Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Large Flow Detection over Arbitrary Windows: An Algorithm Exact Outside an Ambiguity Region

Many networking and security applications can benefit from exact detection of large flows over arbitrary windows (i.e. any possible time window). Existing large flow detectors that only check the average throughput over certain time period cannot detect bursty flows and are therefore easily fooled by attackers. However, no scalable approaches provide exact classification in one pass. To address this challenge, we consider a new model of exactness outside an ambiguity region, which is defined to be a range of bandwidths below a high-bandwidth threshold and above a low-bandwidth threshold. Given this new model, we propose a deterministic algorithm, EARDet, that detects all large flows (including bursty flows) and avoids false accusation against any small flows, regardless of the input traffic distribution. EARDet monitors flows over arbitrary time windows and is built on a frequent items finding algorithm based on average frequency. Despite its strong properties, EARDet has low storage overhead regardless of input traffic and is surprisingly scalable because it focuses on accurate classification of large flows and small flows only. Our evaluations confirm that existing approaches suffer from high error rates (e.g., misclassifying 1% of small flows as large flows) in the presence of large flows and bursty flows, whereas EARDet can accurately detect both at gigabit line rate using a small amount of memory that fits into on-chip SRAM.
Accelerated robust sparse coding for fast face recognition

In this paper, we propose an accelerated robust sparse coding (ARSC) method which is based on the combination of linear-regression based classification and robust sparse coding for fast face recognition. First, linear-regression based classification (LRC) is used to select the candidate face set, which can effectively reduce the search scope. Then, robust sparse coding (RSC) is applied to perform accurate face identification in the selected face set. Extensive experimental results on various face databases demonstrate that the proposed ARSC can greatly reduce the computational complexity while achieving high recognition performance.
Linear-Space Substring Range Counting over Polylogarithmic Alphabets

Bille and Grtz (2011) recently introduced the problem of substring range counting, for which we are asked to store compactly a string S of n characters with integer labels in (0;u), such that later, given an interval (a;b) and a pattern P of length m, we can quickly count the occurrences of P whose rst characters' labels are in ( a;b). They showed how to store S in O(n logn= log logn) space and answer queries in O(m + log logu) time. We show that, if S is over an alphabet of size polylog(n), then we can achieve optimal linear space. Moreover, if u = n polylog(n), then we can also reduce the time to O(m). Our results give linear space and time bounds for position-restricted substring counting and the counting versions of indexing substrings with intervals, indexing substrings with gaps and aligned pattern matching.
Shifting Strategies for the Parallel QR Algorithm

Consider the problem of finding all eigenvalues of a real square matrix A that has no special structure to exploit. The QR algorithm has been the method of choice for solving such problems for the past 30 years. However, in recent years it has been suggested that the days of the QR algorithm may be numbered, for the QR algorithm has proven difficult to parallelize. Such predictions are at best premature. A simple modification of the shifting strategy promises to improve the parallel performance of the QR algorithm significantly and keep the competition at bay for years to come.
On the latency, energy and area of checkpointed, superscalar register alias tables

We present two full-custom implementations of the Register Alias Table (RAT) for a 4-way superscalar dynamically-scheduled processor in a commercial 130nm CMOS technology. The implementations differ in the way they organize the embedded global checkpoints (GCs) which support speculative execution. In the first implementation, representative of early designs, the GCs are organized as shift registers. In the second implementation, representative of more recent proposals, the GCs are organized as random access buffers. We measure the impact of increasing the number of GCs on the latency, energy, and area of the RAT. The results support the importance of recent techniques that reduce the number of GCs while maintaining performance.
Moderately roughened- and roughened-surface implants used as rigid orthodontic anchorage: a case series.

