Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Information Sharing under Network Dynamics

We study how to spread $k$ tokens of information to every node on an $n$-node dynamic network, the edges of which are changing at each round. This basic {\em gossip problem} can be completed in $O(n + k)$ rounds in any static network, and determining its complexity in dynamic networks is central to understanding the algorithmic limits and capabilities of various dynamic network models. Our focus is on token-forwarding algorithms, which do not manipulate tokens in any way other than storing, copying and forwarding them. We first consider the {\em strongly adaptive} adversary model where in each round, each node first chooses a token to broadcast to all its neighbors (without knowing who they are), and then an adversary chooses an arbitrary connected communication network for that round with the knowledge of the tokens chosen by each node. We show that $\Omega(nk/\log n + n)$ rounds are needed for any randomized (centralized or distributed) token-forwarding algorithm to disseminate the $k$ tokens, thus resolving an open problem raised in~\cite{kuhn+lo:dynamic}. The bound applies to a wide class of initial token distributions, including those in which each token is held by exactly one node and {\em well-mixed} ones in which each node has each token independently with a constant probability. We also show several upper bounds in varying models.
Propensity Score Matching for Education Data: Worked Examples

Abstract Randomized controlled trials are not always feasible in educational research, so researchers must use alternative methods to study treatment effects. Propensity score matching is one such method for observational studies that has shown considerable growth in popularity since it was first introduced in the early 1980s. This paper outlines the concept of propensity scores by explaining their theoretical principles and providing two examples of their usefulness within the realm of educational research. Through worked examples, we highlight the effectiveness of propensity scores as a method for reducing bias and increasing the balance between treatment and comparison groups. To aid in the understanding and future use of propensity scores, we provide R syntax for all our analyses.
Dopaminergic modulation of axonal potassium channels and action potential waveform in pyramidal neurons of prefrontal cortex

• Dopamine and its receptors in prefrontal cortex (PFC) play an important role in regulating synaptic transmission and PFC‐mediated cognitive functions. • Considering that presynaptic action potential waveform can modulate postsynaptic responses, we investigated whether axonal K+ channels and action potential waveform are subjected to modulation by dopamine. • Patch‐clamp recording from the axon of PFC pyramidal neurons showed that the activation of D1 and D2 dopamine receptors decreased and enhanced axonal K+ currents, respectively. Further experiments revealed that intracellular cAMP–PKA pathway was involved in this dopaminergic modulation of axonal K+ currents. • Recording from axons disconnected from the soma revealed that the dopaminergic modulation still occurred, indicating the presence of functional dopamine receptors along the axon. • We further demonstrate that axonal action potentials were substantially prolonged by D1 receptor activation. Taken together, our results reveal a new mechanism for dopaminergic modulation of neuronal signalling in PFC.
Resurrecting the Law: State Formation and Legal Debates in Nineteenth-Century Greece

This paper discusses the legal debates of nineteenth-century Greece and the attempts to produce a legal framework following the establishment of the modern Greek state. These debates had both a practical significance since such a framework was essential for the creation of a modern state, and an ideological one since the chosen framework would be a statement about how the new state perceived itself, its history, and its place in Europe. These questions were particularly relevant in the case of civil law as Greek legal scholars contemplated whether to accept the use of customary law, or to reject it, and if so what laws should replace it. In this paper, I examine this debate within the context of European legal developments and the process of codification undertaken throughout Europe from the late eighteenth to the nineteenth centuries, as well as the ideological and practical implications of the debate. I argue that, despite the belief that the efforts of Greek legal scholars led to the elimination of the use of customary law from the Greek judicial system, my research in the archival material of the Appeals Court of Athens indicates that customary law was still dominant a generation after the establishment of the modern Greek state. I conclude that a re-examination of the role and practices of the Greek courts in the nineteenth century is much needed as their flexibility thirty years after the creation of the Greek state is closer to the legal pluralism of the courts of the Ottoman period than to the model advocated by the contemporary legal scholars who demanded a ‘modern’ judicial system to assist the renaissance of the Greek nation.
Reduction of Lipid Peroxidation in Reperfused Isolated Rabbit Hearts by Diltiazem

