Miracle-dz/UniFAR-FTUs huggingface dataset:
Induction of Apoptosis and Antitumor Activity of Eel Skin Mucus, Containing Lactose-Binding Molecules, on Human Leukemic K562 Cells

For innate immune defense, lower animals such as fish and amphibian are covered with skin mucus, which acts as both a mechanical and biochemical barrier. Although several mucus sources have been isolated and studied for their biochemical and immunological functions, the precise mechanism(s) of action remains unknown. In the present study, we additionally found the eel skin mucus (ESM) to be a promising candidate for use in anti-tumor therapy. Our results showed that the viability of K562 cells was decreased in a dose-dependent manner by treatment with the isolated ESM. The cleaved forms of caspase-9, caspase-3 and poly adenosine diphosphate-ribose polymerase were increased by ESM. The levels of Bax expression and released cytochrome C were also increased after treatment with ESM. Furthermore, during the ESM mediated-apoptosis, phosphorylation levels of ERK1/2 and p38 but not JNK were increased and cell viabilities of the co-treated cells with ESM and inhibitors of ERK 1/2 or p38 were also increased. In addition, treatment with lactose rescued the ESM-mediated decrease in cell viability, indicating lactose-containing glycans in the leukemia cells acted as a counterpart of the ESM for interaction. Taken together, these results suggest that ESM could induce mitochondria-mediated apoptosis through membrane interaction of the K562 human leukemia cells. To the best of our knowledge, this is the first observation that ESM has anti-tumor activity in human cells.
Gesture-based Bootstrapping for Egocentric Hand Segmentation

Accurately identifying hands in images is a key sub-task for human activity understanding with wearable first-person point-of-view cameras. Traditional hand segmentation approaches rely on a large corpus of manually labeled data to generate robust hand detectors. However, these approaches still face challenges as the appearance of the hand varies greatly across users, tasks, environments or illumination conditions. A key observation in the case of many wearable applications and interfaces is that, it is only necessary to accurately detect the user's hands in a specific situational context. Based on this observation, we introduce an interactive approach to learn a person-specific hand segmentation model that does not require any manually labeled training data. Our approach proceeds in two steps, an interactive bootstrapping step for identifying moving hand regions, followed by learning a personalized user specific hand appearance model. Concretely, our approach uses two convolutional neural networks: (1) a gesture network that uses pre-defined motion information to detect the hand region; and (2) an appearance network that learns a person specific model of the hand region based on the output of the gesture network. During training, to make the appearance network robust to errors in the gesture network, the loss function of the former network incorporates the confidence of the gesture network while learning. Experiments demonstrate the robustness of our approach with an F1 score over 0.8 on all challenging datasets across a wide range of illumination and hand appearance variations, improving over a baseline approach by over 10%.
Cellular immunity survey against urinary tract infection using pVAX/fimH cassette with mammalian and wild type codon usage as a DNA vaccine

Purpose FimH (the adhesion fragment of type 1 fimbriae) is implicated in uropathogenic Escherichia coli (UPEC) attachment to epithelial cells through interaction with mannose. Recently, some studies have found that UPEC can thrive intracellularly causing recurrent urinary tract infection (UTI). Almost all vaccines have been designed to induce antibodies against UPEC. Yet, the humoral immune response is not potent enough to overcome neither the primary UTI nor recurrent infections. However, DNA vaccines offer the possibility of inducing cell mediated immune responses and may be a promising preventive tool. Materials and Methods In this study, we employed two different open reading frames within mammalian (mam) and wild type (wt) codons of fimH gene. Optimized fragments were cloned in pVAX-1. Expression of the protein in COS-7 was confirmed by western blot analysis after assessing pVAX/fimH(mam) and pVAX/fimH(wt). The constructs were injected to BALB/c mice at plantar surface of feet followed by electroporation. Results The mice immunized with both constructs following booster injection with recombinant FimH showed increased interferon-γ and interleukin-12 responses significantly higher than non-immunized ones (p<0.05). The immunized mice were challenged with UPEC and then the number of bacteria recovered from the immunized mice was compared with the non-immunized ones. Decreased colony count in immunized mice along with cytokine responses confirmed the promising immune response by the DNA vaccines developed in this study. Conclusion In conclusion, DNA vaccines of UPEC proteins may confer some levels of protection which can be improved by multiple constructs or boosters.
Ultrasound-guided angioplasty of dialysis fistula – technique description

