Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of cooperation in multilevel public goods games with community structures

In a community-structured population, public goods games (PGG) occur both within and between communities. Such type of PGG is referred as multilevel public goods games (MPGG). We propose a minimalist evolutionary model of the MPGG and analytically study the evolution of cooperation. We demonstrate that in the case of sufficiently large community size and community number, if the imitation strength within community is weak, i.e., an individual imitates another one in the same community almost randomly, cooperation as well as punishment are more abundant than defection in the long run; if the imitation strength between communities is strong, i.e., the more successful strategy in two individuals from distinct communities is always imitated, cooperation and punishment are also more abundant. However, when both of the two imitation intensities are strong, defection becomes the most abundant strategy in the population. Our model provides insight into the investigation of the large-scale cooperation in public social dilemma among contemporary communities.
Real-time vehicle and lane detection with embedded hardware

For autonomously acting robots and driver assistance systems powerful optical stereo sensor systems are required. Object positions and environmental conditions have to be acquired in real-time. In this paper an algorithm based on a hardware-software co-design is applied. A depth-map is generated with a hierarchical detection method. A depth-histogram is generated by using the density distribution of the disparity in the depth-map. It is used for object detection. The object clustering can be accomplished without calculation of 3D-points, due to the almost identical mapping of the objects over the whole distance, within the histogram. A lane detection is applied by using a Hough transform. The suitability at night and the detection of small objects like bikers is proven.
INTEGRAL SELF-AFFINE TILES IN Rn II. LATTICE TILINGS

Let A be an expanding n n integer matrix with j det A j m A standard digit set D for A is any complete set of coset representatives for Z A Z Associated to a given D is a set T A D which is the attractor of an a ne iterated function system satisfying T d D T d It is known that T A D tiles R n by some subset of Z This paper proves that every standard digit set D gives a set T A D which tiles R with a lattice tiling
Regularized Least Absolute Deviations Regression and an Efficient Algorithm for Parameter Tuning

Linear regression is one of the most important and widely used techniques for data analysis. However, sometimes people are not satisfied with it because of the following two limitations: 1) its results are sensitive to outliers, so when the error terms are not normally distributed, especially when they have heavy-tailed distributions, linear regression often works badly; 2) its estimated coefficients tend to have high variance, although their bias is low. To reduce the influence of outliers, robust regression models were developed. Least absolute deviation (LAD) regression is one of them. LAD minimizes the mean absolute errors, instead of mean squared errors, so its results are more robust. To address the second limitation, shrinkage methods were proposed, which add a penalty on the size of the coefficients. The LASSO is one of these methods and it uses the L1-norm penalty, which not only reduces the prediction error and the variance of estimated coefficients, but also provides an automatic feature selection function. In this paper, we propose the regularized least absolute deviation (RLAD) regression model, which combines the nice features of the LAD and the LASSO together. The RLAD is a regularization method, whose objective function has the form of "loss + penalty. " The "loss" is the sum of the absolute deviations and the "penalty" is the L1-norm of the coefficient vector. Furthermore, to facilitate parameter tuning, we develop an efficient algorithm which can solve the entire regularization path in one pass. Simulations with various settings are performed to demonstrate its performance. Finally, we apply the algorithm to solve the image reconstruction problem and find interesting results.
Aprendizaje con información incompleta en modelos de consumo con múltiples atributos

This paper deals with an intertemporal model of optimization, which is based on multiple attribute utility functions (MUAT). The model assumes that consumers do not know a priori the optimal mixture of attributes which would maximize their utility from consumption. By using a MUAT lineal model, we state that the resulting consumption paths for four “extreme cases” are associated with several learning processes. In particular, we show that optimal equilibria in consumption of goods can be reached before the consumer exhausts her/his budget, a kind of equilibrium situation not analyzed in traditional utility functions.
Web Objects Clustering Through Aggregation for Enhanced Search Results

