A STOCHASTIC SIMULATION-BASED HYBRID INTERVAL FUZZY PROGRAMMING APPROACH FOR OPTIMIZING THE TREATMENT OF RECOVERED OILY WATER

In this paper, a stochastic simulation-based hybrid interval fuzzy programming (SHIFP) approach is developed to aid the decision-making process by solving fuzzy linear optimization problems. Fuzzy set theory, probability theory, and interval analysis are integrated to take into account the effect of imprecise information, subjective judgment, and variable environmental conditions. A case study related to oily water treatment during offshore oil spill clean-up operations is conducted to demonstrate the applicability of the proposed approach. The results suggest that producing a random sequence of triangular fuzzy numbers in a given interval is equivalent to a normal distribution when using the centroid defuzzification method. It also shows that the defuzzified optimal solutions follow the normal distribution and range from 3,000-3,700 tons, given the budget constraint (CAD 110,000-150,000). The normality seems to be able to propagate throughout the optimization process, yet this interesting finding deserves more in-depth study and needs more rigorous mathematical proof to validate its applicability and feasibility. In addition, the optimal decision variables can be categorized into several groups with different probability such that decision makers can wisely allocate limited resources with higher confidence in a short period of time. This study is expected to advise the industries and authorities on how to distribute resources and maximize the treatment efficiency of oily water in a short period of time, particularly in the context of harsh environments

Predicting Task-­specific Performance for Iterative Reconstruction in Computed Tomography

<p>The cross-sectional images of computed tomography (CT) are calculated from a series of projections using reconstruction methods. Recently introduced on clinical CT scanners, iterative reconstruction (IR) method enables potential patient dose reduction with significantly reduced image noise, but is limited by its "waxy" texture and nonlinear nature. To balance the advantages and disadvantages of IR, evaluations are needed with diagnostic accuracy as the endpoint. Moreover, evaluations need to take into consideration the type of the imaging task (detection and quantification), the properties of the task (lesion size, contrast, edge profile, etc.), and other acquisition and reconstruction parameters. </p><p>To evaluate detection tasks, the more acceptable method is observer studies, which involve image preparation, graphical user interface setup, manual detection and scoring, and statistical analyses. Because such evaluation can be time consuming, mathematical models have been proposed to efficiently predict observer performance in terms of a detectability index (d'). However, certain assumptions such as system linearity may need to be made, thus limiting the application of the models to potentially nonlinear IR. For evaluating quantification tasks, conventional method can also be time consuming as it usually involves experiments with anthropomorphic phantoms. A mathematical model similar to d' was therefore proposed for the prediction of volume quantification performance, named the estimability index (e'). However, this prior model was limited in its modeling of the task, modeling of the volume segmentation process, and assumption of system linearity.</p><p>To expand prior d' and e' models to the evaluations of IR performance, the first part of this dissertation developed an experimental methodology to characterize image noise and resolution in a manner that was relevant to nonlinear IR. Results showed that this method was efficient and meaningful in characterizing the system performance accounting for the non-linearity of IR at multiple contrast and noise levels. It was also shown that when certain criteria were met, the measurement error could be controlled to be less than 10% to allow challenging measuring conditions with low object contrast and high image noise.</p><p>The second part of this dissertation incorporated the noise and resolution characterizations developed in the first part into the d' calculations, and evaluated the performance of IR and conventional filtered backprojection (FBP) for detection tasks. Results showed that compared to FBP, IR required less dose to achieve a threshold performance accuracy level, therefore potentially reducing the required dose. The dose saving potential of IR was not constant, but dependent on the task properties, with subtle tasks (small size and low contrast) enabling more dose saving than conspicuous tasks. Results also showed that at a fixed dose level, IR allowed more subtle tasks to exceed a threshold performance level, demonstrating the overall superior performance of IR for detection tasks.</p><p>The third part of this dissertation evaluated IR performance in volume quantification tasks with conventional experimental method. The volume quantification performance of IR was measured using an anthropomorphic chest phantom and compared to FBP in terms of accuracy and precision. Results showed that across a wide range of dose and slice thickness, IR led to accuracy significantly different from that of FBP, highlighting the importance of calibrating or expanding current segmentation software to incorporate the image characteristics of IR. Results also showed that despite IR's great noise reduction in uniform regions, IR in general had quantification precision similar to that of FBP, possibly due to IR's diminished noise reduction at edges (such as nodule boundaries) and IR's loss of resolution at low dose levels. </p><p>The last part of this dissertation mathematically predicted IR performance in volume quantification tasks with an e' model that was extended in three respects, including the task modeling, the segmentation software modeling, and the characterizations of noise and resolution properties. Results showed that the extended e' model correlated with experimental precision across a range of image acquisition protocols, nodule sizes, and segmentation software. In addition, compared to experimental assessments of quantification performance, e' was significantly reduced in computational time, such that it can be easily employed in clinical studies to verify quantitative compliance and to optimize clinical protocols for CT volumetry.</p><p>The research in this dissertation has two important clinical implications. First, because d' values reflect the percent of detection accuracy and e' values reflect the quantification precision, this work provides a framework for evaluating IR with diagnostic accuracy as the endpoint. Second, because the calculations of d' and e' models are much more efficient compared to conventional observer studies, the clinical protocols with IR can be optimized in a timely fashion, and the compliance of clinical performance can be examined routinely.</p>Dissertatio

