Miracle-dz/UniFAR-FTUs huggingface dataset:
Computing Shortest Paths Using A*, Landmarks, and Polygon Inequalities (Abstract)

We introduce a new heuristic for the A* algorithm that references a data structure much smaller than the one required by the ALT heuristic. This heuristic's benefits are permitted by a new approach for computing lower bounds using generalized polygon inequalities, leveraging distance information from two landmarks as opposed to the common single landmark paradigm. In this paper, we demonstrate that this heuristic stores a reduced amount of preprocessing information in comparison to previous landmark algorithms while performing faster search queries.
Uncovering the Chemical Signature of the First Stars in the Universe

The chemical abundance patterns observed in metal-poor Galactic halo stars contain the signature of the first supernovae, and thus allow us to probe the first stars that formed in the universe. We construct a theoretical model for the early chemical enrichment history of the Milky Way, aiming in particular at the contribution from pair-instability supernovae (PISNe). These are a natural consequence of current theoretical models for primordial star formation at the highest masses. However, no metal-poor star displaying the distinct PISN signature has yet been observed. We here argue that this apparent absence of any PISN signature is due to an observational selection effect. Whereas most surveys traditionally focus on the most metal-poor stars, we predict that early PISN enrichment tends to “overshoot,” reaching enrichment levels of [Ca/H] ≃ − 2.5 that would be missed by current searches. We utilize existing observational data to place constraints on the primordial initial mass function (IMF). The number fraction of PISNe in the primordial stellar population is estimated to be <0.07, or ≲ 40% by mass, assuming that metal-free stars have masses in excess of 10 M☉. We further predict, based on theoretical estimates for the relative number of PISNe, that the expected fraction of second-generation stars below [Ca/H] = − 2 with a dominant (i.e., > 90%) contribution from PISNe is merely ~10−4 to 5 × 10−4. The corresponding fraction of stars formed from gas exclusively enriched by PISNe is a factor of ~4 smaller. With the advent of next-generation telescopes and new, deeper surveys, we should be able to test these predictions.
Extinction hazards in experimental Daphnia magna populations: effects of genotype diversity and environmental variation

Extinction is ubiquitous in natural systems and the ultimate fate of all biological populations. However, the factors that contribute to population extinction are still poorly understood, particularly genetic diversity and composition. A laboratory experiment was conducted to examine the influences of environmental variation and genotype diversity on persistence in experimental Daphnia magna populations. Populations were initiated in two blocks with one, two, three, or six randomly selected and equally represented genotypes, fed and checked for extinction daily, and censused twice weekly over a period of 170 days. Our results show no evidence for an effect of the number of genotypes in a population on extinction hazard. Environmental variation had a strong effect on hazards in both experimental blocks, but the direction of the effect differed between blocks. In the first block, variable environments hastened extinction, while in the second block, hazards were reduced under variable food input. This occurred despite greater fluctuations in population size in variable environments in the second block of our experiment. Our results conflict with previous studies, where environmental variation consistently increased extinction risk. They are also at odds with previous studies in other systems that documented significant effects of genetic diversity on population persistence. We speculate that the lack of sexual reproduction, or the phenotypic similarity among our experimental lines, might underlie the lack of a significant effect of genotype diversity in our study.
Image Steganalysis by the Distribution Characters of Stego-images in Reduced Dimension Space

In this paper we propose an Improved Kernel Linear Discriminant Analysis algorithm to analyze the distribution differences between cover images and stego-images in the reduced dimensional space. We observe that the hidden information, the information hidden in the cover images, of stegoimages are clustered in some plane while all other information of cover-images are scattered more evenly in this space and have no other clusters. Based on this fact, we develop a steganalysis scheme to discriminate stego-images from innocent images. The experiment results show the effectiveness of the proposed approach.
The Impact of Network Flows on Community Formation in Models of Opinion Dynamics

We study dynamics of opinion formation in a network of coupled agents. As the network evolves to a steady state, opinions of agents within the same community converge faster than those of other agents. This framework allows us to study how network topology and network flow, which mediates the transfer of opinions between agents, both affect the formation of communities. In traditional models of opinion dynamics, agents are coupled via conservative flows, which result in one-to-one opinion transfer. However, social interactions are often nonconservative, resulting in one-to-many transfer of opinions. We study opinion formation in networks using one-to-one and one-to-many interactions and show that they lead to different community structure within the same network.
Effects of nucleotide changes on the ability of hepatitis delta virus to transcribe, process, and accumulate unit-length, circular RNA

