Miracle-dz/UniFAR-FTUs huggingface dataset:
A Microfabricated Platform for Investigating Multicellular Organization in 3-D Microenvironments

Figure 2: Microscale organization alters cell function. (a) Thousands of micropatterned cell clusters are embedded within a thin hydrogel. (b) Cluster size (and cell-cell interaction) can be varied from single cells (U) to large clusters (III) within a single hydrogel slab. Cells have high viability (green), indicated by fluorescent staining. Scale bars, 100µm. (c) In articular chondrocytes, biosynthesis of a matrix molecule, GAG, is downregulated over 14 days in clusters of increasing size, independent of volumetric seeding density. “Sham” DCP hydrogels, in which cells were initially electropatterned but then randomized prior to hydrogel crosslinking, were indistinguishable from unpatterned controls. Data are mean ± s.e. m. , n = 5 - 6. *, p<0.001 vs. “U”; †, p<0.001 vs. “Sham. ” p
Conditional leaving-one-out and cross-validation for discount estimation in Kneser-Ney-like extensions

The smoothing of n-gram models is a core technique in language modelling (LM). Modified Kneser-Ney (mKN) ranges among one of the best smoothing techniques. This technique discounts a fixed quantity from the observed counts in order to approximate the Turing-Good (TG) counts. Despite the TG counts optimise the leaving-one-out (L1O) criterion, the discounting parameters introduced in mKN do not. Moreover, the approximation to the TG counts for large counts is heavily simplified. In this work, both ideas are addressed: the estimation of the discounting parameters by L1O and better functional forms to approximate larger TG counts. The L1O performance is compared with cross-validation (CV) and mKN baseline in two large vocabulary tasks.
Additive Regression Trees and Smoothing Splines-Predictive Modeling and Interpretation in Data Mining

We suggest a two-phase boosting method, called “additive regression tree and smoothing splines” (ARTSS), which is highly competitive in prediction performance. However, unlike many automated learning procedures, which lack interpretability and operate as a “black box”, ARTSS allows us to (1) estimate the marginal effect smoothly; (2) test the significance of non-additive effects; (3) separate the variable importance on main and interaction effects; (4) select variables and provide a more flexible modeling strategy. We apply ARTSS to two public domain data sets and discuss the understanding developed from the model.
Robust Weighted Graph Transformation Matching for Rigid and Nonrigid Image Registration

This paper presents an automatic point matching algorithm for establishing accurate match correspondences in two or more images. The proposed algorithm utilizes a group of feature points to explore their geometrical relationship in a graph arrangement. The algorithm starts with a set of matches (including outliers) between the two images. A set of nondirectional graphs is then generated for each feature and its K nearest matches (chosen from the initial set). Using the angular distances between edges that connect a feature point to its K nearest neighbors in the graph, the algorithm finds a graph in the second image that is similar to the first graph. In the case of a graph including outliers, the algorithm removes such outliers (one by one, according to their strength) from the graph and re-evaluates the angles until the two graphs are matched or discarded. This is a simple intuitive and robust algorithm that is inspired by a previous work. Experimental results demonstrate the superior performance of this algorithm under various conditions, such as rigid and nonrigid transformations, ambiguity due to partial occlusions or match correspondence multiplicity, scale, and larger view variation.
DME : Documentation Management Environment for Software Product Lines – Tool Demo Proposal

Similar documents arise in software and business situations. Examples are user guides for different versions of a software product, contracts between vendors and clients, and legal documents. The usual practice is to capture similarities in templates that must be copied and manually customized to a new context – often a slow, tedious, and error-prone process. Document Management Environment (DME) automates routine tasks involved in creating and updating documents. DME provides functions to create templates and to generate custom documents from them. Any arbitrary document part can be designated as template’s variation point, and the same interdependent customizations occurring at different variation points can be streamlined. We develop DME to automate generation of documentation of multiple software products (e.g., in reuse via Software Product Line approach), but also plan to explore its potentials in management of general business documents.
Engineering an in situ crosslinkable hydrogel for enhanced remyelination