ENV-624: A NEW HIGH-YIELDING BIO-DISPERSANT PRODUCER MUTATED FROM RHODOCOCCUS ERYTHROPOLIS STRAIN P6-4P

Preeminent effectiveness and feasibility of dispersants have been the key reasons for their widely serving as the response agents in oil spill responses. Moreover, dispersants can also overcome the limitation factors of other countermeasures like accessibility, weather conditions, sea states, and oil thickness. However, the public concerns of the usages of the chemically synthetic dispersants are also essential due to their toxicity and persistency in the ecosystem. Bio-dispersants can be a promising alternative as the proven features of lower toxicity and persistency while with high effectiveness, but its broad application prospects are currently restricted by the high production cost that is 3-10 times more than chemical synthetic ones because of the low productivity. Thus, a hyper bio-dispersant producer will be the desired coping strategy. An isolated bio-dispersant producer from NL offshore, Rhodococcus erythropolis strain P6-4P was selected for generating high-yielding producers by mutation. After UV mutagenesis, 21 enhanced mutants were selected through oil spreading screening method. Further productivity quantify test of critical micelle dilution (CMD) with higher resolution was conducted to these mutants. An outstanding mutant showed CMD as high as 225 while 15.4 is the CMD of the wild type strain, which means the new mutant is 14.6 times increase. The 16S rDNA sequencing results revealed that the 16 S ribosomal DNA of the mutant 100% matched with the original strain indicating the mutation occurred on other parts of the genome which will be identified through next-generation sequencing and comparative analysis in the future study. This mutated high-yielding strain was capable to significantly improve the production rate and the total yield of bio-dispersants. The yield of crude bio-dispersant was 54g per liter with 6 days incubation. At 4mg/uL crude product/crude oil ratio, the dispersion effectiveness was found comparable to Corexit 9500A at 1:25 (dispersant/crude oil ratio). Future works on further mutagenesis base on this new high-producing strain by novel mutation methods were also discussed

Phase Errors Simulation Analysis for GNSS Antenna in Multipath Environment

High-precision GNSS application requires the exact phase center calibration of antenna. Various methods are published to determine the locations of the phase center. In the outfield, when the phase errors that arose by multipath exceed the phase center variations (PCV) tolerance, the calibration values may be not useful. The objective of this paper is thus to evaluate the phase errors that arose by multipath signals. An improved model of antenna receiving signal is presented. The model consists of three main components: (1) an antenna model created by combination of right hand circular polarization (RHCP) and left hand circular polarization (LHCP), (2) a multipath signals model including amplitude, phase, and polarization, and (3) a ground reflection model applying to circular polarization signals. Based on the model, two kinds of novel up-to-down (U/D) ratios are presented. The performance of the model is assessed against the impact of up-to-down ratio of antenna on phase errors