Summary Endovascular procedures are commonly used for treatment of vascular pathologies. These interventions are routinely performed under angiographic control. Angioplasty is increasingly more often used for correction of dialysis fistula – especially dilatation of stenosis. We describe the technique of dialysis fistula angioplasty under ultrasound control. Benefits of this procedure include lack of nephrotoxic contrast, what is especially important in chronic kidney disease patients in pre-dialysis period. Advantages of ultrasound guidance during dialysis fistula angioplasty lead to cause more and more frequent employment of this technique.
Text Localisation and Handwriting Recognition: Application to Numeral Extraction and Recognition

This report discusses several general aspects of text localisation and handwriting recognition. In particular, we consider their applications to extraction and recognition of numerals written on Giro forms. For text localisation, we investigate the problem of extracting text printed or written inside boxes on forms. We review a number of representative methods for solving this problem, describe the implementation of one of them, and present some experimental results obtained on real data. For handwriting recognition, we rst present the standard general methodology, then apply it to handwritten numeral recognition, and nally propose a new approach, called perturbation-based, that allowed us to boost the recognition rate up to 99:1% on a worldwide standard database.
Barriers to firm growth in open economies

Abstract Studies measuring barriers to firm growth assume economies are closed, ignoring information on firm exports. We argue that this information is key to interpreting data and improving the accuracy of model predictions. To do this, we develop a dynamic model with export and domestic barriers. We show theoretically that the closed economy model underestimates barriers and amplifies counterfactuals. By calibrating the model to a set of European countries, we find that the quantitative difference is significant: for example, the closed economy model fails to see that Italian firms are very efficient exporters but poor innovators, and instead concludes that they are mediocre innovators. In terms of predictions, the closed economy model delivers an elasticity of welfare to innovation costs between 31 and 64 percent larger than the open economy model.
EXHAUSTIVE LIST-SCHEDULING HEURISTIC FOR DENSE TASK GRAPHS*

The multiprocessor scheduling problem has usually been "solved" by using heuristic methods. A large number of such heuristics can be found in the literature, but none of them can efficiently be applied to the problem in its most general form. The efficiency of any scheduling heuristic depends on both the task graph structure and the multiprocessor system architecture. List-scheduling heuristics are the most common ones in use. They are based on the definition of the task priority list determining the order in which tasks will be scheduled (assigned to one of the processors). A task can be assigned to a processor in many different ways, but variations of the earliest start heuristics are the most frequent in use. In this paper a scheduling strategy based on the use of multiple task priority lists combined with several assignment heuristics is suggested in order to find optimal (near-optimal at the worst) solutions for a large class of arbitrary task graphs. It is shown that performing an exhaustive search overall feasible task priority lists is not too expensive for scheduling dense task graphs.
Random Graphs for Performance Evaluation of Recommender Systems

The purpose of this article is to introduce a new analytical framework dedicated to measuring performance of recommender systems. The standard approach is to assess the quality of a system by means of accuracy related statistics. However, the specificity of the environments in which recommender systems are deployed requires to pay much attention to speed and memory requirements of the algorithms. Unfortunately, it is implausible to assess accurately the complexity of various algorithms with formal tools. This can be attributed to the fact that such analyses are usually based on an assumption of dense representation of underlying data structures. Whereas, in real life the algorithms operate on sparse data and are implemented with collections dedicated for them. Therefore, we propose to measure the complexity of recommender systems with artificial datasets that posses real-life properties. We utilize recently developed bipartite graph generator to evaluate how state-of-the-art recommender systems' behavior is determined and diversified by topological properties of the generated datasets.
Optimal radio resource allocation for mobile task offloading in cellular networks

