Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative stability of the free boundary in the obstacle problem

We prove some detailed quantitative stability results for the contact set and the solution of the classical obstacle problem in $\mathbb{R}^n$ ($n \ge 2$) under perturbations of the obstacle function, which is also equivalent to studying the variation of the equilibrium measure in classical potential theory under a perturbation of the external field. To do so, working in the setting of the whole space, we examine the evolution of the free boundary $\Gamma^t$ corresponding to the boundary of the contact set for a family of obstacle functions $h^t$. Assuming that $h=h^t (x) = h(t,x)$ is $C^{k+1,\alpha}$ in $[-1,1]\times \mathbb{R}^n$ and that the initial free boundary $\Gamma^0$ is regular, we prove that $\Gamma^t$ is twice differentiable in $t$ in a small neighborhood of $t=0$. Moreover, we show that the "normal velocity" and the "normal acceleration" of $\Gamma^t$ are respectively $C^{k-1,\alpha}$ and $C^{k-2,\alpha}$ scalar fields on $\Gamma^t$. This is accomplished by deriving equations for these velocity and acceleration and studying the regularity of their solutions via single and double layers estimates from potential theory.
Stakeholders ’ environmental influence . An empirical analysis in the Spanish hotel industry Jos !

We draw on the insights of stakeholder theory to explore the extent to which environmental management practices are driven by (i) an attempt to enhance a firm’s legitimacy, and (ii) a response to pressures arising from powerful stakeholders. The material for this investigation has been gathered from a sample of 279 Spanish hotels. The hotel industry which is only marginally affected by environmental regulation and is thus a widely neglected setting in this context, could be a particularly interesting subject for investigation, able to throw some light on the extent to which firms produce different responses to the environmental concerns of their stakeholders. Our results reveal that corporate environmental management practices may be a response to genuine environmental concerns, and we then speak of explicit environmental management, or there may also be reasons different from the environmental, in which case we speak of tacit environmental management. Our findings suggest that explicit and tacit environmental management account for a variety of organizational responses to the environmental demands of stakeholders, depending on (i) the stakeholders’ power regarding environmental issues, (ii) the stakeholders’ use of power to protect the environment, and (iii) the perceived economic advantages of environmental management activities. r 2003 Elsevier Science Ltd. All rights reserved.
Biochemical oxygen demand sensor arrays.

Biochemical oxygen demand (BOD) is one of the most widely utilized parameters in water quality evaluation. BOD as a parameter illustrates the amount of organic compounds susceptible to biochemical degradation in the water. The BOD test lasts for at least 5 -7 days or even up to 21 days. An incubation time this long is not acceptable for monitoring purposes or system control. In order to shorten the BOD measurement time, a multitude of biosensors have been proposed. Unfortunately, BOD biosensors have several limitations, such as short lifetime, limited substrate range, precision etc. Some of those limitations can be overcome by using microbial sensor-arrays. Such bioelectronic tongues can achieve the much wider substrate range usually attributed to multiculture sensors and still maintain the long lifetime of a single culture sensor. This is achieved by separating different cultures from each other in the array and using the signals of separate sensors to produce summarised information via statistical analysis. The purpose of this review is to give a short overview of BOD measurements and discuss the potential of using sensor-arrays for BOD measurements.
Competitive exclusion and coexistence for competitive systems on ordered Banach spaces

The dynamics of competitive maps and semiflows defined on the product of two cones in respective Banach spaces is studied. It is shown that exactly one of three outcomes is possible for two viable competitors. Either one or the other population becomes extinct while the surviving population approaches a steady state, or there exists a positive steady state representing the coexistence of both populations.
PISCES: a tool for predicting software testability

Before a program can fail, a software fault must be executed, that execution must alter the data state, and the incorrect data state must propagate to state that results directly in an incorrect output. This paper describes a tool called PISCES (developed by Reliable Software Technologies Corporation) for predicting the probability that faults in a particular program location will accomplish all three of these steps causing program failure. PISCES is a tool that is used during software verification and validation to predict a program's testability. <<ETX>>
Finite traveling wave solutions in a degenerate cross-diffusion model for bacterial colony

