Search results for: Neural Processing Element (NPE)

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

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Authors: Sonja Djilas, Gordana Ćetković, Jasna Čanadanović-Brunet, Vesna Tumbas Šaponjac, Slađana Stajčić, Jelena Vulić, Milica Vinčić

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In recent years, interest in food rich in bioactive compounds, such as polyphenols, increased the advantages of the functional food products. Bioactive components help to maintain health and prevention of diseases such as cancer, cardiovascular and many other degenerative diseases. Recent research has shown that the fruit pomace, a byproduct generated from the production of juice, can be a potential source of valuable bioactive compounds. The use of fruit industrial waste in the processing of functional foods represents an important new step for the food industry. Sour cherries have considerable nutritional, medicinal, dietetic and technological value. According to the production volume of cherries, Serbia ranks seventh in the world, with a share of 7% of the total production. The use of sour cherry pomace has so far been limited to animal feed, even though it can be potentially a good source of polyphenols. For this study, local variety of sour cherry cv. ‘Feketićka’ was chosen for its more intensive taste and deeper red color, indicating high anthocyanin content. The contents of total polyphenols, flavonoids and anthocyanins, as well as radical scavenging activity on DPPH radicals and reducing power of sour cherry juice and pomace were compared using spectrophotometrical assays. According to the results obtained, 66.91% of total polyphenols, 46.77% of flavonoids, 46.77% of total anthocyanins and 47.88% of anthocyanin monomers from sour cherry fruits have been transferred to juice. On the other hand, 29.85% of total polyphenols, 33.09% of flavonoids, 53.23% of total anthocyanins and 52.12% of anthocyanin monomers remained in pomace. Regarding radical scavenging activity, 65.51% of Trolox equivalents from sour cherries were exported to juice, while 34.49% was left in pomace. However, reducing power of sour cherry juice was much stronger than pomace (91.28% and 8.72% of Trolox equivalents from sour cherry fruits, respectively). Based on our results it can be concluded that sour cherry pomace is still a rich source of natural antioxidants, especially anthocyanins with coloring capacity, therefore it can be used for dietary supplements development and food fortification.

Keywords: antioxidants, polyphenols, pomace, sour cherry

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Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

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Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

Procedia PDF Downloads 152

Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

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This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

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Authors: Vivek Rangarajan, Kim G. Klarke

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With overpopulation threatening the world’s ability to feed itself, food production and protection has become a major issue, especially in developing countries. Almost one-third of the food produced for human consumption, around 1.3 billion tonnes, is either wasted or lost annually. Postharvest decay in particular constitutes a major cause of crop loss with about 20% of fruits and vegetables produced lost during postharvest storage, mainly due to fungal disease. Some of the major phytopathogenic fungi affecting postharvest fruit crops in South Africa include Aspergillus, Botrytis, Penicillium, Alternaria and Sclerotinia spp. To date control of fungal phytopathogens has primarily been dependent on synthetic chemical fungicides, but these chemicals pose a significant threat to the environment, mainly due to their xenobiotic properties and tendency to generate resistance in the phytopathogens. Here, an environmentally benign alternative approach to control postharvest fungal phytopathogens in perishable fruit crops has been presented, namely the application of a bio-fungicide in the form of lipopeptide molecules. Lipopeptides are biosurfactants produced by Bacillus spp. which have been established as green, nontoxic and biodegradable molecules with antimicrobial properties. However, since the Bacillus are capable of producing a large number of lipopeptide homologues with differing efficacies against distinct target organisms, the lipopeptide production conditions and strategy are critical to produce the maximum lipopeptide concentration with homologue ratios to specification for optimum bio-fungicide efficacy. Process conditions, and their impact on Bacillus lipopeptide production, were evaluated in fully instrumented laboratory scale bioreactors under well-regulated controlled and defined environments. Factors such as the oxygen availability and trace element and nitrate concentrations had profound influences on lipopeptide yield, productivity and selectivity. Lipopeptide yield and homologue selectivity were enhanced in cultures where the oxygen in the sparge gas was increased from 21 to 30 mole%. The addition of trace elements, particularly Fe2+, increased the total concentration of lipopeptides and a nitrate concentration equivalent to 8 g/L ammonium nitrate resulted in optimum lipopeptide yield and homologue selectivity. Efficacy studies of the culture supernatant containing the crude lipopeptide mixture were conducted using phytopathogens isolated from fruit in the field, identified using genetic sequencing. The supernatant exhibited antifungal activity against all the test-isolates, namely Lewia, Botrytis, Penicillium, Alternaria and Sclerotinia spp., even in this crude form. Thus the lipopeptide product efficacy has been confirmed to control the main diseases, even in the basic crude form. Future studies will be directed towards purification of the lipopeptide product and enhancement of efficacy.

Keywords: antifungal efficacy, biocontrol, lipopeptide production, perishable crops

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Authors: Olaide Ruth Aderibigbe, Oluwatoyin Oluwole

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Pigeon pea is one of the minor leguminous plants; though underutilised, it is used traditionally by farmers to alleviate hunger and malnutrition. Pigeon pea is cultivated in Nigeria by subsistence farmers. It is rich in protein and minerals, however, its utilisation as food is only common among the poor and rural populace who cannot afford expensive sources of protein. One of the factors contributing to its limited use is the high antinutrient content which makes it indigestible, especially when eaten by children. The development of value-added products that can reduce the antinutrient content and make the nutrients more bioavailable will increase the utilisation of the crop and contribute to reduction of malnutrition. This research, therefore, determined the effects of different roasting temperatures (130 0C, 140 0C, and 150 0C) on the proximate, mineral and antinutrient component of a pigeon pea snack. The brown variety of pigeon pea seeds were purchased from a local market- Otto in Lagos, Nigeria. The seeds were cleaned, washed, and soaked in 50 ml of water containing sugar and salt (4:1) for 15 minutes, and thereafter the seeds were roasted at 130 0C, 140 0C, and 150 0C in an electric oven for 10 minutes. Proximate, minerals, phytate, tannin and alkaloid content analyses were carried out in triplicates following standard procedures. The results of the three replicates were polled and expressed as mean±standard deviation; a one-way analysis of variance (ANOVA) and the Least Significance Difference (LSD) were carried out. The roasting temperatures significantly (P<0.05) affected the protein, ash, fibre and carbohydrate content of the snack. Ready-to-eat snack prepared by roasting at 150 0C significantly had the highest protein (23.42±0.47%) compared the ones roasted at 130 0C and 140 0C (18.38±1.25% and 20.63±0.45%, respectively). The same trend was observed for the ash content (3.91±0.11 for 150 0C, 2.36±0.15 for 140 0C and 2.26±0.25 for 130 0C), while the fibre and carbohydrate contents were highest at roasting temperature of 130 0C. Iron, zinc, and calcium were not significantly (P<0.5) affected by the different roasting temperatures. Antinutrients decreased with increasing temperature. Phytate levels recorded were 0.02±0.00, 0.06±0.00, and 0.07±0.00 mg/g; tannin levels were 0.50±0.00, 0.57±0.00, and 0.68±0.00 mg/g, while alkaloids levels were 0.51±0.01, 0.78±0.01, and 0.82±0.01 mg/g for 150 0C, 140 0C, and 130 0C, respectively. These results show that roasting at high temperature (150 0C) can be utilised as a processing technique for increasing protein and decreasing antinutrient content of pigeon pea.