World Wide Web offer a rich mix of new challenges and opportunities to information computing researchers. The conventional search engine always returns a set of web pages in answer to a user query. Millions of web pages from organizations, institutions and personnel are made public electronically. With the web explosion and never ending raise of digital data, an added effect is the difficulty to retrieve relevant and reliable information from the Web. It is almost impossible for the naive user to get the right information in the answered search results as there is too much unrelated and out dated. The reason for this is rooted deep in the methodology for conventional Information computing on web that supports the indexing granularity for search as a web page. Search engines basically hunt for the potential web pages of user interests. On the contrary the user perspective in today's changing era is the information of a certain 'object' may be in the form of a cluster containing only the relevant data related to the object of interest rather than a tedious list of search results containing all the related and unrelated web pages. The similar theory can be applied to the queries from the point of view of developer. It requires grouping web objects into classes based on their attributes and links. This paper proposes algorithm for clustering web objects into different classes based on their links and identify relations dynamically. Results confirm the efficiency of the proposed approach as the user gets a cluster that contains only objects of interest from all the linked web pages.
Spontaneous immortalization of mouse liver sinusoidal endothelial cells

The spontaneous immortalization of cells in vitro is a rare event requiring genomic instability, such as alterations in chromosomes and mutations in genes. In the present study, we report a spontaneously immortalized liver sinusoidal endothelial cell (LSEC) line generated from mouse liver. These immortalized LSECs showed typical LSEC characteristics with the structure of transcellular fenestrations, the expression of von Willebrand factor (VWF) and the ability to uptake DiI-acetylated-low density lipoprotein (DiI-Ac-LDL). However, these immortalized LSECs lost the ability to form capillary-like structures, and showed clonal and multilayer growth without contact inhibition. Moreover, their proliferation rate increased with the increase in the number of passages. In addition, these cells obained the expression of CD31 and desmin, and showed an upregulation of p53 protein expression; however, their karyotype was normal, and they could not form colonies in soft agar or tumors in SCID mice. In conclusion, in the present study, we successfully established a spontaneously immortalized LSEC line.
Women in the United Arab Emirates : a portrait of progress

There is a lot of books, user manual, or guidebook that related to World Climate Education Place PDF, such as : grade 2 math word problems workbook report of the committee fashion doodles aplia answers key psychology test answer sheet 1 100 lies and fiction in the ancient world anthem study guide answers chapter 1 the unseen 2 3 4 richie tankersley cusick common engine problems with mercruiser engines thin places a pilgrimage home
The everolimus-eluting Xience stent in small vessel disease: bench, clinical, and pathology view

Coronary artery disease (CAD) is the leading cause of morbidity and mortality worldwide. The pathogenesis of CAD relates to the presence of atherosclerotic plaques in the coronary arteries, which are most frequently treated today by percutaneous coronary intervention. Small vessel disease treatment represents one-third of all percutaneous coronary interventions with higher rates of restenosis and major adverse cardiac events. Initially, drug-eluting stents (DES) were developed to reduce in-stent restenosis, improving clinical outcomes and reducing the need for target vessel revascularization. However, late and very late stent thrombosis emerged as a new problem compromising DES’s long-term results. The cobalt–chromium everolimus-eluting stent (CoCr-EES) represents the results of an evolutionary process in DES technology aimed at improving the shortcomings of first-generation DES. Small vessel CAD has historically been an obstacle to long-term patency following implantation of DES. Antirestenotic efficacy has been shown to be of high relevance in small vessels. Therefore, stent selection may play an important role in determining outcomes in this subgroup of patients. This article will review the performance of CoCr-EES in the treatment of small vessel CAD from preclinical, clinical, and pathology perspectives, and it will highlight the most important findings in this regard.
Loose social organisation of AB strain zebrafish groups in a two-patch environment