The circular RNA genome of hepatitis delta virus (HDV) can fold into an unbranched rodlike structure. We mutagenized the two ends of this structure and assayed the effects on the ability of the genomes to replicate and accumulate processed RNA transcripts in transfected cells. The top end, defined as that nearest to the 5' end of the putative mRNA for delta antigen, was much more sensitive than the other end, defined as the bottom. Most of the 22 mutants made at the bottom were able to accumulate RNA as well as the wild type. For deletions extending as close as 2 nucleotides (nt) from the predicted domains needed for the two ribozymes, the accumulation levels dropped to <0.1%. In one mutant, 13 nt of HDV was replaced with 57 nt of non-HDV sequences, and accumulation was at 20% of the wild-type level, consistent with the potential of HDV to act as a vector. However, after replacement with a second sequence, accumulation dropped to 1%. For most of the 14 mutants made at the top of the rod, we observed dramatic inhibitory effects. For example, after removal of 3 bp from the stem adjacent to the terminal loop, accumulation dropped to <0.06% of the wild-type genome level. The top region that we considered was adjacent to both the 5' end of the putative mRNA and the domain that has been proposed to contain a promoter for RNA-directed RNA synthesis. The RNA accumulation abilities of certain mutants were tested under additional different experimental conditions. It was found that after longer times, some mutants began to catch up with the wild type. Also, it was found that certain top mutants gave much greater levels of accumulation when transfected into cells containing the small delta antigen. One interpretation of these data is that certain features at the top of the rod are needed for the accumulation of essential delta antigen mRNA species.
Random tournaments : who plays with whom and how many times ?

The weighted feedback arc set problem on tournaments (WFAS-T) is defined by a weighted tournament graph whose nodes represents the teams/items, and the goal is to find a ranking over the teams that minimizes the sum of the weights of the feedback arcs. We consider the probabilistic version of WFAS-T, in which the weights of the directed edges between every pair of teams sum up to one. A WFAS-T with this probabilistic constraint naturally determines a distribution over the tournament graphs. In this study, we investigate an online learning problem where the learner can observe tournament graphs drawn from this distribution. The goal of the learner is to approximate the solution ranking of the underlying probabilistic WFAS-T problem. We also investigate the partial information case, known from the multi-armed bandit problem, where the learner is allowed to select single edges and observe the corresponding value. Since the probabilistic WFAS-T problem is in general NP-hard [1], our learning algorithm relies on some recent approximation results for WFAS-T [2, 3]. We also consider some interesting special cases where the learner is able to estimate the exact solution, for example where the weights of the tournament graph satisfy the Bradley-Terry assumption [4].
Applying SIGMA to the TREC-7 Filtering Track

This paper presents the research method and results from applying SIGMA (System of Information Gathering Market-based Agents) to the adaptive filtering task of the TREC-7 Filtering Track. Our work in SIGMA is based on the research hypothesis that a multi-agent learning approach, where each agent learns a local model for information filtering, performs better than a single-agent learning approach that approximates the whole input space with a single model. We report on experiments for testing this hypothesis as well as for constructing the feature space model for this task. This has been SIGMA’s first application to TREC experiments and to an IF task over a large document collection. The system was able to scale to the complexity of the task. The performance of SIGMA in TREC-7 is encouraging for further work.
A Case Study of Marketing Effects on Global Distribution Logistics Development

The mutual interaction of marketing and logistics has been widely described in academic articles. For almost a century, many scholars and practitioners have recognised the close relationship between marketing and logistics activities in a marketing channel. Business philosophies such as JIT, QR and ECR implicitly emphasise this relationship as well. However, there is often a gap between marketing and logistics in theory and in practice. This separation results in problems. In logistics especially, the significance of marketing has been occasionally ignored. This is a single case study of distribution logistics development. The case company is a medium-sized high-tech consumer goods producer and distributor. The company has a few production plants and distribution centres and a number of warehouses all over the globe. The marketing function sets demands for logistics concerning product availability in local warehouses and the variety of product mix etc. From the logistics point of view those demands are quite expensive to fulfil. On the other hand, marketing provides important information for logistics. For example, the quality of forecasts and the feasible length of order cycle are dependent on marketing. The goal of the study is to analyse and find out what are the development possibilities and potential within the case when the scope and measures are: i. strictly limited to logistics ii. a combination of logistics and marketing At the beginning, the distribution network was described and appropriate data – sales of different products, forecasts, lead times, replenishment rules and transport costs etc. – were gathered. The network was analysed and development needs and issues were identified. A simulation model was created as a comparison tool of different development steps and scenarios. The development potential of logistics alone and of marketing and logistics together was established by means of simulation. The results indicate that major development potential derives from the co-operation of marketing and logistics, which is conformable with current theories.
Memory for rejected distractors in visual search?

