Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical simulations of figure-8 coil during transcranial magnetic stimulation

As a non-invasive technique of neuromodulation, transcranial magnetic stimulation has become widely used in clinical and scientific applications. The figure-8 coil is the most used coil in transcranial magnetic stimulation, and how to design a suitable figure-8 coil to achieve better stimulation effect is of great value. Analyzing and comparing stimulus depth and focusing parameters of figure-8 coil with different turns indicate that, with increase of coil turns, depth of stimulation of the coil is gradually increased but the focusing performance becomes poor. Finally, In order to give clear guidance to the coil design, this paper has quantitatively analyzed the coil performance and the number of turns. In practical application, the proper number of turns should be selected according to the specific requirements of stimulating the encephalic region. This work has a certain scientific and practical significance in transcranial magnetic stimulation device design, academic research and clinical treatment.
A novel context matching based technique for Web document retrieval

This paper presents a novel context matching technique for the retrieval of Web documents. The aim of the technique is to dynamically generate a context-based measure of document term significance during retrieval that can be used as a substitute or co-contributor of the term frequency measure. Unlike term frequency, which relies on a term to occur multiple times within a document to be considered significant, context matching is based on the notion that if a term in a given document occurs in that document in the context of the query, then that term is deemed to be significant. Context matching has the ability to potentially determine a term to be significant even if it occurs only once in a large document. The proposed technique has been implemented and the experiments were conducted using a TREC benchmark database. A comparative analysis shows that context matching significantly improves retrieval effectiveness and outperforms previously published results.
Financialization of food. Modelling the time-varying relation between agricultural prices and stock market dynamics

This article studies the correlation of agricultural prices with stock market dynamics. We discuss the possible role of financial and macroeconomic factors in driving this time-varying relation, with the aim of understanding what caused positive correlation between agricultural commodities and stocks in recent years. While previous works on commodity-equity correlation have focused on broad commodity indices, we study 16 agricultural prices, in order to assess patterns that are specific to agricultural commodities but also differences across markets. We show that an explanation based on a combination of financialization and financial crisis is consistent with the empirical evidence in most markets, while global demand factors don’t appear to play a significant role. The correlation between agricultural prices and stock market returns tends to increase during periods of financial turmoil. The impact of financial turmoil on the correlation gets stronger as the share of financial investors in agricultural derivatives markets rises. Our findings suggest that the influence of financial shocks on agricultural prices should decrease as global financial tensions settle down but also that, as long as agricultural markets are ‘financialized’, it might rise again when it is less needed, i.e. in the presence of new financial turmoil.
Political Connections, Legal Environment, and Corporate Valuation in Chinese Public Family Firms

Using a uniquely selected family-firm data set, we show that Chinese family firms are, on average, more valuable than nonfamily firms, and that their superior performance can be explained in part by their political connections. Chinese family firms in which the chairperson or CEO is politically active have substantially higher corporate valuations than other family firms. Our findings support the view that the rapid growth of China's private sector is driven by certain alternative mechanisms. As we demonstrate, in an emerging economy, political connections can be a mechanism for responding to the legal system's failure to adequately protect private property rights.
An improved PSO-based approach with dynamic parameter tuning for cooperative multi-robot target searching in complex unknown environments

Target searching in complex unknown environments is a challenging aspect of multi-robot cooperation. In this paper, an improved particle swarm optimisation (PSO) based approach is proposed for a team of mobile robots to cooperatively search for targets in complex unknown environments. The improved cooperation rules for a multi-robot system are applied in the potential field function, which acts as the fitness function of the PSO. The main improvements are the district-difference degree and dynamic parameter tuning. In the simulation studies, various complex situations are investigated and compared to the previous research results. The results demonstrate that the proposed approach can enable the multi-robot system to accomplish the target searching tasks in complex unknown environments.
History versus equilibrium? on the possibility and realist basis of a general critique of traditional equilibrium analysis

This paper responds to Backhouse's (2004) claims that there is no antagonism between history and equilibrium and no case to be made in principle against equilibrium analysis. We first show that Backhouse's partial defense of equilibrium analysis has already been encompassed by heterodox theory. We then identify a "traditional equilibrium approach" to economic analysis and provide a general critique of this approach based on its perceived infidelity to the properties of social reality. Finally, we argue that this exercise exemplifies Lawson's (2005a) thesis that heterodox skepticism of equilibrium analysis is motivated by ontic concerns—that is, concerns with the intrinsic properties of the social material that is being theorized by economists.
A Fault Diagnosis Method Combined Fuzzy Logic with CMAC Neural Network for Power Transformers

