Miracle-dz/UniFAR-FTUs huggingface dataset:
Treatment of Iraqi Municipal Wastewater by up-flow Anaerobic Sludge Blanket Reactor UASB

In this work, the Upflow Anaerobic Sludge Blanket “UASB” reactor treated effluent wastewater to investigate the process performance on a pilot plant scale. Municipal wastewater at high and medium strength with different organic load rate OLR (0.6-9) kg COD m-3day-1 with the flow of 20 l/h, up-flow velocity 0.4 m/h, hydraulic retention time HRT 9 h at a temperature of (20-30 oC) was evaluated. The wastewater concentration, including TSS, COD was measured, and the removal efficiencies of chemical oxygen demand (COD) and total suspended solid TSS were calculated and summarized as 45-85% and 70-75%, respectively, depending on organic load rate OLR. Effluent volatile fatty acids VFA was measured, and the results were in the range between 12-90 mg/L depending on OLR with a slight change in pH (8.3-8.4), which means the conversion of COD to methane and increase ammonia concentration.
Low-cost adsorbents for environmental pollution control: a concise systematic review from the prospective of principles, mechanism and their applications

Abstract Nowadays, water scarcity is an identifiable problem facing society. However, as a result of modernization, water consumption is dramatically in increase although the water supply remains constant. Unfortunately every sector consumes water resulting in massive amounts of wastewater that requires treatment prior to their final disposal that still a challenge to the modern societies. Among the various technologies investigated, adsorption considered the most widely applied technology for safe environmental remediation. In this regard, the term of green adsorbents is introduced that is meant the low-cost materials originated from waste, i.e., agriculture waste to be valuable adsorbents. Thus, extensive list of different adsorbents from natural, industrial waste, agriculture bio-products or modified materials have been applied for the elimination of various contaminants from aqueous matrix are compiled here as a demanding area since it has double benefits as an industrial ecology approach. Also, this article discusses the basic principles of adsorption process including the adsorption isotherm and kinetic models. Although numerous review articles are dealing with low-cost adsorption performances, there is insufficient information on the emerging pollutants elimination. The major focus of this work is highlighting the research on the application of the low-cost adsorbents on the emerging pollutants, namely, pharmaceuticals, pesticides, personal care products and perfluorinated compounds. Scattered information on using various adsorbents are provided information in adsorbing emerging pollutants uptake reached to 920 mg/g. The main parameters that affect the adsorption process and the economic prospective is also discussed. Desorption and recycling scenario is concluded and desorption efficiency could reach to 99%. Finally, the future development of further research and few suggestions are also prospected. Graphical Abstract
A Novel Synthesis and Subsequent Decyclization of Iminothiozolidinones: Expansion of Thiourea Chemistry for Biological Applications

A NOVEL SYNTHESIS AND SUBSEQUENT DECYCLIZATION OF IMINOTHIOZOLIDINONES: EXPANSION OF THIOUREA CHEMISTRY FOR BIOLOGICAL APPLICATIONS By Constance D. Franklin, Ph.D. A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Chemistry at Virginia Commonwealth University Virginia Commonwealth University, 2017 Major Director: Dr. Vladimir A. Sidorov ASSOCIATE PROFESSOR, DEPARTMENT OF CHEMISTRY Small molecule synthesis has become a valuable tool in the study of biological systems. Biologically active compounds can be designed based on well-characterized endogenous systems or they can be found through the screening of large libraries of small molecules. This work involves the development of a small library of cyclic thiourea-based small molecules by use of an unreported synthetic pathway. Briefly, parent thioureas were cyclized by reaction with bromoacetyl bromide, and one or two isomeric heterocycles were found to form. Further studies indicated that the reaction could be easily manipulated by temperature or solvent to effectively control the product distribution. These iminothiozolidinones were characterized by single crystal
The ontology driven SLAM based indoor localization technique

