Miracle-dz/UniFAR-FTUs huggingface dataset:
Late flowering and low synchrony with males enhance female reproductive success in the dioecious palm Chamaedorea pinnatifrons

Background: Dioecious species require a conspecific for sexual reproduction. As such, they demand a high level of flowering synchronization. In this scenario, phenology can deepen the effect of density, sex ratio, and distance over fruit production. Also, pollinator reliability can affect a species reproductive success (RS). Pollinator specialist depend on their few pollinators have a high population size; in contrast, generalist (pollinated by many taxa) can surpass this because of their condition. In this paper, we analyzed the effect of phenology, density, distance and pollinator abundance on the female RS of the dioecious palm Chamaedorea pinnatifrons (Palmae) at a cloud forest in Costa Rica. This palm is pollinated by wind and a single species of thrips (Thysanoptera: Thripidae) in a mixed pollination system. The pollination system seems to be highly specialized, as the thrips species has been recorded only in flowers of Chamaedorea Methods: In the 2012 season we monitored the phenology of a population (n = 88 males, 94 females) in a 40x40 plot. All individuals were sexed, mapped, had their height measured and number of leaves counted. RS was measured as the number of fruits/inflorescence and as fruit set. Generalized Linear Mixed Effects Model (GLMM) were used to test the effect of flowering time, distance to nearest male, density of males, number of flowers, height, number of leaves and number of flowers over the two response variables. We also estimated thrips population by sampling insects directly from staminate inflorescences in anthesis, from early March to mid-May (11 weeks, n = 33 inflorescences). Results: Flowering of C. pinnatifrons lasted five months: it began by early February, had a peak by early April, and ended by July. Mean fruit production was 99.7 (± 12.1 SE, min = 0, max = 735). The amount of fruits produced was significantly higher in inflorescences from individuals with shorter stems, had more flowers, a lower flowering synchrony with males and flowered late. Mean fruit set was 0.144 ± 0.016%. Fruit set was also significantly higher in inflorescences from lower stems, with lower male synchrony and flowered late. The mean amount of thrips sampled in staminate inflorescences increased 13-fold between early March (20.8 ± 10.6 thrips/rachillae) and mid-May (282.0 ± 74.4). Discussion: The higher RS of late flowering plants can be partially explained by the progressive increase in the population of pollinators. Our results in C. pinnatifrons seem to oppose recent analyses in that early flowering plants should be positively selected. A deeper understanding of a species pollination system is necessary to understand the strength of the agents of selection.
On the Development of IETF-based Network Monitoring Probes for High Speed Networks

In the recent years network managers have increasingly relied on monitoring tools to characterize and measure high-layer protocol traffic in order to (a) justify investments on network equipment acquisition, (b) identify most network-consuming users, (c) detect bottlenecks, to mention just a few reasons. The Internet Engineering Task Force (IETF), aware of the mentioned demand, has been making efforts to standardize management mechanisms that allow the characterization and measurement of both protocols and networked applications behavior. However, the development of IETF compliant probes so that they sustain the traffic generated in high speed networks is a current challenge, since communication links operating at 100 Mbps or higher rates require efficient packet filtering and processing mechanisms so that probes do not discard packets. This paper reports the development, by our research group, of an RMON2 compliant SNMP agent. The paper focuses on the project decisions, including the architecture and data structures used (having in mind that the agent is supposed to be deployed in high speed network environments). The paper also presents a performance evaluation of the agent.
Autonomous Decentralized Collaborative Applications : an architecture for collaborative information-dissemination applications

