Search results for: single and multi-objective function

Authors: Mohammad Muslim, M. Shafiq Ansari, Fazil Hasan

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Bracon hebetor Say (Hymenoptera: Braconidae) is considered as a highly cosmopolitan ecto-parasitoid of various species of order Lepidoptera. To study the influence of lepidopteran hosts on population growth of B. hebetor, the newly mated gravid females were released on various host and the eggs laid by such females on respective host were counted and a single egg was allow to develop on single host larvae. The experiment was conducted at 27 ± 1°C, 65 ± 5% RH and 14L: 10D hr in Biological Oxygen Demand (BOD) chamber. Upon hatching the tiny larvae of parasitoid pierced the body of insect host, enter into them and consumed the internal body contents of paralyzed host larvae. Present findings showed that B. hebetor took ~36 days to complete its survivorship on Corcyra cephalonica and Galleria mellonella. However, on Spodoptera littoralis the survivorship decreased to 24 days. Nevertheless, development of H. hebetor’s immature was significantly prolonged on S. littoralis and S. litura compared to other insect hosts tested. Female of B. hebetor took longer time to lay eggs on C. cephalonica and G. mellonella than other hosts tested in this study. Longevity of male and female is significantly prolonged on C. cephalonica and G. mellonella compared to others insect hosts tested. Population growth parameters like mx Ro, rm, Tc, and τ was considerably highest on C. cephalonica and lowest on S. littoralis. Based on the demographic studies C. cephalonica and H. armegera were proved to be the most suitable host for the mass rearing of B. hebetor. Nevertheless, results of present investigation could be utilized to improve the mass-breeding program of B. hebetor, so that sufficient number of B. hebetor’s adults could be provided time to time for the effective control of lepidopteran pests of various economically important crops.

Keywords: Bracon hebetor, lepidopteran hosts, demography, biology, development

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Authors: Marzieh Imani

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Antoni Gaudi and Santiago Calatrava have reputation for designing bio-inspired creative and technical buildings. Even though they have followed different independent approaches towards design, the source of bio-inspiration seems to be common. Taking a closer look at their projects reveals that Calatrava has been influenced by Gaudi in terms of interpreting nature and applying natural principles into the design process. This research firstly discusses the dialogue between Biomimicry and architecture. This review also explores human/nature discourse during the history by focusing on how nature revealed itself to the fine arts. This is explained by introducing naturalism and romantic style in architecture as the outcome of designers’ inclination towards nature. Reviewing the literature, theoretical background and practical illustration of nature have been included. The most dominant practical aspects of imitating nature are form and function. Nature has been reflected in architectural science resulted in shaping different architectural styles such as organic, green, sustainable, bionic, and biomorphic. By defining a set of common aspects of Gaudi and Calatrava‘s design approach and by considering biomimetic design categories (organism, ecosystem, and behaviour as the main division and form, function, process, material, and construction as subdivisions), Gaudi’s and Calatrava’s project have been analysed. This analysis explores if their design approaches are equivalent or different. Based on this analysis, Gaudi’s architecture can be recognised as biomorphic while Calatrava’s projects are literally biomimetic. Referring to these architects, this review suggests a new set of principles by which a bio-inspired project can be determined either biomorphic or biomimetic.

Keywords: biomimicry, Calatrava, Gaudi, nature

Procedia PDF Downloads 288

Authors: Ghulam Hussain, Herrington Lee, Comfort Paul, Jones Richard

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Background: To determine the functional limitations of the lower limbs or readiness to return to sport, most rehabilitation programs use some form of testing; however, it is still unknown what the pass criteria is. This study aims to investigate the differences between the dominant and non-dominant leg performances across several lower limb tasks, which are hop tests, two-dimensional (2D) frontal plane projection angle (FPPA) tests, and isokinetic muscle tests. This study also provides the reference values for the limb symmetry index (LSI) for the hop and isokinetic muscle strength tests. Twenty recreationally active participants were recruited, 11 males and 9 females (age 23.65±2.79 years; height 169.9±3.74 cm; and body mass 74.72±5.81 kg. All tests were undertaken on the dominant and non-dominant legs. These tests are (1) Hop tests, which include horizontal hop for distance and crossover hop tests, (2) Frontal plane projection angle (FPPA): 2D capturing from two different tasks, which are forward hop landing and squatting, and (3) Isokinetic muscle strength tests: four different muscles were tested: quadriceps, hamstring, ankle plantar flexor, and hip extensor muscles. The main outcome measurements were, for the (1) hop tests: maximum distance was taken when undertaking single/crossover hop for distance using a standard tape measure, (2) for the FPPA: the knee valgus angle was measured from the maximum knee flexion position using a single 2D camera, and (3) for the isokinetic muscle strength tests: three different variables were measured: peak torque, peak torque to body weight, and the total work to body weight. All the muscle strength tests have been applied in both concentric and eccentric muscle actions at a speed of 60°/sec. This study revealed no differences between the dominant and non-dominant leg performance, and 85% of LSI was achieved by the majority of the subjects in both hop and isokinetic muscle tests, and; therefore, one leg’s hop performance can define the other.

