Effects of Three Growth Regulators on Selected Characters in Cotton

Crop Scienc

DICE: Diverse Diffusion Model with Scoring for Trajectory Prediction

Road user trajectory prediction in dynamic environments is a challenging but crucial task for various applications, such as autonomous driving. One of the main challenges in this domain is the multimodal nature of future trajectories stemming from the unknown yet diverse intentions of the agents. Diffusion models have shown to be very effective in capturing such stochasticity in prediction tasks. However, these models involve many computationally expensive denoising steps and sampling operations that make them a less desirable option for real-time safety-critical applications. To this end, we present a novel framework that leverages diffusion models for predicting future trajectories in a computationally efficient manner. To minimize the computational bottlenecks in iterative sampling, we employ an efficient sampling mechanism that allows us to maximize the number of sampled trajectories for improved accuracy while maintaining inference time in real time. Moreover, we propose a scoring mechanism to select the most plausible trajectories by assigning relative ranks. We show the effectiveness of our approach by conducting empirical evaluations on common pedestrian (UCY/ETH) and autonomous driving (nuScenes) benchmark datasets on which our model achieves state-of-the-art performance on several subsets and metrics

Genetic and nutrient modulation of acetyl-CoA levels in Synechocystis for <i>n</i>-butanol production

Background: There is a strong interest in using photosynthetic cyanobacteria as production hosts for biofuels and chemicals. Recent work has shown the benefit of pathway engineering, enzyme tolerance, and co-factor usage for improving yields of fermentation products. Results: An n-butanol pathway was inserted into a Synechocystis mutant deficient in polyhydroxybutyrate synthesis. We found that nitrogen starvation increased specific butanol productivity up to threefold, but cessation of cell growth limited total n-butanol titers. Metabolite profiling showed that acetyl-CoA increased twofold during nitrogen starvation. Introduction of a phosphoketolase increased acetyl-CoA levels sixfold at nitrogen replete conditions and increased butanol titers from 22 to 37 mg/L at day 8. Flux balance analysis of photoautotrophic metabolism showed that a Calvin-Benson-Bassham-Phosphoketolase pathway had higher theoretical butanol productivity than CBB-Embden-Meyerhof-Parnas and a reduced butanol ATP demand. Conclusion: These results demonstrate that phosphoketolase overexpression and modulation of nitrogen levels are two attractive routes toward increased production of acetyl-CoA derived products in cyanobacteria and could be implemented with complementary metabolic engineering strategies

Modelling of Passive Heat Removal Systems: A Review with Reference to the Framatome KERENA BWR Reactor: Part I

Passive safety systems are an important feature of currently designed and constructed nuclear power plants. They operate independent of external power supply and manual interventionsand are solely driven by thermal gradients and gravitational force. This brings up new needs forperformance and reliably assessment. This paper provides a review on fundamental approaches to model and analyze the performance of passive heat removal systems exemplified for the passive heat removal chain of the KERENA boiling water reactor concept developed by Framatome. We discuss modelling concepts for one-dimensional system codes such as ATHLET, RELAP and TRACE and furthermore for computational fluid dynamics codes. Part I deals with numerical and experimental methods for modelling of condensation inside the emergency condensers and on the containment cooling condenser while part II deals with boiling and two-phase flow instabilities

Modelling of Passive Heat Removal Systems: A Review with Reference to the Framatome BWR Reactor KERENA: Part II

Passive safety systems are an important feature of currently designed and constructed nuclear power plants. They operate independent of external power supply and manual interventions and are solely driven by thermal gradients and gravitational force. This brings up new needs for performance and reliably assessment. This paper provides a review on fundamental approaches to model and analyze the performance of passive heat removal systems exemplified for the passive heat removal chain of the KERENA boiling water reactor concept developed by Framatome. We discuss modeling concepts for one-dimensional system codes such as ATHLET, RELAP and TRACE and furthermore for computational fluid dynamics codes. Part I dealt with numerical and experimental methods for modeling of condensation inside the emergency condenser and on the containment cooling condenser. This second part deals with boiling and two-phase flow instabilities

A Novel Microfluidic Dielectrophoresis Technology to Enable Rapid Diagnosis of Mycobacteria tuberculosis in Clinical Samples

