Search results for: radial basis function networks

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Vidar Hepsø

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The energy and oil companies on the Norwegian Continental shelf come from a situation where each asset control and manage their energy supply (island mode) and move towards a situation where the assets need to collaborate and coordinate energy use with others due to increased cost and scarcity of electric energy sharing the energy that is provided. Currently, several areas are electrified either with an onshore grid cable or are receiving intermittent energy from offshore wind-parks. While the onshore grid in Norway is well regulated, the offshore grid is still in the making, with several oil and gas electrification projects and offshore wind development just started. The paper will describe the shift in the mindset that comes with operating this new offshore grid. This transition process heralds an increase in collaboration across boundaries and integration of energy management across companies, businesses, technical disciplines, and engagement with stakeholders in the larger society. This transition will be described as a function of the new challenges with increased complexity of the energy mix (wind, oil/gas, hydrogen and others) coupled with increased technical and organization complexity in energy management. Organizational complexity denotes an increasing integration across boundaries, whether these boundaries are company, vendors, professional disciplines, regulatory regimes/bodies, businesses, and across numerous societal stakeholders. New practices must be developed, made legitimate and institutionalized across these boundaries. Only parts of this complexity can be mitigated technically, e.g.: by use of batteries, mixing energy systems and simulation/ forecasting tools. Many challenges must be mitigated with legitimated societal and institutionalized governance practices on many levels. Offshore electrification supports Norway’s 2030 climate targets but is also controversial since it is exploiting the larger society’s energy resources. This means that new systems and practices must also be transparent, not only for the industry and the authorities, but must also be acceptable and just for the larger society. The paper report from ongoing work in Norway, participant observation and interviews in projects and people working with offshore grid development in Norway. One case presented is the development of an offshore floating windfarm connected to two offshore installations and the second case is an offshore grid development initiative providing six installations electric energy via an onshore cable. The development of the offshore grid is analyzed using a capability platform framework, that describes the technical, competence, work process and governance capabilities that are under development in Norway. A capability platform is a ‘stack’ with the following layers: intelligent infrastructure, information and collaboration, knowledge sharing & analytics and finally business operations. The need for better collaboration and energy forecasting tools/capabilities in this stack will be given a special attention in the two use cases that are presented.

Keywords: capability platform, electrification, carbon footprint, control rooms, energy forecsting, operational model

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Authors: Young Ik Suh, Tywan G. Martin

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Sports apps in a smartphone provide up-to-date information and fast and convenient access to live games. The market of sports apps has emerged as the second fastest growing app category worldwide. Further, many sports fans use their smartphones to know the schedule of sporting events, players’ position and bios, videos and highlights. In recent years, a growing number of scholars and practitioners alike have emphasized the importance of interactivity with sports apps, hypothesizing that interactivity plays a significant role in enticing sports apps users and that it is a key component in measuring the success of sports apps. Interactivity in sports apps focuses primarily on two functions: (1) two-way communication and (2) active user control, neither of which have been applicable through traditional mass media and communication technologies. Therefore, the purpose of this study is to examine whether the interactivity function on sports apps leads to positive outcomes such as intent to revisit. More specifically, this study investigates how three major functions of interactivity (i.e., two-way communication, active user control, and real-time information) influence the attitude of sports apps users and their intent to revisit the sports apps. The following hypothesis is proposed; interactivity functions will be positively associated with both attitudes toward sports apps and intent to revisit sports apps. The survey questionnaire includes four parts: (1) an interactivity scale, (2) an attitude scale, (3) a behavioral intention scale, and (4) demographic questions. Data are to be collected from ESPN apps users. To examine the relationships among the observed and latent variables and determine the reliability and validity of constructs, confirmatory factor analysis (CFA) is conducted. Structural equation modeling (SEM) is utilized to test hypothesized relationships among constructs. Additionally, this study compares the proposed interactivity model with a rival model to identify the role of attitude as a mediating factor. The findings of the current sports apps study provide several theoretical and practical contributions and implications by extending the research and literature associated with the important role of interactivity functions in sports apps and sports media consumption behavior. Specifically, this study may improve the theoretical understandings of whether the interactivity functions influence user attitudes and intent to revisit sports apps. Additionally, this study identifies which dimensions of interactivity are most important to sports apps users. From practitioners’ perspectives, this findings of this study provide significant implications. More entrepreneurs and investors in the sport industry need to recognize that high-resolution photos, live streams, and up-to-date stats are in the sports app, right at sports fans fingertips. The result will imply that sport practitioners may need to develop sports mobile apps that offer greater interactivity functions to attract sport fans.

Keywords: interactivity, two-way communication, active user control, real time information, sports apps, attitude, intent to revisit

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Authors: Julio Jesus Salazar, Manuel Andres Jesus De Lama

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There are very few models that serve to analyze the use of water in the socio-economic process. On the supply side, the joint use of groundwater has been considered in addition to the simple limits on the availability of surface water. In addition, we have worked on waterlogging and the effects on water quality (mainly salinity). In this paper, a 'complex' water economy is examined; one in which demands grow differentially not only within but also between sectors, and one in which there are limited opportunities to increase consumptive use. In particular, high-value growth, the growth of the production of irrigated crops of high value within the basins of the case study, together with the rapidly growing urban areas, provides a rich context to examine the general problem of water management at the basin level. At the same time, the long-term aridity of nature has made the eco-environment in the basins located on the coast of Peru very vulnerable, and the exploitation and immediate use of water resources have further deteriorated the situation. The presented methodology is the optimization with embedded simulation. The wide basin simulation of flow and water balances and crop growth are embedded with the optimization of water allocation, reservoir operation, and irrigation scheduling. The modeling framework is developed from a network of river basins that includes multiple nodes of origin (reservoirs, aquifers, water courses, etc.) and multiple demand sites along the river, including places of consumptive use for agricultural, municipal and industrial, and uses of running water on the coast of Peru. The economic benefits associated with water use are evaluated for different demand management instruments, including water rights, based on the production and benefit functions of water use in the urban agricultural and industrial sectors. This work represents a new effort to analyze the use of water at the regional level and to evaluate the modernization of the integrated management of water resources and socio-economic territorial development in Peru. It will also allow the establishment of policies to improve the process of implementation of the integrated management and development of water resources. The input-output analysis is essential to present a theory about the production process, which is based on a particular type of production function. Also, this work presents the Computable General Equilibrium (CGE) version of the economic model for water resource policy analysis, which was specifically designed for analyzing large-scale water management. As to the platform for CGE simulation, GEMPACK, a flexible system for solving CGE models, is used for formulating and solving CGE model through the percentage-change approach. GEMPACK automates the process of translating the model specification into a model solution program.

