Miracle-dz/UniFAR-FTUs huggingface dataset:
Randomness, Predictability, and Complexity in Repeated Interactions v0.02

Nash equilibrium often requires players to adopt a mixed strategy, i.e., a randomized choice between pure strategies. Typically, the player is asked to use some randomizing device, and the story usually ends here. In this paper, we will argue that: (1) Game theory needs to give an account of what counts as a random sequence (of behavior); (2) from a game-theoretic perspective, a plausible account of randnomness is given by algorithmic complexity theory, and, in particular, the complexity measure proposed by Kolmogorov; (3) in certain contexts, strategic reasoning amounts to modelling the opponent’s mind as a Turing machine; (4) this account of random behavior also highlights some interesting aspects on the nature of strategic thinking. Namely, it indicates that it is an art, in the sense that it cannot be reduced to following an algorithm.
Bioethanol a Microbial Biofuel Metabolite; New Insights of Yeasts Metabolic Engineering

Scarcity of the non-renewable energy sources, global warming, environmental pollution, and raising the cost of petroleum are the motive for the development of renewable, eco-friendly fuels production with low costs. Bioethanol production is one of the promising materials that can subrogate the petroleum oil, and it is considered recently as a clean liquid fuel or a neutral carbon. Diverse microorganisms such as yeasts and bacteria are able to produce bioethanol on a large scale, which can satisfy our daily needs with cheap and applicable methods. Saccharomyces cerevisiae and Pichia stipitis are two of the pioneer yeasts in ethanol production due to their abilities to produce a high amount of ethanol. The recent focus is directed towards lignocellulosic biomass that contains 30–50% cellulose and 20–40% hemicellulose, and can be transformed into glucose and fundamentally xylose after enzymatic hydrolysis. For this purpose, a number of various approaches have been used to engineer different pathways for improving the bioethanol production with simultaneous fermentation of pentose and hexoses sugars in the yeasts. These approaches include metabolic and flux analysis, modeling and expression analysis, followed by targeted deletions or the overexpression of key genes. In this review, we highlight and discuss the current status of yeasts genetic engineering for enhancing bioethanol production, and the conditions that influence bioethanol production.
Innovative Model, Tools, and Learning Environments to Promote Active Learning for Undergraduates in Computational Science and Engineering

This paper presents an innovative hybrid learning model as well as the tools, resources, and learning environment to promote active learning for both face-to-face students and online students. Most small universities in the United States lack adequate resources and cost justifiable enrollments to offer Computational Science and Engineering (CSE) courses. The goal of the project was to find an effective and affordable model for small universities to prepare underserved students with marketable analytical skills in CSE. As the primary outcome, the project created a cluster of collaborating institutions that combined students into common classes and used cyberlearning learning tools to deliver and manage instruction. The instrumental tools for educational technologies included Smart Podium, digital projector, teleconference systems such as AdobeConnect, auto tracking camera and high quality audio in both local and remote classrooms. As an innovative active learning environment, an R&D process was used to provide a coherent framework for designing instruction and assessing learning. Course design centered on model-based learning which proposes that students learn complex content by elaborating on their mental model, developing a conceptual model, refining a mathematical model, and conducting experiments to validate and revise their conceptual and mathematical models. A wave lab and underwater robotics lab were used to facilitate the experimental components of hands-on research projects. Course delivery included interactive live online help sessions, immediate feedback to students, peer support, and teamwork which were crucial for student success. Another key feature of instruction of the project was using emerging technologies such as HIMATT (Highly integrated model assessment technology and tools) [11] to evaluate how students think through and model complex, illdefined and ill-structured realistic problems.
An automatic cloud mask algorithm based on time series of MODIS measurements