The proposed technique facilitates time-consuming procedure for setting up Wi-Fi or Bluetooth access points, indoor map building and signal propagation model calibration. The technique based on OWL ontology and the SLAM method includes the phase of forming a training sample, as well as the phase of simultaneous navigation and mapping. The SLAM method implements The Gaussian Process Latent Variable Model (GP-LVM). The proposed method is based on solving the regression problem using machine learning methods to form a training sample, as well as solving the problem of reducing the dimension for simultaneous navigation and map building. As a training sample, the smartphone‘s internal sensor readings (steps and rotation angles) and Wi-Fi received signal strength values obtained using crowd calculations are used. The resulting training sample is used to determine the parameters of the correlation function that sets the correlation between the user‘s localization points. The proposed ontology is intended to determine different events occurring during user’s movement and involve the appropriate phase of the proposed technique.
Air pollution, human health and the benefits of trees: a biomolecular and physiologic perspective

ABSTRACT It is well accepted that particulate matter (PM) can affect human health detrimentally. Chronic and prolonged exposures to particulate matter with an aerodynamic diameter ranging between 2.5 and 10 microns (PM10), 0.1 and 2.5 microns (PM2.5) and less than 0.1 microns in size (UFPM), have been associated with cardiopulmonary diseases. PM is ubiquitously present in urban settings, while primarily absent in forest environments primarily due to the direct interception of airborne pollution particles by trees. Both short- and long-term exposure to trees in forested environments is associated with lower blood pressure and inflammation, as well as enhanced immune function. Additionally, exposure to volatile organic compounds (VOCs) actively released by trees is associated with improved health through enhanced natural killer cell activity, reduced inflammatory responses, and reduced psychological stress. This article presents the results of a literature review on the harmful health effects of air pollution in urban environments, and the potential of forested environments to promote health and disease prevention.
Deep Learning Ability of Students from Superior and Non-Superior Classes at Microscopic Level of Protein

Deep learning is urgently required to achieve scientific literacy and to develop high order thinking skills. This study aimed to describe the deep learning ability of science education major students in a university in East Java at the microscopic level of protein. Twenty students from superior class and thirty students from non-superior class were involved voluntarily in the survey study. By using content analysis that is read carefully students’ tasks, examined students’ ability in identify, define, and explain biochemical aspects of protein case, and apply the knowledge to explain the case, and determined students’ learning status using rubrics, we found that students from both classes successful identified, defined, and explained aspects of protein cases macroscopically. However, microscopically, no students from the superior class explained protein aspects in the cases, while 11% of students from non-superior class explained them successfully. Seven percent of student from non-superior class used their protein knowledge to explain the protein cases they explored successfully. We also found that 7% of students from the non-superior class performed deep learning at microscopic level of protein, while no students from the superior class performed the same. However, majority students from both classes performed surface learning at microscopic level of protein. The results imply that both superior and non-superior students are difficult to learn protein microscopically. Learning strategy to help students attain meaningful learning of biochemistry are needed by the students.
CONSUMER WELL-BEING: PERAN BRAND AUTHENTICITY DAN DAMPAKNYA TERHADAP CONSUMER CITIZENSHIP BEHAVIOR

This article aims to deepen knowledge about the importance of the concept of consumer well-being in marketing research, as well as to build propositions related to the potential for consumer well-being and its consequences for marketing outcomes. Through an in-depth study of the existing literature, it can be revealed that CWB is an important construct in marketing research and consumer behavior. CWB measurement can be done by measuring consumer satisfaction which contributes to several positive states of consumers in the form of positive emotions, attachments, relationships, meaning, and achievement (PERMA). In addition, this article succeeded in building a proposition that brand authenticity can have a significant effect on CWB and marketing outcomes in the form of consumer citizenship behavior. The relationship between these variables is based on self-determination theory.
PHYTOCHEMICAL AND PHARMACOLOGICAL EVALUATION OF EUPHORBIACEAE FAMILY PLANT LEAVES- ACALYPHA INDICA L., CROTON BONPLANDIANUM BAILL

