Search results for: activity models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12433

Search results for: activity models

11743 The Martingale Options Price Valuation for European Puts Using Stochastic Differential Equation Models

Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

Abstract:

In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

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11742 The Hyperbolic Smoothing Approach for Automatic Calibration of Rainfall-Runoff Models

Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

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This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

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11741 A Unified Webcam Proctoring Solution on Edge

Authors: Saw Thiha, Jay Rajasekera

Abstract:

A boom in video conferencing generated millions of hours of video data daily to be analyzed. However, such enormous data pose certain scalability issues to be analyzed efficiently, let alone do it in real-time, as online conferences can involve hundreds of people and can last for hours. This paper proposes an efficient online proctoring solution that can analyze the online conferences real-time on edge devices such as Android, iOS, and desktops. Since the computation can be done upfront on the devices where online conferences take place, it can scale well without requiring intensive resources such as GPU servers and complex cloud infrastructure. According to the linear models, face orientation does indeed impact the perceived eye openness. Also, the proposed z score facial landmark standardization was proven to be functional in detecting face orientation and contributed to classifying eye blinks with single eyelid distance computation while achieving a better f1 score and accuracy than the Eye Aspect Ratio (EAR) threshold method. Last but not least, the authors implemented the solution natively in the MediaPipe framework and open-sourced it along with the reproducible experimental results on GitHub. The solution provides face orientation, eye blink, facial activity, and translation detections out of the box and is highly customizable and extensible.

Keywords: android, desktop, edge computing, blink, face orientation, facial activity and translation, MediaPipe, open source, real-time, video conference, web, iOS, Z score facial landmark standardization

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11740 Developing Location-allocation Models in the Three Echelon Supply Chain

Authors: Mehdi Seifbarghy, Zahra Mansouri

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In this paper a few location-allocation models are developed in a multi-echelon supply chain including suppliers, manufacturers, distributors and retailers. The objectives are maximizing demand coverage, minimizing the total distance of distributors from suppliers, minimizing some facility establishment costs and minimizing the environmental effects. Since nature of the given models is multi-objective, we suggest a number of goal-based solution techniques such L-P metric, goal programming, multi-choice goal programming and goal attainment in order to solve the problems.

Keywords: location, multi-echelon supply chain, covering, goal programming

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11739 A Machine Learning Model for Dynamic Prediction of Chronic Kidney Disease Risk Using Laboratory Data, Non-Laboratory Data, and Metabolic Indices

Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

Abstract:

Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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11738 Isolation, Characterization and Optimization of Alkalophilic and Thermotolerant Lipase from Bacillus subtilis Strain

Authors: Indu Bhushan Sharma, Rashmi Saraswat

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The thermotolerant, solvent stable and alkalophilic lipase producing bacterial strain was isolated from the water sample of the foothills of Trikuta Mountain in Kakryal (Reasi district) in Jammu and Kashmir, India. The lipase-producing microorganisms were screened using tributyrin agar plates. The selected microbe was optimized for maximum lipase production by subjecting to various carbon and nitrogen sources, incubation period and inoculum size. The selected strain was identified as Bacillus subtilis strain kakrayal_1 (BSK_1) using 16S rRNA sequence analysis. Effect of pH, temperature, metal ions, detergents and organic solvents were studied on lipase activity. Lipase was found to be stable over a pH range of 6.0 to 9.0 and exhibited maximum activity at pH 8. Lipolytic activity was highest at 37°C and the enzyme activity remained at 60°C for 24hrs, hence, established as thermo-tolerant. Production of lipase was significantly induced by vegetable oil and the best nitrogen source was found to be peptone. The isolated Bacillus lipase was stimulated by pre-treatment with Mn2+, Ca2+, K+, Zn2+, and Fe2+. Lipase was stable in detergents such as triton X 100, tween 20 and Tween 80. The 100% ethyl acetate enhanced lipase activity whereas, lipase activity were found to be stable in Hexane. The optimization resulted in 4 fold increase in lipase production. Bacillus lipases are ‘generally recognized as safe’ (GRAS) and are industrially interesting. The inducible alkaline, thermo-tolerant lipase exhibited the ability to be stable in detergents and organic solvents. This could be further researched as a potential biocatalyst for industrial applications such as biotransformation, detergent formulation, bioremediation and organic synthesis.

Keywords: bacillus, lipase, thermotolerant, alkalophilic

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11737 The Effect of Sexual Assault on Sport Participation Trajectories from Adolescence through Young Adulthood

Authors: Chung Gun Lee

Abstract:

Objectives: Certain life change events were shown to have strong effects on physical activity-related behavior, but more research is needed to investigate the longer-term effects of different life change events on physical activity-related behaviors. The purpose of this study is to examine the effect of experiencing physically or non-physically forced sexual activity on sports participation from adolescence to young adulthood. Methods: This study used the National Longitudinal Study of Adolescent Health (Add Health) data. Group-based trajectory modeling was utilized to examine the effect of experiencing sexual assault on trajectories of sports participation from adolescence to young adulthood. Results: Male participants were divided into three trajectory groups (i.e., Low-stable, High-decreasing, and High-stable) and female participants were divided into two trajectory groups (i.e., Low-stable and High-decreasing). The main finding of this study is that women who experienced non-physically forced sexual activity significantly decreases sports participation throughout the trajectory in ‘High-decreasing group.’ The effect of non-physically forced sexual activity on women’s sports participation was considerably weakened and became insignificant after including psychological depression in the model as a potential mediator. Discussion: Special attention should be paid to sport participation among women victims of non-physically forced sexual activity. Further studies are needed to examine other potential mediators in addition to psychological depression when examining the effect of non-physically forced sexual activity on sport participation in women.