[1] Quality of aerosol retrievals and atmospheric correction over land depends strongly on accuracy of the cloud mask (CM) algorithm. The heritage CM algorithms developed for AVHRR and MODIS use the latest sensor measurements of spectral reflectance and brightness temperature and perform processing at the pixel level. The algorithms are threshold-based and empirically tuned. They do not explicitly address the classical problem of cloud search, wherein the baseline clear-skies scene is defined for comparison. Here we report on a new land CM algorithm, which explicitly builds and maintains a reference clear-skies image of the surface (refcm) using a time series of MODIS measurements. The new algorithm, developed as part of the multiangle implementation of atmospheric correction (MAIAC) algorithm for MODIS, relies on the fact that clear-skies images of the same surface area have a common textural pattern, defined by the surface topography, boundaries of rivers and lakes, distribution of soils and vegetation, etc. This pattern changes slowly given the daily rate of global Earth observations, whereas clouds introduce high-frequency random disturbances. Under clear skies, consecutive gridded images of the same surface area have a high covariance, whereas in presence of clouds covariance is usually low. This idea is central to initialization of refcm, which is used to derive cloud mask in combination with spectral and brightness temperature tests. The refcm is continuously updated with the latest clear-skies MODIS measurements, thus adapting to seasonal and rapid surface changes. The algorithm is enhanced by an internal dynamic land-water-snow classification coupled with a surface change mask. An initial comparison shows that the new algorithm offers the potential to perform better than the MODIS MOD35 cloud mask in situations where the land surface is changing rapidly and over Earth regions covered by snow and ice.
Regulatory effects of HIF-1alpha on eNOS expressions in the vascular endothelium of pre-diabetic rats with aerobic exercise

Our previous study has demonstrated aerobic exercise contributed to the improvement of endothelial vasodilation functions by nitric oxide (NO) signaling activation during pre-diabetes mellitus. The present study was designed to examine the contribution of hypoxia inducible factor (HIF)-1alpha to the regulation of endothelial nitric oxide synthase (eNOS) expressions in the vascular endothelium of prediabetic rats with HIF-1alpha specific inhibitor echinomycin (Ech) and/or aerobic exercise. The results showed the expressions of eNOS mRNA and protein dramatically decreased after Ech treatment (p<0.05), while significantly increased exercise (p<0.05). Interestingly, no obvious changes of HIF-1alpha mRNA and protein expressions were found after Ech treatment. Further investigation found HIF-1 binding activity was inhibited after Ech treatment, which may contribute to the decrease of eNOS expressions. Together, the present study clearly indicated aerobic exercise induced eNOS expressions through the activation of HIF-1alpha signaling in the vascular endothelium of rat aorta during prediabetes mellitus, which shed a light on further understanding the protective effects of long-term habitual physical activity against vasodilation dysfunctions during pre-diabetes mellitus.
Burnout syndrome in nursing personnel of a referral hospital in Ibague, Colombia, 2014

Objective: To determine the prevalence of the burnout syndrome (BS) in nursing personnel of a referral hospital in a Colombian city and their relation with demographic variables. Materials and methods: a cross-sectional study was carried out on a random sample representative of 174 female and male nurses stratified based on if the nurse was a professional nurse or a nursing assistant in a referral hospital in the city of Ibague, Colombia. The MBI (Maslach Burnout Inventory) scale was used validated in Colombia. Tests of independence t were used for average differences and a oneway variance analysis. In the multivariate analysis, an explanatory binary logistic regression model was built with a measure of association; the OR is accompanied by its respective 95% confidence interval. Results: The prevalence of the Burnout Syndrome was 20.1% (IC 95%: 13.9 26.4), and 52.3% are at risk of suffering from Burnout Syndrome, they were Nursing professionals who had a temporary job or who were supernumeraries, and personnel who worked in services including administration, oncology, orderlies and sterilization. Men and personnel who stated having more than one contract were the people who presented the highest Burnout indicator ratio of 20.1%. In the multivariate analysis, joint factors which perhaps have greater incidence in the presence of Burnout Syndrome include the number of children and the fact of being a man. Conclusions: In comparison with other studies, this study reveals that the prevalence of the burnout syndrome in a referral hospital is greater.
Essays In Algorithmic Market Design Under Social Constraints

