Search results for: loading units

Authors: Anand R. Nair, Markus Trenker

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Lifting body concepts were conceived as early as 1917 and patented by Roy Scroggs. It was an idea of using the fuselage as a lift producing body with no or small wings. Many of these designs were developed and even flight tested between 1920’s to 1970’s, but it was not pursued further for commercial flight as at lower airspeeds, such a configuration was incapable to produce sufficient lift for the entire aircraft. The concept presented in this contribution is combining the lifting body design along with a fixed wing to maximise the lift produced by the aircraft. Conventional aircraft fuselages are designed to be aerodynamically efficient, which is to minimise the drag; however, these fuselages produce very minimal or negligible lift. For the design of an unmanned fixed wing transport aircraft, many of the restrictions which are present for commercial aircraft in terms of fuselage design can be excluded, such as windows for the passengers/pilots, cabin-environment systems, emergency exits, and pressurization systems. This gives new flexibility to design fuselages which are unconventionally shaped to contribute to the lift of the aircraft. The two lifting body concepts presented in this contribution are targeting different applications: For a fast cargo delivery drone, the fuselage is based on a scaled airfoil shape with a cargo capacity of 500 kg for euro pallets. The aircraft has a span of 14 m and reaches 1500 km at a cruising speed of 90 m/s. The aircraft could also easily be adapted to accommodate pilot and passengers with modifications to the internal structures, but pressurization is not included as the service ceiling envisioned for this type of aircraft is limited to 10,000 ft. The next concept to be investigated is called a multi-purpose drone, which incorporates a different type of lifting body and is a much more versatile aircraft as it will have a VTOL capability. The aircraft will have a wingspan of approximately 6 m and flight speeds of 60 m/s within the same service ceiling as the fast cargo delivery drone. The multi-purpose drone can be easily adapted for various applications such as firefighting, agricultural purposes, surveillance, and even passenger transport. Lifting body designs are not a new concept, but their effectiveness in terms of cargo transportation has not been widely investigated. Due to their enhanced lift producing capability, lifting body designs enable the reduction of the wing area and the overall weight of the aircraft. This will, in turn, reduce the thrust requirement and ultimately the fuel consumption. The various designs proposed in this contribution will be based on the general aviation category of aircrafts and will be focussed on unmanned methods of operation. These unmanned fixed-wing transport drones will feature appropriate cargo loading/unloading concepts which can accommodate large size cargo for efficient time management and ease of operation. The various designs will be compared in performance to their conventional counterpart to understand their benefits/shortcomings in terms of design, performance, complexity, and ease of operation. The majority of the performance analysis will be carried out using industry relevant standards in computational fluid dynamics software packages.

Keywords: lifting body concept, computational fluid dynamics, unmanned fixed-wing aircraft, cargo drone

Procedia PDF Downloads 194

Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 358

Authors: Luvuno N. Jele, Warwick W. Hastie, Andrew Green

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Calcarenite is a clastic sedimentary beach rock composed of more than 50% sand sized (0.0625 – 2 mm) carbonate grains. In South Africa, these rocks occur as a narrow belt along most of the coast of KwaZulu-Natal and sporadically along the coast of the Eastern Cape. Calcarenites contain a high percentage of calcium carbonate, and due to a number of its physical and structural features, like porosity, cementing material, sedimentary structures, grain shape, and grain size; they are more prone to chemical and mechanical weathering. The objective of the research is to study the strength and compressibility characteristics of the calcarenites along the coast of KwaZulu-Natal to be able to better understand the geotechnical behaviour of these rocks, which may help to predict areas along the coast which may be potentially susceptible to failure/differential settling resulting in damage to property. A total of 148 cores were prepared and analyzed. Cores were analyzed perpendicular and parallel to bedding. Tests were carried out in accordance with the relevant codes and recommendations of the International Society for Rock Mechanics, American Standard Testing Methods, and Committee of Land and Transport Standard Specifications for Road and Bridge Works for State Road Authorities. Test carried out included: x-ray diffraction, petrography, shape preferred orientation (SPO), 3-D Tomography, rock porosity, rock permeability, ethylene glycol, slake durability, rock water absorption, Duncan swelling index, triaxial compressive strength, Brazilian tensile strength and uniaxial compression test with elastic modulus. The beach-rocks have a uniaxial compressive strength (UCS) ranging from 17,84Mpa to 287,35Mpa and exhibit three types of failure; (1) single sliding shear failure, (2) complete cone development, and (3) splitting failure. Brazilian tensile strength of the rocks ranges from 2.56 Mpa to 12,40 Ma, with those tested perpendicular to bedding showing lower tensile strength. Triaxial compressive tests indicate calcarenites have strength ranging from 86,10 Mpa to 371,85 Mpa. Common failure mode in the triaxial test is a single sliding shear failure. Porosity of the rocks varies from 1.25 % to 26.52 %. Rock tests indicate that the direction of loading, whether it be parallel to bedding or perpendicular to bedding, plays no significantrole in the strength and durability of the calcarenites. Porosity, cement type, and grain texture play major roles.UCS results indicate that saturated cores are weaker in strength compared to dry samples. Thus, water or moisture content plays a significant role in the strength and durability of the beach-rock. Loosely packed, highly porous and low magnesian-calcite bearing calcarenites show a decrease in strength compared to the densely packed, low porosity and high magnesian-calcite bearing calcarenites.

Keywords: beach-rock, calcarenite, cement, compressive, failure, porosity, strength, tensile, grains

Procedia PDF Downloads 72

Authors: Wei Chen

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3D concrete printing technology is a novel and highly efficient construction method that holds significant promise for advancing low-carbon initiatives within the construction industry. In contrast to traditional construction practices, 3D printing offers a manual and formwork-free approach, resulting in a transformative shift in labor requirements and fabrication techniques. This transition yields substantial reductions in carbon emissions during the construction phase, as well as decreased on-site waste generation. Furthermore, when compared to conventionally printed concrete, 3D concrete exhibits mechanical anisotropy due to its layer-by-layer construction methodology. Therefore, it becomes imperative to investigate the influence of the printing process on the mechanical properties of 3D printed strips and to optimize the mechanical characteristics of these coagulated strips. In this study, we conducted three-dimensional reconstructions of printed blocks using both circular and directional print heads, incorporating various overlap distances between strips, and employed CT scanning for comprehensive analysis. Our research focused on assessing mechanical properties and micro-pore characteristics under different loading orientations.Our findings reveal that increasing the overlap degree between strips leads to enhanced mechanical properties of the strips. However, it's noteworthy that once full overlap is achieved, further increases in the degree of coincidence do not lead to a decrease in porosity between strips. Additionally, due to its superior printing cross-sectional area, the square printing head exhibited the most favorable impact on mechanical properties.This paper aims to improve the tensile strength, tensile ductility, and bending toughness of a recently developed ‘one-part’ geopolymer for 3D concrete printing (3DCP) applications, in order to address the insufficient tensile strength and brittle fracture characteristics of geopolymer materials in 3D printing scenarios where materials are subjected to tensile stress. The effects of steel fiber content, and aspect ratio, on mechanical properties, were systematically discussed, including compressive strength, flexure strength, splitting tensile strength, uniaxial tensile strength, bending toughness, and the anisotropy of 3DP-OPGFRC, respectively. The fiber distribution in the printed samples was obtained through x-ray computed tomography (X-CT) testing. In addition, the underlying mechanisms were discussed to provide a deep understanding of the role steel fiber played in the reinforcement. The experimental results showed that the flexural strength increased by 282% to 26.1MP, and the compressive strength also reached 104.5Mpa. A high tensile ductility, appreciable bending toughness, and strain-hardening behavior can be achieved with steel fiber incorporation. In addition, it has an advantage over the OPC-based steel fiber-reinforced 3D printing materials given in the existing literature (flexural strength 15 Mpa); It is also superior to the tensile strength (<6Mpa) of current geopolymer fiber reinforcements used for 3D printing. It is anticipated that the development of this 3D printable steel fiber reinforced ‘one-part’ geopolymer will be used to meet high tensile strength requirements for printing scenarios.

