Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dynamic Executive Function Frame work for Linking Attention, Adjustment and Cognitive flexibility of School Children to Yoga: A Review

In the age group of 5 to 13 years school going children there is always a fast growth of Executive Function (EF) parts of the brain. The EF growth gets shunted in the given school environment, where the growing genes of the children and their syllabus plays a major role. During this period, the children are loaded with heavy school curriculum and thus limiting the learning processes and creatively get lost in curriculum based growth. In this paper we propose to strengthen the EF functioning through a complimentary Yoga frame. This new frame gives us a protocol of yoga techniques to improve, the Attention, Adjustment and Cognitive flexibilities of the mind. Supplementation of yoga along with curriculum inculcates the habit of cognitive aspects of the brain which will make their carriers useful and betterment of the society. Yoga frame for children mediates the link between school curriculum and with EF resulting into better outputs underlying benefits of yoga.
The Met pathway: master switch and drug target in cancer progression

It has been recognized for more than a century that most tumors tend to become more aggressive in clinical behavior over time, although this time course may be variable. This phenomenon has been termed “cancer progression,” a process that appears to develop in a stepwise fashion through qualitatively different stages. Cancer progression relies on the ability of neoplastic cells to abandon their primary site of accretion, trespass tissue boundaries, and penetrate into the vasculature to colonize and repopulate distant sites. Among the various properties associated with cancer progression, the acquisition by neoplastic cells of the capacity to invade locallyand to metastasize is of great clinical significance, and is still the fundamental definition of malignancy. This process represents the aberrant counterpart of a physiological morphogenetic program, known as invasive growth, occurring during embryo development and, in some instances, in adulthood for the generation and maintenance of normal organ complexity and architecture. Here we summarize some of the strategies adopted to inhibit cancer cell growth and spreading. We also review the current findings about cancer and metastasis inhibitors. As we suggest possible directions for drug development, we propose the receptor for the hepatocyte growth factor, Met, as an ideal target for tackling cancer progression. —Mazzone, M. , Comoglio, P. M. The Met pathway: master switch and drug target in cancer progression. FASEB J. 20, 1611–1621 (2006)
Preferential cholesteryl ester acceptors among the LDL subspecies of subjects with familial hypercholesterolemia.

Elevated cholesteryl ester transfer protein-mediated transfer of cholesteryl ester (CE) from high-density lipoprotein (HDL) to low-density lipoprotein (LDL) may contribute to the atherogenicity of LDL in subjects with familial hypercholesterolemia (FH). To identify the major CE acceptors among LDL subspecies, we investigated the qualitative and quantitative features of CE transfer and exchange to LDL on incubation of plasma under physiological conditions. LDL subspecies were fractionated by density-gradient ultra-centrifugation. Both mass transfer and exchange of HDL CE to and with very-low-density lipoprotein plus intermediate-density lipoprotein and LDL were linear for the first 6 hours of incubation. Thereafter mass transfer ceased, but exchange continued at a comparable rate. The rate of CE mass transfer to apolipoprotein B-containing lipoproteins was significantly enhanced in heterozygous FH subjects compared with normolipidemic individuals (91.6 +/- 28.2 versus 52.9 +/- 19.6 micrograms CE/h per milliliter plasma, FH versus normal subjects, P < .02). In FH subjects the predominant LDL subspecies (LDL 3 and 4, d = 1.029 to 1.050 g/mL) accounted for 59.7 +/- 9.2% of the total CE transferred to LDL from HDL. By contrast, expression of CE mass transfer relative to the mass of each lipoprotein acceptor showed the triglyceride (TG)-rich (10.7% to 17.3%), light LDL subspecies (LDL 1 and 2, d = 1.019 to 1.029 g/mL) to represent the preferential CE acceptors (LDL 1 and 2, 94.8 to 136.5 micrograms CE/mg LDL mass; LDL 3 through 5 [d = 1.029 to 1.063 g/mL], 47.1 to 64.1 micrograms CE/mg LDL mass). (ABSTRACT TRUNCATED AT 250 WORDS)
¿Quiénes se fueron? Aproximaciones a los motivos de abandono de un programa de apuntalamiento a las trayectorias educativas de estudiantes universitarios