Objective: Plants are the most important sources of medicines. Now a day the large number of drugs in use is derived from plants. The important advantages for therapeutic uses of medicinal plants in various ailments are their safety besides being effective, economical and easy availability. The present study investigates the phytochemical, and phrmacological activity of two medicinal plants Acalypha indica L. , Croton bonplandianum BAILL Methods: Leaves of two plants from the family Euphorbiaceae - were collected, dried and powdered. The powdered material is subjected to soxhlet extraction using various solvents and allowed to evaporation. The crude extracts thus obtained were used for further investigation of phytochemicals, in vitro antioxidant and antimicrobial activity of aqueous, methanol and chloroform extracts from euphorbiaceae plants- Acalypha indica L. , Croton bonplandianum BAILL. leaves. Results: The phytochemical analysis revealed the presence of carbohydrates, amino acids, proteins, tannins, flavanoids, anthrocyanins and β-cyanins, quinones, glycosides and phenols in aqueous, methanol and chloroform extracts. Terpenoids and coumarins are present in aqueous and methanol extracts and absent in chloroform extracts. Alkaloids present only in the chloroform extract. Quantitative analysis demonstrated that presence of high concentration of proteins, sugars, phenol and tannins in methanol extracts of screened plants. The antioxidant activity of the extracts was evaluated by DPPH Radical Scavenging Assay. The antioxidant activity was compared with standard antioxidant such as ascorbic acid. All the extracts showed significant antioxidant activity. Methanol extract of Acalypha indica L. has high antioxidant activity and low IC 50 value. The plant preparations were also screened individually for antimicrobial activity against three gram negative ( E.coli, S.typimurium, S,paratypi ) and three gram positive ( S.epidermis, B.subtilis, S.aureus ) organisms by disc diffusion method. Conclusion: Results showed that all the extracts were effective against both gram positive and gram negative organisms. The methanol extracts of Acalypha indica L. shows more effectiveness than the other extracts against bacterial species tested.
Accurate Covariance Estimation for Pose Data from Iterative Closest Point Algorithm

One of the fundamental problems of robotics and navigation is the estimation of relative pose of an external object with respect to the observer. A common method for computing the relative pose is the Iterative Closest Point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in down-stream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper we introduce a novel method for estimating uncertainty from sensed data. Using a visual simulation of an automated aerial refueling (AAR) task, we demonstrate significantly more accurate uncertainty estimates using our proposed approach than a naive “Jacobian” method.
Optical filters based on fixed length Thue–Morse plasma-dielectric photonic band multilayers: Comparing two, three, and four materials systems

In this paper, we study the optical filtering properties of plasma-dielectric photonic crystals based on Thue–Morse multilayers. The method of generating the Thue–Morse sequence used in the current paper is different from that used in the available literature. We fix the total multi-material system length and use two, three, and four alternative layers of materials with different refractive indices to study the optical transmission properties of a few proposed structures. We also use plasma layers to have more tunable bandgaps. We employ the transfer matrix method to do our numerical calculations. We change the geometrical parameters, the number of layers, the arrangement of the layers, material refractive indices, and plasma properties and extract their effects on the bandgap behavior. We determine the tunability of the proposed structures to facilitate the selection of the one with desired filtering properties. However, understanding the tunability of our systems can facilitate the devising of optical devices such as an optical filter.
Gas Phase Negative Ion Chemistry: Reactivity and Mechanism in Fundamental Organic Reactions

