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Chessboard and Chess Piece Recognition With the Support of Neural Networks

Chessboard and chess piece recognition is a computer vision problem that has not yet been efficiently solved. Digitization of a chess game state from a picture of a chessboard is a task typically performed by humans or with the aid of specialized chessboards and pieces. However, those solutions are neither easy nor convenient. To solve this problem, we propose a novel algorithm for digitizing chessboard configurations.

We designed a method of chessboard recognition and pieces detection that is resistant to lighting conditions and the angle at which images are captured, and works correctly with numerous chessboard styles. Detecting the board and recognizing chess pieces are crucial steps of board state digitization.

The algorithm achieves 95% accuracy (compared to 60% for the best alternative) for positioning the chessboard in an image, and almost 95% for chess pieces recognition. Furthermore, the sub-process of detecting straight lines and finding lattice points performs extraordinarily well, achieving over 99.5% accuracy (compared to the 74% for the best alternative).

A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe the DNA geometry. The TOPAS-nBio MC toolkit was used to investigate the impact of physics and chemistry models as well as three key parameters (the energy threshold for direct damage, the chemical stage time length, and the probability of damage between hydroxyl radical reactions with DNA) on the induction of DNA damage. Our results show that the difference in physics and chemistry models alone can cause differences up to 34% and 16% in the DNA double strand break (DSB) yield, respectively. Additionally, changing the direct damage threshold, chemical stage length, and hydroxyl damage probability can cause differences of up to 28%, 51%, and 71% in predicted DSB yields, respectively, for the configurations in this study.

Wikipedia: Why is the common knowledge resource still neglected by academics?

Wikipedia is by far the largest online encyclopedia, and the number of errors it contains is on par with the professional sources even in specialized topics such as biology or medicine. Yet, the academic world is still treating it with great skepticism because of the types of inaccuracies present there, the widespread plagiarism from Wikipedia, and historic biases, as well as jealousy regarding the loss of the knowledge dissemination monopoly. This article argues that it is high time not only to acknowledge Wikipedia's quality but also to start actively promoting its use and development in academia.

Schedule-dependent potentiation of chemotherapy drugs by the hypoxia-activated prodrug SN30000

Hypoxia-activated prodrugs (HAPs) are hypothesized to improve the therapeutic index of chemotherapy drugs that are ineffective against tumor cells in hypoxic microenvironments. SN30000 (CEN-209) is a benzotriazine di-N-oxide HAP that potentiates radiotherapy in preclinical models, but its combination with chemotherapy has not been explored. Here we apply multiple models (monolayers, multicellular spheroids and tumor xenografts) to identify promising SN30000/chemotherapy combinations (with chemotherapy drugs before, during or after SN30000 exposure). SN30000, unlike doxorubicin, cisplatin, gemcitabine or paclitaxel, was more active against cells in spheroids than monolayers by clonogenic assay. Combinations of SN30000 and chemotherapy drugs in HCT116/GFP and SiHa spheroids demonstrated hypoxia-and schedule-dependent potentiation of gemcitabine or doxorubicin in growth inhibition and clonogenic assays. Co-administration with SN30000 suppressed clearance of gemcitabine in NIH-III mice, likely due to SN30000-induced hypothermia which also modulated extravascular transport of gemcitabine in tumor tissue as assessed from its diffusion through HCT116 multicellular layer cultures. Despite these systemic effects, the same schedules that gave therapeutic synergy in spheroids (SN30000 3 h before or during gemcitabine, but not gemcitabine 3 h before SN30000) enhanced growth delay of HCT116 xenografts without increasing host toxicity. Identification of hypoxic and S-phase cells by immunohistochemistry and flow cytometry established that hypoxic cells initially spared by gemcitabine subsequently reoxygenate and re-enter the cell cycle, and that this repopulation is prevented by SN30000 only when administered with or before gemcitabine. This illustrates the value of spheroids in modeling tumor microenvironment-dependent drug interactions, and the potential of HAPs for overcoming hypoxia-mediated drug resistance.

Modeling Biological Systems Using Crowdsourcing

Crowdsourcing is a very effective technique for outsourcing work to a vast network usually comprising anonymous people. In this study, we review the application of crowdsourcing to modeling systems originating from systems biology. We consider a variety of verified approaches, including well-known projects such as EyeWire, FoldIt, and DREAM Challenges, as well as novel projects conducted at the European Center for Bioinformatics and Genomics. The latter projects utilized crowdsourced serious games to design models of dynamic biological systems, and it was demonstrated that these models could be used successfully to involve players without domain knowledge. We conclude the review of these systems by providing 10 guidelines to facilitate the efficient use of crowdsourcing.