Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling local and global phenomena with sparse Gaussian processes

Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3) scaling in computational time to O(nm2). Thus far, work has concentrated on models with one covariance function. However, in many practical situations additive models with multiple covariance functions may perform better, since the data may contain both long and short length-scale phenomena. The long length-scales can be captured with global sparse approximations, such as fully independent conditional (FIC), and the short length-scales can be modeled naturally by covariance functions with compact support (CS). CS covariance functions lead to naturally sparse covariance matrices, which are computationally cheaper to handle than full covariance matrices. In this paper, we propose a new sparse Gaussian process model with two additive components: FIC for the long length-scales and CS covariance function for the short length-scales. We give theoretical and experimental results and show that under certain conditions the proposed model has the same computational complexity as FIC. We also compare the model performance of the proposed model to additive models approximated by fully and partially independent conditional (PIC). We use real data sets and show that our model outperforms FIC and PIC approximations for data sets with two additive phenomena.
und mathematische Modellierung Discrete surfaces for architectural design

Geometric problems originating in architecture can lead to interesting research and results in geometry processing, computer aided geometric design, and discrete differential geometry. In this article we survey this development and consider an important problem of this kind: Discrete surfaces (meshes) which admit a multi-layered geometric support structure. It turns out that such meshes can be elegantly studied via the concept of parallel mesh. Discrete versions of the network of principal curvature lines turn out to be parallel to approximately spherical meshes. Both circular meshes and the conical meshes considered only recently are instances of this meta-theorem. We dicuss properties and interrelations of circular and conical meshes, and also their connections to meshes in static equilibrium and discrete minimal surfaces. We conclude with a list of research problems in geometry which are related to architectural design.
Efficacy of nonselective optogenetic control of the medial septum over hippocampal oscillations: the influence of speed and implications for cognitive enhancement

Optogenetics holds great promise for both the dissection of neural circuits and the evaluation of theories centered on the temporal organizing properties of oscillations that underpin cognition. To date, no studies have examined the efficacy of optogenetic stimulation for altering hippocampal oscillations in freely moving wild‐type rats, or how these alterations would affect performance on behavioral tasks. Here, we used an AAV virus to express ChR2 in the medial septum (MS) of wild‐type rats, and optically stimulated septal neurons at 6 Hz and 30 Hz. We measured the corresponding effects of these stimulations on the oscillations of the MS and hippocampal subfields CA1 and CA3 in three different contexts: (1) With minimal movement while the rats sat in a confined chamber; (2) Explored a novel open field; and (3) Learned and performed a T‐maze behavioral task. While control yellow light stimulation did not affect oscillations, 6‐Hz blue light septal stimulations altered hippocampal theta oscillations in a manner that depended on the animal's mobility and speed. While the 30 Hz blue light septal stimulations only altered theta frequency in CA1 while the rat had limited mobility, it robustly increased the amplitude of hippocampal signals at 30 Hz in both regions in all three recording contexts. We found that animals were more likely to make a correct choice during Day 1 of T‐maze training during both MS stimulation protocols than during control stimulation, and that improved performance was independent of theta frequency alterations.
Frequent Subtree Mining - An Overview

Mining frequent subtrees from databases of labeled trees is a new research field that has many practical applications in areas such as computer networks, Web mining, bioinformatics, XML document mining, etc. These applications share a requirement for the more expressive power of labeled trees to capture the complex relations among data entities. Although frequent subtree mining is a more difficult task than frequent itemset mining, most existing frequent subtree mining algorithms borrow techniques from the relatively mature association rule mining area. This paper provides an overview of a broad range of tree mining algorithms. We focus on the common theoretical foundations of the current frequent subtree mining algorithms and their relationship with their counterparts in frequent itemset mining. When comparing the algorithms, we categorize them according to their problem definitions and the techniques employed for solving various subtasks of the subtree mining problem. In addition, we also present a thorough performance study for a representative family of algorithms.
A reliability-based computation method for the weight distribution of LDPC codes using the probabilistic algorithm

In the analysis of maximum-likelihood decoding performance of low-density parity-check (LDPC) codes, the weight distribution is an important factor. Some methods based on the error impluse method have presented in order to estimate the weight distribution of LDPC codes. However, these methods have no scheme which determine the number of codeword in LDPC codes. In this paper, we propose a reliability-based computation method for the weight distribution of LDPC codes using the probabilistic algorithm. Using the proposed method, we can determine the weight distribution of LDPC codes with small failure probability.
Genetic signals of origin, spread, and introgression in a large sample of maize landraces

