Search results for: miRNA:mRNA target prediction

Authors: Sharib Ahmed, Mansoor Rafi, Kamran Ali Awan, Faraz Khaskhali, Amir Maqbool, Altaf Hashmi

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Medical linear accelerators (LINAC’s) used in radiotherapy treatments produce undesired neutrons when they are operated at energies above 8 MeV, both in electron and photon configuration. Neutrons are produced by high-energy photons and electrons through electronuclear (e, n) a photonuclear giant dipole resonance (GDR) reactions. These reactions occurs when incoming photon or electron incident through the various materials of target, flattening filter, collimators, and other shielding components in LINAC’s structure. These neutrons may reach directly to the patient, or they may interact with the surrounding materials until they become thermalized. A work has been set up to study the effect of different parameter on the production of neutron around the room by photonuclear reactions induced by photons above ~8 MeV. One of the commercial available neutron detector (Ludlum Model 42-31H Neutron Detector) is used for the detection of thermal and fast neutrons (0.025 eV to approximately 12 MeV) inside and outside of the treatment room. Measurements were performed for different field sizes at 100 cm source to surface distance (SSD) of detector, at different distances from the isocenter and at the place of primary and secondary walls. Other measurements were performed at door and treatment console for the potential radiation safety concerns of the therapists who must walk in and out of the room for the treatments. Exposures have taken place from Elekta Synergy® linear accelerators for two different energies (10 MV and 18 MV) for a given 200 MU’s and dose rate of 600 MU per minute. Results indicates that neutron doses at 100 cm SSD depend on accelerator characteristics means jaw settings as jaws are made of high atomic number material so provides significant interaction of photons to produce neutrons, while doses at the place of larger distance from isocenter are strongly influenced by the treatment room geometry and backscattering from the walls cause a greater doses as compare to dose at 100 cm distance from isocenter. In the treatment room the ambient dose equivalent due to photons produced during decay of activation nuclei varies from 4.22 mSv.h−1 to 13.2 mSv.h−1 (at isocenter),6.21 mSv.h−1 to 29.2 mSv.h−1 (primary wall) and 8.73 mSv.h−1 to 37.2 mSv.h−1 (secondary wall) for 10 and 18 MV respectively. The ambient dose equivalent for neutrons at door is 5 μSv.h−1 to 2 μSv.h−1 while at treatment console room it is 2 μSv.h−1 to 0 μSv.h−1 for 10 and 18 MV respectively which shows that a 2 m thick and 5m longer concrete maze provides sufficient shielding for neutron at door as well as at treatment console for 10 and 18 MV photons.

Keywords: equivalent doses, neutron contamination, neutron detector, photon energy

Procedia PDF Downloads 437

Authors: Debabrata Adhikari, Mikhail Matveev, Louise Brown, Andy Long, Jan Kočí

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A good understanding of mesoscale permeability of complex architectures in fibrous porous preforms is of particular interest in order to achieve efficient and cost-effective resin impregnation of liquid composite molding (LCM). Fabrics used in structural reinforcements are typically woven or stitched. However, 3D fabric reinforcement is of particular interest because of the versatility in the weaving pattern with the binder yarn and in-plain yarn arrangements to manufacture thick composite parts, overcome the limitation in delamination, improve toughness etc. To predict the permeability based on the available pore spaces between the inter yarn spaces, unit cell-based computational fluid dynamics models have been using the Stokes Darcy model. Typically, the preform consists of an arrangement of yarns with spacing in the order of mm, wherein each yarn consists of thousands of filaments with spacing in the order of μm. The fluid flow during infusion exchanges the mass between the intra and inter yarn channels, meaning there is no dead-end of flow between the mesopore in the inter yarn space and the micropore in the yarn. Several studies have employed the Brinkman equation to take into account the flow through dual-scale porosity reinforcement to estimate their permeability. Furthermore, to reduce the computational effort of dual scale flow, scale separation criteria based on the ratio between yarn permeability to the yarn spacing was also proposed to quantify the dual scale and negligible micro-scale flow regime for the prediction of mesoscale permeability. In the present work, the key parameter to identify the influence of intra yarn permeability on the mesoscale permeability has been investigated with the systematic study of weft and warp yarn spacing on the plane weave as well as the position of binder yarn and number of in-plane yarn layers on 3D weave fabric. The permeability tensor has been estimated using an OpenFOAM-based model for the various weave pattern with idealized geometry of yarn implemented using open-source software TexGen. Additionally, scale separation criterion has been established based on the various configuration of yarn permeability for the 3D fabric with both the isotropic and anisotropic yarn from Gebart’s model. It was observed that the variation of mesoscale permeability Kxx within 30% when the isotropic porous yarn is considered for a 3D fabric with binder yarn. Furthermore, the permeability model developed in this study will be used for multi-objective optimizations of the preform mesoscale geometry in terms of yarn spacing, binder pattern, and a number of layers with an aim to obtain improved permeability and reduced void content during the LCM process.

Keywords: permeability, 3D fabric, dual-scale flow, liquid composite molding

Procedia PDF Downloads 82

Authors: Tomasz Łęga, Marta Sosnowska, Mirosława Panasiuk, Lilit Hovhannisyan, Beata Gromadzka, Marcin Olszewski, Sabina Zoledowska, Dawid Nidzworski

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Toxic heavy metal ion contamination of industrial wastewater has recently become a significant environmental concern in many regions of the world. Although the majority of heavy metals are naturally occurring elements found on the earth's surface, anthropogenic activities such as mining and smelting, industrial production, and agricultural use of metals and metal-containing compounds are responsible for the majority of environmental contamination and human exposure. The permissible limits (ppm) for heavy metals in food, water and soil are frequently exceeded and considered hazardous to humans, other organisms, and the environment as a whole. Human exposure to highly nickel-polluted environments causes a variety of pathologic effects. In 2008, nickel received the shameful name of “Allergen of the Year” (GILLETTE 2008). According to the dermatologist, the frequency of nickel allergy is still growing, and it can’t be explained only by fashionable piercing and nickel devices used in medicine (like coronary stents and endoprostheses). Effective remediation methods for removing heavy metal ions from soil and water are becoming increasingly important. Among others, methods such as chemical precipitation, micro- and nanofiltration, membrane separation, conventional coagulation, electrodialysis, ion exchange, reverse and forward osmosis, photocatalysis and polymer or carbon nanocomposite absorbents have all been investigated so far. The importance of environmentally sustainable industrial production processes and the conservation of dwindling natural resources has highlighted the need for affordable, innovative biosorptive materials capable of recovering specific chemical elements from dilute aqueous solutions. The use of combinatorial phage display techniques for selecting and recognizing material-binding peptides with a selective affinity for any target, particularly inorganic materials, has gained considerable interest in the development of advanced bio- or nano-materials. However, due to the limitations of phage display libraries and the biopanning process, the accuracy of molecular recognition for inorganic materials remains a challenge. This study presents the isolation, identification and characterisation of metal binding phage clones that preferentially recover nickel.

