Miracle-dz/UniFAR-FTUs huggingface dataset:
Impacts of Financial Market Shock on Bank Asset Allocation from the Perspective of Financial Characteristics of Banks

Given ongoing financial disintermediation and the need for central banks to establish interest rate corridors, commercial banks have increasingly enriched their asset allocation choices, forming an allocation pattern that combines traditional credit assets (loans) and financial assets (interbank and securities investment). Due to the long-standing dual interest rate system in China, the yields of credit assets and financial assets have differed, which means the latter has greater volatility. Using the quarterly panel data of 23 listed commercial banks in China from 2002 to 2017, the empirical results of this paper show that the fluctuation of the return rate of the two types of assets will affect the asset allocation of banks. Specifically, on the one hand, when the price of financial assets falls, which leads to the narrowing of the credit spread between the two types of assets, banks reduce transaction demand to prevent loss and reduce their holdings of financial assets, thus increasing the ratio of their credit assets to financial assets. On the other hand, rising benchmark lending rates leads to the increase in the credit financing cost of demanders, reducing the willingness of demanders to lend, forcing the demander to obtain funds through other channels. This results in the decrease in the ratio of credit assets to financial assets. Furthermore, the financial characteristics of banks also influence the dynamic adjustment range of asset allocation. That is, the lower the reserve ratio and capital adequacy ratio, the smaller the impact of financial asset yield volatility on bank asset allocation.
Public Preferences in a National Willingness-to-Pay Survey

Research Summary We use survey data from a nationally representative sample to explore public support for taxpayer-funded victim compensation programs for financial fraud, consumer fraud, identity theft, and burglary. We use contingent valuation (willingness-to-pay) methodology to infer preferences for compensation programs and explore predictors of those preferences. Overall, our findings reveal that the public strongly supports the implementation of victim compensation programs. Our results also indicate, however, that this support may be driven in part by perceptions of benefiting from this program directly in the future. Additionally, a small but notable minority of respondents exhibit preferences for programs without compensation.
Event Detection in Twitter With an Event Knowledge Base

We present two methods for event detection in Twitter using an event knowledge base. The knowledge base used contains world events reported in the media that we identify as multi-lingual clusters of mainstream news stories. Given this fact, we reduce the problem of event detection to matching tweets to mainstream news stories. The first method consists of using URLs to mainstream news sites present in tweets and in the knowledge base. We use this method to build a supervised corpus of tweets and then create and evaluate a supervised classifier as our second method. Experimental evaluation on real-world data shows that the proposed methods perfom well on our dataset.
Imprints of neutrino-pair flavor conversions on nucleosynthesis in ejecta from neutron-star merger remnants

The remnant of neutron star mergers is dense in neutrinos. By employing inputs from one hydrodynamical simulation of a binary neutron star merger remnant with a black hole of $3\ M_\odot$ in the center, dimensionless spin parameter $0.8$ and an accretion torus of $0.3\ M_\odot$, the neutrino emission properties are investigated as the merger remnant evolves. Initially, the local number density of $\bar{\nu}_e$ is larger than that of $\nu_e$ everywhere above the remnant. Then, as the torus approaches self-regulated equilibrium, the local abundance of neutrinos overcomes that of antineutrinos in a funnel around the polar region. The region where the fast pairwise flavor conversions can occur shrinks accordingly as time evolves. Still, we find that fast flavor conversions do affect most of the neutrino-driven ejecta. Assuming that fast flavor conversions lead to flavor equilibration, a significant enhancement of nuclei with mass numbers $A>130$ is found as well as a change of the lanthanide mass fraction by more than a factor of a thousand. Our findings hint towards a potentially relevant role of neutrino flavor oscillations for the prediction of the kilonova (macronova) lightcurves and motivate further work in this direction.
Analysis of complexity metrics of a software code for obfuscating transformations of an executable code

The complexity metrics of the software code applicable for the analysis of binary files, as well as the methods used at overlaying the obfuscating transformations of these files are considered in the article. The results of the research of the metrics dependence on the performed by special software products obfuscating transformations of a vulnerable binary file are presented. The research confirms the applicability of the technique of the automated vulnerabilities search in binary files, whose analysis is difficult due to obfuscating transformations overlay.
WebGIS Application and Research Based on MapObjects Component in .NET Environment