Remyelination has to occur to fully regenerate injured spinal cords or brain tissues. A growing body of evidence has suggested that exogenous cell transplantation is one promising strategy to promote remyelination. However, direct injection of neural stem cells or oligodendrocyte progenitor cells (OPCs) to the lesion site may not be an optimal therapeutic strategy due to poor viability and functionality of transplanted cells resulted from the local hostile tissue environment. The overall objective of this study was to engineer an injectable biocompatible hydrogel system as a supportive niche to provide a regeneration permissive microenvironment for transplanted OPCs to survive, functionally differentiate, and remyelinate central nervous system (CNS) lesions. A highly biocompatible hydrogel, based on thiol‐functionalized hyaluronic acid and thiol‐functionalized gelatin, which can be crosslinked by poly‐(ethylene glycol) diacrylate (PEGDA), was used. These hydrogels were optimized first regarding cell adhesive properties and mechanical properties to best support the growth properties of OPCs in culture. Transplanted OPCs with the hydrogels optimized in vitro exhibited enhanced survival and oligodendrogenic differentiation and were able to remyelinate demyelinated axons inside ethidium bromide (EB) demyelination lesion in adult spinal cord. This study provides a new possible therapeutic approach to treat CNS injuries in which cell therapies may be essential. —Li, X. , Liu, X. , Cui, L. , Brunson, C. , Zhao, W. , Bhat, N. R. , Zhang, N. , Wen, X. Engineering an in situ crosslinkable hydrogel for enhanced remyelination. FASEB J. 27, 1127–1136 (2013). www.fasebj. org
Gravitational waves at aLIGO and vacuum stability with a scalar singlet extension of the standard model

A new gauge singlet scalar field can undergo a strongly first-order phase transition (PT) leading to gravitational waves (GW) potentially observable at aLIGO and stabilizes the electroweak vacuum at the same time by ensuring that the Higgs quartic coupling remains positive up to at least the grand unification (GUT) scale. aLIGO (O5) is potentially sensitive to cosmological PTs at 107–108 GeV, which coincides with the requirement that the singlet scale is less than the standard model (SM) vacuum instability scale, which is between 108 GeV and 1014 GeV. After sampling its parameter space, we identify three benchmark points with a PT at about T≈107 GeV in a gauge singlet extension of the SM. We calculate the nucleation temperature, order parameter, characteristic time scale, and peak amplitude and frequency of GW from bubble collisions during the PT for the benchmarks and find that, in an optimistic scenario, GW from such a PT may be in reach of aLIGO (O5). We confirm that the singlet stabilizes the electroweak vacuum while remaining consistent with zero-temperature phenomenology as well. Thus, this scenario presents an intriguing possibility that aLIGO may detect traces of fundamental physics motivated by vacuum stability at an energy scale that is well above the reach of any other experiment.
Competitive Inhibition of Thyroidal Uptake of Dietary Iodide by Perchlorate Does Not Describe Perturbations in Rat Serum Total T4 and TSH

Background Perchlorate (ClO4−) is an environmental contaminant known to disrupt the thyroid axis of many terrestrial and aquatic species. ClO4− competitively inhibits iodide uptake into the thyroid at the sodium/iodide symporter and disrupts hypothalamic–pituitary–thyroid (HPT) axis homeostasis in rodents. Objective We evaluated the proposed mode of action for ClO4−-induced rat HPT axis perturbations using a biologically based dose–response (BBDR) model of the HPT axis coupled with a physiologically based pharmacokinetic model of ClO4−. Methods We configured a BBDR-HPT/ClO4− model to describe competitive inhibition of thyroidal uptake of dietary iodide by ClO4− and used it to simulate published adult rat drinking water studies. We compared model-predicted serum thyroid-stimulating hormone (TSH) and total thyroxine (TT4) concentrations with experimental observations reported in these ClO4− drinking water studies. Results The BBDR-HPT/ClO4− model failed to predict the ClO4−-induced onset of disturbances in the HPT axis. Using ClO4− inhibition of dietary iodide uptake into the thyroid, the model underpredicted both the rapid decrease in serum TT4 concentrations and the rise in serum TSH concentrations. Conclusions Assuming only competitive inhibition of thyroidal uptake of dietary iodide, BBDR-HPT/ClO4− model calculations were inconsistent with the rapid decrease in serum TT4 and the corresponding increase in serum TSH. Availability of bound iodide in the thyroid gland governed the rate of hormone secretion from the thyroid. ClO4− is translocated into the thyroid gland, where it may act directly or indirectly on thyroid hormone synthesis/secretion in the rat. The rate of decline in serum TT4 in these studies after 1 day of treatment with ClO4− appeared consistent with a reduction in thyroid hormone production/secretion. This research demonstrates the utility of a biologically based model to evaluate a proposed mode of action for ClO4− in a complex biological process.
Forecasting the optimal order quantity in the newsvendor model under a correlated demand

