Miracle-dz/UniFAR-FTUs huggingface dataset:
Specific and quantitative labeling of biomolecules using click chemistry

Specific and highly efficient fluorescent labeling techniques for biomolecules, especially for proteins, are required for the quantitative analyses of bio-phenomena and for subsequent systems biology. Although expression of exogenous proteins fused with fluorescent tags, such as green fluorescent protein, is the most widely used method for quantitative bio-analysis, the following problems need to be considered carefully: (1) precise stoichiometric control in living cells is difficult, and (2) the bulkiness of the fluorescent tags restricts analysis of the inherent physical and biological properties of the proteins. Therefore, novel techniques to specifically and stoichiometrically label intrinsic proteins or other biomolecules in living cells should be developed. Click chemistry reactions (e.g., Huisgen cycloaddition and Staudinger ligation) are the most promising approaches for this purpose, because these chemical reactions have following advantages: (1) bioorthogonal reactions; (2) mild reaction conditions suitable for fragile biomolecules, cells, and tissues; (3) extremely high reaction ratio; (4) small size of the functional groups for the cross-coupling reactions; (5) stable covalent bonding; and (6) simple metabolic labeling procedures in living cells, using various biomolecular analogs. Diverse quantitative biological studies have been carried out using this technology (e.g., quantification of novel synthesized proteins and observation of post-translational modifications). In this review, I explain the basics of chemical probing with click chemistry, and discuss its recent applications in the field of quantitative biology. Furthermore, I discuss the capability, significance, and future of the chemical probing of proteins, with an emphasis on the use of click chemistry in the field of the quantitative biology.
Fitting class-based language models into weighted finite-state transducer framework

In our paper we propose a general way of incorporating class-based language models with many-to-many word-to-class mapping into the ﬁnite-state transducer (FST) framework. Since class-based models alone usually do not improve the recognition accuracy, we also present a method for an efﬁcient language model combination. An example of a word-to-class mapping based on morphological tags is also given. Several word-based and tag-based language models are tested in the task of transcribing Czech broadcast news. Results show that class-based models help to achieve a moderate improvement in recognition accuracy.
Strategic Risk Management Behavior: What Can Utility Functions Tell Us?

The validity of the utility concept, particularly in an expected utility framework, has been questioned because of its inability to predict revealed behavior. In this paper we focus on the global shape of the utility function instead of the local shape of the utility function. We examine the extent of heterogeneity in the global shape of the utility function of decision makers and test whether its shape predicts strategic risk management behavior. We assess the utility functions and relate them to strategic decisions for portfolio managers (N = 104) and hog farmers (N = 239). The research design allows us to examine the robustness of our results and the extent to which the results can be generalized. Furthermore, we assess the shape of the utility functions for these decision makers applying two different methods. This allows us to further test the robustness of our empirical results. If there exists a relationship between the shape of the utility function and strategic decisions, both methods should yield the same result. The empirical results indicate that the global shape of the utility function differs across decision makers (fully concave or convex versus S-shaped), and that the global shape predicts strategic decisions (e.g., asset allocation strategy in the case of portfolio managers; type of production process employed in the case of hog farmers). These findings support the notion that the often criticized concept of utility is a useful concept when studying actual behavior, and highlight the importance of considering decision-maker behavior over a wide outcome range when examining strategic behavior.
The effects of user distribution on CDMA antenna array receivers

This paper discusses the use of sectorised antenna array receivers for the reverse links of cellular code division multiple access (CDMA) systems. The distribution of users in the sector can seriously alter the sector capacity that can be achieved. Simulation results are presented to show the effect of user clustering on system performance for a number of different scenarios.
A location predictor based on dependencies between multiple lifelog data

In this paper, we propose a method for predicting future locations of a person by exploiting the person's past lifelog data. To predict the future location of a person has many applications such as the delivery of information related to the predicted locations: information with limited lifetimes (sales in a supermarket), weather reports, and traffic reports. Most existing methods for prediction only use historical location data, thus they can only handle regular movements; irregular movements are not considered. Our method predicts future locations by using personal calendar entries in addition to GPS(Global positioning system) data. Using calendar entries makes it possible to predict the locations associated with the irregular events indicated by the entries. We make Dynamic Bayesian Networks models for integrating these different kinds of lifelog data so as to yield better predictions. In experiments on real data, our methods can predict irregular movements successfully even with long lead-times, while matching the accuracy of existing schemes in predicting usual movements.
Pervasive 'Calm' Perception for Autonomous Robotic Agents

