Search results for: parametric survival models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8113

Search results for: parametric survival models

7543 Chemometric Estimation of Inhibitory Activity of Benzimidazole Derivatives by Linear Least Squares and Artificial Neural Networks Modelling

Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić, Stela Jokić

Abstract:

The subject of this paper is to correlate antibacterial behavior of benzimidazole derivatives with their molecular characteristics using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on the inhibitory activity of benzimidazole derivatives against Staphylococcus aureus. The data were processed by linear least squares (LLS) and artificial neural network (ANN) procedures. The LLS mathematical models have been developed as a calibration models for prediction of the inhibitory activity. The quality of the models was validated by leave one out (LOO) technique and by using external data set. High agreement between experimental and predicted inhibitory acivities indicated the good quality of the derived models. These results are part of the CMST COST Action No. CM1306 "Understanding Movement and Mechanism in Molecular Machines".

Keywords: Antibacterial, benzimidazoles, chemometric, QSAR.

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7542 Studies on Race Car Aerodynamics at Wing in Ground Effect

Authors: Dharni Vasudhevan Venkatesan, K. E. Shanjay, H. Sujith Kumar, N. A. Abhilash, D. Aswin Ram, V. R. Sanal Kumar

Abstract:

Numerical studies on race car aerodynamics at wing in ground effect have been carried out using a steady 3d, double precision, pressure-based, and standard k-epsilon turbulence model. Through various parametric analytical studies we have observed that at a particular speed and ground clearance of the wings a favorable negative lift was found high at a particular angle of attack for all the physical models considered in this paper. The fact is that if the ground clearance height to chord length (h/c) is too small, the developing boundary layers from either side (the ground and the lower surface of the wing) can interact, leading to an altered variation of the aerodynamic characteristics at wing in ground effect. Therefore a suitable ground clearance must be predicted throughout the racing for a better performance of the race car, which obviously depends upon the coupled effects of the topography, wing orientation with respect to the ground, the incoming flow features and/or the race car speed. We have concluded that for the design of high performance and high speed race cars the adjustable wings capable to alter the ground clearance and the angles of attack is the best design option for any race car for racing safely with variable speeds.

Keywords: external aerodynamics, external flow choking, race car aerodynamics, wing in ground effect

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7541 Innovative Activity and Development: Analysing Firm Data from Eurozone Country-Members

Authors: Ilias A. Makris

Abstract:

In this work, we attempt to associate firm characteristics with innovative activity. We collect microdata from listed firms of selected Eurozone Country-members, after the beginning of 2007 financial crisis. The following literature, several indicators of growth and performance were selected and tested for their ability to interpret innovative activity. The main scope is to examine the possible differences in performance and growth between innovative and non-innovative firms, during a severe recession. Additionally to that, a special focus will be held on whether macroeconomic performance and national innovation system, determines the extent of innovators' performance. Preliminary findings, through correlation matrices and non-parametric tests, strongly indicate the positive relation between innovative activity and most of the measures used (profitability, size, employment), confirming that even during a recessionary period, innovative firms not only survive but also seem to succeed better economic results in almost all indexes relative to non-innovative. However, even though innovators seem to perform better in all economies examined, the extent of that performance seems to be strongly affected by the supportive mechanisms (financial and structural) that their country provides. Thus, it is clear, that the technologically intensive 'gap' between European South and North, during the economic crisis, became chaotic, due to the harsh austerity measures and reduced budgets in those countries, even in sectors with high potentials in economic activity and employment, impairing the effects of crisis and enhancing the vicious circle of recession.

Keywords: eurozone, innovative activity, development, firm performance, non-parametric tests

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7540 Fusion of MOLA-based DEMs and HiRISE Images for Large-Scale Mars Mapping

Authors: Ahmed F. Elaksher, Islam Omar

Abstract:

In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were then digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. Different transformation models, including the affine and projective transformation models, were used with different sets and distributions of tie points. Additionally, we evaluated the use of the MOLA elevations in co-registering the MOLA and HiRISE datasets. The planimetric RMSEs achieved for each model are reported. Results suggested the use of 3D-2D transformation models.