In this paper we describe a model or architecture for autonomous and decentralized collaborative applications to support scientific research, collaborative learning projects and in general collaborative work. We first describe the application environment we had in mind: the design of a peer-to-peer collaborative newspaper application in a large network of schools. We have identified a generic component for decentralized information dissemination and we propose the Fast Consistency algorithm, a new weak consistency replication algorithm designed to satisfy the greatest global demand of fresh data in the shortest time, when network nodes only know some neighbours. This component may be useful to most collaborative or data intensive applications based on peer-to-peer or grid environments, requiring fast and selective replication of information on large and dynamic networks of autonomous agents with incomplete information, with clients or participants with varying degrees of interest, scattered or clustered in different locations, i.e. non-uniform geographic distributions of demand. We then describe LaCOLLA, a peer-to-peer architecture providing common collaborative support services. LaCOLLA supports three main abstractions (groups, events, group objects), services or mechanisms (event dissemination, group storage, group awareness, presence, object sharing, location, movement and replication), grouped in three classes of components (user agent, repository agent, group administration and presence agent) for peer-to-peer collaborative applications. It requires an infrastructure, which can be, among others, the Grid OGSA. This work has been validated by simulation of FC and LaCOLLA with several topologies, distributions of demand, and failures. The results confirm the validity, performance and self-organization of the system.
Crypto Key Generation using Contour Graph Algorithm

Cryptography and biometrics have been identified as two of the most important aspects of digital security environment, for various types of security problems the merging between cryptography and biometrics has led to the development of Bio-Crypto technology. In this paper we propose a cryptography key generating methodology based on graph construction and adjacency matrix of extracted minutiae. The formation of graph relies on contour division of minutiae points area. Minutiae points area is studied on both scenarios (with singular point, and without singular point detection). Results show that with singular point detection the average of minutiae points area dimension is less than in the other case and at some points of threshold, it show an improvement performance comparing to the other one. 100% uniqueness key was achieved on both cases.
Towards the formal analysis of microresonators based photonic systems

Recent developments in the fabrication technology attracted the attention of optical engineers and physicists in the area of VLSI photonics. Due to the physical nature of light-wave systems and their usage in safety critical domains such as human surgeries and high budget space missions, it is indispensable to build high assurance systems. Traditionally, the analysis of such systems has been carried out by paper-and-pencil based proofs and numerical computations. However, these techniques cannot provide perfectly accurate results due to the risk of human error and inherent approximations of numerical algorithms. In order to overcome these limitations, we propose to use higher-order logic theorem proving to improve the analysis in the domain of integrated optics or VLSI photonics. In particular, this paper provides a higher-order logic formalization of optical microresonators which are the most fundamental building blocks of many photonic devices. In order to illustrate the practical utilization of our work, we present the formal analysis of 2-D microresonator lattice optical filters.
Identifying Mammalian MicroRNA Targets Based on Supervised Distance Metric Learning

MicroRNAs (miRNAs) have been emerged as a novel class of endogenous posttranscriptional regulators in a variety of animal and plant species. One challenge facing miRNA research is to accurately identify the target mRNAs, because of the very limited sequence complementarity between miRNAs and their target sites, and the scarcity of experimentally validated targets to guide accurate prediction. In this paper, we propose a new method called SuperMirTar that exploits super vised distance learning to predict miRNA targets. Specifically, we use the experimentally supported miRNA-mRNA pairs as a training set to learn a distance metric function that minimizes the distances between miRNAs and mRNAs with validated interactions, then use the learned function to calculate the distances of test miRNA-mRNA interactions, and those with smaller distances than a predefined threshold are regarded as true interactions. We carry out performance comparison between the proposed approach and seven existing methods on independent datasets; the results show that our method achieves superior performance and can effectively narrow the gap between the number of predicted miRNA targets and the number of experimentally validated ones.
MicroScope in 2017: an expanding and evolving integrated resource for community expertise of microbial genomes

