Miracle-dz/UniFAR-FTUs huggingface dataset:
2D and 3D Self-Assembling Nanofiber Hydrogels for Cardiomyocyte Culture

Collagen is a widely used biomaterial in cardiac tissue engineering studies. However, as a natural material, it suffers from variability between batches that can complicate the standardization of culture conditions. In contrast, synthetic materials are modifiable, have well-defined structures and more homogeneous batches can be produced. In this study, several collagen-like synthetic self-assembling nanofiber hydrogels were examined for their suitability for cardiomyocyte culture in 2D and 3D. Six different nanofiber coatings were used in the 2D format with neonatal rat cardiomyocytes (NRCs) and human embryonic stem-cell-derived cardiomyocytes (hESC-CMs). The viability, growth, and functionality of the 2D-cultured cardiomyocytes were evaluated. The best-performing nanofiber coatings were selected for 3D experiments. Hydrophilic pH-sensitive nanofiber hydrogel coassembled with hyaluronic acid performed best with both NRCs and hESC-CMs. Hydrophilic non-pH-sensitive nanofiber hydrogels supported the growth of NRCs; however, their ability to promote attachment and growth of hESC-CMs was limited. NRCs also grew on hydrophobic nanofiber hydrogels; however, the cell-supporting capacity of these hydrogels was inferior to that of the hydrophilic hydrogel materials. This is the first study demonstrating that hydrophilic self-assembling nanofiber hydrogels support the culture of both NRCs and hESC-CMs, which suggests that these biomaterials hold promise for cardiac tissue engineering.
Is it possible to predict which bilingual speakers have switched language dominance? A discriminant analysis

ABSTRACT Linguistic research on bilinguals has sometimes focused on either first vs. second acquired language or dominant vs. non-dominant language despite situations in which the dominant and first language are no longer the same. Many bilinguals in the U.S. and other countries experience a change in language dominance from a home language to a majority language. The present study examined language history data from young Spanish-English bilingual adults living in the U.S. in an attempt to predict their dominant language. A statistical discriminant analysis was used to create a simple model that made accurate predictions of reported current dominant language at well above chance rates. The variables used were Age of Acquisition (AoA) for English and AoA for Spanish. The results showed that predicted English-dominant speakers learned English earlier and Spanish later, whereas, predicted Spanish-dominant speakers learned English at a relatively older age, and Spanish relatively earlier. This was confirmed by replication in a second sample from the same population. The results of this analysis imply that it is possible to successfully predict language dominance using English AoA and Spanish AoA. Future research should focus on longitudinal studies of dominance switches and cross-validation in other populations of bilinguals.
A primer on U.S. welfare reform

terms of expenditure. The Earned Income Tax Credit (EITC) program, an earnings subsidy program, which provides tax credits to low-income families with earnings, is third largest. The Food Stamp program, which provides food coupons to the poor, and programs for subsidized housing for the poor are fourth and fifth, respectively. The TANF program is, as the table shows, only the sixth largest program in the United States in terms of expenditure, and only half as much is spent on it as is spent on the fifth largest program. TANF’s caseload is also small, although because it provides a cash benefit for all needs and not just a supplemental payment like Food Stamps and the EITC, its expenditure per recipient is larger than that of those two programs. Robert Moffitt
3D Face Acquisition, Modelling and Recognition

This paper presents a novel integrated 3D face verification system. The system comprises of a Structured Light Scanner acquisition stage, with 3D surface fitting and filtering. A-priori information of the human face is utilised to select and extract a region of interest from the face surface, whilst the Iterative Closest Point (ICP) algorithm is employed to establish correspondence between test and target and to compensate for the non-rigid nature of the surfaces. The verification process uses a Euclidean distance classifier across combinations of features extracted from the surfaces and results from a database of 21 subjects are presented.
Gene Transfer of a Synthetic Pacemaker Channel Into the Heart: A Novel Strategy for Biological Pacing

Background— One key element of natural pacemakers is the pacemaker current encoded by the hyperpolarization-activated nucleotide-gated channel (HCN) gene family. Although HCN gene transfer has been used to engineer biological pacemakers, this strategy may be confounded by unpredictable consequences of heteromultimerization with endogenous HCN family members and limited flexibility with regard to frequency tuning of the engineered pacemaker. Methods and Results— To circumvent these limitations, we converted a depolarization-activated potassium-selective channel, Kv1.4, into a hyperpolarization-activated nonselective channel by site-directed mutagenesis (R447N, L448A, and R453I in S4 and G528S in the pore). Gene transfer into ventricular myocardium demonstrated the ability of this construct to induce pacemaker activity with spontaneous action potential oscillations in adult ventricular myocytes and idioventricular rhythms by in vivo electrocardiography. Conclusions— Given the sparse expression of Kv1 family channels in the human ventricle, gene transfer of a synthetic pacemaker channel based on the Kv1 family has novel therapeutic potential as a biological alternative to electronic pacemakers.
Register in Systemic Functional Linguistics*

