Search results for: emergency response training simulator
Commenced in January 2007
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Paper Count: 9746

Search results for: emergency response training simulator

7166 Effects of Transcranial Direct Current Stimulation on Post-Stroke Dysphagia

Authors: Ehsan Kaviani, Azin Golmoradizade

Abstract:

Introduction: Traditionally, tendons are considered to only contain tenocytes that are responsible for the maintenance, repair, and remodeling of tendons. Stem cells, which are termed tendon-derived stem cells, so this study we investigate the effect of transcranial direct current stimulation combined with swallowing training on post-stroke dysphagia. Methods: This review article is about effects of transcranial direct current stimulation (tDCS) on post-stroke dysphagia that were extracted from Science Direct, Pro quest, and Pub med Data Bases. 15 articles had been selected according to inclusion criteria from 2014 to 2019, and 6 of them had been deleted by exclusion criteria. Results: The results of our systematic review suggest that tDCS may represent a promising novel treatment for post-stroke dysphagia. However, to date, little is known about the optimal parameters of tDCS for relieving post-stroke dysphagia. Further studies are warranted to refine this promising intervention by exploring the optimal parameters of tDCS. Conclusion: anodal tDCS over the affected hemisphere may be as effective as cathodal tDCS on the unaffected hemisphere to enhance recovery after subacute ischemic stroke and anodal tdcs applied over the affected pharyngeal motor cortex can enhance the outcome of swallowing training in post-stroke dysphagia.

Keywords: dysphagia, stroke, cortical stimulation, transcranial direct current stimulation

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7165 Electrochemical Behavior and Cathodic Stripping Voltammetric Determination of Dianabol Steroid in Urine at Bare Glassy Carbon Paste Electrode

Authors: N. Al-Orfi, M. S. El-Shahawi, A. S. Bashammakh

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The electrochemical response of glassy carbon electrode (GCE) for the sensitive and selective determination of dianabol steroid (DS) in phosphate, Britton-Robinson (B-R) and HEPES buffers of pH 2.0 - 11, 2.0 - 11 and 6.2 - 8.0, respectively using cyclic voltammetry (CV) and differential pulse- adsorptive cathodic stripping voltammetry (DP-CSV) at bare GCE was studied. The dependence of the CV response of the developed cathodic peak potential (Ep, c), peak current (ip, c) and the current function (ip, c / υ1/2) on the scan rate (υ) at the bare GCE revealed the occurrence of electrode coupled chemical reaction of EC type mechanism. The selectivity of the proposed method was assessed in the presence of high concentrations of major interfering species e.g. uric acid, ascorbic acid, citric acid, glucose, fructose, sucrose, starch and ions Na+, K+, PO4-3, NO3- and SO42-. The recovery of the method was not significant where t(critical)=2.20 > texp=1.81-1.93 at 95% confidence. The analytical application of the sensor for the quantification of DS in biological fluids as urine was investigated. The results were demonstrated as recovery percentages in the range 95±2.5-97±4.7% with relative standard deviation (RSD) of 0.5-1.5%.

Keywords: dianabol, determination, modified electrode, urine

Procedia PDF Downloads 259
7164 Factors Contributing to Work Stress Among Nurses in Hadiya Zone’s Public Hospitals, Central Ethiopia, in 2023

Authors: Asnakech Zekiwos

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Background: Stress in nursing refers to the reactions nurses experience when faced with work demands that exceed their knowledge, skills, or ability to cope. Nursing, as a profession, is particularly susceptible to work-related stress. Methods: A cross-sectional study was conducted among 405 randomly selected nurses working in Hadiya Zone Public Hospitals from March 1 to 30, 2023. Data were collected using a pre-tested self-administered questionnaire. The data were entered using Epi-data version 3.1 and analyzed using SPSS version 20.0. Multivariable logistic regression analysis was performed to identify factors associated with the level of work stress. Variables with a p-value <0.05 were considered statistically significant. Results: In this study, 56% (95% CI 50.9-61.2) of the participants reported being stressed in their work. Several factors were found to be associated with work stress, including being female (AOR=1.94, 95% CI 1.19-3.16), rotating shifts (AOR=2.06, 95% CI 1.31-3.25), working in the intensive care unit (AOR=3.42, 95% CI 1.20-9.73), and having post-basic training (AOR=0.55, 95% CI 0.34-0.92). Conclusion: The study revealed a high level of work stress among nurses in the study area. The zonal health unit takes measures to address work stress by providing job orientation during the hiring process, rotation, and on-the-job training to help nurses cope with and manage stressful events. Stress in public hospitals and among nurses is an important issue that needs attention.

Keywords: stress, nurses, public hospitals, expanded stress scale

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7163 Inf-γ and Il-2 Asses the Therapeutic Response in Anti-tuberculosis Patients at Jamot Hospital Yaounde, Cameroon

Authors: Alexandra Emmanuelle Membangbi, Jacky Njiki Bikoï, Esther Del-florence Moni Ndedi, Marie Joseph Nkodo Mindimi, Donatien Serge Mbaga, Elsa Nguiffo Makue, André Chris Mikangue Mbongue, Martha Mesembe, George Ikomey Mondinde, Eric Walter Perfura-yone, Sara Honorine Riwom Essama

Abstract:

Background: Tuberculosis (TB) is one of the top lethal infectious diseases worldwide. In recent years, interferon-γ (INF-γ) release assays (IGRAs) have been established as routine tests for diagnosing TB infection. However, produced INF-γ assessment failed to distinguish active TB (ATB) from latent TB infection (LTBI), especially in TB epidemic areas. In addition to IFN-γ, interleukin-2 (IL-2), another cytokine secreted by activated T cells, is also involved in immune response against Mycobacterium tuberculosis. The aim of the study was to assess the capacity of IFN-γ and IL2 to evaluate the therapeutic response of patients on anti-tuberculosis treatment. Material and Methods: We conducted a cross-sectional study in the Pneumonology Departments of the Jamot Hospital in Yaoundé between May and August 2021. After signed the informed consent, the sociodemographic data, as well as 5 mL of blood, were collected in the crook of the elbow of each participant. Sixty-one subjects were selected (n= 61) and divided into 4 groups as followed: group 1: resistant tuberculosis (n=13), group 2: active tuberculosis (n=19), group 3 cured tuberculosis (n=16), and group 4: presumed healthy persons (n=13). The cytokines of interest were determined using an indirect Enzyme-linked Immuno-Sorbent Assay (ELISA) according to the manufacturer's recommendations. P-values < 0.05 were interpreted as statistically significant. All statistical calculations were performed using SPSS version 22.0 Results: The results showed that men were more 14/61 infected (31,8%) with a high presence in active and resistant TB groups. The mean age was 41.3±13.1 years with a 95% CI = [38.2-44.7], the age group with the highest infection rate was ranged between 31 and 40 years. The IL-2 and INF-γ means were respectively 327.6±160.6 pg/mL and 26.6±13.0 pg/mL in active tuberculosis patients, 251.1±30.9 pg/mL and 21.4±9.2 pg/mL in patients with resistant tuberculosis, while it was 149.3±93.3 pg/mL and 17.9±9.4 pg/mL in cured patients, 15.1±8.4 pg/mL and 5.3±2.6 pg/mL in participants presumed healthy (p <0.0001). Significant differences in IFN-γ and IL-2 rates were observed between the different groups. Conclusion: Monitoring the serum levels of INF-γ and IL-2 would be useful to evaluate the therapeutic response of anti-tuberculosis patients, particularly in the both cytokines association case, that could improve the accuracy of routine examinations.

Keywords: antibiotic therapy, interferon gamma, interleukin 2, tuberculosis

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7162 Detecting Elderly Abuse in US Nursing Homes Using Machine Learning and Text Analytics

Authors: Minh Huynh, Aaron Heuser, Luke Patterson, Chris Zhang, Mason Miller, Daniel Wang, Sandeep Shetty, Mike Trinh, Abigail Miller, Adaeze Enekwechi, Tenille Daniels, Lu Huynh

Abstract:

Machine learning and text analytics have been used to analyze child abuse, cyberbullying, domestic abuse and domestic violence, and hate speech. However, to the authors’ knowledge, no research to date has used these methods to study elder abuse in nursing homes or skilled nursing facilities from field inspection reports. We used machine learning and text analytics methods to analyze 356,000 inspection reports, which have been extracted from CMS Form-2567 field inspections of US nursing homes and skilled nursing facilities between 2016 and 2021. Our algorithm detected occurrences of the various types of abuse, including physical abuse, psychological abuse, verbal abuse, sexual abuse, and passive and active neglect. For example, to detect physical abuse, our algorithms search for combinations or phrases and words suggesting willful infliction of damage (hitting, pinching or burning, tethering, tying), or consciously ignoring an emergency. To detect occurrences of elder neglect, our algorithm looks for combinations or phrases and words suggesting both passive neglect (neglecting vital needs, allowing malnutrition and dehydration, allowing decubiti, deprivation of information, limitation of freedom, negligence toward safety precautions) and active neglect (intimidation and name-calling, tying the victim up to prevent falls without consent, consciously ignoring an emergency, not calling a physician in spite of indication, stopping important treatments, failure to provide essential care, deprivation of nourishment, leaving a person alone for an inappropriate amount of time, excessive demands in a situation of care). We further compare the prevalence of abuse before and after Covid-19 related restrictions on nursing home visits. We also identified the facilities with the most number of cases of abuse with no abuse facilities within a 25-mile radius as most likely candidates for additional inspections. We also built an interactive display to visualize the location of these facilities.

Keywords: machine learning, text analytics, elder abuse, elder neglect, nursing home abuse

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7161 In Vivo Response of Scaffolds of Bioactive Glass-Ceramic

Authors: Ana Claudia Muniz Rennó, Karina Nogueira

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This study aimed to investigate the in vivo tissue response of the introduction of the bioactive mesh (BM) scaffolds using a model of tibial bone defect implants in rats. Although a previous in vivo study demonstrated a highly positive response of particulate bioactive materials in the morphological and biomechanical properties of the bone callus, the effects of material with superior bioactivity, present in form of meshes have not been studied yet. Eighty male Wistar rats with 3 mm tibial defects were used. Animals were divided into four groups: intact group (IG) – tibia without any injury; bone defect day zero (0dD) – bone defects, sacrificed immediately after injury; bone defect control group (CG) – bone defects without any filler and bone defect filled with BM scaffold. The animals of BM and CG groups were sacrificed 15, 30 and 45 days post-injury to compare the temporal-special effects of the scaffolds on bone healing. The histological analysis revealed an organized newly formed bone at 30 and 45 days post-surgery in the BM. Also, this group presented an increased COX-2 expression on days 15 and 30 post-surgery. Furthermore, the immunohistochemistry analysis revealed that, BM presented a positive immunoexpression of RUNX-2 during all periods evaluated. The biomechanical analysis revealed that at 15 day after surgery, no significant statistically difference was observed between BM and CG and both groups had significantly higher values of maximal load compared to 0dG and significantly lower values than IG. On days 30 and 45 post-surgery, BM presented statistically lower values of maximal load compared to the CG. Nevertheless, at the same periods, BM did not show statistically significant difference compared to the IG maximal load values (p > 0, 05). Our results revealed that the implantation of the BM scaffolds was effective in stimulating newly bone formation.