Keywords: 3D printing concrete, mechanical anisotropy, micro-pore structure, printing technology

Procedia PDF Downloads 53

Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

Procedia PDF Downloads 186

Authors: Sabina Huč, Staffan Svensson, Tomaž Hozjan

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Timber structures may be exposed to various environmental conditions during their service life. Often, the structures have to resist extreme changes in the relative humidity of surrounding air, with simultaneously carrying the loads. Wood material response for this load case is seen as increasing deformation of the timber structure. Relative humidity variations cause moisture changes in timber and consequently shrinkage and swelling of the material. Moisture changes and loads acting together result in mechano-sorptive creep, while sustained load gives viscoelastic creep. In some cases, magnitude of the mechano-sorptive strain can be about five times the elastic strain already at low stress levels. Therefore, analyzing mechano-sorptive creep and its influence on timber structures’ long-term behavior is of high importance. Relatively many one-dimensional rheological models for rheological behavior of wood can be found in literature, while a number of models coupling creep response in each material direction is limited. In this study, mathematical formulation of a coupled two-dimensional mechano-sorptive model and its application to the experimental results are presented. The mechano-sorptive model constitutes of a moisture transport model and a mechanical model. Variation of the moisture content in wood is modelled by multi-Fickian moisture transport model. The model accounts for processes of the bound-water and water-vapor diffusion in wood, that are coupled through sorption hysteresis. Sorption defines a nonlinear relation between moisture content and relative humidity. Multi-Fickian moisture transport model is able to accurately predict unique, non-uniform moisture content field within the timber member over time. Calculated moisture content in timber members is used as an input to the mechanical analysis. In the mechanical analysis, the total strain is assumed to be a sum of the elastic strain, viscoelastic strain, mechano-sorptive strain, and strain due to shrinkage and swelling. Mechano-sorptive response is modelled by so-called spring-dashpot type of a model, that proved to be suitable for describing creep of wood. Mechano-sorptive strain is dependent on change of moisture content. The model includes mechano-sorptive material parameters that have to be calibrated to the experimental results. The calibration is made to the experiments carried out on wooden blocks subjected to uniaxial compressive loaded in tangential direction and varying humidity conditions. The moisture and the mechanical model are implemented in a finite element software. The calibration procedure gives the required, distinctive set of mechano-sorptive material parameters. The analysis shows that mechano-sorptive strain in transverse direction is present, though its magnitude and variation are substantially lower than the mechano-sorptive strain in the direction of loading. The presented mechano-sorptive model enables observing real temporal and spatial distribution of the moisture-induced strains and stresses in timber members. Since the model’s suitability for predicting mechano-sorptive strains is shown and the required material parameters are obtained, a comprehensive advanced analysis of the stress-strain state in timber structures, including connections subjected to constant load and varying humidity is possible.

Keywords: mechanical analysis, mechano-sorptive creep, moisture transport model, timber

Procedia PDF Downloads 220

Authors: Virgilio Angelo Gelera Gener

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This study investigates the role of short-term accommodations on the place brand and real estate development of urban areas. It aims to know the perceptions of the general public, real estate developers, as well as city and barangay-level local government units (LGUs) on how these lodgings affect the place brand and land value of a community. It likewise attempts to identify the personal and institutional variables having a great influence on said perceptions in order to provide a better understanding of these establishments and their relevance within urban localities. Using certain sources, Malate, Manila was identified to be the ideal study area of the thesis. This prompted the employment of mixed methods research as the study’s fundamental data gathering and analytical tool. Here, a survey with 350 locals was done, asking them questions that would answer the aforementioned queries. Thereafter, a Pearson Chi-square Test and Multinomial Logistic Regression (MLR) were utilized to determine the variables affecting their perceptions. There were also Focus Group Discussions (FGDs) with the three (3) most populated Malate barangays, as well as Key Informant Interviews (KIIs) with selected city officials and fifteen (15) real estate company representatives. With that, survey results showed that although a 1992 Department of Tourism (DOT) Circular regards short-term accommodations as lodgings mainly for travelers, most people actually use it for their private/intimate moments. Because of this, the survey further revealed that short-term accommodations exhibit a negative place brand among the respondents though they also believe that it’s still one of society’s most important economic players. Statistics from the Pearson Chi-square Test, on the other hand, indicate that there are fourteen (14) out of seventeen (17) variables exhibiting great influence on respondents’ perceptions. Whereas MLR findings show that being born in Malate and being part of a family household was the most significant regardless of socio-economic level and monthly household income. For the city officials, it was revealed that said lodgings are actually the second-highest earners in the City’s lodging industry. It was further stated that their zoning ordinance treats short-term accommodations just like any other lodging enterprise. So it’s perfectly legal for these establishments to situate themselves near residential areas and/or institutional structures. A sit down with barangays, on the other hand, recognized the economic benefits of short-term accommodations but likewise admitted that it contributes a negative place brand to the community. Lastly, real estate developers are amenable to having their projects built near short-term accommodations, for they do not have any bad views against it. They explained that their projects sites have always been motivated by suitability, liability, and marketability factors only. Overall, these findings merit a recalibration of the zoning ordinance and DOT Circular, as well as the imposition of regulations on their sexually suggestive roadside advertisements. Then, once relevant measures are refined for proper implementation, it can also pave the way for spatial interventions (like visual buffer corridors) to better address the needs of the locals, private groups, and government.

Keywords: estate planning, place brand, real estate development, short-term accommodations

Procedia PDF Downloads 137

Authors: Ernest Moles, Patricia Urbán, María Belén Jiménez-Díaz, Sara Viera-Morilla, Iñigo Angulo-Barturen, Maria Antònia Busquets, Xavier Fernàndez-Busquets

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Bearing in mind the absence of an effective vaccine against malaria and its severe clinical manifestations causing nearly half a million deaths every year, this disease represents nowadays a major threat to life. Besides, the basic rationale followed by currently marketed antimalarial approaches is based on the administration of drugs on their own, promoting the emergence of drug-resistant parasites owing to the limitation in delivering drug payloads into the parasitized erythrocyte high enough to kill the intracellular pathogen while minimizing the risk of causing toxic side effects to the patient. Such dichotomy has been successfully addressed through the specific delivery of immunoliposome (iLP)-encapsulated antimalarials to Plasmodium falciparum-infected red blood cells (pRBCs). Unfortunately, this strategy has not progressed towards clinical applications, whereas in vitro assays rarely reach drug efficacy improvements above 10-fold. Here, we show that encapsulation efficiencies reaching >96% can be achieved for the weakly basic drugs chloroquine (CQ) and primaquine using the pH gradient active loading method in liposomes composed of neutrally charged, saturated phospholipids. Targeting antibodies are best conjugated through their primary amino groups, adjusting chemical crosslinker concentration to retain significant antigen recognition. Antigens from non-parasitized RBCs have also been considered as targets for the intracellular delivery of drugs not affecting the erythrocytic metabolism. Using this strategy, we have obtained unprecedented nanocarrier targeting to early intraerythrocytic stages of the malaria parasite for which there is a lack of specific extracellular molecular tags. Polyethylene glycol-coated liposomes conjugated with monoclonal antibodies specific for the erythrocyte surface protein glycophorin A (anti-GPA iLP) were capable of targeting 100% RBCs and pRBCs at the low concentration of 0.5 μM total lipid in the culture, with >95% of added iLPs retained into the cells. When exposed for only 15 min to P. falciparum in vitro cultures synchronized at early stages, free CQ had no significant effect over parasite viability up to 200 nM drug, whereas iLP-encapsulated 50 nM CQ completely arrested its growth. Furthermore, when assayed in vivo in P. falciparum-infected humanized mice, anti-GPA iLPs cleared the pathogen below detectable levels at a CQ dose of 0.5 mg/kg. In comparison, free CQ administered at 1.75 mg/kg was, at most, 40-fold less efficient. Our data suggest that this significant improvement in drug antimalarial efficacy is in part due to a prophylactic effect of CQ found by the pathogen in its host cell right at the very moment of invasion.