Keywords: antinutrients, pigeon pea, protein, roasting, underutilised species

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Authors: Seyed Mehdi Seyed Alizadeh, Christoph Arns, Shane Latham

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Geomechanical characterization of rocks in detail and its possible implications on flow properties is an important aspect of reservoir characterization workflow. In order to gain more understanding of the microstructure evolution of reservoir rocks under stress a series of axisymmetric triaxial tests were performed on two different analogue rock samples. In-situ compression tests were coupled with high resolution micro-Computed Tomography to elucidate the changes in the pore/grain network of the rocks under pressurized conditions. Two outcrop sandstones were chosen in the current study representing a various cementation status of well-consolidated and weakly-consolidated granular system respectively. High resolution images were acquired while the rocks deformed in a purpose-built compression cell. A detailed analysis of the 3D images in each series of step-wise compression tests (up to the failure point) was conducted which includes the registration of the deformed specimen images with the reference pristine dry rock image. Digital Image Correlation (DIC) technique based on the intensity of the registered 3D subsets and particle tracking are utilized to map the displacement fields in each sample. The results suggest the complex architecture of the localized shear zone in well-cemented Bentheimer sandstone whereas for the weakly-consolidated Castlegate sandstone no discernible shear band could be observed even after macroscopic failure. Post-mortem imaging a sister plug from the friable rock upon undergoing continuous compression reveals signs of a shear band pattern. This suggests that for friable sandstones at small scales loading mode may affect the pattern of deformation. Prior to mechanical failure, the continuum digital image correlation approach can reasonably capture the kinematics of deformation. As failure occurs, however, discrete image correlation (i.e. particle tracking) reveals superiority in both tracking the grains as well as quantifying their kinematics (in terms of translations/rotations) with respect to any stage of compaction. An attempt was made to quantify the displacement field in compression using continuum Digital Image Correlation which is based on the reference and secondary image intensity correlation. Such approach has only been previously applied to unconsolidated granular systems under pressure. We are applying this technique to sandstones with various degrees of consolidation. Such element of novelty will set the results of this study apart from previous attempts to characterize the deformation pattern in consolidated sands.

Keywords: deformation mechanism, displacement field, shear behavior, triaxial compression, X-ray micro-CT

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Authors: Ivelise M. Strozberg, Lucas O. Vale, Maria V. V. Morais

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Expansive soils are characterized by their significant volumetric variations, tending to suffer an increase of this volume when added water in their voids and a decrease of volume when this water is removed. The parameters of resistance (especially the angle of friction, cohesion and specific weight) of expansive or non-expansive soils of the same field present differences, as found in laboratory tests. What is expected is that, through this research, demonstrate that this variation directly affects the results of the calculation of factors of safety for slope stability. The expansibility due to specific clay minerals such as montmorillonites and vermiculites is the most common form of expansion of soils or rocks, causing expansion pressures. These pressures can become an aggravating problem in regions across the globe that, when not previously studied, may present high risks to the enterprise, such as cracks, fissures, movements in structures, breaking of retaining walls, drilling of wells, among others. The study provides results based on analyzes carried out in the Slide 2018 software belonging to the Rocsience group, where the software is a two-dimensional equilibrium slope stability program that calculates the factor of safety or probability of failure of certain surfaces composed of soils or rocks (or both, depending on the situation), - through the methods of: Bishop simplified, Fellenius and Janbu corrected. This research compares the factors of safety of a homogeneous earthfill dam geometry, analysed for operation and end-of-construction situations, having a height of approximately 35 meters, with a slope of 1.5: 1 in the slope downstream and 2: 1 on the upstream slope. As the water level is 32.73m high and the water table is drawn automatically by the Slide program using the finite element method for the operating situation, considering two hypotheses for the use of materials - the first with soils with characteristics of expansion and the second with soils without expansibility. For this purpose, soil samples were collected from the region of São Bento do Una - Pernambuco, Brazil and taken to the soil mechanics laboratory to characterize and determine the percentage of expansibility. There were found 2 types of soils in that area: 1 site of expansive soils (8%) and another with non- expansive ones. Based on the results found, the analysis of the values of factors of safety indicated, both upstream and downstream slopes, the highest values were obtained in the case where there is no presence of materials with expansibility resulting, for one of the situations, values of 1.353 (Fellenius), 1,295 (Janbu corrected) and 1,409 (Bishop simplified). There is a considerable drop in safety factors in cases where soils are potentially expansive, resulting in values for the same situation of 0.859 (Fellenius), 0.809 (Janbu corrected) and 0.842 (Bishop simplified), in the case of higher expansibility (8 %). This shows that the expansibility is a determinant factor in the fall of resistance of soil, determined by the factors of cohesion and angle of friction.

