Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptome Analysis of Red Swamp Crawfish Procambarus clarkii Reveals Genes Involved in Gonadal Development

Background The red swamp crawfish, Procambarus clarkii, has become one of the most economically important cultured species in China. Currently, little is known about the gonadal development of this species. Isolation and characterization of genes are an initial step towards understanding gonadal development of P. clarkii. Results Using the 454 pyrosequencing technology, we obtained a total of 1,134,993 high quality sequence reads from the crawfish testis and ovary libraries. We aimed to identify different genes with a potential role in gonad development. The assembly formed into 22,652 isotigs, distributed by GO analysis across 55 categories in the three ontologies, ‘molecular function’, ‘cellular component’, and ‘biological processes’. Comparative transcript analysis showed that 1,720 isotigs in the ovary were up-regulated and 2138 isotigs were down-regulated. Several gonad development related genes, such as vitellogenin, cyclin B, cyclin-dependent kinases 2, Dmc1 and ubiquitin were identified. Quantitative real-time PCR verified the expression profiles of 14 differentially expressed genes, and confirmed the reliability of the 454 pyrosequencing. Conclusions Our findings provide an archive for future research on gonadal development at a molecular level in P. clarkii and other crustacean. This data will be helpful to develop new ideas for artificial regulation of the reproductive process in crawfish aquaculture.
A New Method of Vulnerability Taxonomy Based on Information Security Attributes

Information security has become the hot issue in the information age. Vulnerabilities existed in information systems threat the information security seriously. Among large number of methods of vulnerability taxonomies, there is not a method on the aspect of information security. A new method of vulnerability taxonomy is proposed based on five attributes of information security, which concludes integrity, availability, confidentiality, controllability and reliability. The proposed method recognizes vulnerabilities in terms of information security, and the feasibility is verified using some common vulnerabilities.
Vehicle-2-vehicle communication channel evaluation using the CVIS platform

The concept of Intelligent Transportation Systems (ITS) presents new research and development challenges in the transportation and ICT (Information and communication technologies) sectors and is currently receiving considerable interest from the research community. Accurate simulation of wireless vehicular communications for large-scale system testing is heavily reliant on the precision of the underlying environmental models. Incorrect assumptions made in these models can lead to erroneous conclusions on the effectiveness of proposed techniques. This paper tries to address this issue in relation to channel modelling in the ITS scenario and presents results from empirical measurements of the IEEE 802.11p communications channel. Utilising prototype CVIS (Cooperative Vehicle-Infrastructure Systems) platform IEEE802.11p equipment, measurement campaigns were carried out in rural, urban and highway scenarios focusing specifically on the Vehicle-to-Vehicle (V2V) communications paradigm. Examining the RSSI and packet loss performance observed during testing, standard matching techniques have been applied in characterising a model of the 802.11p channel for V2V communications in these diverse driving environments. It is shown that a Nakagami matched model is the most accurate fit for the empirical data.
Rising to the Occasion? Youth Political Knowledge and the Voting Age

Voting is a fundamental human right. Yet, individuals that are younger than 18 do typically not have this right since they are considered uninformed. However, recent evidence tentatively suggests that the political knowledge of youths is endogenous to the voting age. I test for the existence of such dynamic adjustments utilizing voting age discontinuities caused by Swedish laws. I employ a regression discontinuity strategy on Swedish register data to estimate the causal effect of early age voting right on political knowledge around age 18. The results do not support the existence of positive causal effects of early age voting right on political knowledge. Thus, we should not expect that 16-year-olds respond by acquiring more political knowledge if they are given the right to vote. This finding weakens the case for a lowering of the voting age from 18 to 16.
Lithium Ameliorates Nucleus Accumbens Phase-Signaling Dysfunction in a Genetic Mouse Model of Mania

Polymorphisms in circadian genes such as CLOCK convey risk for bipolar disorder. While studies have begun to elucidate the molecular mechanism whereby disruption of Clock alters cellular function within mesolimbic brain regions, little remains known about how these changes alter gross neural circuit function and generate mania-like behaviors in Clock-Δ19 mice. Here we show that the phasic entrainment of nucleus accumbens (NAC) low-gamma (30–55 Hz) oscillations to delta (1–4 Hz) oscillations is negatively correlated with the extent to which wild-type (WT) mice explore a novel environment. Clock-Δ19 mice, which display hyperactivity in the novel environment, exhibit profound deficits in low-gamma and NAC single-neuron phase coupling. We also demonstrate that NAC neurons in Clock-Δ19 mice display complex changes in dendritic morphology and reduced GluR1 expression compared to those observed in WT littermates. Chronic lithium treatment ameliorated several of these neurophysiological deficits and suppressed exploratory drive in the mutants. These results demonstrate that disruptions of Clock gene function are sufficient to promote alterations in NAC microcircuits, and raise the hypothesis that dysfunctional NAC phase signaling may contribute to the mania-like behavioral manifestations that result from diminished circadian gene function.
The Application of the Technique of 2D Fragments Stitching Based on Outline Feature in Rejoining Oracle Bones