This paper considers the classical newsvendor model when, (a) demand is autocorrelated, (b) the parameters of the marginal distribution of demand are unknown, and (c) historical data for demand are available for a sample of successive periods. An estimator for the optimal order quantity is developed by replacing in the theoretical formula which gives this quantity the stationary mean and the stationary variance with their corresponding maximum likelihood estimators. The statistical properties of this estimator are explored and general expressions for prediction intervals for the optimal order quantity are derived in two cases: (a) when the sample consists of two observations, and (b) when the sample is considered as sufficiently large. Regarding the asymptotic prediction intervals, specifications of the general expression are obtained for the time-series models AR(1), MA(1), and ARMA(1,1). These intervals are estimated in finite samples using in their theoretical expressions, the sample mean, the sample variance, and estimates of the theoretical autocorrelation coefficients at lag one and lag two. To assess the impact of this estimation procedure on the optimal performance of the newsvendor model, four accuracy implication metrics are considered which are related to: (a) the mean square error of the estimator, (b) the accuracy and the validity of prediction intervals, and (c) the actual probability of running out of stock during the period when the optimal order quantity is estimated. For samples with more than two observations, these metrics are evaluated through simulations, and their values are presented to appropriately constructed tables. The general conclusion is that the accuracy and the validity of the estimation procedure for the optimal order quantity depends upon the critical fractile, the sample size, the autocorrelation level, and the convergence rate of the theoretical autocorrelation function to zero.
Analysis An Agent-Based Model of Wealth Distribution

This model belongs to the large group of essentially neo-classical models that neglect work, production, and productive relations, but rather focuses on distributive interactions in a hunter-gatherer society. We set up an agent-based model where each agent has internal states and behavioral rules. Some states are fixed for the agent’s life, while others change through interaction with other agents or with the external environment. In our model, the agent’s metabolic rate and vision are fixed while wealth can change as agents move around and interact with the environment and indirectly with their co-agents as well. Life in an artificial society takes place in an environment governed by its own rules to provide a space of renewable resources that agents can get, metabolize and accumulate. Finally, there are rules of behavior for agents and for sites of the environment. In our model a movement rule for agent is to look around as far as one can, find the richest site, go there, get the resource. The rule for the environment sites could state: each site refreshes its initial resource capacity at the end of each period. Using this simple microstructure the model tries to "grow" a collective structure such as the wealth distribution. In the first palce, we find that agents’ skill (vision) heterogeneity increases wealth inequality, measured by the Gini coefficient. Secondly, we discover that, switching to a different measure of inequality, the gap between the richest and the poorest agents, does not allow us to obtain a clear understanding of the effects of skill’s heterogeneity. But, we do find that the increase in average vision increases the average wealth. Moreover, we find that inheritance of wealth, neighborhood at birth, metabolism etc. reduces the Gini, while vision inheritance increases it. Finally, our model reproduces a wealth distribution much more skewed than the Pareto’s law. JEL Classification: B41, C65, D31.
Decision, Risk and Operations Working Papers Series Number of Paths versus Number of Basis Functions in American Option Pricing Number of Paths versus Number of Basis Functions in American Option Pricing

