Search results for: booking amount

Authors: Aswathaman Vijayan, Manish Jha, Ullas Theertha

Abstract:

Climate change and Global warming have become an issue for both developed and developing countries and perhaps the biggest threat to the environment. We at ITC Limited believe that a company’s performance must be measured by its Triple Bottom Line contribution to building economic, social and environmental capital. This Triple Bottom Line strategy focuses on - Embedding sustainability in business practices, Investing in social development and Adopting a low carbon growth path with a cleaner environment approach. The Agri Business Division - ILTD operates in the tobacco crop growing regions of Andhra Pradesh and Karnataka province of India. The Agri value chain of the company comprises of two distinct phases: First phase is Agricultural operations undertaken by ITC trained farmers and the second phase is Industrial operations which include marketing and processing of the agricultural produce. This research work covers the Greenhouse Gas (GHG) management strategy of ITC in the Agricultural operations undertaken by the farmers. The agriculture sector adds considerably to global GHG emissions through the use of carbon-based energies, use of fertilizers and other farming operations such as ploughing. In order to minimize the impact of farming operations on the environment, ITC has a taken a big leap in implementing system and process in reducing the GHG impact in farm value chain by partnering with the farming community. The company has undertaken a unique three-pronged approach for GHG management at the farm value chain: 1) GHG inventory at farm value chain: Different sources of GHG emission in the farm value chain were identified and quantified for the baseline year, as per the IPCC guidelines for greenhouse gas inventories. The major sources of emission identified are - emission due to nitrogenous fertilizer application during seedling production and main-field; emission due to diesel usage for farm machinery; emission due to fuel consumption and due to burning of crop residues. 2) Identification and implementation of technologies to reduce GHG emission: Various methodologies and technologies were identified for each GHG emission source and implemented at farm level. The identified methodologies are – reducing the consumption of chemical fertilizer usage at the farm through site-specific nutrient recommendation; Usage of sharp shovel for land preparation to reduce diesel consumption; implementation of energy conservation technologies to reduce fuel requirement and avoiding burning of crop residue by incorporation in the main field. These identified methodologies were implemented at farm level, and the GHG emission was quantified to understand the reduction in GHG emission. 3) Social and farm forestry for CO2 sequestration: In addition, the company encouraged social and farm forestry in the waste lands to convert it into green cover. The plantations are carried out with fast growing trees viz., Eucalyptus, Casuarina, and Subabul at the rate of 10,000 Ha of land per year. The above approach minimized considerable amount of GHG emission at the farm value chain benefiting farmers, community, and environment at a whole. In addition, the CO₂ stock created by social and farm forestry program has made the farm value chain to become environment-friendly.

Keywords: CO₂ sequestration, farm value chain, greenhouse gas, ITC limited

Procedia PDF Downloads 273

Authors: Rohit T. P., Sahil Athrij, Sasi Gopalan

Abstract:

Currently, the content entertainment industry is dominated by mobile devices. As the trends slowly shift towards Augmented/Virtual Reality applications the computational demands on these devices are increasing exponentially and we are already reaching the limits of hardware optimizations. This paper proposes a software solution to this problem. By leveraging the capabilities of cloud computing we can offload the work from mobile devices to dedicated rendering servers that are way more powerful. But this introduces the problem of latency. This paper introduces a protocol that can achieve high-performance low latency Augmented/Virtual Reality experience. There are two parts to the protocol, 1) In-flight compression The main cause of latency in the system is the time required to transmit the camera frame from client to server. The round trip time is directly proportional to the amount of data transmitted. This can therefore be reduced by compressing the frames before sending. Using some standard compression algorithms like JPEG can result in minor size reduction only. Since the images to be compressed are consecutive camera frames there won't be a lot of changes between two consecutive images. So inter-frame compression is preferred. Inter-frame compression can be implemented efficiently using WebGL but the implementation of WebGL limits the precision of floating point numbers to 16bit in most devices. This can introduce noise to the image due to rounding errors, which will add up eventually. This can be solved using an improved interframe compression algorithm. The algorithm detects changes between frames and reuses unchanged pixels from the previous frame. This eliminates the need for floating point subtraction thereby cutting down on noise. The change detection is also improved drastically by taking the weighted average difference of pixels instead of the absolute difference. The kernel weights for this comparison can be fine-tuned to match the type of image to be compressed. 2) Dynamic Load distribution Conventional cloud computing architectures work by offloading as much work as possible to the servers, but this approach can cause a hit on bandwidth and server costs. The most optimal solution is obtained when the device utilizes 100% of its resources and the rest is done by the server. The protocol balances the load between the server and the client by doing a fraction of the computing on the device depending on the power of the device and network conditions. The protocol will be responsible for dynamically partitioning the tasks. Special flags will be used to communicate the workload fraction between the client and the server and will be updated in a constant interval of time ( or frames ). The whole of the protocol is designed so that it can be client agnostic. Flags are available to the client for resetting the frame, indicating latency, switching mode, etc. The server can react to client-side changes on the fly and adapt accordingly by switching to different pipelines. The server is designed to effectively spread the load and thereby scale horizontally. This is achieved by isolating client connections into different processes.

Keywords: 2D kernelling, augmented reality, cloud computing, dynamic load distribution, immersive experience, mobile computing, motion tracking, protocols, real-time systems, web-based augmented reality application

Procedia PDF Downloads 52

Authors: Mohamed Sifan, Brabha Nagaratnam, Julian Thamboo, Keerthan Poologanathan

Abstract:

Ultra high performance concrete (UHPC) is a type of cementitious material known for its exceptional strength, ductility, and durability. However, its production is often associated with high costs due to the significant amount of cementitious materials required and the use of fine powders to achieve the desired strength. The aim of this research is to explore the feasibility of developing cost-effective UHPC mixes using locally available materials. Specifically, the study aims to investigate the use of coarse limestone sand along with other sand types, namely, basalt sand, dolomite sand, and river sand for developing UHPC mixes and evaluating its performances. The study utilises the particle packing model to develop various UHPC mixes. The particle packing model involves optimising the combination of coarse limestone sand, basalt sand, dolomite sand, and river sand to achieve the desired properties of UHPC. The developed UHPC mixes are then evaluated based on their workability (measured through slump flow and mini slump value), compressive strength (at 7, 28, and 90 days), splitting tensile strength, and microstructural characteristics analysed through scanning electron microscope (SEM) analysis. The results of this study demonstrate that cost-effective UHPC mixes can be developed using locally available materials without the need for silica fume or fly ash. The UHPC mixes achieved impressive compressive strengths of up to 149 MPa at 28 days with a cement content of approximately 750 kg/m³. The mixes also exhibited varying levels of workability, with slump flow values ranging from 550 to 850 mm. Additionally, the inclusion of coarse limestone sand in the mixes effectively reduced the demand for superplasticizer and served as a filler material. By exploring the use of coarse limestone sand and other sand types, this study provides valuable insights into optimising the particle packing model for UHPC production. The findings highlight the potential to reduce costs associated with UHPC production without compromising its strength and durability. The study collected data on the workability, compressive strength, splitting tensile strength, and microstructural characteristics of the developed UHPC mixes. Workability was measured using slump flow and mini slump tests, while compressive strength and splitting tensile strength were assessed at different curing periods. Microstructural characteristics were analysed through SEM and energy dispersive X-ray spectroscopy (EDS) analysis. The collected data were then analysed and interpreted to evaluate the performance and properties of the UHPC mixes. The research successfully demonstrates the feasibility of developing cost-effective UHPC mixes using locally available materials. The inclusion of coarse limestone sand, in combination with other sand types, shows promising results in achieving high compressive strengths and satisfactory workability. The findings suggest that the use of the particle packing model can optimise the combination of materials and reduce the reliance on expensive additives such as silica fume and fly ash. This research provides valuable insights for researchers and construction practitioners aiming to develop cost-effective UHPC mixes using readily available materials and an optimised particle packing approach.

