Search results for: prediction interval
Commenced in January 2007
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Edition: International
Paper Count: 3046

Search results for: prediction interval

796 Chatter Prediction of Curved Thin-walled Parts Considering Variation of Dynamic Characteristics Based on Acoustic Signals Acquisition

Authors: Damous Mohamed, Zeroudi Nasredine

Abstract:

High-speed milling of thin-walled parts with complex curvilinear profiles often encounters machining instability, commonly referred to as chatter. This phenomenon arises due to the dynamic interaction between the cutting tool and the part, exacerbated by the part's low rigidity and varying dynamic characteristics along the tool path. This research presents a dynamic model specifically developed to predict machining stability for such curved thin-walled components. The model employs the semi-discretization method, segmenting the tool trajectory into small, straight elements to locally approximate the behavior of an inclined plane. Dynamic characteristics for each segment are extracted through experimental modal analysis and incorporated into the simulation model to generate global stability lobe diagrams. Validation of the model is conducted through cutting tests where acoustic intensity is measured to detect instabilities. The experimental data align closely with the predicted stability limits, confirming the model's accuracy and effectiveness. This work provides a comprehensive approach to enhancing machining stability predictions, thereby improving the efficiency and quality of high-speed milling operations for thin-walled parts.

Keywords: chatter, curved thin-walled part, semi-discretization method, stability lobe diagrams

Procedia PDF Downloads 28
795 Precision Pest Management by the Use of Pheromone Traps and Forecasting Module in Mobile App

Authors: Muhammad Saad Aslam

Abstract:

In 2021, our organization has launched our proprietary mobile App i.e. Farm Intelligence platform, an industrial-first precision agriculture solution, to Pakistan. It was piloted at 47 locations (spanning around 1,200 hectares of land), addressing growers’ pain points by bringing the benefits of precision agriculture to their doorsteps. This year, we have extended its reach by more than 10 times (nearly 130,000 hectares of land) in almost 600 locations across the country. The project team selected highly infested areas to set up traps, which then enabled the sales team to initiate evidence-based conversations with the grower community about preventive crop protection products that includes pesticides and insecticides. Mega farmer meeting field visits and demonstrations plots coupled with extensive marketing activities, were setup to include farmer community. With the help of App real-time pest monitoring (using heat maps and infestation prediction through predictive analytics) we have equipped our growers with on spot insights that will help them optimize pesticide applications. Heat maps allow growers to identify infestation hot spots to fine-tune pesticide delivery, while predictive analytics enable preventive application of pesticides before the situation escalates. Ultimately, they empower growers to keep their crops safe for a healthy harvest.

Keywords: precision pest management, precision agriculture, real time pest tracking, pest forecasting

Procedia PDF Downloads 92
794 Improved Classification Procedure for Imbalanced and Overlapped Situations

Authors: Hankyu Lee, Seoung Bum Kim

Abstract:

The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

Procedia PDF Downloads 308
793 Hydrological Evaluation of Satellite Precipitation Products Using IHACRES Rainfall-Runoff Model over a Basin in Iran

Authors: Mahmoud Zakeri Niri, Saber Moazami, Arman Abdollahipour, Hossein Ghalkhani

Abstract:

The objective of this research is to hydrological evaluation of four widely-used satellite precipitation products named PERSIANN, TMPA-3B42V7, TMPA-3B42RT, and CMORPH over Zarinehrood basin in Iran. For this aim, at first, daily streamflow of Sarough-cahy river of Zarinehrood basin was simulated using IHACRES rainfall-runoff model with daily rain gauge and temperature as input data from 1988 to 2008. Then, the model was calibrated in two different periods through comparison the simulated discharge with the observed one at hydrometric stations. Moreover, in order to evaluate the performance of satellite precipitation products in streamflow simulation, the calibrated model was validated using daily satellite rainfall estimates from the period of 2003 to 2008. The obtained results indicated that TMPA-3B42V7 with CC of 0.69, RMSE of 5.93 mm/day, MAE of 4.76 mm/day, and RBias of -5.39% performs better simulation of streamflow than those PERSIANN and CMORPH over the study area. It is noteworthy that in Iran, the availability of ground measuring station data is very limited because of the sparse density of hydro-meteorological networks. On the other hand, large spatial and temporal variability of precipitations and lack of a reliable and extensive observing system are the most important challenges to rainfall analysis, flood prediction, and other hydrological applications in this country.

Keywords: hydrological evaluation, IHACRES, satellite precipitation product, streamflow simulation

Procedia PDF Downloads 242
792 Status of Hazardous Waste Generation and Its Impacts on Environment and Human Health: A Study in West Bengal

Authors: Sk Ajim Ali

Abstract:

The present study is an attempt to overview on the major environmental and health impacts due to hazardous waste generation and poor management. In present scenario, not only hazardous waste, but as a common term ‘Waste’ is one of the acceptable and thinkable environmental issues. With excessive increasing population, industrialization and standardization of human’s life style heap in extra waste generation which is directly or indirectly related with hazardous waste generation. Urbanization and population growth are solely responsible for establishing industrial sector and generating various Hazardous Waste (HW) and concomitantly poor management practice arising adverse effect on environment and human health. As compare to other Indian state, West Bengal is not too much former in HW generation. West Bengal makes a rank of 7th in HW generation followed by Maharashtra, Gujarat, Tamil Nadu, U.P, Punjab and Andhra Pradesh. During the last 30 years, the industrial sectors in W.B have quadrupled in size, during 1995 there were only 440 HW generating Units in West Bengal which produced 129826 MTA hazardous waste but in 2011, it rose up into 609 units and it produced about 259777 MTA hazardous waste. So, the notable thing is that during a 15 year interval there increased 169 waste generating units but it produced about 129951 MTA of hazardous waste. Major chemical industries are the main sources of HW and causes of adverse effect on the environment and human health. HW from industrial sectors contains heavy metals, cyanides, pesticides, complex aromatic compounds (i.e. PCB) and other chemical which are toxic, flammable, reactive, and corrosive and have explosive properties which highly affect the surrounding environment and human health in and around he disposal sites. The main objective of present study is to highlight on the sources and components of hazardous waste in West Bengal and impacts of improper HW management on health and environment. This study is carried out based on a secondary source of data and qualitative method of research. The secondary data has been collected annual report of WBPCB, WHO’s report, research paper, article, books and so on. It has been found that excessive HW generation from various sources and communities has serious health hazards that lead to the spreading of infectious disease and environmental change.

