Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach for Fast 3D Image Reconstruction on PC

We proposed a new kind of fast 3D image reconstruction method that processes Z-Line data first based on improvement on the traditional FDK algorithm and data parallel computing. This method could organize and partition the reconstruction data effectively, which enables accessing memory continuously and makes it easy to implement the SIMD technique on data parallel computing. At last we developed a fast 3D image reconstruction engine on the Intel Pentium 4 platform, using the SSE/SSE2 technique. The result shows that our algorithm is very effective and we can get a reconstruction speedup of over 20 times without any image precision loss compared with the traditional implementation.
Character superimposition inpainting in surveillance video

Video surveillance systems play an important role in the crime scene investigation, and the digital surveillance system always requires the superimposed video data being subjected to a data compression processing. The purpose of this paper is to study the use of inpainting techniques to remove the characters and inpaint the target region. We give the efficient framework including getting Character Superimposition mask, superimposition movement and inpainting the blanks. The character region is located with the manual ROI selection and varying text extractor, such as the time. The superimposed characters usually have distinguished colors from the original background, so the edges are easily detected. We use the canny operator the get the edge image. The missing information which is effect the structure of the original image is reconstructed using a structure propagating algorithm. The experiment was done with C/C++ in the vs2010 KDE. The framework of this paper showed is powerful to recreate the character superimposition region and helpful to the crime scene investigation.
A Synopsis and New Key to the Species of Rinodina (Ach.) Gray (Physciaceae, Lichenized Ascomycetes) Presently Recognized in North America

Abstract: Sheard J.W. 2018: A synopsis and new key to the species of Rinodina (Ach.) Gray (Physciaceae, lichenized Ascomycetes) presently recognized in North America. - Herzogia 31: 395–423. One new species, Rinodina incurva, fifteen new North American species records for the genus Rinodina (including nine recently described taxa), and range extensions for 61 species are listed. One species, R. aurantiaca, is reduced to synonymy with R. capensis. A total of 111 species are now recognized for North America of which 36 (32 %) are endemic. Disjunctions of seven species with northeastern Asia are discussed. A new key to all species is provided.
The Crystal Structure of Dihydrofolate Reductase-Thymidylate Synthase from Cryptosporidium hominis Reveals a Novel Architecture for the Bifunctional Enzyme

Cryptosporidium hominis is an emerging pathogen that primarily affects immune-compromised patients, including those with AIDS. There is no effective cure at this point for the degenerative wasting disease that can follow infection. Dihydrofolate reductase-thymidylate synthase (DHFR-TS) is a bifunctional enzyme in C. hominis and is crucial in the folate cycle for the production of dTMP, one of the four DNA bases. DHFR-TS is an excellent drug target since its inhibition leads to the death of the pathogen. In apicomplexan protozoa, including C. hominis, the gene for DHFR-TS can be partitioned into a DHFR domain, a linker domain and a TS domain. In human cells, DHFR and TS are separate, monofunctional enzymes. We have determined the X-ray crystal structure of DHFR-TS from C. hominis. The structure reveals that the linker polypeptide between the DHFR and TS domains has important structural interactions with the opposite monomer of the homodimeric enzyme. A comparison of the structure of DHFR-TS from C. hominis and structures of DHFR-TS from Plasmodium falciparum [11] and Leishmania major [5] shows that there are significant structural differences between the apicomplexan and kinetoplastid forms of the enzyme. Additionally, the DHFR and TS domains of the C. hominis enzyme have important sequence and structural differences from the human forms of the enzymes. The species-specific differences are important for future inhibitor design targeting C. hominis.
Instance Learning in Automatic Construction of Domain Ontology

