Miracle-dz/UniFAR-FTUs huggingface dataset:
WristWhirl: One-handed Continuous Smartwatch Input using Wrist Gestures

We propose and study a new input modality, WristWhirl, that uses the wrist as an always-available joystick to perform one-handed continuous input on smartwatches. We explore the influence of the wrist's bio-mechanical properties for performing gestures to interact with a smartwatch, both while standing still and walking. Through a user study, we examine the impact of performing 8 distinct gestures (4 directional marks, and 4 free-form shapes) on the stability of the watch surface. Participants were able to perform directional marks using the wrist as a joystick at an average rate of half a second and free-form shapes at an average rate of approximately 1.5secs. The free-form shapes could be recognized by a $1 gesture recognizer with an accuracy of 93.8% and by three human inspectors with an accuracy of 85%. From these results, we designed and implemented a proof-of-concept device by augmenting the watchband using an array of proximity sensors, which can be used to draw gestures with high quality. Finally, we demonstrate a number of scenarios that benefit from one-handed continuous input on smartwatches using WristWhirl.
Mechanics of Pressure-Adaptive Honeycomb

Pressure-adaptive honeycomb is a new type of adaptive structure that can exhibit great strains by relying on a pressure differential to alter the structural stiffness. The structure consists of a grid of honeycomb cells that extend a significant length perpendicular to the plain of the hexagons. Each cell possesses a pouch that can be pressurized and alter the stiffness of the structure. An analytical model is presented that predicts the stress—strain behavior in principal directions of this pressure-adaptive honeycomb. The predictions of the analytical model are shown to correlate well to experimental tests on a 130-cell aluminum honeycomb specimen that is loaded up to compressive strains of 12.5%. Based on this model, an equivalent material stiffness is defined for the honeycomb cell walls that can be employed in a FEA. An FE approximation of a 145-cell honeycomb beam based on this equivalent material stiffness is shown to correlate well to experimental results of a three-point bend test of such a specimen. The model of equivalent material stiffness greatly reduces the complexity of the FE approximation by eliminating the need to define a pouch or an internal pressure field. Therefore, the prediction method could be used in a design tool for pressure-adaptive honeycomb structures.
Pharmacological selectivity of the cloned human P2U‐purinoceptor: potent activation by diadenosine tetraphosphate

1 The human P2U‐purinoceptor was stably expressed in 1321N1 human astrocytoma cells and the pharmacological selectivity of the expressed receptor was studied by measurement of inositol lipid hydrolysis. 2 High basal levels of inositol phosphates occurred in P2U‐purinoceptor‐expressing cells. This phenomenon was shown to be due to release of large amounts of ATP from 1321N1 cells, and could be circumvented by adoption of an assay protocol that did not involve medium changes. 3 UTP, ATP and ATPγS were full and potent agonists for activation of phospholipase C with EC50 values of 140 nM, 230 nM, and 1.72 μM, respectively. 5BrUTP, 2C1ATP and 8BrATP were also full agonists although less potent than their natural congeners. Little or no effect was observed with the selective P2Y‐, P2X‐, and P2T‐purinoceptor agonists, 2MeSATP, α,β‐MeATP, and 2MeSADP, respectively. 4 Diadenosine tetraphosphate, Ap4A, was a surprisingly potent agonist at the expressed P2U‐purinoceptor with an EC50 (720 nM) in the range of the most potent P2U‐purinoceptor agonists. AP4A may be a physiologically important activator of P2U‐purinoceptors.
On low dimensional random projections and similarity search

Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. However, many similarity search applications often require very low dimension embeddings in order to reduce overhead and boost performance. Inspired by the use of symmetric probability distributions in previous work, we propose a novel RP algorithm, Beta Random Projection, and give its probabilistic analyses based on Beta and Gaussian approximations. We evaluate the algorithm in terms of standard similarity metrics with other RP algorithms as well as the singular value decomposition (SVD). Our experimental results show that BRP preserves both similarity metrics well and, under various dataset types including random point sets, text (TREC5) and images, provides sharper and consistent performance.
Mesoporous silica nanoparticles equipped with surface nanovalves for pH-controlled liberation of doxorubicin

