Miracle-dz/UniFAR-FTUs huggingface dataset:
Materials and Methods Som Text Figs. S1 to S6 References Movies S1 to S5 Inferential Structure Determination

of its circular swimming path. These particles move randomly with an apparent diffusion coefficient of D 0 9.0 T 2.0 mm 2 /s, measured for isolated spermatozoa. A short-range pairwise attraction, arising from the hydrodynamic forces leading to the observed synchronization (20), and a longer range repulsion , which could be of steric or hydro-dynamic origin (21), are assumed (Fig. 4D). Although one cannot describe circular flow by a potential (22), the important features of the observed pattern are captured by our model. Stochastic simulations of this model (SOM text) also revealed two regimes: a random distribution of particles at low densities with a transition toward a hexagonal array of clusters at a critical particle density (Fig. 4E). Assigning to each particle a spermatozoon circling around that position, we generated simulated movies (3) mimicking the experimental observation (Fig. 4F versus Fig. 1B). Moreover, the order parameter c computed for different simulated sperm densities agreed with the experimentally observed dependency (Fig. 4C). Our numerical results were further supported by a 1D mean-field analysis (SOM text), which indicated the existence of a supercritical pitchfork bifurcation at a critical sperm density (23). This critical density was proportional to the interaction strength and inversely proportional to the diffusion coefficient, the latter being associated with the noise in the system. This analysis demonstrates how the activity of biological processes can be regulated by critical points or bifurcations. For example, ciliary metachronal waves (16, 24) might be switched on and off by small physiologically controlled changes of the activity of the individual cilia, thereby tuning the critical density for the onset of the metachronal wave. The only free parameter in our model was the ratio of the maximum interaction potential to the drag coefficient, V 0 /g 0 5 mm 2 /s, which was chosen to match the critical density (Fig. 4C). This allowed us to estimate the interaction force between two spermatozoa F int 0 kgrad(V)k 0 (V 0 /g) Â g/R È 0.03 pN (using R 0 13 mm and g 0 0.07 mNIs/m from above). This force is about 1% of the forward propulsion force of spermatozoa F for È 5 pN (25). Although this hydrodynamic interaction force is smaller than typical adhesion forces involved in sperm cooperation (26), it is evidently large enough to coordinate the cells and to regulate large-scale pattern formation in the absence of chemical signals (27). and members …
Cost-Sensitive Learning via Priority Sampling to Improve the Return on Marketing and CRM Investment

Because of the unbalanced class and skewed profit distribution in customer purchase data, the unknown and variant costs of false negative errors are a common problem for predicting the high-value customers in marketing operations. Incorporating cost-sensitive learning into forecasting models can improve the return on investment under resource constraint. This study proposes a cost-sensitive learning algorithm via priority sampling that gives greater weight to the high-value customers. We apply the method to three data sets and compare its performance with that of competing solutions. The results suggest that priority sampling compares favorably with the alternative methods in augmenting profitability. The learning algorithm can be implemented in decision support systems to assist marketing operations and to strengthen the strategic competitiveness of organizations.
Energy Based Quantization for Image Compression Using Contourlet Transform

This paper presents a new compression technique based on Contourlet Transform (CT) and energy based quantization. Double filter bank structure is used in CT. The Laplacian Pyramid (LP) is used to capture the point discontinuities, and then followed by a Directional Filter Bank (DFB) to link point discontinuities. The coefficients of down sampled low pass version of LP decomposed image are re-ordered in a pre-determined manner and prediction algorithm is used to reduce entropy (bits/pixel). In addition, the coefficients of CT are quantized based on the energy in the particular band. The superiority of proposed algorithm to JPEG is observed in terms of reduced blocking artifacts. The results are also compared with wavelet transform (WT). Superiority of CT to WT is observed when the image contains more contours.
Quantitative Evaluation of Single and Multicore Real-Time DVFS Schedulers in Linux [ TechnicalReport ]

We report on our experience in implementing and evaluating nine, state-of-the-art single and multicore real-time dynamic voltage and frequency scaling (DVFS) schedulers on an embedded Linux platform. The algorithms include CC-EDF, LA-EDF, DRA, AGR, CVFS, and DR, among others, and the platform is a dual-core ARM Cortex-A9 MPCore processor/PandaBoard, running a real-time Linux kernel. Our evaluations reveal the effectiveness of the algorithms’ power savings. However, due to non-negligible scheduling and voltage/frequency transition overheads, non ideal time accounting, and our integrated Linux scheduling environment, their timeliness behaviors deviate from the theoretical. We propose solutions and identify reduced, schedulable total task utilization bounds.
Road following with blind crawling robot