Keywords: cost-effective, limestone powder, particle packing model, ultra high performance concrete

Procedia PDF Downloads 68

Authors: Dario Milani, Guido Morgenthal

Abstract:

Fluid dynamic computation of wind caused forces on bluff bodies e.g light flexible civil structures or high incidence of ground approaching airplane wings, is one of the major criteria governing their design. For such structures a significant dynamic response may result, requiring the usage of small scale devices as guide-vanes in bridge design to control these effects. The focus of this paper is on the numerical simulation of the bluff body problem involving multiscale phenomena induced by small scale devices. One of the solution methods for the CFD simulation that is relatively successful in this class of applications is the Vortex Particle Method (VPM). The method is based on a grid free Lagrangian formulation of the Navier-Stokes equations, where the velocity field is modeled by particles representing local vorticity. These vortices are being convected due to the free stream velocity as well as diffused. This representation yields the main advantages of low numerical diffusion, compact discretization as the vorticity is strongly localized, implicitly accounting for the free-space boundary conditions typical for this class of FSI problems, and a natural representation of the vortex creation process inherent in bluff body flows. When the particle resolution reaches the Kolmogorov dissipation length, the method becomes a Direct Numerical Simulation (DNS). However, it is crucial to note that any solution method aims at balancing the computational cost against the accuracy achievable. In the classical VPM method, if the fluid domain is discretized by Np particles, the computational cost is O(Np2). For the coupled FSI problem of interest, for example large structures such as long-span bridges, the aerodynamic behavior may be influenced or even dominated by small structural details such as barriers, handrails or fairings. For such geometrically complex and dimensionally large structures, resolving the complete domain with the conventional VPM particle discretization might become prohibitively expensive to compute even for moderate numbers of particles. It is possible to reduce this cost either by reducing the number of particles or by controlling its local distribution. It is also possible to increase the accuracy of the solution without increasing substantially the global computational cost by computing a correction of the particle-particle interaction in some regions of interest. In this paper different strategies are presented in order to extend the conventional VPM method to reduce the computational cost whilst resolving the required details of the flow. The methods include temporal sub stepping to increase the accuracy of the particles convection in certain regions as well as dynamically re-discretizing the particle map to locally control the global and the local amount of particles. Finally, these methods will be applied on a test case and the improvements in the efficiency as well as the accuracy of the proposed extension to the method are presented. The important benefits in terms of accuracy and computational cost of the combination of these methods will be thus presented as long as their relevant applications.

Keywords: adaptation, fluid dynamic, remeshing, substepping, vortex particle method

Procedia PDF Downloads 240

Authors: Sesethu G. Njokweni, Marelize Botes, Emile W. H. Van Zyl

Abstract:

An alternative strategy to the production of bioethanol is by examining the degradability of biomass in a natural system such as the rumen of mammals. This anaerobic microbial community has higher cellulolytic activities than microbial communities from other habitats and degrades cellulose to produce volatile fatty acids (VFA), methane and CO₂. VFAs have the potential to serve as intermediate products for electrochemical conversion to hydrocarbon fuels. In vitro mimicking of this process would be more cost-effective than bioethanol production as it does not require chemical pre-treatment of biomass, a sterile environment or added enzymes. The strategies of the carboxylate platform and the co-cultures of a bovine ruminal microbiota from cannulated cows were combined in order to investigate and optimize the bioconversion of agricultural biomass (apple and grape pomace, citrus pulp, sugarcane bagasse and triticale straw) to high value VFAs as intermediates for biofuel production in a consolidated bioprocess. Optimisation of reactor conditions was investigated using five different ruminal inoculum concentrations; 5,10,15,20 and 25% with fixed pH at 6.8 and temperature at 39 ˚C. The ANKOM 200/220 fiber analyser was used to analyse in vitro neutral detergent fiber (NDF) disappearance of the feedstuffs. Fresh and cryo-frozen (5% DMSO and 50% glycerol for 3 months) rumen cultures were tested for the retainment of fermentation capacity and durability in 72 h fermentations in 125 ml serum vials using a FURO medical solutions 6-valve gas manifold to induce anaerobic conditions. Fermentation of apple pomace, triticale straw, and grape pomace showed no significant difference (P > 0.05) in the effect of 15 and 20 % inoculum concentrations for the total VFA yield. However, high performance liquid chromatographic separation within the two inoculum concentrations showed a significant difference (P < 0.05) in acetic acid yield, with 20% inoculum concentration being the optimum at 4.67 g/l. NDF disappearance of 85% in 96 h and total VFA yield of 11.5 g/l in 72 h (A/P ratio = 2.04) for apple pomace entailed that it was the optimal feedstuff for this process. The NDF disappearance and VFA yield of DMSO (82% NDF disappearance and 10.6 g/l VFA) and glycerol (90% NDF disappearance and 11.6 g/l VFA) stored rumen also showed significantly similar degradability of apple pomace with lack of treatment effect differences compared to a fresh rumen control (P > 0.05). The lack of treatment effects was a positive sign in indicating that there was no difference between the stored samples and the fresh rumen control. Retaining of the fermentation capacity within the preserved cultures suggests that its metabolic characteristics were preserved due to resilience and redundancy of the rumen culture. The amount of degradability and VFA yield within a short span was similar to other carboxylate platforms that have longer run times. This study shows that by virtue of faster rates and high extent of degradability, small scale alternatives to bioethanol such as rumen microbiomes and other natural fermenting microbiomes can be employed to enhance the feasibility of biofuels large-scale implementation.

Keywords: agricultural wastes, carboxylate platform, rumen microbiome, volatile fatty acids

Procedia PDF Downloads 106

Authors: Ting Wu, Feiting Hu, Xinyue Zhang, Shuxin Tang, Xiaoyun Xu

Abstract:

As a by-product of yuba, processing wastewater of Yuba (PWY) contains many bioactive components such as soybean isoflavones, soybean polysaccharides and soybean oligosaccharides, which is a good source of prebiotics and has a potential of high value utilization. The use of Lactobacillus plantarum to ferment PWY can be considered as a potential biogenic element, which can regulate the balance of intestinal microbiota. In this study, firstly, Lactobacillus plantarum was used to ferment PWY to improve its content of active components and antioxidant activity. Then, the health effect of fermented processing wastewater of yuba (FPWY) was measured in vitro. Finally, microencapsulation technology was used applied to improve the sustained release of FPWY and reduce the loss of active components in the digestion process, as well as to improving the activity of FPWY. The main results are as follows: (1) FPWY presented a good antioxidant capacity with DPPH free radical scavenging ability (0.83 ± 0.01 mmol Trolox/L), ABTS free radical scavenging ability (7.47 ± 0.35 mmol Trolox/L) and iron ion reducing ability (1.11 ± 0.07 mmol Trolox/L). Compared with non-fermented processing wastewater of yuba (NFPWY), there was no significant difference in the content of total soybean isoflavones, but the content of glucoside soybean isoflavones decreased, and aglyconic soybean isoflavones increased significantly. After fermentation, PWY can effectively reduce the soluble monosaccharides, disaccharides and oligosaccharides, such as glucose, fructose, galactose, trehalose, stachyose, maltose, raffinose and sucrose. (2) FPWY can significantly enhance the growth of beneficial bacteria such as Bifidobacterium, Ruminococcus and Akkermansia, significantly inhibit the growth of harmful bacteria E.coli, regulate the structure of intestinal microbiota, and significantly increase the content of short-chain fatty acids such as acetic acid, propionic acid, butyric acid, isovaleric acid. Higher amount of lactic acid in the gut can be further broken down into short chain fatty acids. (3) In order to improve the stability of soybean isoflavones in FPWY during digestion, sodium alginate and chitosan were used as wall materials for embedding. The FPWY freeze-dried powder was embedded by the method of acute-coagulation bath. The results show that when the core wall ratio is 3:1, the concentration of chitosan is 1.5%, the concentration of sodium alginate is 2.0%, and the concentration of calcium is 3%, the embossing rate is 53.20%. In the simulated in vitro digestion stage, the release rate of microcapsules reached 59.36% at the end of gastric digestion and 82.90% at the end of intestinal digestion. Therefore, the core materials with good sustained-release performance of microcapsules were almost all released. The structural analysis results of FPWY microcapsules show that the microcapsules have good mechanical properties. Its hardness, springness, cohesiveness, gumminess, chewiness and resilience were 117.75± 0.21 g, 0.76±0.02, 0.54±0.01, 63.28±0.71 g·sec, 48.03±1.37 g·sec, 0.31±0.01, respectively. Compared with the unembedded FPWY, the infrared spectrum results showed that the microcapsules had embedded effect on the FPWY freeze-dried powder.