Silica carriers equipped with molecular and supramolecular pH-sensitive nanovalves were designed by combination of sol–gel synthesis and selective postsynthetic modification. Mesoporous structure of synthesized materials was characterized by low-temperature nitrogen adsorption–desorption, small-angle X-ray diffraction and transmission electron microscopy. Chemical immobilization of N-[N′-(N′-phenyl)-2-aminophenyl]aminoalkyl groups was confirmed by IR spectral and chemical analyses of surface layer. Loading and release behaviour of synthesized drug carriers was studied in phosphate buffer solutions with pH 5.0 and pH 7.0 using doxorubicin (Dox) as a test molecule. It was found that the loading efficiency of synthesized materials determined by UV spectroscopy measurements reached 59–76%, whereas cumulative value of Dox released from silica materials equipped with molecular and supramolecular nanovalves into the phosphate buffer solution with pH 5.0 reached up to 48% and 51%, respectively. It was proved that aromatic amino groups and surface supramolecular structures localized near pore openings play an essential role in pH-controlled Dox release.
Routes to embodiment

Research on embodiment is rich in impressive demonstrations but somewhat poor in comprehensive explanations. Although some moderators and driving mechanisms have been identified, a comprehensive conceptual account of how bodily states or dynamics influence behavior is still missing. Here, we attempt to integrate current knowledge by describing three basic psychological mechanisms: direct state induction, which influences how humans feel or process information, unmediated by any other cognitive mechanism; modal priming, which changes the accessibility of concepts associated with a bodily state; sensorimotor simulation, which affects the ease with which congruent and incongruent actions are performed. We argue that the joint impact of these mechanisms can account for most existing embodiment effects. Additionally, we summarize empirical tests for distinguishing these mechanisms and suggest a guideline for future research about the mechanisms underlying embodiment effects.
A hybrid system for reducing the false alarm rate of anomaly intrusion detection system

In this paper, we propose a hybrid intrusion detection system that combines k-Means, and two classifiers: K-nearest neighbor and Naïve Bayes for anomaly detection. It consists of selecting features using an entropy based feature selection algorithm which selects the important attributes and removes the irredundant attributes. This algorithm operates on the KDD-99 Data set; this data set is used worldwide for evaluating the performance of different intrusion detection systems. The next step is clustering phase using k-Means. We have used the KDD99 (knowledge Discovery and Data Mining) intrusion detection contest. This system can detect the intrusions and further classify them into four categories: Denial of Service (DoS), U2R (User to Root), R2L (Remote to Local), and probe. The main goal is to reduce the false alarm rate of IDS1.
Sub-10 nm resolution Electron Beam Lithography in ultrathin HSQ resist layers

The continuous shrinking of the feature size forces scientists and engineers to develop new lithographic techniques and suitable materials which can meet the requirements of the market. Despite its low throughput, EBL remains the number one candidate when writing very small structures. Achieving ultimate resolution with EBL requires not only a very good lithographic tool (with small probe size) but also a highly sensitive electron beam resist which is able to undergo the lithographic process and at the same time yields a very high resolution. Most of the exposures are performed with a SEM and the use of smaller probe sizes (eg, in STEM) is quite limited due to the delicate handling of the thin samples which have to be used in this case. Nowadays, in EBL, as will be demonstrated in this thesis, sub-10 nm features can be obtained using different types of organic and inorganic resists. In order to test the ultimate resolution of this lithographic technique, dense features should be written for which the distance between two adjacent features is equal to the feature size measured after the development process. We might say that fabricating ultrahigh resolution structures using resist based EBL is like a chain reaction which starts with the spin coating of the resists and ends with the development process and inspection session. The goal of this thesis is to understand and explain the phenomena that take place in ultrathin resist layers to be able to optimize the process for generating dense sub 20-nm features. The understanding of the electron scattering that takes place, both in the resist and in the substrate, is a crucial factor when choosing the material for nanolithography. Because the interaction of the beam with the sample is a very complex process, a Monte Carlo simulation has been developed to calculate the bond breaking distributions for different resist materials. By varying one parameter at a time (e.g. resist thickness, resist material, acceleration voltage), the resolution can be predicted from the bond breaking distributions. Ultra-high resolution has been obtained with ultrathin Hydrogen silsesquioxane (HSQ) resist layers. For this specific resist, the most important factors which limit the resolution are being discussed throughout the chapters of this thesis.
mirPub: a database for searching microRNA publications