Keywords: Heavy metal recovery, cleaning water, phage display, nickel

Procedia PDF Downloads 79

Authors: B. Petrović, M. Petrović, L. Rutonjski, I. Djan, V. Ivanović

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Objective: Cardiac pacemakers are very sensitive to radiotherapy treatment from two sources: electromagnetic influence from the medical linear accelerator producing ionizing radiation- influencing electronics within the pacemaker, and the absorption of dose to the device. On the other hand, patients with cardiac pacemakers at the place of a tumor are rather rare, and single clinic hardly has experience with the management of such patients. The widely accepted international guidelines for management of radiation oncology patients recommend that these patients should be closely monitored and examined before, during and after radiotherapy treatment by cardiologist, and their device and condition followed up. The number of patients having both cancer and pacemaker, is growing every year, as both cancer incidence, as well as cardiac diseases incidence, are inevitably growing figures. Materials and methods: Female patient, age 69, was diagnozed with valvular cardiomyopathy and got implanted a pacemaker in 2005 and prosthetic mitral valve in 1993 (cancer was diagnosed in 2012). She was stable cardiologically and came to radiation therapy department with the diagnosis of right breast cancer, with the tumor in upper lateral quadrant of the right breast. Since she had all lymph nodes positive (28 in total), she had to have irradiated the supraclavicular region, as well as the breast with the tumor bed. She previously received chemotherapy, approved by the cardiologist. The patient was estimated to be with the high risk as device was within the field of irradiation, and the patient had high dependence on her pacemaker. The radiation therapy plan was conducted as 3D conformal therapy. The delineated target was breast with supraclavicular region, where the pacemaker was actually placed, with the addition of a pacemaker as organ at risk, to estimate the dose to the device and its components as recommended, and the breast. The targets received both 50 Gy in 25 fractions (where 20% of a pacemaker received 50 Gy, and 60% of a device received 40 Gy). The electrode to the heart received between 1 Gy and 50 Gy. Verification of dose planned and delivered was performed. Results: Evaluation of the patient status according to the guidelines and especially evaluation of all associated risks to the patient during treatment was done. Patient was irradiated by prescribed dose and followed up for the whole year, with no symptoms of failure of the pacemaker device during, or after treatment in follow up period. The functionality of a device was estimated to be unchanged, according to the parameters (electrode impedance and battery energy). Conclusion: Patient was closely monitored according to published guidelines during irradiation and afterwards. Pacemaker irradiated with the full dose did not show any signs of failure despite recommendations data, but in correlation with other published data.

Keywords: cardiac pacemaker, breast cancer, radiotherapy treatment planning, complications of treatment

Procedia PDF Downloads 423

Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

Procedia PDF Downloads 400

Authors: Lahari Ramya Pa, Sudhakar Ib, Madhu Vc, Madhusudhan Reddy Gd, Srinivasa Rao E.

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Selection of suitable armor materials for defense applications is very crucial with respect to increasing mobility of the systems as well as maintaining safety. Therefore, determining the material with the lowest possible areal density that resists the predefined threat successfully is required in armor design studies. A number of light metal and alloys are come in to forefront especially to substitute the armour grade steels. AA5083 aluminium alloy which fit in to the military standards imposed by USA army is foremost nonferrous alloy to consider for possible replacement of steel to increase the mobility of armour vehicles and enhance fuel economy. Growing need of AA5083 aluminium alloy paves a way to develop supplement aluminium alloys maintaining the military standards. It has been witnessed that AA 2xxx aluminium alloy, AA6xxx aluminium alloy and AA7xxx aluminium alloy are the potential material to supplement AA5083 aluminium alloy. Among those cited aluminium series alloys AA7xxx aluminium alloy (heat treatable) possesses high strength and can compete with armour grade steels. Earlier investigations revealed that layering of AA7xxx aluminium alloy can prevent spalling of rear portion of armour during ballistic impacts. Hence, present investigation deals with fabrication of hard layer (made of boron carbide) i.e. layer on AA 7075 aluminium alloy using friction stir processing with an intention of blunting the projectile in the initial impact and backing tough portion(AA7xxx aluminium alloy) to dissipate residual kinetic energy. An analytical approach has been adopted to unfold the ballistic performance of projectile. Penetration of projectile inside the armour has been resolved by considering by strain energy model analysis. Perforation shearing areas i.e. interface of projectile and armour is taken in to account for evaluation of penetration inside the armour. Fabricated surface composites (targets) were tested as per the military standard (JIS.0108.01) in a ballistic testing tunnel at Defence Metallurgical Research Laboratory (DMRL), Hyderabad in standardized testing conditions. Analytical results were well validated with experimental obtained one.

Keywords: AA7075 aluminium alloy, friction stir processing, boron carbide, ballistic performance, target

Procedia PDF Downloads 312

Authors: Chenxiao Yang, Li Li

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In this decade, the sportswear market rapidly expanded while numerous sports brands are conducting fierce competitions to hold their market shares and trying to act as a leader in professional competition sports areas to set the trends. Thus, various advancing sports equipment is being deeply explored to improving athletes’ performance in fierce competitions. Although there is plenty protective equipment such as cuff, running legging, etc., on the market, there is still blank in the field of sportswear during prerace warm-up this important time gap, especially for those competitions host in cold environment. Because there is always time gaps between warm-up and race due to event logistics or unexpected weather factors. Athletes will be exposed to chilly condition for an unpredictable long period of time. As a consequence, the effects of warm-up will be negated, and the competition performance will be degraded. However, reviewing the current market, there is none effective sports equipment provided to help athletes against this harsh environment or the rare existing products are so blocky or heavy to restrict the actions. An ideal thermal-protective sportswear should be light, flexible, comfort and aesthetic at the same time. Therefore, this design research adopted the textile circular knitting methodology to integrate soft silver-coated conductive yarns (ab. SCCYs), elastic nylon yarn and polyester yarn to develop the proposed electrical, thermal sportswear, with the strengths aforementioned. Meanwhile, the relationship between heating performance, stretch load, and energy consumption were investigated. Further, a simulation model was established to ensure providing sufficient warm and flexibility at lower energy cost and with an optimized production, parameter determined. The proposed circular knitting technology and simulation model can be directly applied to instruct prototype developments to cater different target consumers’ needs and ensure prototypes’’ safety. On the other hand, high R&D investment and time consumption can be saved. Further, two prototypes: a kneecap and an elbow guard, were developed to facilitate the transformation of research technology into an industrial application and to give a hint on the blur future blueprint.

Keywords: cold environment, silver-coated conductive yarn, electrical thermal textile, stretchable

Procedia PDF Downloads 257

Authors: Brian Chi Yan Cheng, Hui Guo, Tao Su, Xiu‐qiong Fu, Ting Li, Zhi‐ling Yu

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Rheumatoid arthritis (RA) affects around 1% of the globe population. Yet, there is still no cure for RA. Toll-like receptor 4 (TLR4) signalling has been found to be involved in the pathogenesis of RA, making it a potential therapeutic target for RA treatment. A herbal formula (RL) consisting of fruits of Rosa Multiflora (Eijitsu rose) and flowers of Lonicera Japonica (Japanese honeysuckle) has been used in treating various inflammatory disorders for more than a thousand year. Both of them are rich sources of nutrients and bioactive phytochemicals, which can be used in producing different food products and supplements. In this study, we would evaluate the anti-arthritic effect of RL on collagen-induced arthritis (CIA) in rats and investigate the involvement of TLR4 signaling in the mode of action of RL. Anti-arthritic efficacy was evaluated using CIA rats induced by bovine type II collagen. The treatment groups were treated with RL (82.5, 165, and 330 mg/kg bw per day, p.o.) or positive control indomethacin (0.25 mg/kg bw per day, p.o.) for 35 days. Clinical signs (hind paw volume and arthritis severity scores), changes in serum inflammatory mediators, pro-/antioxidant status, histological and radiographic changes of joints were investigated. Spleens and peritoneal macrophages were used to determine the effects of RL on innate and adaptive immune responses in CIA rats. The involvement of TLR4 signalling pathways in the anti-arthritic effect of RL was examined in cartilage tissue of CIA rats, murine RAW264.7 macrophages and human THP-1 monocytic cells. The severity of arthritis in the CIA rats was significantly attenuated by RL. Antioxidant status, histological score and radiographic score were efficiently improved by RL. RL could also dose-dependently inhibit pro-inflammatory cytokines in serum of CIA rats. RL significantly inhibited the production of various pro-inflammatory mediators, the expression and/or activity of the components of TLR4 signalling pathways in animal tissue and cell lines. RL possesses anti-arthritic effect on collagen-induced arthritis in rats. The therapeutic effect of RL may be related to its inhibition on pro-inflammatory cytokines in serum. The inhibition of the TAK1/NF-κB and TAK1/MAPK pathways participate in the anti-arthritic effects of RL. This provides a pharmacological justification for the dietary use of RL in the control of various arthritic diseases. Further investigation should be done to develop RL into a anti-arthritic food products and/or supplements.

