Miracle-dz/UniFAR-FTUs huggingface dataset:
DERIVING ATMOSPHERIC MOTION VECTORS FROM AIRS MOISTURE RETRIEVAL DATA

Over the last 10 years, polar winds from the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery have been generated by NOAA and the Cooperative Institute for Meteorological Satellite Studies (CIMSS). These datasets are a NOAA/NESDIS operational satellite product that is used at more than 10 major Numerical Weather Prediction (NWP) centers worldwide. The MODIS polar winds product is composed of both infrared window and water vapor tracked features. The water vapor atmospheric motion vectors (AMV) provide a more complete geographic distribution than the infrared window since both cloud and clear-sky features can be tracked in the water vapor images. However, polar orbiting satellites over the next decade (Metop and Suomi National Polar-orbiting Partnership (NPP)) will not have a water vapor channel as part of the imaging instrument, which will result in only infrared window AMVs. This potential gap in clear-sky AMVs provides motivation to investigate the use of Atmospheric Infrared Sounder (AIRS) moisture retrievals from consecutive overlapping Aqua satellite polar passes to extract atmospheric motion from clear and above cloud regions on constant pressure surfaces. Since the AIRS retrieval algorithm results in many tropospheric levels of moisture fields, this method also has the potential to provide vertical wind profiles, as opposed to the current MODIS-derived single-level AMVs.
Terrorism Networks and Trade

We study the impact of transnational terrorism diffusion on security and trade. We set a simple theoretical model predicting that the closer a country to a source of terrorism, the higher the negative spillovers on its trade. The idea is that security measures, which impede trade, are directed both against the source country of terror and its neighbor countries where terrorism may diffuse. In contrast, we demonstrate that countries located far from terror could benefit from an increase in security by trading more. Taken to the test, we empirically document these predictions. We find (1) a direct negative impact of transnational terrorism on trade; (2) an indirect negative impact emanating from terrorism of neighbor countries; and (3) that trade is increasing with remoteness to terror. These results are robust to various definitions of the neighboring relationships among countries. JEL Classification: F12, F13
Aerobic training prevents the impaired vascular reactivity of fructose‐treated rats (1106.22)

Fructose intake is associated with cardiometabolic disorders, but few studies investigated its role on vascular reactivity and the potential effects of exercise training. Thus, we assessed the effect of fructose intake on vascular reactivity in trained rats. Therefore male Wistar rats (n=7/group) received tap water (control group, C) or Fructose 10% (F group) ad libitum for two weeks. Then, rats underwent treadmill exercise for eight weeks (FT group). Caloric intake was higher in fructose groups compared with C group (P<0.01), although we found no change in body weight and in lipid profile, except the higher HDL in FT group (P<0.01). Training increased serum NO (C=296.5±42.8; F=325.8±51.6; FT=718.4±151.2; P<0.01). Regarding body composition, F increased body fat content compared with C and FT groups (P=0.03), whereas the FT group showed higher protein content (P<0.01). Finally, vascular vasoconstrictor reactivity was increased by fructose since F group required lower concentrations of phenylephrine to promote 50% of the maximum contractile effect when compared to C and FT groups (C=1.31‐6±2.4‐7; F=2.43‐7±6.5‐8; FT= 7.99‐7±1.5‐7 M; P<0,01). Vasodilator response to acetylcholine was also impaired in F group and was preserved by exercise training (C= 3.13‐7±1.9‐7; F=3.64‐6±9.6‐7; FT=3.13‐7±1.9‐7M; P<0.01). Thus, aerobic exercise prevented fructose‐impaired vascular reactivity in rats.
Kinematic and Dynamic Controller Design for Autonomous Driving of Car-like Mobile Robot

