18 research outputs found

    3D scientific data mining in ion trajectories

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    In physics, structure of glass and ion trajectories are essentially based on statistical analysis of data acquired through experimental measurement and computer simulation. Invariably, the details of the structure-transport relationships in the data have been mistreated in favour of ensemble average. In this study, we demonstrate a visual approach of such relationship using surface-based visualisation schemes. In particular, we demonstrate a scientific datasets of simulated 3D time-varying model and examine the temporal correlation among ion trajectories. We propose a scheme that uses a three dimensional visual representation with colour scale for depicting the timeline events in ion trajectories and this scheme could be divided into two major part such as global and local time scale. With a collection of visual examples from this study, we demonstrate that this scheme may offer an effective tool for visually mining 3D timeline events of the ion trajectories. This work will potentially form a basis of a novel analysis tool for measuring the effectiveness of visual representation to assist physicist in identifying possible temporal association among complex and chaotic atom movements in ion trajectories

    Copper nanowires based mode-locker for soliton nanosecond pulse generation in erbium-doped fiber laser

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    A mode-locked nanosecond Erbium-doped fiber laser (EDFL) based on copper nanowires (CuNWs) saturable absorber (SA) is successfully demonstrated in this article. The CuNWs were prepared by dissolving the CuNWs solution in a polydimethylsiloxane (PDMS) host polymer. Through the doctor blade technique, a free-standing CuNWs-PDMS film was formed. Upon inserting the film in a laser cavity, nanosecond pulses with a stable mode-locking was observed past the threshold pump power of 104.62 mW. The laser operated at the center frequency of 1.86 MHz and wavelength of 1563.3 nm. At the maximum available pump power of 187.04 mW, the 173 ns mode-locked pulse train achieved the highest pulse energy of 9.14 nJ and the maximum average output power of 1.703 mW. These results vindicate the capacity of the CuNWs film SA in producing nanosecond mode-locked EDFL in the 1550 nm region

    Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)

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    Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic

    Student perception of using case study as a teaching method

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    Active learning has attracted strong advocates among faculty looking for alternatives to traditional teaching methods. Case study has been recently introduced as an add-on teaching method in Malaysia. For Universiti Teknologi Malaysia, the Harvard Business School case studies have been selected to be part of the curriculum to inculcate entrepreneurial thinking skills. This paper discusses the feedback on students’ perceptions of students regarding the implementation of case study discussion in the classroom. Findings show that most students show positive perception of using case study as a teaching method and agree to learn using the same method in the future

    A hybrid of Cuckoo Search and Minimization of Metabolic Adjustment to optimize metabolites production in genome-scale models

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    Metabolic engineering involves the modification and alteration of metabolic pathways to improve the production of desired substance. The modification can be made using in silicogene knockout simulation that is able to predict and analyse the disrupted genes which may enhance the metabolites production. Global optimization algorithms have been widely used for identifying gene knockout strategies. However, their productions were less than theoretical maximum and the algorithms are easily trapped into local optima. These algorithms also require a very large computation time to obtain acceptable results. This is due to the complexity of the metabolic models which are high dimensional and contain thousands of reactions. In this paper, a hybrid algorithm of Cuckoo Search and Minimization of Metabolic Adjustment is proposed to overcome the aforementioned problems. The hybrid algorithm searches for the near-optimal set of gene knockouts that leads to the overproduction of metabolites. Computational experiments on two sets of genome-scale metabolic models demonstrate that the proposed algorithm is better than the previous works in terms of growth rate, Biomass Product Couple Yield, and computation time
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