Search results for: hybrid optimization

Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

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Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim

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Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.

Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation

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Authors: Alison Marshall

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“Santo Niño in Canada – Religion, Migration, and the Filipino Underside” seeks to explore the intersection of religion, migration and the Filipino underside through research participant narratives, archival research, and fieldwork on the cult of Santo Niño in Canada. Santo Niño is the single most revered saint in Filipino religiosity. According to popular lore, the original statue of Santo Niño was brought to the Philippines by Portuguese explorer Ferdinand Magellan in 1521, who claimed the islands on behalf of Spain. While Santo Niño is meant to be a manifestation of Jesus as a child, in Filipino thought and culture he very much resembles pre-Hispanic spirits, as well as patron saints introduced by the Spanish. Santo Niño shrines appear in churches, restaurants, businesses, and homes throughout the diaspora suggesting that he was much more than a Catholic image. He represents a deity who often shares a business or home shrine with non-Christian statues such as lucky cats, the Buddha, Guanyin, and Guangong, and sometimes the Chinese God of the Earth. He represents how Christian culture has been refashioned through indigenous, Chinese, Malay, and Indonesian influences. He embodies the religious superstructure that defines Christian piety and habits. On the one hand, he stands for Jesus, a pious son of God, and yet, on the other hand, he can be a simple vindictive child who punishes those who ignore him. Santo Niño is a complex character linked to the past before Christianity. As Filipinos engage with Santo Niño in Canada, they connect to him as Jesus, the son of God. They are also connecting to a childlike figure who sometimes uses his spiritual power to punish. A hybrid figure who comes came into being at the beginning of the Spanish colonial moment, he is maintained throughout the American one and continues to be a powerful reminder of Filipino identity and resilience when people leave the Philippines for migrant work. As this paper argues, Santo Niño beliefs, practices, and stories unite people in the diaspora regardless of language, gender, or nation. Santo Niño enables one to think about and understand what it means to be Filipino and living migrant lives in the diaspora today. In this way, the cult of Santo Niño expresses both Catholic orthodoxy and the heterodox Filipino underside that includes the use of magical amulets, healing, visions, and spirit mediumship.

Keywords: ethnography, migration, Philippines, religion

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Authors: N. Boontian

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Biological conversion of biomass to methane has received increasing attention in recent years. Grasses have been explored for their potential anaerobic digestion to methane. In this review, extensive literature data have been tabulated and classified. The influences of several parameters on the potential of these feedstocks to produce methane are presented. Lignocellulosic biomass represents a mostly unused source for biogas and ethanol production. Many factors, including lignin content, crystallinity of cellulose, and particle size, limit the digestibility of the hemicellulose and cellulose present in the lignocellulosic biomass. Pretreatments have used to improve the digestibility of the lignocellulosic biomass. Each pretreatment has its own effects on cellulose, hemicellulose and lignin, the three main components of lignocellulosic biomass. Solid-state anaerobic digestion (SS-AD) generally occurs at solid concentrations higher than 15%. In contrast, liquid anaerobic digestion (AD) handles feedstocks with solid concentrations between 0.5% and 15%. Animal manure, sewage sludge, and food waste are generally treated by liquid AD, while organic fractions of municipal solid waste (OFMSW) and lignocellulosic biomass such as crop residues and energy crops can be processed through SS-AD. An increase in operating temperature can improve both the biogas yield and the production efficiency, other practices such as using AD digestate or leachate as an inoculant or decreasing the solid content may increase biogas yield but have negative impact on production efficiency. Focus is placed on substrate pretreatment in anaerobic digestion (AD) as a means of increasing biogas yields using today’s diversified substrate sources.