Keywords: bone, biomaterials, scaffolds, cartilage

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7160 Volatile Organic Compounds Detection by Surface Acoustic Wave Sensors with Nanoparticles Embedded in Polymer Sensitive Layers

Authors: Cristian Viespe, Dana Miu

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Surface acoustic wave (SAW) sensors with nanoparticles (NPs) of various dimensions and concentrations embedded in different types of polymer sensing films for detecting volatile organic compounds (VOCs) were studied. The sensors were ‘delay line’ type with a center frequency of 69.4 MHz on ST-X quartz substrates. NPs with different diameters of 7 nm or 13 nm were obtained by laser ablation with lasers having 5 ns or 10 ps pulse durations, respectively. The influence of NPs dimensions and concentrations on sensor properties such as frequency shift, sensitivity, noise and response time were investigated. To the best of our knowledge, the influence of NP dimensions on SAW sensor properties with has not been investigated. The frequency shift and sensitivity increased with increasing NP concentration in the polymer for a given NP dimension and with decreasing NP diameter for a given concentration. The best performances were obtained for the smallest NPs used. The SAW sensor with NPs of 7 nm had a limit of detection (LOD) of 65 ppm (almost five times better than the sensor with polymer alone), and a response time of about 9 s for ethanol.

Keywords: surface acoustic wave sensor, nanoparticles, volatile organic compounds, laser ablation

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7159 Seismic Fragility Functions of RC Moment Frames Using Incremental Dynamic Analyses

Authors: Seung-Won Lee, JongSoo Lee, Won-Jik Yang, Hyung-Joon Kim

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A capacity spectrum method (CSM), one of methodologies to evaluate seismic fragilities of building structures, has been long recognized as the most convenient method, even if it contains several limitations to predict the seismic response of structures of interest. This paper proposes the procedure to estimate seismic fragility curves using an incremental dynamic analysis (IDA) rather than the method adopting a CSM. To achieve the research purpose, this study compares the seismic fragility curves of a 5-story reinforced concrete (RC) moment frame obtained from both methods, an IDA method and a CSM. Both seismic fragility curves are similar in slight and moderate damage states whereas the fragility curve obtained from the IDA method presents less variation (or uncertainties) in extensive and complete damage states. This is due to the fact that the IDA method can properly capture the structural response beyond yielding rather than the CSM and can directly calculate higher mode effects. From these observations, the CSM could overestimate seismic vulnerabilities of the studied structure in extensive or complete damage states.

Keywords: seismic fragility curve, incremental dynamic analysis, capacity spectrum method, reinforced concrete moment frame

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7158 Actual Fracture Length Determination Using a Technique for Shale Fracturing Data Analysis in Real Time

Authors: M. Wigwe, M. Y Soloman, E. Pirayesh, R. Eghorieta, N. Stegent

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The moving reference point (MRP) technique has been used in the analyses of the first three stages of two fracturing jobs. The results obtained verify the proposition that a hydraulic fracture in shale grows in spurts rather than in a continuous pattern as originally interpreted by Nolte-Smith technique. Rather than a continuous Mode I fracture that is followed by Mode II, III or IV fractures, these fracture modes could alternate throughout the pumping period. It is also shown that the Nolte-Smith time parameter plot can be very helpful in identifying the presence of natural fractures that have been intersected by the hydraulic fracture. In addition, with the aid of a fracture length-time plot generated from any fracture simulation that matches the data, the distance from the wellbore to the natural fractures, which also translates to the actual fracture length for the stage, can be determined. An algorithm for this technique is developed. This procedure was used for the first 9 minutes of the simulated frac job data. It was observed that after 7mins, the actual fracture length is about 150ft, instead of 250ft predicted by the simulator output. This difference gets larger as the analysis proceeds.

Keywords: shale, fracturing, reservoir, simulation, frac-length, moving-reference-point

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7157 Statistical Optimization of Distribution Coefficient for Reactive Extraction of Lactic Acid Using Tri-n-octyl Amine in Oleyl Alcohol and n-Hexane

Authors: Avinash Thakur, Parmjit S. Panesar, Manohar Singh

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The distribution coefficient, KD for the reactive extraction of lactic acid from aqueous solutions of lactic acid using 10-30% (v/v) tri-n-octyl amine (extractant) dissolved in n-hexane (inert diluent) and 20% (v/v) oleyl alcohol (modifier) was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined interactive effect of seven independent variables, viz lactic acid concentration (cl), pH, TOA concentration in organic phase (ψ), treat ratio (φ), temperature (T), agitation speed (ω) and batch agitation time (τ) on distribution coefficient of lactic acid. The regression analysis recommended that the quadratic model is significant (R2 and adjusted R2 are 98.72 % and 98.69 % respectively) for analysis. A numerical optimization had resulted in maximum lactic acid distribution coefficient (KD) of 3.16 at the optimized values for test variables, cl, pH, ψ, φ, T, ω and τ as 0.15 [M], 3.0, 22.75% (v/v), 1.0 (v/v), 26°C, 145 rpm and 23 min respectively. A good agreement between the predicted and experimentally obtained values for distribution coefficient using the optimized conditions was exhibited.

Keywords: Distribution coefficient, tri-n-octylamine, lactic acid, response surface methodology

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7156 Classroom Curriculum That Includes Wisdom Skills

Authors: Brian Fleischli, Shani Robins

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In recent years, the implementation of wisdom skills, including emotional intelligence, mindfulness, empathy, compassion, gratitude, realism (Cognitive-Behavioral Therapy), and humility, within K-12 educational settings has demonstrated significant benefits in reducing stress, anxiety, anger, and conflict among students. This study summarizes the findings of research conducted over several years, showcasing the positive outcomes associated with teaching these skills to elementary and high school students. Additionally, this overview includes an updated synthesis of current literature concerning the application and effectiveness of training these skill sets in K-12 schools. The research outcomes highlight substantial improvements in student well-being and behavior. Demonstrated with treatment group students exhibiting notable reductions in anger, anxiety, depression, and disruptive behaviors compared to control groups. For instance, fourth-grade students showed enhanced empathy, responsibility, and attention, particularly benefiting those with lower initial scores on these measures. Specific interaction effects suggest that older students and males particularly benefit from these interventions, showcasing the nuanced impact of wisdom skill training across different demographics. Furthermore, this presentation emphasizes the critical role of Social and Emotional Learning (SEL) programs in addressing the multifaceted challenges faced by children and adolescents, including mental health issues, academic performance, and social behaviors. The integration of wisdom skills into school curricula not only fosters individual growth and emotional regulation but also enhances overall school climate and academic achievement. In conclusion, the findings contribute to the growing body of empirical evidence supporting the efficacy of teaching wisdom skills in educational settings. The success of these interventions underscores the potential for widespread implementation of evidence-based programs to promote emotional well-being and academic success among students nationwide.

