Search results for: powder fine recycled aggregate
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2562

Search results for: powder fine recycled aggregate

1002 Texture Characteristics and Depositional Environment of the Lower Mahi River Sediment, Mainland Gujarat, India

Authors: Shazi Farooqui, Anupam Sharma

Abstract:

The Mahi River (~600km long) is an important west flowing the river of Central India. It originates in Madhya Pradesh and starts flowing in NW direction and enters into the state of Rajasthan. It flows across southern Rajasthan and then enters into Gujarat and finally debouches in the Gulf of Cambay. In Gujarat state, it flows through all four geomorphic zones i.e. eastern upland zone, shallow buried piedmont zone, alluvial zone and coastal zone. In lower reaches and particularly when it is flowing under the coastal regime, it provides an opportunity to study – 1. Land–Sea interaction and role of relative sea level changes, 2. Coastal/estuarine geological process, 3. Landscape evolution in marginal areas and so on. The Late Quaternary deposits of Mainland Gujarat is appreciably studied by Chamyal and his group of MS University of Baroda, and they have established that the 30-35m thick sediment package of the Mainland Gujarat is comprised of marine, fluvial and aeolian sediments. It is also established that in the estuarine zone, the upper few meter thick sediments package is of marine nature. However, its thickness, characters and the depositional environment including the role of climate and tectonics is still not clearly defined. To understand few aspects of the above mentioned, in the present study, a 17m subsurface sediment core has been retrieved from the estuarine zone of Mahi river basin. The Multiproxy studies which include the textural analysis (grain size), Loss on ignition (LOI), Bulk and clay mineralogy and geochemical studies have been carried out. In the entire sedimentary sequence, the grain size largely varies from coarse sand to clay; however, a solitary gravel bed is also noticed. The lower part (depth 9-17m), is mainly comprised of sub equal proportion of sand and silt. The sediments mainly have bimodal and leptokurtic distribution and deposited in alternate sand-silt package, probably indicating flood deposits. Relatively low moisture (1.8%) and organic carbon (2.4%) with increased carbonate values (12%) indicate that conditions must have to remain oxidizing. The middle part (depth 9–6m) has a 1m thick gravel bed at the bottom and overlain by coarse sand to very fine sand showing fining upward sequence. The presence of gravel bed suggests some kind of tectonic activity resulting into change in base level or enhanced precipitation in the catchment region. The upper part (depth 6–0m; top part of sequence) mainly comprised of fine sand to silt size grains (with appreciable clay content). The sediment of this part is Unimodal and very leptokurtic in nature suggesting wave and winnowing process and deposited in low energy suspension environment. This part has relatively high moisture (2.1%) and organic carbon (2.7%) with decreased carbonate content (4.2%) indicating change in the depositional environment probably under estuarine conditions. The presence of chlorite along with smectite clay mineral further supports the significant marine contribution in the formation of upper part of the sequence.

Keywords: grain size, statistical analysis, clay minerals, late quaternary, LOI

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1001 Hyperspectral Data Classification Algorithm Based on the Deep Belief and Self-Organizing Neural Network

Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

Abstract:

In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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1000 Anti-Obesity Effect of Cordyceps militaris Fermented Black Rice

Authors: Chih-Hung Liang, Jung-Jung Chen, Shen-Shih Chiang

Abstract:

Obesity is defined as abnormal or excessive fat accumulation that presents a risk to health, which are major risk factors for a number of chronic diseases, including diabetes, cardiovascular diseases and cancer. Cordyceps militaris (CM) is a well-known traditional medicine in Asian countries and a rich source of biologically active components. Black rice (Oryza sativa L.) is a special cultivar of rice that contains rich anthocyanins and regarded as a health-promoting food in China and other Eastern. The aim of this study was to investigate the anti-obesity effect of Cordyceps militaris fermented black rice (CB) on HFD-induced BALB/c mice model. The results indicated that administration of low and high dosage of CB powder significantly reduced the body weights (7.38% and 7.78%), body fat ratio (2.37% and 2.78%), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels compared to the HF group (p<0.05). Histopathological analysis showed that the score of fatty liver in HF group (5.0) was significantly higher than CB groups (2.1 and 3.6) (p<0.05). In conclusion, Cordyceps militaris fermented black rice can reduce the body weight via inhibition of the fat accumulation in liver and body and possess the anti-obesity potency.

