Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Spectrum Auction Design with Two-Dimensional Truthful Revelations under Uncertain Spectrum Availability

In this paper, we propose a novel sealed-bid auction framework to address the problem of dynamic spectrum allocation in cognitive radio (CR) networks. We design an optimal auction mechanism that maximizes the moderator's expected utility, when the spectrum is not available with certainty. We assume that the moderator employs collaborative spectrum sensing in order to make a reliable inference about spectrum availability. Due to the presence of a collision cost whenever the moderator makes an erroneous inference, and a sensing cost at each CR, we investigate feasibility conditions that guarantee a non-negative utility at the moderator. We present tight theoretical-bounds on instantaneous network throughput and also show that our algorithm provides maximum throughput if the CRs have i.i. d. valuations. Since the moderator fuses CRs' sensing decisions to obtain a global inference regarding spectrum availability, we propose a novel strategy-proof fusion rule that encourages the CRs to simultaneously reveal truthful sensing decisions, along with truthful valuations to the moderator. Numerical examples are also presented to provide insights into the performance of the proposed auction under different scenarios.
Using Individualized Brain Network for Analyzing Structural Covariance of the Cerebral Cortex in Alzheimer's Patients

Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are “small world. ” There were significant difference between NC and AD group in characteristic path lengths (z = −2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC dataset.
Soccer matches as experiments: how often does the ‘best’ team win?

Models in which the number of goals scored by a team in a soccer match follow a Poisson distribution, or a closely related one, have been widely discussed. We here consider a soccer match as an experiment to assess which of two teams is superior and examine the probability that the outcome of the experiment (match) truly represents the relative abilities of the two teams. Given a final score, it is possible by using a Bayesian approach to quantify the probability that it was or was not the case that ‘the best team won’. For typical scores, the probability of a misleading result is significant. Modifying the rules of the game to increase the typical number of goals scored would improve the situation, but a level of confidence that would normally be regarded as satisfactory could not be obtained unless the character of the game was radically changed.
Interleaving subthalamic nucleus deep brain stimulation to avoid side effects while achieving satisfactory motor benefits in Parkinson disease

Background: Deep brain stimulation (DBS) of the subthalamic nucleus is an effective treatment for advanced Parkinson disease (PD). However, achieving ideal outcomes by conventional programming can be difficult in some patients, resulting in suboptimal control of PD symptoms and stimulation-induced adverse effects. Interleaving stimulation (ILS) is a newer programming technique that can individually optimize the stimulation area, thereby improving control of PD symptoms while alleviating stimulation-induced side effects after conventional programming fails to achieve the desired results. Methods: We retrospectively reviewed PD patients who received DBS programming during the previous 4 years in our hospital. We collected clinical and demographic data from 12 patients who received ILS because of incomplete alleviation of PD symptoms or stimulation-induced adverse effects after conventional programming had proven ineffective or intolerable. Appropriate lead location was confirmed with postoperative reconstruction images. The rationale and clinical efficacy of ILS was analyzed. Results: We divided our patients into 4 groups based on the following symptoms: stimulation-induced dysarthria and choreoathetoid dyskinesias, gait disturbance, and incomplete control of parkinsonism. After treatment with ILS, patients showed satisfactory improvement in PD symptoms and alleviation of stimulation-induced side effects, with a mean improvement in Unified PD Rating Scale motor scores of 26.9%. Conclusions: ILS is a newer choice and effective programming strategy to maximize symptom control in PD while decreasing stimulation-induced adverse effects when conventional programming fails to achieve satisfactory outcome. However, we should keep in mind that most DBS patients are routinely treated with conventional stimulation and that not all patients benefit from ILS. ILS is not recommended as the first choice of programming, and it is recommended only when patients have unsatisfactory control of PD symptoms or stimulation-induced side effects after multiple treatments with conventional stimulation. A return to conventional stimulation may be required if ILS induces new side effects or the needs of the patient change.
Analysis of the transtheoretical model of behavior change

