Miracle-dz/UniFAR-FTUs huggingface dataset:
G-CSF mobilizes CD34+ regulatory monocytes that inhibit graft-versus-host disease

G-SCF–mobilized CD34+ monocytes inhibit graft-versus-host disease by the production of nitric oxide and the induction of regulatory T cells. Monocytes suppress GVHD Hematopoietic stem cell transplantation is a highly successful therapy used in patients with bone marrow dysfunction. However, when the stem cell donor cannot be matched to the recipient, the transplanted cells may attack the host in a process called graft-versus-host disease (GVHD). D’Aveni et al. now show that granulocyte colony-stimulating factor (G-CSF)–mobilized stem cells contain a previously uncharacterized population of immunosuppressive CD34+ cells transcriptionally similar to mature monocytes. These cells induce allogeneic T cell death in response to interferon-γ, resulting in regulatory T cell expansion and immunosuppression. The fraction of these CD34+ monocytes in peripheral blood inversely correlates with GVHD in patients, suggesting that expanding these cells before transplant may decrease the risk of GVHD. Granulocyte colony-stimulating factor (G-CSF) is routinely used to collect peripheral blood stem cells (PBSCs) from healthy donors for allogeneic hematopoietic stem cell transplantation (allo-HSCT). We show that, in both humans and mice, G-CSF mobilizes a subset of CD34+ cells with mature monocyte features. These cells, which are phenotypically and functionally conserved in mice and humans, are transcriptionally distinct from myeloid and monocytic precursors but similar to mature monocytes and endowed with immunosuppressive properties. In response to interferon-γ released by activated T cells, these cells produce nitric oxide, which induces allogeneic T cell death both in vitro and in vivo. These apoptotic T cells are engulfed by macrophages that release transforming growth factor–β and promote regulatory T cell expansion. Indeed, the fraction of CD34+ monocytes in peripheral blood CD34+ cells inversely correlates with the incidence of acute graft-versus-host disease (GVHD) in humans. Therefore, G-CSF–mobilized cells are an attractive candidate population to be expanded ex vivo for cellular therapy against GVHD.
A tracking framework for augmented reality tours on cultural heritage sites

Visual tracking for augmented reality tours is still challenging for cultural heritage sites because of the great variation of tracking targets and environments on such sites. Even at today's state of the art, it is almost impossible to apply just one tracking method to all the various environments with any hope of success. This paper presents a tracking framework to overcome this problem. It consists of different tracking flows, each efficiently using robust visual cues of the target scene. Analysis of the tracking environment enables more practical tracking at the sites. The reliability of the tracking framework is verified through on-site demonstrations at Gyeong-bokgung, the most symbolic cultural heritage site in Korea.
Project towards no drug abuse: a review of the findings and future directions.

OBJECTIVE To provide a review of the evidence from 3 experimental trials of Project Towards No Drug Abuse (TND), a senior-high-school-based drug abuse prevention program. METHODS Theoretical concepts, subjects, designs, hypotheses, findings, and conclusions of these trials are presented. A total of 2,468 high school youth from 42 schools in southern California were surveyed. RESULTS The Project TND curriculum shows reductions in the use of cigarettes, alcohol, marijuana, hard drugs, weapon carrying, and victimization. Most of these results were replicated across the 3 trials. CONCLUSION Project TND is an effective drug and violence prevention program for older teens, at least for one-year follow-up.
Monaural Separation and Classification of Mixed Signals : a Support-vector Regression Perspective

We address the problem of extracting multiple independent sources from a single mixture signal. Standard independentcomponent analysis approaches fail when the number of sources is greater than the number of mixtures. For this case, the sparse-decomposition method [1] has been proposed. The method relies on a dictionary of atomic signals and recovers the degree to which various dictionary atoms are present in the mixture. We show that the sparse-decomposition method is equivalent to a form of support-vector regression (SVR). The training inputs for the SVR are the dictionary atoms, and the corresponding targets are the dot product of the mixture and atom vectors. The SVR perspective provides a new interpretation of the sparse-decomposition method’s hyperparameter, and allows us to generalize and improve the method. The most important insight is that the sources do not have to be identical to dictionary atoms, but rather we can accommodate a many-to-one mapping of source signals to dictionary atoms—a classification of sorts—characterized by a known nonlinear transformation with unknown parameters. The limitation of the SVR perspective is that it cannot recover the signal strength of an atom in the mixture; rather, it can only recover whether or not a particular atom was present. In experiments, we show that our model can handle difficult problems involving classification of sources. Our model may be particularly useful for speech signal processing and CDMA-based mobile communication, where in both cases we have knowledge about the invariances in the signal.
Do Producer Prices Cause Consumer Prices? Some Empirical Evidence