Keywords: wisdom skills, CBT, cognitive behavioral training, mindfulness, empathy, anxiety

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7155 Induction of Adaptive Response in Yeast Cells under Influence of Extremely High Frequency Electromagnetic Field

Authors: Sergei Voychuk

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Introduction: Adaptive response (AR) is a manifestation of radiation hormesis, which deal with the radiation resistance that may be increased with the pretreatment with small doses of radiation. In the current study, we evaluated the potency of radiofrequency EMF to induce the AR mechanisms and to increase a resistance to UV light. Methods: Saccharomyces cerevisiae yeast strains, which were created to study induction of mutagenesis and recombination, were used in the study. The strains have mutations in rad2 and rad54 genes, responsible for DNA repair: nucleotide excision repair (PG-61), postreplication repair (PG-80) and mitotic (crossover) recombination (T2). An induction of mutation and recombination are revealed due to the formation of red colonies on agar plates. The PG-61 and T2 are UV sensitive strains, while PG-80 is sensitive to ionizing radiation. Extremely high frequency electromagnetic field (EHF-EMF) was used. The irradiation was performed in floating mode and frequency changed during exposure from 57 GHz to 62 GHz. The power of irradiation was 100 mkW, and duration of exposure was 10 and 30 min. Treatment was performed at RT and then cells were stored at 28° C during 1 h without any exposure but after that they were treated with UV light (254nm) for 20 sec (strain T2) and 120 sec (strain PG-61 and PG-80). Cell viability and quantity of red colonies were determined after 5 days of cultivation on agar plates. Results: It was determined that EHF-EMF caused 10-20% decrease of viability of T2 and PG-61 strains, while UV showed twice stronger effect (30-70%). EHF-EMF pretreatment increased T2 resistance to UV, and decreased it in PG-61. The PG-80 strain was insensitive to EHF-EMF and no AR effect was determined for this strain. It was not marked any induction of red colonies formation in T2 and PG-80 strain after EHF or UV exposure. The quantity of red colonies was 2 times more in PG-61 strain after EHF-EMF treatment and at least 300 times more after UV exposure. The pretreatment of PG-61 with EHF-EMF caused at least twice increase of viability and consequent decrease of amount of red colonies. Conclusion: EHF-EMF may induce AR in yeast cells and increase their viability under UV treatment.

Keywords: Saccharomyces cerevisiae, EHF-EMF, UV light, adaptive response

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7154 Nonlinear Finite Element Modeling of Reinforced Concrete Flat Plate-Inclined Column Connection

Authors: Rabab Allouzi, Amer Alkloub

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As the complex shaped buildings become a popular trend for architects, this paper is presented to investigate the performance of reinforced concrete flat plate-inclined column connection. The studies on the inclined column and flat plate connections are not sufficient in comparison to those on the conventional structures. The effect of column angle of inclination on the punching shear strength is found significant and studied herein. This paper presents a non-linear finite element based modeling approach to estimate behavior of RC flat plate inclined column connection. Results from simulations of RC flat plate-straight column connection show good agreement with experimental response of specimens tested by other researchers. The model is further used to study the response of inclined columns to punching at various ranges of inclination angles. The inclination angle can be included in the punching shear strength provisions provided by ACI 318-14 to account for the effect of column inclination.

Keywords: punching shear, non-linear finite element, inclined columns, reinforced concrete connection

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7153 Global Modeling of Drill String Dragging and Buckling in 3D Curvilinear Bore-Holes

Authors: Valery Gulyayev, Sergey Glazunov, Elena Andrusenko, Nataliya Shlyun

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Enhancement of technology and techniques for drilling deep directed oil and gas bore-wells are of essential industrial significance because these wells make it possible to increase their productivity and output. Generally, they are used for drilling in hard and shale formations, that is why their drivage processes are followed by the emergency and failure effects. As is corroborated by practice, the principal drilling drawback occurring in drivage of long curvilinear bore-wells is conditioned by the need to obviate essential force hindrances caused by simultaneous action of the gravity, contact and friction forces. Primarily, these forces depend on the type of the technological regime, drill string stiffness, bore-hole tortuosity and its length. They can lead to the Eulerian buckling of the drill string and its sticking. To predict and exclude these states, special mathematic models and methods of computer simulation should play a dominant role. At the same time, one might note that these mechanical phenomena are very complex and only simplified approaches (‘soft string drag and torque models’) are used for their analysis. Taking into consideration that now the cost of directed wells increases essentially with complication of their geometry and enlargement of their lengths, it can be concluded that the price of mistakes of the drill string behavior simulation through the use of simplified approaches can be very high and so the problem of correct software elaboration is very urgent. This paper deals with the problem of simulating the regimes of drilling deep curvilinear bore-wells with prescribed imperfect geometrical trajectories of their axial lines. On the basis of the theory of curvilinear flexible elastic rods, methods of differential geometry, and numerical analysis methods, the 3D ‘stiff-string drag and torque model’ of the drill string bending and the appropriate software are elaborated for the simulation of the tripping in and out regimes and drilling operations. It is shown by the computer calculations that the contact and friction forces can be calculated and regulated, providing predesigned trouble-free modes of operation. The elaborated mathematic models and software can be used for the emergency situations prognostication and their exclusion at the stages of the drilling process design and realization.

