Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of RNA-Seq data reveals involvement of JAK/STAT signalling during leg regeneration in the cricket Gryllus bimaculatus

In the cricket Gryllus bimaculatus, missing distal parts of the amputated leg are regenerated from the blastema, a population of dedifferentiated proliferating cells that forms at the distal tip of the leg stump. To identify molecules involved in blastema formation, comparative transcriptome analysis was performed between regenerating and normal unamputated legs. Components of JAK/STAT signalling were upregulated more than twofold in regenerating legs. To verify their involvement, Gryllus homologues of the interleukin receptor Domeless (Gb’dome), the Janus kinase Hopscotch (Gb’hop) and the transcription factor STAT (Gb’Stat) were cloned, and RNAi was performed against these genes. Gb’domeRNAi, Gb’hopRNAi and Gb’StatRNAi crickets showed defects in leg regeneration. Blastema expression of Gb’cyclinE was decreased in the Gb’StatRNAi cricket compared with that in the control. Hyperproliferation of blastema cells caused by Gb’fatRNAi or Gb’wartsRNAi was suppressed by RNAi against Gb’Stat. The results suggest that JAK/STAT signalling regulates blastema cell proliferation during leg regeneration.
On-the-Job Learning with Bayesian Decision Theory

Our goal is to deploy a high-accuracy system starting with zero training examples. We consider an on-the-job setting, where as inputs arrive, we use real-time crowd-sourcing to resolve uncertainty where needed and output our prediction when confident. As the model improves over time, the reliance on crowdsourcing queries decreases. We cast our setting as a stochastic game based on Bayesian decision theory, which allows us to balance latency, cost, and accuracy objectives in a principled way. Computing the optimal policy is intractable, so we develop an approximation based on Monte Carlo Tree Search. We tested our approach on three datasets—named-entity recognition, sentiment classification, and image classification. On the NER task we obtained more than an order of magnitude reduction in cost compared to full human annotation, while boosting performance relative to the expert provided labels. We also achieve a 8% F1 improvement over having a single human label the whole set, and a 28% F1 improvement over online learning.
A Two-Component Enhancer-Inhibitor Transposon Mutagenesis System for Functional Analysis of the Arabidopsis Genome

A modified Enhancer-Inhibitor transposon system was used to generate a series of mutant lines by single-seed descent such that multiple I insertions occurred per plant. The distribution of original insertions in the population was assessed by isolating transposon-flanking DNA, and a database of insertion sites was created. Approximately three-quarters of the identified insertion sites show similarity to sequences stored in public databases, which demonstrates the power of this regimen of insertional mutagenesis. To isolate insertions in specific genes, we developed three-dimensional pooling and polymerase chain reaction strategies that we then validated by identifying mutants for the regulator genes APETALA1 and SHOOT MERISTEMLESS. The system then was used to identify inserts in a class of uncharacterized genes involved in lipid biosynthesis; one such insertion conferred a fiddlehead mutant phenotype.
Characteristics of Academic Medical Centers and Ischemic Stroke Outcomes