Keywords: anaerobic digestion, lignocellulosic biomass, methane production, optimization, pretreatment

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Authors: Olawale S. Fatoba, Stephen A. Akinlabi, Esther T. Akinlabi, Rezvan Gharehbaghi

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The performance of material surface under wear and corrosion environments cannot be fulfilled by the conventional surface modifications and coatings. Therefore, different industrial sectors need an alternative technique for enhanced surface properties. Titanium and its alloys possess poor tribological properties which limit their use in certain industries. This paper focuses on the effect of hybrid coatings Al-Cu-Fe on a grade five titanium alloy using laser metal deposition (LMD) process. Icosahedral Al-Cu-Fe as quasicrystals is a relatively new class of materials which exhibit unusual atomic structure and useful physical and chemical properties. A 3kW continuous wave ytterbium laser system (YLS) attached to a KUKA robot which controls the movement of the cladding process was utilized for the fabrication of the coatings. The titanium cladded surfaces were investigated for its hardness, corrosion and tribological behaviour at different laser processing conditions. The samples were cut to corrosion coupons, and immersed into 3.65% NaCl solution at 28oC using Electrochemical Impedance Spectroscopy (EIS) and Linear Polarization (LP) techniques. The cross-sectional view of the samples was analysed. It was found that the geometrical properties of the deposits such as width, height and the Heat Affected Zone (HAZ) of each sample remarkably increased with increasing laser power due to the laser-material interaction. It was observed that there are higher number of aluminum and titanium presented in the formation of the composite. The indentation testing reveals that for both scanning speed of 0.8 m/min and 1m/min, the mean hardness value decreases with increasing laser power. The low coefficient of friction, excellent wear resistance and high microhardness were attributed to the formation of hard intermetallic compounds (TiCu, Ti2Cu, Ti3Al, Al3Ti) produced through the in situ metallurgical reactions during the LMD process. The load-bearing capability of the substrate was improved due to the excellent wear resistance of the coatings. The cladded layer showed a uniform crack free surface due to optimized laser process parameters which led to the refinement of the coatings.

Keywords: Al-Cu-Fe coating, corrosion, intermetallics, laser metal deposition, Ti-6Al-4V alloy, wear resistance

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Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

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The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

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Authors: C. Busuioc, I. Stancu, A. Nicoara, A. Zamfirescu, A. Evanghelidis

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The field of tissue engineering has expanded its potential due to the use of composite biomaterials belonging to increasingly complex systems, leading to bone substitutes with properties that are continuously improving to meet the patient's specific needs. Furthermore, the development of biomaterials based on ceramic and polymeric phases is an unlimited resource for future scientific research, with the final aim of restoring the original tissue functionality. Thus, in the first stage, composite scaffolds based on polycaprolactone (PCL) or polylactic acid (PLA) and inorganic powders were prepared by employing the electrospinning technique. The targeted powders were: commercial and laboratory synthesized hydroxyapatite (HAp), as well as barium titanate (BT). By controlling the concentration of the powder within the precursor solution, together with the processing parameters, different types of three-dimensional architectures were achieved. In the second stage, both the mineral powders and hybrid composites were investigated in terms of composition, crystalline structure, and microstructure so that to demonstrate their suitability for tissue engineering applications. Regarding the scaffolds, these were proven to be homogeneous on large areas and loaded with mineral particles in different proportions. The biological assays demonstrated that the addition of inorganic powders leads to modified responses in the presence of simulated body fluid (SBF) or cell cultures. Through SBF immersion, the biodegradability coupled with bioactivity were highlighted, with fiber fragmentation and surface degradation, as well as apatite layer formation within the testing period. Moreover, the final composites represent supports accepted by the cells, favoring implant integration. Concluding, the purposed fibrous materials based on bioresorbable polymers and mineral powders, produced by the electrospinning technique, represent candidates with considerable potential in the field of tissue engineering. Future improvements can be attained by optimizing the synthesis process or by simultaneous incorporation of multiple inorganic phases with well-defined biological action in order to fabricate multifunctional composites.

