Miracle-dz/UniFAR-FTUs huggingface dataset:
Limited feedback for antenna selection in MIMO-OFDM systems

An antenna selection method based on channel state information (CSI) is proposed for an MIMO-OFDM system. In this method, the receiver of the system exploits selection combing to demodulate received signals and estimates the CSI of each pair of transmit and receive antennas. For each subchannel of the system, the transmit antenna in the pair with the maximum magnitude of subchannel response is selected to carry a data sym- bol. The transmitter then is informed of the selection through a feedback channel. As a result, the probability that the magnitude of the subchannel response is small becomes much lower. Since most symbol errors occur while the magnitude of the subchannel response is small, the symbol error rate (SER) of the system can be significantly reduced. The SER expressions for BPSK and M-QAM are provided. Moreover, we combine this method with full-rate full-diversity space-frequency codes. Performance of the space-frequency code is dramatically improved.
Immunogenicity and Efficacy of Flagellin-Fused Vaccine Candidates Targeting 2009 Pandemic H1N1 Influenza in Mice

We have previously demonstrated that the globular head of the hemagglutinin (HA) antigen fused to flagellin of Salmonella typhimurium fljB (STF2, a TLR5 ligand) elicits protective immunity to H1N1 and H5N1 lethal influenza infections in mice (Song et al., 2008, PLoS ONE 3, e2257; Song et al., 2009, Vaccine 27, 5875–5888). These fusion proteins can be efficiently and economically manufactured in E. coli fermentation systems as next generation pandemic and seasonal influenza vaccines. Here we report immunogenicity and efficacy results of three vaccine candidates in which the HA globular head of A/California/07/2009 (H1N1) was fused to STF2 at the C-terminus (STF2.HA1), in replace of domain 3 (STF2R3.HA1), or in both positions (STF2R3.2xHA1). For all three vaccines, two subcutaneous immunizations of BALB/c mice with doses of either 0.3 or 3 µg elicit robust neutralizing (HAI) antibodies, that lead to > = 2 Log10 unit reduction in day 4 lung virus titer and full protection against a lethal A/California/04/2009 challenge. Vaccination with doses as low as 0.03 µg results in partial to full protection. Each candidate, particularly the STF2R3.HA1 and STF2R3.2xHA1 candidates, elicits robust neutralizing antibody responses that last for at least 8 months. The STF2R3.HA1 candidate, which was intermediately protective in the challenge models, is more immunogenic than the H1N1 components of two commercially available trivalent inactivated influenza vaccines (TIVs) in mice. Taken together, the results demonstrate that all three vaccine candidates are highly immunogenic and efficacious in mice, and that the STF2R3.2xHA1 format is the most effective candidate vaccine format.
The Young: Neuroapoptosis Induced by Anesthetics and What to Do About It

Millions of human fetuses, infants, and children are exposed to anesthetic drugs every year in the United States and throughout the world. Anesthesia administered during critical stages of neurodevelopment has been considered safe and without adverse long-term consequences. However, recent reports provide mounting evidence that exposure of the immature animal brain to anesthetics during the period of rapid synaptogenesis, also known as the brain growth spurt period, triggers widespread apoptotic neurodegeneration, inhibits neurogenesis, and causes significant long-term neurocognitive impairment. Herein, we summarize currently available evidence for anesthesia-induced pathological changes in the brain and associated long-term neurocognitive deficits and discuss promising strategies for protecting the developing brain from the potentially injurious effects of anesthetic drugs while allowing the beneficial actions of these drugs to be realized.
Current conveyor realization of synchronized Chua’s circuits for binary communications

A novel application of the current conveyor (CC) device is proposed for the realization of a chaotic communication system based on Chua's oscillators. A slave circuit is unidirectionally coupled to a master circuit to recover private binary signals by generalized Hamiltonian forms. The slave circuit which is called observer has a system of equations which is suitable to be interpreted in mixed mode integrated circuit design. In this manner, (CCs) are used for the coupling and also in the Chua's nonlinear resistor external control. TopSpice simulations are presented taking into account parasitic effects by including the general parameters of a commercially available CC.
International Journal of Advanced Robotic Systems The Puller-Follower Control of Compliant and Noncompliant Antagonistic Tendon Drives in Robotic Systems Regular Paper