Theories of visual search have generally assumed that rejected distractors are marked so as to avoid further processing of these items (memory-driven search). To test this assumption, Horowitz and Wolfe (1998) developed the randomized search paradigm, in which standard static search is compared to dynamic search where items are randomly replotted at new locations throughout a trial. Memory-driven search predicts that search slopes should double in the dynamic condition. After reviewing earlier findings that slopes were similar in the two conditions, we present two new experiments. Experiment 1 replicated and extended our previous findings using a larger range of set sizes, a slower rate of change, and adding a fixed location dynamic condition. Experiment 2 employed stimuli that required overt fixation. Neither experiment showed evidence for memory-driven search. We conclude that visual search is best understood as a series of successive judgements of the momentary probability of target presence.
Joint Subcarrier and Power Allocation in Uplink OFDMA Systems with Incomplete Channel State Information

A joint subcarrier and power allocation in uplink OFDMA systems with incomplete channel state information is proposed. The subcarrier allocation problem is considered as a multi-player discrete, stochastic and finite strategy game, and equal power is allocated to the subcarriers of each user. Particularly, the utility function is based on the channel capability and adds the pricing scheme to guarantee the fairness. The subcarrier allocation is different from the traditional scheme in which the subcarriers are allocated passively. In our process, each of the subcarriers is viewed as a learning automaton to choose the most satisfying user. We adopt the linear reward-inaction algorithm to obtain the Nash equilibrium. Theoretic analysis is given. Simulation results show our allocation scheme has good convergence, and the performance gap is tolerated compared with the complete channel state case.
Dynamic Localization Schemes in Malicious Sensor Networks

Wireless sensor networks (WSN) have recently shown many potential military and civilian applications, especially those used in hostile environments where malicious adversaries can be present. The accuracy of location information is critical for such applications. It is impractical to have a GPS device on each sensor in WSN due to costs. Most of the existing location discovery schemes can only be used in the trusted environment. Recent research has addressed security issues in sensor network localization, but to the best of our knowledge, none have completely solved the secure localization problem. In this paper, we propose novel schemes for secure dynamic localization in sensor networks. These proposed schemes can tolerate up to 50% of beacon nodes being malicious, and they have linear computation time with respect to the number of reference nodes. Our security analysis has showed that our schemes are applicable and resilient to attacks from adversaries. We have further conducted simulations to analyze and compare the performance of these schemes, and to indicate when each should be used. The efficiencies of each method shows why we needed to propose multiple methods.
Assuring Software Quality using data mining methodology: A literature study

Software Quality is the very popular and a very important topic for researchers within the software engineering communities, most probably everyone has an opinion about the meaning of quality. However, many disagreements and conflicts are very often leaded between peoples whose involve in software development, when they implement to it in the real world. This has been highly notable in the case of customer's complaints about faults in the software products. It is well known that many organizations or individuals are relishing many challenges to preserve software product quality, whenever they develop any types of software product. Appearance of defects is the very much contributor to reduce the product quality and prominently increases in development costs and completion time due to amendment and rework time. The success and demand of a software system is not only pivot on cost and proceedings, but also on software quality. In between many software quality features, to identify the vestigial defects in the product has become the actual industry standard. This paper is a study about software quality, software defect and how both are relate to each other and also discuss defect prediction is batter approach in compare defect correction to assure software product quality. We also discuss some data mining methodologies in brief; they are used to build defect prediction models to ensure the level of defect density of target program modules of software product.
The agency problem, investment decision, and optimal financial structure

This article constructs a real options model in which a firm has a privileged right to exercise an irreversible investment project with a stochastic payoff. Supposing that the investment costs are fully sunk, a firm that exercises the investment option after debt is in place will then choose a better state to exercise this option as it issues more bonds. This debt-overhang phenomenon, however, benefits the firm since waiting is itself valuable. Accordingly, the firm will both exercise the investment option later and issue more bonds as compared with a firm that issues bonds upon exercising the investment option.
1 A Bayesian Approach to Learning Low-Dimensional Signal Models from Incomplete Measurements 1

