Miracle-dz/UniFAR-FTUs huggingface dataset:
First results from negative ion beam extraction in ROBIN in surface mode

ROBIN, the first step in the Indian R&D program on negative ion beams has reached an important milestone, with the production of negative ions in the surface conversion mode through Cesium (Cs) vapor injection into the source. In the present set-up, negative hydrogen ion beam extraction is effected through an extraction area of ∼73.38 cm2 (146 apertures of 8mm diameter). The three grid electrostatic accelerator system of ROBIN is fed by high voltage DC power supplies (Extraction Power Supply System: 11kV, 35A and Acceleration Power Supply System: 35kV, 15A). Though, a considerable reduction of co-extracted electron current is usually observed during surface mode operation, in order to increase the negative ion current, various other parameters such as plasma grid temperature, plasma grid bias, extraction to acceleration voltage ratio, impurity control and Cs recycling need to be optimized. In the present experiments, to control and to understand the impurity behavior, a Cryopump (14,000 l/s for Hydrogen) .
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation

Real-time location inference of social media users is the fundamental of some spatial applications such as localized search and event detection. While tweet text is the most commonly used feature in location estimation, most of the prior works suffer from either the noise or the sparsity of textual features. In this paper, we aim to tackle these two problems. We use topic modeling as a building block to characterize the geographic topic variation and lexical variation so that "one-hot" encoding vectors will no longer be directly used. We also incorporate other features which can be extracted through the Twitter streaming API to overcome the noise problem. Experimental results show that our RATE algorithm outperforms several benchmark methods, both in the precision of region classification and the mean distance error of latitude and longitude regression.
Convex Relaxation of Mixture Regression with Efficient Algorithms

We develop a convex relaxation of maximum a posteriori estimation of a mixture of regression models. Although our relaxation involves a semidefinite matrix variable, we reformulate the problem to eliminate the need for general semidefinite programming. In particular, we provide two reformulations that admit fast algorithms. The first is a max-min spectral reformulation exploiting quasi-Newton descent. The second is a min-min reformulation consisting of fast alternating steps of closed-form updates. We evaluate the methods against Expectation-Maximization in a real problem of motion segmentation from video data.
Digital holographic inspection for drying processes of paint films and ink dots

Digital holographic techniques to investigate drying processes of both paint films and ink dot is presented. The proposed technique based on digital holographic interferometry can achieve both visualization of variations and analysis of dryness of paint films in the drying process by using phase changes between two subsequent reconstructed complex amplitudes of the reflected light from the film. To follow the drying processes, holograms are recorded at a constant time interval. Phase-shifting digital holography has been applied to analyze the dryness of commercial paints applied on the metal plate. For analysis of an ink dot having diameter of a few hundred micrometers, digital holographic microscopy is applied to evaluating the time history of dryness of ink dot in the drying process. This paper describes these holographic techniques applied to the commercially available paint and ink and presents some experimental results.
GNET-1: gigabit Ethernet network testbed

GNET-1 is a fully programmable network testbed. It provides functions such as wide area network emulation, network instrumentation, traffic shaping, and traffic generation at gigabit Ethernet wire speeds by programming the core FPGA. GNET-1 is a powerful tool for developing network-aware grid software. It is also a network monitoring and traffic-shaping tool that provides high-performance communication over wide area networks. This work describes several sample uses of GNET-1 and presents its architecture.
Role of physiological ClC-1 Cl− ion channel regulation for the excitability and function of working skeletal muscle

