Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating Unseen Deduplication - from Theory to Practice

Estimating the deduplication ratio of a very large dataset is both extremely useful, but genuinely very hard to perform. In this work we present a new method for accurately estimating deduplication benefits that runs 3X to 15X faster than the state of the art to date. The level of improvement depends on the data itself and on the storage media that it resides on. The technique is based on breakthrough theoretical work by Valiant and Valiant from 2011, that give a provably accurate method for estimating various measures while seeing only a fraction of the data. However, for the use case of deduplication estimation, putting this theory into practice runs into significant obstacles. In this work, we find solutions and novel techniques to enable the use of this new and exciting approach. Our contributions include a novel approach for gauging the estimation accuracy, techniques to run it with low memory consumption, a method to evaluate the combined compression and deduplication ratio, and ways to perform the actual sampling in real storage systems in order to actually reap benefits from these algorithms. We evaluated our work on a number of real world datasets.
Co-Speciation of the Ectoparasite Gyrodactylus teuchis (Monogenea, Platyhelminthes) and Its Salmonid Hosts

Co-speciation is a fundamental concept of evolutionary biology and intuitively appealing, yet in practice hard to demonstrate as it is often blurred by other evolutionary processes. We investigate the phylogeographic history of the monogenean ectoparasites Gyrodactylus teuchis and G. truttae on European salmonids of the genus Salmo. Mitochondrial cytochrome oxidase subunit 1 and the nuclear ribosomal internal transcribed spacer 2 were sequenced for 189 Gyrodactylus individuals collected from 50 localities, distributed across most major European river systems, from the Iberian- to the Balkan Peninsula. Despite both anthropogenic and naturally caused admixture of the principal host lineages among major river basins, co-phylogenetic analyses revealed significant global congruence for host and parasite phylogenies, providing firm support for co-speciation of G. teuchis and its salmonid hosts brown trout (S. trutta) and Atlantic salmon (S. salar). The major split within G. teuchis, coinciding with the initial divergence of the hosts was dated to ~1.5 My BP, using a Bayesian framework based on an indirect calibration point obtained from the host phylogeny. The presence of G. teuchis in Europe thus predates some of the major Pleistocene glaciations. In contrast, G. truttae exhibited remarkably low intraspecific genetic diversity. Given the direct life cycle and potentially high transmission potential of gyrodactylids, this finding is interpreted as indication for a recent emergence (<60 ky BP) of G. truttae via a host-switch. Our study thus suggests that instances of two fundamentally different mechanisms of speciation (co-speciation vs. host-switching) may have occurred on the same hosts in Europe within a time span of less than 1.5 My in two gyrodactylid ectoparasite species.
Characteristics of Patients Presenting to the Academic Emergency Department in Central Anatolia

SUMMARY Objectives Determining the properties of patients admitted to the emergency department (ED) is important to plan for future and quality assurance. In this study, we aimed to evaluate the properties of patients admitted to our ED to improve the quality of care within our hospital. Methods In the study period, the patients: (i) who have their full information in hospital information and management system (HIMS) and (ii) older than 17 years of age were included into the study. Demographic information, admission and discharge rates, mean staying time in the ED, triage categories, International Classification of Diseases – 10 (ICD-10) diagnoses were evaluated. Results During the study period, 32,117 cases were seen by the ED. However, 22,955 patients (71.4%) had complete information in the HIMS. The mean age was 44.92±19.50 and female gender was found 52.2%. The patients who were located in 18–29 age group was the major group of all cases (30.8%). Emergent and urgent cases were 26.1% and 14.8%, respectively. Non-urgent cases were also found (59.1%). The mean age of patients located in the emergent group (55.19±18.59) were significantly higher than urgent and non-urgent group (p≤0.01). The highest patient volume was seen on Sunday, between 20:00 and 22:00 o'clock. The mean staying time in the ED was 183.6 minutes and the admission rate was 17.6%. The three most noted ICD-10 codes were respiratory (16.6%), gastrointestinal (11.3%), musculoskeletal (11.2%) codes. Conclusions The data that was correctly uploaded into the system did not reach our expectation. Data can be more appropriately uploaded by medical secretaries. Registering patient information in a digital atmosphere while performing analyses will undoubtedly have an effect on future focused studies.
A GOOD GESTURE: EXPLORING NONVERBAL COMMUNICATION FOR ROBUST SLDSs

