Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling using LDA with Feedback Mechanisms

Topic models provide a way to identify the latent topics from a collection of documents. Although the identified topics often appear quite representative of the data; just as often, there are parts of the output that appear erroneous or otherwise difficult to interpret by humans. This is a limitation of topic models that can be remedied by user feedback mechanisms. In this paper, I discuss two feedback actions: removing a word from a topic and removing a topic from a document. I apply these two functionalities in the framework of Collapsed Gibbs Sampling of an LDA model using a subset of the Wikipedia dataset. A preliminary evaluation of this method shows that such feedback mechanisms can be useful and efficiently implemented.
NUMBER OF SINGLE-STROKE FLASHES IN THE ALPINE REGION DETERMINED WITH A VIDEO AND FIELD RECORDING SYSTEM

Since 2008, measurements of natural cloud-to-ground (CG) lightning were performed during warm season thunderstorms in the Alpine region of Austria to generate a ground truth data set of lightning strikes. Those measurements were performed with a mobile high speed video and an electric field recording system (VFRS) to observe the optical properties of lightning discharges and to record the ambient electric field. In 2015, the VFRS`s high speed camera was upgraded in order to significantly increase the optical and temporal resolution of the video data. Due to the upgrade it was possible to record a high quality data set during 20 thunderstorm days at 15 different sites between May and August 2015. For this paper these data sets of the Alpine region are used to analyze possible reasons for the detected variation of single-stroke flashes. The ground truth data sets are also compared to formerly published values from different countries. To provide additional information, data of the Austrian Lightning Location System (LLS), ALDIS (Austrian Lightning Detection and Information System), is compared to the VFRS ground truth data, operated by Graz University of Technology, to analyze the reasons for the varying amount of single-stroke flashes in the considered region. Thunderstorm types are classified with radar data and with wind measurements in order to investigate the effect of thunderstorm organization on their lightning characteristics. Compared to values from the literature the percentage of single-stroke flashes in this study present a higher value for negative flashes (26 %) and values in the same range for positive flashes (89 %). Results of this report shall contribute to a better understanding of the lightning process in general and the behavior of thunderstorms in the Alpine region in particular.
In Situ Ultrahigh-resolution Optical Coherence Tomography Characterization of Eye Bank Corneal Tissue Processed for Lamellar Keratoplasty

Purpose: To use optical coherence tomography (OCT) as a noninvasive tool to perform in situ characterization of eye bank corneal tissue processed for lamellar keratoplasty. Methods: A custom-built ultrahigh-resolution OCT (UHR-OCT) was used to characterize donor corneal tissue that had been processed for lamellar keratoplasty. Twenty-seven donor corneas were analyzed. Four donor corneas were used as controls, whereas the rest were processed into donor corneal buttons for lamellar transplantation by using hand dissection, a microkeratome, or a femtosecond laser. UHR-OCT was also used to noninvasively characterize and monitor the viable corneal tissue immersed in storage medium over 3 weeks. Results: The UHR-OCT captured high-resolution images of the donor corneal tissue in situ. This noninvasive technique showed the changes in donor corneal tissue morphology with time while in storage medium. The characteristics of the lamellar corneal tissue with each processing modality were clearly visible by UHR-OCT. The in situ characterization of the femtosecond laser-cut corneal tissue was noted to have more interface debris than shown by routine histology. The effects of the femtosecond laser microcavitation bubbles on the corneal tissue were well visualized at the edges of the lamellar flap while in storage medium. Conclusions: The results of our feasibility study show that UHR-OCT can provide superb, in situ microstructural characterization of eye bank corneal tissue noninvasively. The UHR-OCT interface findings and corneal endothelial disc thickness uniformity analysis are valuable information that may be used to optimize the modalities and parameters for lamellar tissue processing. The UHR-OCT is a powerful approach that will allow us to further evaluate the tissue response to different processing techniques for posterior lamellar keratoplasty. It may also provide information that can be used to correlate with postoperative clinical outcomes. UHR-OCT has the potential to become a routine part of tissue analysis for any eye bank or centers creating customized lamellar corneal tissue for transplantation.
Combining Close and Distant Reading: A Multiscalar Analysis of the English Lake District's Historical Soundscape

This article joins calls for literary scholarship to move beyond the limitations of binary oppositions between ‘close’ and ‘distant’ reading and towards the development of approaches that exploit the macroanalytic potential of digital methods alongside the nuanced analysis that characterises literary scholarship. Drawing on a customised corpus of writing about the English Lake District, we model the application of a multiscalar approach known as geographical text analysis (GTA), which combines aspects of close reading and distant reading, and, in doing so, introduces a new method for literary research. Here, we focus on historical descriptions of the Lake District's soundscape to demonstrate both how perceptions of sound changed over the course of the eighteenth and nineteenth centuries, and how multi-scalar methods can uniquely uncover such historical-literary shifts. Sound, we argue, offers a particularly useful focus since it allows us to draw fruitful parallels between our methods and those applied by the writers we study. In this way, this article advocates for digital humanities scholarship that advances our disciplines in conversation with appropriate historical modes.
A linear program to compare path-complete Lyapunov functions

