Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-frequency analysis of interactions elicited by Vernier stimuli

In five subjects, we measured visual evoked potentials (VEPs) elicited by Vernier targets in which the contrast of the two components of the stimuli were modulated by sinusoids at distinct frequencies f1 and f2. This approach allows for the extraction of VEP signatures of spatial interactions, namely, responses at intermodulation frequencies n1f1 + n2f2, without the need to introduce motion into the stimulus. The most prominent interactions were at the sum frequency f1 + f2, and, for frequency pairs that were sufficiently separated, the difference frequency f1 − f2. These responses had a systematic dependence on the temporal parameters of the stimulus, corresponding to an effective latency of 145 to 165 ms. Fourth-order interactions were also detected, particularly at the frequencies 2f1 ± 2f2. These VEP signatures of interaction were similar to interactions seen for colinear line segments separated by a gap. Thus, for Vernier stimuli devoid of motion, VEP signatures of interaction are readily detected but are not specific to hyperacuity displacements. The distribution of interactions across harmonic orders is consistent with local rectification preceding the spatial interactions. Their effective latencies and dependence on spatial parameters are consistent with interactions within V1 receptive fields or mediated by horizontal connections between cells with a similar orientation tuning within V1.
Sparse multi-band signal recovery based on support refining for modulated wideband converter

The continuous-time sparse multi-band signal can be acquired with sub-Nyquist rate by modulated wideband converter (MWC), which is a novel sampling technique based on compressed sensing and alleviates the pressure of high sampling rate. The performance of existing reconstruction algorithm for MWC suffers from low probability of successful recovery, especially when the signal noise ratio (SNR) is not high. In this paper, a sparse multi-band signal recovery algorithm based on support refining (SRSR) is proposed for MWC. Particularly, the support refining process is incorporated into the reconstruction stage of MWC. The initial support of the original multi-band signal is firstly acquired by the existing multi measurement vector (MMV) algorithm. Then, the support refining process refines the initial support to extract the inaccurate support information. Finally, the whole recovery algorithm ends up with recovering the remaining support by the existing MMV algorithm. Simulation results demonstrate that the proposed SRSR algorithm improves the success rate of sparse multi-band signal recovery and enables MWC require fewer channels of sampling architecture and lower hardware complexity.
Experiments with Reliable Data Delivery in Wireless Sensor Networks

The increasing complexity of Wireless Sensor Networks (WSN) applications require simple, yet reliable, underlying networking mechanisms. In this paper, we describe the experiments performed to establish the real challenges and sources of errors for the reliable data delivery problem. We also discuss several implementation solutions and try to establish the issues that should be taken into account in the design phase. The results are obtained by field measurements, therefore we consider them relevant and useful. Our work relies on tight interaction among transport, routing and medium access layers, with the overall goal of achieving energy efficiency through cross-layer optimizations.
BioThesaurus: a web-based thesaurus of protein and gene names

UNLABELLED BioThesaurus is a web-based system designed to map a comprehensive collection of protein and gene names to protein entries in the UniProt Knowledgebase. Currently covering more than two million proteins, BioThesaurus consists of over 2.8 million names extracted from multiple molecular biological databases according to the database cross-references in iProClass. The BioThesaurus web site allows the retrieval of synonymous names of given protein entries and the identification of protein entries sharing the same names. AVAILABILITY BioThesaurus is accessible for online searching at http://pir.georgetown. edu/iprolink/biothesaurus
Transformational leadership and affective organizational commitment: mediating roles of perceived social responsibility and organizational identification

Purpose - The purpose of this research was to examine the mediating roles of staff-level employee perceptions of corporate social responsibility (PCSR) and organizational identification in the relationship between transformational leadership and affective organizational commitment. Design/methodology/approach - A survey was administered to staff-level employees of private sector companies through social media groups comprising members of the alumni associations of two universities in the northeast of America. A total of 218 responses were received, and the data were analyzed using a serial multiple mediator model. Findings - The research indicates that transformational leadership helps staff-level employees perceive the organization as socially considerate, which in turn adds to their feelings of identification and commitment to the organization. Perceived corporate social responsibility and organizational identification do mediate the relationship between transformational leadership and affective organizational commitment. Leader development programs should consider emphasizing transformational leadership to achieve a win for both organizations and society. Originality/value - This study adds empirical evidence to understand the linkage between transformational leadership and PCSR in staff-level employees. The research provides insight into how leaders can be responsive to stakeholder demands through transformational leadership, how PCSR is engendered at the staff-level, how staff-level employee PCSR contributes organizational value and how PSCR and organizational identification partly explain how transformational leadership effects affective organizational commitment.
Can a managerial intervention focusing on job demands, job resources, and personal resources improve the work situation of employees?

