Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple target tracking using particle filter based multi-scan joint probabilistic data association filter

In this paper, a particle filter based multi-scan JPDA filter is proposed to deal with the data association problem in multiple target tracking. In the proposed multi-scan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multi-scan JPDA algorithm examines the joint association events in a multi-scan sliding window and calculates the marginal posterior probability based on the multi-scan joint association events. The proposed algorithm is illustrated via an example involving tracking of two slowly maneuvering targets based on resolved measurements.
Image restoration from multiple copies: A GMM based method

Recovery of original images from degraded and noisy observations is considered an important task in image processing. Recently, a Piece-wise Linear Estimator (PLE) was proposed for image recovery by using Gaussian Mixture Model (GMM) as a prior for image patches. Despite having much lesser computational requirements, this method yields comparable or better results when compared with the widely used sparse representation techniques for image restoration. In many situations, we might have access to multiple degraded copies of the same image, and would like to exploit the correlation among them for better image recovery. In this work, we extend the GMM based method to the multiple observations scenario, where we estimate the original image by utilizing the collective information available from all degraded copies.
Numerical Hydrodynamics in General Relativity

The current status of numerical solutions for the equations of ideal general relativistic hydrodynamics is reviewed. With respect to an earlier version of the article, the present update provides additional information on numerical schemes, and extends the discussion of astrophysical simulations in general relativistic hydrodynamics. Different formulations of the equations are presented, with special mention of conservative and hyperbolic formulations well-adapted to advanced numerical methods. A large sample of available numerical schemes is discussed, paying particular attention to solution procedures based on schemes exploiting the characteristic structure of the equations through linearized Riemann solvers. A comprehensive summary of astrophysical simulations in strong gravitational fields is presented. These include gravitational collapse, accretion onto black holes, and hydrodynamical evolutions of neutron stars. The material contained in these sections highlights the numerical challenges of various representative simulations. It also follows, to some extent, the chronological development of the field, concerning advances on the formulation of the gravitational field and hydrodynamic equations and the numerical methodology designed to solve them.
FlexStylus: Leveraging Bend Input for Pen Interaction

FlexStylus, a flexible stylus, detects deformation of the barrel as a vector with both a rotational and an absolute value, providing two degrees of freedom with the goal of improving the expressivity of digital art using a stylus device. We outline the construction of the prototype and the principles behind the sensing method, which uses a cluster of four fibre-optic based deformation sensors. We propose interaction techniques using the FlexStylus to improve menu navigation and tool selection. Finally, we describe a study comparing users' ability to match a changing target value using a commercial pressure stylus and the FlexStylus' absolute deformation. When using the FlexStylus, users had a significantly higher accuracy overall. This suggests that deformation may be a useful input method for future work considering stylus augmentation.
Procrastination Beats Prevention: Timely Sufficient Persistence for Efficient Crash Resilience

Preserving the integrity of application data across updates in the presence of failure is an essential function of computing systems, and byte-addressable non-volatile memory (NVM) broadens the range of fault-tolerance strategies that implement it. NVM invites database systems to manipulate durable data directly via load and store instructions, but overheads due to the widely used mechanisms that ensure consistent recovery from failures impair performance, e.g., the logging overheads of transactions. We introduce the concept of Timely Sucient Persistence (TSP) mechanisms, which is relevant to both conventional and emerging computer architectures. For a broad spectrum of faulttolerance requirements, satisfactory TSP mechanisms typically involve lower overheads during failure-free operation than their non-TSP counterparts; hardware and OS support can facilitate TSP mechanisms. We present TSP variants of programs representing two very di↵erent classes of sharedmemory multi-threaded software that store application data in persistent heaps: The first employs conventional mutexes for isolation, and TSP substantially reduces the overhead of a fault-tolerance mechanism based on fine-grained logging. The second class of software employs lock-free and wait-free algorithms; remarkably, TSP is very easy to retrofit onto a non-resilient design and enjoys zero runtime overhead . E xtensive experiments confirm that TSP yields robust crash resilience with substantially reduced overhead.
Multimodal information access across multiple devices

Next generation applications will support a variety of modalities that will be provided by more than one device. Users can carry multiple devices with them or just use fixed devices in their environment. The applications will adapt themselves with respect to rendering according to changes in the user's context. For enabling a wide-spread use of those applications, an infrastructure has to be developed that supports a convenient authoring process for applications as well as a comprehensive runtime, which provides both multimodality and context services. This paper describes the Multimodality Services Component as part of a context-aware runtime for multimodal applications, which was developed as part of the EMODE project. In particular, the Multimodality Services Component is responsible for enabling multimodal interaction with EMODE applications and for the adaptation and transformation of modality-independent user interface descriptions into modality-specific parts, which can be used for generating user interfaces on the used devices. Furthermore, the Multimodality Services Component performs input coordination and interaction with the associated business logic.
Beamforming Techniques for Multichannel audio Signal Separation