Keywords: Cordyceps militaris, black rice, obesity, HFD-induced mice

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999 An Intelligent Search and Retrieval System for Mining Clinical Data Repositories Based on Computational Imaging Markers and Genomic Expression Signatures for Investigative Research and Decision Support

Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

Abstract:

The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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998 Carbon Nitride Growth on ZnO Architectures for Enhanced Photoelectrochemical Water Splitting Application

Authors: Špela Hajduk, Sean P. Berglund, Matejka Podlogar, Goran Dražić, Fatwa F. Abdi, Zorica C. Orel, Menny Shalom

Abstract:

Graphitic carbon nitride materials (g-CN) have emerged as an attractive photocatalyst and electrocatalyst for photo and electrochemical water splitting reaction, due to their environmental benignity nature and suitable band gap. Many approaches were introduced to enhance the photoactivity and electronic properties of g-CN and resulted in significant changes in the electronic and catalytic properties. Here we demonstrate the synthesis of thin and homogenous g-CN layer on highly ordered ZnO nanowire (NW) substrate by growing a seeding layer of small supramolecular assemblies on the nanowires. The new synthetic approach leads to the formation of thin g-CN layer (~3 nm) without blocking all structure. Two different deposition methods of carbon nitride were investigated and will be presented. The amount of loaded carbon nitride significantly influences the PEC activity of hybrid material and all the ZnO/g-CNx electrodes show great improvement in photoactivity. The chemical structure, morphology and optical properties of the deposited g-CN were fully characterized by various techniques as X-ray powder spectroscopy (XRD), scanning electron microscopy (SEM), focused ion beam scanning electron microscopy (FIB-SEM), high-resolution scanning microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS).

Keywords: carbon nitride, photoanode, solar water splitting, zinc oxide

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997 Forecasting Container Throughput: Using Aggregate or Terminal-Specific Data?

Authors: Gu Pang, Bartosz Gebka

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We forecast the demand of total container throughput at the Indonesia’s largest seaport, Tanjung Priok Port. We propose four univariate forecasting models, including SARIMA, the additive Seasonal Holt-Winters, the multiplicative Seasonal Holt-Winters and the Vector Error Correction Model. Our aim is to provide insights into whether forecasting the total container throughput obtained by historical aggregated port throughput time series is superior to the forecasts of the total throughput obtained by summing up the best individual terminal forecasts. We test the monthly port/individual terminal container throughput time series between 2003 and 2013. The performance of forecasting models is evaluated based on Mean Absolute Error and Root Mean Squared Error. Our results show that the multiplicative Seasonal Holt-Winters model produces the most accurate forecasts of total container throughput, whereas SARIMA generates the worst in-sample model fit. The Vector Error Correction Model provides the best model fits and forecasts for individual terminals. Our results report that the total container throughput forecasts based on modelling the total throughput time series are consistently better than those obtained by combining those forecasts generated by terminal-specific models. The forecasts of total throughput until the end of 2018 provide an essential insight into the strategic decision-making on the expansion of port's capacity and construction of new container terminals at Tanjung Priok Port.

Keywords: SARIMA, Seasonal Holt-Winters, Vector Error Correction Model, container throughput

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996 Effect of Mannitol on in Vitro Conservation of Local and Exotic Taro-Genotypes (Colocasia Esculenta Var Esculenta)

Authors: Benjamin Bonsu Bruce, Marian Dorcas Quain David Appiah-Kubi, Gertrude Osei-Diko, Harrison Kwame Dapaah

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Taro [Colocasia esculenta (L.) Schott] is a major staple food and remains a significant crop to many cultural and agricultural customs worldwide. In Ghana, taro is mostly propagated using vegetative material, which is conserved in field collection and recycled from their farms to establish new fields. However, this practice promotes the accumulation of systemic pathogens. Prior exposure to pests and subsequent expression of disease symptoms can also be a huge constraint to sustainable conservation and utilization of taro genetic resources. In vitro, slow growth is one of the most promising techniques to be utilized for conservation. The objective of this study was to find a medium-term in vitro conservation protocol for local and exotic taro genotypes. The medium-term conservation study was conducted using actively growing shoots obtained from in vitro cultures. Explants were cultured to full strength in complete Murashige and Skoog medium supplemented with Mannitol at different concentrations (0g/l, 20g/l, 25g/l, and 30g/l). Another medium that was tested as an additional treatment is the White’s medium. The highest number of shoots (6.33) and leaves (22.67) occurred on medium containing 20 and 25g/l mannitol in genotype SAO 006 as compared to other genotypes, whereas 30g/l mannitol was the best to restrict growth for the entire 6 months period in terms of shoot height (22.50cm). The study reveals that mannitol supplemented culture media could reduce the growth of Colocasia plantlets, especially in stem height. Culture growth following 6 months of conservation, showed that healthy shoot cultures of Taro were obtained after 6 months of storage in a medium containing 20gl⁻¹ and 25gl⁻¹ mannitol.

Keywords: complete murashige, skoog medium, culture conditions, mannitol, slow growth conservation

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995 Hate Speech Detection in Tunisian Dialect

Authors: Helmi Baazaoui, Mounir Zrigui

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This study addresses the challenge of hate speech detection in Tunisian Arabic text, a critical issue for online safety and moderation. Leveraging the strengths of the AraBERT model, we fine-tuned and evaluated its performance against the Bi-LSTM model across four distinct datasets: T-HSAB, TNHS, TUNIZI-Dataset, and a newly compiled dataset with diverse labels such as Offensive Language, Racism, and Religious Intolerance. Our experimental results demonstrate that AraBERT significantly outperforms Bi-LSTM in terms of Recall, Precision, F1-Score, and Accuracy across all datasets. The findings underline the robustness of AraBERT in capturing the nuanced features of Tunisian Arabic and its superior capability in classification tasks. This research not only advances the technology for hate speech detection but also provides practical implications for social media moderation and policy-making in Tunisia. Future work will focus on expanding the datasets and exploring more sophisticated architectures to further enhance detection accuracy, thus promoting safer online interactions.

