Miracle-dz/UniFAR-FTUs huggingface dataset:
The Defects of Stakeholder Theory

Stakeholder theory has been widely offered as a corrective to perceived defects of business and business ethics, and as an alternative model of corporate governance. Indeed, it is now advocated so commonly as to have become a new orthodoxy. Far from being a source of improvements, however, stakeholder theory is fundamentally misguided, incapable of providing better corporate governance, business performance or business conduct. Stakeholder theory is indeed intrinsically incompatible with all substantive objectives, and undermines both private property and accountability.
Semantic trajectory analysis for identifying locations of interest of moving objects

The upsurge in the use of Context Aware Devices in various gadgets has led to the generation of massive mobility data. These gadgets tracks and records particulars of moving objects such as location, time, waypoints etc. in to various geographical databases. The data are recorded in the form of trajectories. Identification of the moving pattern is very much useful for setting up of the architectural platform of transportation systems, design of supply chain networks, preparation of travel itinerary of tourists and the like. In order to understand the characteristic features of the journey made by objects, appropriate mining techniques are essential. Many of the existing trajectory mining applications use geographic features precisely location and time for the pattern identification. Mining of data by considering more parameters will identify divergent locations of interest in the trajectory. The concept of semantic trajectory analysis is gaining acceptance in the domain of trajectory analysis. In this paper we are introducing a conceptual model for the identification of interesting locations on the basis of spatio temporal attributes of moving objects and its semantic features. This model considers direction of the movement of the object as semantic mean for the identification of interesting locations.
Little beneficial effect of maternal vitamin supplement on metabolic disturbances in the offspring from the obese mother mice

Abstract Objective: To examine whether vitamin supplement before and during pregnancy alters the detrimental effect of maternal obesity on the offspring. Methods: Obese C57BL/6 female mice were randomly divided into four groups and fed with the control, vitamin D, folic acid or multivitamin supplement diet before and during pregnancy. Physiologic and biochemical variables were obtained. Results: No significant differences were observed in glucose and lipid variables among offspring from each maternal obese group. Conclusions: Overall, vitamin D, folic acid or multivitamin supplement cannot ameliorate the detrimental effect of maternal obesity on the metabolic disturbances in the offspring.
Money, income, prices, and exchange rates in the Dominican Republic

This paper investigates the information content of money, exchange rates, and foreign variables on real income and prices in the Dominican Republic. The results show that the change in the exchange rate -adjusted to account for financial conditions in the USis a robust predictor of both real income and prices. Money and foreign reserves also contain significant information on prices. These outcomes highlight the pervasive role of the exchange rate and foreign financial conditions on macroeconomic developments in small developing economies.
High‐resolution modeling of human and climate impacts on global water resources

A number of global hydrological models [GHMs) have been developed in recent decades in order to understand the impacts of climate variability and human activities on water resources availability. The spatial resolution of GHMs is mostly constrained at a 0.5° by 0.5° grid [∼50km by ∼50km at the equator). However, for many of the water‐related problems facing society, the current spatial scale of GHMs is insufficient to provide locally relevant information. Here using the PCR‐GLOBWB model we present for the first time an analysis of human and climate impacts on global water resources at a 0.1° by 0.1° grid [∼10km by ∼10km at the equator) in order to depict more precisely regional variability in water availability and use. Most of the model input data (topography, vegetation, soil properties, routing, human water use) have been parameterized at a 0.1° global grid and feature a distinctively higher resolution. Distinct from many other GHMs, PCR‐GLOBWB includes groundwater representation and simulates groundwater heads and lateral groundwater flows based on MODFLOW with existing geohydrological information. This study shows that global hydrological simulations at higher spatial resolutions are feasible for multi‐decadal to century periods.
Vertical root fractures in crowned teeth: a report of 32 cases.

OBJECTIVE To clarify the mode of root fracture in 32 endodontically treated teeth that resulted in vertical root fracture (VRF) despite the provision of a crown for fracture prevention. METHOD AND MATERIALS The teeth included in the study underwent root canal treatment and were restored with crowns without the use of an intracanal post. All teeth underwent photo documentation. Clinical signs and symptoms as well as the patients' ages were recorded. The diameters of the roots and the root canal fillings were measured on radiographs. Fractured roots were investigated using a scanning electron microscope (SEM). RESULTS The mean patient age was 60.2 years. The VRFs in the group occurred most frequently in the mesial roots of the mandibular first molars. The fracture was predominantly buccolingual. The mean ratio measured between the diameters of the root canal obturations and the outer root surfaces in the radiographs was 33.2%. SEM evaluation showed that most fractures ran from the inner to the outer root surface, and the cracks predominantly ran apical to coronal. CONCLUSION Endodontically treated and crowned teeth without root canal posts can develop VRFs. The cracks start at the root canal wall in the apical part of the root and extend toward the outer root surface and coronally. Further investigation is necessary to determine the possible causes and evidence of fracture development.
Some Insights Into Convolutional Neural Networks

