Miracle-dz/UniFAR-FTUs huggingface dataset:
A Deeper Understanding of Consciousness Through the Study of Creativity

Abstract: Creativity is a multilevel process with a biological substratum. Studies of creativity signify the irreducibility of mind and may show the way beyond the quantum consciousness, unraveling its near-paranormal nature. The human mind should be regarded as a means of communication, constituting both a highly sophisticated receiver and a transmitter. The current genetic and psychopathological views of creativity are rooted in the reductionist model of consciousness. They are challenged by the parapsychological perspectives that offer us a broader vision of consciousness. Without adequate intellectual tools and an expanded model of the brain–mind consciousness complex, studies of creativity are inevitably erroneous. Psychography and evidences of discarnate existence may indicate that some original ideas may be flourishing in another dimension, in readiness for transfer to the minds of creative individuals. The assumed link between generativity and mental disorder can be clarified only when we elucidate the creative process, and parasciences may be able to clarify some of the conceptual confusions. Age related decline of creativity supports strongly the view that creativity has also a biological foundation.
Automatic Annotation of Spatial Expression Patterns via Sparse Bayesian Factor Models

Advances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D–4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions.
Classifies Human Cancers Somatic Cells But Triggers a Transcriptional Response that Does Not Transform Mouse Kras Knockin of Oncogenic

KRAS mutations are present at a high frequency in human cancers. The development of therapies targeting mutated KRAS requires cellular and animal preclinical models. We exploited adeno-associated virus–mediated homologous recombination to insert the Kras G12D allele in the genome of mouse somatic cells. Heterozygous mutant cells displayed a constitutively active Kras protein, marked morphologic changes, increased proliferation and motility but were not transformed. On the contrary, mouse cells in which we overexpressed the corresponding Kras cDNA were readily transformed. The levels of Kras activation in knock-in cells were comparable with those present in human cancer cells carrying the corresponding mutation. Kras-mutated cells were compared with their wild-type counterparts by gene expression profiling, leading to the definition of a ‘‘mutated Kras-KI signature’’ of 345 genes. This signature was capable of classifying mouse and human cancers according to their KRAS mutational status, with an accuracy similar to or better than published Ras signatures. The isogenic cells that we have developed recapitulate the oncogenic activation of KRAS occurring in cancer and represent new models for studying Kras-mediated transformation. Our results have implications for the identification of human tumors in which the oncogenic KRAS transcriptional response is activated and suggest new strategies to build mouse models of tumor progression. [Cancer Res 2007;67(18):8468–76]
Development of an IEEE 802 . 11 s Simulation Model for QualNet

In this work, an initial variant of an 802.11s simulation model for the QualNet simulator is described. The tool builds on the existing QualNet 802.11 model by adding capabilities suitable for mesh networking. More specifically, the model provides support for propagation of beacon frames in mesh networks and link establishment procedures by which nodes attach to the network.
A detailed methodology to compute Soft Error Rates in advanced technologies

System reliability has become a key design aspect for computer systems due to the aggressive technology miniaturization. Errors are typically dominated by transient faults due to radiation and are strongly related to the technology used to build hardware. However, there is a lack of detailed methodologies to model and fairly compare Soft Error Rates (SER) across different advanced technologies. This work first describes a common methodology that from (1) technology models, (2) location (latitude, longitude and altitude), (3) operating conditions and (4) circuit descriptions (i.e. SRAM, latches, logic gates) can obtain accurate Soft Error Rates. Then, we use it to characterize soft errors through current and future technologies. Results at the technology layer show that new technologies, such as FinFET and SOI, can reduce SER up to 100x while the location can increase SER up to 650x.
Metrology and visualization of potholes using the microsoft kinect sensor

Pavement distress and wear detection is of prime importance in transportation engineering. Due to degradation, potholes and different types of cracks are formed and they have to be detected and repaired in due course. Estimating the amount of filler material that is needed to fill a pothole is of great interest to prevent any shortage or excess, thereby wastage, of filler material that usually has to be transported from a different location. Metrological and visualization properties of a pothole play an important role in this regard. Using a low-cost Kinect sensor, the pavement depth images are collected from concrete and asphalt roads. Meshes are generated for better visualization of potholes. Area of pothole is analyzed with respect to depth. The approximate volume of pothole is calculated using trapezoidal rule on area-depth curves through pavement image analysis. In addition pothole area, length, and width are estimated. The paper also proposes a methodology to characterize potholes.
Human telomerase RNA and box H/ACA scaRNAs share a common Cajal body–specific localization signal