Keywords: dam. slope. software. swelling soil

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 161

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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Hydrogen is expected to become an undisputed player in the ecological transition throughout the next decades. The decarbonization potential offered by this energy vector provides various opportunities for the so-called “hard-to-abate” sectors, including industrial production of iron and steel, glass, refineries and the heavy-duty transport. In this regard, Italy, in the framework of decarbonization plans for the whole European Union, has been considering a wider use of hydrogen to provide an alternative to fossil fuels in hard-to-abate sectors. This work aims to assess and compare different options concerning the pathway to be followed in the development of the future Italian energy system in order to meet decarbonization targets as established by the Paris Agreement and by the European Green Deal, and to infer a techno-economic analysis of the required asset alternatives to be used in that perspective. To accomplish this objective, the Energy System Optimization Model TEMOA-Italy is used, based on the open-source platform TEMOA and developed at PoliTo as a tool to be used for technology assessment and energy scenario analysis. The adopted assessment strategy includes two different scenarios to be compared with a business-as-usual one, which considers the application of current policies in a time horizon up to 2050. The studied scenarios are based on the up-to-date hydrogen-related targets and planned investments included in the National Hydrogen Strategy and in the Italian National Recovery and Resilience Plan, with the purpose of providing a critical assessment of what they propose. One scenario imposes decarbonization objectives for the years 2030, 2040 and 2050, without any other specific target. The second one (inspired to the national objectives on the development of the sector) promotes the deployment of the hydrogen value-chain. These scenarios provide feedback about the applications hydrogen could have in the Italian energy system, including transport, industry and synfuels production. Furthermore, the decarbonization scenario where hydrogen production is not imposed, will make use of this energy vector as well, showing the necessity of its exploitation in order to meet pledged targets by 2050. The distance of the planned policies from the optimal conditions for the achievement of Italian objectives is be clarified, revealing possible improvements of various steps of the decarbonization pathway, which seems to have as a fundamental element Carbon Capture and Utilization technologies for its accomplishment. In line with the European Commission open science guidelines, the transparency and the robustness of the presented results is ensured by the adoption of the open-source open-data model such as the TEMOA-Italy.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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Authors: Azza A. Ali, Hebatalla I. Ahmed, Asmaa Abdelaty

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Background: Manganese (Mn) is a naturally occurring element. Exposure to high levels of Mn causes neurotoxic effects and represents an environmental risk factor. Mn neurotoxicity is poorly understood but changing of AChE activity, monoamines and oxidative stress has been established. Bisphenol A (BPA) is a synthetic compound widely used in the production of polycarbonate plastics. There is considerable debate about whether its exposure represents an environmental risk. Caffeine is one of the major contributors to the dietary antioxidants which prevent oxidative damage and may reduce the risk of chronic neurodegenerative diseases. Epigallocatechin-3-gallate is another major component of green tea and has known interactions with caffeine. It also has health-promoting effects in CNS. Objective: To evaluate the potential protective effects of Caffeine and/or EGCG against Mn-induced neurotoxicity either alone or in the presence of BPA in rats. Methods: Seven groups of rats were used and received daily for 5 weeks MnCl2.4H2O (10 mg/kg, IP) except the control group which received saline, corn oil and distilled H2O. Mn was injected either alone or in combination with each of the following: BPA (50 mg/kg, PO), caffeine (10 mg/kg, PO), EGCG (5 mg/kg, IP), caffeine + EGCG and BPA +caffeine +EGCG. All rats were examined in five behavioral tests (grid, bar, swimming, open field and Y- maze tests). Biochemical changes in monoamines, caspase-3, PGE2, GSK-3B, glutamate, acetyl cholinesterase and oxidative parameters, as well as histopathological changes in the brain, were also evaluated for all groups. Results: Mn significantly increased MDA and nitrite content as well as caspase-3, GSK-3B, PGE2 and glutamate levels while significantly decreased TAC and SOD as well as cholinesterase in the striatum. It also decreased DA, NE and 5-HT levels in the striatum and frontal cortex. BPA together with Mn enhanced oxidative stress generation induced by Mn while increased monoamine content that was decreased by Mn in rat striatum. BPA abolished neuronal degeneration induced by Mn in the hippocampus but not in the substantia nigra, striatum and cerebral cortex. Behavioral examinations showed that caffeine and EGCG co-administration had more pronounced protective effect against Mn-induced neurotoxicity than each one alone. EGCG alone or in combination with caffeine prevented neuronal degeneration in the substantia nigra, striatum, hippocampus and cerebral cortex induced by Mn while caffeine alone prevented neuronal degeneration in the substantia nigra and striatum but still showed some nuclear pyknosis in cerebral cortex and hippocampus. The marked protection of caffeine and EGCG co-administration also confirmed by the significant increase in TAC, SOD, ACHE, DA, NE and 5-HT as well as the decrease in MDA, nitrite, caspase-3, PGE2, GSK-3B, the glutamic acid in the striatum. Conclusion: Neuronal degeneration induced by Mn showed some inhibition with BPA exposure despite the enhancement in oxidative stress generation. Co-administration of EGCG and caffeine can protect against neuronal degeneration induced by Mn and improve behavioral deficits associated with its neurotoxicity. The protective effect of EGCG was more pronounced than that of caffeine even with BPA co-exposure.

Keywords: manganese, bisphenol a, caffeine, epigallocatechin-3-gallate, neurotoxicity, behavioral tests, rats

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Authors: Neumoin Anton Ivanovich, Opra Denis Pavlovich

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Materials based on titanium oxide compounds are widely used in such areas as solar energy, photocatalysis, food industry and hygiene products, biomedical technologies, etc. Demand for them has also formed in the battery industry (an example of this is the commercialization of Li4Ti5O12), where much attention has recently been paid to the development of next-generation systems and technologies, such as sodium-ion batteries. This dictates the need to search for new materials with improved characteristics, as well as ways to obtain them that meet the requirements of scalability. One of the ways to solve these problems can be the creation of nanomaterials that often have a complex of physicochemical properties that radically differ from the characteristics of their counterparts in the micro- or macroscopic state. At the same time, it is important to control the texture (specific surface area, porosity) of such materials. In view of the above, among other methods, the hydrothermal technique seems to be suitable, allowing a wide range of control over the conditions of synthesis. In the present study, a method was developed for the preparation of mesoporous nanostructured sodium trititanate (Na2Ti3O7) with a hierarchical architecture. The materials were synthesized by hydrothermal processing and exhibit a complex hierarchically organized two-layer architecture. At the first level of the hierarchy, materials are represented by particles having a roughness surface, and at the second level, by one-dimensional nanotubes. The products were found to have high specific surface area and porosity with a narrow pore size distribution (about 6 nm). As it is known, the specific surface area and porosity are important characteristics of functional materials, which largely determine the possibilities and directions of their practical application. Electrochemical impedance spectroscopy data show that the resulting sodium trititanate has a sufficiently high electrical conductivity. As expected, the synthesized complexly organized nanoarchitecture based on sodium trititanate with a porous structure can be practically in demand, for example, in the field of new generation electrochemical storage and energy conversion devices.