The last two decades have seen important advances in our knowledge of maize domestication, thanks in part to the contributions of genetic data. Genetic studies have provided firm evidence that maize was domesticated from Balsas teosinte (Zea mays subspecies parviglumis), a wild relative that is endemic to the mid- to lowland regions of southwestern Mexico. An interesting paradox remains, however: Maize cultivars that are most closely related to Balsas teosinte are found mainly in the Mexican highlands where subspecies parviglumis does not grow. Genetic data thus point to primary diffusion of domesticated maize from the highlands rather than from the region of initial domestication. Recent archeological evidence for early lowland cultivation has been consistent with the genetics of domestication, leaving the issue of the ancestral position of highland maize unresolved. We used a new SNP dataset scored in a large number of accessions of both teosinte and maize to take a second look at the geography of the earliest cultivated maize. We found that gene flow between maize and its wild relatives meaningfully impacts our inference of geographic origins. By analyzing differentiation from inferred ancestral gene frequencies, we obtained results that are fully consistent with current ecological, archeological, and genetic data concerning the geography of early maize cultivation.
Multiple bits distributed moving horizon state estimation for wireless sensor networks

Wireless sensor networks distributed signal processing has to operate under stringent energy and bandwidth limitations. Usually, the observations need to be quantized before they are sent to fusion center (FC). This paper we introduce a multiple bits distributed moving Horizon state estimation approach based on a multiple state single output Gaussian-Markov model. Each sensor node has a thresholds book, then the sensors quantize their measurements to several bits by using the thresholds book which are sent to fusion center. After receiving these information, fusion center make final estimation for system states. Compared with single bit distributed moving horizon state estimation (DMHE), this method ensures that FC need not to send the estimate information back to sensor nodes and provides higher precision of state estimation.
Hierarchical optical switching: a node-level analysis

We consider hybrid optical devices consisting of a waveband (transparent optical) and a wavelength (opaque OEO) switch. Such hybrid devices are suitable for supporting hierarchical optical paths (wavelength and waveband paths). We study the node-level cost-performance tradeoffs using both analytical models and simulations. The results demonstrate a significant cost reduction that could be achieved for a moderately small reduction of throughput.
Popularity-driven coordinated caching in Named Data Networking

The built-in caching capability of future Named Data Networking (NDN) promises to enable effective content distribution at a global scale without requiring special infrastructure. The aim of this work is to design efficient caching schemes in NDN to achieve better performance at both the network layer and application layer. With the specific objective of minimizing the inter-ISP (Internet Service Provider) traffic and average access latency, we first formulate the optimization problems for different objectives and then solve them to obtain the optimal replica placement. Then we develop popularity-driven caching schemes which dynamically place the replicas in the caches on the en-route path in a coordination fashion. Simulation results show that the performances of our caching algorithms are much closer to the optimum and outperform the widely used schemes in terms of the inter-ISP traffic and the average number of access hops. Finally, we thoroughly evaluate the impact of several important design issues such as network topology, cache size, access pattern and content popularity on the caching performance and demonstrate that the proposed schemes are effective, stable, scalable and with reasonably light overhead.
Planar <formula formulatype="inline"><tex Notation="TeX">$Ku$</tex> </formula>-Band 4<formula formulatype="inline"><tex Notation="TeX">$\,\times\,$</tex> </formula>4 Nolen Matrix in SIW Technology

In this paper, a 4 × 4 Nolen matrix beam-forming network for multibeam antenna applications is designed and demonstrated at 12.5-GHz center frequency. The structure is implemented using substrate integrated waveguide (SIW) technology for its attractive advantages including compact size, low loss, light weight, and planar form well suitable for high-density integration with other microwave and millimeter-wave planar integrated circuits. SIW cruciform couplers are used as fundamental building blocks for their wide range of coupling factors and their specific topology well adapted to the serial feeding topology of a Nolen matrix. The network performances are investigated over a 500-MHz frequency bandwidth ranging from 12.25 to 12.75 GHz. The matrix definition based on SIW cruciform couplers is similar to its microstrip counterpart in terms of coupling factors and phase delays. The whole network is fabricated. Measured results are in good agreement with the theoretical predictions, thus validating the proposed design concept. Using this matrix with a four radiating elements array antenna enables us to investigate the impact of the proposed matrix on the beam pointing angles versus frequency.
News Borrowing Revisited: A 50-Year Perspective

Analyzing 50 years’ of New York Times international news coverage (N = 20,765), this study extends research on the “shrinking international news hole,” levels of press freedom, agent (e.g., Times correspondent), and “borrowed” news—information gleaned from local media, including social media. Data show a recent, growing role for social media and an increase in news borrowing, while foreign coverage declined; slight resurgence in foreign coverage during the last quarter-century; reduced wire copy use but increased correspondent news borrowing; and increased coverage of but decreased news borrowing in news from non-free nations. Borrowing from social media was greatest in non-free nations.
Design of Experiments to Study the Impact of Process Parameters on Droplet Size and Development of Non-Invasive Imaging Techniques in Tablet Coating

