Search results for: hierarchical porosity

Authors: Nivedita Ghosh

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In his critique of Lefebvre’s view that ‘technological capacities’ are class-dependent, Francois Hetman argues that technology today is participatory, allowing the entry of individuals from different levels of social stratification. As a result, we are entering into an era of technology operators or ‘clerks’ who become the new decision-makers because of the knowledge they possess of the use of technologies. In response to Hetman’s thesis, this paper argues that knowledge of technology, while indeed providing a momentary space for decision-making, does not necessarily restructure social hierarchies. Through case studies presented from the world of Indian documentary filmmaking, this paper puts forth the view that Hetman’s clerks, despite being technologically advanced, do not break into the filmmaking hierarchical order. This remains true even for a situation where technical knowledge rests most with those in the lowest rungs of the filmmaking ladder. Instead, technological knowledge provides the space for other kinds of relationships to evolve, such as those of ‘trusting the technician’ or ‘admiration for the technician’s work’. Furthermore, what continues to define documentary filmmaking hierarchy is conceptualization capacities of the practitioners, which are influenced by a similarity in socio-cultural backgrounds and film school training accessible primarily to the filmmakers instead of the technicians. Accordingly, the paper concludes with the argument that more than ‘technological-capacities’, it is ‘conceptualization capacities’ which are class-dependent, especially when we study the field of documentary filmmaking.

Keywords: documentary filmmaking, India, technology, knowledge, hierarchy

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Authors: Strahinja Z. Kovačević, Lidija R. Jevrić, Sanja O. Podunavac Kuzmanović

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The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds.

Keywords: antibacterial, benzimidazole, molecular descriptors, QSAR

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Authors: Agoubi Belgacem, Adel Kharroubi

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Geothermal groundwater is the main water source to supply various sectors in El Hamma city, southeastern Tunisia. This region was long the destination of thousands of people from Tunisia and neighboring countries for care and bathing. The main objective of this study is to understand the groundwater mineralization origins and factors that control. The second goal is the appraisal of radon in geothermal groundwater in the study area. For this aim, geothermal groundwater was sampled and collected from different locations (thermal baths and deep wells). Physical parameters were measured and major ions were analyzed. Results reveal three water types. The water first type has Na-Mg-Ca-SO4-Cl facies and T>55°C. The second water type dominated by Na-Ca-Cl-SO4 facies with a temperature < 45 °C. However the third water type is dominated by Ca-SO4-Na-Cl-Mg. The three water types may be controlled by depth and geology. The first represent groundwater from deep aquifer (lower cretaceous), the second type was the shallow aquifer and the first is mixed water from deep and shallow water with a temperature ranging from 45 to 55°C. Measured Radon shows that shallow aquifer has a higher 222Rn concentration (677 to 2903 Bq.m-3) than deep water (203 to 1100 Bq.m-3). R-222 in El Hamma thermal aquifer was controlled by structures, porosity and permeability of aquifers. Geostatistical analyses of hydrogeological data and radon activities confirm the vertical flow and communication between deep and shallow aquifers through vertical faults system.

Keywords: Radon-222, geothermal, water, environment, Tunisia

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Authors: Yina A. Cifuentes Triana, Andrés M. Pinzón Velásco, Marío E. Velásquez Lozano

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In this work the sequencing and genome characterization of a natural isolate of Saccharomyces cerevisiae yeast (strain 202-3), identified with potential for the production of second generation ethanol from sugarcane bagasse hydrolysates is presented. This strain was selected because its capability to consume xylose during the fermentation of sugarcane bagasse hydrolysates, taking into account that many strains of S. cerevisiae are incapable of processing this sugar. This advantage and other prominent positive aspects during fermentation profiles evaluated in bagasse hydrolysates made the strain 202-3 a candidate strain to improve the production of second-generation ethanol, which was proposed as a first step to study the strain at the genomic level. The molecular characterization was carried out by genome sequencing with the Illumina HiSeq 2000 platform paired end; the assembly was performed with different programs, finally choosing the assembler ABYSS with kmer 89. Gene prediction was developed with the approach of hidden Markov models with Augustus. The genes identified were scored based on similarity with public databases of nucleotide and protein. Records were organized from ontological functions at different hierarchical levels, which identified central metabolic functions and roles of the S. cerevisiae strain 202-3, highlighting the presence of four possible new proteins, two of them probably associated with the positive consumption of xylose.