Keywords: environmental impacts, existing HW generation and management practice, hazardous waste (HW), health impacts, recommendation and planning

Procedia PDF Downloads 285
791 Torque Loss Prediction Test Method of Bolted Joints in Heavy Commercial Vehicles

Authors: Volkan Ayik

Abstract:

Loosening as a result of torque loss in bolted joints is one of the most encountered problems resulting in loss of connection between parts. The main reason for this is the dynamic loads to which the joints are subjected while the vehicle is moving. In particular, vibration-induced loads can loosen the joints in any size and geometry. The aim of this study is to study an improved method due to road-induced vibration in heavy commercial vehicles for estimating the vibration performance of bolted joints of the components connected to the chassis, before conducting prototype level vehicle structural strength tests on a proving ground. The frequency and displacements caused by the road conditions-induced vibration loads have been determined for the parts connected to the chassis, and various experimental design scenarios have been formed by matching specific components and vibration behaviors. In the studies, the performance of the torque, washer, test displacement, and test frequency parameters were observed by maintaining the connection characteristics on the vehicle, and the sensitivity ratios for these variables were calculated. As a result of these experimental design findings, tests performed on a developed device based on Junker’s vibration device and proving ground conditions versus test correlation levels were found.

Keywords: bolted joints, junker’s test, loosening failure, torque loss

Procedia PDF Downloads 125
790 Technology in the Calculation of People Health Level: Design of a Computational Tool

Authors: Sara Herrero Jaén, José María Santamaría García, María Lourdes Jiménez Rodríguez, Jorge Luis Gómez González, Adriana Cercas Duque, Alexandra González Aguna

Abstract:

Background: Health concept has evolved throughout history. The health level is determined by the own individual perception. It is a dynamic process over time so that you can see variations from one moment to the next. In this way, knowing the health of the patients you care for, will facilitate decision making in the treatment of care. Objective: To design a technological tool that calculates the people health level in a sequential way over time. Material and Methods: Deductive methodology through text analysis, extraction and logical knowledge formalization and education with expert group. Studying time: September 2015- actually. Results: A computational tool for the use of health personnel has been designed. It has 11 variables. Each variable can be given a value from 1 to 5, with 1 being the minimum value and 5 being the maximum value. By adding the result of the 11 variables we obtain a magnitude in a certain time, the health level of the person. The health calculator allows to represent people health level at a time, establishing temporal cuts being useful to determine the evolution of the individual over time. Conclusion: The Information and Communication Technologies (ICT) allow training and help in various disciplinary areas. It is important to highlight their relevance in the field of health. Based on the health formalization, care acts can be directed towards some of the propositional elements of the concept above. The care acts will modify the people health level. The health calculator allows the prioritization and prediction of different strategies of health care in hospital units.

Keywords: calculator, care, eHealth, health

Procedia PDF Downloads 265
789 Modeling of Full Range Flow Boiling Phenomenon in 23m Long Vertical Steam Generator Tube

Authors: Chaitanya R. Mali, V. Vinod, Ashwin W. Patwardhan

Abstract:

Design of long vertical steam generator (SG) tubes in nuclear power plant involves an understanding of different aspects of flow boiling phenomenon such as flow instabilities, flow regimes, dry out, critical heat flux, pressure drop, etc. The knowledge of the prediction of local thermal hydraulic characteristics is necessary to understand these aspects. For this purpose, the methodology has been developed which covers all the flow boiling regimes to model full range flow boiling phenomenon. In this methodology, the vertical tube is divided into four sections based on vapor fraction value at the end of each section. Different modeling strategies have been applied to the different sections of the vertical tube. Computational fluid dynamics simulations have been performed on a vertical SG tube of 0.0126 m inner diameter and 23 m length. The thermal hydraulic parameters such as vapor fraction, liquid temperature, heat transfer coefficient, pressure drop, heat flux distribution have been analyzed for different designed heat duties (1.1 MW (20%) to 3.3 MW (60%)) and flow conditions (10 % to 80 %). The sensitivity of different boiling parameters such as bubble departure diameter, nucleation site density, bubble departure frequency on the thermal hydraulic parameters was also studied. Flow instability has been observed at 20 % designed heat duty and 20 % flow conditions.

Keywords: thermal hydraulics, boiling, vapor fraction, sensitivity

Procedia PDF Downloads 147
788 Rethinking the Value of Pancreatic Cyst CEA Levels from Endoscopic Ultrasound Fine-Needle Aspiration (EUS-FNA): A Longitudinal Analysis

Authors: Giselle Tran, Ralitza Parina, Phuong T. Nguyen

Abstract:

Background/Aims: Pancreatic cysts (PC) have recently become an increasingly common entity, often diagnosed as incidental findings on cross-sectional imaging. Clinically, management of the lesions is difficult because of uncertainties in their potential for malignant degeneration. Prior series have reported that carcinoembryonic antigen (CEA), a biomarker collected from cyst fluid aspiration, has a high diagnostic accuracy for discriminating between mucinous and non-mucinous lesions, at the patient’s initial presentation. To the author’s best knowledge, no prior studies have reported PC CEA levels obtained from endoscopic ultrasound fine-needle aspiration (EUS-FNA) over years of serial EUS surveillance imaging. Methods: We report a consecutive retrospective series of 624 patients who underwent EUS evaluation for a PC between 11/20/2009 and 11/13/2018. Of these patients, 401 patients had CEA values obtained at the point of entry. Of these, 157 patients had two or more CEA values obtained over the course of their EUS surveillance. Of the 157 patients (96 F, 61 M; mean age 68 [range, 62-76]), the mean interval of EUS follow-up was 29.7 months [3.5-128]. The mean number of EUS procedures was 3 [2-7]. To assess CEA value fluctuations, we defined an appreciable increase in CEA as "spikes" – two-times increase in CEA on a subsequent EUS-FNA of the same cyst, with the second CEA value being greater than 1000 ng/mL. Using this definition, cysts with a spike in CEA were compared to those without a spike in a bivariate analysis to determine if a CEA spike is associated with poorer outcomes and the presence of high-risk features. Results: Of the 157 patients analyzed, 29 had a spike in CEA. Of these 29 patients, 5 had a cyst with size increase >0.5cm (p=0.93); 2 had a large cyst, >3cm (p=0.77); 1 had a cyst that developed a new solid component (p=0.03); 7 had a cyst with a solid component at any time during surveillance (p=0.08); 21 had a complex cyst (p=0.34); 4 had a cyst categorized as "Statistically Higher Risk" based on molecular analysis (p=0.11); and 0 underwent surgical resection (p=0.28). Conclusion: With serial EUS imaging in the surveillance of PC, an increase in CEA level defined as a spike did not predict poorer outcomes. Most notably, a spike in CEA did not correlate with the number of patients sent to surgery or patients with an appreciable increase in cyst size. A spike in CEA did not correlate with the development of a solid nodule within the PC nor progression on molecular analysis. Future studies should focus on the selected use of CEA analysis when patients undergo EUS surveillance evaluation for PCs.

Keywords: carcinoembryonic antigen (CEA), endoscopic ultrasound (EUS), fine-needle aspiration (FNA), pancreatic cyst, spike

Procedia PDF Downloads 142
787 Detection of Internal Mold Infection of Intact Tomatoes by Non-Destructive, Transmittance VIS-NIR Spectroscopy

Authors: K. Petcharaporn

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

Procedia PDF Downloads 363
786 Quantitative Structure-Activity Relationship Analysis of Binding Affinity of a Series of Anti-Prion Compounds to Human Prion Protein

Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Milica Karadžić

Abstract:

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of eighteen compounds with anti-prion activity. The structures and anti-prion activities (expressed in response units, RU%) of the analyzed compounds are taken from CHEMBL database. In the first step of analysis 85 molecular descriptors were calculated and based on them the hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out in order to detect potential significant similarities or dissimilarities among the studied compounds. The calculated molecular descriptors were physicochemical, lipophilicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) descriptors. The first stage of the QSAR analysis was simple linear regression modeling. It resulted in one acceptable model that correlates Henry's law constant with RU% units. The obtained 2D-QSAR model was validated by cross-validation as an internal validation method. The validation procedure confirmed the model’s quality and therefore it can be used for prediction of anti-prion activity. The next stage of the analysis of anti-prion activity will include 3D-QSAR and molecular docking approaches in order to select the most promising compounds in treatment of prion diseases. These results are the part of the project No. 114-451-268/2016-02 financially supported by the Provincial Secretariat for Science and Technological Development of AP Vojvodina.

Keywords: anti-prion activity, chemometrics, molecular modeling, QSAR

Procedia PDF Downloads 304
785 A Machine Learning Approach for Earthquake Prediction in Various Zones Based on Solar Activity

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj

Abstract:

This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares

Procedia PDF Downloads 74
784 LWD Acquisition of Caliper and Drilling Mechanics in a Geothermal Well, A Case Study in Sorik Marapi Field – Indonesia

Authors: Vinda B. Manurung, Laila Warkhaida, David Hutabarat, Sentanu Wisnuwardhana, Christovik Simatupang, Dhani Sanjaya, Ashadi, Redha B. Putra, Kiki Yustendi

Abstract:

The geothermal drilling environment presents many obstacles that have limited the use of directional drilling and logging-while-drilling (LWD) technologies, such as borehole washout, mud losses, severe vibration, and high temperature. The case study presented in this paper demonstrates a practice to enhance data logging in geothermal drilling by deploying advanced telemetry and LWD technologies. This operation is aiming continuous improvement in geothermal drilling operations. The case study covers a 12.25-in. hole section of well XX-05 in Pad XX of the Sorik Marapi Geothermal Field. LWD string consists of electromagnetic (EM) telemetry, pressure while drilling (PWD), vibration (DDSr), and acoustic calliper (ACAL). Through this tool configuration, the operator acquired drilling mechanics and caliper logs in real-time and recorded mode, enabling effective monitoring of wellbore stability. Throughout the real-time acquisition, EM-PPM telemetry had provided a three times faster data rate to the surface unit. With the integration of Caliper data and Drilling mechanics data (vibration and ECD -equivalent circulating density), the borehole conditions were more visible to the directional driller, allowing for better control of drilling parameters to minimize vibration and achieve optimum hole cleaning in washed-out or tight formation sequences. After reaching well TD, the recorded data from the caliper sensor indicated an average of 8.6% washout for the entire 12.25-in. interval. Washout intervals were compared with loss occurrence, showing potential for the caliper to be used as an indirect indicator of fractured intervals and validating fault trend prognosis. This LWD case study has given added value in geothermal borehole characterization for both drilling operation and subsurface. Identified challenges while running LWD in this geothermal environment need to be addressed for future improvements, such as the effect of tool eccentricity and the impact of vibration. A perusal of both real-time and recorded drilling mechanics and caliper data has opened various possibilities for maximizing sensor usage in future wells.

Keywords: geothermal drilling, geothermal formation, geothermal technologies, logging-while-drilling, vibration, caliper, case study

Procedia PDF Downloads 132
783 Training Volume and Myoelectric Responses of Lower Body Muscles with Differing Foam Rolling Periods

Authors: Humberto Miranda, Haroldo G. Santana, Gabriel A. Paz, Vicente P. Lima, Jeffrey M. Willardson

Abstract:

Foam rolling is a practice that has increased in popularity before and after strength training. The purpose of this study was to compare the acute effects of different foam rolling periods for the lower body muscles on subsequent performance (total repetitions and training volume), myoelectric activity and rating of perceived exertion in trained men. Fourteen trained men (26.2 ± 3.2 years, 178 ± 0.04 cm height, 82.2 ± 10 kg weight and body mass index 25.9 ± 3.3kg/m2) volunteered for this study. Four repetition maximum (4-RM) loads were determined for hexagonal bar deadlift and 45º angled leg press during test and retest sessions over two nonconsecutive days. Five experimental protocols were applied in a randomized design, which included: a traditional protocol (control)—a resistance training session without prior foam rolling; or resistance training sessions performed following one (P1), two (P2), three (P3), or four (P4) sets of 30 sec. foam rolling for the lower extremity musculature. Subjects were asked to roll over the medial and lateral aspects of each muscle group with as much pressure as possible. All foam rolling was completed at a cadence of 50 bpm. These procedures were performed on both sides unilaterally as described below. Quadriceps: between the apex of the patella and the ASIS; Hamstring: between the gluteal fold and popliteal fossa; Triceps surae: between popliteal fossa and calcaneus tendon. The resistance training consisted of five sets with 4-RM loads and two-minute rest intervals between sets, and a four-minute rest interval between the hexagonal bar deadlift and the 45º angled leg press. The number of repetitions completed, the myoelectric activity of vastus lateralis (VL), vastus medialis oblique (VMO), semitendinosus (SM) and medial gastrocnemius (GM) were recorded, as well as the rating of perceived exertion for each protocol. There were no differences between the protocols in the total repetitions for the hexagonal bar deadlift (Control - 16.2 ± 5.9; P1 - 16.9 ± 5.5; P2 - 19.2 ± 5.7; P3 - 19.4 ± 5.2; P4 - 17.2 ± 8.2) (p > 0.05) and 45º angled leg press (Control - 23.3 ± 9.7; P1 - 25.9 ± 9.5; P2 - 29.1 ± 13.8; P3 - 28.0 ± 11.7; P4 - 30.2 ± 11.2) exercises. Similar results between protocols were also noted for myoelectric activity (p > 0.05) and rating of perceived exertion (p > 0.05). Therefore, the results of the present study indicated no deleterious effects on performance, myoelectric activity and rating of perceived exertion responses during lower body resistance training.

Keywords: self myofascial release, foam rolling, electromyography, resistance training

Procedia PDF Downloads 226
782 Improvements of the Difficulty in Hospital Acceptance at the Scene by the Introduction of Smartphone Application for Emergency-Medical-Service System: A Population-Based Before-And-After Observation Study in Osaka City, Japan

Authors: Yusuke Katayama, Tetsuhisa Kitamura, Kosuke Kiyohara, Sumito Hayashida, Taku Iwami, Takashi Kawamura, Takeshi Shimazu

Abstract:

Background: Recently, the number of ambulance dispatches has been increasing in Japan and it is, therefore, difficult to accept emergency patients to hospitals smoothly and appropriately because of the limited hospital capacity. To facilitate the request for patient transport by ambulances and hospital acceptance, the emergency information system using information technology has been built up and introduced in various communities. However, its effectiveness has not been insufficiently revealed in Japan. In 2013, we developed a smartphone application system that enables the emergency-medical-service (EMS) personnel to share information about on-scene ambulance and hospital situation. The aim of this study was to assess the introduction effect of this application for EMS system in Osaka City, Japan. Methods: This study was a retrospective study with population-based ambulance records of Osaka Municipal Fire Department. This study period was six years from January 1, 2010 to December 31, 2015. In this study, we enrolled emergency patients that on-scene EMS personnel conducted the hospital selection for them. The main endpoint was difficulty in hospital acceptance at the scene. The definition of difficulty in hospital acceptance at the scene was to make >=5 phone calls by EMS personnel at the scene to each hospital until a decision to transport was determined. The definition of the smartphone application group was emergency patients transported in the period of 2013-2015 after the introduction of this application, and we assessed the introduction effect of smartphone application with multivariable logistic regression model. Results: A total of 600,526 emergency patients for whom EMS personnel selected hospitals were eligible for our analysis. There were 300,131 smartphone application group (50.0%) in 2010-2012 and 300,395 non-smartphone application group (50.0%) in 2013-2015. The proportion of the difficulty in hospital acceptance was 14.2% (42,585/300,131) in the smartphone application group and 10.9% (32,819/300,395) in the non-smartphone application group, and the difficulty in hospital acceptance significantly decreased by the introduction of the smartphone application (adjusted odds ration; 0.730, 95% confidence interval; 0.718-0.741, P<0.001). Conclusions: Sharing information between ambulance and hospital by introducing smartphone application at the scene was associated with decreasing the difficulty in hospital acceptance. Our findings may be considerable useful for developing emergency medical information system with using IT in other areas of the world.

Keywords: difficulty in hospital acceptance, emergency medical service, infomation technology, smartphone application

Procedia PDF Downloads 275
781 Detection of Internal Mold Infection of Intact For Tomatoes by Non-Destructive, Transmittance VIS-NIR Spectroscopy

Authors: K. Petcharaporn, N. Prathengjit

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

Procedia PDF Downloads 519
780 Characterizing Solid Glass in Bending, Torsion and Tension: High-Temperature Dynamic Mechanical Analysis up to 950 °C

Authors: Matthias Walluch, José Alberto Rodríguez, Christopher Giehl, Gunther Arnold, Daniela Ehgartner

Abstract:

Dynamic mechanical analysis (DMA) is a powerful method to characterize viscoelastic properties and phase transitions for a wide range of materials. It is often used to characterize polymers and their temperature-dependent behavior, including thermal transitions like the glass transition temperature Tg, via determination of storage and loss moduli in tension (Young’s modulus, E) and shear or torsion (shear modulus, G) or other testing modes. While production and application temperatures for polymers are often limited to several hundred degrees, material properties of glasses usually require characterization at temperatures exceeding 600 °C. This contribution highlights a high temperature setup for rotational and oscillatory rheometry as well as for DMA in different modes. The implemented standard convection oven enables the characterization of glass in different loading modes at temperatures up to 950 °C. Three-point bending, tension and torsional measurements on different glasses, with E and G moduli as a function of frequency and temperature, are presented. Additional tests include superimposing several frequencies in a single temperature sweep (“multiwave”). This type of test results in a considerable reduction of the experiment time and allows to evaluate structural changes of the material and their frequency dependence. Furthermore, DMA in torsion and tension was performed to determine the complex Poisson’s ratio as a function of frequency and temperature within a single test definition. Tests were performed in a frequency range from 0.1 to 10 Hz and temperatures up to the glass transition. While variations in the frequency did not reveal significant changes of the complex Poisson’s ratio of the glass, a monotonic increase of this parameter was observed when increasing the temperature. This contribution outlines the possibilities of DMA in bending, tension and torsion for an extended temperature range. It allows the precise mechanical characterization of material behavior from room temperature up to the glass transition and the softening temperature interval. Compared to other thermo-analytical methods, like Dynamic Scanning Calorimetry (DSC) where mechanical stress is neglected, the frequency-dependence links measurement results (e.g. relaxation times) to real applications