Keywords: 2D FPPA, hop tests, isokinetic testing, LSI

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Authors: Assamen Ayalew Ejigu, Liang-Chiun Chao

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In recent semiconductor and nanotechnology, quality material synthesis, proper characterizations, and productions are the big challenges. As cuprous oxide (Cu2O) is a promising semiconductor material for photovoltaic (PV) and other optoelectronic applications, this study was aimed at to grow and characterize high quality Cu2O nanorods for the improvement of the efficiencies of thin film solar cells and other potential applications. In this study, well-structured cuprous oxide (Cu2O) nanorods were successfully fabricated using IBSD method in which the Cu2O samples were grown on silicon substrates with a substrate temperature of 400°C in an IBSD chamber of pressure of 4.5 x 10-5 torr using copper as a target material. Argon, and oxygen gases were used as a sputter and reactive gases, respectively. The characterization of the Cu2O nanorods (NRs) were done in comparison with Cu2O thin film (TF) deposited with the same method but with different Ar:O2 flow rates. With Ar:O2 ratio of 9:1 single phase pure polycrystalline Cu2O NRs with diameter of ~500 nm and length of ~4.5 µm were grow. Increasing the oxygen flow rates, pure single phase polycrystalline Cu2O thin film (TF) was found at Ar:O2 ratio of 6:1. The field emission electron microscope (FE-SEM) measurements showed that both samples have smooth morphologies. X-ray diffraction and Rama scattering measurements reveals the presence of single phase Cu2O in both samples. The differences in Raman scattering and photoluminescence (PL) bands of the two samples were also investigated and the results showed us there are differences in intensities, in number of bands and in band positions. Raman characterization shows that the Cu2O NRs sample has pronounced Raman band intensities, higher numbers of Raman bands than the Cu2O TF which has only one second overtone Raman signal at 2 (217 cm-1). The temperature dependent photoluminescence (PL) spectra measurements, showed that the defect luminescent band centered at 720 nm (1.72 eV) is the dominant one for the Cu2O NRs and the 640 nm (1.937 eV) band was the only PL band observed from the Cu2O TF. The difference in optical and structural properties of the samples comes from the oxygen flow rate change in the process window of the samples deposition. This gave us a roadmap for further investigation of the electrical and other optical properties for the tunable fabrication of the Cu2O nano/micro structured sample for the improvement of the efficiencies of thin film solar cells in addition to other potential applications. Finally, the novel morphologies, excellent structural and optical properties seen exhibits the grown Cu2O NRs sample has enough quality to be used in further research of the nano/micro structured semiconductor materials.

Keywords: defect levels, nanorods, photoluminescence, Raman modes

Procedia PDF Downloads 241

Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: Yonosuke Murayama

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We have developed and studied a metastable beta Ti alloy, which shows super-elasticity and low Young’s modulus according to the phase stability of its beta phase. The super-elasticity and low Young’s modulus are required in a wide range of applications in various industrial fields. For example, the metallic implant with low Young’s modulus and non-toxicity is desirable because the large difference of Young’s modulus between the human bone and the implant material may cause a stress-shielding phenomenon. We have investigated the role of Sn and Al in metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys. The metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys form during quenching from the beta field at high temperature. While Cr and V act as beta stabilizers, Sn and Al are considered as elements to suppress the athermal omega phase produced during quenching. The athermal omega phase degrades the properties of super-elasticity and Young’s modulus. Although Al and Sn as single elements are considered as an alpha stabilizer and neutral, respectively, Sn and Al acted also as beta stabilizers when added simultaneously with beta stabilized element of Cr or V in this experiment. The quenched microstructure of Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys shifts from martensitic structure to beta single-phase structure with increasing Cr or V. The Young’s modulus of Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys decreased and then increased with increasing Cr or V, each showing its own minimum value of Young's modulus respectively. The composition of the alloy with the minimum Young’s modulus is a near border composition where the quenched microstructure shifts from martensite to beta. The border composition of Ti-Cr-Sn and Ti-V-Sn alloys required only less amount of each beta stabilizer, Cr or V, than Ti-Cr-Al and Ti-V-Al alloys. This indicates that the effect of Sn as a beta stabilizer is stronger than Al. Sn and Al influenced the competitive relation between stress-induced martensitic transformation and slip deformation. Thus, super-elastic properties of metastable beta Ti-Cr-Sn, Ti-Cr-Al, Ti-V-Sn, and Ti-V-Al alloys varied depending on the alloyed element, Sn or Al.

Keywords: metastable beta Ti alloy, super-elasticity, low Young’s modulus, stress-induced martensitic transformation, beta stabilized element

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Authors: Li Yin, Xiaoqin Wang

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Background and purpose: Cancer diagnosis is part of a complex stochastic process, in which patients' personal and social characteristics influence the choice of diagnosing methods, diagnosing methods, in turn, influence the initial assessment of cancer stage, the initial assessment, in turn, influences the choice of treating methods, and treating methods in turn influence cancer outcomes such as cancer survival. To evaluate diagnosing methods, one needs to estimate and test the causal effect of a regime of cancer diagnosis and treatments. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to estimate and test these causal effects via point effects. The purpose of the work is to estimate and test causal effects under various regimes of cancer diagnosis and treatments via point effects. Challenges and solutions: The cancer stage has influences from earlier diagnosis as well as on subsequent treatments. As a consequence, it is highly difficult to estimate and test the causal effects via standard parameters, that is, the conditional survival given all stationary covariates, diagnosing methods, cancer stage and prognosis factors, treating methods. Instead of standard parameters, we use the point effects of cancer diagnosis and treatments to estimate and test causal effects under various regimes of cancer diagnosis and treatments. We are able to use familiar methods in the framework of single-point causal inference to accomplish the task. Achievements: we have applied this method to stomach cancer survival from a clinical study in Sweden. We have studied causal effects under various regimes, including the optimal regime of diagnosis and treatments and the effect moderation of the causal effect by age and gender.