In order to reuse the existing code resources based on MapObjects component in Web environment,herein a kind of solution for WebGIS is proposed,which was implemented by using Internet Information Services to manage MapObjects application.The system based on MapObjects2.2 GIS component was built by using C# in.NET environment.The server managed by IIS and embedded with Mapobjects component can supply GIS function;Meanwhile,ASP.NET was used to build web pages responding to clients,for it allows us to separate user interface from code files.Besides,web pages being built by ASP.NET have pellucid architecture and better security.In addition,users don't have to download as well as install plug-ins,they can enjoy WebGIS services by using general browser,which increased the using frequency.As a validation for feasibility and high efficiency,a web version of Lanzhou city's traffic digital map was implemented by using the solution as the frame.
An Improved k-means Algorithm for Documents Clustering

This paper first introduces the partitioning-based k-means algorithms for documents clustering. The k-means algorithm adapts to processing the vast amount of documents, but it is sensitive to outliers. So this paper puts forward an idea to separate the clustering centroid from the clustering seed and brings forward an algorithm based on this idea to improve the k-means algorithm. The paper shows the results of the experiments to prove that this algorithm is more veracious and stable than the k-means algorighm.
Efficient quantum tensor product expanders and unitary t-designs via the zigzag product.

A classical t-tensor product expander is a natural way of formalising correlated walks of t particles on a regular expander graph. A quantum t-tensor product expander is a completely positive trace preserving map that is a straightforward analogue of a classical t-tensor product expander. Interest in these maps arises from the fact that iterating a quantum t-tensor product expander gives us a unitary t-design, which has many applications to quantum computation and information. We show that the zigzag product of a high dimensional quantum expander (i.e. t = 1) of moderate degree with a moderate dimensional quantum t-tensor product expander of low degree gives us a high dimensional quantum t-tensor product expander of low degree. Previously such a result was known only for quantum expanders i.e. t = 1. Using the zigzag product we give efficient constructions of quantum t-tensor product expanders in dimension D where t = polylog(D). We then show how replacing the zigzag product by the generalised zigzag product leads to almost-Ramanujan quantum tensor product expanders i.e. having near-optimal almost quadratic tradeoff between the degree and the second largest singular value. Both the products give better tradeoffs between the degree and second largest singular value than what was previously known for efficient constructions.
Gray trend relational clustering and its application in data mining

The characteristics of "poor"information in database and the requirement of "poor" information data mining are analyzed. Based on gray trend relational degree and general system theory, the model of gray trend relational system is investigated. As an application of this model, the gray trend clustering method is presented.Based on scanty data of history sale of a large wine Co. Ltd, according to increasing tendency of sale goods, all kinds of goods are clustered by gray trend clustering method, and the clustering result accords with sale fact. It shows that the gray trend clustering method is valid, convenient and practical.
INDIVIDUAL CULTURAL FACTORS AFFECTING NEW PRODUCT ACCEPTING BEHAVIOR: THE CASE OF ELECTRONIC MARKET IN VIETNAM

Today individualized culture playes an important role in promoting acceptance consumer behavior towards new electronic products in Vietnam. The article explores the influence of individual cultural factors on the consumer accepting behavior. 600 questionnaires in total were distributed among the people residing in HCM city, Vietnam. A structural equation model (SEM) is used to analyze their consumer behavior in relation to new electronic products’ acceptance. According to the analysis of personal factors, fear of risk, innovation and collectiveness significantly influence the consumer acceptance behavior.
Sustainability Assessment Framework: A Mini Review of Assessment Concept