Keywords: cellulosic ethanol, Saccharomyces cerevisiae, genome sequencing, xylose consumption

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Authors: Satyananda Patra, Venugopal Rayasam

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The quality of pellets produced is affected by quality and type of green pellets, amount of addition of binders and fluxing agents along with the provided firing conditions. The green pellet quality depends upon chemistry, mineralogy and granulometry of fines used for pellet making, the feed size, its moisture content and porosity. During firing of green pellets, ingredients present within reacts to form different phases and microstructure. So in turn, physical and metallurgical properties of pellets are influenced by amount and type of binder and flux addition, induration time and temperature. During iron making process, the metallurgical properties of fired pellets are decided by the type and amount of these phases and their chemistry. Green pelletizing and induration studies have been already carried out with magnetite and hematite ore fines but for Indian iron ores of high alumina content showing different pelletizing characters, these studies cannot be directly interpreted. The main objective of proposed research work is to understand the green pelletizing process and determine the water bentonite interaction at different levels. Swelling behavior of bentonite and microstructure of the green pellet are investigated. Conversion of iron ore fines into pellets, the key raw material and process variables that influence the pellet quality needs to be identified and a correlation should be established between them.

Keywords: iron ore, pelletization, binders, green pellets, microstructure

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Authors: B. Kodedova, E. Filova, M. Kralovic, E. Amler

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Vitiligo is the most common depigmentation disorder of the skin characterized by loss of melanocyte in the epidermis that leads to white lesions. One of the possible treatments is autologous transplantation of melanocytes. Biodegradable electrospun polymeric nanofibers provide good mechanical properties and could serve as suitable scaffold for epithelial cells cultivation and follow up transplantation. Moreover the microarchitecture of nanofibers mimics the structure of extracellular matrix and its porosity allows nutrients and waste exchange. The aim of this work was to develop biocompatible and biodegradable polymeric scaffolds suitable for autologous melanocytes transplantation. Electrospun polyvinyl alcohol (PVA) nanofibers were modified by cold methane plasma to lower their hydrofility and to achieve better adhesion, proliferation and viability of the murine melanocyte (Melan-a). Cells were seeded on the modified scaffolds and their adhesion, metabolic activity, proliferation and melanin synthesis was evaluated and compared to non-modified scaffolds. Results clearly indicate that cold methane plasma modified PVA nanofibers are suitable for melanocyte cultivation and may be future candidate for vitiligo treatment. Furthermore, the nanofibers can be functionalized with various bioactive substances, for enhancement of the melanocyte proliferation, melanogenesis or healing and regenerative processes. The project was supported by the Ministry of Education, Youth and Sports NPU I: LO1309 and by Grant Agency of Charles University (grant No. 1228214).

Keywords: melanocyte, nanofibers, polyvinyl alcohol, plasma modification

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Authors: Carolina Pereira Lobato Costa, Cristina Pascual-González, Monica Echeverry, Javier LLorca, Carlos Gonzáléz, Juan Pedro Fernández-Bláquez

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Although the potential of PLA self-reinforced composites for bone applications, not much literature addresses optimal manufacturing conditions. In this regard, this paper describes the woven self-reinforced PLA composites manufacturing processes: the commingling of yarns, weaving, and hot pressing and characterizes the manufactured laminates. Different structures and properties can be achieved by varying the hot compaction process parameters (pressure, holding time, and temperature). The specimens manufactured were characterized in terms of thermal properties (DSC), microstructure (C-scan optical microscope and SEM), strength (tensile test), and biocompatibility (MTT assays). Considering the final device, 155 ℃ for 10 min at 2 MPa act as the more appropriate hot pressing parameters. The laminate produced with these conditions has few voids/porosity, a tensile strength of 30.39 ± 1.21 MPa, and a modulus of 4.09 ± 0.24 GPa. Subsequently to the tensile testing was possible to observe fiber pullout from the fracture surfaces, confirming that this material behaves as a composite. From the results, no single laminate can fulfill all the requirements, being necessary to compromise in function of the priority property. Further investigation is required to improve materials' mechanical performance. Subsequently, process parameters and materials configuration can be adjusted depending on the place and type of implant to suit its function.