Keywords: curvilinear drilling, drill string tripping in and out, contact forces, resistance forces

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7152 Applying the Quad Model to Estimate the Implicit Self-Esteem of Patients with Depressive Disorders: Comparing the Psychometric Properties with the Implicit Association Test Effect

Authors: Yi-Tung Lin

Abstract:

Researchers commonly assess implicit self-esteem with the Implicit Association Test (IAT). The IAT’s measure, often referred to as the IAT effect, indicates the strengths of automatic preferences for the self relative to others, which is often considered an index of implicit self-esteem. However, based on the Dual-process theory, the IAT does not rely entirely on the automatic process; it is also influenced by a controlled process. The present study, therefore, analyzed the IAT data with the Quad model, separating four processes on the IAT performance: the likelihood that automatic association is activated by the stimulus in the trial (AC); that a correct response is discriminated in the trial (D); that the automatic bias is overcome in favor of a deliberate response (OB); and that when the association is not activated, and the individual fails to discriminate a correct answer, there is a guessing or response bias drives the response (G). The AC and G processes are automatic, while the D and OB processes are controlled. The AC parameter is considered as the strength of the association activated by the stimulus, which reflects what implicit measures of social cognition aim to assess. The stronger the automatic association between self and positive valence, the more likely it will be activated by a relevant stimulus. Therefore, the AC parameter was used as the index of implicit self-esteem in the present study. Meanwhile, the relationship between implicit self-esteem and depression is not fully investigated. In the cognitive theory of depression, it is assumed that the negative self-schema is crucial in depression. Based on this point of view, implicit self-esteem would be negatively associated with depression. However, the results among empirical studies are inconsistent. The aims of the present study were to examine the psychometric properties of the AC (i.e., test-retest reliability and its correlations with explicit self-esteem and depression) and compare it with that of the IAT effect. The present study had 105 patients with depressive disorders completing the Rosenberg Self-Esteem Scale, Beck Depression Inventory-II and the IAT on the pretest. After at least 3 weeks, the participants completed the second IAT. The data were analyzed by the latent-trait multinomial processing tree model (latent-trait MPT) with the TreeBUGS package in R. The result showed that the latent-trait MPT had a satisfactory model fit. The effect size of test-retest reliability of the AC and the IAT effect were medium (r = .43, p < .0001) and small (r = .29, p < .01) respectively. Only the AC showed a significant correlation with explicit self-esteem (r = .19, p < .05). Neither of the two indexes was correlated with depression. Collectively, the AC parameter was a satisfactory index of implicit self-esteem compared with the IAT effect. Also, the present study supported the results that implicit self-esteem was not correlated with depression.

Keywords: cognitive modeling, implicit association test, implicit self-esteem, quad model

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7151 Optimization Studies on Biosorption of Ni(II) and Cd(II) from Wastewater Using Pseudomonas putida in a Packed Bed Bioreactor

Authors: K.Narasimhulu, Y. Pydi Setty

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The objective of this present study is the optimization of process parameters in biosorption of Ni(II) and Cd(II) ions by Pseudomonas putida using Response Surface Methodology in a Packed bed bioreactor. The experimental data were also tested with theoretical models to find the best fit model. The present paper elucidates RSM as an efficient approach for predictive model building and optimization of Ni(II) and Cd(II) ions using Pseudomonas putida. In packed bed biosorption studies, comparison of the breakthrough curves of Ni(II) and Cd(II) for Agar immobilized and PAA immobilized Pseudomonas putida at optimum conditions of flow rate of 300 mL/h, initial metal ion concentration of 100 mg/L and bed height of 20 cm with weight of biosorbent of 12 g, it was found that the Agar immobilized Pseudomonas putida showed maximum percent biosorption and bed saturation occurred at 20 minutes. Optimization results of Ni(II) and Cd(II) by Pseudomonas putida from the Design Expert software were obtained as bed height of 19.93 cm, initial metal ion concentration of 103.85 mg/L, and flow rate of 310.57 mL/h. The percent biosorption of Ni(II) and Cd(II) is 87.2% and 88.2% respectively. The predicted optimized parameters are in agreement with the experimental results.

Keywords: packed bed bioreactor, response surface mthodology, pseudomonas putida, biosorption, waste water

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7150 Evaluating the effects of Gas Injection on Enhanced Gas-Condensate Recovery and Reservoir Pressure Maintenance

Authors: F. S. Alavi, D. Mowla, F. Esmaeilzadeh

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In this paper, the Eclipse 300 simulator was used to perform compositional modeling of gas injection process for enhanced condensate recovery of a real gas condensate well in south of Iran here referred to as SA4. Some experimental data were used to tune the Peng-Robinson equation of state for this case. Different scenarios of gas injection at current reservoir pressure and at abandonment reservoir pressure had been considered with different gas compositions. Methane, carbon dioxide, nitrogen and two other gases with specified compositions were considered as potential gases for injection. According to the obtained results, nitrogen leads to highest pressure maintenance in the reservoir but methane results in highest condensate recovery among the selected injection gases. At low injection rates, condensate recovery percent is strongly affected by gas injection rate but this dependency shifts to zero at high injection rates. Condensate recovery is higher in all cases of injection at current reservoir pressure than injection at abandonment pressure. Using a constant injection rate, increasing the production well bottom hole pressure results in increasing the condensate recovery percent and time of gas breakthrough.

Keywords: gas-condensate reservoir, case-study, compositional modelling, enhanced condensate recovery, gas injection

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7149 Level of Grief, Emotional Impact and Coping Strategies of Internal Medicine Residents in Response to a Patient’s Death

Authors: Florge Francis A. Sy

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Physicians develop emotional and psychological distress after facing a patient’s death. This can result in stress or burnout. Coping mechanisms in dealing with these deaths may be maladaptive. Determining grief, emotional impact, and coping strategies in physicians is necessary to identify those needing intervention. This can be done by employing validated assessment tools such as the Texas Revised Inventory of Grief (TRIG) scale, Impact of Events Scale (IES), and BriefCOPE tool, respectively. This prospective, observational study was done in a private hospital in Cebu City. Fifty-five internal medicine residents were included and tasked to answer a survey based on their most memorable patient death encounter. The TRIG, IES, and BriefCOPE scores were determined. Participants were divided into severe grief and non-severe grief based on TRIG scores, low-impact, moderate-impact, and high-impact based on IES, and low-use, moderate-use, and high-use based on the BriefCOPE. The differences in the groups’ characteristics were statistically determined, and a p-value of < 0.05 was significant. The participants’ average age was 28.45 years. Most were female and single. Most belonged to the non-severe group based on TRIG, a moderate-impact group based on the IES, and high-use group based on the BriefCOPE. However, 21.8% reported severe grief, 27.3% reported high-impact, and 10.9% had low use of coping strategies. The proportion of residents who encountered CPR prior to the patient’s death was greater in the severe group. Proportions of both high-impact and non-high impact groups were comparable. The proportion of female residents was higher in the high-use group. There were a number of residents who reported severe grief, high emotional impact, and low coping strategies. This highlights the need for interventions such as debriefing after CPR or formal training in residency programs in dealing with emotional burden to counteract maladaptive coping behaviors and prevent negative outcomes.