This paper proposes a new control strategy for noncompliant and compliant antagonistic tendon drives. It is applied to a succession of increasingly complex single‐joint systems, starting with a linear and noncompliant system and ending with a revolute, nonlinearly tendon coupled and compliant system. The last configuration mimics the typical human joint structure, used as a model for certain joints of the anthropomimetic robot ECCEROBOT. The control strategy is based on a biologically inspired puller‐ follower concept, which distinguishes the roles of the agonist and antagonist motors. One actuator, the puller, is considered as being primarily responsible for the motion, while the follower prevents its tendon from becoming slack by maintaining its tendon force at some non‐zero level. Certain movements require switching actuator roles; adaptive co‐contraction is used to prevent tendons slackening, while maintaining energetic efficiency. The single‐joint control strategy is then evaluated in a multi‐ joint system. Dealing with the gravitational and dynamic effects arising from the coupling in a multi‐joint system, a robust control design has to be applied with on‐line gravity compensation. Finally, an experiment corresponding to object grasping is presented to show the controller’s robustness to external disturbances.
AHEMS: Asynchronous Hardware-Enforced Memory Safety

This paper presents AHEMS (Asynchronous Hardware-Enforced Memory Safety), an architectural support for enforcing spatial and temporal memory safety to protect against memory corruption attacks. We integrated AHEMS with the Leon3 open-source processor and prototype on an FPGA. In an evaluation of the detection coverage using 677 security test cases (including spatial and temporal memory errors), selected from the Juliet Test Suite, AHEMS detected all but one memory safety violation. The missed test case involves overflow of a sub-object in a data structure whose detection is not supported by the current prototype. Performance assessment using the Olden benchmarks shows an average 10.6% overhead, and negligible impact on the processor-critical path (0.06% overhead) and power consumption (0.5% overhead).
Enhanced clustering based AODV-R protocol using Ant Colony Optimization in VANETS

Vehicular Adhoc Networks (VANETS) enable the vehicles to communicate with each other as well as with road side units. But developing an efficient routing for these networks potentially due to the large mobility and regular changes in these networks is a challenging job. In VANETS transmission links are at the risk of disconnection. Thus the development of the efficient routing mechanism is needed in VANETS. It is observed in literature survey that the AODV-R outperforms all other related protocols. But still issues related to congestion control needs to be addressed. This paper proposes a Ant Colony Optimization based AODV-R protocol for better data aggregation and route selection. The proposed methodology has shown quite significant improvement over available ones.
Relational Data Mining and Subgroup Discovery

In Inductive Logic Programming (ILP), the recent shift of attention from program synthesis to knowledge discovery resulted in advanced relational data mining techniques that are practically applicable for discovering knowledge in relational databases. This paper gives a brief introduction to ILP, presents the state-of-the-art ILP techniques for relational knowledge discovery and outlines recent approaches to relational subgroup discovery.
Extracellular environment contribution to astrogliosis—lessons learned from a tissue engineered 3D model of the glial scar

Glial scars are widely seen as a (bio)mechanical barrier to central nervous system regeneration. Due to the lack of a screening platform, which could allow in-vitro testing of several variables simultaneously, up to now no comprehensive study has addressed and clarified how different lesion microenvironment properties affect astrogliosis. Using astrocytes cultured in alginate gels and meningeal fibroblast conditioned medium, we have built a simple and reproducible 3D culture system of astrogliosis mimicking many features of the glial scar. Cells in this 3D culture model behave similarly to scar astrocytes, showing changes in gene expression (e.g., GFAP) and increased extra-cellular matrix production (chondroitin 4 sulfate and collagen), inhibiting neuronal outgrowth. This behavior being influenced by the hydrogel network properties. Astrocytic reactivity was found to be dependent on RhoA activity, and targeting RhoA using shRNA-mediated lentivirus reduced astrocytic reactivity. Further, we have shown that chemical inhibition of RhoA with ibuprofen or indirectly targeting RhoA by the induction of extracellular matrix composition modification with chondroitinase ABC, can diminish astrogliosis. Besides presenting the extracellular matrix as a key modulator of astrogliosis, this simple, controlled and reproducible 3D culture system constitutes a good scar-like system and offers great potential in future neurodegenerative mechanism studies, as well as in drug screenings envisaging the development of new therapeutic approaches to minimize the effects of the glial scar in the context of central nervous system disease.
Basic Concepts of Formal Ontology

The term ‘formal ontology’ was first used by the philosopher Edmund Husserl in his Logical Investigations to signify the study of those formal structures and relations – above all relations of part and whole – which are exemplified in the subject-matters of the different material sciences. We follow Husserl in presenting the basic concepts of formal ontology as falling into three groups: the theory of part and whole, the theory of dependence, and the theory of boundary, continuity and contact. These basic concepts are presented in relation to the problem of providing an account of the formal ontology of the mesoscopic realm of everyday experience, and specifically of providing an account of the concept of individual substance.
Generalized Analysis in Sequence Kernel SVM

