Miracle-dz/UniFAR-FTUs huggingface dataset:
Clustering Stock Market Companies via K- Means Algorithm

One of the main concepts in pattern recognition is clustering. This technique is used as important knowledge discovery tools in modern machine learning process. Clustering of high-performance companies is very important not only for investors, but also for the creditors, financial creditors, stockholders, etc. Hence, firms’ clustering is considered as one of the important issues in Tehran Stock Exchange (TSE). To this end, we have used financial statement data of three industries in TSE for the year 2012. After selecting profit criteria (attributes) and prioritizing them using AHP, k means clustering algorithm is used to classify these companies. Also, to obtain the optimal number of clusters, different validity measures are presented. The identification of clusters of companies of TSE can be exploited to improve planning and get to more comprehensive decision making about companies.
Clustering-based Missing Value Imputation for Data Preprocessing

Missing value imputation is an actual yet challenging issue confronted by machine learning and data mining. Existing missing value imputation is a procedure that replaces the missing values in a dataset by some plausible values. The plausible values are generally generated from the dataset using a deterministic, or random method. In this paper we propose a new and efficient missing value imputation based on data clustering, called CRI (clustering-based random imputation). In our approach, we fill up the missing values of an instance with those plausible values that are generated from the data similar to this instance using a kernel-based random method. Specifically, we first divide the dataset (exclude instances with missing values) into clusters. And then each of those instances with missing-values is assigned to a cluster most similar to it. Finally, missing values of an instance A are thus patched up with those plausible values that are generated using a kernel-based method to those instances from A's cluster. Our experiments (some of them are with the decision tree induction system C 5.0) have proved the effectiveness of our proposed method in missing value imputation task.
Effects of Decabrominated Diphenyl Ether (PBDE-209) in Regulation of Growth and Apoptosis of Breast, Ovarian, and Cervical Cancer Cells

Background: Polybrominated diphenyl ethers (PBDEs), commonly used in building materials, electronics, plastics, polyurethane foams, and textiles, are health hazards found in the environment. Objective: In this study we investigated the effects of PBDE-209, a deca-PBDE, on the regulation of growth and apoptosis of breast, ovarian, and cervical cancer cells as well as the underlying protein alterations. Methods: We used MCF-7 and MCF-7/ADR (multidrug-resistant MCF-7) breast cancer cell lines, the HeLa cervical cancer cell line, the OVCAR-3 ovarian cancer cell line, and the normal CHO (Chinese hamster ovary) cell line to assess the effects of PBDE-209 using cell viability, immunofluorescence, and flow cytometric assays. Western blot assays were used to detect changes in protein expression. To assess the effects of PBDE-209 on apoptosis, we used the protein kinase Cα (PKCα) inhibitor Gö 6976, the extracellular signal-regulated kinase (ERK) inhibitor PD98059, and tamoxifen. Results: Our data indicate that PBDE-209 increased viability and proliferation of the tumor cell lines and in CHO cells in a dose- and time-dependent manner. PBDE-209 also altered cell cycle distribution by inducing the S phase or G2/M phase. Furthermore, PBDE-209 partially suppressed tamoxifen-induced cell apoptosis in the breast cancer cell lines (MCF-7 and MCF-7/ADR) but suppressed Gö 6976- and PD98059-induced apoptosis in all cell lines. At the molecular level, PBDE-209 enhanced PKCα and ERK1/2 phosphorylation in the cell lines. Conclusions: Our data demonstrate that PBDE-209 is able to promote proliferation of various cancer cells from the female reproductive system and normal ovarian CHO cells. Furthermore, it reduced tamoxifen, PKCα, and ERK inhibition-induced apoptosis. Finally, PBDE-209 up-regulated phosphorylation of PKCα and ERK1/2 proteins in tumor cells and in CHO cells.
Multi-scale bio-inspired place recognition

This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.
Visualizing and Evaluating the Performance of Overlay-Based Pub/Sub Systems

