Miracle-dz/UniFAR-FTUs huggingface dataset:
A growing partitional clustering based on particle swarm optimization

This paper proposes a growing partitional clustering method based on particle swarm optimization (PSO) namely PSOGC for handling data with non-spherical or non-linearly separable distribution. Particularly, PSOGC uses PSO to optimize the cluster centers. In each iteration of PSO, the particles encoding candidate cluster centers are evolved according to their social and personal knowledge. Given the candidate cluster centers, a growing strategy increasingly absorbs nearby data samples into the corresponding cluster based on k-nearest neighbor graph. The fitness of each particle is evaluated in terms of intra-cluster connectivity and inter-cluster disconnectivity of the resultant clustering. The combination of PSO and growing strategy ensures the stability of global search and the robustness of partition on data of different non-spherical shapes. Experimental results on six synthetic and three UCI real-world data sets demonstrate the efficiency of PSOGC.
Corrosion and Thermal Fatigue Behaviors of TiC/Ni Composite Coating by Self-Propagating High-Temperature Synthesis in Molten Aluminum Alloy

TiC/Ni composite coatings on H13 steel plates were fabricated in situ by self-propagating high-temperature synthesis and combined with a pseudo-heat isostatic press. The microstructure of the coating was characterized by X-ray diffraction and scanning electron microscopy. The microhardness, corrosion, and thermal fatigue behaviors of the coating were investigated by a microhardness test, immersion test, and thermal fatigue test, respectively. The results showed that the in situ coating consisted of TiC and Ni binder phases. Spheroidal TiC particles were enveloped by a nearly continuous Ni binder phase. Coating showed good metallurgical bonding in the interface. The corrosive mechanism of the coating surface in molten aluminum alloy involves the Ni binder phase being etched by aluminum to form AlNi3 and the oxidization of the TiC-reinforced phase. The corrosive mechanism that occurred at the front of the corrosion involves the Ni binder phase of the coating being etched by aluminum to form AlNi3, while the TiC skeleton still maintains the original organizational structure. Hot fatigue cracks began at the defective tips of the coating and propagated in the TiC-reinforced phase. The crack is a trans-granular fracture, which is the result of brittle rupture.
Behavioral Neuroscience

Fear is often measured as freezing (defined as the suppression of all movement except that required for respiration) a prominent species-specific defense reaction in both rats and mice, with a long history of study (discussed below) (Bolles, 1970). Contextual fear has garnered a very high level of interest because it is dependent on the hippocampus and as such, has become a leading model of declarative memory. As with human declarative memory, hippocampal lesions produce a time-limited and selective deficit of contextual fear, such that lesions made 1 day after training produce a severe retrograde amnesia of contextual fear, but those made one month or more after training produce little or no deficit (Kim and Fanselow, 1992; Anagnostaras et al., 1999b). Cued memory usually does not depend on the hippocampus, but can, especially as in trace conditioning, or when the ventral hippocam-In contrast, both contextual and tone fear depend on the amygdala for the lifetime of the animal (Gale et al., 2004; Poulos et al., 2009). Pavlovian fear conditioning is an effective assay for memory enhancements and deficits because: (1) The task is robust in rats and mice, with conditioning occurring even after a single trial (Anagnostaras et al., 2000). (2) The assay is not labor intensive; for example, a training session lasts 3–10 min, with 1-15 tone-shock pairings, as compared to several training days for most other forms of hippocampus-dependent memory. (3) The equipment is readily available and compact, allowing many animals to be tested at once (up to 16 in a small office-sized room). " The frightened man at first stands like a statue motionless and breathless, or crouches down as if instinctively to escape observation .
Generalized adaptive view-based appearance model: Integrated framework for monocular head pose estimation

