Study on Load Model of PV Generation Planning

AbstractIn distribution system planning with photovoltaic generations (PVGs), if load is not properly modeled in the simulation, the accuracy of results will be affected. A large number of studies show that load characteristics play a impotrant role in the system analysis. This paper presented the resultant load model, and on this basis, studied the impacts of the constant power load model and constant impedance load model on PV generation planning. Simulation results show that the selection of load models has an important impact on PV generation planning

Hypothesis testing for medical imaging analysis via the smooth Euler characteristic transform

Shape-valued data are of interest in applied sciences, particularly in medical imaging. In this paper, inspired by a specific medical imaging example, we introduce a hypothesis testing method via the smooth Euler characteristic transform to detect significant differences among collections of shapes. Our proposed method has a solid mathematical foundation and is computationally efficient. Through simulation studies, we illustrate the performance of our proposed method. We apply our method to images of lung cancer tumors from the National Lung Screening Trial database, comparing its performance to a state-of-the-art machine learning model

Biomarkers of HIV-1 associated dementia: proteomic investigation of sera

Background: New, more sensitive and specific biomarkers are needed to support other means of clinical diagnosis of neurodegenerative disorders. Proteomics technology is widely used in discovering new biomarkers. There are several difficulties with in-depth analysis of human plasma/ serum, including that there is no one proteomic platform that can offer complete identification of differences in proteomic profiles. Another set of problems is associated with heterogeneity of human samples in addition intrinsic variability associated with every step of proteomic investigation. Validation is the very last step of proteomic investigation and it is very often difficult to validate potential biomarker with desired sensitivity and specificity. Even though it may be possible to validate a differentially expressed protein, it may not necessarily prove to be a valid diagnostic biomarker. Results: In the current study we report results of proteomic analysis of sera from HIV-infected individuals with or without cognitive impairment. Application of SELDI-TOF analysis followed by weak cation exchange chromatography and 1-dimensional electrophoresis led to discovery of gelsolin and prealbumin as differentially expressed proteins which were not detected in this cohort of samples when previously investigated by 2-dimensional electrophoresis with Difference Gel Electrophoresis technology. Conclusion: Validation using western-blot analysis led us to conclude that relative change of the levels of these proteins in one patient during a timeframe might be more informative, sensitive and specific than application of average level estimated based on an even larger cohort of patients

Intercenter reliability and validity of the rhesus macaque GeneChip

BACKGROUND: The non-human primate (NHP) research community has been intensely interested in obtaining whole-genome expression arrays for their work. Recently, novel approaches were used to generate the DNA sequence information for a rhesus GeneChip. To test the reliability of the rhesus GeneChip across different centers, RNA was isolated from five sources: cerebral cortex, pancreas, thymus, testis, and an immortalized fibroblast cell line. Aliquots of this RNA were sent to each of three centers: Yerkes National Primate Research Center, Oregon National Primate Research Center and the University of Nebraska Medical Center. Each center labeled the samples and hybridized them with two rhesus macaque GeneChips. In addition, rhesus samples were hybridzed with human GeneChips to compare with samples hybridized with the rhesus GeneChip. RESULTS: The results indicate that center effects were minimal and the rhesus GeneChip appears highly reliable. To test the validity of the rhesus GeneChip, five of the most differentially expressed genes among tissues identified in the reliability experiments were chosen for analysis with Quantitative PCR. For all 5 genes, the qPCR and GeneChip results were in agreement with regard to differential expression between tissues. Significantly more probesets were called present when rhesus samples were hybridized with the rhesus GeneChip than when these same samples were hybridized with a human GeneChip. CONCLUSION: The rhesus GeneChip is both a reliable and a valid tool for examining gene expression and represents a significant improvement over the use of the human GeneChip for rhesus macaque gene expression studies

Impact of lung cancer screening results on participant health-related quality of life and state anxiety in the National Lung Screening Trial

