Search results for: water resources yield and planning model

Authors: Nikolaos Mamalis

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The work of the eminent architect and composer has undoubtedly been influenced both by his architecture and collaboration with Le Corbusier and by the conquests of the musical avant-garde of the 20th century (Schoenberg, Messian, Bartock, electroacoustic music). It is known that the golden mean and the Fibonacci sequence played a momentous role in the Architectural Avant-garde (Modulor) and expanded on musical pursuits. Especially in the 50s (serialism), it was a structural tool for composition. Xenakis' architectural and musical work (Sacrifice, Metastasis, Rebonds, etc.) received the influence of the Golden Section, as has been repeatedly demonstrated. However, the idea of this retrospective sequence and the reflection raised by the search for new proportions, both in the architectural and the musical work of Xenakis, was not limited to constituting a step, a workable formula that acted unifyingly with regard to the other parameters of the musical work, or as an aesthetic model that makes sense - philosophically and poetically - an anthropocentric dimension as in other composers (see Luigi Nono) ̇ triggered a qualitative leap, an opening of the composer to the assimilation of mathematical concepts and scientific types in music and the consolidation of new sound horizons of stochastic music.

Keywords: golden ratio, music, space, stochastic music

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Authors: Paulomi Polly Burey, Mark Lynch

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It has been shown that laboratory activities can help cement understanding of theoretical concepts, but it is difficult to deliver such an activity to an online cohort and issues such as occupational health and safety in the students’ learning environment need to be considered. Chemistry, in particular, is one of the sciences where practical experience is beneficial for learning, however typical university experiments may not be suitable for the learning environment of a distance learner. Food provides an ideal medium for demonstrating chemical concepts, and along with a few simple physical and virtual tools provided by educators, analytical chemistry can be experienced by distance learners. Food chemistry experiments were designed to be carried out in a home-based environment that 1) Had sufficient scientific rigour and skill-building to reinforce theoretical concepts; 2) Were safe for use at home by university students and 3) Had the potential to enhance student learning by linking simple hands-on laboratory activities with high-level virtual science. Two main components of the resources were developed, a home laboratory experiment component, and a virtual laboratory component. For the home laboratory component, students were provided with laboratory kits, as well as a list of supplementary inexpensive chemical items that they could purchase from hardware stores and supermarkets. The experiments used were typical proximate analyses of food, as well as experiments focused on techniques such as spectrophotometry and chromatography. Written instructions for each experiment coupled with video laboratory demonstrations were used to train students on appropriate laboratory technique. Data that students collected in their home laboratory environment was collated across the class through shared documents, so that the group could carry out statistical analysis and experience a full laboratory experience from their own home. For the virtual laboratory component, students were able to view a laboratory safety induction and advised on good characteristics of a home laboratory space prior to carrying out their experiments. Following on from this activity, students observed laboratory demonstrations of the experimental series they would carry out in their learning environment. Finally, students were embedded in a virtual laboratory environment to experience complex chemical analyses with equipment that would be too costly and sensitive to be housed in their learning environment. To investigate the impact of the intervention, students were surveyed before and after the laboratory series to evaluate engagement and satisfaction with the course. Students were also assessed on their understanding of theoretical chemical concepts before and after the laboratory series to determine the impact on their learning. At the end of the intervention, focus groups were run to determine which aspects helped and hindered learning. It was found that the physical experiments helped students to understand laboratory technique, as well as methodology interpretation, particularly if they had not been in such a laboratory environment before. The virtual learning environment aided learning as it could be utilized for longer than a typical physical laboratory class, thus allowing further time on understanding techniques.

Keywords: chemistry, food science, future pedagogy, STEM education

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Authors: Yagya Raj Pandeya, Joonwhoan Lee

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The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

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Authors: E. L. Albuquerque, U. L. Fulco, G. S. Ourique

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The focus of this work is on the numerical investigation of the charge transport properties of the de novo-designed alpha3 polypeptide, as well as in its variants, all of them probed by gene engineering. The theoretical framework makes use of a tight-binding model Hamiltonian, together with ab-initio calculations within quantum chemistry simulation. The alpha3 polypeptide is a 21-residue with three repeats of the seven-residue amino acid sequence Leu-Glu-Thr-Leu-Ala-Lys-Ala, forming an alpha–helical bundle structure. Its variants are obtained by Ala→Gln substitution at the e (5th) and g (7th) position, respectively, of the alpha3 polypeptide amino acid sequence. Using transmission electron microscopy and atomic force microscopy, it was observed that the alpha3 polypeptide and one of its variant do have the ability to form fibrous assemblies, while the other does not. Our main aim is to investigate whether or not the biased alpha3 polypeptide and its variants can be also identified by quantum charge transport measurements through current-voltage (IxV) curves as a pattern to characterize their fibrous assemblies. It was observed that each peptide has a characteristic current pattern, which may be distinguished by charge transport measurements, suggesting that it might be a useful tool for the development of biosensors.

