Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure and Performance of Space-Time Block Code

This paper introduce the structure of STBC (space time block code) which is based on the crossing coding. First we introduce the Alamouti code, then we give the rules of the construct STBC. We also introduce the STTC in the 3GPP, which is the critical transmit diversity technology. After that we compare the performance of the different receive antennas and different modulation in the Rayleigh fading channel. From the simulation results we can draw the conclusions that the STBC could improve performance
Feeding behaviour of avian dispersers of mistletoe fruit in the Loskop Dam Nature Reserve, South Africa

The dispersal of three mistletoe species [Tapinanthus (formerly Loranthus) leendertziae, T. natalitius ssp. zeyheri and Viscum combreticola by birds was studied in the Loskop Dam Nature Reserve, South Africa. Eight of the 27 species of frugivorous birds present were observed feeding on mistletoe fruit. The yel-lowfronted tinker barbet Pogoniulus chrysoconus was the most important single disperser of mistletoes, consuming 64%, 80% and 94% of the fruit of the above mistletoe species respectively, and being behaviourally most suited to the dispersal of mistletoe seed. The other seven avian species were incidental mistletoe fruit eaters. Seasonal variations in mistletoe eating by different birds are mainly related to the preference for Tapinanthus fruit by species other than the tinker barbet. Three ways of handling mistletoe seeds are described: regurgitation (in more than 80% of the cases), defaecation and ‘pecking’. Very few interactions between birds occurred on mistletoe plants. No interspecific aggressi.
Preparation and Characterization of an Aromatic Polyimide and Its Use as a Selective Membrane for H2O2

Selectivity behavior to electroactive and non-electroactive substances of a polyimide prepared from 2,2'-dimethyl-4,4'-diaminobiphenyl and the corresponding dianhydride was examined by electrochemical methods. From the excellent electrochemical findings obtained, it was observed that polyimide film was only permeable to hydrogen peroxide among the substances examined. Therefore, it is claimed that the mentioned polymeric film can be successfully used as a hydrogen peroxide-selective membrane in the presence of electroactive and non-electroactive interferents.
Quality Estimation of the Interpolation of Missing Speech Signal Segments

New method for approximation of intensity and period of fundamental frequency characteristics of speech signals is proposed and incorporated in algorithm of restoration of speech signal distorted by lengthy impulsive noise or gap. The suitability of presented restoration technique is judged by evaluating quality of restored speech signal. The quality is estimated using perceptual evaluation of speech quality (PESQ) algorithm that is based on ITU recommendation P.862. Shown that proposed method is more accurate in restoration of distorted speech segment where characteristics of speech signal have non-linear change in time. Ill. 3, bibl. 8 (in English; summaries in English, Russian and Lithuanian).
Bacterial adhesion and biofilms on surfaces

Bacterial adhesion has become a significant problem in industry and in the domicile, and much research has been done for deeper understanding of the processes involved. A generic biological model of bacterial adhesion and population growth called the bacterial biofilm growth cycle, has been described and modified many times. The biofilm growth cycle encompasses bacterial adhesion at all levels, starting with the initial physical attraction of bacteria to a substrate, and ending with the eventual liberation of cell clusters from the biofilm matrix. When describing bacterial adhesion one is simply describing one or more stages of biofilm development, neglecting the fact that the population may not reach maturity. This article provides an overview of bacterial adhesion, cites examples of how bac- terial adhesion afiects industry and summarises methods and instrumentation used to improve our understanding of the adhesive prop- erties of bacteria.
Indices of Nutritional Status in Cottontail Rabbits Fed Controlled Diets

Forty-two captive cottontail rabbits (Sylvilagus floridanus) were used to evaluate indices of nutritional status. They were fed either ad libitum or 25 percent restricted diets for 6 weeks after which one-half of each group was placed on the opposite diet for 3 weeks. Nutritional restriction for 6 weeks caused a reduction in body weight (P < 0.01). Rabbits switched to ad libitum diets for 3 weeks gained weight, whereas those switched to restricted diets lost weight (P < 0.01). Blood urea nitrogen (BUN) levels were higher in rabbits on restricted diets than in those on ad libitum diets for the last 3 weeks, whereas no significant differences were found in serum cholesterol levels. Recent nutritional restriction (3 weeks) significantly (P < 0.01) reduced the fat content of bone marrow. J. WILDL. MANAGE. 42(1):154-158 The need to determine the nutritional status of animal populations often arises in wildlife management. Various physiological indices have been employed for this purpose. One of the first was fat content of femur bone marrow (Cheatum 1949). In adult mammals, bone marrow performs an important function of fat storage; in long bones, marrow receives abundant vascularization and is very responsive to and reflective of nutritional status. While there have been extensive investigations of the use of bone marrow fat as an index of nutritional status for large mammals in the field (Riney 1955, Greer 1968, Neiland 1970), comparable studies of small mammals and controlled experimentation on responses of marrow fat to different nutritional levels are lacking. Recently, more precise, accurate, and responsive indices of nutritional status have been developed as the need for more intensive management of our wildlife resources has occurred. In this respect, serum cholesterol (Coblentz 1975) and BUN (Kirkpatrick et al. 1975) have been employed in studies with white-tailed deer (Odocoileus virginianus). The objective of this experiment was to determine the value of serum cholesterol, BUN, and fat content of femur and tibia bone marrow as physiological indices of nutritional status in cottontail rab-
A Survey on Text Simplification

