Search results for: magnetic solvent extraction

Authors: Majid Azizi, Payam Ghorbannezhad, Mostafa Amiri, Mohammad Ghofrani

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Environmental issues in the furniture industry are of great importance due to the use of natural materials such as wood and chemical substances like adhesives and paints. These issues encompass environmental conservation and managing pollution and waste generated. Improper use of wood resources, along with the use of chemicals and their release, leads to the depletion of natural resources, damage to forests, and the emission of greenhouse gases. Therefore, identifying influential indicators in the life cycle assessment of classic furniture and proposing solutions to reduce environmental impacts becomes crucial. In this study, the life cycle of classic furniture was evaluated using a hierarchical analytical process from cradle to grave. The life cycle assessment was employed to assess the environmental impacts of the furniture industry, ranging from raw material extraction to waste disposal and recycling. The most significant indicators in the furniture industry's production chain were also identified. The results indicated that the wood quality indicator is the most essential factor in the life cycle of classic furniture. Furthermore, the relative contribution of each type of traditional furniture was proposed concerning impact categories in the life cycle assessment. The results showed that among the three proposed types, the design and production of furniture with prefabricated parts had the most negligible impact in categories such as global warming potential and ozone layer depletion compared to furniture design with solid wood and furniture design with recycled components. Among the three suggested types of furniture to reduce environmental impacts, producing furniture with solid wood or other woods was chosen as the most crucial solution.

Keywords: life cycle assessment, analytic hierarchy process, environmental issues, furniture

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: A. Sezai Sarac

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Acrylonitrile (AN) copolymers with typical comonomers of vinyl acetate (VAc) or methyl acrylate (MA) exhibit better mechanical behaviors than its homopolymer. To increase processability of conjugated polymer, and to obtain a hybrid nano-structure multi-stepped emulsion polymerization was applied. Such products could be used in, i.e., drug-delivery systems, biosensors, gas-sensors, electronic compounds, etc. Incorporation of a number of flexible comonomers weakens the dipolar interactions among CN and thereby decreases melting point or increases decomposition temperatures of the PAN based copolymers. Hence, it is important to consider the effect of comonomer on the properties of PAN-based copolymers. Acrylonitrile vinylacetate (AN–VAc ) copolymers have the significant effect to their thermal behavior and are also of interest as precursors in the production of high strength carbon fibers. AN is copolymerized with one or two comonomers, particularly with vinyl acetate The copolymer of AN and VAc can be used either as a plastic (VAc > 15 wt %) or as microfibers (VAc < 15 wt %). AN provides the copolymer with good processability, electrochemical and thermal stability; VAc provides the mechanical stability. The free radical copolymerization of AN and VAc copolymer and core Shell structure of polyprrole composites,and nanofibers of poly(m-anthranilic acid)/polyacrylonitrile blends were recently studied. Free radical copolymerization of acrylonitrile (AN) – with different comonomers, i.e. acrylates, and styrene was realized using ammonium persulfate (APS) in the presence of a surfactant and in-situ polymerization of conjugated polymers was performed in this reaction medium to obtain core-shell nano particles. Nanofibers of such nanoparticles were obtained by electrospinning. Morphological properties of nanofibers are investigated by scanning electron microscopy (SEM) and atomic force spectroscopy (AFM). Nanofibers are characterized using Fourier Transform Infrared - Attenuated Total Reflectance spectrometer (FTIR-ATR), Nuclear Magnetic Resonance Spectroscopy (1H-NMR), differential scanning calorimeter (DSC), thermal gravimetric analysis (TGA), and Electrochemical Impedance Spectroscopy. The electrochemical Impedance results of the nanofibers were fitted to an equivalent curcuit by modelling (ECM).

Keywords: core shell nanoparticles, nanofibers, ascrylonitile copolymers, hybrid nanostructures

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Authors: Sakshi V. Tantak, Vishap K. Malik, Neelanjney Pilarisetty

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A patent is an exclusive right granted for an invention. It can be a product or a process that provides an innovative method of doing something, or offers a new technical perspective or solution to a problem. A patent can be obtained by making the technical information and details about the invention publicly available. The patent owner has exclusive rights to prevent or stop anyone from using the patented invention for commercial uses. Any commercial usage, distribution, import or export of a patented invention or product requires the patent owner’s consent. It has been observed that the central and important parts of patents are scripted in idiosyncratic and complex linguistic structures that can be difficult to read, comprehend or interpret for the masses. The abstracts of these patents tend to obfuscate the precise nature of the patent instead of clarifying it via direct and simple linguistic constructs. This makes it necessary to have an efficient access to this knowledge via concise and transparent summaries. However, as mentioned above, due to complex and repetitive linguistic constructs and extremely long sentences, common extraction-oriented automatic text summarization methods should not be expected to show a remarkable performance when applied to patent documents. Other, more content-oriented or abstractive summarization techniques are able to perform much better and generate more concise summaries. This paper proposes an efficient summarization system for patents using artificial intelligence, natural language processing and deep learning techniques to condense the knowledge and essential information from a patent document into a single summary that is easier to understand without any redundant formatting and difficult jargon.

