Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential expression and feature selection in the analysis of multiple omics studies

With the rapid advances of high-throughput technologies in the past decades, various kinds of omics data have been generated from many labs and accumulated in the public domain. These studies have been designed for different biological purposes, including the identification of differentially expressed genes, the selection of predictive biomarkers, etc. Effective meta-analysis of omics data from multiple studies can improve statistical power, accuracy and reproducibility of single study. This dissertation covered a few methods for differential expression (Chapter 2 and 3) and feature selection (Chapter 4) in the analysis of multiple omics studies. In Chapter 2, we proposed a full Bayesian hierarchical model for RNA-seq meta-analysis by modeling count data, integrating information across genes and across studies, and modeling differential signals across studies via latent variables. A Dirichlet process mixture prior was further applied on the latent variables to provide categorization of detected biomarkers according to their differential expression patterns across studies. We used both simulations and a real application on multiple brain region HIV-1 transgenic rats to demonstrate improved sensitivity, accuracy and biological findings of our method. In Chapter 3, we extended the previous Bayesian model to jointly integrate transcriptomic data from the two platforms: microarray and RNA-seq. In Chapter 4, we considered a general framework for variable screening with multiple omics studies and further proposed a novel two-step screening procedure for high-dimensional regression analysis in this framework. Compared to the one-step procedure and rank-based sure independence screening procedure, our procedure greatly reduced false negative errors while keeping a low false positive rate. Theoretically, we showed that our procedure possesses the sure screening property with weaker assumptions on signal strengths and allows the number of features to grow at an exponential rate of the sample size. Public health significance: The proposed methods are useful in detecting important biomarkers that are either differentially expressed or predictive of clinical outcomes. This is essential for searching for potential drug targets and understanding the disease mechanism. Such findings in basic science can be translated into preventive medicine or potential treatment for disease to promote human health and improve the global healthcare system.
OCA Indexes and Convergence Process in Europe

This paper evaluates the European monetary convergence for period 2001 and 2013. The main purpose of this contribution is the estimation of the so-called OCA index, which indicates the proximity of two economic areas. The paper is theoretically based mainly on the research of Bayoumi and Eichengreen (1997), and Horvath and Komarek (2003). Selection and calculation of variables precedes the econometric analysis, and those variables correspond to the basic characteristics of an optimum currency area. Although the estimated model fulfills the conditions of economic and econometric verifications, its explanatory capabilities are significantly reduced due to the limited set of input data. Results of the analysis point to relatively stable values of indices in the period, but their further examination of the development in time reveals a steady deterioration in the case of almost all economies. That means that the convergence process was not proven because a decrease in OCA indexes values over the time was not observed. According to the results of comparison, methodological approach of the OCA indexes cannot be considered reliable because minor differences in calculation give different outputs.
Filtering Strategies for Robust Myoelectric Pattern Classification

Recent investigations into the use of real-time, pattern recognition based myoelectric control systems have shown excellent results in terms of classification accuracy and limb controllability under clinical supervision. Longer term, continuous use appears to be subject to deterioration in classification accuracy and usability due to factors including electrode displacement, electrode/skin interface impedance, and user variability. In this work, a simple filtering strategy for improved robustness to external noise is introduced. Recorded signals are digitally filtered to remove noise vulnerable frequencies while retaining discriminatory myoelectric information for classification.
Study of Fairness of Resource Adaptation Based on Utility

Nash bargaining solution (NBS) is applied to the resource allocation in wireless networks so that a fair allocation scheme, based on utility, was proposed. Through a case study, the new scheme was proved to be superior to the existing scheme of equal utility value. A distributed model of the scheme was also introduced. The users could maximize independently their own net utility with the model in a proper pricing policy. As a result, the network achieves an optimized total utility.
Monetary Policy Changes,Bank Credits and Accounting Conservatism

How macroeconomic policies(e.g.monetary policies) affect economic growth through their impacts on firm behaviors has been a less explored research area.This paper attempts to explore this issue by studying the impact of monetary policy changes on the relationship between firm-level accounting conservatism and firms' access to bank credits.In particular,the authors predict that firm accounting policies become more conservative in order to obtain bank credits when central bank tightens the monetary policies.Using Chinese stock market data from 1998 to 2008,and using central bank's interest rate policy changes,the paper defines the year of 2004,2006 and 2007 as tight monetary policy years,and finds the evidence that support the author's conjecture. It is further found that firms that are more dependable on external financing,and with higher debt level use more conservative accounting policies,while firms with large cash balance and state-controlled firms use less conservative accounting policies.Finally,the paper concludes in tight monetary policy periods,accounting conservatism helps firms to obtain better access to bank credits.
Business Cycles and Currency Returns

