Miracle-dz/UniFAR-FTUs huggingface dataset:
Is There an Optimization in Bounded Rationality? The Ratio of Aspiration Levels

Simon’s (1955) famous paper was one of the first to cast doubt on the validity of rational choice theory; it has been supplemented by many more papers in the last three and a half decades. Nevertheless, rational choice theory plays a crucial role in classical and neoclassical economic theory, which presumes a completely rational agent. The central points characterizing such an agent are: (1) The agent uses all the information that is given to him. (2) The agent has clear preferences with respect to the results of different actions. (3) The agent has adequate competences to optimize his decisions. As an alternative to this conception, Simon (1955) himself suggests the concept of “bounded rationality”. In this context, Simon (1956) discusses a principle, which he names the “satisficing principle” (for explanations with respect to this notion cf. Gigerenzer & Todd 1999, p. 13). It assumes that, instead of searching for an optimal action, the search for an action terminates if an alternative has been found that satisfies a given “aspiration level”. It will be demonstrated that although the satisficing principle is nothing but a heuristic, there is a mathematical optimization at work when aspiration levels are used in this kind of problems. The question about the optimal aspiration level can be posed. Optimization within the framework of bounded rationality is possible. However, the way in which such an optimization can be achieved is very simple: Optimal thresholds in binary sequential decisions rest with the median.
Social License to Acquire Abroad

I examine the strategic impact of corporate social responsibility (CSR) on international expansion. When going abroad, firms often face liabilities of foreignness, newness, and origin. I argue that information about their CSR activities can help circumvent these liabilities and affect the outcome of international expansion. A quantitative analysis of 4,130 cross-border M&A announcements by firms from Brazil, Russia, India, China, and South Africa (1990-2011) shows that positive (negative) news about CSR is associated with greater (lower) likelihood of and faster (slower) M&A deal completion. Thus, social license to acquire, or social approval of the acquiring firm by the relevant stakeholders, plays an important role in gaining access abroad. The study bridges instrumental stakeholder theory, corporate social responsibility, international business, and strategic management research.
Studies on Modeling Corona Attenuation of Dynamic Overvoltages

An experimental and theoretical study is presented in this paper on the corona characteristics of conductor bundles under dynamic overvoltages. Measurements have been made in the outdoor test cages of Institut de recherche d'Hydro-Québec (IREQ) on two bundles, under conditions of fair weather and heavy rain, for steady 60 Hz voltages as well as dynamic overvoltages. Based on the data on corona currents and losses obtained, a nonlinear resistance model of corona is proposed for attenuation studies. The Suliciu model for corona, originally developed for unipolar impulses, has been also adopted for dynamic overvoltages. Both these corona models are used to study the influence of corona on the dynamic overvoltages developed during line energisation and load shedding of a single phase line.
Approaches to Skills Mismatch in the Labour Market: A Literature Review

Skills mismatch in the labour market describes the fact that levels or types of skills of individuals are inadequate in view of particular job requirements. There exists no accepted unified theory of skills mismatch. The overeducation literature, inspired by several classical theoretical frameworks (human capital theory, job competition, and assignment models), attempts to define and measure the incidence of the phenomenon, but often understates the heterogeneity of both jobs and manpower. Some authors have tried to make up for this deficit by focusing on specific groups or individual abilities. By contrast, a competence approach places the observed no-causality relationship between training and occupation at the centre of its analysis, rather than considering it as a market imperfection. By doing so, it provides an alternative way of conceptualising skills mismatch, and promisingly challenges the normative assumptions and current applications of the classical frameworks.
Threat From Being Social: Vulnerability Analysis of Social Network Coupled Smart Grid

Social networks (SNs) have been gradually applied by utility companies as an addition to smart grid and are proved to be helpful in smoothing load curves and reducing energy usage. However, SNs also bring in new threats to smart grid: misinformation in SNs may cause smart grid users to alter their demand, resulting in transmission line overloading and in turn leading to catastrophic impact to the grid. In this paper, we discuss the interdependence in the SN coupled smart grid and focus on its vulnerability. That is, how much can the smart grid be damaged when misinformation related to it diffuses in SNs? To analytically study the problem, we propose the misinformation attack problem in social-smart grid that identifies the top critical nodes in the SN, such that the smart grid can be greatly damaged when misinformation propagates from those nodes. This problem is challenging as we have to incorporate the complexity of the two networks concurrently. Nevertheless, we propose a technique that can explicitly take into account information diffusion in SN, power flow balance, and cascading failure in smart grid integratedly when evaluating node criticality, based on which we propose various strategies in selecting the most critical nodes. Also, we introduce controlled load shedding as a protection strategy to reduce the impact of cascading failure. The effectiveness of our algorithms is demonstrated by experiments on the IEEE bus test cases as well as the Pegase data set.
Comparative study on data mining classification methods for cervical cancer prediction using pap smear results