Bagging by Learning to Singulate Layers Using Interactive Perception

Many fabric handling and 2D deformable material tasks in homes and industry require singulating layers of material such as opening a bag or arranging garments for sewing. In contrast to methods requiring specialized sensing or end effectors, we use only visual observations with ordinary parallel jaw grippers. We propose SLIP: Singulating Layers using Interactive Perception, and apply SLIP to the task of autonomous bagging. We develop SLIP-Bagging, a bagging algorithm that manipulates a plastic or fabric bag from an unstructured state, and uses SLIP to grasp the top layer of the bag to open it for object insertion. In physical experiments, a YuMi robot achieves a success rate of 67% to 81% across bags of a variety of materials, shapes, and sizes, significantly improving in success rate and generality over prior work. Experiments also suggest that SLIP can be applied to tasks such as singulating layers of folded cloth and garments. Supplementary material is available at https://sites.google.com/view/slip-bagging/

Causal relationship between gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study

ObjectiveEmerging evidence has provided compelling evidence linking gut microbiota (GM) and diabetic nephropathy (DN) via the “gut-kidney” axis. But the causal relationship between them hasn’t been clarified yet. We perform a Two-Sample Mendelian randomization (MR) analysis to reveal the causal connection with GM and the development of DN, type 1 diabetes nephropathy (T1DN), type 2 diabetes nephropathy (T2DN), type 1 diabetes mellitus (T1DM), and type 2 diabetes mellitus (T2DM).MethodsWe used summary data from MiBioGen on 211 GM taxa in 18340 participants. Generalized MR analysis methods were conducted to estimate their causality on risk of DN, T1DN, T2DN, T1DM and T2DM from FinnGen. To ensure the reliability of the findings, a comprehensive set of sensitivity analyses were conducted to confirm the resilience and consistency of the results.ResultsIt was showed that Class Verrucomicrobiae [odds ratio (OR) =1.5651, 95%CI:1.1810-2.0742,PFDR=0.0018], Order Verrucomicrobiales (OR=1.5651, 95%CI: 1.1810-2.0742, PFDR=0.0018) and Family Verrucomicrobiaceae (OR=1.3956, 95%CI:1.0336-1.8844, PFDR=0.0296) had significant risk of DN. Our analysis found significant associations between GM and T2DN, including Class Verrucomimicrobiae (OR=1.8227, 95% CI: 1.2414-2.6763, PFDR=0.0139), Order Verrucomimicrobiae (OR=1.5651, 95% CI: 1.8227-2.6764, PFDR=0.0024), Rhodospirillales (OR=1.8226, 95% CI: 1.2412-2.6763, PFDR=0.0026), and Family Verrucomicroniaceae (OR=1.8226, 95% CI: 1.2412-2.6763, PFDR=0.0083). The Eubacteriumprotogenes (OR=0.4076, 95% CI: 0.2415-0.6882, PFDR=0.0021) exhibited a protection against T1DN. Sensitivity analyses confirmed that there was no significant heterogeneity and pleiotropy.ConclusionsAt the gene prediction level, we identified the specific GM that is causally linked to DN in both T1DM and T2DM patients. Moreover, we identified distinct microbial changes in T1DN that differed from those seen in T2DN, offering valuable insights into GM signatures associated with subtype of nephropathy

Fish Waste Based Lipopeptide Production and the Potential Application as a Bio-Dispersant for Oil Spill Control

There is a growing acceptance worldwide for the application of dispersants as a marine oil spill response strategy. The development of more effective dispersants with less toxicity and higher biodegradability would be a step forward in improving public acceptance and regulatory approvals for their use. By applying advances in environmental biotechnology, a bio-dispersant agent with a lipopeptide biosurfactant produced by Bacillus subtilis N3-1P as the key component was formulated in this study. The economic feasibility of producing biosurfactant (a high-added-value bioproduct) from fish waste-based peptone as a nutrient substrate was evaluated. Protein hydrolyzate was prepared from cod liver and head wastes obtained from fish processing facilities. Hydrolysis conditions (i.e., time, temperature, pH and enzyme to substrate level) for preparing protein hydrolyzates were optimized by response surface methodology using a factorial design. The critical micelle dilution (CMD) value for biosurfactant produced from the fish liver and head waste generated peptones was 54.72 and 47.59 CMD, respectively. Biosurfactant product generated by fish liver peptone had a low critical micelle concentration of 0.18 g L–1 and could reduce the surface tension of distilled water to 27.9 mN/m. Structure characterization proved that the generated biosurfactant product belongs to the lipopeptide class. An alternative to the key surfactant dioctyl sulfosuccinate sodium (DOSS) used in Corexit 9500 has been proposed based on a binary mixture of lipopeptides and DOSS that exhibited synergistic effects. Using the standard baffled flask test, a high dispersion efficiency of 76.8% for Alaska North Slope oil was achieved at a biodispersant composition of 80/20 (v/v) of lipopeptides/DOSS. The results show that fish waste can be utilized to produce a more effective, environmentally acceptable and cost-efficient biodispersant that can be applied to oil spills in the marine environment

