What Are You Looking At? Team Fight Prediction Through Player Camera

Esport is a large and still growing industry with vast audiences. Multiplayer Online Battle Arenas (MOBAs), a sub-genre of esports, possess a very complex environment, which often leads to experts missing important coverage while broadcasting live competitions. One common game event that holds significant importance for broadcasting is referred to as a team fight engagement. Professional player's own knowledge and understanding of the game may provide a solution to this problem. This paper suggests a model that predicts and detects ongoing team fights in a live scenario. This approach outlines a novel technique of deriving representations of a complex game environment by relying on player knowledge. This is done by analysing the positions of the in-game characters and their associated cameras, utilising this data to train a neural network. The proposed model is able to both assist in the production of live esport coverage as well as provide a live, expert-derived, analysis of the game without the need of relying on outside sources

Toxicity bioassay of waste cooking oil-based biodiesel on marine microalgae

The world biodiesel production is increasing at a rapid rate. Despite its perceived safety for the environment, more detailed toxicity studies are mandatory, especially in the field of aquatic toxicology. While considerable attention has been paid to biodiesel combustion emissions, the toxicity of biodiesel in the aquatic environment has been poorly understood. In our study, we used an algae culture growth-inhibition test (OECD 201) for the comparison of the toxicity of B100 (pure biodiesel), produced by methanol transesterification of waste cooking oil (yellow grease), B0 (petroleum diesel fuel) and B20 (diesel-biodiesel blended of 20% biodiesel and 80% petroleum diesel fuel by volume). Two marine diatoms Attheya ussuriensis and Chaetoceros muelleri, the red algae Porphyridium purpureum and Raphidophyte Heterosigma akashiwo were employed as the aquatic test organisms. A sample of biodiesel from waste cooking oil without dilution with petroleum diesel (B100) showed the highest level of toxicity for the microalgae A. ussuriensis, C. muelleri and H. akashiwo, compared to hexane, methanol, petroleum diesel (B0) and diluted sample (B20). The acute EC50 in the growth-inhibition test (96 h exposure) of B100 for the four species was in the range of 3.75–23.95 g/L whereas the chronic toxicity EC50 (7d exposure) was in the range of 0.42–16.09 g/L

Exploring the relationship between video game expertise and fluid intelligence

Hundreds of millions of people play intellectually-demanding video games every day. What does individual performance on these games tell us about cognition? Here, we describe two studies that examine the potential link between intelligence and performance in one of the most popular video games genres in the world (Multiplayer Online Battle Arenas: MOBAs). In the first study, we show that performance in the popular MOBA League of Legends' correlates with fluid intelligence as measured under controlled laboratory conditions. In the second study, we also show that the age profile of performance in the two most widely-played MOBAs (League of Legends and DOTA II) matches that of raw fluid intelligence. We discuss and extend previous videogame literature on intelligence and videogames and suggest that commercial video games can be useful as 'proxy' tests of cognitive performance at a global population level

Inhibition of nuclear factor kappa-B signaling reduces growth in medulloblastoma in vivo

Abstract Background Medulloblastoma is a highly malignant pediatric brain tumor that requires surgery, whole brain and spine irradiation, and intense chemotherapy for treatment. A more sophisticated understanding of the pathophysiology of medulloblastoma is needed to successfully reduce the intensity of treatment and improve outcomes. Nuclear factor kappa-B (NFκB) is a signaling pathway that controls transcriptional activation of genes important for tight regulation of many cellular processes and is aberrantly expressed in many types of cancer. Methods To test the importance of NFκB to medulloblastoma cell growth, the effects of multiple drugs that inhibit NFκB, pyrrolidine dithiocarbamate, diethyldithiocarbamate, sulfasalazine, curcumin and bortezomib, were studied in medulloblastoma cell lines compared to a malignant glioma cell line and normal neurons. Expression of endogenous NFκB was investigated in cultured cells, xenograft flank tumors, and primary human tumor samples. A dominant negative construct for the endogenous inhibitor of NFκB, IκB, was prepared from medulloblastoma cell lines and flank tumors were established to allow specific pathway inhibition. Results We report high constitutive activity of the canonical NFκB pathway, as seen by Western analysis of the NFκB subunit p65, in medulloblastoma tumors compared to normal brain. The p65 subunit of NFκB is extremely highly expressed in xenograft tumors from human medulloblastoma cell lines; though, conversely, the same cells in culture have minimal expression without specific stimulation. We demonstrate that pharmacological inhibition of NFκB in cell lines halts proliferation and leads to apoptosis. We show by immunohistochemical stain that phosphorylated p65 is found in the majority of primary tumor cells examined. Finally, expression of a dominant negative form of the endogenous inhibitor of NFκB, dnIκB, resulted in poor xenograft tumor growth, with average tumor volumes 40% smaller than controls. Conclusions These data collectively demonstrate that NFκB signaling is important for medulloblastoma tumor growth, and that inhibition can reduce tumor size and viability in vivo. We discuss the implications of NFκB signaling on the approach to managing patients with medulloblastoma in order to improve clinical outcomes.</p

