Miracle-dz/UniFAR-FTUs huggingface dataset:
Effecting Factors of Somatic Embryogenesis and Plant Regeneration in Vetiver

Axillary buds and aseptic adventitious buds of vetiver (Vetiveria zizanioides (L.) Nash) were used as explants to investigate the factors that affected somatic embryogenesis and plant generation. The explants were cultured on MS medium supplemented with 2,4-dichlorophenoxyacetic acid (2,4-D) or and 6-benzyladenine (6-BA). The results showed the explants could regenerate via somatic embryogenesis when the medium contained only 2,4-D without or with little content of 6-BA. Callus induction frequency in different cultivars was significantly varied, eg: cv. Zomba had highest induction frequency, up to 96.7%, but cv. Malaysia the lowest, less than 30%, whereas that in cv. Kandy and cv. Sunshine was almost the same. Regeneration ability in embryonic calli could be maintained for a long time, the regeneration frequency being still over 80%, regardless of subculture times from 0 to 23. The differentiation ability of embryonic calli was inhibited at temperature of 3-7℃, under which only 40.5%-50.0% of them could regenerate.
Interference Precancellation for Resource Management in Heterogeneous Cellular Networks

Network densification by installing more cellular stations (cells) with smaller coverage is promising to improve wireless capacity to meet the explosive growth of cellular traffic. The macrocellular base station and smaller cells with different coverage form heterogeneous cellular networks. Typically, the smaller cells operate in the same spectrum as the macrocells. Most of the existing interference mitigation approaches either rely on resource isolation or power auto-configuration. In cellular networks, the data to all cells and the mobile stations (MSs) are originated from the core cellular network. We take advantage of this characteristic and propose a technique called interference precancellation. If the exact interferer to an MS is identified, the victim cell that serves the victim MS transmits the interference precanceled signal, which is the signal intended for the victim MS subtracts the interference signal. The interference precanceled signal and the interference signal scramble at the victim MS and became the intended signal. With interference precancellation, the interferer and the victim cell can utilize the same set of resources and thus the capacity is further improved. However, some MSs are interference-free, and for MSs whose exact interferers cannot be determined, the MSs still require resource isolation. Therefore, we propose an algorithm for resource management with interference precancellation (RMIP) that jointly considers MSs experiencing a different level of interference. Through experiments on GNU Radio/USRP, we show that the known interference signal can be precanceled and the combination of the interference signal and the precanceled signal becomes the intended signal. Simulation results show that if all exact interferers are identified, RMIP algorithm achieves higher throughput compared with pure resource isolation.
Dragonflies of the world

Here, for the first time, is a comprehensive and accessible overview of one of the world’s most popular insect groups, the Odonata. Written for interested amateurs as well as more experienced professionals, Dragonflies of the World covers their evolution, ecology, behaviour, physiology and taxonomy. It describes their unique attributes and the distinctive features of the suborders, superfamilies, families and subfamilies.
Ultrastructural Distribution of the α7 Nicotinic Acetylcholine Receptor Subunit in Rat Hippocampus

Acetylcholine (ACh) is an important neurotransmitter in the mammalian brain; it is implicated in arousal, learning, and other cognitive functions. Recent studies indicate that nicotinic receptors contribute to these cholinergic effects, in addition to the established role of muscarinic receptors. In the hippocampus, where cholinergic involvement in learning and memory is particularly well documented, α7 nicotinic acetylcholine receptor subunits (α7 nAChRs) are highly expressed, but their precise ultrastructural localization has not been determined. Here, we describe the results of immunogold labeling of serial ultrathin sections through stratum radiatum of area CA1 in the rat. Using both anti-α7 nAChR immunolabeling and α-bungarotoxin binding, we find that α7 nAChRs are present at nearly all synapses in CA1 stratum radiatum, with immunolabeling present at both presynaptic and postsynaptic elements. Morphological considerations and double immunolabeling indicate that GABAergic as well as glutamatergic synapses bear α7 nAChRs, at densities approaching those observed for glutamate receptors in CA1 stratum radiatum. Postsynaptically, α7 nAChRs often are distributed at dendritic spines in a perisynaptic annulus. In the postsynaptic cytoplasm, immunolabeling is associated with spine apparatus and other membranous structures, suggesting that α7 nAChRs may undergo dynamic regulation, with insertion into the synapse and subsequent internalization. The widespread and substantial expression of α7 nAChRs at synapses in the hippocampus is consistent with an important role in mediating and/or modulating synaptic transmission, plasticity, and neurodegeneration.
Measurement Errors in Consumption Surveys and the Estimation of Poverty and Inequality Indices