An American option grants the holder the right to select the time at which to exercise the option, so pricing an American option entails solving an optimal stopping problem. Difficulties in applying standard numerical methods to complex pricing problems have motivated the development of techniques that combine Monte Carlo simulation with dynamic programming. One class of methods approximates the option value at each time using a linear combination of basis functions, and combines Monte Carlo with backward induction to estimate optimal coefficients in each approximation. We analyze the convergence of such a method as both the number of basis functions and the number of simulated paths increase. We get explicit results when the basis functions are polynomials and the underlying process is either Brownian motion or geometric Brownian motion. We show that the number of paths required for worst-case convergence grows exponentially in the degree of the approximating polynomials in the case of Brownian motion, faster in the case of geometric Brownian motion.
Impact of Rotation Correction after Brace Treatment on Prognosis in Adolescent Idiopathic Scoliosis

Study Design Level 4 retrospective review. Purpose Brace treatment is the standard nonoperative treatment for adolescent idiopathic scoliosis (AIS). Rotation correction is also important, because AIS involves a rotation deformity. The purpose of this study was to evaluate the impact of rotation correction after Osaka Medical College (OMC) brace treatment on clinical outcomes in AIS. Overview of Literature Brace treatment has a significant effect on the progression of AIS. However, few reports have examined rotation correction after brace treatment. Methods A total of 46 patients who wore the OMC brace were retrospectively reviewed. The curve magnitude was determined according to the Cobb method, and the rotation angle of the apical vertebrae was measured by the modified Nash-Moe method. Based on the difference in the rotation angle before and after the initial brace treatment, patients were divided into two groups. Group A (n=33) was defined as no change or improvement of the rotation angle; group B (n=13) was defined as deterioration of the rotation angle. If the patients had curve or rotation progression of 5° or more at skeletal maturity, or had undergone surgery, the treatment was considered a failure. Results Differences of rotation angle between before and after the initial brace treatment were 2°±2° in group A and –3°±2° in group B (p<0.001). The rates of treatment failure were 42% in group A and 77% in group B (p<0.05). This study included 25 patients with Lenke type 1 (54%). Group A (24%) with Lenke type 1 also had a significantly better success rate of brace treatment than group B (75%) (p<0.05). Conclusions Insufficient rotation correction increased brace treatment failure. Better rotation correction resulted in a higher success rate of brace treatment in patients with Lenke type 1.
Evaluation of Core Hopping on POWER7

Controlling and limiting the peak runtime temperature of a microprocessor has the potential to reduce chip leakage power consumption, improve chip reliability, reduce provisioned cooling, and reduce operational costs. Previously, the technique of core hopping has been proposed as one method to reduce peak runtime temperature. However, there is no study that shows core hopping is beneficial for modern many-core microprocessors found in high-end servers. This paper thoroughly examines heat spreading in the 8-core POWER7 microprocessor which provides 5 temperature sensors per core. We find that the POWER7 heatsink has excellent heat spreading capabilities which negates the benefits of core hopping. We conclude that high-performance servers with similar thermal solutions will also not see benefit from core-hopping methods.
Role for Non-Proteolytic Control of M-phase Promoting Factor Activity at M-phase Exit

M-phase Promoting Factor (MPF; the cyclin B-cdk 1 complex) is activated at M-phase onset by removal of inhibitory phosphorylation of cdk1 at thr-14 and tyr-15. At M-phase exit, MPF is destroyed by ubiquitin-dependent cyclin proteolysis. Thus, control of MPF activity via inhibitory phosphorylation is believed to be particularly crucial in regulating transition into, rather than out of, M-phase. Using the in vitro cell cycle system derived form Xenopus eggs, here we show, however, that inhibitory phosphorylation of cdk1 contributes to control MPF activity during M-phase exit. By sampling extracts at very short intervals during both meiotic and mitotic exit, we found that cyclin B1-associated cdk1 underwent transient inhibitory phosphorylation at tyr-15 and that cyclin B1-cdk1 activity fell more rapidly than the cyclin B1 content. Inhibitory phosphorylation of MPF correlated with phosphorylation changes of cdc25C, the MPF phosphatase, and physical interaction of cdk1 with wee1, the MPF kinase, during M-phase exit. MPF down-regulation required Ca++/calmodulin-dependent kinase II (CaMKII) and cAMP-dependent protein kinase (PKA) activities at meiosis and mitosis exit, respectively. Treatment of M-phase extracts with a mutant cyclin B1-cdk1AF complex, refractory to inhibition by phosphorylation, impaired binding of the Anaphase Promoting Complex/Cyclosome (APC/C) to its co-activator Cdc20 and altered M-phase exit. Thus, timely M-phase exit requires a tight coupling of proteolysis-dependent and proteolysis-independent mechanisms of MPF inactivation.
CATS: a linearizable and self-organizing key-value store