Keywords: water economy, simulation, modeling, integration

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Authors: Sara Saboonian, Pierre Filion

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The dispersed-suburban model has been the dominant one across North America for the past seventy years, characterized by automobile reliance, low density, and land-use specialization. Two planning models have emerged as possible alternatives to address the ills inflicted by this development pattern. First, there is intensification, which promotes efficient infrastructure by connecting high-density, multi-functional, and walkable nodes with public transit services within the suburban landscape. Second is green infrastructure, which provides environmental health and human well-being by preserving and restoring ecosystem services. This research studies incompatibilities and the possibility of amalgamating the two alternatives in an attempt to develop a comprehensive alternative to suburban model that advocates density, multi-functionality and transit- and pedestrian-conduciveness, with measures capable of mitigating the adverse environmental impacts of compactness. The research investigates three Canadian urban growth centers, where intensification is the current planning practice, and the awareness of green infrastructure benefits is on the rise. However, these three centers are contrasted by their development stage, the presence or absence of protected natural land, their environmental approach, and their adverse environmental consequences according to the planning cannons of different periods. The methods include reviewing the literature on green infrastructure planning, criticizing the Ontario provincial plans for intensification, surveying residents’ preferences for alternative models, and interviewing officials who deal with the local planning for the centers. Moreover, the research draws on recalling debates between New Urbanism and Landscape/Ecological Urbanism. The case studies expose the difficulties in creating urban growth centres that accommodate green infrastructure while adhering to intensification principles. First, the dominant status of intensification and the obstacles confronting intensification have monopolized the planners’ concerns. Second, the tension between green infrastructure and intensification explains the absence of the green infrastructure typologies that correspond to intensification-compatible forms and dynamics. Finally, the lack of highlighted social-economic benefits of green infrastructure reduces residents’ participation. Moreover, the results from the research provide insight into predominating urbanization theories, New Urbanism and Landscape/Ecological Urbanism. In order to understand political, planning, and ecological dynamics of such blending, dexterous context-specific planning is required. Findings suggest the influence of the following factors on amalgamating intensification and green infrastructure. Initially, producing ecosystem services-based justifications for green infrastructure development in the intensification context provides an expert-driven backbone for the implementation programs. This knowledge-base should be translated to effectively imbue different urban stakeholders. Moreover, due to the limited greenfields in intensified areas, spatial distribution and development of multi-level corridors such as pedestrian-hospitable settings and transportation networks along green infrastructure measures are required. Finally, to ensure the long-term integrity of implemented green infrastructure measures, significant investment in public engagement and education, as well as clarification of management responsibilities is essential.

Keywords: ecosystem services, green infrastructure, intensification, planning

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Authors: Renée M. Ripken, Johannes G. E. Gardeniers, Séverine Le Gac

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Controlling the multiphase behavior of aqueous biomass mixtures is essential when working in the biomass conversion industry. Here, the vapor/liquid equilibria (VLE) of ethylene glycol, glycerol, and xylitol were studied for temperatures between 25 and 200 °C and pressures of 1 to 10 bar. These experiments were performed in a microfluidic platform, which exhibits excellent heat transfer properties so that equilibrium is reached fast. Firstly, the saturated vapor pressure as a function of the temperature and the substrate mole fraction of the substrate was calculated using AspenPlus with a Redlich-Kwong-Soave Boston-Mathias (RKS-BM) model. Secondly, we developed a high-pressure and high-temperature microfluidic set-up for experimental validation. Furthermore, we have studied the multiphase flow pattern that occurs after the saturation temperature was achieved. A glass-silicon microfluidic device containing a 0.4 or 0.2 m long meandering channel with a depth of 250 μm and a width of 250 or 500 μm was fabricated using standard microfabrication techniques. This device was placed in a dedicated chip-holder, which includes a ceramic heater on the silicon side. The temperature was controlled and monitored by three K-type thermocouples: two were located between the heater and the silicon substrate, one to set the temperature and one to measure it, and the third one was placed in a 300 μm wide and 450 μm deep groove on the glass side to determine the heat loss over the silicon. An adjustable back pressure regulator and a pressure meter were added to control and evaluate the pressure during the experiment. Aqueous biomass solutions (10 wt%) were pumped at a flow rate of 10 μL/min using a syringe pump, and the temperature was slowly increased until the theoretical saturation temperature for the pre-set pressure was reached. First and surprisingly, a significant difference was observed between our theoretical saturation temperature and the experimental results. The experimental values were 10’s of degrees higher than the calculated ones and, in some cases, saturation could not be achieved. This discrepancy can be explained in different ways. Firstly, the pressure in the microchannel is locally higher due to both the thermal expansion of the liquid and the Laplace pressure that has to be overcome before a gas bubble can be formed. Secondly, superheating effects are likely to be present. Next, once saturation was reached, the flow pattern of the gas/liquid multiphase system was recorded. In our device, the point of nucleation can be controlled by taking advantage of the pressure drop across the channel and the accurate control of the temperature. Specifically, a higher temperature resulted in nucleation further upstream in the channel. As the void fraction increases downstream, the flow regime changes along the channel from bubbly flow to Taylor flow and later to annular flow. All three flow regimes were observed simultaneously. The findings of this study are key for the development and optimization of a microreactor for hydrogen production from biomass.

Keywords: biomass conversion, high pressure and high temperature microfluidics, multiphase, phase diagrams, superheating

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Authors: Amanda Gregorim Fernandes, Lorena Cardoso Cintra, Rosalia Santos Amorim Jesuino, Fabricia Paula De Faria, Marcio José Poças Fonseca

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Bioethanol is one of the most promising biofuels and able to replace fossil fuels and reduce its different environmental impacts and can be generated from various agroindustrial waste. The Brazil is in first place in bioethanol production to be the largest producer of sugarcane. The bagasse sugarcane (SCB) has lignocellulose which is composed of three major components: cellulose, hemicellulose and lignin. Cellulose is a homopolymer of glucose units connected by glycosidic linkages. Among all species of Penicillium, Penicillium echinulatum has been the focus of attention because they produce high quantities of cellulase and the mutant strain 9A02S1 produces higher enzyme levels compared to the wild. Among the cellulases, the cellobiohydrolases enzymes are the main components of the cellulolytic system of fungi, and are also responsible for most of the potential hydrolytic in enzyme cocktails for the industrial processing of plant biomass and several cellobiohydrolases Penicillium had higher specific activity against cellulose compared to CBH I from Trichoderma reesei. This fact makes it an interesting pattern for higher yields in the enzymatic hydrolysis, and also they are important enzymes in the hydrolysis of crystalline regions of cellulose. Therefore, finding new and more active enzymes become necessary. Meanwhile, β-glycosidases act on soluble substrates and are highly dependent on cellobiohydrolases and endoglucanases action to provide the substrate in the hydrolysis of the biomass, but the cellobiohydrolases and endoglucanases are highly dependent β-glucosidases to maintain efficient hydrolysis. Thus, there is a need to understand the structure-function relationships that govern the catalytic activity of cellulolytic enzymes to elucidate its mechanism of action and optimize its potential as industrial biocatalysts. To evaluate the enzyme β-glucosidase of Penicillium echinulatum (PeBGL1) the gene was synthesized from the assembly sequence from a library in induction conditions and then the PeBGL1 gene was cloned in the vector pPICZαA and transformed into P. pastoris GS115. After processing, the producers of PeBGL1 were analyzed for enzyme activity and protein profile where a band of approximately 100 kDa was viewed. It was also carried out the zymogram. In partial characterization it was determined optimum temperature of 50°C and optimum pH of 6,5. In addition, to increase the secreted recombinant PeBGL1 production by Pichia pastoris, three parameters of P. pastoris culture medium were analysed: methanol, nitrogen source concentrations and the inoculum size. A 23 factorial design was effective in achieving the optimum condition. Altogether, these results point to the potential application of this P. echinulatum β-glucosidase in hydrolysis of cellulose for the production of bioethanol.