Based on the edge feature extraction of oracle bones, two-dimensional fragments contour matching algorithm based on angular sequence is proposed to obtain the most likely njugating outcome between two pieces. The algorithm is combined with the multi-scale space, which not only solves the sharp corner problem of oracle bone conjugating effectively, also improves the computational efficiency and accuracy of matching fragments. The algorithm produced better results in oracle bones conjugating.
A NOVEL SOLUTION FOR HEALTH INFORMATICS

As organizations grow larger and more distributed, the problems of maintaining corporate awareness and effective communication channels escalate. The clinical domain poses particular challenges to maintaining good corporate communications because users have limited time to access information and often have negative technology perceptions. This paper highlights how a screen saver application, initially designed to increase privacy and security, developed into a new communication medium improving corporate communication across the organization. An ethnographic study of the application within a hospital setting, analyzed using grounded theory methods, details the iterative and organic development of the design through 'community of practice' involvement. This application and the evolutionary process through which it was developed were found to not only increase awareness of resources, activities and hospital changes but also positively influence users' perceptions of, involvement in and ownership of general IT developments. User involvement also raised the importance, for the designers, of application usability, quality and aesthetics.
Postprandial carbohydrate metabolism in healthy subjects and those with type 2 diabetes fed starches with slow and rapid hydrolysis rates determined in vitro

The objective of the present study was to investigate the effects of starches with differing rates of hydrolysis on exposure to pancreatin in vitro on postprandial carbohydrate metabolism in healthy subjects and in subjects with type 2 diabetes. Two test starches, prepared from uncooked native granular starch products, and naturally enriched with 13C, were consumed in a randomized crossover design by eight healthy and thirteen type 2 diabetic subjects. One starch was characterized in vitro as being rapidly hydrolysed (R, 94% after 180min), and the other was more slowly hydrolysed (S, 51% after 180min). Each subject consumed 50g of each test starch. In addition, the type 2 diabetic subjects consumed 89·7g of the S starch on a separate occasion. Blood samples were taken at 10min intervals for 3h, and at 20min intervals for a further 3h during a 6h postprandial period. Breath 13CO2 enrichment was measured at the same time points, and indirect calorimetry was performed for seven 20min sessions immediately before and during the 6h postprandial period. With the R starch, plasma glucose concentrations and serum insulin concentrations rose faster and the maximum glucose change was approximately 1·8 times that for the S starch, averaged across both subject groups. The areas under the curves for glucose and insulin were, respectively, 1·7 and 1·8 times higher for the R starch compared with the S starch, averaged across both subject groups. The rate of 13CO2 output and the proportion of 13C recovered in breath after consumption of the R starch was similar for both subject groups. The results provide evidence that starches which have different rates of hydrolysis in vitro result in different patterns of glycaemia and insulinaemia in both healthy adults and in diet-controlled type 2 diabetic subjects. Data from the hydrolysis of novel starch products in vitro, therefore, are useful in predicting glycaemic responses in vivo.
Identification of confusion and surprise in spoken dialog using prosodic features

Sensitivity to a user’s emotional state offers promise in improving the state of the art in spoken dialog systems. In this work, we attempt to detect the speaker’s states of confusion and surprise using prosodic features from his/her utterances. We have collected a corpus of utterances in realistic settings using an experimental methodology aimed at eliciting confusion and surprise from users. Classification experiments have yielded up to a 27.2% improvement over baseline performance using F0 and power features. We achieved the greatest success at classification of emotions that were most successfully elicited. Index Terms: emotion detection, realistic settings, data collection methodology, self-report
Formation control of mobile robots using decentralized nonlinear model predictive control

This paper presents a distributed nonlinear model predictive controller (NMPC) for formation control of a group of omnidirectional mobile robots. In this approach the controllers are distributed to the agents, and the terms of coupling allow the use of fixed and time-varying formations. The path following problem is expressed through a dynamic model of the robot's state errors, and the coordination problem is solved through adjustments in the robots' speeds combined with the path update rate for each robot. Experimental results are provided to demonstrate the performance of the proposed control strategy using real and virtual robots.
Exploiting Web Browsing Activities for User Needs Identification