A major bottleneck in the realization of autonomous robotic agents performing complex manipulation tasks are the requirements that these tasks impose onto perception mechanisms. There is a strong need to scale robot perception capabilities along two dimensions: First, the variations of appearances and perceptual properties that real-world objects exhibit. Second, the variety of perceptual tasks, like categorizing and localizing, decomposing objects into their functional parts, perceiving the affordances they provide. This paper, addresses this need by organizing perception into a two-stage process. First, a pervasive and 'calm' perceptual component runs continually and interprets the incoming image stream to form a general purpose hybrid (symbolic/sub-symbolic) belief state. This is used by the second component, the task-directed perception subsystem, to perform the respective perception tasks in a more informed way. We describe and discuss the first component and explain how it can manage realistic belief states, form a memory of past perceptual experiences, and compute valuable perceptual attributes without delaying plan execution. It does so by exploiting that perception is not a one-shot task but rather a secondary task that is pervasively and calmly performed throughout the lifetime of the robot. We show system operating on a leading-edge manipulation platform.
Signal-based Music Searching and Browsing

This paper describes an approach to the problem of finding songs in some sense similar to a query song. This is a problem of increasing importance, because consumers owning large digital music collections wish to navigate these and to add new songs by searching on-line. The technological approach is described, leading to the description of a simple demonstrator.
Optimal energy-efficient cooperative sensing scheduling for Cognitive Radio Networks with QoS guarantee

Cooperative spectrum sensing, which can profoundly improve the ability of discovering the spectrum opportunities, is regarded as an enabling mechanism for Cognitive Radio Networks (CRNs). One of the most fundamental problems in cooperative spectrum sensing is how to assign Secondary Users (SUs) to sense different primary channels such that SUs can achieve a good balance between sensing accuracy and the exploration of potential “spectrum holes”. This problem becomes more challenging when the primary channels require heterogeneous detection probabilities for incumbent protection. In this paper, the Cooperative Sensing Scheduling with QoS guarantee (CSS-Q) problem is studied for designing energy-efficient CRNs.We first explore the inherent structure of the CSS-Q problem and find several useful properties for it. Then, based on these properties a novel and efficient algorithm is proposed to solve the problem optimally. Sufficient numerical results are also presented to validate our analysis.
Move-ability: A philosophy of education study that develops an alternative understanding of inclusion through posthumanist theories using a diffractive reading

This is a study within the field of philosophy of education that seeks to develop an alternative understanding of inclusion within education in light of current changes in society. It discusses a shift within educational research from the field of diversity education towards the field of democratic education, and argues that an idea of separation between subjects implies a tension in the theory calling for this shift. Departing from a posthumanist theoretical framework, an interdisciplinary examination is performed, which suggests that humanist presumptions of separation of matter and meaning lie behind the idea mentioned above. It offers the concept of move-ment, which rather takes departure in the ongoing material-discursive entanglement of matter and meaning in the world’s ongoing process of becoming. The analysis method used in the study is the posthumanist methodology of diffractive reading, whose aim is reading texts through each other in order to develop alternative ideas. The analysis reads the contemporary notion of inclusion within the field of democratic education, and the concept of move-ment, through each other. The analysis results in the developed concept of move-ability, which understands inclusion as an ongoing, relational and performative phenomenon, in a way that more clearly emphasizes movability, transformation and relationality. Finally, the thesis performs a brief discussion of the concept of move-ability, in relation to educational practice. The discussion calls for further engagement within educational research, in order to develop educational approaches in which the concept can come to matter. (Less)
Adaptive long range vision in unstructured terrain

A novel probabilistic online learning framework for autonomous off-road robot navigation is proposed. The system is purely vision-based and is particularly designed for predicting traversability in unknown or rapidly changing environments. It uses self-supervised learning to quickly adapt to novel terrains after processing a small number of frames, and it can recognize terrain elements such as paths, man-made structures, and natural obstacles at ranges up to 30 meters. The system is developed on the LAGR mobile robot platform and the performance is evaluated using multiple metrics, including ground truth.
Benzene Exposure Near the U.S. Permissible Limit Is Associated with Sperm Aneuploidy