Keywords: immunoliposomal nanoparticles, malaria, prophylactic-therapeutic polyvalent activity, targeted drug delivery

Procedia PDF Downloads 347

Authors: Carlos E. Rodríguez-Rodríguez, Karla Ruiz-Hidalgo, Kattia Madrigal-Zúñiga, Juan Salvador Chin-Pampillo, Mario Masís-Mora, Elizabeth Carazo-Rojas

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One of the main causes of contamination linked to agricultural activities is the spillage and disposal of pesticides, especially during the loading, mixing or cleaning of agricultural spraying equipment. One improvement in the handling of pesticides is the use of biopurification systems (BPS), simple and cheap degradation devices where the pesticides are biologically degraded at accelerated rates. The biologically active core of BPS is the biomixture, which is constituted by soil pre-exposed to the target pesticide, a lignocellulosic substrate to promote the activity of ligninolitic fungi and a humic component (peat or compost), mixed at a volumetric proportion of 50:25:25. Considering the known ability of lignocellulosic fungi to degrade a wide range of organic pollutants, and the high amount of lignocellulosic waste used in biomixture preparation, the bioaugmentation of biomixtures with these fungi represents an interesting approach for improving biomixtures. The present work aimed at evaluating the effect of the bioaugmentation of rice husk based biomixtures with the fungus Trametes versicolor in the removal of the insectice/nematicide carbofuran (CFN) and to optimize the composition of the biomixture to obtain the best performance in terms of CFN removal and mineralization, reduction in formation of transformation products and decrease in residual toxicity of the matrix. The evaluation of several lignocellulosic residues (rice husk, wood chips, coconut fiber, sugarcane bagasse or newspaper print) revealed the best colonization by T. versicolor in rice husk. Pre-colonized rice husk was then used in the bioaugmentation of biomixtures also containing soil pre-exposed to CFN and either peat (GTS biomixture) or compost (GCS biomixture). After spiking with 10 mg/kg CBF, the efficiency of the biomixture was evaluated through a multi-component approach that included: monitoring of CBF removal and production of CBF transformation products, mineralization of radioisotopically labeled carbofuran (14C-CBF) and changes in the toxicity of the matrix after the treatment (Daphnia magna acute immobilization test). Estimated half-lives of CBF in the biomixtures were 3.4 d and 8.1 d in GTS and GCS, respectively. The transformation products 3-hydroxycarbofuran and 3-ketocarbofuran were detected at the moment of CFN application, however their concentration continuously disappeared. Mineralization of 14C-CFN was also faster in GTS than GCS. The toxicological evaluation showed a complete toxicity removal in the biomixtures after 48 d of treatment. The composition of the GCS biomixture was optimized using a central composite design and response surface methodology. The design variables were the volumetric content of fungally pre-colonized rice husk and the volumetric ratio compost/soil. According to the response models, maximization of CFN removal and mineralization rate, and minimization in the accumulation of transformation products were obtained with an optimized biomixture of composition 30:43:27 (pre-colonized rice husk:compost:soil), which differs from the 50:25:25 composition commonly employed in BPS. Results suggest that fungal bioaugmentation may enhance the performance of biomixtures in CFN removal. Optimization reveals the importance of assessing new biomixture formulations in order to maximize their performance.

Keywords: bioaugmentation, biopurification systems, degradation, fungi, pesticides, toxicity

Procedia PDF Downloads 287

Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

Procedia PDF Downloads 144

Authors: T. Heiman, D. Olenik-Shemesh

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Over the past decade, with the rapid growth of electronic communication, the internet and, in particular, social networking has become an inseparable part of people's daily lives. Along with its benefits, a new type of online aggression has emerged, defined as cyber bullying, a form of interpersonal aggressive behavior that takes place through electronic means. Cyber-bullying is characterized by repetitive behavior over time of maladaptive authority and power usage using computers and cell phones via sending insulting messages and hurtful pictures. Preliminary findings suggest that the prevalence of involvement in cyber-bullying among higher education students varies between 10 and 35%. As to date, universities are facing an uphill effort in trying to restrain online misbehavior. As no studies examined the relationships between cyber-bullying involvement with personal aspects, and its impacts on academic achievement and work functioning, this present study examined the nature of cyber-bullying involvement among 1,052 undergraduate students (mean age = 27.25, S.D = 4.81; 66.2% female), coping with, as well as the effects of social support, perceived self-efficacy, well-being, and body-perception, in relation to cyber-victimization. We assume that students in higher education are a vulnerable population and at high risk of being cyber-victims. We hypothesize that social support might serve as a protective factor and will moderate the relationships between the socio-emotional variables and the occurrence of cyber- victimization. The findings of this study will present the relationships between cyber-victimization and the social-emotional aspects, which constitute risk and protective factors. After receiving approval from the Ethics Committee of the University, a Google Drive questionnaire was sent to a random sample of students, studying in the various University study centers. Students' participation was voluntary, and they completed the five questionnaires anonymously: Cyber-bullying, perceived self-efficacy, subjective well-being, social support and body perception. Results revealed that 11.6% of the students reported being cyber-victims during last year. Examining the emotional and behavioral reactions to cyber-victimization revealed that female emotional and behavioral reactions were significantly greater than the male reactions (p < .001). Moreover, females reported on a significant higher social support compared to men; male reported significantly on a lower social capability than female; and men's body perception was significantly more positive than women's scores. No gender differences were observed for subjective well-being scale. Significant positive correlations were found between cyber-victimization and fewer friends, lower grades, and work ineffectiveness (r = 0.37- .40, p < 0 .001). The results of the Hierarchical regression indicated significantly that cyber-victimization can be predicted by lower social support, lower body perception, and gender (female), that explained 5.6% of the variance (R2 = 0.056, F(5,1047) = 12.47, p < 0.001). The findings deepen our understanding of the students' involvement in cyber-bullying, and present the relationships of the social-emotional and academic aspects on cyber-victim students. In view of our findings, higher education policy could help facilitate coping with cyber-bullying incidents, and student support units could develop intervention programs aimed at reducing cyber-bullying and its impacts.

Keywords: academic and personal factors, cyber-victimization, social support, higher education

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Authors: Shanaka Gunasekara, Maleen Jayasuriya, Nalin Harischandra, Lilantha Samaranayake, Gamini Dissanayake

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One serious facet of the worsening Human-Elephant conflict (HEC) in nations such as Sri Lanka involves elephant-train collisions. Endangered Asian elephants are maimed or killed during such accidents, which also often result in orphaned or disabled elephants, contributing to the phenomenon of lone elephants. These lone elephants are found to be more likely to attack villages and showcase aggressive behaviour, which further exacerbates the overall HEC. Furthermore, Railway Services incur significant financial losses and disruptions to services annually due to such accidents. Most elephant-train collisions occur due to a lack of adequate reaction time. This is due to the significant stopping distance requirements of trains, as the full braking force needs to be avoided to minimise the risk of derailment. Thus, poor driver visibility at sharp turns, nighttime operation, and poor weather conditions are often contributing factors to this problem. Initial investigations also indicate that most collisions occur in localised “hotspots” where elephant pathways/corridors intersect with railway tracks that border grazing land and watering holes. Taking these factors into consideration, this work proposes the leveraging of recent developments in Convolutional Neural Network (CNN) technology to detect elephants using an RGB/infrared capable camera around known hotspots along the railway track. The CNN was trained using a curated dataset of elephants collected on field visits to elephant sanctuaries and wildlife parks in Sri Lanka. With this vision-based detection system at its core, a prototype unit of an early warning system was designed and tested. This weatherised and waterproofed unit consists of a Reolink security camera which provides a wide field of view and range, an Nvidia Jetson Xavier computing unit, a rechargeable battery, and a solar panel for self-sufficient functioning. The prototype unit was designed to be a low-cost, low-power and small footprint device that can be mounted on infrastructures such as poles or trees. If an elephant is detected, an early warning message is communicated to the train driver using the GSM network. A mobile app for this purpose was also designed to ensure that the warning is clearly communicated. A centralized control station manages and communicates all information through the train station network to ensure coordination among important stakeholders. Initial results indicate that detection accuracy is sufficient under varying lighting situations, provided comprehensive training datasets that represent a wide range of challenging conditions are available. The overall hardware prototype was shown to be robust and reliable. We envision a network of such units may help contribute to reducing the problem of elephant-train collisions and has the potential to act as an important surveillance mechanism in dealing with the broader issue of human-elephant conflicts.