This paper firstly aims to evaluate the incidence of measurement error affecting the main variables collected in surveys on consumption. The assessment is carried out on two Tanzania surveys which provide both diary and panel data. Diary data can be employed to obtain reliability coefficients for time-invariant variables. When variables vary over time, as in the case of panel data, an estimation of the incidence of measurement error on the total variance can be obtained by applying models which allow the decomposition of observed variability into true dynamics and noise (e.g. the Heise model and the latent Markov model). Some evaluations of the reliability of the data are also conducted on the basis of the internal consistency criterion, an approach that does not require panel data. On the basis of the reliability estimates obtained, examples of possible impacts of measurement errors on poverty analysis are briefly discussed. These experiments clearly show the importance of the topic in poverty and inequality data analysis.
Small signal analysis of peak current mode controlled Zeta converter

Bu calismada, tepe akim-modu kontrollu, izole edilmemis Zeta donusturucunun kucuk isaret analizi sunulmustur. Yapilan analizde PWM anahtarlama modeli Surekli Iletim Modu’nda (SIM) degerlendirilmistir. Kontrol isaretinden cikis gerilimine olan transfer fonksiyonu cikis kondansatorundeki esr (esdeger seri direnc) de dâhil olmak uzere sembolik formda elde edilmistir. Transfer fonksiyonuna ait sifirlarin kesin cozumleri sembolik olarak verilmistir. Ancak, elde edilen tepe akim modu kontrollu PWM anahtarlama modelinin paydasi 5. mertebeden bir polinom oldugundan, kutuplarin ve kalite faktorlerinin sembolik formda bulunmasi icin yaklasik kok analizi kullanilmasi gerekmektedir. Bu analiz kullanilarak yaklasik kutuplar ve kalite faktorleri de sembolik formda turetilmistir.
Simplified Thermal Model of Spaces Cooled with Combined Positive Displacement Ventilation and Chilled Ceiling System

An improved plume-multilayer model was developed and validated to represent thermal transport in enclosures conditioned by radiant cooling and displacement ventilation systems. A novel approach was developed to estimate wall plumes for non-isothermal surfaces using the similarity solution derived for power law representation of temperature difference between the room air and the wall. The nonuniform wall plume flow rates predicted by the model agreed well with flow rates in an enclosure produced by computational fluid dynamics (CFD) simulations. Wall plumes associated with a nonuniformly heated wall with varying temperature difference between the wall and the air were found to be substantially higher than the plume predicted by isothermal wall correlation. The wall plume model is integrated with a multilayer space thermal model to predict the stratification height in the space, the vertical distribution of wall and air temperatures as a function of the chilled ceiling temperature and space air supply conditions. The plume-multilayer model results were compared with results of three-dimensional CFD simulations using commercially available software. Three test cases were considered for the simulations at cooling loads of 40 W/m2 (12.7 Btu/h·ft2), 67 W/m2 (21.2 Btu/h·ft2), and 100 W/m2 (31.7 Btu/h·ft2) and supply airflow rates per unit area of 22.5 (1.2 ft3/min·ft2), 30 (1.6 ft3/min·ft2), and 37.5 m3/h·m2 (2.1 ft3/min·ft2), respectively. The vertical wall and average air temperatures for each layer agreed well with the results of the plume-multilayer model, showing maximum errors in values of average air temperature of 0.13°C (0.23°F), 0.37°C (0.66°F), and 0.3°C (0.54°F) for the low, medium, and high load cases, respectively. The simplified model accurately predicted the stratification height at a maximum error of ±0.05 m (0.16 ft) in the three test cases. The stratification height is overestimated by 35% if wall plumes are neglected in the plume-multilayer model.
Web-based Responsive Support System for the Efficient IoT Control