Keywords: processing wastewater of yuba, lactobacillus plantarum, intestinal microbiota, microcapsule

Procedia PDF Downloads 52

Authors: Lucas L. L. Fortes, Sandro T. M. Gonçalves

Abstract:

In this work, it is analyzed the wideband performance with the mesh discretization impoverishment of the Conformal Finite Difference Time-Domain (C-FDTD) approaches developed by Raj Mittra, Supriyo Dey and Wenhua Yu for the Finite Difference Time-Domain (FDTD) method. These approaches are a simple and efficient way to optimize the scattering simulation of curved surfaces for Dielectric and Perfect Electric Conducting (PEC) structures in the FDTD method, since curved surfaces require dense meshes to reduce the error introduced due to the surface staircasing. Defined, on this work, as D-FDTD-Diel and D-FDTD-PEC, these approaches are well-known in the literature, but the improvement upon their application is not quantified broadly regarding wide frequency bands and poorly discretized meshes. Both approaches bring improvement of the accuracy of the simulation without requiring dense meshes, also making it possible to explore poorly discretized meshes which bring a reduction in simulation time and the computational expense while retaining a desired accuracy. However, their applications present limitations regarding the mesh impoverishment and the frequency range desired. Therefore, the goal of this work is to explore the approaches regarding both the wideband and mesh impoverishment performance to bring a wider insight over these aspects in FDTD applications. The D-FDTD-Diel approach consists in modifying the electric field update in the cells intersected by the dielectric surface, taking into account the amount of dielectric material within the mesh cells edges. By taking into account the intersections, the D-FDTD-Diel provides accuracy improvement at the cost of computational preprocessing, which is a fair trade-off, since the update modification is quite simple. Likewise, the D-FDTD-PEC approach consists in modifying the magnetic field update, taking into account the PEC curved surface intersections within the mesh cells and, considering a PEC structure in vacuum, the air portion that fills the intersected cells when updating the magnetic fields values. Also likewise to D-FDTD-Diel, the D-FDTD-PEC provides a better accuracy at the cost of computational preprocessing, although with a drawback of having to meet stability criterion requirements. The algorithms are formulated and applied to a PEC and a dielectric spherical scattering surface with meshes presenting different levels of discretization, with Polytetrafluoroethylene (PTFE) as the dielectric, being a very common material in coaxial cables and connectors for radiofrequency (RF) and wideband application. The accuracy of the algorithms is quantified, showing the approaches wideband performance drop along with the mesh impoverishment. The benefits in computational efficiency, simulation time and accuracy are also shown and discussed, according to the frequency range desired, showing that poorly discretized mesh FDTD simulations can be exploited more efficiently, retaining the desired accuracy. The results obtained provided a broader insight over the limitations in the application of the C-FDTD approaches in poorly discretized and wide frequency band simulations for Dielectric and PEC curved surfaces, which are not clearly defined or detailed in the literature and are, therefore, a novelty. These approaches are also expected to be applied in the modeling of curved RF components for wideband and high-speed communication devices in future works.

Keywords: accuracy, computational efficiency, finite difference time-domain, mesh impoverishment

Procedia PDF Downloads 105

Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

Abstract:

There is a growing interest on the synthesis and characterization of nanoalloys since the unique chemical, and physical properties of nanoalloys can be tuned and, consequently, new structural motifs can be created by varying the type of constituent elements, atomic and magnetic ordering, as well as size and shape of the nanoparticles. Due to the fine size effects, magnetic nanoalloys have considerable attention with their enhanced mechanical, electrical, optical and magnetic behavior. As an important magnetic nanoalloy, the novel application area of Fe-Ni based nanoalloys is expected to be widened in the chemical, aerospace industry and magnetic biomedical applications. Noble metals have been using in biomedical applications for several years because of their surface plasmon properties. In this respect, iron-nickel nanoalloys are promising materials for magnetic biomedical applications because they show novel properties such as superparamagnetism and surface plasmon resonance property. Also, there is great attention for the usage Fe-Ni based nanoalloys as radar absorbing materials in aerospace and stealth industry due to having high Curie temperature, high permeability and high saturation magnetization with good thermal stability. In this study, FeNi₃ bimetallic nanoalloys were synthesized by mechanical alloying in a planetary high energy ball mill. In mechanical alloying, micron size powders are placed into the mill with milling media. The powders are repeatedly deformed, fractured and alloyed by high energy collision under the impact of balls until the desired composition and particle size is achieved. The experimental studies were carried out in two parts. Firstly, dry mechanical alloying with high energy dry planetary ball milling was applied to obtain FeNi₃ nanoparticles. Secondly, dry milling was followed by surfactant-assisted ball milling to observe the surfactant and solvent effect on the structure, size, and properties of the FeNi₃ nanoalloys. In the first part, the powder sample of iron-nickel was prepared according to the 1:3 iron to nickel ratio to produce FeNi₃ nanoparticles and the 1:10 powder to ball weight ratio. To avoid oxidation during milling, the vials had been filled with Ar inert gas before milling started. The powders were milled for 80 hours in total and the synthesis of the FeNi₃ intermetallic nanoparticles was succeeded by mechanical alloying in 40 hours. Also, regarding the particle size, it was found that the amount of nano-sized particles raised with increasing milling time. In the second part of the study, dry milling of the Fe and Ni powders with the same stoichiometric ratio was repeated. Then, to prevent agglomeration and to obtain smaller sized nanoparticles with superparamagnetic behavior, surfactants and solvent are added to the system, after 40-hour milling time, with the completion of the mechanical alloying. During surfactant-assisted ball milling, heptane was used as milling medium, and as surfactants, oleic acid and oleylamine were used in the high energy ball milling processes. The characterization of the alloyed particles in terms of microstructure, morphology, particle size, thermal and magnetic properties with respect to milling time was done by X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, vibrating-sample magnetometer, and differential scanning calorimetry.

Keywords: iron-nickel systems, magnetic nanoalloys, mechanical alloying, nanoalloy characterization, surfactant-assisted ball milling

Procedia PDF Downloads 154

Authors: Siyamak Ziyaei, Siti Khalijah Mazlan, Petros Lappas

Abstract:

Compressed Natural Gas (CNG) mainly consists of Methane CH₄ and has a low carbon to hydrogen ratio relative to other hydrocarbons. As a result, it has the potential to reduce CO₂ emissions by more than 20% relative to conventional fuels like diesel or gasoline Although Natural Gas (NG) has environmental advantages compared to other hydrocarbon fuels whether they are gaseous or liquid, its main component, CH₄, burns at a slower rate than conventional fuels A higher pressure and a leaner cylinder environment will overemphasize slow burn characteristic of CH₄. Lean combustion and high compression ratios are well-known methods for increasing the efficiency of internal combustion engines. In order to achieve successful CNG lean combustion in Spark Ignition (SI) engines, a strong ignition system is essential to avoid engine misfires, especially in ultra-lean conditions. Turbulent Jet Ignition (TJI) is an ignition system that employs a pre-combustion chamber to ignite the lean fuel mixture in the main combustion chamber using a fraction of the total fuel per cycle. TJI enables ultra-lean combustion by providing distributed ignition sites through orifices. The fast burn rate provided by TJI enables the ordinary SI engine to be comparable to other combustion systems such as Homogeneous Charge Compression Ignition (HCCI) or Controlled Auto-Ignition (CAI) in terms of thermal efficiency, through the increased levels of dilution without the need of sophisticated control systems. Due to the physical geometry of TJIs, which contain small orifices that connect the prechamber to the main chamber, scavenging is one of the main factors that reduce TJI performance. Specifically, providing the right mixture of fuel and air has been identified as a key challenge. The reason for this is the insufficient amount of air that is pushed into the pre-chamber during each compression stroke. There is also the problem that combustion residual gases such as CO₂, CO and NOx from the previous combustion cycle dilute the pre- chamber fuel-air mixture preventing rapid combustion in the pre-chamber. An air-controlled active TJI is presented in this paper in order to address these issues. By applying air to the pre-chamber at a sufficient pressure, residual gases are exhausted, and the air-fuel ratio is controlled within the pre-chamber, thereby improving the quality of combustion. This paper investigates the 3D-simulated combustion characteristics of a Direct Injected (DI-CNG) fuelled SI en- gine with a pre-chamber equipped with an air channel by using AVL FIRE software. Experiments and simulations were performed at the Worldwide Mapping Point (WWMP) at 1500 Revolutions Per Minute (RPM), 3.3 bar Indicated Mean Effective Pressure (IMEP), using only conventional spark plugs as the baseline. After validating simulation data, baseline engine conditions were set for all simulation scenarios at λ=1. Following that, the pre-chambers with and without an auxiliary fuel supply were simulated. In the simulated (DI-CNG) SI engine, active TJI was observed to perform better than passive TJI and spark plug. In conclusion, the active pre-chamber with an air channel demon-strated an improved thermal efficiency (ηth) over other counterparts and conventional spark ignition systems.