Abstract Knowledge regarding the effects on employees of occupational intervention programs targeting psychosocial factors at work, including job demands, job resources, and personal resources, is limited and existing studies show mixed findings. This study aimed to investigate potential effects on employees’ job demands (i.e., workload, unnecessary tasks, unreasonable tasks), job resources (i.e., feedback, control, goal clarity), and personal resources (i.e., signaling and limit-setting strategies) of an intervention targeting managers’ ways of improving the psychosocial work environment among their staff (SWEActManager). Questionnaire data from employees (n = 40) of a Swedish municipality, whose managers (n = 4) participated in the program, and referents (n = 58 employees), were collected before and after the program. The program included four three-hour workshops delivered during a six-week period. Results from 2(group) × 2(time) ANOVAs showed that all three demands increased over time, while job control decreased. There were no significant group effects. One interaction effect only was significant: Unnecessary tasks increased more among referents than in the intervention group. The few significant short-term effects probably relate to challenges in designing and implementing organizational interventions targeting managers, and evaluating their effects among subordinates. This study adds to the limited research regarding the effects of organizational psychosocial interventions, including managers for their subordinates’ demands and resources in a changing working life.
Enhanced Password Authentication Through Typing Biometrics With The K-Means Clustering Algorithm

Password authentication is the most commonly used identification system in today's computer world. It can be enhanced using typing biometrics as a secondary check. Our research focuses on using the time period between keystrokes as the measure of the typing pattern. Each user's typing pattern can be viewed as a cluster of measurements that can be differentiated from clusters of other users. The effect of different metric spaces for cluster analysis was also investigated. The measurements of the keystroke latency are analysed using the modified K-means clustering algorithm to classify the users.
On Crossing Sets, Disjoint Sets and the Pagenumber 1

Let G = (V;E) be a t-partite graph with n vertices and m edges, where the partite sets are given. We present an O(n2m1:5) time algorithm to construct drawings of G in the plane so that the size of the largest set of pairwise crossing edges, and at the same time, the size of the largest set of disjoint (pairwise non-crossing) edges are O(pt m). As an application we embed G in a book of O(pt m) pages, in O(n2m1:5) time, resolving an open question for the pagenumber problem. A similar result is obtained for the dual of the pagenumber or the queuenumber. Our algorithms are obtained by derandomizing a probabilistic proof.
Algebraic Cryptanalysis of MQQ Public Key Cryptosystem by MutantXL

In this paper, we present an efficient attack of the multivariate Quadratic Quasigroups (MQQ) cryptosystem. Our cryptanalysis breaks MQQ cryptosystems by solving systems of multivariate quadratic polynomial equations using a modified version of the MutantXL algorithm. We present experimental results comparing the behavior of our implementation of MutantXL to Magma’s implementation of F4 on MQQ systems (≥ 135 bit). Based on our results we show that the MutantXL implementation solves with much less memory than Magma’s implementation of F4 algorithm.
Dynamical Mass Constraints on Low-Mass Pre-Main-Sequence Stellar Evolutionary Tracks: An Eclipsing Binary in Orion with a 1.0 M☉ Primary and a 0.7 M☉ Secondary

We report the discovery of a double-lined, spectroscopic, eclipsing binary in the Orion star-forming region. We analyze the system spectroscopically and photometrically to empirically determine precise, distance-independent masses, radii, effective temperatures, and luminosities for both components. The measured masses for the primary and secondary, accurate to ~1%, are 1.01 and 0.73 M☉, respectively; thus, the primary is a definitive pre-main-sequence solar analog, and the secondary is the lowest-mass star yet discovered among pre-main-sequence eclipsing binary systems. We use these fundamental measurements to test the predictions of pre-main-sequence stellar evolutionary tracks. None of the models we examined correctly predict the masses of the two components simultaneously, and we implicate differences between the theoretical and empirical effective temperature scales for this failing. All of the models predict the observed slope of the mass-radius relationship reasonably well, though the observations tend to favor models with low convection efficiencies. Indeed, considering our newly determined mass measurements together with other dynamical mass measurements of pre-main-sequence stars in the literature, as well as measurements of Li abundances in these stars, we show that the data strongly favor evolutionary models with inefficient convection in the stellar interior, even though such models cannot reproduce the properties of the present-day Sun.
Ant Colonies for the reconstruction of artificial 3D Objects

Ant Colony Models are artificial simulations of real ant colonies [1], [2]. The way real ants behave in nature inspire cooperation and competition strategies for virtual agent: the emergence of intelligent behavior and swarm-based self- organization can be used to solve difficult problems. In this work an Ant Colony Model for 3D objects reconstruction is presented. The accuracy in reconstructing 3D object is tested on artificial 3D objects and on 10 real Computed Tomography (CT) images of human lungs.
A Comparative Study of Mapping Solutions for Enabling Metadata Interoperability