The number of woman with cervical cancer in Indonesia is getting higher. Indonesia becomes the country with the highest number of women with cervical cancer in the world. Cervical cancer became the highest cause of cancer deaths in women globally. There has been a lot of research using data mining techniques with variety of different data mining models that can be used for analyzing cervical cancer. In this research, data that be used were obtained from the medical records of the Pap smear test results. There are 38 symptoms and 7 classes. Naïve Bayes, Support Vector Machines (SVM), and Random Forest Tree was used to evaluate the performance of the classifier. The performance matric that used in this study are accuracy, recall, precision, and ROC curve. Based on the performance matric, Random Forest Tree is the best classifier among other classifiers to classify Pap smear results.
An adaptive wrapper algorithm for file transfer applications to support optimal large file transfers

The overall file transmission time between peer machines is affected by network conditions, file dispatching and retrieval systems, error detection and the processing capabilities of the peers. Improving the network condition or the peers processing capabilities for speedup will incur higher cost. We introduce a Wrapper Algorithm for the dispatching and retrieval systems at the peers. The algorithm performs file compression-decompression, file split-merge and file chunk scheduling processes to speedup the file transfer time of large files. The Wrapper Algorithm is wrapped around RSYNC and the results reveal an overall reduction of file transfer time of up to 66%.
Cooperative DNA binding of the bovine papillomavirus E2 transcriptional activator is antagonized by truncated E2 polypeptides

Cooperative DNA binding of the bovine papillomavirus type 1 (BPV-1) E2 transcriptional activator (E2-TA) is thought to play a role in the transcriptional synergism of multiple E2-responsive DNA elements (J. Ham, N. Dostatni, J.-M. Gauthier, and M. Yaniv, Trends Biochem. Sci. 16:440-444, 1991). Binding-equilibrium considerations show that such involvement is unlikely, thereby suggesting that the E2-TA cooperative capacity may have evolved to play other, different roles. The role of cooperative interactions in the antagonistic activity of BPV-1-positive and BPV-1-negative E2 regulatory proteins was investigated by an in vitro quantitative gel shift assay. Viral repressor E2-TR, a truncated peptide encompassing the activator DNA-binding domain, possesses a small but measurable cooperative capacity. Furthermore, the minimal E2 DNA-binding domain interacts with the activator in a positive, heterocooperative manner. As a result, the in vitro competition of full-length and truncated E2 peptides appears to be (macroscopically) noncooperative. This heterocooperative effect is probably dominant in latently infected G0-G1 cells, in which repressor E2-TR is 10- to 20-fold more abundant than the activator. The data are discussed considering the possible role of homo- and heterocooperative DNA binding in E2-conditional gene expression.
Deep generative models of genetic variation capture mutation effects

The functions of proteins and RNAs are determined by a myriad of interactions between their constituent residues, but most quantitative models of how molecular phenotype depends on genotype must approximate this by simple additive effects. While recent models have relaxed this constraint to also account for pairwise interactions, these approaches do not provide a tractable path towards modeling higher-order epistasis. Here, we show how latent variable models with nonlinear dependencies can be applied to capture beyond-pairwise constraints in biomolecules. We present a new probabilistic model for sequence families, DeepSequence, that can predict the effects of mutations across a variety of deep mutational scanning experiments significantly better than site independent or pairwise models that are based on the same evolutionary data. The model, learned in an unsupervised manner solely from sequence information, is grounded with biologically motivated priors, reveals latent organization of sequence families, and can be used to extrapolate to new parts of sequence space.
Frictional Characteristics in Deeper Part of Seismogenic Transition Zones on a Subduction Plate Boundary

By virtue of dense networks of GPS and highly sensitive seismic stations, occurrences of deep low-frequency tremors/earthquakes have been recognized worldwide in the deep portions of subduction plate boundaries (e.g., Schwartz & Rokosky, 2007). Since these tremors and earthquakes have moment release rate smaller than that of regular earthquakes, the low-frequency tremors (LFTs) /earthquakes are classified into “slow-earthquake” group (Ide et al., 2007). The slow-earthquakes occur sometimes independently and sometimes break into chain-reaction propagating at a speed of about 10 km/day. However, a systematic explanation of the origin of such slow-earthquake migrations in some subduction zones is still lacking. First of this study, we investigate the mechanisms of slow-earthquake migration by comparing observational results and numerical simulation results. Since some LFTs are found to be modulated by Earth tides (e.g., Nakata et al., 2008) and the moment release rate of the slow earthquake group is much smaller than that of regular earthquakes (Ide et al., 2007), they likely have low-stress drop and are sensitive to shear stress perturbations possibly induced by the preseismic slip of nearby megathrust earthquakes. Second of this study, we propose a new method to detect precursory change around the large asperity prior to a megathrust earthquake, focusing on the spatio-temporal change of migration speed and moment release rate for nearby slow earthquakes. Recently, lowfrequency tremors/earthquakes have been also detected in the shallower portion of frictional transition zone on the subduction plate boundaries (Obana & Kodaira, 2009). Third of this study, we also perform another numerical simulation of shallow low-frequency tremors/earthquakes, comparing with the characteristics of the deep low-frequency tremors/earthquakes and discussing the strategy of Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) toward an anticipated Tonankai Earthquake.
Growth And Implications Of Social E-Commerce And Group Buying Daily Deal Sites: The Case Of Groupon And Livingsocial