Summary: Identifying, amongst millions of publications available in MEDLINE, those that are relevant to specific microRNAs (miRNAs) of interest based on keyword search faces major obstacles. References to miRNA names in the literature often deviate from standard nomenclature for various reasons, since even the official nomenclature evolves. For instance, a single miRNA name may identify two completely different molecules or two different names may refer to the same molecule. mirPub is a database with a powerful and intuitive interface, which facilitates searching for miRNA literature, addressing the aforementioned issues. To provide effective search services, mirPub applies text mining techniques on MEDLINE, integrates data from several curated databases and exploits data from its user community following a crowdsourcing approach. Other key features include an interactive visualization service that illustrates intuitively the evolution of miRNA data, tag clouds summarizing the relevance of publications to particular diseases, cell types or tissues and access to TarBase 6.0 data to oversee genes related to miRNA publications. Availability and Implementation: mirPub is freely available at http://www.microrna. gr/mirpub/. Contact: vergoulis@imis.athena-innovation.gr or dalamag@imis.athena-innovation.gr Supplementary information: Supplementary data are available at Bioinformatics online.
DEVELOPMENT AND VALIDATION OF STABILITY INDICATING RP-HPLC METHOD FOR THE SIMULTANEOUS ESTIMATION OF METOPROLOL SUCCINATE AND CILNIDIPINE IN BULK AND PHARMACEUTICAL DOSAGE FORM

Objective: Development and validation of stability indicating RP-HPLC method for the simultaneous estimation of Metoprolol succinate and Cilnidipine in bulk and pharmaceutical dosage form. Methods: The separation was carried out on STD Kromasil 150 C 18 (4.6 mm X 150 mm, 5 µ) column using acetonitrile: sodium dihydrogen ortho phosphate buffer (adjusted to pH 5 with 10 % OPA) in the ratio of 65: 35 % v/v as eluent. The flow rate was 0.8 ml/min and effluent was detected at 230 nm. Results: The retention time of Metoprolol succinate and Cilnidipine were found to be 2.27 and 3.26 min, respectively. The linear dynamic range was 62.5-375 μg/ml for Metorolol succinate and 12.5-75 μg/ml for Cilnidipine, respectively. Percentage recoveries for Metoprolol succinate and Cilnidipine were 99.73 – 99.93 % and 99.92 – 99.96 %, respectively. All the analytical validation parameters were determined and found in the limit as per ICH guidelines, which indicates the validity of the method. Conclusion: A simple, efficient and reproducible stability indicating RP-HPLC method for the simultaneous determination of Metoprolol Succinate and Cilnidipine in pharmaceutical dosage form has been developed and validated. The developed method was also found to be precise and robust for the simultaneous determination of Metoprolol succinate and Cilnidipine in tablet dosage forms.
THE POLITICAL ECOLOGY OF GRASSLAND CONSERVATION IN QINGHAI PROVINCE , CHINA : DISCOURSE , POLICIES AND THE HERDERS