Keywords: woven fabric, self-reinforced polymer composite, poly(lactic acid), biodegradable

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Authors: Bayar Shahab

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The fast development of technology that has advanced neuroscience and human interaction with computers has enabled solutions to various problems, and issues of this new era have been found and are being found like no other time in history. Brain-computer interface so-called BCI has opened the door to several new research areas and have been able to provide solutions to critical and important issues such as supporting a paralyzed patient to interact with the outside world, controlling a robot arm, playing games in VR with the brain, driving a wheelchair or even a car and neurotechnology enabled the rehabilitation of the lost memory, etc. This review work presents state-of-the-art methods and improvements of canonical correlation analyses (CCA), which is an SSVEP-based BCI method. These are the methods used to extract EEG signal features or, to be said in a different way, the features of interest that we are looking for in the EEG analyses. Each of the methods from oldest to newest has been discussed while comparing their advantages and disadvantages. This would create a great context and help researchers to understand the most state-of-the-art methods available in this field with their pros and cons, along with their mathematical representations and usage. This work makes a vital contribution to the existing field of study. It differs from other similar recently published works by providing the following: (1) stating most of the prominent methods used in this field in a hierarchical way (2) explaining pros and cons of each method and their performance (3) presenting the gaps that exist at the end of each method that can open the understanding and doors to new research and/or improvements.

Keywords: BCI, CCA, SSVEP, EEG

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Authors: Monjurul Hasan, Golam Kibria, Abdus Salam

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Pervious concrete is a form of lightweight porous concrete, obtained by eliminating the fine aggregate from the normal concrete mix. The advantages of this type of concrete are lower density, lower cost due to lower cement content, lower thermal conductivity, relatively low drying shrinkage, no segregation and capillary movement of water. In this paper an investigation is made on the mechanical response of the pervious concrete at zero fine level (zero fine concrete) made with local brick aggregate. Effect of aggregate size variation on the strength, void ratio and permeability of the zero fine concrete is studied. Finally, a comparison is also presented between the stone aggregate made pervious concrete and brick aggregate made pervious concrete. In total 75 concrete cylinder were tested for compressive strength, 15 cylinder were tested for void ratio and 15 cylinder were tested for permeability test. Mix proportion (cement: Coarse aggregate) was kept fixed at 1:6 (by weights), where water cement ratio was valued 0.35 for preparing the sample specimens. The brick aggregate size varied among 25mm, 19mm, 12mm. It has been found that the compressive strength decreased with the increment of aggregate size but permeability increases and concrete made with 19mm maximum aggregate size yields the optimum value. No significant differences on the strength and permeability test are observed between the brick aggregate made zero fine concrete and stone aggregate made zero fine concrete.

Keywords: pervious concrete, brick aggregate concrete, zero fine concrete, permeability, porosity

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Authors: Popoola M. Oyenola

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Concrete plays the important role and a huge percentage of concrete is being utilized in every construction practices. Natural river sand is one of the major ingredients of concrete, is becoming expensive due to excessive cost of accessibility from sources. Also large scale depletion of sources creates environmental problems. Therefore, there is a need of economic alternative materials. Quarry dust is a waste obtained during quarrying process. It has been rampantly used in different construction practices and could be used as an effective fine aggregate instead of river sand. Partial and total replacement of fine aggregate in conventional concrete with quarry dust has been empirically conducted with the view to examining primarily the compressive strength of the resulting composite and possible total utilization of quarry dust as fine aggregate in the production of medium grade concrete. The results of the study showed that its specific gravity, porosity and water absorption showed satisfactory performance. The percentage replacement of natural river sand with quarry dust for a designed strength of 25N/mm2 varied at intervals of 10% up to a maximum value of 100%. A total of 132 cubes of 150 x 150 x 150mm were cast and tested at 7, 14 and 28 days of hydration. Compressive strength increases with curing age in all the mixes. Compressive strength decreases with increase in percentage of quarry dust. Generally the compressive strength of concrete incorporating quarry dust attained strength of 22.47 N/mm2 after 28 days which makes it a suitable aggregate for the production medium grade concrete.

