Predicting Round and Game Winners in CSGO

Win probabilities have become a staple on scoreboards in physical sports such as baseball and basketball. Esports, or competitive video games with sponsored teams and major audiences, typically lack this detailed statistical analysis, beyond bare-bones metrics and commentator intuition. However, the advantage of esports in their tendency to have a central record of every game event makes them ripe for statistical analysis through machine learning. Previous research has covered popular video game genres such as MOBAs, and has found success in predicting game winners most of the time [1]. Counterstrike: Global Offensive (CSGO) is an esport that is unique in its round and game-based nature, allowing researchers to examine how short and long-term decisions can interplay in competitive environments. We introduce a dataset of CSGO games To assess factors such as player purchasing decisions and individual scores, we introduce 3 round and game win probability models. Finally, we evaluate the performances of the models. We successfully predict winners in the majority of cases, better than the map average baseline win statistics.

Accumulation of TERT in Mitochondria Shows Two Opposing Effects on Apoptosis

Telomerase reverse transcriptase (TERT) is a protein that catalyzes the reverse transcription of telomere elongation. TERT is also expected to play a noncanonical role beyond telomere lengthening since it localizes not only in the nucleus but also in mitochondria, where telomeres do not exist. Several studies have reported that mitochondrial TERT regulates apoptosis induced by oxidative stress. However, there remains controversy about whether mitochondrial TERT promotes or inhibits apoptosis, mainly due to the lack of information on changes in the TERT distribution in individual cells over time. Here we simultaneously detected apoptosis and TERT localization after oxidative stress in individual HeLa cells by live-cell tracking. This tracking revealed that the stress-induced accumulation of TERT in mitochondria resulted in apoptosis but that the accumulation positively correlated with the time until cell death. The results suggest a new model in which mitochondrial TERT has two opposing effects at different stages of apoptosis: it predetermines apoptosis at the first stage of cell-fate determination but also delays apoptosis at the second stage. Because these distinct effects respectively support both sides of the controversy regarding the role of mitochondrial TERT in apoptosis, our model integrates two opposing hypotheses. Furthermore, detailed statistical analysis of TERT mutations, which have been predicted to inhibit TERT transport to mitochondria, revealed that these mutations suppress apoptosis independent of the mitochondrial localization of TERT. Together, these results indicate that the non-canonical functions of TERT affect a wide range of apoptotic pathways.

A Randomized controlled trial of the Effect of intraVenous iron on Anaemia in Malawian Pregnant women (REVAMP): Statistical analysis plan

Background: Anaemia affects more than half of Africa’s pregnancies. Standard care, with oral iron tablets, often fails to achieve results, with compliance and gastrointestinal side-effects being a significant issue. In recent years, intravenous iron formulations have become safe, effective, and quick to administer, allowing the complete iron requirements of pregnancy to be provided in one 15-minute infusion. The Randomized controlled trial of the Effect of intraVenous iron on Anaemia in Malawian Pregnant women (REVAMP) will evaluate whether a modern intravenous iron formulation, ferric carboxymaltose (FCM), given once during the second trimester is effective and safe in improving maternal and neonatal outcomes for treatment of moderate to severe anaemia in sub-Saharan Africa. The objective was to publish the detailed statistical analysis plan for the REVAMP trial prior to unblinding the allocated treatments and performing the analysis. Methods: REVAMP is a multicentre, two-arm, open-label, parallel-group randomized control trial (RCT) in 862 pregnant women in their second trimester. The trial statistician developed the statistical analysis plan in consultation with the trial management team based on the protocol, data collection forms, and study outcomes available in the blinded study database. Results: The detailed statistical analysis plan will support the statistical analyses and reporting of the REVAMP trial after unblinding the treatment allocations. Conclusions: A statistical analysis plan allows for transparency as well as reproducibility of reporting and statistical analyses.

Analysis of Calcareous Soils for Two Various Facies within the Nature Reserve of El-Mergueb (M’sila, Algeria)

This research was conducted on the protected area of El-Mergueb at M’sila province. The zone of El-Mergueb is located about 180 km south of the capital Algiers, at an altitude from 550 to 800 m, and is characterised by arid climate. The zone of El-Mergueb has a landscape from the steppe to Alfa that lies just as well in the flat ridges hills that in their slopes and in the top part of the ravines. Alfa tenacissima dominates the most geographical space of El-Mergueb. This study is based on the analysis of the homogenous and heterogeneous facies by the determination of the content of calcium carbonate (CaCO3), active calcium carbonate (ACCE) and gypsum through monitoring these chemical parameters during 3 years: 2017, 2018, 2019. Six soil profiles of 15 soil samples collected in the site of study were studied and several chemical soil properties were considered. These factors included: soil pH, calcium carbonate (CaCO3), active total carbonate (CA), gypsum (CaSO4) and electrical conductivity (EC). Principal component analysis (PCA) was used to identify the variations in soil properties. Results showed that there are significant relationships between some soil factors and two PCA axes. The results thus obtained showed that the content of CaCO3 and CA analysed ranged from average to high. The average of gypsum and salinity was low. Floristic diversity defined 284 species. The data on the chemical characteristics of the soil studied have been the subject of a detailed statistical analysis (PCA). Our database consisted of quantitative variables. The implementation of the PCA to the soils studied showed a major dominance of the limestone in the two stations, which explains the alkaline pH and the low concentration of gypsum. Finally, these types of high total limestone are the most observed in the majority of steppe and arid soils.