E-commerce has changed the nature of the value propositions that companies now offer to their customers. The convergence of content sites and social networks has resulted in emerging ecommerce business models. The group buying/local daily deals e-commerce platform represents the collective bargaining power that individuals can leverage to obtain daily deals on local products, services and “experiences”. These local discounted deals are distributed via e-mail and the websites of companies like Groupon and LivingSocial that have established themselves as the sector leaders. The convergence of traditional and electronic business models, as well as traditional and new business practices, are changing the face of global business as we know it. In this study, the authors critically reflect on the strategic management implications of the convergence of content, community and commerce in the form of social e-commerce and daily deal sites. The authors consider the implications of the rapid growth experienced by daily deal social group buying sites, in terms of strategy, and question its long-term value-creation. Future investors are urged to consider the long-term value-creation and not merely the short-term payoff of these sites. Merchants are urged to consider the practical implications of offering coupons on these sites for the day-to-day operation of their businesses.
Defining IT Success Through the Service Catalog

This book covers Service Catalog fundamentals the use of Service Catalogs as a core IT tool covering the services themselves, default capabilities, measures and primary means of access and provision. It then shows how this tool is pivotal in demonstrating the value IT provides to facilitate business operations. Written by industry experts and using real case studies, this valuable title takes the reader beyond the theoretical to focus on the real business benefits of Service Catalogs and how to implement them successfully within an organization.
Calcium sparks and [Ca2+]i waves in cardiac myocytes.

Local elevations in intracellular calcium ("Ca2+ sparks") in heart muscle are elementary sarcoplasmic reticulum (SR) Ca(2+)-release events. Ca2+ sparks occur at a low rate in quiescent cells but can also be evoked by electrical stimulation of the cell to produce the cell-wide Ca2+ transient. In this study we investigate how Ca2+ sparks are related to propagating waves of elevated cytosolic Ca2+ induced by "Ca2+ overload. " Single ventricular myocytes from rat were loaded with the Ca(2+)-sensitive indicator fluo 3 and imaged with a confocal microscope. After extracellular Ca2+ concentration was increased from 1 to 10 mM to produce Ca2+ overload, the frequency of spontaneous Ca2+ sparks, which occur at the t tubule/SR junction, increased approximately 4-fold, whereas the spark amplitude and spatial size increased 4.1-and 1.7-fold, respectively. In addition, a spectrum of larger subcellular events, including propagating Ca2+ waves, was observed. Ca2+ sparks were seen to occur at the majority (65%) of the sites of wave initiation. For slowly propagating Ca2+ waves, discrete Ca(2+)-release events, similar to Ca2+ sparks, were detected in the wave front. These Ca2+ sparks appeared to recruit other sparks along the wave front so that the wave progressed in a saltatory manner. We conclude that Ca2+ sparks are elementary events that can explain both the initiation and propagation of Ca2+ waves. In addition, we show that Ca2+ waves and electrically evoked Ca2+ transients have the same time course and interact with each other in a manner that is consistent with both phenomena having the same underlying mechanism(s). These results suggest that SR Ca2+ release during Ca2+ waves, like that during normal excitation-contraction coupling, results from the spatial and temporal summation of Ca2+ sparks.
Bimodal Vertex Splitting: Acceleration of Quadtree Triangulation for Terrain Rendering

SUMMARY Massive digital elevation models require a large number of geometric primitives that exceed the throughput of the existing graphics hardware. For the interactive visualization of these datasets, several adaptive reconstruction methods that reduce the number of primitives have been introduced over the decades. Quadtree triangulation, based on subdivision of the terrain into rectangular patches at di ﬀ erent resolutions, is the most frequently used terrain reconstruction method. This usually accomplishes the triangulation using LOD (level-of-detail) selection and crack removal based on geometric errors. In this paper, we present bimodal vertex splitting, which performs LOD selection and crack removal concurrently on a GPU. The ﬁrst mode splits each vertex for LOD selection and the second splits each vertex for crack removal. By performing these two operations concurrently on a GPU, we can e ﬃ ciently accelerate the rendering speed by reducing the computation time and amount of transmission data in comparison with existing quadtree-based rendering methods.
Security issues in VANET