La masificacion universitaria, que conlleva un incremento en la cantidad de ingresantes a las universidades, plantea situaciones novedosas a ese nivel educativo en terminos de composicion social del estudiantado. Distintos intentos de dar respuesta a esas problematicas han surgido, algunos de ellos, provenientes de organizaciones de la sociedad civil. En el presente articulo presentamos los resultados de parte de una evaluacion de un programa educativo de apuntalamiento a la trayectoria universitaria de jovenes provenientes de sectores vulnerables de Argentina. Especificamente, abordamos los motivos aducidos por aquellas personas “ex – participantes” para concluir su incursion en el Programa. Con este objetivo se desplego una investigacion cuya estrategia metodologica fue cualitativa y consto de la realizacion de 15 entrevistas en profundidad a jovenes que dejaron de formar parte del programa evaluado. Con el fin de dar cuenta de los repertorios que explican la salida del Programa de los “ex becarios”, se los dividio en dos grandes grupos: quienes salieron del Programa por sugerencia de las organizaciones de la sociedad civil que lo gestionan, y a traves de las cuales se materializaba su adhesion a la estrategia; y quienes se “salieron” por iniciativa propia. La investigacion da cuenta de tendencias actuales para las trayectorias universitarias, que combinan periodos de abandono con la promesa —muchas veces cumplida—de continuar los estudios, y la necesidad de compatibilizar el estudio con el trabajo.
Chemical evolution and depletion pattern in Damped Lyman α systems

Dust depletion plays a key role in understanding the nature of Damped Lyman α systems (DLAs). In this paper we point out a previously unnoticed anticorrelation between the observed abundance ratio [X/Zn] (where Zn is assumed to be undepleted and X stands for the refractories Fe, Cr and Ni) and metal column density ([Zn/H] + log(NHI)) in DLAs. We suggest that this trend is an unambiguous sign of dust depletion, since metal column density is a measure of the amount of dust along the line of sight. Assuming that DLAs are (proto-) galactic disks and using detailed chemical evolution models with metallicity dependent yields we study chemical evolution and dust depletion patterns for α and iron−peak elements in DLAs. When observational constraints on the metal column density of DLAs are taken into account (as suggested in Boissé et al. 1998) we find that our models reproduce fairly well the observed mild redshift evolution of the abundances of 8 elements (Al, Si, S, Cr, Mn, Fe, Zn and Ni) as well as the observed scatter at a given redshift. By considering the aforementioned dependence of abundance ratios on metal column density, we further explore the general dust depletion pattern in DLAs, comparing to our model results and to a solar reference pattern. We find that for low metal column densities (no depletion), our models compare fairly well to the data, while a solar pattern has difficulties with Mn. At high metal column densities (amount of depletion ∼0.5 dex), the solar pattern describes the data quite well, while our models have difficulties with S. We suggest that further measurements of those key elements, i.e. Zn, S and Mn, will help us to gain more insight into the nature of DLAs. The presently uncertain nucleosynthesis of Zn in massive stars (on which a large part of these conclusions is based) should be carefully scrutinised.
Context modulation of Sensor Data Applied to Activity Recognition in Smart Homes

In this paper we present a method of modulating the context of data captured in smart homes. We show that we can dramatically adapt their sensor network topology and that this approach can be used to help understand various aspects of such sensor environments. We demonstrate how, with our software, we can discover the importance of individual sensors, clusters of sensors and sensor categories for resident identification and activity recognition. Finally, we validate the utility of context modulation in a number of experimental scenarios that show how the activity recognition is affected by each sensor topology elicited by these scenarios.
Global Technology, Local Adoption: A Cross-Country Investigation of Internet Adoption by Companies in the United States and China