Browsing sessions are rich in elements useful to build profiles of user interests, but at the same time HTML pages include noise data, such as ads and navigation menus. Moreover, pages might cover several different topics. For these reasons they are often ignored in personalized approaches. We propose a novel approach for implicitly recognizing valuable text descriptions of current user needs based on the implicit feedback revealed through web browsing interactions.
Magnetic field amplification in cold dark matter anisotropic collapse

We use the Zel’dovich approximation to analyse the amplification of magnetic fields in gravitational collapse of cold dark matter during the mildly nonlinear regime, and identify two key features. First, the anisotropy of collapse effectively eliminates one of the magnetic components, confining the field in the pancake plane. Second, in agreement with recent numerical simulations, we find that the shear anisotropy can amplify the magnetic field well beyond the isotropic case. Our results suggest that the magnetic strengths observed in spiral and disk galaxies today might have originated from seeds considerably weaker than previous estimates.
Research on Model Checking Technology of UML

To checking the correctness of UML models, we integrate UML and Model Checking effectually in software development. At the beginning, we select class diagram, state diagram and collaboration diagram from UML models to define a system description model, verification model and system constraints. Following, based on the homomorphic mapping method, this paper proposes a method for transforming the UML verification model to PROMELA model, uses the hierarchical automata to describe the state machine and defines its formal semantic, and then verifies the correctness of models with SPIN. Finally, we conduct research on an example, and the experiment result proves the correctness of this method.
Supportive Accountability: A Model for Providing Human Support to Enhance Adherence to eHealth Interventions

The effectiveness of and adherence to eHealth interventions is enhanced by human support. However, human support has largely not been manualized and has usually not been guided by clear models. The objective of this paper is to develop a clear theoretical model, based on relevant empirical literature, that can guide research into human support components of eHealth interventions. A review of the literature revealed little relevant information from clinical sciences. Applicable literature was drawn primarily from organizational psychology, motivation theory, and computer-mediated communication (CMC) research. We have developed a model, referred to as “Supportive Accountability. ” We argue that human support increases adherence through accountability to a coach who is seen as trustworthy, benevolent, and having expertise. Accountability should involve clear, process-oriented expectations that the patient is involved in determining. Reciprocity in the relationship, through which the patient derives clear benefits, should be explicit. The effect of accountability may be moderated by patient motivation. The more intrinsically motivated patients are, the less support they likely require. The process of support is also mediated by the communications medium (eg, telephone, instant messaging, email). Different communications media each have their own potential benefits and disadvantages. We discuss the specific components of accountability, motivation, and CMC medium in detail. The proposed model is a first step toward understanding how human support enhances adherence to eHealth interventions. Each component of the proposed model is a testable hypothesis. As we develop viable human support models, these should be manualized to facilitate dissemination.
Approximate statistical properties of reconstructed images using model-based bootstrapping

In tomographic image reconstructions, it is often necessary to compute certain statistics of a reconstructed image. These quantities can be used, for example, to analyze the noise properties of a reconstruction. This paper introduces the model-based bootstrapping method to approximate mean and variance-covariance matrix of a reconstruction. This approximation is versatile and can be implemented in different tomographic reconstructions, such as emission and transmission tomographies. This paper also considers the possibility of computational load reduction by a simultaneous multiplicative iterative reconstruction algorithm.
Use of the Technical Field-Oriented User Dictionaries

Japio performs various patent-related translation businesses, and owns the original patent-documentderived bilingual technical term database (Japio Terminology Database) to be served for the translators. Currently the database contains more than 780,000 J-E technical terms. To adapt the database to the Patent Translation Task, Japio compiled machine translation dictionaries from it. 34 technical field-oriented dictionaries were created based on Japio’s original technical fields. Terms are evaluated and selected according to their actual frequency in the bilingual patent document corpus of concerned technical field.
On the Use of Stochastic Hessian Information in Unconstrained Optimization

This paper describes how to incorporate stochastic curvature information in a NewtonCG method and in a limited memory quasi-Newton method for large scale optimization. The motivation for this work stems from statistical learning and stochastic optimization applications in which the objective function is the sum of a very large number of loss terms, and can be evaluated with a varying degree of precision. Curvature information is incorporated into two proposed semi-stochastic algorithms via a matrix-free conjugate gradient iteration, which is applied to a system using a sampled (or stochastic) Hessian based on a small batch size. The efficiency of the proposed methods is illustrated using a machine learning application involving speech recognition. ∗Department of Computer Science, University of Colorado, Boulder, CO, USA. This author was supported by National Science Foundation grant CMMI 0728190 and Department of Energy grant DE-SC0001774. †Department of Industrial Engineering and Management Sciences, Northwestern University. This author was supported by an NSERC fellowship and a grant from Google Inc. ‡Google Research. §Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA. This author was supported by National Science Foundation grant DMS-0810213 and by Department of Energy grant DE-FG02-87ER25047-A004.
Robust Matching Cost Function for Stereo Correspondence Using Matching by Tone Mapping and Adaptive Orthogonal Integral Image

