Miracle-dz/UniFAR-FTUs huggingface dataset:
Volume-of-Fluid Interface Tracking with Smoothed Surface Stress Methods for Three-Dimensional Flows

Motivated by the need for three-dimensional methods for interface calculations that can deal with topology changes, we describe a numerical scheme, built from a volume-of-fluid interface tracking technique that uses a piecewise-linear interface calculation in each cell. Momentum balance is computed using explicit finite volume/finite differences on a regular cubic grid. Surface tension is implemented by the continuous surface stress or continuous surface force method. Examples and verifications of the method are given by comparing simulations to analytical results and experiments, for sedimenting droplet arrays and capillary waves at finite Reynolds number. In the case of a pinching pendant drop, both three-dimensional and axisymmetric simulations are compared to experiments. Agreement is found both before and after the reconnections.
Energy and Environmental Aspects of Using Corn Stover for Fuel Ethanol

Corn stover is the residue that is left behind after corn grain harvest. We have constructed a life‐cycle model that describes collecting corn stover in the state of Iowa, in the Midwest of the United States, for the production and use of a fuel mixture consisting of 85% ethanol/15% gasoline (known as “E85”) in a flexible‐fuel light‐duty vehicle. The model incorporates results from individual models for soil carbon dynamics, soil erosion, agronomics of stover collection and transport, and biocon‐version of stover to ethanol.
Joint inversion of seismic and gravity gradiometry data using Gramian constraints

This paper develops a method of joint inversion of seismic and gravity gradiometry data based on the concept of a Gramian stabilizer, which enforces the linear relationships between the different model parameters and their attributes or transforms. We take into account the existence of empirical linear relationships between the log density and log seismic velocity according to Gardner's equation, and use this relationship in the construction of the corresponding Gramian stabilizer. At the same time, the developed algorithm does not require a priori knowledge of the specific parameters of the correlation between the density and velocity, and instead provides the means to find these parameters from the inversion without actual measurement of the physical properties of the rock samples. The developed algorithm of joint inversion is based on modeling the seismic responses using the integral equation (IE) method. The regularized inversion involves minimization of the Tikhonov parametric functional with a Gramian stabilizer using the regularized conjugate gradient method.
Lessons Learned on Systematic Metric System Development at a Large IT Service Provider

Even though a lot of work was contributed to extend and enhance metric requirements gathering techniques, metric systems are often developed chaotically and a solid dedicated metric system engineering approach is still missing. This paper provides our experiences at developing a metric system together with a large IT service provider and presents an overview on our reference architecture for enterprise measurement infrastructures. Furthermore we give some insights into our metric systems engineering approach which integrates software engineering best practices, modern ideas like micro services, and well established metric related techniques such as GQM.
A Poster-Session Review to Reinforce Course Concepts and Improve Scientific Communication Skills†

A poster-session review is a novel learning activity designed to help students master material, monitor understanding, and practice communicating scientific information. For this strategy, each student is asked to become an expert on a randomly assigned topic from the semester. They create small posters summarizing the most important concepts from their topic and predict likely exam questions from this material. During lecture or lab, students present their work in a poster session and spend time viewing other students’ work. Prior to a comprehensive final exam, undergraduate genetics students participated in a poster-session review and were surveyed about the perceived benefits. They self-reported that the activity helped them understand a genetics topic, prepare for the final exam, and improve their scientific communication skills. A poster-session review can be incorporated into any undergraduate biology course to help achieve these goals.
Effects of screening for postconcussive syndrome (PCS) on PCS symptom self-report and neuropsychological test performance

Abstract Objective: Many non-neurological factors are related to postconcussive syndrome (PCS) symptom report and neuropsychological test performance in mild traumatic brain injury (mTBI). Use of mTBI screening instruments may also contribute to report of PCS symptoms and neuropsychological performance. We examined the impact of randomized PCS screening feedback on PCS symptom report and neuropsychological performance in 152 young adults with no history of mTBI. Method: Participants were 158 undergraduates attending a medium-sized Midwestern university who completed the Postconcussive Syndrome Questionnaire (PCSQ) prior to the study and were randomly assigned to one of three conditions. Participants were either given feedback that they endorsed more symptoms than average, feedback that they endorsed fewer symptoms than average, or neutral information. Participants then completed the PCSQ for a second time as well as the Auditory Verbal Learning Test and Paced Auditory Serial Addition Test. Results: Contrary to expectations, participants receiving feedback that they endorsed more symptoms than average did not endorse more PCSQ symptoms post-feedback than participants in other conditions (p = .12); however, consistent with expectations, they demonstrated poorer verbal learning (p = .005) and delayed recall (p = .04) than participants in the below average feedback condition and reported higher rates of retrospective recall of prior mTBI than participants in the neutral condition (p = .01). Conclusion: Results suggest that feedback from screening measures can influence individuals’ performance and retrospective recall of their personal TBI history. Findings have implications for use of screening measures for PCS in clinical and research settings.
Robust technique of localizing blurred image splicing based on exposing blur type inconsistency