Accurately estimating the person's head position and orientation is an important task for a wide range of applications such as driver awareness and human-robot interaction. Over the past two decades, many approaches have been suggested to solve this problem, each with its own advantages and disadvantages. In this paper, we present a probabilistic framework called generalized adaptive viewbased appearance model (GAVAM) which integrates the advantages from three of these approaches: (1) the automatic initialization and stability of static head pose estimation, (2) the relative precision and user-independence of differential registration, and (3) the robustness and bounded drift of keyframe tracking. In our experiments, we show how the GAVAM model can be used to estimate head position and orientation in real-time using a simple monocular camera. Our experiments on two previously published datasets show that the GAVAM framework can accurately track for a long period of time (>2 minutes) with an average accuracy of 3.5deg and 0.75 in with an inertial sensor and a 3D magnetic sensor.
Are Older Adults More Social Than Younger Adults? Social Importance Increases Older Adults' Prospective Memory Performance

ABSTRACT The purpose of this study was to explore the influence of social importance on prospective remembering in younger and older adults as a possible factor contributing to the age-prospective memory paradox. Using a between-subjects design, 40 younger and 40 older adults worked on a time-based prospective memory task in which social importance was varied. Overall, younger adults outperformed older adults in the prospective memory task. Importantly, in contrast to younger adults, older adults' prospective memory performance was significantly better in the social importance condition than in the standard condition. This interaction was not reflected in participants' time-monitoring behaviour. Findings are discussed in the context of recent prospective memory theories.
[Quality of life in patients with obsessive-compulsive disorder: relations with cognitive functions and clinical symptoms].

OBJECTIVE To compare quality of life in patients with obsessive-compulsive disorder with that in healthy subjects and to relate quality of life to cognitive functions and the severity of clinical symptoms. METHODS Twenty-three patients who met DSM-IV criteria for obsessive compulsive disorder and 22 healthy subjects were included in the study. Quality of life (Turkish Quality of Life Scale-Brief Form) and cognitive functions were investigated in all subjects. In the patient group the relation of quality of life to the cognitive functions and to the severity of clinical symptoms and in the control group the relation of quality of life to the cognitive functions was investigated. RESULTS The comparison of quality of life between the patient and control groups showed a significant difference (F= 2.60, p= 0.04). The significant differences between the two groups in psychological and social scores were responsible for the overall significant difference. The scores of quality of life were correlated with the scores of the cognitive tests (Trail Making Test, Auditory Consonant Trigram Test and Digit Span Test) and the severity of obsessive-compulsive symptoms. CONCLUSION The present study revealed that quality of life is lower in patients with obsessive-compulsive disorder than in healthy subjects and is related to cognitive functions and the severity of obsessive-compulsive symptoms.
Blind Dereverberation Based on Generalized Spectral Subtraction by Multi-channel LMS Algorithm

A blind dereverberation method based on power spectral subtraction (SS) using a multi-channel least mean squares algorithm was previously proposed. The results of isolated word speech recognition experiments showed that this method achieved significant improvement over conventional cepstral mean normalization (CMN). In this paper, we propose a blind dereverberation method based on generalized spectral subtraction (GSS), which has been shown to be effective for noise reduction, instead of power SS. Furthermore, we extend the missing feature theory (MFT), which was initially proposed to enhance the robustness of additive noise, to dereverberation. The reliability of each spectral component is calculated through the signal-to-reverberation ratio obtained from the spectrum of dereverberant speech based on GSS. The proposed dereverberation method based on GSS with MFT is evaluated on a large vocabulary continuous speech recognition task. The dereverberation method based on GSS with MFT and beamforming achieves a relative word error reduction rate of 11.4% and 32.6% compared to the dereverberation method based on power SS with beamforming and the conventional CMN with beamforming, respectively.
A numerical study of propagation effects in a wireless mesh test bed

The present layout of the indoor wireless mesh network test-bed build at the Meraka Institute is introduced. This is followed by a description of a numerical electromagnetic model for the complete test-bed, including the coupling and diffraction effects, as generated with WIPL-D Pro. The results of numerical simulations are compared with the measurements. The findings help to quantify errors and provide grounds for suggestions towards improving the test-bed's design.
[11C]‐DASB, a tool for in vivo measurement of SSRI‐induced occupancy of the serotonin transporter: PET characterization and evaluation in cats