Christian M. I. M. Matthiessen elaborates on the Systemic Functional Linguistics (SFL) approach to register in this contribution to the inaugural issue of Register Studies. He is Chair Professor of the Department of English at the Hong Kong Polytechnic University, where he pursues a scholarly agenda that includes developing the theory of Systemic Functional Linguistics and applying it to text and discourse analysis, functional grammar, issues related to language evolution and typology, and comprehensive descriptive models of register. Throughout his career, Matthiessen has made major contributions to SFL theories and methods. Among his major works is Lexicogrammatical Cartography: English Systems (1995, International Language Sciences Publishers). More than any other scholar, Matthiessen has expounded on Halliday’s early ideas on register and applied SFL theory to describing models of register variation. He remains an active researcher in the area of register studies which includes his registerial cartography – the comprehensive and systematic description of the registers in a language. Matthiessen’s work has left an indelible mark on the theory and systematic study of patterns of register in language use.
Neuroanatomical Alterations in High-Functioning Adults with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental condition, affecting cognition and behavior throughout the life span. With recent advances in neuroimaging techniques and analytical approaches, a considerable effort has been directed toward identifying the neuroanatomical underpinnings of ASD. While gray-matter abnormalities have been found throughout cortical, subcortical, and cerebellar regions of affected individuals, there is currently little consistency across findings, partly due to small sample-sizes and great heterogeneity among participants in previous studies. Here, we report voxel-based morphometry of structural magnetic resonance images in a relatively large sample of high-functioning adults with ASD (n = 66) and matched typically-developing controls (n = 66) drawn from multiple studies. We found decreased gray-matter volume in posterior brain regions, including the posterior hippocampus and cuneus, as well as increased gray-matter volume in frontal brain regions, including the medial prefrontal cortex, superior and inferior frontal gyri, and middle temporal gyrus in individuals with ASD. We discuss our results in relation to findings obtained in previous studies, as well as their potential clinical implications.
Supersymmetric Galileons

Galileon theories are of considerable interest since they allow for stable violations of the null energy condition. Since such violations could have occurred during a high-energy regime in the history of our universe, we are motivated to study supersymmetric extensions of these theories. This is carried out in this paper, where we construct generic classes of N=1 supersymmetric Galileon Lagrangians. They are shown to admit non-equivalent stress-energy tensors and, hence, vacua manifesting differing conditions for violating the null energy condition. The temporal and spatial fluctuations of all component fields of the supermultiplet are analyzed and shown to be stable on a large number of such backgrounds. In the process, we uncover a surprising connection between conformal Galileon and ghost condensate theories, allowing for a deeper understanding of both types of theories.
Product recommendations using linear predictive modeling

Recommendation systems apply statistical and knowledge discovery techniques to the problem of making product recommendations and they are achieving widespread success in E-Commerce these days. A successful recommendation system fulfils several purposes and the choice of the methodology significantly influences the quality of recommendations and other aspects including scalability. As the volume of data in the e-commerce is growing massively, the system should also be able to address the need to provide the recommendations either by in-memory calculations or offline calculations, both demanding the high performance. For a large number of customers and products, the linear regression with a proper model selection can provide significantly better results and performance. Recommendations engines are increasingly becoming a popular choice for solving the problem of content discovery enabling the user to find personally relevant content that they might not have known was available. In this paper, we consider linear regression technique for analyzing large-scale dataset for the purpose of useful recommendations to e-commerce customers by offline calculations of model results.
Behavioral Adaptive Autonomy. A milestone on the Alife route to AI

While central to robotics, biology and cognitive science, the concept of autonomy remains still difficult to make operative in the realm of Alife simulation models of cognitive agents. Its deep significance as a transition concept between life and cognition (a milestone on the Alife route to AI) remains obscured in the intricate relation between metabolic/constructive processes and behavioral adaptive processes in living systems. Within a naturalized and biologically inspired dynamical approach to cognition a definition of behavioral adaptive autonomyis provided: homeostatic maintenance of essential variables under viability constraints through self-modulating behavioral coupling with the environment, hierarchically decoupled from metabolic (constructive) processes. This definition allows for a naturalized notion of behavioral adaptive functionality (that defines a proper level of modelling within Alife), structurally and interactively emergent: the mapping of the agent-environment system’s state space trajectories into the viability subspace of the essential variables of the organism.
Cost-Based Data-Partitioning for Intra-Query Parallelism