Keywords: dynamic mechanical analysis, oscillatory rheometry, Poisson's ratio, solid glass, viscoelasticity

Procedia PDF Downloads 85
779 A Radiographic Superimposition in Orthognathic Surgery of Class III Skeletal Malocclusion

Authors: Albert Suryaprawira

Abstract:

Patients requiring correction of severe Class III skeletal discrepancy historically has been among the most challenging treatments for orthodontists. Correction of an aesthetic and functional problem is crucially important. This is a case report of an adult male aged 18 years who complained of difficulty in chewing and speaking. Patient has a prominent profile with mandibular excess. The pre-treatment cephalometric radiograph was taken to analyse the skeletal problem and to measure the amount of bone movement and the prediction soft tissue response. The panoramic radiograph was also taken to analyse bone quality, bone abnormality, third molar impaction, etc. Before the surgery, the pre-surgical cephalometric radiograph was taken to re-evaluate the plan and to settle the final amount of bone cut. After the surgery, the post-surgical cephalometric radiograph was taken to confirm the result with the plan. The superimposition between those radiographs was performed to analyse the outcome. It includes the superimposition of the cranial base, maxilla, and mandible. Superimposition is important to describe the amount of hard and soft tissue movement. It is also important to predict the possibility of relapse after the surgery. The patient needs to understand all the surgical plan, outcome and relapse prevention. The surgery included mandibular set back by bilateral sagittal split osteotomies. Although the discrepancy was severe using this combination of treatment and the use of radiographic superimposition, an aesthetically pleasing and stable result was achieved.

Keywords: cephalometric, mandibular set back, orthognathic, superimposition

Procedia PDF Downloads 258
778 The Relationship between Coping Styles and Internet Addiction among High School Students

Authors: Adil Kaval, Digdem Muge Siyez

Abstract:

With the negative effects of internet use in a person's life, the use of the Internet has become an issue. This subject was mostly considered as internet addiction, and it was investigated. In literature, it is noteworthy that some theoretical models have been proposed to explain the reasons for internet addiction. In addition to these theoretical models, it may be thought that the coping style for stressing events can be a predictor of internet addiction. It was aimed to test with logistic regression the effect of high school students' coping styles on internet addiction levels. Sample of the study consisted of 770 Turkish adolescents (471 girls, 299 boys) selected from high schools in the 2017-2018 academic year in İzmir province. Internet Addiction Test, Coping Scale for Child and Adolescents and a demographic information form were used in this study. The results of the logistic regression analysis indicated that the model of coping styles predicted internet addiction provides a statistically significant prediction of internet addiction. Gender does not predict whether or not to be addicted to the internet. The active coping style is not effective on internet addiction levels, while the avoiding and negative coping style are effective on internet addiction levels. With this model, % 79.1 of internet addiction in high school is estimated. The Negelkerke pseudo R2 indicated that the model accounted for %35 of the total variance. The results of this study on Turkish adolescents are similar to the results of other studies in the literature. It can be argued that avoiding and negative coping styles are important risk factors in the development of internet addiction.

Keywords: adolescents, coping, internet addiction, regression analysis

Procedia PDF Downloads 176
777 Frustration Measure for Dipolar Spin Ice and Spin Glass

Authors: Konstantin Nefedev, Petr Andriushchenko

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Usually under the frustrated magnetics, it understands such materials, in which ones the interaction between located magnetic moments or spins has competing character, and can not to be satisfied simultaneously. The most well-known and simplest example of the frustrated system is antiferromagnetic Ising model on the triangle. Physically, the existence of frustrations means, that one cannot select all three pairs of spins anti-parallel in the basic unit of the triangle. In physics of the interacting particle systems, the vector models are used, which are constructed on the base of the pair-interaction law. Each pair interaction energy between one-component vectors can take two opposite in sign values, excluding the case of zero. Mathematically, the existence of frustrations in system means that it is impossible to have all negative energies of pair interactions in the Hamiltonian even in the ground state (lowest energy). In fact, the frustration is the excitation, which leaves in system, when thermodynamics does not work, i.e. at the temperature absolute zero. The origin of the frustration is the presence at least of one ''unsatisfied'' pair of interacted spins (magnetic moments). The minimal relative quantity of these excitations (relative quantity of frustrations in ground state) can be used as parameter of frustration. If the energy of the ground state is Egs, and summary energy of all energy of pair interactions taken with a positive sign is Emax, that proposed frustration parameter pf takes values from the interval [0,1] and it is defined as pf=(Egs+Emax)/2Emax. For antiferromagnetic Ising model on the triangle pf=1/3. We calculated the parameters of frustration in thermodynamic limit for different 2D periodical structures of Ising dipoles, which were on the ribs of the lattice and interact by means of the long-range dipolar interaction. For the honeycomb lattice pf=0.3415, triangular - pf=0.2468, kagome - pf=0.1644. All dependencies of frustration parameter from 1/N obey to the linear law. The given frustration parameter allows to consider the thermodynamics of all magnetic systems from united point of view and to compare the different lattice systems of interacting particle in the frame of vector models. This parameter can be the fundamental characteristic of frustrated systems. It has no dependence from temperature and thermodynamic states, in which ones the system can be found, such as spin ice, spin glass, spin liquid or even spin snow. It shows us the minimal relative quantity of excitations, which ones can exist in system at T=0.