Rapid technological advances over the past few decades---in particular, the rise of the internet---has significantly reshaped and expanded the meaning of our everyday social activities, including our interactions with our social circle, the media, and our political and economic activities This dissertation aims to tackle some of the unique societal challenges underlying the design of automated online platforms that interact with people and organizations---namely, those imposed by legal, ethical, and strategic considerations. I narrow down attention to fairness considerations, learning with repeated trials, and competition for market share. In each case, I investigate the broad issue in a particular context (i.e. online market), and present the solution my research offers to the problem in that application. Addressing interdisciplinary problems, such as the ones in this dissertation, requires drawing ideas and techniques from various disciplines, including theoretical computer science, microeconomics, and applied statistics. The research presented here utilizes a combination of theoretical and data analysis tools to shed light on some of the key challenges in designing algorithms for today's online markets, including crowdsourcing and labor markets, online advertising, and social networks among others. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Computer and Information Science First Advisor Michael Kearns Second Advisor Ali Jadbabaie Subject Categories Computer Sciences This dissertation is available at ScholarlyCommons: https://repository.upenn. edu/edissertations/2331 ESSAYS IN ALGORITHMIC MARKET DESIGN UNDER SOCIAL CONSTRAINTS
Migration and Climate Change in Rural Africa

We analyse whether migration is an adaptation that households employ to cope with climate in Ghana and Nigeria. If migration is part of the present adaptation portfolio of households in developing countries, it is reasonable to expect that it will also be an adaptation to future climate change. It is important to stress that we are interested in long-term climatic conditions rather than in short-term weather fluctuations. The data to test these predictions are drawn from two different household surveys: the Nigeria General Household Survey and the Ghana Living Standard Survey. We find a hill-shaped relationship between temperature in the dry season and the propensity to migrate in households that operate farms. We also find a significant hill-shaped relationship between precipitations in the wet seasons and the propensity to migrate in farm households. Climate has instead no significant impact on the propensity to migrate in non-farm households. Climate change scenarios generated by General Circulation model reveal that, ceteris paribus, migration may decline in Ghana and in Nigeria.
The Structure-To-Function Relationships of Gammaherpesvirus-Encoded Long Non-Coding RNAs and Their Contributions to Viral Pathogenesis

Advances in next-generation sequencing have facilitated the discovery of a multitude of long non-coding RNAs (lncRNAs) with pleiotropic functions in cellular processes, disease, and viral pathogenesis. It came as no surprise when viruses were also revealed to transcribe their own lncRNAs. Among them, gammaherpesviruses, one of the three subfamilies of the Herpesviridae, code their largest number. These structurally and functionally intricate non-coding (nc) transcripts modulate cellular and viral gene expression to maintain viral latency or prompt lytic reactivation. These lncRNAs allow for the virus to escape cytosolic surveillance, sequester, and re-localize essential cellular factors and modulate the cell cycle and proliferation. Some viral lncRNAs act as “messenger molecules”, transferring information about viral infection to neighboring cells. This broad range of lncRNA functions is achieved through lncRNA structure-mediated interactions with effector molecules of viral and host origin, including other RNAs, proteins and DNAs. In this review, we discuss examples of gammaherpesvirus-encoded lncRNAs, emphasize their unique structural attributes, and link them to viral life cycle, pathogenesis, and disease progression. We will address their potential as novel targets for drug discovery and propose future directions to explore lncRNA structure and function relationship.
Quantile estimation and the statistical relative efficiency curve

