Miracle-dz/UniFAR-FTUs huggingface dataset:
Delay diversity codes for frequency selective channels

Space-time coding for the flat fading, quasi-static MIMO wireless channel has received widespread attention. This paper treats space-time code design for frequency selective channels from a single carrier modulation perspective. We present a general framework for analyzing space-time codes for delay spread channels based on PEP analysis. It is shown that as in the flat fading case, diversity gain is driven by the minimum rank of the pairwise codeword difference matrices. Delay spread, however, imposes a block Hankel structure on the codewords which may prevent certain codes designed for the flat fading case from exploiting full spatio-temporal diversity when used over frequency selective channels. We explicitly show this diversity loss for the delay diversity code. We show that a properly generalized delay diversity (GDD) code achieves full diversity over frequency selective channels. Finally we propose an extension to the GDD which fits naturally in a multi-carrier setting.
Better practices for youth tobacco cessation: evidence of review panel.

OBJECTIVES To offer programmers, policy makers, and researchers a scientific basis for developing and selecting smoking cessation treatments for adolescents. METHODS An evidence review panel systematically rated published and unpublished reports of cessation treatments for youth to make recommendations on theoretical foundations, delivery settings, types of intervention, and provider type. RESULTS Twenty studies had sufficient validity to inform the recommendations. The 9 studies that reported treatments that increased cessation were based on social cognitive theory. CONCLUSIONS Cognitive-behavioral interventions are a promising approach for helping young smokers quit smoking. Evidence is insufficient to draw other conclusions at this time.
Stabilizing Nonlinear Control Using Damper Currents Sliding Mode Observer of Synchronous Generator

In this article, a new observer-based nonlinear controller for excitation control of synchronous generator is presented. First, a nonlinear sliding mode observer for the synchronous machine damper currents is developed. Second, the existence of a control law for the complete seventh order model of a generator, which takes into account the stator dynamics as well as the damper effects, is proved by using the theory of Lyapunov. The stabilizing feedback law for the power system is shown to be Globally Exponentially Stable (GES) in the context of Lyapunov theory. Simulation results, for a single-Machine-Infinite-Bus (SMIB) power system, are given to demonstrate the effectiveness of the proposed combined obsever-controller for the transient stabilization and voltage regulation.
Finite State Control of FES-Assisted Walking with Spring Brake Orthosis

This paper presents finite state control (FSC) of paraplegic walking with wheel walker using functional electrical stimulation (FES) with spring brake orthosis (SBO). The work is a first effort towards restoring natural like swing phase in paraplegic gait through a new hybrid orthosis, referred to as spring brake orthosis (SBO). This mechanism simplifies the control task and results in smooth motion and more-natural like trajectory produced by the flexion reflex for gait in spinal cord injured subjects. The study is carried out with a model of humanoid with wheel walker using the Visual Nastran (Vn4D) dynamic simulation software. Stimulated muscle model of quadriceps is developed for knee extension. Fuzzy logic control (FLC) is developed in Matlab/Simulink to regulate the muscle stimulation pulse-width required to drive FES-assisted walking gait and the computed motion is visualised in graphic animation from Vn4D and finite state control is used to control the transaction between all walking states. Finite state control (FSC) is used to control the switching of brakes, FES and spring during walking cycle.
Detecting Periodic Elements in Higher Topological Hochschild Homology