Keywords: frustrations, parameter of order, statistical physics, magnetism

Procedia PDF Downloads 170
776 Predicting Entrepreneurial Intentions among Undergraduates Using Theory of Planned Behaviour

Authors: Mohammed Abubakar Mawoli

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Theory of Planned Behavior (TPB) is a useful tool for predicting entrepreneurial intentions among individuals or groups of people. In view of the Nigerian government’s renewed educational policies and programs to prepare Nigerian undergraduates towards self-reliance and employers of labor after graduation, it becomes pertinent to empirically examine and predict the undergraduate’s entrepreneurial intentions at graduation. Thus, this study primarily examines the undergraduates entrepreneurial intentions using TPB, which includes perceived desirability, perceived social norm, and perceived feasibility factors. In so doing, a questionnaire research method was adopted in which 219 copies of a questionnaire distributed to final year undergraduates were belonging to five departments with a total population of 487 students. A combination of relative frequency, mean standard deviation and multiple regression statistical tools were employed for data analysis. The study found that TPB components exert a significant composite effect on undergraduate’s entrepreneurial intentions. Based on individual contribution of the independent variables, Perceived Desirability is the strongest predictor of the undergraduate’s entrepreneurial intentions, while Perceived Social Norm is a strong predictor of the undergraduate’s entrepreneurial intentions. However, Perceived Feasibility is not a strong predictor of student’s entrepreneurial intentions. The study therefore, recommends that the Perceived desirability, which is formed and shaped by ones level of education and skills acquisition, be improved upon to create the expected positive impact on graduates entrepreneurial intentions and possible venture creation.

Keywords: entrepreneurship, entrepreneurship education, entrepreneurial intentions, planned behaviour, prediction, Nigeria

Procedia PDF Downloads 301
775 Tuberculosis and Associated Transient Hyperglycaemia in Peri-Urban South Africa: Implications for Diabetes Screening in High Tuberculosis/HIV Burden Settings

Authors: Mmamapudi Kubjane, Natacha Berkowitz, Rene Goliath, Naomi S. Levitt, Robert J. Wilkinson, Tolu Oni

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Background: South Africa remains a high tuberculosis (TB) burden country globally and the burden of diabetes – a TB risk factor is growing rapidly. As an infectious disease, TB also induces transient hyperglycaemia. Therefore, screening for diabetes in newly diagnosed tuberculosis patients may result in misclassification of transient hyperglycaemia as diabetes. Objective: The objective of this study was to determine and compare the prevalence of hyperglycaemia (diabetes and impaired glucose regulation (IGR)) in TB patients and to assess the cross-sectional association between TB and hyperglycaemia at enrolment and after three months of follow-up. Methods: Consecutive adult TB and non-TB participants presenting at a TB clinic in Cape Town were enrolled in this cross-sectional study and follow-up between July 2013 and August 2015. Diabetes was defined as self-reported diabetes, fasting plasma glucose (FPG) ≥ 7.0 mmol·L⁻¹ or glycated haemoglobin (HbA1c) ≥ 6.5%. IGR was defined as FPG 5.5– < 7.0 mmol·L⁻¹ or HbA1c 5.7– < 6.5%. TB patients initiated treatment. After three months, all participants were followed up and screened for diabetes again. The association between TB and hyperglycaemia was assessed using logistic regression adjusting for potential confounders including sex, age, income, hypertension, waist circumference, previous prisoner, marital status, work status, HIV status. Results: Diabetes screening was performed in 852 participants (414 TB and 438 non-TB) at enrolment and in 639 (304 TB and 335 non-TB) at three-month follow-up. The prevalence of HIV-1 infection was 69.6% (95% confidence interval (CI), 64.9–73.8 %) among TB patients, and 58.2% (95% CI, 53.5–62.8 %) among the non-TB participants. Glycaemic levels were much higher in TB patients than in the non-TB participants but decreased over time. Among TB patients, the prevalence of IGR was 65.2% (95% CI 60.1 - 69.9) at enrollment and 21.5% (95% CI 17.2-26.5) at follow-up; and was 50% (45.1 - 54.94) and 32% (95% CI 27.9 - 38.0) respectively, among non-TB participants. The prevalence of diabetes in TB patients was 12.5% (95% CI 9.69 – 16.12%) at enrolment and 9.2% (95% CI, 6.43–13.03%) at follow-up; and was 10.04% (95% CI, 7.55–13.24%) and 8.06% (95% CI, 5.58–11.51) respectively, among non-TB participants. The association between TB and IGT was significant at enrolment (adjusted odds ratio (OR) 2.26 (95% CI, 1.55-3.31) but disappeared at follow-up 0.84 (0.53 - 1.36). However, the TB-diabetes association remained positive and significant both at enrolment (2.41 (95% CI, 1.3-4.34)) and follow-up (OR 3.31 (95% CI, 1.5 - 7.25)). Conclusion: Transient hyperglycaemia exists during tuberculosis. This has implications on diabetes screening in TB patients and suggests a need for diabetes confirmation tests during or after TB treatment. Nonetheless, the association between TB and diabetes noted at enrolment persists at 3 months highlighting the importance of diabetes control and prevention for TB control. Further research is required to investigate the impact of hyperglycaemia (transient or otherwise) on TB outcomes to ascertain the clinical significance of hyperglycemia at enrolment.

Keywords: diabetes, impaired glucose regulation, transient hyperglycaemia, tuberculosis

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774 Physiological Insight into an Age Old Biocontrol Practice in Banana Cultivation

Authors: Susmita Goswami, Joyeeta Mitra, Indu Gaur, Neha Bhadauria, Shilpi Shilpi, Prabir K. Paul