Keywords: computer vision, deep learning, human-elephant conflict, wildlife early warning technology

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Authors: Z. Nurzaireena, K. Azalea, T. Azirawaty, S. Jameela, G. Muralitharan

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The aim of this study is the review of the management practices of sickle cell disease patients during pregnancy, as well as the maternal and neonatal outcome at Ampang Hospital, Selangor. The study consisted of a review of pregnant patients with sickle cell disease under follow up at the Hematology Clinic, Ampang Hospital over the last seven years to assess their management and maternal-fetal outcome. The results of the review show that Ampang Hospital is considered the public hematology centre for sickle cell disease and had successfully managed three pregnancies throughout the last seven years. Patients’ presentations, managements and maternal-fetal outcome were compared and reviewed for academic improvements. All three patients were seen very early in their pregnancy and had been given a regime of folic acid, antibiotics and thrombo-prophylactic drugs. Close monitoring of maternal and fetal well being was done by the hematologists and obstetricians. Among the patients, there were multiple admissions during the pregnancy for either a painful sickle cell bone crisis, haemolysis following an infection and anemia requiring phenotype- matched blood and exchange transfusions. Broad spectrum antibiotics coverage during and infection, hydration, pain management and venous-thrombolism prophylaxis were mandatory. The pregnancies managed to reach near term in the third trimester but all required emergency caesarean section for obstetric indications. All pregnancies resulted in live births with good fetal outcome. During post partum all were nursed closely in the high dependency units for further complications and were discharged well. Post partum follow up and contraception counseling was comprehensively given for future pregnancies. Sickle cell disease is uncommonly seen in the East, especially in the South East Asian region, yet more cases are seen in the current decade due to improved medical expertise and advance medical laboratory technologies. Pregnancy itself is a risk factor for sickle cell patients as increased thrombosis event and risk of infections can lead to multiple crisis, haemolysis, anemia and vaso-occlusive complications including eclampsia, cerebrovasular accidents and acute bone pain. Patients mostly require multiple blood product transfusions thus phenotype-matched blood is required to reduce the risk of alloimmunozation. Emphasizing the risks and complications in preconception counseling and establishing an ultimate pregnancy plan would probably reduce the risk of morbidity and mortality to the mother and unborn child. Early management for risk of infection, thromboembolic events and adequate hydration is mandatory. A holistic approach involving multidisciplinary team care between the hematologist, obstetricians, anesthetist, neonatologist and close nursing care for both mother and baby would ensure the best outcome. In conclusion, sickle cell disease by itself is a high risk medical condition and pregnancy would further amplify the risk. Thus, close monitoring with combine multidisciplinary care, counseling and educating the patients are crucial in achieving the safe outcome.

Keywords: anaemia, haemoglobinopathies, pregnancy, sickle cell disease

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Authors: Miroslaw Wendeker, Piotr Kacejko, Mariusz Duk, Pawel Karpinski

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The research in the field of aircraft internal combustion engines is currently driven by the needs of decreasing fuel consumption and CO2 emissions, while fulfilling the level of safety. Currently, reciprocating aircraft engines are found in sports, emergency, agricultural and recreation aviation. Technically, they are most at a pre-war knowledge of the theory of operation, design and manufacturing technology, especially if compared to that high level of development of automotive engines. Typically, these engines are driven by carburetors of a quite primitive construction. At present, due to environmental requirements and dealing with a climate change, it is beneficial to develop aircraft piston engines and adopt the achievements of automotive engineering such as computer-controlled low-pressure injection, electronic ignition control and biofuels. The paper describes simulation research of the innovative power and control systems for the aircraft radial engine of high power. Installing an electronic ignition system in the radial aircraft engine is a fundamental innovative idea of this solution. Consequently, the required level of safety and better functionality as compared to the today’s plug system can be guaranteed. In this framework, this research work focuses on describing a methodology for optimizing the electronically controlled ignition system. This attempt can reduce emissions of toxic compounds as a result of lowered fuel consumption, optimized combustion and engine capability of efficient combustion of ecological fuels. New, redundant elements of the control system can improve the safety of aircraft. Consequently, the required level of safety and better functionality as compared to the today’s plug system can be guaranteed. The simulation research aimed to determine the vulnerability of the values measured (they were planned as the quantities measured by the measurement systems) to determining the optimal ignition angle (the angle of maximum torque at a given operating point). The described results covered: a) research in steady states; b) velocity ranging from 1500 to 2200 rpm (every 100 rpm); c) loading ranging from propeller power to maximum power; d) altitude ranging according to the International Standard Atmosphere from 0 to 8000 m (every 1000 m); e) fuel: automotive gasoline ES95. The three models of different types of ignition coil (different energy discharge) were studied. The analysis aimed at the optimization of the design of the innovative ignition system for an aircraft engine. The optimization involved: a) the optimization of the measurement systems; b) the optimization of actuator systems. The studies enabled the research on the vulnerability of the signals to the control of the ignition timing. Accordingly, the number and type of sensors were determined for the ignition system to achieve its optimal performance. The results confirmed the limited benefits, in terms of fuel consumption. Thus, including spark management in the optimization is mandatory to significantly decrease the fuel consumption. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: piston engine, radial engine, ignition system, CFD model, engine optimization

Procedia PDF Downloads 361

Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Alex B. Cusick

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The objective of this study is to improve upon the current ²³⁸PuO₂ fuel technology for space and defense applications. Modern RTGs (radioisotope thermoelectric generators) utilize the heat generated from the radioactive decay of ²³⁸Pu to create heat and electricity for long term and remote missions. Application of RTG technology is limited by the scarcity and expense of producing the isotope, as well as the power output which is limited to only a few hundred watts. The scarcity and expense make the efficient use of ²³⁸Pu absolutely necessary. By utilizing the decay of ²³⁸Pu, not only to produce heat directly but to also indirectly induce fission in ²³⁹Pu (which is already present within currently used fuel), it is possible to see large increases in temperature which allows for a more efficient conversion to electricity and a higher power-to-weight ratio. This concept can reduce the quantity of ²³⁸Pu necessary for these missions, potentially saving millions on investment, while yielding higher power output. Current work investigating radioisotope power systems have focused on improving efficiency of the thermoelectric components and replacing systems which produce heat by virtue of natural decay with fission reactors. The technical feasibility of utilizing (α,n) reactions to induce fission within current radioisotopic fuels has not been investigated in any appreciable detail, and our study aims to thoroughly investigate the performance of many such designs, develop those with highest capabilities, and facilitate experimental testing of these designs. In order to determine the specific design parameters that maximize power output and the efficient use of ²³⁸Pu for future RTG units, MCNP6 simulations have been used to characterize the effects of modifying fuel composition, geometry, and porosity, as well as introducing neutron moderating, reflecting, and shielding materials to the system. Although this project is currently in the preliminary stages, the final deliverables will include sophisticated designs and simulation models that define all characteristics of multiple novel RTG fuels, detailed enough to allow immediate fabrication and testing. Preliminary work has consisted of developing a benchmark model to accurately represent the ²³⁸PuO₂ pellets currently in use by NASA; this model utilizes the alpha transport capabilities of MCNP6 and agrees well with experimental data. In addition, several models have been developed by varying specific parameters to investigate their effect on (α,n) and (n,fi ssion) reaction rates. Current practices in fuel processing are to exchange out the small portion of naturally occurring ¹⁸O and ¹⁷O to limit (α,n) reactions and avoid unnecessary neutron production. However, we have shown that enriching the oxide in ¹⁸O introduces a sufficient (α,n) reaction rate to support significant fission rates. For example, subcritical fission rates above 10⁸ f/cm³-s are easily achievable in cylindrical ²³⁸PuO₂ fuel pellets with a ¹⁸O enrichment of 100%, given an increase in size and a ⁹Be clad. Many viable designs exist and our intent is to discuss current results and future endeavors on this project.

