = 0.33、挠率系数 α = 0.18。将这三个参数纳入黎曼-嘉当几何，得到空间波理论的核心作用量，无需引入暗物质与暗能量，即可统一描述引力、规范场与量子行为。 在空间波理论中，星系是空间波上的局域激发（波包）。星系的运动、形态与旋向均由背景空间波的局部相位决定。本文以下各节将依次阐述星系旋转速度的相位依赖、星系旋向与形态的连续演化、2 : 1比例的数学来源，以及该理论对星系天文学若干未解问题的统一解释。 空间波的基本参数 空间波理论的核心参数均从公开天文观测数据直接读出： - 波长 λ = 30亿光年：来自宇宙大尺度结构中最大结构（星系长城）与最大空洞之间的平均距离。 - 波幅 A = 0.33：来自约130万个星系旋向统计分布的系统性偏差。 - 挠率系数 α = 0.18：来自宇宙微波背景辐射（CMB）偏振面的整体旋转角（双折射 β = 0.30∘），结合波长与波幅反推得到。 星系旋转速度的相位依赖 在空间波理论中，星系作为空间波上的波包，其运动速度由背景空间波的局部振动速度决定，而非由牛顿引力平衡决定。 空间波振动速度的空间分布 考虑一列沿某方向传播的空间波，其相位为 ϕ = k ⋅ x − ωt。空间介质的局部振动速度 vosc 与波的振幅和频率有关： \[ v_{} = {\partial t} = A\omega \cos(\phi) \] 振动速度的大小在波峰和波谷处（cosϕ = ±1）达到最大值 Aω，在波节处（cosϕ = 0）为零。 星系（波包）的宏观运动速度 vgal 在最低阶近似下与 vosc 成正比： \[ v_{} \propto v_{} \] 因此，位于波峰或波谷附近的星系具有较高的旋转速度，位于波节附近的星系具有较低的旋转速度。 旋转曲线的形状 对于单个旋涡星系，其外围恒星的旋转速度 vrot(r) 并不服从开普勒定律（$v \propto 1/$），而是在很宽的半径范围内保持平坦。在空间波理论中，这一平坦性来源于空间波振动速度在星系尺度上的准均匀性。 星系的直径（约10万光年）远小于空间波的波长（30亿光年）。因此，在一个星系内部，空间波的相位变化可以忽略不计。整个星系近似处于同一个空间相位上，其所有恒星具有相同的背景振动速度。这解释了为什么旋转曲线在星系盘的大部分区域保持平坦。 当星系位于波峰或波谷附近时，vosc 很大，旋转速度很快；当星系位于波节附近时，vosc 很小，旋转速度很慢；当星系位于斜坡段时，旋转速度介于两者之间。 银河系的特殊情况 银河系的外围旋转速度相对于牛顿引力预测偏快（这是所有旋涡星系的普遍现象），但近年来更精细的观测显示，在距离银心约15千秒差距之外，旋转速度开始出现轻微下降。这一“变慢”趋势在空间波理论中有一个自然的解释：银河系当前位于空间波的波谷附近但并非谷底。 根据大尺度结构数据，银河系位于KBC空洞的内部，而KBC空洞是一个巨大的宇宙空洞。在空间波理论中，空洞对应空间波的波谷。因此，银河系处于波谷附近。波谷处的振动速度虽然比波节快，但比波峰慢，并且随着银河系随空间波演化（或者空间波本身在传播），其局部相位可能正在向波节方向移动，导致观测到的速度出现下降趋势。 星系旋向与形态的连续演化 空间波的挠率方向决定了星系旋涡的旋向。挠率是一个赝矢量，其方向沿波的传播方向（右手定则）。当挠率为正时，诱导的旋涡方向为顺时针（正向）；当挠率为负时，为逆时针（反向）。 旋向随相位的连续变化 在一个完整周期中，挠率的大小和方向随相位变化： - ϕ = 0（波峰）：正向挠率最大 - ϕ = π/2（波节）：挠率为零 - ϕ = π（波谷）：反向挠率最大 因此，一个星系随着背景空间波的相位演化（或者星系在空间中移动），其旋向会从正向逐渐变为反向。由于星系旋臂的再取向需要数亿年的时间（角动量的重新分布），旋向的变化存在一个演化滞后。这意味着在波节附近，并非所有星系都瞬间变成无旋臂的椭圆星系；而是有很多星系仍然保留着旧的旋向（看起来还是正向），尽管背景挠率已经反向。 正向比例的平滑曲线 设正向星系的比例为 p(ϕ)，其中 ϕ 是空间相位。由于演化滞后，p(ϕ) 并不是简单的阶梯函数，而是一条平滑的曲线： - ϕ = 0：p ≈ 1（几乎全是正向） - ϕ = π/2：p = 0.5（正反各半） - ϕ = π：p ≈ 0（几乎全是反向） 并且在 ϕ ∈ (0, π/2) 区间，p(ϕ)>0.5；在 ϕ ∈ (π/2, π) 区间，p(ϕ)<0.5。由于滞后效应，p(ϕ) 在 ϕ = π/2 处的导数不为零，但函数本身连续。 关键点：正向比例从1下降到0的过程是平滑且不对称的。