The main purpose of this paper is to examine the relationship between consumer price index (CPI) and producer price index (PPI) in Malaysia. This research considers monthly data of consumer price index and producer price index from January 1986 to April 2007. The Johansen cointegration method suggests that there is long-run equilibrium relationship between these two variables. Both Engle Granger and Toda-Yamamoto causality tests find that there is uni-directional causality running from PPI to CPI.
Regional innovation systems, clusters, and knowledge networking

How can we dare to produce ‘just another’special issue and set of papers dealing with topics thathave already been debated so extensively in recent years: knowledge networks, innovativeclusters and other types of systems of relationships? Or in other words: Is there still some scopefor adding further scientiﬁc value to this debate, given the wealth of conceptual and empiricalstudies that have been compiled in other special issues and publications? To name just a fewseminal works, several journal issues have been devoted to similar topics, like ‘networks andeconomic agglomerations’ (Burger et al. 2009), ‘network analysis application in innovationstudies’ (Kastelle and Steen 2010), or ‘innovation and entrepreneurship: the effect of locationand context’ (Montoro-Sanchez and Ribeiro Soriano 2011). And also this journal’s specialissues which has already brought out other sets of papers on ‘spatial knowledge diffusionthrough collaborative networks’ (Autant-Bernard et al. 2007), and ‘knowledge spillover agentsand regional development’(Trippl and Maier 2010). Beyond that, important conceptual aspectsof the role of innovation-oriented collaboration for (regional) economic development have beenwidely discussed under the labels, for instance, of regional innovation systems (Cooke et al.2004), triple helix (Etzkowitz and Leydesdorff 2000; Leydesdorff 2005) and, in the simplestexpression, networks (Christopherson et al. 2008; Grabher and Powell 2005; Kogut 2000) forquite some time. This has been accompanied by an increasing focus on empirical studies thatdeal with the methodological issues of how to adequately capture the essential features ofrelevant actor collaborations (see for instance, Cantner and Graf 2006; Graf 2006; Huber 2009;Kratke and Brandt 2009; Ponds et al. 2007). Social network analysis has emerged as a particu-larly appealing tool to regional scientists that offers various options for investigating structuraland spatial patterns of knowledge-intensive networking (Knoke and Yang 2008; Ter Wal andBoschma 2009). Given this wealth of perspectives and modes of investigation applied hitherto, what makesus conﬁdent that the collection of contributions presented in this journal volume still raises the
On Convolutional Lattice Codes and Lattice Decoding Using Trellis Structure

Constructing hypercubic lattices from convolutional codes based on Constructions A and D is investigated in this paper and their error performance in a point-to-point communication system is studied. Moreover, analogous to Construction A/D, single/multilayer code lattices are proposed. As Construction D requires certain minimum Euclidean distance criteria, we propose methods to guarantee the distance requirements of Construction D, which results in a superior lattice construction compared with Construction A. Due to the key role of soft input soft out decoding algorithms in improving the performance of a code, lattice decoding based on the Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm for lattices constructed from convolutional codes is also proposed in this paper. Moreover, as the BCJR algorithm requires knowledge of the statistical characteristics of modulo lattice additive noise (MLAN), the probability density function of MLAN is derived in closed form.
Nonlinear Models of Measurement Errors