Keywords: japanese honeysuckle, rheumatoid arthritis, rosa multiflora, rosehip

Procedia PDF Downloads 420

Authors: Michela Quadrini

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Chord diagrams occur in mathematics, from the study of RNA to knot theory. They are widely used in theory of knots and links for studying the finite type invariants, whereas in molecular biology one important motivation to study chord diagrams is to deal with the problem of RNA structure prediction. An RNA molecule is a linear polymer, referred to as the backbone, that consists of four types of nucleotides. Each nucleotide is represented by a point, whereas each chord of the diagram stands for one interaction for Watson-Crick base pairs between two nonconsecutive nucleotides. A chord diagram is an oriented circle with a set of n pairs of distinct points, considered up to orientation preserving diffeomorphisms of the circle. A linear chord diagram (LCD) is a special kind of graph obtained cutting the oriented circle of a chord diagram. It consists of a line segment, called its backbone, to which are attached a number of chords with distinct endpoints. There is a natural fattening on any linear chord diagram; the backbone lies on the real axis, while all the chords are in the upper half-plane. Each linear chord diagram has a natural genus of its associated surface. To each chord diagram and linear chord diagram, it is possible to associate the intersection graph. It consists of a graph whose vertices correspond to the chords of the diagram, whereas the chord intersections are represented by a connection between the vertices. Such intersection graph carries a lot of information about the diagram. Our goal is to define an LCD equivalence class in terms of identity of intersection graphs, from which many chord diagram invariants depend. For studying these invariants, we introduce a new representation of Linear Chord Diagrams based on a set of appropriate topological operators that permits to model LCD in terms of the relations among chords. Such set is composed of: crossing, nesting, and concatenations. The crossing operator is able to generate the whole space of linear chord diagrams, and a multiple context free grammar able to uniquely generate each LDC starting from a linear chord diagram adding a chord for each production of the grammar is defined. In other words, it allows to associate a unique algebraic term to each linear chord diagram, while the remaining operators allow to rewrite the term throughout a set of appropriate rewriting rules. Such rules define an LCD equivalence class in terms of the identity of intersection graphs. Starting from a modelled RNA molecule and the linear chord, some authors proposed a topological classification and folding. Our LCD equivalence class could contribute to the RNA folding problem leading to the definition of an algorithm that calculates the free energy of the molecule more accurately respect to the existing ones. Such LCD equivalence class could be useful to obtain a more accurate estimate of link between the crossing number and the topological genus and to study the relation among other invariants.

Keywords: chord diagrams, linear chord diagram, equivalence class, topological language

Procedia PDF Downloads 192

Authors: Mustafa Sengul, Enes Sahin, Sertac Arslan

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Pumpjets are one of the marine propulsion systems frequently used in underwater vehicles nowadays. The reasons for frequent use of pumpjet as a propulsion system are that it has higher relative efficiency at high speeds, better cavitation, and acoustic performance than its rivals. Pumpjets are composed of rotor, stator, and duct, and there are two different types of pumpjet configurations depending on the desired hydrodynamic characteristic, which are with accelerating and decelerating duct. Pumpjet with an accelerating channel is used at cargo ships where it works at low speeds and high loading conditions. The working principle of this type of pumpjet is to maximize the thrust by reducing the pressure of the fluid through the channel and throwing the fluid out from the channel with high momentum. On the other hand, for decelerating ducted pumpjets, the main consideration is to prevent the occurrence of the cavitation phenomenon by increasing the pressure of the fluid about the rotor region. By postponing the cavitation, acoustic noise naturally falls down, so decelerating ducted systems are used at noise-sensitive vehicle systems where acoustic performance is vital. Therefore, duct design becomes a crucial step during pumpjet design. This study, it is aimed to optimize the duct geometry of a decelerating ducted pumpjet for a highly speed underwater vehicle by using proper optimization tools. The target output of this optimization process is to obtain a duct design that maximizes fluid pressure around the rotor region to prevent from cavitation and minimizes drag force. There are two main optimization techniques that could be utilized for this process which are parameter-based optimization and gradient-based optimization. While parameter-based algorithm offers more major changes in interested geometry, which makes user to get close desired geometry, gradient-based algorithm deals with minor local changes in geometry. In parameter-based optimization, the geometry should be parameterized first. Then, by defining upper and lower limits for these parameters, design space is created. Finally, by proper optimization code and analysis, optimum geometry is obtained from this design space. For this duct optimization study, a commercial codedparameter-based optimization algorithm is used. To parameterize the geometry, duct is represented with b-spline curves and control points. These control points have x and y coordinates limits. By regarding these limits, design space is generated.

Keywords: pumpjet, decelerating duct design, optimization, underwater vehicles, cavitation, drag minimization

Procedia PDF Downloads 186

Authors: Francesco Pantano, Marta Fogolari, Michele Iuliani, Sonia Simonetti, Silvia Cavaliere, Marco Russano, Fabrizio Citarella, Bruno Vincenzi, Silvia Angeletti, Giuseppe Tonini

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Background: Although immune checkpoint inhibitors (ICIs) have changed the treatment paradigm of non–small cell lung cancer (NSCLC), these drugs fail to elicit durable responses in the majority of NSCLC patients. The gut microbiota, able to regulate immune responsiveness, is emerging as a promising, modifiable target to improve ICIs response rates. Since the oral microbiome has been demonstrated to be the primary source of bacterial microbiota in the lungs, we investigated its composition as a potential predictive biomarker to identify and select patients who could benefit from immunotherapy. Methods: Thirty-five patients with stage IV squamous and non-squamous cell NSCLC eligible for an anti-PD-1/PD-L1 as monotherapy were enrolled. Saliva samples were collected from patients prior to the start of treatment, bacterial DNA was extracted using the QIAamp® DNA Microbiome Kit (QIAGEN) and the 16S rRNA gene was sequenced on a MiSeq sequencing instrument (Illumina). Results: NSCLC patients were dichotomized as “Responders” (partial or complete response) and “Non-Responders” (progressive disease), after 12 weeks of treatment, based on RECIST criteria. A prevalence of the phylum Candidatus Saccharibacteria was found in the 10 responders compared to non-responders (abundance 5% vs 1% respectively; p-value = 1.46 x 10-7; False Discovery Rate (FDR) = 1.02 x 10-6). Moreover, a higher prevalence of Saccharibacteria Genera Incertae Sedis genus (belonging to the Candidatus Saccharibacteria phylum) was observed in "responders" (p-value = 6.01 x 10-7 and FDR = 2.46 x 10-5). Finally, the patients who benefit from immunotherapy showed a significant abundance of TM7 Phylum Sp Oral Clone FR058 strain, member of Saccharibacteria Genera Incertae Sedis genus (p-value = 6.13 x 10-7 and FDR=7.66 x 10-5). Conclusions: These preliminary results showed a significant association between oral microbiota and ICIs response in NSCLC patients. In particular, the higher prevalence of Candidatus Saccharibacteria phylum and TM7 Phylum Sp Oral Clone FR058 strain in responders suggests their potential immunomodulatory role. The study is still ongoing and updated data will be presented at the congress.