In this paper, we consider road following to autonomously navigate a mobile robot through an environment while keeping the robot on the specified road. Contrary to existing approaches based on a forward looking camera, we consider the problem for a technically blind walking robot without any exteroceptive sensors. The only feedback considered is an estimation of tactile information that is determined from the robot servo drives. The proposed control law is based on an on-line classification of the previously learned terrains which is utilized to identify a situation when a robot starts to crawl off the desired road terrain. The controller steers the robot to keep its body and all its legs on the road while crawling forward with a constant velocity. The experimental results support feasibility of the proposed minimalistic approach and allows the robot to autonomously navigate in an outdoor environment and follow urban park pathways and avoid off-road parts.
Publikation II

(2000) Purification of recombinant hydantoinase and L-N-carbamoylase from Arthrobacter aurescens expressed in E. coli: Comparison of wild-type and genetically modified proteins. J. Chromatogr. B. Abstract Two enzymes, hydantoinase (HyuH) and L-N-carbamoylase (HyuC), are required for the biocatalytic production of natural and unnatural, optically pure L-amino acids starting from D,L-5-monosubstituted hydantoins using the so called 'hydantoinase-method'. For the preparation of immobilized enzymes, which omit several drawbacks of whole cell biocatalysts, purified or at least enriched HyuH and HyuC have to be provided. In order to simplify existing purification protocols several genetically modified derivatives of HyuH and HyuC from Arthrobacter aurescens DSM 3747 have been cloned and expressed in E. coli. A fusion protein consisting of maltose-binding protein (MalE) and HyuH resulted in an enhanced solubility of the hydantoinase, which easily forms inclusion bodies. On the other hand the fusion protein could easily be purified with high yield (76%) by just one chromatographic step (amylose resin) and the complex purification protocol of the wild-type enzyme could therefore be simplified and shortened significantly. Interestingly, the specific activity of the MalE-HyuH fusion protein was as high as the one of the wild-type enzyme despite the molecular mass was doubled. A second modification of HyuH carrying a histidine-tag was efficiently bound to a metal affinity matrix but inactivated completely during elution from the column at either low pH or in the presence of imidazole. In the case of HyuC an aspartate-tag has been added to the biocatalyst to allow an integrated purification-immobilization procedure since this enzyme is immobilized efficiently only via its carboxylic groups. The diminished isoelectric point of the Asp-tagged HyuC resulted in a simplified purification procedure. Compared to the wild-type enzyme expressed in E. coli HyuC-Asp 6 was shifted off the elution range of the contaminating proteins and higher purification factors were obtained even in the capturing step. In contrast to HyuH, it was possible to purify a L-N-carbamoylase carrying a histidine-tag to apparent homogeneity using immobilized metal affinity chromatography. Therefore, the existing three step purification protocol was reduced to one chromatographic step and the yield of this relatively unstable protein enhanced remarkably.
Sketchy Shade Strokes

As a contribution to the world of Non-Photorealistic Rendering, we present an algorithm for rendering sketch based shade strokes on a 3dimensional polygon model. Animation is an important component of our scheme, thus a lot of our work has been put into the construction of a robust temporally coherent rendering system. This has been made possible by the use of a sophisticated Level of Detail structure. The model is analyzed while read into the program, extracting information such as curvature and principle directions, in order to present the model in a trustworthy manner and to bring out the features of the model. We have chosen to trade refined but few strokes for numerous expressive strokes, which produces an attractive overall picture. The algorithm is extendible in many directions and a few of these are discussed in this paper.
Topical Promethazine Side Effects: Our Experience and Review of the Literature

Promethazine hydrochloride is a first-generation H1 receptor antagonist, antihistamine, and antiemetic medication that can also have strong sedative effects. The apparent ability of topical H1r/2r antagonists to target epidermal H1/2r was translated into increased efficacy in the treatment of inflammatory dermatoses, likely due to decreased inflammation and enhanced barrier function.
Usability for Mobile Commerce Across Multiple Form Factors

Current research on usability for mobile commerce has focused on single platforms and very limited aspects of commerce activities. We conducted an exploratory study to examine usability problems and to identify potential research questions concerning wireless solutions for consumer e-commerce. By using cognitive walkthrough and heuristic evaluation methods, we evaluated the usability of ten wireless sites in three platforms: WAP-enabled mobile phones, Palm OS based wireless PDAs, and Pocket PCs running Windows CE operating systems. This article discusses our usability findings pertaining to user tasks, content presentation, search, navigation systems, and the design constraints imposed by form factors. It also provides design guidelines based on our study and examines research implications for wireless interface design.
The Anthropomimetic Principle

