Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized Memory Reveals the Survival Strategy for a Multi-agent Competition

We present a fractional model to clarify the dynamical evolution of how and under what circumstances--in a multi-agent economic area--newly founded ventures prolong their existence throughout the market. Since the increase in the number of newly-established firms in a market may generally lead to the reduction of the market share of players in the contest, after a while some may be faded out in the market. In this regard, considering a long term evolution, all firms are exposed to be eliminated and to give up their market share. That is why managers have the concern of attracting more customers to satisfy at least a minimum market share, and ideally prolong their firm's lifetime. On the other side, due to the establishment of more newly founded ventures in a certain industry, it is vital to be flexible and run new strategies. The triggered strategies not only must be on time but also must be led to lengthening the additional survival time. In the present study, it is shown that the existence of memory or lack of memory in the evolution may not be the case, but also having a strategy plays a significant role in survival. Hence, in spite of expo-sure to the risk of missing market share, the recalling of the past offered services and products of the weaker firm -- compared with the whole market -- may prolong the time-length of surviving in the market. In this regard, managers corresponding to the weaker firm will be able to quantitatively make decisions toward two main concepts, firstly the strategical usage of their firms' reputation and secondly, launching new features and services. The aim behind this optimization is to delay the time of reaching a minimum market share.
Tetrahedron maps and symmetries of three dimensional integrable discrete equations

A relationship between the tetrahedron equation for maps and the consistency property of integrable discrete equations on $\mathbb{Z}^3$ is investigated. Our approach is a generalization of a method developed in the context of Yang-Baxter maps, based on the invariants of symmetry groups of the lattice equations. The method is demonstrated by a case-by-case analysis of the octahedron type lattice equations classified recently, leading to some new examples of tetrahedron maps and integrable coupled lattice equations.
Photometric and spectroscopic diversity of Type II supernovae

Hydrogen-rich (Type II) supernovae (SNe) exhibit considerable photometric and spectroscopic diversity. Extending previous work that focused exclusively on photometry, we simultaneously model the multi-band light curves and optical spectra of Type II SNe using red supergiant (RSG) progenitors that are characterized by their H-rich envelope masses or the mass and extent of an enshrouding cocoon at the star’s surface. Reducing the H-rich envelope mass yields faster declining light curves, a shorter duration of the photospheric phase, and broader line profiles at early times. However, there is only a modest boost in early-time optical brightness. Increasing the mass of the circumstellar material (CSM) is more effective at boosting the early-time brightness and producing a fast-declining light curve while leaving the duration of the photospheric phase intact. It also makes the optical color bluer, delays the onset of recombination, and can severely reduce the speed of the fastest ejecta material. The early ejecta interaction with CSM is conducive to producing featureless spectra at 10−20 d and a weak or absent Hα absorption during the recombination phase. The slow decliners SNe 1999em, 2012aw, and 2004et can be explained with a 1.2 × 1051 erg explosion in a compact (∼600 R⊙) RSG star from a 15 M⊙ stellar evolution model. A small amount of CSM (<0.2 M⊙) improves the match to the SN photometry before 10 d. With more extended RSG progenitors, models predict lower ejecta kinetic energies, but the SN color stays blue for too long and the spectral line widths are too narrow. The fast decliners SNe 2013ej and 2014G may require 0.5−1.0 M⊙ of CSM, although this depends on the CSM structure. A larger boost to the luminosity (as needed for the fast decliners SNe 1979C or 1998S) requires interaction with a more spatially extended CSM, which might also be detached from the star.
Fast response of pulsed laser deposited Zinc ferrite thin film as a chemo-resistive gas sensor

Thin films of ZnFe2O4 deposited by pulsed laser technique are here demonstrated as one of the interesting materials for sensing of ethanol. The response transients were fitted well to one-site Langmuir adsorption model. Activation energies for (I) adsorption and reaction of ethanol and (II) desorption (i.e. recovery process) of ethanol from zinc ferrite thin film surface were obtained on the basis of this model. In this paper, we showed the effect of operating temperature and gas-concentration on the response time of thin film sensor materials. At the operating temperature 340oC, the ZnFe2O4 thin film showed high (84%) as well as immediate response to 500 ppm of ethanol, with its resistance being saturated within ~12 seconds, which stands far superior to the response time of nano crystalline powders. Those films were also observed to have a good repeatability of their sensor response, thus representing a major step towards low-cost large-scale production of this class of devices.
Dynamic Origin–Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter

Modern intelligent transportation systems provide data that allow real-time dynamic demand prediction, which is essential for planning and operations. The main challenge of prediction of dynamic origin–destination (O-D) demand matrices is that demand cannot be directly measured by traffic sensors; instead, it has to be inferred from aggregate traffic flow data on traffic links. Specifically, spatial correlation, congestion and time dependent factors need to be considered in general transportation networks. This paper proposes a novel O-D prediction framework combining heterogeneous prediction in graph neural networks and Kalman filter to recognize spatial and temporal patterns simultaneously. The underlying road network topology is converted into a corresponding line graph in the newly designed fusion line graph convolutional networks (FL-GCNs), which provide a general framework of predicting spatial-temporal O-D flows from link information. Data from the New Jersey Turnpike network are used to evaluate the proposed model. The results show that the proposed approach yields the best performance under various prediction scenarios. In addition, the advantage of combining deep neural networks and Kalman filter is demonstrated.
New β Cep pulsators discovered with K2 space photometry

We present the discovery of three new β Cep pulsators, three new pulsators with frequency groupings, and frequency patterns in a B3Ib star, all of which show pulsations with frequencies as high as about 17 d−1, with K2 space mission photometry. Based on a Fourier analysis and iterative pre-whitening, we present a classification and evaluate the potential for asteroseismic modelling. We include the lists of pulsation frequencies for three new β Cep pulsators, CD-28 12286, CD-27 10876, LS 3978, and additional pulsation mode frequencies for the known β Cep pulsator HD 164741. In addition, we characterize the regular frequency spacing found in the new pulsator HD 169173, and discuss its origin. We place the newly discovered variables in a colour–magnitude diagram using parallaxes from GaiaDR2 (second data release), showcasing their approximate location in the massive star domain. The identified frequency lists of these multiperiodic pulsators are a good starting point for future forward seismic modelling, after identification of at least one pulsation frequency from high-resolution time-series spectroscopy and/or multicolour photometry.
COMPARATIVE ANALYSIS OF INTERNET OF THINGS LIGHTWEIGHT AUTHENTICATION PROTOCOL DESIGN SCHEMES

Abstract— Lightweight authentication is a branch of the modern authentication techniques, which intended to be used in constraints network such IoT and WSN which has devices with low or extremely low resources. There are several ways for designing a lightweight authentication protocol, researchers are competing to find the best ways that fit with the features of the Internet of Things. In this paper, we propose generalized approaches to design lightweight authentication protocols. Also, we highlight some principals and security requirements for the implementation of lightweight authentication. Finally, we provide a comparative study of using symmetric and asymmetric cryptography techniques for designing lightweight authentication protocols for IoT.
An Ultra-Low Power 28 nm FD-SOI Low Noise Amplifier Based on Channel Aware Receiver System Analysis

This study investigates the benefit of an optimal and energy-efficient reconfiguration technique for the design of channel-aware receiver aiming Internet of Things (IoT) applications. First, it demonstrates the interest for adaptive receivers based on an estimation of the received power and compares the proposed channel-aware receiver with the State Of the Art. It is shown that the lifetime of the Wireless Sensor (WS) battery can be extended by a factor of five with the optimization of operating points of the tunable receiver while maintaining similar performances than industrial modules. The design of an Ultra-Low Power (ULP) inductorless Low Noise Amplifier (LNA), which fits the low power mode of the tunable receiver, is then optimized and described. The back-gate biasing of Fully Depleted Silicon-On-Insulator (FD-SOI) technology to lower the power consumption by more than 25% still maintaining performances is evaluated. The proposed LNA has been implemented in ST-Microelectronics 28 nm FD-SOI Technology, its active area is only 0.0015 mm2. The measured performances at 2.4 GHz exhibit more than 16 dB of voltage Gain (Gv), 7.3 dB of Noise Figure (NF), and a −16 dBm Input referred third-order Intercept Point (IIP3). The LNA consumes 300 µW from a 0.6 V supply.
IBBJ Summer 2018 , Vol 4 , No 3 Quorum Sensing in Microbial Virulence

Cell-to cell communication occurs via a signaling pathway referred to as quorum sensing. There are four main types of these systems according to the chemical nature of signal molecules used by microorganisms to elicit expression of target genes in response to environmental stimuli or need of microbial communities. Type I system acts by using acyl homoserine lactones as signals to trigger the expression of virulence genes in Pseudomonas aeruginosa and members of the Enterobacteriacae family. Other groups of bacteria possess a second system which uses certain furanones as a universal language among different species. Pathogenic Shigella spp. , Salmonella, and Escherichia coli rely on catecholamines of the human host for inducing a third quorum sensing system in infection. Short cyclic peptides act mainly in Staphylococcus spp. and Enteroccocus faecalis to activate a forth system involved in their pathogenicity. Therefore, it is essential to analyze these systems for the design of antimicrobials that could eliminate pathogens or abolish their harmful activities.
The Impact of Institutional Ownership on the Performance of Companies Listed In the Egyptian Stock Market

