Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel HA/β-TCP-Collagen Composite Enhanced New Bone Formation for Dental Extraction Socket Preservation in Beagle Dogs

Past studies in humans have demonstrated horizontal and vertical bone loss after six months following tooth extraction. Many biomaterials have been developed to preserve bone volume after tooth extraction. Type I collagen serves as an excellent delivery system for growth factors and promotes angiogenesis. Calcium phosphate ceramics have also been investigated because their mineral chemistry resembles human bone. The aim of this study was to compare the performance of a novel bioresorbable purified fibrillar collagen and hydroxyapatite/β-tricalcium phosphate (HA/β-TCP) ceramic composite versus collagen alone and a bovine xenograft-collagen composite in beagles. Collagen plugs, bovine graft-collagen composite and HA/β-TCP-collagen composite were implanted into the left and right first, second and third mandibular premolars, and the fourth molar was left empty for natural healing. In total, 20 male beagle dogs were used, and quantitative and histological analyses of the extraction ridge was done. The smallest width reduction was 19.09% ± 8.81% with the HA/β-TCP-collagen composite at Week 8, accompanied by new bone formation at Weeks 4 and 8. The HA/β-TCP-collagen composite performed well, as a new osteoconductive and biomimetic composite biomaterial, for socket bone preservation after tooth extraction.
Effect of epigallocatechin-3-gallate on a pattern separation task and hippocampal neurogenesis in a mouse model of down syndrome

ii For my parents and their unwavering support throughout the years; Even while chasing my dreams far from home, I have never once felt alone iii ACKNOWLEDGEMENTS I would like to thank my advisor, Dr. Charles Goodlett, for your questions that made me think critically, your trust and encouragement to take on any challenge, and your humor for introducing me to Monty Python and Led Zeppelin. I would also like to thank the members of my committee, Dr. Roper and Dr. Beth, for their support and feedback throughout this project. I have been lucky to have a great team working alongside me, and I want to thank for all their help running the behavioral and immunohistochemistry experiments. I would also like to thank Mike and Mike for their daily podcasts as I manually counted thousands of cells. Thanks to all of my fellow graduate students, especially those in 304, for their encouragement day in and day out. I would also like to thank my brothers Rose for all their continued support from afar. Finally, I would like to thank my boyfriend Aaron for his enduring patience and understanding. Down syndrome (DS) is caused by three copies of human chromosome 21 (Hsa21) and results in an array of phenotypes including intellectual disability. Ts65Dn mice, the most extensively studied DS model, have three copies of ~50% of the genes on Hsa21 and display many phenotypes associated with DS, including cognitive deficits. DYRK1A is found in three copies in humans with Trisomy 21 and in Ts65Dn mice, and is involved in a number of critical pathways including CNS development and osteoclastogenesis. Epigallocatechin-3-gallate (EGCG), the main polyphenol in green tea, inhibits Dyrk1a activity. We have shown that a three-week EGCG treatment (~10mg/kg/day) during adolescence normalizes skeletal abnormalities in Ts65Dn mice, yet the same dose did not rescue deficits in the Morris water maze spatial learning task (MWM) or novel object recognition (NOR). Others have reported that An EGCG dose of 2-3 mg per day (90mg/ml) improved hippocampal-dependent task deficits in Ts65Dn mice. The current study investigated deficits in a radial arm maze pattern separation task in Ts65Dn mice. Pattern separation requires differentiation between similar memories acquired during learning episodes; distinguishing between these similar memories is thought to depend on distinctive encoding in the hippocampus. Pattern separation has vii been linked to functional activity of newly generated granule cells in the dentate gyrus. Recent studies …
Sensing Tensors With Gaussian Filters

Sparse recovery from linear Gaussian measurements has been the subject of much investigation since the breaktrough papers Candès et al. and Donoho on compressed sensing. Application to sparse vectors and sparse matrices via least squares penalized with sparsity promoting norms is now well understood thanks to tools, such as Gaussian mean width, statistical dimension, and the notion of descent cones. Extention of these ideas to low rank tensor recovery is starting to enjoy considerable interest due to its many potential applications to independent component analysis, hidden Markov models, Gaussian mixture models, and hyperspectral image analysis, to name a few. In this paper, we demonstrate that the recent approach of Vershynin provides useful error bounds in the tensor setting with the nuclear norm or the Romera-Paredes–Pontil penalization.
Diagnosis of cytomegalovirus infection: a review.

