Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative Decision-Making in Decentralized Multiple-Robot Systems: The Best-of-N Problem

Multiple-robot systems (MRS) that are decentrally organized have many benefits over centralized systems. Decentralized systems are less affected by computational and communicative bottlenecks, and they are more robust to the loss of individual member robots. System-level cognitive operations, though, are much more difficult to implement in decentralized systems. One example is the best-of-N decision-making problem, in which a team attempts to unanimously select a single alternative from a list that maximizes a given metric. This is a valuable operation, since many system-level operations can be expressed in this form. Optimal best-of-N decision-making, however, is intractable in large decentralized systems. The contribution of this paper is a biologically inspired algorithm that enables a decentralized MRS composed of very simple robots to make good, unanimous decisions. In a series of physical experiments using real robots, the best decision was made at least 80% of the time. In all, 100% of the decisions achieved perfect consensus, which prevented the MRS from becoming fragmented. The decisions are made using anonymous, local communication, with no direct comparisons of the available alternatives by the individual robots.
Programmable voltage mode multifunctional filter using modified CMOS current controlled current conveyor transconductance amplifier

The SISO voltage mode multifunctional filter topology is realized in this paper using a modified CCCCTA which realizes low-pass, high-pass, band-pass and band reject filter responses. The proposed topology consists of a CCCCTA, two 8-bit capacitor banks and a programmable input circuit using switches and VDTA. This circuit reduces the requirement of large amount of biasing current, given wider voltage transfer range and lesser power dissipation. The proposed filter gives a control over filter parameters such as Q-factor and cut off frequency by digitally controlling the capacitor bank. Required filter response is selected by programmable input circuit using same circuit topology. The circuit is simulated using Cadence Virtuoso UMC 180nm CMOS technology at ±1.5V power supply voltage.
High-Resolution Measurements of Face-to-Face Contact Patterns in a Primary School

Background Little quantitative information is available on the mixing patterns of children in school environments. Describing and understanding contacts between children at school would help quantify the transmission opportunities of respiratory infections and identify situations within schools where the risk of transmission is higher. We report on measurements carried out in a French school (6–12 years children), where we collected data on the time-resolved face-to-face proximity of children and teachers using a proximity-sensing infrastructure based on radio frequency identification devices. Methods and Findings Data on face-to-face interactions were collected on Thursday, October 1st and Friday, October 2nd 2009. We recorded 77,602 contact events between 242 individuals (232 children and 10 teachers). In this setting, each child has on average 323 contacts per day with 47 other children, leading to an average daily interaction time of 176 minutes. Most contacts are brief, but long contacts are also observed. Contacts occur mostly within each class, and each child spends on average three times more time in contact with classmates than with children of other classes. We describe the temporal evolution of the contact network and the trajectories followed by the children in the school, which constrain the contact patterns. We determine an exposure matrix aimed at informing mathematical models. This matrix exhibits a class and age structure which is very different from the homogeneous mixing hypothesis. Conclusions We report on important properties of the contact patterns between school children that are relevant for modeling the propagation of diseases and for evaluating control measures. We discuss public health implications related to the management of schools in case of epidemics and pandemics. Our results can help define a prioritization of control measures based on preventive measures, case isolation, classes and school closures, that could reduce the disruption to education during epidemics.
Security Control of Cyber-Physical System Under Continuous Collaborative Attacks

This paper mainly studied the state feedback control problem of Cyber-Physical System(CPS) with noise under the collaborative attacks of DoS and FDIAs. Firstly, by analyzing the impact of continuous collaborative attacks on different communication channels, a class of switched systems containing persistent collaborative network attacks, system noise and measurement noise are established according to different communication topologies. Secondly, by utilizing Lyapunov stability theory, sufficient conditions for the index stability of state feedback control is obtained, and a state feedback controller method based on Kalman filter estimation was provided based on linear matrix inequality technology. Finally, the feasibility and effectiveness of the method were verified through a simulation example.
Does the Cognitive Interview Promote the Coherence of Narrative Accounts in Children With and Without an Intellectual Disability?