Keywords: residents, grief, emotional impact, coping, patient death

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7148 Building Energy Modeling for Networks of Data Centers

Authors: Eric Kumar, Erica Cochran, Zhiang Zhang, Wei Liang, Ronak Mody

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The objective of this article was to create a modelling framework that exposes the marginal costs of shifting workloads across geographically distributed data-centers. Geographical distribution of internet services helps to optimize their performance for localized end users with lowered communications times and increased availability. However, due to the geographical and temporal effects, the physical embodiments of a service's data center infrastructure can vary greatly. In this work, we first identify that the sources of variances in the physical infrastructure primarily stem from local weather conditions, specific user traffic profiles, energy sources, and the types of IT hardware available at the time of deployment. Second, we create a traffic simulator that indicates the IT load at each data-center in the set as an approximator for user traffic profiles. Third, we implement a framework that quantifies the global level energy demands using building energy models and the traffic profiles. The results of the model provide a time series of energy demands that can be used for further life cycle analysis of internet services.

Keywords: data-centers, energy, life cycle, network simulation

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7147 A Comparative Asessment of Some Algorithms for Modeling and Forecasting Horizontal Displacement of Ialy Dam, Vietnam

Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

Abstract:

In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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7146 Analytical Model of Locomotion of a Thin-Film Piezoelectric 2D Soft Robot Including Gravity Effects

Authors: Zhiwu Zheng, Prakhar Kumar, Sigurd Wagner, Naveen Verma, James C. Sturm

Abstract:

Soft robots have drawn great interest recently due to a rich range of possible shapes and motions they can take on to address new applications, compared to traditional rigid robots. Large-area electronics (LAE) provides a unique platform for creating soft robots by leveraging thin-film technology to enable the integration of a large number of actuators, sensors, and control circuits on flexible sheets. However, the rich shapes and motions possible, especially when interacting with complex environments, pose significant challenges to forming well-generalized and robust models necessary for robot design and control. In this work, we describe an analytical model for predicting the shape and locomotion of a flexible (steel-foil-based) piezoelectric-actuated 2D robot based on Euler-Bernoulli beam theory. It is nominally (unpowered) lying flat on the ground, and when powered, its shape is controlled by an array of piezoelectric thin-film actuators. Key features of the models are its ability to incorporate the significant effects of gravity on the shape and to precisely predict the spatial distribution of friction against the contacting surfaces, necessary for determining inchworm-type motion. We verified the model by developing a distributed discrete element representation of a continuous piezoelectric actuator and by comparing its analytical predictions to discrete-element robot simulations using PyBullet. Without gravity, predicting the shape of a sheet with a linear array of piezoelectric actuators at arbitrary voltages is straightforward. However, gravity significantly distorts the shape of the sheet, causing some segments to flatten against the ground. Our work includes the following contributions: (i) A self-consistent approach was developed to exactly determine which parts of the soft robot are lifted off the ground, and the exact shape of these sections, for an arbitrary array of piezoelectric voltages and configurations. (ii) Inchworm-type motion relies on controlling the relative friction with the ground surface in different sections of the robot. By adding torque-balance to our model and analyzing shear forces, the model can then determine the exact spatial distribution of the vertical force that the ground is exerting on the soft robot. Through this, the spatial distribution of friction forces between ground and robot can be determined. (iii) By combining this spatial friction distribution with the shape of the soft robot, in the function of time as piezoelectric actuator voltages are changed, the inchworm-type locomotion of the robot can be determined. As a practical example, we calculated the performance of a 5-actuator system on a 50-µm thick steel foil. Piezoelectric properties of commercially available thin-film piezoelectric actuators were assumed. The model predicted inchworm motion of up to 200 µm per step. For independent verification, we also modelled the system using PyBullet, a discrete-element robot simulator. To model a continuous thin-film piezoelectric actuator, we broke each actuator into multiple segments, each of which consisted of two rigid arms with appropriate mass connected with a 'motor' whose torque was set by the applied actuator voltage. Excellent agreement between our analytical model and the discrete-element simulator was shown for both for the full deformation shape and motion of the robot.

Keywords: analytical modeling, piezoelectric actuators, soft robot locomotion, thin-film technology

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7145 O-(2-18F-Fluoroethyl)-L-Tyrosine Positron Emission Tomography/Computed Tomography in Patients with Suspicious Recurrent Low and High-Grade Glioma

Authors: Mahkameh Asadi, Habibollah Dadgar

Abstract:

The precise definition margin of high and low-grade glioma is crucial for choosing best treatment approach after surgery and radio-chemotherapy. The aim of the current study was to assess the O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) positron emission tomography (PET)/computed tomography (CT) in patients with low (LGG) and high grade glioma (HGG). We retrospectively analyzed 18F-FET PET/CT of 10 patients (age: 33 ± 12 years) with suspicious for recurrent LGG and HGG. The final decision of recurrence was made by magnetic resonance imaging (MRI) and registered clinical data. While response to radio-chemotherapy by MRI is often complex and sophisticated due to the edema, necrosis, and inflammation, emerging amino acid PET leading to better interpretations with more specifically differentiate true tumor boundaries from equivocal lesions. Therefore, integrating amino acid PET in the management of glioma to complement MRI will significantly improve early therapy response assessment, treatment planning, and clinical trial design.

