Search results for: wavelet decomposition

Authors: Slavka Zeković, Miodrag Vujošević, Tamara Maričić

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The paper provides a comprehensive analysis of the sustainable development in the Belgrade Metropolitan Region - BMA (level NUTS 2) preliminary evaluating the three chosen components: 1) economic growth and developmental changes; 2) competitiveness; and 3) territorial concentration and industrial specialization. First, we identified the main results of development changes and economic growth by applying Shift-share analysis on the metropolitan level. Second, the empirical evaluation of competitiveness in the BMA is based on the analysis of absolute and relative values of eight indicators by Spider method. Paper shows that the consideration of the national share, industrial mix and metropolitan/regional share in total Shift share of the BMA, as well as economic/functional specialization of the BMA indicate very strong process of deindustrialization. Allocative component of the BMA economic growth has positive value, reflecting the above-average sector productivity compared to the national average. Third, the important positive role of metropolitan/regional component in decomposition of the BMA economic growth is highlighted as one of the key results. Finally, comparative analysis of the industrial territorial concentration in the BMA in relation to Serbia is based on location quotient (LQ) or Balassa index as a valid measure. The results indicate absolute and relative differences in decrease of industry territorial concentration as well as inefficiency of utilizing territorial capital in the BMA. Results are important for the increase of regional competitiveness and territorial distribution in this area as well as for improvement of sustainable metropolitan and sector policies, planning and governance on this level.

Keywords: Belgrade Metropolitan Area (BMA), comprehensive analysis / evaluation, economic growth, competitiveness, sustainable development

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Authors: Kevin Wang, Jian Ge, Yinan Zhao, Kevin Willis

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Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars).

Keywords: algorithms, astronomy data analysis, deep learning, exoplanet detection methods, small planets, habitable planets, transit photometry

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Authors: Jerzy Ejsmont, Beata Świeczko-Żurek, Grzegorz Ronowski

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Gas cylinders in general and particularly cylinders containing acetylene constitute a great potential danger for fire and rescue services involved in salvage operations. Experiments show that gas cylinders with acetylene, oxygen, hydrogen, CNG, LPG or CO2 may blow after short exposition to heat with very destructive effect as fragments of blown cylinder may fly even several hundred meters. In the case of acetylene, the explosion may occur also several hours after the cylinder is cooled down. One of the possible neutralization procedures that in many cases may be used to prevent explosions is shooting dangerous cylinders by rifle bullets. This technique is used to neutralize acetylene cylinders in a few European countries with great success. In Poland research project 'BLOW' was launched in 2014 with the aim to investigate phenomena related to fire influence on industrial and home used cylinders and to evaluate usefulness of the shooting technique. All together over 100 gas cylinders with different gases were experimentally tested at the military blasting grounds and in shelters. During the experiments cylinder temperature and pressure were recorded. In the case of acetylene that is subjected to thermal decomposition also concentration of hydrogen was monitored. Some of the cylinders were allowed to blow and others were shot by snipers. It was observed that shooting hot cylinders has never created more dangerous situations than letting the cylinders to explode spontaneously. In a great majority of cases cylinders that were punctured by bullets released gas in a more or less violent but relatively safe way. The paper presents detailed information about experiments and presents particularities of behavior of cylinders containing different gases. Extensive research was also done in order to select bullets that may be safely and efficiently used to puncture different cylinders. The paper shows also results of those experiments as well as gives practical information related to techniques that should be used during shooting.

Keywords: fire, gas cylinders, neutralization, shooting

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Authors: Timothy L. Porter, T. Randy Dillingham

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Vegetation growth and decomposition, along with soil microbial activity play a complex role in the production of greenhouse gases originating in forest soils. The absorption or emission (respiration) of these gases is a function of many factors relating to the soils themselves, the plants, and the environment in which the plants are growing. For this study, we have constructed a battery-powered, portable field mass spectrometer for use in analyzing gases in the soils surrounding trees, plants, and other areas. We have used the instrument to sample in real-time the greenhouse gases carbon dioxide and methane in soils where plant life may be contributing to the production of gases such as methane. Gases such as isoprene, which may help correlate gas respiration to microbial activity have also been measured. The instrument is composed of a quadrupole mass spectrometer with part per billion or better sensitivity, coupled to battery-powered turbo and diaphragm pumps. A unique ambient air pressure differentially pumped intake apparatus allows for the real-time sampling of gases in the soils from the surface to several inches below the surface. Results show that this instrument is capable of instant, part-per-billion sensitivity measurement of carbon dioxide and methane in the near surface region of various forest soils. We have measured differences in soil respiration resulting from forest thinning, forest burning, and forest logging as compared to pristine, untouched forests. Further studies will include measurements of greenhouse gas respiration as a function of temperature, microbial activity as measured by isoprene production, and forest restoration after fire.