As a kind of deep learning model, convolutional neural networks (CNNs) have greatly boosted the state-of-the-art performance and have found their successful applications in many fields, such as computer version, pattern recognition, natural language processing, etc. Many distinguished CNN models, for example, AlexNet, Google inception net, VGGNet, and so on, have been developed for various tasks. In this paper, we provide some insights into convolutional neural networks in three aspects: activation function, convolution operation, pooling operation, and we also discuss the training of CNNs. The insights presented in this paper will provide the potential readers with further understanding of CNNs.
An in-motion alignment method for inertial navigation system based on unfalsified adaptive control theory

An adaptive gyro compassing algorithm is designed based on Unfalsified Adaptive Control Theory (UAC) to solve the in-motion alignment problem of Inertial Navigation System (SINS). The typical way of solving the problem is through filtering, yet the major factor that affects the performance of the filters is the model error as well as the plant properties such as system noise, which make it not optimal as expected. Gyro compassing method is designed based on classical control theory, which can be viewed as a fixed gain PI controller. The control coefficients do not rely on the noise statistics. The problem of gyro compassing is that the controller gain need to be tuned to get good performance and thus is not optimal. Unfalsified Adaptive Control is introduced to fix this problem. UAC belongs to the class of control methods called adaptive supervisory switching control. It selects the best controller from a candidate controller set and switches it into the control loop by calculating the fictitious reference signal of each candidate controller, only using the information from the plant output. In this paper we designed a UAC gyro compassing algorithm which is independent to system model.
Irrational executives and corporate governance

The top managers of companies have a great influence on the investment and financing policies of the companies that they lead. According to the economic principal-agent theory, rational managers look after their own interests, even if this is at the cost of shareholders and other stakeholders. Literature on corporate governance describes the workings and effectiveness of mechanisms to constrain these agency problems. However, recent studies on behavioural corporate finance show that managers do not always act rationally and that this irrationality can have a quantifiable negative value impact in strategic decisions. The central question to this paper is this: what influence can corporate governance have in reducing the negative effects of irrational behaviour in managers?
International technology transfer and domestic patent policy: An empirical analysis of Indian industry

Firms in the developing countries transfer technology predominantly produced in the developed economies through different modes namely market-mediated channels including trade in goods and services, foreign direct investment, licensing or non-market channels like employees turnover. Multitude of host country’s factors (locational and policy related) influences the mode-choice decision of multinational enterprises among exports, FDI and licensing to work in a host country. Among these factors, provision for the protection of patent rights reduces transactions costs that lead to externalization in form of arm’s-length licensing against FDI. India has made patent policy changes during the post globalization period to comply with Trade Related Intellectual Property Rights Agreement. Accordingly, this study attempts to find the influence of the patent policy changes on licensing strategy of the Indian manufacturing industry. This paper is based on panel data of 51 industries for period 1989-90 to 2009-10. We have checked each panel data regression for the presence of heteroscedasticity, contemporaneous correlation and serial correlation. In case of the presence of heteroscedasticity and contemporaneous correlation the results are based on heteroskedastic panels corrected standard errors and correlated panels corrected standard errors. As the modeling is based on macro-panel data having large number of industries (N) and time period (T) each data series is checked for unit-root using panel data unit-root tests. The study uses Fisher type test. We estimate the model after controlling for the general policy changes in India following the liberalization, privatization and globalization of the economy. We are able to establish a substitutable relationship between licensing from international market and in-house R&D. The removal of licensing regulations of different industries has a positive influence on the firm’s decision to license. We also find a complementary relationship between capital goods import and licensing. Thus, policy makers should allow for easy capital imports to facilitate technology transfers. The study indicates that patent policy influences technology transfer to India albeit negatively and limited to patent-sensitive industries confirming the monopoly power effect for such industries. Thus, policy makers have to use regulatory approach to facilitate transfers instead of merely relying on the market approach. Moreover, with respect to patent-sensitive industries there is need to closely watch the licensing behavior of the technology owners for anti-competitive practices.
Lateral preference patterns as possible correlates of successfully switched left hand writing: Data and a theory