We find a strong link between currency excess returns and the relative strength of the business cycle. Buying currencies of strong economies and selling currencies of weak economies generates high returns both in the cross section and time series of countries. These returns stem primarily from spot exchange rate predictability, are uncorrelated with common currency investment strategies, and cannot be understood using traditional currency risk factors in either unconditional or conditional asset pricing tests. We also show that a business cycle factor implied by our results is priced in a broad currency cross section.
Creating Optimal Portfolio and the Efficient Frontier Using Microsoft Excel ®

Portfolio managers and investors strive to achieve the best possible trade-off between risk and return, and one of the tools they use is constructing mean-variance efficient portfolios. Finance students learn about optimal portfolios and efficient frontiers, though it is difficult to replicate them unless they have access to sophisticated software. This paper develops a teaching module that uses Microsoft Excel® to create mean-variance portfolios and traces out the efficient frontier using real-world data. In the process, the students learn to determine optimal investment allocations in a portfolio, select the optimum investment portfolio given investor’s objectives and preferences and learn about factors that influence different asset allocations. For multiple assets (N>3), the paper uses Matrix algebra in Excel®. The paper enables students and investors to learn how to construct real-world mean-variance efficient portfolios using Excel®.
Assessment of the prominent Open Source and Free Data Mining Tools

The fundamental thought process of Data mining is to analyze the information from alternate point of view then name it and typify it keeping in mind the end goal to secure helpful data by utilizing their different new procedures and tools. Today, the different information mining apparatuses accessible that analysts requirements for assessing their information. Alongside the expanding significance of this science, there was fast increment in the quantity of free and open source apparatuses created to actualize its ideas. It wouldn't be anything but difficult to choose which device plays out the coveted undertaking better, in addition to we can't depend exclusively on depiction given by the seller . Distinctive devices incorporated into data mining like, WEKA, Tanagra, Rapid Miner, Orange, KNIME etc are reviewed in this paper and their advantages and disadvantages are presented and furthermore think about their features. For the scientists this comparative review would be helpful to make a best determination of the device
Arbitrage Opportunities: Anatomy and Remediation

We introduce an experimental design where arbitrage opportunities emerge reliably and repeatedly. We observe significantly higher sell-side than buy-side arbitrage opportunities. We study ways to mitigate them. Relaxing margin requirements, shortsale restrictions, or both have neither statistically nor economically significant effects. Increasing competition (more participants, each with small stakes), and more impactful, participants’ stakes (few wealthy participants each with large exposures), generate large reductions in arbitrage opportunities. Hence, we advocate increased competition for small markets, and allowance for large stakes in large markets, rather than relaxation of rules on margin purchases or shortsales.
Analysis of Human-Swarm Visualizations

Interest in robotic swarms has increased exponentially. Prior research determined that humans perceive biological swarm motions as a single entity, rather than perceiving the individuals. An open question is how the swarm’s visual representation and the associated task impact human performance when identifying current swarm tasks. The majority of the existing swarm visualizations present each robot individually. Swarms typically incorporate large numbers of individuals, where the individuals exhibit simple behaviors, but the swarm appears to exhibit more intelligent behavior. As the swarm size increases, it becomes increasingly difficult for the human operator to understand the swarm’s current state, the emergent behaviors, and predict future outcomes. Alternative swarm visualizations are one means of mitigating high operator workload and risk of human error. Five visualizations were evaluated for two tasks, go to and avoid, in the presence or absence of obstacles. The results indicate that visualizations incorporating representations of individual agents resulted in higher accuracy when identifying tasks.
Developing a Java-based Genetic Algorithm to Solve the Travelling Salesman Problem

In this paper, software was developed to solve the travelling salesman problem. The Travelling Salesman Problem is a computational optimization problem that requires a lot of time to solve using brute force algorithm. The research aims at developing java-based software that provides an optimum solution to the Travelling Salesman Problem using the concepts of genetic algorithm within reasonable time frame.
On the relevance of double tax treaties

This paper investigates the effects of double tax treaties (DTTs) on foreign direct investment (FDI) after controlling for their relevance in the presence of treaty shopping. DTTs cannot be considered a bilateral issue, but must be viewed as a network. We define tax distance as the cost of channelling corporate income from one country to another and, by considering treaty shopping through intermediate jurisdictions, we calculate the shortest (i.e. the cheapest) distance between any two countries. We show that relevant tax treaties—which reduce the direct tax distance both over domestic law and the entire existing treaty network—will increase FDI by about 18%.
A User-Centric Housing Recommender System