Keywords: barium titanate, electrospinning, fibre networks, hydroxyapatite, smart scaffolds

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Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

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Authors: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

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Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, Melon, Optimization, Processing

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: Swapnila V. Shinde, Hemant P. Joshi, Sumit R. Dhas, Dhananjaysingh B. Rajput

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The objective of the present study is to develop hydro-dynamically balanced system for atenolol, β-blocker as a single unit floating tablet. Atenolol shows pH dependent solubility resulting into a bioavailability of 36%. Thus, site specific oral controlled release floating drug delivery system was developed. Formulation includes novice use of rate controlling polymer such as locust bean gum (LBG) in combination of HPMC K4M and gas generating agent sodium bicarbonate. Tablet was prepared by direct compression method and evaluated for physico-mechanical properties. The statistical method was utilized to optimize the effect of independent variables, namely amount of HPMC K4M, LBG and three dependent responses such as cumulative drug release, floating lag time, floating time. Graphical and mathematical analysis of the results allowed the identification and quantification of the formulation variables influencing the selected responses. To study the gastrointestinal transit of the optimized gastro-retentive formulation, in vivo gamma scintigraphy was carried out in six healthy rabbits, after radio labeling the formulation with 99mTc. The transit profiles demonstrated that the dosage form was retained in the stomach for more than 5 hrs. The study signifies the potential of the developed system for stomach targeted delivery of atenolol with improved bioavailability.

Keywords: floating tablet, factorial design, gamma scintigraphy, antihypertensive model drug, HPMC, locust bean gum

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Authors: W. Nootcharin, S. Sujittra, K. Mayuso, K. Kornphimol, M. Rawiwan

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Silver has distinct antibacterial properties and has been used as a component of commercial products with many applications. An increasing number of commercial products cause risks of silver effects for human and environment such as the symptoms of Argyria and the release of silver to the environment. Therefore, the detection of silver in the aquatic environment is important. The colorimetric chemosensor is designed by the basic of ligand interactions with a metal ion, leading to the change of signals for the naked-eyes which are very useful method to this application. Dithizone ligand is considered as one of the effective chelating reagents for metal ions due to its high selectivity and sensitivity of a photochromic reaction for silver as well as the linear backbone of dithizone affords the rotation of various isomeric forms. The present study is focused on the conformation and interaction of silver ion and silver nanoparticles (AgNPs) with dithizone using density functional theory (DFT). The interaction parameters were determined in term of binding energy of complexes and the geometry optimization, frequency of the structures and calculation of binding energies using density functional approaches B3LYP and the 6-31G(d,p) basis set. Moreover, the interaction of silver–dithizone complexes was supported by UV–Vis spectroscopy, FT-IR spectrum that was simulated by using B3LYP/6-31G(d,p) and 1H NMR spectra calculation using B3LYP/6-311+G(2d,p) method compared with the experimental data. The results showed the ion exchange interaction between hydrogen of dithizone and silver atom, with minimized binding energies of silver–dithizone interaction. However, the result of AgNPs in the form of complexes with dithizone. Moreover, the AgNPs-dithizone complexes were confirmed by using transmission electron microscope (TEM). Therefore, the results can be the useful information for determination of complex interaction using the analysis of computer simulations.

Keywords: silver nanoparticles, dithizone, DFT, NMR

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Yi-Hsiang Pan, Chen-Hui Huang, Ching-Hsiang Chen, Wei-Ting Hsu

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The purposes of the study were to explore the students' learning effect of physical education curriculum between merging Teaching Personal and Social Responsibility (TPSR) with sport education model and TPSR with traditional teaching model, which these learning effects included sport self-efficacy, sport enthusiastic, group cohesion, responsibility and game performance. The participants include 3 high school physical education teachers and 6 physical education classes, 133 participants with experience group 75 students and control group 58 students, and each teacher taught an experimental group and a control group for 16 weeks. The research methods used questionnaire investigation, interview, focus group meeting. The research instruments included personal and social responsibility questionnaire, sport enthusiastic scale, group cohesion scale, sport self-efficacy scale and game performance assessment instrument. Multivariate Analysis of covariance and Repeated measure ANOVA were used to test difference of students' learning effects between merging TPSR with sport education model and TPSR with traditional teaching model. The findings of research were: 1) The sport education model with TPSR could improve students' learning effects, including sport self-efficacy, game performance, sport enthusiastic, group cohesion and responsibility. 2) The traditional teaching model with TPSR could improve students' learning effect, including sport self-efficacy, responsibility and game performance. 3) the sport education model with TPSR could improve more learning effects than traditional teaching model with TPSR, including sport self-efficacy, sport enthusiastic,responsibility and game performance. 4) Based on qualitative data about learning experience of teachers and students, sport education model with TPSR significant improve learning motivation, group interaction and game sense. The conclusions indicated sport education model with TPSR could improve more learning effects in physical education curriculum. On other hand, the curricular projects of hybrid TPSR-Sport Education model and TPSR-Traditional Teaching model are both good curricular projects of moral character education, which may be applied in school physical education.