Keywords: photogrammetry, Mars, MOLA, HiRISE

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7539 Evaluation of QSRR Models by Sum of Ranking Differences Approach: A Case Study of Prediction of Chromatographic Behavior of Pesticides

Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

Abstract:

The present study deals with the selection of the most suitable quantitative structure-retention relationship (QSRR) models which should be used in prediction of the retention behavior of basic, neutral, acidic and phenolic pesticides which belong to different classes: fungicides, herbicides, metabolites, insecticides and plant growth regulators. Sum of ranking differences (SRD) approach can give a different point of view on selection of the most consistent QSRR model. SRD approach can be applied not only for ranking of the QSRR models, but also for detection of similarity or dissimilarity among them. Applying the SRD analysis, the most similar models can be found easily. In this study, selection of the best model was carried out on the basis of the reference ranking (“golden standard”) which was defined as the row average values of logarithm of retention time (logtr) defined by high performance liquid chromatography (HPLC). Also, SRD analysis based on experimental logtr values as reference ranking revealed similar grouping of the established QSRR models already obtained by hierarchical cluster analysis (HCA).

Keywords: chemometrics, chromatography, pesticides, sum of ranking differences

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7538 Exploration of Critical Success Factors in Business and Management in Artificial Intelligence Era

Authors: Najah Kalifah Almazmomi

Abstract:

In the time of artificial intelligence (AI), there is a need to know the determinants of success in business management, which are taking on a new dimension. This research purports to scrutinize the Critical Success Factors (CSFs) that drive and ignite the fire of success to help uncover the subtle and profound dynamics that might be operative in organizations. By means of a systematic literature review and a number of empirical methods, the paper is aimed at determining and assessing the key aspects of CSFs, putting emphasis on their role and meaning in the context of AI technology adoption. Some central features such as leadership ways, innovation models, strategic thinking methodologies, organizational culture transformations, and human resource management approaches are compared and contrasted with the AI-driven revolution. Additionally, this research will explore the interactive effects of these factors and their joint impact on the success, survival, and flexibility of a business in the current environment, which is changing due to AI development. Through the use of different qualitative and quantitative methodologies, the research concludes that the findings are significant in understanding the relative roles of individual CSFs and in studying the interactions between them in such an AI-enabled business environment.

Keywords: critical success factors, business and management, artificial intelligence, leadership strategies

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7537 Dual Language Immersion Models in Theory and Practice

Authors: S. Gordon

Abstract:

Dual language immersion is growing fast in language teaching today. This study provides an overview and evaluation of the different models of Dual language immersion programs in US K-12 schools. First, the paper provides a brief current literature review on the theory of Dual Language Immersion (DLI) in Second Language Acquisition (SLA) studies. Second, examples of several types of DLI language teaching models in US K-12 public schools are presented (including 50/50 models, 90/10 models, etc.). Third, we focus on the unique example of DLI education in the state of Utah, a successful, growing program in K-12 schools that includes: French, Chinese, Spanish, and Portuguese. The project investigates the theory and practice particularly of the case of public elementary and secondary school children that study half their school day in the L1 and the other half in the chosen L2, from kindergarten (age 5-6) through high school (age 17-18). Finally, the project takes the observations of Utah French DLI elementary through secondary programs as a case study. To conclude, we look at the principal challenges, pedagogical objectives and outcomes, and important implications for other US states and other countries (such as France currently) that are in the process of developing similar language learning programs.

Keywords: dual language immersion, second language acquisition, language teaching, pedagogy, teaching, French

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7536 Impact of Firm Location and Organizational Structure on Receipt and Effectiveness of Social Assistance

Authors: Nalanda Matia, Julia Zhao, Amber Jaycocks, Divya Sinha

Abstract:

Social assistance programs for businesses are intended to improve their survival and growth in the face of catastrophic events like the COVID-19 pandemic. However, that goal remains unfulfilled when the mostwantingbusinesses fail to participate in such programs. Reasons for non-participation can include lack of information, inability to cope with applications and program compliance, as well as some programs’ non-entitlement status. Some of these factors may be associated with the organizational and locational characteristics of these businesses. This research investigates these organizational and locational factorsthat determine receipt and effectiveness of social assistance among the firms that receive it. of A sample of firms from the universe of 3 rounds of Small Business Administration backed Paycheck Protection Program recipient and similarly profiled non recipient businesses are used to analyze this question. Initial results show firm organizational factors like size and spatial factors like broadband coverage at firm location impact application for and subsequent receipt of assistance for digitally administered programs. Further, Line of business and wage structure of recipients’ impact effectiveness of the assistance dollars.

Keywords: public economics, economics of social assistance, firm organizational structure, survival analysis

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7535 Fixed-Bed Column Studies of Green Malachite Removal by Use of Alginate-Encapsulated Aluminium Pillared Clay

Authors: Lazhar mouloud, Chemat Zoubida, Ouhoumna Faiza

Abstract:

The main objective of this study, concerns the modeling of breakthrough curves obtained in the adsorption column of malachite green into alginate-encapsulated aluminium pillared clay in fixed bed according to various operating parameters such as the initial concentration, the feed rate and the height fixed bed, applying mathematical models namely: the model of Bohart and Adams, Wolborska, Bed Depth Service Time, Clark and Yoon-Nelson. These models allow us to express the different parameters controlling the performance of the dynamic adsorption system. The results have shown that all models were found suitable for describing the whole or a definite part of the dynamic behavior of the column with respect to the flow rate, the inlet dye concentration and the height of fixed bed.