The in vivo pharmacological profile of [11C]‐DASB, a new radioligand developed for in vivo imaging of the serotonin transporter (SERT), was evaluated in the cat brain using positron emission tomography (PET). The in vivo distribution of [11C]‐DASB binding was consistent with the known distribution of SERT sites in the cat brain in vitro with high uptakes of radioactivity in the midbrain and thalamus, intermediate levels in striatum, and modest to low levels of radioactivity in the neocortex and cerebellum, respectively. [11C]‐DASB binding potential (BP) values ranged from about 0.2 in the neocortex to 2.2 in the midbrain. Radioligand binding in all brain regions except cerebellum was markedly reduced following pretreatment with fluoxetine and citalopram, but was unaffected by pretreatment with GBR12909, maprotiline, and haloperidol, indicating specificity of [11C]‐DASB binding to the SERT. Two cats were each examined using PET and [11C]‐DASB in a longitudinal fashion (from 30 min and up to 24 days) following a single i.v. dose of: 1) fluoxetine, and 2) citalopram at different dosages. Both drugs induced similar degrees of SERT occupancy at 30 min postinjection (∼90%). A comparison of citalopram and fluoxetine pharmacokinetics in the same animal and at the same dosage (1 mg/kg) showed that citalopram SERT occupancy and plasma half‐lives were 9 times and 14 times shorter, respectively, than those of fluoxetine and norfluoxetine. In addition, studies performed after injection of the monoamine oxidase inhibitor tranylcypromine suggested that high levels of synaptic serotonin may compete with [11C]‐DASB for binding on the SERT. These studies indicate that [11C]‐DASB is a suitable PET radioligand for measuring drug occupancy of the SERT in vivo and has potential for monitoring in vivo changes in serotonin levels. Synapse 47:123–133, 2003. © 2002 Wiley‐Liss, Inc.
Branch prediction for free

Many compilers rely on branch prediction to improve program performance by identifying frequently executed regions and by aiding in scheduling instructions.Profile-based predictors require a time-consuming and inconvenient compile-profile-compile cycle in order to make predictions. We present a program-based branch predictor that performs well for a large and diverse set of programs written in C and Fortran. In addition to using natural loop analysis to predict branches that control the iteration of loops, we focus on heuristics for predicting non-loop branches, which dominate the dynamic branch count of many programs. The heuristics are simple and require little program analysis, yet they are effective in terms of coverage and miss rate. Although program-based prediction does not equal the accuracy of profile-based prediction, we believe it reaches a sufficiently high level to be useful. Additional type and semantic information available to a compiler would enhance our heuristics.
Geography, International Trade and Technological Diffusion

International trade has been considered as a mechanism for knowledge diffusion that offers the opportunity to improve technological capabilities of importing countries. By importing capital goods from developed countries, developing countries could achieve their economic development despite their insufficient investments in technology. Many studies dealing with this subject provide strong empirical evidence of technological externalities contributing to the economic openness of these countries. In this paper, we suppose first that, regardless of prices and policy tariffs, imports could also be explained by geographic factors. We try to explain the intensity of knowledge diffusion by the geographic location of importing countries with regard to their trading partners. Under the hypothesis that the knowledge diffused has the characteristic of a public good, our estimations show that importing from the nearest G6 countries allows more knowledge spillovers for some developing countries, however we conclude that geographic location of importing countries is not the only factor that determines the intensity of technological diffusion. Knowledge spillovers also depend on the evolution of the geographic structure of imports for these countries and on the kind of goods they import (knowledge intensive or not).
Methods Activity profiling of ectomycorrhiza communities in two forest soils using multiple enzymatic tests