Atomisation of an aqueous solution for tablet film coating is a complex process with multiple factors determining droplet formation and properties. The importance of droplet size for an efficient process and a high quality final product has been noted in the literature, with smaller droplets reported to produce smoother, more homogenous coatings whilst simultaneously avoiding the risk of damage through over-wetting of the tablet core. In this work the effect of droplet size on tablet film coat characteristics was investigated using X-ray microcomputed tomography (XμCT) and confocal laser scanning microscopy (CLSM). A quality by design approach utilising design of experiments (DOE) was used to optimise the conditions necessary for production of droplets at a small (20 μm) and large (70 μm) droplet size. Droplet size distribution was measured using real-time laser diffraction and the volume median diameter taken as a response. DOE yielded information on the relationship three critical process parameters: pump rate, atomisation pressure and coating-polymer concentration, had upon droplet size. The model generated was robust, scoring highly for model fit (R2 = 0.977), predictability (Q2 = 0.837), validity and reproducibility. Modelling confirmed that all parameters had either a linear or quadratic effect on droplet size and revealed an interaction between pump rate and atomisation pressure. Fluidised bed coating of tablet cores was performed with either small or large droplets followed by CLSM and XμCT imaging. Addition of commonly used contrast materials to the coating solution improved visualisation of the coating by XμCT, showing the coat as a discrete section of the overall tablet. Imaging provided qualitative and quantitative evidence revealing that smaller droplets formed thinner, more uniform and less porous film coats.
Functional prediction of hypothetical proteins in human adenoviruses

Assigning functional information to hypothetical proteins in virus genomes is crucial for gaining insight into their proteomes. Human adenoviruses are medium sized viruses that cause a range of diseases. Their genomes possess proteins with uncharacterized function known as hypothetical proteins. Using a wide range of protein function prediction servers, functional information was obtained about these hypothetical proteins. A comparison of functional information obtained from these servers revealed that some of them produced functional information, while others provided little functional information about these human adenovirus hypothetical proteins. The PFP, ESG, PSIPRED, 3d2GO, and ProtFun servers produced the most functional information regarding these hypothetical proteins.
Cell Counting in Human Endobronchial Biopsies - Disagreement of 2D versus 3D Morphometry

Question Inflammatory cell numbers are important endpoints in clinical studies relying on endobronchial biopsies. Assumption-based bidimensional (2D) counting methods are widely used, although theoretically design-based stereologic three-dimensional (3D) methods alone offer an unbiased quantitative tool. We assessed the method agreement between 2D and 3D counting designs in practice when applied to identical samples in parallel. Materials and Methods Biopsies from segmental bronchi were collected from healthy non-smokers (n = 7) and smokers (n = 7), embedded and sectioned exhaustively. Systematic uniform random samples were immunohistochemically stained for macrophages (CD68) and T-lymphocytes (CD3), respectively. In identical fields of view, cell numbers per volume unit (NV) were assessed using the physical disector (3D), and profiles per area unit (NA) were counted (2D). For CD68+ cells, profiles with and without nucleus were separately recorded. In order to enable a direct comparison of the two methods, the zero-dimensional CD68+/CD3+-ratio was calculated for each approach. Method agreement was tested by Bland-Altmann analysis. Results In both groups, mean CD68+/CD3+ ratios for NV and NA were significantly different (non-smokers: 0.39 and 0.68, p<0.05; smokers: 0.49 and 1.68, p<0.05). When counting only nucleated CD68+ profiles, mean ratios obtained by 2D and 3D counting were similar, but the regression-based Bland-Altmann analysis indicated a bias of the 2D ratios proportional to their magnitude. This magnitude dependent deviation differed between the two groups. Conclusions 2D counts of cell and nuclear profiles introduce a variable size-dependent bias throughout the measurement range. Because the deviation between the 3D and 2D data was different in the two groups, it precludes establishing a ‘universal conversion formula’.
MQuery: Fast Graph Query via Semantic Indexing for Mobile Context

Mobile is becoming a ubiquitous platform for context-aware intelligent computing. One fundamental but usually ignored issue is how to efficiently manage (e.g., index and query) the mobile context data. To this end, we present a unified framework and have developed a toolkit, referred to as MQuery. More specifically, the mobile context data is represented in the standard RDF (Resource Description Framework) format. We propose a compressed-index method which takes less than 50% of the memory cost (of the traditional method) to index the context data. Four query interfaces have been developed for efficiently querying the context data including: instance query, neighbor query, shortest path query, and connection subgraph query. Experimental results on two real datasets demonstrate the efficiency of MQuery.
A new approach for off-line handwritten Arabic word recognition using KNN classifier