The calcium-channel inhibiting agent, diltiazem, has been shown to enhance salvage of reperfused myocardium independent of effects on coronary blood flow or myocardial work. Because lipid peroxidation may be a mediator of reperfusion injury and modifiable by calcium-sensitive pathways, we evaluated the effects of diltiazem on the formation of malondialdehyde (MDA), a product of lipid peroxidation, in isolated rabbit hearts perfused with buffer under control conditions or after 60 minutes of ischemia with or without 3 minutes of reperfusion. Diltiazem (5xl0∼7 M) reduced tissue MDA content in seven reperfused hearts compared with levels measured in 14 hearts reperfused without drug (1.54 ± 1.09 [SD] compared with 3.57 ± 1.88 nmol/g, p<0.05). Superoxide dismutase and catalase were ineffective in reducing tissue MDA content in reperfused hearts (n=8; MDA concentration, 3.88 ± 2.82 nmol/g) although they were effective in preventing lipid peroxidation in separate studies in which oxygen-centered free radicals were generated directly by an infusion of xanthine oxidase and hypoxanthine. These results suggest that the salutary effects of diltiazem in the setting of reperfusion may be mediated by reduction of lipid peroxidation at a locus not accessible to scavengers of oxygen-centered free radicals or by a mechanism not mediated by free radical pathways.
Generalization Effects in Evaluative Conditioning: Evidence for Attitude Transfer Effects from Single Exemplars to Social Categories

The present research investigated whether evaluatively conditioned attitudes toward members of a social category (CSs) generalize to other stimuli belonging to the same category as the CSs (generalization at the stimulus level) and to the category itself (generalization at the category level). In four experiments, USs were paired with schematic or naturalistic CSs belonging to certain fictitious groups. Afterward, attitudes toward the CSs, toward non-presented exemplars of the CS category, and toward the CS category were assessed. Results revealed evidence for generalization effects in EC on both the stimulus and the category level. Transfer effects were greater when participants’ awareness of the CS–US contingency (CA) was high. Moreover, we found differences in generalization between the stimulus and category level, indicating that different processes might contribute to the effects. Theoretical and practical implications such as using EC as a tool for changing attitudes toward social groups will be discussed.
Non-negative matrix factorization as a feature selection tool for maximum margin classifiers

Non-negative matrix factorization (NMF) has previously been shown to be a useful decomposition tool for multivariate data. Non-negative bases allow strictly additive combinations which have been shown to be part-based as well as relatively sparse. We pursue a discriminative decomposition by coupling NMF objective with a maximum margin classifier, specifically a support vector machine (SVM). Conversely, we propose an NMF based regularizer for SVM. We formulate the joint update equations and propose a new method which identifies the decomposition as well as the classification parameters. We present classification results on synthetic as well as real datasets.
Using Temporal Features of Observers’ Physiological Measures to Distinguish Between Genuine and Fake Smiles

Future affective computing research could be enhanced by enabling the computer to recognise a displayer's mental state from an observer's reaction (measured by physiological signals), using this information to improve recognition algorithms, and eventually to computer systems which are more responsive to human emotions. In this paper, an observer's physiological signals are analysed to distinguish displayers’ genuine from fake smiles. Overall, thirty smile videos were collected from four benchmark database and classified as showing genuine or fake smiles. Overall, forty observers viewed videos. We generally recorded four physiological signals: pupillary response (PR), electrocardiogram (ECG), galvanic skin response (GSR), and blood volume pulse (BVP). A number of temporal features were extracted after a few processing steps, and minimally correlated features between genuine and fake smiles were selected using the NCCA (canonical correlation analysis with neural network) system. Finally, classification accuracy was found to be as high as 98.8 percent from PR features using a leave-one-observer-out process. In comparison, the best current image processing technique [1] on the same video data was 95 percent correct. Observers were 59 percent (on average) to 90 percent (by voting) correct by their conscious choices. Our results demonstrate that humans can non-consciously (or emotionally) recognise the quality of smiles 4 percent better than current image processing techniques and 9 percent better than the conscious choices of groups.
The Reporting and Sustainable Business Marketing