Dissolved gas analysis (DGA) is an effective method for early detection of incipient faults in power transformers. To improve the accuracy of fault diagnosis, a fault diagnosis method combined fuzzy logic with cerebellar model articulation controller (CMAC) neural network is proposed in this paper. The proposed fuzzy CMAC neural network (FCMAC) has an optimization mechanism to ensure high diagnosis accuracy for all general fault types. Firstly, it uses fuzzy logic to extract diagnosis rules from a lot of fault samples, and then, the extracted rules are employed to optimize CMAC network. Many real fault samples are analyzed by FCMAC for the purpose of verification, and the analyzed results are also compared with those analyzed by IEC ratio method and those by the CMAC neural network. The comparison results show that the proposed method has remarkable diagnosis accuracy.
Understanding Shared Leadership in Agile Development: A Case Study

In agile software development methods such as Scrum, software is developed in self-organizing teams. In such teams, leadership should be diffused rather than centralized; also the team-members need to affect managerial decisions for achieving the benefits of a self-managed team. When the team and team leaders share leadership, leadership is rotated to the person with the key knowledge, skills, and abilities for the particular issues facing the team at any given moment. Therefore, we argue that the team leadership in Scrum should be divided among the Product-owner, Scrummaster, and the self-organizing team. If teams are to succeed at implementing shared leadership in Scrum, not only do the vertical (or traditional) leaders need training and development but so too do the team members themselves.
Are Dividends Associated with the Quality of Earnings

SYNOPSIS: We examine whether dividend paying status is associated with the quality of earnings. We find dividend paying status is associated with (1) lower absolute values of discretionary accruals; (2) lower standard deviation and absolute magnitude of the errors associated with the mapping of accruals into cash flows; and (3) more value relevant earnings. We also find evidence that the positive association between dividend paying status and earnings quality is stronger (weaker) when the size of dividend payouts is larger (smaller). Overall, our results suggest dividend paying status is indicative of firms’ earnings quality.
Further evidence on knowledge spillover and the joint determination of audit and non‐audit fees

Purpose - For more than 25 years auditing research has examined whether knowledge spillovers or synergies exist from the joint provision of audit and non-audit services as well as whether the audit client benefits from knowledge spillovers. However, empirical evidence on knowledge spillover remains mixed and elusive. This article seeks to contribute to this debate, using a large sample covering both the pre- and the post-Sarbanes-Oxley Act (SOX) era. A post-SOX focus can be potentially informative because SOX has fundamentally changed the mix of audit and non-audit services that can be offered to audit clients. Design/methodology/approach - A two-stage least squares regression model is used to control for simultaneous bias due to the joint determination of audit and non-audit fees. A panel dataset is also used. Findings - A strong and significant negative relationship is found between audit fees and non-audit fees. The results suggest that knowledge spillover flows from non-audit to the audit side, as well as from the audit side to the non-audit side. For the overall sample, a 1 percent increase in non-audit fees is associated with a 0.59 percent decrease in audit fees. Similarly, a 1 percent increase in audit fees is associated with a 0.49 percent decrease in non-audit fees. Research limitations/implications - Though a comprehensive set of determinants of audit and non-audit fees is used, it is possible that the model may not include some other unknown determinants of fees paid to auditors. Practical implications - The study contributes to the debate on whether regulators should ban all non-audit services. It is found that when the same audit firm performs both audit and non-audit services, there are synergies, i.e. insight learned from performing one function helps the other. Social implications - At the economy level, the findings suggest that cost savings, due to knowledge spillover, are partly passed on to the clients, particularly by Big 4 auditors. Originality/value - The findings on the existence of knowledge spillover in the post-SOX era are potentially informative to regulators, auditors, audit clients, and audit committee members.
Nutrient balance in the diet of spring-calving, pasture-fed dairy cows

Abstract AIMS: To report the nutrient composition of pastures fed to spring-calving dairy cows in the Manawatu region of New Zealand, and describe changes in the nutrient composition of these pastures over a 12-month period. Having done this we sought to: (1) compare the nutrient composition of the pasture offered with the nutrient requirements of spring-calving dairy cows; (2) identify periods when individual nutrient surpluses and deficits are likely; and, (3) identify nutrients that demonstrate a high level of variability between sampling occasions. METHODS: Seven farms took part in the study. Each farm was visited monthly from August 1996 to July 1997. Samples of pasture were taken at each visit and submitted for estimation of crude protein (CP), non-structural carbohydrate (NSC), neutral detergent fibre (NDF), acid detergent fibre (ADF), calcium (Ca), phosphorus (P), magnesium (Mg), sodium (Na), potassium (K), chlorine (Cl), sulphur (S), iron (Fe), copper (Cu) and zinc (Zn). RESULTS:> Sampled pastures were characterised by low to marginal metabolisable energy (ME), NSC, Ca, Mg and Zn concentrations when compared with recommended dietary nutrient concentrations for lactating and non-lactating dairy cattle in New Zealand. Analyses revealed relatively high CP, NDF, K, and dietary cation-anion difference (DCAD) concentrations. CONCLUSIONS: These analyses identify broad trends in the nutrient balance of a pasture-only feeding regime and provide a useful reference for planning feed strategies for spring-calving, pasture-fed dairy herds in this region. Recommended changes to on-farm practice should only be made after considering the whole farm system, not made solely on the basis of perceived deficiencies or excesses of individual nutrients.
High content image cytometry in the context of subnuclear organization

