Search results for: measurement models

Authors: Chiara Cesali

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The effects of climate change are increasingly evident: increases in temperature (i.e. global warming), greater frequency of extreme weather events, i.e. storms, floods, which often affect transport infrastructures. Large-scale climatological models with long-term horizons (up to 2100) show the possibility of significant increases in precipitation in the future, according to the greenhouse gas emissions scenarios from IPCC. Consequently, the insufficiency of existing hydraulic works (i.e. bridges, culverts, drainage systems) may be more frequent, or those currently being designed may become insufficient in the future. Thus, the hydraulic design methods of transport infrastructure must begin to take into account the influence of climate change. To this purpose, criteria for applying to the hydraulic design of a railway infrastructure some of the approaches currently available for determining design rainfall intensity and/or peak discharge flow on the basis of possible climate change scenarios are defined and proposed in the paper. Some application cases are also described.

Keywords: climate change, hydraulic design, precipitation, railway

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Authors: Shruti Motiwale, Xianlin Zhou, Reuben H. Kraft

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Military and sports personnel are often required to wear heavy helmets for extended periods of time. This leads to excessive cyclic loads on the neck and an increased chance of injury. Computational models offer one approach to understand and predict the time progression of disc degeneration under severe cyclic loading. In this paper, we have applied an analytic non-linear damage evolution model to estimate damage evolution in an intervertebral disc due to cyclic loads over decade-long time periods. We have also proposed a novel strategy for inclusion of recovery in the damage model. Our results show that damage only grows 20% in the initial 75% of the life, growing exponentially in the remaining 25% life. The analysis also shows that it is crucial to include recovery in a damage model.

Keywords: cervical spine, computational biomechanics, damage evolution, intervertebral disc, continuum damage mechanics

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Authors: Nagore Guerra Bilbao, Clemente Lobato Fraile

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This paper outlines the design and development of the MENDEPRO questionnaire, designed to analyze mentoring performance within a professional development process carried out with professors at the University of the Basque Country, Spain. The study took into account the international research carried out over the past two decades into teachers' professional development, and was also based on a thorough review of the most common instruments used to identify and analyze mentoring styles, many of which fail to provide sufficient psychometric guarantees. The present study aimed to gather empirical data in order to verify the metric quality of the questionnaire developed. To this end, the process followed to validate the theoretical construct was as follows: The formulation of the items and indicators in accordance with the study variables; the analysis of the validity and reliability of the initial questionnaire; the review of the second version of the questionnaire and the definitive measurement instrument. Content was validated through the formal agreement and consensus of 12 university professor training experts. A reduced sample of professors who had participated in a lifelong learning program was then selected for a trial evaluation of the instrument developed. After the trial, 18 items were removed from the initial questionnaire. The final version of the instrument, comprising 33 items, was then administered to a sample group of 99 participants. The results revealed a five-dimensional structure matching theoretical expectations. Also, the reliability data for both the instrument as a whole (.98) and its various dimensions (between .91 and .97) were very high. The questionnaire was thus found to have satisfactory psychometric properties and can therefore be considered apt for studying the performance of mentoring in both induction programs for young professors and lifelong learning programs for senior faculty members.

Keywords: higher education, mentoring, professional development, university teaching

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Authors: Rahma Fitriani, Zerlita Fahdha Pusdiktasari, Herman Cahyo Diartho

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Spatial panel model is commonly used to specify more complicated behavior of economic agent distributed in space at an individual-spatial unit level. There are several spatial panel models which can be adapted based on certain assumptions. A package called splm in R has several functions, ranging from the estimation procedure, specification tests, and model selection tests. In the absence of prior assumptions, a comprehensive procedure which utilizes the available functions in splm must be formed, which is the objective of this study. In this way, the best specification and model can be fitted based on data. The implementation of the procedure works well. It specifies SARAR-FE as the best model for agricultural productivity growth of the 38 East Java’s Regencies/Municipalities.

