Miracle-dz/UniFAR-FTUs huggingface dataset:
Size, hatching rate, and hatching period of sexually and asexually produced eggs in the facultatively parthenogenetic termite Reticulitermes speratus(Isoptera: Rhinotermitidae)

Facultative parthenogenesis, or condition-dependent alternation of sexual and asexual reproduction, is widespread in animals. Parthenogenesis enables unmated females to reproduce and thus has a great adaptive significance, especially under low pairing efficiency. In the termite Reticulitermes speratus Kolbe, females that fail to pair with males found colonies cooperatively with partner females and reproduce parthenogenetically. We compared the quality of parthenogenetic and sexual eggs in terms of size, hatching rate, and hatching period. We developed a method to culture isolated eggs until hatching under sterile conditions and in appropriate humidity. We successfully isolated, sterilized, and maintained the eggs on agar plates containing 200 ppm tetracycline. Females of female-female (FF) pairs began to lay eggs at the same time as those of female-male (FM) pairs. Nevertheless, the parthenogenetic eggs were significantly larger than sexual eggs. While the two types of eggs had similar hatching rates, parthenogenetic eggs had longer hatching periods (36.36±0.16 [SE] days) than sexual eggs (34.95±0.12 SE). We conclude that primary queens invest more resources into each parthenogenetic egg than each sexual egg, and that parthenogenetic eggs are as viable as sexual eggs.
A trade off between mlo resistance to powdery mildew and increased susceptibility of barley to a newly important disease, Ramularia leaf spot

Ramularia leaf spot (RLS), caused by the fungus Ramularia collo-cygni, is a serious, recently emerged disease of barley in Europe and other temperate regions. This study investigated the trade off between strong resistance to powdery mildew conferred by mlo mutant alleles and increased susceptibility to RLS. In field trials and seedling tests, the presence of mlo alleles increased severity of RLS. Genetic analysis of a doubled-haploid population identified one quantitative trait locus for susceptibility to RLS, colocalizing with the mlo-11 allele for mildew resistance. The effect of mlo-11 on RLS severity was environmentally sensitive. Analysis of near-isogenic lines of different mlo mutations in various genetic backgrounds confirmed that mlo alleles increased RLS severity in seedlings and adult plants. For mlo resistance to mildew to be fully effective, the genes ROR1 and ROR2 are required. RLS symptoms were significantly reduced on mlo-5 ror double mutants but fungal DNA levels remained as high as in mlo-5 single mutants, implying that ror alleles modify the transition of the fungus from endophytism to necrotrophy. These results indicate that the widespread use of mlo resistance to control mildew may have inadvertently stimulated the emergence of RLS as a major disease of barley.
Autonomic Power & Performance Management for Large-Scale Data Centers

With the rapid growth of servers and applications spurred by the Internet, the power consumption of servers has become critically important and must be efficiently managed. High energy consumption also translates into excessive heat dissipation which in turn, increases cooling costs and causes servers to become more prone to failure. This paper presents a theoretical and experimental framework and general methodology for hierarchical autonomic power & performance management in high performance distributed data centers. We optimize for power & performance (performance/watt) at each level of the hierarchy while maintaining scalability. We adopt mathematically-rigorous optimization approach to provide the application with the required amount of memory at runtime. This enables us to transition the unused memory capacity to a low power state. Our experimental results show a maximum performance/watt improvement of 88.48% compared to traditional techniques. We also present preliminary results of using game theory to optimize performance/watt at the cluster level of a data center. Our cooperative technique reduces the power consumption by 65% when compared to traditional techniques (min-min heuristic).
Lessons in Language Design: Cost/Benefit Analysis of VHDL Features

This paper looks at the design of one successful hardware description language, VHSIC Hardware Description Language (VHDL) with a critical evaluation of particular language features. In the paper we identify features of VHDL that burden the language in terms of development time (i.e. price), performance of the implementation, and user-friendliness. We suggest a useful and instinctive tool to assess the redundancy of language features. We also give an explanation as to why such superfluous features are included in VHDL. While it is quite obvious that the restandardization process is not designed to remove features from VHDL, it is interesting, at the end of a major language redesign process, to draw lessons that can benefit language designers, implementors, and users.
A study on human like characteristics in real time strategy games

Computer controlled characters (NPCs) are important in any video game to make the game world interesting, give more depth to a game and make the game playable. In almost any game the player has to cooperate with, fight against or interact with NPCs. This is especially true for single-player games but NPCs are also important in most multi-player games. When creating NPCs the developers often strive to create human like characters that behave reasonably intelligent in most cases. We have performed a study aiming to give an idea of the characteristics of human like NPCs in real-time strategy (RTS) games. In the study participants were asked to watch a recording of an RTS game and decide and motivate if the players in the game were controlled by a human player or a computer. We recorded matches were human players played against bots as well as bots playing against other bots. The results were categorized into different groups and they showed that some characteristics, for example simultaneous movement, are perceived as very bot-like and other things such as ability to try different tactics are perceived as humanlike.
Drosophila p120-catenin is crucial for endocytosis of the dynamic E-cadherin–Bazooka complex