The annotation of genomes from NGS platforms needs to be automated and fully integrated. However, maintaining consistency and accuracy in genome annotation is a challenging problem because millions of protein database entries are not assigned reliable functions. This shortcoming limits the knowledge that can be extracted from genomes and metabolic models. Launched in 2005, the MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Effective comparative analysis requires a consistent and complete view of biological data, and therefore, support for reviewing the quality of functional annotation is critical. MicroScope allows users to analyze microbial (meta)genomes together with post-genomic experiment results if any (i.e. transcriptomics, re-sequencing of evolved strains, mutant collections, phenotype data). It combines tools and graphical interfaces to analyze genomes and to perform the expert curation of gene functions in a comparative context. Starting with a short overview of the MicroScope system, this paper focuses on some major improvements of the Web interface, mainly for the submission of genomic data and on original tools and pipelines that have been developed and integrated in the platform: computation of pan-genomes and prediction of biosynthetic gene clusters. Today the resource contains data for more than 6000 microbial genomes, and among the 2700 personal accounts (65% of which are now from foreign countries), 14% of the users are performing expert annotations, on at least a weekly basis, contributing to improve the quality of microbial genome annotations.
Black gram (Vigna Mungo L.) foliage supplementation to crossbred cows: effects on feed intake, nutrient digestibility and milk production

Objective An experiment was conducted to examine the effect of dietary supplementation of dried and ground foliage of black gram (Vigna mungo L.) on feed intake and utilization, and production performance of crossbred lactating cows. Methods Eighteen lactating crossbred (Bos taurus×Bos indicus) cows (body weight 330.93± 10.82 kg) at their second and mid lactation (milk yield 6.77±0.54 kg/d) were randomly divided into three groups of six each in a completely randomized block design. Three supplements were formulated by quantitatively replacing 0, 50, and 100 per cent of dietary wheat bran of concentrate mixture with dried and ground foliage of black gram. The designated supplement was fed to each group with basal diet of rice straw (ad libitum) to meet the requirements for maintenance and milk production. Daily feed intake and milk yield was recorded. A digestion trial was conducted to determine the total tract digestibility of various nutrients. Results The daily feed intake was increased (p<0.05) with the supplementation of black gram foliage. Although the digestibility of dry matter, organic matter, crude protein, and ether extract did not vary (p>0.05), the fibre digestibility was increased (p<0.05), which ultimately improved (p<0.05) the total digestible nutrients content of composite diet. Although, the average milk yield (kg/animal/d) and composition did not differ (p>0.05) among the groups, milk yield was increased by 10 per cent with total replacement of wheat bran in concentrate mixture with of black gram foliage. The economics of milk production calculated as feed cost per kg milk yield (INR 10.61 vs 7.98) was reduced by complete replacement of wheat bran with black gram foliage. Conclusion Black gram foliage could be used as complete replacement for wheat bran in concentrate mixture of dairy cows in formulating least cost ration for economic milk production in small holders’ animal production.
Designing and Analysing STEM Studios for preservice teacher education

There is a need for approaches to understand the teaching and learning of STEM and STEAM in schools in order to prepare preservice teachers for innovative classroom practice. In this paper we use a combined design approach to examine the activity of school students, preservice teachers and graduate STEAM students in two STEM Studios at a University in Queensland. We present our revised conceptual model based on earlier iterations as part of an OLT funded project. Multimodal learning analytics approaches will be applied in order to understand the integration of knowledge processes, epistemic cognition, collaboration and tool use.
The Moloney Murine Leukemia Virus Repressor Binding Site Represses Expression in Murine and Human Hematopoietic Stem Cells

ABSTRACT The Moloney murine leukemia virus (MLV) repressor binding site (RBS) is a major determinant of restricted expression of MLV in undifferentiated mouse embryonic stem (ES) cells and mouse embryonal carcinoma (EC) lines. We show here that the RBS repressed expression when placed outside of its normal MLV genome context in a self-inactivating (SIN) lentiviral vector. In the lentiviral vector genome context, the RBS repressed expression of a modified MLV long terminal repeat (MNDU3) promoter, a simian virus 40 promoter, and three cellular promoters: ubiquitin C, mPGK, and hEF-1a. In addition to repressing expression in undifferentiated ES and EC cell lines, we show that the RBS substantially repressed expression in primary mouse embryonic fibroblasts, primary mouse bone marrow stromal cells, whole mouse bone marrow and its differentiated progeny after bone marrow transplant, and several mouse hematopoietic cell lines. Using an electrophoretic mobility shift assay, we show that binding factor A, the trans-acting factor proposed to convey repression by its interaction with the RBS, is present in the nuclear extracts of all mouse cells we analyzed where expression was repressed by the RBS. In addition, we show that the RBS partially repressed expression in the human hematopoietic cell line DU.528 and primary human CD34+ CD38− hematopoietic cells isolated from umbilical cord blood. These findings suggest that retroviral vectors carrying the RBS are subjected to high rates of repression in murine and human cells and that MLV vectors with primer binding site substitutions that remove the RBS may yield more-effective gene expression.
Understanding the Usefulness of Ideation Tools with the Grounding Lenses