Keywords: sodium trititanate, hierarchical materials, mesoporosity, nanotubes, hydrothermal synthesis

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Authors: A. Aslihan Gokaltun, Martin L. Yarmush, Ayse Asatekin, O. Berk Usta

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Poly(dimethylsiloxane) (PDMS) is one of the most widely used materials in the fabrication of microfluidic devices. It is easily patterned and can replicate features down to nanometers. Its flexibility, gas permeability that allows oxygenation, and low cost also drive its wide adoption. However, a major drawback of PDMS is its hydrophobicity and fast hydrophobic recovery after surface hydrophilization. This results in significant non-specific adsorption of proteins as well as small hydrophobic molecules such as therapeutic drugs limiting the utility of PDMS in biomedical microfluidic circuitry. While silicon, glass, and thermoplastics have been used, they come with problems of their own such as rigidity, high cost, and special tooling needs, which limit their use to a smaller user base. Many strategies to alleviate these common problems with PDMS are lack of general practical applicability, or have limited shelf lives in terms of the modifications they achieve. This restricts large scale implementation and adoption by industrial and research communities. Accordingly, we aim to tailor biocompatible PDMS surfaces by developing a simple and one step bulk modification approach with novel smart materials to reduce non-specific molecular adsorption and to stabilize long-term cell analysis with PDMS substrates. Smart polymers that blended with PDMS during device manufacture, spontaneously segregate to surfaces when in contact with aqueous solutions and create a < 1 nm layer that reduces non-specific adsorption of organic and biomolecules. Our methods are fully compatible with existing PDMS device manufacture protocols without any additional processing steps. We have demonstrated that our modified PDMS microfluidic system is effective at blocking the adsorption of proteins while retaining the viability of primary rat hepatocytes and preserving the biocompatibility, oxygen permeability, and transparency of the material. We expect this work will enable the development of fouling-resistant biomedical materials from microfluidics to hospital surfaces and tubing.

Keywords: cell culture, microfluidics, non-specific protein adsorption, PDMS, smart polymers

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Authors: Svetlana Strinyuk, Viacheslav Lanin

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Academic English has become lingua franca for international scientific community which stimulates universities to introduce English for Specific Purposes (EAP) courses into curriculum. Teaching L2 EAP students might be fulfilled with corpus technologies and digital stylistics. A special software developed to reach the manifold task of teaching, assessing and researching academic writing of L2 students on basis of digital stylistics and multidimensional analysis was created. A set of annotations (style markers) – grammar, lexical and syntactic features most significant of academic writing was built. Contrastive comparison of two corpora “model corpus”, subject domain limited papers published by competent writers in leading academic journals, and “students’ corpus”, subject domain limited papers written by last year students allows to receive data about the features of academic writing underused or overused by L2 EAP student. Both corpora are tagged with a special software created in GATE Developer. Style markers within the framework of research might be replaced depending on the relevance and validity of the result which is achieved from research corpora. Thus, selecting relevant (high frequency) style markers and excluding less relevant, i.e. less frequent annotations, high validity of the model is achieved. Software allows to compare the data received from processing model corpus to students’ corpus and get reports which can be used in teaching and assessment. The less deviation from the model corpus students demonstrates in their writing the higher is academic writing skill acquisition. The research showed that several style markers (hedging devices) were underused by L2 EAP students whereas lexical linking devices were used excessively. A special software implemented into teaching of EAP courses serves as a successful visual aid, makes assessment more valid; it is indicative of the degree of writing skill acquisition, and provides data for further research.

Keywords: corpus technologies in EAP teaching, multidimensional analysis, GATE Developer, corpus stylistics

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Authors: Tom Nakotte, Hongmei Luo

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Lead chalcogenide-based (PbS, PbSe, and PbTe) quantum dots (QDs) were synthesized for the purpose of implementing them in radiation detectors. Pb based materials have long been of interest for gamma and x-ray detection due to its high absorption cross section and Z number. The emphasis of the studies was on exploring how to control charge carrier transport within thin films containing the QDs. The properties of QDs itself can be altered by changing the size, shape, composition, and surface chemistry of the dots, while the properties of carrier transport within QD films are affected by post-deposition treatment of the films. The QDs were synthesized using colloidal synthesis methods and films were grown using multiple film coating techniques, such as spin coating and doctor blading. Current QD radiation detectors are based on the QD acting as fluorophores in a scintillation detector. Here the viability of using QDs in solid-state radiation detectors, for which the incident detectable radiation causes a direct electronic response within the QD film is explored. Achieving high sensitivity and accurate energy quantification in QD radiation detectors requires a large carrier mobility and diffusion lengths in the QD films. Pb chalcogenides-based QDs were synthesized with both traditional oleic acid ligands as well as more weakly binding oleylamine ligands, allowing for in-solution ligand exchange making the deposition of thick films in a single step possible. The PbS and PbSe QDs showed better air stability than PbTe. After precipitation the QDs passivated with the shorter ligand are dispersed in 2,6-difloupyridine resulting in colloidal solutions with concentrations anywhere from 10-100 mg/mL for film processing applications, More concentrated colloidal solutions produce thicker films during spin-coating, while an extremely concentrated solution (100 mg/mL) can be used to produce several micrometer thick films using doctor blading. Film thicknesses of micrometer or even millimeters are needed for radiation detector for high-energy gamma rays, which are of interest for astrophysics or nuclear security, in order to provide sufficient stopping power.