Given a commutative ring spectrum $R$ let $\Lambda_XR$ be the Loday functor constructed by Brun, Carlson and Dundas. Given a prime $p\geq 5$ we calculate $\pi_*(\Lambda_{S^n}H\mathbb{F}_p)$ and $\pi_*(\Lambda_{T^n}H\mathbb{F}_p)$ for $n\leq p$, and use these results to deduce that $v_{n-1}$ in the $n-1$-th connective Morava $K$-theory of $(\Lambda_{T^{n}}H\mathbb{F}_p)^{hT^{n}}$ is non-zero and detected in the homotopy fixed point spectral sequence by an explicit element, which class we name the Rognes class. To facilitate these calculations we introduce Multifold Hopf algebras. Each axis circle in $T^n$ gives rise to a Hopf algebra structure on $\pi_*(\Lambda_{T^n}H\mathbb{F}_p)$, and the way these Hopf Algebra structures interact is encoded with a Multifold Hopf algebra structure. This structure puts several restrictions on the possible algrebra structures on $\pi_*(\Lambda_{T^n}H\mathbb{F}_p)$ and is a vital tool in the calculations above.
OSEECH: Optimize scalable energy efficient clustering hierarchy protocol in wireless sensor networks

Networks that do not include the use of wires or no physical links are required for communication is called Wireless Sensor Networks. Node deployment is done in the network that can also be called as sensor nodes and the responsibility or the task of these nodes is to enable communication in the network. These nodes have some energy value on which the performance of network depends like more is the residual energy of the nodes. The network performance also depends on the round for which first dead node is obtained and the round for which last alive node is achieved. Much advancement has been done in the field of energy efficient protocols to improve the energy efficiency of network. Clustering process was introduced and then techniques for Cluster head selection were developed and still more to come. Two most considered factors for designing energy efficient protocols are distance between the nodes and the energy value of nodes. The conventional protocols like LEACH, HEED, DEEC, SEECH are designed for improving the energy efficiency in WSNs. The effort in the paper is proposing one such protocol for improving energy efficiency in WSNs and this protocol is an up gradation in the SEECH protocol. The weight age factor is introduced in proposed technique for considering the energy value & the distance of nodes. The results are then optimized using Genetic Algorithm. The results are demonstrated and proved using MATLAB.
On the average values of the irreducible characters of finite groups of Lie type on geometric unipotent classes

In 1980, Lusztig posed the problem of showing the existence of a unipotent support for the irreducible characters of a nite reductive group G(F q ). This is de ned in terms of certain average values of the irreducible characters on unipotent classes. The problem was solved by Lusztig [16] for the case where q is a power of a su ciently large prime. In this paper we show that, in general, these average values can be expressed in terms of the Green functions of G. In good characteristic, these Green functions are given by polynomials in q. Combining this with Lusztig's results, we can then establish the existence of unipotent supports whenever q is a power of a good prime. 1991 Mathematics Subject Classi cation: Primary 20C33, secondary 20G40.
Sequential Estimation and Diffusion of Information Over Networks: A Bayesian Approach With Exponential Family of Distributions

Diffusion networks where nodes collaboratively estimate the parameters of stochastic models from shared observations and other estimates have become an established research topic. In this paper the problem of sequential estimation where information in the network diffuses with time is formulated abstractly and independently from any particular model. The objective is to reach a generic solution that is applicable to a wide class of popular models and based on the exponential family of distributions. The adopted Bayesian and information-theoretic paradigms provide probabilistically consistent means for incorporation of shared observations in the implemented estimation of the unknowns by the nodes as well as for effective combination of the “knowledge” of the nodes over the network. It is shown and illustrated on four examples that under certain conditions, the resulting algorithms are analytically tractable, either directly or after simple approximations. The examples include linear regression, Kalman filtering, logistic regression, and inference of an inhomogeneous Poisson process. The first two examples have their more or less direct counterparts in the state-of-the-art diffusion literature whereas the latter two are new.
Dynamic Reconfiguration in DEVS Component-based Modeling and Simulation 1

Dynamic reconfiguration refers to the ability of a system to dynamically change its structure and interface according to different situations. It provides component-based modeling and simulation environments with powerful modeling capability and the extra flexibility to design and analyze complex systems. In this paper, we discuss dynamic reconfiguration, specifically the variable structure and interface change capability, in DEVS modeling and simulation environments. The operations of structure and interface changes are discussed and their operation boundaries are defined. Three examples are given to illustrate the role of dynamic reconfiguration and how it can be used to model and design adaptive complex systems. Principles for the implementation of dynamic reconfiguration are also presented and illustrated in the DEVSJAVA modeling and simulation environment.
Calculation of eddy current loss and thermal analysis for adjustable permanent magnetic coupler