Keywords: abstractive summarization, deep learning, natural language Processing, patent document

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Authors: Merkineh Markos Lorato, Gedefaw Diress Alene

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Introduction: Visual impairment is any condition of the eye or visual system that results in loss/reduction of visual functioning. It significantly influences the academic routine and social activities of children, and the effect is severe for low-income countries like Ethiopia. So, this study aimed to determine the pooled prevalence of visual impairment among school children in Ethiopia. Methods: Databases such as Medical Literature Analysis and Retrieval System Online, Excerpta Medica dataBASE, World Wide Web of Science, and Cochrane Library searched to retrieve eligible articles. In addition, Google Scholar and a reference list of the retrieved eligible articles were addressed. Studies that reported the prevalence of visual impairment were included to estimate the pooled prevalence. Data were extracted using a standardized data extraction format prepared in Microsoft Excel and analysis was held using STATA 11 statistical software. I² was used to assess the heterogeneity. Because of considerable heterogeneity, a random effect meta-analysis model was used to estimate the pooled prevalence of visual impairment among school children in Ethiopia. Results: The result of 9 eligible studies showed that the pooled prevalence of visual impairment among school children in Ethiopia was 7.01% (95% CI: 5.46, 8.56%). In the subgroup analysis, the highest prevalence was reported in South Nations Nationalities and Tigray region together (7.99%; 3.63, 12.35), while the lowest prevalence was reported in Addis Ababa (5.73%; 3.93, 7.53). Conclusion: The prevalence of visual impairment among school children is significantly high in Ethiopia. If it is not detected and intervened early, it will cause a lifetime threat to visually impaired school children, so that school vision screening program plan and its implementation may cure the life quality of future generations in Ethiopia.

Keywords: visual impairment, school children, Ethiopia, prevalence

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Authors: Indranil Chakraborty, Kalyan Mandal

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Three new α-hydroxy carboxylate group functionalized MnFe₂O₄ nanoparticles (NPs) have been developed to explore the microscopic origin of ligand modified fluorescence and magnetic properties of nearly monodispersed MnFe₂O₄ NPs. The surface functionalization has been carried out with three small organic ligands (tartrate, malate, and citrate) having different number of α-hydroxy carboxylate functional group along with steric effect. Detailed study unveils that α-hydroxy carboxylate moiety of the ligands plays key role to generate intrinsic fluorescence in functionalized MnFe₂O₄ NPs through the activation of ligand to metal charge transfer transitions, associated with ligand-Mn²⁺/Fe³⁺ interactions along with d-d transition corresponding to d-orbital energy level splitting of Fe³⁺ ions on NP surface. Further, MnFe₂O₄ NPs show a maximum 140.88% increase in coercivity and 97.95% decrease in magnetization compared to its bare one upon functionalization. The ligands that induce smallest crystal field splitting of d-orbital energy level of transition metal ions are found to result in strongest ferromagnetic activation of the NPs. Finally, our developed tartrate functionalized MnFe₂O₄ (T-MnFe₂O₄) NPs have been utilized for studying DNA binding interaction and nuclease activity for stimulating their beneficial activities toward diverse biomedical applications. The spectroscopic measurements indicate that T-MnFe₂O₄ NPs bind calf thymus DNA by intercalative mode. The ability of T-MnFe₂O₄ NPs to induce DNA cleavage was studied by gel electrophoresis technique where the complex is found to promote the cleavage of pBR322 plasmid DNA from the super coiled form I to linear coiled form II and nicked coiled form III with good efficiency. This may be taken into account for designing new biomolecular detection agents and anti-cancer drug which can open up a new door toward diverse non-invasive biomedical applications.

Keywords: MnFe₂O₄ nanoparticle, α-hydroxy carboxylic acid, comparative fluorescence, magnetism study, DNA interaction, nuclease activity

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Authors: Mohammad H. Yarmohammadian, Reza Safdari, Mahmoud Keyvanara, Nahid Tavakoli

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One of the greatest challenges in disaster and emergencies is patient tracking. The concept of tracking has different denotations. One of the meanings refers to tracking patients’ physical locations and the other meaning refers to tracking patients ‘medical needs during emergency services. The main goal of patient tracking is to provide patient safety during disaster and emergencies and manage the flow of patient and information in different locations. In most of cases, there are not sufficient and accurate data regarding the number of injuries, medical conditions and their accommodation and transference. The objective of the present study is to survey on patient tracking issue in natural disaster and emergencies. Methods: This was a narrative study in which the population was E-Journals and the electronic database such as PubMed, Proquest, Science direct, Elsevier, etc. Data was gathered by Extraction Form. All data were analyzed via content analysis. Results: In many countries there is no appropriate and rapid method for tracking patients and transferring victims after the occurrence of incidents. The absence of reliable data of patients’ transference and accommodation, even in the initial hours and days after the occurrence of disasters, and coordination for appropriate resource allocation, have faced challenges for evaluating needs and services challenges. Currently, most of emergency services are based on paper systems, while these systems do not act appropriately in great disasters and incidents and this issue causes information loss. Conclusion: Patient tracking system should update the location of patients or evacuees and information related to their states. Patients’ information should be accessible for authorized users to continue their treatment, accommodation and transference. Also it should include timely information of patients’ location as soon as they arrive somewhere and leave therein such a way that health care professionals can be able to provide patients’ proper medical treatment.

Keywords: patient tracking, challenges, disaster, emergency

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Thais Cardoso Franco, Caio Nahuel Sousa Fagonde, Willer Gomes dos Santos

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Aurora Borealis is an optical phenomenon composed of luminous events observed in the night skies in the polar regions resulting from disturbances in the magnetosphere due to the impact of solar wind particles with the Earth's upper atmosphere, channeled by the Earth's magnetic field, which causes atmospheric molecules to become excited and emit electromagnetic spectrum, leading to the display of lights in the sky. However, there are still different implications of this phenomenon under study: high intensity auroras are often accompanied by geomagnetic storms that cause blackouts on Earth and impair the transmission of signals from the Global Navigation Satellite Systems (GNSS). Auroras are also known to occur on other planets and exoplanets, so the activity is an indication of active space weather conditions that can aid in learning about the planetary environment. In order to improve understanding of the phenomenon, this research aims to design a satellite formation flying solution for collecting and transmitting data for monitoring aurora borealis in northern hemisphere, an approach that allows studying the event with multipoint data collection in a reduced time interval, in order to allow analysis from the beginning of the phenomenon until its decline. To this end, the ideal number of satellites, the spacing between them, as well as the ideal topology to be used will be analyzed. From an orbital study, approaches from different altitudes, eccentricities and inclinations will also be considered. Given that at large relative distances between satellites in formation, controllers tend to fail, a study on the efficiency of nonlinear adaptive control methods from the point of view of position maintenance and propellant consumption will be carried out. The main orbital perturbations considered in the simulation: non-homogeneity terrestrial, atmospheric drag, gravitational action of the Sun and the Moon, accelerations due to solar radiation pressure and relativistic effects.