In this paper, we propose an effective web service software platform for remote monitoring and control. In order to propose a system configuration that can check the object information on the web in real time to improve the performance of the web service, the object information reception module and the web viewer system are configured. As IoT devices grow, the environment becomes too complicated to identify and control the status of many devices. We have proposed that these problems be easily controlled in a web-based environment and current status information can be viewed in real time
FEATURE VECTOR GENERATION FOR THE FACIAL EXPRESSION RECOGNITION USING NEO-FUZZY SYSTEM

Context. The article is devoted to the problem of a training data set forming for the automatic human emotions recognition system on the basis of a multidimensional extended neo-fuzzy neuron. The aspects of choice the attributes vector’s dimension and composition, their influence on the system learning rate are considered. The object of research is the method of multidimensional data clustering. The subject of research is two-dimensional images geometric features systematization. Objective. The main goal of the work is to develop an approach to person’s face expression description using geometric features fixed set that can be obtained by video sequence frames processing. Method. To study the facial expressions recognition system it is proposed to form a feature vector consisting of characteristic points coordinates. There were selected points that relate to the location and shape of the eyelids, eyebrows, eye pupils, lips contours, nose wings, nasolabial folds. Such points can be easily found during the automatic image processing using known contour detectors. Also, the possibility of using for the human facial expression description not the coordinates of characteristic points, but the distances between them, was investigated. From these distances a different feature vector was created, the properties of which were compared with the points coordinates vector. Results. The developed recognition system on the basis of a multidimensional extended neo-fuzzy neuron have been implemented in software and investigated for solving the problem of facial expression classification. A comparison between the attribute vectors that are different in composition and dimension is made. The structure for the feature vector, which provides high system learning rate, and does not require the additional structural elements was chosen. Conclusions. The experimental study fully confirms the effectiveness of the developed approach for the human facial expressions recognition using a multidimensional extended neo-fuzzy neuron.
Seeing History : Analyzing Large-Scale Historical Visual Datasets using Deep Neural Networks

Scholars are increasingly applying computational methods to analyze the visual aspects of large-scale digitized visual datasets.1 Inspiring examples are the work of Seguin on visual pattern discovery in large databases of paintings and Moretti’s and Impett’s large-scale analysis of body postures in Aby Warburg’s Atlas Mnemosyne.2 In our paper, we will present two datasets of historical images and accompanying metadata harvested from Dutch digitized newspapers and reflect on ways to improve existing neural networks for historical research. We will discuss how large historical visual datasets can be used for historical research using neural networks. We will do this by describing two case studies, and will end our paper by arguing for the need for a benchmarked dataset with historical visual material. The sets were produced during two researcher-in-residence projects at the National Library of the Netherlands. The first set (SIAMESET) consists of more than 400,000 advertisements published in two major national newspapers between 1945 and 1995.3 Using the penultimate layer in a Convolutional Neural Network (CNN), 2,048 visual aspects were abstracted from these images, which can be used to group images together.4 The second dataset (CHRONIC) includes about 313,000 classified images from newspapers published between 1860 and 1922.5 The images were classified using a pipeline that consists of three classifiers. The first one detects images with faces, the second categorizes images according to eight different categories (buildings, cartoons, chess problems, crowds, logos, schematics, sheet music, and weather reports), and the last one sorts images as either photographs or drawings.6 We developed two tools to query these datasets. The first tool (SIAMESE) offers exploratory search in the advertisement dataset, which enables users to find images sharing a degree of visual similarity and can be used to detect visual trends in large visual datasets.7 For example, you can input an advertisement with a particular design, or perhaps a shape or object,
A Robust Optimization Methodology for Multi-objective Location-transportation Problem in Disaster Response Phase under Uncertainty