Adjustable permanent magnetic coupler adopts a new type of magnetic circuit coupling principle, generates inductive magnetic field in copper collar surface by cutting magnetic induction lines, transmits torque by coupled action between inductive magnetic field and permanent magnetic field. Hence, it necessarily causes eddy current loss and heating problem. The paper builds the mathematical model of 3D sporting eddy current field according to the relevant theory of electromagnetism, employs the 3D finite element method to calculate eddy current field in copper collar region, then determines eddy current and eddy current loss in copper collar surface, finally, studies the influence of related design parameters on heat.
Governance in the 21st century

The Africa in focus series is an initiative of the Human and Social Sciences Research Council (HSRC) that creates a forum for African scholars to frame research questions and examine critical issues affecting the African continent in the 21st century. The series should inspire robust debate to help inform the orientation of public policy in Africa. Will Africa's recuperative powers have dispelled the shadows of historically imposed predicaments by the end of the century? This question is at the core of this first volume in the series, in which contributors wrestle with 'lived realities' related to the unfolding process of democratic transformation across the African continent. The volume interrogates a range of issues: knowledge and its transformation; the need to manage natural resources; the economy viewed through the lens of actual livelihoods; other thorny challenges affecting social well-being in Africa and Africa's relationship with the rest of the world. In the early part of this 21st century, colonial legacies continue to circumscribe many of the hopes and aspirations pinned on democracy by people of the African continent. The challenges of the African state cannot always be explained through reference to the past, and the contributors put forward strong arguments for self-reliance among African people, ethical leadership, economic democracy, the indigenisation of knowledge and institutional reform. This seminal collection will be of interest to political scholars, students and professionals in the field of African Studies, as well as to policy-makers and public officials across the continent.
Detection of Diabetic Sensorimotor Polyneuropathy by Corneal Confocal Microscopy in Type 1 Diabetes

OBJECTIVE We aimed to determine the corneal confocal microscopy (CCM) parameter that best identifies diabetic sensorimotor polyneuropathy (DSP) in type 1 diabetes and to describe its performance characteristics. RESEARCH DESIGN AND METHODS Concurrent with clinical and electrophysiological examination for classification of DSP, CCM was performed on 89 type 1 diabetic and 64 healthy subjects to determine corneal nerve fiber length (CNFL), density, tortuosity, and branch density. Area under the curve (AUC) and optimal thresholds for DSP identification in those with diabetes were determined by receiver operating characteristic (ROC) curve analysis. RESULTS DSP was present in 33 (37%) subjects. With the exception of tortuosity, CCM parameters were significantly lower in DSP case subjects. In ROC curve analysis, AUC was greatest for CNFL (0.88) compared with fiber density (0.84, P = 0.0001), branch density (0.73, P < 0.0001), and tortuosity (0.55, P < 0.0001). The threshold value that optimized sensitivity and specificity for ruling in DSP was a CNFL of ≤14.0 mm/mm2 (sensitivity 85%, specificity 84%), associated with positive and negative likelihood ratios of 5.3 and 0.18. An alternate approach that used separate threshold values maximized sensitivity (threshold value ≥15.8 mm/mm2, sensitivity 91%, negative likelihood ratio 0.16) and specificity (≤11.5 mm/mm2, specificity 93%, positive likelihood ratio 8.5). CONCLUSIONS Among CCM parameters, CNFL best discriminated DSP cases from control subjects. A single threshold offers clinically acceptable operating characteristics, although a strategy that uses separate thresholds to respectively rule in and rule out DSP has excellent performance while minimizing unclassified subjects. We hypothesize that values between these thresholds indicate incipient nerve injury that represents those individuals at future neuropathy risk.
Use of conventional and -omics based methods for health claims of dietary antioxidants: a critical overview