Keywords: charge transport properties, electronic transmittance, current-voltage characteristics, biological sensor

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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

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Authors: Morteza Ghorbani, Reza Ghorbani

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Cavitation phenomenon has attracted much attention in the mechanical and biomedical technologies. Despite the simplicity and mostly low cost of the devices generating cavitation bubbles, the physics behind the generation and collapse of these bubbles particularly in micro/nano scale has still not well understood. In the chemical industry, micro/nano bubble generation is expected to be applicable to the development of porous materials such as microcellular plastic foams. Moreover, it was demonstrated that the presence of micro/nano bubbles on a surface reduced the adsorption of proteins. Thus, the micro/nano bubbles could act as antifouling agents. Micro and nano bubbles were also employed in water purification, froth floatation, even in sonofusion, which was not completely validated. Small bubbles could also be generated using micro scale hydrodynamic cavitation. In this study, compared to the studies available in the literature, we are proposing a novel approach in micro scale utilizing the energy produced during the interaction of the spray affected by the hydrodynamic cavitating flow and a thin aluminum plate. With a decrease in the size, cavitation effects become significant. It is clearly shown that with the aid of hydrodynamic cavitation generated inside the micro/mini-channels in addition to the optimization of the distance between the tip of the microchannel configuration and the solid surface, surface temperatures can be increased up to 50C under the conditions of this study. The temperature rise on the surfaces near the collapsing small bubbles was exploited for energy harvesting in small scale, in such a way that miniature, cost-effective, and environmentally friendly energy-harvesting devices can be developed. Such devices will not require any external power and moving parts in contrast to common energy-harvesting devices, such as those involving piezoelectric materials and micro engine. Energy harvesting from thermal energy has been widely exploited to achieve energy savings and clean technologies. We are proposing a cost effective and environmentally friendly solution for the growing individual energy needs thanks to the energy application of cavitating flows. The necessary power for consumer devices, such as cell phones and laptops, can be provided using this approach. Thus, this approach has the potential for solving personal energy needs in an inexpensive and environmentally friendly manner and can trigger a shift of paradigm in energy harvesting.

Keywords: cavitation, energy, harvesting, micro scale

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Authors: Yuzuru Mitsui, Takashi Ikegami

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The exponents of Taylor’s law in deterministic chaotic systems are computed, and their meanings are intensively discussed. Taylor’s law is the scaling relationship between the mean and variance (in both space and time) of population abundance, and this law is known to hold in a variety of ecological time series. The exponents found in the temporal Taylor’s law are different from those of the spatial Taylor’s law. The temporal Taylor’s law is calculated on the time series from the same locations (or the same initial states) of different temporal phases. However, with the spatial Taylor’s law, the mean and variance are calculated from the same temporal phase sampled from different places. Most previous studies were done with stochastic models, but we computed the temporal and spatial Taylor’s law in deterministic systems. The temporal Taylor’s law evaluated using the same initial state, and the spatial Taylor’s law was evaluated using the ensemble average and variance. There were two main discoveries from this work. First, it is often stated that deterministic systems tend to have the value two for Taylor’s exponent. However, most of the calculated exponents here were not two. Second, we investigated the relationships between chaotic features measured by the Lyapunov exponent, the correlation dimension, and other indexes with Taylor’s exponents. No strong correlations were found; however, there is some relationship in the same model, but with different parameter values, and we will discuss the meaning of those results at the end of this paper.

Keywords: chaos, density effect, population dynamics, Taylor’s law

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Authors: Xiao-Li Liu, Ling-Yun Zhao, Xing-Jie Liang, Hai-Ming Fan

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Owing to their unique properties, magnetic nanoparticles have been used as diagnostic and therapeutic agents for biomedical applications. Highly monodispersed magnetic nanoparticles with controlled particle size and surface coating have been successfully synthesized as a model system to investigate the effect of surface coating on the T2 relaxivity and specific absorption rate (SAR) under an alternating magnetic field, respectively. Amongst, by using mPEG-g-PEI to solubilize oleic-acid capped 6 nm magnetic nanoparticles, the T2 relaxivity could be significantly increased by up to 4-fold as compared to PEG coated nanoparticles. Moreover, it largely enhances the cell uptake with a T2 relaxivity of 92.6 mM-1s-1 for in vitro cell MRI. As for hyperthermia agent, SAR value increase with the decreased thickness of PEG surface coating. By elaborate optimization of surface coating and particle size, a significant increase of SAR (up to 74%) could be achieved with a minimal variation on the saturation magnetization (<5%). The 19 nm magnetic nanoparticles with 2000 Da PEG exhibited the highest SAR of 930 W•g-1 among the samples, which can be maintained in various simulated physiological conditions. This systematic work provides a general strategy for the optimization of surface coating of magnetic core for high performance MRI contrast agent and hyperthermia agent.