Keywords: hate speech detection, Tunisian Arabic, AraBERT, Bi-LSTM, Gemini annotation tool, social media moderation

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994 Chemopreventive Potency of Medicinal and Eatable Plant, Gromwell Seed on in Vitro and in Vivo Carcinogenesis Systems

Authors: Harukuni Tokuda, Xu FengHao, Nobutaka Suzuki

Abstract:

As part of an ongoing our projects to investigate the anti-tumor promoring properties (chemopreventive potency) of Gromwell seed, dry powder materials and its active compounds were carried out through useful test systems. Gromwell seed (Coix lachryma-jobi seed) (GS) is a grass crop that has long been used and played a role in traditional medicine as a nourishing food, and for the treatment of various aliments, paticularly cancer. The application of a new screening procedure which utilizes the synergistic effect of short-chain fatty acids and phorbol esters in enable rapid and easy detection of naturally occurring substances(anti-tumor promoters chemo-preventive agents) with inhibition of Epstein-Barr virus(EBV) activation, using human lymphblastoid cells. In addition, we have now extended these investigations to a new tumorigenesis model in which we initiated the tumors with DMBA intiation and promoted with 1.7 nmol of TPA in two-stage mouse skin test and other models. these results provide a basis for further development of these botanical supplements for human cancer chemoprevention and observations seem that this materials more extensively as one of the trials for the purpose of complementary and alternative medicine.

Keywords: chemoprevention, medicinal plant, mouse, carcinogenesis systems

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993 Study of Nanocrystalline Al Doped Zns Thin Films by Chemical Bath Deposition Method

Authors: Hamid Merzouk, Djahida Touati-Talantikite, Amina Zaabar

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New nanosized materials are in huge expansion worldwide. They play a fundamental role in various industrial applications thanks their unique and functional properties. Moreover, in recent years, a great effort has been made to the design and control fabrication of nanostructured semiconductors such zinc sulphide. In recent years, much attention has been accorded in doped and co-doped ZnS to improve the ZnS films quality. We present in this work the preparation and characterization of ZnS and Al doped ZnS thin films. Nanoparticles ZnS and Al doped ZnS films are prepared by chemical bath deposition method (CBD), for various dopant concentrations. Thin films are deposed onto commercial microscope glass slides substrates. Thiourea is used as sulfide ion source, zinc acetate as zinc ion source and manganese acetate as manganese ion source in alkaline bath at 90 °C. X-ray diffraction (XRD) analyses are carried out at room temperature on films and powders with a powder diffractometer, using CuKα radiation. The average grain size obtained from the Debye–Scherrer’s formula is around 10 nm. Films morphology is examined by scanning electron microscopy. IR spectra of representative sample are recorded with the FTIR between 400 and 4000 cm-1.The transmittance (70 %) is performed with the UV–VIS spectrometer in the wavelength range 200–800 nm. This value is enhanced by Al doping.

Keywords: ZnS, nanostructured semiconductors, thin films, chemical bath deposition

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992 Bioproduction of Indirubin from Fermentation and Renewable Sugars Through Genomic and Metabolomic Engineering of a Bacterial Strain

Authors: Vijay H. Ingole, Efthimia Lioliou

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Indirubin, a key bioactive component of traditional Chinese medicine, has gained increasing recognition for its potential in modern biomedical applications, particularly in pharmacology and therapeutics. The present work aimed to harness the potential by engineering an Escherichia coli strain capable of high-yield indirubin production. Through meticulous genetic engineering, we optimized the metabolic pathways in E. coli to enhance indirubin synthesis. Further, to explored the optimization of culture media and indirubin yield via batch and fed-batch fermentation techniques. By fine-tuning upstream process (USP) parameters, including nutrient composition, pH, temperature, and aeration, we established conditions that maximized both cell growth and indirubin production. Additionally, significant efforts were dedicated to refining downstream process (DSP) conditions for the extraction, purification, and quantification of indirubin. Utilizing advanced biochemical methods and analytical techniques such as UHPLC, we ensured the production of high purity indirubin. This approach not only improved the economic viability of indirubin bioproduction but also aligned with the principles of green production and sustainability.

