Miracle-dz/UniFAR-FTUs huggingface dataset:
Level truncation and the quartic tachyon coupling

We discuss the convergence of level truncation in bosonic open string field theory. As a test case we consider the calculation of the quartic tachyon coupling γ4. We determine the exact contribution from states up to level L = 28 and discuss the L→∞ extrapolation by means of the BST algorithm. We determine in a self-consistent way both the coupling and the exponent ω of the leading correction to γ4 at finite L that we assume to be ~ 1/Lω. The results are γ4 = −1.7422006(9) and |ω−1|10−4.
Immigration and Inequality

Immigration has long been a controversial topic among economists. The issue nearly disappeared in the 1960s, but over the past three decades professional interest has picked up as immigrant inflows have surged. The new immigration has attracted attention in part because of its sheer size—approximately 1.25 million people per year over the first half of this decade— and in part because of its composition. A third or more of the new arrivals are undocumented immigrants from Mexico and Central America with low education and limited English skills (Jeffrey Passel 2005). These immigrants presumably compete for the same jobs held by the least-skilled native workers, contributing to a trifecta of economic factors—technology, trade, and immigration—that are thought to have led to a rise in skill differentials in the US economy since the late 1970s. This paper presents an overview and synthesis of research on the connection between immigration and wage inequality, focusing on the evidence derived from comparisons across
Millennial‐scale precipitation changes in southern Brazil over the past 90,000 years

A U‐Th dated 90,000 year‐long speleothem oxygen isotope record from southern Brazil anti‐correlates remarkably with the cave calcite records from eastern China, but positively correlates with the speleothem record from northeastern Brazil, suggesting an interhemispheric anti‐phasing of rainfall on both millennial and orbital timescales, likely related to displacement in the mean position of the intertropical convergence zone and associated asymmetry in Hadley circulation. The phase relationships among these records are consistent with the hypothesis that abrupt climate events during the last glacial period are triggered by oceanic circulation changes in the high latitudes and enhanced by tropical feedbacks.
Unraveling the Complex Relationship Triad between Lipids, Obesity, and Inflammation

Obesity today stands at the intersection between inflammation and metabolic disorders causing an aberration of immune activity, and resulting in increased risk for diabetes, atherosclerosis, fatty liver, and pulmonary inflammation to name a few. Increases in mortality and morbidity in obesity related inflammation have initiated studies to explore different lipid mediated molecular pathways of attempting resolution that uncover newer therapeutic opportunities of anti-inflammatory components. Majorly the thromboxanes, prostaglandins, leukotrienes, lipoxins, and so forth form the group of lipid mediators influencing inflammation. Of special mention are the omega-6 and omega-3 fatty acids that regulate inflammatory mediators of interest in hepatocytes and adipocytes via the cyclooxygenase and lipoxygenase pathways. They also exhibit profound effects on eicosanoid production. The inflammatory cyclooxygenase pathway arising from arachidonic acid is a critical step in the progression of inflammatory responses. New oxygenated products of omega-3 metabolism, namely, resolvins and protectins, behave as endogenous mediators exhibiting powerful anti-inflammatory and immune-regulatory actions via the peroxisome proliferator-activated receptors (PPARs) and G protein coupled receptors (GPCRs). In this review we attempt to discuss the complex pathways and links between obesity and inflammation particularly in relation to different lipid mediators.
DriverDBv2: a database for human cancer driver gene research