Keywords: magnetic nanoparticles, magnetic hyperthermia, magnetic resonance imaging, surface modification

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Authors: M. Osibemhe, I. O. Onoagbe

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Diabetes mellitus is a common disease that has no known cure. The available orthodox drugs used for its management have one or more disadvantages. This study investigated the potency of aqueous and ethanol extracts of Strophanthus hispidus (SH) stem bark in the management of diabetes mellitus. Glucose concentration and lipid profile parameters of normal and streptozotocin-induced diabetic rats were monitored for 12weeks. Diabetes mellitus was induced by intraperitoneal injection of streptozotocin (55 mg/kg). Male rats (wistar strain) numbering 30 were randomly selected into six groups of five rats each. Groups 1 and 6 served as normal and diabetic control respectively and received distilled water for 12weeks. Groups 2 and 3 were normal rats treated orally with the aid of a gavage, 250 mg/kg of aqueous and ethanol extracts respectively for 12weeks. Groups 4 and 5 were diabetic rats and were treated with the respective dose of aqueous and ethanol extracts for the same period. A significant (P˂0.05) progressive decrease in blood glucose concentrations of both normal and diabetic rats treated with the extracts were observed from the 2nd to 12th weeks when compared with the respective controls. No significant (P˃0.05) effects were observed in the basal values of both normal and diabetic rats. Administration of both extracts of SH to diabetic rats significantly (P˂0.05) lowered the concentrations of Total cholesterol, TG, and LDL, whereas it increases the concentration of HDL when compared with diabetic control. The concentrations of total cholesterol and LDL in normal rats treated with SH were also reduced when compared with normal control whereas SH had no significant (P˃0.05) effect on HDL. However, TG level of normal control was significantly (P˂0.05) lower than normal rats treated with both extracts. A progressive increase in weight of normal and diabetic rats treated with the extracts was observed on the 2nd – 12th weeks of administration, whereas diabetic control showed a progressive decrease in weight. The findings from this study indicated that SH has hypoglycemic and anti-lipidemic properties as well as anti-diabetic potentials. It also showed that ethanol extract had greater glucose lowering effect. Hence, SH may be considered as a potent anti-diabetic plant and could be used as alternative drug for the management of diabetes mellitus.

Keywords: concentration, ethanol extract, hypoglycemic, total cholesterol

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Authors: T. Y. Liu, C. H. Lin, Y. M. Ferng

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Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyse the flow field and pressure distributions of the wing blades. Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm. Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyse the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: horizontal axis wind turbine, turbulence model, noise, fluid dynamics

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Authors: Franca De Sarno, Alfonso Maria Ponsiglione, Enza Torino

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Recent advances in diagnostic imaging technology have significantly contributed to a better understanding of specific changes associated with diseases progression. Among different imaging modalities, Magnetic Resonance Imaging (MRI) represents a noninvasive medical diagnostic technique, which shows low sensitivity and long acquisition time and it can discriminate between healthy and diseased tissues by providing 3D data. In order to improve the enhancement of MRI signals, some imaging exams require intravenous administration of contrast agents (CAs). Recently, emerging research reports a progressive deposition of these drugs, in particular, gadolinium-based contrast agents (GBCAs), in the body many years after multiple MRI scans. These discoveries confirm the need to have a biocompatible system able to boost a clinical relevant Gd-chelate. To this aim, several approaches based on engineered nanostructures have been proposed to overcome the common limitations of conventional CAs, such as the insufficient signal-to-noise ratios due to relaxivity and poor safety profile. In particular, nanocarriers, labeling or loading with CAs, capable of carrying high payloads of CAs have been developed. Currently, there’s no a comprehensive understanding of the thermodynamic contributions enable of boosting the efficacy of conventional CAs by using biopolymers matrix. Thus, considering the importance of MRI in diagnosing diseases, here it is reported a successful example of the next generation of these drugs where the commercial gadolinium chelate is incorporate into a biopolymer nanostructure, formed by cross-linked hyaluronic acid (HA), with improved relaxation properties. In addition, they are highlighted the basic principles ruling biopolymer-CA interactions in the perspective of their influence on the relaxometric properties of the CA by adopting a multidisciplinary experimental approach. On the basis of these discoveries, it is clear that the main point consists in increasing the rigidification of readily-available Gd-CAs within the biopolymer matrix by controlling the water dynamics, the physicochemical interactions, and the polymer conformations. In the end, the acquired knowledge about polymer-CA systems has been applied to develop of Gd-based HA nanoparticles with enhanced relaxometric properties.

Keywords: biopolymers, MRI, nanoparticles, contrast agent

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Authors: Zahid Khalil, Saad Ul Haque, Asif Khan

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Decision making about identifying suitable sites for any project by considering different parameters is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30-meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pairwise comparison method, also known as Analytical Hierarchy Process (AHP) is taken into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision-making about suitable sites analysis for small dams using geospatial data with minimal amount of ground data. This suitability maps can be helpful for water resource management organizations in determination of feasible rainwater harvesting structures (RWH).