Numerous experimental and theoretical studies have probed reactions using gas phase ion chemistry to develop an intrinsic understanding of kinetics, mechanisms and structure-energy relationships. The fundamental knowledge gained from these studies allows predictive tools to be developed for understanding chemical systems (earth’s atmosphere, biological, etc.). This thesis describes the reactive characteristics and competitive processes within several organic ion-molecule reactions. An overview of the basic principles of gas phase ion-molecule reactions and the experimental methods employed in our studies are given in Chapters 1-2. In Chapter 3, comparisons of the reactivity and mechanistic pathways between the reactions of alkyl iodides with CN ̄ in the gas phase and several solvents are reported. The mechanistic results are strikingly similar; however, a tighter gas phase transition state is suggested. In Chapter 4, competition between the substitution (SN2) and elimination (E2) reactions of alkyl iodides with Cl ̄, CN ̄, and HS ̄ is evaluated. Contrary to previous studies, our results reveal competition between the SN2 and E2 pathways. Discussions cover reaction efficiencies, kinetic isotope effects, linear basicity-reactivity relationships, electrostatic models, and transition state looseness parameters. In Chapter 5, our investigation of the α-effect in the gas phase shows enhanced validating an intrinsic origin of the effect. Variations in electron affinities and bond strengths between the normal and α-anions indicate that HOO ̄ has distinctive thermochemical properties.
A Hybrid GSTARX-Jordan RNN Model for Forecasting Space-Time Data with Calendar Variation Effect

Generalized Space-Time Autoregressive (GSTAR) is one of the space-time models. The GSTAR model has its limitations of not being able to model a nonlinear time series, and this can be overcome by applying a hybrid model on GSTAR. This research aims to propose modeling hybrid Time Series Regression (TSR) and hybrid GSTARX-Jordan RNN, where TSR and GSTARX model as a linear component involving the predictor variable, which is an effect of calendar variation and Jordan-RNN as a nonlinear component. This research focused on a simulation study to evaluate the goodness of the model hybrid GSTARX-Jordan RNN. There were some scenarios experimented, i.e. simulation studies in data that have linear noise and non-linear noise. The results showed that a hybrid GSTARX-FFNN, GSTARX-DLNN, and GSTARX-Jordan RNN model is the best model for predicting simulation data containing trend, seasonality, calendar variations, and nonlinear noise series compared with TSR, and GSTARX models. In general, it is in line with the results of the 2018 M4 forecasting competition show that combined models or hybrid models tend to provide more accurate forecast performance than forecast results with individual models.
Research on the Key Technology and System Architecture of Smart Research Travel in Novel Coronavirus Epidemic

In December 2019, China’s research travel market plummeted as a result of the novel coronavirus epidemic. In the context of a depressed research market in the Information Age, the concept of “Internet + research” emerged. First, according to symbiosis theory, the symbiotic units of smart research travel are determined. Then, based on a structural design of smart research travel data system, key technologies in big data, cloud computing, and Internet of Things are described in detail. Finally, based on the traditional browser/server architecture model of computers, a smart research travel system architecture suitable for the epidemic situation is constructed. The purpose of this study is to build a new ecology of research travel, optimize resource allocation, and promote the healthy, stable, and sustainable development of research travel in the country.
An assessment of a unmanned aerial vehicle‐based broadcast scenario assuming random terrestrial user locations

With the advent of the new decade, unmanned aerial vehicles (UAVs) will increasingly play an active role mainly as broadband transmission relays for broadcast applications. In the present study, we consider a feasible network where a transmitter, mounted on a hill, is connected through an optical wireless link with a UAV, hovering at a certain height above the earth. The UAV provides coverage over a circular geographic area and communicates through a radio frequency (RF) link with a ground user who is randomly located inside the circular region. In this context, a mixed optical/RF link is established where the performance is thoroughly investigated in terms of the outage probability. We assume that the optical wireless link is affected by a plethora of deteriorating factors, including the presence of fog, or the atmospheric scintillation, while the RF link is subject to small ‐ scale fading. Depending on the appearance of fog or turbulence, two different problems occur with a different mathematical formulation. For both cases, we extract closed ‐ form expressions for the signal ‐ to ‐ noise ratio statistics, which are the critical component towards determining the outage probability. Then, the impact of the impairments for some typical parameter values is properly depicted in appropriate graphs.
High Level Synchronization and Computations of Feed Forward Cut-Set based Multiply Accumulate Unit