The process of image tampering is nothing but digital process that needs the knowledge good visual creativity as well as image properties. There are different kinds of image tampering such as copy & move, splicing, resize, cropping etc. In this paper we are focusing on blurred image splicing. The image splicing is done for many reasons, the most critical impacts of image splicing related to security and forensic analysis. Therefore it is required to have automated technique which can able to detect and localize the tampered region from input digital image accurately and efficiently. In this paper we are presenting efficient method for localizing blurred image splicing using blur type inconsistency. This method overcomes the limitations of existing framework for blurred image splicing localization depending on partial blur type inconsistency. The proposed method is based on block based processing. Image is divided into overlapping blocks, after that local blur type detection is performed by extracting the features in order to estimate the local blur kernels. The estimation is done using maximum a posteriori (MAP) technique. Using the extracted features, we further do the processing of blocks classification into motion blur (Negative class) and out-of-focus (Positive class) in order to generate invariant blur type regions. Then the technique of fine splicing location is then applied in order to increase the regions boundary precision. To overcome the problem of conflicts between out-of-focus block and motion blur block if they presented in same area, we are using fuzzy logic rules. This can improve the accuracy of slicing detection process as compared to existing.
Diversity analysis on imbalanced data sets by using ensemble models

Many real-world applications have problems when learning from imbalanced data sets, such as medical diagnosis, fraud detection, and text classification. Very few minority class instances cannot provide sufficient information and result in performance degrading greatly. As a good way to improve the classification performance of weak learner, some ensemble-based algorithms have been proposed to solve class imbalance problem. However, it is still not clear that how diversity affects classification performance especially on minority classes, since diversity is one influential factor of ensemble. This paper explores the impact of diversity on each class and overall performance. As the other influential factor, accuracy is also discussed because of the trade-off between diversity and accuracy. Firstly, three popular re-sampling methods are combined into our ensemble model and evaluated for diversity analysis, which includes under-sampling, over-sampling, and SMOTE [1] - a data generation algorithm. Secondly, we experiment not only on two-class tasks, but also those with multiple classes. Thirdly, we improve SMOTE in a novel way for solving multi-class data sets in ensemble model - SMOTEBagging.
Identifying disease candidate genes via large-scale gene network analysis

Gene Regulatory Networks (GRN) provide systematic views of complex living systems, offering reliable and large-scale GRNs to identify disease candidate genes. A reverse engineering technique, Bayesian Model Averaging-based Networks (BMAnet), which ensembles all appropriate linear models to tackle uncertainty in model selection that integrates heterogeneous biological data sets is introduced. Using network evaluation metrics, we compare the networks that are thus identified. The metric 'Random walk with restart (Rwr)' is utilised to search for disease genes. In a simulation our method shows better performance than elastic-net and Gaussian graphical models, but topological quantities vary among the three methods. Using real-data, brain tumour gene expression samples consisting of non-tumour, grade III and grade IV are analysed to estimate networks with a total of 4422 genes. Based on these networks, 169 brain tumour-related candidate genes were identified and some were found to relate to 'wound', 'apoptosis', and 'cell death' processes.
Towards a Resource for Lexical Semantics: A Large German Corpus with Extensive Semantic Annotation

We describe the ongoing construction of a large, semantically annotated corpus resource as reliable basis for the large-scale acquisition of word-semantic information, e.g. the construction of domain-independent lexica. The backbone of the annotation are semantic roles in the frame semantics paradigm. We report experiences and evaluate the annotated data from the first project stage. On this basis, we discuss the problems of vagueness and ambiguity in semantic annotation.
Learning New Sensorimotor Contingencies: Effects of Long-Term Use of Sensory Augmentation on the Brain and Conscious Perception