Electrical membrane properties of skeletal muscle fibers have been thoroughly studied over the last five to six decades. This has shown that muscle fibers from a wide range of species, including fish, amphibians, reptiles, birds, and mammals, are all characterized by high resting membrane permeability for Cl− ions. Thus, in resting human muscle, ClC-1 Cl− ion channels account for ∼80% of the membrane conductance, and because active Cl− transport is limited in muscle fibers, the equilibrium potential for Cl− lies close to the resting membrane potential. These conditions—high membrane conductance and passive distribution—enable ClC-1 to conduct membrane current that inhibits muscle excitability. This depressing effect of ClC-1 current on muscle excitability has mostly been associated with skeletal muscle hyperexcitability in myotonia congenita, which arises from loss-of-function mutations in the CLCN1 gene. However, given that ClC-1 must be drastically inhibited (∼80%) before myotonia develops, more recent studies have explored whether acute and more subtle ClC-1 regulation contributes to controlling the excitability of working muscle. Methods were developed to measure ClC-1 function with subsecond temporal resolution in action potential firing muscle fibers. These and other techniques have revealed that ClC-1 function is controlled by multiple cellular signals during muscle activity. Thus, onset of muscle activity triggers ClC-1 inhibition via protein kinase C, intracellular acidosis, and lactate ions. This inhibition is important for preserving excitability of working muscle in the face of activity-induced elevation of extracellular K+ and accumulating inactivation of voltage-gated sodium channels. Furthermore, during prolonged activity, a marked ClC-1 activation can develop that compromises muscle excitability. Data from ClC-1 expression systems suggest that this ClC-1 activation may arise from loss of regulation by adenosine nucleotides and/or oxidation. The present review summarizes the current knowledge of the physiological factors that control ClC-1 function in active muscle.
ScreenCrayons: annotating anything

ScreenCrayons is a system for collecting annotations on any type of document or visual information from any application. The basis for the system is a screen capture upon which the user can highlight the relevant portions of the image. The user can define any number of topics for organizing notes. Each topic is associated with a highlighting "crayon. " In addition the user can supply annotations in digital ink or text. Algorithms are described that summarize captured images based on the highlight strokes so as to provide overviews of many annotations as well as being able to "zoom in" on particular information about a given note and the context of that note.
Joint fall and aspect angle recognition using fine-grained micro-Doppler classification

Activity recognition and monitoring are finding important applications in ambient assisted living healthcare. Among the various types of motions which researchers are attempting to detect and recognize, fall detection has gained significant interest. In this paper, we investigate the application of high-frequency (24 GHz) FMCW radar for multi-perspective micro-Doppler (μ-D) activity recognition. Data from two different types of motion; falling and picking-up an object, were collected from three aspect angles and put through a fine-grained classifier to not only differentiate the motions, but to also identify their aspect towards the radar receivers. A key novel component of this work is the application of the fine-grained classification task, where a label discriminate sparse representation classifier is proposed to improve recognition performance over very similar μ-D signatures. This is achieved by learning a discriminate dictionary constrained by the label information and meanwhile preventing the overfitting problem. The greatest increase in classification performance was found to be of the order of 8 %.
Comparison of Systolic Blood Pressure Measurements by Auscultation and Visual Manometer Needle Jump

Purpose This study was designed to investigate differences in systolic blood pressure measurements as obtained through auscultation and observation of the visual jump on the manometer. Methods Men (n = 21; 26.9 ± 7.4 yrs) and women (n = 22; 29.3 ± 13.9 yrs) volunteered to have resting systolic blood pressure (SBP) assessments. During the same cardiac inflation-deflation cycle of traditional sphygmomanometry, the initial visual jump of the manometer needle and first Korotkoff sound heard were recorded. Duplicate assessments were made in each arm with 30 sec between intra-arm trials. Results Paired t-test results indicated there were no within-method differences between arms for visual jump (R: 132.1 ± 11.3; L: 131.8 ± 10.5 mmHg) or auscultation (R: 116.8 ± 9.0; L: 113.5 ± 8.8 mmHg). There were methodological differences within arm with visual jump being the higher of the two (right: t(42) = −12.69; left: t(42) = −11.37; p < . 001). Conclusion If visual jump determination of SBP cannot be avoided, re-assessment using a more traditional method (i.e. auscultation) is recommended.
Recognizing Buildings through Deep Learning: A Case Study on Half-timbered Framed Buildings in Calw City