Sustainability assessment is viewed as a vital instrument to aid in the shift towards sustainability which is simply an appraisal method which integrates an iterative and pluralistic procedure. Sustainability assessment is viewed as a vital instrument to aid in the shift towards sustainability. Sustainability assessment is a rather complex appraisal technique conducted for supporting decision-making and policy in an extensive environmental, economic and social perspective. Sustainability assessment transcends a technical or scientific evaluation. Sustainability assessment tools are essentially a structured process encompassing different field-specific analytical methods and models. The growth of indicators in numerous fields has influenced sustainability assessment methodologies to a great extent. In general two broad approaches for sustainability can be distinguished, top-down and bottom-up. Despite the abundance and diversified procedures for evaluating sustainability, indicators based assessment is one of the most widely used platform. Many parties feel that the presence of conceptual inconsistencies and the absence of operational definitions have hampered attempts to appraise, let alone achieve, sustainability. Assessing the sustainability assessment schemes in a quantitative manner requires the identification and integration of diverse phenomena or indicators, in a framework consistent with the evolving concept of sustainability. In fact, integration of indicators for sustainability assessment, have been at the forefront of various political, academic and scientific researches. Existing sustainability assessments schemes typically provide interpretation in the form of comparative value analysis where impacts are scored based on pre-set values, utility analysis where impacts are ranked on a uniform scale and weighted, cost-benefit analysis where positive and negative impacts are apportioned to monetary values, multi-criteria analysis where quantitative as well as qualitative impacts are scaled on pre-set criteria or risk assessment where degrees in risk reduction is identified relative to pre-set risk thresholds. Consequently, the paper that follows provides an integrative analysis of existing sustainability assessment approaches. Such review not only offers a very valuable insight on the features of existing sustainability assessment schemes, but also highlighting gaps to a certain ext
Corporate Culture

Corporate culture is an omnibus term that includes many elements that are relevant to a firm, like norms, values, knowledge, and customs. Economists have made great progress recently in devising methods of measuring different aspects of corporate culture. These empirical measures of culture have explained mergers and acquisitions, corporate risk-taking, and unethical behaviors observed in corporations, among other topics. We argue that unpacking corporate culture into its components is the right way to research it empirically. Theories of corporate culture are still in development, and we discuss the major contributions thus far. We argue that a theory of the firm and of corporate decision-making that is based on corporate culture is more germane to the practical realities of firms’ inner workings than prevailing theories based on property rights and agency costs. Corporate culture has the potential to set the theoretical paradigm for all corporate finance research. Expected final online publication date for the Annual Review of Financial Economics, Volume 13 is November 2022. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Design of a low-power wireless sensor network node

A novel low-power wireless sensor network node is designed and TinyOS is transplanted in the node.Power consumption and performance are considered for hardware design of the sensor node.The node has lower power consumption and further communication than other network node platform.By improving the design implement chain environment of TinyOS for the new MSP430 series processor, the software programming can not be restricted to GCC translator-editor.Furthermore, the RF protocol stack of RF transceiver CC2520 is realized and TinyOS is transplanted to the node.
Introduction to Quantitative Genetics

So far in this course we have dealt entirely either with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus or with the evolution of molecular sequences. Even last week when we were dealing with population genomic data, data from hundreds or thousands of loci, we were treating the variation at each locus separately and combining results across loci. I have some old notes on gametic disequilibrium and how allele frequencies change at two loci simultaneously, but they’re in the “Old notes, no longer updated” section of the book version of these notes (https://figshare.com/articles/journal_contribution/Lecture_notes_ in_population_genetics/100687), and we didn’t discuss them. In every example we’ve considered so far we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
Internal Marketing and Employee's Innovative Work Behavior: The Mediating Role of Job Embeddedness.

Despite a lot of research work on innovative work behavior, the research is not only inconclusive but still to develop a consensus on a single best antecedent of innovative work behavior. Innovative work behavior remains in the limelight of research due to its direct relationship with organizational innovation. Innovative work behavior is an employee’s behavior that demands to be investigated with employee’s specific antecedent. Internal marketing is an emerging concept of human resource management that is the only employee’s specific antecedent to consider the employee as an internal customer and his/her job as a domestic product. Management literature has yet not investigated internal marketing as an antecedent of innovative work behavior. While conducting any research, the target sector for research is of paramount importance. Public and private sectors differ in culture, organizational structure and an administrative point of view. The private sector contributes more than the public sector and specifically the industrial sector. Industrial sector contributes 25% of the economy and in the industrial sector, engineering sector contributes 13.5% in the GDP. In Pakistan, the focus of the past research has been in the service sector and neglected the manufacturing sector which is a backbone of the country. Similarly, the past studies in the manufacturing sector focused the organizational specific variables and overlooked internal marketing with innovative work behavior. This study is based on social exchange theory to develop an integrated model of innovative work behavior which is mandatory for innovation in the manufacturing sector of Pakistan. In the model, innovative work behavior is dependent variable with independent variable internal marketing and its dimensions like strategic rewards, internal communication, training and development, leadership and empowerment. In the model, job embeddedness is a mediating variable, social capital and intrinsic motivations are the moderating variables. Data were collected from the sample of the manufacturing sector. There are more than 450 auto parts manufacturing firms in Pakistan located in different cities.
Research on query semantic expansion based on mutual information