Keywords: turbulent jet ignition, active air control turbulent jet ignition, pre-chamber ignition system, active and passive pre-chamber, thermal efficiency, methane combustion, internal combustion engine combustion emissions

Procedia PDF Downloads 65

Authors: Juan Pablo Bertuzzi, Mauro Chiarella

Abstract:

Employing a communication studies perspective and a socio-technological approach, this paper introduces a theoretical framework for understanding the concept of hybrid world; the avatarization phenomena; and the communicational archetype of co-hybridization. This analysis intends to make a contribution to future design of virtual reality experimental applications. Ultimately, this paper presents an ongoing research project that proposes the study of human-avatar interactions in digital educational environments, as well as an innovative reflection on inner digital communication. The aforementioned project presents the analysis of human-avatar interactions, through the development of an interactive experience in virtual reality. The goal is to generate an innovative communicational dimension that could reinforce the hypotheses presented throughout this paper. Being thought for its initial application in educational environments, the analysis and results of this research are dependent and have been prepared in regard of a meticulous planning of: the conception of a 3D digital platform; the interactive game objects; the AI or computer avatars; the human representation as hybrid avatars; and lastly, the potential of immersion, ergonomics and control diversity that can provide the virtual reality system and the game engine that were chosen. The project is divided in two main axes: The first part is the structural one, as it is mandatory for the construction of an original prototype. The 3D model is inspired by the physical space that belongs to an academic institution. The incorporation of smart objects, avatars, game mechanics, game objects, and a dialogue system will be part of the prototype. These elements have all the objective of gamifying the educational environment. To generate a continuous participation and a large amount of interactions, the digital world will be navigable both, in a conventional device and in a virtual reality system. This decision is made, practically, to facilitate the communication between students and teachers; and strategically, because it will help to a faster population of the digital environment. The second part is concentrated to content production and further data analysis. The challenge is to offer a scenario’s diversity that compels users to interact and to question their digital embodiment. The multipath narrative content that is being applied is focused on the subjects covered in this paper. Furthermore, the experience with virtual reality devices proposes users to experiment in a mixture of a seemingly infinite digital world and a small physical area of movement. This combination will lead the narrative content and it will be crucial in order to restrict user’s interactions. The main point is to stimulate and to grow in the user the need of his hybrid avatar’s help. By building an inner communication between user’s physicality and user’s digital extension, the interactions will serve as a self-guide through the gameworld. This is the first attempt to make explicit the avatarization phenomena and to further analyze the communicational archetype of co-hybridization. The challenge of the upcoming years will be to take advantage from these forms of generalized avatarization, in order to create awareness and establish innovative forms of hybridization.

Keywords: avatar, hybrid worlds, socio-technology, virtual reality

Procedia PDF Downloads 115

Authors: Tugba G. Isin Ozkan, Yoshiharu Fujii

Abstract:

One of the most important constrains that decrease the crop yields are weeds. Increased amount and number of chemical herbicides are being utilized every day to control weeds. Chemical herbicides which cause environmental effects, and limitations on implementation of them have led to the nonchemical alternatives in the management of weeds. It is needed increasingly the application of allelopathy as a nonherbicidal innovation to control weed populations in integrated weed management. It is not only because of public concern about herbicide use, but also increased agricultural costs and herbicide resistance weeds. Allelopathy is defined as a common biological phenomenon, direct or indirect interaction which one plant or organism produces biochemicals influence the physiological processes of another neighboring plant or organism. Biochemicals involved in allelopathy are called allelochemicals that influence beneficially or detrimentally the growth, survival, development, and reproduction of other plant or organisms. All plant parts could have allelochemicals which are secondary plant metabolites. Allelochemicals are released to environment, influence the germination and seedling growth of neighbors' weeds; that is the way how allelopathy is applied for weed control. Crop cultivars have significantly different ability for inhibiting the growth of certain weeds. So, a high commercial value crop Corylus avellana L. and its byproducts were chosen to introduce for their allelopathic potential in this research. Edible nut of Corylus avellana L., commonly known as hazelnut is commercially valuable crop with byproducts; skin, hard shell, green leafy cover, and tree leaf. Research on allelopathic potential of a plant by using the sandwich bioassay method and investigation growth inhibitory activity is the first step to develop new and environmentally friendly alternatives for weed control. Thus, the objective of this research is to determine allelopathic potential of C. avellana L. and its byproducts by using sandwich method and to determine effective concentrations (EC) of their extracts for inducing half-maximum elongation inhibition on radicle of test plant, EC50. The sandwich method is reliable and fast bioassay, very useful for allelopathic screening under laboratory conditions. In experiments, lettuce (Lactuca sativa L.) seeds will be test plant, because of its high sensitivity to inhibition by allelochemicals and reliability for germination. In sandwich method, the radicle lengths of dry material treated lettuce seeds and control lettuce seeds will be measured and inhibition of radicle elongation will be determined. Lettuce seeds will also be treated by the methanol extracts of dry hazelnut parts to calculate EC₅₀ values, which are required to induce half-maximal inhibition of growth, as mg dry weight equivalent mL-1. Inhibitory activity of extracts against lettuce seedling elongation will be evaluated, like in sandwich method, by comparing the radicle lengths of treated seeds with that of control seeds and EC₅₀ values will be determined. Research samples are dry parts of Turkish hazelnut, C. avellana L. The results would suggest the opportunity for allelopathic potential of C. avellana L. with its byproducts in plant-plant interaction, might be utilized for further researches, could be beneficial in finding bioactive chemicals from natural products and developing of natural herbicides.

Keywords: allelopathy, Corylus avellana L., EC50, Lactuca sativa L., sandwich method, Turkish hazelnut

Procedia PDF Downloads 148

Authors: N. K. Ambujam, V. Sudha

Abstract:

Reservoirs are being contaminated all around the world with point source and Non-Point Source (NPS) pollution. The most common NPS pollutants are sediments and nutrients. Krishnagiri Reservoir (KR) has been chosen for the present case study, which is located in the tropical semi-arid climatic zone of Tamil Nadu, South India. It is the main source of surface water in Krishnagiri district to meet the freshwater demands. The reservoir has lost about 40% of its water holding capacity due to sedimentation over the period of 50 years. Hence, from the research and management perspective, there is a need for a sound knowledge on the spatial and seasonal variations of KR water quality. The present study encompasses the specific objectives as (i) to investigate the longitudinal heterogeneity and seasonal variations of physicochemical parameters, nutrients and biological characteristics of KR water and (ii) to examine the extent of degradation of water quality in KR. 15 sampling points were identified by uniform stratified method and a systematic monthly sampling strategy was selected due to high dynamic nature in its hydrological characteristics. The physicochemical parameters, major ions, nutrients and Chlorophyll a (Chl a) were analysed. Trophic status of KR was classified by using Carlson's Trophic State Index (TSI). All statistical analyses were performed by using Statistical Package for Social Sciences programme, version-16.0. Spatial maps were prepared for Chl a using Arc GIS. Observations in KR pointed out that electrical conductivity and major ions are highly variable factors as it receives inflow from the catchment with different land use activities. The study of major ions in KR exhibited different trends in their values and it could be concluded that as the monsoon progresses the major ions in the water decreases or water quality stabilizes. The inflow point of KR showed comparatively higher concentration of nutrients including nitrate, soluble reactive phosphorus (SRP), total phosphors (TP), total suspended phosphorus (TSP) and total dissolved phosphorus (TDP) during monsoon seasons. This evidently showed the input of significant amount of nutrients from the catchment side through agricultural runoff. High concentration of TDP and TSP at the lacustrine zone of the reservoir during summer season evidently revealed that there was a significant release of phosphorus from the bottom sediments. Carlson’s TSI of KR ranged between 81 and 92 during northeast monsoon and summer seasons. High and permanent Cyanobacterial bloom in KR could be mainly due to the internal loading of phosphorus from the bottom sediments. According to Carlson’s TSI classification Krishnagiri reservoir was ranked in the hyper-eutrophic category. This study provides necessary basic data on the spatio-temporal variations of water quality in KR and also proves the impact of point and NPS pollution from the catchment area. High TSI warrants a greater threat for the recovery of internal P loading and hyper-eutrophic condition of KR. Several expensive internal measures for the reduction of internal loading of P were introduced by many scientists. However, the outcome of the present research suggests for the innovative algae harvesting technique for the removal of sediment nutrients.

