Underwater Fish Detection using Deep Learning for Water Power Applications

Clean energy from oceans and rivers is becoming a reality with the development of new technologies like tidal and instream turbines that generate electricity from naturally flowing water. These new technologies are being monitored for effects on fish and other wildlife using underwater video. Methods for automated analysis of underwater video are needed to lower the costs of analysis and improve accuracy. A deep learning model, YOLO, was trained to recognize fish in underwater video using three very different datasets recorded at real-world water power sites. Training and testing with examples from all three datasets resulted in a mean average precision (mAP) score of 0.5392. To test how well a model could generalize to new datasets, the model was trained using examples from only two of the datasets and then tested on examples from all three datasets. The resulting model could not recognize fish in the dataset that was not part of the training set. The mAP scores on the other two datasets that were included in the training set were higher than the scores achieved by the model trained on all three datasets. These results indicate that different methods are needed in order to produce a trained model that can generalize to new data sets such as those encountered in real world applications.Comment: Accepted at CSCI 201

Investigation of stiffness as a biomarker in ovarian cancer cells

In this dissertation, we developed cell stiffness as a biomarker in ovarian cancer for the purpose of grading metastatic potential. By measuring single cell stiffness with atomic force microscopy and quantifying in vitro invasiveness of healthy and cancerous ovarian cells, we demonstrated that cancerous ovarian cells have reduced stiffness compared to the healthy ones and invasive ovarian cancer cells are more deformable than noninvasive ovarian cancer cells. The difference in cell stiffness between two genetically similar cell lines was attributed to actin-mediated cytoskeletal remodeling as revealed by comparative gene expression profile analysis, and was further confirmed by fluorescent visualization of actin cytoskeletal structures. The actin cytoskeletons were innovatively quantified and correlates with cell stiffness distributions, further implicating actin-mediated cytoskeletal remodeling in stiffness alteration from the perspective of structure-property relationship. The correlation between stiffness and metastatic potential was also demonstrated in pancreatic cancer cell line AsPC-1, which shows reduced invasivess and increased stiffness upon treatment with N-acetyl-L-cysteine (NAC), a well known antioxidant, reactive oxygen species (ROS), scavenger and glutathione precursor. The correlation between cell stiffness and metastatic potential as demonstrated in ovarian and pancreatic cancer cells indicated that mechanical stiffness may be a useful biomarker to evaluate the relative metastatic potential of ovarian and perhaps other types of cancer cells, and might be useful clinically with the development of rapid biomechanical assaying techniques. We have also investigated the stiffness evolution through progression of the cell cycle for the healthy ovarian phenotype and the invasive cancer ovarian phenotype, and found that the healthy phenotype at G1 phase are significantly stiffer than other single cells except the invasive phenotype at late mitosis; other groups are not significantly different from each other. We have also investigated intracellular heterogeneity and mechanical nonlinearity in single cells. To this end, we developed a methodology to analyze the deformation-dependent mechanical nonlinearity using a pointwise Hertzian method, and tested the method on ultrathin polydimethylsiloxane (PDMS) films which underwent extremely large strains (greater than 50%). Mechanical stiffening due to large strain and geometrical confinement were observed. The onset of nonlinearity or mechanical stiffening occurs at 45% of the film thickness, the geometry induced stiffening causes an increase in stiffness which shows a strong power law dependence on film thickness. By applying the pointwise Hertzian method on stiffness measurements with AFM that were collected on living cells, we also investigated the nonlinear and heterogeneous mechanics of single cells, since attachment of cells to stiff substrate during indentation may impact their mechanical responses. Even under natural biological conditions, cells confined in narrow spaces may experience heightened mechanical stiffness. Through indentation-dependent force mapping, analysis of the local cell stiffness demonstrated spatial variation. The results indicated that the mechanical properties of single cells are highly nonlinear and are dependent upon the subcellular features under the applied force as well as the dimensions of the cellular material. We identified single cell stiffness as a potential biomarker of the metastatic potential in ovarian cancer, and quantified the effect of geometrical confinement on cell mechanics. The results presented in this dissertation not only made contributions to the development of accurate, non-invasive clinical methods to estimate metastatic potential of ovarian and perhaps other types of cancer, but also shed light on the intracellular mechanical information by developing new techniques to quantify the effect of geometry on cell mechanics.Ph.D

A Novel Prognostic Predictor of Immune Micro-environment and Therapeutic Response in Kidney Renal Clear Cell Carcinoma based on Necroptosis-related Gene Signature