To achieve the global efforts to end tuberculosis, affordable diagnostics suitable for true point-of-care implementation are required to reach the missing millions. In addition, diagnostics with increased sensitivity and expanded drug susceptibility testing are needed to address drug resistance and to diagnose low-bacterial burden cases. The laboratory-on-a-chip technology described herein used dielectrophoresis to selectively isolate Mycobacterium tuberculosis from sputum samples, purifying the bacterial population ahead of molecular confirmation by multiplex real-time quantitative PCR. After optimization using a panel of 50 characterized sputum samples, the performance of the prototype was assessed against the current gold standards, screening 100 blinded sputum samples using characterized and biobanked sputum provided by Foundation for Innovative New Diagnostics. Concordance with culture diagnosis was 100% for smear-negative samples and 87% for smear-positive samples. Of the smear-positive samples, the high burden sample concordance was 100%. Samples were diagnosed on the basis of visual assessment of the dielectrophoresis array and by multiplex real-time quantitative PCR assay. The results described herein demonstrate the potential of the CAPTURE-XT technology to provide a powerful sample preparation tool that could function as a front-end platform for molecular detection. This versatile tool could equally be applied as a visual detection diagnostic, potentially associated with bacterial identification for low-cost screening or coupled with an expanded PCR assay for genotypic drug susceptibility testing

A Novel Microfluidic Dielectrophoresis Technology to Enable Rapid Diagnosis of Mycobacteria tuberculosis in Clinical Samples

To achieve the global efforts to end tuberculosis, affordable diagnostics suitable for true point-of-care implementation are required to reach the missing millions. In addition, diagnostics with increased sensitivity and expanded drug susceptibility testing are needed to address drug resistance and to diagnose low-bacterial burden cases. The laboratory-on-a-chip technology described herein used dielectrophoresis to selectively isolate Mycobacterium tuberculosis from sputum samples, purifying the bacterial population ahead of molecular confirmation by multiplex real-time quantitative PCR. After optimization using a panel of 50 characterized sputum samples, the performance of the prototype was assessed against the current gold standards, screening 100 blinded sputum samples using characterized and biobanked sputum provided by Foundation for Innovative New Diagnostics. Concordance with culture diagnosis was 100% for smear-negative samples and 87% for smear-positive samples. Of the smear-positive samples, the high burden sample concordance was 100%. Samples were diagnosed on the basis of visual assessment of the dielectrophoresis array and by multiplex real-time quantitative PCR assay. The results described herein demonstrate the potential of the CAPTURE-XT technology to provide a powerful sample preparation tool that could function as a front-end platform for molecular detection. This versatile tool could equally be applied as a visual detection diagnostic, potentially associated with bacterial identification for low-cost screening or coupled with an expanded PCR assay for genotypic drug susceptibility testing

Influence of Prototropic Reactions on the Absorption and Fluorescence Spectra of Methyl p-dimethylaminobenzoate and Its Two Ortho Derivatives

The influence of prototropic reactions on the spectral characteristics of methyl p-dimethylaminobenzoate (I) and its o-methoxy (II) and o-hydroxy (III) derivatives has been studied using steady-state spectroscopic technique and quantum-chemical calculations. This study concerns the solvent-induced shift of the absorption, locally excited (LE) and intramolecular charge transfer (ICT) fluorescence bands in the neat tetrahydrofuran (THF) and its hydrochloric acid solutions at different HCl concentrations. On the basis of the experimental results and quantum-chemical calculations, it was shown that in a hydrochloric acid solution the studied molecules exist as a mixture of neutral, mono-, and dicationic forms. Additionally, the results of spectroscopic measurements were used to calculate, according to the Benesi-Hildebrand method, the equilibrium constants of protopropic reactions in the ground, S0, and excited, S1, states. Our findings predestine molecules I and II to be used as acid fluorescence probes in a region of 0–2.5 M of [H+] concentrations

Improving cyanobacteria productivity: From theory to assay

Bio-based production of biochemicals and biofuels holds great promises for the transition towards a more sustainable society. With increasing levels of carbon dioxide (CO2) in the atmosphere, cyanobacteria stand apart as natural catalysts directly converting CO2 and light to product. However, current product productivities and titers do not meet the standard set by the petroleum-based industry. In particular, the solar-to-product efficiency needs to be drastically improved to make the process economically more interesting. As proof of concept, this thesis puts an emphasis on identifying metabolic limitations towards increased solar-to-product efficiency using model-guided formulation of strategies and genome-wide screening, followed by novel practical implementations. It follows previous works identifying the intracellular ATP/NADPH ratio as an important variable to balance photosynthesis, carbon fixation, product synthesis and biomass formation to ensure more performant metabolic engineering designs of photoautotrophs.   In Paper I, we identified in silico growth-coupled metabolic designs linking product formation to growth to increase productivity and stability of the engineered strain. In Paper II, we found computationally and experimentally that carbon rerouting gave the best results to increase product formation. In Paper III, we used the CRISPRi system to further maximize carbon rerouting to product synthesis in growth-arrest strategies. Finally, in Paper IV, we conduct a genome-wide screening using a CRISPRi library and identified key targets to improve product synthesis, product tolerance and growth. We also demonstrate experimentally some of the strategies found in Paper I. This thesis suggests that growth-arrest production is a promising avenue to maximize the solar-to-product efficiency and asserts that systems biology tools will be needed to identify and tackle the remaining strain instability associated with those designs.QC 2020-08-11</p