Keywords: colloidal synthesis, lead chalcogenide, radiation detectors, quantum dots

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Authors: Bill D. Geis

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Suicide wrongful death forensic cases are the fastest rising tort in mental health law. It is estimated that suicide-related cases have accounted for 15% of U.S. malpractice claims since 2006. Most suicide-related personal injury claims fall into the legal category of “wrongful death.” Though mental health experts may be called on to address a range of forensic questions in wrongful death cases, the central consultation that most experts provide is about the negligence element—specifically, the issue of whether the clinician met the clinical standard of care in assessing, treating, and managing the deceased person’s mental health care. Standards of care, varying from U.S. state to state, are broad and address what a reasonable clinician might do in a similar circumstance. This fact leaves the issue of the suicide standard of care, in each case, up to forensic experts to put forth a reasoned estimate of what the standard of care should have been in the specific case under litigation. Because the general state guidelines for standard of care are broad, forensic experts are readily retained to provide scientific and clinical opinions about whether or not a clinician met the standard of care in their suicide assessment, treatment, and management of the case. In the past and in much of current practice, the assessment of suicide has centered on the elicitation of verbalized suicide ideation. Research in recent years, however, has indicated that the majority of persons who end their lives do not say they are suicidal at their last medical or psychiatric contact. Near-term risk assessment—that goes beyond verbalized suicide ideation—is needed. Our previous research employed structural equation modeling to predict lethal suicide risk--eight negative thought patterns (feeling like a burden on others, hopelessness, self-hatred, etc.) mediated by nine transdiagnostic clinical factors (mental torment, insomnia, substance abuse, PTSD intrusions, etc.) were combined to predict acute lethal suicide risk. This structural equation model, the Lethal Suicide Risk Pattern (LSRP), Acute model, had excellent goodness-of-fit [χ2(df) = 94.25(47)***, CFI = .98, RMSEA = .05, .90CI = .03-.06, p(RMSEA = .05) = .63. AIC = 340.25, ***p < .001.]. A further SEQ analysis was completed for this paper, adding a measure of Acute Suicide Ideation to the previous SEQ. Acceptable prediction model fit was no longer achieved [χ2(df) = 3.571, CFI > .953, RMSEA = .075, .90% CI = .065-.085, AIC = 529.550].This finding suggests that, in this additional study, immediate verbalized suicide ideation information was unhelpful in the assessment of lethal risk. The LSRP and other dynamic, near-term risk models (such as the Acute Suicide Affective Disorder Model and the Suicide Crisis Syndrome Model)—going beyond elicited suicide ideation—need to be incorporated into current clinical suicide assessment training. Without this training, the standard of care for suicide assessment is out of sync with current research—an emerging dilemma for the forensic evaluation of suicide wrongful death cases.

Keywords: forensic evaluation, standard of care, suicide, suicide assessment, wrongful death

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Authors: Cemil Atakara, Hüseyin Eryaman

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The use of glass as an envelope of a building has been increasing in the twentieth century. For more transparency and dematerialization new glass facade types have emerged in the past two decades which depends on point fixed glazing system (PFGS). The aim of this study is to analyze of the PFGS systems which are used on the glass curtain wall according to their types, degree, architectural and structural effects. This new system is desired because it enhances the transparency of the façade and it minimizes the component of the frames or of the profiles. This PFGS led to new structural elements which use cables, rods, trusses when designing a glass building facades, this structural element called the suspended glass system with pre-stressed cable truss (SGSPCT) which has been used for the first time in 1980 in Serres building. The twenty glass buildings which are designed in different systems have been analyzed during this study. After these analyses five selected SGSPCT building analyzed deeply and one skeletal frame building selected from Lefkosa redesigned according to the analysis results. These selected buildings have been included of various cable-truss system typologies and degree. The methodology of this study is building analysis method and literature survey with the help of books, articles, magazines, drawings, internet sources and applied connection details of the glass buildings. The selected five glass buildings and case building have been detailed analyzed with their architectural drawings, photographs and details. A gridshell structure can be compared with a shell structure; it consists of discrete members connecting nodal points. As these nodal points lie on the surface of an imaginary shell, their shapes function almost identically. Difference between shell and gridshell structures can be found in the fact that, due to their free-form and thus, due to the presence of bending forces, gridshells are required to resist loading through their cross-section. This research is divided into parts. A general study about the glass building and cable-glass and grid shell system will be done in the first chapters. Structural analyses and detailed analyses with schematic drawings with the plans, sections of the selected buildings will be explained in the second part. The third part it consists of the advantages and disadvantages of the use of the SGSPCT and Grid Shell in architecture. The study consists of four chapters including the introduction chapter. The general information of the SGSPCT and glazing system has been mentioned in the first chapter. Structural features, typologies, transparency principle and analytical information on systems have been explained of the selected buildings in the second chapter. The detailed analyses of case building have been done according to their schematic drawings with the plans, sections in the third chapter. After third chapter SGSPCT discussed on to the case building and selected buildings. SGSPCT systems have been compared with their advantages and disadvantages to the other systems. Advantages of cable-truss systems and SGSPCT have been concluded that the use of glass substrates in the last chapter.

Keywords: cable truss, glass, grid shell, transparency

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Authors: N. Stevulova, I. Schwarzova, V. Hospodarova, J. Junak, J. Briancin

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Sustainability is becoming a priority for developers and the use of environmentally friendly materials is increasing. Nowadays, the application of raw materials from renewable sources to building materials has gained a significant interest in this research area. Lignocellulosic aggregates and cellulosic fibers are coming from many different sources such as wood, plants and waste. They are promising alternative materials to replace synthetic, glass and asbestos fibers as reinforcement in inorganic matrix of composites. Natural fibers are renewable resources so their cost is relatively low in comparison to synthetic fibers. With the consideration of environmental consciousness, natural fibers are biodegradable so their using can reduce CO₂ emissions in the building materials production. The use of cellulosic fibers in cementitious matrices have gained importance because they make the composites lighter at high fiber content, they have comparable cost - performance ratios to similar building materials and they could be processed from waste paper, thus expanding the opportunities for waste utilization in cementitious materials. The main objective of this work is to find out the possibility of using different wastes: hemp hurds as waste of hemp stem processing and recycled fibers obtained from waste paper for making cement composite products such as mortars based on cellulose fibers. This material was made of cement mortar containing organic filler based on hemp hurds and recycled waste paper. In addition, the effects of fibers and their contents on some selected physical and mechanical properties of the fiber-cement plaster composites have been investigated. In this research organic material have used to mortars as 2.0, 5.0 and 10.0 % replacement of cement weight. Reference sample is made for comparison of physical and mechanical properties of cement composites based on recycled cellulosic fibers and lignocellulosic aggregates. The prepared specimens were tested after 28 days of curing in order to investigate density, compressive strength and water absorbability. Scanning Electron Microscopy examination was also carried out.