We examined whether the cognitive interview (CI) procedure enhanced the coherence of narrative accounts provided by children with and without intellectual disabilities (ID), matched on chronological age. Children watched a videotaped magic show; one day later, they were interviewed using the CI or a structured interview (SI). Children interviewed using the CI reported more correct details than those interviewed using the SI. Additionally, children interviewed using the CI reported more contextual background details, more logically ordered sequences, more temporal markers, and fewer inconsistencies in their stories than those interviewed using the SI. However, the CI did not increase the number of story grammar elements compared with the SI. Overall children interviewed with the CI told better stories than those interviewed with the SI. This finding provided further support for the effectiveness of the CI with vulnerable witnesses, particularly children with ID.
Comparative Study on Incremental Capacity Analysis with Machine Learning Algorithms for State of Health Estimation of Lithium-Ion Batteries

The state of health (SOH) of lithium-ion batteries is a critical metric that indicates the degradation level and remaining capacity of batteries. Incremental capacity analysis (ICA) method transforms relatively even battery charging or discharging curves as easily identifiable incremental capacity (IC) peaks. There usually exists a high correlation between the SOH and IC peaks, which provides an efficient means for battery SOH estimation. Machine learning algorithms are usually employed with the ICA method to determine the correlation. This paper mainly employs IC peaks with different machine learning algorithms, including Gaussian process regression (GPR), support vector machine, and regression tree for battery SOH estimation. The performance of the three algorithms in terms of estimation accuracy, R-squared, training time, and prediction speed is comprehensively compared and analyzed. The validation results show that the GPR method presents a superior performance in comparison with the other two algorithms.
Publicly Verifiable Secret Sharing Member-join Protocol For Threshold Signatures

Publicly verifiable secret sharing (PVSS) allows not only shareholders themselves but also everyone verify the shares of a secret distributed by a dealer. It has a lot of electronic applications. In this paper, we propose a publicly verifiable member-join protocol for threshold signatures. In our proposal, a new member can join a PVSS scheme to share the secret only with the help of old shareholders. What’s more, everyone besides the new member can verify the validity of the new member’s share, while only the new member knows his share. Different from previous protocols, our protocol can tolerate a mobile adversary. This proposal adapts to many electronic applications. Finally, we analyze the security of our scheme.
Out of work and on the air: Television news of unemployment

Issues concerning the ideological role of television are examined through a study of television news coverage of unemployment during the first six months of 1983. The study focuses on the explanations of unemployment contained in the coverage and the thematic structure of the news stories. The stories were found to contain few explicit explanations, but a diversity of thematic structures revealed the societal frameworks within which television journalists construct stories about this issue. The diversity of thematic structures raises questions as to whether television acts as disseminator of a “dominant ideology” or as a “cultural forum. ”
Minimum detection limit of an in-house nested-PCR assay for herpes simplex virus and varicella zoster virus.

INTRODUCTION Herpes simplex virus (HSV) and varicella zoster virus (VZV) are responsible for a variety of human diseases, including central nervous system diseases. The use of polymerase chain reaction (PCR) techniques on cerebrospinal fluid samples has allowed the detection of viral DNA with high sensitivity and specificity. METHODS Serial dilutions of quantified commercial controls of each virus were subjected to an in-house nested-PCR technique. RESULTS The minimum detection limits for HSV and VZV were 5 and 10 copies/µL, respectively. CONCLUSIONS The detection limit of nested-PCR for HSV and VZV in this study was similar to the limits found in previous studies.
A saliency-based method of simulating visual attention in virtual scenes