Background Benzene is a common industrial chemical known to induce leukemia and other blood disorders, as well as aneuploidy, in both human blood cells and sperm at exposures > 10 ppm. Recent reports have identified health effects at exposure levels < 1 ppm, the permissible exposure limit (PEL; 8 hr) set by the U.S. Occupational Safety and Health Administration. Objective We investigated whether occupational exposures to benzene near 1 ppm induce aneuploidy in sperm. Methods We used multicolor fluorescence in situ hybridization to measure the incidence of sperm with numerical abnormalities of chromosomes X, Y, and 21 among 33 benzene-exposed men and 33 unexposed men from Chinese factories. Individual exposures were assessed using personal air monitoring and urinary concentrations of benzene and trans,trans-muconic acid (E,E-MA). Air benzene concentrations were not detectable in unexposed men; in exposed men, concentrations ranged from below the detection limit to 24 ppm (median, 2.9 ppm), with 27% of exposed men (n = 9) having concentrations of ≤ 1 ppm. Exposed men were categorized into low and high groups based on urinary E,E-MA (median concentrations of 1.9 and 14.4 mg/L, respectively; median air benzene of 1 and 7.7 ppm, respectively), and aneuploidy frequencies were compared with those of unexposed men. Results Sperm aneuploidy increased across low- and high-exposed groups for disomy X [incidence rate ratio (IRR) = 2.0; 95% confidence interval (CI), 1.1–3.4; and IRR = 2.8; 95% CI, 1.5–4.9, respectively], and for overall hyperhaploidy for the three chromosomes investigated (IRR = 1.6; 95% CI, 1.0–2.4; and IRR = 2.3; 95% CI, 1.5–3.6, respectively). We also found elevated disomy X and hyperhaploidy in the nine men exposed to ≤ 1 ppm benzene compared with unexposed men (IRR = 1.8; 95% CI, 1.1–3.0; and IRR = 2.0; 95% CI, 1.1–3.9, respectively). Conclusions Benzene appeared to increase the frequencies of aneuploid sperm for chromosomes associated with chromosomal abnormality syndromes in human offspring, even in men whose air benzene exposure was at or below the U.S. permissible exposure limit.
Non-Transitive Connectivity and DHTs

The most basic functionality of a distributed hash table, or DHT, is to partition a key space across the set of nodes in a distributed system such that all nodes agree on the partitioning. For example, the Chord DHT assigns each node a random identifier from the key space of integers modulo 2160 and maps each key to the node whose identifier most immediately follows it. Chord is thus said to implement the successor relation, and so long as each node in the network knows its predecessor in the key space, any node can compute which keys are mapped onto it. An implicit assumption in Chord and other DHT protocols is that all nodes are able to communicate with each other, yet we know this assumption is unfounded in practice. We say a set of three hosts, A, B, and C, exhibit non-transitivity if A can communicate with B, and B can communicate with C, but A cannot communicate with C. As we show in Section 2, 2.3% of all pairs of nodes on PlanetLab exhibit transient periods in which they cannot communicate with each other, but in which they can communicate through a third node. These transient periods of non-transitivity occur for many reasons, including link failures, BGP routing updates, and ISP peering disputes (e.g., [13]). Such non-transitivity in the underlying network is problematic for DHTs. Consider for example the Chord network illustrated in Figure 1. Identifiers increase from the left, so node B is the proper successor to key k. If nodes A and B are unable to communicate with each other, A will believe that C is its successor. Upon receiving a lookup request for k, A will return C to the requester. If the requester then tries to insert a document associated with k at node C, node C would refuse, since according to its view it is not responsible for key k. While this example may seem contrived, it is in fact quite common. If each pair of nodes with adjacent identifiers in a 300-node Chord network (independently) has a 0.1% chance of being unable to communicate, then we expect that there is a 1−0.999300≈ 26% chance that some pair will be unable to communicate at any time. However, both nodes in such a pair have a 0.9992 chance of being able to communicate with the node that most immediately precedes them both. A B C k
THE METACHRONAL WAVE OF LATERAL CILIA OF MYTILUS EDULIS

The form of beat of cilia and the structure of the metachronal wave on the lateral gill epithelium of Mytulus edulis have been studied on living material by interference-contrast microscopy and stroboscopic illumination, and compared with the same features in rapid-fixed preparations studied by light microscopy and with the scanning electron microscope. The most striking finding is that the beat of the cilia is not planar, as previously assumed, but involves a sideways movement in the recovery stroke Previous reports on nonplanar ciliary beating from protozoan examples describe a planar effective stroke and a counterclockwise rotation in the recovery stroke; in this molluscan example there is a clockwise rotation in the recovery stroke The lateral inclination of the cilia in the recovery stroke is in the same direction as the propagation of the waves, and the orientation of cilia in the recovery stroke is thought to determine whether the waves move to the left or right of the direction of the effective stroke
Rate maintenance and resonance in the entorhinal cortex

Throughout the brain, neurons encode information in fundamental units of spikes. Each spike represents the combined thresholding of synaptic inputs and intrinsic neuronal dynamics. Here, we address a basic question of spike train formation: how do perithreshold synaptic inputs perturb the output of a spiking neuron? We recorded from single entorhinal principal cells in vitro and drove them to spike steadily at ∼5 Hz (theta range) with direct current injection, then used a dynamic‐clamp to superimpose strong excitatory conductance inputs at varying rates. Neurons spiked most reliably when the input rate matched the intrinsic neuronal firing rate. We also found a striking tendency of neurons to preserve their rates and coefficients of variation, independently of input rates. As mechanisms for this rate maintenance, we show that the efficacy of the conductance inputs varied with the relationship of input rate to neuronal firing rate, and with the arrival time of the input within the natural period. Using a novel method of spike classification, we developed a minimal Markov model that reproduced the measured statistics of the output spike trains and thus allowed us to identify and compare contributions to the rate maintenance and resonance. We suggest that the strength of rate maintenance may be used as a new categorization scheme for neuronal response and note that individual intrinsic spiking mechanisms may play a significant role in forming the rhythmic spike trains of activated neurons; in the entorhinal cortex, individual pacemakers may dominate production of the regional theta rhythm.
Managing Large Networks of Virtual Machines