The organization of proteins in space and time is essential to their function. To accurately quantify subcellular protein characteristics in a population of cells with regard for the stochasticity of events in a natural context, there is a fast‐growing need for image‐based cytometry. Simultaneously, the massive amount of data that is generated by image‐cytometric analyses, calls for tools that enable pattern recognition and automated classification. In this article, we present a general approach for multivariate phenotypic profiling of individual cell nuclei and quantification of subnuclear spots using automated fluorescence mosaic microscopy, optimized image processing tools, and supervised classification. We demonstrate the efficiency of our analysis by determination of differential DNA damage repair patterns in response to genotoxic stress and radiation, and we show the potential of data mining in pinpointing specific phenotypes after transient transfection. The presented approach allowed for systematic analysis of subnuclear features in large image data sets and accurate classification of phenotypes at the level of the single cell. Consequently, this type of nuclear fingerprinting shows potential for high‐throughput applications, such as functional protein assays or drug compound screening. © 2009 International Society for Advancement of Cytometry
Arabidopsis REGULATOR OF AXILLARY MERISTEMS1 Controls a Leaf Axil Stem Cell Niche and Modulates Vegetative Development[W]

Shoot branching is a major determinant of variation in plant stature. Branches, which form secondary growth axes, originate from stem cells activated in leaf axils. The initial steps by which axillary meristems (AMs) are specified and their stem cells organized are still poorly understood. We identified gain- and loss-of-function alleles at the Arabidopsis thaliana REGULATOR OF AXILLARY MERISTEMS1 (RAX1) locus. RAX1 is encoded by the Myb-like transcription factor MYB37 and is an Arabidopsis homolog of the tomato (Solanum lycopersicum) Blind gene. RAX1 is transiently expressed in a small central domain within the boundary zone separating shoot apical meristem and leaf primordia early in leaf primordium development. RAX1 genetically interacts with CUP-SHAPED COTYLEDON (CUC) genes and is required for the expression of CUC2 in the RAX1 expression domain, suggesting that RAX1 acts through CUC2. We propose that RAX1 functions to positionally specify a stem cell niche for AM formation. RAX1 also affects the timing of developmental phase transitions by negatively regulating gibberellic acid levels in the shoot apex. RAX1 thus defines a novel activity that links the specification of AM formation with the modulation of the rate of progression through developmental phases.
Smiling for the Delayed Volatility Swap

Using change of time method, we derive a closed-form formula for the volatility swap in an adjusted version of the Heston model with stochastic volatility with delay. The numerical result is presented for underlying EURUSD on September 30th 2011. The novelty of the paper is two-fold: application of change of time method to the delayed Heston model and calculation of the volatility swap for this model.
Do Bidder Managers Knowingly Pay Too Much for Target Firms

This study examines the stock transactions of top managers of bidder firms for their personal accounts as signals about their motivations regarding corporate takeovers. Overall, the data indicate that, prior to takeover announcements, top managers increase their net purchases rather than sales. Bidder managers purchase more shares when the stock price reaction to the takeover announcement is large and positive than when it is large and negative. Bidder managers are also more optimistic in cash offers than in equity offers. Overall, the evidence does not appear to support the hypothesis that bidder managers knowingly pay too much for target firms. Copyright 1990 by the University of Chicago.
Prototype learning algorithms for nearest neighbor classifier with application to handwritten character recognition

This paper reviews some prototype learning algorithms for nearest neighbor (NN) classifier design land evaluates their performances in handwritten character recognition. The algorithms include the well-known LVQ and those that globally optimize an objective function, as well as some newly derived variants. Experimental results of handwritten numeral recognition and Chinese character recognition show that the global optimization algorithms generally outperform LVQ. Particularly, the generalized LVQ of Sato and Yamada (1998) and a new algorithm MAXP2 yield best results.
Counterfeit purchase typologies during an economic crisis