We previously presented DriverDB, a database that incorporates ∼6000 cases of exome-seq data, in addition to annotation databases and published bioinformatics algorithms dedicated to driver gene/mutation identification. The database provides two points of view, ‘Cancer’ and ‘Gene’, to help researchers visualize the relationships between cancers and driver genes/mutations. In the updated DriverDBv2 database (http://ngs.ym.edu.tw/driverdb) presented herein, we incorporated >9500 cancer-related RNA-seq datasets and >7000 more exome-seq datasets from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and published papers. Seven additional computational algorithms (meaning that the updated database contains 15 in total), which were developed for driver gene identification, are incorporated into our analysis pipeline, and the results are provided in the ‘Cancer’ section. Furthermore, there are two main new features, ‘Expression’ and ‘Hotspot’, in the ‘Gene’ section. ‘Expression’ displays two expression profiles of a gene in terms of sample types and mutation types, respectively. ‘Hotspot’ indicates the hotspot mutation regions of a gene according to the results provided by four bioinformatics tools. A new function, ‘Gene Set’, allows users to investigate the relationships among mutations, expression levels and clinical data for a set of genes, a specific dataset and clinical features.
Network Function Virtualization and Software-Defined Networking: Advancing Multimedia Distribution

This special issue is dedicated to the exploration of how systems based on software-defined networking (SDN) and network function virtualization (NFV) can enhance multimedia distribution. Bringing together researchers from both the networking and multimedia research communities, this issue showcases emerging research and creates a discussion from diverse viewpoints regarding how the greater visibility, agility, and flexibility promised by NFV and SDN will enable innovative architectures for multimedia distribution, potentially transforming the entire delivery chain of multimedia content.
Handling Inductance in Early Power Grid Verification

As part of integrated circuit design verification, one should check if the voltage drop on the power grid exceeds some critical threshold. One way to do this is by simulation, but that is computationally expensive and gets prohibitive for large circuits with a large variety of possible operational modes. Another limitation of a simulation-based approach is that it requires complete knowledge of the logic circuitry drawing current from the grid, thus precluding grid verification early in the design process. In this paper, we model the grid as an RLC circuit and we propose three verification techniques that can be applied in the early stages of the design process. These techniques do not require exact knowledge of the circuit currents. Instead, the currents drawn by the logic beneath the power grid are described by means of current constraints that capture the uncertainty about circuit details and activity. The first verification approach gives the exact worst-case voltage drop at every node of the grid, but it is slow. A second faster approach gives conservative bounds on the worst-case voltage drop at every node of the grid. The third approach is much faster; it is a conservative approach which simply checks if the grid voltage drop exceeds some pre-defined thresholds, without actually computing the worst-case voltage drop at every node
Modeling the Demographic Effects of Endocrine Disruptors

In this article we describe a series of strategic models of populations and individuals subject to challenge by endocrine disruptors. These models are not designed to be fitted to detailed data on specific species but rather are intended to provide general insights on the relative importance of different demographic mechanisms in the population context. Therefore, the models contain the minimum necessary biological detail, but in recompense they are highly accessible to mathematical analysis. We show that, over a range of models with contrasting biological detail, population viability is controlled by the number of female offspring that result from the average female’s lifetime reproductive activity. Thus, male fertility changes have little effect at the population level until they become severe enough to reduce this average female output. We argue that in many circumstances endocrine disruptors are likely to produce directly deleterious effects on female fecundity at levels far below those required to reduce male fertility to dangerously low levels. Finally, we formulate a simple model of individual energetics that we argue can form the basis of a strategic discussion of the likely sensitivity of female demographic parameters to chemically induced changes in physiological function.
Histone Acetylation and Chromatin Remodeling Are Required for UV-B–Dependent Transcriptional Activation of Regulated Genes in Maize[W]