comprises eight departments, associated research institutions and the Norwegian College of Veterinary Medicine in Oslo. Noragric was established in 1986, and its contribution to international development lies in the interface between research, education (Bachelor, Master and PhD programmes) and assignments. The Noragric Master theses are the final theses submitted by students in order to fulfil the requirements under the Noragric Master programme " Management of Natural Resources and Sustainable Agriculture " (MNRSA), " Development Studies " and other Master programmes. The findings in this thesis do not necessarily reflect the views of Noragric. Extracts from this publication may only be reproduced after prior consultation with the author and on condition that the source is indicated. For rights of reproduction or translation contact Noragric. iii Acknowledgements I would like to give a big thanks to my supervisor, Dr. Poul Wisborg, who has been patient, encouraging and helping me along the way. Thanks for all your advice and your time! Your help has been invaluable. Great thanks go to Dr. Marc Foggin. Thanks for all your help with finding respondents and information. Big thanks also go to Dr. Fiona Worthy for all your help, and to all the other staff in Plateau Perspective. Your home in Zhiduo is fascinating! I would also like to give special thanks to Carmen and Marvin Smith, who let me stay in their house, while conducting the field work. Your warmth and hospitality will never be forgotten. Big thanks also goes to NorServe staff, Tsebchen, by whom many of my interviews were made possible, and also for showing such engagement and care for fellow Tibetans. And sweet thanks to Lhamo. Thanks to NorServe who gave me this opportunity. I am further grateful for the support from Chinese authorities. Thanks to the Environmental Bureau, the Animal Husbandry Bureau, Yushu Grassland Station and Yushu County government. Thanks for finding time to meet with me and for the valuable information. taking time to meet me and the information I was provided with. Thanks also go to my translators, and especially to Eric who took me to his hometown and let me stay with his family. Last, but not the least, I would like to give a big thanks to the herders for opening their homes to me. My family and friends have been there in the ups and downs of writing this thesis. You have been helping and encouraging as …
Extensive Variation in the O-Antigen Gene Cluster within One Salmonella enterica Serogroup Reveals an Unexpected Complex History

ABSTRACT The 46 serogroups of Salmonella enterica have different O-antigens, and each is thought to have a specific form of the O-antigen cluster. Comparison of the 145 serovars of serogroup B revealed much more intraserogroup genetic diversity than expected. The O27 factor, due to an α 1-6 linkage between O units in place of the more common α 1-2 linkage and previously thought to be due to a converting bacteriophage, is now shown to be due to a wzyα(1-6) gene located within the major gene cluster. Surprisingly a remnant of this gene in all O27− serovars shows that the ancestor was O27+. There are six distinct gene cluster forms, five apparently derived by a series of deletions and one by an insertion from an ancestral O27+ form present in 57 serovars. The history of the gene cluster and movement between subspecies I and II can be traced. Two of the derivative forms still have a functional wzyα(1-6) gene, while in three it has been inactivated by deletion or insertion. Two of the forms lacking a functional wzyα(1-6) gene have the wzyα(1-2) gene first described for strain LT2 as rfc, whereas for the third the wzy gene has not been located.
Controlling Deliberation with the Success Probability in a Dynamic Environment

This paper describes a novel method to interleave planning with execution in a dynamic environment. Though, in such planning, it is very important to control deliberation: to determine the timing for interleaving them, few research has been done. To cope with this problem, we propose a method to determine the interleave timing with the success probability, SP, that a plan will be successfully executed in an environment. We also developed a method to compute it efficiently with Bayesian networks and implemented SIP system. The system stops planning when the locally optimal plan's SP falls below an execution threshold, and executes the plan. Since SP depends on dynamics of an environment, a system does reactive behavior in a very dynamic environment, and becomes deliberative in a static one. We made experiments in Tileworld by changing dynamics and observation costs. As a result, we found the optimal threshold between reactivity and deliberation in some problem classes. Furthermore we found out the optimal threshold is robust against the change of dynamics and observation cost, and one of the classes in which SIP works well is that the dynamics itself changes.
Light field rendering