Disruption of mitochondrial and lysosomal functions by human CACNA1C variants expressed in HEK 293 and CHO cells

ObjectiveTo investigate the pathogenesis of three novel de novo CACNA1C variants (p.E411D, p.V622G, and p.A272V) in causing neurodevelopmental disorders and arrhythmia.MethodsSeveral molecular experiments were carried out on transfected human embryonic kidney 293 (HEK 293) and Chinese hamster ovary (CHO) cells to explore the effects of p.E411D, p.V622G, and p.A272V variants on electrophysiology, mitochondrial and lysosomal functions. Electrophysiological studies, RT-qPCR, western blot, apoptosis assay, mito-tracker fluorescence intensity, lyso-tracker fluorescence intensity, mitochondrial calcium concentration test, and cell viability assay were performed. Besides, reactive oxygen species (ROS) levels, ATP levels, mitochondrial copy numbers, mitochondrial complex I, II, and cytochrome c functions were measured.ResultsThe p.E411D variant was found in a patient with attention deficit-hyperactive disorder (ADHD), and moderate intellectual disability (ID). This mutant demonstrated reduced calcium current density, mRNA, and protein expression, and it was localized in the nucleus, cytoplasm, lysosome, and mitochondria. It exhibited an accelerated apoptosis rate, impaired autophagy, and mitophagy. It also demonstrated compromised mitochondrial cytochrome c oxidase, complex I, and II enzymes, abnormal mitochondrial copy numbers, low ATP levels, abnormal mitochondria fluorescence intensity, impaired mitochondrial fusion and fission, and elevated mitochondrial calcium ions. The p.V622G variant was identified in a patient who presented with West syndrome and moderate global developmental delay. The p.A272V variant was found in a patient who presented with epilepsy and mild ID. Both mutants (p.V622G and p.A272V) exhibited reduced calcium current densities, decreased mRNA and protein expressions, and they were localized in the nucleus, cytoplasm, lysosome, and mitochondria. They exhibited accelerated apoptosis and proliferation rates, impaired autophagy, and mitophagy. They also exhibited abnormal mitochondrial cytochrome c oxidase, complex I and II enzymes, abnormal mitochondrial copy numbers, low ATP, high ROS levels, abnormal mitochondria fluorescence intensity, impaired mitochondrial fusion and fission, as well as elevated mitochondrial calcium ions.ConclusionThe p.E411D, p.V622G and p.A272V mutations of human CACNA1C reduce the expression level of CACNA1C proteins, and impair mitochondrial and lysosomal functions. These effects induced by CACNA1C variants may contribute to the pathogenesis of CACNA1C-related disorders

UV Stimulated Manganese Dioxide for the Persulfate Catalytic Degradation of Bisphenol A

One of the most commonly produced industrial chemicals worldwide, bisphenol A (BPA), is used as a precursor in plastics, resins, paints, and many other materials. It has been proved that BPA can cause long-term adverse effects on ecosystems and human health due to its toxicity as an endocrine disruptor. In this study, we developed an integrated MnO2/UV/persulfate (PS) process for use in BPA photocatalytic degradation from water and examined the reaction mechanisms, degradation pathways, and toxicity reduction. Comparative tests using MnO2, PS, UV, UV/MnO2, MnO2/PS, and UV/PS processes were conducted under the same conditions to investigate the mechanism of BPA catalytic degradation by the proposed MnO2/UV/PS process. The best performance was observed in the MnO2/UV/PS process in which BPA was completely removed in 30 min with a reduction rate of over 90% for total organic carbon after 2 h. This process also showed a stable removal efficiency with a large variation of pH levels (3.6 to 10.0). Kinetic analysis suggested that 1O2 and SO4