In the text-independent speaker recognition system, Support Vector Machine (SVM) equipped with sequence kernel has been widely used. In this paper, a generic structure conceiving sequence kernel has been encapsulated and in the structure we make an analytical comparison between two well used sequence kernel system-GMM Super vector Kernel (GSK) and Generalized Linear Discriminant Sequence (GLDS) showing how different attribute and levels of cues conveyed by speech utterances are being characterized within different sequence kernel. In the NIST 2006 SRE corpus, recognition rate improves significantly compared with the traditional GMM and Universal Background Models (GMM-UBM) system.
Coupling blood flow and neural function in the retina: a model for homeostatic responses to ocular perfusion pressure challenge

Retinal function is known to be more resistant than blood flow to acute reduction of ocular perfusion pressure (OPP). To understand the mechanisms underlying the disconnect between blood flow and neural function, a mathematical model is developed in this study, which proposes that increased oxygen extraction ratio compensates for relative ischemia to sustain retinal function. In addition, the model incorporates a term to account for a pressure‐related mechanical stress on neurons when OPP reduction is achieved by intraocular pressure (IOP) elevation. We show that this model, combining ocular blood flow, oxygen extraction ratio, and IOP mechanical stress on neurons, accounts for retinal function over a wide range of OPP manipulations. The robustness of the model is tested against experimental data where ocular blood flow, oxygen tension, and retinal function were simultaneously measured during acute OPP manipulation. The model provides a basis for understanding the retinal hemodynamic responses to short‐term OPP challenge.
A rule-based static dataflow clustering algorithm for efficient embedded software synthesis

In this paper, an efficient embedded software synthesis approach based on a generalized clustering algorithm for static dataflow subgraphs embedded in general dataflow graphs is proposed. The clustered subgraph is quasi-statically scheduled, thus improving performance of the synthesized software in terms of latency and throughput compared to a dynamically scheduled execution. The proposed clustering algorithm outperforms previous approaches by a faster computation and a more compact representation of the derived quasi-static schedules. This is achieved by a rule-based approach, which avoids an explicit enumeration of the state space. Experimental results show significant improvements in both performance and code size when compared to a state-of-the-art clustering algorithm.
An Examination of Teachers’ Perceptions of Principal Support for Change and Teachers’ Collaboration and Communication around Literacy Instruction in Reading First Schools

Little research has directly examined whether principal leadership can increase the degree to which teachers work together regularly in focused ways around content. Prior research has shown that reform efforts seeking to alter the process of teaching can be successful if teachers collaborate to build capacity and improve instruction. Furthermore, the research literature has highlighted supportive principal leadership as a key component of teachers’ perception of an effective collaborative change process. This study examines the empirical link between teachers’ perceptions of principal support for change and teachers’ reports of the degree of collaboration and communication with one another around literacy. The data for this study was collected in all 165 Reading First schools in Michigan in the 2006-2007 school year. Survey data was collected from 1,738 teachers across all schools. Data for this study was collected as part of the evaluation of Reading First in Michigan. Literacy teachers in kindergarten through third grade completed surveys at three points throughout the school year (fall, winter, and spring). These surveys contained questions about principal support for change and collaboration and communication around literacy. The primary analytic method employed in this study was multilevel modeling. Factor analysis and full information maximum likelihood estimation were also used. The measure of principal support for change was a significant positive predictor of teachers’ assessment of the degree of regular collaboration and communication around reading instruction; a one standard deviation increase in teachers’ reports of principal support for change was associated with a 0.202 standard deviation increase in teachers’ assessment of the degree of collaboration and communication around literacy when controlling for the other variables in the model. This paper demonstrates that the degree to which teachers report collaboration and communication around literacy in Reading First schools is significantly related to their perceptions of principal support for change. If policymakers expect teachers to collaborate around issues of instruction, then they need to consider the principal's role in supporting change in the school by encouraging teachers to improve their instruction and take the risks associated with innovation. In sum, the results of this study are important for educators, as the role of the principal is potentially critical for positive changes in teacher collaboration and, consequently, student achievement in high-poverty schools.
ARP Spoofing Based Access Control for DLNA Devices

With the prevalence of digital content and Internet, a variety of digital applications and intelligent home applications are involved in daily family life. DLNA (Digital Living Network Alliance) has provided standard guidelines to improve the interoperability of DLNA-capable devices and to enhance the usability of digital contents through DLNA Certified devices. In current DLNA specification, a DLNA device advertises its presence to everyone in the local network. Any control point application receiving the advertisement can access or control the device, and the device cannot keep its content and services away from unwanted control points. In this paper we propose an external or non-intrusive access control approach to protect devices from illegal access in DLNA networks. This approach exploits an ARP (Address Resolution Protocol) spoofing technique and a flexible list of access policies to block unauthorized DLNA requests. A software system named as DACS is implemented to realize the access control mechanism proposed in this paper. Without changing the DLNA specification, our system can be applied seamlessly with any "old" or "new" DLNA devices.
Towards an Ontological Language for Game Analysis