A prerequisite for enabling uniform access to metadata in distributed, autonomous repositories is to deal with the heterogeneities among metadata information objects. Metadata mapping is one possible technique for handling incompatible metadata originating from distinct repositories and mapping solutions are its technical manifestation. Currently, there exists a variety of mapping solutions, with different conceptual characteristics and varying potential of solving solving specific types of interoperability problems. In this work, we give a comprehensive overview of existing mapping solutions and systematically compare their features and characteristics. Our analysis shows that the majority of mapping solutions are standalone-systems and support experts in mapping and integrating structured and semi-structured metadata. Solutions that conceive mapping as being a process and target broader metadata environments such as the Web are still rare.
Universality of Citation Distributions for Academic Institutions and Journals

Citations measure the importance of a publication, and may serve as a proxy for its popularity and quality of its contents. Here we study the distributions of citations to publications from individual academic institutions for a single year. The average number of citations have large variations between different institutions across the world, but the probability distributions of citations for individual institutions can be rescaled to a common form by scaling the citations by the average number of citations for that institution. We find this feature seems to be universal for a broad selection of institutions irrespective of the average number of citations per article. A similar analysis for citations to publications in a particular journal in a single year reveals similar results. We find high absolute inequality for both these sets, Gini coefficients being around 0.66 and 0.58 for institutions and journals respectively. We also find that the top 25% of the articles hold about 75% of the total citations for institutions and the top 29% of the articles hold about 71% of the total citations for journals.
On Minimum Feedback Vertex Sets in Bipartite Graphs and Degree-Constraint Graphs

SUMMARY We consider the minimum feedback vertex set problem for some bipartite graphs and degree-constrained graphs. We show that the problem is linear time solvable for bipartite permutation graphs and NP-hard for grid intersection graphs. We also show that the problem is solvable in O(n 2 log 6 n) time for n-vertex graphs with maximum degree at
Proving multilevel security of a system design

Two nearly equivalent models of multilevel security are presented. The use of multiple models permits the utilization of each model for purposes where that model is particularly advantageous. In this case, the more general model is simple and easily comprehensible, being more abstract, and is useful for exposition of the meaning of multilevel security. The less general model relates well to design specifications and permits straightforward proof of the security of a system design. The correspondence between the two models is easily demonstrated. The two models when applied appropriately are more useful for defining and proving the multilevel security of systems than existing models. The utility of the two models and their relationship to existing models is discussed and the proof of the security of one particular system design is illustrated. The technique for accomplishing the security proof is straightforward and can be extensively automated.
Effective Instruction for Engaging Culturally Diverse Students in Higher Education.

Engagement is related to important student outcomes such as persistence, retention, and grades. It is key to all students’ learning, but it may be particularly important for culturally diverse students who may have fewer models and other resources for keeping themselves engaged. As the institutions of higher education become increasingly culturally and linguistically diverse, instructors are challenged to engage a more diverse student population. This paper describes how three university instructors applied the Center for Research on Education, Diversity, and Excellence (CREDE) Standards for Effective Pedagogy to their instruction in courses of general psychology, educational psychology, and statistics in order to increase students’ cognitive and social engagement. The CREDE Standards are strategies of instruction that incorporate small group discussions and making connections between students’ prior experiences and abstract concepts.
Functional test selection based on unsupervised support vector analysis

Extensive software-based simulation continues to be the mainstream methodology for functional verification of designs. To optimize the use of limited simulation resources, coverage metrics are essential to guide the development of effective test suites. Traditional coverage metrics are defined based on either a functional model or a structural model of the design. If our goal is to select a subset of tests from a set of tests, using these coverage metrics require simulation of the entire set before the effectiveness of tests can be compared. In this paper, we propose a novel methodology that estimates the input space covered by a set of tests. We use unsupervised support vector analysis to learn such a space, resulting in a subset of tests that represent the original set of tests. A direct application of this methodology is to select tests before simulation in order to reduce simulation cycles. Consequently, simulation effectiveness can be improved. Experimental results based on application of the proposed methodology to the OpenSparc Tl processor are reported to demonstrate the practicality of our approach.
Is the United States Still a Land of Opportunity? Recent Trends in Intergenerational Mobility