Keywords: radioisotope thermoelectric generators (RTG), Pu-238, subcritical reactors, (alpha, n) reactions

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Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

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The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

Procedia PDF Downloads 137

Authors: Atin Adhikari, Sushma Kurella, Pratik Banerjee, Nabanita Mukherjee, Yamini M. Chandana Gollapudi, Bushra Shah

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Different sharp instruments, drilling machines, and high speed rotary instruments are routinely used in dental clinics during dental cleaning. Therefore, these cleaning procedures release a lot of oral microorganisms including bacteria in clinic air and may cause significant occupational bioaerosol exposure risks for dentists, dental hygienists, patients, and dental clinic employees. Two major goals of this study were to quantify volumetric airborne concentrations of bacteria and to assess overall microbial activity in this type of occupational environment. The study was conducted in several dental clinics of southern Georgia and 15 dental cleaning procedures were targeted for sampling of airborne bacteria and testing of overall microbial activity in settled dusts over clinic floors. For air sampling, a Biostage viable cascade impactor was utilized, which comprises an inlet cone, precision-drilled 400-hole impactor stage, and a base that holds an agar plate (Tryptic soy agar). A high-flow Quick-Take-30 pump connected to this impactor pulls microorganisms in air at 28.3 L/min flow rate through the holes (jets) where they are collected on the agar surface for approx. five minutes. After sampling, agar plates containing the samples were placed in an ice chest with blue ice and plates were incubated at 30±2°C for 24 to 72 h. Colonies were counted and converted to airborne concentrations (CFU/m3) followed by positive hole corrections. Most abundant bacterial colonies (selected by visual screening) were identified by PCR amplicon sequencing of 16S rRNA genes. For understanding overall microbial activity in clinic floors and estimating a general cleanliness of the clinic surfaces during or after dental cleaning procedures, ATP levels were determined in swabbed dust samples collected from 10 cm2 floor surfaces. Concentration of ATP may indicate both the cell viability and the metabolic status of settled microorganisms in this situation. An ATP measuring kit was used, which utilized standard luciferin-luciferase fluorescence reaction and a luminometer, which quantified ATP levels as relative light units (RLU). Three air and dust samples were collected during each cleaning procedure (at the beginning, during cleaning, and immediately after the procedure was completed (n = 45). Concentrations at the beginning, during, and after dental cleaning procedures were 671±525, 917±1203, and 899±823 CFU/m3, respectively for airborne bacteria and 91±101, 243±129, and 139±77 RLU/sample, respectively for ATP levels. The concentrations of bacteria were significantly higher than typical indoor residential environments. Although an increasing trend for airborne bacteria was observed during cleaning, the data collected at three different time points were not significantly different (ANOVA: p = 0.38) probably due to high standard deviations of data. The ATP levels, however, demonstrated a significant difference (ANOVA: p <0.05) in this scenario indicating significant change in microbial activity on floor surfaces during dental cleaning. The most common bacterial genera identified were: Neisseria sp., Streptococcus sp., Chryseobacterium sp., Paenisporosarcina sp., and Vibrio sp. in terms of frequencies of occurrences, respectively. The study concluded that bacterial exposure in dental clinics could be a notable occupational biohazard, and appropriate respiratory protections for the employees are urgently needed.

Keywords: bioaerosols, hospital hygiene, indoor air quality, occupational biohazards

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Authors: Meiling Yu, Nadia Rouatbi, Khuloud T. Al-Jamal

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Background: Treatment of neurological disorders with modern medical and surgical approaches remains difficult. Gene therapy, allowing the delivery of genetic materials that encodes potential therapeutic molecules, represents an attractive option. The treatment of brain diseases with gene therapy requires the gene-editing tool to be delivered efficiently to the central nervous system. In this study, we explored the efficiency of different delivery routes, namely intravenous (i.v.), intra-cranial (i.c.), and intra-nasal (i.n.), to deliver stable nucleic acid-lipid particles (SNALPs) containing gene-editing tools namely Cas9 mRNA and sgRNA encoding for GFP as a reporter protein. We hypothesise that SNALPs can reach the brain and perform gene-editing to different extents depending on the administration route. Intranasal administration (i.n.) offers an attractive and non-invasive way to access the brain circumventing the blood–brain barrier. Successful delivery of gene-editing tools to the brain offers a great opportunity for therapeutic target validation and nucleic acids therapeutics delivery to improve treatment options for a range of neurodegenerative diseases. In this study, we utilised Rosa26-Cas9 knock-in mice, expressing GFP, to study brain distribution and gene-editing efficiency of SNALPs after i.v.; i.c. and i.n. routes of administration. Methods: Single guide RNA (sgRNA) against GFP has been designed and validated by in vitro nuclease assay. SNALPs were formulated and characterised using dynamic light scattering. The encapsulation efficiency of nucleic acids (NA) was measured by RiboGreen™ assay. SNALPs were incubated in serum to assess their ability to protect NA from degradation. Rosa26-Cas9 knock-in mice were i.v., i.n., or i.c. administered with SNALPs to test in vivo gene-editing (GFP knockout) efficiency. SNALPs were given as three doses of 0.64 mg/kg sgGFP following i.v. and i.n. or a single dose of 0.25 mg/kg sgGFP following i.c.. knockout efficiency was assessed after seven days using Sanger Sequencing and Inference of CRISPR Edits (ICE) analysis. In vivo, the biodistribution of DiR labelled SNALPs (SNALPs-DiR) was assessed at 24h post-administration using IVIS Lumina Series III. Results: Serum-stable SNALPs produced were 130-140 nm in diameter with ~90% nucleic acid loading efficiency. SNALPs could reach and stay in the brain for up to 24h following i.v.; i.n. and i.c. administration. Decreasing GFP expression (around 50% after i.v. and i.c. and 20% following i.n.) was confirmed by optical imaging. Despite the small number of mice used, ICE analysis confirmed GFP knockout in mice brains. Additional studies are currently taking place to increase mice numbers. Conclusion: Results confirmed efficient gene knockout achieved by SNALPs in Rosa26-Cas9 knock-in mice expressing GFP following different routes of administrations in the following order i.v.= i.c.> i.n. Each of the administration routes has its pros and cons. The next stages of the project involve assessing gene-editing efficiency in wild-type mice and replacing GFP as a model target with therapeutic target genes implicated in Motor Neuron Disease pathology.