ABSTRACT The intracellular functions of classical cadherins are mediated through the direct binding of two catenins: β-catenin and p120-catenin (also known as CTNND1 in vertebrates, and p120ctn in Drosophila). Whereas β-catenin is crucial for cadherin function, the role of p120-catenin is less clear and appears to vary between organisms. We show here that p120-catenin has a conserved role in regulating the endocytosis of cadherins, but that its ancestral role might have been to promote endocytosis, followed by the acquisition of a new inhibitory role in vertebrates. In Drosophila, p120-catenin facilitates endocytosis of the dynamic E-cadherin–Bazooka subcomplex, which is followed by its recycling. The absence of p120-catenin stabilises this subcomplex at the membrane, reducing the ability of cells to exchange neighbours in embryos and expanding cell–cell contacts in imaginal discs. Summary: In Drosophila, p120-catenin facilitates endocytosis of the dynamic E-cadherin, which is followed by its recycling. Consequently, p120-catenin regulates cell shape and promotes the ability of cells to exchange neighbours.
- 1-Vascular endothelial growth factor regulates myeloid cell leukemia-1 expression through neuropilin-1-dependent activation of c-MET signaling in human prostate cancer cells

Shumin Zhang (szhang5@emory.edu) Haiyen E Zhau (haiyen.zhau@cshs.org) Adeboye O Osunkoya (adeboye.osunkoya@emory.edu) Shareen Iqbal (aiqbal@learnlink.emory.edu) Xiaojian Yang (xyang29@gmail.com) Songqing Fan (fansongqing2000@yahoo.com.cn) Zhengjia Chen (zchen38@emory.edu) Ruoxiang Wang (rwang2@emory.edu) Fray F Marshall (fmarsha@emory.edu) Leland WK Chung (leland.chung@cshs.org) Daqing Wu (dwu2@emory.edu)
Novel Speech Signal Processing Algorithms for High-Accuracy Classification of Parkinson's Disease

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support vector machines. We use an existing database consisting of 263 samples from 43 subjects, and demonstrate that these new dysphonia measures can outperform state-of-the-art results, reaching almost 99% overall classification accuracy using only ten dysphonia features. We find that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects. We see these results as an important step toward noninvasive diagnostic decision support in PD.
Airborne measurement of OH reactivity during INTEX-B

The measurement of OH reactivity, the inverse of the OH lifetime, provides a powerful tool to investigate atmospheric photochemistry. A new airborne OH reactivity instrument was designed and deployed for the first time on the NASA DC-8 aircraft during the second phase of Inter- continental Chemical Transport Experiment-B (INTEX-B) campaign, which was focused on the Asian pollution out- flow over Pacific Ocean and was based in Hawaii and Alaska. The OH reactivity was measured by adding OH, generated by photolyzing water vapor with 185 nm UV light in a moveable wand, to the flow of ambient air in a flow tube and mea- suring the OH signal with laser induced fluorescence. As the wand was pulled back away from the OH detector, the OH signal decay was recorded; the slope of 1ln(signal)/1 time was the OH reactivity. The overall absolute uncer- tainty at the 2 confidence levels is about 1 s 1 at low al- titudes (for decay about 6 s 1 ), and 0.7 s 1 at high altitudes (for decay about 2 s 1 ). From the median vertical profile obtained in the second phase of INTEX-B, the measured OH reactivity (4.0±1.0 s 1 ) is higher than the OH reactiv-
Richardson's Method of Segment Counting versus Box-Counting

Fractal analysis has become a popular method in all branches of scientific investigation including biology and medicine. This paper presents solution for many unresolved questions about the methodology of fractal theory, precisely in connection between fractal geometry and fractal analysis. While some concepts in fractal theory are determined descriptively and/or qualitatively, this paper provides their exact mathematical definition or explanation. Also, we present results in applying two basic length-related methods on two dimensional neuronal images and discuss their applicability.
Behavioral and Psychosocial Assessment Tools

Achenbach Child Behavior Checklist 106 Social Skills Rating System 106 Psychosocial Assessments 107 Children’s Depression Inventory 107 Reynolds Adolescent Depression Scale 2 107 Self-Esteem 107 Piers–Harris Children’s Self Concept Scale, Second Edition 107 Self-Perception Profile for Children 107 Anxiety 108 State-Trait Anxiety Inventory for Children 108 Measures of Eating Disorders 108 The Kids’ Eating Disorder Survey 108 The Eating Disorder Inventory 108 The Eating Attitudes Test 108 The Diagnostic Survey for Eating Disorders 109 Family Measures 109 Family Adaptability and Cohesion Evaluation Scales 109 Family Environment Scale 109 Conclusion 110 References 110
MadLINQ: large-scale distributed matrix computation for the cloud