Theories of embodied cognition propose that perception is shaped by sensory stimuli and by the actions of the organism. Following sensorimotor contingency theory, the mastery of lawful relations between own behavior and resulting changes in sensory signals, called sensorimotor contingencies, is constitutive of conscious perception. Sensorimotor contingency theory predicts that, after training, knowledge relating to new sensorimotor contingencies develops, leading to changes in the activation of sensorimotor systems, and concomitant changes in perception. In the present study, we spell out this hypothesis in detail and investigate whether it is possible to learn new sensorimotor contingencies by sensory augmentation. Specifically, we designed an fMRI compatible sensory augmentation device, the feelSpace belt, which gives orientation information about the direction of magnetic north via vibrotactile stimulation on the waist of participants. In a longitudinal study, participants trained with this belt for seven weeks in natural environment. Our EEG results indicate that training with the belt leads to changes in sleep architecture early in the training phase, compatible with the consolidation of procedural learning as well as increased sensorimotor processing and motor programming. The fMRI results suggest that training entails activity in sensory as well as higher motor centers and brain areas known to be involved in navigation. These neural changes are accompanied with changes in how space and the belt signal are perceived, as well as with increased trust in navigational ability. Thus, our data on physiological processes and subjective experiences are compatible with the hypothesis that new sensorimotor contingencies can be acquired using sensory augmentation.
Multicriteria analysis for evaluation and selecting e-markets in business-to-business e-business

This paper presents a multicriteria analysis approach for evaluating and selecting e-markets in conducting organizational business-to-business e-business. The multi-dimensional nature of the evaluation and selection process for choosing the most appropriate e-market in developing organizational business-to-business e-business is handled in the context of multicriteria analysis, the subjectiveness and imprecision of the human evaluation process is modeled with the use of pairwise comparison represented by linguistic variables approximated by triangular fuzzy numbers. An efficient algorithm is developed for producing a success index for every alternative e-market across all selection criteria, on which the selection decision can be made. An example is presented for demonstrating the applicability of the proposed multicriteria analysis approach for solving the problem of selecting the most appropriate e-market in a specific situation in order to develop a successful business-to-business e-business in an organization.
Localization and tracking with Multipath Exploitation Radar

This paper illustrates the exquisite localization and tracking performance that is obtainable in urban areas with Multipath Exploitation Radar (MER). First, the MER concept is described. Next, Cramer-Rao Lower Bounds of the desired localization and tracking quantities are derived and evaluated with representative parameters. Measured data is then used to demonstrate that this performance can be achieved in practice. Finally, ideas for future MER research are discussed.
A Structural Approach to Contact Recommendations in Online Social Networks

People generally form network ties with those similar to them. However, it is not always easy for users of social media sites to find people to connect with, decreasing the utility of the network for its users. This position paper looks at different ways we can make friend recommendations, or suggest users to follow on the microblogging site Twitter. We examine a number of ways in which similarity can be defined, and the implications of these differences for community-building. People may want different things for friend suggestions, which has implications for both future research and product design.
Structurally Orthogonal Finite Precision Implementation of the Eight Point DCT

This paper presents a novel approach to the finite precision implementation of the eight point discrete cosine transform (DCT). Two multiplierless computational schemes of the plane rotation block are constructed to obtain the transform approximations maintaining orthogonality regardless of their coefficient quantization. This is the main difference with respect to the solutions based on lifting schemes being developed in recent years, characterized by inherent biorthogonality. In our technique, structural orthogonality comes at the cost of a complexity increase. To keep it at a moderate level, we implement rotations effectively using the denormalized lattice and the three-value coordinate rotation digital computer (CORDIC) algorithm with double mu-rotations
Distinct synaptic properties of perisomatic inhibitory cell types and their different modulation by cholinergic receptor activation in the CA3 region of the mouse hippocampus

Perisomatic inhibition originates from three types of GABAergic interneurons in cortical structures, including parvalbumin‐containing fast‐spiking basket cells (FSBCs) and axo‐axonic cells (AACs), as well as cholecystokinin‐expressing regular‐spiking basket cells (RSBCs). These interneurons may have significant impact in various cognitive processes, and are subjects of cholinergic modulation. However, it is largely unknown how cholinergic receptor activation modulates the function of perisomatic inhibitory cells. Therefore, we performed paired recordings from anatomically identified perisomatic interneurons and pyramidal cells in the CA3 region of the mouse hippocampus. We determined the basic properties of unitary inhibitory postsynaptic currents (uIPSCs) and found that they differed among cell types, e.g. GABA released from axon endings of AACs evoked uIPSCs with the largest amplitude and with the longest decay measured at room temperature. RSBCs could also release GABA asynchronously, the magnitude of the release increasing with the discharge frequency of the presynaptic interneuron. Cholinergic receptor activation by carbachol significantly decreased the uIPSC amplitude in all three types of cell pairs, but to different extents. M2‐type muscarinic receptors were responsible for the reduction in uIPSC amplitudes in FSBC– and AAC–pyramidal cell pairs, while an antagonist of CB1 cannabinoid receptors recovered the suppression in RSBC–pyramidal cell pairs. In addition, carbachol suppressed or even eliminated the short‐term depression of uIPSCs in FSBC– and AAC–pyramidal cell pairs in a frequency‐dependent manner. These findings suggest that not only are the basic synaptic properties of perisomatic inhibitory cells distinct, but acetylcholine can differentially control the impact of perisomatic inhibition from different sources.
Physiological Concentrations of Epinephrine Potentiate Thromboxane A2 Release from Platelets in the Isolated Rat Heart