Keywords: cancer diagnosis, causal effect, point effect, G-formula, sequential causal effect

Procedia PDF Downloads 196

Authors: Kassim A. Jassim

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In the present paper, we introduce and discuss a new class Kp(λ,α) of meromorphic multivalent functions in the punctured unit disk U*={z∈¢:0<|z|<1} defined by Ruscheweyh derivative. We obtain some sufficient conditions for the functions belonging to the class Kp(λ,α).

Keywords: meromorphic multivalent function, Ruscheweyh derivative, hadamard product

Procedia PDF Downloads 337

Authors: Nidhi Choudhary, Silke A. Peeters, Ciaran T. Lennon, Dmytro Besprozvannyy, Harm C. M. Knoops, Robert H. Hadfield

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Superconducting Nanowire Single Photon Detectors (SNSPDs) have become leading devices in quantum optics and photonics, known for their exceptional efficiency in detecting single photons from ultraviolet to mid-infrared wavelengths with minimal dark counts, low noise, and reduced timing jitter. Recent advancements in materials science focus attention on refractory metal thin films such as NbN and NbTiN to enhance the optical properties and superconducting performance of SNSPDs, opening the way for next-generation detectors. These films have been deposited by several different techniques, such as atomic layer deposition (ALD), plasma pro-advanced plasma processing (ASP) and magnetron sputtering. The fabrication flexibility of these films enables precise control over morphology, crystallinity, stoichiometry and optical properties, which is crucial for optimising the SNSPD performance. Hence, it is imperative to study the optical and superconducting properties of these materials across a wide range of wavelengths. This study provides a comprehensive analysis of the optical and superconducting properties of some important materials in this category (NbN, NbTiN) by different deposition methods. Using Variable angle ellipsometry spectroscopy (VASE), we measured the refractive index, extinction, and absorption coefficient across a wide wavelength range (200-1700 nm) to enhance light confinement for optical communication devices. The critical temperature and sheet resistance were measured using a four-probe method in a custom-built, cryogen-free cooling system with a Sumitomo RDK-101D cold head and CNA-11C compressor. Our results indicate that ALD-deposited NbN shows a higher refractive index and extinction coefficient in the near-infrared region (~1500 nm) than sputtered NbN of the same thickness. Further, the analysis of the optical properties of plasma pro-ASP deposited NbTiN was performed at different substrate bias voltages and different thicknesses. The analysis of substrate bias voltage indicates that the maximum value of the refractive index and extinction coefficient observed for the substrate biasing of 50-80 V across a substrate bias range of (0 V - 150 V). The optical properties of sputtered NbN films are also investigated in terms of the different substrate temperatures during deposition (100 °C-500 °C). We find the higher the substrate temperature during deposition, the higher the value of the refractive index and extinction coefficient has been observed. In all our superconducting thin films ALD-deposited NbN films possess the highest critical temperature (~12 K) compared to sputtered (~8 K) and plasma pro-ASP (~5 K).

Keywords: optical communication, thin films, superconductivity, atomic layer deposition (ALD), niobium nitride (NbN), niobium titanium nitride (NbTiN), SNSPD, superconducting detector, photon-counting.

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Authors: Huimin Zhao, Xiaoquan Liu, Haochen Liu

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The major challenge facing Alzheimer's Disease (AD) drug development is how to effectively improve cognitive function in clinical practice. Growing evidence indicates that stimulating hippocampal neurogenesis is a strategy for restoring cognition in animal models of AD. The mitogen-activated protein kinase (MAPK) pathway is a crucial factor in neurogenesis, which is negatively regulated by Dual-specificity phosphatase 16 (DUSP16). Transcriptome analysis of post-mortem brain tissue revealed up-regulation of DUSP16 expression in AD patients. Additionally, DUSP16 was involved in regulating the proliferation and neural differentiation of neural progenitor cells (NPCs). Nevertheless, whether the effect of DUSP16 on ameliorating cognitive disorders by influencing NPCs differentiation in AD mice remains unclear. Our study demonstrates an association between DUSP16 SNPs and clinical progression in individuals with mild cognitive impairment (MCI). Besides, we found that increased DUSP16 expression in both 3×Tg and SAMP8 models of AD led to NPC differentiation impairments. By silencing DUSP16, cognitive benefits, the induction of AHN and synaptic plasticity, were observed in AD mice. Furthermore, we found that DUSP16 is involved in the process of NPC differentiation by regulating c-Jun N-terminal kinase (JNK) phosphorylation. Moreover, the increased DUSP16 may be regulated by the ETS transcription factor (ELK1), which binds to the promoter region of DUSP16. Loss of ELK1 resulted in decreased DUSP16 mRNA and protein levels. Our data uncover a potential regulatory role for DUSP16 in adult hippocampal neurogenesis and provide a possibility to find the target of AD intervention.