Keywords: forest, soil, greenhouse, quadrupole

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Authors: Rabia Ashfaq, Saeed Iqbal, Atiq ur Rehman, Irfanullah Khan

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An extensive series of radiopharmaceuticals have been explored in order to discover a better brain tumour diagnostic agent. Tc99m labelling with cysteine and its derivatives in liposomes shows effective tagging of about 70% to 80 %. Due to microscopic size it successfully crossed the brain barrier in 2 minutes which gradually decreases in 5 to 15 minutes. HMPAO labelled with Tc99m is another important radiopharmaceutical used to study brain perfusion but it comes with a flaw that it’s only functional during epilepsy. 1, 1 ECD is purely used in Tc99m ECD formulation; because it not only tends to cross the blood brain barrier but it can be metabolized which can be easily entrapped in human brain. Radio labelling of Cysteine with Tc99m at room temperature was performed which yielded no good results. Hence cysteine derivatives with salicylaldehyde were prepared that produced about 75 % yield for ligand. In order to perform it’s radio labelling a suitable solvent DMSO was selected and physical parameters were performed. Elemental analyser produced remarkably similar results for ligand as reported in literature. IR spectra of Ligand in DMSO concluded in the absence of SH stretch and presence of N-H vibration. Thermal analysis of the ligand further suggested its decomposition pattern with no distinct curve for a melting point. Radio labelling of ligand was performed which produced excellent results giving up to 88% labelling at pH 5.0. Clinical trials using Rabbit were performed after validating the products reproducibility. The radiopharmaceutical prepared was injected into the rabbit. Dynamic as well as static study was performed under the SPECT. It showed considerable uptake in the kidneys and liver considering it suitable for the Hypatobilliary study.

Keywords: marcapto compounds, 99mTc - radiolabeling, salicylaldicysteine, thiozolidine

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Authors: Rohit Sharma, Fabio Cozzi

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A 3C-2D PIV technique was applied to investigate the swirling flow generated by an axial plus tangential type swirl generator. This work is focused on the near-exit region of an isothermal swirling jet to characterize the effect of swirl on the flow field and to identify the large coherent structures both in unconfined and confined conditions for geometrical swirl number, S_g = 4.6. Effects of the Reynolds number on the flow structure were also studied. The experimental results show significant effects of the confinement on the mean velocity fields and its fluctuations. The size of the recirculation zone was significantly enlarged upon confinement compared to the free swirling jet. Increasing in the Reynolds number further enhanced the recirculation zone. The frequency characteristics have been measured with a capacitive microphone which indicates the presence of periodic oscillation related to the existence of precessing vortex core, PVC. Proper orthogonal decomposition of the jet velocity field was carried out, enabling the identification of coherent structures. The time coefficients of the first two most energetic POD modes were used to reconstruct the phase-averaged velocity field of the oscillatory motion in the swirling flow. The instantaneous minima of negative swirl strength values calculated from the instantaneous velocity field revealed the presence of two helical structures located in the inner and outer shear layers and this structure fade out at an axial location of approximately z/D = 1.5 for unconfined case and z/D = 1.2 for confined case. By phase averaging the instantaneous swirling strength maps, the 3D helical vortex structure was reconstructed.

Keywords: acoustic probes, 3C-2D particle image velocimetry (PIV), precessing vortex core (PVC), recirculation zone (RZ)

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Authors: Abobakr Khidir Ziyada, Cecilia Devi Wilfred

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In the present work, a new series of 3-propanenitrile imidazolium-based Room Temperature Ionic Liquids (RTILs), incorporating dioctyl sulfosuccinate (DOSS) were prepared by reacting imidazole with acrylonitrile and then reacting the product with allyl chloride, 2-chloroethanol, and benzyl chloride. After the reaction had been completed, metathesis reaction was carried out using sodium dioctyl sulfosuccinate. The densities and viscosities of the present RTILs were measured at atmospheric pressure at T=293.15 to 353.15 K, the refractive index was measured at T=293.15 to 333.15 K, whereas, the start and decomposition temperatures were determined at heating rate 10°C. min^-1. The thermal expansion coefficient, densities at a range of temperatures and pressures, molecular volume, molar refraction, standard entropy and the lattice energy of these RTILs were also estimated. The present RTILs showed higher densities, similar refractive indices, and higher viscosities compared to the other 1-alkyl-3-propanenitrile imidazolium-based RTILs. The densities of the present synthesized RTILs are lower compared to the other nitrile-functionalized ILs. These present RTILs showed a weak temperature dependence on the thermal expansion coefficients, αp=5.0 × 10^−4 to 7.50 × 10−4 K^-1. Empirical correlations were proposed to represent the present data on the physical properties. The lattice energy for the present RTILs was similar to other nitrile–based imidazolium RTILs. The present RTILs showed very high molar refraction when compared similar RTILs incorporating other anions.

Keywords: dioctyl sulfosuccinate, nitrile ILs, 3-propanenitrile, anion, room temperature ionic liquids, RTIL

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Authors: Albana Hasimi, Edlira Tako, Elvin Çomo, Partizan Malkaj, Blerina Papajani, Ledjan Malaj, Mirela Ndrita

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Many endeavors have been exerted during the last years for developing new artificial polymeric membranes which fulfill the demanded conditions for biomedical uses. One of the most tested polymers is Poly(vinyl alcohol) [PVA]. Ours groups, is based on the possibility of using PVA for personal protective equipment against covid. In them, we explore the possibility of modifying the properties of the polymer by adding Montmorillonite [MMT]. Heat-treatment above the glass transition temperature are used to improve mechanical properties mainly by increasing the crystallinity of the polymer, which acts as a physical network. Temperature-Modulated Differential Scanning Calorimetry (TMDSC) measurements indicated that the presence of 0.5% MMT in PVA causes a higher Tg value and shaped peak of crystallinity. Decomposition is observed at two of the melting points of the crystals during heating 25-240oC and overlap of the recrystallization ridges during cooling 240-25oC. This is indicative of the presence of two types (quality or structure ) of polymer crystals. On the other hand, some indication of improvement of the quality of the crystals by heat-treatment is given by the distinct non-reversing contribution to melting. Data on sorption and transport of water in polyvinyl alcohol films: PVA pure and PVA/MMT matrix, modified by thermal treatment, are presented. The thermal treatment has aftereffect the films become more rigid, and because of this, the water uptake is significantly lower in membranes. That is indicates by analysis of the resulting water uptake kinetics. The presence 0.5% w/w of MMT has no significant impact on the properties of PVA membranes. Water uptake kinetics deviates from Fick’s law due to slow relaxation of glassy polymer matrix for all membranes category.