In this paper we propose a research framework to explore the possibilities that state-of-the-art embodied conversational agents (ECAs) technology can offer to overcome typical robustness problems in spoken language dialogue systems (SLDSs), such as error detection and recovery, changes of turn and clarification requests, that occur in many human-machine dialogue situations in real applications. Our goal is to study the effects of nonverbal communication throughout the dialogue, and find out to what extent ECAs can help overcome user frustration in critical situations. In particular, we have created a gestural repertoire that we will test and continue to refine and expand, to fit as closely as possible the users’ expectations and intuitions, and to favour a more efficient and pleasant dialogue flow for the users. We also describe the test environment we have designed, simulating a realistic mobile application, as well as the evaluation methodology for the assessment, in forthcoming tests, of the potential benefits of adding nonverbal communication in complex dialogue situations.
The relationship between software development team size and software development cost

the relationship between software development team size and software development cost Most of the software developMent cost is related to the programmers' salaries and recent evidence shows that team-related factors can affect project performance and its cost. Selecting an appropriate team size for software development projects continues to be a challenge for most project managers. Larger teams represent better distribution of skills, but lead to higher communication and coordination costs. 8 Smaller teams lead to lower communication and coordination costs, but lead to programming biases that make software maintenance costly. Smaller teams, due to homogeneous programmer backgrounds, may lack the problem solving expertise for large size complex projects. In addition to programmer skills, Gorla and Lam10 have noted that heterogeneity in team member personality may be desirable in certain phases of the SDLC. Additionally, Gorla and Lam 10 emphasize that diverse expertise in IT and business application experience is always desirable in any project. Software development project tools provide advance coordination and communication capabilities and are often used to control communication and coordination costs for large sized teams. Without the use of software development tools, it is easy to show that team communication requirements increase exponentially with the increase in team size. Since most projects use advance software development tools, the assumption of exponential increase in software development cost with increase in team size will seldom hold true in real world. Even a linear relationship between software development cost and team size may be considered a mute point, at best. Understanding the relationship and impact of team size on software development cost is important because most managers, when confronted with strict deadlines, are tempted to increase team size. Among the reasons for increasing team size are: 9, 6 1. Pressure to meet the schedule, as competitive advantage of the technology decreases with time, 2. Assigning one person to a project does not mean linear completion time, and 3. Dividing work into small sub-projects allows many people to work on the project simultaneously, which reduces the project completion time. Although increasing team size for strict deadlines appears to be a good strategy, it is not really clear if it works well. For example, Biffl and Gutjahr 5
Accelerated Stochastic Quasi-Newton Optimization on Riemann Manifolds

We propose an L-BFGS optimization algorithm on Riemannian manifolds using minibatched stochastic variance reduction techniques for fast convergence with constant step sizes, without resorting to linesearch methods designed to satisfy Wolfe conditions. We provide a new convergence proof for strongly convex functions without using curvature conditions on the manifold, as well as a convergence discussion for nonconvex functions. We discuss a couple of ways to obtain the correction pairs used to calculate the product of the gradient with the inverse Hessian, and empirically demonstrate their use in synthetic experiments on computation of Karcher means for symmetric positive definite matrices and leading eigenvalues of large scale data matrices. We compare our method to VR-PCA for the latter experiment, along with Riemannian SVRG for both cases, and show strong convergence results for a range of datasets.
Archiving With Guaranteed Convergence And Diversity In Multi-objective Optimization

Over the past few years, the research on evolutionary algorithms has demonstrated their niche in solving multi-objective optimization problems, where the goal is to find a number of Pareto-optimal solutions in a single simulation run. However, none of the multi-objective evolutionary algorithms (MOEAs) has a proof of convergence to the true Pareto-optimal solutions with a wide diversity among the solutions. In this paper we discuss why a number of earlier MOEAs do not have such properties. A new archiving strategy is proposed that maintains a subset of the generated solutions. It guarantees convergence and diversity according to well-defined criteria, i.e. e-dominance and e-Pareto optimality.
Earthquake nucleation and its relationship to earthquake clustering

Earthquake clustering phenomena such as aftershocks, foreshocks, and pairing of mainshocks are prominent and characteristic features of earthquake occurrence. Because the earthquake nucleation process controls the time and place of occurrence of earthquakes, non-linear dependence of nucleation times on stress changes can strongly affect the spatial and temporal patterns of earthquake occurrence. Earthquake nucleation on faults with rateand statedependent fault properties has this characteristic, and appears to quantitatively represent the details and broad statistical patterns of earthquake clustering.
Fuzzy order-equivalence for similarity measures