A number of techniques have been proposed for flying through scenes by redisplaying previously rendered or digitized views. Techniques have also been proposed for interpolating between views by warping input images, using depth information or correspondences between multiple images. In this paper, we describe a simple and robust method for generating new views from arbitrary camera positions without depth information or feature matching, simply by combining and resampling the available images. The key to this technique lies in interpreting the input images as 2D slices of a 4D function - the light field. This function completely characterizes the flow of light through unobstructed space in a static scene with fixed illumination. We describe a sampled representation for light fields that allows for both efficient creation and display of inward and outward looking views. We have created light fields from large arrays of both rendered and digitized images. The latter are acquired using a video camera mounted on a computer-controlled gantry. Once a light field has been created, new views may be constructed in real time by extracting slices in appropriate directions. Since the success of the method depends on having a high sample rate, we describe a compression system that is able to compress the light fields we have generated by more than a factor of 100:1 with very little loss of fidelity. We also address the issues of antialiasing during creation, and resampling during slice extraction.
Fibroblast Growth Factor Receptors-1 and -3 Play Distinct Roles in the Regulation of Bladder Cancer Growth and Metastasis: Implications for Therapeutic Targeting

Fibroblast growth factor receptors (FGFRs) are activated by mutation and overexpressed in bladder cancers (BCs), and FGFR inhibitors are currently being evaluated in clinical trials in BC patients. However, BC cells display marked heterogeneity in their responses to FGFR inhibitors, and the biological mechanisms underlying this heterogeneity are not well defined. Here we used a novel inhibitor of FGFRs 1–3 and RNAi to determine the effects of inhibiting FGFR1 or FGFR3 in a panel of human BC cell lines. We observed that FGFR1 was expressed in BC cells that also expressed the “mesenchymal” markers ZEB1 and vimentin, whereas FGFR3 expression was restricted to the E-cadherin- and p63-positive “epithelial” subset. Sensitivity to the growth-inhibitory effects of BGJ-398 was also restricted to the “epithelial” BC cells and it correlated directly with FGFR3 mRNA levels but not with the presence of activating FGFR3 mutations. In contrast, BGJ-398 did not strongly inhibit proliferation but did block invasion in the “mesenchymal” BC cells in vitro. Similarly, BGJ-398 did not inhibit primary tumor growth but blocked the production of circulating tumor cells (CTCs) and the formation of lymph node and distant metastases in mice bearing orthotopically implanted “mesenchymal” UM-UC3 cells. Together, our data demonstrate that FGFR1 and FGFR3 have largely non-overlapping roles in regulating invasion/metastasis and proliferation in distinct “mesenchymal” and “epithelial” subsets of human BC cells. The results suggest that the tumor EMT phenotype will be an important determinant of the biological effects of FGFR inhibitors in patients.
Uncertainty-based active learning with instability estimation for text classification

This article deals with pool-based active learning with uncertainty sampling. While existing uncertainty sampling methods emphasize selection of instances near the decision boundary to increase the likelihood of selecting informative examples, our position is that this heuristic is a surrogate for selecting examples for which the current learning algorithm iteration is likely to misclassify. To more directly model this intuition, this article augments such uncertainty sampling methods and proposes a simple instability-based selective sampling approach to improving uncertainty-based active learning, in which the instability degree of each unlabeled example is estimated during the learning process. Experiments on seven evaluation datasets show that instability-based sampling methods can achieve significant improvements over the traditional uncertainty sampling method. In terms of the average percentage of actively selected examples required for the learner to achieve 99% of its performance when training on the entire dataset, instability sampling and sampling by instability and density methods achieve better effectiveness in annotation cost reduction than random sampling and traditional entropy-based uncertainty sampling. Our experimental results have also shown that instability-based methods yield no significant improvement for active learning with SVMs when a popular sigmoidal function is used to transform SVM outputs to posterior probabilities.