Keywords: Hemp hurds, organic filler, recycled paper, sustainable building materials

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Authors: Siti Rahmawati

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Indonesia has had long period of monetary economic crisis and it is followed by an upward trend in the price of fuel oil. This situation impacts all aspects of tuna fishermen community. For instance, the basic needs of fishing communities increase and the lower purchasing power then lead to economic and social instability as well as the health of fishermen household. To understand this AHP method is applied to acknowledge the model of tuna fisheries management priorities and cold chain marketing channel and the utilization levels that impact on human health. The study is designed as a development research with the number of 180 respondents. The data were analyzed by Analytical Hierarchy Process (AHP) method. The development of tuna fishery business can improve productivity of production with economic empowerment activities for coastal communities, improving the competitiveness of products, developing fish processing centers and provide internal capital for the development of optimal fishery business. From economic aspects, fishery business is more attracting because the benefit cost ratio of 2.86. This means that for 10 years, the economic life of this project can work well as B/C> 1 and therefore the rate of investment is economically viable. From the health aspects, tuna can reduce the risk of dying from heart disease by 50%, because tuna contain selenium in the human body. The consumption of 100 g of tuna meet 52.9% of the selenium in the body and activating the antioxidant enzyme glutathione peroxidaxe which can protect the body from free radicals and stimulate various cancers. The results of the analytic hierarchy process that the quality of tuna products is the top priority for export quality as well as quality control in order to compete in the global market. The implementation of the policy can increase the income of fishermen and reduce the poverty of fishermen households and have impact on the human health whose has high risk of disease.

Keywords: management of tuna, social, economic, health

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Authors: Muhammad Qasim, Dolors Puigjaner, Josep Maria López, Joan Herrero, Carme Olivé, Gerard Fortuny

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Computational modeling of the human pelvis using the finite element (FE) method has become extremely important to understand the mechanics of prostate motion and deformation when transrectal ultrasound (TRUS) guided biopsy is performed. The number of reliable and validated hyperelastic constitutive FE models of the male pelvis region is limited, and given models did not precisely describe the anatomical behavior of pelvis organs, mainly of the prostate and its neoplasms location. The motion and deformation of the prostate during TRUS-guided biopsy makes it difficult to know the location of potential lesions in advance. When using this procedure, practitioners can only provide roughly estimations for the lesions locations. Consequently, multiple biopsy samples are required to target one single lesion. In this study, the whole pelvis model (comprised of the rectum, bladder, pelvic muscles, prostate transitional zone (TZ), and peripheral zone (PZ)) is used for the simulation results. An isotropic hyperelastic approach (Signorini model) was used for all the soft tissues except the vesical muscles. The vesical muscles are assumed to have a linear elastic behavior due to the lack of experimental data to determine the constants involved in hyperelastic models. The tissues and organ geometry is taken from the existing literature for 3D meshes. Then the biomechanical parameters were obtained under different testing techniques described in the literature. The acquired parametric values for uniaxial stress/strain data are used in the Signorini model to see the anatomical behavior of the pelvis model. The five mesh nodes in terms of small prostate lesions are selected prior to biopsy and each lesion’s final position is targeted when TRUS probe force of 30 N is applied at the inside rectum wall. Code_Aster open-source software is used for numerical simulations. Moreover, the overall effects of pelvis organ deformation were demonstrated when TRUS–guided biopsy is induced. The deformation of the prostate and neoplasms displacement showed that the appropriate material properties to organs altered the resulting lesion's migration parametrically. As a result, the distance traveled by these lesions ranged between 3.77 and 9.42 mm. The lesion displacement and organ deformation are compared and analyzed with our previous study in which we used linear elastic properties for all pelvic organs. Furthermore, the visual comparison of axial and sagittal slices are also compared, which is taken for Magnetic Resource Imaging (MRI) and TRUS images with our preliminary study.

Keywords: code-aster, magnetic resonance imaging, neoplasms, transrectal ultrasound, TRUS-guided biopsy

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Authors: German Hernandez-Alonso, Antonio Lazcano, Arturo Becerra

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Until today, viruses remain controversial and poorly understood; about their origin, this problem represents an enigma and one of the great challenges for the contemporary biology. Three main theories have tried to explain the origin of viruses: regressive evolution, escaped host gene, and pre-cellular origin. Under the perspective of the escaped host gene theory, it can be assumed a cellular origin of viral components, like protein RNA-binding domains. These universal distributed RNA-binding domains are related to the RNA metabolism processes, including transcription, processing, and modification of transcripts, translation, RNA degradation and its regulation. In the case of viruses, these domains are present in important viral proteins like helicases, nucleases, polymerases, capsid proteins or regulation factors. Therefore, they are implicated in the replicative cycle and parasitic processes of viruses. That is why it is possible to think that those domains present low levels of divergence due to selective pressures. For these reasons, the main goal for this project is to create a catalogue of the RNA-binding domains found in all the available viral proteomes, using bioinformatics tools in order to analyze its evolutionary process, and thus shed light on the general virus evolution. ProDom database was used to obtain larger than six thousand RNA-binding domain families that belong to the three cellular domains of life and some viral groups. From the sequences of these families, protein profiles were created using HMMER 3.1 tools in order to find distant homologous within greater than four thousand viral proteomes available in GenBank. Once accomplished the analysis, almost three thousand hits were obtained in the viral proteomes. The homologous sequences were found in proteomes of the principal Baltimore viral groups, showing interesting distribution patterns that can contribute to understand the evolution of viruses and their host-virus interactions. Presence of cellular RNA-binding domains within virus proteomes seem to be explained by closed interactions between viruses and their hosts. Recruitment of these domains is advantageous for the viral fitness, allowing viruses to be adapted to the host cellular environment.