The nuclear proteomes of maize (Zea mays) lines that differ in UV-B tolerance were compared by two-dimensional gel electrophoresis after UV light treatment. Differential accumulation of chromatin proteins, particularly histones, constituted the largest class identified by mass spectrometry. UV-B–tolerant landraces and the B73 inbred line show twice as many protein changes as the UV-B–sensitive b, pl W23 inbred line and transgenic maize expressing RNA interference constructs directed against chromatin factors. Mass spectrometic analysis of posttranslational modifications on histone proteins demonstrates that UV-B–tolerant lines exhibit greater acetylation on N-terminal tails of histones H3 and H4 after irradiation. These acetylated histones are enriched in the promoter and transcribed regions of the two UV-B–upregulated genes examined; radiation-sensitive lines lack this enrichment. DNase I and micrococcal nuclease hypersensitivity assays indicate that chromatin adopts looser structures around the selected genes in the UV-B–tolerant samples. Chromatin immunoprecipitation experiments identified additional chromatin factor changes associated with the nfc102 test gene after UV-B treatment in radiation-tolerant lines. Chromatin remodeling is thus shown to be a key process in acclimation to UV-B, and lines deficient in this process are more sensitive to UV-B.
A longitudinal twin study of fears from middle childhood to early adulthood: evidence for a developmentally dynamic genome.

CONTEXT While the nature of common fears changes over development, we do not know whether genetic effects on fear-proneness are developmentally stable or developmentally dynamic. OBJECTIVE To determine the temporal pattern of genetic and environmental effects on the level of intensity of common fears. DESIGN Prospective, 4-wave longitudinal twin study. Structural modeling was performed with Mx. SETTING General community. PARTICIPANTS Two thousand four hundred ninety twins and their parents from the Swedish Twin Study of Child and Adolescent Development. MAIN OUTCOME MEASURE The level of parent- and/or self-reported fears obtained at ages 8 to 9, 13 to 14, 16 to 17, and 19 to 20 years. RESULTS Thirteen questionnaire items formed 3 distinct fear factors: situational, animal, and blood/injury. For all 3 fears, the best-fit model revealed developmentally dynamic effects and, in particular, evidence for both genetic attenuation and innovation. That is, genetic factors influencing fear intensity at age 8 to 9 years decline substantially in importance over time. Furthermore, new sets of genetic risk factors impacting fear intensity "come on line" in early adolescence, late adolescence, and early adulthood. As the twins aged, the influence of the shared environment declined and unique environment increased. No sex effects were found for situational fears while for animal and blood/injury fears, genetic factors in males and females were correlated but not identical. Shared environmental factors were both more important and more stable for animal fears than for situational or blood/injury fears. CONCLUSIONS Genetic effects on fear are developmentally dynamic from middle childhood to young adulthood. As children age, familial-environmental influences on fears decline in importance.
RTX proteins: a highly diverse family secreted by a common mechanism

Repeats-in-toxin (RTX) exoproteins of Gram-negative bacteria form a steadily growing family of proteins with diverse biological functions. Their common feature is the unique mode of export across the bacterial envelope via the type I secretion system and the characteristic, typically nonapeptide, glycine- and aspartate-rich repeats binding Ca2+ ions. In this review, we summarize the current state of knowledge on the organization of rtx loci and on the biological and biochemical activities of therein encoded proteins. Applying several types of bioinformatic screens on the steadily growing set of sequenced bacterial genomes, over 1000 RTX family members were detected, with the biological functions of most of them remaining to be characterized. Activities of the so far characterized RTX family members are then discussed and classified according to functional categories, ranging from the historically first characterized pore-forming RTX leukotoxins, through the large multifunctional enzymatic toxins, bacteriocins, nodulation proteins, surface layer proteins, up to secreted hydrolytic enzymes exhibiting metalloprotease or lipase activities of industrial interest.
Prediction of Breast Cancer Metastasis by Gene Expression Profiles: A Comparison of Metagenes and Single Genes