Automatic detection and recognition of specific types of urban buildings is extremely important for a variety of applications ranging from outdoor urban reconstruction to navigation. In this paper we propose a system for the automatic detection and recognition of urban buildings. Most of the existing work relies on the exploitation of handcrafted features for recognizing buildings. However, due to their complex structure it is rarely a priori known which features are important for the recognition task. Our method overcomes this drawback by exploiting a deep learning framework, based on convolutional neural networks, which automatically construct highly descriptive features directly from raw data. We evaluate the performance of our method on the recognition of half-timbered framed buildings in Calw city in Germany.
A Privacy-Aware Architecture for Sharing Web Histories

1 Net Trust is a distributed reputation system that identifies fraudulent web sites by aggregating individual opinions and browsing histories over user-selected social networks. This paper examines the security properties intrinsic to any correct implementation of Net Trust’s ratings system and the privacy properties arising from the paper’s proposed rich-client/thin-server implementation architecture. The ratings system protects against Sybil attacks, corruption by en masse bogus ratings distribution, and distinguishes fraudulent web sites from the trustworthy ones by leveraging the browsing behavior in trusted social networks rather than link topology of third-parties. The implementation architecture maintains high data availability while empowering browser-history owners with final control over data access. This paper analyzes Net Trust’s participants, attackers, security and privacy goals, and implementation choices.
Characterization of the volatile composition of essential oils of some lamiaceae spices and the antimicrobial and antioxidant activities of the entire oils.

The essential oils of Ocimum basilicum L. , Origanum vulgare L. , and Thymus vulgaris L. were analyzed by means of gas chromatography-mass spectrometry and assayed for their antioxidant and antimicrobial activities. The antioxidant activity was evaluated as a free radical scavenging capacity (RSC), together with effects on lipid peroxidation (LP). RSC was assessed measuring the scavenging activity of the essential oils on 2,2-diphenyl-1-picrylhydrazil (DPPH(*)) and OH(*) radicals. Effects on LP were evaluated following the activities of essential oils in Fe(2+)/ascorbate and Fe(2+)/H(2)O(2) systems of induction. Essential oils exhibited very strong RSCs, reducing the DPPH radical formation (IC(50)) in the range from 0.17 (oregano) to 0.39 microg/mL (basil). The essential oil of T. vulgaris exhibited the highest OH radical scavenging activity, although none of the examined essential oils reached 50% of neutralization (IC(50)). All of the tested essential oils strongly inhibited LP, induced either by Fe(2+)/ascorbate or by Fe(2+)/H(2)O(2). The antimicrobial activity was tested against 13 bacterial strains and six fungi. The most effective antibacterial activity was expressed by the essential oil of oregano, even on multiresistant strains of Pseudomonas aeruginosa and Escherichia coli. A significant rate of antifungal activity of all of the examined essential oils was also exhibited.
Notes on searching in multidimensional monotone arrays

A two-dimensional array A=(a/sub i,j/) is called monotone if the maximum entry in its ith row lies below or to the right of the maximum entry in its (i- 1)-st row. An array A is called totally monotone if every 2*2 subarray (i.e., every 2*2 minor) is monotone. The notion of two-dimensional totally monotone arrays is generalized to multidimensional arrays, and a wide variety of problems are exhibited involving computational geometry, dynamic programming, VLSI river routing, and finding certain kinds of shortest paths that can be solved efficiently by finding maxima in totally monotone arrays. <<ETX>>
Effects of decreased muscle activity on developing axial musculature in nicb107 mutant zebrafish (Danio rerio)

