Miracle-dz/UniFAR-FTUs huggingface dataset:
Actions of Two Bi-Articular Muscles of the Lower Extremity: A Review

The extremities of the human body contain several bi-articular muscles. The actions produced by muscles at the joints they cross are greatly influenced by joint moment arms and muscle length. These factors are dynamic and subject to change as joint angles are altered. Therefore, to more completely understand the actions of such muscles, the angles of both joints must be manipulated. This report reviews investigations, which have explored the actions of two bi-articular muscles of the lower extremities (gastrocnemius and rectus femoris) as the joints they cross are moved into various combinations of angles. The findings have both clinical and physical performance ramifications.
Multi-finger manipulation of virtual objects

The manipulation of a virtual object by means of a digital glove is a tedious task for repetitive position and orientation adjustments. In this paper we try to overcome the lack of force feedback of general purpose digital gloves. We propose a solution based only on the interpretation of instantaneous hand posture variations. From this knowledge, a virtual contact model analog to the Coulomb law allows to evaluate the instantaneous nature of the contact, firm or sliding, between virtual sensors attached to the fingers and the virtual object. Although no force feedback is supplied, we are able to derive a visual restitution consistent with the user manipulative intentions while respecting the integrity of solid interaction with friction.
China's Economic Development

The authors identify three major factors in the growth of the Chinese economy: economic decentralization and political centralization; the urban–rural divide; and relational society. These are explored in depth via analyses of factors including urban and rural economic development and their political and social foundations, industrial agglomeration, transitions of public services and governmental responsibilities towards them and developmental imbalances and mechanisms. It is illustrated that whilst contemporary China has obviously made great economic strides, a wide variety of problems are accumulating over time. The book concludes that following three decades of high economic growth, China now faces great challenges for sustainable growth, and the institutions of China’s economy have reached a critical point. Strategies for dealing with these challenges and requirements for the successful future development of China are thus prescribed.
Mn-euvering manganese: the role of transporter gene family members in manganese uptake and mobilization in plants

Manganese (Mn), an essential trace element, is important for plant health. In plants, Mn serves as a cofactor in essential processes such as photosynthesis, lipid biosynthesis and oxidative stress. Mn deficient plants exhibit decreased growth and yield and are more susceptible to pathogens and damage at freezing temperatures. Mn deficiency is most prominent on alkaline soils with approximately one third of the world's soils being too alkaline for optimal crop production. Despite the importance of Mn in plant development, relatively little is known about how it traffics between plant tissues and into and out of organelles. Several gene transporter families have been implicated in Mn transport in plants. These transporter families include NRAMP (natural resistance associated macrophage protein), YSL (yellow stripe-like), ZIP (zinc regulated transporter/iron-regulated transporter [ZRT/IRT1]-related protein), CAX (cation exchanger), CCX (calcium cation exchangers), CDF/MTP (cation diffusion facilitator/metal tolerance protein), P-type ATPases and VIT (vacuolar iron transporter). A combination of techniques including mutant analysis and Synchrotron X-ray Fluorescence Spectroscopy can assist in identifying essential transporters of Mn. Such knowledge would vastly improve our understanding of plant Mn homeostasis.
An Upper Limit on the Reflected Light from the Planet Orbiting the Star τ Bootis

The planet orbiting τ Boo at a separation of 0.046 AU could produce a reflected light flux as bright as 1 × 10-4 relative to that of the star. A spectrum of the system will contain a reflected light component which varies in amplitude and Doppler shift as the planet orbits the star. Assuming the secondary spectrum is primarily the reflected stellar spectrum, we can limit the relative reflected light flux to be less than 5 × 10-5. This implies an upper limit of 0.3 for the planetary geometric albedo near 480 nm, assuming a planetary radius of 1.2 RJup. This albedo is significantly less than that of any of the giant planets of the solar system and is not consistent with certain published theoretical predictions.
Is the use of self-rated health measures to assess health inequalities misleading?