Recommender systems are very useful in assisting users to reduce the complexities involved in their decision making processes. It is particularly difficult for people to make decisions on housing choices because different options exist with different facilities, in different locations and with varied cost implications. This paper proposes a hybrid user-centric housing recommender system that is implemented to assist potential house buyers and tenants to generate house listings based on their preferences with the aid of fuzzy logic and item-based collaborative filtering. A virtual tour of the houses is also provided for better choice making.
Modelling Intervalling Effect of High Frequency Trading on Portfolio Volatility

This paper theoretically examines whether reducing the minimum trading interval could affect portfolio volatility. Modelling the underlying de-trended asset price with Ornstein Uhlenbeck process, the paper investigates the volatility of portfolios that employ buy and hold strategy and momentum strategy. The paper presents theoretical evidence that the fast trading could increase portfolio price fluctuation and hence potentially suggests another cost of high frequency trading, besides the well-known damages including herding, aggressive trading strategies dark pools, immediate-or-cancel type orders.
Understanding travel risks in a developing country: a bottom up approach

ABSTRACT This paper explores travel risk associated with natural disasters focusing on a developing country context using a bottom-up approach. A mixed method was used to identify seven travel risk types from tourists’ perspective. The exploratory sequential design was applied to 52 respondents in the qualitative phase and 605 respondents in the quantitative phase. The study area was West Sumatra, Indonesia, a popular tourist destination that is prone to natural disasters. This study found different dimensions of travel risk and provide scales for future research in Indonesia and other developing countries.
Assessment of the Financial Sustainability of China’s New Rural Pension Plan: Does the Demographic Policy Reform Matter?

Rural China is experiencing a rapid aging process caused by low fertility and large-scale rural-to-urban migration, which will place an increasing payment burden on the rural pension plan. To allay the negative impact of the aging transition, China has recently carried out a demographic policy reform, replacing the famous one-child policy with the two-child policy. This paper evaluates the impacts of the demographic policy reform on the financial sustainability of China’s New Rural Pension Plan (NRPP). By applying the cohort component population projection method and building actuarial models, the solvency sustainability of the NRPP between 2019 and 2080 is estimated under six demographic policy scenarios, followed by sensitivity analysis. The simulation results show that under the one-child policy, the current and the accumulated pension fund would run deficits in 2030 and 2042, and then the pension deficits would expand rapidly. The two-child policy would relieve the pension pressure moderately before 2075, but thereafter, the pension deficits would become much worse. Sensitivity analysis of a series of demographics and pension parameters on the financial sustainability of the NRPP are displayed. On average, the long-term pension gap may not be avoided for the NRPP, regardless of raising the contribution rate, delaying the retirement age, or encouraging people to have more children.
Did the American Recovery and Reinvestment Act Help Counties Most Affected by the Great Recession?

One of the statements of purpose of the American Recovery and Reinvestment Act (ARRA) was "to assist those most impacted by the recession. " To consider this facet, the ARRA is assessed along this dimension using the concept of risk-sharing. We estimate a trend-stationary autoregressive model of county-level wage income dynamics with each county subject to an idiosyncratic shock and a common shock (with county-specific factor loading). These shocks are used to estimate a redistributive fiscal policy function. The fiscal-offset is 33.6% for the common shock and 6.64% for the county-specific shock. Both of these fiscal policy parameters are statistically and economically significant.
The financialisation of urban infrastructure: A framework of analysis

The literature on the financialisation of urban infrastructure typically traces how an infrastructure asset’s balance sheet is (re)engineered to create a financial asset. What the literature neglects are the processes by which an asset generates urban flows. Attention to these processes, we argue, not only gives better insight into the processes of financialisation of infrastructure but also exposes how the act of financing affects the operations of cities through its influence on the performance of infrastructure assets. The argument presented in the article is informed by case studies of infrastructure investments revealed in interviews conducted in New York, London and Sydney. This material is drawn on to generate a framework for understanding the relationships between infrastructure investing and the infrastructure-enabled flows of a city. This framework has three dimensions through which the financialisation process is seen to be mediated. These are capital structure, organisational structure and regulatory structure. The article argues that these mezzanine-level conceptualisations enable us to explore the to-and-fro between financing and operating cities. A key proposition is that the physical flows of a city are basic not only to the design and enactment of an investment instrument but also to its financial viability. The realisation of this relationship has changed the way investors approach infrastructure assets as investment products. Implications for urban management are drawn.
Networked Cooperation: How the European Union Mobilizes Peacekeeping Forces to Project Power Abroad