• Data on the diversity and distribution of enzyme activities in native ectomycorrhizal (ECM) communities are inadequate. • A microplate multiple enzymatic test was developed which makes it possible to measure eight enzyme activities on 14 individual, excised ECM root tips. Hydrolytic and oxidative enzymes are involved in the decomposition of lignocellulose, chitin and phosphorus-containing organic compounds. This test system was used to describe the functional diversity of ECM communities in two forest sites. • This set of tests proved to be accurate and sensitive enough to reveal a high diversity of activity profiles, depending on the fungal symbiont and the soil horizon. Ectomycorrhizas can be classified into specialists and generalists, and appear to complement each other in the same horizon to collectively perform all eight activities studied. • By including a higher number of different assays for more detailed analyses, ECM activity profiling will provide a valuable tool for studying the functional diversity of ECM communities.
A*Prune: an algorithm for finding K shortest paths subject to multiple constraints

We present a new algorithm, A*Prune, to list (in order of increasing length) the first K multiple-constrained-shortest-path (KMCSP) between a given pair of nodes in a digraph in which each are is associated with multiple quality of-service (QoS) metrics. The algorithm constructs paths starting at the source and going towards the destination. But, at each iteration, the algorithm gets rid of all paths that are guaranteed to violate the constraints, thereby keeping only those partial paths that have the potential to be turned into feasible paths, from which the optimal paths are drawn. The choice of which path to be extended first and which path can be pruned depend upon a projected path cost function, which is obtained by adding the cost already incurred to get to an intermediate node to an admissible cost to go the remaining distance to the destination. The Dijkstra's shortest path algorithm is a good choice to give a good admissible cost. Experimental results show that A*Prune is comparable to the current best known /spl epsiv/-approximate algorithms for most of randomly generated graphs, BA*Prune, which combines the A*Prune with any known polynomial time /spl epsiv/-approximate algorithms to give either optimal or /spl epsiv/-approximate solutions to the KMCSP problem, is also presented.
Space-Time Filtering, Sampling and Motion Uncertainty

Abstract : The structure of filters which are space-time oriented is analyzed. Basically, this paper consists of two parts. The first presents the cascade of space-time DOG as an energy filter, discusses its general properties and show how to compute its energy. The second part discusses the consequences of applying the sampling theorem to uniformly translating patterns in the presence of motion uncertainty. It is shown that, for a given motion uncertainty, there exists a bound on the maximum sampling interval, such that for larger values aliasing will occur. Keywords: Dog filters; Machine Vision.
Age-related inhibition and learning effects: Evidence from transitive performance

In the absence of sufficient cognitive stimulation, intelligence — and with it, a capacity for learning new things — tends to degrade with age. In this paper I explore a novel hypothesis: that this may be an adaptive solution, since learning is facilitated by temporarily inhibiting action selection and thus introducing temporal delays. An older animal that is not being cognitively challenged may be in a sufficiently stable environment that reducing the delay before action at the cost of also reducing learning capacity may be a sensible tradeoff. I support parts of this model by matching a simulation of it to known reaction-time results, and by providing an account for previously unexplained task-learning results in adult and aged macaques.
Regularization parameter estimation for spectral regression discriminant analysis based on perturbation theory

Spectral regression discriminant analysis (SRDA) is an important subspace learning method. It has a tunable parameter, i.e., the regularization parameter, which critically affects the performance. However, how to set this parameter automatically has not been well solved to date. In SRDA, this regularization parameter was only set as a constant, which is usually suboptimal. In this paper, we develop a new algorithm to automatically estimate the regularization parameter of SRDA based on the perturbation linear discriminant analysis (PLDA). Experiments on multiple data sets demonstrate the effectiveness of the proposed method.
Refinements in the Object Oriented Software Development Process