Text Simplification (TS) aims to reduce the linguistic complexity of content to make it easier to understand. Research in TS has been of keen interest, especially as approaches to TS have shifted from manual, hand-crafted rules to automated simplification. This survey seeks to provide a comprehensive overview of TS, including a brief description of earlier approaches used, discussion of various aspects of simplification (lexical, semantic and syntactic), and latest techniques being utilized in the field. We note that the research in the field has clearly shifted towards utilizing deep learning techniques to perform TS, with a specific focus on developing solutions to combat the lack of data available for simplification. We also include a discussion of datasets and evaluations metrics commonly used, along with discussion of related fields within Natural Language Processing (NLP), like semantic similarity.
A Comparison of Mixed Multiscale Finite Element Methods for Multiphase Transport in Highly Heterogeneous Media

In this study, we systemically review and compare two mixed multiscale finite element methods (MMsFEM) for multiphase transport in highly heterogeneous media. In particular, we will consider the mixed multiscale finite element method using limited global information, simply denoted by MMsFEM, and the mixed generalized multiscale finite element method (MGMsFEM) with residual driven online multiscale basis functions. Both methods are within the framework of MMsFEM, where the pressure equation is solved in the coarse grids with carefully constructed multiscale basis functions for the velocity. The multiscale basis functions in both methods include local and global media information. In terms of MsFEM using limited global information, only one multiscale basis function is utilized in each local neighborhood, while multiple bases are used in MGMsFEM. We will test and compare these two methods using the benchmark three‐dimensional SPE10 model. A range of coarse grid sizes and different combinations of basis functions (offline and online) will be considered with CPU time reported for each case. In our numerical experiments, we observe good accuracy by the two above methods. Finally, we will discuss and compare the advantages and disadvantages of the two methods in terms of accuracy and computational costs.
Assessing the Quality-of-Experience of Adaptive Bitrate Video Streaming

The diversity of video delivery pipeline poses a grand challenge to the evaluation of adaptive bitrate (ABR) streaming algorithms and objective quality-of-experience (QoE) models. Here we introduce so-far the largest subject-rated database of its kind, namely WaterlooSQoE-IV, consisting of 1350 adaptive streaming videos created from diverse source contents, video encoders, network traces, ABR algorithms, and viewing devices. We collect human opinions for each video with a series of carefully designed subjective experiments. Subsequent data analysis and testing/comparison of ABR algorithms and QoE models using the database lead to a series of novel observations and interesting findings, in terms of the effectiveness of subjective experiment methodologies, the interactions between user experience and source content, viewing device and encoder type, the heterogeneities in the bias and preference of user experiences, the behaviors of ABR algorithms, and the performance of objective QoE models. Most importantly, our results suggest that a better objective QoE model, or a better understanding of human perceptual experience and behaviour, is the most dominating factor in improving the performance of ABR algorithms, as opposed to advanced optimization frameworks, machine learning strategies or bandwidth predictors, where a majority of ABR research has been focused on in the past decade. On the other hand, our performance evaluation of 11 QoE models shows only a moderate correlation between state-of-the-art QoE models and subjective ratings, implying rooms for improvement in both QoE modeling and ABR algorithms. The database is made publicly available at: \url{this https URL}.
Distributed Vehicle Grid Integration Over Communication and Physical Networks

This paper proposes a distributed framework for vehicle grid integration (VGI) taking into account the communication and physical networks. To this end, we model the electric vehicle (EV) behaviour that includes time of departure, time of arrival, state of charge, required energy, and its objectives, e.g., avoid battery degradation. Next, we formulate the centralised day ahead distribution market (DADM) which explicitly represents the physical system, supports unbalanced three phase networks with delta and wye connections, and incorporates the charging needs of EVs. The solution of the centralised market requires knowledge of EV information in terms of desired energy, departure and arrival times that EV owners are reluctant in providing. Moreover, the computational effort required to solve the DADM in cases of numerous EVs is very intensive. As such, we propose a distributed solution of the DADM clearing mechanism over a time-varying communication network. We illustrate the proposed VGI framework through the 13-bus, 33- bus, and 141-bus distribution feeders.
ConfEx: A Framework for Automating Text-based Software Configuration Analysis in the Cloud