Keywords: adolescent, group-based trajectory modeling, sexual assault, young adult

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11736 Intensive Use of Software in Teaching and Learning Calculus

Authors: Nodelman V.

Abstract:

Despite serious difficulties in the assimilation of the conceptual system of Calculus, software in the educational process is used only occasionally, and even then, mainly for illustration purposes. The following are a few reasons: The non-trivial nature of the studied material, Lack of skills in working with software, Fear of losing time working with software, The variety of the software itself, the corresponding interface, syntax, and the methods of working with the software, The need to find suitable models, and familiarize yourself with working with them, Incomplete compatibility of the found models with the content and teaching methods of the studied material. This paper proposes an active use of the developed non-commercial software VusuMatica, which allows removing these restrictions through Broad support for the studied mathematical material (and not only Calculus). As a result - no need to select the right software, Emphasizing the unity of mathematics, its intrasubject and interdisciplinary relations, User-friendly interface, Absence of special syntax in defining mathematical objects, Ease of building models of the studied material and manipulating them, Unlimited flexibility of models thanks to the ability to redefine objects, which allows exploring objects characteristics, and considering examples and counterexamples of the concepts under study. The construction of models is based on an original approach to the analysis of the structure of the studied concepts. Thanks to the ease of construction, students are able not only to use ready-made models but also to create them on their own and explore the material studied with their help. The presentation includes examples of using VusuMatica in studying the concepts of limit and continuity of a function, its derivative, and integral.

Keywords: counterexamples, limitations and requirements, software, teaching and learning calculus, user-friendly interface and syntax

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11735 A Novel Peptide Showing Universal Effect against Multiple Viruses in Vitro and in Vivo

Authors: Hanjun Zhao, Ke Zhang, Bojian Zheng

Abstract:

Background: So far, there is no universal antiviral agent which can inhibit multiple viral infections. More and more drug-resistant viral strains emerge after the antiviral drug application for treatment. Defensins are the front line of host innate immunity and have broad spectrum antibacterial and antiviral effects. However, there is limited data to show if these defensins have good antiviral activity in vivo and what the antiviral mechanism is. Subjects: To investigate a peptide with widespread antivirus activity in vitro and in vivo and illustrate the antiviral mechanism. Methods: Antiviral peptide library designed from mouse beta defensins was synthesized by the company. Recombinant beta defensin was obtained from E. coli. Antiviral activity in vitro was assayed by plaque assay, qPCR. Antiviral activity in vivo was detected by animal challenge with 2009 pandemic H1N1 influenza A virus. The antiviral mechanism was assayed by western blot, ELISA, and qPCR. Conclusions: We identify a new peptide which has widespread effects against multiple viruses (H1N1, H5N1, H7N9, MERS-CoV) in vitro and has efficient antivirus activity in vivo. This peptide inhibits viral entry into target cells and subsequently blocks viral replication. The in vivo study of the antiviral peptide against other viral infections and the investigation of its more detail antiviral mechanism are ongoing.

Keywords: antiviral peptide, defensin, Influenza A virus, mechanism

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11734 Antifungal Activity of Silver Colloidal Nanoparticles against Phytopathogenic Fungus (Phomopsis sp.) in Soybean Seeds

Authors: J. E. Mendes, L. Abrunhosa, J. A. Teixeira, E. R. de Camargo, C. P. de Souza, J. D. C. Pessoa

Abstract:

Among the many promising nanomaterials with antifungal properties, metal nanoparticles (silver nanoparticles) stand out due to their high chemical activity. Therefore, the aim of this study was to evaluate the effect of silver nanoparticles (AgNPs) against Phomopsis sp. AgNPs were synthesized by silver nitrate reduction with sodium citrate and stabilized with ammonia. The synthesized AgNPs have further been characterized by UV/Visible spectroscopy, Biophysical techniques like Dynamic light scattering (DLS) and Scanning Electron Microscopy (SEM). The average diameter of the prepared silver colloidal nanoparticles was about 52 nm. Absolute inhibitions (100%) were observed on treated with a 270 and 540 µg ml-1 concentration of AgNPs. The results from the study of the AgNPs antifungal effect are significant and suggest that the synthesized silver nanoparticles may have an advantage compared with conventional fungicides.