The increasing capabilities of mobile devices (MDs) enable users to run desktoplevel applications and tasks anywhere. However, the local execution of resource-demanding mobile tasks, such as real-time rendering in 3D gaming, may result in poor performance and short battery lifetime on MDs. One solution to the resource scarcity problem on MDs is to offload resource-demanding mobile tasks to surrogates, which are remote servers with stronger capabilities. When multiple MDs in the same cell attempt to offload mobile tasks to surrogates through a cellular network, the communication latencies for data transmissions may be high due to limited radio resources. To improve the offloading performance of mobile tasks, the limited radio resources should be carefully scheduled to reduce the communication latencies of data transmissions. As motivated, we pose the optimal radio resource allocation problem for the mobile task offloading in cellular networks, and solve the problem. Moreover, extensive numerical results show the performance comparison of the optimal radio resource allocation plan and two baseline plans.
Interference characteristics in power-controlled cognitive radio networks

Dynamic spectrum access using cognitive radios has been proposed as an approach to meet the increasing demand for radio spectrum. Under this novel access paradigm unlicensed cognitive radios are allowed to utilize the white spaces across licensed spectrum on a non-interfering basis. Realization of this concept therefore requires a model translating the regulatory constraint on aggregate interference to system design parameters. Thus far, a few models of aggregate interference have been proposed however, these mainly examine the distribution of interference without explicitly modelling transmit power control. In this paper a statistical model of interference aggregation in power-controlled cognitive radio networks is developed. In particular, distribution of the aggregate interference is characterized in terms of parameters such as density of cognitive radios and access points as well as the underlying propagation environment. The model is further extended to account for the effect of correlated shadowing on the distribution of aggregate interference.
Using Mobile & Personal Sensing Technologies to Support Health Behavior Change in Everyday Life: Lessons Learned

Lifestyle modification is a key facet of the prevention and management of chronic diseases. Mobile devices that people already carry provide a promising platform for facilitating these lifestyle changes. This paper describes key lessons learned from the development and evaluation of two mobile systems for encouraging physical activity. We argue that by supporting persistent cognitive activation of health goals, encouraging an extensive range of relevant healthy behaviors, focusing on long-term patterns of activity, and facilitating social support as an optional but not primary motivator, systems can be developed that effectively motivate behavior change and provide support when and where people make decisions that affect their health.
Resolution of a Supertree / Supermatrix Paradox

Systematic Biology Publication details, including instructions for authors and subscription information: http://www.informaworld. com/smpp/title~content=t713658732 Resolution of a Supertree/Supermatrix Paradox John Gatesy a; Conrad Matthee b; Rob DeSalle c; Cheryl Hayashi a a Department of Biology, University of California, Riverside, California 92521, USA. b Department of Zoology, University of Stellenbosch, Stellenbosch 7602, South Africa. c Department of Invertebrates, American Museum of Natural History, Central Park West at 79th Street, New York, New York 10024, USA.
Foraging biology predicts food web complexity

Food webs, the networks of feeding links between species, are central to our understanding of ecosystem structure, stability, and function. One of the key aspects of food web structure is complexity, or connectance, the number of links expressed as a proportion of the total possible number of links. Connectance (complexity) is linked to the stability of webs and is a key parameter in recent models of other aspects of web structure. However, there is still no fundamental biological explanation for connectance in food webs. Here, we propose that constraints on diet breadth, driven by optimal foraging, provide such an explanation. We show that a simple diet breadth model predicts highly constrained values of connectance as an emergent consequence of individual foraging behavior. When combined with features of real food web data, such as taxonomic and trophic aggregation and cumulative sampling of diets, the model predicts well the levels of connectance and scaling of connectance with species richness, seen in real food webs. This result is a previously undescribed synthesis of foraging theory and food web theory, in which network properties emerge from the behavior of individuals and, as such, provides a mechanistic explanation of connectance currently lacking in food web models.
Static model of pneumatic flexible rotary joint