Keywords: bioethanol, biotechnology, beta-glucosidase, penicillium echinulatum

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Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

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High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

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Authors: C. Villamizar, M. Serrato

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In the pursuit of athletic performance, the role of physical training which is determined by a number of charges or taxes on physiological stress and musculoskeletal systems of the human body generated by the intensity and duration is fundamental. Given the physical demands of these activities both training and competitive must take into account the optimal relationship with a straining process recovery post favoring the process of overcompensation which aims to facilitate the return and rising energy potential and protein synthesis also of different tissues. Allowing muscle function returns to baseline or pre-exercise states. If this recovery process is not performed or is not allowed in a proper way, will result in an increased state of fatigue. Active recovery, is one of the strategies implemented in the sport for a return to pre-exercise physiological states. However, there are some adverse assumptions regarding the negative effects, as is the possibility of increasing the degradation of muscle glycogen and thus delaying the synthesis thereof. For them, it is necessary to investigate what would be the effects generated application made at different times after the effort. The aim of this study was to determine the effects of active recovery post effort made at three different times: immediately, at 12 and 24 hours on biochemical markers creatine kinase in youth soccer player’s categories. A randomized controlled trial with allocation to three groups was performed: A. active recovery immediately after the effort; B. active recovery performed at 12 hours after the effort; C. active recovery made at 24 hours after the effort. This study included 27 subjects belonging to a Colombian soccer team of the second division. Vital signs, weight, height, BMI, the percentage of muscle mass, fat mass percentage, personal medical history, and family were valued. The velocity, explosive force and Creatin Kinase (CK) in blood were tested before and after interventions. SAFT 90 protocol (Soccer Field specific Aerobic Test) was applied to participants for generating fatigue. CK samples were taken one hour before the application of the fatigue test, one hour after the fatigue protocol and 48 of the initial CK sample. Mean age was 18.5 ± 1.1 years old. Improvements in jumping and speed recovery the 3 groups (p < 0.05), but no statistically significant differences between groups was observed after recuperation. In all participants, there was a significant increment of CK when applied SAFT 90 in all the groups (median 103.1-111.1). The CK measurement after 48 hours reflects a recovery in all groups, however the group C, a decline below baseline levels of -55.5 (-96.3 /-20.4) which is a significant find. Other research has shown that CK does not return quickly to their baseline, but our study shows that active recovery favors the clearance of CK and also to perform recovery 24 hours after the effort generates higher clearance of this biomarker.

Keywords: active recuperation, creatine phosphokinase, post training, young soccer players

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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: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

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Authors: Mir Jalil Razavi, Tianming Liu, Xianqiao Wang

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Cortical folding, characterized by convex gyri and concave sulci, has an intrinsic relationship to the brain’s functional organization. Understanding the mechanism of the brain’s convoluted patterns can provide useful clues into normal and pathological brain function. During the development, the cerebral cortex experiences a noticeable expansion in volume and surface area accompanied by tremendous tissue folding which may be attributed to many possible factors. Despite decades of endeavors, the fundamental mechanism and key regulators of this crucial process remain incompletely understood. Therefore, to taking even a small role in unraveling of brain folding mystery, we present a mechanical model to find mechanism of 3-hinges formation in a growing brain that it has not been addressed before. A 3-hinge is defined as a gyral region where three gyral crests (hinge-lines) join. The reasons that how and why brain prefers to develop 3-hinges have not been answered very well. Therefore, we offer a theoretical and computational explanation to mechanism of 3-hinges formation in a growing brain and validate it by experimental observations. In theoretical approach, the dynamic behavior of brain tissue is examined and described with the aid of a large strain and nonlinear constitutive model. Derived constitute model is used in the computational model to define material behavior. Since the theoretical approach cannot predict the evolution of cortical complex convolution after instability, non-linear finite element models are employed to study the 3-hinges formation and secondary morphological folds of the developing brain. Three-dimensional (3D) finite element analyses on a multi-layer soft tissue model which mimics a small piece of the brain are performed to investigate the fundamental mechanism of consistent hinge formation in the cortical folding. Results show that after certain amount growth of cortex, mechanical model starts to be unstable and then by formation of creases enters to a new configuration with lower strain energy. By further growth of the model, formed shallow creases start to form convoluted patterns and then develop 3-hinge patterns. Simulation results related to 3-hinges in models show good agreement with experimental observations from macaque, chimpanzee and human brain images. These results have great potential to reveal fundamental principles of brain architecture and to produce a unified theoretical framework that convincingly explains the intrinsic relationship between cortical folding and 3-hinges formation. This achieved fundamental understanding of the intrinsic relationship between cortical folding and 3-hinges formation would potentially shed new insights into the diagnosis of many brain disorders such as schizophrenia, autism, lissencephaly and polymicrogyria.

Keywords: brain, cortical folding, finite element, three hinge

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Authors: Hamed Yaghoubi, Esmaeil Salahi, Fateme Taati

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The effective shear and bulk viscosity, as well as dynamic viscosity, describe the rheological properties of the ceramic body during the liquid phase sintering process. The rheological parameters depend on the physical and thermomechanical characteristics of the material such as relative density, temperature, grain size, and diffusion coefficient and activation energy. The main goal of this research is to acquire a comprehensive understanding of the response of an incompressible viscose ceramic material during liquid phase sintering process such as stress-strain relations, sintering and hydrostatic stress, the prediction of anisotropic shrinkage and heterogeneous densification as a function of sintering time by including the simultaneous influence of gravity field, and frictional force. After raw materials analysis, the standard hard porcelain mixture as a ceramic body was designed and prepared. Three different experimental configurations were designed including midpoint deflection, sinter bending, and free sintering samples. The numerical method for the ceramic specimens during the liquid phase sintering process are implemented in the CREEP user subroutine code in ABAQUS. The numerical-experimental procedure shows the anisotropic behavior, the complete difference in spatial displacement through three directions, the incompressibility for ceramic samples during the sintering process. The anisotropic shrinkage factor has been proposed to investigate the shrinkage anisotropy. It has been shown that the shrinkage along the normal axis of casting sample is about 1.5 times larger than that of casting direction, the gravitational force in pyroplastic deformation intensifies the shrinkage anisotropy more than the free sintering sample. The lowest and greatest equivalent creep strain occurs at the intermediate zone and around the central line of the midpoint distorted sample, respectively. In the sinter bending test sample, the equivalent creep strain approaches to the maximum near the contact area with refractory support. The inhomogeneity in Von-Misses, pressure, and principal stress intensifies the relative density non-uniformity in all samples, except in free sintering one. The symmetrical distribution of stress around the center of free sintering sample, cause to hinder the pyroplastic deformations. Densification results confirmed that the effective bulk viscosity was well-defined with relative density values. The stress analysis confirmed that the sintering stress is more than the hydrostatic stress from start to end of sintering time so, from both theoretically and experimentally point of view, the sintering process occurs completely.