Keywords: antifungal activity, Phomopsis sp., seeds, silver nanoparticles, soybean

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11733 Synthesis and Analgesic activity of 2-(p-Substituted phenyl)-3-[4-(N-Substituted amino) methyl-2-oxo indoilin-3-ylidene]benzenesulfonyl Quinazolin-4(3H)-One Derivatives

Authors: N. Gopal, K. Jaasminerjiit, L. Z. Xiang

Abstract:

Quinazoline-4(3H)-one ring system has been consistently regarded as promising privileged structural icon owing to its pharmacodynamic versatility in many of its synthetic derivatives as well as in several naturally occurring alkaloids. The literature reveals that 2nd & 3rd positions of the quinazolin-4(3H)-one pharmacophore are the target for substitution with other moieties. On the other hand, sulphanilamide derivatives and isatin moiety also displayed valuable biological activities. Hence, it was thought worthwhile to study the effects of three pharmacophoric moieties like quinazolinone, sulphanilamide and isatin in a single molecule for the better analgesic activity with lower toxicity. Series of novel 2,3-disubstituted quinazolin-4(3H)-one derivatives have been synthesised from the intermediate Schiff base of 2-(4’-substitutedphenyl)-3-[(N-2-oxoindolin-3-ylidene)-4”-sulphonamidophenyl]-quinazolin-4(3H)-one derivatives, which was prepared from reacting 2-(substituted phenyl)-4H-benzo[d][1,3]-oxazin-4-one with sulphanilamide. The required benzoxazinone derivatives were prepared by reacting anthranilic acid with benzoyl chloride. All the compounds structure was characterised by using H1 NMR, IR and Mass spectroscopy. The intermediate Schiff base and final Mannich base compounds were evaluated for their analgesic activity by acetic acid-induced writhing method at the dose of 25mg/kg, 50 mg/kg, and 100 mg/kg (bw) and Diclofenac (25mg/kg of body weight) will be used as the reference drugs. From the results of the study, it has been observed that final Mannich base showed a better analgesic activity when compared to the parent Schiff bases, it was found that compound substituted with N-methyl piperazine at 1st position of the indole nucleus of the final quinazolinone derivatives (GA4B1) i.e. 2-(4’-methoxy phenyl)-3-[4-(N-(1-N-methyl piperazine amine) methyl-2-oxo indoilin-3-ylidene] benzenesulfonyl quinazolin-4(3H)-one increases the analgesic activity and among the synthesised compounds, GA4B1 exhibited quite superior analgesic activity. The remaining Schiff bases and Mannich base derivatives exhibited moderate analgesic activity. All the compounds showed a dose dependent activity. None of the synthesised compound showed ulcer index whereas the standard drug, diclofenac [25 mg/kg (bw)] showed significantly higher gross ulcer index values.

Keywords: analgesic activity, isatin, mannich base, quinazolin-4(3H)-one

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11732 Antibacterial Activity of Nickel Oxide Composite Films with Chitosan/Polyvinyl Chloride/Polyethylene Glycol

Authors: Ali Garba Danjani, Abdulrasheed Halliru Usman

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Due to the rapidly increasing biological applications and antibacterial properties of versatile chitosan composites, the effects of chitosan/polyvinyl chloride composites film were investigated. Chitosan/polyvinyl chloride films were prepared by a casting method. Polyethylene glycol (PEG) was used as a plasticizer in the blending stage of film preparation. Characterizations of films were done by Scanning Electron microscopy (SEM), Fourier transforms infrared spectroscopy (FTIR), and thermogravimetric analyzer (TGA). Chitosan composites incorporation enhanced the antibacterial activity of chitosan films against Escherichia coli and Staphylococcus aureus. The composite film produced is proposed as packaging or coating material because of its flexibility, antibacterial efficacy, and good mechanical strength.

Keywords: chitosan, polymeric nanocomposites, antibacterial activity, polymer blend

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11731 Blind Speech Separation Using SRP-PHAT Localization and Optimal Beamformer in Two-Speaker Environments

Authors: Hai Quang Hong Dam, Hai Ho, Minh Hoang Le Ngo

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This paper investigates the problem of blind speech separation from the speech mixture of two speakers. A voice activity detector employing the Steered Response Power - Phase Transform (SRP-PHAT) is presented for detecting the activity information of speech sources and then the desired speech signals are extracted from the speech mixture by using an optimal beamformer. For evaluation, the algorithm effectiveness, a simulation using real speech recordings had been performed in a double-talk situation where two speakers are active all the time. Evaluations show that the proposed blind speech separation algorithm offers a good interference suppression level whilst maintaining a low distortion level of the desired signal.

Keywords: blind speech separation, voice activity detector, SRP-PHAT, optimal beamformer

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11730 Prediction of Anticancer Potential of Curcumin Nanoparticles by Means of Quasi-Qsar Analysis Using Monte Carlo Method

Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain

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The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.

Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR

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11729 Analysis of the Elastic Energy Released and Characterization of the Eruptive Episodes Intensity’s during 2014-2015 at El Reventador Volcano, Ecuador

Authors: Paúl I. Cornejo

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The elastic energy released through Strombolian explosions has been quite studied, detailing various processes, sources, and precursory events at several volcanoes. We realized an analysis based on the relative partitioning of the elastic energy radiated into the atmosphere and ground by Strombolian-type explosions recorded at El Reventador volcano, using infrasound and seismic signals at high and moderate seismicity episodes during intense eruptive stages of explosive and effusive activity. Our results show that considerable values of Volcano Acoustic-Seismic Ratio (VASR or η) are obtained at high seismicity stages. VASR is a physical diagnostic of explosive degassing that we used to compare eruption mechanisms at El Reventador volcano for two datasets of explosions recorded at a Broad-Band BB seismic and infrasonic station located at ~5 kilometers from the vent. We conclude that the acoustic energy EA released during explosive activity (VASR η = 0.47, standard deviation σ = 0.8) is higher than the EA released during effusive activity; therefore, producing the highest values of η. Furthermore, we realized the analysis and characterization of the eruptive intensity for two episodes at high seismicity, calculating a η three-time higher for an episode of effusive activity with an occasional explosive component (η = 0.32, and σ = 0.42), than a η for an episode of only effusive activity (η = 0.11, and σ = 0.18), but more energetic.

Keywords: effusive, explosion quakes, explosive, Strombolian, VASR

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11728 The Relationships between Physical Activity Levels, Enjoyment of Physical Activity, and Body Mass Index among Bruneian Secondary School Adolescents

Authors: David Xiaoqian Sun, Khairunnisa Binti Haji Sibah, Jr., Lejak Anak Ambol

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The purpose of the study was to examine the relationships between objectively measured physical activity levels (PALs), enjoyment of physical activity (EPA), and body mass index (BMI) among adolescents. A total of 188 12-14-year-old Bruneian secondary school adolescents (88 boys and 100 girls) voluntarily took part in this study. Subjects wore the RT3 accelerometer for seven consecutive days in order to measure their PALs. Times of students’ engagement in total (TPA), light (LPA), moderate (MPV), and vigorous PA (VPA) were obtained from the accelerometer. Their BMIs were calculated from their body height and weight. Physical Activity Enjoyment Scale (PACES) was administrated to obtain their EPA levels. Four key enjoyment factors including fun factors, positive perceptions, unexciting in doing activities, and negative perceptions were identified. Subjects’ social economic status (SES) was provided by school administration. Results show that all the adolescents did not meet the recommended PA guidelines even though boys were engaged in more MVPA than girls. No relationships were found between BMI and all PALs in both boys and girls. BMI was significantly related to the PACES scores (r = -.22, p = 0.01), fun factors (r = -.20, p = 0.05) and positive perceptions (r =-.21, p < 0.05). The PACES scores were significantly related to LPA (r = .18, p = 0.01) but not related to MVPA (r = .04, p > 0.05). After controlling for age and SES, BMI was only significantly related to the PACES scores in girls (r = -.27, p < .01) but boys (r = -.06, p > 0.05). Fun factors were significantly related to LPA and MVPA (p < .01) in girls while negative perceptions were significantly related to LPA and MVPA (p < .01) in boys. This study provides evidence that enjoyment may be a trigger of LPA but MVPA and may be influenced by their BMI status particularly in girls. Based on these findings, physical and health educators are suggested to not only make PA more enjoyable, but also consider gender differences in promoting adolescents' participation in MVPA.

Keywords: accelerometer, body mass index, enjoyment of physical activity, moderate to vigorous physical activity

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11727 Evaluation of ROS Mediated Apoptosis Induced by Tuber Extract of Dioscorea Bulbifera on Human Breast Adenocarcinoma

Authors: Debasmita Dubey, Rajesh Kumar Meher, Smruti Pragya Samal, Pradeep Kumar Naik

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Background: To determine antioxidant properties and anticancer activity by ROS and mitochondrial transmembrane potential mediated apoptosis against MCF7, MDA-MB-231, cell line. Methods: Leaf sample was extracted using methanol by microwave digestion technique. The antioxidant properties of the methanolic extract were determined by a DPPH scavenging assay. In vitro anticancer activity, mitochondrial transmembrane potential, apoptosis activity and DNA fragmentation study, as well as intracellular ROS activity of most potential leaf extract, were also determined by using the MDA-MB-231cell line. In vivo animal toxicity study was carried out using mice model. Results: Methanolic leaf extract has shown the highest antioxidant, as well as anticancer activity, is based on the assay conducted. For the identification of active phytochemicals from methanolic extract, High-resolution mass spectroscopy-LCMS was used. In vitro cytotoxicity study against MCF-7 and MDA-MB-231 cell line and IC 50 value was found to be 37.5µg/ml. From histopathological studies, no toxicity in liver and kidney tissue was identified. Conclusion: This plant tuber can be used as a regular diet to reduce the chance of breast cancer. Further, more studies should be conducted to isolate and identify the responsible compound.