Introduction Cytomegalovirus (CMV) infects between 40100% of adults throughout the world, depending primarily on socio-economic status. However, other relevent factors include the degree and form of sexual activity such that, in the UK, homosexual men have a seroprevalence of 80% compared with 42% of sexually active male heterosexuals. ' These individuals may present to genitourinary medicine clinics with CMV-related symptoms, most of whom will be infected with HIV. As a member of the herpes group of viruses, infection with CMV leads to a state of latency with the capacity to reactivate at any time. Primary infection in the immunocompetent is usually asymptomatic but may be associated with a mononucleosis-type illness. Reactivation is of major consequence in those who are immunocompromised in whom it may be associated with retinitis, colitis, pneumonitis or encephalitis, all of which carry significant morbidity.2 The availability of effective anti-CMV therapy has heightened the requirement for rapid, sensitive methods of CMV detection, and these will be discussed in detail. By contrast, serological diagnosis of CMV infection (ie antibody determination) depends on a functional immune system and, we believe, plays little role in CMV diagnosis in the immunocompromised individual. Despite the severe symptomatology associated with CMV, it is important to realise that infection does not equate with disease. Thus, virological evidence of CMV infection must always be interpreted within the clinical context before treatment is considered.
What are you talking about? Grounding dialogue in a perspective-aware robotic architecture

While key for human-robot interaction, natural language interpretation is a notoriously difficult task, especially because the interaction context is at the same time essential for dialogue understanding, difficult to build for machines, and depends on each speaker point of view. However, robots as embodied artifacts, can perceive their environment and interactors, and hence compute symbolic models from various perspectives. This allows in turn to build symbolic contexts for dialogues. In this paper, we introduce DIALOGS, a component for natural language interpretation that relies on these structured symbolic models of the world to ground verbal interaction.
High Yield Production and Refolding of the Double-Knot Toxin, an Activator of TRPV1 Channels

A unique peptide toxin, named double-knot toxin (DkTx), was recently purified from the venom of the tarantula Ornithoctonus huwena and was found to stably activate TRPV1 channels by targeting the outer pore domain. DkTx has been shown to consist of two inhibitory cysteine-knot (ICK) motifs, referred to as K1 and K2, each containing six cysteine residues. Beyond this initial characterization, however, the structural and functional details about DkTx remains elusive in large part due to the lack of a high yielding methodology for the synthesis and folding of this cysteine-rich peptide. Here, we overcome this obstacle by generating pure DkTx in quantities sufficient for structural and functional analyses. Our methodology entails expression of DkTx in E. coli followed by oxidative folding of the isolated linear peptide. Upon screening of various oxidative conditions for optimizing the folding yield of the toxin, we observed that detergents were required for efficient folding of the linear peptide. Our synthetic DkTx co-eluted with the native toxin on HPLC, and irreversibly activated TRPV1 in a manner identical to native DkTx. Interestingly, we find that DkTx has two interconvertible conformations present in a 1∶6 ratio at equilibrium. Kinetic analysis of DkTx folding suggests that the K1 and K2 domains influence each other during the folding process. Moreover, the CD spectra of the toxins shows that the secondary structures of K1 and K2 remains intact even after separating the two knots. These findings provide a starting point for detailed studies on the structural and functional characterization of DkTx and utilization of this toxin as a tool to explore the elusive mechanisms underlying the polymodal gating of TRPV1.
$6\qfkurqrxvv()/:ulwlqjj(qylurqphqwwiruwkhh ,qwhuqhw Learning Environment Content Authoring Content

In this paper, we describe the design and implementation of a synchronous EFL computer assisted English writing environment. In addition to supporting the basic writing function requirements, two novel mechanisms, namely, (1) synchronous text co-editing, and (2) voice delivery, have been designed to provide fundamental capabilities over the Internet. As a result, the designed system exploits the integration of computers and networking capabilities with linguistic and pedagogical principles crucial to web-based language learning. The system integrates CMC tools with database technology for the specific purpose of archiving the communications between tutors and students. Since the platform offers a bank of comments that are frequently used in these online tutorials, the system can store and tabulate each token instance when a comment is used. This database then offers instant cumulative profiles into tutor-learner interaction and into the common language errors or difficulties uncovered in the tutorials. Such an archive supports research into language learning difficulties and into patterns of tutor-learner interaction. This data is valuable in the assessment of pedagogical effectiveness and in the development of online tutorial materials that meet the attested needs of learners.
Use of pyrosequencing to detect clinically relevant polymorphisms in dihydropyrimidine dehydrogenase.