Keywords: anisotropic shrinkage, ceramic material, liquid phase sintering process, rheological properties, numerical-experimental procedure

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Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

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Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

Procedia PDF Downloads 123

Authors: Aleksandra Dudkowska, Gabriela Gic-Grusza

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Wind wave-induced sediment transport is an important multidimensional and multiscale dynamic process affecting coastal seabed changes and coastline evolution. The knowledge about sediment transport rate is important to solve many environmental and geotechnical issues. There are many types of sediment transport models but none of them is widely accepted. It is bacause the process is not fully defined. Another problem is a lack of sufficient measurment data to verify proposed hypothesis. There are different types of models for longshore sediment transport (LST, which is discussed in this work) and cross-shore transport which is related to different time and space scales of the processes. There are models describing bed-load transport (discussed in this work), suspended and total sediment transport. LST models use among the others the information about (i) the flow velocity near the bottom, which in case of wave-currents interaction in coastal zone is a separate problem (ii) critical bed shear stress that strongly depends on the type of sediment and complicates in the case of heterogeneous sediment. Moreover, LST rate is strongly dependant on the local environmental conditions. To organize existing knowledge a series of sediment transport models intercomparisons was carried out as a part of the project “Development of a predictive model of morphodynamic changes in the coastal zone”. Four classical one-grid-point models were studied and intercompared over wide range of bottom shear stress conditions, corresponding with wind-waves conditions appropriate for coastal zone in polish marine areas. The set of models comprises classical theories that assume simplified influence of turbulence on the sediment transport (Du Boys, Meyer-Peter & Muller, Ribberink, Engelund & Hansen). It turned out that the values of estimated longshore instantaneous mass sediment transport are in general in agreement with earlier studies and measurements conducted in the area of interest. However, none of the formulas really stands out from the rest as being particularly suitable for the test location over the whole analyzed flow velocity range. Therefore, based on the models discussed a new unified formula for longshore sediment transport rate estimation is introduced, which constitutes the main original result of this study. Sediment transport rate is calculated based on the bed shear stress and critical bed shear stress. The dependence of environmental conditions is expressed by one coefficient (in a form of constant or function) thus the model presented can be quite easily adjusted to the local conditions. The discussion of the importance of each model parameter for specific velocity ranges is carried out. Moreover, it is shown that the value of near-bottom flow velocity is the main determinant of longshore bed-load in storm conditions. Thus, the accuracy of the results depends less on the sediment transport model itself and more on the appropriate modeling of the near-bottom velocities.

Keywords: bedload transport, longshore sediment transport, sediment transport models, coastal zone

Procedia PDF Downloads 367

Authors: Kyriaki Hatziagapiou, Konstantinos Bethanis, Olti Nikola, Elias Christoforides, Eleni Koniari, Eleni Kakouri, George Lambrou, Christina Kanaka-Gantenbein

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Glioblastoma multiforme (GBM) remains a serious health challenge, as current therapeutic modalities continue to yield unsatisfactory results, with the average survival rarely exceeding 1-2 years. Natural compounds still provide some of the most promising approaches for discovering new drugs. The non-psychotropic cannabidiol (CBD) deriving from Cannabis sativa L. provides such promise. CBD is endowed with anticancer, antioxidant, and genoprotective properties as established in vitro and in in vivo experiments. CBD’s selectivity towards cancer cells and its safe profile suggest its usage in cancer therapies. However, the bioavailability of oral CBD is low due to poor aqueous solubility, erratic gastrointestinal absorption, and significant first-pass metabolism, hampering its therapeutic potential and resulting in a variable pharmacokinetic profile. In this context, CBD can take great advantage of nanomedicine-based formulation strategies. Cyclodextrins (CDs) are cyclic oligosaccharides used in the pharmaceutical industry to incorporate apolar molecules inside their hydrophobic cavity, increasing their stability, water solubility, and bioavailability or decreasing their side effects. CBD-inclusion complexes with CDs could be a good strategy to improve its properties, like solubility and stability to harness its full therapeutic potential. The current research aims to study the potential cytotoxic effect of CBD and CBD-CDs complexes CBD-RMβCD (randomly methylated β-cyclodextrin) and CBD-HPβCD (hydroxypropyl-b-CD) on the A172 glioblastoma cell line. CBD is diluted in 10% DMSO, and CBD/CDs solutions are prepared by mixing solid CBD, solid CDs, and dH2O. For the biological assays, A172 cells are incubated at a range of concentrations of CBD, CBD-RMβCD and CBD-HPβCD, RMβCD, and HPβCD (0,03125-4 mg/ml) at 24, 48, and 72 hours. Analysis of cell viability after incubation with the compounds is performed with Alamar Blue viability assay. CBD’s dilution to DMSO 10% was inadequate, as crystals are observed; thus cytotoxicity experiments are not assessed. CBD’s solubility is enhanced in the presence of both CDs. CBD/CDs exert significant cytotoxicity in a dose and time-dependent manner (p < 0.005 for exposed cells to any concentration at 48, 72, and 96 hours versus cells not exposed); as their concentration and time of exposure increases, the reduction of resazurin to resofurin decreases, indicating a reduction in cell viability. The cytotoxic effect is more pronounced in cells exposed to CBD-HPβCD for all concentrations and time-points. RMβCD and HPβCD at the highest concentration of 4 mg/ml also exerted antitumor action per se since manifesting cell growth inhibition. The results of our study could afford the basis of research regarding the use of natural products and their inclusion complexes as anticancer agents and the shift to targeted therapy with higher efficacy and limited toxicity. Acknowledgments: The research is partly funded by ΙΚΥ (State Scholarships Foundation) – Post-doc Scholarships-Partnership Agreement 2014-2020.

Keywords: cannabidiol, cyclodextrins, glioblastoma, hydroxypropyl-b-Cyclodextrin, randomly-methylated-β-cyclodextrin

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Authors: Reyna Singh, David Lokhat, Milan Carsky

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The world crude oil demand is projected to rise to 108.5 million bbl/d by the year 2035. With reserves estimated at 869 billion tonnes worldwide, coal is an abundant resource. This work was aimed at producing a high value hydrocarbon liquid product from the Direct Coal Liquefaction (DCL) process at, comparatively, mild operating conditions. Via hydrogenation, the temperature-staged approach was investigated. In a two reactor lab-scale pilot plant facility, the objectives included maximising thermal dissolution of the coal in the presence of a hydrogen donor solvent in the first stage, subsequently promoting hydrogen saturation and hydrodesulphurization (HDS) performance in the second. The feed slurry consisted of high grade, pulverized bituminous coal on a moisture-free basis with a size fraction of < 100μm; and Tetralin mixed in 2:1 and 3:1 solvent/coal ratios. Magnetite (Fe3O4) at 0.25wt% of the dry coal feed was added for the catalysed runs. For both stages, hydrogen gas was used to maintain a system pressure of 100barg. In the first stage, temperatures of 250℃ and 300℃, reaction times of 30 and 60 minutes were investigated in an agitated batch reactor. The first stage liquid product was pumped into the second stage vertical reactor, which was designed to counter-currently contact the hydrogen rich gas stream and incoming liquid flow in the fixed catalyst bed. Two commercial hydrotreating catalysts; Cobalt-Molybdenum (CoMo) and Nickel-Molybdenum (NiMo); were compared in terms of their conversion, selectivity and HDS performance at temperatures 50℃ higher than the respective first stage tests. The catalysts were activated at 300°C with a hydrogen flowrate of approximately 10 ml/min prior to the testing. A gas-liquid separator at the outlet of the reactor ensured that the gas was exhausted to the online VARIOplus gas analyser. The liquid was collected and sampled for analysis using Gas Chromatography-Mass Spectrometry (GC-MS). Internal standard quantification methods for the sulphur content, the BTX (benzene, toluene, and xylene) and alkene quality; alkanes and polycyclic aromatic hydrocarbon (PAH) compounds in the liquid products were guided by ASTM standards of practice for hydrocarbon analysis. In the first stage, using a 2:1 solvent/coal ratio, an increased coal to liquid conversion was favoured by a lower operating temperature of 250℃, 60 minutes and a system catalysed by magnetite. Tetralin functioned effectively as the hydrogen donor solvent. A 3:1 ratio favoured increased concentrations of the long chain alkanes undecane and dodecane, unsaturated alkenes octene and nonene and PAH compounds such as indene. The second stage product distribution showed an increase in the BTX quality of the liquid product, branched chain alkanes and a reduction in the sulphur concentration. As an HDS performer and selectivity to the production of long and branched chain alkanes, NiMo performed better than CoMo. CoMo is selective to a higher concentration of cyclohexane. For 16 days on stream each, NiMo had a higher activity than CoMo. The potential to cover the demand for low–sulphur, crude diesel and solvents from the production of high value hydrocarbon liquid in the said process, is thus demonstrated.