Keywords: CRISPR, nanoparticles, brain diseases, administration routes

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Authors: Alireza Barari, Saeed Shirali, Ahmad Abdi

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Abstract: Introduction: Physical activity may be related to male reproductive function by affecting on thehypothalamic-pituitary-gonadal(HPG) axis. Our aim was to determine the effects of 6 weeks resistance exercise on reproductive hormones, HPG axis. The hypothalamic-pituitary-gonadal (HPG) axis refers tothe effects of endocrine glands in three-level including (i) the hypothalamic releasing hormone GnRH, which is synthesized in in a small heterogenous neuronal population and released in a pulsatile fashion, (ii) the anterior pituitary hormones, follicle-stimulating hormone(FSH) and luteinizing hormone (LH) and (iii) the gonadal hormones, which include both steroid such as testosterone (T), estradiol and progesterone and peptide hormones (such as inhibin). Hormonal changes that create a more anabolic environment have been suggested to contribute to the adaptation to strength exercise. Physical activity has an extensive impact on male reproductive function depending upon the intensity and duration of the exercise and the fitness level of the individual. However, strenuous exercise represents a physical stress and inflammation changed that challenges homeostasis. Materials and methods: Sixteen male volunteered were included in a 6-week control period followed by 6 weeks of resistance training (leg press, lat pull, chest press, squat, seatedrow, abdominal crunch, shoulder press, biceps curl and triceps press down) four times per week. intensity of training loading was 60%-75% of one maximum repetition. Participants performed 3 sets of 10 repetitions. Rest periods were two min between exercises and sets. Start with warm up exercises include: The muscles relax and stretch the body, which was for 10 minutes. Body composition, VO2max and the circulating level of free testosterone (fT), luteinizing hormone (LH), follicle-stimulating hormone (FSH), sex hormone binding globulin (SHBG) and inhibin B measured prior and post 6-week intervention. The hormonal levels of each serum sample were measured using commercially available ELISA kits. Analysis of anthropometrical data and hormonal level were compared using the independent samples t- test in both groups and using SPSS (version 19). P ≤ 0.05 was considered statistically significant. Results: For muscle strength, both lower- and upper-body strength were increased significantly. Aerobic fitness level improved in trained participant from 39.4 ± 5.6 to 41.9 ± 5.3 (P = 0.002). fT concentration rise progressively in the trained group and was significantly greater than those in the control group (P = 0.000). By the end of the 6-week resistance training, serum SHBG significantly increased in the trained group compared with the control group (P = 0.013). In response to resistance training, LH, FSH and inhibin B were not significantly changed. Discussion: According to our finfings, 6 weeks of resistance training induce fat loss without any changes in body weight and BMI. A decline of 25.3% in percentage of body fat with statiscally same weight was due to increase in muscle mass that happened during resistance exercise periods . Six weeks of resistance training resulted in significant improvement in BF%, VO2max and increasing strength and the level of fT and SHBG.

Keywords: resistance, hypothalamic, pituitary, gonadal axis

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Authors: Kimberley Adamek

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According to the Council on Tall Buildings, there has been a rapid increase in the construction of tall or “megatall” buildings over the past two decades. Simultaneously, the New England Journal of Medicine has reported that there has been a steady increase in climate related natural disasters since the 1970s; the eastern expansion of the USA's infamous Tornado Alley being just one of many current issues. In the future, this could mean that tall buildings, which already guide high speed winds down to pedestrian levels would have to withstand stronger forces and protect pedestrians in more extreme ways. Although many projects are required to be verified within wind tunnels and a handful of cities such as San Francisco have included wind testing within building code standards, there are still many examples where wind is only considered for basic loading. This typically results in and an increase of structural expense and unwanted mitigation strategies that are proposed late within a project. When building cities, architects rarely consider how each building alters the invisible patterns of wind and how these alterations effect other areas in different ways later on. It is not until these forces move, overpower and even destroy cities that people take notice. For example, towers have caused winds to blow objects into people (Walkie-Talkie Tower, Leeds, England), cause building parts to vibrate and produce loud humming noises (Beetham Tower, Manchester), caused wind tunnels in streets as well as many other issues. Alternatively, there exist towers which have used their form to naturally draw in air and ventilate entire facilities in order to eliminate the needs for costly HVAC systems (The Met, Thailand) and used their form to increase wind speeds to generate electricity (Bahrain Tower, Dubai). Wind and weather exist and effect all parts of the world in ways such as: Science, health, war, infrastructure, catastrophes, tourism, shopping, media and materials. Working in partnership with a leading wind engineering company RWDI, a series of tests, images and animations documenting discovered interactions of different building forms with wind will be collected to emphasize the possibilities for wind use to architects. A site within San Francisco (due to its increasing tower development, consistently wind conditions and existing strict wind comfort criteria) will host a final design. Iterations of this design will be tested within the wind tunnel and computational fluid dynamic systems which will expose, utilize and manipulate wind flows to create new forms, technologies and experiences. Ultimately, this thesis aims to question the amount which the environment is allowed to permeate building enclosures, uncover new programmatic possibilities for wind in buildings, and push the boundaries of working with the wind to ensure the development and safety of future cities. This investigation will improve and expand upon the traditional understanding of wind in order to give architects, wind engineers as well as the general public the ability to broaden their scope in order to productively utilize this living phenomenon that everyone constantly feels but cannot see.

Keywords: wind engineering, climate, visualization, architectural aerodynamics

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Authors: Fatna Benmessaoud, Mohammed Cheikh, Vencent Velay, Vanessa Vedal, Farhad Rezai-Aria, Christine Boher

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The global mechanical behavior of materials is strongly linked to their microstructure, especially their crystallographic texture and their grains morphology. These material aspects determine the mechanical fields character (heterogeneous or homogeneous), thus, they give to the global behavior a degree of anisotropy according the initial microstructure. For these reasons, the prediction of global behavior of materials in relationship with the microstructure must be performed with a multi-scale approach. Therefore, multi-scale modeling in the context of crystal plasticity is widely used. In this present contribution, a phenomenological elasto-viscoplastic model developed in the crystal plasticity context and finite element method are used to investigate the effects of crystallographic texture and grains sizes on global behavior of a polycrystalline equiaxed Ti-6Al-4V alloy. The constitutive equations of this model are written on local scale for each slip system within each grain while the strain and stress mechanical fields are investigated at the global scale via finite element scale transition. The beta phase of Ti-6Al-4V alloy modeled is negligible; its percent is less than 10%. Three families of slip systems of alpha phase are considered: basal and prismatic families with a burgers vector and pyramidal family with a burgers vector. The twinning mechanism of plastic strain is not observed in Ti-6Al-4V, therefore, it is not considered in the present modeling. Nine representative elementary volumes (REV) are generated with Voronoi tessellations. For each individual equiaxed grain, the own crystallographic orientation vis-à-vis the loading is taken into account. The meshing strategy is optimized in a way to eliminate the meshing effects and at the same time to allow calculating the individual grain size. The stress and strain fields are determined in each Gauss point of the mesh element. A post-treatment is used to calculate the local behavior (in each grain) and then by appropriate homogenization, the macroscopic behavior is calculated. The developed model is validated by comparing the numerical simulation results with an experimental data reported in the literature. It is observed that the present model is able to predict the global mechanical behavior of Ti-6Al-4V alloy and investigate the microstructural parameters' effects. According to the simulations performed on the generated volumes (REV), the macroscopic mechanical behavior of Ti-6Al-4V is strongly linked to the active slip systems family (prismatic, basal or pyramidal). The crystallographic texture determines which family of slip systems can be activated; therefore it gives to the plastic strain a heterogeneous character thus an anisotropic macroscopic mechanical behavior. The average grains size influences also the Ti-6Al-4V mechanical proprieties, especially the yield stress; by decreasing of the average grains size, the yield strength increases according to Hall-Petch relationship. The grains sizes' distribution gives to the strain fields considerable heterogeneity. By increasing grain sizes, the scattering in the localization of plastic strain is observed, thus, in certain areas the stress concentrations are stronger than other regions.