Keywords: spatial panel, specification, splm, agricultural productivity growth

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Authors: Fujio Akagi, Hiroaki Ito, Shin-Ichi Inage

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The aim of this study is to develop a combustion model that can be applied uniformly to laminar and turbulent premixed flames while considering the effect of the Lewis number (Le). The model considers the effect of Le on the transport equations of the reaction progress, which varies with the chemical species and temperature. The distribution of the reaction progress variable is approximated by a hyperbolic tangent function, while the other distribution of the reaction progress variable is estimated using the approximated distribution and transport equation of the reaction progress variable considering the Le. The validity of the model was evaluated under the conditions of propane with Le > 1 and methane with Le = 1 (equivalence ratios of 0.5 and 1). The estimated results were found to be in good agreement with those of previous studies under all conditions. A method of introducing a turbulence model into this model is also described. It was confirmed that conventional turbulence models can be expressed as an approximate theory of this model in a unified manner.

Keywords: combustion model, laminar flame, Lewis number, turbulent flame

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Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

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This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

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Authors: Z. V. P. Murthy, Preeti Arunachalam, Sangeeta Balram

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Removal of metal ions from different wastewaters has become important due to their effects on living beings. Cadmium is one of the heavy metals found in different industrial wastewaters. There are many conventional methods available to remove heavy metals from wastewaters like adsorption, membrane separations, precipitation, electrolytic methods, etc. and all of them have their own advantages and disadvantages. The present work deals with the use of natural biosorbents (chitin and chitosan) to separate cadmium ions from aqueous solutions. The adsorption data were fitted with different isotherms and kinetics models. Amongst different adsorption isotherms used to fit the adsorption data, the Freundlich isotherm showed better fits for both the biosorbents. The kinetics data of adsorption of cadmium showed better fit with pseudo-second order model for both the biosorbents. Chitosan, the derivative from chitin, showed better performance than chitin. The separation results are encouraging.

Keywords: chitin, chitosan, cadmium, isotherm, kinetics

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Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

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Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: building energy management, machine learning, operation planning, simulation-based optimization

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Authors: Dominik Halstrup, Marlene Schriever

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The industry, as one of the main energy consumer, is of critical importance along the way of transforming the energy system to Renewable Energies. The distributed character of the Energy Transition demands for further flexibility being introduced to the grid. In order to shed further light on the acceptance of Electric Energy Storage (ESS) from an industrial point of view, this study therefore examines the German manufacturing industry. The analysis in this paper uses data composed of a survey amongst 101 manufacturing companies in Germany. Being part of a two-stage research design, both qualitative and quantitative data was collected. Based on a literature review an acceptance concept was developed in the paper and four user-types identified: (Dedicated) User, Impeded User, Forced User and (Dedicated) Non-User and incorporated in the questionnaire. Both descriptive and bivariate analysis is deployed to identify the level of acceptance in the different organizations. After a factor analysis has been conducted, variables were grouped to form independent acceptance factors. Out of the 22 organizations that do show a positive attitude towards ESS, 5 have already implemented ESS and show a positive attitude towards ESS. They can be therefore considered ‘Dedicated Users’. The remaining 17 organizations have a positive attitude but have not implemented ESS yet. The results suggest that profitability plays an important role as well as load-management systems that are already in place. Surprisingly, 2 organizations have implemented ESS even though they have a negative attitude towards it. This is an example for a ‘Forced User’ where reasons of overriding importance or supporters with overriding authority might have forced the company to implement ESS. By far the biggest subset of the sample shows (critical) distance and can therefore be considered ‘(Dedicated) Non-Users’. The results indicate that the majority of the respondents have not thought ESS in their own organization through yet. For the majority of the sample one can therefore not speak of critical distance but rather a distance due to insufficient information and the perceived unprofitability. This paper identifies the relative state of acceptance of ESS in the manufacturing industry as well as current reasons for hindrance and perspectives for future growth of ESS in an industrial setting from a policy level. The interest that is currently generated by the media could be channeled and taken into a more substantial and individual discussion about ESS in an industrial setting. If the current perception of profitability could be addressed and communicated accordingly, ESS and their use in for instance cooperative business models could become a topic for more organizations in Germany and other parts of the world. As price mechanisms tend to favor existing technologies, policy makers need to further access the use of ESS and acknowledge the positive effects when integrated in an energy system. The subfields of generation, transmission and distribution become increasingly intertwined. New technologies and business models, such as ESS or cooperative arrangements entering the market, increase the number of stakeholders. Organizations need to find their place within this array of stakeholders.

