A System Dynamic Approach for Evaluating the Effect of Shocking News on Stock Market - Case Study: Volkswagen’s Scandal

Master's Thesis in System DynamicsGEO-SD351INTL-JUSINTL-SVINTL-MNINTL-PSYKINTL-KMDMASV-SYSDYINTL-HFINTL-ME

Nanozyme-based biosensing for clinical diagnosis of COVID-19: A mini review

Several clinical methods had been utilized for diagnosis of COVID-19 for instance, real-time reverse transcription-polymerase chain reaction (rRT-PCR), hematology examination, polymerase chain reaction (PCR), diagnostic guidelines based on clinical features, and Chest CT scans. However, the accurate current methods are time-consuming and expensive and other methods are inaccurate. To solve these drawbacks, nanozyme-based sensors have been developed for the reliable, accurate, and rapid detection of SARS-CoV-2. The main basis of these sensors is the detection of color variation of a nanozyme-mediated oxidation reaction in the presence and the absence of antigens of COVID-19. Besides, some of methods are based on probing the fluorescence of these systems as the clinical signal toward detection of SARS-CoV-2. This mini review focused on overviewing the nanozymes-based methods toward COVID-19 diagnosis. The historical background of COVID-19 was reviewed. Thereafter, the biomedical applications of nanozymes was discussed and finally, the recent progress of early diagnosis of COVID-19 based on nanozymatic systems was briefly reviewed

Investigating Evaluation Frameworks for Electronic Health Record: A Literature Review

BACKGROUND: There are various electronic health records (EHRs) evaluation frameworks with multiple dimensions and numerous sets of evaluation measures, while the coverage rate of evaluation measures in a common framework varies in different studies. AIM: This study provides a literature review of the current EHR evaluation frameworks and a model for measuring the coverage rate of evaluation measures in EHR frameworks. METHODS: The current study was a comprehensive literature review and a critical appraisal study. The study was conducted in three phases. In Phase 1, a literature review of EHR evaluation frameworks was conducted. In Phase 2, a three-level hierarchical structure was developed, which includes three aspects, 12 dimensions, and 110 evaluation measures. Subsequently, evaluation measures in the identified studies were categorized based on the hierarchical structure. In Phase 3, relative frequency (RF) of evaluation measures in different dimensions and aspects for each of the identified studies were determined and categorized as follows: Appropriate, moderate, and low coverage. RESULTS: Out of a total of 8276 retrieved articles, 62 studies were considered relevant. The RF range in the second and third level of the hierarchical structure was between 8.6%–91.94% and 0.2%–61%, respectively. “Ease of use” and “system quality” were the most frequent evaluation measure and dimension. Our results indicate that identified studies cover at least one and at most nine evaluation dimensions and current evaluation frameworks focus more on the technology aspect. Almost in all identified studies, evaluation measures related to the technology aspect were covered. However, evaluation measures related to human and organization aspects were covered in 68% and 84% of the identified studies, respectively. CONCLUSION: In this study, we systematically reviewed all literature presenting any type of EHR evaluation framework and analyzed and discussed their aspects and features. We believe that the findings of this study can help researchers to review and adopt the EHR evaluation frameworks for their own particular field of usage

Building Robust Transcriptomes with Master Splicing Factors

Coherent splicing networks arise from many discrete splicing decisions regulated in unison. Here, we examine the properties of robust, context-specific splicing networks. We propose that a subset of key splicing regulators, or “master splicing factors,” respond to environmental cues to establish and maintain tissue transcriptomes during development.United States. Public Health Service (RO1-GM34277)United States. Public Health Service (R01-CA133404)United States. Public Health Service (U54-CA112967)National Cancer Institute (U.S.) (P30-CA14051