Keywords: human breast adenocarcinoma, ROS, mitochondrial transmembrane, apoptosis

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11726 Seasonal Stirred Variations in Chemical Composition and Antifungal Activity of Medicinal Plants Turraea holstii and Clausena anisata

Authors: Francis Machumi, Ester Innocent, Pius Yanda, Philip C. Stevenson

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Curative dependence of traditionally used medicinal plants on season of harvest is an alleged claim by traditional health practitioners. This study intended to verify these claims by investigating antifungal activity and chemical composition of traditionally used medicinal plants Turraea holstii and Clausena anisata harvested in rainy season and dry season. The antifungal activities were determined by broth microdilution method whereas chemical profiling of the extracts from the plant materials was done by gas chromatography (GC). Results indicated that extracts of plant materials harvested in dry season showed enhanced antifungal activity as compared to extracts of plant materials harvested in rainy season. GC chromatograms showed overalls increase in number and amount of chemical species for extracts of plant materials harvested in dry season as compared to extracts of plant materials harvested in rainy season.

Keywords: antifungal activity, chemical composition, medicinal plants, seasonal dependence

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11725 Biotechnology Approach: A Tool of Enhancement of Sticky Mucilage of Pulicaria Incisa (Medicinal Plant) for Wounds Treatment

Authors: Djamila Chabane, Asma Rouane, Karim Arab

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Depending of the chemical substances responsible for the pharmacological effects, a future therapeutic drug might be produced by extraction from whole plants or by callus initiated from some parts. The optimized callus culture protocols now offer the possibility to use cell culture techniques for vegetative propagation and open minds for further studies on secondary metabolites and drug establishment. In Algerian traditional medicine, Pulicaria incisa (Asteraceae) is used in the treatment of daily troubles (stomachache, headhache., cold, sore throat and rheumatic arthralgia). Field findings revealed that many healers use some fresh parts (leaves, flowers) of this plant to treat skin wounds. This study aims to evaluate the healing efficiency of artisanal cream prepared from sticky mucilage isolated from calluses on dermal wounds of animal models. Callus cultures were initiated from reproductive explants (young inflorescences) excised from adult plants and transferred to a MS basal medium supplemented with growth regulators and maintained under dark for for months. Many calluses types were obtained with various color and aspect (friable, compact). Several subcultures of calli were performed to enhance the mucilage accumulation. After extraction, the mucilage extracts were tested on animal models as follows. The wound healing potential was studied by causing dermal wounds (1 cm diameter) at the dorsolumbar part of Rattus norvegicus; different samples of the cream were applied after hair removal on three rats each, including two controls (one treated by Vaseline and one without any treatment), two experimental groups (experimental group 1, treated with a reference ointment "Madecassol® and experimental group 2 treated by callus mucilage cream for a period of seventeen days. The evolution of the healing activity was estimated by calculating the percentage reduction of the area wounds treated by all compounds tested compared to the controls by using AutoCAD software. The percentage of healing effect of the cream prepared from callus mucilage was (99.79%) compared to that of Madecassol® (99.76%). For the treatment time, the significant healing activity was observed after 17 days compared to that of the reference pharmaceutical products without any wound infection. The healing effect of Madecassol® is more effective because it stimulates and regulates the production of collagen, a fibrous matrix essential for wound healing. Mucilage extracts also showed a high capacity to heal the skin without any infection. According to this pharmacological activity, we suggest to use calluses produced by in vitro culture to producing new compounds for the skin care and treatment.

Keywords: calluses, Pulicaria incisa, mucilage, Wounds

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11724 Energy Related Carbon Dioxide Emissions in Pakistan: A Decomposition Analysis Using LMDI

Authors: Arsalan Khan, Faisal Jamil

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The unprecedented increase in anthropogenic gases in recent decades has led to climatic changes worldwide. CO2 emissions are the most important factors responsible for greenhouse gases concentrations. This study decomposes the changes in overall CO2 emissions in Pakistan for the period 1990-2012 using Log Mean Divisia Index (LMDI). LMDI enables to decompose the changes in CO2 emissions into five factors namely; activity effect, structural effect, intensity effect, fuel-mix effect, and emissions factor effect. This paper confirms an upward trend of overall emissions level of the country during the period. The study finds that activity effect, structural effect and intensity effect are the three major factors responsible for the changes in overall CO2 emissions in Pakistan with activity effect as the largest contributor to overall changes in the emissions level. The structural effect is also adding to CO2 emissions, which indicates that the economic activity is shifting towards more energy-intensive sectors. However, intensity effect has negative sign representing energy efficiency gains, which indicate a good relationship between the economy and environment. The findings suggest that policy makers should encourage the diversification of the output level towards more energy efficient sub-sectors of the economy.