Keywords: adsorption column, malachite green, pillared clays, alginate, modeling, mathematic models, encapsulation.

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7534 An Improvement of a Dynamic Model of the Secondary Sedimentation Tank and Field Validation

Authors: Zahir Bakiri, Saci Nacefa

Abstract:

In this paper a comparison in made between two models, with and without dispersion term, and focused on the characterization of the movement of the sludge blanket in the secondary sedimentation tank using the solid flux theory and the velocity settling. This allowed us develop a one-dimensional models, with and without dispersion based on a thorough experimental study carried out in situ and the application of online data which are the mass load flow, transfer concentration, and influent characteristic. On the other hand, in the proposed model, the new settling velocity law (double-exponential function) used is based on the Vesilind function.

Keywords: wastewater, activated sludge, sedimentation, settling velocity, settling models

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7533 Ocular Complications, Adverse Effects of the Procedure, Side-effects of Medications Used for Graft Survival, and Preventable Vision Loss in Live-related Renal Transplant Recipients: Experience at a Transplant Centre in Pakistan

Authors: Fatema Ali Lanewala, Akhtar Jamal Khan

Abstract:

The ocular complications in renal transplant recipients at the biggest transplant center in Pakistan were seen to be diverse, multiple, and sight-threatening. These complications could mainly be due to the primary disease causing renal failure, the process of transplantation, and/or the medications used pre and post-transplantation. A retrospective case series recently published in the Journal of Pakistan Medical Association highlights the common ocular pathologies encountered in renal transplant population. Majority of the patients suffered from cataract, which is a known side-effect of long-term steroids routinely used for graft survival. There was a unique finding in Pakistani population, never reported before from any other transplant centre world over; a large number of recipients was reported to be suffering from night blindness, which significantly improved on vitamin A supplementation. There were a variety of other ocular complications seen which emphasizes the necessity of ocular care and routine examination of transplant recipient’s eyes by an ophthalmologist in order to avoid visual compromise and improve the quality of life of the transplant recipient.

Keywords: cataract, night blindness, ocular complications, renal transplantation

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7532 Mapping Poverty in the Philippines: Insights from Satellite Data and Spatial Econometrics

Authors: Htet Khaing Lin

Abstract:

This study explores the relationship between a diverse set of variables, encompassing both environmental and socio-economic factors, and poverty levels in the Philippines for the years 2012, 2015, and 2018. Employing Ordinary Least Squares (OLS), Spatial Lag Models (SLM), and Spatial Error Models (SEM), this study delves into the dynamics of key indicators, including daytime and nighttime land surface temperature, cropland surface, urban land surface, rainfall, population size, normalized difference water, vegetation, and drought indices. The findings reveal consistent patterns and unexpected correlations, highlighting the need for nuanced policies that address the multifaceted challenges arising from the interplay of environmental and socio-economic factors.

Keywords: poverty analysis, OLS, spatial lag models, spatial error models, Philippines, google earth engine, satellite data, environmental dynamics, socio-economic factors

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7531 The Significance of Seasonality on the Airport Efficiency in Touristic Regions

Authors: Ioanna Pagoni, Annitsa Koumoutsidi

Abstract:

The aim of this paper is to estimate the efficiency of airports that are located in touristic regions. It focuses on the regional airports of Greece, which are located at the mainland and the islands that constitute touristic destinations. Most of these airports share the following characteristics. They operate at levels below capacity with a high level of seasonality to their traffic. In addition, in such airports, the operation of charter and low-cost airlines is significant. The efficiency of the study airports is calculated by using the non-parametric data envelopment analysis during the period of 2010-2016. The selected inputs include several airport infrastructure measures such as passenger terminal size, aircraft parking area, runway length, and the number of check-in counters, while the number of employees in each airport is also used. The number of passengers and aircraft movements are selected as outputs. The effect of seasonality, as well as the operation of charter airlines and low-cost carriers on airport efficiency, is estimated by running proper regression models. Preliminary findings indicate that low-cost and charter airlines contribute to increasing airport efficiency for most of the study airports. The results of this research could be useful for airlines, airport operators, hotel businesses, and other tourism-related operators.