Ejection of marine microplastics by raindrops: a computational and experimental study

Raindrops impacting water surfaces such as lakes or oceans produce myriads of tiny droplets which are ejected into the atmosphere at very high speeds. Here we combine computer simulations and experimental measurements to investigate whether these droplets can serve as transport vehicles for the transition of microplastic particles with diameters of a few tens of μm from ocean water to the atmosphere. Using the Volume-of-Fluid lattice Boltzmann method, extended by the immersed-boundary method, we performed more than 1600 raindrop impact simulations and provide a detailed statistical analysis on the ejected droplets. Using typical sizes and velocities of real-world raindrops – parameter ranges that are very challenging for 3D simulations – we simulate straight impacts with various raindrop diameters as well as oblique impacts. We find that a 4mm diameter raindrop impact on average ejects more than 167 droplets. We show that these droplets indeed contain microplastic concentrations similar to the ocean water within a few millimeters below the surface. To further assess the plausibility of our simulation results, we conduct a series of laboratory experiments, where we find that microplastic particles are indeed contained in the spray. Based on our results and known data – assuming an average microplastic particle concentration of 2.9 particles per liter at the ocean surface – we estimate that, during rainfall, about 4800 microplastic particles transition into the atmosphere per square kilometer per hour for a typical rain rate of $10 \frac {\text {mm}}{\mathrm {h}}$ 10 mm h and vertical updraft velocity of $0.5 \frac {\mathrm {m}}{\mathrm {s}}$ 0.5 m s .

Volatility of Financial Metrics: Important Data for Contingent Consideration Valuations

This article presents the first detailed statistical analysis of the volatilities of various commonly encountered financial metrics used in contingent consideration (and earn-out) agreements. The valuation of contingent consideration using an option-based methodology and non-equity volatilities is becoming more common in business valuation. We provide clear evidence that the volatility of five financial metrics—revenue; earnings before interest, taxes, depreciation, and amortization (EBITDA); EBIT, net income, and total assets—is strongly, negatively related to firm size and profitability. However, contrary to common belief, the volatility of these metrics is not related to a firm's financial leverage. We also calculated the volatilities using four different methodologies that are employed in practice. Although no theory guides the selection of methodologies, based upon our work, we have found that the year-over-year growth rate, using a quarterly frequency, provides the most reasonable results.

Nutritional Inadequacy: Unraveling the Methodological Challenges for the Application of the Probability Approach or the EAR Cut-Point Method—A Pregnancy Perspective

The aim of this study was to unravel the methodological challenges when exploring nutritional inadequacy, involving 608 healthy pregnant women. The usual intake of twenty-one nutrients was recorded by employing a validated FFQ. Simulated datasets of usual intake were generated, with randomly imposed uncertainty. The comparison between the usual intake and the EAR was accomplished with the probability approach and the EAR cut-point method. Point estimates were accompanied by bootstrap confidence intervals. Bootstrap intervals applied on the risk of inadequacy for raw and simulated data tended in most cases to overlap. A detailed statistical analysis, aiming to predict the level of inadequacy, as well as the application of the EAR cut-point method, along with bootstrap intervals, could effectively be used to assess nutrient inadequacy. However, the final decision for the method used depends on the distribution of nutrient-intake under evaluation. Irrespective of the applied methodology, moderate to high levels of inadequacy, calculated from FFQ were identified for certain nutrients (e.g. vitamins C, B6, magnesium, vitamin A), while the highest were recorded for folate and iron. Considering that micronutrient-poor, obesogenic diets are becoming more common, the underlying rationale may help towards unraveling the complexity characterizing nutritional inadequacies, especially in vulnerable populations.