Keywords: acceptance, energy storage solutions, German energy transition, manufacturing industry

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Authors: Venkat Garigapati

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To date, more than a dozen oligonucleotide products are approved as injectable products for clinical use. However, there is no single oligo nucleotide product approved for clinical use. Oral delivery of oligo nucleotides is patient friendly administration however, many challenges involved in the development of oral formulation. Over the course of last twenty plus years, the research in this space aimed to address these challenges. This paper describes the issues involved in solubility, stability, enzymatic (nuclease) induced degradation, and permeation of nucleotides in the Gastrointestinal (GI) and how to overcome these challenges. Also, the translation of in vitro data to in vivo models hinders the formulation development. This paper describes the challenges involved in the development of Oligo Nucleotide products for oral administration. It also discusses the chemistry and formulation strategies for oral administration of oligonucleotides.

Keywords: oral adminstration, oligo nucleotides, stability, permeation, gastrointestinal tract

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Authors: Samuel Kwaku Essien, Catherine Trask, Niels Koehncke, Brenna Bath

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Background: Low back disorder (LBD) is the most common musculoskeletal problem among farmers, with higher prevalence than other occupations. Operators of tractors and other farm machinery such as combines or all-terrain vehicles (ATV) can have considerable cumulative exposure to whole body vibration (WBV). Although there appears to be an association between LBD and WBV, lack of prospective studies makes the relationship between LBD and WBV unclear. Purpose: This study investigates the association between WBV and LBD among Saskatchewan farmers using a prospective cohort study Methods: The Saskatchewan Farm Injury Cohort Study Phase I (2007) and II (2013) data were used. Baseline data were collected via postal questionnaire on accumulated yearly tractor, combine, and ATV use as well as several covariates to support a biopsychosocial model of LBD. Follow-up data on musculoskeletal symptoms were collected for the 6-year with sample size of 1149. Questions on ‘low back trouble’ (ache, pain, discomfort) experienced in the last 12 months answered by farmer participants as ‘yes’ or ‘no’. A GEE-modified Poisson approach was performed using SPSS 22 and SAS 9.4. Results: Twelve-month Prevalence of LBD was 59.8%. In multivariate analysis of the 6-year follow-up, LBD was associated with ATV operation and tractor operation, with a dose-response relationship for annual accumulated tractor operation. Although combine operation ≥ 61 hrs/year was related to LBD in bivariate analysis, this difference did not persist after adjustment for confounder. Age was found to be a confounder in relationship between WBV and LBD and no interactions were found. Conclusion: Longer annual tractor operation and older age are important predictors of LBD symptoms in farmers. Future research involving direct measurement can help identify appropriate prevention strategies.

Keywords: agriculture, low back disorder, low back pain, occupational health

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Authors: Zoi Konsoula

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Antioxidant-rich extracts were prepared from pomegranate peels, seeds and juice using methanol and ethanol and their antioxidant activity was evaluated by the 1,1-diphenyl-2-picrylhydrazine (DPPH) radical scavenging and Ferric Reducing Antioxidant Power (FRAP) method. Both analytical methods indicated a higher antioxidant activity in extracts prepared from peels, which was comparable to that of butylated hydroxytoluene (BHT). Furthermore, the antioxidant activity was correlated to the phenolic and flavonoid content of the various extracts. The antioxidant effectiveness of the extracts was also assessed using corn oil as the oxidation substrate. More specifically, preheated corn oil samples stabilized with extracts at a concentration of 250 ppm, 500 ppm or 1,000 ppm were subjected to accelerated aging (100 oC, 10 days) and the extent of oxidative alteration was followed by the measurement of the peroxide, conjugated dienes and trienes, as well as p-aniside value. BHT at its legal limit (200 ppm) served as standard besides the control sample. Results from the different parameters were in agreement with each other suggesting that pomegranate extracts can stabilize corn oil effectively under accelerated conditions, at all concentrations tested. However, the magnitude of oil stabilization depended strongly on the amount of extract added and this was positively correlated with their phenolic content. Pomegranate peel extracts, which exhibited the highest not only phenolic and flavonoid content but also antioxidant activity, were more potent in inhibiting oxidative deterioration. Both methanolic and ethanolic peel extracts at a concentration of 500 ppm exerted a stabilizing effect comparable to that of BHT, while at a concentration of 1000 ppm they exhibited higher stabilization efficiency in comparison to BHT. Finally, heating oil samples resulted in a time dependent decrease in their antioxidant capacity. Samples containing peel extracts appeared to retain their antioxidant capacity for a longer period, indicating that these extracts contained active compounds that offered superior antioxidant protection to corn oil.