Is the use of self-rated health measures to assess health inequalities misleading? In three studies published in IJE, 1–3 authors examined whether the association between self-rated health (SRH) and mortality varied by socioeconomic status (SES). They then used the empirical results to comment on the potential discordance in the magnitude of social inequalities in health when estimated using SRH as opposed to mortality. The three studies, however, arrived at different conclusions about the potential misestimation of health inequalities when using SRH instead of mortality. Huisman and colleagues concluded that a weak interaction between SRH and education whilst predicting mortality is unlikely to result in over-estimation of educational differences in health status. 1 Meanwhile, Singh-Manoux and colleagues concluded that use of SRH might underestimate health inequalities by income and occupation. 3 Dowd and colleagues reported that 'self-rated health does not predict mortality as well at lower levels of SES', but do not speculate on whether this will result in over-or underestimation of social inequalities in health. 2 Testing whether the association between SRH and mortality varies by SES can at best provide indirect clues as to whether the use of SRH (instead of mortality) over-or underestimates health inequalities. Furthermore, interpretations of interactions in generalized linear models are not straightforward. It is, therefore, surprising that the authors did not directly test whether social inequalities in health are misestimated, even though this seems possible with the datasets they used for their analyses. Using the Established Populations for the Epide-miologic Study of the Elderly (EPESE) dataset 4 —the same dataset used by Idler and colleagues in their classic study showing that SRH predicts mortality 5 — we conducted a direct test of the difference in social inequalities in health when predicting SRH compared with mortality. We used education and income collected in 1982 to predict poor SRH in 1994 and mortality before 1994 in the New Haven EPESE study population. The mean (SD) age of subjects in 1982 was 74.2 (6.8). As shown in the Table 1, compared with those with a college degree or more, the odds ratio (OR) for reporting fair/poor/bad health for those with less than a high school education was 2.28 (95% CI 1.22–4.25); the corresponding OR for mortality was 2.04 (95% CI 1.41–2.94). Concordance in the ORs were observed across other educational categories as well as by income (Table 1). We also tested for the presence of an interaction …
Face Detection for Improved Security at Parking Lot Checkpoints

In order to detect and respond to criminal activity in and around residential, industrial, and commercial areas, security personnel need efficient access to security video footage. In this paper, we introduce a new system, SAFES, whose aim is to enable rapid search of security video footage acquired at parking lot security checkpoints by indexing that footage according to the faces that appear in it. SAFES is trained by example to extract the faces appearing in a security video stream automatically. Our initial prototype, although needing improvement, demonstrates the promise of the approach.
Using Collaborative Filtering in a new domain: traffic analysis

The importance of information systems is increasing every day. In order to ensure their right operation, it is necessary to analyze a huge amount of traffic generated by different devices. However, classical techniques for operation and management are reactive and not proactive, what can evolve in a failure in the system. In this work we propose a new approach where we analyze network traffic using Collaborative Filtering. In other domains, these systems have proved to filter thousands of items according to user needs and tastes. They can predict user preferences and recommend relevant items for the user. In this sense, in this new domain, relevant items are data flows, so our goal is to recommend flows which are related to the traffic already captured.
A comprehensive monitoring framework for virtual computing environment

Virtualization can divide or aggregate the underlying resource flexibly, and it attracts attention from both academic and industry in recent years. Guest operating systems in virtual machines can be various, and the states of virtual machines changes all the time. Due to the complexity of virtual computing environment, it brings tremendous challenges for security monitoring. Existing monitoring mechanism can not adapt to the dynamic and diversity of virtual machines. Therefore, a comprehensive monitoring framework, named ComMon, is proposed in this paper, which implements comprehensive monitoring from three aspects: network, process, and file. It has the characteristics of real-time, transparency and generality.
INCLUSION AS A REFORM: HOW SECONDARY GENERAL EDUCATORS MAKE SENSE OF AND ENACT THEIR ROLES AS TEACHERS OF STUDENTS WITH DISABILITIES

Title of Dissertation: INCLUSION AS A REFORM: HOW SECONDARY GENERAL EDUCATORS MAKE SENSE OF AND ENACT THEIR ROLES AS TEACHERS OF STUDENTS WITH DISABILITIES Amanda Stefanski, Doctor of Philosophy, 2014 Dissertation directed by: Dr. Linda Valli Department of Teaching and Learning, Policy and Leadership Federal legislation and individual state requirements have prompted exponential growth in the inclusion of students with special needs in the general education classroom, for which general education teachers report not feeling prepared. In addition to an accompanying increase in both preservice and in-service offerings, various organizations have established standards detailing the expectations for what general education teachers should know and be able to do; however, there is minimal research that examines these standards in terms of the teachers who are expected to meet them or to determine why certain inclusive practices are more often and easily enacted than others. My goal in this study was to examine the ways that teachers make sense of their roles and responsibilities related to students with disabilities and learn more about how and why certain inclusive practices are enacted more than others. Because teachers say they “weren’t prepared” for this student population, an equally important goal was to connect that information to recommendations for teacher preparation. I designed the current study using sensemaking theory (Weick, 1995) and Spillane’s (1999) model of enactment zones as a framework to address the research questions. The findings of this study suggest that teachers identified the same inclusive practices as had been detailed in the literature: instructional and professional practices, legal requirements, and dispositions. Through a combination of direct questioning and culling through teachers’ responses with a sensemaking lens, I identified two facilitating factors and seven barriers that affect teachers’ enactment of these roles and responsibilities. The various data (focus group, interview, and observations) yielded specific information about whether and how inclusive practices are being enacted in secondary inclusive settings, and a secondary analysis focusing primarily on how teachers made sense of these practices provided additional insight into their enactments. Additionally, the teachers in this study provided three specific ways that teacher preparation (preservice and in-service) can be adapted in such a way that a total redesign is not required: SHOW ME examples of inclusive practices, GIVE ME the tools to do them more effectively, and LET ME practice them. INCLUSION AS A REFORM: HOW SECONDARY GENERAL EDUCATORS MAKE SENSE OF AND ENACT THEIR ROLES AS TEACHERS OF STUDENTS WITH DISABILITIES
A Born approximation from backscattering data for live loads in Lamé system