Background and Purpose— Data supporting the efficacy of stroke center characteristics are limited. Methods— A questionnaire detailing stroke treatment practices was sent to 42 academic medical centers in the University Health Systems Consortium. In-hospital mortality of all emergency department admissions for ischemic stroke at these institutions was evaluated in a database of discharge abstracts during 1997–1999. Institutional characteristics were evaluated as predictors of in-hospital mortality after adjustment for age, sex, race, hospital treatment volume of ischemic stroke, and admission status (emergent, urgent, elective). Length of stay (LOS), total hospital charges, and frequency of tissue plasminogen activator (tPA) administration were evaluated as secondary outcomes. We used a multivariable method called generalized estimating equations, which broadens confidence intervals to adjust for clustering of variables at institutions. Results— Thirty-two institutions completed the questionnaire, and 29 of these were included in the database of discharge abstracts. In-hospital deaths occurred in 758 (7.0%) of the 10 880 ischemic stroke patients admitted through the emergency department. In-hospital deaths were less frequent at hospitals with a vascular neurologist (odds ratio [OR] 0.51; 95% CI, 0.36 to 0.74;P <0.0001) and at those with guidelines stating that only neurologists could administer tPA (OR, 0.65; 95% CI, 0.49 to 0.88;P =0.004). There was a trend toward fewer deaths at hospitals with a dedicated stroke team available by pager (OR, 0.76; 95% CI, 0.56 to 1.04;P =0.09). The presence of a dedicated neurological intensive care unit, stroke unit, and written clinical pathway for stroke were not significantly associated with in-hospital death. LOS was shorter at hospitals with a vascular neurologist (P =0.01). Conclusions— Academic medical centers with a vascular neurologist and those with written guidelines limiting tPA administration to neurologists had lower rates of in-hospital mortality for ischemic stroke patients.
DENSITOMETRIC ANALYSIS OF BODY COMPOSITION: REVISION OF SOME QUANTITATIVE ASSUMPTIONS *

One can trace to Archimedes the idea that in a system consisting of two additive components which are mixed but the densities of which are known ( d l , d 2 ) , the determination of the density of the system ( D ) allows one to calculate the proportional masses of the two components. Let’s denote these components as W1 and W2.S Then, in a system with total weight W = W1 + Wz, the general equation for calculating component W1 expressed as a fraction (w1) of the total body weight is:
In-line water heating system for industrial application

Due to the increase of electricity prices in South Africa and the World, there exists the need for energy efficient water heating systems. The authors of this paper conducted a literature study on existing water heating systems. The study shows that there is a possibility of designing more efficient water heating system at lower cost. An in-line water heating system for industrial applications was designed and tested. Before the system was designed a Finite Element Method analysis of the system was carried out to predict the systems’ pressure and temperature. During a physical model test the energy consumption was measured and compared to a conventional storage water heating system. The designed in-line water heating system is shown to be more energy efficient than the conventional storage water heating system. It also had a variety of advantages such as: size, adaptability to a variety of locations, and robustness.
Topic model-based link community detection with adjustable range of overlapping

Complex networks have attracted much research attentions. Community detection is an important problem in complex network which is useful in a variety of applications such as information propagation, link prediction, recommendations and marketing. In this paper, we focus on discovering overlapping community structure using link partition. We proposed a LDA-based link partition (LBLP) method which can find communities with adjustable range of overlapping. This method employs topic model to detect link partition, which can calculate the community belonging factor for each link. Based on the belonging factor, link partitions with bridge links can be found efficiently. We validate the effectiveness of our solution on both real-world and synthesized networks. The experiment results demonstrate that the approach can find meaningful and relevant link community structure.
Chamfering and Deburring of Back Sides of Micro-Through Holes by EDM

It is difficult to miniaturize tools for chamfering and deburring the back sides of micro-through holes. Therefore, chamfering and deburring by EDM were attempted using tool electrodes with the middle part thinner than the other parts. The tungsten tool electrodes were fabricated by wire electrodischarge grinding, and the back sides of micro-through holes drilled in copper and brass sheets were processed. As a result, chamfering was successfully carried out on the back sides of a microhole with a diameter of 60 μm, a deep hole with an aspect ratio of 5 and a noncircular hole. Furthermore, the chamfering of the front and back sides of a hole using a single tool electrode, round chamfering, deburring and counterboring were possible by adjusting the tool electrode shape. In deburring, the burr was removed with hardly any removal of the edge of the hole. EDM, microhole, chamfering, deburring, counter boring, back side
Ocean wind field mapping from synthetic aperture radar and its application to research and applied problems

