Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Prediction of Academic School of Students for Real-Time

This study presented the five predictive models to predict the student’s study school based on their demographics, personal, social, and grade features. Using the Orange stable version 3.23. 0 machine learning tool, the authors performed numerous experiments to identify the study place (school) of students. The dataset stored the records and attributes of two senior secondary schools in Portugal. A binary classification problem has solved using the five machine learning algorithms. Also, the training time and testing time of each classifier have been compared. After the preprocessing, 875 instances and 31 attributes were practically analyzed in the Orange workflow environment. This experiential study’s findings presented five predicted models and proved that Artificial Neural Network outperformed others with providing the most accuracy of 84.7%. The second winner classifier Random Forest attained an accuracy of 83.7% with 10-folds. Increasing holdout ratios and folds significantly improved the prediction accuracies of each classifier. Also, full cross-validation (leave one out) is recommended for this dataset compared to others. Based on the testing time of 8.2 seconds, the Random Forest classifier has been suggested, and the Neural Network is recommended owing to the highest prediction accuracy. The school predictive models supported identifying the school to be aware of student situations in their academic, personal, and social life.
Seeking an Empathy-abled Conversational Agent

A fairly novel area of research, at the conjunction between Artificial Intelligence (AI) and Human-Computer Interaction (HCI), resides in developing conversational agents as more users prefer this type of interaction to conventional interfaces. In this paper, we present an open-domain empathic chatbot, encompassing two of the biggest challenges of dialog systems: understanding emotions and offering appropriate responses. Although these tasks are trivial for a human, it is difficult to create a system that can recognize others’ feelings in a discussion. The proposed model is developed based on the Generative Pre-Trained Transformer and it uses two datasets, PersonaChat and Empathetic Dialogues to achieve an empathic chatbot with a cordial personality. The measured performance - 18.20 perplexity, 6.56 BLEU score, and 6.56 accuracy - comes close to the state-of-the-art models, while offering a further refined dialogue persona.
Synthesis and characterization of tetrapyridophenazine ligand and its novel 1-D metal-organic wave-like coordination polymer of Ni(II) ion

Abstract A protonated tpphz ligand, H2tpphz · 2 H2O · 2 Cl, 1, and novel 1-D coordination polymer of the type [Ni2(μ2-tpphz)(μ2-tp)(H2O)6]n · (tp) · 3.65(H2O), 2 (where tpphz = tetrapyrido[3,2-a:2′,3′-c:3′′,2′′-h:2′′′,3′′′-j]phenazine, and H2tp = terephthalic acid) have been synthesized and characterized by single crystal X-ray diffraction analysis. The asymmetric units in both structures consist of half of their formula. In the crystal structure 1, different types of hydrogen bonds together with π—π stacking are dominant. In the structure of 2, Ni(II) ion is coordinated by two N atoms from tpphz, one oxygen atoms from terephthalic acid and three water oxygen atoms in a distorted meridional octahedral geometry. Each tp ligand bridges two Ni(II) centers through monodentate carboxylate group. In the overall structure of 2, the Ni(II) centers are connected by tp and tpphz ligands to create a 1-D wave-like chain with a period of 20.91 Å running parallel down [1, 2].
Agri-food exports and agricultural output in selected EU member states

: This sectoral study of the largest food exporters in the EU focuses on the impact of foreign trade in products made from agricultural commodities on the prospects of agricultural output development. In particular, the study analyses the interdependencies between the output and exports of selected goods. The methodology of vector autoregression was applied to describe the analysed relationships. The results of analyses support the hypothesis about the stimulating role of exports for output and, in the case of certain countries, identify the opposite direction of the causal relationship. The impact of exports on agricultural output is of a short-term nature. Exports appear to be more exogenous than output. The degree of exogeneity of agri-food exports is lowest in the Netherlands.
Tea waste and food waste as a potential feedstock for biogas production

Recent strategies on fuel‐development to reduce oil dependency to mitigate greenhouse gas emissions and to utilize domestic resources have generated interest in the search for alternative sources of fuel supplies. In this context, the industrial waste may be regarded as potential alternatives for biogas production. This study entails a detailed characterization of tea waste and food waste to evaluate their potential as an alternate feedstock to cattle dung for biogas production. The samples were characterized for volatile matter, moisture content, ash content and carbon hydrogen nitrogen (CHN). Property analysis of the biomass was also done by scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). The volatile matter content in tea and food waste was found to be 64.17% and 36.05% respectively, which is quite encouraging. The carbon‐to‐nitrogen (C:N) ratio, chemical oxygen demand and total solids of the sample also attributed its suitability for biogas production. The thermal behavior and heating values interpreted higher lignin content in tea waste. The lab scale study was conducted with combination of food waste/cattle dung and tea waste/cattle dung that showed higher biogas production in comparison to cattle dung alone implying their potential as biogas feedstock. © 2016 American Institute of Chemical Engineers Environ Prog, 35: 1247–1253, 2016
Production of cellulose nanofibrils and films from elephant grass using deep eutectic solvents and a solid acid catalyst