In a modern technology-based application, digital signal processing (DSP) is a major priority one, in this gadgets application, the Multiply Accumulate Unit (MAC) will occupy more memory usages, power consumptions and critical path delay. Due to the number of arithmetic operations, this MAC unit will play’s a major role in this application product. Thus, the pipelined based architecture will be used to reduce the number of critical paths delay and to improve the performance of MAC architecture. However, the number of flip flops will be increased in the MAC unit, due to number of pipelined architectures. Consequently, it will increase the area and the power consumption. Thus, proposed work of this paper will get a novelty process of feed forward cut-set based MAC architecture with high level synchronization of XOR-MUX full adder with compressor technique. It will reduce the number of logic gates in MAC architecture and hence prove the performance in FPGA Implementation of LUT based area, critical path delay and average power consumption.
Hierarchical graph attention network for relation extraction

Previous research on relation extraction has proved the effectiveness of using dependency trees, which build non-local connections between tokens. However, the existing dependency-based models treat the dependency trees as an inherently flat graph, which causes a loss of dependency information for representing sentences. Besides, they fail to consider the fact that the importance of tokens on the dependency tree varies with different relations to be extracted. In this paper, we propose a novel hierarchical graph attention network HierGAT, which can generate multi-level dependency trees and extract key information from them to improve relation extraction. Specifically, it contains multiple dependency-based graph attention layers, each of which takes a different dependency tree generated by an adaptive subtree pruning strategy as input, and distinguishes the importance of different tokens in a dependency tree. Finally, HierGAT integrates the output token representations of each layer with a multi-head attention mechanism, and learns sentence representation for relation extraction through a pooling layer. The experimental results demonstrate that our method outperforms state-of-the-art baselines on the benchmark datasets.
Síntesis de chalconas preniladas potencialmente bioactivas mediante reacciones consecutivas de reordenamiento y condensación de Claisen

The introduction of prenyl and hydroxyl groups in the structure of chalcones could produce new structural analogs with potential biological activity. The synthesis of these compounds is an interesting way for obtaining new therapeutic agents. Using Claisen's rearrangement and condensation reactions assisted by microwaves two prenylated chalcones were obtained with moderate yields (47-52%) and a high degree of purity. The synthetized compounds were structurally characterized by nuclear resonance spectroscopy, infrared spectroscopy, high resolution mass spectrometry and elementary analysis. Keywords: prenylated chalcones, Claisen's rearrangement, Claisen's condensation.
L’analyse des variables explicatives de l’adoption du Social CRM par les PME de Tourisme au Maroc : Résultats d’une étude exploratoire

Le « Social CRM » est un nouveau paradigme qui a récemment émergé pour décrire l’utilisation des médias sociaux en faveur de la gestion de la relation client. Aujourd’hui, le « Social CRM » offre aux entreprises l’opportunité d’être à l’écoute des clients et de pouvoir créer de la valeur en partenariat avec eux. L’objectif de ce papier est d’expliquer l’adoption du « Social CRM » par les PME de tourisme au Maroc. Il propose un modèle conceptuel regroupant différents facteurs déterminants de l’adoption, et qui a pour fondement théorique la théorie d’adoption des innovations de Rogers et le cadre TOE de Tornatzky and Fleischer 1990. Pour apporter des éléments de réponse à notre problématique de recherche, nous avons mené une première étude exploratoire auprès d’une dizaine de PME à la région Tanger-TétouanAl Hoceima. L’analyse des résultats a été faite à l’aide du logiciel N vivo12. L’analyse a montré que les principaux facteurs influençant l’adoption du « Social CRM », sont le soutien du Top Management, les connaissances des employés en SI, l’avantage relatif, la compatibilité, la facilité d’utilisation, la testabilité, l’observabilité des résultats, et la pression concurrentielle. Aussi bien, un nouveau groupe de facteurs est à ajouter au modèle initial qui sont les caractéristiques liées au dirigeant de la PME. Pour pouvoir généraliser les résultats, une nouvelle étude quantitative confirmatoire sera mise en œuvre à l’échelle nationale.