Keywords: energy consumption, CO2 emissions, decomposition analysis, LMDI, intensity effect

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11723 Physical Activity, Mental Health, and Body Composition in College Students after COVID-19 Lockdown

Authors: Manuela Caciula, Luis Torres, Simion Tomoiaga

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Introduction: The SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), more commonly referred to as COVID-19, has wreaked havoc on all facets of higher education since its inception in late 2019. College students, in particular, significantly reduced their daily energy expenditure and increased the time spent sitting to listen to online classes and complete their studies from home. This change, in combination with the associated COVID-19 lockdown, presumably decreased physical activity levels, increased mental health symptoms, and led to the promotion of unhealthy eating habits. Objectives: The main objective of this study was to determine the current self-reported physical activity levels, mental health symptoms, and body composition of college students after the COVID-19 lockdown in order to develop future interventions for the overall improvement of health. Methods: All participants completed pre-existing, well-validated surveys for both physical activity (International Physical Activity Questionnaire - long form) and mental health (Hospital Anxiety and Depression Scale). Body composition was assessed in person with the use of an Inbody 570 device. Results: Of the 90 American college students (M age = 22.52 ± 4.54, 50 females) who participated in this study, depressive and anxious symptom scores consistent with 58% (N = 52) heightened symptomatology, 17% (N = 15) moderate borderline symptomatology, and 25% (N = 23) asymptomatology were reported. In regard to physical activity, 79% (N = 71) of the students were highly physically active, 18% (N = 16) were moderately active, and 3% (N = 3) reported low levels of physical activity. Additionally, 46% (N = 41) of the students maintained an unhealthy body fat percentage based on World Health Organization recommendations. Strong, significant relationships were found between anxiety and depression symptomatology and body fat percentage (P = .003) and skeletal muscle mass (P = .015), with said symptomatology increasing with added body fat and decreasing with added skeletal muscle mass. Conclusions: Future health interventions for American college students should be focused on strategies to reduce stress, anxiety, and depressive characteristics, as well as nutritional information on healthy eating, regardless of self-reported physical activity levels.

Keywords: physical activity, mental health, body composition, COVID-19

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11722 Early Prediction of Disposable Addresses in Ethereum Blockchain

Authors: Ahmad Saleem

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Ethereum is the second largest crypto currency in blockchain ecosystem. Along with standard transactions, it supports smart contracts and NFT’s. Current research trends are focused on analyzing the overall structure of the network its growth and behavior. Ethereum addresses are anonymous and can be created on fly. The nature of Ethereum network and addresses make it hard to predict their behavior. The activity period of an ethereum address is not much analyzed. Using machine learning we can make early prediction about the disposability of the address. In this paper we analyzed the lifetime of the addresses. We also identified and predicted the disposable addresses using machine learning models and compared the results.

Keywords: blockchain, Ethereum, cryptocurrency, prediction

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11721 Three-Dimensional Model of Leisure Activities: Activity, Relationship, and Expertise

Authors: Taekyun Hur, Yoonyoung Kim, Junkyu Lim

Abstract:

Previous works on leisure activities had been categorizing activities arbitrarily and subjectively while focusing on a single dimension (e.g. active-passive, individual-group). To overcome these problems, this study proposed a Korean leisure activities’ matrix model that considered multidimensional features of leisure activities, which was comprised of 3 main factors and 6 sub factors: (a) Active (physical, mental), (b) Relational (quantity, quality), (c) Expert (entry barrier, possibility of improving). We developed items for measuring the degree of each dimension for every leisure activity. Using the developed Leisure Activities Dimensions (LAD) questionnaire, we investigated the presented dimensions of a total of 78 leisure activities which had been enjoyed by most Koreans recently (e.g. watching movie, taking a walk, watching media). The study sample consisted of 1348 people (726 men, 658 women) ranging in age from teenagers to elderlies in their seventies. This study gathered 60 data for each leisure activity, a total of 4860 data, which were used for statistical analysis. First, this study compared 3-factor model (Activity, Relation, Expertise) fit with 6-factor model (physical activity, mental activity, relational quantity, relational quality, entry barrier, possibility of improving) fit by using confirmatory factor analysis. Based on several goodness-of-fit indicators, the 6-factor model for leisure activities was a better fit for the data. This result indicates that it is adequate to take account of enough dimensions of leisure activities (6-dimensions in our study) to specifically apprehend each leisure attributes. In addition, the 78 leisure activities were cluster-analyzed with the scores calculated based on the 6-factor model, which resulted in 8 leisure activity groups. Cluster 1 (e.g. group sports, group musical activity) and Cluster 5 (e.g. individual sports) had generally higher scores on all dimensions than others, but Cluster 5 had lower relational quantity than Cluster 1. In contrast, Cluster 3 (e.g. SNS, shopping) and Cluster 6 (e.g. playing a lottery, taking a nap) had low scores on a whole, though Cluster 3 showed medium levels of relational quantity and quality. Cluster 2 (e.g. machine operating, handwork/invention) required high expertise and mental activity, but low physical activity. Cluster 4 indicated high mental activity and relational quantity despite low expertise. Cluster 7 (e.g. tour, joining festival) required not only moderate degrees of physical activity and relation, but low expertise. Lastly, Cluster 8 (e.g. meditation, information searching) had the appearance of high mental activity. Even though clusters of our study had a few similarities with preexisting taxonomy of leisure activities, there was clear distinctiveness between them. Unlike the preexisting taxonomy that had been created subjectively, we assorted 78 leisure activities based on objective figures of 6-dimensions. We also could identify that some leisure activities, which used to belong to the same leisure group, were included in different clusters (e.g. filed ball sports, net sports) because of different features. In other words, the results can provide a different perspective on leisure activities research and be helpful for figuring out what various characteristics leisure participants have.

