An Improved Modeling for Low-grade Organic Rankine Cycle Coupled with Optimization Design of Radial-inflow Turbine

This document is the Accepted Manuscript of the following article: Lijing Zhai, Guoqiang Xu, Jie Wen, Yongkai Quan, Jian Fu, Hongwei Wu, and Tingting Li, ‘An improved modeling for low-grade organic Rankine cycle coupled with optimization design of radial-inflow turbine’, Energy Conversion and Management, Vol. 153: 60-70, December 2017. Under embargo. Embargo end date: 10 October 2018. The final, published version is available online at DOI: https://doi.org/10.1016/j.enconman.2017.09.063. Published by Elsevier Ltd.Organic Rankine cycle (ORC) has been proven to be an effective and promising technology to convert low-grade heat energy into power, attracting rapidly growing interest in recent years. As the key component of the ORC system, turbine significantly influences the overall cycle performance and its efficiency also varies with different working fluids as well as in different operating conditions. However, turbine efficiency is generally assumed to be constant in the conventional cycle design. Aiming at this issue, this paper couples the ORC system design with the radial-inflow turbine design to investigate the thermodynamic performance of the ORC system and the aerodynamic characteristics of radial-inflow turbine simultaneously. The constrained genetic algorithm (GA) is used to optimize the radial-inflow turbine with attention to six design parameters, including degree of reaction, velocity ratio, loading coefficient, flow coefficient, ratio of wheel diameter, and rotational speed. The influence of heat source outlet temperature on the performance of the radial-inflow turbine and the ORC system with constant mass flow rate of the heat source and constant heat source inlet temperature is investigated for four kinds of working fluids. The net electrical powers achieved are from few tens kWs to one hundred kWs. The results show that the turbine efficiency decreases with increasing heat source outlet temperature and that the decreasing rate of turbine efficiency becomes faster in the high temperature region. The optimized turbine efficiency varies from 88.06% (using pentane at the outlet temperature of 105 ºC) to 91.01% (using R245fa at the outlet temperature of 80 ºC), which appears much higher compared to common values reported in the literature. Furthermore, the cycle efficiency increases monotonously with the growth of the heat source outlet temperature, whereas the net power output has the opposite trend. R123 achieves the maximum cycle efficiency of 12.21% at the heat source outlet temperature of 110 ºC. Based on the optimized results, the recommended ranges of the key design parameters for ORC radial-inflow turbine are presented as well.Peer reviewe

Effect of Dihuang rougui decoction on ovariectomyinduced osteoporosis in rats

Purpose: To investigate the effect of Dihuang Rougui Decoction (DRD) on ovariectomy-induced osteoporosis in rats.Methods: Female Sprague-Dawley rats were randomly assigned to a  normal group (control) and five ovariectomy (OVX) subgroups: OVX with vehicle (OVX), OVX with positive control drug (alendronate sodium tablets, 1.6 mg/kg/week), and OVX + DRD (75, 150 or 300 mg/kg/day). After the rats were subjected to ovariectomy for 4 weeks, fosamax or DRD were administered daily (orally) for 16 weeks. The bone mineral density (BMD) of the L4 vertebrae and right femurs of the rats was evaluated. Serum hormones estradiol (E2), follicle-stimulating  hormone (FSH) and luteinizing hormone (LH) levels and serum alkaline phosphatase (ALP), osteocalcin (OC) and telopeptides of collagen type I (CTx) levels of the rats were determined. The bone tissue morphology of the rats was examined by microscopy.Results: The results show that DRD dose-dependently inhibited bone  mineral density (BMD) reduction of L4 vertebrae and femurs (both p < 0.05). DRD significantly increased serum E2, FSH and LH levels (p < 0.05) in the osteoporotic rats, and significantly lowered serum ALP, CTx and OC concentrations, compared to OVX group (p < 0.01). Compared with OVX model group, bone trabeculae in all three DRD groups and nilestriol groups were wider, and the space and connections markedly increased. Furthermore, the medullary cavity reduced in size.Conclusion: These findings indicate that DRD mitigates OVX-induced  osteoporosis in rats, and thus, the decoction has a potential for clinical  management of osteoporosis patients.Keywords: Dihuang Rougui decoction, Osteoporosis, Ovariectomy, Bone mineral density, Serum bone marker, Bone tissue morpholog

Antenna array calibration methods based on simultaneous perturbation

Antenna arrays have gained significant interest in millimetre-wave communication systems as an enabling technology to achieve higher capacity and mitigate the high propagation loss. Such arrays with a large bandwidth need to be efficiently calibrated to maximise their performance. An antenna array calibration method based on a stochastic approximation algorithm and simultaneous perturbation has been developed and the procedures to implement it in both frequency and time domains have been presented. The approaches to define objective functions and establish gradient approximations to fulfill a successful convergence for acquiring calibration coefficients in both domains have been explored. In the time domain implementation, only a fraction of the measurement time was required to calibrate an antenna array of ultrawide bandwidth compared with other methods using a perturbation technique. The effectiveness of the proposed method has been validated via numerical experiments in both domains

Changes in the proteomic profiles of mouse brain after infection with cyst-forming Toxoplasma gondii