To gain a better understanding of the global diffusion of e-business among organizations in developed and developing countries and to investigate the relationships among e-business contexts, economic environment, and organizational adoption, we conducted a firm-level survey in two countries — the United States and China — and tested a research framework built upon the technology-organization-environment framework. Empirical data from 262 US firms and 175 Chinese firms provided evidence about the extent of organizational adoption of ebusiness. Major findings include: 1) Chinese firms lag in using e-business-related technologies, especially interorganizational technologies; 2) US firms make more extensive use of the Internet; and 3) government regulation plays a more important role in China than in the US. Moreover, using structural equation modelling, we further teased out four adoption facilitators in general — technology competence, enterprise integration, competition intensity, and regulatory environment. These factors played different roles in different economic environments. The paper concludes with a discussion of the major results and implications. Keyword: Internet, electronic business, adoption, innovation diffusion, global environment, cross-country study, technologyorganization-environment framework A u t h o r s Sean Xu (xxu00@gsm.uci.edu) is a doctoral student of Information Systems in the Graduate School of Management at the University of California, Irvine. His research focuses on e-business adoption/diffusion in a global environment and the business value of IT and e-business. Kevin Zhu (kzhu@uci.edu) received his PhD from Stanford University and is currently an Assistant Professor of Information Systems in the Graduate School of Management at the University of California, Irvine. His research focuses on e-business, global electronic markets, strategic IT investments, and economic/organizational impacts of IT. Jennifer L. Gibbs (jlgibbs@uci.edu) is Senior Research Fellow at the Center for Research on Information Technology and Organizations (CRITO), at the University of California, Irvine. Her research focuses on social impacts of information technology in global teams and organizations. She is currently researching global e-commerce diffusion across numerous countries. Global Technology, Local Adoption: A Cross-Country Investigation of Internet Adoption by Companies in the United States and China SEAN XU, KEVIN ZHU, AND JENNIFER GIBBS
Comparative study of CMOS- and FinFET-based 10T SRAM cell in subthreshold regime

This article presents a variability resilient FinFET based 10T SRAM cell. Critical design metrics of SRAM cells are estimated at subthreshold region and compared with that of conventional MOSFET based 10T SRAM cell. The FinFET based SRAM cell offers 2.33× and 1.29× improvements in Read Access Time (T<sub>RA</sub>) and Write Access Time (T<sub>WA</sub>) respectively. The proposed bitcell also offers 7.06× and 1.54× improvements in T<sub>RA</sub> and T<sub>WA</sub> variability respectively compared to its MOSFET counterpart. Moreover, our bitcell exhibits 20% higher read static noise margin (RSNM) at a cost of 5% reduction in write static noise margin @ 400 mV.
Sexual orientation moderates the association between parental overprotection and stress biomarker profiles

ABSTRACT Early experiences with parents may be particularly difficult for lesbian, gay and bisexual (LGB) individuals who face stigma that is linked to potentially distinct stress-related biobehavioural profiles. This study examined the association between parental bonding in relation to acute stress (cortisol reactivity) and chronic stress (allostatic load) in LGB and heterosexual individuals. The sample consisted of 87 healthy adults (mean [SD] age = 24.6 [0.6] years; LGB: n = 46, 43% women; and heterosexual n = 41, 49% women). Regressions tested the main effects of retrospectively assessed parental overprotection and care before the age of 16 on stress reactive cortisol (area under the curve) and allostatic load (indexed using 21 neuroendocrine, immune, metabolic and cardiovascular biomarkers), and whether sexual orientation status moderated this association. Results revealed that parental overprotection was associated with increased cortisol reactivity only for LGB participants, but not for heterosexual participants. By contrast, parental overprotection was associated with higher allostatic load only for heterosexual participants, but not for LGB participants. While the functional significance of this requires further study, these preliminary findings suggest that adaptive processes among LGB individuals may mitigate the negative effects of parental overprotection on markers of chronic stress.
Rok1p is a putative RNA helicase required for rRNA processing