Keywords: positron emission tomography, amino acid positron emission tomography, magnetic resonance imaging, low and high grade glioma

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7144 Lentiviral-Based Novel Bicistronic Therapeutic Vaccine against Chronic Hepatitis B Induces Robust Immune Response

Authors: Mohamad F. Jamiluddin, Emeline Sarry, Ana Bejanariu, Cécile Bauche

Abstract:

Introduction: Over 360 million people are chronically infected with hepatitis B virus (HBV), of whom 1 million die each year from HBV-associated liver cirrhosis or hepatocellular carcinoma. Current treatment options for chronic hepatitis B depend on interferon-α (IFNα) or nucleos(t)ide analogs, which control virus replication but rarely eliminate the virus. Treatment with PEG-IFNα leads to a sustained antiviral response in only one third of patients. After withdrawal of the drugs, the rebound of viremia is observed in the majority of patients. Furthermore, the long-term treatment is subsequently associated with the appearance of drug resistant HBV strains that is often the cause of the therapy failure. Among the new therapeutic avenues being developed, therapeutic vaccine aimed at inducing immune responses similar to those found in resolvers is of growing interest. The high prevalence of chronic hepatitis B necessitates the design of better vaccination strategies capable of eliciting broad-spectrum of cell-mediated immunity(CMI) and humoral immune response that can control chronic hepatitis B. Induction of HBV-specific T cells and B cells by therapeutic vaccination may be an innovative strategy to overcome virus persistence. Lentiviral vectors developed and optimized by THERAVECTYS, due to their ability to transduce non-dividing cells, including dendritic cells, and induce CMI response, have demonstrated their effectiveness as vaccination tools. Method: To develop a HBV therapeutic vaccine that can induce a broad but specific immune response, we generated recombinant lentiviral vector carrying IRES(Internal Ribosome Entry Site)-containing bicistronic constructs which allow the coexpression of two vaccine products, namely HBV T- cell epitope vaccine and HBV virus like particle (VLP) vaccine. HBV T-cell epitope vaccine consists of immunodominant cluster of CD4 and CD8 epitopes with spacer in between them and epitopes are derived from HBV surface protein, HBV core, HBV X and polymerase. While HBV VLP vaccine is a HBV core protein based chimeric VLP with surface protein B-cell epitopes displayed. In order to evaluate the immunogenicity, mice were immunized with lentiviral constructs by intramuscular injection. The T cell and antibody immune responses of the two vaccine products were analyzed using IFN-γ ELISpot assay and ELISA respectively to quantify the adaptive response to HBV antigens. Results: Following a single administration in mice, lentiviral construct elicited robust antigen-specific IFN-γ responses to the encoded antigens. The HBV T- cell epitope vaccine demonstrated significantly higher T cell immunogenicity than HBV VLP vaccine. Importantly, we demonstrated by ELISA that antibodies are induced against both HBV surface protein and HBV core protein when mice injected with vaccine construct (p < 0.05). Conclusion: Our results highlight that THERAVECTYS lentiviral vectors may represent a powerful platform for immunization strategy against chronic hepatitis B. Our data suggests the likely importance of Lentiviral vector based novel bicistronic construct for further study, in combination with drugs or as standalone antigens, as a therapeutic lentiviral based HBV vaccines. THERAVECTYS bicistronic HBV vaccine will be further evaluated in animal efficacy studies.

Keywords: chronic hepatitis B, lentiviral vectors, therapeutic vaccine, virus-like particle

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7143 Effect of Different Plan Shapes on the Load Carrying Capacity of a Steel Frame under Extreme Loading

Authors: Omid Khandel, Azadeh Parvin

Abstract:

An increase in accidental explosions in recent years has increased the interest on investigating the response and behavior of structures in more details. The present work focused on finite element analysis of multistory steel frame structures with different plan shapes subjected to blast loadings. In order to study the effect of the geometry of the building, three different shapes for the plan of the building were modeled and studied; Rectangular, Square and L shape plans. The nonlinear dynamic analysis was considered in this study. The relocation technique was also used to improve the behavior of structure. The accuracy of the multistory frame model was confirmed with those of the existing study in the literature and they were in good agreement. The effect of span length of the buildings was also considered. Finite element analysis of various scenarios for relocating the plastic hinges and improving the response of the structure was performed. The base shear versus displacement curves were compared to reveal the best possible scenarios to provide recommendations to designers and practitioners.

Keywords: nonlinear dynamic analysis, plastic hinge relocation, Retrofit, SAP2000

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7142 Two Dimensional Numerical Analysis for the Seismic Response of the Geosynthetic-Reinforced Soil Integral Abutments

Authors: Dawei Shen, Ming Xu, Pengfei Liu

Abstract:

The joints between simply supported bridge decks and abutments need to be regularly repaired, which would greatly increase the cost during the service life of the bridge. Simply supported girder bridges suffered the most severe damage during earthquakes. Another type of bridge, the integral bridge, of which the superstructure and abutment are rigidly connected, was also used in some European countries. Because no bearings or joints exit in the integral bridge, this type of bridge could significantly reduce maintenance requirements and costs. However, conventional integral bridge usually result in high earth pressure on the abutment and surface settlement in the backfill. To solve these problems, a new type of integral bridge, geosynthetic-reinforced soil (GRS) integral bridge, was come up in recent years. This newly invented bridge has not been used in engineering practices. There was a lack of research on the seismic behavior of the conventional and new type of integral abutments. In addition, no common design code could be found for the calculation of seismic pressure of soil behind the abutment. This paper developed a dynamic constitutive model, which can consider the soil behaviors under cyclic loading. Numerical analyses of the seismic response of a full height integral bridge and GRS integral bridge were carried out using the two-dimensional numerical code, FLAC. A parametric study was also performed to investigate the soil-structure interaction. The results are presented below. The seismic responses of GRS integral bridge together with conventional simply supported bridge, GRS conventional bridge and conventional integral bridge were investigated. The results show that the GRS integral bridge holds the highest seismic stability, followed by conventional integral bridge, GRS simply supported bridge and conventional simply supported bridge. Compared with the integral bridge with 1 m thick abutments, the GRS integral bridge with 0.4 m thick abutments is subjected to a smaller bending moment, and the natural frequency and horizontal displacement remains almost the same. Geosynthetic-reinforcement will be more effective when the abutment becomes thinner or the abutment is higher.