Keywords: quarry dust, concrete, aggregates, compressive strength

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Authors: Seemal Mazhar Khan, Tahira Mubashar

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The present research aimed to investigate the relationship in perceived organizational justice, organizational trust and employee engagement in bank employees. It was hypothesized: there is likely to be a relationship in perceived organizational justices, organizational trust and employee engagement; perceived organizational justice and organizational trust are likely to predict employee engagement; there is likely to be effect of bank type and designation on perceived organizational justice, organizational trust and employee engagement. The sample consisted of 150 bank employees (50 from government, 50 from private and 50 from privatized banks) selected from different banks in Lahore, Pakistan. Correlational research design was used to conduct this study. Perceived Organizational Justices Questionnaire, Organizational Trust Questionnaire and Employee Engagement Scale were used for assessment. Pearson product moment correlation, hierarchical regression and multivariate analysis of covariance were applied. Results showed a positive significant relationship in perceived organizational justice and organizational engagement and there were also a positive significant relation between organizational trust and job and organizational engagement. Results showed that organizational trust predicts organizational engagement after controlling the effect of age, marital status and socio-economic status and there is a significant interaction effect of bank type and designation level on organizational trust in bank employees. The findings of the research can serve as a platform for the awareness of important antecedents of employee engagement and organizations can inculcate trust for better and improved engagement of its employees, thereby, enhancing the productivity of their employees.

Keywords: bank employees, organizational engagement, perceived organizational justice, trust

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Authors: S. A. Agbalajobi, W. A. Bello

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This study examines rock properties of crushed aggregate in some selected quarries in Kwara state, Nigeria. Some physical properties (chemical composition, mineral composition, particle size distribution) of gneiss sample were determined using ISRM standards. The physicomechanical properties (specific gravity, dry density, porosity, water absorption, point load index, tensile, and compressive strength) of the gneiss rock were evaluated. The analysis on the gneiss samples revealed the mean dry density and the unit weight are 2.52 g/m3, 2.63 g/m3, 2.38 g/m3; and 24.1 kN/m3, 25.78 kN/m3, 23.33 kN/m3, respectively (for locations A,B,C). The water absorption level of the gneiss rock sample ranged from 0.38 % – 0.57 % for the three locations. The mean Schmidt hammer rebound value ranged from 51.0 – 52.4 for the three locations and mean point load index values ranged from 9.89 – 10.56 MPa classified as very high strength while the uniaxial compressive strength of the rock samples revealed that its strength ranged from 120 - 139 MPa (for location A, B, and C) classified as strong rock. The aggregate impact value test and aggregate crushing value test conducted on the gneiss aggregates from the three locations in accordance with British Standard. The gneiss sample from the three locations (A, B, and C) is a good material for the production of construction works such as concrete, bricks, pavement, embankment among others, the compressive strength of the material is within the accepted limit.

Keywords: gneiss, aggregate impact, aggregate crushing, physic-mechanical properties, rock hardness

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Authors: Di Wei, Xing Hu, Yangjun Chen, Baofeng Li, Hong Chen

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To achieve the research purpose of guiding the spatial morphology design of blocks through the indicators to obtain a good wind environment, it is necessary to find the most suitable type and value range of each urban spatial morphology indicator. At present, most of the relevant researches is based on the numerical simulation of the ideal block shape and rarely proposes the results based on the complex actual block types. Therefore, this paper firstly attempted to make theoretical speculation on the main factors influencing indicators' effectiveness by analyzing the physical significance and formulating the principle of each indicator. Then it was verified by the field wind environment measurement and statistical analysis, indicating that Porosity(P₀) can be used as an important indicator to guide the design of block wind environment in the case of deep street canyons, while Frontal Area Density (λF) can be used as a supplement in the case of shallow street canyons with no height difference. Finally, computational fluid dynamics (CFD) was used to quantify the impact of block height difference and street canyons depth on λF and P₀, finding the suitable type and value range of λF and P₀. This paper would provide a feasible wind environment index system for urban designers.

