Search results for: generating function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5892

Search results for: generating function

5682 Evaluation of the Internal Quality for Pineapple Based on the Spectroscopy Approach and Neural Network

Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

Abstract:

In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the Spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are Class balancing, Data shuffling, and Standardization were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the Sequential model and Relu activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: neural network, pineapple, soluble solid content, spectroscopy

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5681 Symbolic Analysis of Input Impedance of CMOS Floating Active Inductors with Application in Fully Differential Bandpass Amplifier

Authors: Kittipong Tripetch

Abstract:

This paper proposes studies of input impedance of two types of the CMOS active inductor. It derives two input impedance formulas. The first formula is the input impedance of a grounded active inductor. The second formula is an input impedance of floating active inductor. After that, these formulas can be used to simulate magnitude and phase response of input impedance as a function of current consumption with MATLAB. Common mode rejection ratio (CMRR) of a fully differential bandpass amplifier is derived based on superposition principle. CMRR as a function of input frequency is plotted as a function of current consumption

Keywords: grounded active inductor, floating active inductor, fully differential bandpass amplifier

Procedia PDF Downloads 426
5680 Human LACE1 Functions Pro-Apoptotic and Interacts with Mitochondrial YME1L Protease

Authors: Lukas Stiburek, Jana Cesnekova, Josef Houstek, Jiri Zeman

Abstract:

Cellular function depends on mitochondrial function and integrity that is therefore maintained by several classes of proteins possessing chaperone and/or proteolytic activities. In this work, we focused on characterization of LACE1 (lactation elevated 1) function in mitochondrial protein homeostasis maintenance. LACE1 is the human homologue of yeast mitochondrial Afg1 ATPase, a member of SEC18-NSF, PAS1, CDC48-VCP, TBP family. Yeast Afg1 was shown to be involved in mitochondrial complex IV biogenesis, and based on its similarity with CDC48 (p97/VCP) it was suggested to facilitate extraction of polytopic membrane proteins. Here we show that LACE1, which is a mitochondrial integral membrane protein, exists as part of three complexes of approx. 140, 400 and 500 kDa and is essential for maintenance of fused mitochondrial reticulum and lamellar cristae morphology. Using affinity purification of LACE1-FLAG expressed in LACE1 knockdown background we show that the protein physically interacts with mitochondrial inner membrane protease YME1L. We further show that human LACE1 exhibits significant pro-apoptotic activity and that the protein is required for normal function of the mitochondrial respiratory chain. Thus, our work establishes LACE1 as a novel factor with the crucial role in mitochondrial homeostasis maintenance.

Keywords: LACE1, mitochondria, apoptosis, protease

Procedia PDF Downloads 312
5679 Optimality Conditions for Weak Efficient Solutions Generated by a Set Q in Vector Spaces

Authors: Elham Kiyani, S. Mansour Vaezpour, Javad Tavakoli

Abstract:

In this paper, we first introduce a new distance function in a linear space not necessarily endowed with a topology. The algebraic concepts of interior and closure are useful to study optimization problems without topology. So, we define Q-weak efficient solutions generated by the algebraic interior of a set Q, where Q is not necessarily convex. Studying nonconvex vector optimization is valuable since, for a convex cone K in topological spaces, we have int(K)=cor(K), which means that topological interior of a convex cone K is equal to the algebraic interior of K. Moreover, we used the scalarization technique including the distance function generated by the vectorial closure of a set to characterize these Q-weak efficient solutions. Scalarization is a useful approach for solving vector optimization problems. This technique reduces the optimization problem to a scalar problem which tends to be an optimization problem with a real-valued objective function. For instance, Q-weak efficient solutions of vector optimization problems can be characterized and computed as solutions of appropriate scalar optimization problems. In the convex case, linear functionals can be used as objective functionals of the scalar problems. But in the nonconvex case, we should present a suitable objective function. It is the aim of this paper to present a new distance function that be useful to obtain sufficient and necessary conditions for Q-weak efficient solutions of general optimization problems via scalarization.

Keywords: weak efficient, algebraic interior, vector closure, linear space

Procedia PDF Downloads 228
5678 The Modality of Multivariate Skew Normal Mixture

Authors: Bader Alruwaili, Surajit Ray

Abstract:

Finite mixtures are a flexible and powerful tool that can be used for univariate and multivariate distributions, and a wide range of research analysis has been conducted based on the multivariate normal mixture and multivariate of a t-mixture. Determining the number of modes is an important activity that, in turn, allows one to determine the number of homogeneous groups in a population. Our work currently being carried out relates to the study of the modality of the skew normal distribution in the univariate and multivariate cases. For the skew normal distribution, the aims are associated with studying the modality of the skew normal distribution and providing the ridgeline, the ridgeline elevation function, the $\Pi$ function, and the curvature function, and this will be conducive to an exploration of the number and location of mode when mixing the two components of skew normal distribution. The subsequent objective is to apply these results to the application of real world data sets, such as flow cytometry data.