In this paper we study the existence of finite traveling wave solutions in a degenerate cross-diffusion system modeling the growth of bacteria colony. The importance of establishing the existence lies in the fact that the analysis of the stability of the wave front provides partial answers to the intriguing spatial patterns of the colony. There have been very few results on the finite traveling wave solutions of degenerate parabolic system. One reason is that the traditional method often leads to phase plane analysis on higher dimension which is usually a difficult task. Our method in this paper is based on Schauder fixed point theorem and shooting arguments.
Novel Sensorless Drive Method for BLDC Machine

This paper presents the theory and practice required to implement a novel sensorless operation technique for the brushless DC (BLDC) machine. The proposed new sensorless drive method breaks through the chronic problem of the sensorless BLDC machine drives, lack of low speed operation, so that it ensures highly accurate, robust sensorless operation from near zero to high speed. For this purpose, a physically insightful, speed-independent function, based on a new flux linkage function, is used. A simulation result of the proposed sensorless method is shown, and the result discussed.
Engaging the Public in Policy Research: Are Community Researchers the Answer?

A case has been made for engaging the public in scientific research as co-producers of knowledge. These arguments challenge elite models of policy research and suggest the need for an ambitious expansion of more inclusive scientific public policy research. Enabling the public to be meaningfully involved in complex policy research remains a challenge. This paper explores a range of attempts to involving the public in public policy research. It uses a binary framing to typify some key debates and differences in approaches between community-based participatory research, and citizen science. Approaches to community-based participatory research in the social sciences offer a set of engagement principles which are an alternative to an elite model of policy research. Citizen science offers a focus on the use of scientific methods by lay people, but this approach is currently under-utilized in public policy research and could be expanded. How could the strengths of each be more fully integrated and harnessed? A case study of community policy research is presented, in which an attempt was made to use a more fully integrated approach in a local policy context, identifying the potential and challenges. Based on a framework of three features of democratic and scientific policy research, it argues that more public participation in public policy research would be helped by more attention to the strengths of the democratic potential emphasised by participatory community-based research, alongside the potential of scientific robustness em-phasised by citizen science. One conclusion drawn is that a professional and scientific orientation to public policy re-search can be retained without necessarily being professionally dominated. Research methods and skills are tools to which more people outside the profession could have access, if academics facilitate the process of democratization of policy research.
Equilibrium Counterfactuals: Joint Estimation and Control with Structural Models∗

The objective of applied structural microeconometrics is to identify policy-invariant parameters so alternative policies can be assessed. However, the common practice of treating policy changes as zero probability "counterfactuals" violates rational expectations: Agents understand policy changes are positive probability events which the structural estimation is intended to inform. We analytically characterize the implications for moment-based parameter inference. As shown, if a policy change is optimal, inference is biased. Further, the standard identifying assumption, constant partial derivative sign, is neither necessary nor suffi cient with policy control. We offer an alternative identifying assumption: constant total differential sign with inference-policy feedback. It is shown that under this assumption, rational expectations can be imposed computationally (algorithmically) to generate unbiased inference and optimal policy. The quantitative importance of these effects in applied settings is illustrated by calibrating the Leland (1994) model to the Tax Cuts and Jobs Act of 2017. ∗We thank seminar participants at the CEPR ESSET Meetings, Minnesota, San Diego, Dallas, Georgia State, Imperial, Oxford, and Dauphine.
A Machine Learning Approach to Forecast Bitcoin Prices

Bitcoin is an established cryptographic digital currency whose value lays in the computational complexity rather than a physical commodity. Bitcoin is an open source software program with three aspects. (i) Peer-to-Peer network – low barrier entry; (ii) Mining – inevitable concentration of power; (iii) Software upgrades. The nodes on the network follow a decentralized consensus for establishing the value of ledger and updating the blockchain which serves as a single source of truth for all transactions. As cryptocurrencies are developing more compelling utilities, creating ever faster and safer payment systems they are shifting the “money paradigm”. Bitcoins are an evolution in money and provide a unique opportunity to forecast their price unlike the existing fiat currencies. The goal of this paper is to implement, train and evaluate several machine learning models in order to predict the price of the most popular cryptocurrency – Bitcoins. The various machine learning algorithms employed are – Linear Regression, K-Nearest Neighbors, Ridge Regression, Lasso Regression, Polynomial Regression, Linear Support Vector Machine, and Kernel Support Vector Machine.
Organizational identity strength, identification, and commitment and their relationships to turnover intention: Does organizational hierarchy matter?

