Selective Sampling for Example-based Word Sense Disambiguation

This paper proposes an efficient example sampling method for example-based word sense disambiguation systems. To construct a database of practical size, a considerable overhead for manual sense disambiguation (overhead for supervision) is required. In addition, the time complexity of searching a large-sized database poses a considerable problem (overhead for search). To counter these problems, our method selectively samples a smaller-sized effective subset from a given example set for use in word sense disambiguation. Our method is characterized by the reliance on the notion of training utility: the degree to which each example is informative for future example sampling when used for the training of the system. The system progressively collects examples by selecting those with greatest utility. The paper reports the effectiveness of our method through experiments on about one thousand sentences. Compared to experiments with other example sampling methods, our method reduced both the overhead for supervision and the overhead for search, without the degeneration of the performance of the system.Comment: 25 pages, 14 Postscript figure

Subspace Variational Quantum Simulator

Quantum simulation is one of the key applications of quantum computing, which can accelerate research and development in chemistry, material science, etc. Here, we propose an efficient method to simulate the time evolution driven by a static Hamiltonian, named subspace variational quantum simulator (SVQS). SVQS employs the subspace-search variational eigensolver (SSVQE) to find a low-energy subspace and further extends it to simulate dynamics within the low-energy subspace. More precisely, using a parameterized quantum circuit, the low-energy subspace of interest is encoded into a computational subspace spanned by a set of computational basis, where information processing can be easily done. After the information processing, the computational subspace is decoded to the original low-energy subspace. This allows us to simulate the dynamics of low-energy subspace with lower overhead compared to existing schemes. While the dimension is restricted for feasibility on near-term quantum devices, the idea is similar to quantum phase estimation and its applications such as quantum linear system solver and quantum metropolis sampling. Because of this simplicity, we can successfully demonstrate the proposed method on the actual quantum device using Regetti Quantum Cloud Service. Furthermore, we propose a variational initial state preparation for SVQS, where the initial states are searched from the simulatable eigensubspace. Finally, we demonstrate SVQS on Rigetti Quantum Cloud Service

A Case of High-Grade Glioma in an Eloquent Area Treated with Awake Craniotomy in an 85-year-old Patient

An 85-year-old woman presented with aphasia due to an occupying lesion in the left frontal lobe near the language area. Complete resection of the contrast-enhancing lesion was performed under awake conditions. The pathological diagnosis was anaplastic astrocytoma, and postoperative radiochemotherapy was administered. Awake surgery is a useful technique to reduce postoperative neurological sequelae and to maximize surgical resection. Although the patient was elderly, which is generally considered high risk, she did not have any severe neurological deficits and had a good outcome. Even in the extreme elderly, awake surgery can be useful for gliomas in language cortices

Neurosurgery for brain metastasis from breast cancer

Breast cancer is the most common malignancy among women worldwide, and the main cause of death in patients with breast cancer is metastasis. Metastasis to the central nervous system occurs in 10% to 16% of patients with metastatic breast cancer, and this rate has increased because of recent advancements in systemic chemotherapy. Because of the various treatments available for brain metastasis, accurate diagnosis and evaluation for treatment are important. Magnetic resonance imaging (MRI) is one of the most reliable preoperative examinations not only for diagnosis of metastatic brain tumors but also for estimation of the molecular characteristics of the tumor based on radiographic information such as the number of lesions, solid or ring enhancement, and cyst formation. Surgical resection continues to play an important role in patients with a limited number of brain metastases and a relatively good performance status. A single brain metastasis is a good indication for surgical treatment followed by radiation therapy to obtain longer survival. Surgical removal is also considered for two or more lesions if neurological symptoms are caused by brain lesions of >3 cm with a mass effect or associated hydrocephalus. Although maximal safe resection with minimal morbidity is ideal in the surgical treatment of brain tumors, supramarginal resection can be achieved in select cases. With respect to the resection technique, en bloc resection is generally recommended to avoid leptomeningeal dissemination induced by piecemeal resection. An operating microscope, neuronavigation, and intraoperative neurophysiological monitoring are essential in modern neurosurgical procedures, including tumor resection. More recently, supporting surgical instruments have been introduced. The use of endoscopic surgery has dramatically increased, especially for intraventricular lesions and in transsphenoidal surgery. An exoscope helps neurosurgeons to comfortably operate regardless of patient positioning or anatomy. A tubular retractor can prevent damage to the surrounding brain tissue during surgery and is a useful instrument in combination with both an endoscope and exoscope. Additionally, 5-aminolevulinic acid (5-ALA) is a promising reagent for photodynamic detection of residual tumor tissue. In the near future, novel treatment options such as high-intensity focused ultrasound (HIFU), laser interstitial thermal therapy (LITT), oncolytic virus therapy, and gene therapy will be introduced