Keywords: catalyst, coal, liquefaction, temperature-staged

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Authors: M. Soleimani, D. Cree, C. Chafe, L. Bates

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The accidental release of petroleum products into the environment could have harmful consequences to our ecosystem. Different techniques such as mechanical separation, membrane filtration, incineration, treatment processes using enzymes and dispersants, bioremediation, and sorption process using sorbents have been applied for oil spill remediation. Most of the techniques investigated are too costly or do not have high enough efficiency. This study was conducted to determine the sorption performance of hemp byproducts (cellulosic materials) in terms of sorption capacity and kinetics for hydrophobic and hydrophilic fluids. In this study, heavy oil, light oil, diesel fuel, and water/water vapor were used as sorbate fluids. Hemp stalk in different forms, including loose material (hammer milled (HM) and shredded (Sh) with low bulk densities) and densified forms (pellet form (P) and crumbled pellets (CP)) with high bulk densities, were used as sorbents. The sorption/retention tests were conducted according to ASTM 726 standard. For a quick-purpose application of the sorbents, the sorption tests were conducted for 15 min, and for an ideal sorption capacity of the materials, the tests were carried out for 24 h. During the test, the sorbent material was exposed to the fluid by immersion, followed by filtration through a stainless-steel wire screen. Water vapor adsorption was carried out in a controlled environment chamber with the capability of controlling relative humidity (RH) and temperature. To determine the kinetics of sorption for each fluid and sorbent, the retention capacity also was determined intervalley for up to 24 h. To analyze the kinetics of sorption, pseudo-first-order, pseudo-second order and intraparticle diffusion models were employed with the objective of minimal deviation of the experimental results from the models. The results indicated that HM and Sh materials had the highest sorption capacity for the hydrophobic fluids with approximately 6 times compared to P and CP materials. For example, average retention values of heavy oil on HM and Sh was 560% and 470% of the mass of the sorbents, respectively. Whereas, the retention of heavy oil on P and CP was up to 85% of the mass of the sorbents. This lower sorption capacity for P and CP can be due to the less exposed surface area of these materials and compacted voids or capillary tubes in the structures. For water uptake application, HM and Sh resulted in at least 40% higher sorption capacity compared to those obtained for P and CP. On average, the performance of sorbate uptake from high to low was as follows: water, heavy oil, light oil, diesel fuel. The kinetic analysis indicated that the second-pseudo order model can describe the sorption process of the oil and diesel better than other models. However, the kinetics of water absorption was better described by the pseudo-first-order model. Acetylation of HM materials could improve its oil and diesel sorption to some extent. Water vapor adsorption of hemp fiber was a function of temperature and RH, and among the models studied, the modified Oswin model was the best model in describing this phenomenon.

Keywords: environment, fiber, petroleum, sorption

Procedia PDF Downloads 106

Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

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The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

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Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

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Authors: Gadanya, A.M., Ponfa, S., Jibril, M.M., Abubakar, S. M.

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Background: Edible insects such as grasshopper are important sources of food for humans, and have been consumed as traditional foods by many indigenous communities especially in Africa, Asia, and Latin America. These communities have developed their skills and techniques in harvesting, preparing, consuming, and preserving edible insects, widely contributing to the role played by the use of insects in human nutrition. Aim/ objective: This study was aimed at determining the effect of insect enriched sprouted soyabean /millet based food on some gut health markers in albino rats. Methods. Four different formulations of Complementary foods (i.e Complementary Food B (CFB): sprouted millet (SM), Complementary Food C (CFC): sprouted soyabean (SSB), Complementary Food D (CFD): sprouted soybean and millet (SSBM) in a ratio of (50:50) and Complementary Food E (CFE): insect (grasshopper) enriched sprouted soybean and millet (SSBMI) in a ratio of (50:25:25)) were prepared. Proximate composition and short chain fatty acid contents were determined. Thirty albino rats were divided into5 groups of six rats each. Group 1(CDA) were fed with basal diet and served as a control group, while groups 2,3,4 and 5 were fed with the corresponding complimentary foods CFB, CFC, CFD and CFE respectively daily for four weeks. Concentrations of fecal protein, serum total carotenoids and nitric oxide were determined. DNA extraction for molecular isolation and characterization were carried out followed by PCR, the use of mega 11 software and NCBI blast for construction of the phylogenetic tree and organism identification respectively. Results: Significant increase (P<0.05) in percentage ash, fat, protein and moisture contents, as well as short chain fatty acid (acetate, butyrate and propionate) concentrations were recorded in the insect enriched sprouted composite food (CFE) when compared with the CFA, CFB, CFC and CFD composite food. Faecal protein, carotenoid and nitric oxide concentrations were significantly lower (P>0.05) in group 5 in comparison to groups 1to 4. Ruminococcus bromii and Bacteroidetes were molecularly isolated and characterized by 16s rRNA from the sprouted millet/sprouted soybean and the insect enriched sprouted soybean/sprouted millet based food respectively. The presence of these bacterial strains in the feaces of the treated rats is an indication that the gut of the treated rats is colonized by good gut bacteria, hence, an improved gut health. Conclusion: Insect enriched sprouted soya bean/sprouted millet based complementary diet showed a high composition of ash, fat, protein and fiber. Thus, could increase the availability of short chain fatty acids whose role to the host organism cannot be overemphasized. It was also found to have decrease the level of faecal protein, carotenoid and nitric oxide in the serum which is an indication of an improvement in the immune system function.