Modern cloud services have complex architectures, often comprising many software components, and depend on hundreds of configurations parameters to function correctly, securely, and with high performance. Due to the prevalence of open-source software, developers can easily deploy services using third-party software without mastering the configurations of that software. As a result, configuration errors (i.e., misconfigurations) are among the leading causes of service disruptions and outages. While existing cloud automation tools ease the process of service deployment and management, support for detecting misconfigurations in the cloud has not been addressed thoroughly, likely due to the lack of frameworks suitable for consistent parsing of unstandardized configuration files. This paper introduces ConfEx, a framework that enables discovery and extraction of text-based software configurations in the cloud. ConfEx uses a novel vocabulary-based technique to identify configuration files in cloud system instances with unlabeled content. To extract the information in these files, ConfEx leverages existing configuration parsers and post-processes the extracted data for analysis. We show that ConfEx achieves over 99% precision and 100% recall in identifying configuration files on 7805 popular Docker Hub images. Using two applied examples, we demonstrate that ConfEx also enables detecting misconfigurations in the cloud via existing tools that are designed for configurations represented as key-value pairs, revealing 184 errors in public Docker Hub images.
Controlling Dialogue Generation with Semantic Exemplars

Dialogue systems pretrained with large language models generate locally coherent responses, but lack fine-grained control over responses necessary to achieve specific goals. A promising method to control response generation is exemplar-based generation, in which models edit exemplar responses that are retrieved from training data, or hand-written to strategically address discourse-level goals, to fit new dialogue contexts. We present an Exemplar-based Dialogue Generation model, EDGE, that uses the semantic frames present in exemplar responses to guide response generation. We show that controlling dialogue generation based on the semantic frames of exemplars improves the coherence of generated responses, while preserving semantic meaning and conversation goals present in exemplar responses.
Generating Adjacency Matrix for Video-Query based Video Moment Retrieval

In this paper, we continue our work on Video-Query based Video Moment retrieval task. Based on using graph convolution to extract intra-video and inter-video frame features, we improve the method by using similarity-metric based graph convolution, whose weighted adjacency matrix is achieved by calculating similarity metric between features of any two different timesteps in the graph. Experiments on ActivityNet v1.2 and Thumos14 dataset shows the effectiveness of this improvement, and it outperforms the state-of-the-art methods.
Strong exciton-photon coupling in large area MoSe2 and WSe2 heterostructures fabricated from two-dimensional materials grown by chemical vapor deposition

Two-dimensional semiconducting transition metal dichalcogenides embedded in optical microcavities in the strong exciton-photon coupling regime may lead to promising applications in spin and valley addressable polaritonic logic gates and circuits. One significant obstacle for their realization is the inherent lack of scalability associated with the mechanical exfoliation commonly used for fabrication of two-dimensional materials and their heterostructures. Chemical vapor deposition offers an alternative scalable fabrication method for both monolayer semiconductors and other two-dimensional materials, such as hexagonal boron nitride. Observation of the strong light-matter coupling in chemical vapor grown transition metal dichalcogenides has been demonstrated so far in a handful of experiments with monolayer molybdenum disulfide and tungsten disulfide. Here we instead demonstrate the strong exciton-photon coupling in microcavities composed of large area transition metal dichalcogenide/hexagonal boron nitride heterostructures made from chemical vapor deposition grown molybdenum diselenide and tungsten diselenide encapsulated on one or both sides in continuous few-layer boron nitride films also grown by chemical vapor deposition. These transition metal dichalcogenide/hexagonal boron nitride heterostructures show high optical quality comparable with mechanically exfoliated samples, allowing operation in the strong coupling regime in a wide range of temperatures down to 4 Kelvin in tunable and monolithic microcavities, and demonstrating the possibility to successfully develop large area transition metal dichalcogenide based polariton devices.
Model-based Automated Testing of Mobile Applications: An Industrial Case Study

Automatic testing of mobile applications has been a well-researched area in recent years. However, testing in industry is still a very manual practice, as research results have not been fully transferred and adopted. Considering mobile applications, manual testing has the additional burden of adequate testing posed by a large number of available devices and different configurations, as well as the maintenance and setup of such devices.In this paper, we propose and evaluate the use of a model-based test generation approach, where generated tests are executed on a set of cloud-hosted real mobile devices. By using a model-based approach we generate dynamic, less brittle, and implementation simple test cases. The test execution on multiple real devices with different configurations increase the confidence in the implementation of the system under test. Our evaluation shows that the used approach produces a high coverage of the parts of the application related to user interactions. Nevertheless, the inclusion of external services in test generation is required in order to additionally increase the coverage of the complete application. Furthermore, we present the lessons learned while transferring and implementing this approach in an industrial context and applying it to the real product.
On Qualitative Shape Inferences: a journey from geometry to topology