The importance of Ontology is being recognized in various research and application areas.Constructing domain(Ontology) takes too much time and manpower.Hence,it is of great significance to do some research on constructing domain(Ontology) automatically.Instance is an important element of Ontology.Learning instance from domain corpus is a key issue in automatic construction of domain Ontology.A domain Ontology construction system OntoAGS has been developed.Given some domain corpus,OntoAGS can construct domain Ontology automatically.The instance learning method of this system is based on pattern matching algorithm.Experiments show that OntoAGS can generally learn more instances and more accurately than text-to-onto system which is a popular Ontology semi-automatic construction system.
DEVELOPMENT OF A PHOTOEMISSION DC GUN AT JAEA

The next generation light source such as X-ray FEL oscillator requires high brightness electron gun with megahertz repetition rate. We have developed a photoemission DC gun at JAEA. By employing a segmented insulator with guard rings, we successfully applied 500 kV on the ceramics with a central stem electrode for eight hours without any discharge in 2009. In 2011 we reached 526 kV with NEG pumps and electrodes in place, before suffering another field emission problem from the cathode electrode. The problem may be attributed to small dust inside our gun chamber. We also generated high current beam up to 10 mA and obtained charge extracted lifetime of 30 C. In this paper, our current status of development will be presented.
Brief paper Actor-critic algorithms for hierarchical Markov decision processes

We consider the problem of control of hierarchical Markov decision processes and develop a simulation based two-timescale actor-critic algorithm in a general framework. We also develop certain approximation algorithms that require less computation and satisfy a performance bound. One of the approximation algorithms is a three-timescale actor-critic algorithm while the other is a two-timescale algorithm, however, which operates in two separate stages. All our algorithms recursively update randomized policies using the simultaneous perturbation stochastic approximation (SPSA) methodology. We brieiy present the convergence analysis of our algorithms. We then present numerical experiments on a problem of production planning in semiconductor fabs on which we compare the performance of all algorithms together with policy iteration. Algorithms based on certain Hadamard matrix based deterministic perturbations are found to show the best results. 2006 Elsevier Ltd. All rights reserved.
The wage-setting power of firms: Rent-sharing and monopsony in South Africa

Using administrative tax records from South Africa for the period 2011â€“14, I find thatÂ firm wage premia explain 25 per cent of the total wage variance, 60 per cent of the gender wageÂ gap, and 40 per cent of the gap between workers in the middle and the bottom of the incomeÂ distribution. Next, I argue that in contrast to the rent-sharing literature, many studies ofÂ monopsony fail to use firm-level wage variation. I address this by using the estimated firm wageÂ premia to estimate how wages are related to rent-sharing and monopsony power.I find that theÂ average worker switching from a firm in the 25th percentile to the 75th percentile in profitabilityÂ is paid 32 per cent more; and that the same switch across the distribution of monopsony, asÂ measured by the Herfindahlâ€“Hirschman Index in industry-by-local labour market hires,Â decreases wages by 10 per cent on average. When monopsony is measured using a separationsÂ approach, I find a labour supply elasticity of 0.75, suggesting substantial wage-setting power. Â Finally, I provide additional evidence supporting the applicability of the monopsony model in explaining these results. Differences in labour supply elasticities across gender and incomeÂ groups account remarkably well for the corresponding average gaps in firm wage premia, andÂ unions substantially increase rent-sharing in firms.
Experimental Performance Evaluation of Cloud-Based Analytics-asa-Service

An increasing number of Analytics-as-a-Service (AaaS) solutions has recently seen the light, in the landscape of cloud-based services. These services allow flexible composition of compute and storage components, that create powerful data ingestion and processing pipelines. This work is a first attempt at an experimental evaluation of analytic application performance executed using a wide range of storage service configurations. We present an intuitive notion of data locality, that we use as a proxy to rank different service compositions in terms of expected performance. Through an empirical analysis, we dissect the performance achieved by analytic workloads and unveil problems due to the impedance mismatch that arise in some configurations. Our work paves the way to a better understanding of modern cloud-based analytic services and their performance, both for its end-users and their providers.
EFFECT OF NITROGEN LEVELS ON YIELD , NITROGEN UPTAKE AND EFFICIENCY OF POTATO VARIETIES UNDER TARAI REGION OF UTTARAKHAND