Keywords: mode, modality, multivariate skew normal, finite mixture, number of mode

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5677 Modelling for Temperature Non-Isothermal Continuous Stirred Tank Reactor Using Fuzzy Logic

Authors: Nasser Mohamed Ramli, Mohamad Syafiq Mohamad

Abstract:

Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of differential equations into S-function using MATLAB. The reactor model and S-function are developed using m.file. After developing the S-function of CSTR model, User-Defined functions are used to link to SIMULINK file. Results that are obtained from simulation and temperature control were better when using Fuzzy logic control compared to PID control.

Keywords: CSTR, temperature, PID, fuzzy logic

Procedia PDF Downloads 457
5676 Measurement of CES Production Functions Considering Energy as an Input

Authors: Donglan Zha, Jiansong Si

Abstract:

Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: bias of technical change, CES production function, elasticity of substitution, energy input

Procedia PDF Downloads 282
5675 The Effects on Hand Function with Robot-Assisted Rehabilitation for Children with Cerebral Palsy: A Pilot Study

Authors: Fen-Ling Kuo, Hsin-Chieh Lee, Han-Yun Hsiao, Jui-Chi Lin

Abstract:

Background: Children with cerebral palsy (CP) usually suffered from mild to maximum upper limb dysfunction such as having difficulty in reaching and picking up objects, which profoundly affects their participation in activities of daily living (ADLs). Robot-assisted rehabilitation provides intensive physical training in improving sensorimotor function of the hand. Many researchers have extensively studied the effects of robot-assisted therapy (RT) for the paretic upper limb in patients with stroke in recent years. However, few studies have examined the effect of RT on hand function in children with CP. The purpose of this study is to investigate the effectiveness of Gloreha Sinfonia, a robotic device with a dynamic arm support system mainly focus on distal upper-limb training, on improvements of hand function and ADLs in children with CP. Methods: Seven children with moderate CP were recruited in this case series study. RT using Gloreha Sinfonia was performed 2 sessions per week, 60 min per session for 6 consecutive weeks, with 12 times in total. Outcome measures included the Fugl-Meyer Assessment-upper extremity (FMA-UE), the Box and Block Test, the electromyography activity of the extensor digitorum communis muscle (EDC) and brachioradialis (BR), a grip dynamometer for motor evaluation, and the ABILHAND-Kids for measuring manual ability to manage daily activities, were performed at baseline, after 12 sessions (end of treatment) and at the 1-month follow-up. Results: After 6 weeks of robot-assisted treatment of hand function, there were significant increases in FMA-UE shoulder/elbow scores (p=0.002), FMA-UE wrist/hand scores (p=0.002), and FMA-UE total scores (p=0.002). There were also significant improvements in the BR mean value (p = 0.015) and electrical agonist-antagonist muscle ratio (p=0.041) in grasping a 1-inch cube task. These gains were maintained for a month after the end of the intervention. Conclusion: RT using Gloreha Sinfonia for hand function training may contribute toward the improvement of upper extremity function and efficacy in recruiting BR muscle in children with CP. The results were maintained at one month after intervention.

Keywords: activities of daily living, cerebral palsy, hand function, robotic rehabilitation

Procedia PDF Downloads 114
5674 Q-Efficient Solutions of Vector Optimization via Algebraic Concepts

Authors: Elham Kiyani

Abstract:

In this paper, we first introduce the concept of Q-efficient solutions in a real linear space not necessarily endowed with a topology, where Q is some nonempty (not necessarily convex) set. We also used the scalarization technique including the Gerstewitz function generated by a nonconvex set to characterize these Q-efficient solutions. The algebraic concepts of interior and closure are useful to study optimization problems without topology. Studying nonconvex vector optimization is valuable since topological interior is equal to algebraic interior for a convex cone. So, we use the algebraic concepts of interior and closure to define Q-weak efficient solutions and Q-Henig proper efficient solutions of set-valued optimization problems, where Q is not a convex cone. Optimization problems with set-valued maps have a wide range of applications, so it is expected that there will be a useful analytical tool in optimization theory for set-valued maps. These kind of optimization problems are closely related to stochastic programming, control theory, and economic theory. The paper focus on nonconvex problems, the results are obtained by assuming generalized non-convexity assumptions on the data of the problem. In convex problems, main mathematical tools are convex separation theorems, alternative theorems, and algebraic counterparts of some usual topological concepts, while in nonconvex problems, we need a nonconvex separation function. Thus, we consider the Gerstewitz function generated by a general set in a real linear space and re-examine its properties in the more general setting. A useful approach for solving a vector problem is to reduce it to a scalar problem. In general, scalarization means the replacement of a vector optimization problem by a suitable scalar problem which tends to be an optimization problem with a real valued objective function. The Gerstewitz function is well known and widely used in optimization as the basis of the scalarization. The essential properties of the Gerstewitz function, which are well known in the topological framework, are studied by using algebraic counterparts rather than the topological concepts of interior and closure. Therefore, properties of the Gerstewitz function, when it takes values just in a real linear space are studied, and we use it to characterize Q-efficient solutions of vector problems whose image space is not endowed with any particular topology. Therefore, we deal with a constrained vector optimization problem in a real linear space without assuming any topology, and also Q-weak efficient and Q-proper efficient solutions in the senses of Henig are defined. Moreover, by means of the Gerstewitz function, we provide some necessary and sufficient optimality conditions for set-valued vector optimization problems.