Keywords: formation flying, nonlinear adaptive control method, aurora borealis, adaptive SDRE method

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Authors: Farha Mizana Shamsudin, Shahidan Radiman, Yusof Abdullah, Nasri Abdul Hamid

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Oxide dispersion strengthened (ODS) ferritic steels are amongst the most promising candidates for large scale structural materials to be applied in next generation fission and fusion nuclear power reactors. This kind of material is relatively stable at high temperature, possess remarkable mechanical properties and comparatively good resistance from neutron radiation damage. The superior performance of ODS ferritic steels over their conventional properties is attributed to the high number density of nano-sized dispersoids that act as nucleation sites and stable sinks for many small helium bubbles resulting from irradiation, and also as pinning points to dislocation movement and grain growth. ODS ferritic steels are usually produced by powder metallurgical routes involving mechanical alloying (MA) process of Y2O3 and pre-alloyed or elemental metallic powders, and then consolidated by hot isostatic pressing (HIP) or hot extrusion (HE) techniques. In this study, Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (designated as 14YWT) was produced by mechanical alloying process and followed by hot isostatic pressing (HIP) technique. Crystal structure and morphology of this sample were identified and characterized by using X-ray Diffraction (XRD) and field emission scanning electron microscope (FESEM) respectively. The magnetic measurement of this sample at room temperature was carried out by using a vibrating sample magnetometer (VSM). FESEM micrograph revealed a homogeneous microstructure constituted by fine grains of less than 650 nm in size. The ultra-fine dispersoids of size between 5 nm to 19 nm were observed homogeneously distributed within the BCC matrix. The EDS mapping reveals that the dispersoids contain Y-Ti-O nanoclusters and from the magnetization curve plotted by VSM, this sample approaches the behavior of soft ferromagnetic materials. In conclusion, ODS Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (14YWT) ferritic steel was successfully produced by HIP technique in this present study.

Keywords: hot isostatic pressing, magnetization, microstructure, ODS ferritic steel

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Authors: Byung Wook Yang, Sae Kyul Kim, Seung Il Ahn, Jae Hee Choi, Heejung Jung, Yejin Choi, Byung Yong Kim, Young Tae Hahm

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Opuntia ficus-indica is a member of the Cactaceae family that is widely grown in all the semiarid countries throughout the world. Opuntia ficus-indica var. Saboten (OFS), commonly known as prickly pear cactus, is commercially cultivated as a dietary foodstuffs and medicinal stuffs in Jeju Island, Korea. Owing to high viscosity of OFS’ pad, its application to the commercial field has been limited. When the low viscosity of OFS’s pad is obtained, it is useful for the manufacture of healthy food in the related field. This study was performed to obtain the optimal digestion conditions of food-grade enzymes (Pectinex, Viscozyme and Celluclast) with the powder of OFS stem. And also, the contents of water-soluble dietary fiber (WSDF) of the dried powder prepared by the extraction of OFS stem were monitored and optimized using the response surface methodology (RSM), which included 20 experimental points with 3 replicates for two independent variables (fermentation temperature and time). A central composite design was used to monitor the effect of fermentation temperature (30-90 °C, X1) and fermentation time (1-10h, X2) on dependent variables, such as viscosity (Y1), water-soluble dietary fiber (Y2) and dietary fiber yield (Y3). Estimated maximum values at predicted optimum conditions were in agreement with experimental values. Optimum temperature and duration were 50°C and 12 hours, respectively. Viscosity value reached 3.4 poise. Yield of water-soluble dietary fiber is determined in progress.

Keywords: Opuntia ficus-indica var. saboten, enzymatic fermentation, response surface methodology, water-soluble dietary fiber, viscosity

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Olga Gomez De Miranda, Jose R. Ochoa-Gomez, Stefaan De Wildeman, Luciano Monsegue, Soraya Prieto, Leire Lorenzo, Cristina Dineiro

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The chemical industry is facing a new revolution. As long as processes based on the exploitation of fossil resources emerged with force in the XIX century, Society currently demands a new radical change that will lead to the complete and irreversible implementation of a circular sustainable economic model. The implementation of biorefineries will be essential for this. There, renewable raw materials as sugars and other biomass resources are exploited for the development of new materials that will partially replace their petroleum-derived homologs in a safer, and environmentally more benign approach. Isosorbide, (1,4:3,6-dianhydro-d-glucidol) is a primary bio-based derivative obtained from the plant (poly) saccharides and a very interesting example of a useful chemical produced in biorefineries. It can, in turn, be converted to other secondary monomers as isosorbide bis-methyl carbonate (IBMC), whose main field of application can be as a key biodegradable intermediary substitute of bisphenol-A in the manufacture of polycarbonates, or as an alternative to the toxic isocyanates in the synthesis of new polyurethanes (non-isocyanate polyurethanes) both with a huge application market. New products will present advantageous mechanical or optical properties, as well as improved behavior in non-toxicity and biodegradability aspects in comparison to their petro-derived alternatives. A robust production process of IBMC, a biomass-derived chemical, is here presented. It can be used with different raw material qualities using dimethyl carbonate (DMC) as both co-reactant and solvent. It consists of the transesterification of isosorbide with DMC under soft operational conditions, using different basic catalysts, always active with the isosorbide characteristics and purity. Appropriate isolation processes have been also developed to obtain crude IBMC yields higher than 90%, with oligomers production lower than 10%, independently of the quality of the isosorbide considered. All of them are suitable to be used in polycondensation reactions for polymers obtaining. If higher qualities of IBMC are needed, a purification treatment based on nanofiltration membranes has been also developed. The IBMC reaction-isolation conditions established in the laboratory have been successfully modeled using appropriate software programs and moved to a pilot-scale (production of 100 kg of IBMC). It has been demonstrated that a highly efficient IBMC production process able to be up-scaled under suitable market conditions has been obtained. Operational conditions involved the production of IBMC involve soft temperature and energy needs, no additional solvents, and high operational efficiency. All of them are according to green manufacturing rules.