Rbfox2 controls autoregulation in RNA-binding protein networks

The tight regulation of splicing networks is critical for organismal development. To maintain robust splicing patterns, many splicing factors autoregulate their expression through alternative splicing-coupled nonsense-mediated decay (AS-NMD). However, as negative autoregulation results in a self-limiting window of splicing factor expression, it is unknown how variations in steady-state protein levels can arise in different physiological contexts. Here, we demonstrate that Rbfox2 cross-regulates AS-NMD events within RNA-binding proteins to alter their expression. Using individual nucleotide-resolution cross-linking immunoprecipitation coupled to high-throughput sequencing (iCLIP) and mRNA sequencing, we identified >200 AS-NMD splicing events that are bound by Rbfox2 in mouse embryonic stem cells. These “silent” events are characterized by minimal apparent splicing changes but appreciable changes in gene expression upon Rbfox2 knockdown due to degradation of the NMD-inducing isoform. Nearly 70 of these AS-NMD events fall within genes encoding RNA-binding proteins, many of which are autoregulated. As with the coding splicing events that we found to be regulated by Rbfox2, silent splicing events are evolutionarily conserved and frequently contain the Rbfox2 consensus UGCAUG. Our findings uncover an unexpectedly broad and multilayer regulatory network controlled by Rbfox2 and offer an explanation for how autoregulatory splicing networks are tuned.United States. Public Health Service (RO1-GM34277)National Cancer Institute (U.S.). Integrative Cancer Biology Program (Grant CA112967)National Cancer Institute (U.S.) (Koch Institute Support (Core) Grant P30-CA14051)David H. Koch Graduate Fellowshi

Large eddy simulation of an ignition front in a heavy duty partially premixed combustion engine

In partially premixed combustion engines high octane number fuels are injected into the cylinder during the late part of the compression cycle, giving the fuel and oxidizer enough time to mix into a desirable stratified mixture. If ignited by auto-ignition such a gas composition can react in a combustion mode dominated by ignition wave propagation. 3D-CFD modeling of such a combustion mode is challenging as the rate of fuel consumption can be dependent on both mixing history and turbulence acting on the reaction wave. This paper presents a large eddy simulation (LES) study of the effects of stratification in scalar concentration (enthalpy and reactant mass fraction) due to large scale turbulence on the propagation of reaction waves in PPC combustion engines. The studied case is a closed cycle simulation of a single cylinder of a Scania D13 engine running PRF81 (81% iso-octane and 19% n-heptane). Two injection timings are investigated; start of injection at -17 CAD aTDC and -30 CAD aTDC. One-equation transported turbulence sub-grid closure is used for the unresolved momentum and scalar fluxes and the fuel spray is modelled using a Lagrangian particle tracking (LPT) approach. Initial flow conditions (prior to intake valve closing) are generated using a scale forcing method with a prescribed large-scale swirl mean flow motion. Fuel reactivity is modeled using finite rate chemistry based on a skeletal chemical kinetic mechanism (44 species, 140 reactions). The results are compared with optical engine experimental data and satisfactory agreement with the experiments is obtained in terms of the liquid spray length, cylinder pressure trace and ignition location. A majority of the fuel consumption is found to be in ignition fronts where small variations in temperature at low fuel concentrations are observed to cause large stratification in ignition delay time

Effects of fuel cetane number on the structure of diesel spray combustion: An accelerated Eulerian stochastic fields method

An Eulerian stochastic fields (ESF) method accelerated with the chemistry coordinate mapping (CCM) approach for modelling spray combustion is formulated, and applied to model diesel combustion in a constant volume vessel. In ESF-CCM, the thermodynamic states of the discretised stochastic fields are mapped into a low-dimensional phase space. Integration of the chemical stiff ODEs is performed in the phase space and the results are mapped back to the physical domain. After validating the ESF-CCM, the method is used to investigate the effects of fuel cetane number on the structure of diesel spray combustion. It is shown that, depending of the fuel cetane number, liftoff length is varied, which can lead to a change in combustion mode from classical diesel spray combustion to fuel-lean premixed burned combustion. Spray combustion with a shorter liftoff length exhibits the characteristics of the classical conceptual diesel combustion model proposed by Dec in 1997 (http://dx.doi.org/10.4271/970873), whereas in a case with a lower cetane number the liftoff length is much larger and the spray combustion probably occurs in a fuel-lean-premixed mode of combustion. Nevertheless, the transport budget at the liftoff location shows that stabilisation at all cetane numbers is governed primarily by the auto-ignition process