GIRISH CHANDRA*, MANOJ RAGHAV1, UDIT KUMAR2 AND PANKAJ KUMAR3 *Department of Life Science, SGRRITS, Patel Nagar, Dehradun 248 001, Uttarakhand, INDIA 1Department of Veg. Sci. GBPUA&T Pantnagar, U.S. Nagar, Uttarakhand, INDIA 2 Department of Hort. , RPCAU, Pusa, Samastipur 848 125, Bihar, INDIA 3GPB, UUHF, CoF, Ranichauri, Tehri Garhwal, Uttarakhand, Pin 249 199 e-mail:girishctiwari24@gmail.com
Detection of Listeria monocytogenes in wild and cultured Nile Tilapia fish (Oreochromis niloticus)

In the present study one hundred random samples of wild and cultured (50 each) of fresh Nile Tilapia fish (Oreochromis niloticus) which were purchased from fish sale markets in Assiut City. These samples were subjected to bacteriological examination for determination their contamination by Listeria spp. The obtained microbiological results showed that the overall incidence of Listeria spp. were 22 % and 16 % in the examined wild and cultured Nile Tilapia fish samples, respectively. The identified Listeria spp. were L. monocytogens (6 and 10 %). Concerning the other Listeria species, 11 isolates, nine isolates (19%) were L. ivanovii, one isolate (2%) were L. seeligeri and one (2%) isolate were L. welshimeri. In conclusion, the obtained results revealed that some wild and cultured Nile Tilapia fish was contaminated with L. monocytogenes; this pathogens could pose a serious risk to public health. It is thus necessary to perform continuous surveillance for L. monocytogenes in aquatic fish in Assiut.
Towards the Data-driven System for Rhetorical Parsing of Russian Texts

Results of the first experimental evaluation of machine learning models trained on Ru-RSTreebank – first Russian corpus annotated within RST framework – are presented. Various lexical, quantitative, morphological, and semantic features were used. In rhetorical relation classification, ensemble of CatBoost model with selected features and a linear SVM model provides the best score (macro F1 = 54.67 ± 0.38). We discover that most of the important features for rhetorical relation classification are related to discourse connectives derived from the connectives lexicon for Russian and from other sources.
Generational Mobile CPU Design Trends and Its Impact on Performance , Energy , and User Satisfaction *

Over the past decade, mobile CPUs have evolved from embedded processors to desktop-like single-chip multiprocessors. Yet, mobile CPUs, like any embedded processor, operate under a stricter set of power, thermal and energy constraints than their desktop counterparts. Therefore, the rapid design innovation, pervasiveness in society, and power-constrained nature of mobile hardware necessitate the need to understand the implications of their current design trends on future designs. Our work quantitatively analyzes mobile CPU design trends and how they have impacted the end-user, hardware design, and the holistic mobile device. To that end, we conduct a measurement-based study across ten cutting-edge mobile CPU designs released throughout the past seven years. These mobile CPU designs span seven different microarchitectures, five major process technology nodes, different cache configurations and memory technologies, and also multicore designs. To the best of our knowledge, our study is the first of its kind to rigorously evaluate mobile CPU design trends. In doing so, we make four key observations. Each observation is quantitatively reinforced – valuable in and of itself – regardless of whether it aligns with conventional wisdom or is surprising:
Global Optimality in Deep Neural Networks with Regularization

Global Optimality in Deep Neural Networks with Regularization Youngjin Koh Department of Mathematical Sciences The Graduate School Seoul National University In recent years, Deep Neural Networks(DNNs) have shown a dramatic success in many domains. However, the theoretical reasons for explaining the performance remain elusive. One of the most important key issue is the error optimization problem. In general, minimizing the loss function of the DNNs is a non-convex problem, hence the optimization algorithms may fail to find the global minimum. In this paper, we introduce several conditions for a local minimum to be globally optimal. In particular, we provide the conditions in DNNs with regularization and suggest the efficient network structure and regularization function. We also apply the theoretical results to the practical DNNs.
Genotyping Isolates of Beauveria spp . by rDNA-ITS Sequencing and RAPD Markers