Keywords: biomass, catalyst, isosorbide bis-methyl carbonate, polycarbonate, polyurethane, transesterification

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Authors: Samaneh Nabavi, Hadi Shirzad, Somayeh Khanjani, Shirin Jalili

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Quantum dots (QDs) are semiconductor nanocrystals that exhibit intrinsic optical and electrical properties that are size dependent due to the quantum confinement effect. Quantum confinement is brought about by the fact that in bulk semiconductor material the electronic structure consists of continuous bands, and that as the size of the semiconductor material decreases its radius becomes less than the Bohr exciton radius (the distance between the electron and electron-hole) and discrete energy levels result. As a result QDs have a broad absorption range and a narrow emission which correlates to the band gap energy (E), and hence QD size. QDs can thus be tuned to give the desired wavelength of fluorescence emission.Due to their unique properties, QDs have attracted considerable attention in different scientific areas. Also, they have been considered for forensic applications in recent years. The ability of QDs to fluoresce up to 20 times brighter than available fluorescent dyes makes them an attractive nanomaterial for enhancing the visualization of latent fingermarks, or poorly developed fingermarks. Furthermore, the potential applications of QDs in the detection of nitroaromatic explosives, such as TNT, based on directive fluorescence quenching of QDs, electron transfer quenching process or fluorescence resonance energy transfer have been paid to attention. DNA analysis is associated tightly with forensic applications in molecular diagnostics. The amount of DNA acquired at a criminal site is inherently limited. This limited amount of human DNA has to be quantified accurately after the process of DNA extraction. Accordingly, highly sensitive detection of human genomic DNA is an essential issue for forensic study. QDs have also a variety of advantages as an emission probe in forensic DNA quantification.

Keywords: forensic science, quantum dots, DNA typing, explosive sensor, fingermark analysis

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Authors: Adebola Ajayi, Francis B. Aiyeleye, Olakunke M. Makanjuola, Olalekan J. Adebowale

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Cocoyam, a generic term for both xanthoma and colocasia, is a traditional staple root crop in many developing countries in Africa, Asia and the Pacific. It is mostly cultivated as food crop which is very rich in vitamin B6, magnesium and also in dietary fiber. The cocoyam starch is easily digested and often used for baby food. Drying food is a method of food preservation that removes enough moisture from the food so bacteria, yeast and molds cannot grow. It is a one of the oldest methods of preserving food. The effect of drying methods on the proximate composition and functional properties of extracted cocoyam starch flour were studied. Freshly harvested cocoyam cultivars at matured level were washed with portable water, peeled, washed and grated. The starch in the grated cocoyam was extracted, dried using sun drying, oven and cabinet dryers. The extracted starch flour was milled into flour using Apex mill and packed and sealed in low-density polyethylene film (LDPE) 75 micron thickness with Nylon sealing machine QN5-3200HI and kept for three months under ambient temperature before analysis. The result showed that the moisture content, ash, crude fiber, fat, protein and carbohydrate ranged from 6.28% to 12.8% 2.32% to 3.2%, 0.89% to 2.24%%, 1.89% to 2.91%, 7.30% to 10.2% and 69% to 83% respectively. The functional properties of the cocoyam starch flour ranged from 2.65ml/g to 4.84ml/g water absorption capacity, 1.95ml/g to 3.12ml/g oil absorption capacity, 0.66ml/g to 7.82ml/g bulk density and 3.82% to 5.30ml/g swelling capacity. Significant difference (P≥0.5) was not obtained across the various drying methods used. The drying methods provide extension to the shelf-life of the extracted cocoyam starch flour.

Keywords: cocoyam, extraction, oven dryer, cabinet dryer

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Authors: Héctor González Espinosa, Ricardo Ivan Cordova Chávez, Alejandra Contreras Ramos, Itzia Irene Padilla Martínez, José Guadalupe Trujillo Ferrara, Marvin Antonio Soriano Ursúa

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Boronic acids are able to create diester bonds with carbohydrates because of their hydroxyl groups; in nature, there are some organoborates with these characteristics, such as the calcium fructoborate, formed by the union of two fructose molecules and a boron atom, synthesized by plants. In addition, it has been observed that, in animal cells only the compounds with cis-diol functional groups are capable of linking to boric or boronic acids. The formation of these organoboron compounds could impair the physical and chemical properties of the precursors, even their acute toxicity. In this project, two carbohydrate-derived boron-containing compounds from D-fructose and D-arabinose and phenylboronic acid are analyzed by different spectroscopy techniques such as Raman, Infrared with Fourier Transform Infrared (FT-IR), Nuclear Magnetic Resonance (NMR) and X-ray diffraction crystallography to describe their chemical characteristics. Also, an acute toxicity test was performed to determine their LD50 using the Lorke’s method. It was confirmed by multiple spectra the formation of the adducts by the generation of the diester bonds with a β-D-pyranose of fructose and arabinose. The most prominent findings were the presence of signals corresponding to the formation of new bonds, like the stretching of B-O bonds, or the absence of signals of functional groups like the hydroxyls presented in the reagents used for the synthesis of the adducts. The NMR spectra yielded information about the stereoselectivity in the synthesis reaction, observed by the interaction of the protons and their vicinal atoms in the anomeric and second position carbons; but also, the absence of a racemic mix by the finding of just one signal in the range for the anomeric carbon in the 13C NMR spectra of both adducts. The acute toxicity tests by the Lorke’s method showed that the LD50 value for both compounds is 1265 mg/kg. Those results let us to propose these adducts as highly safe agents for further biological evaluation with medical purposes.