Model Refinement is a dependency relationship that relates two elements that represent the same concept at different levels of abstraction. In the UML specification document this relationship, like others concepts, is still described in an ambiguous, informal way. In order to avoid inconsistencies and wrong model interpretations, in this article we propose, in first instance, a formalization of the Use Case specification, represented by a conversation between an actor and the system. The Use Case conversation does not have representation in the UML metamodel. In second instance we propose to formalize the refinement relation between model elements of the same kind, such as refinement relation between Use Cases and between Collaborations. Then on top of these formalizations, we discuss refinement relation between models of different kind (use case models and collaboration models realizing them) This work provides an enhancement to the UML metamodel specification. The formalization proposed should be used as a formal foundation for the construction of case tools performing consistency checking of models. Support offered by tools will improve the quality of software development process.
Biomechanical Evaluation of Strength and Stiffness of Subtalar Joint Arthrodesis Screw Constructs

Background: Subtalar arthrodesis is a common treatment for end-stage subtalar joint arthritis as well as many other clinical problems. The best method of subtalar arthrodesis fixation is unknown. The purpose of this study was to compare the strength of subtalar arthrodesis fixation methods including a single posterior screw (SP), 2 posterior minimally divergent screws (MD) and a 2 screw highly divergent screw (HD) construct for subtalar arthrodesis. Methods: A biomechanical study was performed including the three different screw configurations (SP, MD, HD). These surrogate bone specimens were subjected to applied inversion and eversion torques about the subtalar joint axis on a servo-hydraulic load frame. Torsional stiffness of the construct and the maximum torque for each configuration were measured. Additionally, a cadaver study was performed using 5 fresh-frozen cadaver specimens. The perpendicular distance from the divergent screw guide-wire placement was measured from anatomic structures. Results: The HD screw configuration was found to have the highest torsional stiffness in both inversion and eversion, followed by the MD construct and then the SP construct. Similarly, the HD construct had the highest maximum torque versus the MD and SP constructs. All between-group differences were statistically significant (P < .05). The mean distance from key structures to the divergent screw included the sural nerve (13 mm), peroneus brevis tendon (18 mm), tibialis anterior tendon (8 mm), and tibialis posterior tendon (21 mm). Conclusion: This biomechanical and cadaver study supports the use of 2 screws for fixation of subtalar arthrodesis over a single posterior screw. Additionally, we describe a biomechanically superior and potentially safe, alternative 2-screw divergent construct. Clinical Relevance: This study gives biomechanical support for 2 screw, divergent fixation of subtalar arthrodesis or a single over a single screw or two screw minimally divergent construct.
Ultra-Fast Analysis of Plasma and Intracellular Levels of HIV Protease Inhibitors in Children: A Clinical Application of MALDI Mass Spectrometry

HIV protease inhibitors must penetrate into cells to exert their action. Differences in the intracellular pharmacokinetics of these drugs may explain why some patients fail on therapy or suffer from drug toxicity. Yet, there is no information available on the intracellular levels of HIV protease inhibitors in HIV infected children, which is in part due to the large amount of sample that is normally required to measure the intracellular concentrations of these drugs. Therefore, we developed an ultra-fast and sensitive assay to measure the intracellular concentrations of HIV protease inhibitors in small amounts of peripheral blood mononuclear cells (PBMCs), and determined the intracellular concentrations of lopinavir and ritonavir in HIV infected children. An assay based on matrix-assisted laser desorption/ionization (MALDI) - triple quadrupole mass spectrometry was developed to determine the concentrations of HIV protease inhibitors in 10 µL plasma and 1×106 PBMCs. Precisions and accuracies were within the values set by the FDA for bioanalytical method validation. Lopinavir and ritonavir did not accumulate in PBMCs of HIV infected children. In addition, the intracellular concentrations of lopinavir and ritonavir correlated poorly to the plasma concentrations of these drugs. MALDI-triple quadrupole mass spectrometry is a new tool for ultra-fast and sensitive determination of drug concentrations which can be used, for example, to assess the intracellular pharmacokinetics of HIV protease inhibitors in HIV infected children.