BACKGROUND Low-dose computed tomography (LDCT) lung screening has been associated with a 20% reduction in lung cancer mortality. A major barrier to the adoption of lung screening is the potential negative psychological impact of a false-positive (FP) screen, occurring in 20% to 50% of those screened. The objective of this study was to assess the impact of abnormal findings on health-related quality of life (HRQoL) and anxiety in the American College of Radiology (ACRIN)/National Lung Screening Trial (NLST). METHODS The NLST was a randomized screening trial comparing LDCT with chest X-ray screening (CXR). This study was part of the original protocol. A total of 2812 participants at 16 of 23 ACRIN sites who had baseline HRQoL assessments were asked to complete the Short Form-36 and the State Trait Anxiety Inventory (form Y-1) questionnaires to assess short-term (1 month) and long-term (6 months) effects of screening. FP were lung cancer–free at 1 year, and true-positives (TP) were not. RESULTS Of the total participants, 1024 (36.4%) participants were FP, 63 (2.2%) were TP, 344 (12.2%) had significant incidental findings (SIFs), and 1381 (49.1%) had negative screens. Participants had been randomized to LDCT (n = 1947) and CXR (n = 865). Short-term and long-term HRQoL and state anxiety did not differ across participants with FP, SIF, or negative screens. Short-term and long-term HRQoL were lower and anxiety was higher for TP participants compared to participants with FP, SIF, and negative screens. CONCLUSIONS In a large multicenter lung screening trial, participants receiving a false-positive or SIF screen result experienced no significant difference in HRQoL or state anxiety at 1 or at 6 months after screening relative to those receiving a negative result. Cancer 2014;120:3401–3409. © 2014 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. In a large multi-center lung screening trial, participants receiving a false positive or significant incidental finding screen result experienced no significant difference in health related quality of life or state anxiety at 1 or at 6 months after screening relative to those receiving a negative result

Large scale analysis of positional effects of single-base mismatches on microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Affymetrix GeneChips utilize 25-mer oligonucleotides probes linked to a silica surface to detect targets in solution. Mismatches due to single nucleotide polymorphisms (SNPs) can affect the hybridization between probes and targets. Previous research has indicated that binding between probes and targets strongly depends on the positions of these mismatches. However, there has been substantial variability in the effect of mismatch type across studies.</p> <p>Methods</p> <p>By taking advantage of naturally occurring mismatches between rhesus macaque transcripts and human probes from the Affymetrix U133 Plus 2 GeneChip, we collected the largest 25-mer probes dataset with single-base mismatches at each of the 25 positions on the probe ever used in this type of analysis.</p> <p>Results</p> <p>A mismatch at the center of a probe led to a greater loss in signal intensity than a mismatch at the ends of the probe, regardless of the mismatch type. There was a slight asymmetry between the ends of a probe: effects of mismatches at the 3' end of a probe were greater than those at the 5' end. A cross study comparison of the effect of mismatch types revealed that results were not in good agreement among different reports. However, if the mismatch types were consolidated to purine or pyrimidine mismatches, cross study conclusions could be generated.</p> <p>Conclusion</p> <p>The comprehensive assessment of the effects of single-base mismatches on microarrays provided in this report can be useful for improving future versions of microarray platform design and the corresponding data analysis algorithms.</p

Applying Multivariate Adaptive Splines to Identify Genes With Expressions Varying After Diagnosis in Microarray Experiments

Purpose: To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. Methods: A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis. Results: In total, 1640 probe sets (genes) were reliably identified to have turning points along with the age at diagnosis in their expression profiling, of which 927 expressed lower after turning points and 713 expressed higher after the turning points. K-means clustered them into 3 groups with turning points centering at 54, 62.5, and 72, respectively. The pathway analysis showed that the identified genes were actively involved in various cancer-related functions or networks. Conclusions: In this article, we applied the nonparametric multivariate adaptive splines method to a publicly available gene expression data and successfully identified genes with expressions varying before and after breast cancer diagnosis