Keywords: antioxidant activity, corn oil, oxidative deterioration, pomegranate

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Authors: Luis A. Anchordoqui, Jorge F. Soriano, Diego F. Torres

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Auger data show evidence for a correlation between ultrahigh-energy cosmic rays (UHECRs) and nearby starburst galaxies. This intriguing correlation is consistent with data collected by the Telescope Array, which have revealed a much more pronounced directional 'hot spot' in arrival directions not far from the starburst galaxy M82. In this work, we assume starbursts are sources of UHECRs, and we investigate the prospects to use the observed distribution of UHECR arrival directions to constrain galactic magnetic field models. We show that if the Telescope Array hot spot indeed originates on M82, UHECR data would place a strong constraint on the turbulent component of the galactic magnetic field.

Keywords: galactic magnetic field, Pierre Auger observatory, telescope array, ultra-high energy cosmic rays

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Authors: Byung Cheol Kim

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This study explores a method for the signal-noise separation challenge in project control, focusing on the limitations of traditional deterministic approaches that use single-point performance metrics to predict project outcomes. We detail how traditional methods often overlook future uncertainties, resulting in tracking biases when reliance is placed solely on immediate data without adjustments for predictive accuracy. Our investigation led to the development of the Predictive Tracking Project Control (PTPC) framework, which incorporates network simulation and Bayesian control models to adapt more effectively to project dynamics. The PTPC introduces controlled disturbances to better identify and separate tracking biases from useful predictive signals. We will demonstrate the efficacy of the PTPC with examples, highlighting its potential to enhance real-time project monitoring and decision-making, marking a significant shift towards more accurate project management practices.

Keywords: predictive tracking, project control, signal-noise separation, Bayesian inference

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Authors: Nguyen Van Que, Nguyen Huy The

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This paper presents combined natural and forced convection of humid air flow. The film condensation of water vapour on a cold floor was investigated using ANSYS Fluent software. User-defined Functions(UDFs) were developed and added to address the issue of film condensation at the surface of the floor. Those UDFs were validated by analytical results on a flat plate. The film condensation model based on mass transfer was used to solve phase change. On the floor, condensation rate was obtained by mass fraction change near the floor. The study investigated effects of inlet velocity, inlet relative humidity and cold floor temperature on the condensation rate. The simulations were done in both 2D and 3D models to show the difference and need for 3D modeling of condensation.

Keywords: heat and mass transfer, convection, condensation, relative humidity, user-defined functions

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Authors: Pawan Kumar Sharma, J. Stephan Sampath Kumar, D. Manikandavelu, V. Senthil Kumar

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The total amount of productivity in the system is the gross primary productivity. The present study was carried out to understand the relationship between productivity in the cages and water depth. The experiment was conducted in the fish cages installed in the pond at the Directorate of Sustainable Aquaculture, Thanjavur, Tamil Nadu Dr. J. Jayalalithaa Fisheries University, Tamil Nadu (10° 47' 13.1964'' N; 79° 8' 16.1700''E). Primary productivity was estimated by light and dark bottle method. The measurement of primary productivity was done at different depths viz., 20 cm, 40 cm, and 60 cm. Six Biological Oxygen Demand bottles of 300 ml capacity were collected and tagged. The productivity was obtained in mg O2/l/hr. The maximum dissolved oxygen level at 20 cm depth was observed 5.62 ± 0.22 mg/l/hr in the light bottle in pond water while the minimum dissolved oxygen level at 20 cm depth in a cage was observed 3.62 ± 0.18 mg/l/hr in dark bottle. In the same way, the maximum and minimum value of dissolved oxygen was observed at 40, and 60 cm depth and results were compared. A slight change in pH was observed in the cage and pond. The maximum gross primary productivity observed was 1.97 mg/l/hr in pond at 20 cm depth while minimum gross primary productivity observed was 0.82±0.16 mg/l/hr in a cage at 60 cm depth. The community respiration was also variable with the depth in both cage and pond. Maximum community respiration was found 1.50±0.19 mg/l/hr in pond at 20 cm depth. A strong positive linear relationship was observed between primary productivity and fish yields in ponds. The pond primary productivity can contribute substantially to the nutrition of farm-raised aquaculture species, including shrimp. The growth of phytoplankton’s is dependent on the sun light, availability of primary nutrients (N, P, and K) in the water body and transparency, so to increase the primary productivity fertilization through organic manure may be done that will clean to the pond environment also.