Keywords: alzheimer's disease, cognitive function, DUSP16, hippocampal neurogenesis

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Authors: Rinat Arbel-Goren, Joel Stavans

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Cell-to-cell variations in transcript or protein abundance, called noise, may give rise to phenotypic variability between isogenic cells, enhancing the probability of survival under stress conditions. These variations may be introduced by post-transcriptional regulatory processes such as non-coding, small RNAs stoichiometric degradation of target transcripts in bacteria. We study the iron homeostasis network in Escherichia coli, in which the RyhB small RNA regulates the expression of various targets as a model system. Using fluorescence reporter genes to detect protein levels and single-molecule fluorescence in situ hybridization to monitor transcripts levels in individual cells, allows us to compare noise at both transcript and protein levels. The experimental results and computer simulations show that extrinsic noise buffers through a feed-forward loop configuration the increase in variability introduced at the transcript level by iron deprivation, illuminating the important role that extrinsic noise plays during stress. Surprisingly, extrinsic noise also decouples of fluctuations of two different targets, in spite of RyhB being a common upstream factor degrading both. Thus, phenotypic variability increases under stress conditions by the decoupling of target fluctuations in the same cell rather than by increasing the noise of each. We also present preliminary results on the adaptation of cells to prolonged iron deprivation in order to shed light on the evolutionary role of post-transcriptional downregulation by small RNAs.

Keywords: cell-to-cell variability, Escherichia coli, noise, single-molecule fluorescence in situ hybridization (smFISH), transcript

Procedia PDF Downloads 164

Authors: Siamak Samani, Nadereh Sohrabi

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Psychological nano-therapy is a new method based on systems theory. According to the theory, systems with severe dysfunctions are resistant to changes. Psychological nano-therapy helps the therapists to break this ice. Two key concepts in psychological nano-therapy are nano-functions and nano-behaviors. The most important step in psychological nano-therapy in family therapy is selecting the most effective nano-function and nano-behavior. The aim of this study was to check the effectiveness of psychological nano-therapy for family therapy. One group pre-test-post-test design (quasi-experimental Design) was applied for research. The sample consisted of ten families with severe marital conflict. The important character of these families was resistance for participating in family therapy. In this study, sending respectful (nano-function) text massages (nano-behavior) with cell phone were applied as a treatment. Cohesion/respect sub scale from self-report family processes scale and family readiness for therapy scale were used to assess all family members in pre-test and post-test. In this study, one of family members was asked to send a respectful text massage to other family members every day for a week. The content of the text massages were selected and checked by therapist. To compare the scores of families in pre-test and post-test paired sample t-test was used. The results of the test showed significant differences in both cohesion/respect score and family readiness for therapy between per-test and post-test. The results revealed that these families have found a better atmosphere for participation in a complete family therapy program. Indeed, this study showed that psychological nano-therapy is an effective method to make family readiness for therapy.

Keywords: family therapy, family conflicts, nano-therapy, family readiness

Procedia PDF Downloads 660

Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Wesam Rohouma

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The aim of this paper is to investigate the use of repetitive controller to regulate the output voltage of three phase four leg matric converter for an Aircraft Ground Power Supply Unit. The proposed controller improve the steady state error and provide good regulation during different loading. Simulation results of 7.5 KW converter are presented to verify the operation of the proposed controller.

Keywords: matrix converter, Power electronics, controller, regulation

Procedia PDF Downloads 1507

Authors: K. S. Zaytsev, Y. R. Nartsissov

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Glycine is one of the key inhibitory neurotransmitters in Central nervous system (CNS) meanwhile glycinergic transmission is highly dependable on its appropriate reuptake from synaptic cleft. Glycine transporters (GlyT) of types 1 and 2 are the enzymes providing glycine transport back to neuronal and glial cells along with Na⁺ and Cl⁻ co-transport. The distribution and stoichiometry of GlyT1 and GlyT2 differ in details, and GlyT2 is more interesting for the research as it reuptakes glycine to neuron cells, whereas GlyT1 is located in glial cells. In the process of GlyT2 activity, the translocation of the amino acid is accompanied with binding of both one chloride and three sodium ions consequently (two sodium ions for GlyT1). In the present study, we developed a computer simulator of GlyT2 and GlyT1 activity based on known experimental data for quantitative estimation of membrane glycine transport. The trait of a single protein functioning was described using the probability approach where each enzyme state was considered separately. Created scheme of transporter functioning realized as a consequence of elemental steps allowed to take into account each event of substrate association and dissociation. Computer experiments using up-to-date kinetic parameters allowed receiving the number of translocated glycine molecules, Na⁺ and Cl⁻ ions per time period. Flexibility of developed software makes it possible to evaluate glycine reuptake pattern in time under different internal characteristics of enzyme conformational transitions. We investigated the behavior of the system in a wide range of equilibrium constant (from 0.2 to 100), which is not determined experimentally. The significant influence of equilibrium constant in the range from 0.2 to 10 on the glycine transfer process is shown. The environmental conditions such as ion and glycine concentrations are decisive if the values of the constant are outside the specified range.