We provide an algorithmic procedure allowing to compare stability certificates for discrete-time switching systems and in specific Path-Complete Lyapunov functions (PCLFs). These mathematical objects consist of a set of positive definite functions and a set of Lyapunov inequalities, encoded in a directed, labeled graph. Given two such graphs, we formulate necessary and sufficient conditions to decide if the existence of a PCLF for the first graph implies existence of a PCLF for the second graph, where the corresponding set of functions is constructed by conic combinations of the set of functions related to the first PCLF. The conditions depend only on the topologies of the two graphs and can be verified by solving a linear program. It is the first systematic approach to compare the conservativeness of PCLFs.
Are clownfish groups composed of close relatives? An analysis of microsatellite DNA variation in Amphiprion percula

A central question of evolutionary ecology is: why do animals live in groups? Answering this question requires that the costs and benefits of group living are measured from the perspective of each individual in the group. This, in turn, requires that the group's genetic structure is elucidated, because genetic relatedness can modulate the individuals’ costs and benefits. The clown anemonefish, Amphiprion percula, lives in groups composed of a breeding pair and zero to four nonbreeders. Both breeders and nonbreeders stand to gain by associating with relatives: breeders might prefer to tolerate nonbreeders that are relatives because there is little chance that relatives will survive to breed elsewhere; nonbreeders might prefer to associate with breeders that are relatives because of the potential to accrue indirect genetic benefits by enhancing anemone and, consequently, breeder fitness. Given the potential benefits of associating with relatives, we use microsatellite loci to investigate whether or not individuals within groups of A. percula are related. We develop seven polymorphic microsatellite loci, with a number of alleles (range 2–24) and an observed level of heterozygosity (mean = 0.5936) sufficient to assess fine‐scale genetic structure. The mean coefficient of relatedness among group members is 0.00 ± 0.10 (n = 9 groups), and there are no surprising patterns in the distribution of pairwise relatedness. We conclude that A. percula live in groups of unrelated individuals. This study lays the foundation for further investigations of behavioural, population and community ecology of anemonefishes which are emerging as model systems for evolutionary ecology in the marine environment.
Retrograde amnesia after hippocampal damage: Recent vs. remote memories in two tasks

We review evidence from experiments conducted in our laboratory on retrograde amnesia in rats with damage to the hippocampal formation. In a new experiment reported here, we show that N‐methyl‐D‐aspartate (NMDA)‐induced hippocampal damage produced retrograde amnesia for both hidden platform and two‐choice visible platform discriminations in the Morris water task. For both problems there was a significant trend for longer training‐surgery intervals to be associated with worse retention performance. Little support is offered by our work for the concept that there is a process involving hippocampal‐dependent consolidation of memories in extrahippocampal permanent storage sites. Long‐term memory consolidation may take place within the hippocampus. The hippocampus may be involved permanently in storage and/or retrieval of a variety of relational and nonrelational memories if it was intact at the time of learning, even involving information which is definitely not affected in anterograde amnesia after hippocampal damage. Hippocampus 2001;11:27–42. © 2001 Wiley‐Liss, Inc.
Computer Simulation of the Dynamics of Plasma-Surface Interactions in Vacuum Arc Cathode Spots

After an introductory definition of the vacuum arc cathode spot, its main theoretical aspects are highlighted. Most of the review is being devoted to the E-diagram method as well as to advanced nonstationary cathode spot models. A survey of the aim of the present computer simulation and its development following the author's very first concept of "dynamic field emission" is also given. The cathode spot model subjected to the computer simulation is described in detail, considering the laws of conservation of charge, mass, and energy in the complete cathode spot system. A short survey of the computational procedure is also given here. The main computational results may be summarized as follows: Within the actual model assumptions, a steady-state self-sustaining cathode spot does not exist. On the one hand, plasma-wall interactions with steady-state thermal equilibrium exist below the balance conditions of mass and energy, while on the other hand, real cathode spots that meet the requirements of both mass and energy balance never show thermal equilibrium but are characterized by thermal runaway. Therefore, instability is an inherent feature of cathode spots. Finally, a comparison between computational values and representative experimental results of cathode spot characteristics shows a rather good agreement, further supporting the principal validity of a model devoted particularly to a theoretical specification of the vacuum arc cathode spot.
Production of the Pseudomonas aeruginosa Neuraminidase Is Increased under Hyperosmolar by Genes Involved in Alginate Expression Conditions and Is Regulated

