Miracle-dz/UniFAR-FTUs huggingface dataset:
Decreasing, not increasing, leaf area will raise crop yields under global atmospheric change

Without new innovations, present rates of increase in yields of food crops globally are inadequate to meet the projected rising food demand for 2050 and beyond. A prevailing response of crops to rising [CO2] is an increase in leaf area. This is especially marked in soybean, the world's fourth largest food crop in terms of seed production, and the most important vegetable protein source. Is this increase in leaf area beneficial, with respect to increasing yield, or is it detrimental? It is shown from theory and experiment using open‐air whole‐season elevation of atmospheric [CO2] that it is detrimental not only under future conditions of elevated [CO2] but also under today's [CO2]. A mechanistic biophysical and biochemical model of canopy carbon exchange and microclimate (MLCan) was parameterized for a modern US Midwest soybean cultivar. Model simulations showed that soybean crops grown under current and elevated (550 [ppm]) [CO2] overinvest in leaves, and this is predicted to decrease productivity and seed yield 8% and 10%, respectively. This prediction was tested in replicated field trials in which a proportion of emerging leaves was removed prior to expansion, so lowering investment in leaves. The experiment was conducted under open‐air conditions for current and future elevated [CO2] within the Soybean Free Air Concentration Enrichment facility (SoyFACE) in central Illinois. This treatment resulted in a statistically significant 8% yield increase. This is the first direct proof that a modern crop cultivar produces more leaf than is optimal for yield under today's and future [CO2] and that reducing leaf area would give higher yields. Breeding or bioengineering for lower leaf area could, therefore, contribute very significantly to meeting future demand for staple food crops given that an 8% yield increase across the USA alone would amount to 6.5 million metric tons annually.
on Circuit , Power and Computing Technologies [ ICCPCT ] Literature survey on Face and Face Expression Recognition

Face Expression Recognition (FER) has become a very interesting and challenging area in computer vision field due to its wide application possibilities. Mental state Recognition, Human Computer Interaction, Human behavior understanding etc. are some of its applications. Because of its wide application possibilities Face expression recognition has attained a very crucial role in the area of facial image processing. In this paper some of the tailor made face expression Recognition algorithms are presented. This paper also gives a brief insight into the feature extraction method of these face expression recognition techniques. The features extraction technique plays a crucial role in the efficiency of these algorithms. In this paper a few Face Expression Recognition techniques like Patched Geodesic Texture Transform, Curvelet Feature Extraction, Bag of Words Method, Local Directional Number Pattern, Regional Registration Technique, Gradient Feature Matching etc. which are used to recognize the facial expression are presented. Keywords— Face Expression Recognition, Feature Extraction, Patched Geodesic Texture Transform, Curvelet Feature Extraction, Bag of Words Method, Local Directional Number Pattern, Regional Registration Technique, Gradient Feature Matching
Splitting Complex English Sentences

This paper applies parsing technology to the task of syntactic simplification of English sentences, focusing on the identification of text spans that can be removed from a complex sentence. We report the most comprehensive evaluation to-date on this task, using a dataset of sentences that exhibit simplification based on coordination, subordination, punctuation/parataxis, adjectival clauses, participial phrases, and appositive phrases. We train a decision tree with features derived from text span length, POS tags and dependency relations, and show that it significantly outperforms a parser-only baseline.
Progress on Preparation, Microstructure and Property of Graphene Reinforced Aluminum Matrix Composite

Graphene with unique two-dimensional structure and excellent mechanical properties, is one of the most ideal reinforcements. With the increasing progress of aluminum matrix composites, graphene reinforced aluminum matrix composites have attracted great interests. This paper mainly reviews the latest progress on preparation of graphene reinforced aluminum matrix composites, and especially discusses the effective dispersion technique of graphene. Meanwhile, the microstructure and interfacial structure of graphene reinforced aluminum matrix composites are also emphasized and discussed. The results showed that graphene can significantly improve the mechanical properties of composites and refine the matrix grain. By controlling preparation parameters, the graphene agglomeration can be effectively solved, and the adverse interface reaction between graphene and substrate can be avoided. Finally, the current challenges and solutions of graphene reinforced aluminum matrix composites were presented.
Reference traces by simulation for Tracking Control-logic