The Publish/Subscribe (pub/sub) paradigm is receiving an increasing amount of attention both in research and in industry, as it provides a loosely coupled and scalable interaction scheme suitable for large-scale distributed systems. Designers of such system face many difficulties related to finding the correct balance of performance, as many desired properties of pub/sub systems are at stake with each other. Also, many considerations must be taken with regards to the overlays formed by these systems both in terms of maintenance of the overlay as well as structural properties such as clustering and connectivity. With these issues in mind, we propose VIZPUB, a tool for visualizing the performance of overlay-based pub/sub systems. VIZPUB is able to log local information from every node participating in the overlay, and collect this information to a single site. Then, our tool is able to calculate certain system-wide metrics and produce step-by-step visualizations of the overlay in question. To the best of our knowledge, VIZPUB is the first tool of its kind. It is a generic tool intended to be used with any overlay-based system. We describe the system architecture and explore the capabilities of VIZPUB by providing examples of visualizations and what information we may derive from them. Also, we test the potential of using our tool as a convenient framework for evaluating pub/sub system on a set of specific overlay topology metrics. We presented a poster and held a live demonstration of VIZPUB at the ACM International Conference of Distributed Event Based Systems (DEBS), hosted in Mumbai in May 2014. Here, the value of our contribution was confirmed as we were voted best poster/demonstration by the participants attending the conference. Due to interest in our tool, we choose to make our implementation code open source and available in a public repository.1 Hopefully, VIZPUB may serve as a lasting contribution to the research community. 1htttp://github.com/vizpub/vizpub
Comparison of the prognostic accuracy of scoring systems, cardiopulmonary exercise testing, and plasma biomarkers: a single-centre observational pilot study.

BACKGROUND Current approaches to risk assessment before major surgery have important limitations. The aim of this pilot study was to compare predictive accuracy of preoperative scoring systems, plasma biomarkers, and cardiopulmonary exercise testing (CPET) for complications after major non-cardiac surgery. METHODS Single-centre, observational study of patients aged ≥40 yr undergoing major elective non-cardiac surgery. Before surgery, risk scores were calculated and blood samples collected for measurement of plasma biomarkers. Patients underwent CPET for measurement of anaerobic threshold (AT) and peak oxygen consumption ( peak). After surgery, patients were followed for 28 days to evaluate complications and major adverse cardiac events (MACE). Data are presented as area under the receiver operating characteristic curve (AUROC) with 95% confidence intervals. RESULTS A total of 100 patients were recruited between April 2009 and October 2010; 17 of whom did not proceed to surgery. CPET variables suggested good predictive accuracy for MACE [AT: AUROC 0.83 (0.69-0.96); peak AUROC 0.81 (0.69-0.96)] and poor predictive accuracy for all complications [AT: AUROC 0.64 (0.52-0.77); peak AUROC 0.64 (0.52-0.77)]. There was a trend towards predictive accuracy of the plasma biomarkers B-type natriuretic peptide and estimated glomerular filtration rate (calculated from serum creatinine) for MACE but not all complications. C-reactive protein, ASA score, and revised cardiac risk index had little or no predictive value. CONCLUSIONS These pilot data suggest that CPET and plasma biomarkers may improve risk assessment before surgery. Only large clinical studies can confirm this observation and define the optimal use of these tests in clinical practice.
Toward a Greener GATT: Environmental Trade Measures and the Shrimp-Turtle Case

The World Trade Organization (WTO) Appellate Body issued the most important ruling to date on the status of environmental trade measures under the General Agreement on Tariffs and Trade (GATT)1 in its 1998 report in the “shrimp-turtle” case.2 At issue in this case was section 609 of Public Law 101-162,3 a U.S. statute that the U.S. Court of International Trade had interpreted as a ban on shrimp imports from countries not certified by the United States as having adopted “a regulatory program governing the incidental taking of . sea turtles . that is comparable to that of the United States. ”4 The United States adopted such a program to promote the conservation of sea turtles, which are endangered species. This program includes a requirement that U.S. trawlers use turtle excluder devices (TEDs) to protect sea turtles from incidental capture and drowning in shrimping nets. India, Malaysia, Pakistan, and Thailand complained that the U.S. ban on shrimp imports violated GATT Article XI,5 which prohibits
The Automated Acquisition of Suggestions from Tweets

This paper targets at automatically detecting and classifying user's suggestions from tweets. The short and informal nature of tweets, along with the imbalanced characteristics of suggestion tweets, makes the task extremely challenging. To this end, we develop a classification framework on Factorization Machines, which is effective and efficient especially in classification tasks with feature sparsity settings. Moreover, we tackle the imbalance problem by introducing cost-sensitive learning techniques in Factorization Machines. Extensively experimental studies on a manually annotated real-life data set show that the proposed approach significantly improves the baseline approach, and yields the precision of 71.06% and recall of 67.86%. We also investigate the reason why Factorization Machines perform better. Finally, we introduce the first manually annotated dataset for suggestion classification.
Collaborative Social Group Influence for Event Recommendation