Keywords: Remote sensing, GIS, AHP, RWH

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Authors: Jiwoo Park, Junseok Yoon, Jeong Kim, Beomsoo Kang

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Multi-Point Stretch Forming (MPSF) process is suitable for flexible manufacturing, and it has several advantages including that it could be applied to various forming such as sheet metal forming, single curved surface forming and double curved one. In this study, a systematic numerical simulation was carried out for atypical double curved surface forming using the multiple die stretch forming process. In this simulation, urethane pads were defined based on hyper-elastic material model as a cushion for the smooth forming surface. The deformation behaviour on elastic recovery was also investigated to consider the exact result after the last forming process, and then the experiment was also carried out to confirm the formability of this forming process. By comparing the simulation and experiment results, the suitability of the multiple die stretch forming process for the atypical double curved surface was verified. Consequently, it is confirmed that the multi-point stretch forming process has the capability and feasibility of being used to manufacture the double curved surfaces of sheet metal.

Keywords: multi-point stretch forming, double curved surface, numerical simulation, manufacturing

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Authors: Karolina Wieczorek, Zofia Przypaśniak

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Climate change is a rapidly growing threat to global health, and part of the responsibility to combat it lies within the healthcare sector itself, including adequate education of future medical professionals. To mitigate the consequences, the General Medical Council (GMC) has equipped medical schools with a list of outcomes regarding sustainability teaching. Students are expected to analyze the impact of the healthcare sector’s emissions on climate change. The delivery of the related teaching content is, however, often inadequate and insufficient time is devoted for exploration of the topics. Teaching curricula lack in-depth exploration of the learning objectives. This study aims to assess the extent and characteristics of climate change and sustainability subjects teaching in the curriculum of a chosen UK medical school (Barts and The London School of Medicine and Dentistry). It compares the data to the national average scores from the Climate Change and Sustainability Teaching (C.A.S.T.) in Medical Education Audit to draw conclusions about teaching on a regional level. This is a single-center audit of the timetabled sessions of teaching in the medical course. The study looked at the academic year 2020/2021 which included a review of all non-elective, core curriculum teaching materials including tutorials, lectures, written resources, and assignments in all five years of the undergraduate and graduate degrees, focusing only on mandatory teaching attended by all students (excluding elective modules). The topics covered were crosschecked with GMC Outcomes for graduates: “Educating for Sustainable Healthcare – Priority Learning Outcomes” as gold standard to look for coverage of the outcomes and gaps in teaching. Quantitative data was collected in form of time allocated for teaching as proxy of time spent per individual outcomes. The data was collected independently by two students (KW and ZP) who have received prior training and assessed two separate data sets to increase interrater reliability. In terms of coverage of learning outcomes, 12 out of 13 were taught (with the national average being 9.7). The school ranked sixth in the UK for time spent per topic and second in terms of overall coverage, meaning the school has a broad range of topics taught with some being explored in more detail than others. For the first outcome 4 out of 4 objectives covered (average 3.5) with 47 minutes spent per outcome (average 84 min), for the second objective 5 out of 5 covered (average 3.5) with 46 minutes spent (average 20), for the third 3 out of 4 (average 2.5) with 10 mins pent (average 19 min). A disproportionately large amount of time is spent delivering teaching regarding air pollution (respiratory illnesses), which resulted in the topic of sustainability in other specialties being excluded from teaching (musculoskeletal, ophthalmology, pediatrics, renal). Conclusions: Currently, there is no coherent strategy on national teaching of climate change topics and as a result an unstandardized amount of time spent on teaching and coverage of objectives can be observed.

Keywords: audit, climate change, sustainability, education

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Kadri Koçer, Sezer Kefeli

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This paper proposes a comparison of hydrodynamic performance and stability characteristic for an underwater vehicle which has two type of tail design, namely X and +tail-body configurations. The effects of these configurations on the underwater vehicle’s hydrodynamic performance and maneuvering characteristic will be investigated comprehensively. Hydrodynamic damping coefficients for modeling the motion of the underwater vehicles will be predicted. Additionally, forces and moments due to control surfaces will be compared using computational fluid dynamics methods. In the aviation, the X tail-body configuration is widely used for high maneuverability requirements. However, in the underwater, the + tail-body configuration is more commonly used than the X tail-body configuration for its stability characteristics. Thus it is important to see the effect and differences of the tail designs in the underwater world. For CFD analysis, the incompressible, three-dimensional, and steady Navier-Stokes equations will be used to simulate the flows. Also, k-ε Realizable turbulence model with enhanced wall treatment will be taken. Numerical results is verified with experimental results for verification. The overall goal of this study is to present the advantages and disadvantages of hydrodynamic performance and stability characteristic for X and + tail-body configurations of the underwater vehicle.