Keywords: algebraic interior, Gerstewitz function, vector closure, vector optimization

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5673 Electrical Properties of Cement-Based Piezoelectric Nanoparticles

Authors: Moustafa Shawkey, Ahmed G. El-Deen, H. M. Mahmoud, M. M. Rashad

Abstract:

Piezoelectric based cement nanocomposite is a promising technology for generating an electric charge upon mechanical stress of concrete structure. Moreover, piezoelectric nanomaterials play a vital role for providing accurate system of structural health monitoring (SHM) of the concrete structure. In light of increasing awareness of environmental protection and energy crises, generating renewable and green energy form cement based on piezoelectric nanomaterials attracts the attention of the researchers. Herein, we introduce a facial synthesis for bismuth ferrite nanoparticles (BiFeO3 NPs) as piezoelectric nanomaterial via sol gel strategy. The fabricated piezoelectric nanoparticles are uniformly distributed to cement-based nanomaterials with different ratios. The morphological shape was characterized by field emission scanning electron microscopy (FESEM) and high-resolution transmission electron microscopy (HR-TEM) as well as the crystal structure has been confirmed using X-ray diffraction (XRD). The ferroelectric and magnetic behaviours of BiFeO3 NPs have been investigated. Then, dielectric constant for the prepared cement samples nanocomposites (εr) is calculated. Intercalating BiFeO3 NPs into cement materials achieved remarkable results as piezoelectric cement materials, distinct enhancement in ferroelectric and magnetic properties. Overall, this present study introduces an effective approach to improve the electrical properties based cement applications.

Keywords: piezoelectric nanomaterials, cement technology, bismuth ferrite nanoparticles, dielectric

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5672 Assessing the Impact of Physical Inactivity on Dialysis Adequacy and Functional Health in Peritoneal Dialysis Patients

Authors: Mohammad Ali Tabibi, Farzad Nazemi, Nasrin Salimian

Abstract:

Background: Peritoneal dialysis (PD) is a prevalent renal replacement therapy for patients with end-stage renal disease. Despite its benefits, PD patients often experience reduced physical activity and physical function, which can negatively impact dialysis adequacy and overall health outcomes. Despite the known benefits of maintaining physical activity in chronic disease management, the specific interplay between physical inactivity, physical function, and dialysis adequacy in PD patients remains underexplored. Understanding this relationship is essential for developing targeted interventions to enhance patient care and outcomes in this vulnerable population. This study aims to assess the impact of physical inactivity on dialysis adequacy and functional health in PD patients. Methods: This cross-sectional study included 135 peritoneal dialysis patients from multiple dialysis centers. Physical inactivity was measured using the International Physical Activity Questionnaire (IPAQ), while physical function was assessed using the Short Physical Performance Battery (SPPB). Dialysis adequacy was evaluated using the Kt/V ratio. Additional variables such as demographic data, comorbidities, and laboratory parameters were collected to control for potential confounders. Statistical analyses were performed to determine the relationships between physical inactivity, physical function, and dialysis adequacy. Results: The study cohort comprised 70 males and 65 females with a mean age of 55.4 ± 13.2 years. A significant proportion of the patients (65%) were categorized as physically inactive based on IPAQ scores. Inactive patients demonstrated significantly lower SPPB scores (mean 6.2 ± 2.1) compared to their more active counterparts (mean 8.5 ± 1.8, p < 0.001). Dialysis adequacy, as measured by Kt/V, was found to be suboptimal (Kt/V < 1.7) in 48% of the patients. There was a significant positive correlation between physical function scores and Kt/V values (r = 0.45, p < 0.01), indicating that better physical function is associated with higher dialysis adequacy. Also, there was a significant negative correlation between physical inactivity and physical function (r = -0.55, p < 0.01). Additionally, physically inactive patients had lower Kt/V ratios compared to their active counterparts (1.3 ± 0.3 vs. 1.8 ± 0.4, p < 0.05). Multivariate regression analysis revealed that physical inactivity was an independent predictor of reduced dialysis adequacy (β = -0.32, p < 0.01) and poorer physical function (β = -0.41, p < 0.01) after adjusting for age, sex, comorbidities, and dialysis vintage. Conclusion: This study underscores the critical role of physical activity and physical function in maintaining adequate dialysis in peritoneal dialysis patients. These findings highlight the need for targeted interventions to promote physical activity in this population to improve their overall health outcomes. Future research should focus on developing and evaluating exercise programs tailored for PD patients to enhance their physical function and dialysis adequacy. The findings suggest that interventions aimed at increasing physical activity and improving physical function may enhance dialysis adequacy and overall health outcomes in this population. Further research is warranted to explore the mechanisms underlying these associations and to develop targeted strategies for enhancing patient care.