Companies have to communicate to be noticed on the market, to promote their services and products, and to give assurances that they are a credible partner in the relationship with stakeholders. In this article, starting from the importance of marketing communication in business, an index of sustainability communication was created for the companies listed on the Bucharest Stock Exchange for the period 2008–2009, during the financial crisis, seeking to show the awareness of the difficult moment and the use of communication. Then, based on the relevance of accounting information model, we study the relationship between the index of sustainability communication and the share price, basically its influence on the future performance of the company. The regression analysis emphasizes the positive influence of the index of sustainability communication on the share price.
Temporal lobe structural evaluation after transsylvian selective amygdalohippocampectomy.

OBJECTIVE Mesial temporal lobe epilepsy (MTLE) is the most common type of focal epilepsy in adolescents and adults, and in 65% of cases, it is related to hippocampal sclerosis (HS). Selective surgical approaches to the treatment of MTLE have as their main goal resection of the amygdala and hippocampus with minimal damage to the neocortex, temporal stem, and optic radiations (ORs). The object of this study was to evaluate late postoperative imaging findings on the temporal lobe from a structural point of view. METHODS The authors conducted a retrospective evaluation of all patients with refractory MTLE who had undergone transsylvian selective amygdalohippocampectomy (SAH) in the period from 2002 to 2015. A surgical group was compared to a control group (i.e., adults with refractory MTLE with an indication for surgical treatment of epilepsy but who did not undergo the surgical procedure). The inferior frontooccipital fasciculus (IFOF), uncinate fasciculus (UF), and ORs were evaluated on diffusion tensor imaging analysis. The temporal pole neocortex was evaluated using T2 relaxometry. RESULTS For the IFOF and UF, there was a decrease in anisotropy, voxels, and fibers in the surgical group compared with those in the control group (p < 0.001). An increase in relaxometry time in the surgical group compared to that in the control group (p < 0.001) was documented, suggesting gliosis and neuronal loss in the temporal pole. CONCLUSIONS SAH techniques do not seem to totally preserve the temporal stem or even spare the neocortex of the temporal pole. Therefore, although the transsylvian approaches have been considered to be anatomically selective, there is evidence that the temporal pole neocortex suffers structural damage and potentially functional damage with these approaches.
REDD : A Public Data Set for Energy Disaggregation Research

Energy and sustainability issues raise a large number of problems that can be tackled using approaches from data mining and machine learning, but traction of such problems has been slow due to the lack of publicly available data. In this paper we present the Reference Energy Disaggregation Data Set (REDD), a freely available data set containing detailed power usage information from several homes, which is aimed at furthering research on energy disaggregation (the task of determining the component appliance contributions from an aggregated electricity signal). We discuss past approaches to disaggregation and how they have inﬂuenced our design choices in collecting data, we describe the hardware and software setups for the data collection, and we present initial benchmark disaggregation results using a well-known Factorial Hidden Markov Model (FHMM) technique.
Maximum Processing Rates of Memory Bound Systems

Multiresource queuing systems are of particular maportance in modding compnter systems because a job must have access to a processor and main memory sunultaneousIy in order to proceed. Existing methods of determining maximum processing rates for multiresourcequeuing systems are limited to small memory sizes because problem compleraty grows exponentially with increasing memory size. By restneting our attention to a particular scheduling discipline (first-come-first-loaded or FCFL) and treating memory as the limiting resource, methods of calculating maximum processing ~ates of memory bound systems for reahstic mare memory sizes are derived. The distribution of the number of jobs loaded under the FCFL pohey is given m terms of a convolution of the memory request size distribution. The time averaged behavior of the number of loaded jobs is also found. Finally, the framework is extended to allow multiple job classes in the input stream. The results of fins approach allow one to estimate main memory size requirements from a workload characterization given m terms of arrival rate, memory size distribution, and CPU service rate.
Effect of Oral Pregabalin Premedication on Post-Operative Pain in Laparoscopic Gastric Bypass Surgery