Keywords: bioinformatics tools, distant homology, RNA-binding domains, viral evolution

Procedia PDF Downloads 382

Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Kevin Tinkham, Ella Quigley

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Structural integrity for cladding products is a key performance parameter, especially concerning fire performance. Cladding products such as PIR-based sandwich panels are tested rigorously, in line with industrial standards. Physical fire tests are necessary to ensure the customer's safety but can give little information about critical behaviours that can help develop new materials. Numerical modelling is a tool that can help investigate a fire's behaviour further by replicating the fire test. However, fire is an interdisciplinary problem as it is a chemical reaction that behaves fluidly and impacts structural integrity. An analysis using Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) is needed to capture all aspects of a fire performance test. One method is a two-way coupling analysis that imports the updated changes in thermal data, due to the fire's behaviour, to the FEA solver in a series of iterations. In light of our recent work with Tata Steel U.K using a two-way coupling methodology to determine the fire performance, it has been shown that a program called FDS-2-Abaqus can make predictions of a BS 476 -22 furnace test with a degree of accuracy. The test demonstrated the fire performance of Tata Steel U.K Trisomet product, a Polyisocyanurate (PIR) based sandwich panel used for cladding. Previous works demonstrated the limitations of the current version of the program, the main limitation being the computational cost of modelling three Trisomet panels, totalling an area of 9 . The computational cost increases substantially, with the intention to scale up to an LPS 1181-1 test, which includes a total panel surface area of 200 .The FDS-2-Abaqus program is developed further within this paper to overcome this obstacle and better accommodate Tata Steel U.K PIR sandwich panels. The new developments aim to reduce the computational cost and error margin compared to experimental data. One avenue explored is a multi-scale approach in the form of Reduced Order Modeling (ROM). The approach allows the user to include refined details of the sandwich panels, such as the overlapping joints, without a computationally costly mesh size.Comparative studies will be made between the new implementations and the previous study completed using the original FDS-2-ABAQUS program. Validation of the study will come from physical experiments in line with governing body standards such as BS 476 -22 and LPS 1181-1. The physical experimental data includes the panels' gas and surface temperatures and mechanical deformation. Conclusions are drawn, noting the new implementations' impact factors and discussing the reasonability for scaling up further to a whole warehouse.

Keywords: fire testing, numerical coupling, sandwich panels, thermo fluids

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Authors: Massimiliano Panella, Sara Bortoluzzi, Sophia Russotto, Daniele Nicolini, Carmela Rinaldi

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Osteoporosis affects more than 200 million people worldwide. About 75% of osteoporosis cases are undiagnosed or diagnosed only when a bone fracture occurs. Since osteoporosis related fractures are significant determinants of the burden of disease and health and social costs of aging populations, we believe that this is the early identification and treatment of high-risk patients should be a priority in actual healthcare systems. Screening for osteoporosis by dual energy x-ray absorptiometry (DEXA) is not cost-effective for general population. An alternative is pulse-echo ultrasound (PEUS) because of the minor costs. To this end, we developed an early detection program for osteoporosis with PEUS, and we evaluated is possible impact and sustainability. We conducted a cross-sectional study including 1,050 people in Italy. Subjects with >1 major or >2 minor risk factors for osteoporosis were invited to PEUS bone mass density (BMD) measurement at the proximal tibia. Based on BMD values, subjects were classified as healthy subjects (BMD>0.783 g/cm²) and pathological including subjects with suspected osteopenia (0.783≤BMD>0.719 g/cm²) or osteoporosis (BMD ≤ 0.719 g/cm²). The responder rate was 60.4% (634/1050). According to the risk, PEUS scan was recommended to 436 people, of whom 300 (mean age 45.2, 81% women) accepted to participate. We identified 240 (80%) healthy and 60 (20%) pathological subjects (47 osteopenic and 13 osteoporotic). We observed a significant association between high risk people and reduced bone density (p=0.043) with increased risks for female gender, older ages, and menopause (p<0.01). The yearly cost of the screening program was 8,242 euros. With actual Italian fracture incidence rates in osteoporotic patients, we can reasonably expect in 20 years that at least 6 fractures will occur in our sample. If we consider that the mean costs per fracture in Italy is today 16,785 euros, we can estimate a theoretical cost of 100,710 euros. According to literature, we can assume that the early treatment of osteoporosis could avoid 24,170 euros of such costs. If we add the actual yearly cost of the treatments to the cost of our program and we compare this final amount of 11,682 euros to the avoidable costs of fractures (24,170 euros) we can measure a possible positive benefits/costs ratio of 2.07. As a major outcome, our study let us to early identify 60 people with a significant bone loss that were not aware of their condition. This diagnostic anticipation constitutes an important element of value for the project, both for the patients, for the preventable negative outcomes caused by the fractures, and for the society in general, because of the related avoidable costs. Therefore, based on our finding, we believe that the PEUS based screening performed could be a cost-effective approach to early identify osteoporosis. However, our study has some major limitations. In fact, in our study the economic analysis is based on theoretical scenarios, thus specific studies are needed for a better estimation of the possible benefits and costs of our program.

Keywords: osteoporosis, prevention, public health, screening

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Mustafa M. Donma, Orkide Donma

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Iron is physiologically essential. However, it also participates in the catalysis of free radical formation reactions. Its deficiency is associated with amplified health risks. This trace element establishes some links with another physiological process related to cell death, apoptosis. Both iron deficiency and iron overload are closely associated with apoptosis. Soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) has the ability to trigger apoptosis and plays a dual role in the physiological versus pathological inflammatory responses of tissues. The aim of this study was to investigate the status of these parameters as well as the associations among them in children with obesity, a low-grade inflammatory state. The study was performed on groups of children with normal body mass index (N-BMI) and obesity. Forty-three children were included in each group. Based upon age- and sex-adjusted BMI percentile tables prepared by World Health Organization, children whose values varied between 85 and 15 were included in N-BMI group. Children whose BMI percentile values were between 99 and 95 comprised obese (OB) group. Institutional ethical committee approval and informed consent forms were taken prior to the study. Anthropometric measurements (weight, height, waist circumference, hip circumference, head circumference, neck circumference) and blood pressure values (systolic blood pressure and diastolic blood pressure) were recorded. Routine biochemical analysis including serum iron, total iron binding capacity (TIBC), transferrin saturation percent (Tf Sat %), and ferritin were performed. Soluble tumor necrosis factor-like weak inducer of apoptosis levels were determined by enzyme-linked immunosorbent assay. Study data was evaluated using appropriate statistical tests performed by the statistical program SPSS. Serum iron levels were 91±34 mcrg/dl and 75±31 mcrg/dl in N-BMI and OB children, respectively. The corresponding values for TIBC, Tf Sat %, ferritin were 265 mcrg/dl vs 299 mcrg/dl, 37.2±19.1 % vs 26.7±14.6 %, and 41±25 ng/ml vs 44±26 ng/ml. in N-BMI and OB groups, sTWEAK concentrations were measured as 351 ng/L and 325 ng/L, respectively (p>0.05). Correlation analysis revealed significant associations between sTWEAK levels and iron related parameters (p<0.05) except ferritin. In conclusion, iron contributes to apoptosis. Children with iron deficiency have decreased apoptosis rate in comparison with that of healthy children. sTWEAK is inducer of apoptosis. Obese children had lower levels of both iron and sTWEAK. Low levels of sTWEAK are associated with several types of cancers and poor survival. Although iron deficiency state was not observed in this study, the correlations detected between decreased sTWEAK and decreased iron as well as Tf Sat % values were valuable findings, which point out decreased apoptosis. This may induce a proinflammatory state, potentially leading to malignancies in the future lives of obese children.