Keywords: maneuverability, stability, CFD, tail configuration, hydrodynamic design

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Authors: Ismail S. Bostanci, Ebru Akkaya

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Microalgae-derived biodiesel, fertilizer or industrial chemicals' production with wastewater has great potential. Especially water from a municipal wastewater treatment plant is a very important nutrient source for biofuel production. Microalgae biomass production in open ponds system is lower cost culture systems. There are many hurdles for commercial algal biomass production in large scale. One of the important technical bottlenecks for microalgae production in open system is culture contamination. The algae culture contaminants can generally be described as invading organisms which could cause pond crash. These invading organisms can be competitors, parasites, and predators. Contamination is unavoidable in open systems. Potential contaminant organisms are already inoculated if wastewater is utilized for algal biomass cultivation. Especially, it is important to control contaminants to retain in acceptable level in order to reach true potential of algal biofuel production. There are several contamination management methods in algae industry, ranging from mechanical, chemical, biological and growth condition change applications. However, none of them are accepted as a suitable contamination control method. This experiment describes an innovative contamination control method, 'Recirculated Sedimentation Method', to manage contamination to avoid pond cash. The method can be used for the production of algal biofuel, fertilizer etc. and algal wastewater treatment. To evaluate the performance of the method on algal culture, an experiment was conducted for 90 days at a lab-scale raceway (60 L) reactor with the use of non-sterilized and non-filtered wastewater (secondary effluent and centrate of anaerobic digestion). The application of the method provided the following; removing contaminants (predators and diatoms) and other debris from reactor without discharging the culture (with microscopic evidence), increasing raceway tank’s suspended solids holding capacity (770 mg L-1), increasing ammonium removal rate (29.83 mg L-1 d-1), decreasing algal and microbial biofilm formation on inner walls of reactor, washing out generated nitrifier from reactor to prevent ammonium consumption.

Keywords: contamination control, microalgae culture contamination, pond crash, predator control

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Authors: Loonibha Manandhar, Rajendra Bhandari, Kumud Raj Kafle

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Nepal’s Terai region is a part of the Ganges river basin which is one of the most disaster-prone areas of the world, with recurrent monsoon flooding causing millions in damage and the death and displacement of hundreds of people and households every year. The vulnerability of human settlements to natural disasters such as floods is increasing, and mapping changes in land use practices and hydro-geological parameters is essential in developing resilient communities and strong disaster management policies. The objective of this study was to develop a flood hazard zonation map of Orai Khola watershed and map the decadal land use/land cover dynamics of the watershed. The watershed area was delineated using SRTM DEM, and LANDSAT images were classified into five land use classes (forest, grassland, sediment and bare land, settlement area and cropland, and water body) using pixel-based semi-automated supervised maximum likelihood classification. Decadal changes in each class were then quantified using spatial modelling. Flood hazard mapping was performed by assigning weights to factors slope, rainfall distribution, distance from the river and land use/land cover on the basis of their estimated influence in causing flood hazard and performing weighed overlay analysis to identify areas that are highly vulnerable. The forest and grassland coverage increased by 11.53 km² (3.8%) and 1.43 km² (0.47%) from 1996 to 2016. The sediment and bare land areas decreased by 12.45 km² (4.12%) from 1996 to 2016 whereas settlement and cropland areas showed a consistent increase to 14.22 km² (4.7%). Waterbody coverage also increased to 0.3 km² (0.09%) from 1996-2016. 1.27% (3.65 km²) of total watershed area was categorized into very low hazard zone, 20.94% (60.31 km²) area into low hazard zone, 37.59% (108.3 km²) area into moderate hazard zone, 29.25% (84.27 km²) area into high hazard zone and 31 villages which comprised 10.95% (31.55 km²) were categorized into high hazard zone area.

Keywords: flood hazard, land use/land cover, Orai river, supervised maximum likelihood classification, weighed overlay analysis

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Authors: Andreas Hirseland, Lukas Kerschbaumer

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In Germany, during the past years there constantly are about one million long term unemployed who did not benefit from the prospering labor market while most short term unemployed did. Instead, they are continuously dependent on welfare and sometimes precarious short-term employment, experiencing work poverty. Long term unemployment thus turns into a main obstacle to regular employment, especially if accompanied by other impediments such as low level education (school/vocational), poor health (especially chronical illness), advanced age (older than fifty), immigrant status, motherhood or engagement in care for other relatives. Almost two thirds of all welfare recipients have multiple impediments which hinder a successful transition from welfare back to sustainable and sufficient employment. Hiring them is often considered as an investment too risky for employers. Therefore formal application schemes based on formal qualification certificates and vocational biographies might reduce employers’ risks but at the same time are not helpful for long-term unemployed and welfare recipients. The panel survey ‘Labor market and social security’ (PASS; ~15,000 respondents in ~10,000 households), carried out by the Institute of Employment Research (the research institute of the German Federal Labor Agency), shows that their chance to get back to work tends to fall to nil. Only 66 cases of such unlikely transitions could be observed. In a sequential explanatory mixed-method study, the very scarce ‘success stories’ of unlikely transitions from long term unemployment to work were explored by qualitative inquiry – in-depth interviews with a focus on biography accompanied by qualitative network techniques in order to get a more detailed insight of relevant actors involved in the processes which promote the transition from being a welfare recipient to work. There is strong evidence that sustainable transitions are influenced by biographical resources like habits of network use, a set of informal skills and particularly a resilient way of dealing with obstacles, combined with contextual factors rather than by job-placement procedures promoted by Job-Centers according to activation rules or by following formal paths of application. On the employer’s side small and medium-sized enterprises are often found to give job opportunities to a wider variety of applicants, often based on a slow but steadily increasing relationship leading to employment. According to these results it is possible to show and discuss some limitations of (German) activation policies targeting welfare dependency and long-term unemployment. Based on these findings, indications for more supportive small scale measures in the field of labor-market policies are suggested to help long-term unemployed with multiple impediments to overcome their situation.