Common human diseases, such as cancer, have been associated with multiple types of variation in the genome, including sequence repeats and deletions and single-nucleotide polymorphisms (SNPs) (1). Of these, SNPs are the most abundant in the human genome (2)(3). As a result of the efforts of many groups (4), an estimated 5 million SNPs are now deposited in public databases (5), providing a resource for determining how genomic variation affects human biology. Building on this work, many groups have shown that drug response is also influenced by genomic variation (6). Multiple SNPs have been identified that have a major impact on response to chemotherapy (7)(8)(9)(10)(11); it is therefore necessary to have rapid and efficient SNP evaluation techniques to analyze genes that influence chemotherapy response. Dihydropyrimidine dehydrogenase (DPD) is the initial and rate-limiting enzyme in the three-step degradation of uracil to β-alanine (12). This is the only endogenous pathway for production of the neurotransmitter β-alanine (13). DPD also degrades >80% of the anticancer agent 5-fluorouracil (5-FU), a pyrimidine analog used to treat colorectal cancer, and limits the oral absorption of the drug (13). DPD activity is found to be highest in liver and mononuclear cells, but it is also present in most other human tissues (14). Variation in DPD activity can lead to nonbeneficial physiologic conditions. A complete absence of DPD has been associated with the hereditary metabolic disorder thymine-uraciluria (9). This is characterized by mental retardation and is sometimes accompanied by other neurologic disorders, such as microcephaly, motor retardation, and autism (9). In addition, decreased DPD activity leads to severe toxicity from 5-FU even when typical doses are administered. This is often accompanied by severe diarrhea, neutropenia, and sometimes, neurotoxicity (9). The DPYD gene located on chromosome 1p20 …
The Impact of College Sports Success on the Quantity and Quality of Student Applications

Empirical studies have produced mixed results on the relationship between a school’s sports success and the quantity and quality of students that apply to the school. This study uses two unique data sets to shed additional light on the indirect benefits that sports success provides to NCAA Division I schools. Key findings include the following: (1) football and basketball success significantly increases the quantity of applications to a school, with estimates ranging from 2% to 8% for the top 20 football schools and the top 16 basketball schools each year, (2) private schools see increases in application rates after sports success that are two to four times higher than public schools, (3) the extra applications received are composed of both low and high SAT scoring students, thus providing potential for schools to improve their admission outcomes, and (4) schools appear to exploit these increases in applications by improving both the number and the quality of incoming students.
Hierarchical shrinkage in time-varying parameter models

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach.
Childhood Health Status and Adulthood Cardiovascular Disease Morbidity in Rural China: Are They Related?

Cardiovascular diseases (CVDs) are among the top health problems of the Chinese population. Although mounting evidence suggests that early childhood health status has an enduring effect on late life chronic morbidity, no study so far has analyzed the issue in China. Using nationally representative data from the 2013 China Health and Retirement Longitudinal Study (CHARLS), a Probit model and Two-Stage Residual Inclusion estimation estimator were applied to analyze the relationship between childhood health status and adulthood cardiovascular disease in rural China. Good childhood health was associated with reduced risk of adult CVDs. Given the long-term effects of childhood health on adulthood health later on, health policy and programs to improve the health status and well-being of Chinese populations over the entire life cycle, especially in persons’ early life, are expected to be effective and successful.
Shape Correspondence through Landmark Sliding Paper # 346

Mainly motivated by statistical shape analysis, this paper presents a novel landmark-based method for accurate shape correspondence, where the general goal is to align multiple shape instances by identifying a set of corresponded landmark points along those shapes. Different from previous methods, we consider both global shape deformation and local geometric features in defining the shape-correspondence cost function to achieve a consistency between the landmark correspondence and the underlying shape correspondence. According to this cost function, we develop a novel landmark-sliding algorithm to achieve optimal landmark-based shape correspondence. The proposed method is able to correspond various 2D shapes, like closed-curve shapes, open-curve shapes, selfcrossing shapes, and multiple-curve shapes. We also discuss other related practical issues, including landmark initialization and regularization parameter selection. The proposed method has been tested on various biological shapes arising from medical image analysis and validated in constructing statistical shape models.
A QUALITATIVE APPROACH OF THE ASSOCIATION BETWEEN THE TODDLER’S ATTACHMENT STYLE AND THE DYADIC INTERACTION WITH THE MOTHER