Most humanoid robots are essentially conventional robots that fit within the morphological envelope of a human. However, for robots that are intended to help in the understanding of human cognition and action, a much higher level of biological inspiration may be necessary. This paper sets out some of the requirements for an anthropomimetic robot – one which imitates not just the human form, but also the biological structures and functions that enable and constrain perception and action – and describes the design, construction, and initial performance of such a robot. The findings to date indicate that the combination of a realistic skeleton, series-elastic actuators, and a foveated vision system gives a unique insight into the problems the human brain has to solve in the areas of perception and action.
AN FUZZY NEURAL APPROACH FOR MEDICAL IMAGE RETRIEVAL

Image retrieval based on a query image is necessary for effective and efficient use the information that is stored in medical image databases. Medical Image Retrieval is difficult as not only the localization and directionality of human visual system is to be considered but also the pathological condition. Image identification and segmentation for feature extraction pose a challenge to image retrieval process. Challenges posed include large number of images to be processed for the image retrieval and identifying the region of interest automatically to optimize the search. In this study, we propose a novel image segmentation algorithm Fuzzy Edge Detection and Segmentation (FEDS). The proposed FEDS algorithm is tested on medical images and for classification of images, a bell fuzzy multilayer perceptron is proposed. The proposed neural network Bell Fuzzy Multi Layer Perceptron (BF-MLP) Neural network is constructed by introducing a fuzzy logic in hidden layer with the sugeno model and bell function. The proposed neural network consists of two layers with the first layer being a tanh activation function and the second layer containing the bell fuzzy activation function. The proposed FEDS method was implemented using Matlab and Modelsim. A total of 44 images were considered with three class labels. The edge obtained for which segmentation is done using the proposed segmentation algorithm. The proposed BF-MLP neural network algorithm was implemented using Visual Studio and the classification accuracy compared with MLP Neural Network with sigmoid activation function. In this study, a fuzzy segmentation algorithm and a fuzzy classification algorithm is proposed to improve the medical image retrieval accuracy. The proposed segmentation algorithm, Fuzzy Edge Detection and Segmentation (FEDS), was implemented using Matlab and features were extracted using Fast Hartley Transform (FHT). The extracted features were used to train the proposed neural network, Bell Fuzzy Multi Layer Perceptron Neural Network (BF-MLP). 44 images with 3 class labels were used to test the algorithm and classification accuracy of 93.2% was obtained.
Role of Toll-Like Receptors in Pathogen Recognition

SUMMARY The innate immune system relies on a vast array of non-clonally expressed pattern recognition receptors for the detection of pathogens. Pattern recognition receptors bind conserved molecular structures shared by large groups of pathogens, termed pathogen-associated molecular patterns. The Toll-like receptors (TLRs) are a recently discovered family of pattern recognition receptors which show homology with the Drosophila Toll protein and the human interleukin-1 receptor family. Engagement of different TLRs can induce overlapping yet distinct patterns of gene expression that contribute to an inflammatory response. The TLR family is characterized by the presence of leucine-rich repeats and a Toll/interleukin-1 receptor-like domain, which mediate ligand binding and interaction with intracellular signaling proteins, respectively. Most TLR ligands identified so far are conserved microbial products which signal the presence of an infection, but evidence for some endogenous ligands that might signal other danger conditions has also been obtained. Molecular mechanisms for pathogen-associated molecular pattern recognition still remain elusive but seem to be more complicated than initially anticipated. In most cases, direct binding of microbial ligands to TLRs still has to be demonstrated. Moreover, Drosophila TLRs bind endogenous ligands, generated through a proteolytic cascade in response to an infection. In the case of endotoxin, recognition involves a complex of TLR4 and a number of other proteins. Moreover, TLR heterodimerization further extends the spectrum of ligands and modulates the response towards specific ligands. The fact that TLR expression is regulated in both a cell type- and stimulus-dependent fashion further contributes to the complexity.
UNIFORM CONVERGENCE OF THE NEWTON METHOD FOR AUBIN CONTINUOUS MAPS

In this paper we prove that the Newton method applied to the generalized equation y ∈ f(x) + F(x) with a C 1 function f and a set-valued map F acting in Banach spaces, is locally convergent uniformly in the parameter y if and only if the map (f +F) 1 is Aubin continuous at the reference point. We also show that the Aubin continuity actually implies uniform Q-quadratic convergence provided that the derivative of f is Lipschitz continuous. As an application, we give a characterization of the uniform local Q-quadratic convergence of the sequential quadratic programming method applied to a perturbed nonlinear program.
Ingroup Identification, Outgroup Infrahumanization, and Intention to Mobilize in Land Use Conflicts