Measurement errors in economic data are pervasive and nontrivial in size. The presence of measurement errors causes biased and inconsistent parameter estimates and leads to erroneous conclusions to various degrees in economic analysis. While linear errors-in-variables models are usually handled with well-known instrumental variable methods, this article provides an overview of recent research papers that derive estimation methods that provide consistent estimates for nonlinear models with measurement errors. We review models with both classical and nonclassical measurement errors, and with misclassification of discrete variables. For each of the methods surveyed, we describe the key ideas for identification and estimation, and discuss its application whenever it is currently available. (JEL C20, C26, C50)
Gas Sensors Based on Electrospun Nanofibers

Nanofibers fabricated via electrospinning have specific surface approximately one to two orders of the magnitude larger than flat films, making them excellent candidates for potential applications in sensors. This review is an attempt to give an overview on gas sensors using electrospun nanofibers comprising polyelectrolytes, conducting polymer composites, and semiconductors based on various sensing techniques such as acoustic wave, resistive, photoelectric, and optical techniques. The results of sensing experiments indicate that the nanofiber-based sensors showed much higher sensitivity and quicker responses to target gases, compared with sensors based on flat films.
Type III or allosteric kinase inhibitors for the treatment of non-small cell lung cancer

Introduction: In recent times, there has been much interest in the development of pharmacological kinase inhibitors that treat NSCLC. Furthermore, treatment options have been guided by the development of a wide panel of synthetic small molecule kinase inhibitors. Most of the molecules developed belong to the type I class of inhibitors that target the ATP-binding site in its active conformation. The high sequence similarity in the ATP-binding site among members of the kinase families often results in low selectivity and additional toxicities. Also, second mutations in the ATP-binding site, such as threonine to methionine at position 790, have been described as a mechanism of resistance to ATP-competitive kinase inhibitors. For these reasons, alternative drug development approaches targeting sites other than the ATP cleft are being pursued. The class III or allosteric inhibitors, which bind outside the ATP-binding site, have been shown to negatively modulate kinase activity. Areas covered: In this review, the authors discuss the most well-characterised allosteric inhibitors that have reached clinical development in NSCLC. Expert opinion: Great progress has made in developing inhibitors with entirely new modes of action. That being said, it is important to highlight that despite their apparent simplicity, biochemical assays will remain at the core of drug discovery activities to better explore these new opportunities.
Participation of metabotropic glutamate receptors in pentetrazol‐induced kindled seizure

Purpose: The present study was undertaken to clarify the effects of (RS)‐1‐aminoindan‐1,5‐dicarboxylic acid (AIDA), a metabotropic glutamate receptor (mGluR) 1 antagonist, (2R,4R)‐4‐aminopyrrolidine‐2,4‐dicarboxylate ((2R,4R)‐APDC), a mGluR2/3 agonist, and L‐(+)‐2‐amino‐4‐phosphonobutyric acid (L‐AP4), a mGluR4/8 agonist, on pentetrazol‐induced kindled seizures.
Potential Field based Integrated Exploration for Multi-robot Teams

In this paper we present an approach for multi-robot cooperative exploration based on the potential field generated by several basic behaviours. When an unknown environment is explored the uncertainty in the localization normally grows, this fact may cause the failure of the Simultaneous Localization and Mapping (SLAM) algorithm, and thus constructing an useless and inaccurate map. The exploration algorithm described here considers the current knowledge of the environment, the location of the robots and the uncertainty in their positions in order to return to previously explored areas when it is needed. These actions definitely help the SLAM algorithm to build a precise map. Several simulations are presented that demonstrate the validity of the
INHIBITORY EFFECT OF MAST CELL-MEDIATED ACUTE AND CHRONIC ALLERGIC REACTIONS BY DODUTANG