Summary In the present study we sought to clarify the functional distinctions between organization identity strength, organizational identification, and organizational commitment. Data were obtained from 10 948 employees of a large steel manufacturer. First, confirmatory factor analysis was used to test the discriminant validity of the three focal constructs. Next, drawing on research that suggests hierarchical differentiation may influence individuals’ conceptual frame of reference, we examined each focal construct’s measurement equivalence across three hierarchical levels (officers, n ¼ 1,056, middle-management, n ¼ 1049, workers, n ¼ 1050). Finally, multigroup structural equation modeling was used to simultaneously estimate the between-group correlations between turnover intention and organization identity strength, organizational identification, and organizational commitment. Results indicated that (a) the measures used to reflect the three focal constructs were empirically distinct, (b) the focal constructs were conceptually equivalent across hierarchical levels, and (c) the pattern of correlations with turnover intention was different for employees with management responsibilities versus workers with no management responsibility. The present findings suggest perceptions of a strong organizational identity, organizational identification, and organizational commitment may influence employees’ turnover intention in unique ways, depending on their hierarchical level within the organization. Copyright # 2006 John Wiley & Sons, Ltd. The relationship between an individual member and the employing organization has long been known to have an impact on the attitudes, behavior, and well-being of individuals. In this regard, two of the more researched constructs include organizational identification and organizational commitment, both of which were developed in an attempt to understand, predict, and influence employee behavior. Organizational identification, as the more recent of the two perspectives, examines the process whereby an individual’s identity becomes psychologically intertwined with the organization’s identity. Although a long-standing interest to sociologists and social psychologists, the social identity approach, subsuming both social identity theory and self-categorization theory, has only recently emerged as an important perspective in organizational behavior research (see Pratt, 1998; van Dick, 2004, for reviews). The second perspective, which encompasses organizational commitment, views the
The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun

This paper argues for the recognition of important experiential aspects of consumption. Specifically, a general framework is constructed to represent typical consumer behavior variables. Based on this paradigm, the prevailing information processing model is contrasted with an experiential view that focuses on the symbolic, hedonic, and esthetic nature of consumption. This view regards the consumption experience as a phenomenon directed toward the pursuit of fantasies, feelings, and fun.
“ Beacons Collect Information from Users ” : Unpacking People ’ s Misunderstandings of Bluetooth Beacon Technology

Copyright is held by the author/owner. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee. Poster presented at the 14th Symposium on Usable Privacy and Security (SOUPS 2018). Abstract Bluetooth beacon technology is an emerging Internet of Things (IoT) technology, designed to transform proximity-based services in various domains, such as retail and education. While this technology is gaining popularity, little is known regarding people’s understandings or misunderstandings about how beacon-based systems work. This is an important question because people’s understandings of beacons influence their perceptions and attitudes and can affect the acceptance and adoption of this emerging technology. Drawing from a preliminary study of 15 semistructured interviews, we uncovered a number of misunderstandings that our participants had about how beacon-based systems work, such as that beacons can directly collect information from users. Our findings help explain people’s concerns about beacons and provide suggestions for the future design of beacons.
Outer raceway fault detection and localization for deep groove ball bearings by using thermal imaging

This paper discusses outer raceway fault detection and localization for rolling element bearings by means of thermal imaging. In particular, deep groove ball bearings have been monitored. Whereas bearings in industrial applications are usually fully covered, the used test setup allows to monitor the uncovered bearings to understand their heat increase and propagation. The main contribution of this paper is the methodology to process and analyse the thermal data of the bearings. The presented methodology is applied on both a healthy bearing and a bearing with outer raceway fault. By revealing significantly higher temperatures for the faulty bearing than for the healthy bearing, thermal imaging enables fault detection. Additionally, the stationary characteristic of the outer ring allows to locate the outer raceway fault by means of its thermal impact.
'Birds of a Feather Flock Together': The Impact of Choice of Spouse on Family Labor Income Inequality

This paper discusses the effects of the substantial rise in labor force participation of married women on the level, structure and trend in family labor income inequality. An interesting question is to what extent the rise in women's labor force participation has led to a tendency of "flocking together", i.e. whether women with high labor income are married to men with high labor income, or vice versa. Based on the decomposition of the Gini coefficient and a related index for the extent of "flocking together" applied to income data for Norway for the period 1973-1997 we find a tendency of "flocking together" for couples with at least one labor income and couples with two labor incomes. For couples with only one labor income (i.e. couples where only one labor income is above the threshold given by the statistical definition of labor income) the decomposition of the Gini coefficient indicates that there is no tendency of "flocking together". For this group women's labor income gives an equalizing contribution to family labor income inequality. This illustrates the importance of distinguishing between one- and two-income families in analysis of family labor income inequality.
Proactive Business Intelligence : Discovering Key Performance Indicators with the Rule Extraction Matrix Method