ANDREEA M. IONESCU1*, CARMEN COSTEA-BĂRLUŢIU2 ABSTRACT. The quality of toddler’s experience with the caregiver impacts the structuring of the internal working models of attachment (Bowlby, 1980, 1988), further used as means of comfort and security, and prototypes for later close relationships. Using inductive qualitative techniques, our study aims to describe specific schemes of mothertoddler interaction, for each of the attachment styles. Semi-structured interactions of 27 mother-child dyads were videotaped in their familiar environment and the films were qualitatively analyzed, for each group of toddlers previously identified as having the same attachment style. The interactions of secure toddlers and their mothers were marked by synchronized actions, joy of interacting, closeness, and security. Mothers of ambivalent children displayed a more dominant action, with discordances between the social and psychological level of communication. Avoidant toddler-mother dyads presented a higher balance between their relational spaces, maintaining contact, with a low level of intimacy. The absence of a coherent strategy defined the interaction between the toddlers with disorganized attachment and their mothers. Our results confirm previous findings in the field of attachment in early childhood and add up to these results by providing a methodology to approach these interactions and the use of video recordings as ways to develop interventions aiming to increase the attachment security.
Modular specification and verification of object-oriented programs

A method for modular specification and verification using the ideas of subtype and normal type is presented. The method corresponds to informal techniques used by object-oriented programmers. The key idea is that objects of a subtype must behave like objects of that type's supertypes. An example program is used to show the reasoning problems that supertype abstraction may cause and how the method resolves them. Subtype polymorphism is addressed, and specification and verification update is discussed. A set of syntactic and semantic constraints on subtype relationships, which formalize the intuition that each object of a subtype must behave like some object of each of its supertypes, is examined. These constraints are the key to the soundness of the method. To state them precisely, a formal model of abstract type specifications is used. <<ETX>>
Review Article Peroxisome Proliferator-activated Receptors in Diabetic Nephropathy

Recommended by Nigel Brunskill Diabetic nephropathy is a leading cause of end-stage renal disease, which is increasing in incidence worldwide, despite intensive treatment approaches such as glycemic and blood pressure control in patients with diabetes mellitus. New therapeutic strategies are needed to prevent the onset of diabetic nephropathy. Peroxisome proliferator-activated receptors (PPARs) are ligand-activated nuclear transcription factors that play important roles in lipid and glucose homeostases. These agents might prevent the progression of diabetic nephropathy, since PPAR agonists improve dyslipidemia and insulin resistance. Furthermore, data from murine models suggest that PPAR agonists also have independent renoprotective effects by suppressing inflammation, oxidative stress, lipotoxicity, and activation of the renin-angiotensin system. This review summarizes data from clinical and experimental studies regarding the relationship between PPARs and diabetic nephropathy. The therapeutic potential of PPAR agonists in the treatment of diabetic nephropathy is also discussed.
FROM EMPIRICAL BAYES TO FULL BAYES: METHODS FOR ANALYZING TRAFFIC SAFETY DATA

Summary Trac safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the eect of covariates on the outcome of interest. In this light, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors.
Appreciative Inquiry – a Research Tool for Institutional Change

Appreciative Inquiry (AI) emanated from the PhD work of David Cooperrider at Case Western Reserve University in the 1980s. Founded upon social constructionist theories (Berger & Luckmann,1966, Gergen, 2009), it is an approach to organizational change that eschews former Organization Development (OD) deficit models in favour of a positive approach to change that builds a vision for the future based upon what already works well within an existing system. It also provides a framework for researching or evaluating different forms of professional practice, including learning, teaching and the student experience. Its self-empowering philosophy, effected through the ‘4-D’ process (Discover, Dream, Design and Destiny), is realized through the collaborative working of all stakeholders within an institution; through systematic participation in a jointly constructed vision of an organization’s future, they become an integral part of its success. At its core is the unconditional positive question, which seeks out the best of ‘what is’ in order to prompt the collective imagination to envision ‘what might be’. The use of AI within higher education in the UK is not yet well-developed and existing studies of the application of AI to this context have tended to focus principally on the areas of teaching and institutional change. It is suggested that through the publication of recent books such as ‘Appreciative Inquiry in Higher Education: A Transformative Force’ (Cockell, McArthur-Blair & Schiller, 2013), it will perhaps become more widely adopted in this context.