Keywords: indirubin, bacterial strain, fermentation, HPLC

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991 Evaluation of Modified Asphalt Mixture with Hospital Spun-Bond Waste for Enhanced Crack Resistance

Authors: Ziba Talaeizadeh, Taghi Ebadi

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Hospitals and medical centers generate a wide array of infectious waste on a daily basis, leading to pressing environmental concerns associated with proper disposal. Disposable plastic items and spun-bond clothing, commonly made from polypropylene, pose a significant risk of disease transmission, necessitating specialized waste management strategies. Incorporating these materials into bituminous asphalt production offers a potential solution, as it can modify asphalt mixtures and reduce susceptibility to cracking. This study aims to assess the crack resistance of asphalt mixtures modified with hospital spun-bond waste. Asphalt mixtures were prepared using the Marshall method, with spun-bond waste added in varying proportions (5% to 20%). The Semi-Circular Bending (SCB) test was conducted to evaluate asphalt fracture behavior under Mode I loading at controlled speeds of 5, 20, and 50 millimeters per minute and an average temperature of 25°C. Parameters such as fracture energy (FE) and Crack Resistance Index (CRI) were quantified. The results indicate that the addition of 10% to 15% spun-bond polypropylene polymer enhances the performance of the modified mixture, resulting in an 18% increase in fracture energy and an 11% reduction in cracking stiffness compared to the control sample. Further investigations involving factors like compaction level, bitumen type, and aggregate grading are recommended to address medical waste management and mitigate asphalt pavement cracking issues.

Keywords: asphalt cracking, hospital waste, semi-circular bending test, spun-bond

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990 Cocrystals of Etodolac: A Crystal Engineering Approach with an Endeavor to Enhance Its Biopharmaceutical Assets

Authors: Sakshi Tomar, Renu Chadha

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Cocrystallization comprises a selective route to the intensive design of pharmaceutical products with desired physiochemical and pharmacokinetic properties. The present study is focused on the preparation, characterization, and evaluation of etodolac (ET) co-crystals with coformers nicotinamide (ETNI) and Glutaric acid (ETGA), using cocrystallization approach. Preliminarily examination of the prepared co-crystal was done by differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FT-IR), powder X-ray diffraction (PXRD). DSC thermographs of ETNI and ETGA cocrystals showed single sharp melting endotherms at 144°C and 135°C, respectively, which were different from the melting of drugs and coformers. FT-IR study points towards carbonyl-acid interaction sandwiched between the involving molecules. The emergence of new peaks in the PXRD pattern confirms the formation of new crystalline solid forms. Both the cocrystals exhibited better apparent solubility, and 3.8-5.0 folds increase in IDR were established, as compared to pure etodolac. Evaluations of these solid forms were done using anti-osteoarthritic activities. All the results indicate that etodolac cocrystals possess better anti-osteoarthritic efficacy than free drug. Thus loom of cocrystallization has been found to be a viable approach to resolve the solubility and bioavailability issues that circumvent the use of potential antiosteoarthritic molecules.

Keywords: bioavailability, etodolac, nicotinamide, osteoarthritis

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989 Experimental and Theoretical Approach, Hirshfeld Surface, Reduced Density Gradient, Molecular Docking of a Thiourea Derivative

Authors: Noureddine Benharkat, Abdelkader Chouaih, Nourdine Boukabcha

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A thiourea derivative compound was synthesized and subjected to structural analysis using single-crystal X-ray diffraction (XRD). The crystallographic data unveiled its crystallization in the P21/c space group within the monoclinic system. Examination of the dihedral angles indicated a notable non-planar structure. To support and interpret these resulats, density functional theory (DFT) calculations were conducted utilizing the B3LYP functional along with a 6–311 G (d, p) basis set. Additionally, to assess the contribution of intermolecular interactions, Hirshfeld surface analysis and 2D fingerprint plots were employed. Various types of interactions, whether weak intramolecular or intermolecular, within a molecule can significantly impact its stability. The distinctive signature of non-covalent interactions can be detected solely through electron density analysis. The NCI-RDG analysis was employed to investigate both repulsive and attractive van der Waals interactions while also calculating the energies associated with intermolecular interactions and their characteristics. Additionally, a molecular docking study was studied to explain the structure-activity relationship, revealing that the title compound exhibited an affinity energy of -6.8 kcal/mol when docked with B-DNA (1BNA).

Keywords: computational chemistry, density functional theory, crystallography, molecular docking, molecular structure, powder x-ray diffraction, single crystal x-ray diffraction

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988 Effectiveness of Jackfruit Seed Starch as Coagulant Aid in Landfill Leachate Treatment

Authors: Mohd Suffian Yusoff, Noor Aina Mohamad Zuki, Mohd Faiz Muaz Ahmad Zamri

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Currently, aluminium sulphate (alum), ferric chloride and polyaluminium chloride (PAC) are the most common coagulants being used for leachate coagulation-flocculation treatment. However, the impact of these residual’s coagulants have sparked huge concern ceaselessly. Therefore, development of natural coagulant as an alternative coagulant for treatment process has been given full attentions. In this attempt jackfruit seed starch (JSS) was produce by extraction method. The removal efficiency was determined using jar test method. The removal of organic matter and ammonia were compared between JSS used in powder form and diluted form in leachate. The yield of starch from the extraction method was 33.17 % with light brown in colour. The removal of turbidity was the highest at pH 8 for both diluted and powdered JSS with 38% and 8.7% of removal. While for colour removal the diluted JSS showed 18.19% of removal compared to powdered JSS. The diluted JSS also showed the highest removal of suspended solid with 3.5% compared to powdered JSS with 2.8%. Instead of coagulant, JSS as coagulant aid has succeed to reduce the dosage of PAC from 900 mg/L to 528 mg/L by maintaining colour and turbidity removal up to 94% and 92 % respectively. The JSS coagulant also has decreased the negative charge of the leachate nearly to the neutral charge (0.209 mv). The result proved that JSS was more effective to be used as coagulant aid landfill leachate treatment.

