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Aim The aim of this study was to evaluate various prognostic factors and their impact on the outcome of patients with bifrontal brain contusions and to define the critical volume of bifrontal brain contusions and to advice early surgery

Background: The novel coronavirus disease (COVID-19), first recognised in Wuhan City, China, has spread rapidly around the world. As a result, record numbers of students are not attending University due to temporary closures mandated by governments in an attempt to reduce the number of cases. The COVID-19 outbreak has created challenges for academics and students in the process of adapting to online teaching and learning. Purpose: The aim of this study was to explore the experiences of bioscience academics during the COVID-19 pandemic in June 2020. Design and methods: Perspectives from academics across eight countries (Brazil, Georgia, Indonesia, Nigeria, Saudi Arabia, Sri Lanka, UK and USA) were included giving a global insight into the phenomena. A descriptive multiple case study approach was used with each academic in their context as the case. Thematic content analysis was used to analyse data, which enabled themes to emerge. Results and Conclusions: Three major themes emerged from the experiences of the participants: (1) teaching methods, (2) emotions, and (3) support networks. Our results suggest there have been both benefits and challenges to the change in teaching methods and this is reflected in similarities across the case studies. One key finding was that both students and staff need to be better trained to use online platforms, and adequate peer support and technical support must be given to improve program effectiveness. The results of this study have contributed new information on teaching and learning throughout the pandemic and can be used as a platform for further research and also as a reflection for those making high-level decisions in policy in education in these interesting times.

Because of high density, low heat input LBW is an efficient welding Technique in industries and it offers low distortion. Numerical simulation provides the temperature field and weld pool size, which minimize the cost and trial experiments. A CFD model is developed to perform numerical simulation of pulsed laser beam on Ti-6Al-4V alloy of thickness 2mm.Taguchi adopted L9 OA to minimize number of numerical simulations. The ANOVA gives the effect and contribution of each process parameters such as pulse frequency(A), pulse width(B), absorber power(C) and welding speed(D) on performance indicators bead width(α), depth of penetration(β), Heat affected zone(γ)and maximum temperature(δ) are studied. Numerical simulations are validated through comparison of existing test by pulsed mode. A simple reliable modified Taguchi approach is followed to get a set of optimal LBW parameters for maximum DP and minimum BW.

This paper deals with pulsed mode laser beam welding (LBW) on 2 mm thick Ti-6Al-4V alloy sheets. ANSYS Fluent 16.0 version is utilized to develop a generic model with Vc++ code. The model is validated with test results. The optimal LBW parameters are obtained by maximizing the depth of penetration (DP) and minimizing the weld bead width (BW). To minimise the number of numerical simulations, Taguchi approach is adopted. The LBW parameters considered are pulse frequency, pulse width and welding speed, the absorbed power is kept as constant. The performance indicators are width of fusion zone, depth of penetration, heat affected zone and maximum temperature. The optimal LBW parameters are found to be dependent on the process indicators. A simple reliable modified Taguchi approach is followed to get a set of optimal LBW parameters for maximum DP and minimum BW.

This research thoroughly examines the effectiveness of several metaheuristic algorithms in optimizing the dimensions of renewable energy systems in smart grids. It focuses on the urgent need for sustainable and efficient integration of energy. This study examines several optimization strategies by analyzing simulated datasets that represent renewable energy production profiles, energy consumption patterns, and battery storage performance. The data illustrates variations in the availability of renewable energy, with solar energy fluctuating between 500 kWh and 600 kWh, wind energy ranging from 280 kWh to 320 kWh, and hydro energy varying from 180 kWh to 220 kWh. Moreover, energy consumption patterns remain stable sectors, with throughout consumption levels ranging from 400 kWh to 430 kWh, 450 kWh to 480 kWh, and 600 kWh to 630 kWh, respectively. The examination of battery storage performance indicates that the charging efficiency ranges from 90% to 94% and the discharging efficiency ranges from 85% to 89%. Additionally, the depth of discharge ranges from 80% to 84% and the cycle life spans from 2000 cycles to 2400 cycles. By using several metaheuristic algorithms, the research produces a wide range of ideal size arrangements for solar panels, wind turbines, hydro turbines, and battery capacity. These suggested solutions exhibit variances that span from 3.23% to 20%. The results highlight the susceptibility of these algorithms to optimization goals, underlining the need of selecting appropriate algorithms that align with particular limitations and aims. The study's results illuminate the potential of metaheuristic algorithms in attaining effective and sustainable integration of renewable energy systems inside smart grids. This paves the path for informed decision-making and future developments in renewable energy management methods.