In this article, we introduce a new practical tool—relative efficiency curve (REC)—for comparison of two competing statistical procedures. While in other scientific areas the term of REC has been around for some time, in statistics it seems to be new. In estimation, the curve is constructed by employing asymptotic properties of quantile estimators. Suppose two consistent and asymptotically normal estimators of a fixed quantile of the underlying distribution are available. Plotting of the ratio of their variances versus quantiles at various probability levels yields an REC. Such a curve provides information about the accuracy of one estimator relative to another when both are designed to estimate the same (fixed but arbitrary) quantile of the distribution. Thus, depending on the objective of application, the REC can help one choose between parametric, robust parametric, empirical nonparametric or other method of estimation for the measure of interest. Further, other possibilities for defining (statistical) RECs are also discussed, and illustrative examples for (equivalent) Pareto and exponential, and lognormal and normal distributions are provided. Specifically, graphs of RECs of maximum likelihood, method of trimmed moments, and empirical nonparametric estimators of distribution quantiles are presented.
Investigating Link Attributes of Graph Visualizations in Mobile Augmented Reality

© 2018 Copyright is held by the owner/author(s). Figure 1: Screenshot of the prototype. The picture shows the graph used in the study with different edge variants, a labeled node, and link details for a selected link. Abstract Current mobile devices have the necessary technological capabilities to support situated, augmented reality (AR) visualizations. Especially when dealing with data that is inherently spatial in nature or has a strong connection to the physical environment, 3D data visualizations may be suitable. One specific use case is the node-link visualization of network connections and their edge attributes, e. g. , to show link capacity or connectivity in LAN or IoT networks. So far, however, there has been very little research on which visual variables to use. We implemented eight link variants and report on the findings of an initial study in which we compared these different visual variables for edge attributes in 3D AR node-link diagrams.
An adaptive learning algorithm for a route choice problem in uncertain traffic environments

This paper describes how user equilibrium in a congested network has been conventionally formulated using mathematical optimization procedures. These approaches assume drivers’ behaviors with complete information in the sense that each driver knows the other drivers’ behaviors and their payoff functions. If each driver doesn’t know the other drivers’ strategies, they cannot optimize each others’ strategy. In such a situation, an adaptive heuristics may be a relevant approach to obtain a better solution. To establish behavioral rules of route choice under incomplete information, the paper uses a smooth fictitious play and a regret matching model developed in game theory. The model combines these two approaches. The paper also proposes a new algorithm that can be applicable to a complex situation in traffic environments.
Haplogroup E3b1a2 as a Possible Indicator of Settlement in Roman Britain by Soldiers of Balkan Origin

The invasion of Britain by the Roman military in CE 43, and the subsequent occupation of Britain for nearly four centuries, brought thousands of soldiers from the Balkan peninsula to Britain as part of auxiliary units and as regular legionnaires. The presence of Haplogroup E3b1a-M78 among the male populations of present-day Wales, England and Scotland, and its nearly complete absence among the modern male population of Ireland, provide a potential genetic indicator of settlement during the 1st through 4th Centuries CE by Roman soldiers from the Balkan peninsula and their male Romano-British descendants. Haplotype data from several major genetic surveys of Britain and Ireland are examined, analyzed and correlated with historical, epigraphic and archaeological information, with the goal of identifying any significant phylogeographic associations between E3b1a-M78 and those known RomanoBritish settlements and military posts that were associated specifically with Roman soldiers of Balkan origin. Studies by Cruciani et al. (2007), Perecic et al. (2005), and Marjanovic et al. (2005), examining the distribution of E3b1aM78 and E3b1a2-V13 in the Balkans, are analyzed further to provide evidence of phylogeographic associations between the E3b1a2 haplotypes identified within the Balkans by these studies and those regions of the Balkans occupied first by the Roman army in antiquity. E3b1a2 is found to be at its highest frequency worldwide in the geographic region corresponding closely to the ancient Roman province of Moesia Superior, a region that today encompasses Kosovo, southern Serbia, northern Macedonia and extreme northwestern Bulgaria. The Balkan studies also provide evidence to support the use of E3b1a-M78 (in the present study) as a close proxy for the presence of E3b1a2-V13 (representing 85% of the parent E3b1a-M78 clade) in both the Balkans and in Britain.
Web Semantic and Ontology