SUMMARY The present paper discusses the effects of decreased muscle activity (DMA) on embryonic development in the zebrafish. Wild-type zebrafish embryos become mobile around 18 h post-fertilisation, long before the axial musculature is fully differentiated. As a model for DMA, the nicb107 mutant was used. In nicb107 mutant embryos, muscle fibres are mechanically intact and able to contract, but neuronal signalling is defective and the fibres are not activated, rendering the embryos immobile. Despite the immobility, distinguished slow and fast muscle fibres developed at the correct location in the axial muscles, helical muscle fibre arrangements were detected and sarcomere architecture was generated. However, in nicb107 mutant embryos the notochord is flatter and the cross-sectional body shape more rounded, also affecting muscle fibre orientation. The stacking of sarcomeres and myofibril arrangement show a less regular pattern. Finally, expression levels of several genes were changed. Together, these changes in expression indicate that muscle growth is not impeded and energy metabolism is not changed by the decrease in muscle activity but that the composition of muscle is altered. In addition, skin stiffness is affected. In conclusion, the lack of muscle fibre activity did not prevent the basal muscle components developing but influenced further organisation and differentiation of these components.
Jasmine: a real-time local-event detection system based on geolocation information propagated to microblogs

We propose a system for detecting local events in the real-world using geolocation information from microblog documents. A local event happens when people with a common purpose gather at the same time and place. To detect such an event, we identify a group of Twitter documents describing the same theme that were generated within a short time and a small geographic area. Timestamps and geotags are useful for finding such documents, but only 0.7% of documents are geotagged and not sufficient for this purpose. Therefore, we propose an automatic geotagging method that identifies the location of non-geotagged documents. Our geotagging method successfully increased the number of geographic groups by about 115 times. For each group of documents, we extract co-occurring terms to identify its theme and determine whether it is about an event. We subjectively evaluated the precision of our detected local events and found that it had 25.5% accuracy. These results demonstrate that our system can detect local events that are difficult to identify using existing event detection methods. A user can interactively specify the size of a desired event by manipulating the parameters of date, area size, and the minimum number of Twitter users associated with the location. Our system allows users to enjoy the novel experience of finding a local event happening near their current location in real time.
ICTs, domestication and language-games: a Wittgensteinian approach to media uses

This article acknowledges the vital role that the Domestication Research-perspective has in media research, but criticizes it for being analytically ambiguous in its use of the central term `domestication'. By way of a contrastive set of data from an ongoing research project, we argue for a dislocation of `domestication' from the domestic and the private. Instead, we wish to retain the meaning and use of the term to acts of domesticating, i.e. processes of `taming the wild'. By connecting our arguments to Wittgenstein's concept of the `language-game', we emphasize the practical aspect of language and meaning, and how ICTs become meaningful only as parts of practical-communicative contexts. We argue that this steering towards `domestication' as contextualization highlights the universal and fundamental process of enculturation. Such a turn frees the perspective from historical and cultural specificities and thereby accentuates its analytical potential in a post-national, globalized world.
Current mirror array: A novel lightweight strong PUF topology with enhanced reliability

In this work, we present a novel design of physical unclonable function (PUF) based on the topology of current mirror array (CMA). The proposed strong PUF exploits the randomness in the current mirror transistors and generates the response bit by comparing the accumulated current values. Thresholding and reference current are used to increase the reliability of the proposed PUF without requiring additional hardware resources. The proposed PUF structure is also analysed in terms of its difficulty of model building for measurement-prediction attack. Measurement results on 0. 35μm test chips demonstrate that the proposed PUF outperforms other state-of-the-art designs with smaller area/bit of 9 × 10−36μm2 and lower native bit error rate (BER) of 0.16%.
Folded catadioptric cameras