Sampling, coding and streaming even the most essential data, e.g., in medical imaging and weather monitoring applications, now produce a data deluge that severely stresses the available analog-todigital converter, communication bandwidth, and digital storage resources. Surprisingly, while the ambient data dimension is large in many problems, the relevant information in the data can reside in a much lower dimensional space. This observation has lead to several important theoretical and algorithmic developments under different low-dimensional modeling frameworks, such as compressive sensing [1], [2], matrix completion [3], [4], and general factor-model representations [5], [6]. These approaches have enabled new measurement systems, tools and methods for information extraction from dimensionality-reduced or incomplete data. A key aspect of maximizing the potential of such techniques is to develop appropriate data models, and in this paper we investigate this challenge from the perspective of nonparametric Bayesian analysis.
New Evidence on the Economic Determinants of Postsecondary Schooling Choices

The effects of tuition costs, financial aid, and individual attributes on college choice are analyzed using a conditional logit model. The results confirm that financial aid can be an important determinant of postsecondary school attendance and that individual academic ability relative to the academic standards of a college is an important determinant of which of available college alternatives is chosen.
Metonymy : Discovering Classes of Meanings

We address the problem of interpretation of logical metonymy using a statistical method. Previous approaches to logical metonymy produce interpretations in the form of verb senses, whereas our definition of the interpretation is a cluster of verb senses. Such a class-based computational model of logical metonymy is novel and more informative than the previous ones. It also complies with the linguistic theories, which we empirically validate. We propose feature sets not previously used for verb clustering. In addition to this we conduct an experiment to prove that our representation is intuitive to human subjects. The system clusters the senses with the F-measure of 0.64 as compared to the gold standard, given that the human agreement on the task is 0.76.
Regulation of ES cell differentiation by functional and conformational modulation of p53

Embryonic stem (ES) cell lines were used to examine the role of p53 during in vitro differentiation. Undifferentiated ES cells express high levels of p53 exclusively in the wild‐type conformation, immunoprecipitable by monoclonal antibody PAb246, and p53 was found to be functionally active as determined by its ability to bind DNA specifically and to activate transcription of target genes. Differentiation in vitro resulted in a decrease in the levels of p53 and in a shift in its conformational status to the mutant form, detectable by monoclonal antibody PAb240, with a concomitant loss of functional activity. The presence of functional p53 in the undifferentiated ES cells renders them hypersensitive to UV irradiation, whereas the differentiated cells were resistant to UV treatment. ES cells lacking p53 exhibit enhanced proliferation in both the undifferentiated and differentiated state, and apoptosis accompanying differentiation was found to be reduced. Furthermore, wild‐type ES cells undergoing apoptosis expressed functional p53. Expression of the temperature‐sensitive p53val135 mutant in wild‐type ES cells resulted in a reduction of apoptosis accompanying differentiation when it adopted a mutant conformation at 39°C. These data demonstrate that functional inactivation of p53 allows differentiating cells to escape from apoptosis, and suggest that the conformational switch could regulate the inactivation process.
An Incremental OCL Compiler for Modeling Environments

In software engineering, reliability and development time are two of the most important aspects, therefore, modeling environments, which aide both, are widely used during software development. UML and OCL became industry standards, and are supported by many CASE tools. OCL code checking, which has to be performed by these tools, has a specialty, as not all of the information necessary for compilation is available from the code, the related model contains the types, navigations and attributes. The build time of OCL code fragments is increased if the development tool supports distributed modeling, because in this case, model element checking has to be performed in a model repository that cannot be held in memory. In this paper, we introduce a method that enables incremental OCL code building and therefore reduces the development time. Incremental builds require higher complexity than simple builds, thus balancing between the two methods is also considered.
Integrating romanized Nepali spellchecker with SMS based decision support system for Nepalese farmers

Now-a-days the role of Information and Communication Technology (ICT) to develop and strengthen the sector of agriculture has become seemingly promising. ICT can help a farmer to get relevant information regarding different agricultural information like crop, diseases, marketing, etc. Also, studies have depicted that mobile phone penetration in Nepal have increased in the recent years. This have opened a new possibility for implementing SMS (Short Message Service) based information dissemination services in order to reduce information asymmetry prominent in the country due to extreme geography. This work proposes an approach based on simple SMS service for disseminating agricultural knowledge to the needy farmers in a cost effective and easily deployable manner. Here, the farmers can get consultancy expert advices by sending simple queries (in romanized Nepali language) as a SMS to a central knowledge base. But, the end users, may not provide correct spelling in their queires. Therefore, we integrated a domain specific (i.e. romanized Nepali) spell checker for improving robustness of the system. The purposed approach is seemingly promising than other advanced mobile applications because the general farmer community use simple handset with basic features only.