APL and the Office of Research and Applications of the National Oceanic and Atmospheric Administration have developed a system to use near-real-time satellite synthetic aperture radar (SAR) data from the Radarsat-1 and Envisat satellites to produce high-resolution (subkilometer) maps of the ocean surface wind field in coastal areas. These maps have shown diverse meteorological phenomena, from gap flows to atmospheric roll vortices. In this article, we describe how SAR can measure wind over the ocean surface and then present examples illustrating how such measurements may be applied. The first application is a scientific one in which SAR wind fields are used to understand the dynamics and spatial variability of barrier jets off the west coast of Canada and the southern coast of Alaska. The second application is a practical one in which high-resolution SAR wind maps are used to determine the optimal placement of offshore wind turbines for generating electric power.
On the Compilation of Plan Constraints and Preferences

State trajectory and preference constraints are the two language features introduced in PDDL3 (Gerevini & Long 2005) for describing benchmarks of the 5th international planning competition. In this work we make existing solver technology applicable to planning with PDDL3 domains by compiling the new constructs back to PDDL2 (Fox & Long 2003). State trajectory constraints are translated into LTL formulae and further to Buchi automata, one for each constraint. These automata are compiled to grounded PDDL and the results are merged with the grounded representation of the original problem. Preference constraints are compiled away using numerical state variables. We provide encouraging experimental results in heuristic search planning.
The effect of bolt tightening methods and sequence on the performance of gasketed bolted flange joint assembly

This paper presents results of the effect of different bolt tightening sequences and methods on the performance of gasketed bolted flange joint using nonlinear finite element analysis. Bolt preload scatter due to elastic interactions, flange stress variation and bolt bending due to flange rotation and gasket contact stress variation is difficult to eliminate in torque control method i.e. tightening one bolt at a time. Although stretch control method (tightening more than one bolt at time) eradicates the bolt preload scatter, flange stress variation is relatively high. Flange joint`s performance is compared to establish relative merits and demerits of both the methods and different bolt tightening sequences.
A query calculus for spatio-temporal object databases

The development of any comprehensive proposal for spatio-temporal databases involves significant extensions to many aspects of a non-spatio-temporal architecture. One aspect that has received less attention than most is the development of a query calculus that can be used to provide a semantics for spatio-temporal queries and underpin an effective query optimization and evaluation framework. We show how a query calculus for spatio-temporal object databases that builds upon the monoid calculus proposed by Fegaras and Maier (2000) for ODMG-compliant database systems can be developed. The paper shows how an extension of the ODMG type system with spatial and temporal types can be accommodated into the monoid approach. It uses several queries over historical (possibly spatial) data to illustrate how, by mapping them into monoid comprehensions, the way is open for the application of a logical optimizer based on the normalization algorithm proposed by Fegaras and Maier.
Selecting Vertical Handover Candidates in WLAN Hotspots

Future wireless networks will consist of multiple heteroge neous access technologies such as UMTS, WLAN, and WiMax. These technologies differ greatly regardi ng medium access scheme, network capacity, QoS support, choice of data rates, and other vario us parameters such as power consumption and AAA aspects. In the literature, different network acces s selection and handover strategies have been discussed in order to maximize the utilization for such a heterogeneous network. Thereby, it is still an open issue how to select ”inefficient” mobiles as v ertical handover candidates. This work presents a novel scheme for the selection of handover candid ates in WLAN hotspots. After discussing the design rationale of the decision metric, simulation stu dies show the impact of single and multiple handovers on remaining users in the cell.
Discoidin Domain Receptor 1 Tyrosine Kinase Has an Essential Role in Mammary Gland Development