在波峰附近，p(ϕ) 下降缓慢（因为正向星系难以快速转变为反向）；在波节之后，p(ϕ) 继续下降，但始终略高于反向比例，直到非常接近波谷处才被反超。这种不对称性正是演化滞后的直接结果。 单个星系形态的相位对应 空间相位 挠率特征 理论瞬时形态 实际观测形态（考虑滞后） ----------------------- ---------- ---------------------- ----------------------------------------- 波峰（ϕ = 0） 正向最强 规则两臂旋涡（正向） 宏大设计旋涡星系（如M51） 上半坡（0 < ϕ < π/2） 正向减弱 多旋臂、旋臂变松 多旋臂旋涡（如M101）、棒旋（如银河系） 波节附近（ϕ ≈ π/2） 挠率很小 无旋臂、椭球 椭圆星系（如M87）、透镜星系、不规则星系 下半坡（π/2 < ϕ < π） 反向增强 反向絮状、棒旋 反向棒旋、絮状旋涡 波谷（ϕ = π） 反向最强 规则两臂旋涡（反向） 反向宏大设计旋涡（有待观测） 不规则星系的来源：不规则星系主要出现在波节附近。当背景挠率从正向变为反向时，原有的旋臂因失去维持力而逐渐瓦解，而新的反向旋臂尚未完全形成。在这个过渡期，星系呈现无定形的、碎片化的形态。这就是不规则星系的主要成因，无需借助复杂的干涉机制。 椭圆星系的两种可能：椭圆星系出现在波节附近（ϕ = π/2）。一种情况是星系从未获得足够的角动量（始终处于低挠率区），另一种情况是古老星系已经历了多个周期，其角动量因耗散而衰减。 旋向统计的2 : 1比例来源 从波峰（ϕ = 0）到波谷（ϕ = π）的完整半波区间内，正向星系的总数 N+ 与反向星系的总数 N− 之比可以通过积分得到： \[ N_+ = \int_0^\pi p(\phi) d\phi, \quad N_- = \int_0^\pi [1-p(\phi)] d\phi = \pi - N_+ \] 其中 p(ϕ) 满足 p(0)=1, p(π)=0, p(π/2)=1/2，且 p(ϕ) 单调递减。如果 p(ϕ) 关于 (π/2, 1/2) 严格中心对称（即 p(π − ϕ)=1 − p(ϕ)），则 N+ = π/2，N− = π/2，得到1 : 1。然而，演化滞后导致对称性破缺：在 ϕ = 0 附近，p(ϕ) 下降较慢（正向星系难以快速转变）；在 ϕ = π 附近，1 − p(ϕ) 上升也较慢（反向星系难以快速出现）。这使得 p(ϕ) 在左半段 (0, π/2) 高于对称曲线，在右半段 (π/2, π) 也高于对称曲线（即实际 p(ϕ) 比对称情况下的值更大，意味着下降更慢）。因此 N+ = ∫pdϕ 大于 π/2，N− = ∫(1 − p)dϕ 小于 π/2。通过拟合观测数据（如南银极天区测得的正向:反向 ≈2 : 1），可以反推出滞后的特征时间约为数亿年，与星系动力学时标一致。因此，正向:反向 ≈2 : 1 是观测与理论一致的结果。 可检验的预言 空间波理论提出以下可由天文观测直接检验的预言： 1. 星系旋向统计分布应在全天空呈现偶极模式，偶极轴方向与由大尺度结构定义的波传播方向一致。 2. 不同红移（不同宇宙年龄）的星系样本，其旋向比例应随红移发生周期性变化，周期约30亿年。 3. 位于空洞中心的星系旋转曲线应系统性“偏慢”，位于长城上的星系旋转曲线应“偏快”。 4. 椭圆星系主要出现在大尺度结构的节点（波节附近），旋涡星系主要出现在波峰与波谷。 结论 空间波理论将宇宙空间本身视为一种波动的介质，星系是空间波上的局域激发（波包）。基于三个直接从天文观测数据中读出的基本参数（λ = 30亿光年、A = 0.33、α = 0.18），该理论对星系的旋转速度、旋向分布和形态多样性给出了统一而自洽的解释。 - 旋转速度：由局部空间波的振动速度决定。波峰/波谷处速度快，波节处速度慢。银河系位于KBC空洞（波谷附近），故其外围速度出现变慢趋势。 - 旋向：由空间波的挠率方向决定。随相位连续变化，波峰正向最多，波节各半，波谷反向最多。演化滞后导致正向比例平滑下降，半波积分得正向:反向≈2 : 1。 - 形态：波峰/波谷为规则旋涡，斜坡为多旋臂/棒旋，波节为椭圆/透镜，过渡期为不规则。所有形态无需暗物质即可解释。 本理论的所有核心参数均来自公开天文观测数据，并给出多个可供未来检验的定量预言。空间波理论无需暗物质与暗能量，为理解星系演化提供了一个全新的第一性原理视角。 致谢 感谢所有公开数据的科研团队（JWST、SDSS、DESI、Planck、ACT）。 