Keywords: airport efficiency, data envelopment analysis, low-cost carriers, charter airlines, seasonality

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7530 Development of a Tilt-Rotor Aircraft Model Using System Identification Technique

Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

Abstract:

The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

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7529 Outcomes of the Gastrocnemius Flap Performed by Orthopaedic Surgeons in Salvage Revision Knee Arthroplasty: A Retrospective Study at a Tertiary Orthopaedic Centre

Authors: Amirul Adlan, Robert McCulloch, Scott Evans, Michael Parry, Jonathan Stevenson, Lee Jeys

Abstract:

Background and Objectives: The gastrocnemius myofascial flap is used to manage soft-tissue defects over the anterior aspect of the knee in the context of a patient presenting with a sinus and periprosthetic joint infection (PJI) or extensor mechanism failure. The aim of this study was twofold: firstly, to evaluate the outcomes of gastrocnemius flaps performed by appropriately trained orthopaedic surgeons in the context of PJI and, secondly, to evaluate the infection-free survival of this patient group. Methods: We retrospectively reviewed 30 patients who underwent gastrocnemius flap reconstruction during staged revision total knee arthroplasty for prosthetic joint infection (PJI). All flaps were performed by an orthopaedic surgeon with orthoplastics training. Patients had a mean age of 68.9 years (range 50–84) and were followed up for a mean of 50.4 months (range 2–128 months). A total of 29 patients (97 %) were categorized into Musculoskeletal Infection Society (MSIS) local extremity grade 3 (greater than two compromising factors), and 52 % of PJIs were polymicrobial. The primary outcome measure was flap failure, and the secondary outcome measure was a recurrent infection. Results: Flap survival was 100% with no failures or early returns to theatre for flap problems such as necrosis or haematoma. Overall infection-free survival during the study period was 48% (13 of 27 infected cases). Using limb salvage as the outcome, 77% (23 of 30 patients) retained the limb. Infection recurrence occurred in 48% (10 patients) in the type B3 cohort and 67% (4 patients) in the type C3 cohort (p = 0.65). Conclusion: The surgical technique for a gastrocnemius myofascial flap is reliable and reproducible when performed by appropriately trained orthopaedic surgeons, even in high-risk groups. However, the risks of recurrent infection and amputation remain high within our series due to poor host and extremity factors.

Keywords: gastrocnemius flap, limb salvage, revision arthroplasty, outcomes

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7528 Geopotential Models Evaluation in Algeria Using Stochastic Method, GPS/Leveling and Topographic Data

Authors: M. A. Meslem

Abstract:

For precise geoid determination, we use a reference field to subtract long and medium wavelength of the gravity field from observations data when we use the remove-compute-restore technique. Therefore, a comparison study between considered models should be made in order to select the optimal reference gravity field to be used. In this context, two recent global geopotential models have been selected to perform this comparison study over Northern Algeria. The Earth Gravitational Model (EGM2008) and the Global Gravity Model (GECO) conceived with a combination of the first model with anomalous potential derived from a GOCE satellite-only global model. Free air gravity anomalies in the area under study have been used to compute residual data using both gravity field models and a Digital Terrain Model (DTM) to subtract the residual terrain effect from the gravity observations. Residual data were used to generate local empirical covariance functions and their fitting to the closed form in order to compare their statistical behaviors according to both cases. Finally, height anomalies were computed from both geopotential models and compared to a set of GPS levelled points on benchmarks using least squares adjustment. The result described in details in this paper regarding these two models has pointed out a slight advantage of GECO global model globally through error degree variances comparison and ground-truth evaluation.

Keywords: quasigeoid, gravity aomalies, covariance, GGM

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7527 Parametric Study and Design on under Reamed Pile - An Experimental and Numerical Study

Authors: S. Chandrakaran, Aarthy D.

Abstract:

Abstract: Under reamed piles are piles which are of different types like bored cast in-situ pile or bored compaction concrete piles where one or more bulbs are provided. In this paper, the design procedure of under reamed pile by both experimental study and numerical study using PLAXIS 3D Foundation software was studied. The soil chosen for study was M Sand. The Single and double under reamed pile modelling was made using mild steel. The pile load test experiment was conducted in the laboratory and the ultimate compression load for 25 mm settlement on single and double under reamed pile was observed and finally the result was compared with conventional pile (pile without bulb). The parametric influence on under reamed pile was studied by varying the geometrical parameters like diameter of bulbs, spacing between bulbs, position of bulbs and number of bulbs. The results of the numerical model showed that when the diameter of bulb D u =2.5D, the ultimate compression load for an under-reamed pile with a single bulb increased by 55 % compared to a pile without a bulb. It was observed that when the spacing between the bulbs was S=6D u with three different positions of bulb from bottom of pile as D u , 2D u and 3D u , the ultimate compression load increased by 88%, 94% and 73 % respectively, compared to the ultimate compression load for 25 mm settlement on conventional pile and if spacing was more than 6D u , ultimate compression load for 25 mm settlement started to decrease. It was observed that when the bucket length was more than 2D u , the ultimate compression

