Miracle-dz/UniFAR-FTUs huggingface dataset:
The design and implementation of an instrument for converting angular velocity to linear velocity based on arduino atmega 2560

The experiment tool of converting angular velocity into linear velocity has been built to support the physics education in the Physics Department of Tadulako University. In this project, the experimental tool has been designed, manufactured, and tested to convert the angular velocity value to linear velocity based on Arduino ATMega 2560. The stages of this research begin with the design and manufacture: mechanical system, optical sensor circuit, stepper motor circuit, the circuit of LCD and keypad controlled by Arduino ATMega 2560. The next step is the building controlling program as the brain of this instrument. This experimental tool has been tested and working properly. It operates for a rotation speed range of 1 rpm - 112 rpm. The value of converted linear velocity both theoretically and measured value is relatively the same.
Consumer Behavior Choice in the Era of Shared Mobility: The Role of Proximity, Competition, and Quality

Shared mobility services, which allow users to make point-to-point trips on an as-needed basis, have drastically impacted people’s travel behavior in the last few years. In this study, we propose a decision choice model to examine the factors that influence the restaurant choice of individuals who use shared mobility services. Our model incorporates key elements from the spatial interaction model and the theory of the individual decision making from economics. We analyze individuals’ travel behavior using trip-level data, along with point of interest data, restaurant reviews and average prices, and travel route characteristics. We find that the effect of proximity of a restaurant depends on the total distance of the trip. For shorter trips, an individual is less likely to choose a restaurant that is further away. However, if an individual decides to travel a long distance to a restaurant, she is more likely to choose a restaurant that is further. Additionally, with increasing travel distance (or competition) there is a decreased preference for a restaurant with a higher price. The quality (online reviews) of a restaurant does not seem to have a significant impact on the choice of the restaurant. Implications of the study are discussed.
Intention Games: Towards Strategic Coexistence between Partially Honest and Blind Players.

Strategic interactions between competitive entities are generally considered from the perspective of complete revelation of benefits achieved from those interactions, in the form of public payoff functions and/or beliefs, in the announced games. However, there exist strategic interplays between competitors where the players have a choice to strategise under the availability of private payoffs, in similar competitive settings. In this contribution, we propose a formal framework for a competitive ecosystem where each player is permitted to defect from publicly optimal strategies under certain private payoffs greater than announced payoffs, given that these defections have certain acceptable bounds in the long run as agreed by all players. We call this game theoretic construction an Intention Game. We formally define an Intention Game, and notions of participational equilibria that exist in such interactions that permit public defections. We compare Intention Games with conventional strategic form games, and demonstrate a type-theoretic construction of Intention Games. In a partially honest setting, we give Intention Game instances of a Cournot competition, secure interactions between mobile applications, an Internet services' data sourcing competition between Internet service providers through content delivery networks, and a Bitcoin mining competition. We give a use of Intention Games to determine player participation in a cryptographic protocol. Finally, we demonstrate the possibility of a dual model of the Intention Games framework.
Reflection phenomena of waves in a semiconductor nanostructure elasticity medium

ABSTRACT This paper presents a coupled nonlocal elasticity theory and a three-phase lag model to study the reflection of thermo-elastic wave in a semiconducting nanostructure medium. The nonlocal elasticity theory and three-phase lag thermal conduction model are used to formulate the governing equations. A heat equation with a fractional order is incorporated to study thermal effects on the propagation of the wave. Governing equations are decomposed into longitudinal and transverse components using the decomposition method. It is observed that four waves are propagating in the medium, in which three are longitudinal waves and one is a transverse wave. The reflection coefficients of the reflected waves are obtained analytically and are presented graphically for a particular material. The effects of the nonlocal parameters , and the fractional time derivative ‘ ’ are discussed on the basis of the numerical results. Some earlier published results can be obtained without nonlocal parameters .
Operation of Distribution Network Considering Compressed Air Energy Storage Unit and Its Reactive Power Support Capability

Energy storage is playing an increasingly important role in power system operation due to its ability to shave the peak and fill the valley. Advanced adiabatic compressed-air energy storage (AA-CAES) is a clean and scalable energy storage technology and has attracted wide attention recently. This paper proposes a multi-state operation model of AA-CAES capturing the dynamic change of internal physical status. A stand-by state is introduced, at which AA-CAES works like a condenser that produces only reactive power. It brings two benefits. First, the facility is started up and shut down less frequently, which helps extend its service time. Second, it can provide continuous reactive power support all day long, unlike on-load tap changers or shunt capacitors whose voltage regulation strategy is discrete and suffers from a very low switching frequency. Taking AA-CAES into account, the optimal operation of a distribution network is formulated as a bi-objective dynamic optimal power flow problem. Nash bargaining is employed to extract a single Pareto optimal solution that fairly compromises two objectives. To solve the operation problem in a tractable manner, the bargaining objective and power flow constraints are convexified, giving rise to a mixed-integer second-order cone program. A feasibility recovery algorithm is developed to find a physically meaningful solution whenever the convex relaxation on power flow is inexact. Case studies on the IEEE 33-bus system demonstrate the effectiveness and advantages of the proposed method.
Distributed ID/Locator Resolution System for Inter Mesh Networks