Complex interactions occur in virtual reality systems, requiring the modelling of next-generation attention models to obtain believable virtual human animations. This paper presents a saliency model that is neither domain nor task specific, which is used to animate the gaze of virtual characters. A critical question is addressed: What types of saliency attract attention in virtual environments and how can they be weighted to drive an avatar's gaze? Saliency effects were measured as a function of their total frequency. Scores were then generated for each object in the field of view within each frame to determine the most salient object within the virtual environment. This paper compares the resulting saliency gaze model to tracked gaze, in which avatars' eyes are controlled by head-mounted mobile eye-trackers worn by human subjects, random gaze model informed by head-orientation for saccade generation, and static gaze featuring non-moving centered eyes. Results from the evaluation experiment and graphical analysis demonstrate a promising saliency gaze model that is not just believable and realistic but also target-relevant and adaptable to varying tasks. Furthermore, the saliency model does not use any prior knowledge of the content or description of the virtual scene.
Thriving under Stress: Selective Translation of HIV-1 Structural Protein mRNA during Vpr-Mediated Impairment of eIF4E Translation Activity

Translation is a regulated process and is pivotal to proper cell growth and homeostasis. All retroviruses rely on the host translational machinery for viral protein synthesis and thus may be susceptible to its perturbation in response to stress, co-infection, and/or cell cycle arrest. HIV-1 infection arrests the cell cycle in the G2/M phase, potentially disrupting the regulation of host cell translation. In this study, we present evidence that HIV-1 infection downregulates translation in lymphocytes, attributable to the cell cycle arrest induced by the HIV-1 accessory protein Vpr. The molecular basis of the translation suppression is reduced accumulation of the active form of the translation initiation factor 4E (eIF4E). However, synthesis of viral structural proteins is sustained despite the general suppression of protein production. HIV-1 mRNA translation is sustained due to the distinct composition of the HIV-1 ribonucleoprotein complexes. RNA-coimmunoprecipitation assays determined that the HIV-1 unspliced and singly spliced transcripts are predominantly associated with nuclear cap binding protein 80 (CBP80) in contrast to completely-spliced viral and cellular mRNAs that are associated with eIF4E. The active translation of the nuclear cap binding complex (CBC)-bound viral mRNAs is demonstrated by ribosomal RNA profile analyses. Thus, our findings have uncovered that the maintenance of CBC association is a novel mechanism used by HIV-1 to bypass downregulation of eIF4E activity and sustain viral protein synthesis. We speculate that a subset of CBP80-bound cellular mRNAs contribute to recovery from significant cellular stress, including human retrovirus infection.
The role of norepinephrine in spatial reference and spatial working memory

The adrenergic system (utilizing norepinephrine, NE, as a neurotransmitter) is implicated in hippocampusbased learning and memory, in addition to its well known peripheral actions mediated by the sympathetic nervous system. We have produced a strain of mice in which the gene coding for the enzyme dopamine betahydroxylase (Dbh), which catalyzes the synthesis of NE from dopamine, has been disrupted. Mice recessive (Dbh-/-) for the Dbh gene mutation lack endogenous NE and epinephrine, while heterozygous mice (Dbh+/ -) have normal levels of NE and epinephrine and display normal phenotype. Previous studies have indicated that NE is necessary and sufficient for the retrieval of intermediate-term contextual and spatial memories, but is not necessary for the retrieval or consolidation of emotional memories in general (Thomas et al. 1996). We tested whether this relationship would stand for memories that were appetitive rather than aversive. We tested 20 Dbh-/and 20 Dbh+/mice in an eight-arm radial maze. We found no difference between KOs and controls in ability to recall spatial cues 24 hours after training. This negative result indicated that NE may not be critical for retrieval of all hippocampus-dependent memories but specifically those that are aversive. Using a more standard variation of the above protocol on the radial arm maze, we used this apparatus to test the role of NE in spatial working memory. We found significant, robust differences between Dbh-/and Dbh+/mice after a training period of approximately 14 days. To test whether this difference was due to a potential deficit in acquisition or performance, we restored NE in Dbh-/mice by administering the synthetic precursor L-DOPS after four days of stable behavioral differences between genotypes. In a separate trial, we also restored NE signaling with dexmedetomidine, a selective alpha-2 receptor agonist. A gradual improvement by Dbh-/mice to levels comparable to Dbh+/mice indicated that NE is critical for the acquisition of spatial working memory, and suggested a role for the alpha-2 adrenergic receptor in the processing of spatial working memory.
EDFI: A Dependable Fault Injection Tool for Dependability Benchmarking Experiments