ABSTRACT Dodutang has been used for treatment of various allergic inflammation diseases in Korea. However, it is still unclear how Dodutang prevents these diseases in experimental animal models. Mast cells play an important roles in allergic and other inflammatory reactions by producing a spectrum of powerful mediators including preformed and de novo synthesized cytokines. In this study, we investigated the effect of Dodutang on mast cell-mediated allergic and inflammatory reactions. Dodutang (0.001–5 g/L) significantly inhibited the histamine release from rat peritoneal mast cells activated by compound 48/80. Dodutang (0.001–5 g/kg) dose-dependantly inhibited the passive cutaneous anaphylaxis reaction activated by anti-dinitrophenyl (DNP) IgE in a rat model, especially, by 78.96% at the concentration of 5 g/kg. In addition, Dodutang potently inhibited the secretion of tumor necrosis factor-α (TNF-α), interleukin (IL)-1β in phorbol 12-myristate 13-acetate plus calcium ionophore A23187-stimulated human mast cells. However, IL-6 secretion was enhanced at the same conditions. Dodutang also inhibited the main inflammatory cytokine TNF-α protein expression in human mast cells. These results provide evidences that Dodutang may be beneficial in the treatment of acute and chronic allergic diseases.
Querying over Federated SPARQL Endpoints - A State of the Art Survey

The increasing amount of Linked Data and its inherent distributed nature have attracted signicant attention throughout the research community and amongst practitio- ners to search data, in the past years. Inspired by research results from traditional distributed databases, dierent approaches for managing federation over SPARQL Endpoints have been introduced. SPARQL is the standardised query language for RDF, the default data model used in Linked Data deployments and SPARQL Endpoints are a popular access mechanism provided by many Linked Open Data (LOD) repositories. In this paper, we initially give an overview of the federation framework infrastructure and then proceed with a comparison of existing SPARQL federation frameworks. Finally, we highlight shortcomings in existing frameworks, which we hope helps spawning new research directions.
Structural Analysis of the Hemagglutinin from the Recent 2013 H7N9 Influenza Virus

ABSTRACT In March 2013, the Chinese Center for Disease Control and Prevention reported human infections with an H7N9 influenza virus, and by 20 July 2013, the numbers of laboratory-confirmed cases had climbed to 134, including 43 fatalities and 127 hospitalizations. The newly emerging H7N9 viruses constitute an obvious public health concern because of the apparent severity of this outbreak. Here we focus on the hemagglutinins (HAs) of these viruses and assess their receptor binding phenotype in relation to previous HAs studied. Glycan microarray and kinetic analyses of recombinant A(H7N9) HAs were performed to compare the receptor binding profile of wild-type receptor binding site variants at position 217, a residue analogous to one of two positions known to switch avian to human receptor preference in H2N2 and H3N2 viruses. Two recombinant A(H7N9) HAs were structurally characterized, and a mutational study of the receptor binding site was performed to analyze important residues that can affect receptor preference and affinity. Results highlight a weak human receptor preference of the H7N9 HAs, suggesting that these viruses require further adaptation in order to adapt fully to humans.
Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential

Purpose of review The application of artificial intelligence in the diagnosis of obstructive lung diseases is an exciting phenomenon. Artificial intelligence algorithms work by finding patterns in data obtained from diagnostic tests, which can be used to predict clinical outcomes or to detect obstructive phenotypes. The purpose of this review is to describe the latest trends and to discuss the future potential of artificial intelligence in the diagnosis of obstructive lung diseases. Recent findings Machine learning has been successfully used in automated interpretation of pulmonary function tests for differential diagnosis of obstructive lung diseases. Deep learning models such as convolutional neural network are state-of-the art for obstructive pattern recognition in computed tomography. Machine learning has also been applied in other diagnostic approaches such as forced oscillation test, breath analysis, lung sound analysis and telemedicine with promising results in small-scale studies. Summary Overall, the application of artificial intelligence has produced encouraging results in the diagnosis of obstructive lung diseases. However, large-scale studies are still required to validate current findings and to boost its adoption by the medical community.
Session Based Logging (SBL) for IP-Traceback on Network Forensics

The widely acknowledged problem of reliably identifying the origin of information in cyberspace has been the subject of much research. Due to the nature of the Internet protocol, the source IP can be easily falsified which results in numerous problems including infamous denial of service attacks. The combination of smart devices with powerful processing capabilities once observed only in mainframe computers decades ago and the presence of the Internet which allows communications between all those devices exacerbate the problem. In this paper, we propose a novel technique called Session Based Logging (SBL) for simple and effective IP-Traceback and logging mechanism. SBL is easy to implement and also has significant advantage of saving storage space over previously proposed schemes. Moreover the SBL approach has clear edge under sensitive privacy regulations since it does not need to capture detailed contents of each individual communication session. Experimental results show its potential and ease of execution from free of any agent software installation on the logging machine. The proposed SBL scheme on this paper currently supports only TCP sessions but we believe this approach could be further extended to UDP connections which have many inherent network security problems.
A low complexity representation of the coherent point spread function in the presence of aberrations and arbitrarily large defocus by

