Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Mining of Closed Repetitive Gapped Subsequences from a Sequence Database

There is a huge wealth of sequence data available, for example, customer purchase histories, program execution traces, DNA, and protein sequences. Analyzing this wealth of data to mine important knowledge is certainly a worthwhile goal.In this paper, as a step forward to analyzing patterns in sequences, we introduce the problem of mining closed repetitive gapped subsequences and propose efficient solutions. Given a database of sequences where each sequence is an ordered list of events, the pattern we would like to mine is called repetitive gapped subsequence, which is a subsequence (possibly with gaps between two successive events within it) of some sequences in the database. We introduce the concept of repetitive support to measure how frequently a pattern repeats in the database. Different from the sequential pattern mining problem, repetitive support captures not only repetitions of a pattern in different sequences but also the repetitions within a sequence. Given a userspecified support threshold min_sup, we study finding the set of all patterns with repetitive support no less than min_sup. To obtain a compact yet complete result set and improve the efficiency, we also study finding closed patterns. Efficient mining algorithms to find the complete set of desired patterns are proposed based on the idea of instance growth. Our performance study on various datasets shows the efficiency of our approach. A case study is also performed to show the utility of our approach.
Unchaining in Design-Space Optimization of Streaming Applications

Data-streaming applications are frequently pipelined and deployed on hybrid systems to meet performance requirements and resource constraints. With freedom in the design of algorithms and architectures, the search complexity can explode. A popular approach to reducing search complexity is to decompose the search space while preserving optimality. We present a novel decomposition technique called unchaining that partitions the problem such that the resulting sub problems are less complex. Thanks to unchaining, the number of sub problems from the decomposition is linear in the number of chained blocks in the variable-constraint matrix (instead of being their product). Finally, we present a queueing network model and the quantitative search space reduction for a real world implementation of a bio sequence search application called BLASTN.
Effects of Selective iNOS Inhibitor on Spatial Memory in Recovered and Non-recovered Ketamine Induced-anesthesia in Wistar Rats

Nitric oxide (NO) is thought to be involved in spatial learning and memory in several brain areas such as hippocampus. This study examined the effects of post-training intrahippocampal microinjections of 1400W as a selective inducible nitric oxide synthase (iNOS) inhibitor on spatial memory, in both anesthetized and non-anesthetized situations in rats. In the present work, 4-day training trials of animals were conducted. Spatial memory was tested 48 h after the drug infusions. For microinjection of 1400W into CA1 region of the hippocampus in conscious animals, guide cannula was implanted into the CA1 area and 1400W was infused after recovery from surgical anesthesia. In anesthetized animals, 1400W was microinjected directly into CA1 region by Hamilton syringe during anesthesia. After completion of training, 1400W (10, 50 and 100 μM/side) were microinjected bilaterally (1 μL/side) and testing trials were performed 48 h after drug infusions in both groups of cannulated and non-cannulated rats. Significant reduction was observed in escape latency and traveled distance in animals that received 1400W (100 μM/side, * P < 0.05) via cannula after recovery in comparison with control group. Moreover, microinjection of 1400W (100 μM/side) in post recovery phase also caused a significant (*** P < 0.001) reduction in time and distance of finding the hidden platform in comparison with anesthetized situation. These results suggest that 1400W has a significant improvement on spatial memory, and memory enhancement induced by iNOS inhibitor can be affected by anesthesia in a period of time.
Exploiting High Level Scene Cues in Stereo Reconstruction

We present a novel approach to 3D reconstruction which is inspired by the human visual system. This system unifies standard appearance matching and triangulation techniques with higher level reasoning and scene understanding, in order to resolve ambiguities between different interpretations of the scene. The types of reasoning integrated in the approach includes recognising common configurations of surface normals and semantic edges (e.g. convex, concave and occlusion boundaries). We also recognise the coplanar, collinear and symmetric structures which are especially common in man made environments.
Changes in Biomass, Mineral Composition, and Quality of Cardoon in Response to NO3-:Cl- Ratio and Nitrate Deprivation from the Nutrient Solution