The focus of this paper is on the Transtheoretical Model of Behavior Change (TTM). A description of the model, the applications toward modifying health behavior, and the model’s criticisms will all be examined. Through research of published literature, the paper concludes that the model does in fact seem to support health behavior change and shows potential for effective, appropriate intervention. More research is necessary in the area of measurement validity, criteria consistency, and application over unique populations to make the model more widely accepted. Introduction The purpose of this paper is to describe the Transtheoretical Model of Behavior Change, discuss the applications it has for modifying health behaviors, and discuss the criticisms of the model. There are many thoughts, ideas, and theories that try to explain how people modify their own behaviors but not one of them is universally agreed upon. The Transtheoretical Model of Behavior Change (TTM), created by Prochaska and DiClemente (1983), is one of the more popular theories used to describe this event. The TTM is a model of intentional change that focuses on the decision-making abilities of the individual rather than the social and biological influences on behavior as other approaches tried (Velicer, Prochaska, Fava, Norman, & Redding, 1998; Scholl, 2002). This model grew from systematic integration of more than 300 theories of psychotherapy, along with analysis of the leading theories of behavior change (Prochaska & Velicer, 1997). The critical assumptions of the TTM and main constructs which include the stages of change, processes of change, self-efficacy, and decisional balance will be examined in detail below (Patten, Vollman, & Thurston, 2000; Prochaska & Velicer, 1997; Velicer et al., 1998; Scholl, 2002).
Secrecy Sum-Rates for Multi-User MIMO Regularized Channel Inversion Precoding

In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter α and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter αLS of the precoder using large-system analysis. We show that the RCI precoder with αLS outperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed α. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing α and the power allocation vector. The jointly optimized precoder outperforms RCI with αLS and equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas.
A Nine-Level Inverter Topology for Medium-Voltage Induction Motor Drive With Open-End Stator Winding

A new scheme for nine-level voltage space-vector generation for medium-voltage induction motor (IM) drives with open-end stator winding is presented in this paper. The proposed nine-level power converter topology consists of two conventional three-phase two-level voltage source inverters powered by isolated dc sources and six floating-capacitor-connected <formula formulatype="inline"><tex Notation="TeX">$H$</tex></formula>-bridges. The <formula formulatype="inline"><tex Notation="TeX">$H$</tex></formula>-bridge capacitor voltages are effectively maintained at the required asymmetrical levels by employing a space vector modulation (SVPWM) based control strategy. An interesting feature of this topology is its ability to function in five- or three-level mode, in the entire modulation range, at full-power rating, in the event of any failure in the <formula formulatype="inline"><tex Notation="TeX">$H$</tex></formula> -bridges. This feature significantly improves the reliability of the proposed drive system. Each leg of the three-phase two-level inverters used in this topology switches only for a half cycle of the reference voltage waveform. Hence, the effective switching frequency is reduced by half, resulting in switching loss reduction in high-voltage devices. The transient as well as the steady-state performance of the proposed nine-level inverter-fed IM drive system is experimentally verified in the entire modulation range including the overmodulation region.
TOWARD AN “AUSTRIAN” THEORY OF SUSTAINABLE COMPETITIVE ADVANTAGE: THE ROLE OF VALUE-ENHANCING COMPETITIVE ACTIONS GOCE ANDREVSKI

We develop a dynamic model of sustainable competitive advantage in hypercompetitive environments. We argue that competitive advantages of firms can be sustainable even if resource-based advantages of firms can be quickly replicated by rivals or when the barriers to entry are almost non-existent. This is accomplished through intensive entrepreneurial activity of firms during the equilibrating tendencies of the market process. We develop a concept of valueenhancing entrepreneurial actions to show that the intensity with which a firm recognizes more productive resource combinations and progressively enhances the value of its products and services is primary driver of sustainable competitive advantage. We then complement the Austrian methodological individualism with the network embeddedness to provide more comprehensive, contextualized understanding of sustainability of competitive advantages in hypercompetitive environments.
A novel lip-reading method using RGB-D camera