Background Toxoplasma gondii is an opportunistic pathogenic protozoan parasite, which infects approximately one third of the human population worldwide, causing opportunistic zoonotic toxoplasmosis. The predilection of T. gondii for the central nervous system (CNS) causes behavioral disorders and fatal necrotizing encephalitis and thus constitutes a major threat especially to AIDS patients. Methods In the present study, we explored the proteomic profiles of brain tissues of the specific pathogen-free (SPF) Kunming mice at 7 d, 14 d and 21 d after infection with cysts of the Toxoplasma gondii Prugniaud (PRU) strain (Genotype II), by two-dimensional gel electrophoresis (2-DE) combined with MALDI-TOF/TOF tandem mass spectrometry (MS/MS). Results A total of 60 differentially expressed protein spots were selected. Fifty-six spots were successfully identified, which corresponded to 45 proteins of the mouse. Functional analysis using a Gene Ontology database showed that these proteins were mainly involved in metabolism, cell structure, signal transduction and immune responses, and will be beneficial for the understanding of molecular mechanisms of T. gondii pathogenesis. Conclusions This study identified some mouse brain proteins involved in the response with cyst-forming T. gondii PRU strain. These results provided an insight into the responsive relationship between T. gondii and the host brain tissues, which will shed light on our understanding of the mechanisms of pathogenesis in toxoplasmic encephalitis, and facilitate the discovery of new methods of diagnosis, prevention, control and treatment of toxoplasmic encephalopathy

Identification of prognostic cancer-associated fibroblast markers in luminal breast cancer using weighted gene co-expression network analysis

BackgroundCancer-associated fibroblasts (CAFs) play a pivotal role in cancer progression and are known to mediate endocrine and chemotherapy resistance through paracrine signaling. Additionally, they directly influence the expression and growth dependence of ER in Luminal breast cancer (LBC). This study aims to investigate stromal CAF-related factors and develop a CAF-related classifier to predict the prognosis and therapeutic outcomes in LBC.MethodsThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to obtain mRNA expression and clinical information from 694 and 101 LBC samples, respectively. CAF infiltrations were determined by estimating the proportion of immune and cancer cells (EPIC) method, while stromal scores were calculated using the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Weighted gene co-expression network analysis (WGCNA) was used to identify stromal CAF-related genes. A CAF risk signature was developed through univariate and least absolute shrinkage and selection operator method (LASSO) Cox regression model. The Spearman test was used to evaluate the correlation between CAF risk score, CAF markers, and CAF infiltrations estimated through EPIC, xCell, microenvironment cell populations-counter (MCP-counter), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. The TIDE algorithm was further utilized to assess the response to immunotherapy. Additionally, Gene set enrichment analysis (GSEA) was applied to elucidate the molecular mechanisms underlying the findings.ResultsWe constructed a 5-gene prognostic model consisting of RIN2, THBS1, IL1R1, RAB31, and COL11A1 for CAF. Using the median CAF risk score as the cutoff, we classified LBC patients into high- and low-CAF-risk groups and found that those in the high-risk group had a significantly worse prognosis. Spearman correlation analyses demonstrated a strong positive correlation between the CAF risk score and stromal and CAF infiltrations, with the five model genes showing positive correlations with CAF markers. In addition, the TIDE analysis revealed that high-CAF-risk patients were less likely to respond to immunotherapy. Gene set enrichment analysis (GSEA) identified significant enrichment of ECM receptor interaction, regulation of actin cytoskeleton, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathway gene sets in the high-CAF-risk group patients.ConclusionThe five-gene prognostic CAF signature presented in this study was not only reliable for predicting prognosis in LBC patients, but it was also effective in estimating clinical immunotherapy response. These findings have significant clinical implications, as the signature may guide tailored anti-CAF therapy in combination with immunotherapy for LBC patients

Seroprevalence of Toxoplasma gondii infection in pet dogs in Lanzhou, Northwest China

<p>Abstract</p> <p>Background</p> <p>In recent years, surveys of <it>Toxoplasma gondii </it>infection in dogs have been reported worldwide, including China. However, little is known about the prevalence of <it>T. gondii </it>in pet dogs in Northwest China. In the present study, the prevalence of <it>T. gondii </it>in pet dogs in Lanzhou, China was investigated using the modified agglutination test (MAT).</p> <p>Results</p> <p>In this survey, antibodies to <it>T. gondii </it>were found in 28 of 259 (10.81%) pet dogs, with MAT titers of 1:20 in 14 dogs, 1:40 in nine, 1:80 in four, and 1:160 or higher in one dog. The prevalence ranged from 6.67% to 16.67% among dogs of different ages, with low rates in young pet dogs, and high rates in older pet dogs. The seroprevalence in dogs >3 years old was higher than that in dogs ≤1 years old, but the difference was not statistically significant (<it>P ></it>0.05). The seroprevalence in male dogs was 12.50% (17 of 136), and in female dogs it was 8.94% (11 of 123), but the difference was not statistically significant (<it>P ></it>0.05).</p> <p>Conclusions</p> <p>A high prevalence of <it>T. gondii </it>infection was found in pet dogs in Lanzhou, Northwest China, which has implications for public health in this region. In order to reduce the risk of exposure to <it>T. gondii</it>, further measures and essential control strategies should be carried out rationally in this region.</p

Optimization of Traced Neuron Skeleton Using Lasso-Based Model

Reconstruction of neuronal morphology from images involves mainly the extraction of neuronal skeleton points. It is an indispensable step in the quantitative analysis of neurons. Due to the complex morphology of neurons, many widely used tracing methods have difficulties in accurately acquiring skeleton points near branch points or in structures with tortuosity. Here, we propose two models to solve these problems. One is based on an L1-norm minimization model, which can better identify tortuous structure, namely, a local structure with large curvature skeleton points; the other detects an optimized branch point by considering the combination patterns of all neurites that link to this point. We combined these two models to achieve optimized skeleton detection for a neuron. We validate our models in various datasets including MOST and BigNeuron. In addition, we demonstrate that our method can optimize the traced skeletons from large-scale images. These characteristics of our approach indicate that it can reduce manual editing of traced skeletons and help to accelerate the accurate reconstruction of neuronal morphology