Key performance indicators have been around for a long time; organizations tend to provide their employees with metrics on strategic levels, such as market-share or profitability. By using metrics and performance indicators, organizations aim to influence the awareness of employees on targets. Performance increases are bound to occur, when employees are conscious of their personal results by metrics. However, an abundance of definitions of metrics overwhelm employees with values which are hard to grasp. By defining key performance indicators, relating to goals and strategic aspects of the organizations, meaningful indicators can be defined on an operational and tactical level, therefore, preventing cognitive overload. This paper describes the extraction of key performance indicators by using the Rule Extraction Matrix (REM) Method. This method is constructed using several aspects of current data mining methods such as the CRISP-DM model, providing a solid base to determine the nominal value of a performance metric. The REM-method enables organizations to manage their performance by using key performance indicators extracted from data and literature. Thresholds to the key performance indicators are provided by business rules, to allow integration with systems and readability by analysts. Validation of the REM-method is performed by a case study at a large Dutch Internet services provider and expert interviews were performed. The REM-method is an addition to the performance measurement field and further enhances an organization’s ability to define their performance.
A cyclic component estimation using the AR process and its error: an application to economic time series

This paper deals with a method for the estimation of the signal cyclic component's period using an autoregressive model. The application to economic time series is presented on the example of the index of industrial production data for EU countries. As the economic time series are usually relatively short, the properties of the method are explored and quantified in the case of its application to short sample size signals. A number of computer experiments has been performed using the harmonic signal corrupted by noise and the autoregressive model of the second order. The results of the experiments are represented in the graphical form. It could be noticed that the mean value of the errors could result to significant values while the variance of the error is generally almost negligible. The difference between the spectrum estimation from the whole data differs from the case of using the sliding window spectrum estimation.
Replication Data for: Real-time analysis of insoluble particles in glacial ice using single-particle mass spectrometry

Insoluble aerosol particles trapped in glacial ice provide insight into past climates, but analysis requires information on climatically relevant particle properties, such as size, abundance, and internal mixing. We present a new analytical method using a time-of-flight single-particle mass spectrometer (SPMS) to determine the composition and size of insoluble particles in glacial ice over an aerodynamic size range of ∼ 0.2–3.0 μm diameter. Using samples from two Greenland ice cores, we developed a procedure to nebulize insoluble particles suspended in melted ice, evaporate condensed liquid from those particles, and transport them to the SPMS for analysis. We further determined size-dependent extraction and instrument transmission efficiencies to investigate the feasibility of determining particle-class-specific mass concentrations. We find SPMS can be used to provide constraints on the aerodynamic size, composition, and relative abundance of most insoluble particulate classes in ice core samples. We describe the importance of post-aqueous processing to particles, a process which occurs due to nebulization of aerosols from an aqueous suspension of originally soluble and insoluble aerosol components. This study represents an initial attempt to use SPMS as an emerging technique for the study of insoluble particulates in ice cores.
Development of enzyme-linked immunosorbent assay for human leptospirosis serodiagnosis using leptospira secretome antigen

Secretome (extracellular proteins) has been considered as a potential diagnostic biomarker, vaccine and therapeutic candidates for bacterial infections. In this research, secretomes of two reference Leptospira spp, namely, pathogenic L. interrogans serovar Autumnalis strain Akiyami and saprophytic L. biflexa serogroup Semaranga serovar Patoc strain P136 were evaluated for their immunogenicity to microscopic agglutination test (MAT)-positive leptospirosis patients’ sera in IgMand IgG-ELISAs in comparison to a whole Leptospira homogenate antigen. At a single serum dilution of 1:1,000, sensitivity of the pathogenic Leptospira secretome antigen-based IgMand IgG-ELISAs was 90% (18/20) and 75% (15/20), respectively, when compared with that of the MAT assay. Thus, Leptospira secretome provides a potential antigen source in serodiagnosis of leptospirosis.