In this thesis we introduce a new method for analyzing the diffraction integral for evaluating the point spread function. The new method is based on the use of higher order Airy functions along with Zernike and Taylor expansions. Our approach is applicable when we are considering a finite, arbitrary number of aberrations and arbitrary large defocus simultaneously. We present an upper bound for the complexity and the convergence rate of this method. We also compare the cost and accuracy of this method to traditional ones and show the efficiency of our method through these comparisons. In particular, we rigorously show that this method is constructed in a way that the complexity of the analysis (i.e the number of terms needed for expressing the light disturbance) does not increase as either of defocus or resolution of interest increases. This has applications in several fields such as biological microscopy, lithography and multi-domain optimization in optical systems. Thesis Supervisor: Daniela Pucci de Farias Title: Assistant Professor, Mechanical Engineering
Direct Ionic Regulation of the Activity of Myo-Inositol Biosynthesis Enzymes in Mozambique Tilapia

Myo-inositol (Ins) is a major compatible osmolyte in many cells, including those of Mozambique tilapia (Oreochromis mossambicus). Ins biosynthesis is highly up-regulated in tilapia and other euryhaline fish exposed to hyperosmotic stress. In this study, enzymatic regulation of two enzymes of Ins biosynthesis, Ins phosphate synthase (MIPS) and inositol monophosphatase (IMPase), by direct ionic effects is analyzed. Specific MIPS and IMPase isoforms from Mozambique tilapia (MIPS-160 and IMPase 1) were selected based on experimental, phylogenetic, and structural evidence supporting their role for Ins biosynthesis during hyperosmotic stress. Recombinant tilapia IMPase 1 and MIPS-160 activity was assayed in vitro at ionic conditions that mimic changes in the intracellular milieu during hyperosmotic stress. The in vitro activities of MIPS-160 and IMPase 1 are highest at alkaline pH of 8.8. IMPase 1 catalytic efficiency is strongly increased during hyperosmolality (particularly for the substrate D-Ins-3-phosphate, Ins-3P), mainly as a result of [Na+] elevation. Furthermore, the substrate-specificity of IMPase 1 towards D-Ins-1-phosphate (Ins-1P) is lower than towards Ins-3P. Because MIPS catalysis results in Ins-3P this results represents additional evidence for IMPase 1 being the isoform that mediates Ins biosynthesis in tilapia. Our data collectively demonstrate that the Ins biosynthesis enzymes are activated under ionic conditions that cells are exposed to during hypertonicity, resulting in Ins accumulation, which, in turn, results in restoration of intracellular ion homeostasis. We propose that the unique and direct ionic regulation of the activities of Ins biosynthesis enzymes represents an efficient biochemical feedback loop for regulation of intracellular physiological ion homeostasis during hyperosmotic stress.
Vowel-Rhotic Metathesis in Guarayu1

Guarayu (Tupí-Guaraní, Bolivia) has undergone a diachronic process of metathesis in which a word-final tap /ɾ/ exchanged positions with a preceding high nonfront vowel /ɨ/ or /u/. We propose a scenario for how such an exchange could occur, using Guarayu as a case study. A tap/vowel metathesis is presented as a timing readjustment that led to an exchange of phonemic status between a phonemic vowel on one side of the tap and an automatic intrusive vowel on the other. We suggest that, in Guarayu, this realignment may have been facilitated by an insufficiency of phonetic cues that a listener might routinely use to accurately perceive and locate the transition between the vowel and tap involved in the exchange. We propose that phonological factors also played a role and that metathesis was perception optimizing, and we report the results of a speech perception experiment that supports this interpretation. Connections are drawn between the Guarayu metathesis and patterns of vowel epenthesis and deletion known to occur as alternatives to metathesis in other languages.