Keywords: crystallinity, montmorillonite, nanocomposite, poly (vinyl alcohol)

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Authors: Alvaro Ramírez, Martín Muñoz-Morales, Ester López- Fernández, Javier Llanos, C. Ania

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Carbon blacks are value-added materials typically produced through the incomplete combustion or thermal decomposition of hydrocarbons. Traditionally, they have been used as catalysts in many different applications, but in the last decade, their potential in green chemistry has gained significant attention. Among them, the electrochemical production of H₂O₂ has attracted interest because of their properties as high oxidant capacity or their industrial interest as a bleaching agent. Carbon blacks are commonly used in this application in a catalytic ink that is drop-casted on supporting electrodes and acts as catalysts for the electrochemical production of H₂O₂ through oxygen reduction reaction (ORR). However, the different structural and electrochemical behaviors of each type of carbon black influence their applications. In this line, the term ‘carbon black’, has to be considered as a generic name that does not guarantee any physicochemical properties if any further description is mentioned. In fact, different specific surface area (SSA), surface functional groups, porous structure, and electro catalysts effect seem very important for electrochemical applications, and considerable differences were found during the analysis of four types of carbon blacks. Thus, the aim of this work is to evaluate the influence of SSA, porous structure, oxygen functional groups, and structural defects to differentiate among these carbon blacks (e.g. Vulcan XC72, Superior Graphite Co, Printex XE2, and Prolabo) for H₂O₂ production via ORR, using carbon paper as electrode support with improved selectivity and efficiency. Results indicate that the number and size of pores, along with surface functional groups, are key parameters that significantly affect the overall process efficiency.

Keywords: carbon blacks, oxygen reduction reaction, hydrogen peroxide, porosity, surface functional groups

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Mauricio Cruz, Andrés Díaz García, Martha Isabel Gómez, Juan Carlos Serrato Bermúdez

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The disadvantages of using natural substrates in SSF processes have been well recognized and mainly are associated to gradual decomposition of the substrate, formation of agglomerates and decrease of porosity bed generating limitations in the mass and heat transfer. Additionally, in several cases, materials with a high agricultural value such as sour milk, beets, rice, beans and corn have been used. Thus, the use of economic inert supports (natural or synthetic) in combination with a nutrient suspension for the production of biocontrol microorganisms is a good alternative in SSF processes, but requires further studies in the fields of modeling and optimization. Therefore, the aim of this work is to compare the performance of two inert supports, a synthetic (polyurethane foam) and a natural one (rice husk), identifying the factors that have the major effects on the productivity of T. asperellum Th204 and the maximum specific growth rate in a PROPHYTA L05® fixed bed bioreactor. For this, the six factors C:N ratio, temperature, inoculation rate, bed height, air moisture content and airflow were evaluated using a fractional design. The factors C:N and air flow were identified as significant on the productivity (expressed as conidia/dry substrate•h). The polyurethane foam showed higher maximum specific growth rate (0.1631 h-1) and productivities of 3.89 x107 conidia/dry substrate•h compared to rice husk (2.83x106) and natural substrate based on rice (8.87x106) used as control. Finally, a quadratic model was generated and validated, obtaining productivities higher than 3.0x107 conidia/dry substrate•h with air flow at 0.9 m3/h and C:N ratio at 18.1.

Keywords: bioprocess, scale up, fractional design, C:N ratio, air flow

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Authors: Arjun G. Koppad

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The study was conducted in Joida taluk of Uttara Kannada district, Karnataka, India, to assess the land use land cover (LULC) and forest aboveground biomass using L band SAR data. The study area covered has dense, moderately dense, and sparse forests. The sampled area was 0.01 percent of the forest area with 30 sampling plots which were selected randomly. The point center quadrate (PCQ) method was used to select the tree and collected the tree growth parameters viz., tree height, diameter at breast height (DBH), and diameter at the tree base. The tree crown density was measured with a densitometer. Each sample plot biomass was estimated using the standard formula. In this study, the LULC classification was done using Freeman-Durden, Yamaghuchi and Pauli polarimetric decompositions. It was observed that the Freeman-Durden decomposition showed better LULC classification with an accuracy of 88 percent. An attempt was made to estimate the aboveground biomass using SAR backscatter. The ALOS-2 PALSAR-2 L-band data (HH, HV, VV &VH) fully polarimetric quad-pol SAR data was used. SAR backscatter-based regression model was implemented to retrieve forest aboveground biomass of the study area. Cross-polarization (HV) has shown a good correlation with forest above-ground biomass. The Multi Linear Regression analysis was done to estimate aboveground biomass of the natural forest areas of the Joida taluk. The different polarizations (HH &HV, VV &HH, HV & VH, VV&VH) combination of HH and HV polarization shows a good correlation with field and predicted biomass. The RMSE and value for HH & HV and HH & VV were 78 t/ha and 0.861, 81 t/ha and 0.853, respectively. Hence the model can be recommended for estimating AGB for the dense, moderately dense, and sparse forest.