The controls for reconfigurable manufacturing systems RMS have to be capable not only of identifying exceptions on-line, but also simultaneously developing on-line strategies for unpredictable customer orders or inaccurate estimate of processing times. Trace-driven simulators are an efficient alternative but maintaining large traces can present storage and portability problems. This paper proposes a distribution-driven trace generation methodology as an alternative to traditional trace-driven simulation. An adaptation of the Least Recently Used Stack Model is used to concisely capture the key locality features in a trace and a two-position Markov chain model is used for trace generation. Simulation and analysis of a variety of RMS application traces demonstrate the characteristics of the synthetic traces should be generally very well preserved and similar to their real trace, and we also highlight the potential performance improvement over Tracking Control-Logic.
Study on the Surface Damage Layer in Multiple Grinding of Quartz Glass by Molecular Dynamics Simulation

The paper focuses on the surface damage of quartz glass in multiple grinding, so as to find out the machining parameters that can improve the surface quality of quartz glass. Molecular dynamics (MD) method is adopted to machine the quartz glass. Firstly, the initial grinding is done on quartz glass with the depth of 12 Å. Based on the initial grinding, no feed grinding processes are done for three times separately and the feed grinding processes are carried out on the damage layer left by the previous process. By the coordination number (CN), machined surface topographies of quartz glass are gained and regions of densification are marked. Moreover, the damage layer thickness of different machined surface is also calculated. By analyzing the density of different surface damage layers, the regulation of the density distribution is obtained. Finally, the nanoindentation hardness is gained by different load-displacement curves in nanoindentation simulation. The results show that the first no feed grinding and the second feed grinding can improve the accuracy and quality of grinding. Too many no feed grinding processes and other feed grinding processes will induce serious damage of the machined surface, which is clearly showed in the obvious increase in the density, hardness and thickness of the damage layer. At last, the results of the density analysis and nanoindentation also proved that the densification and hardness of quartz glass cannot increase unlimited. The results can be applied in the ultra-precision grinding of quartz glass to control the thickness of damage layer and improve the quality of processing.
The orf13 T-DNA Gene of Agrobacterium rhizogenes Confers Meristematic Competence to Differentiated Cells1

Plant infections by the soil bacterium Agrobacterium rhizogenes result in neoplastic disease with the formation of hairy roots at the site of infection. Expression of a set of oncogenes residing on the stably integrated T-DNA is responsible for the disease symptoms. Besides the rol (root locus) genes, which are essential for the formation of hairy roots, the open reading frame orf13 mediates cytokinin-like effects, suggesting an interaction with hormone signaling pathways. Here we show that ORF13 induced ectopic expression of KNOX (KNOTTED1-like homeobox) class transcription factors, as well as of several genes involved in cell cycle control in tomato (Lycopersicon esculentum). ORF13 has a retinoblastoma (RB)-binding motif and interacted with maize (Zea mays) RB in vitro, whereas ORF13, bearing a point mutation in the RB-binding motif (ORF13*), did not. Increased cell divisions in the vegetative shoot apical meristem and accelerated formation of leaf primordia were observed in plants expressing orf13, whereas the expression of orf13* had no influence on cell division rates in the shoot apical meristem, suggesting a role of RB in the regulation of the cell cycle in meristematic tissues. On the other hand, ectopic expression of LeT6 was not dependent on a functional RB-binding motif. Hormone homeostasis was only altered in explants of leaves, whereas in the root no effects were observed. We suggest that ORF13 confers meristematic competence to cells infected by A. rhizogenes by inducing the expression of KNOX genes and promotes the transition of infected cells from the G1 to the S phase by binding to RB.
FACIAL EXPRESSIONS OF EMOTION INTERPERSONAL TRAIT INFERENCES