Background: Necroptosis, a cell death of caspase-independence, plays a pivotal role in cancer biological regulation. Although necroptosis is closely associated with oncogenesis, cancer metastasis, and immunity, there remains a lack of studies determining the role of necroptosis-related genes (NRGs) in the highly immunogenic cancer type, kidney renal clear cell carcinoma (KIRC). Methods: The information of clinicopathology and transcriptome was extracted from TCGA database. Following the division into the train and test cohorts, a three-NRGs (TLR3, FASLG, ZBP1) risk model was identified in train cohort by LASSO regression. The overall survival (OS) comparison was conducted between different risk groups through Kaplan-Meier analysis, which was further validated in test cohort. The Cox proportional hazards regression model was introduced to assess its impact of clinicopathological factors and risk score on survival. ESTIMATE and CIBERSORT algorithms were introduced to evaluate immune microenvironment, while enrichment analysis was conducted to explore the biological significance. Correlation analysis was applied for the correlation assessment between checkpoint gene expression and risk score, between gene expression and therapeutic response. Gene expressions from TCGA were verified by GEO datasets and immunohistochemistry (IHC) analysis. Results: This NRGs-related signature predicted poorer OS in high-risk group, which was also verified in test cohort. Risk score could also independently predict survival outcome of KIRC. Significant changes were also found in immune microenvironment and checkpoint gene expressions between different risk groups, with immune functional enrichment in high-risk group. Interestingly, therapeutic response was correlated with the expressions of NRGs. The expressions of NRGs from TCGA were consistent with those from GEO datasets and IHC analysis. Conclusion: The NRGs-related signature functions as a novel prognostic predictor of immune microenvironment and therapeutic response in KIRC

SPIDER-WEB enables stable, repairable, and encryptible algorithms under arbitrary local biochemical constraints in DNA-based storage

DNA has been considered as a promising medium for storing digital information. Despite the biochemical progress in DNA synthesis and sequencing, novel coding algorithms need to be constructed under the specific constraints in DNA-based storage. Many functional operations and storage carriers were introduced in recent years, bringing in various biochemical constraints including but not confined to long single-nucleotide repeats and abnormal GC content. Existing coding algorithms are not applicable or unstable due to more local biochemical constraints and their combinations. In this paper, we design a graph-based architecture, named SPIDER-WEB, to generate corresponding graph-based algorithms under arbitrary local biochemical constraints. These generated coding algorithms could be used to encode arbitrary digital data as DNA sequences directly or served as a benchmark for the follow-up construction of coding algorithms. To further consider recovery and security issues existing in the storage field, it also provides pluggable algorithmic patches based on the generated coding algorithms: path-based correcting and mapping shuffling. They provide approaches for probabilistic error correction and symmetric encryption respectively.Comment: 30 pages; 12 figures; 2 table

Salvianolic Acid B Inhibits Activation of Human Primary Hepatic Stellate Cells Through Downregulation of the Myocyte Enhancer Factor 2 Signaling Pathway

Various isoforms of myocyte enhancer factor 2 (MEF2) have been shown to play a role in the activation of rat hepatic stellate cells (HSCs) in culture. The signals that regulate MEF2 in HSCs are unknown. In addition, whether MEF2s regulate the activation of human HSCs (H-HSCs) is unclear. Here, we studied the expression and function of MEF2s in H-HSCs. Our data showed that the levels of MEF2A, C, and D proteins were high in liver tissues from patients with cirrhosis and increased during culture-induced activation of primary H-HSCs. Exposure of H-HSCs to transforming growth factor beta 1 (TGF-β1) led to a significant increase in MEF2A and C protein levels and enhanced MEF2 activity. Interestingly, TGF-β1 did not further enhance MEF2D levels. Furthermore, TGF-β1 activated p38 mitogen-activated protein kinase (MAPK) and led to increased phosphorylation of MEF2C at its p38 recognition site. Inhibition of p38 MAPK inhibited both TGF-β1- and culture-induced activation of MEF2. The activity of collagen I reporter in H-HSCs was significantly reduced when MEF2A and MEF2C were blocked with overexpression of dominant negative MEF2 mutants. Salvianolic-acid B (SA-B), a water-soluble element of Salvia miltiorrhiza known to have anti-fibrosis effects, attenuated both basal and TGF-β1-induced increased levels of MEF2A and C mRNA and protein. In addition, SA-B inhibited MEF2 activity, which correlated with reduced expression of the HSC activation markers, α-smooth muscle actin (α-SMA), and collagen I. Administration of SA-B reduced MEF2A in vivo, which was accompanied by reduced levels of α-SMA in a model of dimethylnitrosamine-induced rat liver fibrosis. We concluded that the MEF2 transcription factor was stimulated by TGF-β1 in H-HSCs. Antagonizing TGF-β1-induced activation of the MEF2 signaling pathway may account in part for the anti-fibrosis effects of SA-B