Keywords: glycine, inhibitory neurotransmitters, probability approach, single protein functioning

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Ju-Hong Lee, Yi-Lin Shieh

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Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

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Authors: Ali Ashraf, Ghazaleh Aghaee, Sedigheh Samimian, Mohaya Farzin

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Objectives: Previous studies have indicated the positive effect of physical activity and sports on different aspects of health, such as muscle endurance and sleep cycle. However, in university students, particularly medical students, who have limited time and a stressful lifestyle, there have been limited studies exploring this matter with proven statistical results. In this regard, this study aims to find out how regular physical activity can influence the academic performance of medical students during their internship period. Methods: This was a descriptive-analytical study. Overall, 160 medical students (including 80 women and 88 men) voluntarily participated in the study. The Baecke Physical Activity Questionnaire was applied to determine the student’s physical activity levels. The student's academic performance was determined based on their total average academic scores. The data were analyzed in SPSS version 16 software using the independent t-test, Pearson correlation, and linear regression. Results: The average age of the students was 26.0±1.5 years. Eighty-eight students (52.4%) were male, and 142 (84.5%) were single. The student's mean total average academic score was 16.2±1.2, and their average physical activity score was 8.3±1.1. The student's average academic score was not associated with their gender (P=0.427), marital status (P=0.645), and age (P=0.320). However, married students had a significantly lower physical activity level compared to single students (P=0.020). The results indicated a significant positive correlation between student's physical activity levels and average academic scores (r=+0.410 and P<0.001). This correlation was independent of the student’s age, gender, and marital status based on the regression analysis. Conclusion: The results of the current study suggested that the physical activity level in medical students was low to moderate in most cases, and there was a significant direct relationship between student’s physical activity level and academic performance, independent of age, gender, and marital status.

Keywords: exercise, education, physical activity, academic performance

Procedia PDF Downloads 49

Authors: Daniela Magalhaes, Jorge Pedro, Pedro Souteiro, Joao S. Neves, Sofia Castro-Oliveira, Vanessa Guerreiro, Rita Bettencourt- Silva, Maria M. Costa, Ana Varela, Joana Queiros, Paula Freitas, Davide Carvalho

Abstract:

Introduction: Obesity is an independent risk factor for renal dysfunction. Our aims were: (1) evaluate the impact of bariatric surgery (BS) on renal function; (2) clarify the factors determining the postoperative evolution of the glomerular filtration rate (GFR); (3) access the occurrence of oxalate-mediated renal complications. Methods: We investigated a cohort of 1448 obese patients who underwent bariatric surgery. Those with basal GFR (GFR0) < 30mL/min or without information about the GFR 2-year post-surgery (GFR2) were excluded. Results: We included 725 patients, of whom 647 (89.2%) women, with 41 (IQR 34-51) years, a median weight of 112.4 (IQR 103.0-125.0) kg and a median BMI of 43.4 (IQR 40.6-46.9) kg/m2. Of these, 459 (63.3%) performed gastric bypass (RYGB), 144 (19.9%) placed an adjustable gastric band (AGB) and 122 (16.8%) underwent vertical gastrectomy (VG). At 2-year post-surgery, excess weight loss (EWL) was 60.1 (IQR 43.7-72.4) %. There was a significant improve of metabolic and inflammatory status, as well as a significant decrease in the proportion of patients with diabetes, arterial hypertension and dyslipidemia (p < 0.0001). At baseline, 38 (5.2%) of subjects had hyperfiltration with a GFR0 ≥ 125mL/min/1.73m2, 492 (67.9%) had a GFR0 90-124 mL/min/1.73m2, 178 (24.6%) had a GFR0 60-89 mL/min/1.73m2, and 17 (2.3%) had a GFR0 < 60 mL/min/1.73m2. GFR decreased in 63.2% of patients with hyperfiltration (ΔGFR=-2.5±7.6), and increased in 96.6% (ΔGFR=22.2±12.0) and 82.4% (ΔGFR=24.3±30.0) of the subjects with GFR0 60-89 and < 60 mL/min/1.73m2, respectively ( p < 0.0001). This trend was maintained when adjustment was made for the type of surgery performed. Of 321 patients, 10 (3.3%) had a urinary albumin excretion (UAE) > 300 mg/dL (A3), 44 (14.6%) had a UAE 30-300 mg/dL (A2) and 247 (82.1%) has a UAE < 30 mg/dL (A1). Albuminuria decreased after surgery and at 2-year follow-up only 1 (0.3%) patient had A3, 17 (5.6%) had A2 and 283 (94%) had A1 (p < 0,0001). In multivariate analysis, the variables independently associated with ΔGFR were BMI (positively) and fasting plasma glucose (negatively). During the 2-year follow-up, only 57 of the 725 patients had transient urinary excretion of calcium oxalate crystals. None has records of oxalate-mediated renal complications at our center. Conclusions: The evolution of GFR after BS seems to depend on the initial renal function, as it decreases in subjects with hyperfiltration, but tends to increase in those with renal dysfunction. Our results suggest that BS is associated with improvement of renal outcomes, without significant increase of renal complications. So, apart the clear benefits in metabolic and inflammatory status, maybe obese adults with nondialysis-dependent CKD should be referred for bariatric surgery evaluation.

