Performance comparison of point and spatial access methods

In the past few years a large number of multidimensional point access methods, also called multiattribute index structures, has been suggested, all of them claiming good performance. Since no performance comparison of these structures under arbitrary (strongly correlated nonuniform, short "ugly") data distributions and under various types of queries has been performed, database researchers and designers were hesitant to use any of these new point access methods. As shown in a recent paper, such point access methods are not only important in traditional database applications. In new applications such as CAD/CIM and geographic or environmental information systems, access methods for spatial objects are needed. As recently shown such access methods are based on point access methods in terms of functionality and performance. Our performance comparison naturally consists of two parts. In part I we w i l l compare multidimensional point access methods, whereas in part I I spatial access methods for rectangles will be compared. In part I we present a survey and classification of existing point access methods. Then we carefully select the following four methods for implementation and performance comparison under seven different data files (distributions) and various types of queries: the 2-level grid file, the BANG file, the hB-tree and a new scheme, called the BUDDY hash tree. We were surprised to see one method to be the clear winner which was the BUDDY hash tree. It exhibits an at least 20 % better average performance than its competitors and is robust under ugly data and queries. In part I I we compare spatial access methods for rectangles. After presenting a survey and classification of existing spatial access methods we carefully selected the following four methods for implementation and performance comparison under six different data files (distributions) and various types of queries: the R-tree, the BANG file, PLOP hashing and the BUDDY hash tree. The result presented two winners: the BANG file and the BUDDY hash tree. This comparison is a first step towards a standardized testbed or benchmark. We offer our data and query files to each designer of a new point or spatial access method such that he can run his implementation in our testbed

Consistent Testing for an Implication of Supermodular Dominance

Supermodularity, or complementarity, is a popular concept in economics which can characterize many objective functions, including utility, social welfare, and production functions. Further, supermodular dominance captures a preference for greater interdependence among inputs of those functions, and it can be applied to examine which input set would produce higher expected utility, social welfare, or production. However, contrary to the profuse literature on supermodularity, to the best of our knowledge, there is no existing work on either testing or empirical analysis for supermodular dominance. In this paper, we propose a consistent test for a useful implication of supermodular dominance and suggest a correlation dominance testing for Gaussian random variables as a special case. The test is based on a novel bootstrap critical value, which has potentially enhanced power performance by exploiting the information on the contact set on which the null hypothesis is binding. We also conduct Monte Carlo simulations to explore the finite sample performance of our tests. We then apply our test to analyze two economic questions. We first investigate whether the interdependence of stock returns among major firms has increased after the COVID-19, and find evidence supporting this conjecture. We also compare the interdependence of patent citations depending on distance, where greater interdependence can imply greater expected social welfare effect. The results suggest that, in most cases, between-state citations seem to have greater interdependence than within-state citations, implying that lively interaction between firms across states might engender greater expected social welfare than knowledge spillover within a geographically confined area

Selection of Optimized Retaining Wall Technique Using Self-Organizing Maps

Construction projects in urban areas tend to be associated with high-rise buildings and are of very large-scales; hence, the importance of a project’s underground construction work is significant. In this study, a rational model based on machine learning (ML) was developed. ML algorithms are programs that can learn from data and improve from experience without human intervention. In this study, self-organizing maps (SOMs) were utilized. An SOM is an alternative to existing ML methods and involves a subjective decision-making process because a developed model is used for data training to classify and effectively recognize patterns embedded in the input data space. In addition, unlike existing methods, the SOM can easily create a feature map by mapping multidimensional data to simple two-dimensional data. The objective of this study is to develop an SOM model as a decision-making approach for selecting a retaining wall technique. N-fold cross-validation was adopted to validate the accuracy of the SOM model and evaluate its reliability. The findings are useful for decision-making in selecting a retaining wall method, as demonstrated in this study. The maximum accuracy of the SOM was 81.5%, and the average accuracy was 79.8%

Relations Between QRS|T Angle, Cardiac Risk Factors, and Mortality in the Third National Health and Nutrition Examination Survey (NHANES III)