Beamforming is a signal processing technique. It has been studied in many areas such as radar, sonar, seismology and wireless communications, to name but a few. It can be used for a myriad of purposes, such as detecting the presence of a signal, estimating the direction of arrival, and enhancing a desired signal from its measurements corrupted by noise, competing sources and reverberation. Actually, Beamforming has been adopted by the audio research society, mostly to separate or extract speech for noisy environment. Beamforming techniques basically approach the problem from a spatial point of view. A microphone array is used to form a spatial filter which can extract a signal from a specific direction and reduce the contamination of signals from other directions. In this paper we survey some Beamforming techniques used for multichannel audio signal separation.
Propagator or Influencer? A Data-driven Approach for Evaluating Emotional Effect in Online Information Diffusion

Reposting is the basic and key behavior for information diffusion in online social networks. It would be beneficial to understand the influence factors of reposting behavior and predict future reposting status, which could be practically applied in breaking news detection, marketing, social media researches and so on. Existing reposting analytics and prediction approaches mainly focus on factors related to the original information content and the social influence of the information publishers. However, online information diffuses by viral cascades instead of single-source broadcast in social network, which means some reposting behavior actually occurs in information propagators rather than the original publishers. In some social networks, users are allowed to comment when they repost, which represents their views and attitudes to the information they propagate. In this paper, we evaluate how emotional tendencies of information propagators influence future reposting. We first propose a modified sentiment analysis method and present emotional analysis on the user-generated content in online diffusion. Experiments are conducted with a real-world dataset and the results indicate the effectiveness of our finegrained emotional features in reposting prediction.
The Effect of Intensive and Extensive Reading Strategies on Reading Comprehension: A Case of Iranian High School Students

This study was an attempt to investigate the effect of intensive and extensive reading strategies on EFL learners' reading comprehension. To achieve this goal, seventy EFL learners were conveniently selected from two different high schools in Shiraz. All the participants in this study were third grade high school students and most of them were male. To be determined, if the two groups have the same level of reading comprehension or not; both of them took pre and post reading exams. It should be mentioned that the extensive group with the help of their teacher became familiar with various books other than their text book for ten weeks. During this period, they studied their ideal books out of class without fear of exam. Whereas the intensive group studied their text book, plus ten texts. In order to obtain students’ feedback, an interview was conducted with five students in each group in relation to the effect of these two strategies on reading comprehension. In general, the results from the interview and reading exam indicated that these two strategies, in particular extensive reading had positive effect on EFL learners reading comprehension.
Structural Requirements for Cooperativity in Ileal Bile Acid-binding Proteins*

Background: Ileal bile acid-binding proteins display different degrees of binding cooperativity. Results: The structure of a low cooperativity protein complexed with bile salts was determined. The protein was mutated to enhance its cooperativity. Conclusion: Cooperative binding requires few latch residues to stabilize an H-bond network. Significance: Knowledge of the determinants of cooperativity in protein carriers is the key to understanding bile acid trafficking. Ileal bile acid-binding proteins (I-BABP), belonging to the family of intracellular lipid-binding proteins, control bile acid trafficking in enterocytes and participate in regulating the homeostasis of these cholesterol-derived metabolites. I-BABP orthologues share the same structural fold and are able to host up to two ligands in their large internal cavities. However variations in the primary sequences determine differences in binding properties such as the degree of binding cooperativity. To investigate the molecular requirements for cooperativity we adopted a gain-of-function approach, exploring the possibility to turn the noncooperative chicken I-BABP (cI-BABP) into a cooperative mutant protein. To this aim we first solved the solution structure of cI-BABP in complex with two molecules of the physiological ligand glycochenodeoxycholate. A comparative structural analysis with closely related members of the same protein family provided the basis to design a double mutant (H99Q/A101S cI-BABP) capable of establishing a cooperative binding mechanism. Molecular dynamics simulation studies of the wild type and mutant complexes and essential dynamics analysis of the trajectories supported the role of the identified amino acid residues as hot spot mediators of communication between binding sites. The emerging picture is consistent with a binding mechanism that can be described as an extended conformational selection model.
Towards semantic methodologies for automatic regulatory compliance support