Autonomous driving technologies are taken into account for numerous applications such as spraying agricultural chemicals, mowing golf course grass, unmanned military operations and commercial applications such as self-driving cars. This paper presents a kinematic and dynamic controller design of autonomous mobile robot for a car like vehicle to self-drive using GPS. In this paper, a simple kinematic bicycle model is introduced and Model Predictive Controller (MPC) is derived for controlling the mobile robot. Computational simulation results show that the robot can successfully navigate and drive toward a final destination reacting to the changes in the environment. Finally this study presents experimental results to show the effectiveness of the proposed controller. 
Implementation of Consensus Control Using Lambda-Edge Architecture

—Swarm robotics are an important ﬁeld to researchers because of their ability to perform complex tasks that no individual in the swarm could accomplish otherwise. They have the advantage of being able to cover a larger area and collect more data, but at the cost of a reliance on networked communications that increase delay in the system. Because of this reliance on networked communication, swarm robotics can be easily adapted to work with cloud based controls, which offer far more computational power to the system. Cloud controls have been further improved by the use of unique architectures such as the Lambda-Edge architecture, which splits tasks into batch and speed components that are only partly run on the cloud in order to increase responsiveness. This paper proposes a cloud control system that uses the Lambda-Edge architecture in order to control a swarm that is capable of learning an unknown sensor function and distributing individuals based on it. The control system is then proven using a Gazebo simulation.
PII: S0032-3861(98)00474-1

The computational method described in this paper allows the calculation of the dielectric relaxation strength of an amorphous polymer based solely upon its chemical structure. The 4,4 9 oxydiphthalic anhydride (ODPA) dianhydride and bis-aminophenoxybenzene (APB) diamine based polyimides, ( b-CN) APB–ODPA and APB–ODPA were studied. Amorphous cells were constructed and then poled using molecular dynamics. Dielectric relaxation strengths of De 1⁄4 17.8 for (b-CN) APB–ODPA andDe 1⁄4 7.7 for APB–ODPA were predicted. These values are in excellent agreement with the experimental values. It was found that both the pendant nitrile dipole and the backbone anhydride residue dipole make significant contributions to the polyimides’ dielectric response. Specifically, it was shown that the difference in the magnitude of the dielectric relaxations is directly attributable to the nitrile dipole. The size of the relaxations indicate an absence of cooperative dipolar motions. The model was used to explain these results in terms of the average orientation of the nitrile and anhydride dipoles to within 518 and 638, respectively, of the applied electric field. q 1999 Elsevier Science Ltd. All rights reserved.
Modeling Behavioral Dynamics of Multi-Agent Learning using Artiﬁcial Intelligence and Digital Twins

Biomimetic social interactions between animals and robots is an interesting scientiﬁc ﬁeld that involve both biologists and engineers. The perspective of this ﬁeld is to study animal abilities and deliver innovative strategies for creating robots with more ﬂexible and adaptive behaviors in unstructured environments. Biomimetic robots, unlike traditional behavioral observations, can exhibit speciﬁc behavioral patterns on demand, thus enabling researchers in behavioral ecology to examine and / or manipulate selected behaviors in animals with a high degree of reliability. The contribution of this paper is to create a socially aware digital twin of a robot-animal platform that mimics some aspects of sensory and behavior of the physical robot. The proposed digital twin attempts to understand the behavior of the animals as a ﬀ ected by the robot along with the robots’ behavior as a ﬀ ected through interactions with the animals in this mixed-society. The digital twin of the robot-animal is investigated in a swarm of ﬁsh where the social function of aggregations can be seen in several aspects of their behavior. The experimental results show collective intelligence of a digital twin in a swarm of ﬁsh emerges in a decentralized way from the actions of individual ﬁsh responding to local stimuli from the environment and, most importantly, from other members of the swarm.
The interplay between citizen initiatives and invited participation in urban planning: An interaction research project

In the global competition for investment many cities become objects for gentrification with subsequent reshaping of certain areas and withdrawal of the state from others, a process reinforced by restrictions in public expenditure. In Sweden and other European countries suburbs are increasingly viewed as ‘peripheries’ attributed with ‘territorial stigma’ (Wacquant 2003) and commonly portrayed as places of ‘fundamental otherness’ (Dahlstedt 2005). Electoral participation is significantly lower in these areas than the national average (Tahvilzadeh 2009) and the inhabitants are underrepresented in other democratic activities (Blomqvist 2005).
Smart Commiutinty, Smart Transportation and Big Data