The synthesis of ribosomes involves many small nucleolar ribonucleoprotein particles (snoRNPs) as transacting factors. Yeast strains lacking the snoRNA, snR10, are viable but are impaired in growth and delayed in the early pre-rRNA cleavages at sites A0, A1, and A2, which lead to the synthesis of 18S rRNA. The same cleavages are inhibited by genetic depletion of the essential snoRNP protein Gar1p. Screens for mutations showing synthetic lethality with deletion of the SNR10 gene or with a temperature-sensitive gar1 allele both identified the ROK1 gene, encoding a putative, ATP-dependent RNA helicase of the DEAD-box family. The ROK1 gene is essential for viability, and depletion of Rok1p inhibits pre-rRNA processing at sites A0, A1, and A2, thereby blocking 18S rRNA synthesis. Indirect immunofluorescence by using a ProtA-Rok1p construct shows the protein to be predominantly nucleolar. These results suggest that Rok1p is required for the function of the snoRNP complex carrying out the early pre-rRNA cleavage reactions.
Noise Modeling Of Static Cmos Gates For Low-noise Circuit Synthesis

This paper presents an efficient method for supply-current spectrum estimation for the static CMOS family of digital gates. It extends the previous approach (Blackiewicz, 2006), that considered only the noise due to a gate output switching, by including the noise generated by glitching, and short impulses. Estimation of digital circuit noise is used in early design planning of modern mixed-signal system-on-chips (MS-SoCs), composed of sensitive analogue and usually noisy digital blocks, to reduce substrate coupling-noise in analogue blocks through proper floorplan design (Blackiewicz, 2005)
Developing a Hybrid Approach by Data Mining for Intrusion Detection in Computer Networks

Intrusion usually with financial incentives, destruction, misuse or other reasons accomplished. Intrusion detection systems known as one of the key elements of infrastructur e in many organizations is security. These systems are models and hardware and software patterns that are automating processes. Intrusion detection system will notify the user as a warning. These alarms are sometimes correct and sometimes incorrect. In this paper for intrusion detection we propose a data mining hybrid method. Result show that the proposed method has high performance.
Deep learning for Emotional Analysis

The detection of emotions in textual data lets us discover more about the writer. The automatic detection of emotions is useful in a large amount of applications. Furthermore, new developments in deep learning have made it effective in more domains. This research combines the two areas and explores a deep learning method for emotional analysis. The method is benchmarked against current methods using the ISEAR and a Twitter dataset. The deep learning method shows an improvement of 2% for precision and 1% for recall and F1 score compared to the current state of the art. Our research shows that the new developments in deep learning have made it viable for emotional analysis research.
Analytical model of the KL divergence for gamma distributed data: Application to fault estimation

Incipient fault diagnosis has become a key issue for reliability and safety of industrial processes. Data-driven methods are effective for feature extraction and feature analysis using multivariate statistical techniques. Beside fault detection, fault estimation is essential for making the appropriate decision (safe stop or fault accommodation). Therefore, in this paper, we have developed an analytical model of the Kullback-Leibler Divergence (KLD) for Gamma distributed data to be used for the fault severity estimation. In the Principal Component Analysis (PCA) framework, the proposed model of the KLD has been analysed and compared to an estimated value of the KLD using the Monte-Carlo estimator. The results show that for incipient faults (<;10%) in usual noise conditions (SNR>40dB), the analytical model is accurate enough with a relative error around 10%.
Medusozoan phylogeny and character evolution clarified by new large and small subunit rDNA data and an assessment of the utility of phylogenetic mixture models.