Keywords: albuminuria, bariatric surgery, glomerular filtration rate, renal function

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Authors: Timothy L. Porter, T. Randy Dillingham

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Vegetation growth and decomposition, along with soil microbial activity play a complex role in the production of greenhouse gases originating in forest soils. The absorption or emission (respiration) of these gases is a function of many factors relating to the soils themselves, the plants, and the environment in which the plants are growing. For this study, we have constructed a battery-powered, portable field mass spectrometer for use in analyzing gases in the soils surrounding trees, plants, and other areas. We have used the instrument to sample in real-time the greenhouse gases carbon dioxide and methane in soils where plant life may be contributing to the production of gases such as methane. Gases such as isoprene, which may help correlate gas respiration to microbial activity have also been measured. The instrument is composed of a quadrupole mass spectrometer with part per billion or better sensitivity, coupled to battery-powered turbo and diaphragm pumps. A unique ambient air pressure differentially pumped intake apparatus allows for the real-time sampling of gases in the soils from the surface to several inches below the surface. Results show that this instrument is capable of instant, part-per-billion sensitivity measurement of carbon dioxide and methane in the near surface region of various forest soils. We have measured differences in soil respiration resulting from forest thinning, forest burning, and forest logging as compared to pristine, untouched forests. Further studies will include measurements of greenhouse gas respiration as a function of temperature, microbial activity as measured by isoprene production, and forest restoration after fire.

Keywords: forest, soil, greenhouse, quadrupole

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

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Authors: Anit S. Malhotra, Ajay Duseja, Neelam Chadha

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Endothelial dysfunction is a precursor to atherosclerosis, and flow-mediated dilatation (FMD) in the brachial artery is the commonest method to evaluate endothelial function in humans. Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver disorders encountered in clinical practice. An earlier meta-analysis had quantitatively assessed the degree of endothelial dysfunction using FMD. However, the largest study investigating the relation of FMD with NAFLD was published after that meta-analysis. In addition, that meta-analysis did not include some studies, including one from our centre. Therefore, an updating the previous meta-analysis was considered important. We searched PubMed, Cochrane Library, Embase, Scopus, SCI, Google Scholar, conference proceedings, and references of included studies till June 2017 to identify observational studies evaluating endothelial function using FMD in patients with non-alcoholic fatty liver disease. Data was analyzed using MedCalc. Fourteen studies were found eligible for inclusion in the meta-analysis. Patients with NAFLD had lower brachial artery FMD as compared to controls, standardized mean difference (random effects model) being –1.279%; 95% confidence interval (CI), –1.478 to –0.914. The effect size became smaller after addition of the recent study with the largest sample size was included compared with the earlier meta-analysis. In conclusion, patients with NAFLD had low FMD values indicating that they are at a higher risk of cardiovascular disease although our results suggest the effect size is not as large as reported previously.

Keywords: endothelial dysfunction, flow-mediated dilatation, meta-analysis, non-alcoholic fatty liver disease

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Authors: Mohamed Fawzy Elzarei, Yousef Mohammed Al-Dakheel, Ali Mohamed Alseaf

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Modern molecular techniques, like single marker analysis for linked traits to these markers, can provide us with rapid and accurate genetic results. In the last two decades of the last century, the applications of molecular techniques were reached a faraway point in cattle, sheep, and pig. In goats, especially in our region, the application of molecular techniques is still far from other species. As reported by many researchers, microsatellites marker is one of the suitable markers for lie studies. The single marker linked to traits of interest is one technique allowed us to early select animals without the necessity for mapping the entire genome. Simplicity, applicability, and low cost of this technique gave this technique a wide range of applications in many areas of genetics and molecular biology. Also, this technique provides a useful approach for evaluating genetic differentiation, particularly in populations that are poorly known genetically. The expected breeding value (EBV) and yield deviation (YD) are considered as the most parameters used for studying the linkage between quantitative characteristics and molecular markers, since these values are raw data corrected for the non-genetic factors. A total of 17 microsatellites markers (from chromosomes 6, 14, 18, 20 and 23) were used in this study to search for areas that could be responsible for genetic variability for some milk traits and search of chromosomal regions that explain part of the phenotypic variance. Results of single-marker analyses were used to identify the linkage between microsatellite markers and variation in EBVs of these traits, Milk yield, Protein percentage, Fat percentage, Litter size and weight at birth, and litter size and weight at weaning. The estimates of the parameters from forward and backward solutions using stepwise regression procedure on milk yield trait, only two markers, OARCP9 and AGLA29, showed a highly significant effect (p≤0.01) in backward and forward solutions. The forward solution for different equations conducted that R2 of these equations were highly depending on only two partials regressions coefficient (βi,) for these markers. For the milk protein trait, four marker showed significant effect BMS2361, CSSM66 (p≤0.01), BMS2626, and OARCP9 (p≤0.05). By the other way, four markers (MCM147, BM1225, INRA006, andINRA133) showed highly significant effect (p≤0.01) in both backward and forward solutions in association with milk fat trait. For both litter size at birth and at weaning traits, only one marker (BM143(p≤0.01) and RJH1 (p≤0.05), respectively) showed a significant effect in backward and forward solutions. The estimates of the parameters from forward and backward solution using stepwise regression procedure on litter weight at birth (LWB) trait only one marker (MCM147) showed highly significant effect (p≤0.01) and two marker (ILSTS011, CSSM66) showed a significant effect (p≤0.05) in backward and forward solutions.