Theorists have argued that facial expressions of emotion serve the inter- personal function of allowing one animal to predict another's behavior. Humans may extend these predictions into the indefinite future, as in the case of trait infer- ence. The hypothesis that facial expressions of emotion (e.g., anger, disgust, fear, happiness, and sadness) affect subjects' interpersonal trait inferences (e.g., domi- nance and affiliation) was tested in two experiments. Subjects rated the disposi- tional affiliation and dominance of target faces with either static or apparently mov- ing expressions. They inferred high dominance and affiliation from happy expressions, high dominance and low affiliation from angry and disgusted expres- sions, and low dominance from fearful and sad expressions. The findings suggest that facial expressions of emotion convey not only a targets internal state, but also differentially convey interpersonal information, which could potentially seed trait inference.
Identifying Promoter Elements Necessary for Enamelin Tissue-Specific Expression

Enamel development requires the strictly regulated spatiotemporal expression of genes encoding enamel matrix proteins. The mechanisms orchestrating the initiation and termination of gene transcription at each specific stage of amelogenesis are unknown. In this study, we identify cis- regulatory regions necessary for normal enamelin (Enam) expression. Sequence analysis of the Enam promoter 5′-noncoding region identified potentially important cis-regulatory elements located within 5.2 kb upstream of the Enam translation initiation site. DNA constructs containing 5.2 or 3.9 kb upstream of the Enam translation initiation site were linked to an LacZ reporter gene and used to generate transgenic mice. The 3.9-kb Enam-LacZ transgenic lines showed no expression in ameloblasts, but ectopic LacZ staining was detected in osteoblasts. In contrast, the 5.2-kb Enam-LacZ construct was sufficient to mimic the endogenous Enam ameloblast-specific expression pattern. Our study provides new insights into the molecular control of Enam cell- and stage-specific expression.
A numerical implementation of gridless compressed sensing

Atomic norm denoising has been recently introduced as a generalization of the Least Absolute Shrinkage and Selection Operator (LASSO) to overcome the problem of off-grid parameters. The method has been found to possess many interesting theoretical properties. However, its implementation has been only discussed in a special case of spectral line estimation by uniform sampling. In this paper, we propose a general numerical method to solve the atomic norm denoising problem. The complexity of the proposed algorithm is proportional to the complexity of a single-parameter search in the parameter space and thus in many interesting cases, including frequency estimation it enjoys fast realization.
Conjugated polymer–silicon nanowire array hybrid Schottky diode for solar cell application

The hybrid Schottky diode based on silicon nanowire arrays (SiNWs) and poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) (PEDOT:PSS) has been fabricated for high performance solar cells. The length of SiNWs on a silicon substrate, which is prepared by metal-assisted chemical etching, can be tuned by adjusting the length of the etching time. In addition, the average distances between the adjacent silicon nanowires can be controlled by changing the immersing time in a saturated PCl5 solution. The hybrid devices are made from the SiNWs with different wire lengths and various distances between adjacent wires by spin-casting PEDOT:PSS on the silicon substrates. It is found that the length and density play leading roles in the electric output characteristics. The device made from SiNWs with optimum morphology can achieve a power conversion efficiency of 7.3%, which is much improved in comparison with that of the planar one. The measurement of the transient photovoltage decay and the analysis of the current versus voltage curve indicate that the charge recombination process is a dominant factor on the device performance.
Cryptosporidiosis among patients infected with human immunodeficiency virus. Factors related to symptomatic infection and survival.