Keywords: oral microbiota, immune checkpoint inhibitors, non-small cell lung cancer, predictive biomarker

Procedia PDF Downloads 78

Authors: Mingjiang Dai, Qian Shi, Fang Hu, Songsheng Lin, Huijun Hou, Chunbei Wei

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A diamond-like carbon (DLC) is considered as a promising protective film since its high hardness and excellent tribological properties. However, DLC films are very sensitive to the environmental condition, its friction coefficient could dramatic change in high humidity, therefore, limited their further application in aerospace, the watch industry, and micro/nano-electromechanical systems. Therefore, most studies focus on the low friction coefficient of DLC films at a high humid environment. However, this is out of satisfied in practical application. An important thing was ignored is that the DLC coated components are usually used in the diversed environment, which means its friction coefficient may evidently change in different humid condition. As a result, the invalidation of DLC coated components or even sometimes disaster occurred. For example, DLC coated minisize gears were used in the watch industry, and the customer may frequently transform their locations with different weather and humidity even in one day. If friction coefficient is not stable in dry and high moisture conditions, the watch will be inaccurate. Thus, it is necessary to investigate the stable tribological behavior of DLC films in various environments. In this study, a-C:H:Si films were deposited by multi-function magnetron sputtering system, containing one ion source device and a pair of SiC dual mid-frequent targets and two direct current Ti/C targets. Hydrogenated carbon layers were manufactured by sputtering the graphite target in argon and methane gasses. The silicon was doped in DLC coatings by sputtering silicon carbide targets and the doping content were adjusted by mid-frequent sputtering current. The microstructure of the film was characterized by Raman spectrometry, X-ray photoelectron spectroscopy, and transmission electron microscopy while its friction behavior under different humidity conditions was studied using a ball-on-disc tribometer. The a-C:H films with Si content from 0 to 17at.% were obtained and the influence of Si content on the structure and tribological properties under the relative humidity of 50% and 85% were investigated. Results show that the a-C:H:Si film has typical diamond-like characteristics, in which Si mainly existed in the form of Si, SiC, and SiO2. As expected, the friction coefficient of a-C:H films can be effectively changed after Si doping, from 0.302 to 0.176 in RH 50%. The further test shows that the friction coefficient value of a-C:H:Si film in RH 85% is first increase and then decrease as a function of Si content. We found that the a-C:H:Si films with a Si content of 3.75 at.% show a stable friction coefficient of 0.13 in different humidity environment. It is suggestion that the sp3/sp2 ratio of a-C:H films with 3.75 at.% Si was higher than others, which tend to form the silica-gel-like sacrificial layers during friction tests. Therefore, the films deliver stable low friction coefficient under controlled RH value of 50 and 85%.

Keywords: diamond-like carbon, Si doping, moisture environment, table low friction coefficient

Procedia PDF Downloads 350

Authors: Priscila A. Bernardes, Marcos E. Buzanskas, Luciana C. A. Regitano, Ricardo V. Ventura, Danisio P. Munari

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Genotype imputation has been used to reduce genomic selections costs. In order to increase haplotype detection accuracy in methods that considers the linkage disequilibrium, another approach could be used, such as combined genotype data from different panels. Therefore, this study aimed to evaluate the linkage disequilibrium and haplotype blocks in two high-density panels before and after the imputation to a combined panel in Nelore beef cattle. A total of 814 animals were genotyped with the Illumina BovineHD BeadChip (IHD), wherein 93 animals (23 bulls and 70 progenies) were also genotyped with the Affymetrix Axion Genome-Wide BOS 1 Array Plate (AHD). After the quality control, 809 IHD animals (509,107 SNPs) and 93 AHD (427,875 SNPs) remained for analyses. The combined genotype panel (CP) was constructed by merging both panels after quality control, resulting in 880,336 SNPs. Imputation analysis was conducted using software FImpute v.2.2b. The reference (CP) and target (IHD) populations consisted of 23 bulls and 786 animals, respectively. The linkage disequilibrium and haplotype blocks studies were carried out for IHD, AHD, and imputed CP. Two linkage disequilibrium measures were considered; the correlation coefficient between alleles from two loci (r²) and the |D’|. Both measures were calculated using the software PLINK. The haplotypes' blocks were estimated using the software Haploview. The r² measurement presented different decay when compared to |D’|, wherein AHD and IHD had almost the same decay. For r², even with possible overestimation by the sample size for AHD (93 animals), the IHD presented higher values when compared to AHD for shorter distances, but with the increase of distance, both panels presented similar values. The r² measurement is influenced by the minor allele frequency of the pair of SNPs, which can cause the observed difference comparing the r² decay and |D’| decay. As a sum of the combinations between Illumina and Affymetrix panels, the CP presented a decay equivalent to a mean of these combinations. The estimated haplotype blocks detected for IHD, AHD, and CP were 84,529, 63,967, and 140,336, respectively. The IHD were composed by haplotype blocks with mean of 137.70 ± 219.05kb, the AHD with mean of 102.10kb ± 155.47, and the CP with mean of 107.10kb ± 169.14. The majority of the haplotype blocks of these three panels were composed by less than 10 SNPs, with only 3,882 (IHD), 193 (AHD) and 8,462 (CP) haplotype blocks composed by 10 SNPs or more. There was an increase in the number of chromosomes covered with long haplotypes when CP was used as well as an increase in haplotype coverage for short chromosomes (23-29), which can contribute for studies that explore haplotype blocks. In general, using CP could be an alternative to increase density and number of haplotype blocks, increasing the probability to obtain a marker close to a quantitative trait loci of interest.

Keywords: Bos taurus indicus, decay, genotype imputation, single nucleotide polymorphism

Procedia PDF Downloads 259

Authors: Mohkammad Nur Cahyadi, Hepi Hapsari Handayani, Agus Budi Raharjo, Ronny Mardianto, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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PDAM (local water company) determines customer charges by considering the customer's building or house. Charges determination significantly affects PDAM income and customer costs because the PDAM applies a subsidy policy for customers classified as small households. Periodic updates are needed so that pricing is in line with the target. A thorough customer survey in Surabaya is needed to update customer building data. However, the survey that has been carried out so far has been by deploying officers to conduct one-by-one surveys for each PDAM customer. Surveys with this method require a lot of effort and cost. For this reason, this research offers a technology called moblie mapping, a mapping method that is more efficient in terms of time and cost. The use of this tool is also quite simple, where the device will be installed in the car so that it can record the surrounding buildings while the car is running. Mobile mapping technology generally uses lidar sensors equipped with GNSS, but this technology requires high costs. In overcoming this problem, this research develops low-cost mobile mapping technology using a webcam camera sensor added to the GNSS and IMU sensors. The camera used has specifications of 3MP with a resolution of 720 and a diagonal field of view of 78⁰. The principle of this invention is to integrate four camera sensors, a GNSS webcam, and GPS to acquire photo data, which is equipped with location data (latitude, longitude) and IMU (roll, pitch, yaw). This device is also equipped with a tripod and a vacuum cleaner to attach to the car's roof so it doesn't fall off while running. The output data from this technology will be analyzed with artificial intelligence to reduce similar data (Cosine Similarity) and then classify building types. Data reduction is used to eliminate similar data and maintain the image that displays the complete house so that it can be processed for later classification of buildings. The AI method used is transfer learning by utilizing a trained model named VGG-16. From the analysis of similarity data, it was found that the data reduction reached 50%. Then georeferencing is done using the Google Maps API to get address information according to the coordinates in the data. After that, geographic join is done to link survey data with customer data already owned by PDAM Surya Sembada Surabaya.

