Miracle-dz/UniFAR-FTUs huggingface dataset:
Impediments to general purpose Content Based Image search

Challenges faced by prevailing text metadata paradigms for online image search have inspired overwhelming research in Content Based Image Retrieval (CBIR). A multitude of approaches have been introduced within the literature, yet relatively few image search engines have been made publicly available on the web. Aside from challenges facing the user, such as describing a visual query using keywords, or finding an appropriate example image to initiate a visual search, all systems must inevitably grapple with the sensory and semantic gaps [Smeulders et al. 2000], which essentially represent a loss of information in the abstraction process. In this work, we challenge commonly suggested approaches to improving CBIR and illustrate drawbacks of relying on textual data, as well as visual data, in general CBIR search. We provide cogent examples using online visual search engines Behold#8482;, Tiltomo Beta, Pixilimar, and Riya#8482; Beta. These examples demonstrate the effect of semantic ambiguities in natural language, which extend to search terms and text tags.
A framework architecture based model for cloud computing adaptive migration

Cloud computing is increasingly adopted by organizations at a rapid pace thanks to its attractive characteristics. However, this adoption is not yet structured enough to guarantee a successful migration towards these environments. Several questions are raised but not yet entirely answered since this new form of computing offering is still in its formative stage. Main difficulties are confronted specially because cloud computing change radically IT infrastructure and more generally architecture. This paper thus proposes a model for cloud computing adaptive migration to guide the organization throughout the migration process while taking into consideration architectural principles and constraints.
ONTOLOGIES SUPPORTING COOPERATIONS IN MASS CUSTOMIZATION - A PRAGMATIC APPROACH

Mass Customization (MC) as a modern competitive strategy enables enterprises to act in dynamic markets with high customer satisfaction. But, for a successful implementation of this management concept, effective information logistics is essential. Ontologies are considered as a promising approach for optimizing inter-organizational and distributed cooperation. Although there have been several publications on ontologies and their usage we are going to show that none of these approaches can satisfy the requirements of the Mass Customization domain completely. They either do not consider requirements like natural distribution and inherent heterogeneity of all members along the supply chain nor customer needs sufficiently, which are both typical properties in this domain. In this paper, a formal conceptualization of Mass Customization scenarios within an ontology will be introduced. Doing so, we will firstly illustrate the general concept of ontologies. Then we will discuss the components of an MC-ontology and its sub-models. The originalities of a particular domain are shown for the shoe industry as an example.
Prediction of an U 2 S 3 -type polymorph of Al 2 O 3 at 3.7 Mbar

We predict by first principles a phase transition in alumina at 3.7 Mbar and room temperature from the CaIrO3-type polymorph to another with the U2S3-type structure. Because alumina is used as window material in shock-wave experiments, this transformation should be important for the analysis of shock data in this pressure range. Comparison of our results on all high-pressure phases of alumina with shock data suggests the presence of two phase transitions in shock experiments: the corundum to Rh2O3(II)-type structure and the Rh2O3(II)-type to CaIrO3-type structure. The transformationtotheU2S3-typepolymorphisinthepressurerange reached in the mantle of recently discovered terrestrial exoplanets and suggests that the multi-megabar crystal chemistry of planetforming minerals might be related to that of the rare-earth sulfides. alumina first-principles calculation high-pressure phase transition postperovskite rare-earth sulfide structure
Human eye feature extraction based on segmented binarization

For facial feature extraction problems, eye feature extraction is a basic and critical work. This paper presents a human eye feature extraction method based on segmented binarization. After binarization we detect the eye corner points by the corner detector which is based on the curve scale space. The detector uses adaptive threshold and dynamic region of support. Due to the corner detection errors, we propose a method which uses the mean of the local area around the corner to correct them. Experiments show that the proposed method is effective.
Supervised Keyphrase Extraction as Positive Unlabeled Learning