The computation core of many data-intensive applications can be best expressed as matrix computations. The MadLINQ project addresses the following two important research problems: the need for a highly scalable, efficient and fault-tolerant matrix computation system that is also easy to program, and the seamless integration of such specialized execution engines in a general purpose data-parallel computing system. MadLINQ exposes a unified programming model to both matrix algorithm and application developers. Matrix algorithms are expressed as sequential programs operating on tiles (i.e., sub-matrices). For application developers, MadLINQ provides a distributed matrix computation library for . NET languages. Via the LINQ technology, MadLINQ also seamlessly integrates with DryadLINQ, a data-parallel computing system focusing on relational algebra. The system automatically handles the parallelization and distributed execution of programs on a large cluster. It outperforms current state-of-the-art systems by employing two key techniques, both of which are enabled by the matrix abstraction: exploiting extra parallelism using fine-grained pipelining and efficient on-demand failure recovery using a distributed fault-tolerant execution engine. We describe the design and implementation of MadLINQ and evaluate system performance using several real-world applications.
Fuzzy C-means and spatial correlation based clustering for cooperative spectrum sensing

A cluster formation algorithm is proposed to save the wastage of energy in cooperative spectrum sensing (CSS), in which small number of groups called clusters are made using fuzzy c-means (FCM). Based on spatial correlation, only limited number of SUs are selected from each cluster, whose sensing information is forwarded to their cluster head (CHs). The primary goal of cognitive radio network is spectrum sensing, that determines whether a particular spectrum hole is free or not, so that secondary users (SUs) can utilize that spectrum, if it is not occupied. Many factors such as shadowing and multipath fading problem may degrade the detection performance of spectrum sensing. To overcome these problems CSS schemes were proposed, in which different number of SUs collaborate with each other and share their sensing information with fusion center (FC) to make the final decision of PU's activity. This may increase the overhead for the FC when a huge number of SUs are involved in sensing. The proposed algorithm consumes small energy and achieves the highest efficiency as compare to non-clustering and conventional clustering techniques.
Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker

In MRI, the main magnetic field polarizes the electron cloud of a molecule, generating a chemical shift for observer protons within the molecule and a magnetic susceptibility inhomogeneity field for observer protons outside the molecule. The number of water protons surrounding a molecule for detecting its magnetic susceptibility is vastly greater than the number of protons within the molecule for detecting its chemical shift. However, the study of tissue magnetic susceptibility has been hindered by poor molecular specificities of hitherto used methods based on MRI signal phase and T2* contrast, which depend convolutedly on surrounding susceptibility sources. Deconvolution of the MRI signal phase can determine tissue susceptibility but is challenged by the lack of MRI signal in the background and by the zeroes in the dipole kernel. Recently, physically meaningful regularizations, including the Bayesian approach, have been developed to enable accurate quantitative susceptibility mapping (QSM) for studying iron distribution, metabolic oxygen consumption, blood degradation, calcification, demyelination, and other pathophysiological susceptibility changes, as well as contrast agent biodistribution in MRI. This paper attempts to summarize the basic physical concepts and essential algorithmic steps in QSM, to describe clinical and technical issues under active development, and to provide references, codes, and testing data for readers interested in QSM. Magn Reson Med 73:82–101, 2015. © 2014 The Authors. Magnetic Resonance in Medicine Published by Wiley Periodicals, Inc. on behalf of International Society of Medicine in Resonance. This is an open access article under the terms of the Creative commons Attribution License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited.
Effects of first language processes and representations on second language perception: The case of vowel epenthesis by Japanese speakers

Aims and objectives/purpose/research questions: Japanese speakers are known to perceive “illusory vowels” within consonant clusters illicit in their language. The present study examines how this perceptual vowel epenthesis is affected by first language (L1) processes (restoration of vowels devoiced through Japanese high vowel devoicing), L1 representations (loanword representations in Japanese speakers’ lexicons), and proficiency in English. Design/methodology/approach: The participants judged the presence or absence of a mora (e.g., ム /mu/) in an auditorily presented English word (e.g., homesick). The 40 test items contained a heterosyllabic consonant cluster with four different voicing patterns to examine whether the vowel restoration process is related to vowel epenthesis. Twenty of the test items are frequently used as loanwords in Japanese, meaning that they are stored in the L1 lexicon with a vowel inserted inside the consonant cluster (e.g., /hoomusikku/). The other 20 are low-frequency items that are virtually nonwords for the non-native participants. Data and analysis: The vowel epenthesis rates and reaction times (RTs) were obtained from 14 introductory learners, 15 intermediate learners, and 19 native speakers. Findings/conclusions: The results show the main effects of Voice, Loanword Representation, and Proficiency, as well as the interaction among the three factors. Negative correlations between vowel epenthesis rates and RTs were also observed for the learners. The results indicate differential effects of vowel restoration and loanwords on perceptual epenthesis by learners of different proficiency levels. Originality: The present study was one of the first attempts to test the relation between proficiency and perceptual vowel epenthesis using real English words. Significance/implications: The findings demonstrate the robustness of L1 processes and representations in second language perception while substantiating the existing argument for early vowel epenthesis. They also raise questions regarding the effects of training and the role of native speaker input.
Genomic Tools and Their Implications for Vegetable Breeding