Due to similarities between Arabic letters, and the various writing styles employed, recognition of Arabic handwritten text can be difficult. In this paper, an off-line Arabic handwritten word recognition system is proposed, in which technical details are presented in terms of three stages, i.e. preprocessing, feature extraction and classification. Firstly, words are segmented from input scripts and also normalized in size. Secondly, each segmented word is divided into overlapping blocks. Absolute mean values computed for each block of segmented words constitutes a feature vector. Finally, the resulting feature vectors are used to classify the words using the K nearest Neighbour classifier (KNN). The proposed system has been successfully tested on the IFN/ENIT database consisting of 32492 Arabic handwritten words which are written by more than 1000 different writers. Experimental results show a good recognition rate when compared with other methods.
An extended Evolving Spiking Neural Network model for spatio-temporal pattern classification

This paper proposes a new model of an Evolving Spiking Neural Network (ESNN) for spatio-temporal data (STD) classification problems. The proposed ESNN model incorporates an additional layer for capturing both spatial and temporal components of the STD and then transforms them into high dimensional spiking patterns. These patterns are learned and classified in the evolving classification layer of the ESNN. A fast time-to-first-spike learning algorithm is used that enables the new model to be more suitable for learning from the STD streams in an adaptive and incremental manner. The proposed method is evaluated on a benchmark sign language video that is spatio-temporal in nature. The results show that the proposed method is able to capture important spatio-temporal information from the STD stream. This results in significantly higher classification accuracy than the traditional time-delay MLP neural network model. Future directions for the development of ESNN models for STD are discussed.
History, Location, and Species Matter: Insights for Human–Wildlife Conflict Mitigation From India

ABSTRACT Preventing loss of crops, threats to livestock, damage to property, and human injury and death attributed to wildlife are conservation challenges. We surveyed over 5,000 households around 11 reserves in India to examine these issues and mitigation efforts. Crops were lost by 71% of households, livestock by 17%, and human injury and death were reported by 3% of households (losses attributed to 32 species). Households deployed 12 mitigation measures with nighttime watching, scare devices, and fencing used the most. A household’s conflict history (>20 years for livestock loss, 10–20 years for crop loss), proximity to reserves, and crops grown or livestock owned were associated with higher mitigation use. There were differences across reserves, with households in Rajasthan least likely to use mitigation. Crop protection (88%) was more likely than livestock protection (32%). Investments in conflict mitigation should consider the history, location, species, socioeconomic variations among households, and differences in regional policies.
Graspit! A versatile simulator for robotic grasping

A robotic grasping simulator, called Graspit! , is presented as versatile tool for the grasping community. The focus of the grasp analysis has been on force-closure grasps, which are useful for pick-and-place type tasks. This work discusses the different types of world elements and the general robot definition, and presented the robot library. The paper also describes the user interface of Graspit! and present the collision detection and contact determination system. The grasp analysis and visualization method were also presented that allow a user to evaluate a grasp and compute optimal grasping forces. A brief overview of the dynamic simulation system was provided.
Comparisons Instead of Ratings: Towards More Stable Preferences

More and more personalization systems are emerging to reduce the information overload of the Web. As a result, it has become vital to model users' preferences accurately. Our focus lies in the quality of users' expressed preferences, in terms of reliability and stability through time. Today, users are often brought to express their preferences through ratings on a multi-point scale. However, several studies have highlighted problems with ratings. We propose a new preference modality whereby users compare items two-by two ("I prefer x to y"). This initial work on comparisons shows that users are in favor of this new preference mechanism and that comparisons are almost 20% more stable over time than those conveyed through ratings, thus more reliable. These encouraging findings let us think that comparisons may lead to a better user modeling and an increase in the quality of personalization services, such as recommender systems.
Mechatronic-oriented Engineering of Manufacturing Systems Taking the Example of the Body Shop

In order to cope with the various challenges in the automotive industry, new and integrated strategies are required. In this way, the concept of mechatronic-oriented digital production engineering is introduced, taking the example of the body shop. With the focus on the overall lifecycle of a manufacturing system a central planning and data integration platform represented by a mechatronic plant model is established. This cross-domain and 3D-oriented model, which includes mechanical, electrical, and information-technical plant data, assumes different functions in the course of a complete production engineering project: not only does it form the basis for the accomplishment of virtual startups, it is also profitably used for maintenance services in the real factory.