Keywords: acute toxicity, adduct, boron, carbohydrate, diester bond

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Authors: V. K. Srivastava

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Graphene has recently attracted an increasing attention in nanocomposites applications because it has 200 times greater strength than steel, making it the strongest material ever tested. Graphene, as the fundamental two-dimensional (2D) carbon structure with exceptionally high crystal and electronic quality, has emerged as a rapidly rising star in the field of material science. Graphene, as defined, as a 2D crystal, is composed of monolayers of carbon atoms arranged in a honeycombed network with six-membered rings, which is the interest of both theoretical and experimental researchers worldwide. The name comes from graphite and alkene. Graphite itself consists of many graphite-sheets stacked together by weak van der Waals forces. This is attributed to the monolayer of carbon atoms densely packed into honeycomb structure. Due to superior inherent properties of graphene nanoplatelets (GnP) over other nanofillers, GnP particles were added in epoxy resin with the variation of weight percentage. It is indicated that the DMA results of storage modulus, loss modulus and tan δ, defined as the ratio of elastic modulus and imaginary (loss) modulus versus temperature were affected with addition of GnP in the epoxy resin. In epoxy resin, damping (tan δ) is usually caused by movement of the molecular chain. The tan δ of the graphene nanoplatelets/epoxy resin composite is much lower than that of epoxy resin alone. This finding suggests that addition of graphene nanoplatelets effectively impedes movement of the molecular chain. The decrease in storage modulus can be interpreted by an increasing susceptibility to agglomeration, leading to less energy dissipation in the system under viscoelastic deformation. The results indicates the tan δ increased with the increase of temperature, which confirms that tan δ is associated with magnetic field strength. Also, the results show that the nanohardness increases with increase of elastic modulus marginally. GnP filled epoxy resin gives higher value than the epoxy resin, because GnP improves the mechanical properties of epoxy resin. Debonding of GnP is clearly observed in the micrograph having agglomeration of fillers and inhomogeneous distribution. Therefore, DMA and nanohardness studies indiacte that the elastic modulus of epoxy resin is increased with the addition of GnP fillers.

Keywords: agglomeration, elastic modulus, epoxy resin, graphene nanoplatelet, loss modulus, nanohardness, storage modulus

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Authors: Lorico D. S. Lapitan Jr., Yihan Xu, Yuan Guo, Dejian Zhou

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The ability of ultrasensitive detection of specific genes and discrimination of single nucleotide polymorphisms is important for clinical diagnosis and biomedical research. Herein, we report the development of a new ultrasensitive approach for label-free DNA detection using magnetic nanoparticle (MNP) assisted rapid target capture/separation in combination with signal amplification using poly-enzyme tagged polymer nanobead. The sensor uses an MNP linked capture DNA and a biotin modified signal DNA to sandwich bind the target followed by ligation to provide high single-nucleotide polymorphism discrimination. Only the presence of a perfect match target DNA yields a covalent linkage between the capture and signal DNAs for subsequent conjugation of a neutravidin-modified horseradish peroxidase (HRP) enzyme through the strong biotin-nuetravidin interaction. This converts each captured DNA target into an HRP which can convert millions of copies of a non-fluorescent substrate (amplex red) to a highly fluorescent product (resorufin), for great signal amplification. The use of polymer nanobead each tagged with thousands of copies of HRPs as the signal amplifier greatly improves the signal amplification power, leading to greatly improved sensitivity. We show our biosensing approach can specifically detect an unlabeled DNA target down to 10 aM with a wide dynamic range of 5 orders of magnitude (from 0.001 fM to 100.0 fM). Furthermore, our approach has a high discrimination between a perfectly matched gene and its cancer-related single-base mismatch targets (SNPs): It can positively detect the perfect match DNA target even in the presence of 100 fold excess of co-existing SNPs. This sensing approach also works robustly in clinical relevant media (e.g. 10% human serum) and gives almost the same SNP discrimination ratio as that in clean buffers. Therefore, this ultrasensitive SNP biosensor appears to be well-suited for potential diagnostic applications of genetic diseases.

Keywords: DNA detection, polymer beads, signal amplification, single nucleotide polymorphisms

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Authors: James Britton, Vijaya Krishna, Manus Biggs, Abhay Pandit

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Regeneration of the spinal cord after injury remains a great challenge due to the complexity of this organ. Inflammation and gliosis at the injury site hinder the outgrowth of axons and hence prevent synaptic reconnection and reinnervation. Hyaluronic acid (HA) is the main component of the spinal cord extracellular matrix and plays a vital role in cell proliferation and axonal guidance. In this study, we have synthesized and characterized a photo-cross-linkable HA-tyramine (tyr) hydrogel from a chemical, mechanical, electrical, biological and structural perspective. From our experimentation, we have found that HA-tyr can be synthesized with controllable degrees of tyramine substitution using click chemistry. The complex modulus (G*) of HA-tyr can be tuned to mimic the mechanical properties of the native spinal cord via optimization of the photo-initiator concentration and UV exposure. We have examined the degree of tyramine-tyramine covalent bonding (polymerization) as a function of UV exposure and photo-initiator use via Photo and Nuclear magnetic resonance spectroscopy. Both swelling and enzymatic degradation assays were conducted to examine the resilience of our 3D printed hydrogel constructs in-vitro. Using a femtosecond 780nm laser, the two-photon polymerization of HA-tyr hydrogel in the presence of riboflavin photoinitiator was optimized. A laser power of 50mW and scan speed of 30,000 μm/s produced high-resolution spatial patterning within the hydrogel with sustained mechanical integrity. Using dorsal root ganglion explants, the cytocompatibility of photo-crosslinked HA-tyr was assessed. Using potentiometry, the electrical conductivity of photo-crosslinked HA-tyr was assessed and compared to that of native spinal cord tissue as a function of frequency. In conclusion, we have developed a biocompatible hydrogel that can be used for photolithographic 3D printing to fabricate tissue engineered constructs for neural tissue regeneration applications.