Next generation sequencing (NGS) technologies have led to the rapid accumulation of genome sequences through whole-genome sequencing and re-sequencing of crop species. Genomic resources provide the opportunity for a new revolution in plant breeding by facilitating the dissection of complex traits. Among vegetable crops, reference genomes have been sequenced and assembled for several species in the Solanaceae and Cucurbitaceae families, including tomato, pepper, cucumber, watermelon, and melon. These reference genomes have been leveraged for re-sequencing of diverse germplasm collections to explore genome-wide sequence variations, especially single nucleotide polymorphisms (SNPs). The use of genomewide SNPs and high-throughput genotyping methods has led to the development of new strategies for dissecting complex quantitative traits, such as genome-wide association study (GWAS). In addition, the use of multi-parent populations, including nested association mapping (NAM) and multiparent advanced generation intercross (MAGIC) populations, has helped increase the accuracy of quantitative trait loci (QTL) detection. Consequently, a number of QTL have been discovered for agronomically important traits, such as disease resistance and fruit traits, with high mapping resolution. The molecular markers for these QTL represent a useful resource for enhancing selection efficiency via marker-assisted selection (MAS) in vegetable breeding programs. In this review, we discuss current genomic resources and markertrait association analysis to facilitate genome-assisted breeding in vegetable species in the Solanaceae and Cucurbitaceae families.
Defining the Role of prolamin-box binding factor1 Gene During Maize Domestication.

The prolamin-box binding factor1 (pbf1) gene encodes a transcription factor that controls the expression of seed storage protein (zein) genes in maize. Prior studies show that pbf1 underwent selection during maize domestication although how it affected trait change during domestication is unknown. To assay how pbf1 affects phenotypic differences between maize and teosinte, we compared nearly isogenic lines (NILs) that differ for a maize versus teosinte allele of pbf1 Kernel weight for the teosinte NIL (162mg) is slightly but significantly greater than that for the maize NIL (156mg). RNAseq data for developing kernels show that the teosinte allele of pbf1 is expressed at about twice the level of the maize allele. However, RNA and protein assays showed no difference in zein profile between the two NILs. The lower expression for the maize pbf1 allele suggests that selection may have favored this change; however, how reduced pbf1 expression alters phenotype remains unknown. One possibility is that pbf1 regulates genes other than zeins and thereby is a domestication trait. The observed drop in seed weight associated with the maize allele of pbf1 is counterintuitive but could represent a negative pleiotropic effect of selection on some other aspect of kernel composition.
Encapsulation of Antioxidants by Spray-drying

This study provides an encapsulation process of at le st one antioxidant in a carbohydrate matrix, by homogenization and spray-dr ying. The method involves homogenization of the antioxidant with the carbohyd rate matrix in water, at controlled speed and temperature, followed by spray-drying und er well established conditions. The process parameters used in the spray-drying are all selected and/or manipulated to produce an encapsulated antioxidant product of very fine particle size of 0.08±0.02 microns analysed by Scanning Electron Microscopy (S EM) and Laser Scattering. Such encapsulated antioxidant products are very stable, protected from oxidation and are useful for being incorporated into beverages, such as near-waters, supplements products, pharmaceutical and cosmetic products.
Transfer Learning with Graph Co-Regularization

Transfer learning is established as an effective technology to leverage rich labeled data from some source domain to build an accurate classifier for the target domain. The basic assumption is that the input domains may share certain knowledge structure, which can be encoded into common latent factors and extracted by preserving important property of original data, e.g., statistical property and geometric structure. In this paper, we show that different properties of input data can be complementary to each other and exploring them simultaneously can make the learning model robust to the domain difference. We propose a general framework, referred to as Graph Co-Regularized Transfer Learning (GTL), where various matrix factorization models can be incorporated. Specifically, GTL aims to extract common latent factors for knowledge transfer by preserving the statistical property across domains, and simultaneously, refine the latent factors to alleviate negative transfer by preserving the geometric structure in each domain. Based on the framework, we propose two novel methods using NMF and NMTF, respectively. Extensive experiments verify that GTL can significantly outperform state-of-the-art learning methods on several public text and image datasets.