BACKGROUND Osseointegrated implants, especially Brånemark turned-surface implants, have been shown to function as stable and efficient orthodontic anchors. While it is generally accepted that prostheses can be attached to implants that have been used as anchors, it has not been clarified if the same applies to moderately roughened- and roughened-surface implants. PURPOSE The purpose of the present study was to assess the differences between moderately roughened- and roughened-surface implants that are used as orthodontic anchors and then bonded with prostheses and those that are bonded with prostheses without serving as orthodontic anchors. MATERIALS AND METHODS A total of 43 moderately roughened- and roughened-surface implants (ITI titanium plasma spray TPS] Straumann AG, Waldenburg, Switzerland], ITI sandblasted large-grit acid-etched SLA] Straumann AG], Nobel TiUnite Nobel Biocare AB, Göteborg, Sweden]) were placed in 11 partially edentulous patients, aged 35-61 years (two men and nine women). After an appropriate healing period, orthodontic therapy was performed in 11 patients using 27 implants as orthodontic anchors. After completion of the orthodontic therapy, the prostheses were attached at the same time to both types of implants: the 27 implants that were used as anchors, and 16 implants that were not used as anchors. All 11 patients were followed up regularly. RESULTS Regardless of use as orthodontic anchorage, all implants maintained osseointegration and continued to function properly. CONCLUSION No differences existed in therapeutic results after prosthesis bonding whether or not moderately roughened- and roughened-surface implants were used as orthodontic anchors.
Enlarging the Time Budget for Neural Network Based Predictors for Access Interval Prediction

Embedded systems implemented on a single chip commonly contain several Processing Elements (PEs). To optimize both area and energy efficiency, these individual PEs are often linked to the same Tightly Coupled Memory (TCM). Nonetheless, the advantage of memory sharing is offset by potential conflicts. Recently introduced systems with offline conflict detection and memory arbitration avoid the performance degradation of online arbiters. Access Interval Prediction (AIP) is exploited to detect the conflicts offline by forecasting the time interval between two memory accesses. In this context, neural network models for time-series prediction are the State-of-the-Art AIP units. However, the influence of the latency of these neural network predictors on the accuracy of the AIP system has not been considered yet. Our analysis shows a significant degradation of the system accuracy by the predictor latency. To enlarge the time budget for calculation, we introduce a novel neural network AIP predictor that predicts the next-but-one memory access. Further, we present an advanced system model that integrates two independent next-but-one predictors. By combining multiple predictors, we can maintain the high accuracy of the AIP system even for implementations that exhibit high latency. For example, our system model demonstrates a 2.59 times higher accuracy compared to the State-of-the-Art AIP with neural networks when executing the models with a latency of 5 cycles.
Effects of Active and Passive Recovery Conditions on Blood Lactate, Rating of Perceived Exertion, and Performance During Resistance Exercise

Active recovery has proven an effective means in reducing blood lactate concentration ([La−]) after various activities, yet its effects on performance are less clear. We investigated the effects of passive and active recovery on blood [La−], rating of perceived exertion (RPE), and performance during a resistance training workout. Fifteen resistance-trained males completed 3 workouts, each consisting of 6 sets of parallel squat exercise performed at 85% of 10 repetition maximum (10RM). Each set was separated by a 4-minute recovery period. Recovery was randomly assigned from the following: passive sitting; pedaling at 25% of onset of blood lactate accumulation (OBLA) exercise intensity (25%-OBLA); and pedaling at 50% of OBLA exercise intensity (50%-OBLA). Active recovery was performed on a bicycle ergometer at 70 rev·min−1. Performance was determined postworkout by a maximal repetition performance (MRP) squat test using 65% of 10RM. Blood samples were collected: prewarm-up; post-second, postfourth, postsixth, and MRP sets; and postsecond, postfourth, and postsixth recovery periods. Significant differences (p ≤ 0.05) were observed in [La−], and RPE among the 3 recoveries, with 25%-OBLA lower than passive and 50%-OBLA. Total repetitions to exhaustion for the MRP were: passive (24.1 ± 1.8); 25%-OBLA (29.3 ± 1.8); and 50%-OBLA (23.1 ± 1.7), with 25%-OBLA being significantly greater than passive and 50%-OBLA. In this investigation, active recovery at 25%-OBLA proved to be the most effective means of reducing [La−] during recovery and increasing performance following a parallel squat workout.
Pharmacological repositioning of Achyranthes aspera as an antidepressant using pharmacoinformatic tools PASS and PharmaExpert: a case study with wet lab validation$