Keywords: mobile mapping, GNSS, IMU, similarity, classification

Procedia PDF Downloads 66

Authors: J. Knight, E. Barberà

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Language learning strategies have been defined as thoughts and actions, consciously chosen and operationalized by language learners, to help them in carrying out a multiplicity of tasks from the very outset of learning to the most advanced levels of target language performance. While research in the field of Second Language Acquisition has focused on ‘good’ language learners, the effectiveness of strategy-use and orchestration by effective learners in face-to-face classrooms much less research has attended to learner strategies in online contexts, particular strategies in relation to technological tool use which can be part of a task design. In addition, much research on learner strategies and strategy use has been explored focusing on cognitive, attitudinal and metacognitive behaviour with less research focusing on the social aspect of strategies. This study focuses on how learners mediate with a technological tool designed to support synchronous spoken interaction and how this shape their spoken interaction in the opening of their talk. A case study approach is used incorporating notions from communities of practice theory to analyse and understand learner strategies of dyads carrying out a role play task. The study employs analysis of transcripts of spoken interaction in the openings of the talk along with log files of tool use. The study draws on results of previous studies pertaining to the same tool as a form of triangulation. Findings show how learners gain pre-task planning time through technological tool control. The strategies involving learners’ choices to enter and exit the tool shape their spoken interaction qualitatively, with some cases demonstrating long silences whilst others appearing to start the pedagogical task immediately. Who/what learners orientate to in the openings of the talk: an audience (i.e. the teacher), each other and/or screen-based signifiers in the opening moments of the talk also becomes a focus. The study highlights how tool use as a social practice should be considered a learning strategy in online contexts whereby different usages may be understood in the light of the more usual asynchronous social practices of the online community. The teachers’ role in the community is also problematised as the evaluator of the practices of that community. Results are pertinent for task design for synchronous speaking tasks. The use of community of practice theory supports an understanding of strategy use that involves both metacognition alongside social context revealing how tool-use strategies may need to be orally (socially) negotiated by learners and may also differ from an online language community.

Keywords: learner strategy, tool use, community of practice, speaking task

Procedia PDF Downloads 329

Authors: Nigatu Tadesse, Li Juan, Liuhong Ming

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Gastric cancer (GC) is the fifth most common and fourth deadly cancer in the world with limited treatment options at late advanced stage in which surgical therapy is not recommended with chemotherapy remain as the mainstay of treatment. However, the occurrence of chemoresistance as well as intera-tumoral and inter-tumoral heterogeneity of response to targeted and immunotherapy underlined a clear unmet treatment need in gastroenterology. Several molecular and cellular alterations ascribed for chemo resistance in GC including cancer stem cells (CSC) and tumor microenvironment (TME) remodeling. Cancer cells including CSC bears higher metabolic demand and major changes in TME involves alterations of gut microbiota interacting with nutrients metabolism. Metabolic upregulation in lipids, carbohydrates, amino acids, fatty acids biosynthesis pathways identified as a common hall mark in GC. Metabolic addiction to methionine metabolism occurs in many cancer cells to promote the biosynthesis of S-Adenosylmethionine (SAM), a universal methyl donor molecule for high rate of transmethylation in GC and promote cell proliferation. Targeting methionine metabolism found to promotes chemo-sensitivity with treatment non-heterogeneity. Methionine restriction (MR) promoted the arrest of cell cycle at S/G2 phase and enhanced downregulation of GC cells resistance to apoptosis (including ferroptosis), which suggests the potential of synergy with chemotherapies acting at S-phase of the cell cycle as well as inducing cell apoptosis. Accumulated evidences showed both the biogenesis as well as intracellular metabolism of exogenous methionine could be safe and effective target for therapy either alone or in combination with chemotherapies. This review article provides an over view of the upregulation in methionine biosynthesis pathway and the molecular signaling through the PI3K/Akt/mTOR-c-MYC axis to promote metabolic reprograming through activating the expression of L-type aminoacid-1 (LAT1) transporter and overexpression of Methionine adenosyltransferase 2A(MAT2A) for intercellular metabolic conversion of exogenous methionine to SAM in GC, and the potential of targeting with novel therapeutic agents such as methioninase (METase), Methionine adenosyltransferase 2A (MAT2A), c-MYC, methyl like transferase 16 (METTL16) inhibitors that are currently under clinical trial development stages and future perspectives.

Keywords: gastric cancer, methionine metabolism, pi3k/akt/mtorc1-c-myc axis, gut microbiota, MAT2A, c-MYC, METTL16, methioninase

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Authors: H. Pegram, R. Stevens, L. De Girolamo

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Aligned electrospun nanofibres act as effective neuronal and glial cell scaffolds that can be layered to contain multiple sheets harboring different cell populations. This allows personalised biofunctional prostheses to be manufactured with both acellular and cellularised layers for the treatment of spinal cord injury. Additionally, the manufacturing route may be configured to produce in-vitro 3D cell based model of spinal cord injury to aid drug development and enhance prosthesis performance. The goal of this investigation was to optimise the multi-layer scaffold design parameters for prosthesis manufacture, to enable the development of multi-layer patient specific implant therapies. The work has also focused on the fabricating aligned nanofibre scaffolds that promote in-vitro neuronal and glial cell population growth, cell-to-cell interaction and long-term survival following trauma to mimic an in-vivo spinal cord lesion. The approach has established reproducible lesions and has identified markers of trauma and regeneration marked by effective neuronal migration across the lesion with glial support. The investigation has advanced the development of an in-vitro model of traumatic spinal cord injury and has identified a route to manufacture prostheses which target the repair spinal cord injury. Evidence collated to investigate the multi-layer concept suggests that physical cues provided by nanofibres provide both a natural extra-cellular matrix (ECM) like environment and controls cell proliferation and migration. Specifically, aligned nanofibre layers act as a guidance system for migrating and elongating neurons. On a larger scale, material type in multi-layer systems also has an influence in inter-layer migration as cell types favour different material types. Results have shown that layering nanofibre membranes create a multi-level scaffold system which can enhance or prohibit cell migration between layers. It is hypothesised that modifying nanofibre layer material permits control over neuronal/glial cell migration. Using this concept, layering of neuronal and glial cells has become possible, in the context of tissue engineering and also modelling in-vitro induced lesions.

Keywords: electrospinning, layering, lesion, modeling, nanofibre

Procedia PDF Downloads 118

Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

Procedia PDF Downloads 88

Authors: Mostafa Shahriari, Theophile Chaumont-Frelet, David Pardo

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Resistivity measurements are used to characterize the Earth’s subsurface. They are categorized into two different groups: (a) those acquired on the Earth’s surface, for instance, controlled source electromagnetic (CSEM) and Magnetotellurics (MT), and (b) those recorded with borehole logging instruments such as Logging-While-Drilling (LWD) devices. LWD instruments are mostly used for geo-steering purposes, i.e., to adjust dip and azimuthal angles of a well trajectory to drill along a particular geological target. Modern LWD tools measure all nine components of the magnetic field corresponding to three orthogonal transmitter and receiver orientations. In order to map the Earth’s subsurface and perform geo-steering, we invert measurements using a gradient-based method that utilizes the derivatives of the recorded measurements with respect to the inversion variables. For resistivity measurements, these inversion variables are usually the constant resistivity value of each layer and the bed boundary positions. It is well-known how to compute derivatives with respect to the constant resistivity value of each layer using semi-analytic or numerical methods. However, similar formulas for computing the derivatives with respect to bed boundary positions are unavailable. The main contribution of this work is to provide an adjoint-based formulation for computing derivatives with respect to the bed boundary positions. The key idea to obtain the aforementioned adjoint state formulations for the derivatives is to separate the tangential and normal components of the field and treat them differently. This formulation allows us to compute the derivatives faster and more accurately than with traditional finite differences approximations. In the presentation, we shall first derive a formula for computing the derivatives with respect to the bed boundary positions for the potential equation. Then, we shall extend our formulation to 3D Maxwell’s equations. Finally, by considering a 1D domain and reducing the dimensionality of the problem, which is a common practice in the inversion of resistivity measurements, we shall derive a formulation to compute the derivatives of the measurements with respect to the bed boundary positions using a 1.5D variational formulation. Then, we shall illustrate the accuracy and convergence properties of our formulations by comparing numerical results with the analytical derivatives for the potential equation. For the 1.5D Maxwell’s system, we shall compare our numerical results based on the proposed adjoint-based formulation vs those obtained with a traditional finite difference approach. Numerical results shall show that our proposed adjoint-based technique produces enhanced accuracy solutions while its cost is negligible, as opposed to the finite difference approach that requires the solution of one additional problem per derivative.