Fault injection is a pivotal technique in dependability benchmarking. Unfortunately, existing general-purpose fault injection tools either inject faults in predetermined memory locations or resort to random injection, approaches that generally result in poor fault coverage and controllability guarantees. This makes it difficult to reproduce or compare experiments across different systems or workloads. This paper presents EDFI, a new tool for dependable general-purpose fault injection experiments. EDFI combines static and dynamic program instrumentation to perform execution-driven fault injection, a technique which allows realistic software faults to be injected in a controlled way as the target system executes. Our instrumentation strategy guarantees a predetermined fault load distribution during the entirety of the experiment, independently of the particular system or workload considered. Our evaluation confirms that EDFI significantly improves the precision and controllability of prior tools, at the cost of only modest memory and performance overhead during fault-free execution.
Essays on Political Corruption

This dissertation presents three essays offering explanations for the persistence of corruption despite electoral competition. The first essay, co-authored with Adam Glynn and Nahomi Ichino, asks what the effect of electoral systems is on corruption. Persson, Tabellini and Trebbi (2003) proposed that plurality electoral systems should lead to lower corruption compared to proportional representation (PR) systems because the former creates a direct link between voters and politicians whom voters can hold accountable for corruption. The empirical question remains unresolved, however, in part due to the endogeneity of the electoral institutions and difficulties in measuring corruption. Using nonparametric methods and new data to reduce sensitivity to these problems, we find no evidence for this hypothesis. Instead, we find some evidence in the opposite direction, that PR leads to less corruption. The second essay makes a theoretical distinction between voters’ perceptions of the corruption of the political system and of individual politicians. Evidence from original interviews and focus group discussions, as well as public opinion data shows that many Ugandan citizens perceive their political system to be highly corrupt. In particular, they perceive corrupt acts to be widespread, do not expect perpetrators to be punished, and have difficulty distinguishing “honest” candidates. These characteristics cause voters who perceive the system to be highly corrupt to be less likely to punish overtly corrupt individuals by withdrawing electoral support. In some cases, they even prefer clearly corrupt candidates. The third essay argues that to understand when voters hold politicians accountable for corruption, it is necessary to understand who they perceive to be corrupt. It presents
Can Changes in Arterial Pressure be Used to Detect Changes in Cardiac Output during Volume Expansion in the Perioperative Period?

Background:Cardiac output (CO) is rarely monitored during surgery, and arterial pressure remains the only hemodynamic parameter for assessing the effects of volume expansion (VE). However, whether VE-induced changes in arterial pressure accurately reflect changes in CO has not been demonstrated. The authors studied the ability of VE-induced changes in arterial pressure and in pulse pressure variation to detect changes in CO induced by VE in the perioperative period. Methods:The authors studied 402 patients in four centers. Hemodynamic variables were recorded before and after VE. Response to VE was defined as more than 15% increase in CO. The ability of VE-induced changes in arterial pressure to detect changes in CO was assessed using a gray zone approach. Results:VE increased CO of more than 15% in 205 patients (51%). Areas under the receiver operating characteristic curves for VE-induced changes in systolic, diastolic, means, and pulse pressure ranged between 0.64 and 0.70, and sensitivity and specificity ranged between 52 and 79%. For these four arterial pressure–derived parameters, large gray zones were found, and more than 60% of the patients lay within this inconclusive zone. A VE-induced decrease in pulse pressure variation of 3% or more allowed detecting a fluid-induced increase in CO of more than 15% with a sensitivity of 90% and a specificity of 77% and a gray zone between 2.2 and 4.7% decrease in pulse pressure variation including 14% of the patients. Conclusion:Only changes in pulse pressure variation accurately detect VE-induced changes in CO and have a potential clinical applicability.
SINR-Threshold Scheduling with Binary Power Control for D2D Networks