Keywords: 3D printing, hyaluronic acid, photolithography, spinal cord injury

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Authors: Gonzalo Ortiz de Elguea-Culebras, Raúl Sánchez-Vioquea, Adela Mena-Morales, Manuel Alaiz, Enrique Melero-Bravo, Esteban García-Romero, Javier Vioque, Lourdes Marchante-Cuevas, Julio Girón-Calle

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Saffron (Crocus sativus L.) is a highly valued crop for the manufacture of spice that consists of the dried stigma of the flowers. This is in contrast to other underutilized parts of the saffron plant as leaves, which represent abundant biomass whose use might help to enhance the sustainability of the saffron crop. Saffron leaves contain significant amounts of phenolic compounds, 7.8 equivalent grams of gallic acid per 100g of extract, and are very promising compounds in terms of exploring novel uses of saffron leaves. Given that phenolic compounds have numerous effects on cancer-related biological pathways, we have investigated the in vitro antiproliferative effect of saffron leaf polyphenols against human colon adenocarcinoma cells (Caco-2). Polyphenols were extracted from leaves with 70% ethanol, defatted with hexane, and purified by solid phase extraction using C18 silica gel and then silica gel 60. Analysis of polyphenols was performed by HPLC-ESI-MS. Di-, tri-, and tetrahexosides of quercetin, kaempferol, and isorhamnetin, as well as C-hexosides like isoorientin and vitexin, were tentatively identified. Polyphenols strongly inhibited the proliferation of Caco-2 cells, which is consistent with model studies in which several of the polyphenols identified in saffron leaves have demonstrated their potential as chemopreventive agents in cancer. Due to the low profitability that saffron leaf currently represents, we consider these results very encouraging and that this by-product deserves further investigation as a potential source of active molecules against colorectal cancer.

Keywords: saffron leaves, agricultural by-products, polyphenols, antiproliferative effect, human colon adenocarcinoma cells

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Authors: Mahmoud A Rabah, Sabah M. Abelbasir

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Lead-calcium alloy containing up to 0.10% calcium was recovered from spent rechargeable sealed acid lead batteries. Two techniques were investigated to explore the effect of flux salts on the extent and quality of the recovered alloy, pyro-metallurgical and electrochemical methods. About 10 kg of the spent batteries were collected for testing. The sample was washed with hot water and dried. The plastic cases of the batteries were mechanically cut, and the contents were dismantled manually, the plastic containers were shredded for recycling. The electrode plates were freed from the loose powder and placed in SiC crucible and covered with alkali chloride salts. The loaded crucible was heated in an electronically controlled chamber furnace type Nabertherm C3 at temperatures up to 800 °C. The obtained metals were analyzed. The effect of temperature, rate of heating, atmospheric conditions, composition of the flux salts on the extent and quality of the recovered products were studied. Results revealed that the spent rechargeable batteries contain 6 blocks of 6 plates of Pb-Ca alloy each. Direct heating of these plates in a silicon carbide crucible under ambient conditions produces lead metal poor in calcium content ( < 0.07%) due to partial oxidation of the alloying calcium element. Rate of temperature increase has a considerable effect on the yield of the lead alloy extraction. Flux salts composition benefits the recovery process. Sodium salts are more powerful as compared to potassium salts. Lead calcium alloy meeting the standard specification was successfully recovered from the spent rechargeable acid lead batteries with a very competitive cost to the same alloy prepared from primary resources.

Keywords: rechargeable lead batteries, lead-calcium alloy, waste recovery, flux salts, thermal recovery

Procedia PDF Downloads 363

Authors: Ming-Hong Chen

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In the study, the mechanical and financial feasibility for the compressed air energy storage (CAES) system in the porous media reservoir in Taiwan is evaluated. In 2035, Taiwan aims to install 16.7 GW of wind power and 40 GW of photovoltaic (PV) capacity. However, renewable energy sources often generate more electricity than needed, particularly during winter. Consequently, Taiwan requires long-term, large-scale energy storage systems to ensure the security and stability of its power grid. Currently, the primary large-scale energy storage options are Pumped Hydro Storage (PHS) and Compressed Air Energy Storage (CAES). Taiwan has not ventured into CAES-related technologies due to geological and cost constraints. However, with the imperative of achieving net-zero carbon emissions by 2050, there's a substantial need for the development of a considerable amount of renewable energy. PHS has matured, boasting an overall installed capacity of 4.68 GW. CAES, presenting a similar scale and power generation duration to PHS, is now under consideration. Taiwan's geological composition, being a porous medium unlike salt caves, introduces flow field resistance affecting gas injection and extraction. This study employs a program analysis model to establish the system performance analysis capabilities of CAES. The finite volume model is then used to assess the impact of porous media, and the findings are fed back into the system performance analysis for correction. Subsequently, the financial implications are calculated and compared with existing literature. For Taiwan, the strategic development of CAES technology is crucial, not only for meeting energy needs but also for decentralizing energy allocation, a feature of great significance in regions lacking alternative natural resources.