Keywords: landfill leachate, natural coagulant, jackfruit seed starch, coagulant

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987 Modelling and Optimisation of Floating Drum Biogas Reactor

Authors: L. Rakesh, T. Y. Heblekar

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This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

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986 Mineralogy and Thermobarometry of Xenoliths in Basalt from the Chanthaburi-Trat Gem Fields, Thailand

Authors: Apichet Boonsoong

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In the Chanthaburi-Trat basalts, xenoliths are composed of essentially ultramafic xenoliths (particularly spinel lherzolite) with a few of an aggregate of feldspar. Some 19 ultramafic xenoliths were collected from 13 different locations. They range in size from 3.5 to 60mm across. Most are weathered and oxidized on the surface but fresh samples are obtained from cut surfaces. Chemical analyses were performed on carbon-coated polished thin sections using a fully automated CAMECA SX-50 electron microprobe (EMPA) in wavelength-dispersive mode. In thin section, they are seen to consist of variable amounts of olivine, clinopyroxene, orthopyroxene with minor spinel and plagioclase, and are classed as lherzolite. Modal compositions of the ultramafic nodules vary with olivine (60-75%), clinopyroxene (20-30%), orthopyroxene (0-15%), minor spinel (1-3%) and plagioclase (<1%). The essential minerals form an equigranular, medium- to coarse-grained, granoblastic texture, and all are in mutual contact indicating attainment of equilibrium. Reaction rims are common along the nodule margins and in some are also present along grain boundaries. Zoning occurs in clinopyroxene, and to a lesser extent in orthopyroxene. The homogeneity of mineral compositions in lherzolite xenoliths suggests the attainment of equilibrium. The equilibration temperatures of these xenoliths are estimated to be in the range of 973 to 1063°C. Pressure estimates are not so easily obtained because no suitable barometer exists for garnet-free lherzolites and so an indirect method was used. The general mineral assemblage of the lherzolite xenoliths and the absence of garnet indicate a pressure range of approximately 12–19kbar, which is equivalent to depths approximately of 38 to 60km.

Keywords: chanthaburi-trat basalts, spinel lherzolite, xenoliths, 973 to 1063°C, 38 to 60km

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985 Subjective Quality Assessment for Impaired Videos with Varying Spatial and Temporal Information

Authors: Muhammad Rehan Usman, Muhammad Arslan Usman, Soo Young Shin

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The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment.

Keywords: frame freezing, mean opinion score, objective assessment, subjective evaluation

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984 Study and Analysis of Permeable Articulated Concrete Blocks Pavement: With Reference to Indian Context

Authors: Shrikant Charhate, Gayatri Deshpande

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Permeable pavements have significant benefits like managing runoff, infiltration, and carrying traffic over conventional pavements in terms of sustainability and environmental impact. Some of the countries are using this technique, especially at locations where durability and other parameters are of importance in nature; however, sparse work has been done on this concept. In India, this is yet to be adopted. In this work, the progress in the characterization and development of Permeable Articulated Concrete Blocks (PACB) pavement design is described and discussed with reference to Indian conditions. The experimentation and in-depth analysis was carried out considering conditions like soil erosion, water logging, and dust which are significant challenges caused due to impermeability of pavement. Concrete blocks with size 16.5’’x 6.5’’x 7’’ consisting of arch shape (4’’) at beneath and ½” PVC holes for articulation were casted. These blocks were tested for flexural strength. The articulation process was done with nylon ropes forming series of concrete block system. The total spacing between the blocks was kept about 8 to 10% of total area. The hydraulic testing was carried out by placing the articulated blocks with the combination of layers of soil, geotextile, clean angular aggregate. This was done to see the percentage of seepage through the entire system. The experimental results showed that with the shape of concrete block the flexural strength achieved was beyond the permissible limit. Such blocks with the combination could be very useful innovation in Indian conditions and useful at various locations compared to the traditional blocks as an alternative for long term sustainability.