Keywords: gut-health, insect, millet, soybean, sprouted

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Authors: Annette Louise Dupont

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Background and Introduction: Broadly defined, hybridity is a condition of racial and cultural ‘cross-pollination’ which arises as a result of contact between colonized and colonizer. It remains a highly contested concept in postcolonial studies as it is implicitly underpinned by colonial notions of ‘racial purity.’ While some postcolonial scholars argue that individuals exercise significant agency in the construction of their hybrid subjectivities, others underscore associated experiences of exclusion, marginalization, and alienation. Kuwait and the Philippines are among the most disparate of contemporary postcolonial states. While oil resources transformed the former British Mandate of Kuwait into one of the world’s richest countries, enduring poverty in the former US colony of the Philippines drives a global diaspora which produces multiple Filipino hybridities. Although more Filipinos work in the Arabian Gulf than in any other region of the world, scholarly and literary accounts of their experiences of hybridization in this region are relatively scarce when compared to those set in North America, Australia, Asia, and Europe. Study Aims and Significance: This paper aims to address this existing lacuna by investigating hybridity and other postcolonial themes in a novel by a Kuwaiti author which vividly portrays the lives of immigrants and citizens in Kuwait and which gives a rare voice and insight into the struggles of an Arab-Filipino and European-Filipina. Specifically, this paper explores the relationships between colonial discourses of ‘black’ and ‘white’ and postcolonial discourses pertaining to ‘brown’ Filipinos and ‘brown’ Arabs, in order to assess their impacts on the protagonists’ hybrid subjectivities. Methodology: Foucault’s notions of discourse not only provide a conceptual basis for analyzing the colonial ideology of Orientalism, but his theories related to the social exclusion of the ‘mad’ also elucidate the mechanisms by which power can operate to marginalize, alienate and subjectify the Other, therefore a Foucauldian lens is applied to the analysis of postcolonial themes and hybrid subjectivities portrayed in the novel. Findings: The study finds that Kuwaiti and Filipino discursive practices mirror those of former white colonialists and colonized black laborers and that these discursive practices combine with a former British colonial system of foreign labor sponsorship to create a form of governmentality in Kuwait which is based on exclusion and control. The novel’s rich social description and the reflections of the key protagonist and narrator suggest that such fiction has a significant role to play in highlighting the historical and cultural specificities of experiences of postcolonial hybridity in under-researched geographic, economic, social, and political settings. Whereas hybridity can appear abstract in scholarly accounts, the significance of literary accounts in which the lived experiences of hybrid protagonists are anchored to specific historical periods, places and discourses, is that contextual particularities are neither obscured nor dehistoricized. Conclusions: The application of Foucauldian theorizations of discourse, disciplinary, and biopower to the analysis of this Kuwaiti literary text serves to extend an understanding of the effects of contextually-specific discourses on hybrid Filipino subjectivities, as well as a knowledge of prevailing social dynamics in a little-researched postcolonial Arabian Gulf state.

Keywords: Filipino, Foucault, hybridity, Kuwait

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Authors: Z. Karahaliloğlu, E. Yalçın, M. Demirbilek, E.B. Denkbaş

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Critical-sized bone defects caused by trauma, bone diseases, prosthetic implant revision or tumor excision cannot be repaired by physiological regenerative processes. Current orthopedic applications for critical-sized bone defects are to use autologous bone grafts, bone allografts, or synthetic graft materials. However, these strategies are unable to solve completely the problem, and motivate the development of novel effective biological scaffolds for tissue engineering applications and regenerative medicine applications. In particular, scaffolds combined with a variety of bio-agents as fundamental tools emerge to provide the regeneration of damaged bone tissues due to their ability to promote cell growth and function. In this study, a magnetic silk fibroin (SF) hydrogel scaffold was prepared by electrogelation process of the concentrated Bombxy mori silk fibroin (8 %wt) aqueous solution. For enhancement of osteoblast-like cells (SaOS-2) growth and adhesion, basal fibroblast growth factor (bFGF) were conjugated physically to the HSA-coated magnetic nanoparticles (Fe3O4) and magnetic SF e-gel scaffolds were prepared by incorporation of Fe3O4, HSA (human serum albumin)=Fe3O4 and HSA=Fe3O4-bFGF nanoparticles. HSA=Fe3O4, HSA=Fe3O4-bFGF loaded and bare SF e-gels scaffolds were characterized using scanning electron microscopy (SEM.) For cell studies, human osteoblast-like cell line (SaOS-2) was used and an MTT assay was used to assess the cytotoxicity of magnetic silk fibroin e-gel scaffolds and cell density on these surfaces. For the evaluation osteogenic activation, ALP (alkaline phosphatase), the amount of mineralized calcium, total protein and collagen were studied. Fe3O4 nanoparticles were successfully synthesized and bFGF was conjugated to HSA=Fe3O4 nanoparticles with %97.5 of binding yield which has a particle size of 71.52±2.3 nm. Electron microscopy images of the prepared HSA and bFGF incorporated SF e-gel scaffolds showed a 3D porous morphology. In terms of water uptake results, bFGF conjugated HSA=Fe3O4 nanoparticles has the best water absorbability behavior among all groups. In the in-vitro cell culture studies realized using SaOS-2 cell line, the coating of Fe3O4 nanoparticles surface with a protein enhance the cell viability and HSA coating and bFGF conjugation, the both have an inductive effect in the cell proliferation. One of the markers of bone formation and osteoblast differentiation, according to the ALP activity and total protein results, HSA=Fe3O4-bFGF loaded SF e-gels had significantly enhanced ALP activity. Osteoblast cultured HSA=Fe3O4-bFGF loaded SF e-gels deposited more calcium compared with SF e-gel. The proposed magnetic scaffolds seem to be promising for bone tissue regeneration and used in future work for various applications.

Keywords: basic fibroblast growth factor (bFGF), e-gel, iron oxide nanoparticles, silk fibroin

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Authors: Ryan A. Black, Stacey A. McCaffrey

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Over the past few decades, great strides have been made towards improving the science in the measurement of psychological constructs. Item Response Theory (IRT) has been the foundation upon which statistical models have been derived to increase both precision and accuracy in psychological measurement. These models are now being used widely to develop and refine tests intended to measure an individual's level of academic achievement, aptitude, and intelligence. Recently, the field of clinical psychology has adopted IRT models to measure psychopathological phenomena such as depression, anxiety, and addiction. Because advances in IRT measurement models are being made so rapidly across various fields, it has become quite challenging for psychologists and other behavioral scientists to keep abreast of the most recent developments, much less learn how to employ and decide which models are the most appropriate to use in their line of work. In the same vein, IRT measurement models vary greatly in complexity in several interrelated ways including but not limited to the number of item-specific parameters estimated in a given model, the function which links the expected response and the predictor, response option formats, as well as dimensionality. As a result, inferior methods (a.k.a. Classical Test Theory methods) continue to be employed in efforts to measure psychological constructs, despite evidence showing that IRT methods yield more precise and accurate measurement. To increase the use of IRT methods, this study endeavors to provide a comprehensive overview of binary IRT models; that is, measurement models employed on test data consisting of binary response options (e.g., correct/incorrect, true/false, agree/disagree). Specifically, this study will cover the most basic binary IRT model, known as the 1-parameter logistic (1-PL) model dating back to over 50 years ago, up until the most recent complex, 4-parameter logistic (4-PL) model. Binary IRT models will be defined mathematically and the interpretation of each parameter will be provided. Next, all four binary IRT models will be employed on two sets of data: 1. Simulated data of N=500,000 subjects who responded to four dichotomous items and 2. A pilot analysis of real-world data collected from a sample of approximately 770 subjects who responded to four self-report dichotomous items pertaining to emotional consequences to alcohol use. Real-world data were based on responses collected on items administered to subjects as part of a scale-development study (NIDA Grant No. R44 DA023322). IRT analyses conducted on both the simulated data and analyses of real-world pilot will provide a clear demonstration of how to construct, evaluate, and compare binary IRT measurement models. All analyses will be performed using the new IRT procedure in SAS 9.4. SAS code to generate simulated data and analyses will be available upon request to allow for replication of results.