Abstract Traditional knowledge guides the use of plants for restricted therapeutic indications, but their pharmacological actions may be found beyond their ethnic therapeutic indications employing emerging computational tools. In this context, the present study was envisaged to explore the novel pharmacological effect of Achyranthes aspera (A. aspera) using PASS and PharmaExpert software tools. Based on the predicted mechanisms of the antidepressant effect for all analysed phytoconstituents of A. aspera, one may suggest its significant antidepressant action. The possible mechanism of this novel pharmacological effect is the enhancement of serotonin release, in particular caused by hexatriacontane. Therefore, pharmacological validation of the methanolic extract, hexatriacontane rich (HRF) and hexatriacontane lacking fraction (HLF) of A. aspera was carried out using the Forced Swimming Test and Tail suspension test in mice. The cortical and hippocampal monoamine and their metabolite levels were measured using high performance liquid chromatography (HPLC). A. aspera methanolic extract, HRF treatments showed a significant antidepressant effect comparable to imipramine. Further, the corresponding surge in cortical and hippocampal monoamine and their metabolite levels was also observed with these treatments. In conclusion, A. aspera has shown a significant antidepressant effect, possibly due to hexatriacontane, by raising monoamine levels.
Estimating the embedding capacity of a color image using Color Difference

Digital image watermarking has been widely applied to solve the copyright protection problems of the color image, related to illegal usage or distribution. The invisible image watermarking scheme is the type where the watermark is hidden in the cover image. Estimating the embedding capacity and maintaining perceptual quality of the cover image are the important issues in invisible watermarking. We propose a scheme for quantifying the embedding capacity of the color image considering Human Visual System (HVS). This scheme uses the threshold value of Just Noticeable Color Difference (JNCD) to estimate the number of bits that can be changed between the perceptual indistinguishable colors. The maximum change in the number of bits of a color is used to estimate tolerable embedding capacity of color. The watermark embedding capacity of image is calculated by summing the capacity of colors of an image.
Improvement of Bacillus subtilis for poly‐γ‐glutamic acid production by genome shuffling

Poly‐γ‐glutamic acid (γ‐PGA) is a promising microbial polymer with potential applications in industry, agriculture and medicine. The use of high γ‐PGA‐producing strains is an effective approach to improve productivity of γ‐PGA. In this study, we developed a mutant, F3‐178, from Bacillus subtilis GXA‐28 using genome shuffling. The morphological characteristics of F3‐178 and GXA‐28 were not identical. Compared with GXA‐28 (18.4 ± 0.8 g l−1), the yield of γ‐PGA was 1.9‐fold higher in F3‐178 (34.3 ± 1.2 g l−1). Results from batch fermentation in 3.7 l fermenter showed that F3‐178 was satisfactory for industrial production of γ‐PGA. Metabolic studies suggested that the higher γ‐PGA yield in F3‐178 could be attributed to increased intracellular flux and uptake of extracellular glutamate. Real‐time PCR indicated that mRNA level of pgsB in F3‐178 was 18.8‐fold higher than in GXA‐28, suggesting the higher yield might be related to the overexpression of genes involved in γ‐PGA production. This study demonstrated that genome shuffling can be used for rapid improvement of γ‐PGA strains, and the possible mechanism for the improved phenotype was also explored at the metabolic and transcriptional levels.
SSVEP Brain-Computer Interface Decoding Based on Spatio-temporal TRCA Filtering and Least Squares Data Migration