Keywords: cage aquaculture, water depth, net primary productivity, gross primary productivity, community respiration

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Authors: Robert Michael, Kayla Tobin, William Foster, Rachel Fairchild

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The COVID-19 pandemic has caused significant disruptions in education, particularly in the teaching of health and physical education (HPE). This study examined a cohort of teachers that experienced being a preservice and first-year teacher during various stages of the pandemic. Qualitative data collection was conducted by interviewing six teachers from different schools in the Eastern U.S. over a series of structured interviews. Thematic analysis was employed to analyze the data. The pandemic significantly impacted the way HPE was taught as schools shifted to virtual and hybrid models. Findings revealed five major themes: (a) You want me to teach HOW?, (b) PE without equipment and six feet apart, (c) Behind the Scenes, (d) They’re back…I became a behavior management guru, and (e) The Pandemic Crater. Overall, this study highlights the significant challenges faced by preservice and first-year teachers in teaching physical education during the pandemic and underscores the need for ongoing support and resources to help them adapt and succeed in these challenging circumstances.

Keywords: teacher education, preservice teachers, first year teachers, health and physical education

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Authors: Roberta Martino, Viviana Ventre

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Empirical evidence has, over time, confirmed that the behavior of individuals is inconsistent with the descriptions provided by the Discounted Utility Model, an essential reference for calculating the utility of intertemporal prospects. The model assumes that individuals calculate the utility of intertemporal prospectuses by adding up the values of all outcomes obtained by multiplying the cardinal utility of the outcome by the discount function estimated at the time the outcome is received. The trend of the discount function is crucial for the preferences of the decision maker because it represents the perception of the future, and its trend causes temporally consistent or temporally inconsistent preferences. In particular, because different formulations of the discount function lead to various conclusions in predicting choice, the descriptive ability of models with a hyperbolic trend is greater than linear or exponential models. Suboptimal choices from any time point of view are the consequence of this mechanism, the psychological factors of which are encapsulated in the discount rate trend. In addition, analyzing the decision-making process from a psychological perspective, there is an equivalence between the selection of dominated prospects and a degree of impatience that decreases over time. The first part of the paper describes and investigates the anomalies of the discounted utility model by relating the cognitive distortions of the decision-maker to the emotional factors that are generated during the evaluation and selection of alternatives. Specifically, by studying the degree to which impatience decreases, it’s possible to quantify how the psychological and emotional mechanisms of the decision-maker result in a lack of decision persistence. In addition, this description presents inconsistency as the consequence of an inconsistent attitude towards time-delayed choices. The second part of the paper presents an experimental phase in which we show the relationship between inconsistency and impatience in different contexts. Analysis of the degree to which impatience decreases confirms the influence of the decision maker's emotional impulses for each anomaly in the utility model discussed in the first part of the paper. This work provides an application in the field of personalized behavioral finance. Indeed, the numerous behavioral diversities, evident even in the degrees of decrease in impatience in the experimental phase, support the idea that optimal strategies may not satisfy individuals in the same way. With the aim of homogenizing the categories of investors and to provide a personalized approach to advice, the results proven in the experimental phase are used in a complementary way with the information in the field of behavioral finance to implement the Analytical Hierarchy Process model in intertemporal choices, useful for strategic personalization. In the construction of the Analytic Hierarchy Process, the degree of decrease in impatience is understood as reflecting irrationality in decision-making and is therefore used for the construction of weights between anomalies and behavioral traits.