Leaf extracts of cultivated cardoon (Cynara cardunculus L. var. altilis DC) are an important source of phenols. Soilless culture represents an important and alternative tool to traditional agriculture, since it allows a precise control of plant nutrition and the maximization of yield and quality of the product. Reducing N supply, while keeping quantity as high as possible is desirable for environmental and health-related reasons, especially that N deficiency can lead to improved concentrations of secondary plant metabolites. Two greenhouse experiments were carried out in order to determine the effect of a decreasing NO3-:Cl- ratio (80:20, 60:40, 40:60, or 20:80) and nitrate deprivation (0, 5, 10, or 15 days before harvest) on biomass production, leaf chlorophyll content and fluorescence, mineral composition, and phytochemicals in leaves of cardoon ‘Bianco Avorio’ grown in a floating system. Total phenols, flavonoids and antioxidant capacity increased linearly with Cl- availability, especially when nitrate was replaced by 80% of chloride (20:80 NO3-:Cl- ratio), without having a detrimental effect on yield. Total nitrogen and nitrate concentration in leaves decreased linearly with increasing Cl- in the nutrient solution. Total phenols and antioxidant capacity recorded after 15 days of nitrate deprivation were higher by 43.1, 42.8, and 44.3% and by 70.5, 40.9, and 62.2%, at 59, 97 and 124 days after sowing, respectively compared to the control treatment. The decrease in leaf nitrate content recorded under N-deprivation occurred more rapidly than the reduction in total nitrogen. Thus, up to 15 days of nitrate withdrawal can lower nitrates without sharply reduce total nitrogen or affecting growth and biomass of cultivated cardoon. The use of N-free nutrient solution prior to harvest or the replacement of nitrates with chlorides could be adopted among growers to improve the quality of the product and enhance sustainability of crop production system.
Improved Bounds for RIC in Compressed Sensing

This paper improves bounds for restricted isometry constant (RIC) in compressed sensing. Let Φ be a m × n real matrix and k be a positive integer with k ≤ n. The main results of this paper show that if the restricted isometry constant of Φ satisfies δk+ak < 3 2 − 1 + √ (4a+ 3)2 − 8 8a for a > 3 8 , then k-sparse solution can be recovered exactly via l1 minimization in the noiseless case. In particular, when a = 1, 1.5, 2 and 3, we have δ2k < 0.5746, δ2. 5k < 0.7074∗, δ3k < 0.7731 and δ4k < 0.8445, which are the best bounds for RIC to our knowledge.
Chip-Level Redundancy in Distributed Shared-Memory Multiprocessors

Distributed shared-memory (DSM) multiprocessors provide a scalable hardware platform, but lack the necessary redundancy for mainframe-level reliability and availability. Chip-level redundancy in a DSM server faces a key challenge: the increased latency to check results among redundant components. To address performance overheads, we propose a checking filter that reduces the number of checking operations impeding the critical path of execution. Furthermore, we propose to decouple checking operations from the coherence protocol, which simplifies the implementation and permits reuse of existing coherence controller hardware. Our simulation results of commercial workloads indicate average performance overhead is within 4% (9% maximum) of tightly coupled DMR solutions.
Understanding intrinsic characteristics and system implications of flash memory based solid state drives

Flash Memory based Solid State Drive (SSD) has been called a "pivotal technology" that could revolutionize data storage systems. Since SSD shares a common interface with the traditional hard disk drive (HDD), both physically and logically, an effective integration of SSD into the storage hierarchy is very important. However, details of SSD hardware implementations tend to be hidden behind such narrow interfaces. In fact, since sophisticated algorithms are usually, of necessity, adopted in SSD controller firmware, more complex performance dynamics are to be expected in SSD than in HDD systems. Most existing literature or product specifications on SSD just provide high-level descriptions and standard performance data, such as bandwidth and latency. In order to gain insight into the unique performance characteristics of SSD, we have conducted intensive experiments and measurements on different types of state-of-the-art SSDs, from low-end to high-end products. We have observed several unexpected performance issues and uncertain behavior of SSDs, which have not been reported in the literature. For example, we found that fragmentation could seriously impact performance -- by a factor of over 14 times on a recently announced SSD. Moreover, contrary to the common belief that accesses to SSD are uncorrelated with access patterns, we found a strong correlation between performance and the randomness of data accesses, for both reads and writes. In the worst case, average latency could increase by a factor of 89 and bandwidth could drop to only 0.025MB/sec. Our study reveals several unanticipated aspects in the performance dynamics of SSD technology that must be addressed by system designers and data-intensive application users in order to effectively place it in the storage hierarchy.
Hyperbolic Structures on 3-manifolds, I: Deformation of acylindrical manifolds

This is the first in a series of papers showing that Haken manifolds have hyperbolic structures; this first was published, the second two have existed only in preprint form, and later preprints were never completed. This eprint is only an approximation to the published version, which is the definitive form for part I, and is provided for convenience only. All references and quotations should be taken from the published version, since the theorem numbering is different and not all corrections have been incorporated into the present version. Parts II and III will be made available as eprints shortly.
A case for fully decentralized dynamic VM consolidation in clouds