- World population growing in conjunction with the preference to live in the cities; make the city management a challenging issue. Traditional Cities with their common features will not be able to handle the human needs. As a result, smart city and its beneficial outcomes will attract lots of attention in the following years. In fact, Smart city/community that is the field of collecting and processing data from so many different areas while making proper decisions and feeding to all parts of the system will be the future style of the cities. In other words, smart community is a complex big data problem which should combine different fields of research to make a unit environment. This paper will deal with all aspects of the smart community. There will be also explained different categories of the smart communities in addition to their future challenges.
CONSENT DECREES IN CARTEL INVESTIGATIONS IN BRAZIL

The purpose of this paper is to analyze certain aspects in the fight against cartels based on agreements between the government and a cartel member, who will provide assistance during the investigation. This paper also provides some notes on the likely effects of this kind of strategy on the antitrust policy. It has become more often the practice of agreements among agents accused of cartel and the antitrust authorities, which agreements are referred to as consent decrees. These agreements are believed to be highly advantageous to the Public Administration and not to jeopardize the efficiency of the policy to fight cartels through leniency. The main benefit of these agreements, especially in view of the tardiness of the Judiciary Branch, would be the opportunity for the antitrust authorities to rapidly resolve a case, thus avoiding the expenditure of public resources that could be used in other * MSc in Regulation London School of Economics and Political Science; LLM in Economic Law University of São Paulo; PhD Candidate in Economic Law University of São Paulo. LEOPOLDO UBIRATAN CARREIRO PAGOTTO 164 Rev. Derecho Competencia. Bogotá (Colombia), vol. 5 N° 5, 163-187, enero-diciembre 2009 investigations. Both leniency agreements and consent decrees are designed as an optimum regulatory strategy for antitrust agencies. Should one consider this strategy as the closest to an “ideal” strategy to fight cartels? To try to answer to this question, the paper shall be divided into the following sections: • Operation of agreements with cartels in the United States; • Operation of agreements with cartels in Brazil; • Rationale of agreements with cartels; and • Possible noises of the institutional endowment of Brazil as regards the use of consent decrees.
INFLUENCE OF INTEGRATED MANAGEMENT SYSTEM ON QUALITY MANAGEMENT PERFORMANCE

Standard ISO 9001:2015 defines some common requirements focused on overall functioning of quality management system in organizations that concern: nonconformity control, corrective actions, customer satisfaction, etc. All these requirements are repeated in standards ISO 14001 and OHSAS 18001 and they should be integrated in a single management system in an organization. The number of implemented standards should increase key performance indicators of the organization`s processes but, in some cases, they can also lead to overlapping and fuzziness. Having in mind that the knowledge of the organization based on leadership awareness was always essential for the functioning of management systems, the authors wanted to explore the correlation between a number of implemented standards and leadership awareness on quality management essential constructs. This paper provides the results of a survey of 50 ISO certified companies in region, which were analyzed and corresponding conclusions were made.
in Computer Science and Software Engineering

— Predicting the location of the protein in the cell helps us to understand its structure and function better. Subcellular localization is a well-designed representation of proteins. We need a reliable method for predicting the protein subcellular locations. It would be significant in interpreting the original data produced by the large scale genome sequencing projects. The aim of this paper is to provide an overview of the use Hidden Markov Model for the prediction of protein subcellular sites. Using sequence data, HMM achieves higher prediction accuracy than any other methods in many cases. HMM adds some beneficial structural and parametric assumptions such as hidden state variables that are useful for prediction. Currently this method is limited to time series data.
Traces on graphs and higher-rank graphs