Background The popularity of a large number of microarray applications has in cancer research led to the development of predictive or prognostic gene expression profiles. However, the diversity of microarray platforms has made the full validation of such profiles and their related gene lists across studies difficult and, at the level of classification accuracies, rarely validated in multiple independent datasets. Frequently, while the individual genes between such lists may not match, genes with same function are included across such gene lists. Development of such lists does not take into account the fact that genes can be grouped together as metagenes (MGs) based on common characteristics such as pathways, regulation, or genomic location. Such MGs might be used as features in building a predictive model applicable for classifying independent data. It is, therefore, demanding to systematically compare independent validation of gene lists or classifiers based on metagene or individual gene (SG) features. Methods In this study we compared the performance of either metagene- or single gene-based feature sets and classifiers using random forest and two support vector machines for classifier building. The performance within the same dataset, feature set validation performance, and validation performance of entire classifiers in strictly independent datasets were assessed by 10 times repeated 10-fold cross validation, leave-one-out cross validation, and one-fold validation, respectively. To test the significance of the performance difference between MG- and SG-features/classifiers, we used a repeated down-sampled binomial test approach. Results MG- and SG-feature sets are transferable and perform well for training and testing prediction of metastasis outcome in strictly independent data sets, both between different and within similar microarray platforms, while classifiers had a poorer performance when validated in strictly independent datasets. The study showed that MG- and SG-feature sets perform equally well in classifying independent data. Furthermore, SG-classifiers significantly outperformed MG-classifier when validation is conducted between datasets using similar platforms, while no significant performance difference was found when validation was performed between different platforms. Conclusion Prediction of metastasis outcome in lymph node–negative patients by MG- and SG-classifiers showed that SG-classifiers performed significantly better than MG-classifiers when validated in independent data based on the same microarray platform as used for developing the classifier. However, the MG- and SG-classifiers had similar performance when conducting classifier validation in independent data based on a different microarray platform. The latter was also true when only validating sets of MG- and SG-features in independent datasets, both between and within similar and different platforms.
Effects of medial septal or unilateral hippocampal inactivations on reference and working spatial memory in rats

The memory performances of rats receiving a reversible inactivation of either the medial septum or one side of the ventral hippocampus were compared in a radial arm maze task allowing the assessment of both working and reference memory. After pre‐surgery training, rats were chronically equipped with bilateral cannulae into the ventral hippocampus and a single cannula into the medial septum. Following post‐surgery retraining, animals received a series of test trials during which they received saline or lidocaine injections in either the medial septum or one side of the ventral hippocampus. Lidocaine injections in either structure resulted in both reference and working memory deficits. However, animals were more impaired after septal injections than after unilateral hippocampal injections. This result suggests that the septo‐hippocampal formation acts as a functionally homogeneous structure essential for spatial processing. © 1994 Wiley‐Liss, Inc.
Compact VHF quadrifilar helix antenna

This papers addresses the miniaturization of quadrifilar helix antennas (QHAs) for space application. An innovative miniaturization technique combining modified fractal curves and sinusoidal profiles is proposed in order to fit the dimension of QHA with the launching constraints. Reduction size ratio up to 70% is obtained without a significant degradation of the radiation pattern, directivity, polarization purity and input matching. The impact of the miniaturization technique as function of the relative height is analyzed and several conclusions are conducted.
Sub-Thermal Subthreshold Characteristics in Top–Down InGaAs/InAs Heterojunction Vertical Nanowire Tunnel FETs

This letter demonstrates top-down InGaAs/ InAs heterojunction vertical nanowire tunnel FETs with sub-thermal subthreshold characteristics over two orders of magnitude of current. A minimal subthreshold swing of 53 mV/decade at <inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm {ds}} = 0.3$ </tex-math></inline-formula> V has been obtained at room temperature. An I<sub>60</sub> (defined as the highest current level where the subthreshold characteristics exhibit a transition from sub- to super-60 mV/decade behavior) of 4.3 nA/<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> has been achieved at <inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm {ds}} = 0.3$ </tex-math></inline-formula> V. Compared with an earlier device generation, much reduced temperature dependence of the subthresholdcharacteristics is observed in this letter. The major difference between the two device generations is the drastically reduced interface trap density, evidenced by the improvement in the subthreshold swing of InGaAs vertical nanowire MOSFETs fabricated at the same time. This result suggests oxide–semiconductor interface trap-assisted tunnelling the main leakage mechanism in III-V TFETs fabricated by our process. The improvement in the interface quality has been enabled by improved gate oxide deposition and post-deposition treatment.
A Hierarchical VQSVM for Imbalanced Data Sets