Many design studies were focused on how to form a card-based inspiration tool to support designers in the early stage of their design process. Although there is a great deal of studies on bridging the gap between design theories and instances through card-based design, however, there is little guidance, on how to pragmatically evaluate the usefulness. Using a set of deck, Interaction Tarot, based on the structure of Tarot, as an example, this paper argues that the Horizontal and Vertical Groundings (HG & VG), often used to generate intermediate-level knowledge such as strong concepts [12], can serve as analytical criteria for evaluating the quality of card-based design tool pragmatically. To address this, we conducted an HCI workshop with multiple brainstorming sessions with Interaction Tarot. The questionnaire data, tool usage, and interview accounts are categorized or quantified with respect to HG & VG, to ascertain how a card-based tool helps designers facilitate the design ideation in practical use. The findings could provide proper empirical evidence to demonstrate how design researchers use the set of two lenses (HG & VG) to have better understandings of a card-based tool in supporting the design inspiration.
Scalable performance of ScaleGraph for large scale graph analysis

Scalable analysis of massive graphs has become a challenging issue in high performance computing environments. ScaleGraph is an X10 library aimed for large scale graph analysis scenarios. This paper evaluates scalability of ScaleGraph library for degree distribution calculation, betweeness centrality, and spectral clustering algorithms. We make scalability evaluation by analyzing a synthetic Kronecker graph with 40.3 million edges (for all the three algorithms), and a real social network with 69 million edges (for degree distribution calculation) on Tsubame 2.0 distributed memory environment.
Leveraging Diverse Lexical Resources for Textual Entailment Recognition

Since the problem of textual entailment recognition requires capturing semantic relations between diverse expressions of language, linguistic and world knowledge play an important role. In this article, we explore the effectiveness of different types of currently available resources including synonyms, antonyms, hypernym-hyponym relations, and lexical entailment relations for the task of textual entailment recognition. In order to do so, we develop an entailment relation recognition system which utilizes diverse linguistic analyses and resources to align the linguistic units in a pair of texts and identifies entailment relations based on these alignments. We use the Japanese subset of the NTCIR-9 RITE-1 dataset for evaluation and error analysis, conducting ablation testing and evaluation on hand-crafted alignment gold standard data to evaluate the contribution of individual resources. Error analysis shows that existing knowledge sources are effective for RTE, but that their coverage is limited, especially for domain-specific and other low-frequency expressions. To increase alignment coverage on such expressions, we propose a method of alignment inference that uses syntactic and semantic dependency information to identify likely alignments without relying on external resources. Evaluation adding alignment inference to a system using all available knowledge sources shows improvements in both precision and recall of entailment relation recognition.
A Review:SIFT Hardware Implementation For Real Time Feature Extraction

In pattern recognition and image processing, feature extraction is simple form of dimensionality reduction. The transformation of the input data's into a set of features is known as feature extraction. The large set of data's is to be analyzed and performed accurately from the features of the input data. By using SIFT (Scale Invariant feature transform) the hardware resources can be minimized and it could be performed as a process of parallel and the pipeline based VLSI architecture. We propose two parallel SIFT feature extraction algorithms using general multi-core processors, as well as some techniques to optimize the performance on multi-core. The proposed architecture led to a 6.7x faster speed on a dual-socket, quad-core system, which facilitated an average 45 frames/second for a VGA (640×480) video. Some implementations and accelerations of SIFT feature extraction on graphics processing units (GPUs) were introduced. With the parallelism and powerful computational ability, they achieved high processing speed.
Peer-to-Peer Selection and Channel Assignment for Wireless Mesh Networks