We propose an ID/Locator resolution system for super wide area wireless mesh networks constructed using Delaunay overlay networks. Unlike conventional mobile ad-hoc network protocols, the proposed system does not use flooding to spread the locator notification messages of each node. The proposed method sends one-hop locator notifications on skip links such as skip graphs. The proposed system realized scalability by controlling the route, frequency, and storing locations of the locator notification message. Specifically, when the number of nodes increases, the average load on communication links and the message database of each node are approximately O(log n), where n is the total number of nodes. The scalability of the proposed method is confirmed through simulations.
Mechanical Impedance Control of Cooperative Robot During Object Manipulation Based on External Force Estimation Using Recurrent Neural Network

This paper proposes a compliant motion control for human-cooperative robots to absorb collision force when persons accidentally touch the robots even while the robot is manipulating an object. In the proposed method, an external force estimator, which can distinguish the net external force from the object manipulation force, is realized using an inverse dynamics model acquired by a recurrent neural network (RNN). By implementing a mechanical impedance control to the estimated external force, the robot can quickly and precisely carry the object keeping the mechanical impedance control functioned and can generate a compliant motion to the net external force only when the person touches it during manipulation. Since the proposed method estimates the external force from the generalized force based on the learned inverse dynamics, it is not necessary to install any sensors on the manipulated object to measure the external force. This allows the robot to detect the collision even when the person touches anywhere on the manipulated object. The RNN inverse dynamics model is evaluated by the leave-one-out cross-validation and it was found that it works well for unknown trajectories excluded from the learning process. Although the details were omitted due to the limitation of the page length, similar to the simulations, the RNN inverse dynamics model was evaluated using unknown trajectories in the six degree-of-freedom experiments, and it has been verified that it functions properly even for the unknown trajectories. Finally, the validity of the proposed method has been confirmed by experiments in which a person touches a robot while it is manipulating an object with six degrees of freedom.
SPI-GCN: A Simple Permutation-Invariant Graph Convolutional Network

A wide range of machine learning problems involve handling graph-structured data. Existing machine learning approaches for graphs, however, often imply computing expensive graph similarity measures, preprocessing input graphs, or explicitly ordering graph nodes. In this work, we present a novel and simple convolutional neural network architecture for supervised learning on graphs that is provably invariant to node permutation. The proposed architecture operates directly on arbitrary graphs and performs no node sorting. It also uses a simple multi-layer perceptron for prediction as opposed to conventional convolution layers commonly used in other deep learning approaches for graphs. Despite its simplicity, our architecture is competitive with state-of-the-art graph kernels and existing graph neural networks on benchmark graph classification data sets. Our approach clearly outperforms other deep learning algorithms for graphs on multiple multiclass classification tasks. We also evaluate our approach on a real-world original application in materials science, on which we achieve extremely reasonable results.
Caracterização morfométrica de folíolos de Moringa oleifera por método destrutivo

RESUMO: O objetivo deste estudo foi caracterizar morfométricamente folíolos de mudas de M. oleifera por método destrutivo. A pesquisa foi realizada no Centro de Ciências Agrárias e Ambientais da Universidade Estadual da Paraíba. Foram coletados 200 folíolos de M. oleifera, nos quais foram realizadas medidas para determinação do comprimento (C) e da largura (L) e, posteriormente, a área foliar foi determinada utilizando-se do softwareImageJ ®. Verificou-se que folíolos de M. oleifera possuem comprimento médio de 1,595±0,474 cm, com valores variando de 0,695 cm a 2,831 cm, largura média dos folíolos de 1,142±0,329 cm, variando de 0,443 a 1,950 cm e área média de 1,445±0,800 cm 2 , com valores variando entre 0,253 cm 2 e 3,602 cm 2. Trabalhos complementares são sugeridos para criação de modelos lineares para determinação da área dos folíolos por métodos não destrutivos.
The roles of 'old' and 'new' media tools and technologies in the facilitation of violent extremism and terrorism

