We integrate Penrose's (1959) theory of firm growth with the spinout literature to identify a previously overlooked type of new venture: the Penrosean spinout. Penrose identified the accumulation of managerial capacity as a natural byproduct of routine firm operations and a catalyst of firm growth. However, managerial capacity may also accumulate in non-managerial employees, particularly in low-tech sectors such as the trades, where workers readily observe and absorb the full range of activities required to run an enterprise. When it does accumulate, excess managerial capacity may catalyze not firm growth but new firm formation — a spinout. In a pure Penrosean spinout, employer and employee need not disagree about the product, the market, or the production process; they disagree about whether to expand the business, and on what terms. Our framework makes three contributions. First, it identifies an endogenous mechanism of entrepreneurial entry: the seeds of new firm formation are sown continuously in the normal course of business, not only in response to technological disruption or novel market insight. Second, it explains persistent industry fragmentation in low-tech sectors as a structural consequence of the routine leakage of managerial capacity through spinouts. Third, it offers a novel account of why noncompete agreements and occupational licensing are prevalent among low-wage workers who possess little proprietary technical knowledge. By extending spinout theory beyond high-tech contexts, we contribute to a more comprehensive understanding of the emergence of entrepreneurial firms.
Aviation safety incident reports are largely composed of unstructured narrative text, creating significant barriers to systematic causal analysis and proactive risk management. This study introduces an automated framework that employs Large Language Models (LLMs) to construct the Aviation Safety Hazard Causal Knowledge Graph (ASH-CKG). By combining few-shot learning with a hybrid relation normalization strategy, the framework reduced around 3000 relation variants to 185 canonical expressions (a 93.71% reduction in diversity), ensuring the structural rigor required for safety analysis. To facilitate dynamic, decision-oriented querying of the static graph, we developed a Retrieval-Augmented Generation (RAG) with Path-pruning and Chain-of-Thought (RAG-P-CoT-QA) module, which optimizes multi-hop subgraph retrieval and generates logically coherent, contextually relevant responses. Quantitative evaluations show that the proposed framework achieves competitive answer relevance while improving semantic similarity and evidence grounding over the Vanilla KG-QA baseline. Crucially, this framework empowers safety managers to transition from basic information retrieval to proactive decision support, offering a data-driven foundation for uncovering latent risk interactions and refining safety mitigation strategies within Safety Management Systems (SMS).
Advances in understanding the molecular landscape of gastroesophageal junction (GEJ) adenocarcinoma underscore the need for biomarker-driven treatment approaches. The Society of Surgical Oncology (SSO) Gastrointestinal (GI) Disease Site Working Group has developed practice guidelines for the biomarker-based management of nonmetastatic GEJ adenocarcinoma, with specific integration of microsatellite instability (MSI) status. Although multimodal therapy has improved outcomes, treatment strategies for GEJ adenocarcinoma remain largely stage-based rather than biomarker-directed. With emerging evidence supporting the prognostic and predictive roles of MSI-high (MSI-H), human epidermal growth factor receptor 2 (HER2), and other novel targets, there is an urgent need for clear guidance on how to incorporate biomarkers into the management of resectable disease. These guidelines provide evidence-based recommendations to support precision oncology in GEJ cancer care.
Combinations of additive manufacturing methods such as inkjet printing and various 3D printing techniques have led to advances in customizable electronic devices by reducing the need for the complex assembly of individually fabricated components. Such combinations are particularly attractive for the fabrication of electrochemical sensing platforms, where the sizes and spatial configurations of electrodes enable (or limit) the sensitivity of the sensors. However, to realize the potential of the combined fabrication methods, the parameters of each printing technique must be mutually compatible. For instance, electrochemical sensing assemblies consisting of inkjet-printed metals on 3D-printed plastics require post-processing steps that convert nanoparticular metals in precursor ink to conformal, mechanically stable, conductive films with negligible alteration to the underlying plastic substrate. While traditional sintering techniques convert inks to conductive metal films, the use of high temperatures are not compatible with structures printed via fused deposition modeling, for instance. In this proof-of-concept study, commercial gold inks were inkjet-printed onto 3D-printed poly(lactic acid) (PLA) substrates. Optimization of the printing parameters and IR sintering resulted in stable, electrochemically active working electrodes. Surface characterization via scanning electron microscopy confirmed the formation of a homogeneous coating, and X-ray photoelectron spectroscopy data revealed the presence of gold on the surface. Electrical characterization via a four-point probe demonstrated a low sheet resistance, indicating the suitability of these electrodes for electrochemical measurements. Electrochemical data revealed that these gold electrodes are electrochemically active, and the diffusion-limited behavior of a redox probe was observed as expected. Additionally, these electrodes were tested for detecting lead in standard solutions, showing a linear response to lead concentrations, which indicates their potential in sensing applications. However, the detection range is significantly higher than the EPA-approved limit for lead concentrations in water, suggesting that electrode sensitivity requires further improvement. These findings have implications for fabricating inkjet-printed gold electrodes as sensors while highlighting the need for additional modifications to meet regulatory detection limits for heavy metal analysis.
The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 3,200 new measurements from 903 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Most of the 118 reviews are updated, including many that are heavily revised. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 96 review articles. Volume 2 consists of the Particle Listings and contains also 22 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group ( pdg.lbl.gov ) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app. The PDG API (Application Programming Interface) provides access to the data published in the Review in machine-readable format.