Keywords: forest, biomass, LULC, back scatter, SAR, regression

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Jackson Niyongabo

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This study addresses a notable gap in the existing literature on the relationship between energy consumption, economic growth, and CO₂ emissions, particularly within the African context. While numerous studies have explored these dynamics globally and regionally across various development levels, few have delved into the nuances of regions and income levels specific to African countries. Furthermore, the evaluation of the interplay between green growth policies, green energy technologies, and their impact on environmental quality has been underexplored. This research aims to fill these gaps by conducting a comprehensive analysis of the transition from conventional economic growth and energy consumption to a paradigm of green growth coupled with green energy utilization across the African continent from 1980 to 2018. The study is structured into three main parts: an empirical examination of the long-term effects of energy intensity, renewable energy consumption, and economic growth on CO₂ emissions across diverse African regions and income levels; an estimation of the long-term impact of green growth and green energy use on CO₂ emissions for countries implementing green policies within Africa, as well as at regional and global levels; and a comparative analysis of the impact of green growth policies on environmental degradation before and after implementation. Employing advanced econometric methods and panel estimators, the study utilizes a testing framework, panel unit tests, and various estimators to derive meaningful insights. The anticipated results and conclusions will be elucidated through causality tests, impulse response, and variance decomposition analyses, contributing valuable knowledge to the discourse on sustainable development in the African context.

Keywords: economic growth, green growth, energy consumption, CO₂ emissions, econometric models, green energy

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Authors: Yassets Egaña, Patricio Núñez, Juan C. Rios, Ivan Balic, Alex Manquez, Yarela Flores, Maria C. Gatica, Sergio Diez De Medina, Rocio Tijaro-Rojas

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Globally, humans produce millions of tons of waste per year. An important percentage of this waste is plastic, which frequently ends up in landfills and oceans. During the last decades, the greatest plastics production in history have been made, a few amount of this plastic is recycled, the rest ending up as plastic pollution in soils and seas. Plastic pollution is disastrous for the environment, affecting essential species, quality of consumption water, and some economic activities such as tourism, in different parts of the world. Due to its durability and decomposition on micro-plastics, animals and humans are accumulating a variety of plastic components without having clear their effects on human health, economy, and wildlife. In dry regions as the Atacama Desert, up to 95% of the water consumption comes from underground reservoirs, therefore preventing the soil pollution is an urgent need. This contribution focused on isolating, genotyping and optimizing microorganisms that use plastic waste as the only source of food to construct a batch-type bioreactor able to degrade in a faster way the plastic waste before it gets the desert soils and groundwater consumed by people living in this areas. Preliminary results, under laboratory conditions, has shown an improved degradation of polyethylene when three species of bacteria and three of fungi act on a selected plastic material. These microorganisms have been inoculated in dry soils, initially lacking organic matter, under environmental conditions in the laboratory. Our team designed and constructed a prototype using the natural conditions of the region and the best experimental results.

Keywords: biological breakdown, plastic bags, prototype, desert regions

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Authors: Luanna B. Prevost, Kelli Carter, Margaurete Romero, Kirsti Martinez

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Writing is an essential scientific practice, yet, in several countries, the increasing university science class-size limits the use of written assessments. Written assessments allow students to demonstrate their learning in their own words and permit the faculty to evaluate students’ understanding. However, the time and resources required to grade written assessments prohibit their use in large-enrollment science courses. This study examined the use of machine learning algorithms to automatically analyze student writing and provide timely feedback to the faculty about students' writing in biology. Written responses to questions about matter and energy transformation were collected from large-enrollment undergraduate introductory biology classrooms. Responses were analyzed using the LightSide text mining and classification software. Cohen’s Kappa was used to measure agreement between the LightSide models and human raters. Predictive models achieved agreement with human coding of 0.7 Cohen’s Kappa or greater. Models captured that when writing about matter-energy transformation at the ecosystem level, students focused on primarily on the concepts of heat loss, recycling of matter, and conservation of matter and energy. Models were also produced to capture writing about processes such as decomposition and biochemical cycling. The models created in this study can be used to provide automatic feedback about students understanding of these concepts to biology faculty who desire to use formative written assessments in larger enrollment biology classes, but do not have the time or personnel for manual grading.

Keywords: machine learning, written assessment, biology education, text mining

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Authors: Amandeep Kaur, N. S. Atri, Munruchi Kaur

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Herbivorous dung is a special substrate for the growth of fungi. Fungi growing thereon are known as coprophilous. These fungi are amongst the most abundant taxa in the ecosystem, which regulate the decomposition of dung organic matter, nutrient dynamics and maintenance of ecological balance on the earth. The coprophilous fungi represent a diverse group of saprobes, including taxa from most major fungal groups belonging to Zygomycota, Ascomycota and Basidiomycota. The present work, however, has been focused on the basidiomycetous coprophilous mushrooms belonging to the order Agaricales. The research work includes the results of eco-taxonomic studies of coprophilous mushrooms in Punjab, India, on the basis of a survey of dung localities of the state. The mushrooms were collected growing as saprobes on dung of various domesticated and wild herbivorous animals in pastures, grasslands, zoos, and on dung heaps in villages, etc. The present study observed the frequency of distribution of coprophilous mushrooms in different taxonomic categories in different regions of the state in various seasons on different dung types along with their growing habit. The paper also discusses their economic utility as edible, inedible, poisonous, medicinal and hallucinogenic species. The study has shown that animal dung is a good niche for the growth of mushrooms. However, the natural habitats with dung deposits are getting destroyed because of different developmental activities. Livestock in agriculture-based societies like Punjab state in India should be managed in a manner that favors their grazing in the wild places and thereby the growth of coprophilous mushrooms so that a significant role in ecological balance on the earth is established.