Keywords: inactivity, physical function, peritoneal dialysis, dialysis adequacy

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5671 Design of a Photovoltaic Power Generation System Based on Artificial Intelligence and Internet of Things

Authors: Wei Hu, Wenguang Chen, Chong Dong

Abstract:

In order to improve the efficiency and safety of photovoltaic power generation devices, this photovoltaic power generation system combines Artificial Intelligence (AI) and the Internet of Things (IoT) to control the chasing photovoltaic power generation device to track the sun to improve power generation efficiency and then convert energy management. The system uses artificial intelligence as the control terminal, the power generation device executive end uses the Linux system, and Exynos4412 is the CPU. The power generating device collects the sun image information through Sony CCD. After several power generating devices feedback the data to the CPU for processing, several CPUs send the data to the artificial intelligence control terminal through the Internet. The control terminal integrates the executive terminal information, time information, and environmental information to decide whether to generate electricity normally and then whether to convert the converted electrical energy into the grid or store it in the battery pack. When the power generation environment is abnormal, the control terminal authorizes the protection strategy, the power generation device executive terminal stops power generation and enters a self-protection posture, and at the same time, the control terminal synchronizes the data with the cloud. At the same time, the system is more intelligent, more adaptive, and longer life.

Keywords: photo-voltaic power generation, the pursuit of light, artificial intelligence, internet of things, photovoltaic array, power management

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5670 Preliminary Study of the Phonological Development in Three and Four Year Old Bulgarian Children

Authors: Tsvetomira Braynova, Miglena Simonska

Abstract:

The article presents the results of research on phonological processes in three and four-year-old children. For the purpose of the study, an author's test was developed and conducted among 120 children. The study included three areas of research - at the level of words (96 words), at the level of sentence repetition (10 sentences) and at the level of generating own speech from a picture (15 pictures). The test also gives us additional information about the articulation errors of the assessed children. The main purpose of the icing is to analyze all phonological processes that occur at this age in Bulgarian children and to identify which are typical and atypical for this age. The results show that the most common phonology errors that children make are: sound substitution, an elision of sound, metathesis of sound, elision of a syllable, and elision of consonants clustered in a syllable. All examined children were identified with the articulatory disorder from type bilabial lambdacism. Measuring the correlation between the average length of repeated speech and the average length of generated speech, the analysis proves that the more words a child can repeat in part “repeated speech,” the more words they can be expected to generate in part “generating sentence.” The results of this study show that the task of naming a word provides sufficient and representative information to assess the child's phonology.

Keywords: assessment, phonology, articulation, speech-language development

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5669 On Stochastic Models for Fine-Scale Rainfall Based on Doubly Stochastic Poisson Processes

Authors: Nadarajah I. Ramesh

Abstract:

Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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5668 First Order Moment Bounds on DMRL and IMRL Classes of Life Distributions

Authors: Debasis Sengupta, Sudipta Das

Abstract:

The class of life distributions with decreasing mean residual life (DMRL) is well known in the field of reliability modeling. It contains the IFR class of distributions and is contained in the NBUE class of distributions. While upper and lower bounds of the reliability distribution function of aging classes such as IFR, IFRA, NBU, NBUE, and HNBUE have discussed in the literature for a long time, there is no analogous result available for the DMRL class. We obtain the upper and lower bounds for the reliability function of the DMRL class in terms of first order finite moment. The lower bound is obtained by showing that for any fixed time, the minimization of the reliability function over the class of all DMRL distributions with a fixed mean is equivalent to its minimization over a smaller class of distribution with a special form. Optimization over this restricted set can be made algebraically. Likewise, the maximization of the reliability function over the class of all DMRL distributions with a fixed mean turns out to be a parametric optimization problem over the class of DMRL distributions of a special form. The constructive proofs also establish that both the upper and lower bounds are sharp. Further, the DMRL upper bound coincides with the HNBUE upper bound and the lower bound coincides with the IFR lower bound. We also prove that a pair of sharp upper and lower bounds for the reliability function when the distribution is increasing mean residual life (IMRL) with a fixed mean. This result is proved in a similar way. These inequalities fill a long-standing void in the literature of the life distribution modeling.