Keywords: apoptosis, children, iron-related parameters, obesity, soluble tumor necrosis factor-like weak inducer of apoptosis

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Authors: Andrew Fox, Tao Zhang, Yuanhong Zhao, Qingping Yang

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The furniture manufacturing industry has been slow in general to adopt the latest manufacturing technologies, historically relying heavily upon specialised conventional machinery. This approach not only requires high levels of specialist process knowledge, training, and capital investment but also suffers from significant subtractive manufacturing waste and high logistics costs due to the requirement for centralised manufacturing, with high levels of furniture product not re-cycled or re-used. This paper aims to address the problems by introducing suitable digital manufacturing technologies to create step changes in furniture manufacturing design, as the traditional design practices have been reported as building in 80% of environmental impact. In this paper, a 3D printing robot for furniture manufacturing is reported. The 3D printing robot mainly comprises a KUKA industrial robot, an Arduino microprocessor, and a self-assembled screw fed extruder. Compared to traditional 3D printer, the 3D printing robot has larger motion range and can be easily upgraded to enlarge the maximum size of the printed object. Generative design is also investigated in this paper, aiming to establish a combined design methodology that allows assessment of goals, constraints, materials, and manufacturing processes simultaneously. ‘Matrixing’ for part amalgamation and product performance optimisation is enabled. The generative design goals of integrated waste reduction increased manufacturing efficiency, optimised product performance, and reduced environmental impact institute a truly lean and innovative future design methodology. In addition, there is massive future potential to leverage Single Minute Exchange of Die (SMED) theory through generative design post-processing of geometry for robot manufacture, resulting in ‘mass customised’ furniture with virtually no setup requirements. These generatively designed products can be manufactured using the robot based additive manufacturing. Essentially, the 3D printing robot is already functional; some initial goals have been achieved and are also presented in this paper.

Keywords: additive manufacturing, generative design, robot, sustainability

Procedia PDF Downloads 125

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: A. Kyprianou, A. Tjirkallis

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Condition monitoring of structures in service is very important as it provides information about the risk of damage development. One of the essential constituents of structural condition monitoring is the damage detection methodology. In the context of condition monitoring of in service structures a damage detection methodology analyses data obtained from the structure while it is in operation. Usually, this means that the data could be affected by operational and environmental conditions in a way that could mask the effects of a possible damage on the data. This, depending on the damage detection methodology, could lead to either false alarms or miss existing damages. In this article a damage detection methodology that is based on the Spatio-temporal continuous wavelet transform (SPT-CWT) analysis of a sequence of experimental time responses of a cantilever beam is proposed. The cantilever is subjected to white and pink noise excitation to simulate different operating conditions. In addition, in order to simulate changing environmental conditions, the cantilever is subjected to heating by a heat gun. The response of the cantilever beam is measured by a high-speed camera. Edges are extracted from the series of images of the beam response captured by the camera. Subsequent processing of the edges gives a series of time responses on 439 points on the beam. This sequence is then analyzed using the SPT-CWT to identify damage. The algorithm proposed was able to clearly identify damage under any condition when the structure was excited by white noise force. In addition, in the case of white noise excitation, the analysis could also reveal the position of the heat gun when it was used to heat the structure. The analysis could identify the different operating conditions i.e. between responses due to white noise excitation and responses due to pink noise excitation. During the pink noise excitation whereas damage and changing temperature were identified it was not possible to clearly identify the effect of damage from that of temperature. The methodology proposed in this article for damage detection enables the separation the damage effect from that due to temperature and excitation on data obtained from measurements of a cantilever beam. This methodology does not require information about the apriori state of the structure.

Keywords: spatiotemporal continuous wavelet transform, damage detection, data normalization, varying temperature

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Authors: Zeinab Farhat, Nicolas Errien, Romuald Wernert, Véronique Verriele, Frédéric Amiard, Philippe Daniel

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Ovarian cancer, also known as the silent killer, is the fifth most common cancer among women worldwide, and its death rate is higher than that of other gynecological cancers. The low survival rate of women with high-grade serous ovarian carcinoma highlights the critical need for the development of new methods for early detection and diagnosis of the disease. The aim of this study was to evaluate if Raman spectroscopy combined with chemometric methods such as Principal Component Analysis (PCA) could differentiate between cancerous and normal tissues from different types of samples, such as paraffin embedding, chemical deparaffinized, formalin-fixed and fresh samples of the same normal and malignant ovarian tissue. The method was applied specifically to two critical spectral regions: the signature region (860-1000 〖cm〗^(-1)) and the high-frequency region (2800-3100 〖cm〗^(-1) ). The mean spectra of paraffin-embedded in normal and malignant tissues showed almost similar intensity. On the other hand, the mean spectra of normal and cancer tissues from chemical deparaffinized, formalin-fixed, and fresh samples show significant intensity differences. These spectral differences reflect variations in the molecular composition of the tissues, particularly lipids and proteins. PCA, which was applied to distinguish between cancer and normal tissues, was performed on whole spectra and on selected regions—the PCA score plot of paraffin-embedded shows considerable overlap between the two groups. However, the PCA score of chemicals deparaffinized, formalin-fixed, and fresh samples showed a good discrimination of tissue types. Our findings were validated by analyses of a set of samples whose status (normal and cancerous) was not previously known. The results of this study suggest that Raman Spectroscopy associated with PCA methods has the capacity to provide clinically significant differentiation between normal and cancerous ovarian tissues.

Keywords: Raman spectroscopy, ovarian cancer, signal processing, Principal Component Analysis, classification

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