Based on the application of a social psychology intergroup perspective to the analysis of people–place relationships, we conducted an experimental study in the context of a land use conflict revolving around the construction of a bridge over the Messina Channel (Italy). We aimed to analyze the relations between the salience of the identification with the ingroup defined by being pro- versus antibridge, outgroup infrahumanization, and the intention to mobilize in the conflict. In two community samples, from Reggio Calabria, where the structure should be placed (n = 107), and from Sciacca, which is more than 200 kilometers away from it (n = 100), the salience of ingroup identification influenced the intention to mobilize via the partial mediation of outgroup infrahumanization. The attitude toward the bridge and the distance from it did not moderate the paths that we have analyzed. Strengths, limitations, and implications for environmental psychology research are discussed.
Notice of Violation of IEEE Publication PrinciplesA Differential Evolution Algorithm for Image Fusion

Image fusion is an integral part of many existing and future surveillance systems. Due to the limited depth-of-focus of optical lenses (especially such with long focal lengths) it is often not possible to get an image which contains all relevant objects in focus. One way to get an everywhere-in-focus image is to fuse the images of the same scene which are taken with different focal settings. This paper describes a novel optimal method for multi-focus image fusion using differential evolution algorithm. The source images are first decomposed into blocks. Then, the sharper blocks are selected by employing a sharpness criterion function. The selected blocks are finally combined to construct the fused image. The motivation of the proposed method lies in the fact that an optimized block size could be more effective than a fixed block size. The experimental results show that the proposed method can perform better than the other traditional methods in terms of both quantitative and visual evaluations.
Parallelizing Optimal Multiple Sequence Alignment by Dynamic Programming

Optimal multiple sequence alignment by dynamic programming, like many highly dimensional scientific computing problems, has failed to benefit from the improvements in computing performance brought about by multi-processor systems, due to the lack of suitable scheme to manage partitioning and dependencies. A scheme for parallel implementation of the dynamic programming multiple sequence alignment is presented, based on a peer to peer design and a multidimensional array indexing method. This design results in up to 5-fold improvement compared to a previously described master/slave design, and scales favourably with the number of processors used. This study demonstrates an approach for parallelising multi-dimensional dynamic programming and similar algorithms utilizing multi-processor architectures.
Condensation Risk in a Room with a High Latent Load and Chilled Ceiling Panels and with Air Supplied from a Liquid Desiccant System

Radiant cooling has shown great advantages when it comes to improving thermal comfort and can also reduce energy demand. But the system may have a high condensation risk if used with a high latent load. This study proposes a new type of ventilation system that uses a radiant cooling panel and air supplied from a liquid desiccant dehumidification system, which provides very dry supply air and chilled water for radiant cooling. This study uses an office with a high latent load to demonstrate the application of such a system in a hot and humid climate. By using a validated computational fluid dynamics (CFD) program to calculate the distributions of air temperature, humidity, and velocity, as well as the predicted mean vote in the office, the results show that the new system could reduce the risk of condensation on the cooling panels and offer a comfortable indoor environment. The new system has great potential when it comes to use in hot and humid climate regions.
The Role of Social Capital in Understanding Entrepreneurship

This study explores the impact of social capital on entrepreneurial activities by using pseudo-panel approach constructed at an age-based cohort level. We assess the effects of social capital, in forms of generalized and institutional trust, civic norms, and networks through associational activities, on entrepreneurship using cohort panel data derived from the World Values Survey (WVS). Moreover, we construct a measure of social capital that incorporates all of these three dimensions. The data from the WVS covers five periods (1990, 1995, 2000, 2005 and 2010) and includes a cross section of 40 countries. The findings indicate that trust measured by either generalized or institutional trust encourages entrepreneurship. Evidence suggests that stronger civic norms positively influence entrepreneurship, whereas participating associational activities has negative impact on entrepreneurship due to over-embeddedness. We also find evidence that a multidimensional measure of social capital is needed for linking social capital to entrepreneurship.
Motion segmentation and appearance change detection based 2D hand tracking

In this paper a novel method called MACS for 2D hand tracking using motion and color information for head-worn monocular color cameras is presented. Many head-mounted devices (HMDs), like eye trackers or Augmented Reality glasses, are equipped with only one color camera capturing the field of view of the user from the ego perspective. To interact with the HMD, hand gestures are an intuitive modality. Hand tracking can be viewed as the first step towards hand gesture recognition. But to recognize hand gestures in industrial or commercial applications, the hand tracking process must produce robust estimations in each frame, given any lighting conditions inside and outside of a building. To achieve this, the presented method creates a motion segmentation, determines a foreground segment and tracks the color appearance of this segment over time to estimate robustly when and roughly where the hand is visible. A sophisticated skin color detection method, fused with the previously generated moving foreground segment, makes the estimation of the hand trajectory more accurate using a simple particle filter with a specialized observation model. This allows for estimating the 2D hand position even in front of complex backgrounds and difficult lighting conditions. A comparison of this new algorithm with other tracking methods is conducted using a thorough evaluation methodology and challenging image sequences with more than 25,000 frames containing different wiping hand gestures.