Keywords: load capcity, under remed bulb . sand, model study, sand

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7526 Effects of Delphinidin on Lipid Metabolism in HepG2 Cells and Diet-Induced Obese Mice

Authors: Marcela Parra-Vargas, Ana Sandoval-Rodriguez, Roberto Rodriguez-Echevarria, Jose Dominguez-Rosales, Juan Armendariz-Borunda

Abstract:

Non-alcoholic fatty liver disease (NAFLD) is characterized by an excess of hepatic lipids, and it is to author’s best knowledge, the most prevalent chronic liver disorder. Anthocyanin-rich food consumption is linked to health benefits in metabolic disorders associated with obesity and NAFLD, although the precise functional role of anthocyanidin delphinidin (Dp) has yet to be established. The aim of this study was to investigate the effect of the Dp in NAFLD metabolic alterations by evaluating prevention or amelioration of hepatic lipid accumulation, as well as molecular mechanisms in two experimental obesity-related models of NALFD. In vitro: HepG2 cells were incubated with sodium palmitate (PA, 1 mM) to induce lipotoxic damage, and concomitantly treated with Dp (180 uM) for 24 h. Subsequently, total lipid accumulation was measured by colorimetric staining with Oil Red O, and total intrahepatic triglycerides were determined by an enzymatic assay. To assess molecular mechanisms, cells were pre-treated with PA for 24 h and then exposed to Dp for 1 h. In vivo: four-week-old male C57BL/6Nhsd mice were allocated in two main groups. Mice were fed with standard diet (control) or high-fat and high-carbohydrate diet (45% fat, HFD) for 16 wk to induce NAFLD. Then HFD was divided into subgroups: one treated orally with Dp (15 mg/kg bw, HFD-Dp) every day for 4 wk, while HFD group treated with vehicle (DMSO). Weight and fasting glucose were recorded weekly, while dietary ingestion was measured daily. Insulin tolerance test was performed at the end of treatment. Liver histology was evaluated with H&E and Masson’s trichrome stain. RT-PCR was used to evaluate gene expression and Western Blot to determine levels of protein in both experimental models. Parametric data were analyzed with one-way ANOVA and Tukey’s post-hoc test. Kruskal-Wallis and Mann-Whitney U test for non-parametric data, and P < 0.5 were considered significant. Dp prevented hepatic lipid accumulation by PA in HepG2 hepatocytes. Furthermore, Dp down-regulated gene expression of SREBP1c, FAS, and CPT1a without modifying AMPK phosphorylation levels. In vivo, Dp oral administration did not ameliorate lipid metabolic alterations raised by HFD. Adiposity, dietary ingestion, fasting glucose, and insulin sensitivity after Dp treatment remained similar to HFD group. Histological analysis showed hepatic damage in HFD groups and no differences between HFD and HFD-Dp groups were found. Hepatic gene expression of ACC and FAS were not altered by HFD. SREBP1c was similar in both HFD and HFD-Dp groups. No significant changes were observed in SREBP1c, ACC, and FAS adipose tissue gene expression by HFD or Dp treatment. Additionally, immunoblotting analysis revealed no changes in pathway SIRT1-LKB-AMPK and PPAR alpha by both HFD groups compared to control. In conclusion, the antioxidant Dp may provoke beneficial effects in the prevention of hepatic lipid accumulation. Nevertheless, the oral dose administrated in mice that simulated the total intake of anthocyanins consumed daily by humans has no effect as a treatment on hepatic lipid metabolic alterations and histological abnormalities associated with exposure to chronic HFD. A healthy lifestyle with regular intake of antioxidants such as anthocyanins may prevent metabolic alterations in NAFLD.

Keywords: anthocyanins, antioxidants, delphinidin, non-alcoholic fatty liver disease, obesity

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7525 The Prognostic Values of Current Staging Schemes in Temporal Bone Carcinoma: A Real-World Evidence-Based Study

Authors: Minzi Mao, Jianjun Ren, Yu Zhao

Abstract:

Objectives: The absence of a uniform staging scheme for temporal bone carcinoma (TBC) seriously impedes the improvement of its management strategies. Therefore, this research was aimed to investigate the prognostic values of two currently applying staging schemes, namely, the modified Pittsburgh staging system (MPB) and Stell’s T classification (Stell-T) in patients with TBC. Methods: Areal-world single-institution retrospectivereview of patientsdiagnosed with TBC between2008 and 2019 was performed. Baseline characteristics were extracted, and patients were retrospectively staged by both the MPB and Stell-T classifications. Cox regression analyseswereconductedtocomparetheoverall survival (OS). Results: A total of 69 consecutive TBC patients were included in thisstudy. Univariate analysis showed that both Stell-T and T- classifications of the modified Pittsburgh staging system (MPB-T) were significant prognostic factors for all TBC patients as well as temporal bone squamous cell carcinoma (TBSCC, n=50) patients (P < 0.05). However, only Stell-T was confirmed to be an independent prognostic factor in TBSCC patients (P = 0.004). Conclusions: Tumor extensions, quantified by both Stell-T and MPB-T classifications, are significant prognostic factors for TBC patients, especially for TBSCC patients. However, only the Stell-T classification is an independent prognostic factor for TBSCC patients.

Keywords: modified pittsburgh staging system, overall survival, prognostic factor, stell’s T- classification, temporal bone carcinoma

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7524 Plant Identification Using Convolution Neural Network and Vision Transformer-Based Models

Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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7523 Sensitivity and Uncertainty Analysis of One Dimensional Shape Memory Alloy Constitutive Models

Authors: A. B. M. Rezaul Islam, Ernur Karadogan

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Shape memory alloys (SMAs) are known for their shape memory effect and pseudoelasticity behavior. Their thermomechanical behaviors are modeled by numerous researchers using microscopic thermodynamic and macroscopic phenomenological point of view. Tanaka, Liang-Rogers and Ivshin-Pence models are some of the most popular SMA macroscopic phenomenological constitutive models. They describe SMA behavior in terms of stress, strain and temperature. These models involve material parameters and they have associated uncertainty present in them. At different operating temperatures, the uncertainty propagates to the output when the material is subjected to loading followed by unloading. The propagation of uncertainty while utilizing these models in real-life application can result in performance discrepancies or failure at extreme conditions. To resolve this, we used probabilistic approach to perform the sensitivity and uncertainty analysis of Tanaka, Liang-Rogers, and Ivshin-Pence models. Sobol and extended Fourier Amplitude Sensitivity Testing (eFAST) methods have been used to perform the sensitivity analysis for simulated isothermal loading/unloading at various operating temperatures. As per the results, it is evident that the models vary due to the change in operating temperature and loading condition. The average and stress-dependent sensitivity indices present the most significant parameters at several temperatures. This work highlights the sensitivity and uncertainty analysis results and shows comparison of them at different temperatures and loading conditions for all these models. The analysis presented will aid in designing engineering applications by eliminating the probability of model failure due to the uncertainty in the input parameters. Thus, it is recommended to have a proper understanding of sensitive parameters and the uncertainty propagation at several operating temperatures and loading conditions as per Tanaka, Liang-Rogers, and Ivshin-Pence model.

Keywords: constitutive models, FAST sensitivity analysis, sensitivity analysis, sobol, shape memory alloy, uncertainty analysis

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7522 Measuring Environmental Efficiency of Energy in OPEC Countries

Authors: Bahram Fathi, Seyedhossein Sajadifar, Naser Khiabani

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Data envelopment analysis (DEA) has recently gained popularity in energy efficiency analysis. A common feature of the previously proposed DEA models for measuring energy efficiency performance is that they treat energy consumption as an input within a production framework without considering undesirable outputs. However, energy use results in the generation of undesirable outputs as byproducts of producing desirable outputs. Within a joint production framework of both desirable and undesirable outputs, this paper presents several DEA-type linear programming models for measuring energy efficiency performance. In addition to considering undesirable outputs, our models treat different energy sources as different inputs so that changes in energy mix could be accounted for in evaluating energy efficiency. The proposed models are applied to measure the energy efficiency performances of 12 OPEC countries and the results obtained are presented.

Keywords: energy efficiency, undesirable outputs, data envelopment analysis

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7521 Enhancing Model Interoperability and Reuse by Designing and Developing a Unified Metamodel Standard