Abstract How does the European Union (EU) recruit troops and police to serve in EU peacekeeping missions? This article suggests that pivotal EU member states and EU officials make strategic use of the social and institutional networks within which they are embedded to bargain reluctant states into providing these forces. These networks offer information on deployment preferences, facilitate side-payments and issue-linkages, and provide for credible commitments. EU operations are consequently not necessarily dependent on intra-EU preference convergence—as is often suggested in the existing literature. Rather, EU force recruitment hinges on highly proactive EU actors, which use social and institutional ties to negotiate fellow states into serving in an EU missions.
Nepotism in Primary Schools

Article History: Received 18.08. 2017 Received in revised form 29.09. 2017 Accepted 02.10. 2017 Available online 30.12. 2017 This study aims to determine the opinions of primary school teachers on whether there is nepotism in their respective schools. The study was designed as a survey. The study in which 1689 teachers working in public primary school in Avcilar, Istanbul in the school year of 2016-2017 were involved on voluntary basis, has a study group of 361 teachers. For the study, data were collected by using ‘Scale for Nepotism in School Administration’ developed by Erdem and Meriç (2012). The scale including 25 items is formed by 4 sub-dimensions, which are planning, organization, coordination and evaluation. As a result of the study, teachers reported that there is never Nepotism in their school. The teachers’ opinions did not significantly vary by their type of employment, sex and union membership. A significant difference was observed between their stage of stepping into career and the other stages according their career stages. There was also a significant difference observed between the classroom teachers and subject matter teachers considering the field of study variable. © 2017 IOJES. All rights reserved
An Investigation into Dairy Cow Welfare in Canada: A Cow and a Human Perspective

Leg injuries on dairy cows are a common and highly visible welfare concern on commercial dairy farms. With greater attention being placed on food animal welfare and limited research being conducted on tiestall farms, this study aimed to identify prevalence and risk factors for hock and knee injuries on dairy cows housed in tiestall barns in Ontario (n = 40) and Quebec (n = 60). A sample of 40 cows was purposively selected per farm, and several animaland farmbased measures were taken. Both hocks and both knees on each cow were scored as injured (presence of lesions or swelling) or not injured (no alterations or hair loss), and the highest score of each of the 2 knees and the 2 hocks was considered the cow’s hock or knee score. Possible animaland farm-based risk factors were incorporated into 2 separate multivariable logistic models for hock injuries and knee injuries respectively at the cow level. Mean (±SD) percentage of cow with hock injuries per farm was found to be 56 ± 18% and mean percentage of knee injuries per farm was found to be 43 ± 23%. Animal-based factors found to be associated with a greater odds of hock injuries at the cow level were increased days in milk (DIM), lower body condition score (BCS), lameness, higher parity, higher cow width, median lying bout duration, and median number of lying bouts. Environmental factors found to be associated with hock
Parallel computation of Doppler spectrum from dynamic sea surfaces at microwave bands

The Doppler spectrum of the electromagnetic (EM) scattering field from the two-dimensional dynamic sea surface is calculated based on the composite scattering model. The two-dimensional dynamic sea surfaces are generally simulated as a superposition of large-scale gravity waves and small-scale capillary ripples. On this basis, the Doppler spectrum of the EM scattering field from the two-dimensional dynamic sea surface can be calculated based on the composite scattering model, which takes both the quasi-specular scattering and Bragg scattering mechanism into account. However, due to the high resolution and real-time dynamic complexity of the dynamic sea surfaces, the calculation of the Doppler spectrum will be computationally expensive and very time-consuming. In this paper, a GPU-based algorithm of Doppler spectrum was proposed by utilizing the Tesla K80 GPUs with diverse CUDA optimization techniques. The GPU-based Doppler spectrum implementation includes five optimization strategies: first, the temporary arrays are utilized to reduce the repeat float-points operations in the loop; then the device memory was effectively exploited to reduce the data transfer time between the CPU and GPU; the fast math compiler option was also utilized to further improve the computation performance of the Doppler spectrum calculation; finally the data transfer time between the device and host memories can be effectively hide by using the asynchronous data transfer (ADT). Compared to the CPU serial program executed on Intel(R) Core(TM) i5-3450 CPU, the GPU-based Doppler spectrum implementation can achieve a significant speedup of1200× .