Keywords: herbivorous dung, psychoactive, seasonal availability, taxo-ecology

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Authors: Julia DeVoy, Olivia Berlin

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The United States exports over 1.6 billion pounds of post-consumer textiles every year, primarily to countries in the Global South. These textiles make their way to landfills and open-air dumps where they decompose, contaminating water systems and releasing harmful greenhouse gases. Through this inequitable system of waste disposal, countries with less political and economic power are coerced into accepting the environmental and health consequences of over-consumption in the Global North. Thus, the global trade of post-consumer textile waste represents a serious issue of environmental justice and a public health hazard. Our research located, characterizes, and quantifies the environmental and human health risks that occur when post-consumer textiles are left to decompose in landfills and open-air dumps in the Global South. In our work, we make use of United Nations International Trade Statistics data to map the global distribution of post-consumer textiles exported from the United States. Next, we present our landfill simulating reactor designed to measure toxicity of leachate resulting from the decomposition of textiles in developing countries and to quantify the related greenhouse gas emissions. This design makes use of low-cost and sustainable materials to promote frugal innovation and make landfill reactors more accessible. Finally, we describe how the data generated from these tools can be leveraged to inform individual consumer behaviors, local policies around textile waste disposal, and global advocacy efforts to mitigate the environmental harms caused by textile waste.

Keywords: sustainability, textile design, public health, built environment

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Authors: Subham Ghosh, Banani Basu, Marami Das

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Background: The development of compact, low-power antenna sensors has resulted in hardware restructuring, allowing for wireless ubiquitous sensing. The antenna sensors can create wireless body-area networks (WBAN) by linking various wireless nodes across the human body. WBAN and IoT applications, such as remote health and fitness monitoring and rehabilitation, are becoming increasingly important. In particular, Parkinson’s disease (PD), a common neurodegenerative disorder, presents clinical features that can be easily misdiagnosed. As a mobility disease, it may greatly benefit from the antenna’s nearfield approach with a variety of activities that can use WBAN and IoT technologies to increase diagnosis accuracy and patient monitoring. Methodology: This study investigates the feasibility of leveraging a single patch antenna mounted (using cloth) on the wrist dorsal to differentiate actual Parkinson's disease (PD) from false PD using a small hardware platform. The semi-flexible antenna operates at the 2.4 GHz ISM band and collects reflection coefficient (Γ) data from patients performing five exercises designed for the classification of PD and other disorders such as essential tremor (ET) or those physiological disorders caused by anxiety or stress. The obtained data is normalized and converted into 2-D representations using the Gabor wavelet transform (GWT). Data augmentation is then used to expand the dataset size. A lightweight deep-learning (DL) model is developed to run on the GPU-enabled NVIDIA Jetson Nano platform. The DL model processes the 2-D images for feature extraction and classification. Findings: The DL model was trained and tested on both the original and augmented datasets, thus doubling the dataset size. To ensure robustness, a 5-fold stratified cross-validation (5-FSCV) method was used. The proposed framework, utilizing a DL model with 1.356 million parameters on the NVIDIA Jetson Nano, achieved optimal performance in terms of accuracy of 88.64%, F1-score of 88.54, and recall of 90.46%, with a latency of 33 seconds per epoch.

Keywords: antenna, deep-learning, GPU-hardware, Parkinson’s disease

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Authors: Abera Kotu, Girma Tesema, Mitiku Tadesse

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This study investigated ACE supported instruction and pre-service mathematics teachers’ mental construction in solving equations and inequalities. A mixed approach with concurrent parallel design was employed. It was conducted on two intact groups of regular first-year pre-service mathematics teachers at Fiche College of Teachers’ Education in which one group was assigned as an intervention group and the other group as a comparison group using the lottery method. There were 33 participants in the intervention and 32 participants in the comparison. Six pre-service mathematics teachers were selected for interview using purposive sampling based on pre-test results. An instruction supported with ACE cycle was given to the intervention group for two weeks duration of time. Written tasks, interviews, and observations were used to collect data. Data collected from written tasks were analyzed quantitatively using independent samples t-test and effect size. Data collected from interviews and observations were analyzed narratively. The findings of the study uncovered that ACE-supported instruction has a moderate effect on Pre-service Mathematics Teachers’ levels of conceptualizations of action, process, object, ad schema. Moreover, the ACE supported group out scored and performed better than the usual traditional method supported groups across the levels of conceptualization. The majority of pre-service mathematics teachers’ levels of conceptualizations were at action and process levels and their levels of conceptualization were linked with genetic decomposition more at action and object levels than object and schema. The use of ACE supported instruction is recommended to improve pre-service mathematics teachers’ mental construction.