The problem of noisy and unbalanced training data for supervised keyphrase extraction results from the subjectivity of keyphrase assignment, which we quantify by crowdsourcing keyphrases for news and fashion magazine articles with many annotators per document. We show that annotators exhibit substantial disagreement, meaning that single annotator data could lead to very different training sets for supervised keyphrase extractors. Thus, annotations from single authors or readers lead to noisy training data and poor extraction performance of the resulting supervised extractor. We provide a simple but effective solution to still work with such data by reweighting the importance of unlabeled candidate phrases in a two stage Positive Unlabeled Learning setting. We show that performance of trained keyphrase extractors approximates a classi-ﬁer trained on articles labeled by multiple an-notators, leading to higher average F 1 scores and better rankings of keyphrases. We apply this strategy to a variety of test collections from different backgrounds and show improvements over strong baseline models.
Enabling Scalable Cloud Infrastructure Using Autonomous VM Migration

Service providers and enterprises capitalize on evolving cloud computing technologies when building datacenters for their own computing infrastructure and/or for providing services to others. Virtual machines and their migration are an important underlying technology of Infrastructure as a Service (IaaS) for building efficient cloud computing infrastructure on a cluster of servers. Autonomous migration of virtual machines is designed to increase the overall resource utilization on a cluster of servers. If a particular computing pattern caused imbalance that triggers migration, this pattern will be remembered or "learned" with its corresponding migration details for future use. In this paper, we use a proactive learning methodology that not only accumulates the past history of computing patterns and resulting migration decisions but more importantly searches all predefined possibilities for the most suitable decisions. We set up an experimental environment that consists of extensive real world benchmarking problems and a cluster of 16 physical machines each of which has on average eight virtual machines. We demonstrate through experimental results that our self regulated autonomous VM migration increases resource utilization of the servers on which cloud computing IaaS is currently running.
A Calcium-Dependent Plasticity Rule for HCN Channels Maintains Activity Homeostasis and Stable Synaptic Learning

Theoretical and computational frameworks for synaptic plasticity and learning have a long and cherished history, with few parallels within the well-established literature for plasticity of voltage-gated ion channels. In this study, we derive rules for plasticity in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and assess the synergy between synaptic and HCN channel plasticity in establishing stability during synaptic learning. To do this, we employ a conductance-based model for the hippocampal pyramidal neuron, and incorporate synaptic plasticity through the well-established Bienenstock-Cooper-Munro (BCM)-like rule for synaptic plasticity, wherein the direction and strength of the plasticity is dependent on the concentration of calcium influx. Under this framework, we derive a rule for HCN channel plasticity to establish homeostasis in synaptically-driven firing rate, and incorporate such plasticity into our model. In demonstrating that this rule for HCN channel plasticity helps maintain firing rate homeostasis after bidirectional synaptic plasticity, we observe a linear relationship between synaptic plasticity and HCN channel plasticity for maintaining firing rate homeostasis. Motivated by this linear relationship, we derive a calcium-dependent rule for HCN-channel plasticity, and demonstrate that firing rate homeostasis is maintained in the face of synaptic plasticity when moderate and high levels of cytosolic calcium influx induced depression and potentiation of the HCN-channel conductance, respectively. Additionally, we show that such synergy between synaptic and HCN-channel plasticity enhances the stability of synaptic learning through metaplasticity in the BCM-like synaptic plasticity profile. Finally, we demonstrate that the synergistic interaction between synaptic and HCN-channel plasticity preserves robustness of information transfer across the neuron under a rate-coding schema. Our results establish specific physiological roles for experimentally observed plasticity in HCN channels accompanying synaptic plasticity in hippocampal neurons, and uncover potential links between HCN-channel plasticity and calcium influx, dynamic gain control and stable synaptic learning.
Regulation of C-C motif chemokine ligand 2 and its receptor in human decidual stromal cells by pregnancy-associated hormones in early gestation.