Many studies have been carried out on lip reading, most of those works are based on color images, while some essential features might not be obtained, like inner lip information. In this paper, RGB-D camera will be introduced for improving the recognition rate of lip reading. We try to complete lip reading through using only gray-scale images. Thirteen groups of words are given, and we present eight features for classification. Volunteers are asked to sit in the front of RGB-D camera. For each word we select 15 frames. KNN is used to select the same words between different volunteers.
Critical behaviour in charging of electric vehicles

The increasing penetration of electric vehicles over the coming decades, taken together with the high cost to upgrade local distribution networks and consumer demand for home charging, suggest that managing congestion on low voltage networks will be a crucial component of the electric vehicle revolution and the move away from fossil fuels in transportation. Here, we model the max-flow and proportional fairness protocols for the control of congestion caused by a fleet of vehicles charging on two real-world distribution networks. We show that the system undergoes a continuous phase transition to a congested state as a function of the rate of vehicles plugging to the network to charge. We focus on the order parameter and its fluctuations close to the phase transition, and show that the critical point depends on the choice of congestion protocol. Finally, we analyse the inequality in the charging times as the vehicle arrival rate increases, and show that charging times are considerably more equitable in proportional fairness than in max-flow.
Descriptional and Computational Aspects of Generating and Accepting Hybrid Networks of Evolutionary Processors

The goal of this paper is to survey in a systematic and uniform way the main results regarding some descriptional and computational aspects of hybrid networks of evolutionary processors viewed both as generating and accepting devices, as well as solving problems with these mechanisms. We start by surveying some results regarding the size complexity of generating hybrid networks of evolutionary processors. Then, we define a computational complexity class of accepting hybrid networks of evolutionary processors and prove that this class equals the classical class NP. In another section, we present a few NP-complete problems and recall how they can be solved in linear time by accepting networks of evolutionary processors with linearly bounded resources (nodes, rules, symbols). We also recall a possible implementation of a solution for the 3-CNF-SAT using WWW. Finally we discuss some possible directions for further research.
Low Randomness Rumor Spreading via Hashing

We consider the classical rumor spreading problem, where a piece of information must be disseminated from a single node to all n nodes of a given network. We devise two simple push-based protocols, in which nodes choose the neighbor they send the information to in each round using pairwise independent hash functions, or a pseudo-random generator, respectively. For several well-studied topologies our algorithms use exponentially fewer random bits than previous protocols. For example, in complete graphs, expanders, and random graphs only a polylogarithmic number of random bits are needed in total to spread the rumor in O(log n) rounds with high probability. Previous explicit algorithms require Omega(n) random bits to achieve the same round complexity. For complete graphs, the amount of randomness used by our hashing-based algorithm is within an O(log n)-factor of the theoretical minimum determined by [Giakkoupis and Woelfel, 2011].
AGENTS: An Architectural Construct to Support Distributed Simulation

2.1 The current DIS standard, 2.0. 4, will soon become the next version of the IEEE standard for distributed simulation. While this standard includes many items missing from the 1.x versions, the standard says nothing about terrain, the synthetic environment, or the architecture for constructing large exercises. To date, no “operational” exercises have been conducted using strictly the DIS standard.
MODELING SUPPLY CHAIN PERFORMANCE VARIABLES

In order to understand the dynamic behavior of the variables that can play a major role in the performance improvement in a supply chain, a System Dynamics-based model is proposed. The model provides an effective framework for analyzing different variables affecting supply chain performance. Among different variables, a causal relationship among different variables has been identified. Variables emanating from performance measures such as gaps in customer satisfaction, cost minimization, lead-time reduction, service level improvement and quality improvement have been identified as goal-seeking loops. The proposed System Dynamics-based model analyzes the affect of dynamic behavior of variables for a period of 10 years on performance of case supply chain in auto business.
Corneal Biomechanical Properties in Different Ocular Conditions and New Measurement Techniques