Keywords: character education, sport season, game performance, sport competence

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Authors: K. P. Valdés García, E. I. Rodríguez Fonseca, L. G. Juárez Cantú

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Suicide is a global, multidimensional and dynamic problem of mental health, which requires a constant study for its understanding and prevention. When research of this phenomenon is done, it is necessary to consider the different characteristics it may have because of the individual and sociocultural variables, the importance of this consideration is related to the generation of effective treatments and interventions. Adolescents are a vulnerable population due to the characteristics of the development stage. The investigation was carried out with the objective of identifying and describing the conceptualization of adolescents of suicide, and in this process, we find possible differences between men and women. The study was carried out in Saltillo, Coahuila, Mexico. The sample was composed of 418 volunteer students aged between 11 and 18 years. The ethical aspects of the research were reviewed and considered in all the processes of the investigation with the participants, their parents and the schools to which they belonged, psychological attention was offered to the participants and preventive workshops were carried in the educational institutions. Natural semantic networks were the instrument used, since this hybrid method allows to find and analyze the social concept of a phenomenon; in this case, the word suicide was used as an evocative stimulus and participants were asked to evoke at least five words and a maximum 10 that they thought were related to suicide, and then hierarchize them according to the closeness with the construct. The subsequent analysis was carried with Excel, yielding the semantic weights, affective loads and the distances between each of the semantic fields established according to the words reported by the subjects. The results showed similarities in the conceptualization of suicide in adolescents, men and women. Seven semantic fields were generated; the words were related in the discourse analysis: 1) death, 2) possible triggering factors, 3) associated moods, 4) methods used to carry it out, 5) psychological symptomatology that could affect, 6) words associated with a rejection of suicide, and finally, 7) specific objects to carry it out. One of the necessary aspects to consider in the investigations of complex issues such as suicide is to have a diversity of instruments and techniques that adjust to the characteristics of the population and that allow to understand the phenomena from the social constructs and not only theoretical. The constant study of suicide is a pressing need, the loss of a life from emotional difficulties that can be solved through psychiatry and psychological methods requires governments and professionals to pay attention and work with the risk population.

Keywords: adolescents, psychological construct, semantic networks, suicide

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Authors: Christian Louis Kühner, Florian Pfeffel, Valentin Nickolai

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Taking care of children, dependents, or pets can be a difficult and time-consuming task. Especially for part- and full-time employees, it can feel exhausting and overwhelming to meet these obligations besides working a job. Thus, working mostly at home and not having to drive to the company can save valuable time and stress. This study aims to show the influence that the working model has on the job satisfaction of employees with care responsibilities in comparison to employees who do not have such obligations. Using structural equation modeling (SEM), the three work models, “work from home”, “working remotely”, and a hybrid model, have been analyzed based on 13 influencing constructs on job satisfaction. These 13 factors have been further summarized into three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, an online survey was conducted with n = 684 employees from the service sector. Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. In addition, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that among the employees with care responsibilities, the higher the proportion of working from home in comparison to working from the office, the more satisfied the employees are with their job. Since the work models that meet the requirements of comprehensive care led to higher job satisfaction amongst employees with such obligations, adapting as a company to such private obligations by employees can be crucial to sustained success. Conversely, the satisfaction level of the working model where employees work at the office is higher for workers without caregiving responsibilities.