Distributed key-value stores provide scalable, fault-tolerant, and self-organizing storage services, but fall short of guaranteeing linearizable consistency in partially synchronous, lossy, partitionable, and dynamic networks, when data is distributed and replicated automatically by the principle of consistent hashing [14]. This work introduces consistent quorums as a solution for achieving atomic consistency. We present the design and implementation of CATS, a key-value store which uses consistent quorums to guarantee linearizability and partition tolerance in such adverse and dynamic network conditions. CATS is scalable, elastic, and self-organizing; key properties for modern cloud storage middleware. Our system evaluation shows that consistency can be achieved with practical performance and modest overhead: 5% decrease in throughput for read-intensive workloads, and 25% throughput loss for write-intensive workloads. CATS delivers submillisecond operation latencies under light load, single-digit millisecond operation latencies at 50% load, and it sustains a throughput of one thousand operations per second, per server, while scaling linearly to hundreds of servers.
New Evidence for Colored Leptons

The recent discovery of CDF anomaly suggest the existence of a new long-lived particle which means a dramatic deviation from standard model. This article summarizes the quantum model of CDF anomaly. The anomaly is interpreted in terms of production of τ-pions which can be regarded as pion like bound states of color octet excitations of τ-leptons and corresponding neutrinos. Colored leptons are one of the basic predictions of TGD distinguishing it from standard model and for 18 years ago were applied to explain the anomalous production of electron-positron pairs in heavy ion collisions near Coulomb wall. First it is shown that the model explains the basic characteristics of the anomaly. Then various alternatives generalizing the earlier model for electro-pion production are discussed and a general formula for differential cross section is deduced. Three alternatives inspired by eikonal approximation generalizing the earlier model inspired by Born approximation to a perturbation series in the Coulomb interaction potential of the colliding charges. The requirement of manifest relativistic invariance for the formula of differential cross section leaves only two options, call them I and II. The production cross section for τ-pion is estimated and found to be consistent with the reported cross section of order 100 pb for option I using same energy cutoff for lepto-pions as in the model for electro-pion production. For option II the production cross section is by several orders of magnitude too small under these assumptions. Since the model involves only fundamental coupling constants, the result can be regarded as a further success of the τ-pion model of CDF anomaly. Analytic expressions for the production amplitude are deduced in the Appendix as a Fourier transform for the inner product of the non-orthogonal magnetic and electric fields of the colliding charges in various kinematical situations. This allows to reduce numerical integrations to an integral over the phase space of lepto-pion and gives a tight analytic control over the numerics.
Structural Biology and Crystallization Communications

BrabA.11339. a: anomalous diffraction and ligand binding guide towards the elucidation of the function of a 'putative b-lactamase-like protein' from Brucella melitensis The crystal structure of a-lactamase-like protein from Brucella melitensis was initially solved by SAD phasing from an in-house data set collected on a crystal soaked with iodide. A high-resolution data set was collected at a synchroton at the Se edge wavelength, which also provided an independent source of phasing using a small anomalous signal from metal ions in the active site. Comparisons of anomalous peak heights at various wavelengths allowed the identification of the active-site metal ions as manganese. In the native data set a partially occupied GMP could be identified. When co-crystallized with AMPPNP or GMPPNP, clear density for the hydrolyzed analogs was observed, providing hints to the function of the protein.