Keywords: analytic hierarchy process, behavioral finance, financial anomalies, impatience, time inconsistency

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Authors: S. Ghorbani, N. I. Polushin

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In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

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Authors: Suhas Kadam, Vishal Chandanshive, Niraj Rane, Sanjay Govindwar

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Fimbristylis dichotoma, Ammannia baccifera, and their co-plantation consortium FA were found to degrade methyl orange, simulated dye mixture, and real textile effluent. Wild plants of Fimbristylis dichotoma and Ammannia baccifera with equal biomass showed 91 and 89% decolorization of methyl orange within 60 h at a concentration of 50 ppm, while 95% dye removal was achieved by consortium FA within 48 h. Floating phyto-beds with co-plantation (Fimbristylis dichotoma and Ammannia baccifera) for the treatment of real textile effluent in a constructed wetland was observed to be more efficient and achieved 79, 72, 77, 66 and 56% reductions in ADMI color value, chemical oxygen demand, biological oxygen demand, total dissolve solid and total suspended solid of textile effluent, respectively. High performance thin layer chromatography, gas chromatography-mass spectroscopy, Fourier transform infrared spectroscopy, Ultra violet-Visible spectroscopy and enzymatic assays confirmed the phytotransformation of parent dye in the new metabolites. T-RFLP analysis of rhizospheric bacteria of Fimbristylis dichotoma, Ammannia baccifera, and consortium FA revealed the presence of 88, 98 and 223 genera which could have been involved in dye removal. Toxicity evaluation of products formed after phytotransformation of methyl orange by consortium FA on bivalves Lamellidens marginalis revealed less damage in the gills architecture when analyzed histologically. Toxicity measurement by Random Amplification of Polymorphic DNA (RAPD) technique revealed normal banding pattern in treated methyl orange sample suggesting less toxic nature of phytotransformed dye products.

Keywords: constructed wetland, phyto-bed, textile effluent, phytoremediation

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Authors: N. F. F. Ebecken, G. C. Pereira

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Ecological systems are exposed and are influenced by various natural and anthropogenic disturbances. They produce various effects and states seeking response symmetry to a state of global phase coherence or stability and balance of their food webs. This research project addresses the development of a computational methodology for modeling plankton food webs. The use of algorithms to establish connections, the generation of representative fuzzy multigraphs and application of technical analysis of complex networks provide a set of tools for defining, analyzing and evaluating community structure of coastal aquatic ecosystems, beyond the estimate of possible external impacts to the networks. Thus, this study aims to develop computational systems and data models to assess how these ecological networks are structurally and functionally organized, to analyze the types and degree of compartmentalization and synchronization between oscillatory and interconnected elements network and the influence of disturbances on the overall pattern of rhythmicity of the system.

Keywords: ecological networks, plankton food webs, fuzzy multigraphs, dynamic of networks

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Authors: M. M. Hefnawy, A. M. A. Homoda, M. A. Abounassif, A. M. Alanazia, A. Al-Majed, Gamal A. E. Mostafa

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PVC membrane sensors using different approach e.g. ion-pair, ionophore, and Schiff-base has been used as testing membrane sensor. Analytical applications of membrane sensors for direct measurement of variety of different ions in complex biological and environmental sample are reported. The most important step of such PVC membrane sensor is the sensing active material. The potentiometric sensors have some outstanding advantages including simple design, operation, wide linear dynamic range, relative fast response time, and rotational selectivity. The analytical applications of these techniques to pharmaceutical compounds in dosage forms are also discussed. The construction and electrochemical response characteristics of Poly (vinyl chloride) membrane sensors for moxifloxacin HCl (MOX) are described. The sensing membranes incorporate ion association complexes of moxifloxacin cation and sodium tetraphenyl borate (NaTPB) (sensor 1), phosphomolybdic acid (PMA) (sensor 2) or phosphotungstic acid (PTA) (sensor 3) as electroactive materials. The sensors display a fast, stable and near-Nernstian response over a relative wide moxifloxacin concentration range (1 ×10-2-4.0×10-6, 1 × 10-2-5.0×10-6, 1 × 10-2-5.0×10-6 M), with detection limits of 3×10-6, 4×10-6 and 4.0×10-6 M for sensor 1, 2 and 3, respectively over a pH range of 6.0-9.0. The sensors show good discrimination of moxifloxacin from several inorganic and organic compounds. The direct determination of 400 µg/ml of moxifloxacin show an average recovery of 98.5, 99.1 and 98.6 % and a mean relative standard deviation of 1.8, 1.6 and 1.8% for sensors 1, 2, and 3 respectively. The proposed sensors have been applied for direct determination of moxifloxacin in some pharmaceutical preparations. The results obtained by determination of moxifloxacin in tablets using the proposed sensors are comparable favorably with those obtained using the US Pharmacopeia method. The sensors have been used as indicator electrodes for potentiometric titration of moxifloxacin.