This article describes the principles and limitations of methods used to investigate reactive oxygen species (ROS) protective properties of dietary constituents and is aimed at providing a better understanding of the requirements for science based health claims of antioxidant (AO) effects of foods. A number of currently used biochemical measurements aimed of determining the total antioxidant capacity and oxidised lipids and proteins are carried out under unphysiologcial conditions and are prone to artefact formation. Probably the most reliable approaches are measurements of isoprostanes as a parameter of lipid peroxidation and determination of oxidative DNA damage. Also the design of the experimental models has a strong impact on the reliability of AO studies: the common strategy is the identification of AO by in vitro screening with cell lines. This approach is based on the assumption that protection towards ROS is due to scavenging, but recent findings indicate that activation of transcription factors which regulate genes involved in antioxidant defence plays a key role in the mode of action of AO. These processes are not adequately represented in cell lines. Another shortcoming of in vitro experiments is that AO are metabolised in vivo and that most cell lines are lacking enzymes which catalyse these reactions. Compounds with large molecular configurations (chlorophylls, anthocyans and polyphenolics) are potent AO in vitro, but weak or no effects were observed in animal/human studies with realistic doses as they are poorly absorbed. The development of -omics approaches will improve the scientific basis for health claims. The evaluation of results from microarray and proteomics studies shows that it is not possible to establish a general signature of alterations of transcription and protein patterns by AO. However, it was shown that alterations of gene expression and protein levels caused by experimentally induced oxidative stress and ROS related diseases can be normalised by dietary AO.
13C NMR spectral data and molecular descriptors to predict the antioxidant activity of flavonoids

Tissue damage due to oxidative stress is directly linked to development of many, if not all, human morbidity factors and chronic diseases. In this context, the search for dietary natural occurring molecules with antioxidant activity, such as flavonoids, has become essential. In this study, we investigated a set of 41 flavonoids (23 flavones and 18 flavonols) analyzing their structures and biological antioxidant activity. The experimental data were submitted to a QSAR (quantitative structure-activity relationships) study. NMR 13C data were used to perform a Kohonen self-organizing map study, analyzing the weight that each carbon has in the activity. Additionally, we performed MLR (multilinear regression) using GA (genetic algorithms) and molecular descriptors to analyze the role that specific carbons and substitutions play in the activity.
Investment Opportunities, Leverage, and the Wealth Gains from Acquistion Program Announcements

We examine the stock price reaction to announcements of the intention to pursue a program of external acquisitions. Using a 1977-92 sample of 65 firms that have announcement dates which (i) can be explicitly identified and (ii) are uncontaminated by other firm-specific events, we confirm the Schipper and Thompson (1983) finding that the mean gain to such announcements is positive. This supports the view that financial markets capitalize the expected benefits of an acquisition program at the time of announcement. Our main focus is on the sources of cross-sectional variation in these gains. Consistent with research on individual acquisitions, shareholders of firms with high Tobin's q gain significantly more than the shareholders of low q firms. However, the share price reaction is a monotonically increasing function of q only for firms with low leverage. Moreover, among the sub-groups of (i) q > 1 firms and (ii) firms that subsequently make at least one acquisition bid in the three years following the program announcement, the share price reaction is lower for high leverage firms than it is for low leverage firms. These results suggest that high leverage is seen as a potential impediment to a successful acquisition program.
Efficient grasp planning using continuous collision detection