INTRODUCTION Maize armyworm, Spodoptera frugiperda, is one of the main pests in maize fields in Brazil, whose severity has been increasing in various agricultural areas (Cruz et al., 1999). Control of S. frugiperda has been made mainly by chemical treatment as soon as the first symptoms appear. One of the alternatives to control of S. frugiperda infestations is based on microbial agents with low environmental impact, high specificity and efficiency in reducing its ability to cause injury to the host plant. In this way, the entomopathogenous fungi Beauveria are interesting biocontrol agents due to their epizootics and aggressiveness (Devi et al., 2001). Many Beauveria isolates have been studied due to their potential use as biopesticides (Devi et al., 2001). However, once phenotypic characteristics are not sufficient to distinguish different Beauveria strains or to monitor field releases of biocontrol agents, molecular analysis are demanded. The most used methods to characterize genotypic variation in fungi are based on PCR, DNA / RNA probes, and protein technologies. Among then, RAPD technology Gaitan et al., 2002) and rDNA-ITS sequencing studies (Wada et al., 2003; Muro et al., 2005) have already been employed successfully for assessing the degree of genetic variation existent among strains of Beauveria spp. As an effort to develop an integrated pest management control program for S. frugiperda, mycosed dead insects from different regions of central Brazil were collected and different fungi pathogens were isolated, among them 24 Beauveria spp. strains. These isolates were tested against S. frugiperda and analyzed by RAPD and rDNA-ITS sequencing in order to evaluate their genetic variability.
Disclosure quality and Competition for capital ∗

We study how competition for capital amongst municipal bond issuers can influence their disclosure decisions. Moody’s 2010 recalibration of the municipal rating scale advantaged heavily upgraded issuers and disadvantaged lightly upgraded issuers. We develop a simple model in which bond issuers compete for capital from the same pool of investors. The disadvantaged issuers respond to the recalibration by offering investors better financing terms to compete for investors’ capital with the advantaged issuers. These better financing terms heighten financing costs that, in turn, can induce and exacerbate a potential conflict between social welfare and government officials’ personal preferences. The conflict of interest calls for higher quality disclosure to assure investors that the government officials will not pursue their personal preference over social welfare. Empirically, we find that Moody’s recalibration induces the disadvantaged issuers to provide timelier financial statements than before the recalibration, particularly when those issuers face relatively intense competition for capital. This evidence supports the idea that issuers competing for capital consider their credit risk relative to their peers when making disclosure decisions. ∗Cheng (scheng7@tulane.edu) is with the Freeman School of Business at Tulane University. Cuny (ccuny@stern.nyu.edu) is with the Stern School of Business at New York University. Xue (hao.xue@duke.edu) is with the Fuqua School of Business at Duke University. We are grateful to Rui Silva and Miguel Ferreira for providing us with the Moody’s recalibration data. We are also grateful to Bill Baber, Gus DeFranco, Angela Gore, Leo Tang (discussant), Rodrigo Verdi, Dushyant Vyas, workshop participants at the 2019 AAA Government and Nonprofit Midyear Meeting, and George Washington University for valuable feedback.
Space Improvements and Equivalences in a Polymorphically Typed Functional Core Language : Context Lemmas and Proofs

We explore space improvements in LRP, a polymorphically typed call-by-need functional core language. A relaxed space measure is chosen for the maximal size usage during an evaluation. It abstracts from the details of the implementation via abstract machines, but it takes garbage collection into account and thus can be seen as a realistic approximation of space usage. The results are: a context lemma for space improving translations and for space equivalences; all but one reduction rule of the calculus are shown to be space improvements, and the exceptional one, the copy-rule, is shown to increase space only moderately. Several further program transformations are shown to be space improvements or space equivalences, in particular the translation into machine expressions is a space equivalence. Some space-worsening program transformations are classified as space-safe upto or as space-leaks. These results are a step forward in making predictions about the change in runtime space behavior of optimizing transformations in call-byneed functional languages.
Modeling and Computer Simulation of Static , Dynamic and Feedback Systems as Tool of Development of Logical Thinking