Purpose – This paper aims to explore, and attempts to explain, consumer perspectives on the purchasing of counterfeit brands. The economic crisis has become a global phenomenon, although in Europe it mostly affected the Mediterranean countries of Southern Europe. In times of economic stress, counterfeit products increase their market share. Design/methodology/approach – The study utilized an email-based open-ended questionnaire as its data collection method. The research used a sample of 83 participants belonging to Generation Y (younger and older) and upper-medium- and high-income class brackets. Findings – Purchasing behaviour of counterfeit products during the economic crisis enabled this study to identify four types of consumers. Furthermore, the results indicated that some consumers have significant interest in counterfeits, whereas some consumers show apathy or indifference towards counterfeiting. Furthermore, some consumers believe that the government’s economic austerity policies cause high-level .
Consistent Learning Bayesian Networks with Thousands of Variables

We have already proposed a constraint-based learning Bayesian network method using Bayes factor. Since a conditional independence test using Bayes factor has consistency, the learning method improves the learning accuracy of the traditional constraint-based learning methods. Additionally, the method is expected to learn larger network structures than the traditional methods do because it greatly improves computational efficiency. However, its expected benefits have not been demonstrated empirically. This report describes some experiments related to the learning of large network structures. Results show that the proposed method can learn surprisingly huge networks with thousands of variables.
Technological Change and the Demand for Currency: An Analysis With Household Data

Advances in the transaction technology allow agents to economize on the cost of cash management. We argue that accounting for the impact of new transaction technologies on currency holding behaviour is important to obtain theoretically consistent estimates of the demand for money. We modify a standard inventory model to study the effect of the withdrawal technology on the demand for currency. An empirical specification for the households demand schedule is suggested in which both the level of currency holdings and the interest rate elasticity of the demand depend on the withdrawal technology available to agents (e.g. ATM card ownership or a high/low density of bank branches, ATMs). The theoretical implications are tested using a unique panel of Italian household data (on currency holdings, deposit interest rates, consumption, development of banking services, etc.) for the 1989-2004 period.
Comprehensive risk measure – current challenges

Purpose - – This paper, based on case-studies with five universal banks from Europe and North America, aims to investigate which types of comprehensive risk measure (CRM) models are being used in the industry, the challenges being faced in implementation and how they are being currently rectified. Undoubtedly, CRM remains the most challenging and ambiguous measure applied to the correlation trading book. The turmoil surrounding the new regulatory framework boils down to the Basel Committee implementing a range of capital charges for market risk to promote “safer” banking in times of financial crisis. This report discusses current issues faced by global banks when complying with the complex set of financial rules imposed by Basel 2.5. Design/methodology/approach - – The current research project is based on in-depth, semi-structured interviews with five universal banks to explore the strides major banks are taking to introduce CRM modelling while complying with the new regulatory requirements. Findings - – There are three measures introduced by the Basel Committee to serve as capital charges for market risk: incremental risk charge; stressed value at risk and CRM. All of these regulatory-driven measures have met with strong criticism for their cumbersome nature and extremely high capital charges. Furthermore, with banks facing imminent implementation deadlines, all challenges surrounding CRM must be rectified. This paper provides some practical insights into how banks are finalising the new methodologies to comply with Basel 2.5. Originality/value - – The introduction of CRM and regulatory approval of new internal market risk models under Basel 2.5 has exerted strong pressure on global banks. The issues and computational challenges surrounding the implementation of CRM methodologies are currently fiercely debated among the affected banks. With little guidance from regulators, it remains very unclear how to implement, calculate and validate CRM in practice. To this end, a need for a study that sheds some light on practices with developing and computing CRM emerged. On submitting this paper to the journal, we have received news that JP Morgan is to pay four regulators $920 million as a result of a CRM-related scandal.
DesignThreats Goals System Adversaries Possible attacks Consequences Stakeholders Environment

Manifold approaches to security requirements engineering have been proposed, yet there is no consensus how to elicit, analyze, or express security needs. This perspective paper systematizes the problem space of security requirements engineering. Security needs result from the interplay of three dimensions: threats, security goals, and system design. Elementary statements can be made in each dimension, but such onedimensional requirements remain partial and insufficient. To understand security needs, one has to analyze their interaction. Distinct analysis tasks arise for each pair of dimensions and are supported by different techniques: risk analysis, as in CORAS, between threats and security goals; security design, as exemplified by the framework of Haley et al., between goals and design; and security design analysis, such as Microsoft’s threat modeling technique with data flow diagrams and STRIDE, between design and threats. All three perspectives are necessary to develop secure systems. Security requirements engineering must iterate through them, because threats determine the relevance of security goals, security design seeks ways to fulfill them, and design choices themselves influence threats and security goals.