Development of 30-day mortality forecast model in patients after surgical treatment of proximal hip fracture

Introduction Fractures of the proximal femur often occur in elderly and senile patients. Most of them have an unfavorable comorbid background. In this regard, there is a high risk of complications in the postoperative period, which requires the development and implementation of an effective forecasting model in clinical practice designed to take measures to avoid adverse treatment outcomes.Objective To develop a regression model to predict the probability of lethal outcome within 30 days after surgery in patients with proximal femur fracture.Material and Methods A retrospective analysis of inpatient case histories of all patients (n = 1222) with proximal femur fracture treated in our hospital in 2018-2019 was performed. A total of 388 cases were selected for the study.Results After a detailed statistical analysis of the physiological parameters of the patients, four independent factors were identified that increased the risk of death during 30 days following surgery: albumin less than 30 g / l (regression coefficient – 1.742; OR – 5.708, 95% CI – 1.904–17.114, p = 0.002), the presence of diabetes mellitus (regression coefficient – 1.141; OR – 3.130, 95% CI –1.022–9.588, p = 0.046), the presence of acute renal injury (regression coefficient – 3.141; OR – 23.136, 95% CI – 3.886–137.735, p = 0.001), the presence of pneumonia (regression coefficient – 2.130; OR – 8.411, 95% CI – 2.453–28.838, p = 0.001). A regression model for predicting 30-day mortality was developed: the constant regression coefficient was 4.371, the area under the ROC-curve corresponding to the probability of 30-day mortality was 0.841 with 95% CI: 0.732–0.951, model sensitivity and specificity – 78.9 and 81.2%, respectively. After a detailed statistical analysis of the patients' physiological parameters, four independent factors were identified that increase the risk of fatal outcome during the next 30 days after surgery: albumin less than 30 g / l (regression coefficient, 1.742; OR – 5.708, 95% CI (1.904 – 17.114), p = 0.002), presence of diabetes mellitus (regression coefficient – 1.141; OR – 3.130, 95% CI (1.022 – 9.588), p = 0.046), presence of acute renal injury (regression coefficient – 3.141; OR – 23.136, 95% CI (3.886 – 137.735), p = 0.001), presence of pneumonia (regression coefficient – 2.130; OR – 8.411, 95% CI (2.453 – 28.838), p = 0.001). Thereby we developed a regression model to predict 30-day mortality: regression coefficient of the constant was 4.371; area under the ROC curve, corresponding to the dependence of the probability of 30-day mortality, was 0.841 with 95% CI (0.732 – 0.951); model sensitivity and specificity were 78.9 and 81.2%, respectively.Conclusion Aregression model for predicting mortality in patients with proximal femur fractures based on independent risk factors has a sufficient level of sensitivity and specificity. Its application is possible in practical health care institutions, where patients with trauma are treated.

Bridge failures, forensic structural engineering and recommendations for design of robust structures

A review of forensic structural engineering, which is a strategy that follows after bridge failure, is presented in the paper. A detailed statistical analysis, and worldwide systematisation of available bridge failure data for the 1966-2020 period, are given. More than six hundred cases of partial or full collapse of bridges are analysed in detail, and causes that have led to their failure are examined. Failure of each of these bridges was in most cases not caused by a single factor, i.e. the main cause was most often just a trigger in the cause-and-effect sequence of events that contributed to such failure. Consequently, in addition to main causes, the influence of human factor, as a precondition leading to failure, is considered in each of the analysed cases. Types of progressive collapse, being a critical structural failure mechanism, are described in the second part of the paper, with an emphasis on bridges. An overview of the theory of structural robustness is also given. Design guidelines and approaches, aimed at preventing catastrophic failure and creating more robust structures, are presented. Methods for achieving robustness in the design of new bridges and in the strengthening of the existing ones are also described, and practical real-life examples are provided.

Statistical Analysis of Rainfall Variability for Tehsils of Palghar District, Maharashtra State, India

A detailed statistical analysis of monthly, seasonal and annual rainfall for Tehsils of Palghar district were carried out using 22 years (1998-2019) daily rainfall data taken from Department of Agriculture, Maharashtra State. The mean, standard deviation and coefficient of variation for monthly, seasonal and annual rainfall were computed for tehsils of Palghar districts. The month of July received maximum monthly mean rainfall for all years (1998 to 2019) in tehsils of Palghar district. The result showed that monthly mean rainfall in month of July was maximum at Jawhar (1147.1 mm) followed by Vikramgad (1071.9 mm), Talasari (1014.3 mm), Vasai (1009.9 mm), Wada (998.5 mm), Mokhada (949.6 mm), Palghar (948.7 mm) and Dahanu (841.6) with contributes 40.4 %, 39.1 %, 38.5 %, 35.4 %, 37.3 %, 37.3 %, 36.9 % and 36.3 % of the annual mean rainfall (1998 to 2019) respectively. The result showed that contribution of rainfall during Monsoon season ranges from 95.5 % to 97.0 % of the annual total rainfall for tehsils of Palghar District. The result showed that average annual rainfall (1998 to 2019) of Vasai, Jawhar, Vikramgad, Wada, Talasari, Palghar, Mokhada and Dahanu were 2855.9 mm, 2839.1 mm, 2738.9 mm, 2674.0 mm, 2633.3 mm, 2570.8 mm, 2543.6 mm and 2318.5 mm respectively.