Left-handers often have had to contend with pressure to switch their preferred writing hand and shift attempt reports are common, especially among older adult left-handers. Three groups of left-handers can be defined by combining two variables, writing hand side and the report of a rightward hand preference shift attempt. The three groups are, first, right hand writers who report a rightward shift (successfully shifted left-handers); second, left hand writers who report a rightward shift attempt (unsuccessfully shifted left-handers); and, finally, left hand writers who do not report a rightward shift attempt. The underlying mechanisms that determine the success or failure of a handwriting shift attempt remain unclear. The present study examined the history of attempts to switch the preferred writing hand in a sample of 1277 adults aged 65 to 100 years of age. Older adults are well suited to participate in such a study because pressure to switch hand preference was especially severe for those who grew up in the early part of the 20th century; reports of rightward shift attempts are more common in this age group than among younger adults. Our results suggest that the three groups of left-handers, distinguished by the presence or absence of a shift history report and writing hand side, can also be distinguished from each other on the basis of their overall lateral preference profiles (the sides of hand, foot, eye, and ear preferences). Left hand writers, with and without reports of a rightward shift history, showed stronger left side lateralisation patterns when compared to right hand writers who reported a rightward switch (the successfully shifted left-handers).
A contribution to the study of the German treasury bills market

We study the yields in the German treasury bills market. We take a detailed look at the yield banks require to buy treasury bills in the primary market, and we also examine the yield households and nonbank firms demand to buy these bills in the secondary market. We use data from real world tenders to show that the bids set by banks are in accordance with the predictions of our theoretical framework. In particular, we show that current monetary policy and the market’s expectations regarding the future path of monetary policy can be used to define an interval in which the bids from banks lie. Our theoretical predictions for the secondary market also match the data.
Production of interleukin (IL)-6 and IL-8 by a choriocarcinoma cell line, BeWo.

To clarify the biological and pathological features of choriocarcinoma, we evaluated the in vitro production of cytokines by a choriocarcinoma cell line, BeWo. We measured the concentration of interleukin (IL)-6 and IL-8 in the culture media of BeWo cells after stimulation with various modulatory agents of cytokine expression by enzyme-linked immunosorbent assays. Northern blot analysis was used to examine the expression of IL-6 and IL-8 mRNA in these cells. A weak expression of IL-6 and IL-8 was detected in unstimulated BeWo cells by both methods. IL-6 transcription and secretion were dose-dependently enhanced by stimulation with IL-1beta, tumour necrosis factor (TNF)-alpha, transforming growth factor (TGF)-beta1 and 12-O-tetradecanoyl phorbol-13-acetate (TPA). Forskolin, lipopolysaccharide and interferon-gamma had no effect on these cytokines production. The TNF-alpha-induced secretion of IL-6 was inhibited by dexamethasone. The TPA-induced production of IL-6 was inhibited by 1-(5-isoquinolinylsulfonyl)-2-methylpiperazine and sphyngosine, suggesting the involvement of a protein kinase C-dependent pathway. Levels of IL-8 mRNA and protein were also dose-dependently increased by stimulation with IL-1beta, TNF-alpha and TPA. In contrast to IL-6, the expression of IL-8 was not affected by TGF-beta1. It is suggested that, in addition to the production of steroidal and non-steroidal hormones, these cytokines may serve as part of a cytokine network that modulates the proliferation and angiogenesis of choriocarcinomas.
Accuracy of available methods for quantifying the heat power generation of nanoparticles for magnetic hyperthermia

Abstract In magnetic hyperthermia, characterising the specific functionality of magnetic nanoparticle arrangements is essential to plan the therapies by simulating maximum achievable temperatures. This functionality, i.e. the heat power released upon application of an alternating magnetic field, is quantified by means of the specific absorption rate (SAR), also referred to as specific loss power (SLP). Many research groups are currently involved in the SAR/SLP determination of newly synthesised materials by several methods, either magnetic or calorimetric, some of which are affected by important and unquantifiable uncertainties that may turn measurements into rough estimates. This paper reviews all these methods, discussing in particular sources of uncertainties, as well as their possible minimisation. In general, magnetic methods, although accurate, do not operate in the conditions of magnetic hyperthermia. Calorimetric methods do, but the easiest to implement, the initial-slope method in isoperibol conditions, derives inaccuracies coming from the lack of matching between thermal models, experimental set-ups and measuring conditions, while the most accurate, the pulse-heating method in adiabatic conditions, requires more complex set-ups.
An Order-p Tensor Factorization with Applications in Imaging

Operations with tensors, or multiway arrays, are increasingly prevalent in many applications involving multiway data analysis. This paper extends a third-order factorization strategy and tensor operations defined in a recent paper [M. E. Kilmer and C. D. Martin, Linear Algebra Appl. , 435 (2011), pp. 641--658] to order-$p$ tensors. The extension to order-$p$ tensors is explained in a recursive way but for computational speed is implemented directly using the fast Fourier transform. A major motivation for considering factorization strategies for order-$p$ tensors is to devise new types of algorithms for general order-$p$ tensors which can be used in applications. We conclude with two applications in imaging. The first application is image deblurring, and the second application is video facial recognition. Both applications involve order-4 tensors.
Complement Inactivation by Recombinant Human C3 Derivatives