As the number of available virtualization tools and their popularity continues to grow, the way in which virtual machines can be managed in a data center is becoming more and more important. A few commercial tools such as VMware ESX and XenEnterprise exist, but they are limited to a certain virtual machine technology and offer no way to expand the tool's capabilities to local needs. This paper discusses an open source management tool, MLN, for large virtual networks transparent of their virtualization platform. The current version supports the two popular open source virtual machine packages: Xen and User Mode Linux. MLN uses an extensible configuration language for the design of the virtual machines and their internal configuration. Large groups of virtual machines can be managed as logical groups. We present a web-server hosting scenario and a on-demand render farm as case studies to show the usefulness of our tool. The text concludes with a short discussion on the difficulties of offering abstraction to virtualization platforms.
PROOF-NETS : THE PARALLEL SYNTAX FOR PROOF-THEORY

The paper is mainly concerned with the extension of proof-nets to additives, for which the best known solution is presented. It proposes two cut-elimination procedures, the lazy one being in linear time. The solution is shown to be compatible with quanti(cid:12)ers, and the structural rules of exponentials are also accommodated.
3D Reconstruction using a sparse laser scanner and a single camera for outdoor autonomous vehicle

This paper presents a 3D scene reconstruction method for autonomous vehicle driving in a wide range of outdoor environments. Autonomous vehicles, most of which currently employ laser and image sensors, are required to have systems for object detection, obstacle avoidance, navigation etc. The one of the most important pieces of information for these systems is an accurate dense 3D depth map. However, range data is much sparser than image data, thus the challenging problem is to reconstruct a dense depth map using sparse range and image data. Here we propose a novel approach to fuse these different types of sensor data to reconstruct 3D scenes which maintains the shape of local objects. Our method features two main phases: the local range modeling phase and 3D depth map reconstruction phase. In the local range modeling phase we interpolate 3D points from the laser scanner using Gaussian Process regression. It estimates 3D measurements across the outdoor environment and accommodates for defective sensor information. In the reconstruction phase, we fuse an image and interpolated points to build a 3D depth map and optimize based on a Markov Random Field. It provides a depth map corresponding to all image pixels. Qualitative and time complexity results show that our approach is robust and fast enough to demonstrate in real-time for an autonomous vehicle in complex urban scenes.
Color Separation Gratings 94-17 362

In this paper, we describe the theory, fabrication and test of a binary optics "echelon. " The echelon is a grating structure which separates electromagnetic radiation of different wavelengths, but it does so according to diffraction order rather than by dispersion within one diffractin order, as is the case with conventional gratings. A prototype echelon, designed for the visible spectrum, is fabricated using the binary optics process. Tests of the prototype show good agreement with theoretical predictions.
Efficient and Effective Analysis of Data Quality using Pattern Tableaux

Data Auditor is a system for analyzing data quality via exploring data semantics. Given a user-supplied constraint, such as a functional dependency or an inclusion dependency, the system computes pattern tableaux, which are concise summaries of subsets of the data that satisfy (or fail) the constraint. The engine of Data Auditor is an efficient algorithm for finding these patterns, which defers expensive computation on patterns until needed during search, thereby pruning wasted effort. We demonstrate the utility of our approach on a variety of data as well as the performance gain from employing this algorithm.
Image Deblurring Blind Deconvolution based on Sparsity Regularization

Blind deconvolution in image deblurring is an openended problem because various heuristic assumptions can be posed on the point-spread function and the sharp image. In this project, we explore the effectiveness of a new heuristic assumption that the image is sparse in terms of its gradient. This heuristic favors sharpness of the recovered image because the edges are sparse. The point-spread function is assumed to be non-negative. Using iterative-shrinkage-thresholding algorithm, the non-convex cost function for the estimated gradient of sharp images is solved. Using iterative-reweighted-least-square algorithm, the norm-2 regression problem for point-spread functions is solved. The algorithm is implemented and then tested in this project. By blurring each test image using various point spread functions, feeding the blurred images into our implementation, and then comparing the estimated point-spread function with the actual point-spread function using SSIM, we find that the algorithm performs pretty well on Gaussian noise and motion blur.