Contemporary DBMS systems already use data-partitioning and data-flow analysis for intra-query parallelism. We study the problem of identifying data-partitioning targets. To rank candidates, we propose a simple cost model that relies on plan structure, operator cost and selectivity for a given base table. We evaluate this model in various optimization schemes and observe how it affects degrees of parallelism and query execution latencies across all TPC-H queries: When compared with the existing näıve model which partitions the largest physical table in the query, our approach identifies significantly better partitioning targets thus resulting in sinificantly higher degree of resource utilization and intra-query parallelism for most queries while having little impact on the remaining queries in the TPC-H benchmark.
A Control Framework for Online Error Control Adaptation in Networked Applications

For many real-time applications running over packet-switched networks, it is important to maintain delivered data quality using a limited amount of network resources. It is therefore natural to employ cost functions that allow online trade-off between the experienced application quality and the resource usage. However, minimizing such cost functions requires perfect knowledge of the network state at the transmission side, while, in general, such information is only partially available. In this paper, we introduce a new adaptive error correction algorithm that optimizes the amount of redundancy based on the available information from the application and the network. An extremum-seeking control algorithm is employed to deal with the high level of uncertainty in the network models. The validity of our approach is illustrated in simulations with varying network loads and loss correlation.
OX40 expression enhances the prognostic significance of CD8 positive lymphocyte infiltration in colorectal cancer

Background OX40 is a TNF receptor family member expressed by activated T cells. Its triggering by OX40 ligand promotes lymphocyte survival and memory generation. Anti-OX40 agonistic monoclonal antibodies (mAb) are currently being tested in cancer immunotherapy. We explored the prognostic significance of tumor infiltration by OX40+ cells in a large colorectal cancer (CRC) collective. Methods OX40 gene expression was analyzed in 50 freshly excised CRC and corresponding healthy mucosa by qRT-PCR. A tissue microarray including 657 clinically annotated CRC specimens was stained with anti-OX40, -CD8 and -FOXP3 mAbs by standard immunohistochemistry. The CRC cohort was randomly split into training and validation sets. Correlations between CRC infiltration by OX40+ cells alone, or in combination with CD8+ or FOXP3+ cells, and clinical-pathological data and overall survival were comparatively evaluated. Results OX40 gene expression in CRC significantly correlated with FOXP3 and CD8 gene expression. High CRC infiltration by OX40+ cells was significantly associated with favorable prognosis in training and validation sets in univariate, but not multivariate, Cox regression analysis. CRC with OX40high/CD8high infiltration were characterized by significantly prolonged overall survival, as compared to tumors with OX40low/CD8high, OX40high/CD8low or OX40low/CD8low infiltration in both uni- and multivariate analysis. In contrast, prognostic significance of OX40+ and FOXP3+ cell infiltration was not enhanced by a combined evaluation. Irrespective of TNM stage, CRC with OX40high/CD8high density infiltrates showed an overall survival similar to that of all stage I CRC included in the study. Conclusions OX40high/CD8high density tumor infiltration represents an independent, favorable, prognostic marker in CRC with an overall survival similar to stage I cancers.
Smartphone Users Want to Be Mocked

To secure users’ sensitive data, Android employs a “takeit-or-leave-it” permissions model. Unfortunately, this model has many well-documented flaws: applications request unnecessary permissions [1, 2], while users don’t understand the implications of permissions requested [3]. An alternative “take-it-or-break-it” approach [5] allows users to selectively enable particular permissions, but many applications require access to specific sensitive information to function properly.
Improving Fairness in DiffServ Networks Using Adaptive Aggregate Markers

Traffic markers differentiate among packets from senders based on their service profile in the differentiated service networks. Researchers have previously revealed that the existing marking mechanism causes the unfairness in aggregates. This study presents a new marking algorithm. Simulation results demonstrate that the fairness of the proposed scheme exceeds that of SRTCM, TRTCM, TSWTCM and ITSWTCM for medium to high network provision levels.
System-level dynamic simulation for a MEMS clamped-beam based on the mechanical description

A method for developing the equivalent lumped electrical circuit based on the mechanical description of MEMS structures is proposed, which is used to carry out the system-level simulation of the dynamic behavior of the electromechanically coupled clamped-beam. The main idea of the method is to take the maximum displacement for the common variable, develop the equivalent mechanical description with the help of the mechanical analysis in combination with the energy principle, and implement the coupling process by feedback mechanism of the controlled sources. The equivalent electrical circuit can be used to simulate the transient response and frequency-shifting characteristic of the beam under electrostatic loads. Simulation from Saber in CoventorWare has confirmed the validity of the method
Family Resources, Peer Support, and Community Nutrition to Improve the Quality of Life Among Elderly