Keywords: microstructural parameters, multi-scale modeling, crystal plasticity, Ti-6Al-4V alloy

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Authors: Nada Poropat Jeletic, Gordana Hrzica

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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

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Authors: Francesca Gullo, Paola Palmero, Massimo Messori

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Transparent wood is considered a promising structural material for the development of environmentally friendly, energy-efficient engineered components. To obtain transparent wood from natural wood materials two approaches can be used: i) bottom-up and ii) top-down. Through the second method, the color of natural wood samples is lightened through a chemical bleaching process that acts on chromophore groups of lignin, such as the benzene ring, quinonoid, vinyl, phenolics, and carbonyl groups. These chromophoric units form complex conjugate systems responsible for the brown color of wood. There are two strategies to remove color and increase the whiteness of wood: i) lignin removal and ii) lignin bleaching. In the lignin removal strategy, strong chemicals containing chlorine (chlorine, hypochlorite, and chlorine dioxide) and oxidizers (oxygen, ozone, and peroxide) are used to completely destroy and dissolve the lignin. In lignin bleaching methods, a moderate reductive (hydrosulfite) or oxidative (hydrogen peroxide) is commonly used to alter or remove the groups and chromophore systems of lignin, selectively discoloring the lignin while keeping the macrostructure intact. It is, therefore, essential to manipulate nanostructured wood by precisely controlling the nanopores in the cell walls by monitoring both chemical treatments and process conditions, for instance, the treatment time, the concentration of chemical solutions, the pH value, and the temperature. The elimination of wood light scattering is the second step in the fabrication of transparent wood materials, which can be achieved through two-step approaches: i) the polymer impregnation method and ii) the densification method. For the polymer impregnation method, the wood scaffold is treated with polymers having a corresponding refractive index (e.g., PMMA and epoxy resins) under vacuum to obtain the transparent composite material, which can finally be pressed to align the cellulose fibers and reduce interfacial defects in order to have a finished product with high transmittance (>90%) and excellent light-guiding. However, both the solution-based bleaching and the impregnation processes used to produce transparent wood generally consume large amounts of energy and chemicals, including some toxic or pollutant agents, and are difficult to scale up industrially. Here, we report a method to produce optically transparent wood by modifying the lignin structure with a chemical reaction at room temperature using small amounts of hydrogen peroxide in an alkaline environment. This method preserves the lignin, which results only deconjugated and acts as a binder, providing both a strong wood scaffold and suitable porosity for infiltration of biobased polymers while reducing chemical consumption, the toxicity of the reagents used, polluting waste, petroleum by-products, energy and processing time. The resulting transparent wood demonstrates high transmittance and low thermal conductivity. Through the combination of process efficiency and scalability, the obtained materials are promising candidates for application in the field of construction for modern energy-efficient buildings.

Keywords: bleached wood, energy-efficient components, hydrogen peroxide, transparent wood, wood composites

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Authors: Kaushikk Iyer, Richard M Hall, David Keeling

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Hardware-in-the-loop (HIL) simulation is an advanced technique for developing and testing complex real-time control systems. This paper presents the benefits of HIL simulation and how it can be implemented and used effectively to develop, test, and validate advanced control algorithms used in a spinal joint Wear simulator for the Tribological testing of spinal disc prostheses. spinal wear simulator is technologically the most advanced machine currently employed For the in-vitro testing of newly developed spinal Discimplants. However, the existing control techniques, such as a simple position control Does not allow the simulator to test non-sinusoidal waveforms. Thus, there is a need for better and advanced control methods that can be developed and tested Rigorouslybut safely before deploying it into the real simulator. A benchtop HILsetupis was created for experimentation, controller verification, and validation purposes, allowing different control strategies to be tested rapidly in a safe environment. The HIL simulation aspect in this setup attempts to replicate similar spinal motion and loading conditions. The spinal joint wear simulator containsa four-Barlinkpowered by electromechanical actuators. LabVIEW software is used to design a kinematic model of the spinal wear Simulator to Validatehow each link contributes towards the final motion of the implant under test. As a result, the implant articulates with an angular motion specified in the international standards, ISO-18192-1, that define fixed, simplified, and sinusoid motion and load profiles for wear testing of cervical disc implants. Using a PID controller, a velocity-based position control algorithm was developed to interface with the benchtop setup that performs HIL simulation. In addition to PID, a fuzzy logic controller (FLC) was also developed that acts as a supervisory controller. FLC provides intelligence to the PID controller by By automatically tuning the controller for profiles that vary in amplitude, shape, and frequency. This combination of the fuzzy-PID controller is novel to the wear testing application for spinal simulators and demonstrated superior performance against PIDwhen tested for a spectrum of frequency. Kaushikk Iyer is a Ph.D. Student at the University of Leeds and an employee at Key Engineering Solutions, Leeds, United Kingdom, (e-mail: [email protected], phone: +44 740 541 5502). Richard M Hall is with the University of Leeds, the United Kingdom as a professor in the Mechanical Engineering Department (e-mail: [email protected]). David Keeling is the managing director of Key Engineering Solutions, Leeds, United Kingdom (e-mail: [email protected]). Results obtained are successfully validated against the load and motion tolerances specified by the ISO18192-1 standard and fall within limits, that is, ±0.5° at the maxima and minima of the motion and ±2 % of the complete cycle for phasing. The simulation results prove the efficacy of the test setup using HIL simulation to verify and validate the accuracy and robustness of the prospective controller before its deployment into the spinal wear simulator. This method of testing controllers enables a wide range of possibilities to test advanced control algorithms that can potentially test even profiles of patients performing various dailyliving activities.

Keywords: Fuzzy-PID controller, hardware-in-the-loop (HIL), real-time simulation, spinal wear simulator

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Authors: Juan Manuel Macia

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The Montreal Port Authority (MPA) wanted to build a new road link via Souligny Avenue to increase the fluidity of goods transported by truck in the Viau Street area of Montreal and to mitigate the current traffic problems on Notre-Dame Street. With the purpose of having a better integration and acceptance of this project with the neighboring residential surroundings, this project needed to include an architectural integration, bringing some artistic components to the bridge design along with some landscaping components. The MPA is required primarily to provide direct truck access to Port of Montreal with a direct connection to the future Assomption Boulevard planned by the City of Montreal and, thus, direct access to Souligny Avenue. The MPA also required other key aspects to be considered for the proposal and development of the project, such as the layout of road and rail configurations, the reconstruction of underground structures, the relocation of power lines, the installation of lighting systems, the traffic signage and communication systems improvement, the construction of new access ramps, the pavement reconstruction and a summary assessment of the structural capacity of an existing service tunnel. The identification of the various possible scenarios began by identifying all the constraints related to the numerous infrastructures located in the area of the future link between the port and the future extension of Souligny Avenue, involving interaction with several disciplines and technical specialties. Several viaduct- and tunnel-type geometries were studied to link the port road to the right-of-way north of Notre-Dame Street and to improve traffic flow at the railway corridor. The proposed design took into account the existing access points to Port of Montreal, the built environment of the MPA site, the provincial and municipal rights-of-way, and the future Notre-Dame Street layout planned by the City of Montreal. These considerations required the installation of an engineering structure with a span of over 60 m to free up a corridor for the future urban fabric of Notre-Dame Street. The best option for crossing this span length was identified by the design and construction of a curved bridge over Notre-Dame Street, which is essentially a structure with a deck formed by a reinforced concrete slab on steel box girders with a single span of 63.5m. The foundation units were defined as pier-cap type abutments on drilled shafts to bedrock with rock sockets, with MSE-type walls at the approaches. The configuration of a single-span curved structure posed significant design and construction challenges, considering the major constraints of the project site, a design for durability approach, and the need to guarantee optimum performance over a 75-year service life in accordance with the client's needs and the recommendations and requirements defined by the standards used for the project. These aspects and the need to include architectural and artistic components in this project made it possible to design, build, and integrate a signature infrastructure project with a sustainable approach, from which the MPA, the commuters, and the city of Montreal and its residents will benefit.