Real-world stereo images are inevitably affected by radiometric differences, including variations in exposure, vignetting, lighting, and noise. Stereo images with severe radiometric distortion can have large radiometric differences and include locally nonlinear changes. In this paper, we first introduce an adaptive orthogonal integral image, which is an improved version of an orthogonal integral image. After that, based on matching by tone mapping and the adaptive orthogonal integral image, we propose a robust and accurate matching cost function that can tolerate locally nonlinear intensity distortion. By using the adaptive orthogonal integral image, the proposed matching cost function can adaptively construct different support regions of arbitrary shapes and sizes for different pixels in the reference image, so it can operate robustly within object boundaries. Furthermore, we develop techniques to automatically estimate the values of the parameters of our proposed function. We conduct experiments using the proposed matching cost function and compare it with functions employing the census transform, supporting local binary pattern, and adaptive normalized cross correlation, as well as a mutual information-based matching cost function using different stereo data sets. By using the adaptive orthogonal integral image, the proposed matching cost function reduces the error from 21.51% to 15.73% in the Middlebury data set, and from 15.9% to 10.85% in the Kitti data set, as compared with using the orthogonal integral image. The experimental results indicate that the proposed matching cost function is superior to the state-of-the-art matching cost functions under radiometric variation.
Automatic image annotation combining SVMS and KNN algorithm

Automatic image annotation has emerged as an important but challenging task in many areas, including web image retrieval, image understanding, Internet data filtering, etc. We consider image annotation task as a Multi-Label Classification (MLC) problem, in which each image can be associated with more than one class. Support Vector Machine (SVMs) performs well in many areas, however it cannot be used to solve the MLC problem directly. While k-Nearest Neighbor algorithm (KNN) has a good performance in MLC problem, an obvious flaw of KNN is its high computational complexity. In this paper, to solve the MLC problem in image annotation with lower computational complexity, we present an image annotation framework combining Support Vector Machine (SVMs) and k-Nearest Neighbor algorithm (KNN). Multiple kinds of features are combined in our method, including edge direction histogram (EDH), gray level co-occurrence matrix (GLCM) and area weighted HSV color histogram. In our system, each image has one label and several tags. Top m possible labels from SVMs result will be as the input of KNN algorithm. Experiments conducted on the typical Corel dataset shows the scheme has obtained higher accuracy.
Service-oriented control system for a differential wheeled robot

Double-wheeled robot is a classical yet populair architecture for a mobile robot, and many algorithms are created to control such robots. The main goal of the paper is to decompose some of this algorithms into services in service-oriented system with an original messaging model.We describe data types that are common for robotics control, and ways to handle them in . NET Framework. We bring a list of various services’ types, and each of them can be implemented in several ways and linked with other services in order to create flexible and highly adjustable control system. Service-oriented systems are scalable, can be distributed on many computers, and provides huge debugging capacities. The service-oriented representation is also very useful when teaching robotics, because each service is relatively simple, and therefore algorithms can be presented to students gradually. In this paper, we also focus on a particular services’ types, which provides the correction of the robot by the feedback, decribe the original algorithm to do so, and compare it with several others.
Robustness and Precision Analysis in Map-Matching based Mobile Robot Self-Localization

In this paper an accuracy analysis is presented for a localization algorithm based on maps correspondence. Initially t he algorithm was developed by Martin Lauer [1], for robotic soccer purposes, a nd it has now been adapted to work on indoor robots localization, using walls and other known fixed objects as references. Infrared range sensors (IR) for low cost applications and Laser Scan Range Finder (LS) for other applica tions were used in our approach and compared experimentally. Precision and robustness analysis was made using increasing amount of laser points (which simulates a varying number of sensors) and results were compared to usi ng similar number of IRs. Several tests were conducted with a real robot alon g a well defined trajectory, following a line previously painted on the floor. V isual markers were placed along the line allowing to keep track of the robot’ s real position with high precision. The experimental results achieved showed that the implemented algorithm works well with a variety of sensors. The results also show that the scan laser range finder is by far the best type of sensor to measure the range of objects indoors. Using only few points the algorith m achieved good results and demonstrated a very high robustness rate and precis ion.