Background Post-operative pain and the administration of opioids to relieve it, is considered to be one of the important issues in surgery wards. This issue is even more significant in obese patients, because of the side effects of opioids. Pregabalin is an analog of gamma aminobutyric acid (GABA) which can be effective in dealing with post-operative pain. Objectives This study will consider the effect of oral pregabalin in relieving the pain of obese patients after gastric bypass surgery. Patients and Methods In a double blind clinical trial, 60 candidates for laparoscopic gastric bypass surgery were enrolled in the study through convenience and non-random sequential sampling, into two groups; pregabalin group and control group. Inclusion criteria consisted of: morbid obesity with a body mass index (BMI) > 35, age 18–50, American Society of Anesthesiologists (ASA) status I or II, and willingness to take part in the study. Patients in the pregabalin group received 300 mg of oral pregabalin on the morning of the surgery. Post-operative pain was controlled by the patient-controlled intravenous analgesia (PCIA) method, an AutoMed infusion pump containing 20 mg of morphine and normal saline (total volume 100 cc) was administered to all patients after surgery. Patients’ level of pain were compared by considering their pain intensity on a visual analog scale (VAS), and the occurrence of nausea/vomiting from recovery, until 24 hours after surgery. Results A total of 60 patients were compared; 30 patients in each of the pregabalin and control groups. Both groups were similar in age and sex distribution. Mean pain intensity levels during the whole follow up were lower in the pregabalin group than in the control group, up to a maximum of 24 hours after the operation (P < 0.001). Incidence of nausea/vomiting was greater in the control group than in the pregabalin group (P < 0.001). Conclusions The findings of this study indicate that oral pregabalin (300 mg dose) can alleviate patients’ pain and nausea/vomiting and notably reduce adverse effects.
Identification and Characterization of 63 MicroRNAs in the Asian Seabass Lates calcarifer

BACKGROUND MicroRNAs (miRNAs) play an important role in the regulation of many fundamental biological processes. So far miRNAs have been only identified in a few fish species, although there are over 30,000 fish species living under different environmental conditions on the earth. Here, we described an approach to identify conserved miRNAs and characterized their expression patterns in different tissues for the first time in a food fish species Asian seabass (Lates calcarifer). METHODOLOGY/PRINCIPAL FINDINGS By combining a bioinformatics analysis with an approach of homolog-based PCR amplification and sequencing, 63 novel miRNAs belonging to 29 conserved miRNA families were identified. Of which, 59 miRNAs were conserved across 10-86 species (E value ≤ 10⁻⁴) and 4 miRNAs were conserved only in fish species. qRT-PCR analysis showed that miR-29, miR-103, miR-125 and several let-7 family members were strongly and ubiquitously expressed in all tissues tested. Interestingly, miR-1, miR-21, miR-183, miR-184 and miR-192 showed highly conserved tissue-specific expression patterns. Exposure of the Asian seabass to lipopolysaccharide (LPS) resulted in up-regulation of over 50% of the identified miRNAs in spleen suggesting the importance of the miRNAs in acute inflammatory immune responses. CONCLUSIONS/SIGNIFICANCE The approach used in this study is highly effective for identification of conserved miRNAs. The identification of 63 miRNAs and determination of the spatial expression patterns of these miRNAs are valuable resources for further studies on post-transcriptional gene regulation in Asian seabass and other fish species. Further identification of the target genes of these miRNAs would shed new light on their regulatory roles of microRNAs in fish.
Sparse Conjoint Analysis Through Maximum Likelihood Estimation