Keywords: curved bridge, steel box girder, medium span, simply supported, industrial and urban environment, architectural integration, design for durability

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Authors: David Bakker, Nikki Rickard

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Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

Procedia PDF Downloads 241

Authors: May Bazzi, Shafik Tokmaj, Younes Saberi, Mats Geijer, Tony Jurkiewicz, Patrik Sund, Anna Bjällmark

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Mobile radiography, employing portable X-ray equipment, has become a routine procedure within hospital settings, with chest X-rays in intensive care units standing out as the most prevalent mobile X-ray examinations. This approach is not limited to hospitals alone, as it extends its benefits to imaging patients in various settings, particularly those too frail to be transported, such as elderly care residents in nursing homes. Moreover, the utility of mobile X-ray isn't confined solely to traditional healthcare recipients; it has proven to be a valuable resource for vulnerable populations, including the homeless, drug users, asylum seekers, and patients with multiple co-morbidities. Mobile X-rays reduce patient stress, minimize costly hospitalizations, and offer cost-effective imaging. While studies confirm its reliability, further research is needed, especially regarding image quality. Recent advancements in lightweight equipment with enhanced battery and detector technology provide the potential for nearly handheld radiography. The main aim of this study was to evaluate a new lightweight mobile X-ray system with two different detectors and compare the image quality with a modern stationary system. Methods: A total of 74 images of the chest (chest anterior-posterior (AP) views and chest lateral views) and pelvic/hip region (AP pelvis views, hip AP views, and hip cross-table lateral views) were acquired on a whole-body phantom (Kyotokagaku, Japan), utilizing varying image parameters. These images were obtained using a stationary system - 18 images (Mediel, Sweden), a mobile X-ray system with a second-generation detector - 28 images (FDR D-EVO II; Fujifilm, Japan) and a mobile X-ray system with a third-generation detector - 28 images (FDR D-EVO III; Fujifilm, Japan). Image quality was assessed by visual grading analysis (VGA), which is a method to measure image quality by assessing the visibility and accurate reproduction of anatomical structures within the images. A total of 33 image criteria were used in the analysis. A panel of two experienced radiologists, two experienced radiographers, and two final-term radiographer students evaluated the image quality on a 5-grade ordinal scale using the software Viewdex 3.0 (Viewer for Digital Evaluation of X-ray images, Sweden). Data were analyzed using visual grading characteristics analysis. The dose was measured by the dose-area product (DAP) reported by the respective systems. Results: The mobile X-ray equipment (both detectors) showed significantly better image quality than the stationary equipment for the pelvis, hip AP and hip cross-table lateral images with AUCVGA-values ranging from 0.64-0.92, while chest images showed mixed results. The number of images rated as having sufficient quality for diagnostic use was significantly higher for mobile X-ray generation 2 and 3 compared with the stationary X-ray system. The DAP values were higher for the stationary compared to the mobile system. Conclusions: The new lightweight radiographic equipment had an image quality at least as good as a fixed system at a lower radiation dose. Future studies should focus on clinical images and consider radiographers' viewpoints for a comprehensive assessment.

Keywords: mobile x-ray, visual grading analysis, radiographer, radiation dose

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Authors: komal verma, V. S. Moholkar

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In this current study, the challenge of effectively treating and mineralizing industrial wastewater prior to its discharge into natural water bodies, such as rivers and lakes, is being addressed. Particularly, the focus is on the wastewater produced by chemical process industries, including refineries, petrochemicals, fertilizer, pharmaceuticals, pesticides, and dyestuff industries. These wastewaters often contain stubborn organic pollutants that conventional techniques, such as microbial processes cannot efficiently degrade. To tackle this issue, a ternary hybrid technique comprising of adsorption, heterogeneous Fenton process, and sonication has been employed. The study aims to evaluate the effectiveness of this approach for treating and mineralizing wastewater from a fertilizer industry located in Northeast India. The study comprises several key components, starting with the synthesis of the Fe3O4@AC nanocomposite using the co-precipitation method. The nanocomposite is then subjected to comprehensive characterization through various standard techniques, including FTIR, FE-SEM, EDX, TEM, BET surface area analysis, XRD, and magnetic property determination using VSM. Next, the process parameters of wastewater treatment are statistically optimized, focusing on achieving a high level of COD (Chemical Oxygen Demand) removal as the response variable. The Fe3O4@AC nanocomposite's adsorption characteristics and kinetics are also assessed in detail. The remarkable outcome of this study is the successful application of the ternary hybrid technique, combining adsorption, Fenton process, and sonication. This approach proves highly effective, leading to nearly complete mineralization (or TOC removal) of the fertilizer industry wastewater. The results highlight the potential of the Fe3O4@AC nanocomposite and the ternary hybrid technique as a promising solution for tackling challenging wastewater pollutants from various chemical process industries. This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result results from synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Micro-convection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe3O4@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater. The Fe3O4@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: chemical oxygen demand (cod), fe3o4@ac nanocomposite, kinetics, lc-ms, rsm, toxicity

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Authors: Jae Won Lee, Kyung Hyun Min, Hong Jae Lee, Sang Cheon Lee

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To date, imaging techniques have attracted much attention in medicine because the detection of diseases at an early stage provides greater opportunities for successful treatment. Consequently, over the past few decades, diverse imaging modalities including magnetic resonance (MR), positron emission tomography, computed tomography, and ultrasound (US) have been developed and applied widely in the field of clinical diagnosis. However, each of the above-mentioned imaging modalities possesses unique strengths and intrinsic weaknesses, which limit their abilities to provide accurate information. Therefore, multimodal imaging systems may be a solution that can provide improved diagnostic performance. Among the current medical imaging modalities, US is a widely available real-time imaging modality. It has many advantages including safety, low cost and easy access for patients. However, its low spatial resolution precludes accurate discrimination of diseased region such as cancer sites. In contrast, MR has no tissue-penetrating limit and can provide images possessing exquisite soft tissue contrast and high spatial resolution. However, it cannot offer real-time images and needs a comparatively long imaging time. The characteristics of these imaging modalities may be considered complementary, and the modalities have been frequently combined for the clinical diagnostic process. Biominerals such as calcium carbonate (CaCO3) and calcium phosphate (CaP) exhibit pH-dependent dissolution behavior. They demonstrate pH-controlled drug release due to the dissolution of minerals in acidic pH conditions. In particular, the application of this mineralization technique to a US contrast agent has been reported recently. The CaCO3 mineral reacts with acids and decomposes to generate calcium dioxide (CO2) gas in an acidic environment. These gas-generating mineralized nanoparticles generated CO2 bubbles in the acidic environment of the tumor, thereby allowing for strong echogenic US imaging of tumor tissues. On the basis of this previous work, it was hypothesized that the loading of MR contrast agents into the CaCO3 mineralized nanoparticles may be a novel strategy in designing a contrast agent for dual imaging. Herein, CaCO3 mineralized nanoparticles that were capable of generating CO2 bubbles to trigger the release of entrapped MR contrast agents in response to tumoral acidic pH were developed for the purposes of US and MR dual-modality imaging of tumors. Gd2O3 nanoparticles were selected as an MR contrast agent. A key strategy employed in this study was to prepare Gd2O3 nanoparticle-loaded mineralized nanoparticles (Gd2O3-MNPs) using block copolymer-templated CaCO3 mineralization in the presence of calcium cations (Ca2+), carbonate anions (CO32-) and positively charged Gd2O3 nanoparticles. The CaCO3 core was considered suitable because it may effectively shield Gd2O3 nanoparticles from water molecules in the blood (pH 7.4) before decomposing to generate CO2 gas, triggering the release of Gd2O3 nanoparticles in tumor tissues (pH 6.4~7.4). The kinetics of CaCO3 dissolution and CO2 generation from the Gd2O3-MNPs were examined as a function of pH and pH-dependent in vitro magnetic relaxation; additionally, the echogenic properties were estimated to demonstrate the potential of the particles for the tumor-specific US and MR imaging.

Keywords: calcium carbonate, mineralization, ultrasound imaging, magnetic resonance imaging

Procedia PDF Downloads 207