The isolated rat heart perfused with washed platelets was used as a model to examine platelet-vessel wall interactions. Release of prostacyclin and thromboxane A2 was measured, using a cascade of smooth muscle bioassay tissues or radioimmunoassays of the stable hydration products. In hearts perfused with rabbit or human platelets, injection of sodium arachidonate caused release of both prostacyclin and thromboxane A2. In hearts perfused with aspirin-pretreated platelets, arachidonate released only prostacyclin indicating that thromboxane A2 originates largely in the platelets. Infusion of epinephrine (0.6–6 nmol/liter) through the heart potentiated arachi- donate-induced release of thromboxane A2. Similar potentiation of thromboxane A2 release was observed in rat hearts perfused with either rabbit or human platelets, and in rabbit hearts perfused with rabbit platelets. In contrast, when rabbit platelets were infused through an incubation coil of tubing in place of the heart, epinephrine did not alter thromboxane A2 release. There was no significant loss of rabbit platelets on perfusion through rat hearts, and no aggregates were observed in the effluent either before or immediately after arachidonate injections, even in the presence of epinephrine. Thus, potentiation of thromboxane A2 production could not be explained by aggregation. However, it is clear from these studies that physiological concentrations of epinephrine can potentiate thromboxane A2 release from platelets when they are stimulated by arachidonic acid within the heart. This could result from a redirection of arachidonate metabolism to a local potentiating factor in the vessel wall. Potentiation of thromboxane A2 release might contribute to myocardial ischemia associated with platelet activation.
Gaussian-binary restricted Boltzmann machines for modeling natural image statistics

We present a theoretical analysis of Gaussian-binary restricted Boltzmann machines (GRBMs) from the perspective of density models. The key aspect of this analysis is to show that GRBMs can be formulated as a constrained mixture of Gaussians, which gives a much better insight into the model’s capabilities and limitations. We further show that GRBMs are capable of learning meaningful features without using a regularization term and that the results are comparable to those of independent component analysis. This is illustrated for both a two-dimensional blind source separation task and for modeling natural image patches. Our findings exemplify that reported difficulties in training GRBMs are due to the failure of the training algorithm rather than the model itself. Based on our analysis we derive a better training setup and show empirically that it leads to faster and more robust training of GRBMs. Finally, we compare different sampling algorithms for training GRBMs and show that Contrastive Divergence performs better than training methods that use a persistent Markov chain.
International Journal of Recent Trends in Engineering , Vol 2 , No . 3 , November 2009 27 Lossless Compression of a Desktop Image For Transmission

We have presented a desktop image compression algorithm for real-time applications such as remote desktop access by desktop image transmission. The desktop image is called as a complex image, because one 800 X 600 true color image has a size of approximately 1.54 MB with pictures and text. The algorithm is called as group extraction and coding (GEC). Real-time image transmission requires that the compression algorithm should not only achieve high compression ratio, but also have excellent visual quality and low complexity. In the extraction/ separation phase of the complex desktop image, we have separated the blocks into picture and text/graphics blocks by thresholding the number of colors contained in each block. Text/graphics block classes have been compressed by using a wavelet based SPIHT lossless coding algorithm, while picture block classes, by JPEG algorithm. The compressed blocks have been combined to form a single bit stream. Experimental results have shown that the GEC has very low complexity and provides visually excellent lossless quality with very good compression ratios.
Practical and Efficient Organization of a Large Valency Dictionary ∗

This paper describes the design and ongoing construction of a large bilingual valency dictionary. The first half describes the existing dictionary of 16,000 Japanese-English patterns, how it was built, how it is used, and points out some shortcomings. The second half introduces three proposals, originally put forward by Somers (1987) to improve the dictionary by separating the complement/adjunct distinction from the use of case-roles, organizing the case roles in a grid, and making the English and Japanese Lexicons separate entities, linked by informative links.