From the implications of the complement system in a large number of diseases, an urgent need for therapeutics effecting reduced complement activity in vivo has emerged. In this study we report the design of a novel class of enzymes of human origin that obliterate functional complement by a noninhibitory, catalytic mechanism. Combining the framework of human C3 and the enzymatic mechanism of cobra venom factor, a nontoxic snake venom protein, we established molecules capable of forming stable C3 convertase complexes. Although the half-life of naturally occurring C3 convertase complexes ranges between 1 and 2 min, these complexes exhibit a half-life of up to several hours. Because the overall identity to human C3 could be extended to >90%, the novel C3 derivatives can be assumed to exhibit low immunogenicity and, therefore, represent promising candidates for therapeutic reduction of complement activity in vivo.
Improved Learning of Structural Support Vector Machines: Training with Latent Variables and Nonlinear Kernels

Structured output prediction in machine learning is the study of learning to predict complex objects consisting of many correlated parts, such as sequences, trees, or matchings. The Structural Support Vector Machine (Structural SVM) algorithm is a discriminative method for structured output learning that allows flexible feature construction with robust control for overfitting. It provides state-of-art prediction accuracies for many structured output prediction tasks in natural language processing, computational biology, and information retrieval. This thesis explores improving the learning of structured prediction rules with structural SVMs in two main areas: incorporating latent variables to extend their scope of application and speeding up the training of structural SVMs with nonlinear kernels. In particular, we propose a new formulation of structural SVM, called Latent Structural SVM, that allows the use of latent variables, and an algorithm to solve the associated non-convex optimization problem. We demonstrate the generality of our new algorithm through several structured output prediction problems, showing improved prediction accuracies with new alternative problem formulations using latent variables. In addition to latent variables, the use of nonlinear kernels in structural SVMs can also improve their expressiveness and prediction accuracies. However their high computational costs during training limit their wider application. We explore the use of approximate cutting plane models to speed up the training of structural SVMs with nonlinear kernels. We provide a theoretical analysis of their iteration complexity and their approximation quality. Experimental results show improved accuracy-sparsity tradeoff when compared against several state-of-art approximate algorithm for training kernel SVMs, with our algorithm having the advantage that it is readily applicable to structured output prediction problems.
Photovoltaic power plant submitted to voltage sags: Model and performance evaluation

This paper brings the PV model of a real PV farm installation with a total power of 917 kW. All the elements of the PV farm (panels and inverter) are described. Simulation on PSCAD and experimental results at the installation are reported. The PV model is submitted to voltage sags originated in the grid as well as their impact on the photovoltaic power plant.
Spillover and Comovement: The Contagion Mechanism of Systemic Risks Between the U.S. and Chinese Stock Markets

In recent years, the measurement and analysis of comovement have become important subjects with theoretical and practical value. The contagion effects specified in this paper include spillover effects under information transfer and coherent movement under common external influences. We propose using the structural conditional correlation model to measure these two contagion mechanisms. Empirical results find significant mean and volatility spillover and dynamic conditional correlation between the residual series of the structural conditional correlation model for China and U.S. stock index returns, which clearly reflect the transmission channel from international markets to China's markets, especially in financial crises. The methodology introduced here may have implications for the control and management of crises.
Supplementation of Nucleosides During Selection can Reduce Sequence Variant Levels in CHO Cells Using GS/MSX Selection System

In the process of generating stable monoclonal antibody (mAb) producing cell lines, reagents such as methotrexate (MTX) or methionine sulfoximine (MSX) are often used. However, using such selection reagent(s) increases the possibility of having higher occurrence of sequence variants in the expressed antibody molecules due to the effects of MTX or MSX on de novo nucleotide synthesis. Since MSX inhibits glutamine synthase (GS) and results in both amino acid and nucleoside starvation, it is questioned whether supplementing nucleosides into the media could lower sequence variant levels without affecting titer. The results show that the supplementation of nucleosides to the media during MSX selection decreased genomic DNA mutagenesis rates in the selected cells, probably by reducing nucleotide mis‐incorporation into the DNA. Furthermore, addition of nucleosides enhance clone recovery post selection and does not affect antibody expression. It is further observed that nucleoside supplements lowered DNA mutagenesis rates only at the initial stage of the clone selection and do not have any effect on DNA mutagenesis rates after stable cell lines are established. Therefore, the data suggests that addition of nucleosides during early stages of MSX selection can lower sequence variant levels without affecting titer or clone stability in antibody expression.