Ontologies have become a popular research topic in many communities. In fact, ontology is a main component of this research; therefore, the definition, structure and the main operations and applications of ontology are provided. Web content consists mainly of distributed hypertext and hypermedia, and is accessed via a combination of keyword based search and link navigation. Hence, the ontology can provide a common vocabulary, and a grammar for publishing data, and can supply a semantic description of data which can be used to preserve the ontologies and keep them ready for inference. This paper provides basic concepts of semantic web, and defines the structure and the main applications of ontology.
Competing Mechanisms : Communication and Equilibrium Robustness

We study competing mechanism games with principals simultaneously designing contracts to deal with agents. Following Epstein and Peters (1999), the traditional approach to characterize equilibrium mechanisms focuses on increasing the complexity of the agents’ message spaces to incorporate all the relevant market information generated by the competing principals. Principals, instead, could not send any signal to agents. Along the lines of Myerson (1982), we extend the traditional approach to allow for principals’ communication. We focus on complete information settings, and show by means of three examples that the restriction to one-sided communication mechanisms involves a loss of generality. ∗Toulouse School of Economics and University of Rome Tor Vergata, e-mail: andrea.attar@tse-fr.eu †University of Rome Tor Vergata, e-mail: eloisa.campioni@uniroma2.it ‡Ipag Business School Paris, e-mail: piaser@gmail.com
MGMT Gene Promoter Methylation Analysis by Pyrosequencing of Brain Tumour

Background: The aim of this study was to determine whether pyrosequencing (PSQ) might be useful to achieve O6-methyl guanine methyltransferase (MGMT) promoter methylation using 1- to 13-year-old archival tissues as a clinical biomarker in routine practice. Methods: The study included 141 formalin-fixed paraffin-embedded (FFPE) glial tumors from the archives of the Pathol ogy Department from 1997-2010. Results: The average percentage of methylation (MP) of the 141 cases was 14.0 ± 16.8%, and methylated cases were 32.3 ± 14.9%. The average MP of each year did not show a linear increasing or decreasing pattern according to the age of the FFPE block (p= 0.771). The average MP of methylated glioblastomas was 35.8 ± 14.7%, 31.8 ± 15.5% for anaplastic astrocytomas, and 22.4± 15.1% for astrocytoma. A tendency was observed toward an increasing pattern of average MP with World Health Organization (WHO) grade (p= 0.063) in astrocytic tumors. A correlation was observed between average MP and WHO grade (p= 0.038) and a bimodal distribution was observed between the methylated and unmethylated cases, using a 9% cut-off value (p< 0.001). Conclusions: The results showed that a quantitative approach for MGMT promoter methylation yielded a 100% success rate for FFPE tissues from archives. PSQ can be used in a retrospective trial, but the cut-off value and calculation method should be further validated.
The Development of Paranormal Belief Scale (PBS) for Science Education in the Context of Turkey

Present study aims to translate and develop Paranormal Belief Questions (Rice, 2003) measuring studentsâ non-scientific beliefs which threat science education. Original version of these questions was asked in Southern Focus Poll (1998). 17 questions about paranormal beliefs were administered to 114 university students from different departments. After translating and developing Paranormal Belief Questions into Turkish, factor analysis was conducted and paranormal beliefs were limited in two dimensions as classical paranormal beliefs and religious paranormal beliefs as parallel with original form. DA©jA vu item that is not consistent with other paranormal beliefs was removed depending on the factor analysis. The results of the current study enable to differentiate scientific beliefs from non-scientific beliefs of students. By this way, science educators can benefit from this scale.
Simulation framework and thorough analysis of the impact of barrier lowering on the current in SB-MOSFETs

In this paper we present a simulation framework to account for the Schottky barrier lowering models in SBMOSFETs within the Synopsys TCAD Sentaurus tool-chain. The improved Schottky barrier lowering model for field emission is considered. A strategy to extract the different current components and thus accurately predict the onand off-current regions are adressed. Detailed investigations of these components are presented along with an improved Schottky barrier lowering model for field emission. Finally, a comparison for the transfer characteristics is shown for simulation and experimental data.