Keywords: leisure, dimensional model, activity, relationship, expertise

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11720 A Large Language Model-Driven Method for Automated Building Energy Model Generation

Authors: Yake Zhang, Peng Xu

Abstract:

The development of building energy models (BEM) required for architectural design and analysis is a time-consuming and complex process, demanding a deep understanding and proficient use of simulation software. To streamline the generation of complex building energy models, this study proposes an automated method for generating building energy models using a large language model and the BEM library aimed at improving the efficiency of model generation. This method leverages a large language model to parse user-specified requirements for target building models, extracting key features such as building location, window-to-wall ratio, and thermal performance of the building envelope. The BEM library is utilized to retrieve energy models that match the target building’s characteristics, serving as reference information for the large language model to enhance the accuracy and relevance of the generated model, allowing for the creation of a building energy model that adapts to the user’s modeling requirements. This study enables the automatic creation of building energy models based on natural language inputs, reducing the professional expertise required for model development while significantly decreasing the time and complexity of manual configuration. In summary, this study provides an efficient and intelligent solution for building energy analysis and simulation, demonstrating the potential of a large language model in the field of building simulation and performance modeling.

Keywords: artificial intelligence, building energy modelling, building simulation, large language model

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11719 Tyrosine Rich Fraction as an Immunomodulatory Agent from Ficus Religiosa Bark

Authors: S. A. Nirmal, G. S. Asane, S. C. Pal, S. C. Mandal

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Objective: Ficus religiosa Linn (Moraceae) is being used in traditional medicine to improve immunity hence present work was undertaken to validate this use scientifically. Material and Methods: Dried, powdered bark of F. religiosa was extracted successively using petroleum ether and 70% ethanol in soxhlet extractor. The extracts obtained were screened for immunomodulatory activity by delayed type hypersensitivity (DTH), neutrophil adhesion test and cyclophosphamide-induced neutropenia in Swiss albino mice at the dose of 50 and 100 mg/kg, i.p. 70% ethanol extract showed significant immunostimulant activity hence subjected to column chromatography to produce tyrosine rich fraction (TRF). TRF obtained was screened for immunomodulatory activity by above methods at the dose of 10 mg/kg, i.p. Results: TRF showed potentiation of DTH response in terms of significant increase in the mean difference in foot-pad thickness and it significantly increased neutrophil adhesion to nylon fibers by 48.20%. Percentage reduction in total leukocyte count and neutrophil by TRF was found to be 43.85% and 18.72%, respectively. Conclusion: Immunostimulant activity of TRF was more pronounced and thus it has great potential as a source for natural health products.

Keywords: Ficus religiosa, immunomodulatory, cyclophosphamide, neutropenia

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11718 Graphitic Carbon Nitride-CeO₂ Nanocomposite for Photocatalytic Degradation of Methyl Red

Authors: Khansaa Al-Essa

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Nanosized ceria (CeO₂) and graphitic carbon nitride-loaded ceria (CeO₂/GCN) nanocomposite have been synthesized by the coprecipitation method and studied its photocatalytic activity for methyl red degradation under Visible type radiation. A phase formation study was carried out by using an x-ray diffraction technique, and it revealed that ceria (CeO₂) is properly supported on the surface of GCN. Ceria nanoparticles and CeO₂/GCN nanocomposite were confirmed by transmission electron microscopy technique. The particle size of the CeO₂, CeO₂/GCN nanocomposite is in the range of 10-15 nm. Photocatalytic activity of the CeO₂/g-C3N4 composite was improved as compared to CeO₂. The enhanced photocatalytic activity is attributed to the increased visible light absorption and improved adsorption of the dye on the surface of the composite catalyst.

Keywords: photodegradation, dye, nanocomposite, graphitic carbon nitride-CeO₂

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11717 A Novel Algorithm for Parsing IFC Models

Authors: Raninder Kaur Dhillon, Mayur Jethwa, Hardeep Singh Rai

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Information technology has made a pivotal progress across disparate disciplines, one of which is AEC (Architecture, Engineering and Construction) industry. CAD is a form of computer-aided building modulation that architects, engineers and contractors use to create and view two- and three-dimensional models. The AEC industry also uses building information modeling (BIM), a newer computerized modeling system that can create four-dimensional models; this software can greatly increase productivity in the AEC industry. BIM models generate open source IFC (Industry Foundation Classes) files which aim for interoperability for exchanging information throughout the project lifecycle among various disciplines. The methods developed in previous studies require either an IFC schema or MVD and software applications, such as an IFC model server or a Building Information Modeling (BIM) authoring tool, to extract a partial or complete IFC instance model. This paper proposes an efficient algorithm for extracting a partial and total model from an Industry Foundation Classes (IFC) instance model without an IFC schema or a complete IFC model view definition (MVD).