Keywords: instrument development, item response theory, latent trait theory, psychometrics

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Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Julia Huggins, Fabien Munyaneza

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Background: Partners In Health – Malawi introduced one of Operational Researches called Primary Health Care (PHC) Surveys in 2020, which seeks to assess progress of delivery of care in the district. The study consists of 5 long surveys, namely; Facility assessment, General Patient, Provider, Sick Child, Antenatal Care (ANC), primarily conducted in 4 health facilities in Neno district. These facilities include Neno district hospital, Dambe health centre, Chifunga and Matope. Usually, these annual surveys are conducted from January, and the target is to present final report by June. Once data is collected and analyzed, there are a series of reviews that take place before reaching final report. In the first place, the manual process took over 9 months to present final report. Initial findings reported about 76.9% of the data that added up when cross-checked with paper-based sources. Purpose: The aim of this approach is to run away from manually pulling the data, do fresh analysis, and reporting often associated not only with delays in reporting inconsistencies but also with poor quality of data if not done carefully. This automation approach was meant to utilize features of new technologies to create visualizations, reports, and dashboards in Power BI that are directly fished from the data source – CommCare hence only require a single click of a ‘refresh’ button to have the updated information populated in visualizations, reports, and dashboards at once. Methodology: We transformed paper-based questionnaires into electronic using CommCare mobile application. We further connected CommCare Mobile App directly to Power BI using Application Program Interface (API) connection as data pipeline. This provided chance to create visualizations, reports, and dashboards in Power BI. Contrary to the process of manually collecting data in paper-based questionnaires, entering them in ordinary spreadsheets, and conducting analysis every time when preparing for reporting, the team utilized CommCare and Microsoft Power BI technologies. We utilized validations and logics in CommCare to capture data with less errors. We utilized Power BI features to host the reports online by publishing them as cloud-computing process. We switched from sharing ordinary report files to sharing the link to potential recipients hence giving them freedom to dig deep into extra findings within Power BI dashboards and also freedom to export to any formats of their choice. Results: This data automation approach reduced research timelines from the initial 9 months’ duration to 5. It also improved the quality of the data findings from the original 76.9% to 98.9%. This brought confidence to draw conclusions from the findings that help in decision-making and gave opportunities for further researches. Conclusion: These results suggest that automating the research data process has the potential of reducing overall amount of time spent and improving the quality of the data. On this basis, the concept of data automation should be taken into serious consideration when conducting operational research for efficiency and decision-making.

Keywords: reporting, decision-making, power BI, commcare, data automation, visualizations, dashboards

Procedia PDF Downloads 86

Authors: Valentina Bonetti

Abstract:

Exergy analysis successfully helps optimizing processes in various sectors. In the built environment, a second-law approach can enhance potential interactions between constructions and their surrounding environment and minimise fossil fuel requirements. Despite the research done in this field in the last decades, practical applications are hard to encounter, and few integrated exergy simulators are available for building designers. Undoubtedly, an obstacle for the diffusion of exergy methods is the strong dependency of results on the definition of its 'reference state', a highly controversial issue. Since exergy is the combination of energy and entropy by means of a reference state (also called "reference environment", or "dead state"), the reference choice is crucial. Compared to other classical applications, buildings present two challenging elements: They operate very near to the reference state, which means that small variations have relevant impacts, and their behaviour is dynamical in nature. Not surprisingly then, the reference state definition for the built environment is still debated, especially in the case of dynamic assessments. Among the several characteristics that need to be defined, a crucial decision for a dynamic analysis is between a fixed reference environment (constant in time) and a variable state, which fluctuations follow the local climate. Even if the latter selection is prevailing in research, and recommended by recent and widely-diffused guidelines, the fixed reference has been analytically demonstrated as the only choice which defines exergy as a proper function of the state in a fluctuating environment. This study investigates the impact of that crucial choice: Fixed or variable reference. The basic element of the building energy chain, the envelope, is chosen as the object of investigation as common to any building analysis. Exergy fluctuations in the building envelope of a case study (a typical house located in a Mediterranean climate) are confronted for each time-step of a significant summer day, when the building behaviour is highly dynamical. Exergy efficiencies and fluxes are not familiar numbers, and thus, the more easy-to-imagine concept of exergy storage is used to summarize the results. Trends obtained with a fixed and a variable reference (outside air) are compared, and their meaning is discussed under the light of the underpinning dynamical energy analysis. As a conclusion, a fixed reference state is considered the best choice for dynamic exergy analysis. Even if the fixed reference is generally only contemplated as a simpler selection, and the variable state is often stated as more accurate without explicit justifications, the analytical considerations supporting the adoption of a fixed reference are confirmed by the usefulness and clarity of interpretation of its results. Further discussion is needed to address the conflict between the evidence supporting a fixed reference state and the wide adoption of a fluctuating one. A more robust theoretical framework, including selection criteria of the reference state for dynamical simulations, could push the development of integrated dynamic tools and thus spread exergy analysis for the built environment across the common practice.

Keywords: exergy, reference state, dynamic, building

Procedia PDF Downloads 203

Authors: Elena Maria Scalisi

Abstract:

Currently, photodegradation by nanoparticles (NPs) is a common solution for wastewater treatment. Nanoparticles are efficient for removing organic and inorganic pollutants, heavy metals from wastewater and killing microorganisms through environmentally friendly. In this context, the major representative of photocatalytic technology for industrial wastewater treatment are TiO₂ nanoparticles (TiO₂-NPs). TiO₂-NPs have a strong catalytic activity that depends to their physicochemical properties. Thanks to their small size (between 1-100 nm), nanoparticles occupy less volume, then their surface area increases. The increase in the surface-to-volume ratio results in the increase of the particle surface energy, which improve their reactivity potential. However, these unique properties represent risks to the ecosystems and organisms when unintentionally TiO₂-NPs are release into the environment and absorbed by living organisms. Several studies confirm that there is a high level of interest concerning the safety of TiO₂-NPs in the aquatic environment, furthermore, ecotoxicological tools are useful to correctly evaluate their toxicity. In the current study, we aimed to characterize potential toxic effects of TiO₂-NP suspension to zebrafish during embryo-larval stages to evaluate parameters such as survival rates, malformation, hatching, the overall length of the larvae heartbeat, and biochemical biomarkers that reflect the acute toxicity and sublethal effects of TiO₂-NPs. Zebrafish embryos were exposed to titanium dioxide nanoparticles (TiO₂-NPs at 1mg/L, 2mg/L, and 4mg/L) from fertilization to the free swimming stage (144hpf). Every day, we recorded the toxicological endpoints, moreover, immunohistochemical analysis has been performed at the end of the exposure. In particular, we have evaluate the expression of the following biomarkers: Heat Shock Protein 70 (HSP70), Poly ADP-Ribose Polymerase-1 (PARP-1), Metallothioneins (MTs). Our results have shown that hatch ability, survival, and malformation rate were not affected by TiO₂ NPs at these exposure levels. However, TiO₂-NPs caused an increase of heartbeat and reduction of body length; at the same time, TiO₂-NPs have inducted the production of ROS and the expression of oxidative stress biomarkers HSP70 and PARP-1. Hight positivity for PARP-1 at all concentration tested was observed. As regards MT, positivity was found in the expression of this biomarker in the whole body of the embryo, with the exception of the end of the tail. Metallothioneins (MT) are biomarkers widely used in environmental monitoring programs for aquatic creatures. At the light of our results i.e. no death until the end of the experiment (144hpf), no malformation and expression of the biomarkers mentioned, it is evident that zebrafish larvae with their natural detoxification pathways are able to resist the presence of toxic substances and then they can tolerate the presence of metal concentrations. However, an excessive oxidative state can compromise cell function, therefore the uncontrolled release of nanoparticles into the environment is severe and must be constantly monitored.