Keywords: potentiometry, PVC, membrane sensors, ion-pair, ionophore, schiff-base, moxifloxacin HCl, sodium tetraphenyl borate, phosphomolybdic acid, phosphotungstic acid

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Authors: Yasuyuki Takahashi, Hayato Ishimura, Masao Miyagawa, Teruhito Mochizuki

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Quantitative measurement of myocardium perfusion is possible with single photon emission computed tomography (SPECT) using a semiconductor detector. However, accumulation of ^99mTc-tetrofosmin in the liver may make it difficult to assess that accurately in the inferior myocardium. Our idea is to reduce the high accumulation in the liver by using dynamic SPECT imaging and a technique called time subtraction. We evaluated the performance of a new SPECT system with a cadmium-zinc-telluride solid-state semi- conductor detector (Discovery NM 530c; GE Healthcare). Our system acquired list-mode raw data over 10 minutes for a typical patient. From the data, ten SPECT images were reconstructed, one for every minute of acquired data. Reconstruction with the semiconductor detector was based on an implementation of a 3-D iterative Bayesian reconstruction algorithm. We studied 20 patients with coronary artery disease (mean age 75.4 ± 12.1 years; range 42-86; 16 males and 4 females). In each subject, 259 MBq of ^99mTc-tetrofosmin was injected intravenously. We performed both a phantom and a clinical study using dynamic SPECT. An approximation to a liver-only image is obtained by reconstructing an image from the early projections during which time the liver accumulation dominates (0.5~2.5 minutes SPECT image-5~10 minutes SPECT image). The extracted liver-only image is then subtracted from a later SPECT image that shows both the liver and the myocardial uptake (5~10 minutes SPECT image-liver-only image). The time subtraction of liver was possible in both a phantom and the clinical study. The visualization of the inferior myocardium was improved. In past reports, higher accumulation in the myocardium due to the overlap of the liver is un-diagnosable. Using our time subtraction method, the image quality of the ^99mTc-tetorofosmin myocardial SPECT image is considerably improved.

Keywords: 99mTc-tetrofosmin, dynamic SPECT, time subtraction, semiconductor detector

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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Authors: Khalil Abdullah Ahmed Khalil, Elsadig Mohamed Ahmed

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Extracts of various plants material capable of decreasing blood sugar have been tested in experimental animal models, and their effects confirmed. Neem or Margose (AzadirachtaIndica) is an indigenous plant believed to have antiviral, antifungal, antidiabetic, and many other properties. In this paper deals with a comparative study of effect of aqueous Neem leaves extract alone or in combination with glibenclamide on alloxan diabetic rabbits. Administration of crude aqueous Neem extract (CANE) alone (1.5 ml/kg/day) as well as the combination of CANE (1.5 ml/kg/day) with glibenclamide (0.25 mg/kg/day) significantly decreased (P<0.05) the concentrations of serum lipids, blood glucose and lipoprotein VLDL and LDL but significantly increased (P<0.05) the concentration of HDL. The change was observed significantly greater when the treatment was given in combination of CANE and glibenclamid than with CANE alone.

Keywords: aqueos neem leaves extract, hypoglycemic, hypolipidemic, cholesterol

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Authors: Ksenija Dumičić, Anita Čeh Časni, Irena Palić

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This paper examines economic and Information and Communication Technology (ICT) development influence on recently increasing Internet purchases by individuals for European Union member states. After a growing trend for Internet purchases in EU27 was noticed, all possible regression analysis was applied using nine independent variables in 2011. Finally, two linear regression models were studied in detail. Conducted simple linear regression analysis confirmed the research hypothesis that the Internet purchases in analysed EU countries is positively correlated with statistically significant variable Gross Domestic Product per capita (GDPpc). Also, analysed multiple linear regression model with four regressors, showing ICT development level, indicates that ICT development is crucial for explaining the Internet purchases by individuals, confirming the research hypothesis.