Keywords: urban spatial morphology indicator, urban microclimate, computational fluid dynamics, block ventilation, correlation analysis

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Authors: Hyunuk Kim, Yang No Yun, Muhammad Sohail, Jong-Ho Moon, Young Cheol Park

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Metal-organic frameworks (MOFs), which are emerging absorbents assembled from metal ions and organic ligands, have attracted attention for their permanent porosity and design of tunable pore size. These microporous materials showed interesting properties for CO₂ storage and separation. In particular, MOFs with high surface area and open metal sites showed the remarkable adsorption capacity and selectivity for CO₂. [Mg₂ (DOBDC)] (DOBDC = 2,5-dioxidobenzene-1,4-dicarboxylate) (MOF-74 or CPO-27) is a well-known absorbent showing an exceptionally high CO₂ sorption capacity at low partial pressure and room temperature. In this work, we synthesized [M₂(DOBDC)(DMF)₂] (M = Mg, Co, Ni) and determined their single-crystal structures by X-ray crystallography. The removal of coordinated guest molecules generates Lewis acidic sites and showed high CO₂ adsorption affinity. Both CO₂ adsorption capacity and surface area are much higher than reported values in literature. To fabricate MMMs, microcrystalline [M₂ (DOBDC)(DMF)₂] was synthesized by microwave reaction and dispersed in PDMS solution. The MMMs with a various amount of [M₂ (DOBDC)(DMF) ₂] in PDMS were fabricated by a solution casting method. [M₂ (DOBDC)(DMF)₂]@PDMS membrane showed higher CO2 permeability and CO₂/N₂ selectivity than those of PDMS. Therefore, we believe that MMMs combining polymer and MOFs provide new materials for CO₂ separation technology.

Keywords: metal-organic frameworks, mixed matrix membrane, CO2/N2 separation, polydimethylsiloxane (PDMS)

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Authors: Lei Zhang

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The carbon cycle greatly influences global change, and the land cover changes contribute to the status and rate of the carbon budget in ecosystems. This paper proposes a land cover classification system for mapping land cover, the national ecological environment assessment, and estimating carbon storage in ecosystems. The classification system consists of basic land cover classes at levels Ⅰ and Ⅱ and auxiliary features at level III. The basic 38 classes characterizing land cover features are derived from 19 criteria referring to composition, structure, pattern, phenology, etc. The basic classes reflect the status of carbon storage in ecosystems. The auxiliary classes at level III complement the attributes of higher levels by 9 criteria. The 5 environmental criteria of temperature, moisture, landform, aspect and slope mainly reflect the potential and intensity of carbon storage in ecosystems. The disturbance of vegetation succession caused by land use type influences the vegetation carbon budget. The other 3 vegetation cover criteria, growth period, and species characteristics further refine the vegetation types. The hierarchical structure of the land cover map (the classes of levels Ⅰ and Ⅱ) is independent of the products of level III, which is helpful for land cover product management and applications. The classification system has been adopted in the Chinese national land cover database for the carbon budget in ecosystems at a 30 m scale.

Keywords: classification system, land cover, ecosystem, carbon storage, object based

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Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

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Authors: Diana Gomez-Cano, J. C. Ochoa-Botero, Roberto Bernal Correa, Yhan Paul Arias

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To obtain high mechanical performance, the fresh conditions of a mortar are decisive. Measuring the absorption of aggregates used in mortar mixes is a fundamental requirement for proper design of the mixes prior to their placement in construction sites. In this sense, absorption is a determining factor in the design of a mix because it conditions the amount of water, which in turn affects the water/cement ratio and the final porosity of the mortar. Thus, this work focuses on the mechanical behavior of recycled mortars manufactured from moisture correction using the Thermogravimetric Balancing Halogen Light (TBHL) technique in comparison with the traditional ASTM C 128 International Standard method. The advantages of using the TBHL technique are favorable in terms of reduced consumption of resources such as materials, energy, and time. The results show that in contrast to the ASTM C 128 method, the TBHL alternative technique allows obtaining a higher precision in the absorption values of recycled aggregates, which is reflected not only in a more efficient process in terms of sustainability in the characterization of construction materials but also in an effect on the mechanical performance of recycled mortars.