A new strategy was developed to produce cellulose nanofibrils (CNFs) and films from raw elephant grass using deep eutectic solvents and a recyclable spent coffee-derived solid acid (SC-SO3H) catalyst with assistance of ultrasonic disintegration and a suction filtration film forming method. The effects of a solid acid and reused solid acid were comprehensively studied by comparing with catalyst-free conditions and using sulfuric acid as the catalyst. The CNF fibers obtained from this novel SC-SO3H catalyst method showed the longest fiber length. The corresponding films achieved the strongest tensile strength of 79.8 MPa and the elongation at break of 13.6%, and best thermostability. In addition, the performance of CNFs and films prepared by the fourth recovered SC-SO3H-4 catalyst was close to that obtained with the first use. The SC-SO3H could be reused by a simple decantation method, meaning this novel method has the potential for green and sustainable preparation of CNFs and films.
Evaluating the Effectiveness of Community Detection Algorithms for Influence Maximization in Social Networks

Influence maximization, a classic optimization problem in social networks, targets to find a set of influential users capable of producing maximum influence spread under a particular diffusion model. Community structure, an important topological property of social networks, also plays a significant role in various dynamical processes, including the spreading of information in networks. Realizing the impact of community structure in information spreading, some community-based influence maximization methods have been proposed recently, and these studies show that community-based influence maximization methods perform better than the traditional influence maximization. However, the impact of the method used to detect communities on influence spread in the influence maximization problem is unknown, the need to verify and find the most effective community detection method suitable for influence maximization is essential. This paper addresses this problem by computing the influence spread of k influential nodes selected by an influential node selection method from the k largest communities extracted by the various community detection algorithms on a network. Experiments have been conducted to evaluate the performance of community detection algorithms and their impact on influence maximization on both artificial and real-world networks by employing four heuristic influence maximization methods under IC diffusion model.
Assertion & Functional Coverage Driven Verification of AMBA Advance Peripheral Bus Protocol Using System Verilog

Design and Verification of the AMBA based Advanced Peripheral bus is presented in this paper. Verification environment is constructed using the System Verilog, it has features like Functional coverage, Assertion coverage, constrained Randomization and Code coverage. ; Functional coverage makes sure that Hardware Descriptive Language (HDL) Code written performs all the functionality described in the Design specification; Code coverage shows total RTL codes is covered by the test cases. Assertions are used as additional checkers for making sure there are no protocol violation in the designed protocol. APB 4.0 protocol is completely designed and verified, there is no data loss in the designed system, AMBA’s APB is used for low power low-cost interfacing of high speed and low speed Systems. This paper focuses on APB protocols verification and covers all the internal transactions of the APB protocol, complete cycle for designing of the verification environment is discussed in detail, the designed system can be successfully implemented in any Microcontroller system having very high and low speed peripherals. Designing is done by Verilog HDL using Mentor graphics tools Questa and Precision Pro is used for simulation of the Verification Environment respectively. 100 percentage Functional coverage with 1030 Bins & 97 percentage code coverage is achieved.
X-ray Photoelectron Spectroscopy: A Unique Tool To Determine the Internal Heterostructure of Nanoparticles

We review the existing literature on the application of X-ray photoelectron spectroscopy in the study of nanocrystals. The unique ability of this technique to provide quantitative and reliable descriptions of highly complex internal structures of a variety of nanocrystals has been discussed in detail. We show that an accurate description of the nanocrystal internal structure is crucial and a prerequisite to understand many different properties, particularly optical properties, of such nanocrystal systems. We also discuss limitations and future outlook of this technique.
Investing with Cryptocurrencies—a Liquidity Constrained Investment Approach*

Cryptocurrencies have left the dark side of the finance universe and become an object of study for asset and portfolio management. Since they have low liquidity compared to traditional assets, one needs to take into account liquidity issues when adding them to a portfolio. We propose a Liquidity Bounded Risk-return Optimization (LIBRO) approach, which is a combination of risk-return portfolio optimization under liquidity constraints. Cryptocurrencies are included in portfolios formed with stocks of the S&P 100, US Bonds, and commodities. We illustrate the importance of the liquidity constraints in an in-sample and out-of-sample study. LIBRO improves the weight optimization in the sense that it only adds cryptocurrencies in tradable amounts depending on the intended investment amount. The returns greatly increase compared to portfolios consisting only of traditional assets. We show that including cryptocurrencies in a portfolio can indeed improve its risk–return trade-off.
Nanoparticles and Shrimp: An Interdisciplinary Lab Series in Chemistry and Biology for Undergraduate Engineering Students