Keywords: inverse problem, bed boundary positions, electromagnetism, potential equation

Procedia PDF Downloads 164

Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 150

Authors: Ali Abdul Kadhim, Fue Lien

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Solid particle distribution on an impingement surface has been simulated utilizing a graphical processing unit (GPU). In-house computational fluid dynamics (CFD) code has been developed to investigate a 3D turbulent impinging jet using the lattice Boltzmann method (LBM) in conjunction with large eddy simulation (LES) and the multiple relaxation time (MRT) models. This paper proposed an improvement in the LBM-cellular automata (LBM-CA) probabilistic method. In the current model, the fluid flow utilizes the D3Q19 lattice, while the particle model employs the D3Q27 lattice. The particle numbers are defined at the same regular LBM nodes, and transport of particles from one node to its neighboring nodes are determined in accordance with the particle bulk density and velocity by considering all the external forces. The previous models distribute particles at each time step without considering the local velocity and the number of particles at each node. The present model overcomes the deficiencies of the previous LBM-CA models and, therefore, can better capture the dynamic interaction between particles and the surrounding turbulent flow field. Despite the increasing popularity of LBM-MRT-CA model in simulating complex multiphase fluid flows, this approach is still expensive in term of memory size and computational time required to perform 3D simulations. To improve the throughput of each simulation, a single GeForce GTX TITAN X GPU is used in the present work. The CUDA parallel programming platform and the CuRAND library are utilized to form an efficient LBM-CA algorithm. The methodology was first validated against a benchmark test case involving particle deposition on a square cylinder confined in a duct. The flow was unsteady and laminar at Re=200 (Re is the Reynolds number), and simulations were conducted for different Stokes numbers. The present LBM solutions agree well with other results available in the open literature. The GPU code was then used to simulate the particle transport and deposition in a turbulent impinging jet at Re=10,000. The simulations were conducted for L/D=2,4 and 6, where L is the nozzle-to-surface distance and D is the jet diameter. The effect of changing the Stokes number on the particle deposition profile was studied at different L/D ratios. For comparative studies, another in-house serial CPU code was also developed, coupling LBM with the classical Lagrangian particle dispersion model. Agreement between results obtained with LBM-CA and LBM-Lagrangian models and the experimental data is generally good. The present GPU approach achieves a speedup ratio of about 350 against the serial code running on a single CPU.

Keywords: CUDA, GPU parallel programming, LES, lattice Boltzmann method, MRT, multi-phase flow, probabilistic model

Procedia PDF Downloads 190

Authors: Veerle Van Hoeck, Ingrid Somers, Dany Morisset

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Anti-nutritional factors such as non-starch polysaccharides (NSP) are present in viscous cereals used to feed poultry. Therefore, exogenous carbohydrases are commonly added to monogastric feed to degrade these NSP. Our hypothesis is that xylanase not only improves laying hen performance and digestibility but also induces a significant shift in microbial composition within the intestinal tract and, thereby, can cause a prebiotic effect. In this context, a better understanding of whether and how the chicken gut flora can be modulated by xylanase is needed. To do so, in the herein laying hen study, the effects of dietary supplementation of xylanase on performance, digestibility, and cecal microbiome were evaluated. A total of 96 HiSex laying hens was used in this experiment (3 diets and 16 replicates of 2 hens). Xylanase was added to the diets at concentrations of 0, 45,000 (15 g/t XygestTM HT) and 90,000 U/kg (30 g/t Xygest HT). The diets were based on wheat (~55 %), soybean, and sunflower meal. The lowest dosage, 45,000 U/kg, significantly increased average egg weight and improved feed efficiency compared to the control treatment (p < 0.05). Egg quality parameters were significantly improved in the experiment in response to the xylanase addition. For example, during the last 28 days of the trial, the 45,000 U/kg and the 90,000 U/kg treatments exhibited an increase in Haugh units and albumin heights (p < 0.05). Compared with the control, organic matter digestibility and N retention were drastically improved in the 45,000 U/kg treatment group, which implies better nutrient digestibility at this lowest recommended dosage compared to the control (p < 0.05). Furthermore, gross energy and crude fat digestibility were improved significantly for birds fed 90,000 U/kg group compared to the control. Importantly, 16S rRNA gene analysis revealed that xylanase at 45,000 U/kg dosages can exert a prebiotic effect. This conclusion was drawn based on studying the sequence variation in the 16S rRNA gene in order to characterize diverse microbial communities of the cecal content. A significant increase in beneficial bacteria (Lactobacilli spp and Enterococcus casseliflavus) was documented when adding 45,000 U/kg xylanase to the diet of laying hens. In conclusion, dietary supplementation of xylanase, even at the lowest dose of (45,000 U/kg), significantly improved laying hen performance and digestibility. Furthermore, it is generally accepted that a proper bacterial balance between the number of beneficial bacteria and pathogenic bacteria in the intestine is vital for the host. It seems that the xylanase enzyme is able to modulate the laying hen microbiome beneficially and thus exerts a prebiotic effect. This microbiome plasticity in response to the xylanase provides an attractive target for stimulating intestinal health.

Keywords: laying hen, prebiotic, XygestTM HT, xylanase

Procedia PDF Downloads 112

Authors: Ali Hashemifarzad, Jens Zum Hingst

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The structure of the world’s energy systems has changed significantly over the past years. One of the most important challenges in the 21st century in Germany (and also worldwide) is the energy transition. This transition aims to comply with the recent international climate agreements from the United Nations Climate Change Conference (COP21) to ensure sustainable energy supply with minimal use of fossil fuels. Germany aims for complete decarbonization of the energy sector by 2050 according to the federal climate protection plan. One of the stipulations of the Renewable Energy Sources Act 2017 for the expansion of energy production from renewable sources in Germany is that they cover at least 80% of the electricity requirement in 2050; The Gross end energy consumption is targeted for at least 60%. This means that by 2050, the energy supply system would have to be almost completely converted to renewable energy. An essential basis for the development of such a sustainable energy supply from 100% renewable energies is to predict the energy requirement by 2050. This study presents two scenarios for the final energy demand in Germany in 2050. In the first scenario, the targets for energy efficiency increase and demand reduction are set very ambitiously. To build a comparison basis, the second scenario provides results with less ambitious assumptions. For this purpose, first, the relevant framework conditions (following CUTEC 2016) were examined, such as the predicted population development and economic growth, which were in the past a significant driver for the increase in energy demand. Also, the potential for energy demand reduction and efficiency increase (on the demand side) was investigated. In particular, current and future technological developments in energy consumption sectors and possible options for energy substitution (namely the electrification rate in the transport sector and the building renovation rate) were included. Here, in addition to the traditional electricity sector, the areas of heat, and fuel-based consumptions in different sectors such as households, commercial, industrial and transport are taken into account, supporting the idea that for a 100% supply from renewable energies, the areas currently based on (fossil) fuels must be almost completely be electricity-based by 2050. The results show that in the very ambitious scenario a final energy demand of 1,362 TWh/a is required, which is composed of 818 TWh/a electricity, 229 TWh/a ambient heat for electric heat pumps and approx. 315 TWh/a non-electric energy (raw materials for non-electrifiable processes). In the less ambitious scenario, in which the targets are not fully achieved by 2050, the final energy demand will need a higher electricity part of almost 1,138 TWh/a (from the total: 1,682 TWh/a). It has also been estimated that 50% of the electricity revenue must be saved to compensate for fluctuations in the daily and annual flows. Due to conversion and storage losses (about 50%), this would mean that the electricity requirement for the very ambitious scenario would increase to 1,227 TWh / a.