Keywords: compressed-air energy storage, efficiency, porous media, financial feasibility

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Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Joshue Perez, Javier Araluce

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, the following paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for indepth gesture classification. This tandem of MediaPipe's extraction prowess and MPL's analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System (ROS), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: gesture detection, mediapipe, multiperceptron layer, robot operating system

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Authors: C. Y. Ng, A. M. Johan, A. E. Kajuputra

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Wave-in-deck phenomenon for fixed jacket platforms at shallow water condition has been reported as a notable risk to the workability and reliability of the platform. Reduction in reservoir pressure, due to the extraction of hydrocarbon for an extended period of time, has caused the occurrence of seabed subsidence. Platform experiencing subsidence promotes reduction of air gaps, which eventually allows the waves to attack the bottom decks. The impact of the wave-in-deck generates additional loads to the structure and therefore increases the values of the moment arms. Higher moment arms trigger instability in terms of overturning, eventually decreases the reserve strength ratio (RSR) values of the structure. The mechanics of wave-in-decks, however, is still not well understood and have not been fully incorporated into the design codes and standards. Hence, it is necessary to revisit the current design codes and standards for platform design optimization. The aim of this study is to evaluate the effects of RSR due to wave-in-deck on four-legged jacket platforms in Malaysia. Base shear values with regards to calibration and modifications of wave characteristics were obtained using SESAM GeniE. Correspondingly, pushover analysis is conducted using USFOS to retrieve the RSR. The effects of the contributing factors i.e. the wave height, wave period and water depth with regards to the RSR and base shear values were analyzed and discussed. This research proposal is important in optimizing the design life of the existing and aging offshore structures. Outcomes of this research are expected to provide a proper evaluation of the wave-in-deck mechanics and in return contribute to the current mitigation strategies in managing the issue.

Keywords: wave-in-deck loads, wave effects, water depth, fixed jacket platforms

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Authors: Sankha Chakrabortty, Biswajit Ruj, Parimal Pal

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Methanol is one of the most important chemical products and intermediates. It can be used as a solvent, intermediate or raw material for a number of higher valued products, fuels or additives. From the last one decay, the total global demand of methanol has increased drastically which forces the scientists to produce a large amount of methanol from a renewable source to meet the global demand with a sustainable way. Different types of non-renewable based raw materials have been used for the synthesis of methanol on a large scale which makes the process unsustainable. In this circumstances, photocatalytic conversion of CO₂ into methanol under solar/UV excitation becomes a viable approach to give a sustainable production approach which not only meets the environmental crisis by recycling CO₂ to fuels but also reduces CO₂ amount from the atmosphere. Development of such sustainable production approach for CO₂ conversion into methanol still remains a major challenge in the current research comparing with conventional energy expensive processes. In this backdrop, the development of environmentally friendly materials, like photocatalyst has taken a great perspective for methanol synthesis. Scientists in this field are always concerned about finding an improved photocatalyst to enhance the photocatalytic performance. Graphene-based hybrid and composite materials with improved properties could be a better nanomaterial for the selective conversion of CO₂ to methanol under visible light (solar energy) or UV light. The present invention relates to synthesis an improved heterogeneous graphene-based photocatalyst with improved catalytic activity and surface area. Graphene with enhanced surface area is used as coupled material of copper-loaded titanium oxide to improve the electron capture and transport properties which substantially increase the photoinduced charge transfer and extend the lifetime of photogenerated charge carriers. A fast reduction method through H₂ purging has been adopted to synthesis improved graphene whereas ultrasonication based sol-gel method has been applied for the preparation of graphene coupled copper loaded titanium oxide with some enhanced properties. Prepared photocatalysts were exhaustively characterized using different characterization techniques. Effects of catalyst dose, CO₂ flow rate, reaction temperature and stirring time on the efficacy of the system in terms of methanol yield and productivity have been studied in the present study. The study shown that the newly synthesized photocatalyst with an enhanced surface resulting in a sustained productivity and yield of methanol 0.14 g/Lh, and 0.04 g/gcat respectively, after 3 h of illumination under UV (250W) at an optimum catalyst dosage of 10 g/L having 1:2:3 (Graphene: TiO₂: Cu) weight ratio.

Keywords: renewable energy, CO₂ capture, photocatalytic conversion, methanol

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Authors: Di Luo, Maria Buchberger, Anja Pickhard

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Objectives: The purpose of this study was to assess and compare the diagnostic accuracy of four common morphological approaches, including sonography, computed tomography (CT), positron emission tomography/computed tomography (PET/CT), and magnetic resonance imaging (MRI) for the evaluation of cervical lymph node metastases in head and neck squamous cell carcinoma (HNSCC) patients. Material and Methods: Included in this retrospective study were 26 patients diagnosed with HNSCC between 2010 and 2011 who all underwent sonography, CT, PET/CT, and MRI imaging before neck dissection. Morphological data were compared to the corresponding histopathological results. Statistical analysis was performed with SPSS statistic software (version 26.0), calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for detection of cervical lymph node metastases. Results: The 5-year survival rate of the patient collective was 55.5%.Risk factors for survival included initial primary tumor stage, initial lymph node stage, initial metastasis status, and therapeutic approaches. Cox regression showed initial metastasis status(HR 8.671, 95%CI 1.316-57.123, p=0.025) and therapeutic approaches(HR 6.699, 95%CI 1.746-25.700, p=0.006)to be independent predictive risk factors for survival. Sensitivity was highest for MRI (96% compared to 85% for sonography and 89% for CT and PET/CT). Specificity was comparable with 95 % for CT and 98 % for sonography and PET/CT, but only 68% for MRI. While the MRI showed the least PPV (34%) compared to all other methods (85% for sonography,75% for CT, and 86% for PET/CT), the NPV was comparable in all methods(98-99%). The overall accuracy of cervical lymph node metastases detection was comparable for sonography, CT, and PET/CT with 96%,97%,94%, respectively, while MRI had only 72% accuracy. Conclusion: Since the initial status of metastasis is an independent predictive risk factor for patients’ survival, efficient detection is crucial to plan adequate therapeutic approaches. Sonography, CT, and PET/CT have better diagnostic accuracy than MRI for the evaluation of cervical lymph node metastases in HNSCC patients.