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'Malbhog’, an indigenous banana variety, much prized for its flavour and delicacy suffers production losses due to Fusarium oxysporum f.sp. cubense. The pathogen enters young plants through feeder roots causing wilting of plants ultimately leading to death of plants. The pathogen spreads rapidly to other plants in the field. In eastern part of India, this variety escapes the onslaught of the pathogen when either co-cultivated or rotated with Amorphophallus campanulatus (yam). The present study provides an insight into the physiological aspect of the biocontrol by yam. In vitro application of sterile aqueous extract of yam tuber (100gm/100ml distilled water and its 1:10 and 1:100 dilutions) were mixed with PDA media which was substantially inoculated with spores of Fusarium oxysporum f.sp. cubense. The extract could significantly reduce germination of pathogen spores. Banana variety susceptible to Fusarium sp was raised in soil rite under aseptic conditions. Spores of the pathogen (106 spores/ml) were inoculated into the soil rite. The plants were spread with aqueous extract of yam. The control plants were treated with sterilized distilled water. The activity of phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO) and peroxidase (POX) were estimated in leaves and roots at interval of 24 hours for 5 days after treatment. The incidence of wilt disease was recorded after two weeks. The results demonstrated that yam extract could induce significant activity of PAL, PPO and POX along with accumulation of phenols in both roots and leaves of banana plants. However, significantly high activity of enzymes and phenol accumulation was observed in roots. The disease incidence was significantly low in yam treated plants. The results clearly demonstrated the control of the pathogen due to induction of defense mechanism in the host by the extract. The observed control of the pathogen in the field could possibly be due to induction of such defense responses in host by exudates leached into the soil from yam tubers. Yam extract could be a potential source of environment-friendly biocide against Panama wilt of banana.

Keywords: Amorphophallus campanulatus, banana, Fusarium oxysporum f.sp. cubense, phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), peroxidase (POX)

Procedia PDF Downloads 264
773 A Hierarchical Method for Multi-Class Probabilistic Classification Vector Machines

Authors: P. Byrnes, F. A. DiazDelaO

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The Support Vector Machine (SVM) has become widely recognised as one of the leading algorithms in machine learning for both regression and binary classification. It expresses predictions in terms of a linear combination of kernel functions, referred to as support vectors. Despite its popularity amongst practitioners, SVM has some limitations, with the most significant being the generation of point prediction as opposed to predictive distributions. Stemming from this issue, a probabilistic model namely, Probabilistic Classification Vector Machines (PCVM), has been proposed which respects the original functional form of SVM whilst also providing a predictive distribution. As physical system designs become more complex, an increasing number of classification tasks involving industrial applications consist of more than two classes. Consequently, this research proposes a framework which allows for the extension of PCVM to a multi class setting. Additionally, the original PCVM framework relies on the use of type II maximum likelihood to provide estimates for both the kernel hyperparameters and model evidence. In a high dimensional multi class setting, however, this approach has been shown to be ineffective due to bad scaling as the number of classes increases. Accordingly, we propose the application of Markov Chain Monte Carlo (MCMC) based methods to provide a posterior distribution over both parameters and hyperparameters. The proposed framework will be validated against current multi class classifiers through synthetic and real life implementations.

Keywords: probabilistic classification vector machines, multi class classification, MCMC, support vector machines

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772 Flow Characteristics around Rectangular Obstacles with the Varying Direction of Obstacles

Authors: Hee-Chang Lim

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The study aims to understand the surface pressure distribution around the bodies such as the suction pressure in the leading edge on the top and side-face when the aspect ratio of bodies and the wind direction are changed, respectively. We carried out the wind tunnel measurement and numerical simulation around a series of rectangular bodies (40d×80w×80h, 80d×80w×80h, 160d×80w×80h, 80d×40w×80h and 80d×160w×80h in mm3) placed in a deep turbulent boundary layer. Based on a modern numerical platform, the Navier-Stokes equation with the typical 2-equation (k-ε model) and the DES (Detached Eddy Simulation) turbulence model has been calculated, and they are both compared with the measurement data. Regarding the turbulence model, the DES model makes a better prediction comparing with the k-ε model, especially when calculating the separated turbulent flow around a bluff body with sharp edged corner. In order to observe the effect of wind direction on the pressure variation around the cube (e.g., 80d×80w×80h in mm), it rotates at 0º, 10º, 20º, 30º, and 45º, which stands for the salient wind directions in the tunnel. The result shows that the surface pressure variation is highly dependent upon the approaching wind direction, especially on the top and the side-face of the cube. In addition, the transverse width has a substantial effect on the variation of surface pressure around the bodies, while the longitudinal length has little or no influence.

Keywords: rectangular bodies, wind direction, aspect ratio, surface pressure distribution, wind-tunnel measurement, k-ε model, DES model, CFD

Procedia PDF Downloads 238
771 The Possibility of Using Somatosensory Evoked Potential(SSEP) as a Parameter for Cortical Vascular Dementia

Authors: Hyunsik Park

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As the rate of cerebrovascular disease increases in old populations, the prevalence rate of vascular dementia would be expected. Therefore, authors designed this study to find out the possibility of somatosensory evoked potentials(SSEP) as a parameter for early diagnosis and prognosis prediction of vascular dementia in cortical vascular dementia patients. 21 patients who met the criteria for vascular dementia according to DSM-IV,ICD-10and NINDS-AIREN with the history of recent cognitive impairment, fluctuation progression, and neurologic deficit. We subdivided these patients into two groups; a mild dementia and a severe dementia groups by MMSE and CDR score; and analysed comparison between normal control group and patient control group who have been cerebrovascular attack(CVA) history without dementia by using N20 latency and amplitude of median nerve. In this study, mild dementia group showed significant differences on latency and amplitude with normal control group(p-value<0.05) except patient control group(p-value>0.05). Severe dementia group showed significant differences both normal control group and patient control group.(p-value<0.05, <001). Since no significant difference has founded between mild dementia group and patient control group, SSEP has limitation to use for early diagnosis test. However, the comparison between severe dementia group and others showed significant results which indicate SSEP can predict the prognosis of vascular dementia in cortical vascular dementia patients.