ABSTRACT Various types of collagen have been identified as potential ligands for the two mammalian discoidin domain receptor tyrosine kinases, DDR1 and DDR2. Here, we used a recombinant fusion protein between the extracellular domain of DDR1 and alkaline phosphatase to detect specific receptor binding sites during mouse development. Major sites of DDR1-binding activity, indicative of ligand expression, were found in skeletal bones, the skin, and the urogenital tract. Ligand expression in the uterus during implantation and in the mammary gland during pregnancy colocalized with the expression of the DDR1 receptor. The generation of DDR1-null mice by gene targeting yielded homozygous mutant animals that were viable but smaller in size than control littermates. The majority of mutant females were unable to bear offspring due to a lack of proper blastocyst implantation into the uterine wall. When implantation did occur, the mutant females were unable to lactate. Histological analysis showed that the alveolar epithelium failed to secrete milk proteins into the lumen of the mammary gland. The lactational defect appears to be caused by hyperproliferation and abnormal branching of mammary ducts. These results suggest that DDR1 is a key mediator of the stromal-epithelial interaction during ductal morphogenesis in the mammary gland.
Joint latent topic models for text and citations

In this work, we address the problem of joint modeling of text and citations in the topic modeling framework. We present two different models called the Pairwise-Link-LDA and the Link-PLSA-LDA models. The Pairwise-Link-LDA model combines the ideas of LDA [4] and Mixed Membership Block Stochastic Models [1] and allows modeling arbitrary link structure. However, the model is computationally expensive, since it involves modeling the presence or absence of a citation (link) between every pair of documents. The second model solves this problem by assuming that the link structure is a bipartite graph. As the name indicates, Link-PLSA-LDA model combines the LDA and PLSA models into a single graphical model. Our experiments on a subset of Citeseer data show that both these models are able to predict unseen data better than the baseline model of Erosheva and Lafferty [8], by capturing the notion of topical similarity between the contents of the cited and citing documents. Our experiments on two different data sets on the link prediction task show that the Link-PLSA-LDA model performs the best on the citation prediction task, while also remaining highly scalable. In addition, we also present some interesting visualizations generated by each of the models.
Multiple query optimization based on data prediction in wireless sensor networks

Multiple query optimization is one of the most recent fields in query processing of wireless sensor networks. It is very likely for a network to be queried by multiple users simultaneously while these queries may have many commonalities and overlapping data. The overlapping data includes geographical locations, data acquisition conditions or specified actions in the query plans. Using the traditional techniques, the queries will be executed independently and execution of redundant and repetitious operations by sensor nodes leads to energy wastage in the sensor network. Therefore, it is possible to prevent the network from consuming too much energy, by applying multiple query optimization methods. In this work, a prediction based component is used for making decisions about the way of merging queries, in environment monitoring applications. Simulation results demonstrate a considerable reduction of transmitted messages and energy consumption in wireless sensor networks.
Synthesis and Characterization of Silicon Oxycarbide Derived Nanocomposites Obtained through Ceramic Processing of TEOS/PDMS Preceramic Materials

Bulk silicon oxycarbide derived ceramic nanocomposites have been prepared by the application of the conventional ceramic processing to preceramic materials. Tetraethylortosilicate/ polydimethylsiloxane preceramic materials obtained by sol-gel process were thermally treated and attrition milled to 4 micrometers. Subsequently, the preceramic powders were pyrolized at 1100 °C to obtain silicon oxycarbide powders that were pressed and sintered at 1550 °C up to 16 hours. Silicon oxycarbide glasses obtained at 1100 °C from pyrolysis of preceramic materials consist of a Si-O-C network and a carbon like graphite phase well dispersed. At annealing temperatures higher than 1100°C silicon oxycarbide glasses undergo a rearrangement which involves a phase separation to silica and silicon carbide and a segregation of carbon like graphite phase. At these temperatures the material can be considered as a glassy matrix nanocomposite. At temperatures higher than 1500 °C the carbothermal reduction occurs with the consumption of both silica and free carbon phase. However, the nanocomposite structure is maintained but with different constituents. The silicon oxycarbide glasses obtained at 1100 °C are amorphous. However, as a result of all involving processes taken place during the ceramic process, the nanocomposites formed at 1550 °C comprise a silica matrix and nanodomains of carbon like graphite and silicon carbide both of them displaying an incipient crystallization. Structure and crystalline size evolution, from preceramic materials to silicon oxycarbide derived nanocomposites, have been determined by FT-IR and Raman spectroscopies, XRD and 29Si-MASNMR.
Remote Sensing of Ocean Oil-Spill Pollution