Keywords: against-all-odds, economic sociology, long-term unemployment, mixed-methods

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Authors: O. J. Osunkeye, P. O. Fakolade, B. E. Olorede

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Broilers productions depend on the provision of adequate and goo quality feed containing all the nutrients, including proteins, carbohydrate, fats, vitamins, minerals and water. All these nutrients have to be provided at a required amount to support maximum productivity and normal physiological functions and demands. Among these nutrients proteins are particularly important, since they are essential for meat and muscle production, optimum growth and health status. Poultry production industry in the developing countries is been threatened because of the over dependency on Soybean meal as one of the key/major conventional protein stuff for feeding livestock. Even the competition between man and livestock for Soybean and other protein sources made the price of this feed stuff to be on the increase. Hence the needs to seek for an alternative feed stuff which is cheap and less competitive. This study showed the blood profile, organ and carcass characteristics and performance of broilers fed with Cowpea Testa Meal (CTM) based diets. Four diets were formulated with Cowpea Testa replacing Soybean at 0%, 15%, 30%, and 50% graded levels. One hundred and twenty day-old unsexed broiler birds were allotted to these four treatments with 3 replicates of 10 birds per replicate. The results showed no significant differences in all the haematological parameters measured (P>0.05), the serum metabolites analysis revealed significant different in Cholesterol (99.8 mg/dl, 112.84 mg/dl, 131.07 mg/dl and 97.66 mg/dl respectively) (P<0.05) among others. There were significant differences within the diets for average daily weight gain, average feed intake and feed to gain ratio. The birds on control (0%) and CTM gained more weight than those fed with 30% and 50% CTM diets. The organs and carcass primal cuts of the broilers expressed significant different for the spleen (0.12 g, 0.09 g, 0.11 g and 0.14 g respectively), lungs (0.97 g, 0.72 g, 0.77 g and 1.01g respectively) and proventriculus (0.96 g, 0.99 g, 0.81 g and 0.85 g respectively) (P<0.05). For the carcass, there were no significant differences (P<0.05) in the breast, thigh, drumstick, wing and neck except for the Back (21.27 g, 21.04 g, 17.71 g, and 17.89 g respectively). In conclusion, CTM inclusion in broiler’s diet could be used as an alternative feed stuff in replacement of Soybean meal up to 15% without any adverse effects as revealed by the blood profile and to increase the growth performance of the birds.

Keywords: physiological functions, cholesterol, blood profiles, CTM and carcass analysis

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Authors: Alyona Gencheva

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The most common way to study diagnostic results is using specialized programs at a stationary workplace. Magnetic Resonance Imaging is presented in a two-dimensional (2D) format, and Computed Tomography sometimes looks like a three-dimensional (3D) model that can be interacted with. The main idea of the research is to compare ways of displaying diagnostic results in virtual reality that can help a surgeon during or before an operation in augmented reality. During the experiment, the medical staff examined liver vessels in the abdominal area and heart boundaries. The search time and detection accuracy were measured on black-and-white and coloured scans. Usability testing in virtual reality shows convenient ways of interaction like hand input, voice activation, displaying risk to the patient, and the required number of scans. The results of the experiment will be used in the new C# program based on Magic Leap technology.

Keywords: augmented reality, computed tomography, magic leap, magnetic resonance imaging, usability testing, VTE risk

Procedia PDF Downloads 99

Authors: M. Rahimi, F. Corman

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This paper study the travel behavior of passengers in a public transport disruption under information provision strategies. We develop a within-day approach for multi-agent simulation to evaluate the behavior of the agents, under comprehensive scenarios through various information exposure, equilibrium, and non-equilibrium scenarios. In particular, we quantify the effects of information strategies in disruption situation on passengers’ satisfaction, number of involved agents, and the caused delay. An agent-based micro-simulation model (MATSim) is applied for the city of Zürich, Switzerland, for the purpose of activity-based simulation in a multimodal network. Statistic outcome is analysed for all the agents who may be involved in the disruption. Agents’ movement in the public transport network illustrates agents’ adaptations to available information about the disruption. Agents’ delays and utility reveal that information significantly affects agents’ satisfaction and delay in public transport disruption. Besides, while the earlier availability of the information causes the fewer consequent delay for the involved agents, however, it also leads to more amount of affected agents.