This report examines directed graphs, which consist of vertices and oriented edges between them. Every directed graph E has an associated graph C*-algebra, C∗(E), as defined by Kumjian and Pask in [5]. Such a C∗-algebra is generated by a collection of partial isometries and projections satisfying relations defined via the graph E. The study of graph algebras focuses on understanding graph-theoretic conditions on a graph E which control algebraic or analytic behavior of C∗(E). We will study the properties of well-known graph product operations, such as the tensor product, on directed graphs and higher rank graphs. Higher rank graphs, or k-graphs, introduced by Alex Kumjian and David Pask are the multidimensional analogue to directed graphs. Products on k-graphs are of particular interest due to the fact that the tensor product of the C*-algebras of 1-graphs correspond to the C*-algebra of their product 2-graph, as shown by Johnston and Reynolds. This report also focuses on graph traces, functions from the vertices of a graph to the natural numbers, as introduced by Hjelmborg, Tomforde, and Johnson. The set of these traces on directed graphs is isomorphic to the set of tracial states on the associated C*-algebra. Extreme graphs traces, which are graph traces that cannot be
Design of Wideband Compact Electric-Inductive- Capacitive (ELC) Inclusions for Metamaterials

Alternative designs for wideband compact electric-inductive-capacitive (ELC) inclusions, which can be used to construct metamaterials with desired high permittivity over a wide frequency band, are proposed and analyzed in this letter. To design a compact ELC inclusion, we incorporate a meander line (ML) into the conventional ELC structure. This helps to increase the equivalent inductance, which could lower the resonant frequency of the structure effectively. To expand the operating bandwidth, we introduce incremental variations in the dimensions of the ML. This helps create multiresonant responses of metamaterials, which could achieve high permittivity over a wide frequency band. The proposed design, which has an electrical size of about 1/14 of the wavelength in free space, can achieve approximately 40% more bandwidth than the single-resonance case for permittivity values greater than 3.5, or a 350 MHz bandwidth at 5 GHz. Experimental verifications were carried out to verify the design concept.
A review of Single-Phase Inverter Topology for Grid Connected Small Distributed Renewable Energy Generation

This paper focuses on inverter technologies for industrial and grid connected applications. The injection of photovoltaic power into the utility grid has gained attention in renewable energy generation and distribution. The development of modern and innovative inverter configurations have improved parameters like efficiency, size, weight, reliability etc. which in turn influences the cost of producing inverters. In this paper, various inverter topologies are presented depending upon the number of power processing stages, the type of power decoupling between the PV module and grid, whether they utilizes a transformer (either line or high frequency) or not and the type of grid-connected power stage. Single-stage inverters provides a simple structure and low cost but suffers from limited range of input voltage variations whereas multiple stage inverters provides a wide range of input voltage variations but suffers from high cost, complex structure and low efficiency. Some transformer-less topologies based on hybrid and multilevel techniques and some soft-switching inverter topologies are also discussed which are desirable for high efficiency, low cost and compact structure. The use of advanced semiconductor devices and de-coupling capacitor are also indicated for further increase of efficiency and lowering the cost.
Developer strategies in smartphone application markets

This exploratory study uses interviews with 29 developer teams conducted during the development process of a focal mobile application to identify four strategies forming the basis of their app’s intended competitive advantage. I then use objective data from secondary sources to examine which combinations of these strategies, along with the resources and capabilities of the developer team, led to timely app release, high app ratings and high app downloads. Preliminary results suggest that the emphasis placed by many developer teams on complementary assets as a foundation for success is misplaced. While owned complementary assets are associated with timely release, accessed complementary assets are associated with major delays in release or even outright failure. Neither owned nor accessed complementary assets appear to be associated with high rating or high downloads.
Exchange Rates and Monetary Dynamics in Sierra Leone: Evidence from a Modified Money Demand Function