Conjoint analysis (CA) is a classical tool used in preference assessment, where the objective is to estimate the utility function of an individual, or a group of individuals, based on expressed preference data. An example is choice-based CA for consumer profiling, i.e., unveiling consumer utility functions based solely on choices between products. A statistical model for choice-based CA is investigated in this paper. Unlike recent classification-based approaches, a sparsity-aware Gaussian maximum likelihood (ML) formulation is proposed to estimate the model parameters. Drawing from related robust parsimonious modeling approaches, the model uses sparsity constraints to account for outliers and to detect the salient features that influence decisions. Contributions include conditions for statistical identifiability, derivation of the pertinent Cramér-Rao Lower Bound (CRLB), and ML consistency conditions for the proposed sparse nonlinear model. The proposed ML approach lends itself naturally to ℓ1-type convex relaxations which are well-suited for distributed implementation, based on the alternating direction method of multipliers (ADMM). A particular decomposition is advocated which bypasses the apparent need for outlier communication, thus maintaining scalability. The performance of the proposed ML approach is demonstrated by comparing against the associated CRLB and prior state-of-the-art using both synthetic and real data sets.
A Comparison of Rhythmic Similarity Measures

Measuring the similarity between rhythms is a fundamental problem in computational music theory, with many applications such as music information retrieval and copyright infringement resolution. A common way to represent a rhythm is as a binary sequence where a zero denotes a rest (silence) and a one represents a beat or note onset. This paper compares various measures of rhythm similarity including the Hamming distance, the Euclidean interval-vector distance, the interval-dierence distance measure of Coyle and Shmulevich, the swap distance, and the chronotonic distance measures of Gustafson and Hofmann-Engl. Traditionally, rhythmic similarity measures are compared according to how well rhythms may be recognized with them, how ecien tly they can be retrieved from a data base, or how well they model human perception and cognition of rhythms. In contrast, here similarity measures are compared on the basis of how much insight they provide about the structural inter-relationships that exist within families of rhythms, when phylogenetic trees and graphs are computed from the distance matrices determined by these similarity measures. For two collections of rhythms, namely the 4/4 time and 12/8 time clave-bell time lines used in traditional African and Afro-American music, the chronotonic and swap distances appear to be superior to the other measures, and each has its own atractive features. The similarity measures are also compared according to their computational complexity.
Instability in dynamic fracture.

Cracks in brittle materials have terminal velocities far below theoretical predictions. To address this problem we have investigated the propagation of cracks in a brittle plastic (polymethylmethacrylate). Velocity measurements with resolution an order of magnitude better than past experiments reveal the existence of a critical velocity at which the velocity begins to oscillate, the mean acceleration drops sharply, and a pattern is formed on the fracture surface. Thus the dynamics of cracks may be governed by a dynamical instability.
Impedance matching and tuning of non-resonant mobile terminal antennas

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto. fi Author Risto Valkonen Name of the doctoral dissertation Impedance matching and tuning of non-resonant mobile terminal antennas Publisher School of Electrical Engineering Unit Department of Radio Science and Engineering Series Aalto University publication series DOCTORAL DISSERTATIONS 40/2013 Field of research Radio Engineering Manuscript submitted 25 October 2012 Date of the defence 15 March 2013 Permission to publish granted (date) 8 January 2013 Language English Monograph Article dissertation (summary + original articles)
Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach

Abstract Employing a large number of financial indicators, we use Bayesian model averaging (BMA) to forecast real-time measures of economic activity. The indicators include credit spreads based on portfolios, constructed directly from the secondary market prices of outstanding bonds, sorted by maturity and credit risk. Relative to an autoregressive benchmark, BMA yields consistent improvements in the prediction of the cyclically sensitive measures of economic activity at horizons from the current quarter out to four quarters hence. The gains in forecast accuracy are statistically significant and economically important and owe almost exclusively to the inclusion of credit spreads in the set of predictors.