Approach Social Determinants of Health and nutritional status is an important concept to improve the living conditions and quality of life conducive to the elderly (Elderly). For the 29th of May in Indonesia declared a National Elderly Day in order to build an organization of elderly people strong and independent so as to be a group of elderly people who can handle any kind of health and nutrition problems were able to find a solution aspiration elderly group. This study aimed to analyze the influence of determinant factors on the quality of life among elderly so that it can be a reference to the design of health and nutrition promotion models to improve Reviews their quality of life. This quantitative study was crosssectional design conducted in Surakarta, Central Java Province from March to September 2018. Methods, There were 122 elderly selected as research subjects. The dependent variables were nutritional status and the quality of life. The independent variables were age, education, income, behavior, family support, peer support, and the support of community nutrition. Data were collected using questionnaires and nutritional status Analyzed using path analysis. The result, The Quality of elderly life increases with increasing levels of education, income, positive behavior of community nutrition, and peer support. The quality of elderly life decreases with increasing age. Integrative nutrition and health promotion models to improve the quality of elderly life are designed by improving the role of peer support, increasing education, income and positive behavior of community nutrition. Conclusion, Family Resources, with a culture of healthy hygienic behavior and Peer Support, through religious activities and associations gathering and Community Nutrition to Improve the Quality of Life among Elderly shows there are many elderly people who smoke at home (46.2%)
Unobserved Heterogeneity in Freight Shippers’ Mode Choice Behaviour

The objective of this paper is to investigate the prevalence of observed and unobserved heterogeneity in tastes influencing shippers’ mode choice behavior. The study is based on data from a stated preference exercise undertaken in Java, Indonesia. The data were analyzed using a mixed logit model, capable of accommodating random taste heterogeneity and panel effects associated with the stated preference data collection method. The results indicate the presence of significant levels of taste heterogeneity, only some of which can be accounted for by conventional commodity-type based segmentations. The analysis goes on to apply latent class methods to identify behaviorally homogeneous segments. This segmentation turns out to depend not only on commodity type but also a number of other attributes describing the shipper. The implications of these findings are discussed.
High performance coach education : a symbolic interactionist perspective

This thesis focuses on the experiences of those individuals involved in the formation, consumption, management, and delivery of the United Kingdom Coaching Certificate Coach Level 4 (UKCC CL4) award. An ethnographically inspired fieldwork engagement of 18 months followed cohorts of UKCC CL4 coaches from British Canoeing and British Judo as they undertook this education journey. This research comes at a time when UK sporting agencies have invested considerable resources into elite coach education and have established novel relationships with Higher Education institutions (HEi) to assist in the delivery of such programmes. Despite this investment, there is a scarcity of empirically informed studies detailing the processes undertaken. Little is understood in terms of what aspirations, thoughts, fears, and beliefs the participants have had, which includes an understanding of the problems and contradictions inherent in the UKCC CL4 award itself. Over 50 interviews with coaches, course tutors, Governing Body (GB) staff and sports organisations’ personnel were conducted; the data gleaned from these were analysed using the theories inherent in the writings of traditional symbolic interactionists, such as Blumer (e.g. Blumer, 1946; 1969), Cooley (e.g. Cooley, 1907; 1910; 1918), Mead (Mead, 1934), and Strauss (e.g. Strauss, 1959; 1978). Findings indicate that there are three main areas of significance: that the individuals responsible for the management of the relationship between the sport GB and the HEi partner are of central importance; that over the period of the UKCC CL4 award, well thought out and constructed links between the theoretical aspects covered in the delivery and practice of coaches resulted in stronger levels of attainment; and, that a number of the coaches completing the UKCC CL4 programme developed an ongoing desire for further academic educational experience having established a strong commitment to personal development. The significance of this work is that it provides empirically informed guidelines for the development of similar coach education programmes at home in the UK and abroad by privileging the views and experiences of those participants directly involved in high performance coach education.
A fusion approach based on wrapper and filter feature selection methods using majority vote and feature weighting

An essential issue in machine learning is identifying a representative features set that serve to construct robust classification models for a particular task. This paper addresses the problem of feature selection for credit scoring. Many feature selection methods were proposed in the past few years to construct accurate credit scoring model. Instead of using a single feature selection method, we propose a new fusion approach that utilizes a number of diverse feature selection methods to do the job. Many approaches have been proposed to build such accurate credit model, of which filters and wrappers were the most popular. A fusion of this two approaches, is thoroughly investigated in this work and several comparisons are carried out to compare the proposed fusion method with the individual approaches. Evaluations on two credit datasets show that feature subsets selected by the fusion method improves classification accuracy.