Service robot, bionic robot and agricultural robot must directly contact with organism, which requires high security and adaptability. Flexible pneumatic actuators and joints can meet this demand. A type of flexible pneumatic rotary joint is proposed in this paper, based on the flexible pneumatic actuator FPA. The rotation movement is realized by inflating and deflating the rotary joint chamber. According to the principle of equilibrium of moments, the static model of rotary joint are established. Impact of the parameters initial angle, average radius and shell thickness on the output angle of rotary joint is simulated with MATLAB. The experimental results are basically consistent with that of simulation, which implies the validity of rotary joint static model.
Multiscale modeling in computational biomechanics

Biomechanics is broadly defined as the scientific discipline that investigates the effects of forces acting on and within biological structures. The realm of biomechanics includes the circulatory and respiratory systems, tissue mechanics and mechanotransduction, and the musculoskeletal system and motor control. As in many other biological phenomena, many spatial scales are crossed by biomechanics research: intracellular, multicellular, and extracellular matrices; and tissue, organ, and multiorgan systems. It is well established that the effect of forces at higher scales influence behavior at lower scales and that lower-scale properties influence higher-scale response. However, computational methods that incorporate these interactions in biomechanics are relatively rare. In general, computational models that include representation of multiple spatial or temporal scales are loosely defined as multiscale. The fact that multiscale modeling is not well defined lends the term to a variety of scenarios within the computational physiology community. In biomechanics, multiscale modeling may mean establishing a hierarchical link between the spatial and temporal scales, while the output of a larger-scale system is passed through a finely detailed representation at a lower scale (e.g., body-level movement simulations that provide net joint loading for tissue-level stress analysis). In reality, multiscale modeling may require more intricate representation of interactions among scales. A concurrent simulation strategy is inevitable to adequately represent nonlinear associations that have been known for decades [1].
Managing Foreign R&D in China

OVERVIEW: China has become one of the most desired locations in which to do R&D. However, it has little innovation of its own, and intellectual property protection is weak. This raises questions: Is China R&D more hype than reality? Do cost advantages really outweigh the risk of losing technology to Chinese competitors? Lessons learned from managing R&D in China show that in order to avoid the typical pitfalls of managing R&D in a developing country, any China-based R&D must be part of an overall China strategy and must also be part of a global R&D effort.
THE SKILL AND HIGHER EDUCATIONAL CONTENT OF UK NET EXPORTS

This paper reports evidence on the factor content of UK trade in 1984 in terms of both broad aggregates of factors and of disaggregated skill categories. It also reports the result of a similar analysis of the higher educational content of UK net exports. This provides not only a measure of the sources of a country's comparative advantage but also of the relative scarcity of factors of production. The study finds that the UK was scare in both skilled manual and semi-skilled manual labor relative to unskilled labor in 1984. It also finds that the UK is relatively poorly endowed in many professional skills in comparison to sales and clerical skills. Higher education, however, is found to be a source of comparative advantage. Copyright 1993 by Blackwell Publishing Ltd
The Reward-Based Negotiation Model on Agent's Honesty and Capability

The likelihood of reaching agreement was increased and quality of an agreement was promoted by exchanging arguments which influence each others’ states, and trust mechanism was introduced into the process of negotiation by combining the agent’s honesty and agent’s capability. This paper proposed a new reward-based negotiation’s model by introducing the concept and algorithm of agent’s honesty and capability.
Performance evaluation of location update schemes for MANET