Businesses and organizations must comply with requirements and expectations such as regulations, policies, mandates and guidelines to meet public standards and avoid hefty penalties. Checking compliance manually is a laborious, extensive and error-prone process. The problems in the process are, to some extent, alleviated by using computerized compliance management systems. However, these systems are experiencing challenges in coping with the frequent changes and updates in the regulations. This paper describes our research on the use of semantic web technologies to support compliance management. In particular, we propose a methodology, RegCMatic that supports the management of the compliance system. Its originality lies on automating the extraction of regulatory information from regulatory texts, and mapping regulations to organizational internal processes. Our proposed methodology is applied to the Pharmaceutical industry, where regulatory information is extracted from the Eudralex EU regulation and modeled using a semantic formalism.
Vision in V 1 for Pre-attentive Segmentation

This paper analyzes computational strategies for segmentation, and argues that an initial stage of human visual segmentation, corresponding to pop-out, is a pre-attentive process we call segmentation without classification, i.e., separating an image into regions without classifying and comparing features within and between regions. This process has been proposed to be implemented in the primary visual cortex, or V1, which detects global region boundaries by detecting the breakdown of homogeneity or translation invariance in inputs. Local intra-cortical interactions mediate contextual influences on cells’ responses from outside their classical receptive fields, making neural activities near region boundaries higher than elsewhere, thus making boundaries more salient and pop-out. A biologically based model of V1 is used to implement the proposal. Examples of how the model performs texture segmentation and figure-ground segregation are demonstrated, thus linking seemingly unrelated data of V1 physiology/anatomy and visual psychophysics. It is further proposed that outputs from V1 provide a saliency map.
Incorporating formative assessment in Iranian EFL writing: a case study

ABSTRACT Undergraduate students' experience of assessment in universities is usually of summative assessment which provides only limited information to help students improve their performance. By contrast, formative assessment is informative and forward-looking, possessing the leverage to inform students of their day-to-day progress and inform teachers of how to better tailor their instruction to students' immediate learning needs. Despite these potentials, studies carried out on the use of formative assessment in English as a foreign language (EFL) contexts are somehow rare. The current study reports on incorporating formative assessment in an L2 writing course in Iran. The analysis of data from pre- and post-study writing tasks, pre- and post-study questionnaires, and semi-structured interviews revealed that first-year undergraduate students were offered opportunities to improve various aspects of their writing and to develop positive attitudes toward writing as well as formative assessment. However, the students reported several challenges that could have implications for the further implementation of formative assessment in similar contexts.
Device performance degradation to hot-carrier injection at energies below the Si-SiO2energy barrier

Device performance degradation due to hot-carriers having energies below the Si-SiO2energy barrier are examined. For a test device with Leff= 0.3 µm and Tox5 nm, transconductance degradation and/or threshold voltage shift have been detected at a drain voltage of 2.5 V, which is lower than the Si-SiO2energy barrier(∼ 3.2 eV). In particular, transconductance degradation, rather than threshold voltage shift, is more noticeable. No sharp cut-off is shown near a drain voltage of 3 V. This transconductance degradation is mainly due to an interface state increase caused by drain avalanche hot-carrier injection. It was also found that the time, τ, that it takes forG_{m} or V_{th}to degrade a certain degree, can be expressed as\tau \propto (1/V_{D})for a VDrange of greater than 2.5 V. This degradation occurs in the same way as for long channel devices at VD> 3 V. Thus, hot carrier-related device degradation may be one of the most stringent problems in submicron MOS FETs, even after the power supply voltage is reduced.
Optimal Allocation of Resources in Female Sex Worker Targeted HIV Prevention Interventions: Model Insights from Avahan in South India

Background The Avahan programme has provided HIV prevention activities, including condom promotion, to female sex workers (FSWs) in southern India since 2004. Evidence suggests Avahan averted 202,000 HIV infections over 4 years. For replicating this intervention elsewhere, it is essential to understand how the intervention’s impact could have been optimised for different budget levels. Methods Behavioural data were used to determine how condom use varied for FSWs with different levels of intervention intensity. Cost data from 64 Avahan districts quantified how district-level costs related to intervention scale and intensity. A deterministic model for HIV transmission amongst FSWs and clients projected the impact and cost of intervention strategies for different scale and intensity, and identified the optimal strategies that maximise impact for different budget levels. Results As budget levels increase, the optimal intervention strategy is to first increase intervention intensity which achieves little impact, then scale-up coverage to high levels for large increases in impact, and lastly increase intensity further for small additional gains. The cost-effectiveness of these optimal strategies generally improves with increasing resources, while straying from these strategies can triple costs for the same impact. Projections suggest Avahan was close to being optimal, and moderate budget reductions (≥20%) would have reduced impact considerably (>40%). Discussion Our analysis suggests that tailoring the design of HIV prevention programmes for FSWs can improve impact, and that a certain level of resources are required to achieve demonstrable impact. These insights are critical for optimising the use of limited resources for preventing HIV.
A Mathematical Model of Skeletal Muscle Disease and Immune Response in the mdx Mouse