Authors: Arash Gharibi

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Mankind has always used models to solve problems. Essentially, models are simplified versions of reality, whose need stems from having to deal with complexity; many processes or phenomena are too complex to be described completely. Thus a fundamental model requirement is that it contains the characteristic features that are essential in the context of the problem to be solved or described. Models are used in virtually every scientific domain to deal with various problems. During the recent decades, the number of models has increased exponentially. Publication of models as part of original research has traditionally been in in scientific periodicals, series, monographs, agency reports, national journals and laboratory reports. This makes it difficult for interested groups and communities to stay informed about the state-of-the-art. During the modeling process, many important decisions are made which impact the final form of the model. Without a record of these considerations, the final model remains ill-defined and open to varying interpretations. Unfortunately, the details of these considerations are often lost or in case there is any existing information about a model, it is likely to be written intuitively in different layouts and in different degrees of detail. In order to overcome these issues, different domains have attempted to implement their own approaches to preserve their models’ information in forms of model documentation. The most frequently cited model documentation approaches show that they are domain specific, not to applicable to the existing models and evolutionary flexibility and intrinsic corrections and improvements are not possible with the current approaches. These issues are all because of a lack of unified standards for model documentation. As a way forward, this research will propose a new standard for capturing and managing models’ information in a unified way so that interoperability and reusability of models become possible. This standard will also be evolutionary, meaning members of modeling realm could contribute to its ongoing developments and improvements. In this paper, the current 3 of the most common metamodels are reviewed and according to pros and cons of each, a new metamodel is proposed.

Keywords: metamodel, modeling, interoperability, reuse

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7520 Implied Adjusted Volatility by Leland Option Pricing Models: Evidence from Australian Index Options

Authors: Mimi Hafizah Abdullah, Hanani Farhah Harun, Nik Ruzni Nik Idris

Abstract:

With the implied volatility as an important factor in financial decision-making, in particular in option pricing valuation, and also the given fact that the pricing biases of Leland option pricing models and the implied volatility structure for the options are related, this study considers examining the implied adjusted volatility smile patterns and term structures in the S&P/ASX 200 index options using the different Leland option pricing models. The examination of the implied adjusted volatility smiles and term structures in the Australian index options market covers the global financial crisis in the mid-2007. The implied adjusted volatility was found to escalate approximately triple the rate prior the crisis.

Keywords: implied adjusted volatility, financial crisis, Leland option pricing models, Australian index options

Procedia PDF Downloads 360
7519 Prevalence, Median Time, and Associated Factors with the Likelihood of Initial Antidepressant Change: A Cross-Sectional Study

Authors: Nervana Elbakary, Sami Ouanes, Sadaf Riaz, Oraib Abdallah, Islam Mahran, Noriya Al-Khuzaei, Yassin Eltorki

Abstract:

Major Depressive Disorder (MDD) requires therapeutic interventions during the initial month after being diagnosed for better disease outcomes. International guidelines recommend a duration of 4–12 weeks for an initial antidepressant (IAD) trial at an optimized dose to get a response. If depressive symptoms persist after this duration, guidelines recommend switching, augmenting, or combining strategies as the next step. Most patients with MDD in the mental health setting have been labeled incorrectly as treatment-resistant where in fact they have not been subjected to an adequate trial of guideline-recommended therapy. Premature discontinuation of IAD due to ineffectiveness can cause unfavorable consequences. Avoiding irrational practices such as subtherapeutic doses of IAD, premature switching between the ADs, and refraining from unjustified polypharmacy can help the disease to go into a remission phase We aimed to determine the prevalence and the patterns of strategies applied after an IAD was changed because of a suboptimal response as a primary outcome. Secondary outcomes included the median survival time on IAD before any change; and the predictors that were associated with IAD change. This was a retrospective cross- sectional study conducted in Mental Health Services in Qatar. A dataset between January 1, 2018, and December 31, 2019, was extracted from the electronic health records. Inclusion and exclusion criteria were defined and applied. The sample size was calculated to be at least 379 patients. Descriptive statistics were reported as frequencies and percentages, in addition, to mean and standard deviation. The median time of IAD to any change strategy was calculated using survival analysis. Associated predictors were examined using two unadjusted and adjusted cox regression models. A total of 487 patients met the inclusion criteria of the study. The average age for participants was 39.1 ± 12.3 years. Patients with first experience MDD episode 255 (52%) constituted a major part of our sample comparing to the relapse group 206(42%). About 431 (88%) of the patients had an occurrence of IAD change to any strategy before end of the study. Almost half of the sample (212 (49%); 95% CI [44–53%]) had their IAD changed less than or equal to 30 days. Switching was consistently more common than combination or augmentation at any timepoint. The median time to IAD change was 43 days with 95% CI [33.2–52.7]. Five independent variables (age, bothersome side effects, un-optimization of the dose before any change, comorbid anxiety, first onset episode) were significantly associated with the likelihood of IAD change in the unadjusted analysis. The factors statistically associated with higher hazard of IAD change in the adjusted analysis were: younger age, un-optimization of the IAD dose before any change, and comorbid anxiety. Because almost half of the patients in this study changed their IAD as early as within the first month, efforts to avoid treatment failure are needed to ensure patient-treatment targets are met. The findings of this study can have direct clinical guidance for health care professionals since an optimized, evidence-based use of AD medication can improve the clinical outcomes of patients with MDD; and also, to identify high-risk factors that could worsen the survival time on IAD such as young age and comorbid anxiety