Shape inference is classically ill-posed, because it involves a map from the (2D) image domain to the (3D) world. Standard approaches regularize this problem by either assuming a prior on lighting and rendering or restricting the domain, and develop differential equations or optimization solutions. While elegant, the solutions that emerge in these situations are remarkably fragile. We exploit the observation that people infer shape qualitatively; that there are quantitative differences between individuals. The consequence is a topological approach based on critical contours and the Morse-Smale complex. This paper provides a developmental review of that theory, emphasizing the motivation at different stages of the research.
PhysCap

Marker-less 3D human motion capture from a single colour camera has seen significant progress. However, it is a very challenging and severely ill-posed problem. In consequence, even the most accurate state-of-the-art approaches have significant limitations. Purely kinematic formulations on the basis of individual joints or skeletons, and the frequent frame-wise reconstruction in state-of-the-art methods greatly limit 3D accuracy and temporal stability compared to multi-view or marker-based motion capture. Further, captured 3D poses are often physically incorrect and biomechanically implausible, or exhibit implausible environment interactions (floor penetration, foot skating, unnatural body leaning and strong shifting in depth), which is problematic for any use case in computer graphics. We, therefore, present PhysCap, the first algorithm for physically plausible, real-time and marker-less human 3D motion capture with a single colour camera at 25 fps. Our algorithm first captures 3D human poses purely kinematically. To this end, a CNN infers 2D and 3D joint positions, and subsequently, an inverse kinematics step finds space-time coherent joint angles and global 3D pose. Next, these kinematic reconstructions are used as constraints in a real-time physics-based pose optimiser that accounts for environment constraints (e.g., collision handling and floor placement), gravity, and biophysical plausibility of human postures. Our approach employs a combination of ground reaction force and residual force for plausible root control, and uses a trained neural network to detect foot contact events in images. Our method captures physically plausible and temporally stable global 3D human motion, without physically implausible postures, floor penetrations or foot skating, from video in real time and in general scenes. PhysCap achieves state-of-the-art accuracy on established pose benchmarks, and we propose new metrics to demonstrate the improved physical plausibility and temporal stability.
On Measuring Divergence for Magnetic Field Modeling

A physical magnetic field has a divergence of zero. Numerical error in constructing a model field and computing the divergence, however, introduces a finite divergence into these calculations. A popular metric for measuring divergence is the average fractional flux . We show that scales with the size of the computational mesh, and may be a poor measure of divergence because it becomes arbitrarily small for increasing mesh resolution, without the divergence actually decreasing. We define a modified version of this metric that does not scale with mesh size. We apply the new metric to the results of DeRosa et al., who measured for a series of nonlinear force-free field models of the coronal magnetic field based on solar boundary data binned at different spatial resolutions. We compute a number of divergence metrics for the DeRosa et al. data and analyze the effect of spatial resolution on these metrics using a nonparametric method. We find that some of the trends reported by DeRosa et al. are due to the intrinsic scaling of . We also find that different metrics give different results for the same data set and therefore there is value in measuring divergence via several metrics.
A Simple Proof of Optimal Approximations

The fundamental result of Li, Long, and Srinivasan on approximations of set systems has become a key tool across several communities such as learning theory, algorithms, combinatorics and data analysis (described as `the pinnacle of a long sequence of papers'). The goal of this paper is to give a simpler, self-contained, modular proof of this result for finite set systems. The only ingredient we assume is the standard Chernoff's concentration bound. This makes the proof accessible to a wider audience, readers not familiar with techniques from statistical learning theory, and makes it possible to be covered in a single self-contained lecture in an algorithms course.
Language Models as Knowledge Bases: On Entity Representations, Storage Capacity, and Paraphrased Queries

Pretrained language models have been suggested as a possible alternative or complement to structured knowledge bases. However, this emerging LM-as-KB paradigm has so far only been considered in a very limited setting, which only allows handling 21k entities whose name is found in common LM vocabularies. Furthermore, a major benefit of this paradigm, i.e., querying the KB using natural language paraphrases, is underexplored. Here we formulate two basic requirements for treating LMs as KBs: (i) the ability to store a large number facts involving a large number of entities and (ii) the ability to query stored facts. We explore three entity representations that allow LMs to handle millions of entities and present a detailed case study on paraphrased querying of facts stored in LMs, thereby providing a proof-of-concept that language models can indeed serve as knowledge bases.