Keywords: European union, Internet purchases, multiple linear regression model, outlier

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Authors: Alaoui Hamza, Moutacalli Mohamed Tarik, Chebak Ahmed

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The number of people suffering from hemiplegia is growing each year. This lower limb disability affects all the aspects of their lives by taking away their autonomy. This implicates their close relatives, as well as the health system to provide the necessary care they need. The integration of exoskeletons in the medical field became a promising solution to resolve this issue. This paper presents an exoskeleton designed to help hemiplegic people get back the sensation and ability of normal walking. For this purpose, three step models have been created. The first step allows a simple forward movement of the leg. The second method is designed to overcome some obstacles in the patient path, and finally the third step model gives the patient total control over the device. Each of the control methods was designed to offer a solution to the challenges that the patients may face during the walking process.

Keywords: ability of normal walking, exoskeleton, hemiplegic patients, lower limb motion- mechatronics

Procedia PDF Downloads 153

Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

Procedia PDF Downloads 148

Authors: Jie Lin, Yiwen Pan, Li Zhang, Zhangyong Xia

Abstract:

Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipids, immune cells, and extracellular matrix in the arterial walls. This pathological process can lead to the formation of plaques that can obstruct blood flow and trigger various cardiovascular diseases such as heart attack and stroke. The underlying molecular mechanisms still remain unclear, although many studies revealed the dysfunction of endothelial cells, recruitment and activation of monocytes and macrophages, and the production of pro-inflammatory cytokines and chemokines in atherosclerosis. This study aimed to identify hub genes involved in the progression of atherosclerosis and to analyze their biological function in silico, thereby enhancing our understanding of the disease’s molecular mechanisms. Through the analysis of microarray data, we examined the gene expression in media and neo-intima from plaques, as well as distant macroscopically intact tissue, across a cohort of 32 hypertensive patients. Initially, 112 differentially expressed genes (DEGs) were identified. Subsequent immune infiltration analysis indicated a predominant presence of 27 immune cell types in the atherosclerosis group, particularly noting an increase in monocytes and macrophages. In the Weighted gene co-expression network analysis (WGCNA), 10 modules with a minimum of 30 genes were defined as key modules, with blue, dark, Oliver green and sky-blue modules being the most significant. These modules corresponded respectively to monocyte, activated B cell, and activated CD4 T cell gene patterns, revealing a strong morphological-genetic correlation. From these three gene patterns (modules morphology), a total of 2509 key genes (Gene Significance >0.2, module membership>0.8) were extracted. Six hub genes (CD36, DPP4, HMOX1, PLA2G7, PLN2, and ACADL) were then identified by intersecting 2509 key genes, 102 DEGs with lipid-related genes from the Genecard database. The bio-functional analysis of six hub genes was estimated by a robust classifier with an area under the curve (AUC) of 0.873 in the ROC plot, indicating excellent efficacy in differentiating between the disease and control group. Moreover, PCA visualization demonstrated clear separation between the groups based on these six hub genes, suggesting their potential utility as classification features in predictive models. Protein-protein interaction (PPI) analysis highlighted DPP4 as the most interconnected gene. Within the constructed key gene-drug network, 462 drugs were predicted, with ursodeoxycholic acid (UDCA) being identified as a potential therapeutic agent for modulating DPP4 expression. In summary, our study identified critical hub genes implicated in the progression of atherosclerosis through comprehensive bioinformatic analyses. These findings not only advance our understanding of the disease but also pave the way for applying similar analytical frameworks and predictive models to other diseases, thereby broadening the potential for clinical applications and therapeutic discoveries.

Keywords: atherosclerosis, hub genes, drug prediction, bioinformatics

Procedia PDF Downloads 67

Authors: G. Julius P. Roy, Prateek Saxena, Sanjeev Singh

Abstract:

Power distribution utilities two decades ago would collect data from its customers not later than a period of at least one month. The origin of SmartGrid and AMI has subsequently increased the sampling frequency leading to 1000 to 10000 fold increase in data quantity. This increase is notable and this steered to coin the tern Big Data in utilities. Power distribution industry is one of the largest to handle huge and complex data for keeping history and also to turn the data in to significance. Majority of the utilities around the globe are adopting SmartGrid technologies as a mass implementation and are primarily focusing on strategic interdependence and synergies of the big data coming from new information sources like AMI and intelligent SCADA, there is a rising need for new models of data management and resurrected focus on analytics to dissect data into descriptive, predictive and dictatorial subsets. The goal of this paper is to is to bring load disaggregation into smart energy toolkit for commercial usage.

Keywords: data management, analytics, energy data analytics, smart grid, smart utilities

Procedia PDF Downloads 780