Keywords: alternative raw materials, halogen light, recycled mortar, resources optimization, water absorption

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Authors: Meilee Shen

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Buddhist nuns in Taiwan have shouldered various responsibilities in educational, cultural, economic, and social aspects that transforms and transcends Chinese Buddhism to a higher level in Taiwan and overseas. In the recent years, Nuns in Taiwan have formed various associations to reach their goals and satisfy their needs. This research will focus on the following: 1. How to distinguish a Buddhist organization from temple? 2. Whether the forming of female Buddhist organizations reveals religious purpose or gender conflict in Buddhism? 3. How can nuns in Taiwan be unified together to establish their identification? This paper will mainly study on the Chinese Buddhist Bhikkhuni Association (CBBA) because they have gained allies together to work for religious causes and social needs since 1996. However, with a mission to promote female practitioners’ role in Buddhist circle, CBBA did not contribute much to the gender issue in Buddhism. The research found that CBBA did not achieve their goal to unite nuns in Taiwan because they failed to support nuns' education and did not recruit young and highly educated ones as CBBA's faculties. In conclusion, the research suggests i) to connect with other Buddhist organizations in order to achieve the dream of unity, ii) to fill the generation gap by overturn hierarchical system in Buddhist community and create a new environment for new generation to grow, iii) to shift financial contribution from social charity to nuns’ education to promote female role in Buddhism in the future.

Keywords: Bhikkhuni in Taiwan, Bhikkhuni population and education, Buddhism in Taiwan, Chinese Buddhist Bhikkhuni Association

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Authors: Strahinja Kovačević, Lidija Jevrić, Miloš Kuzmanović, Sanja Podunavac-Kuzmanović

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In this paper, various derivatives of benzimidazole have been evaluated against Gram-negative bacteria Escherichia coli. For all investigated compounds the minimum inhibitory concentration (MIC) was determined. Quantitative structure-activity relationships (QSAR) attempts to find consistent relationships between the variations in the values of molecular properties and the biological activity for a series of compounds so that these rules can be used to evaluate new chemical entities. The correlation between MIC and some absorption, distribution, metabolism and excretion (ADME) parameters was investigated, and the mathematical models for predicting the antibacterial activity of this class of compounds were developed. The quality of the multiple linear regression (MLR) models was validated by the leave-one-out (LOO) technique, as well as by the calculation of the statistical parameters for the developed models and the results are discussed on the basis of the statistical data. The results of this study indicate that ADME parameters have a significant effect on the antibacterial activity of this class of compounds. Principal component analysis (PCA) and agglomerative hierarchical clustering algorithms (HCA) confirmed that the investigated molecules can be classified into groups on the basis of the ADME parameters: Madin-Darby Canine Kidney cell permeability (MDCK), Plasma protein binding (PPB%), human intestinal absorption (HIA%) and human colon carcinoma cell permeability (Caco-2).

Keywords: benzimidazoles, QSAR, ADME, in silico

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Authors: Jonathan Galvan-Colin, Ariel Valladares, Renela Valladares, Alexander Valladares

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Both porous materials and bulk metallic glasses have been studied due to their potential applications and their exceptional physical and chemical properties. However, each material presents certain drawbacks which have been thought to be overcome by generating bulk metallic glass foams (BMGF). Although some experimental reports have been performed on multicomponent BMGF, still no ab initio works have been published, as far as we know. We present an approach based on the expanding lattice (EL) method to generate binary amorphous nanoporous Cu64Zr36. Starting from two different configurations: a 108-atom crystalline cubic supercell (cCu64Zr36) and a 108-atom amorphous supercell (aCu64Zr36), both with an initial density of 8.06 g/cm3, we applied EL method to halve the density and to get 50% of porosity. After the lattice expansion the supercells were subject to ab initio molecular dynamics for 500 steps at constant room temperature. Then, the samples were geometry-optimized and characterized with the pair and radial distribution functions, bond-angle distributions and a coordination number analysis. We found that pores appeared along specific spatial directions different from one to another and that they differed in size and form as well, which we think is related to the initial structure. Due to the lack of experimental counterparts our results should be considered predictive and further studies are needed in order to handle a larger number of atoms and its implication on pore topology.