The pathogenesis of Pseudomonas aeruginosa infection in cystic fibrosis (CF) is a complex process attributed to specific characteristics of both the host and the infecting organism. In this study, the properties of the PA0i neuraminidase were examined to determine its potential role in facilitating Pseudomonas colonization of the respiratory epithelium. The PAO1 neuraminidase was 1000-fold more active than the Clostridium perfringens enzyme in releasing sialic acid from respiratory epithelial cells. This effect correlated with increased adherence of PA01 to epithelial cells after exposure to PA0i neuraminidase and was consistent with in vitro studies demonstrating Pseudomonas adherence to asialoganglioside receptors. The regulation of the neuraminidase gene nanA was examined in Pseudomonas and as cloned and expressed in Escherichia coli. In hyperosmolar conditions neuraminidase expression was increased by 50% (P < 0.0004), an effect which was OmpR dependent in E. coli. In Pseudomonas the osmotic regulation of neuraminidase production was dependent upon algR1 and algR2, genes involved in the transcriptional activation of algD, which is responsible for the mucoid phenotype ofPseudomonas and pathognomonic for chronic infection in CF. Under the hyperosmolar conditions postulated to exist in the CF lung, nanA is likely to be expressed to facilitate the initial adherence of Pseudomonas to the respiratory tract. (J. Clin. Invest. 1992. 89:1866-1874.)
A Wiener model for memory high power amplifiers using B-spline function approximation

In this paper we introduce a new Wiener system modeling approach for memory high power amplifiers in communication systems using observational input/output data. By assuming that the nonlinearity in the Wiener model is mainly dependent on the input signal amplitude, the complex valued nonlinear static function is represented by two real valued B-spline curves, one for the amplitude distortion and another for the phase shift, respectively. The Gauss-Newton algorithm is applied for the parameter estimation, which incorporates the De Boor algorithm, including both the B-spline curve and the first order derivatives recursion. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.
Witnessed k-Distance

Distance functions to compact sets play a central role in several areas of computational geometry. Methods that rely on them are robust to the perturbations of the data by the Hausdorff noise, but fail in the presence of outliers. The recently introduced distance to a measure offers a solution by extending the distance function framework to reasoning about the geometry of probability measures, while maintaining theoretical guarantees about the quality of the inferred information. A combinatorial explosion hinders working with distance to a measure as an ordinary power distance function. In this paper, we analyze an approximation scheme that keeps the representation linear in the size of the input, while maintaining the guarantees on the inference quality close to those for the exact but costly representation.
Overexpressing AtPAP 15 Enhances Phosphorus Efficiency in Soybean 1 [ W ] [ OA ]

Low phosphorus (P) availability is a major constraint to crop growth and production, including soybean (Glycine max), on a global scale. However, 50% to 80% of the total P in agricultural soils exists as organic phosphate, which is unavailable to plants unless hydrolyzed to release inorganic phosphate. One strategy for improving crop P nutrition is the enhanced activity of acid phosphatases (APases) to obtain or remobilize inorganic phosphate from organic P sources. In this study, we overexpressed an Arabidopsis (Arabidopsis thaliana) purple APase gene (AtPAP15) containing a carrot (Daucus carota) extracellular targeting peptide in soybean hairy roots and found that the APase activity was increased by 1.5-fold in transgenic hairy roots. We subsequently transformed soybean plants with AtPAP15 and studied three homozygous overexpression lines of AtPAP15. The three transgenic lines exhibited significantly improved P efficiency with 117.8%, 56.5%, and 57.8% increases in plant dry weight, and 90.1%, 18.2%, and 62.6% increases in plant P content, respectively, as compared with wild-type plants grown on sand culture containing phytate as the sole P source. The transgenic soybean lines also exhibited a significant level of APase and phytase activity in leaves and root exudates, respectively. Furthermore, the transgenic lines exhibited improved yields when grown on acid soils, with 35.9%, 41.0%, and 59.0% increases in pod number per plant, and 46.0%, 48.3%, and 66.7% increases in seed number per plant. Taken together, to our knowledge, our study is the first report on the improvement of P efficiency in soybean through constitutive expression of a plant APase gene. These findings could have significant implications for improving crop yield on soils low in available P, which is a serious agricultural limitation worldwide.
Perceptual Visual Feature Learning With Applications in Sports Educational Image Understanding