One way to conserve energy in cloud data centers is to transition idle servers into a power saving state during periods of low utilization. Dynamic virtual machine (VM) consolidation (VMC) algorithms are proposed to create idle times by periodically repacking VMs on the least number of physical machines (PMs). Existing works mostly apply VMC on top of centralized, hierarchical, or ring-based system topologies which result in poor scalability and/or packing efficiency with increasing number of PMs and VMs. In this paper, we propose a novel fully decentralized dynamic VMC schema based on an unstructured peer-to-peer (P2P) network of PMs. The proposed schema is validated using three well known VMC algorithms: First-Fit Decreasing (FFD), Sercon, V-MAN, and a novel migration-cost aware ACO-based algorithm. Extensive experiments performed on the Grid'5000 testbed show that once integrated in our fully decentralized VMC schema, traditional VMC algorithms achieve a global packing efficiency very close to a centralized system. Moreover, the system remains scalable with increasing number of PMs and VMs. Finally, the migration-cost aware ACO-based algorithm outperforms FFD and Sercon in the number of released PMs and requires less migrations than FFD and V-MAN.
Data Compression Adapted Based Binary Image Hiding Method

Due to the prevalence of the Internet and multimedia, one can transmit a huge amount of data via the Internet. Image hiding techniques is often used to prevent data transmitted on a computer network from being hacked by unauthorized users. Generally, in a binary image, only the proximity of edge can be used to carry secret data. Since a little space in a binary image can be used to carry secret data, it is much more difficult to conceal secret data in a binary image than in a gray-level or a color image. This paper provides a hiding method to embed secret data in a binary cover image. The method hides secret data in object boundaries. The experimental results show that the hiding method can give a good capacity rate and cover image quality. In addition, the proposed method can be combined with image compression methods. Keyword: Huffman encoding, arithmetic encoding, image compression, data hiding
Data-Driven Completion of Motion Capture Data

We present a data-driven method for completion of corrupted marker-based motion capture data. Our novel approach is especially suitable for challenging cases, e.g. if complete marker sets of multiple body parts are missing over a long period of time. Without the need for extensive preprocessing we are able to fix missing markers across different actors and motion styles. Our approach can be used for incrementally increasing prior-databases, as the underlying search technique for similar motions scales well to huge databases.
Standardisation of Hotel Descriptions

The description of tourism products (hotel, aviation, renta-car and holiday packages) is strongly supported by natural language expressions. Due to tourism dynamics and the extent of its offers, manual data management is not a reliable nor scalable solution: descriptions are structured in different ways, possibly comprising different languages, complementing and/or overlapping one another. This paper presents a prototype that automatically classifies and extracts relevant knowledge from real operational hotel descriptions retrieved from the KEYforTravel tourism application framework. Captured knowledge is represented in a normalised format enabling the development of new business services.
Interpretation of body-mounted accelerometry in flying animals and estimation of biomechanical power

An idealized energy fluctuation model of a bird's body undergoing horizontal flapping flight is developed, focusing on the biomechanical power discernible to a body-mounted accelerometer. Expressions for flight body power constructed from root mean square dynamic body accelerations and wingstroke frequency are derived from first principles and presented in dimensionally appropriate units. As wingstroke frequency increases, the model generally predicts a gradual transition in power from a linear to an asymptotically cubic relationship. However, the onset of this transition and the degree to which this occurs depends upon whether and how forward vibrations are exploited for temporary energy storage and retrieval. While this may vary considerably between species and individual birds, it is found that a quadrature phase arrangement is generally advantageous during level flight. Gravity-aligned vertical acceleration always enters into the calculation of body power, but, whenever forward acceleration becomes relevant, its contribution is subtractive. Several novel kinematic measures descriptive of flapping flight are postulated, offering fresh insights into the processes involved in airborne locomotion. The limitations of the model are briefly discussed, and departures from its predictions during ascending and descending flight evaluated. These findings highlight how body-mounted accelerometers can offer a valuable, insightful and non-invasive technique for investigating the flight of free-ranging birds and bats.
A Local Method for ObjectRank Estimation

ObjectRank is a method of link structure analysis to evaluate the importance of objects in a database. ObjectRank is known to be computationally expensive, because it requires iterative computations over a large graph. However, in many real applications, it is sufficient to compute the ObjectRank scores for only small fraction of objects. To address this problem, this paper proposes a novel method for estimating ObjectRank scores for specific objects by applying local computation over partial graphs, thereby allowing us to maintain low computational cost even for large graphs. Our basic idea is that, for a given target node, we induce a local graph by checking the edge weights and pruning the edges with considering their weights. We conduct experiments to compare our method with some comparative methods. The experimental results show that our method can reduce the computational cost while maintaining the accuracy.
Comparing commodity SMP system software with a matrix multiplication benchmark