Keywords: ACE teaching cycle, APOS theory, mental construction, genetic composition

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: aerodynamics, flight control, computational fluid dynamics (CFD), flapping-wing flight

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Authors: Amir Zeb, Shailima Rampogu, Minky Son, Ayoung Baek, Sang H. Yoon, Keun W. Lee

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Neurotoxic insults activate calpain, which in turn produces truncated p25 from p35. p25 forms hyperactivated Cdk5/p25 complex, and thereby induces severe neuropathological aberrations including hyperphosphorylated tau, neuroinflammation, apoptosis, and neuronal death. Inhibition of Cdk5/p25 complex alleviates aberrant phosphorylation of tau to mitigate AD pathology. PHA-793887 and Roscovitine have been investigated as selective inhibitors of Cdk5/p25 with IC50 values 5nM and 160nM, respectively, but their mechanistic studies remain unknown. Herein, computational simulations have explored the binding mode and interaction mechanism of PHA-793887 and Roscovitine with Cdk5/p25. Docking results suggested that PHA-793887 and Rsocovitine have occupied the ATP-binding site of Cdk5 and obtained highest docking (GOLD) score of 66.54 and 84.03, respectively. Furthermore, molecular dynamics (MD) simulation demonstrated that PHA-793887 and Roscovitine established stable RMSD of 1.09 Å and 1.48 Å with Cdk5/p25, respectively. Profiling of polar interactions suggested that each inhibitor formed hydrogen bonds (H-bond) with catalytic residues of Cdk5 and could remain stable throughout the molecular dynamics simulation. Additionally, binding free energy calculation by molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) suggested that PHA-793887 and Roscovitine had lowest binding free energies of -150.05 kJ/mol and -113.14 kJ/mol, respectively with Cdk5/p25. Free energy decomposition demonstrated that polar energy by H-bond between the Glu81 of Cdk5 and PHA-793887 is the essential factor to make PHA-793887 highly selective towards Cdk5/p25. Overall, this study provided substantial evidences to explore mechanistic interactions of the selective inhibitors of Cdk5/p25 and could be used as fundamental considerations in the development of structure-based selective inhibitors of Cdk5/p25.

Keywords: Cdk5/p25 inhibition, molecular modeling of Cdk5/p25, PHA-793887 and roscovitine, selective inhibition of Cdk5/p25

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Authors: Allan F. F. Alves, Fernando A. Bacchim Neto, Guilherme Giacomini, Marcela de Oliveira, Ana L. M. Pavan, Maria E. D. Rosa, Diana R. Pina

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Stroke is a worldwide concern, only in Brazil it accounts for 10% of all registered deaths. There are 2 stroke types, ischemic (87%) and hemorrhagic (13%). Early diagnosis is essential to avoid irreversible cerebral damage. Non-enhanced computed tomography (NECT) is one of the main diagnostic techniques used due to its wide availability and rapid diagnosis. Detection depends on the size and severity of lesions and the time spent between the first symptoms and examination. The Alberta Stroke Program Early CT Score (ASPECTS) is a subjective method that increases the detection rate. The aim of this work was to implement an image segmentation system to enhance ischemic stroke and to quantify the area of ischemic and hemorrhagic stroke lesions in CT scans. We evaluated 10 patients with NECT examinations diagnosed with ischemic stroke. Analyzes were performed in two axial slices, one at the level of the thalamus and basal ganglion and one adjacent to the top edge of the ganglionic structures with window width between 80 and 100 Hounsfield Units. We used different image processing techniques such as morphological filters, discrete wavelet transform and Fuzzy C-means clustering. Subjective analyzes were performed by a neuroradiologist according to the ASPECTS scale to quantify ischemic areas in the middle cerebral artery region. These subjective analysis results were compared with objective analyzes performed by the computational algorithm. Preliminary results indicate that the morphological filters actually improve the ischemic areas for subjective evaluations. The comparison in area of the ischemic region contoured by the neuroradiologist and the defined area by computational algorithm showed no deviations greater than 12% in any of the 10 examination tests. Although there is a tendency that the areas contoured by the neuroradiologist are smaller than those obtained by the algorithm. These results show the importance of a computer aided diagnosis software to assist neuroradiology decisions, especially in critical situations as the choice of treatment for ischemic stroke.

Keywords: ischemic stroke, image processing, CT scans, Fuzzy C-means

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Authors: Yu. Mateyshina, A. Ulihin, N. Uvarov

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Supercapacitors are one of the most promising devices for energy storage applications as they can provide higher power density than batteries and higher energy density than conventional dielectric capacitors. Carbon materials with various microtextures are considered as main candidates for supercapacitors in terms of high surface area, interconnected pore structure, controlled pore size, high electrical conductivity and environmental friendliness. The specific capacitance (C) of the electrode material of the Electrochemical Double Layer Capacitors (EDLC) is known to depend on the specific surface area (Ss) and the pore structure. Activated carbons are most commonly used in supercapacitors because of their high surface area (Ss ≥ 1000 m2/g), good adhesion to electrolytes and low cost. In this work, electrochemical properties of new microporous and mesoporous carbon electrode materials were studied. The aim of the work was to investigate the relationship between the specific capacitance and specific surface area in a series of materials prepared from different organic precursors.. As supporting matrixes different carbon samples with Ss = 100-2000 m2/g were used. The materials were modified by treatment in acids (H2SO4, HNO3, acetic acid) in order to enable surface hydrophilicity. Then nanoparticles of transition metal oxides (for example NiO) were deposited on the carbon surfaces using methods of salts impregnation, mechanical treatment in ball mills and the precursors decomposition. The electrochemical characteristics of electrode hybrid materials were investigated in a symmetrical two-electrode cell using an impedance spectroscopy, voltammetry in both potentiodynamic and galvanostatic modes. It was shown that the value of C for the materials under study strongly depended on the preparation method of the electrode and the type of electrolyte (1 M H2SO4, 6 M KOH, 1 M LiClO4 in acetonitryl). Specific capacity may be increased by the introduction of nanoparticles from 50-100 F/g for initial carbon materials to 150-300 F/g for nanocomposites which may be used in supercapacitors. The work is supported by the по SC-14.604.21.0013.