Keywords: geosynthetic-reinforced soil integral bridge, nonlinear hysteretic model, numerical analysis, seismic response

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7141 Unveiling Coaching Style of PE Teachers: A Convergent Parallel Approach

Authors: Arazan Jane V., Badiang, Ronesito Jr. R., Clavesillas Cristine Joy H., Belleza Saramie S.

Abstract:

This study examined the coaching style among the PE Teachers in terms of Autonomy, Supportive style, and Controlling Style. On the other hand, gives opportunities to an athlete to be independent, task-oriented, and acknowledge their feelings and perspective of each individual. A controlling coaching style is also portrayed by the rises and falls over an athlete's training development; when this variance is identified, it might harm training. The selection of the respondents of the study will use a random sample of High School PE teachers of the Division of Davao del Norte with a total of 78 High School PE teachers, which can be broken down into 70 High School PE Teachers for Quantitative data for the survey questionnaire and 8 PE Teachers for Qualitative data (IDI). In the quantitative phase, a set of survey questionnaires will be used to gather data from the participants—the extent of the Implementation Questionnaire. The tool will be a researcher-made questionnaire based on the Coaching Styles of selected High School PE teachers of Davao Del Norte. In the qualitative phase, an interview guide questionnaire will be used. Focus group discussions will be conducted to determine themes and patterns or participants' experiences and insights. The researchers conclude that the degree of coaching style among PE Teachers from the Division of Davao del Norte is high, as seen by the findings of this study, and that coaching style among these teachers is highly noticeable.

Keywords: supportive autonomy style, controlling style, live experiences, exemplified

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7140 Land Cover Remote Sensing Classification Advanced Neural Networks Supervised Learning

Authors: Eiman Kattan

Abstract:

This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

Procedia PDF Downloads 349
7139 Semi-Supervised Learning for Spanish Speech Recognition Using Deep Neural Networks

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

Abstract:

Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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7138 Molecular Dynamics Simulation of Free Vibration of Graphene Sheets

Authors: Seyyed Feisal Asbaghian Namin, Reza Pilafkan, Mahmood Kaffash Irzarahimi

Abstract:

TThis paper considers vibration of single-layered graphene sheets using molecular dynamics (MD) and nonlocal elasticity theory. Based on the MD simulations, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), an open source software, is used to obtain fundamental frequencies. On the other hand, governing equations are derived using nonlocal elasticity and first order shear deformation theory (FSDT) and solved using generalized differential quadrature method (GDQ). The small-scale effect is applied in governing equations of motion by nonlocal parameter. The effect of different side lengths, boundary conditions and nonlocal parameter are inspected for aforementioned methods. Results are obtained from MD simulations is compared with those of the nonlocal elasticity theory to calculate appropriate values for the nonlocal parameter. The nonlocal parameter value is suggested for graphene sheets with various boundary conditions. Furthermore, it is shown that the nonlocal elasticity approach using classical plate theory (CLPT) assumptions overestimates the natural frequencies.

Keywords: graphene sheets, molecular dynamics simulations, fundamental frequencies, nonlocal elasticity theory, nonlocal parameter

Procedia PDF Downloads 500
7137 Distinguishing between Bacterial and Viral Infections Based on Peripheral Human Blood Tests Using Infrared Microscopy and Multivariate Analysis

Authors: H. Agbaria, A. Salman, M. Huleihel, G. Beck, D. H. Rich, S. Mordechai, J. Kapelushnik

Abstract:

Viral and bacterial infections are responsible for variety of diseases. These infections have similar symptoms like fever, sneezing, inflammation, vomiting, diarrhea and fatigue. Thus, physicians may encounter difficulties in distinguishing between viral and bacterial infections based on these symptoms. Bacterial infections differ from viral infections in many other important respects regarding the response to various medications and the structure of the organisms. In many cases, it is difficult to know the origin of the infection. The physician orders a blood, urine test, or 'culture test' of tissue to diagnose the infection type when it is necessary. Using these methods, the time that elapses between the receipt of patient material and the presentation of the test results to the clinician is typically too long ( > 24 hours). This time is crucial in many cases for saving the life of the patient and for planning the right medical treatment. Thus, rapid identification of bacterial and viral infections in the lab is of great importance for effective treatment especially in cases of emergency. Blood was collected from 50 patients with confirmed viral infection and 50 with confirmed bacterial infection. White blood cells (WBCs) and plasma were isolated and deposited on a zinc selenide slide, dried and measured under a Fourier transform infrared (FTIR) microscope to obtain their infrared absorption spectra. The acquired spectra of WBCs and plasma were analyzed in order to differentiate between the two types of infections. In this study, the potential of FTIR microscopy in tandem with multivariate analysis was evaluated for the identification of the agent that causes the human infection. The method was used to identify the infectious agent type as either bacterial or viral, based on an analysis of the blood components [i.e., white blood cells (WBC) and plasma] using their infrared vibrational spectra. The time required for the analysis and evaluation after obtaining the blood sample was less than one hour. In the analysis, minute spectral differences in several bands of the FTIR spectra of WBCs were observed between groups of samples with viral and bacterial infections. By employing the techniques of feature extraction with linear discriminant analysis (LDA), a sensitivity of ~92 % and a specificity of ~86 % for an infection type diagnosis was achieved. The present preliminary study suggests that FTIR spectroscopy of WBCs is a potentially feasible and efficient tool for the diagnosis of the infection type.

Keywords: viral infection, bacterial infection, linear discriminant analysis, plasma, white blood cells, infrared spectroscopy

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