Commodity symmetric multiprocessors (SMPs), though originally intended for transaction processing, because of their availability, are now used for numerical analysis applications in SMP clusters. Dense matrix multiplication is a suitable benchmark as it exposes memory access issues. Various block-based algorithms are compared across Windows 2000 and Linux variants with gcc compiler versions. Differences in compilers may explain differential performance between algorithms.
Molecular Insight into the Steric Shielding Effect of PEG on the Conjugated Staphylokinase: Biochemical Characterization and Molecular Dynamics Simulation

PEGylation is a successful approach to improve potency of a therapeutic protein. The improved therapeutic potency is mainly due to the steric shielding effect of PEG. However, the underlying mechanism of this effect on the protein is not well understood, especially on the protein interaction with its high molecular weight substrate or receptor. Here, experimental study and molecular dynamics simulation were used to provide molecular insight into the interaction between the PEGylated protein and its receptor. Staphylokinase (Sak), a therapeutic protein for coronary thrombolysis, was used as a model protein. Four PEGylated Saks were prepared by site-specific conjugation of 5 kDa/20 kDa PEG to N-terminus and C-terminus of Sak, respectively. Experimental study suggests that the native conformation of Sak is essentially not altered by PEGylation. In contrast, the bioactivity, the hydrodynamic volume and the molecular symmetric shape of the PEGylated Sak are altered and dependent on the PEG chain length and the PEGylation site. Molecular modeling of the PEGylated Saks suggests that the PEG chain remains highly flexible and can form a distinctive hydrated layer, thereby resulting in the steric shielding effect of PEG. Docking analyses indicate that the binding affinity of Sak to its receptor is dependent on the PEG chain length and the PEGylation site. Computational simulation results explain experimental data well. Our present study clarifies molecular details of PEG chain on protein surface and may be essential to the rational design, fabrication and clinical application of PEGylated proteins.
MODELING TIME SERIES DATA OF REAL SYSTEMS

Dynamics of complex systems is studied by first considering a chaotic time series generated by Lorenz equations and adding noise to it. The trend (smooth behavior) is separated from fluctuations at different scales using wavelet analysis and a prediction method proposed by Lorenz is applied to make out of sample predictions at different regions of the time series. The prediction capability of this method is studied by considering several improvements over this method. We then apply this approach to a real financial time series. The smooth time series is modeled using techniques of non linear dynamics. Our results for predictions suggest that the modified Lorenz method gives better predictions compared to those from the original Lorenz method. Fluctuations are analyzed using probabilistic considerations.
Road vehicle localization with 2D push-broom LIDAR and 3D priors

In this paper we describe and demonstrate a method for precisely localizing a road vehicle using a single push-broom 2D laser scanner while leveraging a prior 3D survey. In contrast to conventional scan matching, our laser is oriented downwards, thus causing continual ground strike. Our method exploits this to produce a small 3D swathe of laser data which can be matched statistically within the 3D survey. This swathe generation is predicated upon time varying estimates of vehicle velocity. While in theory this data could be obtained from vehicle speedometers, in reality these instruments are biased and so we also provide a way to estimate this bias from survey data. We show that our low cost system consistently outperforms a high caliber integrated DGPS/IMU system over 26 km of driven path around a test site.
An extendible context-aware service system for mobile computing

Context-aware computing is one of the research fields in pervasive computing and mobile computing. Context-aware systems can react to the user's preference according to the circumstances called context including location, time and other environment conditions. Many context-aware computing paradigms were developed in recent year; however, it is difficult for the present systems to extend the application domains and interoperate with other service systems due to the problem of heterogeneity among systems. In this paper, an extendible context-aware service system importing the concept of context independence is proposed and designed. The main idea of context independence includes the physical context independence and the logical context independence. The approaches of constructing context independence are also provided for the proposed system architecture. The context-aware system thus can easily integrate different service domains and diverse devices into a unifying environment.
Animal Spirits, Financial Crises and Persistent Unemployment

This paper develops a rational expectations model with multiple equilibrium unemployment rates where the price of capital may be unbounded above. I argue that this property is an important feature of any rational-agent explanation of a financial crisis, since for the expansion phase of the crisis to be rational, investors must credibly believe that asset prices could keep increasing forever with positive probability. I explain the sudden crash in asset prices that precipitates a financial crisis as a large negative self-fulfilling shock to the expectation of the future price of capital. This shock causes a permanent reduction in wealth and consumption and a permanent increase in the unemployment rate. My work suggests that economic policies designed to reduce the volatility of asset market movements will significantly increase economic welfare.