Scaling laws relating body mass to species characteristics are among the most universal quantitative patterns in biology. Within major taxonomic groups, the 4 key ecological variables of metabolism, abundance, growth, and mortality are often well described by power laws with exponents near 3/4 or related to that value, a commonality often attributed to biophysical constraints on metabolism. However, metabolic scaling theories remain widely debated, and the links among the 4 variables have never been formally tested across the full domain of eukaryote life, to which prevailing theory applies. Here we present datasets of unprecedented scope to examine these 4 scaling laws across all eukaryotes and link them to test whether their combinations support theoretical expectations. We find that metabolism and abundance scale with body size in a remarkably reciprocal fashion, with exponents near ±3/4 within groups, as expected from metabolic theory, but with exponents near ±1 across all groups. This reciprocal scaling supports "energetic equivalence" across eukaryotes, which hypothesizes that the partitioning of energy in space across species does not vary significantly with body size. In contrast, growth and mortality rates scale similarly both within and across groups, with exponents of ±1/4. These findings are inconsistent with a metabolic basis for growth and mortality scaling across eukaryotes. We propose that rather than limiting growth, metabolism adjusts to the needs of growth within major groups, and that growth dynamics may offer a viable theoretical basis to biological scaling.
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http://dx.doi.org/10.1073/pnas.1900492116 | DOI Listing |
Dirac-vortex cavities have single-mode emitting, scalable mode areas, arbitrary mode degeneracies, and vector-beam vertical emission, which attract more and more researchers' attention. Here, we demonstrate the single-mode of two-dimensional transverse magnetic (TM) Dirac-vortex topological cavity modes that are not only generally available for high power topological surface-emitting lasers (TCSEL) but also are one of the excellent candidates for refractive index sensors. The principle for winding number is studied, and the scaling laws are shown with cavity mode diameters.
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February 2025
Department of Physical Chemistry and Materials Science, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111, Budapest, Hungary.
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January 2025
Department of Psychiatry and Psychotherapy, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
Background: Dialectical behavioral therapy (DBT) and repetitive transcranial magnetic stimulation (rTMS) are both effective in treating borderline personality disorder (BPD). Impulsivity and impaired decision-making are prominent features of BPD, and therapeutic interventions targeting these symptoms could lead to significant improvements.
Objective/hypothesis: We hypothesized that intermittent theta burst stimulation (iTBS), a modified rTMS protocol that targets the left dorsolateral prefrontal cortex, would enhance the therapeutic effects of DBT, leading to greater improvements in impulsivity and decision-making compared with sham stimulation.
ISA Trans
January 2025
College of Control Science and Engineering, Bohai University, Jinzhou 121013, Liaoning, China. Electronic address:
This paper investigates the optimal fixed-time tracking control problem for a class of nonstrict-feedback large-scale nonlinear systems with prescribed performance. In the process of optimal control design, the new critic and actor neural network updating laws are proposed by adopting the fixed-time technique and the simplified reinforcement learning algorithm, which both guarantee the simplified optimal control algorithm and accelerate the convergence rate. Furthermore, the prescribed performance method is contemplated simultaneously, which ensures tracking errors can converge within the prescribed performance bounds in fixed time.
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January 2025
From the Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany.
Background Large-scale secondary use of clinical databases requires automated tools for retrospective extraction of structured content from free-text radiology reports. Purpose To share data and insights on the application of privacy-preserving open-weights large language models (LLMs) for reporting content extraction with comparison to standard rule-based systems and the closed-weights LLMs from OpenAI. Materials and Methods In this retrospective exploratory study conducted between May 2024 and September 2024, zero-shot prompting of 17 open-weights LLMs was preformed.
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