We will study the inverse scattering problem for the Lame equation in elasticity with live loads. We give the definition of a Born approximation of the load from backscattering data. We will see that in 2D, for non-smooth load matrices the main singularities of the matrices are in fact contained in their Born approximations. The singularities are measured in the scale of Sobolev spaces.
Overview Synaptic Plasticity Underlies Behavioral Modification in Invertebrates Plasticity of Mature Synapses and Circuits

The capacity of the nervous system to change—generally referred to as neural plasticity—is obvious during the development of neural circuits. However, the adult brain must also possess substantial plasticity in order to learn new skills, establish new memories, and respond to injury throughout life. Although the mechanisms responsible for ongoing changes in the adult brain are not completely understood, altered neural function in maturity appears to rely primarily on carefully regulated changes in the strength of existing synapses. Experiments carried out in a variety of animals, ranging from sea slugs to primates, have shown that synaptic strength can be altered over periods that range from milliseconds to months. The molecular mechanisms underlying these changes are post-translational modifications of proteins and, in the case of longer-lasting effects, changes in gene expression. To some extent, changes in synaptic circuitry can also occur by localized formation of new axon terminals and dendritic processes. More extensive changes occur when the adult nervous system is damaged by trauma or disease, although regeneration of connections in the brain and spinal cord is sharply limited. Modest optimism regarding this unfortunate clinical situation is warranted by the observation that new neurons can be generated throughout life in a limited number of brain regions, suggesting that new cells can be integrated into existing circuits. An obvious obstacle to exploring change in the brains of humans and other mammals is the enormous number of neurons and the complexity of synap-tic connections. As a consequence, it is difficult to unambiguously attribute a behavioral modification to changes in the properties of specific neurons or synapses. One way to circumvent this dilemma is to examine plasticity in far simpler nervous systems. The assumption in this strategy is that plasticity is so fundamental that its essential cellular and molecular underpinnings are likely to be conserved in the nervous systems of very different organisms. One of the most successful examples of this approach has been that of Eric Kandel and his colleagues at Columbia University using the marine mollusk Aplysia californica (Figure 24.1A). This sea slug has only a few tens of thousands of neurons, many of which are quite large (up to 1 mm in diameter) and in stereotyped locations within the ganglia that make up the animal's nervous system (Figure 24.1B). These attributes make it practical to monitor the electrical and chemical signaling of specific, identifiable nerve
Overlapping Coalition Formation for Efficient Data Fusion in Multi-Sensor Networks

This paper develops new algorithms for coalition formation within multi-sensor networks tasked with performing wide-area surveillance. Specifically, we cast this application as an instance of coalition formation, with overlapping coalitions. We show that within this application area subadditive coalition valuations are typical, and we thus use this structural property of the problem to derive two novel algorithms (an approximate greedy one that operates in polynomial time and has a calculated bound to the optimum, and an optimal branch-and-bound one) to find the optimal coalition structure in this instance. We empirically evaluate the performance of these algorithms within a generic model of a multi-sensor network performing wide area surveillance. These results show that the polynomial algorithm typically generated solutions much closer to the optimal than the theoretical bound, and prove the effectiveness of our pruning procedure.
Generalized Property R and the Schoenflies Conjecture

There is a relation between the generalized Property R Conjecture and the Schoenflies Conjecture that suggests a new line of attack on the latter. The new approach gives a quick proof of the genus 2 Schoenflies Conjecture and suffices to prove the genus 3 case, even in the absence of new progress on the generalized Property R Conjecture. Mathematics Subject Classification (2000). 57Q25, 57N13.
Frequency Control by Decentralized Controllable Heating Loads with H∞ controller