In this paper, we consider a device-to-device communication network in which K transmitter-receiver pairs are sharing spectrum with each other. We propose a novel but simple binary scheduling scheme for this network to maximize the average sum rate of the pairs. According to the scheme, each receiver predicts its Signal-to-Interference-plus-Noise Ratio (SINR), assuming all other user pairs are active, and compares it to a preassigned threshold to decide whether its corresponding transmitter to be activated or not. For our proposed scheme, the optimal threshold that maximizes the expected sum rate is obtained analytically for the two user-pair case and empirically in the general K user-pair case. Simulation results reveal that our proposed SINR-threshold scheduling scheme outperforms ITLinQ [1], FlashLinQ [2] and the method presented in [3] in terms of the expected sum rate (network throughput). In addition, the computational complexity of the proposed scheme is O(K), outperforming both ITLinQ and FlashLinQ that have O(K^2) complexity requirements. Moreover, we also discuss the application of our proposed new scheme into an operator-assisted cellular D2D heterogeneous network.
Estimating room acoustic parameters for speech recognizer adaptation and combination in reverberant environments

This work analyzes the influence of reverberation on automatic speech recognition (ASR) systems and how to compensate its influence, with special focus on the important acoustical parameters i.e. room reverberation time T60 and clarity index C50. A multilayer perceptron (MLP) using features of a spectro-temporal filter bank as input is employed to identify the acoustic conditions spanning various reverberant scenarios. The posterior probabilities of the MLP are used to design a novel selection scheme for adaptation in a cluster-based manner and for system combination achieved by recognizer output voting error reduction (ROVER). A comparison of word error rates is performed considering different training modes, and an average relative improvement of 7.1% is obtained by the proposed system compared to conventional multistyle training.
Impact of a soy drink on climacteric symptoms: an open-label, crossover, randomized clinical trial

Abstract Objectives: The objective of this study is to evaluate the effects of a soy drink with a high concentration of isoflavones (ViveSoy®) on climacteric symptoms. Methods: An open-label, controlled, crossover clinical trial was conducted in 147 peri- and postmenopausal women. Eligible women were recruited from 13 Spanish health centers and randomly assigned to one of the two sequence groups (control or ViveSoy®, 500 mL per day, 15 g of protein and 50 mg of isoflavones). Each intervention phase lasted for 12 weeks with a 6-week washout period. Changes on the Menopause Rating Scale and quality of life questionnaires, as well as lipid profile, cardiovascular risk and carbohydrate and bone metabolism were assessed. Statistical analysis was performed using a mixed-effects model. Results: A sample of 147 female volunteers was recruited of which 90 were evaluable. In both sequence groups, adherence to the intervention was high. Regular consumption of ViveSoy® reduced climacteric symptoms by 20.4% (p = 0.001) and symptoms in the urogenital domain by 21.3% (p < 0.05). It also improved health-related quality life by 18.1%, as per the MRS questionnaire (p <0.05). Conclusion: Regular consumption of ViveSoy® improves both the somatic and urogenital domain symptoms of menopause, as well as health-related quality of life in peri- and postmenopausal women.
Low-complexity iris recognition using one-bit transform and angular radial partitioning

In this paper, a novel low-complexity iris recognition system based on 1-bit transform (1BT) and angular radial partitioning (ARP) is proposed. A binary iris image is obtained using 1BT on iris image. ARP is applied to this binary image and a feature vector is extracted considering the amount of data in the partitions and identification is executed. An important advantage of the proposed approach is its low-complexity. Furthermore, the method gives high identification and verification accuracies.