BACKGROUND Decidua is in close contact with the fetal trophoblasts, and involved in immune relationship of mother to fetus. However, the roles of decidua and decidual stromal cells (DSC) in materno-fetal immune regulation remain to be elucidated. In the present study, the expression and regulation of chemokines and their receptors in decidua and DSCs were investigated. METHODS AND RESULTS The transcription of 18 chemokine receptors in human first-trimester decidual tissue and DSC were first analysed by RT-PCR. Among these receptors, C-C motif chemokine receptor-2 (CCR2) was highly transcribed. It was demonstrated by RT-PCR and immunostaining that both CCR2 and its major ligand, C-C motif chemokine ligand 2 (CCL2, monocyte chemoattractant protein-1), were expressed in decidua and DSC. We then detected CCL2 in the supernatant of primary cultures of DSC by enzyme-linked immunosorbent assay. It was shown that DSC secreted CCL2 spontaneously and continuously over 72 h (21.72 +/- 2.34 ng/ml), and the CCR2 antagonist RS102895 and an inhibitor of the map kinase kinase/mitogen-activated protein kinase (ERK/MAPK) signal pathway decreased significantly the CCL2 secretion of DSC (both P < 0.05). We further studied effects of the pregnancy-associated hormones, estrogen, progesterone or HCG on CCL2 secretion by DSC. CCL2 secretion by DSC was up-regulated by estrogen, progesterone or HCG. CONCLUSIONS CCR2 and CCL2 are co-expressed by human first-trimester DSC and decidual tissue. CCL2 is secreted in an autocrine manner through the ERK/MAPK pathway, and is up-regulated by the pregnancy-associated hormones, estrogen, progesterone and HCG, which suggests that CCL2 may play an important role at materno-fetal interface.
Sustained spiral calcium wave patterns in rat ventricular myocytes

Ca2+ waves, propagating in non-stimulated isolated cardiac myocytes under physiological conditions, are described as planar waves traveling along the longitudinal cell axis [1]. Other patterns of Ca2+ wave propagation – circular or spiral Ca2+ waves [2, 3]– have been observed in physiological conditions as well. Lipp & Niggli, 1993 [2], Ishida et al., 1999 [3] and Engel et al., 1994 [4] have described spiral calcium waves as individual events. We demonstrate hereby existence of repetitive spiral calcium wave patterns in adult rat ventricular cardiomyocytes. The work was done on 20-week old Wistar rats. Myocytes were isolated with retrograde perfusion of the heart with proteolytic enzymes [5] and loaded with calcium indicator Fluo-3/AM (1 μmol/l). The fluorescence emission was recorded with laser scanning confocal microscope LSM 510 Meta, Zeiss (frame rate from 8 to 14 frames/s, excitation/emission 488/515 nm), equipped with C-Apochromat 40/NA = 1.2 water immersion objective. We observed both planar, circular (Fig. 1A, B) and spiral calcium waves (Fig. 1C) in the same myocyte. Figure 1C shows four subsequent spiral waves, demonstrating repetitive propagation of the spiral wave burning from the same origin. We observed an average of 8 spiral waves per cell, ranged 1–49. The median burning time of the spiral wave was 0.9 s, ranged from 0.4 to 13.7 s (n = 133 spiral calcium waves, 12 cells). The percentage of the spiral waves duration with respect to the entire recording time (ranged from 131 to 227 seconds, n = 12 cells) was 10.8%, ranged from 0.6 to 26.5%. The repetitive spiral waves (defined as waves progressed further after reaching its initial position) were detected in 56 cases from all spiral waves observed (n = 133). The spiral wave pattern formation was a reversible process, as we observed also return to planar-type burning. No blebs or hypercontractures were observed when the recording of the cell was finished. 1 Recording of the (A) planar, (B) circular and (C) spiral calcium waves in an isolated rat left ventricular myocyte after staining with calcium indicator Fluo-3/AM imaged with confocal laser scanning microscopy. Frame interval: 113 ms. Scale bar: 20 μm. In contrast to the smaller amplitude of the spiral waves described by Ishida et al., 1999 [3], we observed no difference in relative amplitudes of the calcium waves: planar wave preceding the spiral wave (4.1, range 2.4–6.1), spiral (4.0, range 2.4–6.2) and subsequent planar wave (4.2, range 2.2–5.8, n = 9 waves analyzed) were not significantly different. Moreover, we observed no decrease in the amplitude of the repetitive wave when compared the starting and ending point.This contributes to the stabilization of the spiral burning and allows its long-time propagation. We suggest that the repetitive spiral waves can be considered as a temporary equilibrated state in myocyte calcium wave spreading. As calcium waves are capable of traversing to the adjacent cells via gap junctions [4], a cell with repetitive spiral bursts may negatively impact functioning of the adjacent myocytes.
On the relation between adaptive functioning and the reinforcement function of challenging behavior