Effectively understanding the semantics of sophisticated sceneries is a key module in plenty of artificial intelligence (AI) systems. In this article, we optimally fuse multi-channel perceptual visual features for recognizing scenic pictures with complex spatial configurations, focusing on formulating a deep hierarchical model to actively discover human gaze allocation. In detail, to uncover semantically/visually important patches within each scenery, we utilize the BING objectness descriptor to rapidly and accurately localize multi-scale objects or their components. Subsequently, a local-global feature fusion scenario is proposed to dynamically combine the multiple low-level features from multiple scenic patches. To simulate how humans perceiving semantically/visually important scenic patches, we design a robust deep active learning (RDAL) paradigm that sequentially derives gaze shift path (GSP) and hierarchically learns deep GSP features in a unified architecture. Notably, the key advantage of RDAL is the high tolerance of label noise by adding an elaborately-designed sparse penalty. That is, the contaminated and redundant deep GSP features can be implicitly abandoned. Finally, the refined deep GSP features are integrated into a multi-label SVM for recognizing sceneries of different categories. Empirical comparisons showed that: 1) our method performs competitively on six generic scenery set (average accuracy 2%~4.3% higher than the second best performer), and 2) our deep GSP feature is particularly discriminative to our compiled sport educational image set (average accuracy 7.7% higher than the second best performer).
Augmenting creative design thinking using networks of concepts

Here we propose an interactive system to augment creative design thinking using networks of concepts in a virtual reality environment. We discuss how to augment the human capacity to be creative through dynamic suggestions providing new and original ideas, based on specific semantic network characteristics. We outline directions to explore the structures of the concept network and their connection to creative concept generation. It is expected that augmented creative thinking will allow the user to have more original ideas and thus be more innovative.
A hybrid approach for robust and precise mobile robot navigation with compact environment modeling

In this paper a new localization approach combining the metric and topological paradigm is presented. The main idea is to connect local metric maps by means of a global topological map. This allows a compact environment model which does not require global metric consistency and permits both precision and robustness. The method uses a 360 degree laser scanner in order to extract lines for the metric localization and doors, discontinuities and hallways for the topological approach. The approach has been widely tested in a 50/spl times/25 m portion of the institute building with the new fully autonomous robot Donald Duck. 25 randomly generated test missions were performed with a success ratio of 96% and a mean error at the goal point of 9 mm for an overall trajectory length of 1.15 km.
Control Strategy of Group Behavior for Internet of Things

With the development of the information techniques, Internet of Things has caused extensive concern. The burden of Internet of Things increases as the number of users rises. In order to ease the burden on Internet of Things and improve efficiency of user accessing the Internet of Things, this paper proposed a control strategy of group behavior. We count resources user interested in, and do cluster analysis with these resources. Through cluster analysis these users are divided into different groups, and the users in which have the similar interests called group interests. According to behavior characteristics of different groups, the resources which are group interests are stored in the buffer. On this basis, a control strategy of group behavior is described, and its performance is evaluated.
SurfacePhone: a mobile projection device for single- and multiuser everywhere tabletop interaction

To maintain a mobile form factor, the screen real estate of a mobile device canIn this paper we present SurfacePhone; a novel configuration of a projector phone which aligns the projector to project onto a physical surface to allow tabletop-like interaction in a mobile setup. The projection is created behind the upright standing phone and is touch and gesture-enabled. Multiple projections can be merged to create shared spaces for multi-user collaboration. We investigate this new setup, starting with the concept that we evaluated with a concept prototype. Furthermore we present our technical prototype, a mobile phone case with integrated projector that allows for the aforementioned interaction. We discuss its technical requirements and evaluate the accuracy of interaction in a second user study. We conclude with lessons learned and design guidelines.
A Comparative Study of Javanese Script Classification with GoogleNet, DenseNet, ResNet, VGG16 and VGG19

Purpose: Javanese script is a legacy of heritage or heritage in Indonesia originating from the island of Java needs to be preserved. Therefore, in this study, the classification and identification process of Javanese script letters will be carried out using the CNN method. The purpose of this research is to be able to build a model which can properly classify Javanese script, it can help in the process of recognizing letters in Javanese script easily.Methods: In this study, the Javanese script classification process has been used the transfer learning process of Convolutional Neural Network, namely GoogleNet, DenseNet, ResNet, VGG16 and VGG19. The purpose of using transfer learning is to improve the sequential CNN model, processing can be better and optimal because it utilizes a previously trained model.Result: The results obtained after testing in this study are using the transfer learning method, the GoogleNet model gets an accuracy of 88.75%, the DenseNet model gets an accuracy of 92%, the ResNet model gets an accuracy of 82.75%, the VGG16 model gets an accuracy of 99.25% and the VGG19 model gets an accuracy of 99.50%. Novelty: In previous studies, it is still very rare to discuss the Javanese script classification process using the CNN transfer learning method and which method is the most optimal for performing the Javanese script classification process. In this study, it had been resulted find an effective method to be able to carry out the Javanese script classification process properly and optimally.