This study investigates the relationship between institutional ownership and company performance of listed companies in Egypt. The study used the multiple regressions and a sample data of Eight years panel data of 73 Egyptian companies listed in the Egyptian Stock Market were examined. The results showed that institutional ownership had positive and significant relationship with firm performance. Therefore, the involvement of institutional ownership in monitoring and controlling activities reduced agency conflict and enhanced corporate performance in the emerging economy. While for the effect of different institutional ownership patterns on the performance of companies in term of ROE, It has been shown that the ownership of holding companies (HC), that represent the government ownership, had positive significance effect on firm performance. Besides, each of the following Institutional ownership patterns has positive effect on companies' performance: Bank ownership, insurance ownership, mutual funds ownership (even that the effect is insignificant for banks and investment funds). in aspect of questionnaire of the indicator characteristics of institutional ownership shares, It has been shown that each of the following characteristics have positive role on institutional ownership: company size, law type (the company legal classification according to the law governing it), and the number of board members representatives of institutions , which indicate that institutional owners care about these variables when determining their participations and contributions in joint stock companies.
Large-scale shoreline undulations and role of self-organization processes

This study investigates the large scale spatial variation behaviour of shoreline changes using the beach profile data along approximately 600 km shoreline around Hainan Island, China. It was found that there exists a power-law relationship between the mean shoreline change variance and the corresponding alongshore scale which holds up to 30 km for the annual shoreline change and reduces to 15 km for the seasonal shoreline change. The spatial and seasonal variations of shoreline azimuth, beach sediment size and wave conditions, and their connection with the shoreline change on different scales were studied. The results suggest that the internal feedback mechanisms between various processes with different spatial scales may be responsible for the observed shoreline change patterns, i.e. the annual shoreline behaviour on spatial scale 5–30 km is likely to be the result of selforganization, while the seasonal waves including tropical cyclones and storms exert dominant control of the morphological patterns at spatial scale of 10–25 km.
A Closer Look at Account Sharing: How Sharing Ends, Why, What Makes It Hard?

Little has been done to investigate how online accounts can be designed to support the end of sharing, while protecting the privacy and security of users. To ﬁll this knowledge gap, we conducted semi-structured interviews with 25 people who previously shared online accounts. Our results suggest that, apart from a romantic breakup there are many other reasons why people stop sharing accounts with each other. There is therefore a need for online accounts to be designed to ﬁt these different social contexts. Participants also had trouble in splitting their shared content after the end of sharing. We suggest design recommendations to accommodate the various ending scenarios.
Long Term Monitoring of Geophysical Parameters using SLR

The SLR observation dataset, similarly to the other space geodetic techniques, is a valuable source of data for measuring fundamental geophysical parameters and their temporal variations with respect to different time scales. As an example, the distinctive sensitivity of the SLR technique to global parameters as the origin and scale of the Terrestrial Reference Frame profits from the remarkable length of its observations dataset, allowing the stable and accurate retrieval of those parameters, turning into a reliable maintenance of the TRF. The most recent and updated ASI/CGS analyses of Lageos-I and Lageos-II data cover two decades and provide time series of daily Earth Rotation Parameters (EOP) and Length Of Day (LOD), weekly geocenter offsets with respect to the TRF, weekly J2 estimates, station coordinates and velocities together with orbital parameters, biases, and other technique-based nuisance parameters. The complex interrelation among all the parameters allows the crosschecking and helps in detecting real geophysical signals from the parameters time series. Some of the results coming out from the solutions are shown, with particular emphasis to the terrestrial reference frame monitoring. Comparisons are made with the standard IERS references.
Software Defined Networking: Research Issues, Challenges and Opportunities