Keywords: BIM, CAD, IFC, MVD

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11716 Lobbyists’ Competencies as a Basis for Shaping the Positive Image of Modern Lobbying

Authors: Joanna Dzieńdziora

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Lobbying is an instrument of influence in various decision-making processes. It is also the underestimated issue as a research problem. The lack of research on the modern lobbyist competencies is the most crucial element. The paper presents attempts of finding answers to the following questions: Who should run the lobbying activity? What competencies should a lobbyist possess in order to implement lobbying activities effectively? Searching for answers for the mentioned above questions requires positioning the opportunity to change the image of lobbying in the area of competencies of entities that provide lobbying activities. The aim of the paper is presenting the lobbyist competencies profile in the framework of his professional role. The essence of lobbying activity and its significance in the modern economy as well as areas, the scope of lobbying activities, diagnosis of a modern lobbyist’s competences, lobbyist’s competencies profile that is focused on the professionalization of the lobbying activity, will have been presented in this paper. Indicated research tasks let emerge lobbyist’s competencies in the way that allows identifying and elaborating the lobbyist competencies profile. The profile lets improve lobbying activities. Its elaboration is based on the author’s research results analysis. Taking into consideration the shortages within the theory and research on the lobbying activity, the implementation of this research enables to fill the cognitive gap existing in the theory of management sciences.

Keywords: competencies, competencies profile, lobbying, lobbyist

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11715 Forecasting Performance Comparison of Autoregressive Fractional Integrated Moving Average and Jordan Recurrent Neural Network Models on the Turbidity of Stream Flows

Authors: Daniel Fulus Fom, Gau Patrick Damulak

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In this study, the Autoregressive Fractional Integrated Moving Average (ARFIMA) and Jordan Recurrent Neural Network (JRNN) models were employed to model the forecasting performance of the daily turbidity flow of White Clay Creek (WCC). The two methods were applied to the log difference series of the daily turbidity flow series of WCC. The measurements of error employed to investigate the forecasting performance of the ARFIMA and JRNN models are the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The outcome of the investigation revealed that the forecasting performance of the JRNN technique is better than the forecasting performance of the ARFIMA technique in the mean square error sense. The results of the ARFIMA and JRNN models were obtained by the simulation of the models using MATLAB version 8.03. The significance of using the log difference series rather than the difference series is that the log difference series stabilizes the turbidity flow series than the difference series on the ARFIMA and JRNN.

Keywords: auto regressive, mean absolute error, neural network, root square mean error

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11714 Sexuality and Quality of Life Among Older Adults

Authors: Ahuva Even-Zohar, Shoshi Werner

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Context: Sexuality is an important aspect of overall quality of life for individuals across different age groups and health conditions. Sexual interest and activity continue to be important and play a role in people's life as they age. Despite this, there is limited research on the sexual health of older adults. Research Aim: The study aims to examine the knowledge, attitudes, and sexual activity of older adults and to explore the relationship between sexual activity and quality of life among this population. Methodology: The study involved 203 Jewish participants from Israel, with an average age of 69.59. The participants completed questionnaires administered through an Internet panel. The questionnaires measured variables such as knowledge about and attitudes towards sexuality, sexual activity, quality of life, and socio-demographic information. Findings: The study found that a majority of the participants reported engaging in sexual activity, with most of them experiencing full sexual intercourse. Approximately half of the participants expressed high levels of satisfaction with their sexual activity. The results indicated that older adults demonstrated a moderate level of knowledge and permissive attitudes towards sexuality in later life. Moreover, higher levels of knowledge and permissive attitudes were associated with increased sexual activity. The frequency of sexual activity was identified as a predictor of quality of life, with a mediating effect on the relationship between attitudes towards older adults' sexuality and quality of life. Notably, men and older adults who were married or in a relationship reported higher frequencies of sexual activity compared to women and older adults without a partner. Furthermore, a majority of participants did not seek professional help or discuss their sexual concerns with a therapist. Theoretical Importance: This research contributes to our understanding of a topic that is often considered taboo - sexuality among older adults. It highlights that older adults maintain an interest in sexual activity, and that engaging in such activity contributes to their overall quality of life. Data Collection and Analysis Procedures: The data for this study were collected using structured questionnaires administered through an Internet panel. The questionnaires included closed-ended questions, allowing for quantitative data analysis. Descriptive statistics and regression analysis were performed to examine the relationships between the variables. Questions Addressed: This study aimed to address the following questions: What is the level of knowledge and attitudes towards sexuality among older adults? How prevalent is sexual activity among older adults and what factors are associated with it? How does sexual activity impact the quality of life of older adults? Do older adults seek professional help for their sexual concerns? Conclusion: The main conclusion drawn from this research is that sexuality is a crucial aspect of older adults' lives and significantly contributes to their quality of life. The study emphasizes the need for educational programs aimed at older adults and professionals, which promote the understanding and benefits of sexuality in later life. It also suggests that professionals should actively encourage older individuals to seek help and support when experiencing difficulties related to sexuality.

Keywords: men, older adults, quality of life, sexuality, women

Procedia PDF Downloads 63