Keywords: DMRL, IMRL, reliability bounds, hazard functions

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5667 Epistemological Functions of Emotions and Their Relevance to the Formation of Citizens and Scientists

Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

Abstract:

Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the function that called carrier content: on the latter it arises that emotions give the material reasoning that later transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. In this paper I argue that science education should start from the presence of certain emotions in the learner if it is to form citizens with scientific or cultural future scientists.

Keywords: epistemic emotions, science education, formation of citizens and scientists., philosophy of emotions

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5666 Hybrid Fixation in Management of Proximal Diaphyseal Forearm Bone Fractures in Children

Authors: Tarek Aly

Abstract:

Introduction: Maintenance of the length, providing rotational stability, and preserving functional range of forearm motion is the mainstay of both bone forearm fractures treatment. Conservative treatment in older children may lead to malunion with poor remodeling capacity. Recent studies emphasized that the rate of complications with IM nailing was obviously increased in old children. Open reduction and internal fixation have been criticized for the amount of soft tissue dissection and periosteal stripping needed for fixation and excessive scar formation. The aim of this study was to evaluate the anatomical and functional outcomes of hybrid fixation in the treatment of closed proximal radius and ulna fractures in adolescents between 12 and 17 years of age. Patients and Methods: 30 cases of diaphyseal both bone forearm fractures treated with hybrid fixation (Nail radius – Plate ulna) and were available for a follow-up period of fewer than 24 months. Results: Clinically, 72% of cases had an excellent function, 22% had a good function, 4% had a fair function, and 2% had a poor function. Radiologically, signs of the union had appeared in the radius 2weeks earlier than in the ulna in 55% of cases. Conclusion: A hybrid fixation technique in adolescent proximal both-bones forearm fractures could be a viable option in managing these injuries.

Keywords: hyprid fixation, both bones, forearm, fractures

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5665 The Clinical Characteristics and Their Relationship with Sleep Disorders in Patients with Parkinson Disease Accompanied with Cognitive Impairment

Authors: Peng Guo

Abstract:

Objective To investigate the clinical characteristics and changes of video-polysomnography (v-PSG) in Parkinson disease (PD) patients accompanied with cognitive impairment. Methods Three hundred and ninety-four patients with PD were enrolled in Beijing Tiantan Hospital, according to CI level, the patients were divided into PD without cognitive impairment (PD-NCI), PD with mild cognitive impairment (PD-MCI), and PD with dementia (PDD) group. Collect patient's demographic data, including gender, onset age, education level and duration. The cognitive function of PD patients was evaluated by Montreal cognitive assessment (MoCA) scale, and the overall cognitive function and cognitive domains of the three groups were compared.Using v-PSG to assess the sleep status of patients. Correlation analysis of MoCA Scale and v-PSG results in PD-CI group. Results 1. In 394 cases of PD, 94 cases (23.86%) in PD-NCI group , 177 cases(44.92%) in PD-MCI group , 123 cases (31.22%) in PDD group. 2.There was no significant difference in gender, age of onset, education level and duration in PD-NCI group, PD-MCI group and PDD group (P>0.05). 3. The total score of MoCA scale in PD-NCI group, PD-MCI group and PDD group decreased one by one. In PD-NCI group, PD-MCI group and PDD group, the scores of each cognitive domain in MoCA scale decreased significantly(P<0.05). 4.Compared with the PD-MCI group, PDD group had lower total sleep time, lower sleep efficiency (P<0.05). Compared with PD-NCI group, PDD group had lower total sleep time and lower sleep efficiency (P<0.05).5. The sleep efficiency of PD-CI patients is positively correlated with the total score of MoCA scale, visual spatial function, executive function, delayed recall and attention score(P<0.05). Conclusions The incidence of CI in PD patients was high; The cognitive function and cognitive domains of PD-CI patients were significantly impaired; In patients with PD-CI, total sleep time decreased, sleep efficiency decreased, and it was related to overall cognitive function and partial cognitive impairment.

Keywords: Parkinson disease, cognitive impairment, clinical characteristics, sleep disorders, video-polysomnography

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5664 Forecasting for Financial Stock Returns Using a Quantile Function Model

Authors: Yuzhi Cai

Abstract:

In this paper, we introduce a newly developed quantile function model that can be used for estimating conditional distributions of financial returns and for obtaining multi-step ahead out-of-sample predictive distributions of financial returns. Since we forecast the whole conditional distributions, any predictive quantity of interest about the future financial returns can be obtained simply as a by-product of the method. We also show an application of the model to the daily closing prices of Dow Jones Industrial Average (DJIA) series over the period from 2 January 2004 - 8 October 2010. We obtained the predictive distributions up to 15 days ahead for the DJIA returns, which were further compared with the actually observed returns and those predicted from an AR-GARCH model. The results show that the new model can capture the main features of financial returns and provide a better fitted model together with improved mean forecasts compared with conventional methods. We hope this talk will help audience to see that this new model has the potential to be very useful in practice.