Keywords: initial antidepressant, dose optimization, major depressive disorder, comorbid anxiety, combination, augmentation, switching, premature discontinuation

Procedia PDF Downloads 130
7518 Evaluation of Environmental, Technical, and Economic Indicators of a Fused Deposition Modeling Process

Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

Abstract:

Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: additive manufacturing, decision-makings, environmental impact, predictive models

Procedia PDF Downloads 108
7517 Finite Element Analysis of Raft Foundation on Various Soil Types under Earthquake Loading

Authors: Qassun S. Mohammed Shafiqu, Murtadha A. Abdulrasool

Abstract:

The design of shallow foundations to withstand different dynamic loads has given considerable attention in recent years. Dynamic loads may be due to the earthquakes, pile driving, blasting, water waves, and machine vibrations. But, predicting the behavior of shallow foundations during earthquakes remains a difficult task for geotechnical engineers. A database for dynamic and static parameters for different soils in seismic active zones in Iraq is prepared which has been collected from geophysical and geotechnical investigation works. Then, analysis of a typical 3-D soil-raft foundation system under earthquake loading is carried out using the database. And a parametric study has been carried out taking into consideration the influence of some parameters on the dynamic behavior of the raft foundation, such as raft stiffness, damping ratio as well as the influence of the earthquake acceleration-time records. The results of the parametric study show that the settlement caused by the earthquake can be decreased by about 72% with increasing the thickness from 0.5 m to 1.5 m. But, it has been noticed that reduction in the maximum bending moment by about 82% was predicted by decreasing the raft thickness from 1.5 m to 0.5 m in all sites model. Also, it has been observed that the maximum lateral displacement, the maximum vertical settlement and the maximum bending moment for damping ratio 0% is about 14%, 20%, and 18% higher than that for damping ratio 7.5%, respectively for all sites model.

Keywords: shallow foundation, seismic behavior, raft thickness, damping ratio

Procedia PDF Downloads 137
7516 Leveraging Unannotated Data to Improve Question Answering for French Contract Analysis

Authors: Touila Ahmed, Elie Louis, Hamza Gharbi

Abstract:

State of the art question answering models have recently shown impressive performance especially in a zero-shot setting. This approach is particularly useful when confronted with a highly diverse domain such as the legal field, in which it is increasingly difficult to have a dataset covering every notion and concept. In this work, we propose a flexible generative question answering approach to contract analysis as well as a weakly supervised procedure to leverage unannotated data and boost our models’ performance in general, and their zero-shot performance in particular.

Keywords: question answering, contract analysis, zero-shot, natural language processing, generative models, self-supervision

Procedia PDF Downloads 163
7515 Dow Polyols near Infrared Chemometric Model Reduction Based on Clustering: Reducing Thirty Global Hydroxyl Number (OH) Models to Less Than Five

Authors: Wendy Flory, Kazi Czarnecki, Matthijs Mercy, Mark Joswiak, Mary Beth Seasholtz

Abstract:

Polyurethane Materials are present in a wide range of industrial segments such as Furniture, Building and Construction, Composites, Automotive, Electronics, and more. Dow is one of the leaders for the manufacture of the two main raw materials, Isocyanates and Polyols used to produce polyurethane products. Dow is also a key player for the manufacture of Polyurethane Systems/Formulations designed for targeted applications. In 1990, the first analytical chemometric models were developed and deployed for use in the Dow QC labs of the polyols business for the quantification of OH, water, cloud point, and viscosity. Over the years many models have been added; there are now over 140 models for quantification and hundreds for product identification, too many to be reasonable for support. There are 29 global models alone for the quantification of OH across > 70 products at many sites. An attempt was made to consolidate these into a single model. While the consolidated model proved good statistics across the entire range of OH, several products had a bias by ASTM E1655 with individual product validation. This project summary will show the strategy for global model updates for OH, to reduce the number of models for quantification from over 140 to 5 or less using chemometric methods. In order to gain an understanding of the best product groupings, we identify clusters by reducing spectra to a few dimensions via Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Results from these cluster analyses and a separate validation set allowed dow to reduce the number of models for predicting OH from 29 to 3 without loss of accuracy.

Keywords: hydroxyl, global model, model maintenance, near infrared, polyol

Procedia PDF Downloads 117
7514 Benchmarking Machine Learning Approaches for Forecasting Hotel Revenue

Authors: Rachel Y. Zhang, Christopher K. Anderson

Abstract:

A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

Procedia PDF Downloads 115