Keywords: microsatellites marker, estimated breeding value, stepwise regression, milk traits

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Authors: Fangyuan Shao, Wei Liu, Deli Gao

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Polycrystalline diamond compact (PDC) bits have occupied a large market of unconventional oil and gas drilling. The application of PDC bits benefits from the efficient rock breaking of PDC cutters. In response to increasingly complex formations, many shaped cutters have been invited, but many of them have not been solved by the mechanism of rock breaking. In this paper, two kinds of PDC cutters: a new axe-shaped (NAS) cutter and cylindrical cutter (benchmark) were studied by laboratory experiments. NAS cutter is obtained by optimizing two sides of axe-shaped cutter with curved surfaces. All the cutters were put on a vertical turret lathe (VTL) in the laboratory for cutting tests. According to the cutting distance, the VTL tests can be divided into two modes: single-turn rotary cutting and continuous cutting. The cutting depth of cutting (DOC) was set at 1.0 mm and 2.0 mm in the former mode. The later mode includes a dry VTL test for thermal stability and a wet VTL test for wear resistance. Load cell and 3D optical profiler were used to obtain the value of cutting forces and wear area, respectively. Based on the findings of the single-turn rotary cutting VTL tests, the performance of A NAS cutter was better than the benchmark cutter on elastoplastic material cutting. The cutting forces (normal forces, tangential force, and radial force) and special mechanical energy (MSE) of a NAS cutter were lower than that of the benchmark cutter under the same condition. It meant that a NAS cutter was more efficient on elastoplastic material breaking. However, the wear resistance of a new axe-shaped cutter was higher than that of a benchmark cutter. The results of the dry VTL test showed that the thermal stability of a NAS cutter was higher than that of a benchmark cutter. The cutting efficiency can be improved by optimizing the geometric structure of the PDC cutter. The change of thermal stability may be caused by the decrease of the contact area between cutter and rock at given DOC. The conclusions of this paper can be used as an important reference for PDC cutters designers.

Keywords: axe-shaped cutter, PDC cutter, rotary cutting test, vertical turret lathe

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Authors: Rahy Farooq, Maria Ahmad Khan, Ayesha Isani Majeed

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Objective: The main aim of this research is to assess the knowledge, attitude and practices of female nursing staff and nursing students regarding breast cancer, to provide a baseline for monitoring trends of breast cancer awareness in them. Background: Healthcare professionals are a direct source of information for the patients and the general public as a whole. It is, therefore, essential that the information they convey be accurate and helps in building additional awareness. However, clinical experience does not influence the knowledge, attitude and practices regarding breast cancer. Nurses, being the prime part of the healthcare professionals, play a significant role and hence, their awareness regarding this pressing issue is pertinent. Lack of awareness regarding common presenting symptoms or breast cancer risk factors translates to poor breast cancer screening practices and late diagnosis. Methodology: A cross-sectional study of 280 female nurses was conducted at a tertiary care hospital in Islamabad, Pakistan. A pre-tested structured questionnaire with additional variables like cultural barriers to seeking medical help was used. The scores for outcome variables including knowledge, attitude and practices were pre-defined. Data was analyzed using SPSSv23. Results: Of the 280 participants with a mean age of 28.99±9.98 years, 142 (50.7%) were married, and 138 (49.3%) were unmarried. Mean scores were computed to be 6.14±2.93 (out of 12), 0.30±0.7 (out of 3) and 9.53±1.92 (out of 16) for knowledge, attitude and practice respectively. Using independent sample T-test, a statistically significant correlation was found when means for the score of Attitude was compared with age. With a p-value of 0.018, 117 nurses of age more than 30 years, faced more practical, financial, emotional and service barriers as compared to 163 women younger than 30 years of age. Knowledge of age-related lifetime risks was also significantly poor more in single women; with a p-value of 0.006 for identification of correct age as a risk factor and a p-value of 0.005 for correct identification of risk for development of breast cancer in the lifetime of women. By application of Chi-square test, there was a significant correlation between marital status and cultural barriers to seeking medical help, showing that single women (58.7%) shy away from talking about breast cancer considering it a taboo (p-value 0.028) whereas, more married nurses (59.2%) were apprehensive that they might be considered at fault by the society, as compared to 40.8% of single nurses. (p-value 0.038). Conclusion: Owing to the scarcity of awareness among nurses, this study recognizes the need for delivering effective information to the female nurses regarding breast cancer. Educating patients is likely to be effective if the female nurses play their part and have correct attitudes towards breast cancer practices. A better understanding of the knowledge and practices regarding breast cancer among the nursing population will enable high-risk patients to be recognized early. Therefore, we recommend arrangement of special courses and seminars for all healthcare professionals including the nursing staff.