Keywords: NPS pollution, nutrients, hyper-eutrophication, krishnagiri reservoir

Procedia PDF Downloads 303

Authors: Nada Poropat Jeletic, Gordana Hrzica

Abstract:

Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

Procedia PDF Downloads 114

Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

Abstract:

Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

Procedia PDF Downloads 234

Authors: Yana Snegireva

Abstract:

Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

Procedia PDF Downloads 54

Authors: Kuo Chieh Chao, Thishani Amarathunga, Sangam Shrestha

Abstract:

Rainfall induced slope failures are one of the most damaging and disastrous natural hazards which occur frequently in the world. This type of sliding mainly occurs in the zone above the groundwater level in silty/sandy soils. When the rainwater begins to infiltrate into the vadose zone of the soil, the negative pore-water pressure tends to decrease and reduce the shear strength of soil material. Climate change has resulted in excessive and unpredictable rainfall in all around the world, resulting in landslides with dire consequences to human lives and infrastructure. Such problems could be overcome by examining in detail the causes for such slope failures and recommending effective repair plans for vulnerable locations by considering future climatic change. The selected area for this study is located in the road rehabilitation section from Maubara to Mota Ain road in Timor-Leste. Slope failures and cracks have occurred in 2013 and after repairs reoccurred again in 2017 subsequent to heavy rains. Both observed and future predicted climate data analyses were conducted to understand the severe precipitation conditions in past and future. Observed climate data were collected from NOAA global climate data portal. CORDEX data portal was used to collect Regional Climate Model (RCM) future predicted climate data. Both observed and RCM data were extracted to location-based data using ArcGIS Software. Linear scaling method was used for the bias correction of future data and bias corrected climate data were assigned to GeoStudio Software. Precipitations of wet seasons (December to March ) in 2007 to 2013 is higher than 2001-2006 period and it is more than nearly 40% higher precipitation than usual monthly average precipitation of 160mm.The results of seepage analyses which were carried out using SEEP/W model with observed climate, clearly demonstrated that the pore water pressure within the fill slope was significantly increased due to the increase of the infiltration during the wet season of 2013.One main Regional Climate Models (RCM) was analyzed in order to predict future climate variation under two Representative Concentration Pathways (RCPs).In the projected period of 76 years ahead from 2014, shows that the amount of precipitation is considerably getting higher in the future in both RCP 4.5 and RCP 8.5 emission scenarios. Critical pore water pressure conditions during 2014-2090 were used in order to recommend appropriate remediation methods. Results of slope stability analyses indicated that the factor of safety of the fill slopes was reduced from 1.226 to 0.793 during the dry season to wet season in 2013.Results of future slope stability which were obtained using SLOPE/W model for the RCP emissions scenarios depict that, the use of tieback anchors and geogrids in slope protection could be effective in increasing the stability of slopes to an acceptable level during the wet seasons. Moreover, methods and procedures like monitoring of slopes showing signs or susceptible for movement and installing surface protections could be used to increase the stability of slopes.

Keywords: climate change, precipitation, SEEP/W, SLOPE/W, unsaturated soil

Procedia PDF Downloads 105

Authors: Juergen Junk, Franz Ronellenfitsch, Michael Eickermann

Abstract:

An appropriate weed management in autumn is a prerequisite for an economically successful harvest in the following year. In Luxembourg oilseed rape, wheat and barley is sown from August until October, accompanied by a chemical weed control with soil active herbicides, depending on the state of the weeds and the meteorological conditions. Based on regular ground and surface water-analysis, high levels of contamination by transformation products of respective herbicide compounds have been found in Luxembourg. The most ideal conditions for incorporating soil active herbicides are single rain events. Weed control may be reduced if application is made when weeds are under drought stress or if repeated light rain events followed by dry spells, because the herbicides tend to bind tightly to the soil particles. These effects have been frequently reported for Luxembourg throughout the last years. In the framework of a multisite long-term field experiment (EFFO) weed monitoring, plants observations and corresponding meteorological measurements were conducted. Long-term time series (1947-2016) from the SYNOP station Findel-Airport (WMO ID = 06590) showed a decrease in the number of days with precipitation. As the total precipitation amount has not significantly changed, this indicates a trend towards rain events with higher intensity. All analyses are based on decades (10-day periods) for September and October of each individual year. To assess the future meteorological conditions for Luxembourg, two different approaches were applied. First, multi-model ensembles from the CORDEX experiments (spatial resolution ~12.5 km; transient projections until 2100) were analysed for two different Representative Concentration Pathways (RCP8.5 and RCP4.5), covering the time span from 2005 until 2100. The multi-model ensemble approach allows for the quantification of the uncertainties and also to assess the differences between the two emission scenarios. Second, to assess smaller scale differences within the country a high resolution model projection using the COSMO-LM model was used (spatial resolution 1.3 km). To account for the higher computational demands, caused by the increased spatial resolution, only 10-year time slices have been simulated (reference period 1991-2000; near future 2041-2050 and far future 2091-2100). Statistically significant trends towards higher air temperatures, +1.6 K for September (+5.3 K far future) and +1.3 K for October (+4.3 K), were predicted for the near future compared to the reference period. Precipitation simultaneously decreased by 9.4 mm (September) and 5.0 mm (October) for the near future and -49 mm (September) and -10 mm (October) in the far future. Beside the monthly values also decades were analyzed for the two future time periods of the CLM model. For all decades of September and October the number of days with precipitation decreased for the projected near and far future. Changes in meteorological variables such as air temperature and precipitation did already induce transformations in weed societies (composition, late-emerging etc.) of arable ecosystems in Europe. Therefore, adaptations of agronomic practices as well as effective weed control strategies must be developed to maintain crop yield.

Keywords: CORDEX projections, dry spells, ensembles, weed management

Procedia PDF Downloads 212

Authors: Athina Thanou, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

Abstract:

The problem of museum visitor experience and congestion management – in various forms - has come increasingly under the spotlight over the last few years, since overcrowding can significantly decrease the quality of visitors’ experience. Evidence suggests that on busy days the amount of time a visitor spends inside a crowded house museum can fall by up to 60% compared to a quiet mid-week day. In this paper we consider the aforementioned problem, by treating museums as evolving social systems that induce constraints. However, in a cultural heritage space, as opposed to the majority of social environments, the momentum of the experience is primarily controlled by the visitor himself. Visitors typically behave selfishly regarding the maximization of their own Quality of Experience (QoE) - commonly expressed through a utility function that takes several parameters into consideration, with crowd density and waiting/visiting time being among the key ones. In such a setting, congestion occurs when either the utility of one visitor decreases due to the behavior of other persons, or when costs of undertaking an activity rise due to the presence of other persons. We initially investigate how visitors’ behavioral risk attitudes, as captured and represented by prospect theory, affect their decisions in resource sharing settings, where visitors’ decisions and experiences are strongly interdependent. Different from the majority of existing studies and literature, we highlight that visitors are not risk neutral utility maximizers, but they demonstrate risk-aware behavior according to their personal risk characteristics. In our work, exhibits are organized into two groups: a) “safe exhibits” that correspond to less congested ones, where the visitors receive guaranteed satisfaction in accordance with the visiting time invested, and b) common pool of resources (CPR) exhibits, which are the most popular exhibits with possibly increased congestion and uncertain outcome in terms of visitor satisfaction. A key difference is that the visitor satisfaction due to CPR strongly depends not only on the invested time decision of a specific visitor, but also on that of the rest of the visitors. In the latter case, the over-investment in time, or equivalently the increased congestion potentially leads to “exhibit failure”, interpreted as the visitors gain no satisfaction from their observation of this exhibit due to high congestion. We present a framework where each visitor in a distributed manner determines his time investment in safe or CPR exhibits to optimize his QoE. Based on this framework, we analyze and evaluate how visitors, acting as prospect-theoretic decision-makers, respond and react to the various pricing policies imposed by the museum curators. Based on detailed evaluation results and experiments, we present interesting observations, regarding the impact of several parameters and characteristics such as visitor heterogeneity and use of alternative pricing policies, on scalability, user satisfaction, museum capacity, resource fragility, and operation point stability. Furthermore, we study and present the effectiveness of alternative pricing mechanisms, when used as implicit tools, to deal with the congestion management problem in the museums, and potentially decrease the exhibit failure probability (fragility), while considering the visitor risk preferences.