Keywords: connections, geotextile, permeable ACB, pavements, stone base

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983 Getting to Know the Types of Concrete and its Production Methods

Authors: Mokhtar Nikgoo

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Definition of Concrete and Concreting: Concrete (in French: Béton) in a broad sense is any substance or combination that consists of a sticky substance with the property of cementation. In general, concrete refers to concrete made by Portland cement, which is produced by mixing fine and coarse aggregates, Portland cement and water. After enough time, this mixture turns into a stone-like substance. During the hardening or processing of the concrete, cement is chemically combined with water to form strong crystals that bind the aggregates together, a process called hydration. During this process, significant heat is released called hydration heat. Additionally, concrete shrinks slightly, especially as excess water evaporates, a phenomenon known as drying shrinkage. The process of hardening and the gradual increase in concrete strength that occurs with it does not end suddenly unless it is artificially interrupted. Instead, it decreases more over long periods of time, although, in practical applications, concrete is usually set after 28 days and is considered at full design strength. Concrete may be made from different types of cement as well as pozzolans, furnace slag, additives, additives, polymers, fibers, etc. It may also be used in the way it is made, heating, water vapor, autoclave, vacuum, hydraulic pressures and various condensers.

Keywords: concrete, RCC, batching, cement, Pozzolan, mixing plan

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982 Convergence Analysis of a Gibbs Sampling Based Mix Design Optimization Approach for High Compressive Strength Pervious Concrete

Authors: Jiaqi Huang, Lu Jin

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Pervious concrete features with high water permeability rate. However, due to the lack of fine aggregates, the compressive strength is usually lower than other conventional concrete products. Optimization of pervious concrete mix design has long been recognized as an effective mechanism to achieve high compressive strength while maintaining desired permeability rate. In this paper, a Gibbs Sampling based algorithm is proposed to approximate the optimal mix design to achieve a high compressive strength of pervious concrete. We prove that the proposed algorithm efficiently converges to the set of global optimal solutions. The convergence rate and accuracy depend on a control parameter employed in the proposed algorithm. The simulation results show that, by using the proposed approach, the system converges to the optimal solution quickly and the derived optimal mix design achieves the maximum compressive strength while maintaining the desired permeability rate.

Keywords: convergence, Gibbs Sampling, high compressive strength, optimal mix design, pervious concrete

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981 Groupthink: The Dark Side of Team Cohesion

Authors: Farhad Eizakshiri

Abstract:

The potential for groupthink to explain the issues contributing to deterioration of decision-making ability within the unitary team and so to cause poor outcomes attracted a great deal of attention from a variety of disciplines, including psychology, social and organizational studies, political science, and others. Yet what remains unclear is how and why the team members’ strivings for unanimity and cohesion override their motivation to realistically appraise alternative courses of action. In this paper, the findings of a sequential explanatory mixed-methods research containing an experiment with thirty groups of three persons each and interviews with all experimental groups to investigate this issue is reported. The experiment sought to examine how individuals aggregate their views in order to reach a consensual group decision concerning the completion time of a task. The results indicated that groups made better estimates when they had no interaction between members in comparison with the situation that groups collectively agreed on time estimates. To understand the reasons, the qualitative data and informal observations collected during the task were analyzed through conversation analysis, thus leading to four reasons that caused teams to neglect divergent viewpoints and reduce the number of ideas being considered. Reasons found were the concurrence-seeking tendency, pressure on dissenters, self-censorship, and the illusion of invulnerability. It is suggested that understanding the dynamics behind the aforementioned reasons of groupthink will help project teams to avoid making premature group decisions by enhancing careful evaluation of available information and analysis of available decision alternatives and choices.

Keywords: groupthink, group decision, cohesiveness, project teams, mixed-methods research

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980 Preparation and Conductivity Measurements of LSM/YSZ Composite Solid Oxide Electrolysis Cell Anode Materials

Authors: Christian C. Vaso, Rinlee Butch M. Cervera

Abstract:

One of the most promising anode materials for solid oxide electrolysis cell (SOEC) application is the Sr-doped LaMnO3 (LSM) which is known to have a high electronic conductivity but low ionic conductivity. To increase the ionic conductivity or diffusion of ions through the anode, Yttria-stabilized Zirconia (YSZ), which has good ionic conductivity, is proposed to be combined with LSM to create a composite electrode and to obtain a high mixed ionic and electronic conducting anode. In this study, composite of lanthanum strontium manganite and YSZ oxide, La0.8Sr0.2MnO3/Zr0.92Y0.08O2 (LSM/YSZ), with different wt.% compositions of LSM and YSZ were synthesized using solid-state reaction. The obtained prepared composite samples of 60, 50, and 40 wt.% LSM with remaining wt.% of 40, 50, and 60, respectively for YSZ were fully characterized for its microstructure by using powder X-ray diffraction (XRD), Thermogravimetric analysis (TGA), Fourier transform infrared (FTIR), and Scanning electron microscope/Energy dispersive spectroscopy (SEM/EDS) analyses. Surface morphology of the samples via SEM analysis revealed a well-sintered and densified pure LSM, while a more porous composite sample of LSM/YSZ was obtained. Electrochemical impedance measurements at intermediate temperature range (500-700 °C) of the synthesized samples were also performed which revealed that the 50 wt.% LSM with 50 wt.% YSZ (L50Y50) sample showed the highest total conductivity of 8.27x10-1 S/cm at 600 oC with 0.22 eV activation energy.