The authors reviewed the medical records of 194 human immunodeficiency virus (HIV)-positive patients newly diagnosed with cryptosporidiosis and all 3,564 patients with newly diagnosed acquired immunodeficiency syndrome (AIDS) at San Francisco General Hospital for the period 1986-1992. The study was designed to address three questions: 1) How do AIDS patients who present with cryptosporidiosis differ from other patients with AIDS? 2) What factors are associated with survival among AIDS patients with newly diagnosed cryptosporidiosis? 3) Does a diagnosis of cryptosporidiosis impact survival after AIDS diagnosis? A total of 194 cases of cryptosporidiosis among HIV-infected patients were identified during the study period. Of the 194 patients, 109 (56%) had no prior diagnosis of AIDS. These 109 patients represented 3.1% of the 3,564 newly diagnosed cases of AIDS in the same period. Among the 134 patients with CD4 T-lymphocyte counts performed within 3 months of Cryptosporidium diagnosis, 34 (25%) had CD4 counts greater than 209 cells/ml. In a multivariate conditional logistic regression model, the incidence of Cryptosporidium was related to ethnicity (for blacks vs. whites, matched odds ratio (OR) = 0.15, 95% confidence interval (CI) 0.03-0.73), CD4 count (for a CD4 count of < or = 53 cells/ml vs. > 53 cells/ml, matched OR = 12.60, 95% CI 4.01-39.61), and age (for a 10-year increase, matched OR = 0.51, 95% CI 0.27-0.98). Two factors measured at the time of Cryptosporidium diagnosis were identified as being independently associated with survival (p < 0.001) in the proportional hazards model: CD4 count < or = 53 cells/ml versus > 53 cells/ml (relative hazard = 6.18, 95% CI 2.99-12.76) and hematocrit < or 37% versus > 37% (relative hazard = 2.27, 95% CI 1.22-4.22). The median durations of survival in the four subgroups of Cryptosporidium-infected patients defined by these two variables differed significantly from each other (range, 204-1,119 days). Cryptosporidiosis as an initial AIDS-defining diagnosis was associated with an elevated relative hazard of death in comparison with other AIDS-defining diagnoses (relative hazard = 2.01, 95% CI 1.38-2.93). These data identify the groups of HIV-infected individuals at risk for presentation with symptomatic Cryptosporidium infection; the distinct survival patterns among subgroups of those patients already infected with this parasite; and the survival of AIDS patients with newly diagnosed cryptosporidiosis relative to patients with other AIDS-defining conditions. Such information is necessary for the design of prospective studies, the development of prophylactic strategies, the evaluation of candidate therapies, and the provision of prognostic information to patients.
FACTORS THAT CREATE A POSITIVE TASTING ROOM EXPERIENCE FOR THE CURRENT MILLENNIAL GENERATION

This study was performed to determine what factors create a positive tasting room experience for the current Millennial generation. Other aims of this study was to determine Millennials’ purchase behavior in the future after they have had a positive tasting room experience, how older generations compare to Millennials, and if tasting room managers understand what factors Millennials consider important. Web-based surveys were distributed and collected from 300 respondents, 277 useable, throughout April and May of 2012 in undisclosed locations. The entire sample was comprised of 192 women and 85 men. Of those 277 respondents, 120 were Millennials, 53 were Generation Xers, and 104 were Baby Boomers. Statistical analysis was run to analyze the results from the respondents through SPSS. Statistical tests applied to the data included frequencies, descriptives, cross-tabulations, chi-square, comparing means, one-sample t-tests, one-way ANOVA and f-tests. The analysis suggested that Millennials rated knowledgeable staff, the varieties of wine available to taste and the appearance of the tasting room as most important. This was also the same for the respondents as a whole. As time went on, Millennials as well as older generations were less willing to purchase wine despite the positive tasting room experience they had. Tasting room managers also held a similar opinion about what factors Millennials perceive as important in creating a positive tasting room experience. Tasting room managers rated knowledgeable staff, appearance of the tasting room and a large amount of time interacting with the pourer as most important.
Small-molecule inhibitors of microrna miR-21 function.