Ethanol Oxidation and Toxicity: Role of Alcohol P-450 Oxygenase

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66172/1/j.1530-0277.1986.tb05179.x.pd

Development and internal validation of a clinical prediction model for serious complications after emergency laparotomy

Purpose Emergency laparotomy (EL) is a common operation with high risk for postoperative complications, thereby requiring accurate risk stratification to manage vulnerable patients optimally. We developed and internally validated a predictive model of serious complications after EL. Methods Data for eleven carefully selected candidate predictors of 30-day postoperative complications (Clavien-Dindo grade >  = 3) were extracted from the HELAS cohort of EL patients in 11 centres in Greece and Cyprus. Logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) was applied for model development. Discrimination and calibration measures were estimated and clinical utility was explored with decision curve analysis (DCA). Reproducibility and heterogeneity were examined with Bootstrap-based internal validation and Internal–External Cross-Validation. The American College of Surgeons National Surgical Quality Improvement Program’s (ACS-NSQIP) model was applied to the same cohort to establish a benchmark for the new model. Results From data on 633 eligible patients (175 complication events), the SErious complications After Laparotomy (SEAL) model was developed with 6 predictors (preoperative albumin, blood urea nitrogen, American Society of Anaesthesiology score, sepsis or septic shock, dependent functional status, and ascites). SEAL had good discriminative ability (optimism-corrected c-statistic: 0.80, 95% confidence interval [CI] 0.79–0.81), calibration (optimism-corrected calibration slope: 1.01, 95% CI 0.99–1.03) and overall fit (scaled Brier score: 25.1%, 95% CI 24.1–26.1%). SEAL compared favourably with ACS-NSQIP in all metrics, including DCA across multiple risk thresholds. Conclusion SEAL is a simple and promising model for individualized risk predictions of serious complications after EL. Future external validations should appraise SEAL’s transportability across diverse settings

The Hellenic emergency laparotomy study (HELAS): a prospective multicentre study on the outcomes of emergency laparotomy in Greece

Background Emergency laparotomy (EL) is accompanied by high post-operative morbidity and mortality which varies significantly between countries and populations. The aim of this study is to report outcomes of emergency laparotomy in Greece and to compare them with the results of the National Emergency Laparotomy Audit (NELA). Methods This is a multicentre prospective cohort study undertaken between 01.2019 and 05.2020 including consecutive patients subjected to EL in 11 Greek hospitals. EL was defined according to NELA criteria. Demographics, clinical variables, and post-operative outcomes were prospectively registered in an online database. Multivariable logistic regression analysis was used to identify independent predictors of post-operative mortality. Results There were 633 patients, 53.9% males, ASA class III/IV 43.6%, older than 65 years 58.6%. The most common operations were small bowel resection (20.5%), peptic ulcer repair (12.0%), adhesiolysis (11.8%) and Hartmann’s procedure (11.5%). 30-day post-operative mortality reached 16.3% and serious complications occurred in 10.9%. Factors associated with post-operative mortality were increasing age and ASA class, dependent functional status, ascites, severe sepsis, septic shock, and diabetes. HELAS cohort showed similarities with NELA patients in terms of demographics and preoperative risk. Post-operative utilisation of ICU was significantly lower in the Greek cohort (25.8% vs 56.8%) whereas 30-day post-operative mortality was significantly higher (16.3% vs 8.7%). Conclusion In this study, Greek patients experienced markedly worse mortality after emergency laparotomy compared with their British counterparts. This can be at least partly explained by underutilisation of critical care by surgical patients who are at high risk for death