Keywords: SSEP, cortical vascular dementia, N20 latency, N20 amplitude

Procedia PDF Downloads 304
770 Relatively High Heart-Rate Variability Predicts Greater Survival Chances in Patients with Covid-19

Authors: Yori Gidron, Maartje Mol, Norbert Foudraine, Frits Van Osch, Joop Van Den Bergh, Moshe Farchi, Maud Straus

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Background: The worldwide pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-COV2), which began in 2019, also known as Covid-19, has infected over 136 million people and tragically took the lives of over 2.9 million people worldwide. Many of the complications and deaths are predicted by the inflammatory “cytokine storm.” One way to progress in the prevention of death is by finding a predictive and protective factor that inhibits inflammation, on the one hand, and which also increases anti-viral immunity on the other hand. The vagal nerve does precisely both actions. This study examined whether vagal nerve activity, indexed by heart-rate variability (HRV), predicts survival in patients with Covid-19. Method: We performed a pseudo-prospective study, where we retroactively obtained ECGs of 271 Covid-19 patients arriving at a large regional hospital in The Netherlands. HRV was indexed by the standard deviation of the intervals between normal heartbeats (SDNN). We examined patients’ survival at 3 weeks and took into account multiple confounders and known prognostic factors (e.g., age, heart disease, diabetes, hypertension). Results: Patients’ mean age was 68 (range: 25-95) and nearly 22% of the patients had died by 3 weeks. Their mean SDNN (17.47msec) was far below the norm (50msec). Importantly, relatively higher HRV significantly predicted a higher chance of survival, after statistically controlling for patients’ age, cardiac diseases, hypertension and diabetes (relative risk, H.R, and 95% confidence interval (95%CI): H.R = 0.49, 95%CI: 0.26 – 0.95, p < 0.05). However, since HRV declines rapidly with age and since age is a profound predictor in Covid-19, we split the sample by median age (40). Subsequently, we found that higher HRV significantly predicted greater survival in patients older than 70 (H.R = 0.35, 95%CI: 0.16 – 0.78, p = 0.01), but HRV did not predict survival in patients below age 70 years (H.R = 1.11, 95%CI: 0.37 – 3.28, p > 0.05). Conclusions: To the best of our knowledge, this is the first study showing that higher vagal nerve activity, as indexed by HRV, is an independent predictor of higher chances for survival in Covid-19. The results are in line with the protective role of the vagal nerve in diseases and extend this to a severe infectious illness. Studies should replicate these findings and then test in controlled trials whether activating the vagus nerve may prevent mortality in Covid-19.

Keywords: Covid-19, heart-rate Variability, prognosis, survival, vagal nerve

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769 Wind Speed Forecasting Based on Historical Data Using Modern Prediction Methods in Selected Sites of Geba Catchment, Ethiopia

Authors: Halefom Kidane

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This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights.

Keywords: artificial neural networks, forecasting, min-max normalization, wind speed

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768 Reliability Modeling on Drivers’ Decision during Yellow Phase

Authors: Sabyasachi Biswas, Indrajit Ghosh

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The random and heterogeneous behavior of vehicles in India puts up a greater challenge for researchers. Stop-and-go modeling at signalized intersections under heterogeneous traffic conditions has remained one of the most sought-after fields. Vehicles are often caught up in the dilemma zone and are unable to take quick decisions whether to stop or cross the intersection. This hampers the traffic movement and may lead to accidents. The purpose of this work is to develop a stop and go prediction model that depicts the drivers’ decision during the yellow time at signalised intersections. To accomplish this, certain traffic parameters were taken into account to develop surrogate model. This research investigated the Stop and Go behavior of the drivers by collecting data from 4-signalized intersections located in two major Indian cities. Model was developed to predict the drivers’ decision making during the yellow phase of the traffic signal. The parameters used for modeling included distance to stop line, time to stop line, speed, and length of the vehicle. A Kriging base surrogate model has been developed to investigate the drivers’ decision-making behavior in amber phase. It is observed that the proposed approach yields a highly accurate result (97.4 percent) by Gaussian function. It was observed that the accuracy for the crossing probability was 95.45, 90.9 and 86.36.11 percent respectively as predicted by the Kriging models with Gaussian, Exponential and Linear functions.

Keywords: decision-making decision, dilemma zone, surrogate model, Kriging

Procedia PDF Downloads 309
767 Efficacy of Yoga and Meditation Based Lifestyle Intervention on Inflammatory Markers in Patients with Rheumatoid Arthritis

Authors: Surabhi Gautam, Uma Kumar, Rima Dada

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A sustained acute-phase response in Rheumatoid Arthritis (RA) is associated with increased joint damage and inflammation leading to progressive disability. It is induced continuously by consecutive stimuli of proinflammatory cytokines, following a wide range of pathophysiological reactions, leading to increased synthesis of acute phase proteins like C - reactive protein (CRP) and dysregulation in levels of immunomodulatory soluble Human Leukocyte Antigen-G (HLA-G) molecule. This study was designed to explore the effect of yoga and meditation based lifestyle intervention (YMLI) on inflammatory markers in RA patients. Blood samples of 50 patients were collected at baseline (day 0) and after 30 days of YMLI. Patients underwent a pretested YMLI under the supervision of a certified yoga instructor for 30 days including different Asanas (physical postures), Pranayama (breathing exercises), and Dhayna (meditation). Levels of CRP, IL-6, IL-17A, soluble HLA-G and erythrocyte sedimentation rate (ESR) were measured at day 0 and 30 interval. Parameters of disease activity, disability quotient, pain acuity and quality of life were also assessed by disease activity score (DAS28), health assessment questionnaire (HAQ), visual analogue scale (VAS), and World Health Organization Quality of Life (WHOQOL-BREF) respectively. There was reduction in mean levels of CRP (p < 0.05), IL-6 (interleukin-6) (p < 0.05), IL-17A (interleukin-17A) (p < 0.05) and ESR (p < 0.05) and elevation in soluble HLA-G (p < 0.05) at 30 days compared to baseline level (day 0). There was reduction seen in DAS28-ESR (p < 0.05), VAS (p < 0.05) and HAQ (p < 0.05) after 30 days with respect to the base line levels (day 0) and significant increase in WHOQOL-BREF scale (p < 0.05) in all 4 domains of physical health, psychological health, social relationships, and environmental health. The present study has demonstrated that yoga practices are associated with regression of inflammatory processes by reducing inflammatory parameters and regulating the levels of soluble HLA-G significantly in active RA patients. Short term YMLI has significantly improved pain perception, disability quotient, disease activity and quality of life. Thus this simple life style intervention can reduce disease severity and dose of drugs used in the treatment of RA.

Keywords: inflammation, quality of life, rheumatoid arthritis, yoga and meditation

Procedia PDF Downloads 167