RESUMEN
We propose a neural network-based approach to calculate the value of a chess square-piece combination. Our model takes a triplet (color, piece, square) as the input and calculates a value that measures the advantage/disadvantage of having this piece on this square. Our methods build on recent advances in chess AI, and can accurately assess the worth of positions in a game of chess. The conventional approach assigns fixed values to pieces (= ∞, = 9, = 5, = 3, = 3, = 1). We enhance this analysis by introducing marginal valuations. We use deep Q-learning to estimate the parameters of our model. We demonstrate our method by examining the positioning of knights and bishops, and also provide valuable insights into the valuation of pawns. Finally, we conclude by suggesting potential avenues for future research.
RESUMEN
Virtual sensing technology uses mathematical calculations instead of natural measurements when the latter are too difficult or expensive. Nowadays, application of virtual light sensing technology becomes almost mandatory for daylight analysis at the stage of architectural project development. Daylight Autonomy metrics should be calculated multiple times during the project. A properly designed building can reduce the necessity of artificial lighting, thus saving energy. There are two main daylight performance metrics: Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE). To obtain their values, we have to simulate global illumination for every hour of the year. A light simulation method should therefore be as efficient as possible for processing complex building models. In this paper we present a method for fast calculation of Daylight Autonomy metrics, allowing them to be calculated within a reasonable timescale. We compared our method with straightforward calculations and other existing solutions. This comparison demonstrates good agreement; this proves sufficient accuracy and higher efficiency of the method. Our method also contains an original algorithm for the automatic setting of the sensing area. The sDA metric is calculated considering blinds control, which should open or close them depending on overexposure to direct sunlight. Thus, we developed an optimization procedure to determine the blinds configuration at any time.
RESUMEN
BACKGROUND: Among men with metastatic prostate cancer, about 10% have germline alterations in DNA damage response genes. Most studies have examined BRCA2 alone or an aggregate of BRCA1/2 and ATM. Emerging data suggest that ATM mutations may have distinct biology and warrant individual evaluation. The objective of this study is to determine whether response to prostate cancer systemic therapies differs between men with germline mutations in ATM (gATM) and BRCA2 (gBRCA2). METHODS: This is an international multicenter retrospective matched cohort study of men with prostate cancer harboring gATM or gBRCA2. PSA50 response (≥50% decline in prostate-specific antigen) was compared using Fisher's exact test. RESULTS AND LIMITATIONS: The study included 45 gATM and 45 gBRCA2 patients, matched on stage and year of germline testing. Patients with gATM and gBRCA2 had similar age, Gleason grade, and PSA at diagnosis. We did not observe differences in PSA50 responses to abiraterone, enzalutamide, or docetaxel in metastatic castration resistant prostate cancer between the two groups; however, 0/7 with gATM and 12/14 with gBRCA2 achieved PSA50 response to PARPi (p < .001). Median (95% confidence interval) overall survival from diagnosis to death was 10.9 years (9.5-not reached) versus 9.9 years (7.1-not reached, p = .07) for the gATM and gBRCA2 cohorts, respectively. Limitations include the retrospective design and lack of mutation zygosity data. CONCLUSIONS: Conventional therapies can be effective in gATM carriers and should be considered before PARPi, which shows limited efficacy in this group. Men with gATM mutations warrant prioritization for novel treatment strategies.