Keywords: ceramics, microstructure, fuel cells, electrochemical impedance spectroscopy

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979 Malignancy Assessment of Brain Tumors Using Convolutional Neural Network

Authors: Chung-Ming Lo, Kevin Li-Chun Hsieh

Abstract:

The central nervous system in the World Health Organization defines grade 2, 3, 4 gliomas according to the aggressiveness. For brain tumors, using image examination would have a lower risk than biopsy. Besides, it is a challenge to extract relevant tissues from biopsy operation. Observing the whole tumor structure and composition can provide a more objective assessment. This study further proposed a computer-aided diagnosis (CAD) system based on a convolutional neural network to quantitatively evaluate a tumor's malignancy from brain magnetic resonance imaging. A total of 30 grade 2, 43 grade 3, and 57 grade 4 gliomas were collected in the experiment. Transferred parameters from AlexNet were fine-tuned to classify the target brain tumors and achieved an accuracy of 98% and an area under the receiver operating characteristics curve (Az) of 0.99. Without pre-trained features, only 61% of accuracy was obtained. The proposed convolutional neural network can accurately and efficiently classify grade 2, 3, and 4 gliomas. The promising accuracy can provide diagnostic suggestions to radiologists in the clinic.

Keywords: convolutional neural network, computer-aided diagnosis, glioblastoma, magnetic resonance imaging

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978 An Advanced Approach to Detect and Enumerate Soil-Transmitted Helminth Ova from Wastewater

Authors: Vivek B. Ravindran, Aravind Surapaneni, Rebecca Traub, Sarvesh K. Soni, Andrew S. Ball

Abstract:

Parasitic diseases have a devastating, long-term impact on human health and welfare. More than two billion people are infected with soil-transmitted helminths (STHs), including the roundworms (Ascaris), hookworms (Necator and Ancylostoma) and whipworm (Trichuris) with majority occurring in the tropical and subtropical regions of the world. Despite its low prevalence in developed countries, the removal of STHs from wastewater remains crucial to allow the safe use of sludge or recycled water in agriculture. Conventional methods such as incubation and optical microscopy are cumbersome; consequently, the results drastically vary from person-to-person observing the ova (eggs) under microscope. Although PCR-based methods are an alternative to conventional techniques, it lacks the ability to distinguish between viable and non-viable helminth ova. As a result, wastewater treatment industries are in major need for radically new and innovative tools to detect and quantify STHs eggs with precision, accuracy and being cost-effective. In our study, we focus on the following novel and innovative techniques: -Recombinase polymerase amplification and Surface enhanced Raman spectroscopy (RPA-SERS) based detection of helminth ova. -Use of metal nanoparticles and their relative nanozyme activity. -Colorimetric detection, differentiation and enumeration of genera of helminth ova using hydrolytic enzymes (chitinase and lipase). -Propidium monoazide (PMA)-qPCR to detect viable helminth ova. -Modified assay to recover and enumerate helminth eggs from fresh raw sewage. -Transcriptome analysis of ascaris ova in fresh raw sewage. The aforementioned techniques have the potential to replace current conventional and molecular methods thereby producing a standard protocol for the determination and enumeration of helminth ova in sewage sludge.

Keywords: colorimetry, helminth, PMA-QPCR, nanoparticles, RPA, viable

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977 Machine Learning Invariants to Detect Anomalies in Secure Water Treatment

Authors: Jonathan Heng, Yoong Cheah Huei

Abstract:

A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

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976 Serum Anti-Oxidation Enzymes Response to L-Carnitine Supplementation

Authors: Farah Nameni, Hamidreza Poursadra, Maasumeh Nurani Pilehrud

Abstract:

Exercise training induced Inflammation and stress. Antioxidant, for example L- Carnitine has beneficial effects in immune system and increased antioxidant enzymes activity. L- Carnitine protects the tissue against the oxidative side effect and helps the body to protect against stress during and after acute exercise. The aim of this study was to determine the effect of L-Carnitine on the blood enzymes: GPX SOD, CAT and GR response. In this study, 20 basketball players girls participated. Subjects were randomly assigned into two groups; placebo and supplementation. Antioxidadision enzymes (Superoxide Dismutase, Catalase, Glutathione Reductase, Glutathione Peroxidase) evaluated. L-Carnitine supplement group orally daily received 3000 mg powder for 14 dys. Then all participates trained basketball exercise acute. Blood samples were drawn vein before and immediately after exercise. Superoxide Dismutase, Catalase, Glutathione Reductase, Glutathione Peroxidase were measured, and data was analyzed using repeated measure ANOVA, Bonferroni and t-test. Our results showed: SOD, GPX and GPX (P < 0.05) have a significant increase. These results suggest L-Carnitine supplementation may increase GPX SOD, CAT, and basal anti oxidative capacity. L-Carnitine can modulate the alterations of exercise oxidative damage in girl basketball players.