Objectives: Individuals with intellectual and developmental disabilities (IDD) are at an increased risk to engage in challenging behavior (CB), such as self-injury and aggression. For individuals with IDD, CB is believed to be the product of their disabilities and learning histories. Thus, deficits in adaptive behavior can lead to the occurrence of CB, which can produce reactions on the part of others that inadvertently reinforce the behavior. Research has shown that in most cases, functional behavioral assessment of CB can identify the reinforcement ‘function’ (e.g. to escape non-preferred situations, or gain access to attention), knowledge of which is critical to the development of behavioral treatments. Despite a strong link between deficits in adaptive behavior skills and CB, research has yet to examine how adaptive behavior is related to specific functions of CB. Methods: Vineland-II Parent/Caregiver and Survey results were administered to caregivers of 53 participants receiving treatment for CB. Results were compared to functional analysis outcomes of the participants CB. Results: Participants with CB maintained by automatic (or sensory) reinforcement had significantly lower scores in the Adaptive Behavior Composite, as well as the Socialization and Daily Living Skills domains. Participants with attention-maintained CB had higher scores in certain domains. Conclusions: Although effect sizes for both of these analyses were small, this study was exploratory in nature, and results indicate that the relationship between adaptive behavior and functions for CB warrants further investigation to determine how these impact each other.
Toward an analytic framework for understanding and fostering peer-support communities in using and evolving software products

The fundamental challenge for social computing is to contribute to fostering communities in which humans can transcend the limitation of the unaided,individual human mind by helping each other.Going beyond antidotal examples requires an analytical framework in which to interpret data in order to understand the context- and application-specific nature of these collaborations. We have studied peer-support communities (PSCs) in the context of the SAP Community Network (SCN), which relies on forums and conferences to support their collaboration. This research attempts to create a deeper understanding of the effectiveness of social support provided by peers in software development communities from the following perspectives: Responsiveness--how responsive are communities to the needs of its members? Engagement Intensity--how timely is the peer support? Role Distribution--how wide is the participation of users and in what kind of roles do they participate? Reward System--what is the impact of explicit reward (point) systems on community behavior? The data gained from analyzing these perspectives (and their comparison with open source software peer-support communities) has provided insights and led to an increased understanding of what works in PSCs. Here we articulate some initial design guidelines to further improve the potential benefits gained from these communities.
Correction Annotation for Non-Native Arabic Texts: Guidelines and Corpus

We present our correction annotation guidelines to create a manually corrected nonnative (L2) Arabic corpus. We develop our approach by extending an L1 large-scale Arabic corpus and its manual corrections, to include manually corrected non-native Arabic learner essays. Our overarching goal is to use the annotated corpus to develop components for automatic detection and correction of language errors that can be used to help Standard Arabic learners (native and non-native) improve the quality of the Arabic text they produce. The created corpus of L2 text manual corrections is the largest to date. We evaluate our guidelines using inter-annotator agreement and show a high degree of consistency.
An experimental comparison of audio tempo induction algorithms