Keywords: ab initio molecular dynamics, bulk mettalic glass, porous alloy

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Authors: Dhara Adhnandya Kumara, Novrizal Novrizal

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Hot Dry Rock (HDR) is one of geothermal energy which is abundant in many provinces in Indonesia. Heat exploitation from HDR would need a method which injects fluid to subsurface to crack the rock and sweep the heat. Water is commonly used as the working fluid but known to be less effective in some ways. The new research found out that Supercritical CO2 (SCCO2) can be used to replace water as the working fluid. By studying heat transfer efficiency, pumping power, and characteristics of the returning fluid, we might decide how effective SCCO2 to replace water as working fluid. The method used to study those parameters quantitatively could be obtained from pre-existing researches which observe the returning fluids from the same reservoir with same pumping power. The result shows that SCCO2 works better than water. For cold and hot SCCO2 has lower density difference than water, this results in higher buoyancy in the system that allows the fluid to circulate with lower pumping power. Besides, lower viscosity of SCCO2 impacts in higher flow rate in circulation. The interaction between SCCO2 and minerals in reservoir could induce dehydration of the minerals and enhancement of rock porosity and permeability. While the dissolution and transportation of minerals by SCCO2 are unlikely to occur because of the nature of SCCO2 as poor solvent, and this will reduce the mineral scaling in the system. Under those conditions, using SCCO2 as working fluid for HDR extraction would give great advantages to advance geothermal energy in Indonesia.

Keywords: geothermal, supercritical CO2, injection fluid, hot dry rock

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Smita Singh

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The paper develops a critical framework to the hegemonic discourses resorted to by the dominant powers in the global security architecture. Within this framework, security is viewed as a discourse through which identities and threats are represented and produced to legitimize the security concerns of few at the cost of others. International security have long been driven and dominated by power relations. Since the end of the Cold War, the global transformations have triggered contestations to the idea of security at both theoretical and practical level. These widening and deepening of the concept of security have challenged the existing power hierarchies at the theoretical level but not altered the substance and actors defining it. When discourses are introduced into security studies, several critical questions erupt: how has power shaped security policies of the globe through language? How does one understand the meanings and impact of those discourses? Who decides the agenda, rules, players and outliers of the security? Language as a symbolic system and form of power is fluid and not fixed. Over the years the dominant Western powers, led by the United States of America have employed various discursive practices such as humanitarian intervention, responsibility to protect, non proliferation, human rights, war on terror and so on to reorient the constitution of identities and interests and hence the policies that need to be adopted for its actualization. These power relations are illustrated in this paper through the narratives used in the nonproliferation regime. The hierarchical security dynamics is a manifestation of the global power relations driven by many factors including discourses.

Keywords: hegemonic discourse, global security, non-proliferation regime, power politics

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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Authors: Karim Kheloufi, El Hachemi Amara

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In the present study, a three-dimensional transient numerical model was developed to study the temperature field and cutting kerf shape during laser fusion cutting. The finite volume model has been constructed, based on the Navier–Stokes equations and energy conservation equation for the description of momentum and heat transport phenomena, and the Volume of Fluid (VOF) method for free surface tracking. The Fresnel absorption model is used to handle the absorption of the incident wave by the surface of the liquid metal and the enthalpy-porosity technique is employed to account for the latent heat during melting and solidification of the material. To model the physical phenomena occurring at the liquid film/gas interface, including momentum/heat transfer, a new approach is proposed which consists of treating friction force, pressure force applied by the gas jet and the heat absorbed by the cutting front surface as source terms incorporated into the governing equations. All these physics are coupled and solved simultaneously in Fluent CFD®. The main objective of using a transient phase change model in the current case is to simulate the dynamics and geometry of a growing laser-cutting generated kerf until it becomes fully developed. The model is used to investigate the effect of some process parameters on temperature fields and the formed kerf geometry.