The parallels between engineering and science are vast, as both disciplines apply theory and inquiry to solve complex problems. In order to prepare students for interdisciplinary careers in STEM, we have developed a lab project in which engineering students in an Engineering Chemistry course pair with engineering students taking Cellular and Molecular Biology to investigate the biological relevance of superparamagnetic iron oxide nanoparticles (SPIONs). SPIONs are at the forefront of investigation across several different fields, which makes them an exceptional interdisciplinary educational tool. The collaboration takes place over the course of three (3), 2-hour lab periods, with additional checkpoints during the biology component. Two of these periods are designated for synthesis and characterization of SPIONs by the chemistry students, and one lab period is designated for induction of toxicity assays and cytotoxicity analysis by the biology students. Rather than a traditional written lab report, we have challenged our students to infuse their analysis with creativity by filming a video lab report. Scores are generated based on presentation style and creativity, scientific accuracy, ability to develop and explain their hypothesis, data analysis, and interpretation of findings on a larger scale. Citation: Grove LE, Rogers RP, Alibeik S. 2020. Nanoparticles and shrimp: An interdisciplinary lab series in chemistry and biology for undergraduate engineering students. CourseSource. https://doi.org/10.24918/cs.2020. 52 Editor: Valerie Haywood, Case Western Reserve University Received: 12/12/2019; Accepted: 8/5/2020; Published: 1/5/2021 Copyright: © 2020 Grove, Rogers, and Alibeik. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited. Conflict of Interest and Funding Statement: The authors acknowledge Wentworth Institute of Technology for supporting the development of this activity. None of the authors has a financial, personal, or professional conflict of interest related to this work. Supporting Materials: Supporting Files S1. Toxicity of SPIONs – Lab handout; S2. Toxicity of SPIONs – Maintenance of brine shrimp; S3. Toxicity of SPIONs – Rubric; and S4. Toxicity of SPIONs – Peer evaluation. *Correspondence to: 550 Huntington Avenue, Boston, MA 02115. Email: grovel@wit.edu CourseSource | www.coursesource. org 2020 | Volume 07 1 Lesson
Two-Phase Lattice Boltzmann Simulation of Behavior of a Body with a Viscoelastic Membrane in Fluid Flows (Effect of Internal Fluid Viscosity on Body Behavior)

The behavior of a deformable body with a viscoelasitc membrane in fluid flows is numerically investigated by the two-phase lattice Boltzmann method. In the calculations, the internal fluid of the body is distinguished from the surrounding fluid so that the viscosities of these fluids can be separately specified. Using this method, the deformation of the body under a shear flow is simulated by changing the viscosity ratio η, which is defined as the ratio of the viscosity of the internal fluid to that of the surrounding fluid. It is found that as the viscosity ratio increases, the deformability of the body remains almost constant for 0.1 ≤ η ≤ 1, whereas it decreases linearly for 1 < η ≤ 10. In addition, the behavior of the body in a square pipe flow is simulated for various viscosity ratios. The velocity near the centerline of the pipe decreases with increasing the viscosity ratio, and thus the flow rate becomes reduced. In the case of lower viscosity ratio (0.1 ≤ η ≤ 1), the body becomes a parachute-like shape and approaches toward the centerline of the pipe; that is, axial accumulation is observed. In the case of higher viscosity ratio (e.g., η = 6), the body forms into a slipper-like shape, migrating laterally toward a certain equilibrium position between the wall and the centerline of the pipe.
Wearable E-shaped Textile Antenna for Biomedical Telemetry

The advancements in the wearable textile antenna and their innovative designs have been focused in this paper. The proposed antenna has been designed and fabricated suitable for the applications in the Medical telemetry. Telemetry systems used for patient monitoring, elder people health monitoring, children safety and Fire fighters’ safety measures is a growing research field and where biocompatible antenna designing is required for pollution controlled environment. In this paper, design and development of novel E –shaped textile antenna on a denim material as substrate for the patient telemetry application is proposed and discussed. Biocompatibility, size factor and at the frequency range of 2.45GHz industrial, scientific and Medical (ISM) band.
Ceramics based on concrete wastes prepared by spark plasma sintering

An effective utilization technique is required to recycle fine aggregate in concrete waste because the presence of residual waste cement reduces the quality of the recycled concrete. In this study, recycled aggregate powder (RAP) was prepared by milling Okinawan concrete waste and developing a ceramic compact with high flexural strength using the spark plasma sintering (SPS) method. The RAP raw material consisted mainly of calcite and quartz. The densification gradient of the sintered compact was uniform during sintering at 1123-1273K. At 1273K sintering temperature, Vickers hardness (HV) obtained a maximum of 393 along with 78.9MPa maximum flexural strength, which exceeded the porcelain stoneware tile ISO 13006 standards. Scanning electron microscopy with energy dispersive X-ray (SEM-EDX) element analysis suggested that the inner structure constituted unmelted silica-rich sand particles and melted calcium-rich particles containing waste cement and fine aggregate with limestone. Therefore, it can be concluded that SPS progressed by the liquid-phase sintering phenomenon between sand particles and calcium-rich particles, which contributed to flexural strength and modulus improvement.
Enhancing 5G SDN/NFV Edge with P4 Data Plane Programmability