A Vehicular Ad-Hoc Network or VANET is a form of Mobile Ad-Hoc Network or MANET which provides communication between vehicles and between vehicles and road-side base stations. A vehicle in VANET is considered to be an intelligent mobile node capable of communicating with its neighbors and other vehicles in the network. VANET is different from MANET due to high mobility of nodes and the large scale of networks. Security and privacy are the two main concerns in designing a VANET . Although there are many proposed solutions for improving securities in VANET but security still remains a delicate research subject. The main objectives of this paper is to improve the security issues in VANET.The preliminary efforts were focused on the potential applications, possible attacks, security requirements and the literature review. The long term goal of this project is to come up with an entirely new solution that can be implemented in designing a VANET.
How Bank Competition Affects Real Estate Market and Consumer Welfare

This paper establishes a general model to explore the mechanism through which bank competition affects real estate market and consumer welfare. The model combines three sections, including a representative consumer, an oligopoly real estate industry, and a banking industry. It predicts that several phenomena are likely to appear during the process of banking industry development in emerging economies: 1) The interest rates of loans to real estate firms will slightly increase, while the interest rates of personal loan will significantly decrease. 2) Average price and quantity of transacted houses will rise. 3) The total scale of the banking industry will grow while the profit level will decrease. 4) Consumers will be better off. Based on this model, empirical study is conducted and policy implications are discussed.
Topic Modeling via Nonnegative Matrix Factorization on Probability Simplex

One important goal of document modeling is to extract a set of informative topics from a text corpus and produce a reduced representation of each document. In this paper, we propose a novel algorithm for this task based on nonnegative matrix factorization on a probability simplex. We further extend our algorithm by removing global and generic information to produce more diverse and specific topics. In contrast to other matrix factorization methods, such as latent semantic indexing by singular value decomposition, our model has a solid statistical foundation and is based on a generative model for text corpus. In contrast to purely probabilistic approach, such as probabilistic latent semantic indexing (pLSI) solved by Expectation-Maximization, our method is based on efficient block coordinate decent optimization. Experiments demonstrate that the new method generates more meaningful and diverse topics compared with pLSI and LDA with faster convergence behavior.
Cloned long-term cytolytic T-lymphocyte line with specificity for an immediate-early membrane antigen of murine cytomegalovirus

Long-term cytolytic T-lymphocyte (CTL) lines that are specific for distinct antigens associated with different phases of the replicative cycle of the murine cytomegalovirus (MCMV) were established by cloning of CTL lines derived from lymph nodes of latently infected BALB/c mice. Two CTL clones were characterized in detail. Both displayed the Lyt-2+, L3T4- surface phenotype, and the recognition of their respective target antigens was class I (DLd) major histocompatibility complex antigen restricted. Clone S1 was specific for a structural antigen of MCMV, and clone IE1 detected an MCMV-specified immediate-early (IE) membrane antigen. Clone IE1 retained lytic activity, antigen specificity, and self-restriction after prolonged propagation in the presence of recombinant human interleukin-2 without restimulation by antigen. This interleukin-2-dependent line of the clone IE1, line IE1-IL, can serve as a reference line for the definition of the antigenic determinant IE1 of an IE membrane antigen.
Offline printed Arabic character recognition

Optical Character Recognition (OCR) shows great potential for rapid data entry, but has limited success when applied to the Arabic language. Normal OCR problems are compounded by the right-to-left nature of Arabic and because the script is largely connected. This research investigates current approaches to the Arabic character recognition problem and innovates a new approach. The main work involves a Haar-Cascade Classifier (HCC) approach modified for the first time for Arabic character recognition. This technique eliminates the problematic steps in the pre-processing and recognition phases in additional to the character segmentation stage. A classifier was produced for each of the 61 Arabic glyphs that exist after the removal of diacritical marks. These 61 classifiers were trained and tested on an average of about 2,000 images each. A Multi-Modal Arabic Corpus (MMAC) has also been developed to support this work. MMAC makes innovative use of the new concept of connected segments of Arabic words (PAWs) with and without diacritics marks. These new tokens have significance for linguistic as well as OCR research and applications and have been applied here in the post-processing phase. A complete Arabic OCR application has been developed to manipulate the scanned images and extract a list of detected words. It consists of the HCC to extract glyphs, systems for parsing and correcting these glyphs and the MMAC to apply linguistic constrains. The HCC produces a recognition rate for Arabic glyphs of 87%. MMAC is based on 6 million words, is published on the web and has been applied and validated both in research and commercial use.