Oil spills on the sea surface are observed relatively often. Pollution due to either accidents or deliberate oily discharges from ships represents a serious threat to the marine environment. Operational oil spill monitoring is currently done using a combination of satellite monitoring and aircraft surveillance. The combined use of satellite-based synthetic aperture radar (SAR) images and aircraft surveillance flights is a cost-effective way to monitor oil spills in large ocean areas and catch the polluters. SAR images enable covering large areas, but aircraft observations are needed to prosecute the polluter, and in certain cases to verity the oil spill. Traditionally, oil spill detection is based on single polarization SAR images. Oil spills can be discriminated from look-alikes based on a set of features describing the contrast, shape, homogeneity, source, and surroundings of the slick. Good performance is reported for single-polarization oil spill detection, but in certain cases the oil slicks cannot be discriminated from biogenic films. In the recent years, a number of studies have shown that polarimetric SAR can improve the discrimination between oil slicks and biogenic films. Several features computed from dual-pol or quad-pol images have been proposed. These include both quad-pol features like polarimetric entropy and anisotropy, mean scattering angle, polarimetric span, conformity coefficient, as well as the dual-pol features standard deviation of the copolarized phase difference and the copolarized correlation coefficient. As dual-pol SAR imagery is now available on a regular basis from Cosmo Skymed and TerraSAR-X, and quad-pol data are available from RADARSAT-2, polarimetric SAR can now be utilized on a more regular basis. Optical data from sensors like Aqua MODIS and ENVISAT MERIS can be a useful supplement under certain cloud-free conditions.
Image Super-Resolution via Sparse Bayesian Modeling of Natural Images

Image super-resolution (SR) is one of the long-standing and active topics in image processing community. A large body of works for image super resolution formulate the problem with Bayesian modeling techniques and then obtain its Maximum-A-Posteriori (MAP) solution, which actually boils down to a regularized regression task over separable regularization term. Although straightforward, this approach cannot exploit the full potential offered by the probabilistic modeling, as only the posterior mode is sought. Also, the separable property of the regularization term can not capture any correlations between the sparse coefficients, which sacrifices much on its modeling accuracy. We propose a Bayesian image SR algorithm via sparse modeling of natural images. The sparsity property of the latent high resolution image is exploited by introducing latent variables into the high-order Markov Random Field (MRF) which capture the content adaptive variance by pixel-wise adaptation. The high-resolution image is estimated via Empirical Bayesian estimation scheme, which is substantially faster than our previous approach based on Markov Chain Monte Carlo sampling [1]. It is shown that the actual cost function for the proposed approach actually incorporates a non-factorial regularization term over the sparse coefficients. Experimental results indicate that the proposed method can generate competitive or better results than \emph{state-of-the-art} SR algorithms.
Fundamental frequency estimation based on mean values

Frequency estimation is an important subject of research in different research areas, such as wireless communication, acoustic and speech processing, sonar and radar measurements. Currently there are available methods that use time domain and frequency domain analysis to detect the frequency of a signal. Within this paper a new time domain method is presented, which analyses the mean values of data segments of the investigated signal. The algorithm doesn't require complex operations and gives good results with only two periods of the investigated signal.
Adapting a Generic Data Synchronisation Framework for YAWL to Access Clinical Information Systems at the Task Level

Based on a generic extensible data access framework (DAF) [10], we devised a domain-specific extension to support interoperability of Yawl workflow cases with hospital information systems (HIS). In the scenario considered, the HIS is the principal system that keeps master data and clinical data of the patient. Data transfer between HIS and the Yawl runtime environment is facilitated via exchange of standardized HL7 messages. The solution presented supports read and write tasklevel synchronization of workflow variables using the patient’s case ID as correlation parameter. A first proof-of-concept has been carried out in a real clinical setting.