This paper presents a multi-objective model for location-transportation problem under uncertainty that has been developed to respond to crisis. In the proposed model, humanitarian aid distribution centers (HADC), the number and location of them, the amount of relief goods stored in distribution centers, the amount of relief goods sent to the disaster zone, the number of injured people transferred to medical centers and the delivery of relief regarding the limits of capacity for transport, distribution centers and also available time and budget limits are all considered. This work aims at minimizing unfulfilled needs; that is meaning the number of people have not been transferred to medical centers. In order to take the inevitable uncertainty in some parameters into account, the primal deterministic model has been reformulated by applying the robust optimization approach. Also the performance of the both deterministic and robust models are investigated by solving a numerical example. The results of the study show that the robust counterpart of deterministic model will remain feasible with a high probability in reality.
Acoustics - Spatial properties

In Chapter 2, we presented the spectral properties of sound sources which can be exploited for the separation or enhancement of single-channel signals. In multichannel scenarios, the fact the acoustic scene is observed from different positions in space can also be exploited. In this chapter, we recall basic elements of acoustics and sound engineering, and use them to model multichannel mixtures. We consider the relationship between a source signal and its spatial image in a given channel in Section 3.1, and examine how it translates in the case of microphone recordings or artificial mixtures in Sections 3.2 and 3.3, respectively. We then introduce several possible models in Section 3.4. We summarize the main concepts and provide links to other chapters and more advanced topics in Section 3.5.
Analysis Of High Performance Scientific Programming Workflows

Substantial time is spent on building, optimizing and maintaining large-scale software that is run on supercomputers. However, little has been done to utilize overall resources efficiently when it comes to including expensive human resources. The community is beginning to acknowledge that optimizing the hardware performance such as speed and memory bottlenecks contributes less to the overall productivity than does the development lifecycle of high-performance scientific applications. Researchers are beginning to look at overall scientific workflows for high performance computing. Scientific programming productivity is measured by time and effort required to develop, configure, and maintain a simulation experiment and its constituent parts, together with the time to get to the solution when the programs are executed. There is no systematic framework by means of which scientific programming productivity of the available tools can be evaluated. We propose an evaluation approach that compares programming workflows to identify productivity bottlenecks and suboptimal paths as well as productivity gains. Based on a set of predefined criteria we can evaluate both short-term and long-term productivity criteria. We use these results to suggest improvements to the programming environment or tools. This thesis includes three studies of scientific programming workflows: 1) We apply our evaluation approach to two case studies involving the use of numerical libraries. 2) We evaluate GPU programming models using software engineering complexity metrics. 3) We evaluate use of a high level directive based programming model and a source-to-source compiler with respect to productivity of programming FPGAs using a computational chemistry code. We compare the programmability and performance of the FPGA port with the GPU port of the same code.
Lp-SOLUTIONS FOR REFLECTED BSDES WITH TIME DELAYED GENERATORS

In this paper, we establish the existence and uniqueness of the solution for a class of reflected backward stochastic differential equations with time delayed generator (RBSDEs with time delayed generator, in short) in the case when the terminal value and the obstacle process are Lp-integrable with p ∈]1, 2[ for a sufficiently small Lipschitz constant of the generator and the time horizon T .
An end user’s perspective on activity-based office concepts