We study the collective behaviour of zebrafish shoals of different numbers of individuals (1, 2, 3, 5, 7, 10 and 20 AB zebrafish Danio rerio) in a constraint environment composed of two identical square rooms connected by a corridor. This simple set-up is similar to a natural patchy environment. We track the positions and the identities of the fish and compute the metrics at the group and at the individual levels. First, we show that the number of fish affects the behaviour of each individual in a group, the cohesion of the groups, the preferential interactions and the transition dynamics between the two rooms. Second, during collective departures, we show that the rankings of exit correspond to the topological organisations of the fish prior to their collective departure. This spatial organisation appears in the group a few seconds before a collective departure. These results provide new evidences on the spatial organisation of the groups and the effect of the number of fish on individual and collective behaviours in a patchy environment.
Simulating the Folding of Proteins

3 Introduction . 4 Protein Structure . 4 Protein Thermodynamics . 6 Predicting the Conformation of a Protein . 7 Genetic Algorithms . 7 Methodology . 8 Determining Atom Positions in Cartesian Coordinates . 9 Protein Energy Function. 10 Internal Energy . 10 Electrostatic Solvation Energy . 10 Nonpolar Solvation Energy . 13 Optimization Methods . 14 Gradient Search . 14 Golden Search . 15 Genetic Algorithm . 15 Initialization . 15 Selection . 15 Reproduction . 15 Mutation . 16 Termination . 17 Local Optimization Results . 17 Computation Time. 17
Aspect of Blame in Tweets: A Deep Recurrent Neural Network Approach

Twitter as an information dissemination tool has proved to be instrumental in generating user curated content in short spans of time. Tweeting usually occurs when reacting to events, speeches, about a service or product. This in some cases comes with its fair share of blame on varied aspects in reference to say an event. Our work in progress details how we plan to collect the informal texts, clean them and extract features for blame detection. We are interested in augmenting Recurrent Neural Networks (RNN) with self-developed association rules in getting the most out of the data for training and evaluation. We aim to test the performance of our approach using human-induced terror-related tweets corpus. It is possible tailoring the model to fit natural disaster scenarios.
Ambient Sulphur Dioxide and Female ED Visits for Migraine

Ambient sulphur dioxide (SO2) concentrations may affect the number of female emergency department (ED) visits for migraine. ED visits diagnosed as migraine among females in two cities in Canada, Toronto (N = 704) and Ottawa (N = 3, 358), were analyzed. In the study case-crossover design was used. Conditional logistic regression was realized to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) relative to an increase in an interquartile range (IQR, in Toronto IQR = 2.9 ppb, in Ottawa IQR = 3.9 ppb) of sulphur dioxide. In the constructed conditional logistic regression models, temperature and relative humidity were adjusted in the form of natural splines. In Toronto positive and statistically significant associations of sulphur dioxide with migraine ED visits were obtained: all ages, OR = 1.04 (95% CI: 1.00, 1.08); age group [15, 50], OR = 1.05 (95% CI: 1.01, 1.09). In Ottawa positive correlations were observed: all ages, OR = 1.05 (95% CI: 0.97, 1.13); age group [15, 50], OR = 1.06 (95% CI: 0.97, 1.15). The results suggest that female migraine may be affected by ambient sulphur dioxide.
The Many Meanings of Polarized Proof Theory Written Preliminary Examination II-Critical Review

Proof theory is the study of why a proposition is true in a system, as opposed to the study of which propositions are true. In ordinary classical logic all proofs of the same proposition are indistinguishable, so its proof theory is essentially nonexistent. Polarized logic aims to fill this void as a rich proof theory with classical reasoning principles. In this report we examine polarized logic from the perspective of Noam Zeilberger’s judgmental meaning-theories, and we apply this intuition to two different perspectives on polarization by Girard and Laurent.
Crystal structure of channelrhodopsin, a light-gated cation channel – all cations lead through the monomer –