Similarity measures constitute a central component of machine learning and retrieval systems, and the choice of an appropriate measure is of major importance. In this paper, we consider this issue from the point of view of the order induced by the measures when comparing a set of objects to a given reference, i.e. the ranking from the most similar object to the least similar one. We introduce the notion of fuzzy order- equivalence, based on degrees that quantify the extent to which the induced orders differ. We define these degrees using the generalized Kendall's rank correlation, taking into account the number of order permutations as well as their positions. We then present an automatic and hierarchical classification of usual similarity measures that makes it possible to indicate, for a given number of tolerated variations, the measures that will yield rankings without significant changes; it thus provides a guideline for set data similarity measure selection.
SEMANTIC BLOGGING AND AGGREGATION 2 . 1 The Concept of Semantic Blogging

Sharing of bibliographic information is very important in a research community. SocioBiblog is a semantic blogging system that provides a decentralized environment to share bibliographic information. It uses the SWRC ontology for adding metadata about publications in blogs and aggregates publications from the social network neighborhood and coauthors of the researcher. RSS aggregation has been extended to handle embedded publication metadata in BuRST feeds. The FOAF network of the researchers is crawled to gather FOAF profiles for discovering aggregation feeds. Interoperability with other systems has been maintained by adopting standard formats. The aggregated collections may be searched and filtered flexibly by defining metadata criteria. The aggregated and filtered results can be redistributed as new feeds which can further be used by other systems. Thus, a decentralized ecosystem can be formed where each unit can publish, aggregate and redistribute information.
The Application of Software Defect Types Prediction Based on GreyEntropy Absolute Relational Analysis

In the software development process, reliability prediction can effectively improve its quality. But the small project data sets often restrain the predicting methods of the traditional software detect types, which causes the inaccuracy and unreliability of the predicting results. Grey relational analysis (GRA) is a method which is always used to describe the degree of influence among the factors and suitable for small project data sets. Therefore, on the basis of grey entropy absolute relational analysis (GEARA), we propose a software defect classification prediction method. Firstly, this method chooses an algorithm to carry on analysis and choice for feature attribute, which prediction result has greater relation degree. And then, it detects and removes anomaly project by using anomaly project detection algorithm and gets a set of engineering project. Finally, we use the grey entropy absolute relational analysis to predict software defect type. The simulation experiment indicated that proposed method owe a higher prediction precision than the traditional ones and predicted faster.
REAL TIME TRACKING OF MOVING PEDESTRIAN IN SURVEILLANCE VIDEO

Pedestrian detection is an active area of research in video Surveillance. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel scene-specific detector with adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the prioritized score based transferability. It derived from the prediction consistency with the source classifications, to selectively choose the positive confidence in source domains to the target domain. Through clustering based multimode models are used for SVM classifier with KNN based feature selections. Experimental results show that our approach can improve the pedestrian detection rate, and also with the insufficient labeled data in target scene. Finally, the selected samples are processed with PCA transform to get the resulting features for classification. Performance is based on different parameters by using the support vector machines (SVMs) serving as the classifier. The proposed method, the accuracy of the SVM classifier can be improved significantly.
Two-Dimensional Heterojunction Interlayer Tunneling Field Effect Transistors (Thin-TFETs)

Layered 2-D crystals embrace unique features of atomically thin bodies, dangling bond free interfaces, and step-like 2-D density of states. To exploit these features for the design of a steep slope transistor, we propose a Two-dimensional heterojunction interlayer tunneling field effect transistor (Thin-TFET), where a steep subthreshold swing (SS) of ~14 mV/dec and a high on-current of ~300 μm are estimated theoretically. The SS is ultimately limited by the density of states broadening at the band edges and the on-current density is estimated based on the interlayer charge transfer time measured in recent experimental studies. To minimize supply voltage VDD while simultaneously maximizing on currents, Thin-TFETs are best realized in heterostructures with near broken gap energy band alignment. Using the WSe2/SnSe2 stacked-monolayer heterostructure, a model material system with desired properties for Thin-TFETs, the performance of both n-type and p-type Thin-TFETs is theoretically evaluated. Nonideal effects such as a nonuniform van der Waals gap thickness between the two 2-D semiconductors and finite total access resistance are also studied. Finally, we present a benchmark study for digital applications, showing the Thin-TFETs may outperform CMOS and III-V TFETs in term of both switching speed and energy consumption at low-supply voltages.
A Lily Stylar Pectin Is Necessary for Pollen Tube Adhesion to an in Vitro Stylar Matrix