Keywords: l-carnitine, GPX, SOD, CAT, exercise, GR, anti-oxidant

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975 Influence of Cation Substitution on Magnetic Transitions and Ordering in La2NixCo1-xMnO6 Compounds (x = 0.2 - 0.8)

Authors: Amine.Harbia, Hicham. Moutaabbidb, Yann. Le Godecb, Said. Benmokhtara, Mouhammed. Moutaabbida

Abstract:

This study explores the structural and magnetic characteristics of newly synthesized double perovskite oxides, La₂NiₓCo1-xMnO₆, with x ranging from 0.2 to 0.8. Utilizing X-ray powder diffraction and SQUID magnetometry, we analyzed the compounds that consistently exhibit a monoclinic structure with the P21/n space group at ambient temperature. it findings reveal that as Ni2+ is progressively substituted by Co2+, there is a corresponding decrease in cell parameters, attributable to the smaller ionic radius of Ni2+ (0.69 Å) compared to Co2+ (0.74 Å). The crystal structure features octahedrally coordinated (Co/Ni)2+ and Mn4+ cations with oxygen, forming (Co/Ni)O6 and MnO6 octahedra linked via oxygen atoms along different crystallographic axes. Magnetic characterization conducted over a temperature range of 2 to 300 K in both DC and AC magnetic fields, showed a predominant paramagnetic to ferromagnetic transition between 232 K and 260 K, with the Curie temperature notably increasing with higher x values. Samples with x=0.2, 0.25, and 0.5 exhibited a secondary PM-FM transition between 200 K and 208 K. Cation ordering was quantitatively assessed, indicating a higher ordering in Ni2+-rich samples (x=0.75 and 0.8) at over 96%, whereas the sample with x=0.25 showed minimal ordering. Furthermore, the out-of-phase component of the AC susceptibility displayed frequency-dependent transitions between 65 K and 110 K, suggesting the presence of superparamagnetic domains across all samples.

Keywords: double perovskite oxides, magnetic transitions, cation ordering, squid magnetometry

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974 Tungsten-Based Powders Produced in Plasma Systems

Authors: Andrey V. Samokhin, Nikolay V. Alekseev, Mikhail A. Sinaiskii

Abstract:

The report presents the results of R&D of plasma-chemical production of W, W-Cu, W-Ni-Fe nanopowders as well as spherical micropowders of these compounds for their use in modern 3D printing technologies. Plasma-chemical synthesis of nanopowdersis based on the reduction of tungsten oxide compounds powders in a stream of hydrogen-containing low-temperature thermal plasma generated in an electric arc plasma torch. The synthesis of W-Cu and W-Ni-Fe nanocompositesiscarried out using the reduction of a mixture of the metal oxides. Using the synthesized tungsten-based nanocomposites powders, spherical composite micropowders with a submicron structure canbe manufactured by spray dryinggranulation of nanopowder suspension and subsequent densification and spheroidization of granules by melting in a low-temperature thermal plasma flow. The DC arc plasma systems are usedfor the synthesis of nanopowdersas well as for the spheroidization of microgranuls. Plasma systems have a capacity of up to 1 kg/h for nanopowder and up to 5 kg/h for spheroidized powder. All synthesized nanopowders consist of aggregated particles with sizes less than 100 nm, and nanoparticles of W-Cu and W-Ni-Fe composites have core (W) –shell (Cu or Ni-Fe) structures. The resulting dense spherical microparticles with a size of 20-60 microns have a submicron structure with a uniform distribution of metals over the particle volume. The produced tungsten-based nano- and spherical micropowderscan be used to develop new materials and manufacture products using advanced modern technologies.

Keywords: plasma, powders, production, tungsten-based

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973 Influence of Processing Parameters on the Reliability of Sieving as a Particle Size Distribution Measurements

Authors: Eseldin Keleb

Abstract:

In the pharmaceutical industry particle size distribution is an important parameter for the characterization of pharmaceutical powders. The powder flowability, reactivity and compatibility, which have a decisive impact on the final product, are determined by particle size and size distribution. Therefore, the aim of this study was to evaluate the influence of processing parameters on the particle size distribution measurements. Different Size fractions of α-lactose monohydrate and 5% polyvinylpyrrolidone were prepared by wet granulation and were used for the preparation of samples. The influence of sieve load (50, 100, 150, 200, 250, 300, and 350 g), processing time (5, 10, and 15 min), sample size ratios (high percentage of small and large particles), type of disturbances (vibration and shaking) and process reproducibility have been investigated. Results obtained showed that a sieve load of 50 g produce the best separation, a further increase in sample weight resulted in incomplete separation even after the extension of the processing time for 15 min. Performing sieving using vibration was rapider and more efficient than shaking. Meanwhile between day reproducibility showed that particle size distribution measurements are reproducible. However, for samples containing 70% fines or 70% large particles, which processed at optimized parameters, the incomplete separation was always observed. These results indicated that sieving reliability is highly influenced by the particle size distribution of the sample and care must be taken for samples with particle size distribution skewness.

Keywords: sieving, reliability, particle size distribution, processing parameters

Procedia PDF Downloads 613