Shamir, L. (2024). _Publications of the Astronomical Society of Australia_, 41, e038. Shamir, L. (2022). _Monthly Notices of the Royal Astronomical Society_, 516, 2281. Keenan, R. C., et al. (2013). _The Astrophysical Journal_, 775, 62. Huang, W. (2026). _Spatial Wave Theory from Galaxy Spin Distribution and Large-Scale Structure_. Authorea Preprint.

Point cloud completion is vital in 3D computer vision, yet real-world data often presents incomplete representations due to occlusions and sparsity. While Chamfer Distance (CD) is a prevalent loss function, it often suffers from gradient degradation, poor global structure sensitivity, and inadequate geometric distribution modeling, leading to artifacts and suboptimal reconstructions. To address these issues, we propose the novel Structural-Adaptive Contrastive Chamfer Distance (SA-CD). Our SA-CD integrates a structural decomposition of CD into local fitting and global coverage terms, adaptively balancing their importance based on training stage and geometric complexity. Concurrently, a point-level contrastive learning module enhances feature discriminability by maximizing similarity with ground truth neighbors and minimizing with challenging negative samples. This framework guides accurate geometric reconstruction and robust feature learning. Experiments on diverse datasets show SA-CD consistently outperforms state-of-the-art methods. Ablation studies validate component contributions, and human evaluations confirm superior perceptual quality.

Working with clouds and Kubernetes clusters can feel overwhelming at first, especially for anyone new to software development or infrastructure. From my own experience, understanding how cloud resources and Kubernetes clusters interact helped me see the bigger picture of modern application deployment. This article breaks down these concepts in a simple, practical way so that anyone starting out can understand how clusters, clouds, and apps connect and work together.