In event-based social networks, such as Meetup, social groups refer to self-organized communities that consist of users who share the same interests. In many real-world scenarios, users usually have social group preference and join interested social groups to attend events. It is therefore necessary to consider the influence of social groups to improve the event recommendation performance; however, existing event recommendation models generally consider users' individual preferences and neglect the influence of social groups. To this end, we propose a new Bayesian latent factor model SogBmf that combines social group influence and individual preference for event recommendation. Experiments on real-world data sets demonstrate the effectiveness of the proposed method.
Partitioning for Multi-function Systems

We are interested in optimizing the design of multi-function embedded systems that run a pre-specified set of applications, such as multi-standard audio/video codecs and multi-system phones. Such systems usually have stringent performance constraints and tend to have mixed hardware-software implementations. The current state of the art in the hardware/software codesign of such systems is to design for each application separately. This often leads to application-specific sub-optimal decisions and inconsistent mappings of common nodes in different applications. We use these as the guiding principles to formulate, as a code-sign problem, the design and synthesis of an efficient hardware-software implementation for a multi-function embedded system. Our solution methodology is to first identify nodes that represent similar functionality across different applications. Such " common " nodes are characterized by several metrics. These metrics are quantified and used by a hardware/software partitioning tool to map common nodes to the same resource as far as possible. We demonstrate how this is achieved by modifying a traditional partitioning algorithm (GCLP) used to partition single applications. The overall result of the system-level partitioning process is (1) a hardware or software mapping and (2) a schedule for execution for each node within the application set. On an example set consisting of three video applications, we show that the solution obtained by the use of our method is 38% smaller than that obtained when each application is considered independently.
A tutorial on mixed-domain wave-equation migration and migration velocity analysis

This tutorial describes mixed-domain wave-equation migration and migration velocity analysis techniques in a unified theoretical framework. I review two of the most general mixed-domain migration methods, Fourier finite-difference and generalized screen, and show how other commonly used wave-equation migration methods come about as special cases. I use the Born approximation to derive general expressions for the wave-equation migration velocity analysis operator, and show two simple backprojection examples built around a North Sea dataset.
Promoting Domain-Specific Terms in Topic Models with Informative Priors

Latent Dirichlet Allocation (LDA) models trained without stopword removal often produce topics with high posterior probabilities on uninformative words, obscuring the underlying corpus content. Even when canonical stopwords are manually removed, uninformative words common in that corpus will still dominate the most probable words in a topic. We propose a simple strategy for automatically promoting terms with domain relevance and demoting these domain-specific stop words. Our approach is easily applied within any existing LDA framework and increases the amount of domain-relevant content and reduces the appearance of canonical and humanevaluated stopwords in three very different domains: Department of Labor accident reports, online health forum posts, and NIPS abstracts. Along the way, we show that standard topic quality measures such as coherence and pointwise mutual information act counter-intuitively in presence of common but irrelevant words. We also explain why these standard metrics fall short, propose an additional topic quality metric that targets the stopword problem, and show that it correlates with our human subject experiments.
The Multidimensional Benefits of Participation in Masters Sports: A Case Study of the “Masters Koshien”

The purpose of this study is to explore the multidimensional beneˆts experienced by Masters Sports participants from a case of the Masters Koshien. This study focused on the Masters Koshien to collect qualitative data regarding detailed description of subjective beneˆts of the event participants and investigated what kind of beneˆts do the masters sports participants obtain substantially. Survey interviews were conducted and 1,878 linguistic data items were collected from 304 participants of the 2008 Masters Koshien, our action research program. In the series of thematic analysis, 21 beneˆts of masters sports were extracted and divided into 4 diŠerent dimensions of beneˆts: individual beneˆts, community beneˆts, social beneˆts, and educational beneˆts. It was suggested that this study could reveal three additional beneˆts that previous studies have not been explored such as community beneˆts, social beneˆts, and educational beneˆts of masters sports. Moreover, it was revealed that the Masters Koshien presented the general beneˆts derived from any masters sports and the typical beneˆts of the Masters Koshien's unique status as a mecca-like masters sports event and as an alumni membership sport event.
Polymerization kinetics of ADP- and ADP-Pi-actin determined by fluorescence microscopy