Keywords: museum resource and visitor management, congestion management, propsect theory, cyber physical social systems

Procedia PDF Downloads 159

Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh

Abstract:

The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.

Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain

Procedia PDF Downloads 87

Authors: Katerina Krizova, Inigo Molina

Abstract:

The ongoing climate change affects various natural processes resulting in significant changes in human life. Since there is still a growing human population on the planet with more or less limited resources, agricultural production became an issue and a satisfactory amount of food has to be reassured. To achieve this, agriculture is being studied in a very wide context. The main aim here is to increase primary production on a spatial unit while consuming as low amounts of resources as possible. In Europe, nowadays, the staple issue comes from significantly changing the spatial and temporal distribution of precipitation. Recent growing seasons have been considerably affected by long drought periods that have led to quantitative as well as qualitative yield losses. To cope with such kind of conditions, new techniques and technologies are being implemented in current practices. However, behind assessing the right management, there is always a set of the necessary information about plot properties that need to be acquired. Remotely sensed data had gained attention in recent decades since they provide spatial information about the studied surface based on its spectral behavior. A number of space platforms have been launched carrying various types of sensors. Spectral indices based on calculations with reflectance in visible and NIR bands are nowadays quite commonly used to describe the crop status. However, there is still the staple limit by this kind of data - cloudiness. Relatively frequent revisit of modern satellites cannot be fully utilized since the information is hidden under the clouds. Therefore, microwave remote sensing, which can penetrate the atmosphere, is on its rise today. The scientific literature describes the potential of radar data to estimate staple soil (roughness, moisture) and vegetation (LAI, biomass, height) properties. Although all of these are highly demanded in terms of agricultural monitoring, the crop moisture content is the utmost important parameter in terms of agricultural drought monitoring. The idea behind this study was to exploit the unique combination of SAR (Sentinel-1) and optical (Sentinel-2) data from one provider (ESA) to describe potential crop water stress during dry cropping season of 2019 at six winter wheat plots in the central Czech Republic. For the period of January to August, Sentinel-1 and Sentinel-2 images were obtained and processed. Sentinel-1 imagery carries information about C-band backscatter in two polarisations (VV, VH). Sentinel-2 was used to derive vegetation properties (LAI, FCV, NDWI, and SAVI) as support for Sentinel-1 results. For each term and plot, summary statistics were performed, including precipitation data and soil moisture content obtained through data loggers. Results were presented as summary layouts of VV and VH polarisations and related plots describing other properties. All plots performed along with the principle of the basic SAR backscatter equation. Considering the needs of practical applications, the vegetation moisture content may be assessed using SAR data to predict the drought impact on the final product quality and yields independently of cloud cover over the studied scene.

Keywords: precision agriculture, remote sensing, Sentinel-1, SAR, water content

Procedia PDF Downloads 97

Authors: Irene Carmagnola, Valeria Chiono, Sandra Pacharra, Jochen Salber, Sean McMahon, Chris Lovell, Pooja Basnett, Barbara Lukasiewicz, Ipsita Roy, Xiang Zhang, Gianluca Ciardelli

Abstract:

Thrombosis and restenosis after stenting procedure can be prevented by promoting fast stent wall endothelialisation. It is well known that surface functionalisation with antifouling molecules combining with extracellular matrix proteins is a promising strategy to design biomimetic surfaces able to promote fast endothelialization. In particular, REDV has gained much attention for the ability to enhance rapid endothelialization due to its specific affinity with endothelial cells (ECs). In this work, a two-step plasma treatment was performed to polymerize a thin layer of acrylic acid, used to subsequently graft PEGylated-REDV and polyethylene glycol (PEG) at different molar ratio with the aim to selectively promote endothelial cell adhesion avoiding platelet activation. PEGylate-REDV was provided by Biomatik and it is formed by 6 PEG monomer repetitions (Chempep Inc.), with an NH2 terminal group. PEG polymers were purchased from Chempep Inc. with two different chain lengths: m-PEG6-NH2 (295.4 Da) with 6 monomer repetitions and m-PEG12-NH2 (559.7 Da) with 12 monomer repetitions. Plasma activation was obtained by operating at 50W power, 5 min of treatment and at an Ar flow rate of 20 sccm. Pure acrylic acid (99%, AAc) vapors were diluted in Ar (flow = 20 sccm) and polymerized by a pulsed plasma discharge applying a discharge RF power of 200 W, a duty cycle of 10% (on time = 10 ms, off time = 90 ms) for 10 min. After plasma treatment, samples were dipped into an 1-(3-dimethylaminopropyl)-3- ethylcarbodiimide (EDC)/N-hydroxysuccinimide (NHS) solution (ratio 4:1, pH 5.5) for 1 h at 4°C and subsequently dipped in PEGylate-REDV and PEGylate-REDV:PEG solutions at different molar ratio (100 μg/mL in PBS) for 20 h at room temperature. Surface modification was characterized through physico-chemical analyses and in vitro cell tests. PEGylated-REDV peptide and PEG were successfully bound to the carboxylic groups that are formed on the polymer surface after plasma reaction. FTIR-ATR spectroscopy, X -ray Photoelectron Spectroscopy (XPS) and contact angle measurement gave a clear indication of the presence of the grafted molecules. The use of PEG as a spacer allowed for an increase in wettability of the surface, and the effect was more evident by increasing the amount of PEG. Endothelial cells adhered and spread well on the surfaces functionalized with the REDV sequence. In conclusion, a selective coating able to promote a new endothelial cell layer on polymeric stent surface was developed. In particular, a thin AAc film was polymerised on the polymeric surface in order to expose –COOH groups, and PEGylate-REDV and PEG were successful grafted on the polymeric substrates. The REDV peptide demonstrated to encourage cell adhesion with a consequent, expected improvement of the hemocompatibility of these polymeric surfaces in vivo. Acknowledgements— This work was funded by the European Commission 7th Framework Programme under grant agreement number 604251- ReBioStent (Reinforced Bioresorbable Biomaterials for Therapeutic Drug Eluting Stents). The authors thank all the ReBioStent partners for their support in this work.