Keywords: DJIA, financial returns, predictive distribution, quantile function model

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5663 The Whale Optimization Algorithm and Its Implementation in MATLAB

Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

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Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, implementation, MATLAB

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5662 Volcanoscape Space Configuration Zoning Based on Disaster Mitigation by Utilizing GIS Platform in Mt. Krakatau Indonesia

Authors: Vega Erdiana Dwi Fransiska, Abyan Rai Fauzan Machmudin

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Particularly, space configuration zoning is the very first juncture of a complete space configuration and region planning. Zoning is aimed to define discrete knowledge based on a local wisdom. Ancient predecessor scientifically study the sign of natural disaster towards ethnography approach by operating this knowledge. There are three main functions of space zoning, which are control function, guidance function, and additional function. The control function refers to an instrument for development control and as one of the essentials in controlling land use. Hence, the guidance function indicates as guidance for proposing operational planning and technical development or land usage. Any additional function is useful as a supplementary for region or province planning details. This phase likewise accredits to define boundary in an open space based on geographical appearance. Informant who is categorized as an elder lives in earthquake prone area, to be precise the area is the surrounding of Mount Krakatau. The collected data is one of method for analyzed with thematic model. Later on, it will be verified. In space zoning, long-range distance sensor is applied to determine visualization of the area, which will be zoned before the step of survey to validate the data. The data, which is obtained from long-range distance sensor and site survey, will be overlaid using GIS Platform. Comparing the knowledge based on a local wisdom that is well known by elderly in that area, some of it is relevant to the research, while the others are not. Based on the site survey, the interpretation of a long-range distance sensor, and determining space zoning by considering various aspects resulted in the pattern map of space zoning. This map can be integrated with disaster mitigation affected by volcano eruption.

Keywords: elderly, GIS platform, local wisdom, space zoning

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5661 Effect of Cardio-Specific Overexpression of MUL1, a Mitochondrial Protein on Myocardial Function

Authors: Ximena Calle, Plinio Cantero-López, Felipe Muñoz-Córdova, Mayarling-Francisca Troncoso, Sergio Lavandero, Valentina Parra

Abstract:

MUL1, a mitochondrial E3 ubiquitin ligase anchored to the outer mitochondrial membrane, is highly expressed in the heart. MUL1 is involved in multiple biological pathways associated with mitochondrial dynamics. Increased MUL1 affects the balance between fission and fusion, affecting mitochondrial function, which plays a crucial role in myocardial function. Therefore, it is interesting to evaluate the effect of cardiac-specific overexpression of MUL1 on myocardial function. Aim: To determine heart functionality in a mouse model with cardio-specific overexpression MUL1 protein. Methods and Results: Male C57BL/Tg transgenic mice with cardiomyocyte-specific overexpression of MUL1 (n=10) and control (n=4) were evaluated at 12, 27, and 35 weeks of age. Glucose tolerance curve determination was performed after a 6-hours fast to assess metabolic capacity, treadmill test, and systolic, and diastolic pressure was evaluated by the mouse tail-cuff blood pressure system equipment. The result showed no glucose tolerance curve, and the treadmill test demonstrated no significant changes between groups. However, substantial changes in diastolic function were observed by ultrasound and determination of cardiac hypertrophy proteins by western blot. Conclusions: Cardio-specific overexpression of MUL1 in mice without any treatment affects diastolic cardiac function, thus showing the important role contributed by MUL1 in the heart. Future research should evaluate the effect of cardiomyocyte-specific overexpression of MUL1 in pathological conditions such as a high-fat diet is one of the main risk factors for cardiovascular disease.

Keywords: diastolic dysfunction, hypertrophy cardiac, mitochondrial E3 ubiquitin ligase 1, MUL1

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5660 Application of Acid Base Accounting to Predict Post-Mining Drainage Quality in Coalfields of the Main Karoo Basin and Selected Sub-Basins, South Africa

Authors: Lindani Ncube, Baojin Zhao, Ken Liu, Helen Johanna Van Niekerk

Abstract:

Acid Base Accounting (ABA) is a tool used to assess the total amount of acidity or alkalinity contained in a specific rock sample, and is based on the total S concentration and the carbonate content of a sample. A preliminary ABA test was conducted on 14 sandstone and 5 coal samples taken from coalfields representing the Main Karoo Basin (Highveld, Vryheid and Molteno/Indwe Coalfields) and the Sub-basins (Witbank and Waterberg Coalfields). The results indicate that sandstone and coal from the Main Karoo Basin have the potential of generating Acid Mine Drainage (AMD) as they contain sufficient pyrite to generate acid, with the final pH of samples relatively low upon complete oxidation of pyrite. Sandstone from collieries representing the Main Karoo Basin are characterised by elevated contents of reactive S%. All the studied samples were characterised by an Acid Potential (AP) that is less than the Neutralizing Potential (NP) except for two samples. The results further indicate that the sandstone from the Main Karoo Basin is prone to acid generation as compared to the sandstone from the Sub-basins. However, the coal has a relatively low potential of generating any acid. The application of ABA in this study contributes to an understanding of the complexities governing water-rock interactions. In general, the coalfields from the Main Karoo Basin have much higher potential to produce AMD during mining processes than the coalfields in the Sub-basins.