We report on the tempo induction contest organized during the International Conference on Music Information Retrieval (ISMIR 2004) held at the University Pompeu Fabra in Barcelona, Spain, in October 2004. The goal of this contest was to evaluate some state-of-the-art algorithms in the task of inducing the basic tempo (as a scalar, in beats per minute) from musical audio signals. To our knowledge, this is the first published large scale cross-validation of audio tempo induction algorithms. Participants were invited to submit algorithms to the contest organizer, in one of several allowed formats. No training data was provided. A total of 12 entries (representing the work of seven research teams) were evaluated, 11 of which are reported in this document. Results on the test set of 3199 instances were returned to the participants before they were made public. Anssi Klapuri's algorithm won the contest. This evaluation shows that tempo induction algorithms can reach over 80% accuracy for music with a constant tempo, if we do not insist on finding a specific metrical level. After the competition, the algorithms and results were analyzed in order to discover general lessons for the future development of tempo induction systems. One conclusion is that robust tempo induction entails the processing of frame features rather than that of onset lists. Further, we propose a new "redundant" approach to tempo induction, inspired by knowledge of human perceptual mechanisms, which combines multiple simpler methods using a voting mechanism. Machine emulation of human tempo induction is still an open issue. Many avenues for future work in audio tempo tracking are highlighted, as for instance the definition of the best rhythmic features and the most appropriate periodicity detection method. In order to stimulate further research, the contest results, annotations, evaluation software and part of the data are available at http://ismir2004.ismir. net/ISMIR_Contest. html
Relay based identification of process dynamics under noisy environment

Using an asymmetrical relay based approach, a set of generalized expressions for the identification of integrating first order plus dead time (IFOPDT) and second order plus dead time (ISOPDT) processes are derived. From derived expressions, calculation for unknown process model parameters with small and large dead time is performed. When the process output is subjected to measurement noise, a well known method is attempted in order to extract the important information from the limit cycle output. Examples are illustrated to show the effectiveness of method which successfully recovers the limit cycle under noisy environment. Subsequently, from denoised limit cycle, identified parameters are used for estimation of process model dynamics. Finally, a comparison between identified and actual process is demonstrated through simulation by Nyquist plot.
Force field evolution during human blood platelet activation

Summary Contraction at the cellular level is vital for living organisms. The most prominent type of contractile cells are heart muscle cells, a less-well-known example is blood platelets. Blood platelets activate and interlink at injured blood vessel sites, finally contracting to form a compact blood clot. They are ideal model cells to study the mechanisms of cellular contraction, as they are simple, having no nucleus, and their activation can be triggered and synchronized by the addition of thrombin. We have studied contraction using human blood platelets, employing traction force microscopy, a single-cell technique that enables time-resolved measurements of cellular forces on soft substrates with elasticities in the physiological range (∼4 kPa). We found that platelet contraction reaches a steady state after 25 min with total forces of ∼34 nN. These forces are considerably larger than what was previously reported for platelets in aggregates, demonstrating the importance of a single-cell approach for studies of platelet contraction. Compared with other contractile cells, we find that platelets are unique, because force fields are nearly isotropic, with forces pointing toward the center of the cell area.
Assessing linearity in high dimensions 1 Art

Some standard numerical problems become intractable in high dimensions. Yet successes are often achieved in practice. This may be explained in terms of the underlying target function being somehow simpler than assumed in the intractability arguments. A prototypical form of simplicity is approximate linearity. In moderate dimensions linearity can be investigated by linear regression. In very high dimensions this becomes computationally inefficient and eventually infeasible, as the cost of regression for n observations in d dimensions grows as nd2. This paper presents a quasi-regression method for determining the degree of linearity in a function, where the cost grows only as nd. A bias corrected version of quasi-regression is able to estimate the degree of linearity with a sample size of order d2/3. An example is given of a function on [0, 1]1,000,000, for which the amount of linear variability is accurately estimated from only 100, 000 observations.