The Game Ontology Project (GOP) is creating a framework for describing, analyzing and studying games, by defining a hierarchy of concepts abstracted from an analysis of many specific games. GOP borrows concepts and methods from prototype theory as well as grounded theory to achieve a framework that is always growing and changing as ne w games are analyzed or particular research questions are explored. The top level of the ontolo gy (interface, rules, goals, entities, and entity manipulation) is described as well as a part icular ontological entry. Finally, by engaging in three short discussions centered on relevant games studies research questions, the ontology’s utility is demonstrated.
Protostellar Turbulence Driven by Collimated Outflows

We investigate the global properties of the outflow-driven protostellar turbulence through 3D MHD simulations. The simulations show that the turbulence in regions of active cluster formation is quickly transformed by the forming stars through protostellar outflows, and that strongly influences and perhaps controls protostellar turbulence cluster formation. We find that collimated outflows are more efficient in driving turbulence than spherical outflows that carry the same amounts of momentum. This is because collimated outflows can propagate farther away from their sources, effectively increasing the turbulence driving length; turbulence driven on a larger scale decays more slowly. Gravity plays an important role in shaping the turbulence, generating infall motions that balance the outward motions driven by outflows. The resulting quasi-equilibrium state is maintained through a slow rate of star formation, with a fraction of the total mass converted into stars per free-fall time as low as a few percent. Magnetic fields are dynamically important even in magnetically supercritical clumps, provided that their initial strengths are not far below the critical value for static cloud support. They contain an energy comparable to the turbulent energy and can significantly reduce the rate of star formation. The mass-weighted probability distribution function (PDF) of the volume density of the protostellar turbulence is often, although not always, approximately lognormal. The PDFs of the column density deviate more strongly from lognormal distributions. There is a prominent break in the power spectrum, which may provide a way to distinguish it from other types of turbulence.
Global iceberg detection over distributed data streams

In today's Internet applications or sensor networks we often encounter large amounts of data spread over many physically distributed nodes. The sheer volume of the data and bandwidth constraints make it impractical to send all the data to one central node for query processing. Finding distributed icebergs—elements that may have low frequency at individual nodes but high aggregate frequency—is a problem that arises commonly in practice. In this paper we present a novel algorithm with two notable properties. First, its accuracy guarantee and communication cost are independent of the way in which element counts (for both icebergs and non-icebergs) are split amongst the nodes. Second, it works even when each distributed data set is a stream (i.e., one pass data access only). Our algorithm builds upon sketches constructed for the estimation of the second frequency moment (F2) of data streams. The intuition of our idea is that when there are global icebergs in the union of these data streams the F2 of the union becomes very large. This quantity can be estimated due to the summable nature of F2 sketches. Our key innovation here is to establish tight theoretical guarantees of our algorithm, under certain reasonable assumptions, using an interesting combination of convex ordering theory and large deviation techniques.
Multi-objective Genetic Algorithms: Problem Difficulties and Construction of Test Problems

In this paper, we study the problem features that may cause a multi-objective genetic algorithm (GA) difficulty in converging to the true Pareto-optimal front. Identification of such features helps us develop difficult test problems for multi-objective optimization. Multi-objective test problems are constructed from single-objective optimization problems, thereby allowing known difficult features of single-objective problems (such as multi-modality, isolation, or deception) to be directly transferred to the corresponding multi-objective problem. In addition, test problems having features specific to multi-objective optimization are also constructed. More importantly, these difficult test problems will enable researchers to test their algorithms for specific aspects of multi-objective optimization.
The short-cut network within protein residue networks

A protein residue network (PRN) is a network of interacting amino acids within a protein. We describe characteristics of a sparser, highly central and more volatile sub-network of a PRN called the short-cut network (SCN), as a protein folds under molecular dynamics (MD) simulation with the goal of understanding how proteins form navigable small-world networks within themselves. The edges of an SCN are found via a local greedy search on a PRN. SCNs grow in size and transitivity strength as a protein folds, and SCNs from successful MD trajectories are better formed in these terms. Findings from an investigation on how to model the formation of SCNs using dynamic graph theory, and suggestions to move forward are presented. A SCN is enriched with short-range contacts and its formation correlates positively with secondary structure formation. Thus our approach to modeling PRN formation, in essence protein folding from a graph theoretic view point, is more in tune with the notion of increasing order to a random graph than the other way around, and this increase in order coincides with improved navigability of PRNs.