Keywords: nanoparticles, embryo zebrafish, HSP70, PARP-1

Procedia PDF Downloads 115

Authors: A. Newman-Tancredi, R. Depoortère, P. Gruca, E. Litwa, M. Lason, M. Papp

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The N-methyl-D-aspartic acid (NMDA) receptor antagonist, ketamine, can elicit rapid-acting antidepressant (RAAD) effects in treatment-resistant patients, but it requires parenteral co-administration with a classical antidepressant under medical supervision. In addition, ketamine can also produce serious side effects that limit its long-term use, and there is much interest in identifying RAADs based on ketamine’s mechanism of action but with safer profiles. Ketamine elicits GABAergic interneuron inhibition, glutamatergic neuron stimulation, and, notably, activation of serotonin 5-HT1A receptors in the prefrontal cortex (PFC). Direct activation of the latter receptor subpopulation with selective ‘biased agonists’ may therefore be a promising strategy to identify novel RAADs and, consistent with this hypothesis, the prototypical cortical biased agonist, NLX-101, exhibited robust RAAD-like activity in the chronic mild stress model of depression (CMS). The present study compared the effects of a novel, selective 5-HT1A receptor-biased agonist, NLX-204, with those of ketamine and NLX-101. Materials and methods: CMS procedure was conducted on Wistar rats; drugs were administered either intraperitoneally (i.p.) or by bilateral intracortical microinjection. Ketamine: 10 mg/kg i.p. or 10 µg/side in PFC; NLX-204 and NLX-101: 0.08 and 0.16 mg/kg i.p. or 16 µg/side in PFC. In addition, interaction studies were carried out with systemic NLX-204 or NLX-101 (each at 0.16 mg/kg i.p.) in combination with intracortical WAY-100635 (selective 5-HT1A receptor antagonist; 2 µg/side) or muscimol (GABA-A receptor agonist, 12.5 ng/side). Anhedonia was assessed by CMS-induced decrease in sucrose solution consumption; anxiety-like behavior was assessed using the Elevated Plus Maze (EPM), and cognitive impairment was assessed by the Novel Object Recognition (NOR) test. Results: A single administration of NLX-204 was sufficient to reverse the CMS-induced deficit in sucrose consumption, similarly to ketamine and NLX-101. NLX-204 also reduced CMS-induced anxiety in the EPM and abolished CMS-induced NOR deficits. These effects were maintained (EPM and NOR) or enhanced (sucrose consumption) over a subsequent 2-week period of treatment. The anti-anhedonic response of the drugs was also maintained for several weeks Following treatment discontinuation, suggesting that they had sustained effects on neuronal networks. A single PFC administration of NLX-204 reversed deficient sucrose consumption, similarly to ketamine and NLX-101. Moreover, the anti-anhedonic activities of systemic NLX-204 and NLX 101 were abolished by coadministration with intracortical WAY-100635 or muscimol. Conclusions: (i) The antidepressant-like activity of NLX-204 in the rat CMS model was as rapid as that of ketamine or NLX-101, supporting targeting cortical 5-HT1A receptors with selective, biased agonists to achieve RAAD effects. (ii)The anti-anhedonic activity of systemic NLX-204 was mimicked by local administration of the compound in the PFC, confirming the involvement of cortical circuits in its RAAD-like effects. (iii) Notably, the effects of systemic NLX-204 and NLX-101 were abolished by PFC administration of muscimol, indicating that they act by (indirectly) eliciting a reduction in cortical GABAergic neurotransmission. This is consistent with ketamine’s mechanism of action and suggests that there are converging NMDA and 5-HT1A receptor signaling cascades in PFC underlying the RAAD-like activities of ketamine and NLX-204. Acknowledgements: The study was financially supported by NCN grant no. 2019/35/B/NZ7/00787.

Keywords: depression, ketamine, serotonin, 5-HT1A receptor, chronic mild stress

Procedia PDF Downloads 79

Authors: Kumalbeo Paul Kamani

Abstract:

Marketing plays a very important role in the success of any firm since it represents the means through which a firm can reach its customers and also promotes its products and services. In fact, marketing aids the firm in identifying customers who the business can competitively serve, and tailoring product offerings, prices, distribution, promotional efforts, and services towards those customers. Unfortunately, in many firms, marketing has been reduced to merely advertisement. For effective marketing, firms must go beyond this often-limited function of advertisement. In the fashion industry in particular, marketing faces challenges due to its peculiar characteristics. Previous research for instance affirms the idiosyncrasy and peculiarities that differentiate the fashion industry from other industrial areas. It has been documented that the fashion industry is characterized seasonal intensity, short product life cycles, the difficulty of competitive differentiation, and long time for companies to reach financial stability. These factors are noted to pose obstacles to the fashion entrepreneur’s endeavours and can be the reasons that explain their low survival rates. In recent times, the fashion industry has been described as a market that is accessible market, has low entry barriers, both in terms of needed capital and skills which have all accounted for the burgeoning nature of startups. Yet as already stated, marketing is particularly challenging in the industry. In particular, areas such as marketing, branding, growth, project planning, financial and relationship management might represent challenges for the fashion entrepreneur but that have not been properly addressed by previous research. It is therefore important to assess marketing strategies of fashion firms and the factors influencing their success. This study generally sought to examine marketing strategies of fashion dealers in Ghana and their critical success factors. The study employed the quantitative survey research approach. A total of 120 fashion dealers were sampled. Questionnaires were used as instrument of data collection. Data collected was analysed using quantitative techniques including descriptive statistics and Relative Importance Index. The study revealed that the marketing strategies used by fashion apparels are text messages using mobile phones, referrals, social media marketing, and direct marketing. Results again show that the factors influencing fashion marketing effectiveness are strategic management, marketing mix (product, price, promotion etc), branding and business development. Policy implications are finally outlined. The study recommends among others that there is a need for the top management executive to craft and adopt marketing strategies that enable that are compatible with the fashion trends and the needs of the customers. This will improve customer satisfaction and hence boost market penetration. The study further recommends that the fashion industry in Ghana should seek to ensure that fashion apparels accommodate the diversity and the cultural setting of different customers to meet their unique needs.

Keywords: marketing, fashion, industry, success factors

Procedia PDF Downloads 15