We present new evidence on trends in intergenerational mobility in the U.S. using administrative earnings records. We find that percentile rank-based measures of intergenerational mobility have remained extremely stable for the 1971-1993 birth cohorts. For children born between 1971 and 1986, we measure intergenerational mobility based on the correlation between parent and child income percentile ranks. For more recent cohorts, we measure mobility as the correlation between a child's probability of attending college and her parents' income rank. We also calculate transition probabilities, such as a child's chances of reaching the top quintile of the income distribution starting from the bottom quintile. Based on all of these measures, we find that children entering the labor market today have the same chances of moving up in the income distribution (relative to their parents) as children born in the 1970s. However, because inequality has risen, the consequences of the "birth lottery" - the parents to whom a child is born - are larger today than in the past.
Neuroimage: Clinical Automated White Matter Fiber Tract Identification in Patients with Brain Tumors a R T I C L E I N F O

A B S T R A C T We propose a method for the automated identification of key white matter fiber tracts for neurosurgical planning, and we apply the method in a retrospective study of 18 consecutive neurosurgical patients with brain tumors. Our method is designed to be relatively robust to challenges in neurosurgical tractography, which include peritumoral edema, displacement, and mass effect caused by mass lesions. The proposed method has two parts. First, we learn a data-driven white matter parcellation or fiber cluster atlas using groupwise registration and spectral clustering of multi-fiber tractography from healthy controls. Key fiber tract clusters are identified in the atlas. Next, patient-specific fiber tracts are automatically identified using tractography-based registration to the atlas and spectral embedding of patient tractography. Results indicate good generalization of the data-driven atlas to patients: 80% of the 800 fiber clusters were identified in all 18 patients, and 94% of the 800 fiber clusters were found in 16 or more of the 18 patients. Automated subject-specific tract identification was evaluated by quantitative comparison to subject-specific motor and language functional MRI, focusing on the arcuate fasciculus (language) and corticospinal tracts (motor), which were identified in all patients. Results indicate good colocalization: 89 of 95, or 94%, of patient-specific language and motor activations were intersected by the corresponding identified tract. All patient-specific activations were within 3mm of the corresponding language or motor tract. Overall, our results indicate the potential of an automated method for identifying fiber tracts of interest for neurosurgical planning, even in patients with mass lesions.
A New and Rapid Method for the Determination of Glucose by Measurement of Rate of Oxygen Consumption

Glucose levels in serum, plasma, and urine are determined rapidly and conveniently by a new glucose oxidase method employing a polarographic oxygen sensor with a circuit modified to record the rate of oxygen consumption. The maximum apparent rate of oxygen consumption relative to the rate obtained with a glucose standard provides a direct measure of the glucose level in the sample; results are obtainable within 20 sec. after sample (100 µl.) addition and within 3 min. after a blood sample is withdrawn from a patient. Interferences associated with prior colorimetric glucose oxidase methods are avoided by measuring oxygen consumption instead of hydrogen peroxide formation. The method is described and results are presented showing a standard deviation of less than 1.5% on replicate determinations and a bias of 1% with respect to data obtained on the same samples by the automated ferricyanide method.
eVO: A realtime embedded stereo odometry for MAV applications

The navigation of a miniature aerial vehicle (MAV) in GPS-denied environments requires a robust embedded visual localization method. In this paper, we describe a simple but efficient stereo visual odometry algorithm, called eVO, running onboard our quadricopter MAV at video-rate. The proposed eVO algorithm relies on a keyframe scheme which allows to decrease the estimation drift and to reduce the computational cost. We study quantitatively the influence of the main parameters of the algorithm and tune them for optimal performance on various datasets. The eVO algorithm has been submitted to the KITTI odometry benchmark [1] where it ranks first at the date of submission, with an average translational drift of 1.93% and an average angular drift of less than 0.076 degres/m. Besides, we have made several experiments with our MAV with egolocalization given by eVO, for instance for autonomous 3D environment modeling.
Credibility optimization and power control for secure mobile crowdsourcing

Recent emergence of mobile crowdsourcing applications has made it imperative to ensure security and efficient resource allocation to the users involved in such applications, especially considering the nature of wireless transmission that is power limited and highly vulnerable to eavesdropping. Although there have been some efforts to maximize the report credibility along with power allocation to reporters involved in such applications, security along with long-term system utility maximization is still unexplored. In this paper, we ensure security in mobile crowdsourcing and maximize the utility (incorporating both credibility and power consumption) by provisioning secure transmission rate to each user based on power selection and reporting format selection, considering current channel condition. We propose an online decision algorithm, called FLAPO (Format Selection and Power Control for Credibility Optimization), to optimally choose report format and secrecy rate optimization whenever an event takes place. Leveraging the recently developed Lyapunov optimization technique, we prove that FLAPO achieves the close-to-optimal system utility while bounding the average queue backlog (which translates into average reporting delays). We also perform a simulation study to complement the analysis and the simulation results are consistent with our theoretical analysis.