Keywords: Main Karoo Basin, sub-basin, coal, sandstone, acid base accounting (ABA)

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5659 On q-Non-extensive Statistics with Non-Tsallisian Entropy

Authors: Petr Jizba, Jan Korbel

Abstract:

We combine an axiomatics of Rényi with the q-deformed version of Khinchin axioms to obtain a measure of information (i.e., entropy) which accounts both for systems with embedded self-similarity and non-extensivity. We show that the entropy thus obtained is uniquely solved in terms of a one-parameter family of information measures. The ensuing maximal-entropy distribution is phrased in terms of a special function known as the Lambert W-function. We analyze the corresponding ‘high’ and ‘low-temperature’ asymptotics and reveal a non-trivial structure of the parameter space.

Keywords: multifractals, Rényi information entropy, THC entropy, MaxEnt, heavy-tailed distributions

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5658 Rapides-Des-Îles Main Spillway - Rehabilitation

Authors: Maryam Kamali Nezhad

Abstract:

As part of the project to rehabilitate the main spillway ("main") of the Rapides-des-Îles development in 2019, it was noted that there is a difference between the water level of the intake gauge and the level measured at the main spillway. The Rapides-des-Îles Generating Station is a Hydro-Québec hydroelectric generating station and dam located on the Ottawa River in the Abitibi-Témiscamingue administrative region of Québec. This plant, with an installed capacity of 176 MW, was commissioned in 1966. During the start-up meeting held at the site in May 2019, it was noticed that the water level upstream of the main spillway was considerably higher than the water level at the powerhouse intake. Measurements showed that the level was 229.46 m, whereas the normal operating level (NOL) and the critical maximum level (CML) used in the design were 228.60 m and 229.51 m, respectively. Considering that the water level had almost reached the maximum critical level of the structure despite a flood with a recurrence period of about 100 years, the work was suspended while the project was being decided. This is the first time since the Rapides des îles project was commissioned that a significant difference in elevation between the water level at the powerhouse (intake) and the main spillway has been observed. Following this observation, the contractor's work was suspended. The objective of this study is to identify the reason(s) for this problem and find solutions. Then determine the new upstream levels at the main spillway at which the safety of the structure is ensured and then adjust the engineering of the main spillway in the rehabilitation project accordingly.

Keywords: spillway, rehabilitation, water level, powerhouse, normal operating level, critical maximum level, safety of the structure

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5657 Generating 3D Battery Cathode Microstructures using Gaussian Mixture Models and Pix2Pix

Authors: Wesley Teskey, Vedran Glavas, Julian Wegener

Abstract:

Generating battery cathode microstructures is an important area of research, given the proliferation of the use of automotive batteries. Currently, finite element analysis (FEA) is often used for simulations of battery cathode microstructures before physical batteries can be manufactured and tested to verify the simulation results. Unfortunately, a key drawback of using FEA is that this method of simulation is very slow in terms of computational runtime. Generative AI offers the key advantage of speed when compared to FEA, and because of this, generative AI is capable of evaluating very large numbers of candidate microstructures. Given AI generated candidate microstructures, a subset of the promising microstructures can be selected for further validation using FEA. Leveraging the speed advantage of AI allows for a better final microstructural selection because high speed allows for the evaluation of many more candidate microstructures. For the approach presented, battery cathode 3D candidate microstructures are generated using Gaussian Mixture Models (GMMs) and pix2pix. This approach first uses GMMs to generate a population of spheres (representing the “active material” of the cathode). Once spheres have been sampled from the GMM, they are placed within a microstructure. Subsequently, the pix2pix sweeps over the 3D microstructure (iteratively) slice by slice and adds details to the microstructure to determine what portions of the microstructure will become electrolyte and what part of the microstructure will become binder. In this manner, each subsequent slice of the microstructure is evaluated using pix2pix, where the inputs into pix2pix are the previously processed layers of the microstructure. By feeding into pix2pix previously fully processed layers of the microstructure, pix2pix can be used to ensure candidate microstructures represent a realistic physical reality. More specifically, in order for the microstructure to represent a realistic physical reality, the locations of electrolyte and binder in each layer of the microstructure must reasonably match the locations of electrolyte and binder in previous layers to ensure geometric continuity. Using the above outlined approach, a 10x to 100x speed increase was possible when generating candidate microstructures using AI when compared to using a FEA only approach for this task. A key metric for evaluating microstructures was the battery specific power value that the microstructures would be able to produce. The best generative AI result obtained was a 12% increase in specific power for a candidate microstructure when compared to what a FEA only approach was capable of producing. This 12% increase in specific power was verified by FEA simulation.