Duchenne muscular dystrophy (DMD) is a genetic disease that results in the death of affected boys by early adulthood. The genetic defect responsible for DMD has been known for over 25 years, yet at present there is neither cure nor effective treatment for DMD. During early disease onset, the mdx mouse has been validated as an animal model for DMD and use of this model has led to valuable but incomplete insights into the disease process. For example, immune cells are thought to be responsible for a significant portion of muscle cell death in the mdx mouse; however, the role and time course of the immune response in the dystrophic process have not been well described. In this paper we constructed a simple mathematical model to investigate the role of the immune response in muscle degeneration and subsequent regeneration in the mdx mouse model of Duchenne muscular dystrophy. Our model suggests that the immune response contributes substantially to the muscle degeneration and regeneration processes. Furthermore, the analysis of the model predicts that the immune system response oscillates throughout the life of the mice, and the damaged fibers are never completely cleared.
Multilingual Access to Online Help Systems and Databases

In this paper we present the AMSABEL system, a natural language based information retrieval system. AMSABEL provides access to data stored in a relational database using unrestricted natural language. Queries can be expressed in either, English or Spanish, thereby providing direct access to the database for non-expert users. The system relies on machine learning techniques to translate the original query from natural language into a structured query language and, therefore, does not depend on the contents of the database, as long as training data is available.
Getting the whole picture: combining throughput with content in microscopy

The increasing availability and performance of automated scientific equipment in the past decades have brought about a revolution in the biological sciences. The ease with which data can now be generated has led to a new culture of high-throughput science, in which new types of biological questions can be asked and tackled in a systematic and unbiased manner. High-throughput microscopy, also often referred to as high-content screening (HCS), allows acquisition of systematic data at the single-cell level. Moreover, it allows the visualization of an enormous array of cellular features and provides tools to quantify a large number of parameters for each cell. These features make HCS a powerful method to create data that is rich and biologically meaningful without compromising systematic capabilities. In this Commentary, we will discuss recent work, which has used HCS, to demonstrate the diversity of applications and technological solutions that are evolving in this field. Such advances are placing HCS methodologies at the frontier of high-throughput science and enable scientists to combine throughput with content to address a variety of cell biological questions.
Demonstration of a primitive dissipating-predictive-state planning actor-critic in a game of cat and mouse

This article covers the comparison of a primitive Dissipating-Predictive-State Planning Actor-Critic learning approach with SARSA(λ) (State-Action-Reward-State-Action) on the highly non-stationary competitive Cat and Mouse problem. The primary objective of the new algorithm was to minimize the number of constants that must be optimized before application while maintaining the performance found in other basic learning algorithms such as SARSA. The new approach was able to perform to a satisfactory degree despite the applied algorithm and parameters not being able to demonstrate better overall performance when compared to SARSA. However, from the analysis of this contribution, we were able to gather several important insights to the operations of these two algorithms. Additionally, it must be admitted that there are still many areas of the new algorithm that can be optimized. It would also be worth testing it on a few toy problems, such as grid-world, that have a greater degree of stationarity.
Distributed Mobility Control in Proxy Mobile IPv6 Networks

In future mobile networks, the ever-increasing loads imposed by mobile Internet traffic will force the network architecture to be changed from hierarchical to flat structure. Most of the existing mobility protocols are based on a centralized mobility anchor, which will process all control and data traffic. In the flat network architecture, however, the centralized mobility scheme has some limitations, such as unwanted traffic flowing into the core network, service degradation by a single point of failure, and increased operational costs, etc. This paper proposes mobility schemes for distributed mobility control in the flat network architecture. Based on the Proxy Mobile IPv6 (PMIP), which is a well-known mobility protocol, we propose the three mobility schemes: Signal-driven PMIP (S-PMIP), Data-driven Distributed PMIP (DD-PMIP), and Signal-driven Distributed PMIP (SD-PMIP). By numerical analysis, we show that the proposed distributed mobility schemes can give better performance than the existing centralized scheme in terms of the binding update and packet delivery costs, and that SD-PMIP provides the best performance among the proposed distributed schemes.