Purpose – The activity‐based office concept of the modern office is set to increase productivity through the stimulation of interaction and communication while retaining employee satisfaction and reducing the accommodation costs. Although some research has gone into understanding the added value, there is still a need for sound data on the relationship between office design, its intentions and the actual use after implementation. The purpose of this paper is to address this issue.Design/methodology/approach – An evaluative study on the effectiveness of activity‐based office concepts was carried out to gain more insight in their use. The study included relevant literature on workplace design, combined with an observation and a survey of 182 end‐users from four different service organizations in The Netherlands.Findings – The findings from these case studies underline some known benefits and disadvantages of activity‐based office concepts, and provide insight in the importance of several physical, social an.
GNU Lesser General Public License

1.Preamble. 1 2. GNU LESSER GENERAL PUBLIC LICENSE TERMS AND CONDITIONS FOR COPYING, DISTRIBUTIONANDMODIFICATION . 2 3.NOWARRANTY . 6 4.ENDOFTERMSANDCONDITIONS . 6 5. How to Apply These Terms to Your New Libraries . 6
Supracorpora Databases as Corpus-Based Superstructure for Manual Annotation of Parallel Corpora

This paper presents a new type on corpus-based information resource: supracorpora databases (SCDBs). SCDBs are designed to enhance functionality of linguistic corpora by supporting customizable manual annotation of linguistic items, including multi-word items. This is similar to query result categorization functions available in some corpora and to functions provided by some of the standalone corpus annotation tools, although many features supported by SCDBs are more sophisticated (e.g. they allow for detailed annotation of multi-word linguistic items, including specification of main words and immediate context). More importantly still, SCDBs allow researchers to create annotated translation correspondences (TCs) in parallel corpora. Aggregation of searchable TCs in a SCDB represents a unique information resource that facilitates creation of new explicit knowledge about cross-linguistic correspondences and translation models. An overview of four SCDBs developed up to date is also included in this paper.
Techniques for Segmentation and Classification of Leukocytes in Blood Smear Images - A Review

Leukocytes present in the blood are responsible for providing protection against infections. Differential Blood Count is a medical procedure conducted by pathologists to identify and count the different kinds of leukocytes in blood to aid the identification of diseases. This procedure requires the pathologists to perform microscopic evaluation which is time consuming and human involvement in the process may produce error prone results. Many computer-aided systems have been designed to perform segmentation and categorization of leukocytes from the peripheral blood smear images to automate the process and reduce manual involvement. This paper presents a survey of different techniques proposed by researchers for segmentation and classification of leukocytes accentuating its pros and cons and the scope for future research in this context is also discussed.
Relativistic outflow drives γ-ray emission in 3C345

Aims. On the basis of the first 20 months of Fermi-LAT data and optical monitoring, the quasar 3C 345 has been identified as a γ-ray emitter. We investigate whether there is a connection between the γ-ray and optical variability of 3C 345 and the properties of its parsec-scale radio emission. Methods. We combined the Fermi-LAT data of 3C 345, covering an energy range of 0.1–300 GeV, with 32 Very Long Baseline Array observations of the object made at 43.2 GHz in the period of January 2008–March 2010. Results. The VLBA data reveal the morphology and kinematics of the flow on scales of up to ≈5 milliarcseconds (deprojected linear distances of 380 parsecs). The brightness temperature, Tb(r), measured along the jet first decreases with distance ∝r −(0.95 ± 0.69) and later exhibits a break at ≈0.3 milliarcseconds (mas), with Tb(r) ∝ r −(4.11 ± 0.85) at larger separations. Variations in the γ-ray, optical, and parsec-scale radio emission display a similar long-term trend that persists during the entire VLBA monitoring period. The γ-ray and optical variations on shorter timescales are related to structural changes in the jet on scales of ≈0. 3m as (≈23 parsecs, deprojected), with the γ-ray and optical flares possibly being related to the evolution of four distinct superluminal components identified in the flow. Conclusions. The observations indicate that both the quiescent and flaring components of the γ-ray emission are produced in a region of the jet that extends up to ∼23 pc. This region may correspond to the Compton-loss dominated zone of the flow and its large extent may favor the synchrotron self-Compton mechanism for γ-ray production in the relativistic jet of the quasar 3C 345.