Keywords: breast cancer, cultural barriers, kap, nurses

Procedia PDF Downloads 239

Authors: Norhalim Yunus, Mohamad Husaini Dahalan, Nor Halina Ghazali

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Building technology start-ups from ground zero into world-class companies in form and substance present a rare opportunity for government-affiliated institutions in Malaysia. The challenge of building such start-ups becomes tougher when their core businesses involve commercialization of unproven technologies for the mass market. These simple truths, while difficult to execute, will go a long way in getting a business off the ground and flying high. Malaysian Technology Development Corporation (MTDC), a company founded to facilitate the commercial exploitation of R&D findings from research institutions and universities, and eventually help translate these findings of applications in the marketplace, is an excellent case in point. The purpose of this paper is to examine MTDC as an institution as it explores the concept of ‘it takes a village to raise a child’ in an effort to create and nurture start-ups into established world class Malaysian technology companies. With MTDC at the centre of Malaysia's innovative start-ups, the analysis seeks to specifically answer two questions: How has the concept been applied in MTDC? and what can we learn from this successful case? A key aim is to elucidate how MTDC's journey as a private limited company can help leverage reforms and achieve transformation, a process that might be suitable for other small, open, third world and developing countries. This paper employs a single case study, designed to acquire an in-depth understanding of how MTDC has developed and grown technology start-ups to world-class technology companies. The case study methodology is employed as the focus is on a contemporary phenomenon within a real business context. It also explains the causal links in real-life situations where a single survey or experiment is unable to unearth. The findings show that MTDC maximises the concept of it needs a village to raise a child in totality, as MTDC itself assumes the role of the innovator to 'raise' start-up companies into world-class stature. As the innovator, MTDC creates shared value and leadership, introduces innovative programmes ahead of the curve, mobilises talents for optimum results and aggregates knowledge for personnel advancement. The success of the company's effort is attributed largely to leadership, visionary, adaptability, commitment to innovate, partnership and networking, and entrepreneurial drive. The findings of this paper are however limited by the single case study of MTDC. Future research is required to study more cases of success or/and failure where the concept of it takes a village to raise a child have been explored and applied.

Keywords: start-ups, technology transfer, commercialization, technology incubator

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Authors: Saeed Poormoaied

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Perishability and developing an intelligent control policy for perishable items are the major concerns of marketing managers in a supply chain. In this study, we address a two-echelon supply chain problem for perishable items with a single vendor and a single buyer. The buyer adopts an aged-based continuous review policy which works by taking both the stock level and the aging process of items into account. The vendor works under the warehouse framework, where its lot size is determined with respect to the batch size of the buyer. The model holds for a positive and fixed lead time for the buyer, and zero lead time for the vendor. The demand follows a Poisson process and any unmet demand is lost. We provide exact analytic expressions for the operational characteristics of the system by using the renewal reward theorem. Items have a fixed lifetime after which they become unusable and are disposed of from the buyer's system. The age of items starts when they are unpacked and ready for the consumption at the buyer. When items are held by the vendor, there is no aging process which results in no perishing at the vendor's site. The model is developed under the centralized framework, which takes the expected profit of both vendor and buyer into consideration. The goal is to determine the optimal policy parameters under the service level constraint at the retailer's site. A sensitivity analysis is performed to investigate the effect of the key input parameters on the expected profit and order quantity in the supply chain. The efficiency of the proposed age-based policy is also evaluated through a numerical study. Our results show that when the unit perishing cost is negligible, a significant cost saving is achieved.

Keywords: two-echelon supply chain, perishable items, age-based policy, renewal reward theorem

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Authors: S. Rashmi, Devashish Das, N. Spoorthi, H. V. Manasa

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Energy is essential and plays an important role for overall development of a nation. The global economy literally runs on energy. The use of fossil fuels as energy is now widely accepted as unsustainable due to depleting resources and also due to the accumulation of greenhouse gases in the environment, renewable and carbon neutral biodiesel are necessary for environment and economic sustainability. Unfortunately biodiesel produced from oil crop, waste cooking oil and animal fats are not able to replace fossil fuel. Fossil fuels remain the dominant source of primary energy, accounting for 84% of the overall increase in demand. Today biodiesel has come to mean a very specific chemical modification of natural oils. Objectives: To produce biodiesel from yellow oleander seed oil, to test the yield of biodiesel using different types of catalyst (KOH & NaOH). Methodology: Oil is extracted from dried yellow oleander seeds using Soxhlet extractor and oil expeller (bulk). The FFA content of the oil is checked and depending on the FFA value either two steps or single step process is followed to produce biodiesel. Two step processes includes esterfication and transesterification, single step includes only transesterification. The properties of biodiesel are checked. Engine test is done for biodiesel produced. Result: It is concluded that biodiesel quality parameters such as yield(85% & 90%), flash point(1710C & 1760C),fire point(1950C & 1980C), viscosity(4.9991 and 5.21 mm2/s) for the biodiesel from seed oil of Thevetiaperuviana produced by using KOH & NaOH respectively. Thus the seed oil of Thevetiaperuviana is a viable feedstock for good quality fuel.The outcomes of our project are a substitute for conventional fuel, to reduce petro diesel requirement,improved performance in terms of emissions. Future prospects: Optimization of biodiesel production using response surface method.

Keywords: yellow oleander seeds, biodiesel, quality parameters, renewable sources

Procedia PDF Downloads 447