Several refractive and therapeutic treatments as well as several ocular or systemic diseases might induce changes in the mechanical resistance of the cornea. Furthermore, intraocular pressure measurement, one of the most used clinical tools, is also highly dependent on this characteristic. Corneal biomechanical properties can be measured now in the clinical setting with different instruments. In the present work, we review the potential role of the biomechanical properties of the cornea in different fields of ophthalmology and visual science in light of the definitions of the fundamental properties of matter and the results obtained from the different instruments available. The body of literature published so far provides an insight into how the corneal mechanical properties change in different sight-threatening ocular conditions and after different surgical procedures. The future in this field is very promising with several new technologies being applied to the analysis of the corneal biomechanical properties.
Integrated modeling of driver gaze and vehicle operation behavior to estimate risk level during lane changes

In this paper, we investigate a method for detecting risky lane changes using integrated modeling of driver gaze and vehicle operation behavior. Driver gaze direction and vehicle operation behavior are broken down into discrete acts, e.g., looking in the rear view mirror, braking, etc., and sequences of these actions are jointly modeled using multi-stream hidden Markov models (HMMs). Driving data is recorded on expressways as drivers pass leading vehicles, i.e., the drivers make two lane changes, first to pass leading vehicles and then to move back into their original lanes. Since actual driving risk levels are difficult to measure, the risk level of each lane change is rated by subjects, and we assume their scores represent the “ground-truth” risk level. By jointly modeling gaze and vehicle operation behavior, we improve the performance of risky lane change detection. To more accurately evaluate overall risk, we use data from multiple lane change events. We obtain an average correlation coefficient of 0.80 between HMM likelihood scores and subjective risk evaluation scores by accumulating HMM likelihoods for a period of fourteen minutes. By accumulating these indicators for the previous twenty minutes, a 96.0% risky driving detection rate is achieved with a 7.1% false positive rate.
The impact of intra-die device parameter variations on path delays and on the design for yield of low voltage digital circuits

The yield of low voltage digital circuits is found to be sensitive to local gate delay variations due to uncorrelated intra-die parameter deviations. Caused by statistical deviations of the doping concentration they lead to more pronounced delay variations for minimum transistor sizes. Their influence on path delays in digital circuits is verified using a carry select adder test circuit fabricated in 0.5 /spl mu/m CMOS technologies with two different threshold voltages. The increase of the path delay variations for smaller device dimensions and reduced supply voltages as well as the dependence on the path length is shown. It is found that for circuits with a large number of critical paths with a low logic depth are most sensitive to uncorrelated gate delay variations. Scenarios for future technologies show the increased impact of uncorrelated delay variations on digital design. A reduction of the maximal clock frequency of 9% is found for highly pipelined systems realized in a 0.18 /spl mu/m CMOS technology.
Arrays of MicroLEDs and Astrocytes: Biological Amplifiers to Optogenetically Modulate Neuronal Networks Reducing Light Requirement

In the modern view of synaptic transmission, astrocytes are no longer confined to the role of merely supportive cells. Although they do not generate action potentials, they nonetheless exhibit electrical activity and can influence surrounding neurons through gliotransmitter release. In this work, we explored whether optogenetic activation of glial cells could act as an amplification mechanism to optical neural stimulation via gliotransmission to the neural network. We studied the modulation of gliotransmission by selective photo-activation of channelrhodopsin-2 (ChR2) and by means of a matrix of individually addressable super-bright microLEDs (μLEDs) with an excitation peak at 470 nm. We combined Ca2+ imaging techniques and concurrent patch-clamp electrophysiology to obtain subsequent glia/neural activity. First, we tested the μLEDs efficacy in stimulating ChR2-transfected astrocyte. ChR2-induced astrocytic current did not desensitize overtime, and was linearly increased and prolonged by increasing μLED irradiance in terms of intensity and surface illumination. Subsequently, ChR2 astrocytic stimulation by broad-field LED illumination with the same spectral profile, increased both glial cells and neuronal calcium transient frequency and sEPSCs suggesting that few ChR2-transfected astrocytes were able to excite surrounding not-ChR2-transfected astrocytes and neurons. Finally, by using the μLEDs array to selectively light stimulate ChR2 positive astrocytes we were able to increase the synaptic activity of single neurons surrounding it. In conclusion, ChR2-transfected astrocytes and μLEDs system were shown to be an amplifier of synaptic activity in mixed corticalneuronal and glial cells culture.