First, a hierarchical modelling method, VQSVM, is introduced, and some remarks are discussed. Secondly the proposed VQSVM is applied to a nonstandard learning environment, imbalanced data sets. In cases of extremely imbalanced dataset with high dimensions, standard machine learning techniques tend to be overwhelmed by the large classes. The hierarchical VQSVM contains a set of local models i.e. codevectors produced by the vector quantization and a global model, i.e. support vector machine, to rebalance datasets without significant information loss. Some issues, e.g. distortion and support vectors, have been discussed to address the trade-off between the information loss and undersampling rate. Experiments compare VQSVM with random resampling techniques on some imbalanced datasets with varied imbalance ratios, and results show that the performance of VQSVM is superior or equivalent to random resampling techniques, especially in case of extremely imbalanced large datasets.
Higher Level Meta Programming in Qu-Prolog 3: 0

For representing high level knowledge, such as the mathematical knowledge used in interactive theorem provers and verificaton systems, it is desirable to extend Prolog's concept of data object. A basic reason is that Prolog data objects - Herbrand objects - are terms of a minimal object language, which does not include its own object variables, or quantification over thse variables. Qu-Prolog (Quantifier Prolog) is an extended logic programming concept which takes as its data objects, object terms which may include object level variables, free or bound, and arbitrary quantifiers to bind these variables. Qu-Prolog is unique in allowing its data objects to include free occurrences of object variables. This paper describes Qu-Prolog's data objects and its facilities for computing on those objects. The Qu-Prolog unification algorithm unifies Qu-Prolog terms up to changes of bound variables. The power of Qu-Prolog unification is greatly increased by the inclusion in the language of an evaluable substitution operator which correctly substitutes at unification time for free occurrences of object variables. Some related Qu-Prolog facilities for implementing theorem proving algorithms are described, including a new method for persisting data across queries. Qu-Prolog 3.0 is a compiled implementation which is in experiemntal use, supporting the development of interactive reasoning systems.
Further results on decision fusion in censoring sensor networks: An unknown network size

Energy consumption is a vital concern when implementing distributed decision fusion in most wireless sensor networks. This paper studies the impact of sensor censoring on the decision fusion performance when the number of sensors is unknown at the fusion center. The global decision rule adopted at the fusion center is the Chair-Varshney fusion rule modified to take account of the unknown network size. It is shown that under the assumption of equally likely hypotheses, allowing more transmitting sensors does not necessarily yield better decision fusion; rather, there exists a censoring probability threshold below which the increase in the number of active sensors just incurs more intra-network communication overhead but will not improve the global decision performance. Our findings establish that the design of energy-efficient local detection rules should commence with the censoring rate threshold.
Toll-like receptor 4 restricts retinal progenitor cell proliferation

Retinal neurogenesis ceases by the early postnatal period, although retinal progenitor cells (RPCs) persist throughout life. In this study, we show that in the mammalian eye, the function of Toll-like receptor 4 (TLR4) extends beyond regulation of the innate immune response; it restricts RPC proliferation. In TLR4-deficient mice, enhanced proliferation of cells reminiscent of RPCs is evident during the early postnatal period. In vitro experiments demonstrate that TLR4 acts as an intrinsic regulator of RPC fate decision. Increased TLR4 expression in the eye correlates with the postnatal cessation of cell proliferation. However, deficient TLR4 expression is not sufficient to extend the proliferative period but rather contributes to resumption of proliferation in combination with growth factors. Proliferation in vivo is inhibited by both MyD88-dependent and -independent pathways, similar to the mechanisms activated by TLR4 in immune cells. Thus, our study attributes a novel role to TLR4 as a negative regulator of RPC proliferation.