Keywords: endothelialisation, plasma treatment, stent, surface functionalisation

Procedia PDF Downloads 283

Authors: Vincent Oghenekevbe Olughor, Olusoji Mayowa Ige

Abstract:

Except for a preexisting liver disease and malnutrition, there are no predilections for low serum albumin (SA) levels in humans. At normal reference levels (4.0-6.0g/dl) SA is a universal marker for mortality and morbidity risks assessments where depletion by 1.0g/dl increases mortality risk by 137% and morbidity by 89%.It has 40 known functions contributing significantly to the sustenance of human life. A depletion in SA to <2.2g/dl, in most clinical settings worldwide, leads to loss of oncotic pressure of blood causing clinical manifestations of bipedal Oedema, in which the patients remain conscious. SA also contributes significantly to buffering of blood to a life-sustaining pH of 7.35-7.45. A drop in blood pH to <6.9 will lead to instant coma and death, which can occur after SA continues to deplete after manifestations of bipedal Oedema. In an intervention study conducted in 2014 following the discovery that “SA is depleted during malaria fever”, a Nutraceutical formulated for use as treatment adjunct to prevent SA depletions during malaria to <2.4g/dl after Efficacy testing was found to be satisfactory. There are five known types of Malaria caused by Apicomplexan parasites, Plasmodium: the most lethal being that caused by Plasmodium falciparum causing malignant tertian malaria, in which the fever was occurring every 48 hours coincides with the dumping of malaria-toxins (Hemozoin) into blood, causing contamination: blood must remain sterile. Other Apicomplexan parasites, Toxoplasma and Cryptosporidium, are opportunistic infections of HIV. Separate studies showed SA depletions in MDRTB (multidrug resistant TB), and MDRTB-HIV patients by the same mechanism discovered with malaria and such depletions will be further complicated whenever Apicomplexan parasitic infections co-exist. Both Apicomplexan parasites and the TB parasite belong to the Obligate-group of Parasites, which are parasites that replicate only inside its host; and most of them have capacities to over-consume host nutrients during parasitaemia. In MDRTB patients the body attempts repeatedly to prevent depletions in SA to critical levels in the presence of adequate nutrients and only for a while in MDRTB-HIV patients. These groups of patients will, therefore, benefit from the already tested Nutraceutical in malaria patients. The Nutraceutical bio-Powder was formulated (to BP 1988 specification) from twelve nature-based food-grade nutrients containing all dedicated nutrients for ensuring improved synthesis of Albumin by the liver. The Nutraceutical was administered daily for 38±2days in 23 children, in a prospective phase-2 clinical trial, and its impact on body weight and core blood parameters were documented at the start and end of efficacy testing period. Sixteen children who did not experience malaria-induced depletions of SA had significant SA increase; seven children who experienced malaria-induced depletions of SA had insignificant SA decrease. The Packed Cell Volume Percentage (PCV %), a measure of the Oxygen carrying capacity of blood and the amount of nutrients the body can absorb, increased in both groups. The total serum proteins (SA+ Globulins) increased or decreased within the continuum of normal. In conclusion, MDRTB and MDRTB-HIV patients will benefit from a variant of this Nutraceutical when used as treatment adjunct.

Keywords: antitrypsin-free Nutraceutical, apicomplexan parasites, no predilections for low serum albumin, toxoplasmosis

Procedia PDF Downloads 266

Authors: B. Voucko, M. Benkovic, N. Cukelj, S. Drakula, D. Novotni, S. Balbino, D. Curic

Abstract:

Oxidative stress is considered as one of the causes leading to metabolic disorders in humans. Therefore, the ability of antioxidants to inhibit free radical production is their primary role in the human organism. Antioxidants originating from cereals, especially flavonoids and polyphenols, are mostly bound and indigestible. Micronization damages the cell wall which consecutively results in bioactive material to be more accessible in vivo. In order to ensure complete fragmentation, micronization is often combined with high temperatures (e.g., for bran 200°C) which can lead to degradation of bioactive compounds. The innovative non-thermal technology of cryo-milling is an ultra-fine micronization method that uses liquid nitrogen (LN2) at a temperature of 195°C to freeze and cool the sample during milling. Freezing at such low temperatures causes the material to become brittle which ensures the generation of fine particles while preserving the bioactive content of the material. The aim of this research was to determine if production of ultra-fine material with cryo-milling will result in the augmentation of available bioactive compounds of buckwheat and pumpkin seed cake. For that reason, buckwheat and pumpkin seed cake were ground in a ball mill (CryoMill, Retch, Germany) with and without the use of LN2 for 8 minutes, in a 50 mL stainless steel jar containing one grinding ball (Ø 25 mm) at an oscillation frequency of 30 Hz. The cryo-milled samples were cooled with LN2 for 2 minutes prior to milling, followed by the first cycle of milling (4 minutes), intermediary cooling (2 minutes), and finally the second cycle of milling (further 4 minutes). A continuous process of milling was applied to the samples ground without freezing with LN2. Particle size distribution was determined using the Scirocco 2000 dry dispersion unit (Malvern Instruments, UK). Antioxidant activity was determined by 2,2-Diphenyl-1-picrylhydrazyl (DPPH) test and ferric reducing antioxidant power (FRAP) assay, while the total phenol content was determined using the Folin Ciocalteu method, using the ultraviolet-visible spectrophotometer (Specord 50 Plus, Germany). The content of the free phenolic acids, rutin in buckwheat, tyrosol in pumpkin seed cake, was determined with an HPLC-PDA method (Agilent 1200 series, Germany). Cryo-milling resulted in 11 times smaller size of buckwheat particles, and 3 times smaller size of pumpkin seed particles than milling without the use of LN2, but also, a lower uniformity of the particle size distribution. Lack of freezing during milling of pumpkin seed cake caused a formation of agglomerates due to its high-fat content (21 %). Cryo-milling caused augmentation of buckwheat flour antioxidant activity measured by DPPH test (23,9%) and an increase in available rutin content (14,5%). Also, it resulted in an augmentation of the total phenol content (36,9%) and available tyrosol content (12,5%) of pumpkin seed cake. Antioxidant activity measured with the FRAP test, as well as the content of phenolic acids remained unchanged independent of the milling process. The results of this study showed the potential of cryo-milling for complete raw material utilization in the food industry, as well as a tool for extraction of aimed bioactive components.

Keywords: bioactive, ball-mill, buckwheat, cryo-milling, pumpkin seed cake

Procedia PDF Downloads 115

Authors: Antonella Falanga, Armando Cartenì

Abstract:

Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

Procedia PDF Downloads 40

Authors: Prachi Buche Marathe

Abstract:

Karanja Laad is a city located in the Vidarbha region in the state of Maharashtra, India. It has a huge amount of tangible and intangible heritage in the form of monuments, precincts, a group of structures, festivals and procession route, which is neglected and lost with time. Three different religions Hinduism, Islam and Jainism along with associations of being a birthplace of Swami Nrusinha Saraswati, an exponent of Datta Sampradaya sect and the British colonial layer have shaped the culture and society of the place over the period. The architecture of the town Karanja Laad has enhanced its unique historic and cultural value with a combination of all these historic layers. Karanja Laad is also a traditional trading historic town with unique hybrid architectural style and has a good potential for developing as a tourist place along with the present image of a pilgrim destination of Datta Sampradaya. The aim of the research is to prepare a conservation proposal for the historic town along with the management framework. Objectives of the research are to study the evolution of Karanja town, to identify the cultural resources along with issues of the historic core of the city, to understand Datta sampradaya, and contribution of Saint Nrusinha Saraswati in the religious sect and his association as an important personality with Karanja. The methodology of the research is site visits to the Karanja city, making field surveys for documentation and discussions and questionnaires with the residents to establish heritage and identify potential and issues within the historic core thereby establishing a case for conservation. Field surveys are conducted for town level study of land use, open spaces, occupancy, ownership, traditional commodity and community, infrastructure, streetscapes, and precinct activities during the festival and non-festival period. Building level study includes establishing various typologies like residential, institutional commercial, religious, and traditional infrastructure from the mythological references like waterbodies (kund), lake and wells. One of the main issues is that the loss of the traditional footprint as well as the traditional open spaces which are getting lost due to the new illegal encroachments and lack of guidelines for the new additions to conserve the original fabric of the structures. Traditional commodities are getting lost since there is no promotion of these skills like pottery and painting. Lavish bungalows like Kannava mansion, main temple Wada (birthplace of the saint) have a huge potential to be developed as a museum by adaptive re-use which will, in turn, attract many visitors during festivals which will boost the economy. Festival procession routes can be identified and a heritage walk can be developed so as to highlight the traditional features of the town. Overall study has resulted in establishing a heritage map with 137 heritage structures identified as potential. Conservation proposal is worked out on the town level, precinct level and building level with interventions such as developing construction guidelines for further development and establishing a heritage cell consisting architects and engineers for the upliftment of the existing rich heritage of the Karanja city.