Keywords: energy demand, energy transition, German Energiewende, 100% renewable energy production

Procedia PDF Downloads 117

Authors: Jasmin Cowin, Amany Alkhayat

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This paper will concentrate on a comparative analysis of both the advantages and limitations of using digital learning resources (DLRs). DLRs covered will be Virtual Reality (VR), Mobile Learning (M-learning) and Computer-Assisted Language Learning (CALL) together with their subset, Mobile Assisted Language Learning (MALL) in language education. In addition, best practices for language teaching and the application of established language teaching methodologies such as Communicative Language Teaching (CLT), the audio-lingual method, or community language learning will be explored. Education has changed dramatically since the eruption of the pandemic. Traditional face-to-face education was disrupted on a global scale. The rise of distance learning brought new digital tools to the forefront, especially web conferencing tools, digital storytelling apps, test authoring tools, and VR platforms. Language educators raced to vet, learn, and implement multiple technology resources suited for language acquisition. Yet, questions remain on how to harness new technologies, digital tools, and their ubiquitous availability while using established methods and methodologies in language learning paired with best teaching practices. In M-learning language, learners employ portable computing devices such as smartphones or tablets. CALL is a language teaching approach using computers and other technologies through presenting, reinforcing, and assessing language materials to be learned or to create environments where teachers and learners can meaningfully interact. In VR, a computer-generated simulation enables learner interaction with a 3D environment via screen, smartphone, or a head mounted display. Research supports that VR for language learning is effective in terms of exploration, communication, engagement, and motivation. Students are able to relate through role play activities, interact with 3D objects and activities such as field trips. VR lends itself to group language exercises in the classroom with target language practice in an immersive, virtual environment. Students, teachers, schools, language institutes, and institutions benefit from specialized support to help them acquire second language proficiency and content knowledge that builds on their cultural and linguistic assets. Through the purposeful application of different language methodologies and teaching approaches, language learners can not only make cultural and linguistic connections in DLRs but also practice grammar drills, play memory games or flourish in authentic settings.

Keywords: language teaching methodologies, computer-assisted language learning, mobile learning, virtual reality

Procedia PDF Downloads 219

Authors: Thomas Folegot, Arnaud Levaufre, Léna Bourven, Nicolas Kermagoret, Alexis Caillard, Roger Gallou

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Concern for negative impacts of anthropogenic noise on the ocean’s ecosystems has increased over the recent decades. This concern leads to a similar increased willingness to regulate noise-generating activities, of which shipping is one of the most significant. Dealing with ship noise requires not only knowledge about the noise from individual ships, but also how the ship noise is distributed in time and space within the habitats of concern. Marine mammals, but also fish, sea turtles, larvae and invertebrates are mostly dependent on the sounds they use to hunt, feed, avoid predators, during reproduction to socialize and communicate, or to defend a territory. In the marine environment, sight is only useful up to a few tens of meters, whereas sound can propagate over hundreds or even thousands of kilometers. Directive 2008/56/EC of the European Parliament and of the Council of June 17, 2008 called the Marine Strategy Framework Directive (MSFD) require the Member States of the European Union to take the necessary measures to reduce the impacts of maritime activities to achieve and maintain a good environmental status of the marine environment. The Ocean-Planner is a web-based platform that provides to regulators, managers of protected or sensitive areas, etc. with a decision support tool that enable to anticipate and quantify the effectiveness of management measures in terms of reduction or modification the distribution of underwater noise, in response to Descriptor 11 of the MSFD and to the Marine Spatial Planning Directive. Based on the operational sound modelling tool Quonops Online Service, Ocean-Planner allows the user via an intuitive geographical interface to define management measures at local (Marine Protected Area, Natura 2000 sites, Harbors, etc.) or global (Particularly Sensitive Sea Area) scales, seasonal (regulation over a period of time) or permanent, partial (focused to some maritime activities) or complete (all maritime activities), etc. Speed limit, exclusion area, traffic separation scheme (TSS), and vessel sound level limitation are among the measures supported be the tool. Ocean Planner help to decide on the most effective measure to apply to maintain or restore the biodiversity and the functioning of the ecosystems of the coastal seabed, maintain a good state of conservation of sensitive areas and maintain or restore the populations of marine species.

Keywords: underwater noise, marine biodiversity, marine spatial planning, mitigation measures, prediction

Procedia PDF Downloads 106

Authors: Inkeri Jaaskelainen

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The aim of this study is to shed light on what is it like to study in apprenticeship training using intermediate (or even lower level) Finnish. The aim is to find out and describe these students' experiences and feelings while acquiring a profession in Finnish as it is important to understand how immigrant background adult learners learn and how their needs could be better taken into account. Many students choose apprenticeships and start vocational training while their language skills in Finnish are still very weak. At work, students should be able to simultaneously learn Finnish and do vocational studies in a noisy, demanding, and stressful environment. Learning and understanding new things is very challenging under these circumstances, and sometimes students get exhausted and experience a lot of stress - which makes learning even more difficult. Students are different from each other, and so are their ways to learn. Both duties at work and school assignments require reasonably good general language skills, and, especially at work, language skills are also a safety issue. The empirical target of this study is a group of students with an immigrant background who studied in various fields with intensive L2 support in 2016–2018 and who by now have completed a vocational upper secondary qualification. The interview material for this narrative study was collected from those who completed apprenticeship training in 2019–2020. The data collection methods used are a structured thematic interview, a questionnaire, and observational data. Interviewees with an immigrant background have an inconsistent cultural and educational background - some have completed an academic degree in their country of origin while others have learned to read and write only in Finland. The analysis of the material utilizes thematic analysis, which is used to examine learning and related experiences. Learning a language at work is very different from traditional classroom teaching. With evolving language skills, at an intermediate level at best, rushing and stressing makes it even more difficult to understand and increases the fear of failure. Constant noise, rapidly changing situations, and uncertainty undermine the learning and well-being of apprentices. According to preliminary results, apprenticeship training is well suited to the needs of an adult immigrant student. In apprenticeship training, students need a lot of support for learning and understanding a new communication and working culture. Stress can result in, e.g., fatigue, frustration, and difficulties in remembering and understanding. Apprenticeship training can be seen as a good path to working life. However, L2 support is a very important part of apprenticeship training, and it indeed helps students to believe that one day they will graduate and even get employed in their new country.

Keywords: apprenticeship training, vocational basic degree, Finnish learning, wee-being

Procedia PDF Downloads 119

Authors: B. Orser, A. Riding, Y. Li

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To inform government about how gender gaps in SME ( small and medium-sized enterprise) contracting might be redressed, the research question was: What are the key obstacles to, and response strategies for, increasing the engagement of women business owners among SME suppliers to the government of Canada? Thirty-five interviews with senior policymakers, supplier diversity organization executives, and expert witnesses to the Canadian House of Commons, Standing Committee on Government Operations and Estimates. Qualitative data were conducted and analysed using N’Vivo 11 software. High order response categories included: (a) SME risk mitigation strategies, (b) SME procurement program design, and (c) performance measures. Primary obstacles cited were government red tape and long and complicated requests for proposals (RFPs). The majority of 'common' complaints occur when SMEs have questions about the federal procurement process. Witness responses included use of outcome-based rather than prescriptive procurement practices, more agile procurement, simplified RFPs, making payment within 30 days a procurement priority. Risk mitigation strategies included provision of procurement officers to assess risks and opportunities for businesses and development of more agile procurement procedures and processes. Recommendations to enhance program design included: improved definitional consistency of qualifiers and selection criteria, better co-ordination across agencies; clarification about how SME suppliers benefit from federal contracting; goal setting; specification of categories that are most suitable for women-owned businesses; and, increasing primary contractor awareness about the importance of subcontract relationships. Recommendations also included third-party certification of eligible firms and the need to enhance SMEs’ financial literacy to reduce financial errors. Finally, there remains the need for clear and consistent pre-program statistics to establish baselines (by sector, issuing department) performance measures, targets based on percentage of contracts granted, value of contract, percentage of target employee (women, indigenous), and community benefits including hiring local employees. The study advances strategies to enhance federal procurement programs to facilitate socio-economic policy objectives.