Due to its high stability and information transfer rate, steady-state visual evoked potential (SSVEP) is one of the most widely used brain-computer interface paradigms. However, because of inter-subject variability, SSVEP BCI decoding algorithms still require to be calibrated with a substantial amount of training data before practical application. This study integrates both temporal and spatial filters into the task-related component analysis algorithm to obtain more stable template signals. Additionally, transfer learning is employed to incorporate cross-subject data into the training process, reducing the number of training samples and improving the performance of SSVEP decoding algorithms. where the source domain data is migrated to the target domain using a least squares transform approach. The proposed algorithm is validated on public dataset and results show that, compared to the pure TRCA, the proposed stTRCA-LST algorithm can improve the recognition accuracy by 8.73%. The new algorithm is easy to conduct and can further simplify the calibration effort in practical application of SSVEP-based BCls.
On Prototypes for Winslett's Semantics of DL-Lite ABox Evolution

Evolution of Knowledge Bases expressed in Description Logics (DLs) proved its importance. Most studies on evolution in DLs have focused on modelbased approaches to evolution semantics and in particular on Winslett’s semantics (WS). It was understood that evolution under WS even in tractable DLs, such as DL-Lite, suffers from inexpressibility, i.e., the result of evolution cannot be expressed in the same logics. In this work we show which combination of DLLite logical constructs is responsible for the inexpressibility and explain reasons for such a behaviour. We present novel techniques, based on what we called prototypes, to capture Winslett’s evolution in FO[2] for DL-LiteR. We also discuss which fragments of DL-LiteR are closed under evolution.
An Accelerated Safety Probability Estimation Method for Control Policies of Autonomous Vehicles in Open Environments

One of the critical bottlenecks that influence the development and deployment of autonomous vehicles (AV) is the safety assessment for raised control policies, especially in the situation of taking sensing noise into account. Safety probability estimation is one of the useful tools to describe the performance of control policies. However, these evaluation metrics always require amounts of tests to obtain, especially in open environments, which brings high time costs, no matter with actual vehicles or high-fidelity models. This article proposes an accelerated safety probability estimation method based on multi-fidelity models and a scenario classification method. Our method can accelerate the safety probability estimation process and has a small error. In our test of a desert road scene, our method used 1/750 of the time of the Airsim with Unreal Engine 4 (UE4), and get less than 5% error in most cases.
Effects of the English (H6R) and Tottori (D7N) Familial Alzheimer Disease Mutations on Amyloid β-Protein Assembly and Toxicity*

Mutations in the amyloid β-protein (Aβ) precursor gene cause autosomal dominant Alzheimer disease in a number of kindreds. In two such kindreds, the English and the Tottori, the mutations produce amyloid β-proteins containing amino acid substitutions, H6R and D7N, respectively, at the peptide N terminus. To elucidate the structural and biological effects of the mutations, we began by examining monomer conformational dynamics and oligomerization. Relative to their wild type homologues, and in both the Aβ40 and Aβ42 systems, the English and Tottori substitutions accelerated the kinetics of secondary structure change from statistical coil → α/β → β and produced oligomer size distributions skewed to higher order. This skewing was reflected in increases in average oligomer size, as measured using electron microscopy and atomic force microscopy. Stabilization of peptide oligomers using in situ chemical cross-linking allowed detailed study of their properties. Each substitution produced an oligomer that displayed substantial β-strand (H6R) or α/β (D7N) structure, in contrast to the predominately statistical coil structure of wild type Aβ oligomers. Mutant oligomers functioned as fibril seeds, and with efficiencies significantly higher than those of their wild type homologues. Importantly, the mutant forms of both native and chemically stabilized oligomers were significantly more toxic in assays of cell physiology and death. The results show that the English and Tottori mutations alter Aβ assembly at its earliest stages, monomer folding and oligomerization, and produce oligomers that are more toxic to cultured neuronal cells than are wild type oligomers.
Creative Thought: An Investigation of Conceptual Structures and Processes