Pollen tube cells adhere to the wall surface of the stylar transmitting tract epidermis in lily. This adhesion has been proposed as essential for the proper delivery of the sperm cells to the ovule. An in vitro adhesion bioassay has been used to isolate two stylar molecules required for lily pollen tube adhesion. The first molecule was determined to be a small, cysteine-rich protein with some sequence similarity to lipid transfer proteins and now called stigma/stylar cysteine-rich adhesin (SCA). The second, larger, molecule has now been purified from style fragments and characterized. Chemical composition, specific enzyme degradations, and immunolabeling data support the idea that this molecule required for pollen tube adhesion is a pectic polysaccharide. In vitro binding assays revealed that this lily stylar adhesive pectin and SCA are able to bind to each other in a pH-dependent manner.
Generation of Rapid Eye Movements during Paradoxical Sleep in Humans

Although rapid eye movements (REMs) are a prominent feature of paradoxical sleep (PS), their origin and functional significance remain poorly understood in humans. In animals, including nonhuman primates, REMs during PS are closely related to the occurrence of the so-called PGO waves, i.e., prominent phasic activities recorded throughout the brain but predominantly and most easily in the pons (P), the lateral geniculate bodies (G), and the occipital cortex (O). Therefore, and because the evolution of species is parsimonious, a plausible hypothesis would be that during PS in humans, REMs are generated by mechanisms similar to PGO waves. Using positron emission tomography and iterative cerebral blood flow measurements by H(2)(15)O infusions, we predicted that the brain regions where the PGO waves are the most easily recorded in animals would be differentially more active in PS than in wakefulness, in relation with the density of the REM production [i.e., we looked for the condition (PS versus wakefulness) by performance (REM density) interaction]. Accordingly, we found a significant interaction effect in the right geniculate body and in the primary occipital cortex. The result supports the hypothesis of the existence of processes similar to PGO waves in humans, responsible for REM generation. The interest in the presence of PGO waves in humans is outstanding because the cellular processes involved in, or triggered by, PGO waves might favor brain plasticity during PS.
Experimentally based methodology for charge pumping bulk defect trapping correction

We develop a simple experimental approach to remove bulk trap contributions from charge pumping data collected on devices which suffer from large amounts of bulk dielectric electron trapping. The approach is more desirable and easier to implement than other simulation/device modeling based approaches. We demonstrate the approach using HfO2 based MOSFETs. Additionally, we provide an explanation for the smaller than expected bulk trap contribution to charge pumping current.
Posttraumatic Stress and Sexual Functioning Difficulties in College Women With a History of Sexual Assault Victimization

Objective: College women are at risk for exposure to sexual victimization, which is a risk factor for posttraumatic stress (PTS) and sexual dysfunction. Contemporary models of female sexual functioning identify the role of distal (e.g., sexual abuse) and proximal (e.g., psychological) variables in contributing to female sexual response. This study examined whether and how PTS symptom clusters are related to specific domains of sexual functioning in a sample of sexually active college women who reported a history of sexual victimization. Method: A nonclinical sample of 108 women, recruited from a midsized university, completed online questionnaires assessing sexual victimization history, PTS symptom clusters (i.e., intrusion, avoidance, and hyperarousal), and difficulties with sexual functioning (i.e., desire, arousal, lubrication, orgasm, pain, and distress). Results: Regression analyses indicated that greater intrusive symptoms were associated with more difficulties with orgasm and higher sexual distress. Conclusion: Results confirm the importance of intrusive PTS symptoms in understanding subjective distress and orgasm difficulties in sexual assault survivors. Possible implications of these findings include the integration of trauma-focused therapy with treatment of sexual dysfunction among women with a history of sexual assault. Future research should examine prospective relationships between sexual assault exposure, PTS response, and female sexual dysfunction.
Are Consumers Rational ? Experimental Evidence ?

D some misconceptions, consumer rationality is a property of the researcher rather than the consumer. Consumers become more rational as we are better able to predict their behavior or other important outcomes influenced by their behavior. Perfect rationality results when we achieve accurate predictions. Consequently, at least for many Marketing Science articles, consumers are becoming more rational as we find better ways to predict. However, some experimental consumer behavior articles find the opposite. The difference between experimental and statistical controls explains the divergence in conclusions. Experimental controls test rationality based on whether previously absent variables exhibit significant explanatory power holding known explanatory variables constant. Statistical controls test rationality based on the incremental explanatory power of previously absent variables after accounting for known explanatory variables. Moreover, experimental tests tend to isolate consumer behavior predictions while statistical tests check for sufficient accuracy to choose among different firm strategies. Both perspectives are correct but ask very different questions.