Telomerase is a ribonucleoprotein reverse transcriptase that uses its RNA component as a template for synthesis of telomeric DNA repeats at the ends of linear eukaryotic chromosomes. Here, fluorescence in situ hybridization demonstrates that in HeLa cancer cells, human telomerase RNA (hTR) accumulates in the nucleoplasmic Cajal bodies (CBs). Localization of transiently expressed hTR to CBs is supported by a short sequence motif (411-UGAG-414) that is located in the 3′-terminal box H/ACA RNA-like domain of hTR and that is structurally and functionally indistinguishable from the CB-specific localization signal of box H/ACA small CB-specific RNAs. In synchronized HeLa cells, hTR shows the most efficient accumulation in CBs during S phase, when telomeres are most likely synthesized. CBs may function in post-transcriptional maturation (e.g., cap hypermethylation of hTR), but they may also play a role in the assembly and/or function of telomerase holoenzyme.
Filipino Parenting in the USA

Migration entails complex transformations in family functioning and dynamics, especially when traditional parenting beliefs and practices are not consistent with mainstream norms in the host country. Whereas some culturally embedded parenting beliefs might persist even after migration, others may acculturate or shift to align with child-rearing norms in the host community. Using a qualitative research design with elements of indigenous Filipino psychology (Sikolohiyang Pilipino), this study explored parenting experiences and beliefs of Filipino immigrant parents in the USA, with a specific lens towards examining continuity and change in traditional parenting practices. Results suggest that participants strongly maintain many aspects of traditional Filipino parenting, including teaching Filipino culture and values, employing Filipino parenting practices, observing Filipino traditions, establishing the child’s identity and maintaining a Filipino household. Findings were situated in the context of the research site, the complexities of the acculturation process and the potential challenges of negotiating cultural differences in parenting beliefs and practices.
Architecture for Mobile IP Networks with Multiple Traffic Classes

Future mobile networks should support heterogeneous traffic including voice, video, audio, data, and multimedia. QoS provisioning for different traffic types in cellular networks is essential for their implementation as commercial networks. Mobile users are moving among cells in the network, thus changing the access point (i.e., the base stations engaged in the calls). The network should provide transparent and seamless handovers between the adjacent cells for different application types (i.e., services). On the other hand, network operators are interested in having efficient and maximum possible utilization of the resources. This is a trade between the quality of service on one side, and utilization on the other side. The final target is satisfied users and the highest possible revenue for the service providers or network operator. Various events in a mobile system are happening on different time scales. For example, the connection duration of a call is measured with tens of seconds or minutes, while packet transmission or serving is measured in milliseconds or even microseconds, depending upon wireless link capacity. Furthermore, user movement occurs on different time intervals, measured in seconds, minutes, or hours. This heterogeneity of events needs integration of many different elements in single network architecture. Also, we need to integrate several time scales considering the network design. In a mobile system one should consider the core network (wired part) and the wireless cellular access network (radio network), as well as their mutual functionality. The base stations are wireless access points of the network, which are interconnected via the core network with other nodes,
A MULTI SERVER MULTI USER APPROACH FOR DISTRIBUTED VIRTUAL ENVIRONMENTS

In this paper a VR architecture is described that enables an easy and very scalable way to build up multi user and multi wall projection systems for distributed applications and generic VR interface integration. The approach is based on a multi server architecture and a strict separation of two layers of control of the distributed virtual environment. The 3D representation is full VRML2.0 compliant thus all VRML sensors, events and sounds can be used. The same interactive 3D worlds run in full immersive VR theaters as well as on desktop systems. The virtual environment includes also a wired haptic system and a voice command system, constituting thus a multimodal interface with 3D visualization and haptic as output modalities and tracking, speech and gesture as input modalities.
A syntactical modeling and classification for performance evaluation of Bali traditional dance