Many isolated small power systems are powered by diesel generators, which results in greater operating costs than interconnected large grids. It is therefore desirable to integrate renewable energy sources such as wind power into these small grids. However, due to the fluctuating power generation from renewable energy sources, frequency deviations of power systems become problematic. Distributed intelligent load control can be used to significantly increase renewable energy penetration and cut diesel fuel c onsumption. This paper presents a methodology for grid frequency control by electric water heaters as controllable loads. This system consists of diesel generator, wind farm, and loads. By applying a power consumption controller adopted from H ∞ control theory, grid frequency deviation is maintained around rated value. In order to verify the effectiveness of the proposed system, MATLAB/Simulink is used for simulations .
The Formulae-as-Classes Interpretation of Constructive Set Theory

The main objective of this paper is to show that a certain formulae-asclasses interpretation based on generalized set recursive functions provides a selfvalidating semantics for Constructive Zermelo-Fraenkel Set theory, CZF. It is argued that this interpretation plays a similar role for CZF as the constructible hierarchy for classical set theory, in that it can be employed to show that CZF is expandable by several forms of the axiom of choice without adding more consistency strength.
Applying Local Search and Genetic Evolution in Concept Learning Systems to Detect Intrusion in Computer Networks

The detection of intrusions over computer networks (i.e., network access by non-authorized users) can be cast to the task of detecting anomalous patterns of network traffic. In this case, models of normal traffic have to be determined and compared against the current network traffic. We compare models of network traffic acquired by a system based on a distributed genetic algorithm with the ones acquired by a system based on greedy heuristics. Also we show that representation change of the network data can result in a significant increase in the classification performances of the traffic models. Network data made available from the Information Exploration Shootout project has been chosen as experimental testbed.
Efficient social network approximate analysis on blogosphere based on network structure characteristics

As a typical social media in Web 2.0, blogs have attracted a surge of researches. Unlike the traditional studies, the social networks mined from Internet are very large, which makes a lot of social network analyzing algorithms to be intractable. According to this phenomenon, this paper addresses the novel problem of efficient social networks analyzing on blogs. This paper turns to account the structural characteristics of real large-scale complex networks, and proposes a novel shortest path approximate algorithm to calculate the distance and shortest path between nodes efficiently. The approximate algorithm then is incorporated with social network analysis algorithms and measurements for large-scale social networks analysis. We illustrate the advantages of the approximate analysis through the centrality measurements and community mining algorithms. The experiments demonstrate the effectiveness of the proposed algorithms on blogs, which indicates the necessity of taking account of the structural characteristics of complex networks when optimizing the analysis algorithms on large-scale social networks.
Time-space optimal convex Hull algorithms

A point set S is said to be convex if for any two points p, q in S, the line segment pq is also in S. Any point r on the segment pq can be expressed as a convex corrsbina~ion of the two end points p and q. This idea is readily extended to that of a convex polygon and a convex hull. Given a set S of N distinct points in the two-dimensional Euclidean plane, the convex hull of S, denoted by CH(S), is the smallest convex polygon containing S. A pint inside the convex hull can be represented as a convex combination of the points on the convex hull. The convex hull conrainmenr property of Bezier curves, Bexzier surfaces and B-splines is central to Computer Aided Geometric Design [2].
Predicting Bankruptcy Using Neural Networks in the Current Financial Crisis: A Study of U.S. Commercial Banks

We develop a model of neural networks to study the bankruptcy of U.S. banks. We provide a new model to predict bank defaults some time before the bankruptcy occurs, taking into account the specific features of the current financial crisis. Based on data from the Federal Deposit Insurance Corporation, our results corroborate that distressed banks undertook higher credit risks and were more heavily concentrated on real estate. Interestingly, the distressed banks do not show lower cost efficiency than their wealthy counterparts, suggesting that bank failures are a consequence of careless bank strategies rather than low cost efficiency. After drawing the profile of distressed banks, we use our model to predict future bankruptcies and test the performance of the model by comparing our predictions with the actual bankruptcies between January-June 2010. Our model shows a high discriminant power and is able to differentiate correctly wealthy and distressed banks. Specifically, our model would have been able to predict in December 2009 around 60% of failures that occurred in the first six months of 2010.
Calibrations, monopoles, and fuzzy funnels

We present new non-Abelian solitonic configurations in the low energy effective theory describing a collection of N parallel D1--branes. These configurations preserve 1/4, 1/8, 1/16 and 1/32 of the spacetime supersymmetry. They are solutions to a set of generalised Nahm's equations which are related to self-duality equations in eight dimensions. Our solutions represent D1--branes which expand into fuzzy funnel configurations ending on collections of intersecting D3--branes. Supersymmetry dictates that such intersecting D3--branes must lie on a calibrated three-surface of spacetime and we argue that the generalised Nahm's equations encode the data for the construction of magnetic monopoles on the relevant three-surfaces.