Objectives: This paper focuses on challenges, opportunities and research issues of software defined networking (SDN), as well as how to select the best possible SDN controller, which in result will help to reduce the complexity of a network, price of implementation and maintenance of the network in any big organization. Methods/Statistical Analysis: In order to meet the objective, the review of literature has been carried out in the following contexts; Software defined networking, SDN protocol (Open Flow) and SDN research challenges. Software defined networking is one of the most discussed topic these days. This technology is being considered one of the favorable technologies for isolation of control plane and data plane and logical placement of centralized control from SDN controller. This research focuses on major issues, challenges and current requirements of network implemented in any big organization where traditional network is being implemented. Findings: To solve the issues of multiple located branch networks, cost, technical resources at each location, expertise, separate control plane for configurations, decentralized visibility of network devices, separate VLANs for each branch, complex traffic engineering, limited physical access of branches w.r. t working hours, bandwidth bottleneck at each branch, we surveyed literatures and web resources for the existing SDN controllers like NOX, POX, Ryu, Floodlight, and Open Daylight etc. All these controllers are based on Open Flow protocol. The primary concern is that a conventional system develops gradually, it has a generally abnormal state of operational expenditure and moderately static in nature. SDN holds the guarantee of overcoming those confinements. Major issues which are being faced are increasing requirements from user side, bandwidth availability, hardware (switches requirement at every place), technical resources are required at remote site for configurations, scalability issues, cost, high level processing power at each device, traffic engineering, resiliency against failures, decentralized visibility of hardware devices etc. SDN will helps to improve centralized visibility as all the underlying open flow switches are connected to controller, all switches can be configured from SDN controller without accessing individual switches. Research papers referred in this paper provide a bird eye view of what may cause hurdles further in development and technology integration of technology. Application/Improvements: This research will help how to select the best possible SDN controller which in result will help scalability, less hardware and software requirements, less technical resources requirements, centralized visibility, hassle free traffic engineering and high availability of network.
1 Theoretical Determination of Size Effects in Zeolite-2 Catalyzed Alcohol Dehydration 3

In the upgrading of biomass pyrolysis vapors to hydrocarbons, dehydration accomplishes 10 a primary objective of removing oxygen and acidic zeolites represent promising catalysts for 11 dehydration reaction. Here, we utilize density functional theory calculations to estimate adsorption 12 energetics and intrinsic kinetics of alcohol dehydration over H-ZSM-5, H-BEA, and H-AEL zeolites. 13 ONIOM calculations of adsorption energies were observed to be inconsistent when benchmarked 14 against QM/Hartree-Fock and periodic boundary condition calculations. However, reaction 15 coordinate calculations of adsorbed species and transition states were consistent across all levels 16 considered. Comparison of ethanol, iso-propanol (IPA), and tert-amyl alcohol (TAA) over these 17 three zeolites allowed for a detailed examination of how confinement impacts reaction mechanisms 18 and kinetics. TAA, seen to proceed via a carbocationic mechanism, was found to have the lowest 19 activation barrier, followed by IPA and then ethanol, both of which dehydrate via a concerted 20 mechanism. Barriers in H-BEA were consistently found to be lower than in H-ZSM-5 and H-AEL, 21 attributed to late transition states and either elevated strain or inaccurately estimating long-range 22 electrostatic interactions in H-AEL, respectively. Molecular dynamics simulations revealed that the 23 diffusivity of these three alcohols in H-ZSM-5 are significantly overestimated by Knudsen diffusion, 24 which will complicate experimental efforts to develop a kinetic model for catalytic fast pyrolysis. 25
EQUATION OF STATE FOR LITHIUM IN SHOCK WAVES

An equation of state in the form of an analytic function of the pressure on the specific volume and the internal energy is proposed for lithium in the bcc-solid and liquid phases. The principal Hugoniot adiabat is calculated for the metal and compared with available shockwave data. The results of the calculations are in good agreement with the data over the whole range of kinematic and dynamic characteristics investigated. This equation of state can be used effectively in simulations of shock-wave processes in lithium at high pressures.
From Distributed Sources to Distributed Sinks: Towards Truly Decentralized Event Stream Processing

Distributed stream processing evaluates queries over data produced by geographically distributed sources. To e � ciently handle large amounts of decentralized data, whilst coping with bandwidth restrictions, applications employ in-network processing. To this end, a query is modularized and its operators are assigned to network nodes, especially those that act as data sources. The latter is known as the operator placement problem. Existing solutions to it, however, handle data generated by distributed sources, whereas query results are gathered at one designated node – the sink. We argue that such single-sink solutions are not applicable for non-hierarchical system, in which multiple nodes need to be informed about query results. Also, having a single sink enforces centralisation in compositional applications, where the result of one query is the input to another query. This PhD project therefore aims to develop algorithms for multi-sink operator placement. We show that the computation of network costs for e � cient operator placement, however, requires us to incorporate various aspects of event generation, query processing semantics, and network properties.