We used fluorescence microscopy to determine how polymerization of Mg-ADP-actin depends on the concentration of phosphate. From the dependence of the elongation rate on the actin concentration and direct observations of depolymerizing filaments, we measured the polymerization rate constants of ADP-actin and ADP-Pi-actin. Saturating phosphate reduces the critical concentration for polymerization of Mg-ADP-actin from 1.8 to 0.06 μM almost entirely by reducing the dissociation rate constants at both ends. Saturating phosphate increases the barbed end association rate constant of Mg-ADP-actin 15%, but this value is still threefold less than that of ATP-actin. Thus, ATP hydrolysis without phosphate dissociation must change the conformation of polymerized actin. Analysis of depolymerization experiments in the presence of phosphate suggests that phosphate dissociation near the terminal subunits is much faster than in the interior. Remarkably, 10 times more phosphate is required to slow the depolymerization of the pointed end than the barbed end, suggesting a weak affinity of phosphate near the pointed end. Our observations of single actin filaments provide clues about the origins of the difference in the critical concentration at the two ends of actin filaments in the presence of ATP.
An approach to stability problem of the second order difference equation

The presented research work considers stability criteria of second-order differential equation. The second-order discrete-time oscillator equation is obtained from discretization of second order continuous-time equation using the forward difference operator. The stability criteria are drawn with freezing method and are presented in the terms of the equation coefficients. Finally, an illustrative example is shown.
Context Processing and Cognitive Control in Children and Young Adults

T. S. Braver and colleagues (e.g., T. S. Braver, J. D. Cohen, & D. M. Barch, 2002) have provided a theory of cognitive control that focuses on the role of context processing. According to their theory, an underlying context-processing mechanism is responsible for the cognitive control functions of attention, inhibition, and working memory. In the present study, the authors examined whether T. S. Braver et al.'s theory can account for developmental differences in cognitive control. The authors compared the performance of children (M age = 11.9 years, SD = 0.43 years) with that of young adults (M age = 21.7 years, SD = 3.61 years) on a continuous performance task (AX-CPT) that placed demands on context processing. The results suggest that developmental differences in the cognitive control functions of attention, inhibition, and working memory may be based on age-related changes in an underlying context-processing mechanism.
Resource allocation for Adjustable QoS in OFDMA wireless networks

We propose a centralized resource allocation scheme called Proportional Fairness with Adjustable QoS (PF-AQ) for an OFDMA wireless system, which transmitting data on a frame basis. We have network resources in frequency and time domains. We develop a simple and efficient user selection, subchannel assignment, and time slot allocation based on PF utility function with a consideration of realistic queue length. Our scheme schedules a batch of packets which can extend across multiple time slots at a time, and employs multi-user diversity to maximize system throughput while keeping throughput fairness. Our scheme enhances fairness by the limitation of the maximum number of time slots assigned to each user per frame. QoS in terms of throughput and queue size can also be adjusted by adjusting this limitation.
Crustal and upper mantle structure of southernmost South America inferred from regional waveform inversion

[1] We determine the crustal and upper mantle structure of southern South America by inverting regional seismograms recorded by the Seismic Experiment in Patagonia and Antarctica. We present a waveform inversion method that utilizes a niching genetic algorithm. The niching genetic algorithm differs from the traditional genetic algorithm in that the inversion is performed in multiple subpopulations, thus generating a broader search of the model space and enabling us to examine alternative local error minima. The vertical and transverse waveforms were used, extending from the P arrival to the surface waves, and the inversion was performed at either 0.005–0.06 Hz (larger events) or 0.02–0.06 Hz (smaller events). The inversion included anisotropy by solving for separate SV and SH structures in the upper mantle. Results indicate that crustal thickness varies from 26 to 36 km with thicker values toward the northeast, suggesting that there is little crustal thickening beneath the austral Andes. The average upper mantle velocities are similar to the preliminary reference Earth model (PREM) except that the southernmost region shows velocities of 5% slower than PREM. The upper mantle has up to 5% polarization anisotropy between the Moho and 120 km depth. The strongest anisotropy is localized in a lithospheric lid shallower than 65 km depth, which overlies a pronounced low-velocity zone. This shallow limit to anisotropy is consistent with the relatively small shear wave splitting values found in this region. These results suggest that the anisotropy is limited to lithospheric depths and may imply the absence of a strong mantle flow pattern in the asthenosphere.
Design of CDMA MAC for Microsatellite

Code division multiple access (CDMA) is a digital wireless transmission technology that allows for a large amount of users to share access to a single radio channel. This technology is being widely used in cellular communication and can be extended to store and forward (S&F) payload that provides message relay service for several users with ground terminals, simultaneously. In this paper, the three layered model for the store and forward payload using CDMA medium access control (MAC) is considered. Their design methodologies are discussed assuming static code assignment