Electromagnetic field in matter. Surface enhanced Raman scattering

The polarization and magnetization degrees of freedom are included in the general treatment of the electromagnetic field in matter, and their governing equations are given. Particular cases of solutions are discussed for polarizable, non-magnetic matter, including quasi-static fields, surface plasmons, propagation, zero-point fluctuations of the eigenmodes, especially for a semi-infinite homogeneous body (half-space). The van der Waals London-Casimir force acting between a neutral nano-particle and a half-space is computed and the response of this electromagnetically coupled system to an external field is given, with relevance for the surface enhanced Raman scattering

Radical heminephrectomy for left sided upper pole renal tumor on horseshoe kidney – case report and review of the literature

Ion Chiricuţă Oncological Institute Cluj Napoca, Al V-lea Congres de Urologie, Dializă şi Transplant Renal din Republica Moldova cu participare internaţională (1-13 iunie 2011)Abstract Tumoral pathology of the horseshoe kidney is a rare pathology, only half of the tumors represent renal cell carcinoma. We will present the case of a 45 year old man known with horseshoe kidney diagnosed with a large renal tumor on the left side. CT angiography was performed preoperatively to asses the vascular anomalies of the renal pedicle and it was used for planning the surgical approach. The approach was transperitoneal by subcostal incision with lateral paramedian extension

NeuroBench:Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles. However, the rich diversity of techniques employed in neuromorphic research has resulted in a lack of clear standards for benchmarking, hindering effective evaluation of the advantages and strengths of neuromorphic methods compared to traditional deep-learning-based methods. This paper presents a collaborative effort, bringing together members from academia and the industry, to define benchmarks for neuromorphic computing: NeuroBench. The goals of NeuroBench are to be a collaborative, fair, and representative benchmark suite developed by the community, for the community. In this paper, we discuss the challenges associated with benchmarking neuromorphic solutions, and outline the key features of NeuroBench. We believe that NeuroBench will be a significant step towards defining standards that can unify the goals of neuromorphic computing and drive its technological progress. Please visit neurobench.ai for the latest updates on the benchmark tasks and metrics

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles. However, the rich diversity of techniques employed in neuromorphic research has resulted in a lack of clear standards for benchmarking, hindering effective evaluation of the advantages and strengths of neuromorphic methods compared to traditional deep-learning-based methods. This paper presents a collaborative effort, bringing together members from academia and the industry, to define benchmarks for neuromorphic computing: NeuroBench. The goals of NeuroBench are to be a collaborative, fair, and representative benchmark suite developed by the community, for the community. In this paper, we discuss the challenges associated with benchmarking neuromorphic solutions, and outline the key features of NeuroBench. We believe that NeuroBench will be a significant step towards defining standards that can unify the goals of neuromorphic computing and drive its technological progress. Please visit neurobench.ai for the latest updates on the benchmark tasks and metrics

NeuroBench:A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems

Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. Prior neuromorphic computing benchmark efforts have not seen widespread adoption due to a lack of inclusive, actionable, and iterative benchmark design and guidelines. To address these shortcomings, we present NeuroBench: a benchmark framework for neuromorphic computing algorithms and systems. NeuroBench is a collaboratively-designed effort from an open community of nearly 100 co-authors across over 50 institutions in industry and academia, aiming to provide a representative structure for standardizing the evaluation of neuromorphic approaches. The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings. In this article, we present initial performance baselines across various model architectures on the algorithm track and outline the system track benchmark tasks and guidelines. NeuroBench is intended to continually expand its benchmarks and features to foster and track the progress made by the research community

Induced displacive transition in heterogeneous materials

A model of heterogeneous, composite material is introduced, consisting of randomly distributed identical structural micro-domains endowed with electric charges or dipoles. Two cases are presented, one corresponding to a tightly packed (dense) material, another corresponding to highly-dispersed, small domains. The polarizability is computed in both cases, under the action of an external uniform electric field oscillating in time (a quasi-stationary field), and it is related to the displacement of the micro-domains from their positions of local equilibrium (translations or rotations). It is shown that the polarizability (or electric susceptibility) can exhibit characteristic (resonance) frequencies in the radio-frequency range and, even for moderate external fields, the material can undergo a displacive transition (similar to a ferroelectric transition), governed by non-linearities in the interaction energy of the micro-domains. The shift in the characteristic frequencies of the polarizability is estimated, as caused by the displacive modification