This chapter describes and discusses the roles of media tools and technologies in the facilitation of violent extremism and terrorism. Rather than focusing on how media report on terrorism, we investigate how extremist and terrorist groups and movements themselves have exploited various “traditional” and “new” media tools, from print to digital, outlining the significance that they have had on extremists’ ability to mark territory, intimidate some audiences, connect with other (sympathetic) audiences, radicalize, and even recruit. Underlined is that violent extremists and terrorists of all stripes have, over time, used every means at their disposal to forward their communicative goals. Also worth noting is that ‘old’ media tools are not extinct and while ‘new’ media play a prominent role in contemporary violent extremism and terrorism, ‘old’ tools—everything from murals to magazines—continue to be utilized in tandem with the former.
Preparation and Evaluation of Chocolate Drug Delivery System of Albendazole

Albendazole (ABZ) is a benzimidazole carbamate with a broad spectrum anti-parasitic effect. ABZ was first approved for treatment of helminthic infections in sheep in 1977, and subsequently approved for human use in 1983. In general, most ascariasis, trichuriasis, enterobiasis and hookworm infections can be successfully treated with single dose Albendazole. Albendazole is one of the bitter drug due to which oral administration of Albendazole leads to patient incompliance especially in children. To overcome this limitation it is advisable to formulate dosage form which is most acceptable for pediatric patients. Chocolate is one of the most palatable and favorite in children, so we have developed chocolate drug delivery system. Albendazole chocolate was prepared using cocoa butter, cocoa powder, icing sugar and milk powder using melting method. Dissolution of prepared chocolate was carried out in 0.1 N HCl and saline phosphate buffer. The prepared chocolate was having sweet taste and showed more than 90% drug release in 30 min. The result showed that prepared chocolate is having good dissolution and sweet taste with better patient compliance.
Learning to Seek: Autonomous Source Seeking on a Nano Drone Microcontroller with Deep Reinforcement Learning

Nano drones are uniquely equipped for fully autonomous applications due to their agility, low cost, and small size. However, their constrained form factor limits flight time, sensor payload, and compute capability, which poses a significant limitation on the use of source-seeking nano drones in GPS-denied and highly cluttered environments. The primary goal of our work is to demonstrate the effectiveness of deep reinforcement learning in fully autonomous navigation on highly constrained, general-purpose hardware and present a methodology for future applications. To this end, we present a deep reinforcement learning-based light seeking policy that executes, in conjunction with the flight control stack, on a commercially available off-the-shelf ultra-low-power microcontroller (MCU). We describe our methodology for training and executing deep reinforcement learning policies for deployment on constrained, general-purpose MCUs. By carefully designing the network input, we feed features relevant to the agent in finding the source, while reducing computational cost and enabling inference up to 100 Hz. We verify our approach with simulation and in-field testing on a Bitcraze CrazyFlie, achieving 94% success rate in a highly cluttered and randomized test environment. The policy demonstrates efficient light seeking by reaching the goal in simulation in 65 % fewer steps and with 60% shorter paths, compared to a baseline `roomba' algorithm.
Biomathematical model for gyrotactic free-forced bioconvection with oxygen diffusion in near-wall transport within a porous medium fuel cell

Bioconvection has shown significant promise for environmentally friendly, sustainable “green” fuel cell technologies. The improved design of such systems requires continuous refinements in biomathematical modeling in conjunction with laboratory and field testing. Motivated by exploring deeper the near-wall transport phenomena involved in bio-inspired fuel cells, in the present paper, we examine analytically and numerically the combined free-forced convective steady boundary layer flow from a solid vertical flat plate embedded in a Darcian porous medium containing gyrotactic microorganisms. Gyrotaxis is one of the many taxes exhibited in biological microscale transport, and other examples include magneto-taxis, photo-taxis, chemotaxis and geo-taxis (reflecting the response of microorganisms to magnetic field, light, chemical concentration or gravity, respectively). The bioconvection fuel cell also contains diffusing oxygen species which mimics the cathodic behavior in a proton exchange membrane (PEM) system. The vertical wall is maintained at iso-solutal (constant oxygen volume fraction and motile microorganism density) and iso-thermal conditions. Wall values of these quantities are sustained at higher values than the ambient temperature and concentration of oxygen and biological microorganism species. Similarity transformations are applied to render the governing partial differential equations for mass, momentum, energy, oxygen species and microorganism species density into a system of ordinary differential equations. The emerging eight order nonlinear coupled, ordinary differential boundary value problem features several important dimensionless control parameters, namely Lewis number (Le), buoyancy ratio parameter i.e. ratio of oxygen species buoyancy force to thermal buoyancy force (Nr), bioconvection Rayleigh number (Rb), bioconvection Lewis number (Lb), bioconvection Péclet number (Pe) and the mixed convection parameter ([Formula: see text] spanning the entire range of free and forced convection. The transformed nonlinear system of equations with boundary conditions is solved numerically by a finite difference method with central differencing, tridiagonal matrix manipulation and an iterative procedure. Computations are validated with the symbolic Maple 14.0 software. The influence of buoyancy and bioconvection parameters on the dimensionless temperature, velocity, oxygen concentration and motile microorganism density distribution, Nusselt, Sherwood and gradient of motile microorganism density are studied. The work clearly shows the benefit of utilizing biological organisms in fuel cell design and presents a logical biomathematical modeling framework for simulating such systems. In particular, the deployment of gyrotactic microorganisms is shown to stimulate improved transport characteristics in heat and momentum at the fuel cell wall.
Title : Cellulose fibrillation and interaction with psyllium seed husk heteroxylan