A newly compiled data set of nearly complete sequences of the large subunit of the nuclear ribosome (LSU or 28S) sampled from 31 diverse medusozoans greatly clarifies the phylogenetic history of Cnidaria. These data have substantial power to discern among many of the competing hypotheses of relationship derived from prior work. Moreover, LSU data provide strong support at key nodes that were equivocal based on other molecular markers. Combining LSU sequences with those of the small subunit of the nuclear ribosome (SSU or 18S), we present a detailed working hypothesis of medusozoan relationships and discuss character evolution within this diverse clade. Stauromedusae, comprising the benthic, so-called stalked jellyfish, appears to be the sister group of all other medusozoans, implying that the free-swimming medusa stage, the motor nerve net, and statocysts of ecto-endodermal origin are features derived within Medusozoa. Cubozoans, which have had uncertain phylogenetic affinities since the elucidation of their life cycles, form a clade-named Acraspeda-with the scyphozoan groups Coronatae, Rhizostomeae, and Semaeostomeae. The polyps of both cubozoans and hydrozoans appear to be secondarily simplified. Hydrozoa is comprised by two well-supported clades, Trachylina and Hydroidolina. The position of Limnomedusae within Trachylina indicates that the ancestral hydrozoan had a biphasic life cycle and that the medusa was formed via an entocodon. Recently hypothesized homologies between the entocodon and bilaterian mesoderm are therefore suspect. Laingiomedusae, which has often been viewed as a close ally of the trachyline group Narcomedusae, is instead shown to be unambiguously a member of Hydroidolina. The important model organisms of the Hydra species complex are part of a clade, Aplanulata, with other hydrozoans possessing direct development not involving a ciliated planula stage. Finally, applying phylogenetic mixture models to our data proved to be of little additional value over a more traditional phylogenetic approach involving explicit hypothesis testing and bootstrap analyses under multiple optimality criteria. [18S; 28S; Cubozoa; Hydrozoa; medusa; molecular systematics; polyp; Scyphozoa; Staurozoa. ].
Screening for cognitive impairment with the Montreal Cognitive Assessment in Chinese patients with acute mild stroke and transient ischaemic attack: a validation study

Objective We aimed to establish the cut-off point of the Montreal Cognitive Assessment (MoCA-Beijing) in screening for cognitive impairment (CI) within 2 weeks of mild stroke or transient ischaemic attack (TIA). Methods A total of 80 acute mild ischaemic stroke patients and 22 TIA patients were recruited. They received the MoCA-Beijing and a formal neuropsychological test battery. CI was defined by 1.5 SD below the established norms on a formal neuropsychological test battery. Results Most stroke and TIA patients were in their 50s (53.95±11.43 years old), with greater than primary school level of education. The optimal cut-off point for MoCA-Beijing in discriminating patients with CI from those with no cognitive impairment (NCI) was 22/23 (sensitivity 85%, specificity 88%, positive predictive value=91%, negative predictive value=80%, classification accuracy=86%). The predominant cognitive deficits were characteristic of frontal-subcortical impairment, such as visuomotor speed (46.08%), attention/executive function (42.16%) and visuospatial ability (40.20%). Conclusions A MoCA-Beijing cut-off score of 22/23 is optimally sensitive and specific for detecting CI after mild stroke, and TIA in the acute stroke phase, and is recommended for routine clinical practice.
Multi-camera interference cancellation of time-of-flight (TOF) cameras

In the applications based on depth, multiple TOF cameras are often required to capture the same scene. But if multiple cameras operate simultaneously on the same frequency, they interfere with each other. The multi-camera interference causes a lot of errors in depth measurement. The depth quality is severely reduced, which limits the application of TOF cameras and needs to be resolved. In this paper, a multi-camera interference model is presented. The interference signal for multiple frames is proved to be an ergodic and wide-sense stationary stochastic process. The least square estimation of noninterference signal is proposed to remove the multi-camera interference. The results of experiments prove the approach can recover the depth and amplitude information of multiple TOF cameras from the severe interference.
A Comparison of Machine Learning Algorithms for Prepositional Phrase Attachment

This paper presents work which extends previous corpus-based work on training Machine Learning Algorithms to perform Prepositional Phrase attachment. Besides recreating others’ experiments to see how algorithms’ performance changes with the number of training examples and using n-fold cross-validation to produce more accurate error rates, we implemented our own vanilla Machine Learning Algorithms as a comparison. We also had people perform exactly the same task as the Machine Learning Algorithms to indicate whether the way forward lies in improving Machine Learning Algorithms or in improving the data sets used to train Machine Learning Algorithms. The results from all these experiments feed into our other work transforming the Penn TreeBank into a more useful resource for training Machine Learning Algorithms to do Prepositional Phrase attachment.
Type I D-particle and its interactions

In a previous paper (hep-th/9808141) we showed that the type I string theory contains a stable non-BPS D-particle carrying SO(32) spinor charge. In this paper we formulate the rules for computing the spectrum and interaction of open strings with one or both ends lying on this D-particle.