In this paper, we have developed an analytical model to evaluate the performance of home agent, quorum based, and grid location service update schemes using Markov chain. The model evaluates the performance in terms of the cost of updates and queries. The cost of updates is computed in terms of the hops used in updating a location. The model also considers selective queries for destination search to compute the cost of queries, such that the cost of queries is computed in terms of the hops used in searching for destination. Finally, the average total cost that includes the update cost and query cost is determined. In the model, moving node initiates a location update using a distance based triggering strategy. The average total cost is determined for different threshold distances. The analytical results show that the home agent location update scheme outperforms quorum based and grid location service location update schemes.
A hierarchical reinforcement learning algorithm based on heuristic reward function

A hierarchical reinforcement learning method based on heuristic reward function is proposed to solve the problem of “curse of dimensionality”, that is the states space will grow exponentially in the number of features, and low convergence speed. The method can reduce state spaces greatly and can enhance the speed of the study. Choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply this method to the Tetris game; the experiment result shows that the method can partly solve the “curse of dimensionality” and can enhance the convergence speed prominent.
Empirical science of financial fluctuations : the advent of econophysics

Preface Part 1. Empirical Facts of Financial Market Fluctuations: 1-1. Basic Market Statistics - Quantifying Empirical Economic Fluctuations using the Organizing Principles of Scale Invariance and Universality - Price Fluctuations and Market Activity - Transaction Interval Analysis of High Resolution Foreign Exchange Data 1-2. Cross-Correlations - Random Matrix Theory and Cross-Correlations of Stock Prices - A Random Matrix Theory Approach to Quantifying Collective Behavior of Stock Price Fluctuations - Dynamics of Correlations in the Stock Market - False EUR Exchange Rates vs. DKK, CHF, JPY and USD 1-3. Market Anomalies - Crashes: Symptoms, diagnoses and remedies - Variety of Stock Returns in Normal and Extreme Market Days: The August 1998 Crises - A Mechanism of International Transmission of financial Crises - High Frequency Data Analysis in an Emerging and in a Developed Market - Measuring Long-Range Dependence in Electricity Prices Part 2. Various Approaches to Financial Markets: 2-1. Agent-Based Modeling - Micro-Simulations of Financial Markets and the Stylized Facts - Statistical Property of Price Fluctuations in a Multi-Agent Model - A Speculative Financial Market Model - Spin-Grass Like Network Model for Stock Market - Three Bodies Trading Model in Financial Markets and Its Numerical Simulation Methodology with Genetic Algorithms - Deviation of ARCH(1) Process from Market Price Changes: Based on Feteministic Microscopic Multi-Agent 2-2. Stochastic Modeling - A Simple Model of Volatility Fluctuations in Asset Markets - Self-Similarity of Price Fluctuations and Market Dynamics - Survival Probability of LIFFE bond Futures via the Mittag-Leffler Function - Why is Fat-Tailed? - Market Price Simulator Based on Analog Electrical Circuit - Simulation and Analysis of a Power Law Fluctuation Generator - Deformation of Implied Volatility Surfaces: An Empirical Analysis 2-3. Prediction and Investment Strategy - Predictability of Market Prices - Time-Spaces Scaling of Financial Time Series - Parameter Estimation of a Generalized Langevin Equation of Market Price - Analysis of Stock Markets, Currency Exchanges and Tax Revenues - Trading System Applied to Large Mutual Fund Company Part 3. Other Topics: 3-1. Relation to Economic Theories - Why Financial Markets Will Remain Marginally Inefficient - The Law of Consumer Demand in Japan: A Macroscopic Microeconomic View - A Functional-Analytic and Numerical-Analytic Approach to Nonlinear Economic Models Described by the Master Equation 3-2. Corporate and Individual Statistics - Modelling the Growth Statistics of Economic Organizations - Statistical Laws in the Income of Japanese Companies - Empirical Identification of Competitive Strategies: Russian Bank System - Paretos Las for Income of Individuals - Physics of Personal Income.