Keywords: laser cutting, numerical simulation, heat transfer, fluid flow

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Authors: Abhimanyu Pati, Krishna Kumar Veluri

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The paper intends to bring out a real life experience encountered during actual implementation of a large scale Tier-1 Enterprise Resource Planning (ERP) system in a multi-location, discrete manufacturing organization in India, involved in manufacturing of auto components and aggregates. The business complexities, prior to the implementation of ERP, include multi-product with hierarchical product structures, geographically distributed multiple plant locations with disparate business practices, lack of inter-plant broadband connectivity, existence of disparate legacy applications for different business functions, and non-standardized codifications of products, machines, employees, and accounts apart from others. On the other hand, the manufacturing environment consisted of processes like Assemble-to-Order (ATO), Make-to-Stock (MTS), and Engineer-to-Order (ETO) with a mix of discrete and process operations. The paper has highlighted various business plan areas and concerns, prior to the implementation, with specific focus on strategic issues and objectives. Subsequently, it has dealt with the complete process of ERP implementation, starting from strategic planning, project planning, resource mobilization, and finally, the program execution. The step-by-step process provides a very good learning opportunity about the implementation methodology. At the end, various organizational challenges and lessons emerged, which will act as guidelines and checklist for organizations to successfully align and implement ERP and achieve their business objectives.

Keywords: ERP, ATO, MTS, ETO, discrete manufacturing, strategic planning

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Authors: Elham Zabetian Targhi, Niusha Fardnava, Saba Saghafi

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Urban resilience to Corona Virus has become a major concern for cities these days. Our country also has not been safe from the destructive effects of this virus in social, economic, physical, governance, and management dimensions; and according to official statistics, hundreds of thousands of people in Iran have been infected with this virus and tens of thousands have died so far. Therefore, to measure urban resilience to this pandemic, some criteria and sub-criteria were developed based on the authors’ documentary and field studies, and their significance or weights were determined using analytical-comparative research method using a questionnaire of paired or L-Saati comparisons from the viewpoint of experts in urban sciences and urban development using AHP hierarchical analysis in EXPERT CHOICE software. Then, designing a questionnaire with a five-point Likert scale, the satisfaction of Tehran residents with the extracted criteria and sub-criteria was measured and the correlation between the important criteria in each dimension was assessed using correlation tests in SPSS16 software. According to the obtained results of AHP analysis and the scores of each sub-criterion, the weight of all criteria was normal. In the next stage, according to the pairwise correlation tests between the important criteria in each dimension from the viewpoint of urban science experts and Tehran residents, it was concluded that the reliability of the correlation between the criteria is 99%. In all the cases, the P-value or the same significance level was less than 0.05, which indicated the significance of the pairwise relations between the variables.

Keywords: Urban Resilience, Pandemics, Corona Virus (Covid-19), Criteria.

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Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

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The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structure-process-property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: biosensor, DNA, biomarker, molecular dynamics simulation

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Authors: Taysir Soliman

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One of the current popular clustering techniques is Spectral Clustering (SC) because of its advantages over conventional approaches such as hierarchical clustering, k-means, etc. and other techniques as well. However, one of the disadvantages of SC is the time consuming process because it requires computing the eigenvectors. In the past to overcome this disadvantage, a number of attempts have been proposed such as the Power Iteration Clustering (PIC) technique, which is one of versions from SC; some of PIC advantages are: 1) its scalability and efficiency, 2) finding one pseudo-eigenvectors instead of computing eigenvectors, and 3) linear combination of the eigenvectors in linear time. However, its worst disadvantage is an inter-class collision problem because it used only one pseudo-eigenvectors which is not enough. Previous researchers developed Deflation-based Power Iteration Clustering (DPIC) to overcome problems of PIC technique on inter-class collision with the same efficiency of PIC. In this paper, we developed Parallel DPIC (PDPIC) to improve the time and memory complexity which is run on apache spark framework using sparse matrix. To test the performance of PDPIC, we compared it to SC, ESCG, ESCALG algorithms on four small graph benchmark datasets and nine large graph benchmark datasets, where PDPIC proved higher accuracy and better time consuming than other compared algorithms.

Keywords: spectral clustering, power iteration clustering, deflation-based power iteration clustering, Apache spark, large graph

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

Procedia PDF Downloads 218