MicroRNAs (miRNAs) have recently emerged as an important class of gene regulators, and their misregulation has been linked to a variety of cancers. Small molecule inhibitors of miRNAs would be important tools to elucidate the detailed mechanisms of miRNA function and provide lead structures for the development of new therapeutics. We are reporting a cellular screen for miRNA pathway inhibitors and the first small molecule modifiers of miRNA function.
Guidelines for supporting real‐time multi‐touch applications

Multi‐touch driven user interfaces are becoming increasingly prevalent because of their intuitiveness and because of the reduction in the associated hardware costs. In recognition of this trend, multi‐touch software frameworks (MSFs) have begun to emerge. These frameworks abstract the low level issues of multi‐touch software development and deployment. MSFs therefore enable software developers who are unfamiliar with the complexities of multi‐touch software development to implement and deploy multi‐touch applications more easily. However, some multi‐touch applications have real‐time system requirements, and at present, no MSFs provide support for the development and deployment of such real‐time multi‐touch applications. The implication of this is that software developers are unable to take advantage of MSFs and, therefore, are forced to handle the complexities of multi‐touch and real‐time systems development and deployment for themselves in an ad hoc manner. The primary consequence of this is that the multi‐touch and/or real‐time aspects of the application may not function correctly. In this paper, guidelines are presented for applying real‐time system concepts to support the development and deployment of real‐time multi‐touch applications using MSFs. This serves to increase the probability that the application will meet its timing requirements while also reducing the complexity of the development and deployment process associated with multi‐touch applications. Copyright © 2013 John Wiley & Sons, Ltd.
PAVM: a framework for policy‐aware virtual machine management

The problem of efficient placement of virtual machines (VMs) in cloud computing infrastructure is well studied in the literature. VM placement decision involves selecting a physical machine in the data center to host a specific VM. This decision could play a pivotal role in yielding high efficiency for both the cloud and its users. Also, reallocation of VMs could be performed through migrations to achieve goals like higher server consolidation or power saving. VM placement and reallocation decisions may consider affinities such as memory sharing, CPU processing, disk sharing, and network bandwidth requirements between VMs defined in multiple dimensions. Considering the NP‐hard complexity associated with computing an optimal solution for this VM placement decision problem, existing research employs heuristic‐based techniques to compute an efficient solution. However, most of these approaches are restricted to only a single attribute at a time. That is, a given technique of using heuristics to compute VM placement considers only a single attribute, while completely ignoring the impact of other dimensions of placing VMs. While this approach may improve the efficiency with respect to the affinity attribute in consideration, it may yield degraded performance with respect to other affinities. In addition, the criteria for determining VM‐placement efficiency may vary for different applications. Hence, the overall goal of achieving VM placement efficiency becomes difficult and challenging. We are motivated by this challenging problem of efficient VM placement and propose policy‐aware virtual machine management (PAVM), a generic framework that can be used for efficient VM management in a cloud computing platform based on the service provider‐defined policies to achieve the desired system‐wide goals. This involves efficient means to profile different VM affinities and to use profiled information effectively by intelligent and efficient VM migrations at run time considering multiple attributes at a time. By conducting extensive evaluation through simulation and real experiments that involve VM affinities on the basis of network and memory, we confirmed that the PAVM architecture is capable of improving the efficiency of a cloud system. We elaborate the architecture of a PAVM system, describe its implementation, and present details of our experiments. Copyright © 2016 John Wiley & Sons, Ltd.
An Expectation Maximization Algorithm for Textual Unit Alignment

The paper presents an Expectation Maximization (EM) algorithm for automatic generation of parallel and quasi-parallel data from any degree of comparable corpora ranging from parallel to weakly comparable. Specifically, we address the problem of extracting related textual units (documents, paragraphs or sentences) relying on the hypothesis that, in a given corpus, certain pairs of translation equivalents are better indicators of a correct textual unit correspondence than other pairs of translation equivalents. We evaluate our method on mixed types of bilingual comparable corpora in six language pairs, obtaining state of the art accuracy figures.