Keywords: agent-based simulation, disruption management, passengers’ behavior simulation, public transport

Procedia PDF Downloads 133

Authors: Sophio Kobauri, Tengiz Kantaria, Temur Kantaria, David Tugushi, Nina Kulikova, Ramaz Katsarava

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Nanosized environmentally responsive materials are of special interest for various applications, including targeted drug to a considerable potential for treatment of many human diseases. The important technological advantages of nanoparticles (NPs) usage as drug carriers (nanocontainers) are their high stability, high carrier capacity, feasibility of encapsulation of both hydrophilic or hydrophobic substances, as well as a high variety of possible administration routes, including oral application and inhalation. NPs can also be designed to allow controlled (sustained) drug release from the matrix. These properties of NPs enable improvement of drug bioavailability and might allow drug dosage decrease. The targeted and controlled administration of drugs using NPs might also help to overcome drug resistance, which is one of the major obstacles in the control of epidemics. Various degradable and non-degradable polymers of both natural and synthetic origin have been used for NPs construction. One of the most promising for the design of NPs are amino acid-based biodegradable polymers (AABBPs) which can clear from the body after the fulfillment of their function. The AABBPs are composed of naturally occurring and non-toxic building blocks such as α-amino acids, fatty diols and dicarboxylic acids. The particles designed from these polymers are expected to have an improved bioavailability along with a high biocompatibility. The present work deals with a systematic study of the preparation of NPs by cost-effective polymer deposition/solvent displacement method using AABBPs. The influence of the nature and concentration of surfactants, concentration of organic phase (polymer solution), and the ratio organic phase/inorganic (water) phase, as well as of some other factors on the size of the fabricated NPs have been studied. It was established that depending on the used conditions the NPs size could be tuned within 40-330 nm. As the next step of this research an evaluation of biocompatibility and bioavailability of the synthesized NPs has been performed, using two stable human cell culture lines – HeLa and A549. This part of study is still in progress now.

Keywords: amino acids, biodegradable polymers, nanoparticles (NPs), non-toxic building blocks

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Authors: Cyril Ekuaze

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This paper was instigated by a set of assumption drawn at the introduction to a research work on alternative institutional arrangements for sustaining rural infrastructure in developing countries. Of one of such assumption is the one held that, a problem facing developing countries is the sustaining of infrastructural investment long enough to allow the facility to at least repay the cost of the development as been due to insufficient maintenance. On the contrary, this work argues that, most international partnerships relation with developing nations in developing infrastructures is “vertical modeling” with the hierarchical authority and command flow from top to bottom. The work argued that where international donor partners/agencies set out infrastructural development agenda in the developing nations without cognizance of design suitability and capacity for maintenance by the recipient nations; and where public administrative capacity building in the field of science, technology and engineering requisite for design, development and sustenance of infrastructure in the recipient countries are negated, prospective output becomes problematic.

Keywords: vertical partnerships, responsive failure, infrastructural development, developing countries

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Authors: Isabelle Snyder, Travis Smith

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Microgrid protection presents challenges to conventional protection techniques due to the low-induced fault current. Protection relays present in microgrid applications require a combination of settings groups to adjust based on the architecture of the microgrid in islanded and grid-connected modes. In a radial system where the microgrid is at the other end of the feeder, directional elements can be used to identify the direction of the fault current and switch settings groups accordingly (grid-connected or microgrid-connected). However, with multiple microgrid connections, this concept becomes more challenging, and the direction of the current alone is not sufficient to identify the source of the fault current contribution. ORNL has previously developed adaptive relaying schemes through other DOE-funded research projects that will be evaluated and used as a baseline for this research. The four protection techniques in this study are labeled as follows: (1) Adaptive Current only Protection System (ACPS), Intentional (2) Unbalanced Control for Protection Control (IUCPC), (3) Adaptive Protection System with Communication Controller (APSCC) (4) Adaptive Model-Driven Protective Relay (AMDPR).

Keywords: adaptive relaying, microgrid protection, sequence components, islanding detection

Procedia PDF Downloads 76

Authors: Umair Rashid

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Normally softmax loss is used as the supervision signal in face recognition (FR) system, and it boosts the separability of features. In the last two years, a number of techniques have been proposed by reformulating the original softmax loss to enhance the discriminating power of Deep Convolutional Neural Networks (DCNNs) for FR system. To learn angularly discriminative features Cosine-Margin based softmax has been adjusted as monotonically decreasing angular function, that is the main challenge for angular based softmax. On that issue, we propose monotonically decreasing element for Cosine-Margin based softmax and also, we discussed the effect of different monotonically decreasing parameters on angular Margin softmax for FR system. We train the model on publicly available dataset CASIA- WebFace via our proposed monotonically decreasing parameters for cosine function and the tests on YouTube Faces (YTF, Labeled Face in the Wild (LFW), VGGFace1 and VGGFace2 attain the state-of-the-art performance.