Keywords: procurement, small business, policy, women

Procedia PDF Downloads 99

Authors: Sherly Shelton, Zhaohui Lin

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In recent decades, the inter-annual variability of summer precipitation over the India and Sri Lanka has intensified significantly with an increased frequency of both abnormally dry and wet summers. Therefore prediction of the inter-annual variability of summer precipitation is crucial and urgent for water management and local agriculture scheduling. However, none of the hypotheses put forward so far could understand the relationship to monsoon variability and related factors that affect to the South West Monsoon (SWM) variability in Sri Lanka. This study focused to identify the spatial and temporal variability of SWM rainfall events from June to September (JJAS) over Sri Lanka and associated trend. The monthly rainfall records covering 1980-2013 over the Sri Lanka are used for 19 stations to investigate long-term trends in SWM rainfall over Sri Lanka. The linear trends of atmospheric variables are calculated to understand the drivers behind the changers described based on the observed precipitation, sea surface temperature and atmospheric reanalysis products data for 34 years (1980–2013). Empirical orthogonal function (EOF) analysis was applied to understand the spatial and temporal behaviour of seasonal SWM rainfall variability and also investigate whether the trend pattern is the dominant mode that explains SWM rainfall variability. The spatial and stations based precipitation over the country showed statistically insignificant decreasing trends except few stations. The first two EOFs of seasonal (JJAS) mean of rainfall explained 52% and 23 % of the total variance and first PC showed positive loadings of the SWM rainfall for the whole landmass while strongest positive lording can be seen in western/ southwestern part of the Sri Lanka. There is a negative correlation (r ≤ -0.3) between SMRI and SST in the Arabian Sea and Central Indian Ocean which indicate that lower temperature in the Arabian Sea and Central Indian Ocean are associated with greater rainfall over the country. This study also shows that consistently warming throughout the Indian Ocean. The result shows that the perceptible water over the county is decreasing with the time which the influence to the reduction of precipitation over the area by weakening drawn draft. In addition, evaporation is getting weaker over the Arabian Sea, Bay of Bengal and Sri Lankan landmass which leads to reduction of moisture availability required for the SWM rainfall over Sri Lanka. At the same time, weakening of the SST gradients between Arabian Sea and Bay of Bengal can deteriorate the monsoon circulation, untimely which diminish SWM over Sri Lanka. The decreasing trends of moisture, moisture transport, zonal wind, moisture divergence with weakening evaporation over Arabian Sea, during the past decade having an aggravating influence on decreasing trends of monsoon rainfall over the Sri Lanka.

Keywords: Arabian Sea, moisture flux convergence, South West Monsoon, Sri Lanka, sea surface temperature

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Authors: Hesam Gholami

Abstract:

Elevated suspended sediment loads in riverine systems resulting from accelerated erosion due to human activities are a serious threat to the sustainable management of watersheds and ecosystem services therein worldwide. Therefore, mitigation of deleterious sediment effects as a distributed or non-point pollution source in the catchments requires reliable provenance information. Sediment tracing or sediment fingerprinting, as a combined process consisting of sampling, laboratory measurements, different statistical tests, and the application of mixing or unmixing models, is a useful technique for discriminating the sources of sediments. From 1996 to the present, different aspects of this technique, such as grouping the sources (spatial and individual sources), discriminating the potential sources by different statistical techniques, and modification of mixing and unmixing models, have been introduced and modified by many researchers worldwide, and have been applied to identify the provenance of fine materials in agricultural, rural, mountainous, and coastal catchments, and in large catchments with numerous lakes and reservoirs. In the last two decades, efforts exploring the uncertainties associated with sediment fingerprinting results have attracted increasing attention. The frameworks used to quantify the uncertainty associated with fingerprinting estimates can be divided into three groups comprising Monte Carlo simulation, Bayesian approaches and generalized likelihood uncertainty estimation (GLUE). Given the above background, the primary goal of this study was to apply geochemical fingerprinting within the GLUE framework in the estimation of sub-basin spatial sediment source contributions in the arid Mehran River catchment in southern Iran, which drains into the Persian Gulf. The accuracy of GLUE predictions generated using four different sets of statistical tests for discriminating three sub-basin spatial sources was evaluated using 10 virtual sediments (VS) samples with known source contributions using the root mean square error (RMSE) and mean absolute error (MAE). Based on the results, the contributions modeled by GLUE for the western, central and eastern sub-basins are 1-42% (overall mean 20%), 0.5-30% (overall mean 12%) and 55-84% (overall mean 68%), respectively. According to the mean absolute fit (MAF; ≥ 95% for all target sediment samples) and goodness-of-fit (GOF; ≥ 99% for all samples), our suggested modeling approach is an accurate technique to quantify the source of sediments in the catchments. Overall, the estimated source proportions can help watershed engineers plan the targeting of conservation programs for soil and water resources.

Keywords: sediment source tracing, generalized likelihood uncertainty estimation, virtual sediment mixtures, Iran

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Authors: Bruno R. Mendes, Francisco J. Caldeira, Rita S. Luís

Abstract:

Population ageing is directly correlated to an increase in medicine consumption. Beyond the latter and the polymedicated profile of elderly, it is possible to see a need for pharmacotherapeutic monitoring due to cognitive and physical impairment. In this sense, the tracking, organization and administration of medicines become a daily challenge and the pill-box dispenser system a solution. The pill-box dispenser (system) consists in a small compartmentalized container to unit dose organization, which means a container able to correlate the patient’s prescribed dose regimen and the time schedule of intake. In many European countries, this system is part of pharmacist’s role in clinical pharmacy. Despite this simple solution, therapy compliance is only possible if the patient adheres to the system, so it is important to establish a qualitative and quantitative analysis on the perception of the patient on the benefits and risks of the pill-box dispenser as well as the identification of the ideal system. The analysis was conducted through an observational study, based on the application of a standardized questionnaire structured with the numerical scale of Likert (5 levels) and previously validated on the population. The study was performed during a limited period of time and under a randomized sample of 188 participants. The questionnaire consisted of 22 questions: 6 background measures and 16 specific measures. The standards for the final comparative analysis were obtained through the state-of-the-art on the subject. The study carried out using the Likert scale afforded a degree of agreement and discordance between measures (Sample vs. Standard) of 56,25% and 43,75%, respectively. It was concluded that the pill-box dispenser has greater acceptance among a younger population, that was not the initial target of the system. However, this allows us to guarantee a high adherence in the future. Additionally, it was noted that the cost associated with this service is not a limiting factor for its use. The pill-box dispenser system, as currently implemented, demonstrates an important weakness regarding the quality and effectiveness of the medicines, which is not understood by the patient, revealing a significant lack of literacy when it concerns with medicine area. The characteristics of an ideal system remain unchanged, which means that the size, appearance and availability of information in the pill-box continue to be indispensable elements for the compliance with the system. The pill-box dispenser remains unsuitable regarding container size and the type of treatment to which it applies. Despite that, it might be a future standard for clinical pharmacy, allowing a differentiation of the pharmacist role, as well as a wider range of applications to other age groups and treatments.

Keywords: clinical pharmacy, medicines, patient safety, pill-box dispenser

Procedia PDF Downloads 182