Keywords: built heritage, conservation, Datta Sampradaya, Karanja Laad, Swami Nrusinha Saraswati, procession route

Procedia PDF Downloads 133

Authors: Adriana Haulica

Abstract:

Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

Procedia PDF Downloads 49

Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

Abstract:

— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

Procedia PDF Downloads 168

Authors: Joel Niklaus, Matthias Sturmer

Abstract:

The publication of judicial proceedings is a cornerstone of many democracies. It enables the court system to be made accountable by ensuring that justice is made in accordance with the laws. Equally important is privacy, as a fundamental human right (Article 12 in the Declaration of Human Rights). Therefore, it is important that the parties (especially minors, victims, or witnesses) involved in these court decisions be anonymized securely. Today, the anonymization of court decisions in Switzerland is performed either manually or semi-automatically using primitive software. While much research has been conducted on anonymization for tabular data, the literature on anonymization for unstructured text documents is thin and virtually non-existent for court decisions. In 2019, it has been shown that manual anonymization is not secure enough. In 21 of 25 attempted Swiss federal court decisions related to pharmaceutical companies, pharmaceuticals, and legal parties involved could be manually re-identified. This was achieved by linking the decisions with external databases using regular expressions. An automated re-identification system serves as an automated test for the safety of existing anonymizations and thus promotes the right to privacy. Manual anonymization is very expensive (recurring annual costs of over CHF 20M in Switzerland alone, according to an estimation). Consequently, many Swiss courts only publish a fraction of their decisions. An automated anonymization system reduces these costs substantially, further leading to more capacity for publishing court decisions much more comprehensively. For the re-identification system, topic modeling with latent dirichlet allocation is used to cluster an amount of over 500K Swiss court decisions into meaningful related categories. A comprehensive knowledge base with publicly available data (such as social media, newspapers, government documents, geographical information systems, business registers, online address books, obituary portal, web archive, etc.) is constructed to serve as an information hub for re-identifications. For the actual re-identification, a general-purpose language model is fine-tuned on the respective part of the knowledge base for each category of court decisions separately. The input to the model is the court decision to be re-identified, and the output is a probability distribution over named entities constituting possible re-identifications. For the anonymization system, named entity recognition (NER) is used to recognize the tokens that need to be anonymized. Since the focus lies on Swiss court decisions in German, a corpus for Swiss legal texts will be built for training the NER model. The recognized named entities are replaced by the category determined by the NER model and an identifier to preserve context. This work is part of an ongoing research project conducted by an interdisciplinary research consortium. Both a legal analysis and the implementation of the proposed system design ESRA will be performed within the next three years. This study introduces the system design of ESRA, an end-to-end system for re-identification and anonymization of Swiss court decisions. Firstly, the re-identification system tests the safety of existing anonymizations and thus promotes privacy. Secondly, the anonymization system substantially reduces the costs of manual anonymization of court decisions and thus introduces a more comprehensive publication practice.

Keywords: artificial intelligence, courts, legal tech, named entity recognition, natural language processing, ·privacy, topic modeling

Procedia PDF Downloads 118

Authors: Miguel A. Figueroa, José A. Lara-Ramos, Miguel A. Mueses

Abstract:

Pharmaceutical residues are a section of emerging contaminants of anthropogenic origin that are present in a myriad of waters with which human beings interact daily and are starting to affect the ecosystem directly. Conventional waste-water treatment systems are not capable of degrading these pharmaceutical effluents because their designs cannot handle the intermediate products and biological effects occurring during its treatment. That is why it is necessary to hybridize conventional waste-water systems with non-conventional processes. In the specific case of an ozonation process, its efficiency highly depends on a perfect dispersion of ozone, long times of interaction of the gas-liquid phases and the size of the ozone bubbles formed through-out the reaction system. In order to increase the efficiency of these parameters, the use of a modified flotation cell has been proposed recently as a reactive system, which is used at an industrial level to facilitate the suspension of particles and spreading gas bubbles through the reactor volume at a high rate. The objective of the present work is the development of a mathematical model that can closely predict the kinetic rates of reactions taking place in the flotation cell at an experimental scale by means of identifying proper reaction mechanisms that take into account the modified chemical and hydrodynamic factors in the FeO-catalyzed Ozonation of Diclofenac aqueous solutions in a flotation cell. The methodology is comprised of three steps: an experimental phase where a modified flotation cell reactor is used to analyze the effects of ozone concentration and loading catalyst over the degradation of Diclofenac aqueous solutions. The performance is evaluated through an index of utilized ozone, which relates the amount of ozone supplied to the system per milligram of degraded pollutant. Next, a theoretical phase where the reaction mechanisms taking place during the experiments must be identified and proposed that details the multiple direct and indirect reactions the system goes through. Finally, a kinetic model is obtained that can mathematically represent the reaction mechanisms with adjustable parameters that can be fitted to the experimental results and give the model a proper physical meaning. The expected results are a robust reaction rate law that can simulate the improved results of Diclofenac mineralization on water using the modified flotation cell reactor. By means of this methodology, the following results were obtained: A robust reaction pathways mechanism showcasing the intermediates, free-radicals and products of the reaction, Optimal values of reaction rate constants that simulated Hatta numbers lower than 3 for the system modeled, degradation percentages of 100%, TOC (Total organic carbon) removal percentage of 69.9 only requiring an optimal value of FeO catalyst of 0.3 g/L. These results showed that a flotation cell could be used as a reactor in ozonation, catalytic ozonation and photocatalytic ozonation processes, since it produces high reaction rate constants and reduces mass transfer limitations (Ha > 3) by producing microbubbles and maintaining a good catalyst distribution.

Keywords: advanced oxidation technologies, iron oxide, emergent contaminants, AOTS intensification

Procedia PDF Downloads 87

Authors: Xiaoqing Peng, Aijing Luo, Yang Chen

Abstract:

Background: Cyberchondria, as an "emerging risk" accompanied by the information era, is a new abnormal pattern characterized by excessive or repeated online searches for health-related information and escalating health anxiety, which endangers people's physical and mental health and poses a huge threat to public health. Objective: To explore and discuss the research status, hotspots and trends of Cyberchondria. Methods: Based on a total of 77 articles regarding "Cyberchondria" extracted from Web of Science from the beginning till October 2019, the literature trends, countries, institutions, hotspots are analyzed by bibliometric analysis, the concept definition of Cyberchondria, instruments, relevant factors, treatment and intervention are discussed as well. Results: Since "Cyberchondria" was put forward for the first time in 2001, the last two decades witnessed a noticeable increase in the amount of literature, especially during 2014-2019, it quadrupled dramatically at 62 compared with that before 2014 only at 15, which shows that Cyberchondria has become a new theme and hot topic in recent years. The United States was the most active contributor with the largest publication (23), followed by England (11) and Australia (11), while the leading institutions were Baylor University(7) and University of Sydney(7), followed by Florida State University(4) and University of Manchester(4). The WoS categories "Psychiatry/Psychology " and "Computer/ Information Science "were the areas of greatest influence. The concept definition of Cyberchondria is not completely unified in the world, but it is generally considered as an abnormal behavioral pattern and emotional state and has been invoked to refer to the anxiety-amplifying effects of online health-related searches. The first and the most frequently cited scale for measuring the severity of Cyberchondria called “The Cyberchondria Severity Scale (CSS) ”was developed in 2014, which conceptualized Cyberchondria as a multidimensional construct consisting of compulsion, distress, excessiveness, reassurance, and mistrust of medical professionals which was proved to be not necessary for this construct later. Since then, the Brazilian, German, Turkish, Polish and Chinese versions were subsequently developed, improved and culturally adjusted, while CSS was optimized to a simplified version (CSS-12) in 2019, all of which should be worthy of further verification. The hotspots of Cyberchondria mainly focuses on relevant factors as follows: intolerance of uncertainty, anxiety sensitivity, obsessive-compulsive disorder, internet addition, abnormal illness behavior, Whiteley index, problematic internet use, trying to make clear the role played by “associated factors” and “anxiety-amplifying factors” in the development of Cyberchondria, to better understand the aetiological links and pathways in the relationships between hypochondriasis, health anxiety and online health-related searches. Although the treatment and intervention of Cyberchondria are still in the initial stage of exploration, there are kinds of meaningful attempts to seek effective strategies from different aspects such as online psychological treatment, network technology management, health information literacy improvement and public health service. Conclusion: Research on Cyberchondria is in its infancy but should be deserved more attention. A conceptual consensus on Cyberchondria, a refined assessment tool, prospective studies conducted in various populations, targeted treatments for it would be the main research direction in the near future.

Keywords: cyberchondria, hypochondriasis, health anxiety, online health-related searches

Procedia PDF Downloads 103