Keywords: deep convolutional neural networks, cosine margin face recognition, softmax loss, monotonically decreasing parameter

Procedia PDF Downloads 88

Authors: Hamda M. Al-Ali

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From addressing fundamental questions about the history of the solar system to exploring other planets for any signs of life have always been the core of human space exploration. This triggered humans to explore whether other planets such as Mars could support human life on them. Therefore, many planned space missions to other planets have been designed and conducted to examine the feasibility of human survival on them. However, space missions are expensive and consume a large number of various resources to be successful. To overcome these problems, material efficiency shall be maximized through the use of reusable launch vehicles (RLV) rather than disposable and expendable ones. Material efficiency is defined as a way to achieve service requirements using fewer materials to reduce CO2 emissions from industrial processes. Materials such as aluminum-lithium alloys, steel, Kevlar, and reinforced carbon-carbon composites used in the manufacturing of spacecrafts could be reused in closed-loop cycles directly or by adding a protective coat. Material efficiency is a fundamental principle of a circular economy. The circular economy aims to cutback waste and reduce pollution through maximizing material efficiency so that businesses can succeed and endure. Five strategies have been proposed to improve material efficiency in the space industry, which includes waste minimization, introduce Key Performance Indicators (KPIs) to measure material efficiency, and introduce policies and legislations to improve material efficiency in the space sector. Another strategy to boost material efficiency is through maximizing resource and energy efficiency through material reusability. Furthermore, the environmental effects associated with the rapid growth in the number of space missions include black carbon emissions that lead to climate change. The levels of emissions must be tracked and tackled to ensure the safe utilization of space in the future. The aim of this research paper is to examine and suggest effective methods used to improve material efficiency in space missions so that space and Earth become more environmentally and economically sustainable. The objectives used to fulfill this aim are to identify the materials used in space missions that are suitable to be reused in closed-loop cycles considering material efficiency indicators and circular economy concepts. An explanation of how spacecraft materials could be re-used as well as propose strategies to maximize material efficiency in order to make RLVs possible so that access to space becomes affordable and reliable is provided. Also, the economic viability of the RLVs is examined to show the extent to which the use of RLVs has on the reduction of space mission costs. The environmental and economic implications of the increase in the number of space missions as a result of the use of RLVs are also discussed. These research questions are studied through detailed critical analysis of the literature, such as published reports, books, scientific articles, and journals. A combination of keywords such as material efficiency, circular economy, RLVs, and spacecraft materials were used to search for appropriate literature.

Keywords: access to space, circular economy, material efficiency, reusable launch vehicles, spacecraft materials

Procedia PDF Downloads 96

Authors: I. A. Yola

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Impact of poultry dropping, cow dung and rumen content on utilization and proximate composition of Oreochromis niliticus, Clarias gariepinus and Cyprinus capio in a polyculture system were studied. The research was conducted over a period of 52 weeks. Poultry droppings (PD), cow dung (CD) and rumen content (RC) were applied at three levels 30g,60g and 120g/m2/week, 25g,50g and 100g/m2/week and 22g, 44g and 88g/m2/week treatment, respectively. The control only conventional feed with 40% CP without manure application was used. Physicochemical and biological properties measured were higher in manure pond than control. The difference was statistically significant (P < 0.05) between and within treatments with exception of temperature with a combined mean of 27.900C. The water was consistently alkaline with mean values for pH of 6.61, transparency 22.6cm, conductivity 35.00µhos/cm, dissolved oxygen 4.6 mg/l, biological oxygen demand 2.8mg/l, nitrate and phosphates 0.9mg/l and 0.35mg/l, respectively. The three fish species increase in weight with increased manure rate, with a higher value in PD treatment on C. capio record 340g, O. niloticus weighed 310g and C. gariepinus 280g over the experimental period. Fishes fed supplementary diet (control) grew bigger with highest value on C. capio (685g) O. niloticus (620g) and then C. gariepinus (526g). The differences were statistically significant (P < 0.05). The result of whole body proximate analysis indicated that various manures and rates had an irregular pattern on the protein and ash gain per 100g of fish body weight gain. The combined means for whole fish carcass protein, lipids, moisture, ash and gross energy were 11.84, 2.43, 74.63, 3.00 and 109.9 respectively. The notable exceptions were significant (p < 0.05) increases in body fat and gross energy gains in all fish species accompanied by decreases in percentages of moisture as manure rates increased. Survival percentage decreases from 80% to 70%. It is recommended to use poultry dropping as manure/feeds at the rate of 120kg/ha/week for good performances in polyculture.

Keywords: organic manure, Nile tilapia, African mud fish, common carp, proximate composition

Procedia PDF Downloads 543

Authors: Zhifeng Kong

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Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: over-parameterization, rectified linear units ReLU, convergence, gradient descent, neural networks

Procedia PDF Downloads 134

Authors: Swarn Singh, Suruchi Singh

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In this paper, we present a fourth order two level implicit finite difference scheme for 1D Pennes bio-heat equation. Unconditional stability and convergence of the proposed scheme is discussed. Numerical results are obtained to demonstrate the efficiency of the scheme. In this paper we present a fourth order two level implicit finite difference scheme for 1D Pennes bio-heat equation. Unconditional stability and convergence of the proposed scheme is discussed. Numerical results are obtained to demonstrate the efficiency of the scheme.

Keywords: convergence, finite difference scheme, Pennes bio-heat equation, stability

Procedia PDF Downloads 460