Grasp planning for multifingered robotic hand is still time consuming. The crucial part is to find the contact points with collision detection techniques to evaluate the grasp quality and to guarantee that the hand does not collide with other objects. Our methods to accelerate the collision detection for grasp planning are presented in this paper. Grasping is performed in two steps: hand moving and finger closing. Finger links are a-priori known for both steps. We use precomputed bounding boxes to bound the extent of the finger links' motion to cull the objects that are far from robotic hand. A state-of-the-art continuous collision detection with conservative advancement is integrated to detect collisions between moving robotic hand and objects. For pick-and-place operation the environments by grasping and by placing are merged to one environment for grasp planning to find collision-free grasps for both pick and place. Ray intersections are further used to find out hidden grasping directions. We have tested our approach with three experiments: grasping a standalone object with one hand, two hands and grasping in complex environment. Results with four-fingered SAHands in simulation show the efficiency of the introduced methods.
Improved Minimum Squared Error Algorithm with Applications to Face Recognition

Minimum squared error based classification (MSEC) method establishes a unique classification model for all the test samples. However, this classification model may be not optimal for each test sample. This paper proposes an improved MSEC (IMSEC) method, which is tailored for each test sample. The proposed method first roughly identifies the possible classes of the test sample, and then establishes a minimum squared error (MSE) model based on the training samples from these possible classes of the test sample. We apply our method to face recognition. The experimental results on several datasets show that IMSEC outperforms MSEC and the other state-of-the-art methods in terms of accuracy.
Modeling the Emotional State of Computer Users

We describe the structure of a Bayesian network des ign d to monitor the behavior of a user interacting with a conversational computer and use that information to estimate the user’s emotional state. Our model f emotional state uses two discrete dimensions, valen ce (bad to good) and arousal (calm to excited), to capture the dominant aspects of physical emotional response. Emotion is expressed behaviorally in a variety of w ays, including by linguistic choices, qualities of vocal expression, and movement. In this paper, we focus n vocal expression, and its correlation with emoti onal state, using the psychological literature to sugges t the appropriate parameterization of our Bayesian model.
Research on rapid walking of biped robot based on parametric surface table cart model

Stable walking conditions are reinforced for sliding & wheelspin of robot. Deduced ZMP formula based on jerk which is introduced by 3 ranks Taylor formula. Parametric surface table cart model used for dynamics is proposed. Rapid walking pattern of biped robot is generated based on parametric surface table cart model. Finally, dynamics simulation of the 3-D virtual prototype of the biped robot is completed in the dynamic software, the walking speed is 2.088km/h.
Applying A Machine Intelligence Algorithm for Prediction

This paper presents an application of the C4.5 algorithm for generating prediction rules in various real-world data sets. The data sets consist of different kinds of attribute types including numerical, categorical, and mix types. In our experiments, the C4.5 pruned/unpruned tree algorithm is applied to four different kinds of data sets obtained from the UCI Machine Learning Repository and pools of wells in the region of Saskatchewan, Canada. The result showed that the C4.5 algorithm performed well on categorical, numerical and mix-type data. The pruned C4.5 tree algorithm demonstrated having better performance than the unpruned one when these types of data are concerned. It also discusses the limitations of this algorithm and possible extension when predicting future production performance of oil wells
Introducing the Civil Wars Mediation (CWM) dataset

Mediation is one of the few mechanisms the international community can deploy that will affect civil wars. This article introduces the dataset on mediation in civil wars – termed the Civil War Mediation (CWM) dataset. This is the first dataset to focus solely on civil war mediation. These data contribute to the present state of quantitative research on mediation in three important respects: the data are collected for the period of 1946–2004, are organized by mediation cases and by civil war episode, and provide detailed information about mediation incidences. The article first presents a few variables included in the dataset that are motivated by theoretical arguments from the literature. After a presentation of summary statistics, attention is turned to using the CWM data to explore the determinants of mediation. Mediation is shown to be a function of war type (territorial and internationalized wars are more likely to be mediated), war duration (the longer the war the higher the probability of mediation), supply-side factors (the number of democracies in the world and the global polity average), and stratum (subsequent wars are less likely to be mediated). Battle-related deaths also seem to increase the chances of mediation, though the relationship is only weakly significant. The article concludes with suggestions for future research that can benefit from the dataset.