The 5G network revolution will be enabled by deep integration of Software Defined Networking (SDN) and Network Function Virtualization (NFV) to support multi-tenancy, per-user and per-application quality of service and experience. However, full softwarization and current SDN platforms may not be able to sustain the complexity and the heterogeneity of different requirements, for example, strict latency, jitter, high precision traffic and advanced monitoring. For such services, SDN/NFV needs to be boosted not only considering orchestration and control plane, but also data plane programmability. In this article, the potential of the P4 language is illustrated with the aim to show its disruptive novel functionalities at the data plane level currently not available in a SDN/NFV network, opening the way to new orchestration frameworks and enabling a novel autonomic and flexible network at the edge. Use cases, assessments and softwarized performance results are proposed and discussed in the edge and IoT scenario, targeting advanced traffic engineering, cyber security, multi-tenancy, 5G offloading, and telemetry, to demonstrate the feasibility of such an approach.
Structural and Spectroscopic Properties of Linear Carbon Chains NC_(2n)N and HC_(2n+1)N(n= 1～10)

Using density functional theory, geometries and vibrational frequencies of linear chains NC2nN and HC2n+1N (n = 1～10) have been investigated. Time-dependent density functional theory (TD-DFT) has been used to calculate the vertical transition energies and oscillator strengths for the X 1 Σ +g →11 Σu+ transition in NC2nN (n = 1～10) and X 1Σ + →11Σ+ transition in HC2n+1N (n = 1～7). On the basis of present calculations, the explicit expressions for the size dependence of the excitation energy and the first adiabatic ionization energy in both carbon chains have been suggested.
A nonlocal Weickert type PDE applied to multi-frame super-resolution

In this paper, we propose a nonlocal Weickert type PDE for the multiframe super-resolution task. The proposed PDE can not only preserve singularities and edges while smoothing, but also can keep safe the texture much better. This PDE is based on the nonlocal setting of the anisotropic diffusion behavior by constructing a nonlocal term of Weickert type, which is known by its coherence enhancing diffusion tensor properties. A mathematical study concerning the well-posedness of the nonlocal PDE is also investigated with an appropriate choice of the functional space. This PDE has demonstrated its efficiency by combining the diffusion process of Perona-Malik in the flat regions and the anisotropic diffusion of the Weickert model near strong edges, as well as the ability of the non-local term to preserve the texture. The elaborated experimental results give a great insight into the effectiveness of the proposed nonlocal PDE compared to some PDEs, visually and quantitatively.
Relationship Analysis of Capital Structure and Profitability Ratio in Trade Sector Companies in Indonesia

A composition or a structure of liabilities is the definition of the capital structure of a company. The purpose of the study is to analyze the structure of capital and the performance of finance during the years 2015 to 2018 (4 years) in the enterprise sector is national Trade in Indonesia. The research sample was processed from the annual report data Trade sector companies in Indonesia that are listed on the Indonesia Stock Exchange, this is in accordance with the objectives of this study. The method of analysis in this study uses panel data regression. The relationship between capital structure and profitability ratios will be revealed from this study. Variables independently that structure capital will be in proxy with a debt to equity ratio (DER), debt to asset ratio (DAR), and long-term debt ratio (LTDR). And for variable dependent is the performance of finance will be in proxy with Gross Profit Margin (GPM), Net Profit Margin (NPM), and Return on Capital Employed (ROCE). Research on the company's sector of Commerce in Indonesia resulted in a relationship that significant between variables independent manner together against variable dependent.
Credit Cycles, Fiscal Policy, and Global Imbalances

We study the role that changes in credit and fiscal positions play in explaining current account fluctuations. Empirically, the current account declines when credit increases, and when the fiscal balance declines. We use a two-country model with financial frictions and fiscal policy to study these facts. We estimate the model using annual data for the U.S. and “a rest of the world” aggregate that includes main advanced economies. We find that about 30 percent of U.S. current account balance fluctuations are due to domestic credit shocks, while fiscal shocks explain about 14 percent. We evaluate simple macroprudential policy rules and show that they help reduce global imbalances. By taming the financial cycle, macroprudential rules that react to domestic credit conditions or to domestic house prices would have led to a smaller and less volatile U.S. current account deficit. We also show that a countercylical fiscal policy rule that stabilizes output growth reduces the level and volatility of the U.S. current account deficit.