Keywords: finite element analysis, gaussian mixture models, generative design, Pix2Pix, structural design

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5656 Comparative Performance of Artificial Bee Colony Based Algorithms for Wind-Thermal Unit Commitment

Authors: P. K. Singhal, R. Naresh, V. Sharma

Abstract:

This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

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5655 The Impact of Political Connections on the Funtion of Independent Directors

Authors: Chih-Lin Chang, Tzu-Ching Weng

Abstract:

The purpose of this study is to explore the relationship between corporate political ties and independent directors' functions. With reference to the literature variables such as the characteristics of the relevant board of directors in the past, a single comprehensive function indicator is established as a substitute variable for the function of independent directors, and the impact of political connection on the independent board of directors is further discussed. This research takes Taiwan listed enterprises from 2014 to 2020 as the main research object and conducts empirical research through descriptive statistics, correlation and regression analysis. The empirical results show that companies with political connections will have a positive impact on the number of independent directors; political connections also have a significant positive relationship with the functional part of independent directors, which means that because companies have political connections, they have a positive impact on the seats or functions of independent directors. will pay more attention and increase their oversight functions.

Keywords: political, connection, independent, director, function

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5654 Efficient Treatment of Azo Dye Wastewater with Simultaneous Energy Generation by Microbial Fuel Cell

Authors: Soumyadeep Bhaduri, Rahul Ghosh, Rahul Shukla, Manaswini Behera

Abstract:

The textile industry consumes a substantial amount of water throughout the processing and production of textile fabrics. The water eventually turns into wastewater, where it acts as an immense damaging nuisance due to its dye content. Wastewater streams contain a percentage ranging from 2.0% to 50.0% of the total weight of dye used, depending on the dye class. The management of dye effluent in textile industries presents a formidable challenge to global sustainability. The current focus is on implementing wastewater treatment technology that enable the recycling of wastewater, reduce energy usage and offset carbon emissions. Microbial fuel cell (MFC) is a device that utilizes microorganisms as a bio-catalyst to effectively treat wastewater while also producing electricity. The MFC harnesses the chemical energy present in wastewater by oxidizing organic compounds in the anodic chamber and reducing an electron acceptor in the cathodic chamber, thereby generating electricity. This research investigates the potential of MFCs to tackle this challenge of azo dye removal with simultaneously generating electricity. Although MFCs are well-established for wastewater treatment, their application in dye decolorization with concurrent electricity generation remains relatively unexplored. This study aims to address this gap by assessing the effectiveness of MFCs as a sustainable solution for treating wastewater containing azo dyes. By harnessing microorganisms as biocatalysts, MFCs offer a promising avenue for environmentally friendly dye effluent management. The performance of MFCs in treating azo dyes and generating electricity was evaluated by optimizing the Chemical Oxygen Demand (COD) and Hydraulic Retention Time (HRT) of influent. COD and HRT values ranged from 1600 mg/L to 2400 mg/L and 5 to 9 days, respectively. Results showed that the maximum open circuit voltage (OCV) reached 648 mV at a COD of 2400 mg/L and HRT of 5 days. Additionally, maximum COD removal of 98% and maximum color removal of 98.91% were achieved at a COD of 1600 mg/L and HRT of 9 days. Furthermore, the study observed a maximum power density of 19.95 W/m3 at a COD of 2400 mg/L and HRT of 5 days. Electrochemical analysis, including linear sweep voltammetry (LSV), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were done to find out the response current and internal resistance of the system. To optimize pH and dye concentration, pH values were varied from 4 to 10, and dye concentrations ranged from 25 mg/L to 175 mg/L. The highest voltage output of 704 mV was recorded at pH 7, while a dye concentration of 100 mg/L yielded the maximum output of 672 mV. This study demonstrates that MFCs offer an efficient and sustainable solution for treating azo dyes in textile industry wastewater, while concurrently generating electricity. These findings suggest the potential of MFCs to contribute to environmental remediation and sustainable development efforts on a global scale.

Keywords: textile wastewater treatment, microbial fuel cell, renewable energy, sustainable wastewater treatment

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5653 Status of Hazardous Waste Generation and Its Impacts on Environment and Human Health: A Study in West Bengal

Authors: Sk Ajim Ali

Abstract:

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

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

Procedia PDF Downloads 284