This paper presents a linguistically motivated approach for dance gesture performance evaluation using skeleton tracking to robustly classify arbitrary dance gesture into one of predefined gesture classes and provide performance score in regards to the dance master's gesture. The gesture class in this study is a set common gesture of Bali traditional dances. The dance gesture is represented as a set of skeleton feature descriptors that are extracted from images captured using Kinect depth sensor. A set of rules are learned from the training examples to capture the structure of the gesture motion using grammar inference method. The empiric results showed that elbow and foot of dance performer are the most discriminative features for representing dance gesture of Bali traditional dance. Probabilistic and deterministic grammars achieved 0.92 and 0.95 of average precision for recognizing the tested dance gestures.
A Computation Offloading Scheme Leveraging Parameter Tuning for Real-Time IoT Devices

In recent years, proliferation of the Internet of things (IoT) devices and applications like video processing have caused a paradigm shift in computation requirement and power management in these devices. Furthermore, processing huge amount of data generated by connected IoT devices and meeting real-time deadline requirement of IoT applications is also a challenging problem. To address these challenges, we propose a computation offloading scheme where computing services requested by an IoT device are processed by a relatively resourceful computing devices (e.g., personal computer) in the same local network. In our proposed scheme, both client and server devices tune their tunable parameters, such as operating frequency and number of active cores, to meet the application's real-time deadline requirements. We compare our proposed scheme with contemporary computation offloading models that use cloud computing. Results verify that our proposed scheme provides a performance improvement of 21.4% on average as compared to cloud-based computation offloading schemes.
The economics in interactive information retrieval

Searching is inherently an interactive process usually requiring numerous iterations of querying and assessing in order to find the desired amount of relevant information. Essentially, the search process can be viewed as a combination of inputs (queries and assessments) which are used to "produce" output (relevance). Under this view, it is possible to adapt microeconomic theory to analyze and understand the dynamics of Interactive Information Retrieval. In this paper, we approach the search process as an economics problem and conduct extensive simulations on TREC test collections analyzing various combinations of inputs in the "production" of relevance. The analysis reveals that the total Cumulative Gain (output) obtained during the course of a search session is functionally related to querying and assessing (inputs), and this can be characterized mathematically by the Cobbs-Douglas production function. Further analysis using cost models, that are grounded using cognitive load as the cost, reveals which search strategies minimize the cost of interaction for a given level of output. This paper demonstrates how economics can be applied to formally model the search process. This development establishes the theoretical foundations of Interactive Information Retrieval, providing numerous directions for empirical experimentation that are motivated directly from theory.
Diachronic'Explorer: Keep track of your clusters

We introduce Diachronic'Explorer, a toolbox to produce and visualize diachronic results, which is based on a new complete theoretic framework that we detail. This toolbox, which is dedicated to run diachronic algorithms from clustering results, allows also to explore the complex results at all the granularity levels through a web application.
Using feature locality: can we leverage history to avoid failures during reconfiguration?

Despite the best efforts of software engineers, faults still escape into deployed software. Developers need time to prepare and distribute fixes, and in the interim deployments must either tolerate or avoid failures. Self-adaptive systems, systems that adapt to meet changing requirements in a dynamic environment, have a daunting task if their reconfiguration involves adding or removing functional features, because configurable software is known to suffer from failures that appear only under certain feature combinations. Although configuration-dependent failures may be difficult to provoke, and thus hard to detect in testing, we posit that they also constitute opportunities for reconfiguration to increase system reliability. We further conjecture that the failures that are sensitive to a system configuration depend on similar feature combinations, a phenomenon we call feature-locality, and that this locality can be combined with historical data to predict failure-prone configurations. In a case study on 128 failures reported against released versions of an open source configurable system, we find evidence to support our hypothesis. We show that only a small number of features affect the visibility of these failures, and that over time we can learn these features to avoid future failures.
Collaborative Filtering with Entity Similarity Regularization in Heterogeneous Information Networks

Researchers have been studying hybrid recommender systems which combine user-item rating data with external information in recent years. Some studies suggest that by leveraging additional user and / or item relations, e.g., social network, the performance of the recommendation models can be improved. These studies, nevertheless, mostly utilize a single type of external relationship. Considering the heterogeneity of real-world applications, we propose to position the well-studied recommendation problem in a heterogeneous information network context and attempt to incorporate different recommendation factors. We discuss how heterogeneous information network can benefit recommender systems and then propose a matrix factorization based unified recommendation model to take advantage of both rating data and the related information network. Empirical studies show that our approach outperforms several state-of-the-art recommendation methods on explicit rating data.
Bi-Level Image Compression Estimating the Markov Order of Dependencies