Keywords: supercapacitors, carbon electrode, mesoporous carbon, electrochemistry

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Authors: Shankha Sanyal, Archi Banerjee, Sayan Biswas, Sourya Sengupta, Sayan Nag, Ranjan Sengupta, Dipak Ghosh

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The term ‘gestalt’ has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a 'unified' whole. Music, in general, is polyphonic - i.e. a combination of a number of pure tones (frequencies) mixed together in a manner that sounds harmonious. The study of human brain response due to different frequency groups of the acoustic signal can give us an excellent insight regarding the neural and functional architecture of brain functions. Hence, the study of music cognition using neuro-biosensors is becoming a rapidly emerging field of research. In this work, we have tried to analyze the effect of different frequency bands of music on the various frequency rhythms of human brain obtained from EEG data. Four widely popular Rabindrasangeet clips were subjected to Wavelet Transform method for extracting five resonant frequency bands from the original music signal. These frequency bands were initially analyzed with Detrended/Adaptive Fractal analysis (DFA/AFA) methods. A listening test was conducted on a pool of 100 respondents to assess the frequency band in which the music becomes non-recognizable. Next, these resonant frequency bands were presented to 20 subjects as auditory stimulus and EEG signals recorded simultaneously in 19 different locations of the brain. The recorded EEG signals were noise cleaned and subjected again to DFA/AFA technique on the alpha, theta and gamma frequency range. Thus, we obtained the scaling exponents from the two methods in alpha, theta and gamma EEG rhythms corresponding to different frequency bands of music. From the analysis of music signal, it is seen that loss of recognition is proportional to the loss of long range correlation in the signal. From the EEG signal analysis, we obtain frequency specific arousal based response in different lobes of brain as well as in specific EEG bands corresponding to musical stimuli. In this way, we look to identify a specific frequency band beyond which the music becomes non-recognizable and below which in spite of the absence of other bands the music is perceivable to the audience. This revelation can be of immense importance when it comes to the field of cognitive music therapy and researchers of creativity.

Keywords: AFA, DFA, EEG, gestalt in music, Hurst exponent

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Authors: H. Taylan Selamlar, I. Yavuz, G. Yapar

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It is difficult to make predictions especially about the future and making accurate predictions is not always easy. However, better predictions remain the foundation of all science therefore the development of accurate, robust and reliable forecasting methods is very important. Numerous number of forecasting methods have been proposed and studied in the literature. There are still two dominant major forecasting methods: Box-Jenkins ARIMA and Exponential Smoothing (ES), and still new methods are derived or inspired from them. After more than 50 years of widespread use, exponential smoothing is still one of the most practically relevant forecasting methods available due to their simplicity, robustness and accuracy as automatic forecasting procedures especially in the famous M-Competitions. Despite its success and widespread use in many areas, ES models have some shortcomings that negatively affect the accuracy of forecasts. Therefore, a new forecasting method in this study will be proposed to cope with these shortcomings and it will be called ATA method. This new method is obtained from traditional ES models by modifying the smoothing parameters therefore both methods have similar structural forms and ATA can be easily adapted to all of the individual ES models however ATA has many advantages due to its innovative new weighting scheme. In this paper, the focus is on modeling the trend component and handling seasonality patterns by utilizing classical decomposition. Therefore, ATA method is expanded to higher order ES methods for additive, multiplicative, additive damped and multiplicative damped trend components. The proposed models are called ATA trended models and their predictive performances are compared to their counter ES models on the M3 competition data set since it is still the most recent and comprehensive time-series data collection available. It is shown that the models outperform their counters on almost all settings and when a model selection is carried out amongst these trended models ATA outperforms all of the competitors in the M3- competition for both short term and long term forecasting horizons when the models’ forecasting accuracies are compared based on popular error metrics.

Keywords: accuracy, exponential smoothing, forecasting, initial value

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Authors: Enlin Lo, Ioannis Dogaris, George Philippidis

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Succinic acid is a compound used for manufacturing lacquers, resins, and other coating chemicals. It is also used in the food and beverage industry as a flavor additive. It is predominantly manufactured from petrochemicals, but it can also be produced by fermentation of sugars from renewable feedstocks, such as plant biomass. Bio-based succinic acid has great potential in becoming a platform chemical (building block) for commodity and high-value chemicals. In this study, the production of bio-based succinic acid from sweet sorghum was investigated. Sweet sorghum has high fermentable sugar content and can be cultivated in a variety of climates. In order to avoid competition with food feedstocks, its non-edible ‘bagasse’ (the fiber part after extracting the juice) was targeted. Initially, various conditions of pretreating sweet sorghum bagasse (SSB) were studied in an effort to remove most of the non-fermentable components and expose the cellulosic fiber containing the fermentable sugars (glucose). Concentrated (83%) phosphoric acid was utilized at temperatures 50-80 oC for 30-60 min at various SSB loadings (10-15%), coupled with enzymatic hydrolysis using commercial cellulase (Ctec2, Novozymes) enzyme, to identify the conditions that lead to the highest glucose yields for subsequent fermentation to succinic acid. As the pretreatment temperature and duration increased, the bagasse color changed from light brown to dark brown-black, indicating decomposition, which ranged from 15% to 72%, while the theoretical glucose yield is 91%. With Minitab software statistical analysis, a model was built to identify the optimal pretreatment condition for maximum glucose released. The projected theoretical bio-based succinic acid production is 23g per 100g of SSB, which will be confirmed with fermentation experiments using the bacterium Actinobacillus succinogenes.