Response of Salish Sea circulation and water quality to climate change and sea level rise

There is much interest in the Pacific Northwest community and water quality management agencies to better understand and predict long term changes in the Salish Sea water quality given periodic occurrences of hypoxia and evidence of coastal acidification. However, the projected interaction of riverine and estuarine systems under potential future climate-change scenarios is not well characterized in the Salish Sea area. In this study, the Salish Sea Model of circulation and water quality developed using FVCOM-ICM model was applied to provide insights on how estuarine/nearshore environments may be impacted in the future. It serves as a proof-of-concept assessment of the methods to functionally link downscaled outputs of CESM models for the Pacific Northwest (meteorology and biogeochemistry) to a marine circulation and water-quality model. We present simulated 100-year changes under the RCP8.5 scenario, including projected future increases in air temperature (≈+3.5˚), Pacific Ocean temperature (≈ +2.4°C), and river flow temperatures (≈+3.2°C), in combination with a projected sea level rise of +1.5m and future ocean chemistry changes. Our results show that strong vertical circulation cells in Salish Sea provide mitigation through mixing and continue to serve as a physical buffer, keeping water temperature cooler than over the continental shelf. Despite the mitigation effects, under RCP 8.5 scenario Salish Sea is expected to undergo several significant changes, including: temperature increases (+1.8°C), hypoxia zone expansion, and potential algal species shift (dinoflagellates: +196%; diatom: -14%). Snohomish Estuary, as an intertidal site example, is projected to experience 3 ˚C annual mean surface temperature increase and substantial seawater intrusion

An overview of the Salish Sea model: existence of reflux mixing and recurring hypoxia

An improved version of a diagnostic hydrodynamic and biogeochemical model (nutrients, phytoplankton, carbon, dissolved oxygen, pH) of the Salish Sea has been developed with the ability to simulate characteristic circulation and water quality features. Notable improvements include expansion of the model domain beyond the Salish Sea, encompassing Vancouver Island and out to the continental shelf boundary. In this talk we present an overview of the model setup describing the model domain coverage, modeling framework, development of boundary conditions, and tidal, riverine, wastewater, and meteorological inputs. Ability of the model to reproduce known circulation features within the Salish Sea is highlighted. The existence of a strong circulation cell between Admiralty Inlet and Tacoma Narrows sills is discussed reflecting on the implications of reflux flow back into Central Puget Sound. Simulation of sediment diagenesis processes and coupling to the water column provides improved model performance that is responsive to land based and oceanic nutrient loads. This coupling is also credited with the improvements in simulation of hypoxia in selected sub-basins within the Salish Sea such as Hood Canal, Penn Cove, and East Sound. Using tidally averaged velocity profiles from the Salish Sea Model, we demonstrate that Hood Canal sub-basin, with a sill near the mouth, a deep channel configuration, and a freshwater source at its landward end, behaves like a classic-fjord. The dominant and notable feature is that circulation and exchange in the inner basin of Hood Canal occurs in the upper 40% of the water column while the lower 60% remains poorly mixed and relatively isolated from the exchange. This results in conditions well suited for the settling of organic matter and long residence times \u3e230 days, and causes recurring hypoxia in the inner regions of Hood Canal in late fall

Yield determination of maize hybrids under limited irrigation

Hybrid adoption, irrigation, and planting density are important factors for maize (Zea mays L.) production in semiarid regions. For this study, a 2-yr field experiment was conducted in the Texas High Plains to investigate maize yield determination, seasonal evapotranspiration (ETc), and water-use efficiency (WUE) under limited irrigation. Two hybrids (N74R, a conventional hybrid, and N75H, a drought-tolerant (DT) hybrid) were planted at three water regimes (I100, I75, and I50, referring to 100%, 75%, and 50% of the evapotranspiration requirement) and three planting densities (PD 6, PD 8, and PD 10, referring to 6, 8, and 10 seeds m−2). At I50, drought stress reduced grain yield by 4.78 t/ha for the conventional hybrid but only 4.22 t/ha for the DT hybrid, when compared to I100. Although ETc decreased at I75 and I50, the highest WUE was found at I75. The DT hybrid did not yield more than the conventional hybrid but had greater yield stability at lower water regimes and extracted less soil water. Drought decreased biomass, harvest index, and kernel weight but did not affect kernel number. Higher planting densities increased biomass and kernel number but decreased kernel weight. Kernel number and kernel weight of the conventional hybrid were more sensitive to planting density than the DT hybrid. These data demonstrated that limited irrigation at I75 is an effective way to save water and maintain the maize yield in semiarid areas, and that DT hybrid shows a greater yield stability to plant density under water stress