Conceptual Structures and Processes in Creative Thought - Thomas B. Ward, Steven M. Smith, and Jyotsna Vaid - Thematic Relations and the Creation of Combined Concepts - Edward J. Shoben and Christina L. Gagne - Conceptual Combination: Possibilities and Esthetics - Edward J. Wisniewski - Emergent Attributes in Combined Concepts - James A. Hampton - The Developmental Emergence of Multiplicative Combinations - Friedrich Wilkening, Gudrune Schwarzer, and Annette Rummele - Coherent and Creative Conceptual Combinations - Paul Thagard - Imagination at Work: Conceptual and Linguistic Creativity in Children - Cristina Cacciari, Maria Chiara Levorato, and Pirecarla Cicogna - The Creation of New Concepts: A Multifaceted Approach to Category Learning - Arthur B. Markman, Takashi Yamauchi, and Valerie S. Makin - Creativity: Shifting Across Ontological Categories Flexibly - Michelene T. H. Chi - Polysemy and the Creation of Novel Word Meanings - Gregory L. Murphy - Mundane Creativity in Perceptual Symbol Systems - Lawrence W. Barsalou and Jesse J. Prinz - Creativity in Personality, Developmental, and Social Psychology: Any Links With Cognitive Psychology? - Dean Keith Simonton - Metaphor Comprehension: How Metaphors Create New Categories - Sam Glucksberg, Deanna Ann Manfredi, and Matthew S. McGlone - How Language Reflects the Embodied Nature of Creative Cognition - Raymond W. Gibbs, Jr. - Of "Men" and Metaphors: Shakespeare, Embodiment, and Filing Cabinets - Eva Feder Kittay - Analogy and Creativity in the Worlds of Johannes Kepler - Dedre Gentner, Sarah Brem, Ron Ferguson, Philip Wolff, Arthur B. Markman, and Ken Forbus - How Scientists Think: On-Line Creativity and Conceptual Change in Science - Kevin Dunbar - Mental Models, Space, and Embodied Cognition - Arthur M. Glenberg - Creativity's Camel: The Role of Analogy in Invention - David N. Perkins
Individual differences in excitation and inhibition in visual cortex

The formation of a visual percept in the human brain involves multiple processes, the extent of which may be related to each other within individuals but may show variability between participants. The aim of this thesis was to investigate the relationships between individual variability in various measures of visual processing. The non-invasive neuroimaging methods of magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), magnetoencephalography (MEG) and functional MRI (fMRI) were employed to measure brain structure, neurotransmitter concentration, neuronal oscillations and haemodynamic activity, respectively. Reductions in haemodynamic activity in non-stimulated areas of visual cortex (negative blood oxygen level-dependent responses) were shown to hold useful information about the stimulus, in addition to the responses in stimulated cortex. In general, there were no strong relationships between increased or decreased functional responses in visual cortex and measures of brain structure or of neurotransmitter concentration. Age was the major determinant of individual variability in the frequency of neuronal oscillations. These findings do not replicate results from previous studies that have shown links between individual differences in these measures. This discrepancy was not due to poor repeatability of MRS measures, since methods for optimisation of MRS were identified in this thesis. Simulations were also conducted to determine the sample sizes required in correlational studies involving neuroimaging measures with associated measurement noise. The lack of replication of relationships between neuroimaging measures of individual differences in visual processing is likely to be influenced by low statistical power, due to the small sample sizes and weak relationships tested. Such studies should therefore be conducted and interpreted cautiously, bearing in mind issues of power, demographic mediators of relationships and the likely strength of relationships inferred from the physiological mechanisms linking the variables tested.
Disturbance and Response Time Improvement of Submicrometer Precision Linear Motion System by Using Modified Disturbance Compensator and Internal Model Reference Control

Permanent magnet linear motors are a type of linear motors that are generally used in precision motion control applications. However, the position of motor is easily disturbed by external force, disturbance, and variation in parameters of plant. Therefore, the construction of the high-precision linear motion system is a difficult task. This paper implements a modified disturbance observer and compensator, which includes a novel variable gain, to overcome the effects of unknown parameters of the motor, to minimize the effect of the disturbance, and to reduce the response time of the disturbance. This compensated linear motor is further controlled by the internal model reference control algorithm so that the position of the motor can be tracked with expected response precisely. The authors conducted the experiments and verified the feasibility of the high-precision positioning control. Compared with the case of normal disturbance compensator, the experimental results also illustrate the improvements of the novel variable gain, which reduces the response time toward the command signal and the external disturbance.