Channelrhodopsin (ChR) is a light-gated cation channel derived from green algae. Since the inward flow of cations triggers the neuron firing, neurons expressing ChRs can be optically controlled even within freely moving mammals. Although ChR has been broadly applied to neuro-science research, little is known about its molecular mechanisms. We determined the crystal structure of chimeric ChR at 2.3 Å resolution and revealed its molecular architecture. The integration of structural, electrophysio-logical, and computational analyses provided insight into the molecular basis for the channel function of ChR, and paved the way for the principled design of ChR variants with novel properties.
Optimal Replacement Under Partial Observations

In this paper, we present a framework for the condition-based maintenance optimization. A technical system which can be in one of N operational states or in a failure state is considered. The system state is not observable, except the failure state. The information that is stochastically related to the system state is obtained through condition monitoring at equidistant inspection times. The system can be replaced at any time; a preventive replacement is less costly than failure replacement. The objective is to find a replacement policy minimizing the long run expected average cost per unit time. The replacement problem is formulated as an optimal stopping problem with partial information and transformed to a problem with complete information by applying the projection theorem to a smooth semimartingale process in the objective function. The dynamic equation is derived and analyzed in the piecewise deterministic Markov process stopping framework. The contraction property is shown and an algorithm for the calculation of the value function is presented, illustrated by an example.
Hesitant Fuzzy Soft Sets with Application in Multicriteria Group Decision Making Problems

Soft sets have been regarded as a useful mathematical tool to deal with uncertainty. In recent years, many scholars have shown an intense interest in soft sets and extended standard soft sets to intuitionistic fuzzy soft sets, interval-valued fuzzy soft sets, and generalized fuzzy soft sets. In this paper, hesitant fuzzy soft sets are defined by combining fuzzy soft sets with hesitant fuzzy sets. And some operations on hesitant fuzzy soft sets based on Archimedean t-norm and Archimedean t-conorm are defined. Besides, four aggregation operations, such as the HFSWA, HFSWG, GHFSWA, and GHFSWG operators, are given. Based on these operators, a multicriteria group decision making approach with hesitant fuzzy soft sets is also proposed. To demonstrate its accuracy and applicability, this approach is finally employed to calculate a numerical example.
Preface [Lectures on Behavioral Macroeconomics]

In mainstream economics, and particularly in New Keynesian macroeconomics, the booms and busts that characterize capitalism arise because of large external shocks. The combination of these shocks and the slow adjustments of wages and prices by rational agents leads to cyclical movements. In this book, Paul De Grauwe argues for a different macroeconomics model--one that works with an internal explanation of the business cycle and factors in agents' limited cognitive abilities. By creating a behavioral model that is not dependent on the prevailing concept of rationality, De Grauwe is better able to explain the fluctuations of economic activity that are an endemic feature of market economies. This new approach illustrates a richer macroeconomic dynamic that provides for a better understanding of fluctuations in output and inflation. De Grauwe shows that the behavioral model is driven by self-fulfilling waves of optimism and pessimism, or animal spirits. Booms and busts in economic activity are therefore natural outcomes of a behavioral model. The author uses this to analyze central issues in monetary policies, such as output stabilization, before extending his investigation into asset markets and more sophisticated forecasting rules. He also examines how well the theoretical predictions of the behavioral model perform when confronted with empirical data.
Why Self-Induced Pain Feels Less Painful than Externally Generated Pain: Distinct Brain Activation Patterns in Self- and Externally Generated Pain

Voluntary movement generally inhibits sensory systems. However, it is not clear how such movement influences pain. In the present study, subjects actively or passively experienced mechanical pain or pressure during functional MRI scanning. Pain and pressure were induced using two modified grip strengthener rings, each twined with four crystal bead strings, with polyhedral beads to induce pain, or spherical beads to induce pressure. Subjects held one ring in the left hand and were either asked to squeeze their left hand with their right hand (i.e., active pain or pressure), or to have their left hand squeezed by the experimenter (i.e., passive pain or pressure). Subjects rated the intensity and unpleasantness of the pain sensation lower in the active procedure than in the passive one. Correspondingly, pain-related brain areas were inhibited in the case of self-generated pain, including the primary somatosensory cortex (SI), anterior cingulate cortex (ACC), and the thalamus. These results suggest that active movement behaviorally inhibits concomitant mechanical pain, accompanied by an inhibition of pain response in pain-related brain areas such as the SI cortex. This might be part of the mechanisms underlying the kinesitherapy for pain treatment.
Differences in rotifer communities in two freshwater bodies of different trophic degree (Lake Ohrid and Lake Dojran, Macedonia)