Keywords: cervical lymph node metastases, diagnostic accuracy, head and neck squamous carcinoma, risk factors, survival

Procedia PDF Downloads 117

Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

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Authors: Naim Izet Kajtazi

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Context: The third ventricle colloid cyst (CC) is a benign growth usually located in the third ventricle and can cause various neurological symptoms, including sudden death. Modern surgical interventions may still result in a wide range of complications and cerebral venous thrombosis (CVT) is among them. Process: A 38-year-old female with an existing diagnosis of diabetes mellitus (DM) and hypothyroidism and a six-month history of headaches, blurred vision, and vomiting presented to our clinic three days after the headaches became excessively severe. Neurological examination on admission revealed bilateral papilledema without any associated focal neurological deficits. Brain computed tomography (CT) and magnetic resonance imaging (MRI) confirmed the presence of a third ventricle colloid cyst and associated non-communicating hydrocephalus involving the lateral ventricles. As a result, the patient underwent emergency bilateral external ventricular drainage (EVD) insertion followed by a third ventricular CC excision under neuronavigation through a right frontal craniotomy. Twelve days post-operatively, the patient developed further headaches, followed by a generalized tonic-clonic seizure that led to no postictal neurological deficits. Nonetheless, computed tomography venography of the brain revealed extensive thrombosis of the superior sagittal sinus, inferior sagittal sinus, right sigmoid sinus, and right internal jugular vein. A newly diagnosed CVT was treated with intravenous heparin. The patient was discharged with warfarin, which was discontinued after 12 months. Ten years after her illness, she remained stable and free from any neurological deficits but still suffered from mild chronic headaches. Outcome: Ten years after her illness, she remained stable and free from any neurological deficits but still suffered from mild chronic headaches. Relevance: A preoperative venous study should be performed in all cases to gain a better understanding of the venous anatomy. We advocate meticulous microsurgical techniques to protect the venous system surrounding the foramen of Monro and reduce the amount of retraction during surgery.

Keywords: CVT, seizures, third ventricle colloid cyst, MRI of brain

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Authors: Wojciech Górecki, Anna Sowiżdżał, Grzegorz Machowski, Tomasz Maćkowski, Bartosz Papiernik, Michał Stefaniuk

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The article shows results of the project which aims at evaluating possibilities of effective development and exploitation of natural gas from argillaceous series of the Autochthonous Miocene in the Carpathian Foredeep. To achieve the objective, the research team develop a world-trend based but unique methodology of processing and interpretation, adjusted to data, local variations and petroleum characteristics of the area. In order to determine the zones in which maximum volumes of hydrocarbons might have been generated and preserved as shale gas reservoirs, as well as to identify the most preferable well sites where largest gas accumulations are anticipated a number of task were accomplished. Evaluation of petrophysical properties and hydrocarbon saturation of the Miocene complex is based on laboratory measurements as well as interpretation of well-logs and archival data. The studies apply mercury porosimetry (MICP), micro CT and nuclear magnetic resonance imaging (using the Rock Core Analyzer). For prospective location (e.g. central part of Carpathian Foredeep – Brzesko-Wojnicz area) reprocessing and reinterpretation of detailed seismic survey data with the use of integrated geophysical investigations has been made. Construction of quantitative, structural and parametric models for selected areas of the Carpathian Foredeep is performed on the basis of integrated, detailed 3D computer models. Modeling are carried on with the Schlumberger’s Petrel software. Finally, prospective zones are spatially contoured in a form of regional 3D grid, which will be framework for generation modelling and comprehensive parametric mapping, allowing for spatial identification of the most prospective zones of unconventional gas accumulation in the Carpathian Foredeep. Preliminary results of research works indicate a potentially prospective area for occurrence of unconventional gas accumulations in the Polish part of Carpathian Foredeep.

Keywords: autochthonous Miocene, Carpathian foredeep, Poland, shale gas

Procedia PDF Downloads 223

Authors: Okafor E. Ijeoma, Isimi C. Yetunde, Okoh E. Judith, Kunle O. Olobayo, Emeje O. Martins

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Starch has gained interest as a renewable and environmentally compatible polymer due to the increase in its use. However, starch by itself could not be satisfactorily applied in industrial processes due to some inherent disadvantages such as its hydrophilic character, poor mechanical properties, its inability to withstand processing conditions such as extreme temperatures, diverse pH, high shear rate, freeze-thaw variation and dimensional stability. The range of physical properties of parent starch can be enlarged by chemical modification which invariably enhances their use in a number of applications found in industrial processes and food manufacture. In this study, Manihot esculentus starch was subjected to modification by oxidation. Fourier Transmittance Infra- Red (FTIR) and Raman spectroscopies were used to confirm the synthesis while Scanning Electron Microscopy (SEM) and X- Ray Diffraction (XRD) were used to characterize the new polymer. DPPH (2, 2-diphenyl-1-picryl-hydrazyl-hydrate) free radical assay was used to determine the antioxidant property of the oxidized starch. Our results show that the modification had no significant effect on the foaming capacity as well as on the emulsion capacity. Scanning electron microscopy revealed that oxidation did not alter the predominantly circular-shaped starch granules, while the X-ray pattern of both starch, native and modified were similar. FTIR results revealed a new band at 3007 and 3283cm-1. Differential scanning calorimetry returned two new endothermic peaks in the oxidized starch with an improved gelation capacity and increased enthalpy of gelatinization. The IC50 of oxidized starch was notably higher than that of the reference standard, ascorbic acid.

Keywords: antioxidant activity, DPPH, M. esculentus, oxidation, starch

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