This paper presents a bi-level image compression method based on chain codes and entropy coders. However, the proposed method also includes an order estimation process to estimate the order of dependencies that may exist among the chain code symbols prior to the entropy coding stage. For each bi-level image, the method first obtains its chain code representation and then estimates its order of symbol dependencies. This order value is used to find the conditional and joint symbol probabilities corresponding to our newly defined Markov model. Our order estimation process is based on the Bayesian information criterion (BIC), a statistically based model selection technique that has proved to be a consistent order estimator. In our experiments, we show how our order estimation process can help achieve more efficient compression levels by providing comparisons against some of the most commonly used image compression standards such as the Graphics Interchange Format (GIF), Joint Bi-level Image Experts Group (JBIG), and JBIG2.
Optimized High-Resolution Simulation of a THz Traveling Wave Tube Amplifier

Modeling of complex systems typically requires many iterations of theoretical design, numerical simulation, and analysis. The goal of this project was to develop an automated optimization framework to optimize a 0.22 THz traveling wave tube (TWT) high-power amplifier design. Applications for such an amplifier include three-dimensional (3D) imaging systems for medical uses, detection of concealed hazardous materials, and high-bandwidth communications. An optimization framework was developed for the DoD Supercomputing Resource Center (DSRC) environment to automatically queue and track many simultaneous thousand CPU hour jobs. Results were automatically evaluated, collated, and used to refine simulations, thus saving many man-hours otherwise used for performing parameter scans and analysis. Prior efforts typically required thousands of manually submitted jobs over the course of three years, and resulted in a design that did not meet the desired specifications, e.g., the electron-gun (e-gun) component produced a noisy 4.4 mA, 150 μm diameter electron beam which fed into a 13 dB amplifier that exhibited detrimental backwards-wave oscillations. The automated effort produced thousands of runs over a month and met the design goals with an e-gun providing a low-noise, 10 mA, 100 μm diameter electron beam feeding into a 21 dB amplifier with no backwards-wave oscillations. The work presented here involved thousands of runs consuming around 3.8 million CPU hours. Hence, the near-exclusive access provided by the Capabilities Application Project was critical for the success of this effort.Prior efforts typically required thousands of manually submitted jobs over the course of three years, and resulted in a design that did not meet the desired specifications, e.g., the electron-gun (e-gun) component produced a noisy 4.4 mA, 150 μm diameter electron beam which fed into a 13 dB amplifier that exhibited detrimental backwards-wave oscillations. The automated effort produced thousands of runs over a month and met the design goals with an e-gun providing a low-noise, 10 mA, 100 μm diameter electron beam feeding into a 21 dB amplifier with no backwards-wave oscillations. The work presented here involved thousands of runs consuming around 3.8 million CPU hours. Hence, the near-exclusive access provided by the Capabilities Application Project was critical for the success of this effort.
Measuring basic tempo across languages and some implications for speech rhythm

Basic language-inherent tempo cannot be isolated by the current metrics of speech rhythm. Here we propose the number of syllables per intonation unit as an appropriate measure, also for large-scale comparisons between languages. Applying it to an extended sample of in the meantime 51 languages has not only corroborated our previously reported negative cross-linguistic correlation of this metric with syllable complexity, but has revealed, moreover, significant correlations with several in part directly time-dependent rhythm measures proposed by other authors. We discuss relations between intrinsic tempo and (a) other facets of rhythm and (b) rhythm classifications of language. Index Terms: tempo, metrics, rhythm, syllable complexity, intonation unit, cross-linguistic correlations
Accounting conservatism and disposition effect

The financial crisis in 2008 caused a worldwide economic disruption, and also led to growing in-depth thinking. This article considers the governance role of the accounting conservatism on capital market irrational behavior, the disposition effect, from the angle of accounting. We find that conservatism has apparently offset the effect of “overestimate “and “underestimate” caused by the disposition effect. From an accounting level, we find the governance mechanisms of compensating the inaccurate pricing of market, and the research provides a powerful basis for investors, market regulators and standard setters.