On the surface electrocardiogram, an abnormally wide QRS|T angle reflects changes in the regional action potential duration profiles and in the direction of the repolarization sequence, which is thought to increase the risk of ventricular arrhythmia. We investigated the relation between an abnormal QRS|T angle and mortality in a nationally representative sample of subjects without clinically evident heart disease. We studied 7,052 participants ≥40 years old in the third National Health and Nutrition Examination Survey with 12-lead electrocardiograms. Those with self-reported or electrocardiographic evidence of a previous myocardial infarction, QRS duration of ≥120 ms, or history of heart failure were excluded. Borderline and abnormal spatial QRS|T angles were defined according to gender-specific 75th and 95th percentiles of frequency distributions. All-cause (1,093 women and 1,191 men) and cardiovascular (462 women and 455 men) mortality during the 14-year period was assessed through linkage with the National Death Index. On multivariate analyses, an abnormal spatial QRS|T angle was associated with an increased hazard ratio (HR) for cardiovascular mortality in women (HR 1.82, 95% confidence interval 1.05 to 3.14) and men (HR 2.21, 95% confidence interval 1.32 to 3.68). Also, the multivariate adjusted HR for all-cause mortality associated with an abnormal QRS|T angle was 1.30 (95% confidence interval 0.95 to 1.78) for women and 1.87 (95% confidence interval 1.29 to 2.7) for men. A borderline QRS|T angle was not associated with an increased risk of all-cause or cardiovascular mortality. In conclusion, an abnormal QRS|T angle, as measured on a 12-lead electrocardiogram, was associated with an increased risk of cardiovascular and all-cause mortality in this population-based sample without known heart disease

Interaction between androgen receptor and coregulator SLIRP is regulated by Ack1 tyrosine kinase and androgen

Aberrant activation of the androgen receptor (AR) may play a critical role in castration resistant prostate cancer. After ligand binding, AR is recruited to the androgen responsive element (ARE) sequences on the DNA where AR interaction with coactivators and corepressors modulates transcription. We demonstrated that phosphorylation of AR at Tyr-267 by Ack1/TNK2 tyrosine kinase results in nuclear translocation, DNA binding, and androgen-dependent gene transcription in a low androgen environment. In order to dissect downstream mechanisms, we searched for proteins whose interaction with AR was regulated by Ack1. SLIRP (SRA stem-loop interacting RNA binding protein) was identified as a candidate protein. Interaction between AR and SLIRP was disrupted by Ack1 kinase activity as well as androgen or heregulin treatment. The noncoding RNA, SRA, was required for AR-SLIRP interaction. SLIRP was bound to ARE’s of AR target genes in the absence of androgen. Treatment with androgen or heregulin led to dissociation of SLIRP from the ARE. Whole transcriptome analysis of SLIRP knockdown in androgen responsive LNCaP cells showed that SLIRP affects a significant subset of androgen-regulated genes. Our data suggest that Ack1 kinase and androgen regulate interaction between AR and SLIRP and that SLIRP functions as a coregulator of AR with properties of a corepressor in a context-dependent manner

Androgen receptor targeting drugs in castration-resistant prostate cancer and mechanisms of resistance

Reactivated androgen receptor (AR) signaling drives castration-resistant prostate cancer (CRPC). Novel AR targeting drugs abiraterone and enzalutamide have improved survival of CRPC patients. However, resistance to these agents develops and patients ultimately succumb to CRPC. Potential mechanisms of resistance include the following: 1) Expression of AR splice variants such as the AR-V7 isoform which lacks the ligand-binding domain, 2) AR missense mutations in the ligand-binding domain, such as F876L and T877A, and 3) Mutation or overexpression of androgen biosynthetic enzymes or glucocorticoid receptor. Several novel agents may overcome resistance mechanisms. Galeterone acts through multiple mechanisms that include degradation of AR protein and is being evaluated in CRPC patients positive for AR-V7. EPI-001 and related compounds inhibit AR splice variants by targeting the N-terminal transactivation domain of AR. Promising therapies and novel biomarkers, such as AR-V7, may lead to improved outcomes for CRPC patients

Mechanisms of acquired resistance to androgen receptor targeting drugs in castration-resistant prostate cancer

After initial response to androgen receptor targeting drugs abiraterone or enzalutamide, most patients develop progressive disease and therefore, castration resistant prostate cancer (CRPC) remains a terminal disease. Multiple mechanisms underlying acquired resistance have been postulated. Intratumoral androgen synthesis may resume after abiraterone treatment. A point mutation in the ligand binding domain of androgen receptor may confer resistance to enzalutamide. Emergence of androgen receptor splice variants lacking the ligand binding domain may mediate resistance to abiraterone and enzalutamide. Steroid receptors such as glucocorticoid receptor may substitute for androgen receptor. Drugs with novel mechanisms of action or combination therapy, along with biomarkers for patient selection, may be needed to improve the therapy of CRPC