The study has examined the impact of foreign monetary developments on the demand for real broad money (M2) balances in Sierra Leone. The Autoregressive Distributed Lag (ARDL) modelling technique is employed to estimate the long run relationship and short run dynamics using quarterly data for the period 1983Q1 to 2008Q4. The results suggest that there exists a cointegrating relationship between real M2 and its determinants. In the long run, the coefficient of the exchange rate exerts a negative and statistically significant effect on the demand for real M2, providing evidence of the currency substitution phenomenon. The short run dynamics also indicate the presence of currency substitution but the coefficient of the exchange rate is not significant, which is attributed to the mix of both currency substitution and wealth effects. The results also find statistically significant negative coefficient of the foreign interest rate, being consistent with the argument of the capital mobility effect. The CUSUM and CUSUMSQ stability tests indicate that the model is relatively stable over the study period. Based on the stability results, we conclude that M2 is an appropriate intermediate target in the conduct of the monetary targeting policy framework in Sierra Leone. JEL Classification Codes: E41, E52, F31
CEED Seminar Proceedings 2016 Musulin: CFD Modelling of Inline MEG Contacting

The development of offshore gas fields by long distance subsea tie-back together with subsea processing presents a wide range of opportunities. The dehydration of the natural gas stream is a critical stage in mitigating the risk of hydrate formation and pipeline corrosion. One method to achieve successful subsea dehydration at lower temperatures involves contacting the natural gas with monoethylene glycol (MEG) within an inline contactor. The atomisation of the liquid MEG jet within the inline contactor increases interfacial area, leading to enhanced mass transfer of water vapour. The objectives of this project include characterising the atomisation of a liquid MEG jet within an inline contactor using Computational Fluid Dynamics (CFD) and modelling the contacting performance of the subsequent flow field using a 1D thermodynamic flow model. CFD models replicating liquid jet spray experiments were constructed to validate the CFD approach. The CFD validation found the k-ε turbulence closure model to be more accurate than the k-ω and SST k-ω models. CFD models predicting MEG jet atomisation have highlighted the importance of the momentum flux ratio in addition to the Reynolds and Weber numbers. Quantification of water vapour transfer was achieved by creating a three-fluid, 1D flow model. The results of the 1D flow model reveal the initial droplet size distribution and gas phase velocity are the primary factors governing contactor length.
Canny Edge Detector based on VHDL

— The process of Edge detection refers to the process of location as well as the identification of sharp discontinuities in an image. The abrupt changes in the intensity of pixel are the discontinuities which characterizes boundaries of objects in a scene. Convolution of an image is done in case of certain conventional edge detection techniques. Canny edge detection has remained a standard technique in the field of edge detection. Based on the statistics of an image, the Canny edge detector algorithm performs hysteresis Thresholding which requires computing high and low thresholds. Due to this, this technique becomes more complex. In the proposed work efforts will be made to reduce complexity and latency. The proposed algorithm Performed better compare to the conventional algorithm for edge detection. The canny edge detection algorithm based on VHDL is proposed.
Isolation, identification, and antimicrobial susceptibility of Clostridium perfringens isolates from acute necrotic enteritis of broiler chickens

The aim of this study was to isolate, identify and determine the antimicrobial susceptibility of Clostridium perfringens (CP) isolates from acute necrotic enteritis of broiler chickens. All broiler carcasses diagnosed as necrotic enteritis (NE) were sampled, subjected to microbial tests and 40 isolates were identified according to standard procedures. The antimicrobial susceptibility of CP isolates to 20 antibacterial agents was then determined. The results show widespread resistance among CP isolates. The most frequent resistance was observed to neomycin sulfate (87.5%), and then to lincomycin and tetracycline (both 80%). No isolate was resistant to chloramphenicol and the least frequency of resistance was observed to vancomycin (10%), sulfamethoxazole+trimethoprim (17.5%), and penicillin (20%). All isolates were multiple drug resistant types. There were 39 resistant patterns among the CP isolates, 95% of which were distributed in 38 resistant patterns. These multiple and variable resistance patterns observed among the CP isolates, even among different isolates from one farm, demonstrate a challenge for veterinarians in the field to choose the correct compound to combat the occurrence of NE.