We investigated monogonont rotifers in two natural Macedonian lakes that greatly differ in age, size and trophic state: Lake Ohrid and Lake Dojran. A main characteristic of Lake Ohrid is the scarcity of nutrients and consequently a low level of primary production. Lake Dojran represents a typical eutrophic lake. Results clearly indicate that species numbers are negatively correlated with trophic degree. Qualitative analyses of rotifer compositions in Lakes Ohrid and Dojran showed the presence of 70 and 55 taxa, respectively. Rotifer assemblages differed in their community structure, population densities, and the occurrence pattern of dominant species. The density of rotifers increased with increasing nutrient concentration, varying from min. 0.67 ind. L−1 in June, 2006 to max. 8.2 ind. L−1 in July, 2004 in Lake Ohrid, whereas min. 28.8 ind. L−1 (in December, 2005) and max. 442.5 ind. L−1 (in September, 2005) were recorded in Lake Dojran. Gastropus stylifer and Keratella cochlearis were the most abundant species in the pelagic zone of Lake Ohrid, averaging monthly densities of 1.2 ind. L−1 and 0.6 ind. L−1, respectively, thereby contributing 29% and 15% to rotifer abundance. In contrast, Lake Dojran rotifers were dominated by Brachionus spp. Brachionus diversicornis and Brachionus calyciflorus f. amphiceros were most abundant, comprising 40% and 25% of the total rotifer density. These results corroborate our idea, that the trophic state is an important factor in determining the composition of rotifer communities.
Detecting rogue devices in bluetooth networks using radio frequency fingerprinting

Unauthorized Bluetooth devices or rogue devices can impersonate legitimate devices through address and link key spoofing. Moreover, they can infiltrate a Bluetooth network and initiate other forms of attacks. This paper investigates a novel intrusion detection approach, which makes use of radio frequency fingerprinting (RFF) for profiling, Hotelling’s T 2 statistics for classification and a decision filter, for detecting these devices. RFF is a technique that is used to uniquely identify a transceiver based on the transient portion of the signal it generates. Moreover, the use of a statistical classifier proves advantageous in minimizing requirements for memory. Finally, the detection rate is also improved by incorporating a decision filter, which takes the classification results of a set of events into consideration, prior to rendering the final decision. The average False Alarm Rate of five percent and Detection Rate of ninety-three percent support the feasibility of employing these components to address the aforementioned problem.
Reporting on Risks: The Practice and Ethics of Health and Safety Communication

Preface The Field of Risk Communication The Journalist and the Pursuit of Truth The Scientist and the Pursuit of Truth Covering Medical News Covering Environmental Risks Covering Disasters The Influence of TV, Movies, and the Internet Covering the Health Care Story Ethical Issues in Risk Communication Appendix: In-Depth Reporting Examples Selected Bibliography Index
Searching for a light fermiophobic Higgs boson at the Tevatron

We propose new production mechanisms for light fermiophobic Higgs bosons ($h_f$) with suppressed couplings to vector bosons ($V$) at the Fermilab Tevatron. These mechanisms (e.g. $qq'\to H^\pm h_f$) are complementary to the conventional process $qq'\to Vh_f$, which suffers from a strong suppression of $1/\tan^2\beta$ in realistic models with a $h_f$. The new mechanisms extend the coverage at the Tevatron Run II to the larger $\tan\beta$ region, and offer the possibility of observing new event topologies with up to 4 photons.