Fibrillated cellulose (FC) and its mixture with psyllium seed husk powder (PSY) were investigated to broaden the applications of these two materials by a novel combination. Purified cellulose was processed by a colloid mill and relatively stable suspensions were obtained. An FC suspension shows localised concentrations appearing as flocculates, which can be promoted by heating or centrifugation. The structures of unheated mixtures of FC and PSY appear to be binary phase dispersions while, after heat treatment, FC fibres were incorporated into PSY gels and form composites. Fibrillation on the FC surface does not influence the structure and rheological property of the composite mixtures while fibre disintegration contributes to a denser structure and higher moduli. Fluorescent images show the attachment of PSY heteroxylan aggregates on cellulose and fibrillated cellulose fibres. The interaction is weak and time-dependent because G’ during cooling was higher than that during heating, and declined back to the same value as the start of heating during an isothermal test at 20 ºC. PSY was fractionated according to temperature and only F60 (fraction at 60 ºC) clearly associates with the unfibrillated cellulose fibres, possibly via long arabinan sidechains (similar to hairy pectin) or/and backbone (via interaction with helical domains or/and conformational compatibility). The interaction was promoted by fibrillation, potentially trapping PSY heteroxylan aggregates within the cellulose dispersion. With further fibrillation, smaller FC fibres were generated and form interpenetrating particles with whole PSY or PSY fractions. Highly fibrillated cellulose has a higher surface area and smaller fibrils, which significantly increased the interaction resulting in a clumped structure.
The role of positive emotions in child development: A developmental treatment of the broaden and build theory

ABSTRACT Historically, research on emotions in childhood has been dominated by studies on negative emotions. Consequently, little research has been conducted on the role of positive emotions. Recently, an alternative model of emotion proposed that positive emotions broaden thought-action patterns and build social, intellectual, and physical resources. In this paper, we review studies that examined the emotion of joy in child development and use the Broaden and Build Theory of Positive Emotions as a guide. It is well known that basic emotions are present at birth or emerge within the first two years of life. Thus, a new model of positive emotions would benefit from an understanding of their role in early life and how their broadening and building functions begin. It is our contention that results from past, and future, research on positive emotions will illustrate an important developmental foundation for a lifespan of social, intellectual and physical advantages.
Cyber-physical system for control the heat and mass transfer in the oil reservoir and producing pumping well

A special cyber-physical system is developed to control transient heat and mass transfer during the commissioning of the unified oil production complex consisted of oil reservoir, producing well equipped with electric submersible centrifugal pump, well production tree and ground-based control station. Two main elements of cyber-physical system are following: – computer simulator of heat and mass transfer in virtual oil production complex based on mathematical and numerical models of such processes along with simultaneous visualization of computational results; – portable imitation hardware of real ground-based equipment which is realized as 3D-printed plastic model consisted of control elements (pipeline valves, drossel chamber, ground-based control station) and recording devices (manometers, level indicator, liquid sampler and control station itself). Mechanisms of these elements are replaced by Arduino microchips to simulate the operation of real devices. An important feature of the cyber-physical system is the data exchange and interaction between oil production computer simulator and microcontroller software. Data transfer is going through the COM-ports of computer and microcontroller. The simulator sends calculated working characteristics of oil production complex to the memory of microcontroller, which not only analyzes incoming data but also displays it on the recording devices and forms necessary control parameters, which are sent back to simulator and affect the further behavior of the whole complex. Different elements of the CPS provides the possibility to control and visualize the commissioning of the oil production complex under consideration and the whole system is oriented to simulate the real technological actions performing by specialists in oil production.