Wireless mesh networks are an emerging paradigm for future broadband wireless access networks, with manyapplication areas ranging from content distribution over community networking and providing backhaul networking for sensor devices. In wireless mesh networks, clients connect to wireless routers which are equipped with one or more wireless cards and relay the packets over the wireless links towards internetgateways or the destination. Peer-to-Peer applications are an important class of applications which contributes nowadays to the majority of internet traffic. Therefore, it is important to provide high capacity in the mesh network to support them. However, the capacity of wireless mesh networks depends on many factors such as network topology and size, traffic volume and pattern, interfaces per node and channel assignment scheme used, modulation schemes, routing approaches, etc. In this paper, we develop an analytical framework which allows to estimate theachievable capacity of a wireless mesh network when peer-to-peer applications download many flows simultaneously. The model is based on the collision domain concept and incorporates various channel assignment, replication and peer selection strategies. We investigate the achievable capacity for various scenarios and study the impact of different parameters such as the number of channels or radios used
Position referencing and consistent world modeling for mobile robots

In order to understand its environment, a mobile robot should be able to model consistently this environment, and to locate itself correctly. One major difficulty to be solved is the inaccuracies introduced by the sensors. The approach proposed in this paper to cope with this problem relies on 1) defining general principles to deal with uncertainties : the use of a multisensory system, favo ring of the data collected by the more accurate sensor in a given situation, averaging of different but consistent measurements of the same entity weighted with their associated uncertainties, and 2) a methodology enabling a mobile robot to define its own reference landmarks while exploring its environment. These ideas are presented together with an example of their application on the mobile robot HILARE.
The Effects of Positive Psychological Capital on the Creative Behavior of Employees in Korean Public Organizations: Focusing on the Moderating Role of Innovation-Oriented Culture

최근 공공조직 내부의 혁신과 공무원들의 창의적 행동에 대한 요구가 커지고 있다. 공공조직은 특성상 외부환경변화에 민감하지 않고, 조직 내 위계적, 집단주의적 문화가 강하기 때문에 개인 차원의 창의적 아이디어를 제시하거나 행동을 취하기가 어렵다. 하지만 급변하는 행정환경 속에서 공무원들의 창의적 행동은 효율적인 공공서비스 제공을 위해 매우 중요한 요소이다. 때문에 많은 연구에서는 공무원들이 업무를 수행함에 있어 보다 창의적 행동을 이끌어내기 위한 전략들을 제 시하고 있다. 본 연구는 조직구성원들이 가지고 있는 하나의 자본으로서 긍정심리자본과 조직문화 적 요소로서 혁신지향문화가 창의적 행동에 미치는 영향을 살펴보고자 하였다. 이에 책임운영기관 에서 일하고 있는 공무원 1,064명을 대상으로 실증분석을 실시하였다. 분석결과 성별, 나이 직위에 따라 공공조직 구성원들의 창의적 행동이 달라지는 것을 확인하였다. 또한, 자기효능감, 낙관주의 는 창의적 행동에 긍정적인 영향을 미치는 반면, 회복탄력성은 창의적 행동에 부정적인 영향을 미 치는 것으로 확인되었다. 셋째, 혁신지향 조직문화는 자기효능감, 회복탄력성, 낙관주의가 창의적 행동에 미치는 영향력을 조절하였다. 본 연구는 이러한 연구결과를 바탕으로 공무원들의 창의적 행동을 이끌어 내기 위해 인적자원개발 및 관리 차원에서 개인의 심리자본을 관리하고 조직의 문 화적 요소를 함께 고려해야함을 제시하였다.