Many universities are realizing that modeling and simulation is becoming an important tool in finding the strategy for solving and understanding numerous and diverse problems. The paper introduces the theory of modeling and simulation as one of the possible method in the education. The theory is followed by three case studies illustrating step by step process of development of modeling and computer simulation. The first two cases studies will present possibility of simulation of static and dynamic systems in MS Excel worksheet and chart. The third case study presents creation of simulation model of the feedback regulated process – passing through the labyrinth. Keywords—Dynamic System, Feedback System, Modeling and Simulation, Static System.
2 6 M ay 2 01 6 Hybrid Beamforming for Massive MIMO Backhaul

The uplink where both the transmitter and receiver can use a large antenna array is considered. This is proposed as a method of antenna offloading and connecting small cell access points (SCAP) in a Two-Tier cellular network. Due to having a limited number of RF-chains, hybrid beamformers are designed where phase-only processing is done at the RF-band, followed by digital processing at the baseband. The proposed receiver is a row combiner that clusters sufficiently correlated antenna elements, and its’ performance is compared against random projection via a Discrete Fourier Transform (DFT) matrix. The analogue to the row combiner is a column spreader, which is dependent on the transmit correlation, and repeats the transmitted signal over antenna elements that are correlated. A key benefit of this approach is to reduce the number of phase shifters used, while outperforming the DFT scheme. When only the transmitter has correlation and is RF-chain limited, the baseband precoding vectors are shown to be the eigenvectors of the effective transmit correlation matrix. Depending on the channel correlation, this matrix can be approximated to have a tridiagonal Toeplitz structure with the proposed column spreader (CS). The resulting eigenvalues have a closed form solution which allows us to characterize the sum rate of the system. Most interestingly, the associated eigenvectors do not require knowledge of the effective transmit correlation matrix to be calculated using an Eigenvalue Decomposition (EVD) method.
The Dainamite 2007 Team Description

This paper gives an overview about the structure of the dainamite agent and highlights recent improvements of the world-model and the tactic, which were integrated into our framework. To this end, we present effective and robust methods for dynamic role assignment, movement and reachability analysis and opponent modelling. Finally we conclude by assessing our approaches and presenting current and future work.
DPDKStat : 40 Gbps Statistical Traffic Analysis with Off-the-Shelf Hardware

In recent years, advances in both hardware and software offer to user-space applications O(10Gbps) worth of traffic. Processing data at such line rate with software running on Commercial Off-The-Shelf (COTS) hardware requires careful design. In the literature, this challenge has been extensively studied for Network Intrusion Detection Systems (NIDS), with several proposals achieving scalability by exploiting GPU and NPU multi-core architectures. Yet, NIDS are relatively “easy” to parallelize given their core functionality is to match the input traffic with respect to a large catalog of rules. In this work, we instead focus on more generic Statistical Traffic Analysis (STA) tools. Specifically, we target the design of a passive monitoring solution that extracts hundreds of per-flow metrics collected in different output formats (text logs, RRD database, empirical distributions, etc.). Differently from NIDS, such metrics normally provide an extensive vision of specific traffic dynamics (e.g., TCP anomalies, video streaming QoE, HTTP content delivery, etc.), resulting in a few analysis engines, but an intrinsically more pipelined workflow. Parallelisation is then less trivial than for NIDS. We propose DPDKStat, a high speed STA that combines the Intel DPDK framework with Tstat, a passive traffic analyzer, to achieve 40Gbps of line rate processing. Beside reporting a detailed evaluation of the system using real traffic traces, we contribute an in-depth discussion on the design challenges to achieve scalability, and the lesson learned we believe of common interests for the traffic monitoring research community.