A framework is developed for the design and analysis of single-viewpoint catadioptric cameras that use two or more mirrors. The use of multiple mirrors permits folding of the optics which leads to more compact camera designs than ones that use a single mirror. A dictionary of camera designs that use two conic mirrors is presented. We show that any folded system that uses conic mirrors has a geometrically equivalent system that uses a single conic mirror. This result makes it easy to determine the scene-to-image mapping of a conic folded system. In addition, we discuss the optical benefits of using folded systems. As an example, we choose a camera design from our dictionary and optimize its parameters via optical simulations. This design is used to construct a compact video camera that provides a hemispherical field of view.
Increased Histone Acetyltransferase and Lysine Acetyltransferase Activity and Biphasic Activation of the ERK/RSK Cascade in Insular Cortex During Novel Taste Learning

Changes in gene expression are thought to be involved in neuronal plasticity associated with learning and memory. Although acetylation of lysine residues on histones by histone acetyltransferases (HAT) is an obligatory component of transcription, HAT activity has been largely ignored in studies of the nervous system. We developed a new model for studying novel taste learning using novel solid food presentation to nondeprived animals. Using this behavioral paradigm, we investigated short- and long-term regulation of lysine acetyltransferase activity and the ERK/mitogen-activated protein kinase (MAPK)/RSK cascade in insular cortex, a CNS region known to be crucial for the formation of novel taste memories. We observed that novel taste learning elicited biphasic (acute and long-lasting) activation of two distinct lysine acetyltransferase activities along with the ERK/MAPK cascade in insular cortex. In vitro studies revealed that the ERK cascade could regulate the lysine acetylation of a 42 kDa lysine acetyltransferase substrate, suggesting a causal relationship between ERK activation and lysine acetyltransferase activity in insular cortex. Overall, our studies reveal an unanticipated long-lasting activation of insular cortex signal transduction cascades in novel taste learning. Furthermore, our studies suggest the hypothesis that acute and long-term ERK activation and lysine–histone acetyltransferase activation may play a role in regulating gene expression in single-trial learning and long-term memory formation.
Inferring Same-As Facts from Linked Data: An Iterative Import-by-Query Approach

In this paper we model the problem of data linkage in Linked Data as a reasoning problem on possibly decentralized data. We describe a novel import-by-query algorithm that alternates steps of sub-query rewriting and of tailored querying the Linked Data cloud in order to import data as specific as possible for inferring or contradicting given target same-as facts. Experiments conducted on a real-world dataset have demonstrated the feasibility of this approach and its usefulness in practice for data linkage and disambiguation.
Robust multi-target tracking using spatio-temporal context

In multi-target tracking, the maintaining of the correct identity of targets is challenging. In the presented tracking method, accurate target identification is achieved by incorporating the appearance information of the spatial and temporal context of each target. The spatial context of a target involves local background and nearby targets. The first contribution of the paper is to provide a new discriminative model for multi-target tracking with the embedded classification of each target against its context. As a result, the tracker not only searches for the image region similar to the target but also avoids latching on nearby targets or on a background region. The temporal context of a target includes its appearances seen during tracking in the past. The past appearances are used to train a probabilistic PCA that is used as the measurement model of the target at the present. As the second contribution, we develop a new incremental scheme for probabilistic PCA. It can update accurately the full set of parameters including a noise parameter still ignored in related literature. The experiments show robust tracking performance under the condition of severe clutter, occlusions and pose changes.
MIGRATORY CELL LOCOMOTION VERSUS NERVE AXON ELONGATION

The effects of lanthanum ions (La+++) on the locomotion and adhesion of g lial cells and elongating nerve axons are reported. La+++ increases adhesion of both glia and of nerve growth cones to a plastic substratum. La+++ also markedly reduces glia locomotion, but it does not inhibit nerve elongation. Electron-opaque deposits are seen on the cell surface and within cytoplasmic vesicles of glia and nerves cultured in a La+++-containing medium. Possible modes of action for La+++ are discussed, particularly the possibilities that Ca++ fluxes or Ca++ involvement in adhesion are altered by La+++. The results are consistent with the hypothesis that cell migration and nerve axon elongation differ in mechanism, with respect to both adhesive interactions and the activity of microfilament systems.