According to the phenomenon of users who are accustomed to use a few words to search the information they need on the internet.But people always can not find the exact information they need.The model of the query semantic expansion based on mutual information is proposed.It can not only find the corresponding information of the query but also find the related information according to the inte-resting of user's.
THE EFFECT OF OPERATING COST, OPERATIONAL EFFICIENCY, CREDIT RISK, LIQUIDITY RISK, RISK AVERSION, MARKET SHARE, BI RATE ON MARGIN BANK

ABSTRACT The purpose of this study is to know how the influence of operating cost, operational efficiency, credit risk, liquidity risk, risk aversion, market share, spread of interest ratetobank margin, the study population is 41 banking companies registered in Bursa Efek Indonesia in 2010-2016 and the sample research into 30 companies with research methods. The type of research used is associative research that is associative technique of associative research using quantitative analysis technique (statistic). To know the amount of influence between variable of writer use data analysis with help SPSS 20. The results of analysis using regression analysis found that the operating cost affects the margin banks in banking companies listed on the Indonesia Stock Exchange period 2010-2015. The results of analysis using regression analysis found that operational efficiency, credit risk and liquidity risk affects the margin banks in banking companies listed on the Indonesia Stock Exchange period 2010 - 2016. Meanwhile, risk aversion, market share and BI rate have no effect on bank margin on banking companies listed on Indonesia Stock Exchange period 2010-2015. Key Words: Operating Cost, Operational Efficiency, Credit Risk, Liquidity Risk, Risk Aversion, Market Share, Spread of Interest Rate, Bank Margin
An Opportunistic Routing Protocol based on Contact Ratio

In opportunistic delay tolerant networks, where end-to-end connectivity between any two nodes is not guaranteed, messages are delivered by opportunistic forwarding between nodes using a store-carry-forward mechanism. In this paper, contact ratio to any node is defined as the contact counts to any specific node over total contact counts. Then, an opportunistic routing protocol based on contact ratio is proposed, where messages are forwarded to a node with higher contact ratio.
Essays on multinational firms and international trade

Multinational firms account for more than a half of world trade, and the majority of foreign direct investment (FDI) is horizontal. Since the horizontal FDI is mainly driven by demand factors, this work focuses on the demand component determining choices of firms about entering into particular foreign markets and setting up global sales networks. Importantly, the entry into a new market is subject to uncertainty regarding the perception of firm's product by foreign consumers, as well as the realizations of aggregate demand fluctuations. On top of this, the returns to multinational activity can vary across countries and industries, which generate differences in the foreign-market entry patterns. In this dissertation, I introduce the structural frameworks suitable for the analysis of industry-specific choices of firms about the multinational sales structure under demand risk. This thesis consists of two self-contained chapters. Both chapters are a joint work with Francesco Paolo Conteduca. Chapter 1 titled ``Serving Abroad: Export, M&A, and Greenfield Investment'' studies foreign-market entry patterns in the professional services industry. Chapter 2 titled ``The Structure of Multinational Sales under Demand Risk'' analyzes the effects of demand risk on the location and sales structure of multinational firms in the manufacturing sector.
SSVEP-based BCIs: study of classifier stability over time and effects of human learning on classification accuracy

Brain-computer interfaces (BCI) based on steady-state visual evoked potentials (SSVEP) enable a user to control an application by focusing his/her attention on visual stimuli blinking at specific frequencies. This technique of interaction can enable people suffering from severe motor disabilities to improve their quality of life through regaining a partial autonomy. According to literature, each usage session of a SSVEP-based BCI integrates a calibration phase aimed in particular at computing classifier's parameters. Our objective is to evaluate if the same parameters could be used during several sessions, in order to avoid performing systematically a calibration phase, which is very restrictive for the user. To do so, we analyze stability of classification results over time. On the other hand, the data acquired during our experiments were used to study the possible effects of human learning on interface performance and to confirm or not the state of the art knowledge on this subject. According to literature, SSVEP-based BCIs work well from the first use and their performances do not improve with subject's experience.