Keywords: biomass, cellulose, enzymatic hydrolysis, fermentation, pretreatment, succinic acid

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Authors: Mohannad Mayyas, Farshid Pahlevani, Veena Sahajwalla

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Automotive shredder residue (ASR) is an industrial waste, generated during the recycling process of End-of-life vehicles. The large increasing production volumes of ASR and its hazardous content have raised concerns worldwide, leading some countries to impose more restrictions on ASR waste disposal and encouraging researchers to find efficient solutions for ASR processing. Although a great deal of research work has been carried out, all proposed solutions, to our knowledge, remain commercially and technically unproven. While the volume of waste materials continues to increase, the production of materials from new sustainable sources has become of great importance. Advanced ceramic materials such as nitrides, carbides and borides are widely used in a variety of applications. Among these ceramics, a great deal of attention has been recently paid to Titanium nitride (TiN) owing to its unique characteristics. In our study, we propose a new sustainable approach for ASR management where TiN nanoparticles with ideal particle size ranging from 200 to 315 nm can be synthesized as a by-product. In this approach, TiN is thermally synthesized by nitriding pressed mixture of automotive shredder residue (ASR) incorporated with titanium oxide (TiO2). Results indicated that TiO2 influences and catalyses degradation reactions of ASR and helps to achieve fast and full decomposition. In addition, the process resulted in titanium nitride (TiN) ceramic with several unique structures (porous nanostructured, polycrystalline, micro-spherical and nano-sized structures) that were simply obtained by tuning the ratio of TiO2 to ASR, and a product with appreciable TiN content of around 85% was achieved after only one hour nitridation at 1550 °C.

Keywords: automotive shredder residue, nano-ceramics, waste treatment, titanium nitride, thermal conversion

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Authors: D. Kuvshinov, A. Siswanto, J. Lozano-Parada, W. Zimmerman

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Ozone is well known as a powerful fast reaction rate oxidant. The ozone based processes produce no by-product left as a non-reacted ozone returns back to the original oxygen molecule. Therefore an application of ozone is widely accepted as one of the main directions for a sustainable and clean technologies development. There are number of technologies require ozone to be delivered to specific points of a production network or reactors construction. Due to space constrains, high reactivity and short life time of ozone the use of ozone generators even of a bench top scale is practically limited. This requires development of mini/micro scale ozone generator which can be directly incorporated into production units. Our report presents a feasibility study of a new micro scale rector for ozone generation (MROG). Data on MROG calibration and indigo decomposition at different operation conditions are presented. At selected operation conditions with residence time of 0.25 s the process of ozone generation is not limited by reaction rate and the amount of ozone produced is a function of power applied. It was shown that the MROG is capable to produce ozone at voltage level starting from 3.5kV with ozone concentration of 5.28E-6 (mol/L) at 5kV. This is in line with data presented on numerical investigation for a MROG. It was shown that in compare to a conventional ozone generator, MROG has lower power consumption at low voltages and atmospheric pressure. The MROG construction makes it applicable for emerged and dry systems. With a robust compact design MROG can be used as incorporated unit for production lines of high complexity.

Keywords: dielectric barrier discharge (DBD), micro reactor, ozone, plasma

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Authors: Kajori Banerjee, Laxmi Kant Dwivedi

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“Health transition” is defined to be “a process through which high levels of mortality, morbidity and disability are reduced to low levels by influencing cultural, social and behavioural factors”. Life expectancy in India has been on the rise and parallel the burden of disease and disability has also risen noticeably. Borrowing data from Indian Census (2001, 2011), this study identifies the gender-wise burden of disability by calculating disability free life expectancy (DFLE) and life lived with disability (LWD). Sullivan’s method of calculating DFLE using proportion of disabled is used for this purpose. The change in person years lived with disability in the decade 2001-11 is further decomposed using Arriaga’s method into mortality and disability effects (ME and DE) to check the magnitude and direction of contribution of mortality and disability. Nationally, along with DFLE, LWD has amplified too. Despite having the highest life expectancy and DFLE, LWD in Kerala, was highest for both sexes in 2001. But in 2011, the LWD was highest among the males of Orissa and females of Rajasthan. For the overall population, DE is positive for the prime working age groups of 20-40years indicating that there has been an increase in the disability proportion holding mortality constant for 2001-2011. Females exhibit higher positive DE implying greater loss of healthy years due to disability than males. The findings call for an immediate attention to the causes of rising disability burden among the working population, especially females, as this might heavily effect the availability of quality labour force and its relative economic output in the Indian labour market. This also hints at the degrading quality of the elongated life and needs to be given the required attention to enhance the quality of life lead in the Nation.

Keywords: disability-free life expectancy, disability effect, life expectancy, mortality effect

Procedia PDF Downloads 397