Keywords: care responsibilities, home office, job satisfaction, structural equation modeling

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Authors: Vijay Goud, Ramasamy Alagirusamy, Apurba Das, Dinesh Kalyanasundaram

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Thermoplastic composites render new opportunities as effective processing technology while crafting newer complications into processing. One of the notable challenges is in achieving thorough wettability that is significantly deterred by the high viscosity of the long molecular chains of the thermoplastics. As a result of high viscosity, it is very difficult to impregnate the resin into a tightly interlaced textile structure to fill the voids present in the structure. One potential solution to the above problem, is to pre-deposit resin on the fiber, prior to consolidation. The current study compares DREF spinning, powder coating and film stacking methods of predeposition of resin onto fibers. An investigation into the flexural properties of unidirectional composites (UDC) produced from blending of carbon fiber and polypropylene (PP) matrix in varying forms of fiber, powder and film are reported. Dr. Ernst Fehrer (DREF) yarns or friction spun hybrid yarns were manufactured from PP fibers and carbon tows. The DREF yarns were consolidated to yield unidirectional composites (UDCs) referred to as UDC-D. PP in the form of powder was coated on carbon tows by electrostatic spray coating. The powder-coated towpregs were consolidated to form UDC-P. For the sake of comparison, a third UDC referred as UDC-F was manufactured by the consolidation of PP films stacked between carbon tows. The experiments were designed to yield a matching fiber volume fraction of about 50 % in all the three UDCs. A comparison of mechanical properties of the three composites was studied to understand the efficiency of matrix wetting and impregnation. Approximately 19% and 68% higher flexural strength were obtained for UDC-P than UDC-D and UDC-F respectively. Similarly, 25% and 81% higher modulus were observed in UDC-P than UDC-D and UDC-F respectively. Results from micro-computed tomography, scanning electron microscopy, and short beam tests indicate better impregnation of PP matrix in UDC-P obtained through electrostatic spray coating process and thereby higher flexural strength and modulus.

Keywords: DREF spinning, film stacking, flexural strength, powder coating, thermoplastic composite

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Authors: Ana Pego

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Environmental technologies were developed for decades. Clean technologies emerged a few years ago. In these perspectives, the use of cleantech technologies has become very important due the fact of new era of environmental feats. As such, the market itself has become more competitive, more collaborative towards a better use of clean technologies. This paper shows the importance of clean technologies in offshore energy sector in Portuguese market, its localization and its impact on economy. Clean technologies are directly related with renewable cluster and concomitant with economic and social resource optimization criteria, geographic aspects, climate change and soil features. Cleantech is related with regional development, socio-technical transitions in organisations. There are an economical and social combinations which allow specialisation of regions in activities, higher employment, reduce of energy costs, local knowledge spillover and, business collaboration and competitiveness. The methodology used will be quantitative (IO matrix for Portugal 2013) and qualitative (questionnaires to stakeholders). The mix of both methodologies will confirm whether the use of technologies will allow a positive impact on economic and social variables used on this model. It is expected a positive impact on Portuguese economy both in investment and employment taking in account the localization of offshore renewable activities. This means that the importance of offshore renewable investment in Portugal has a few points which should be pointed out: the increase of specialised employment, localization of specific activities in territory, and increase of value added in certain regions. The conclusion will allow researchers and organisation to compare the Portuguese model to other European regions in order to a better use of natural and human resources.

Keywords: cleantech, economic impact, localisation, territory dynamics

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Authors: Lianxue Shi

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Urban waterfront rail transit stations exert a dual impact on both the waterfront and the transit station, resulting in a concentration of development elements in the surrounding space. In order to more effectively develop the space around the station, this study focuses on the perspective of the integration of station, city, and people. Taking Chongqing as an example, based on the Arc GIS platform, it explores the vitality of the site from the three dimensions of crowd activity heat, space facilities heat, and spatial accessibility. It conducts a comprehensive evaluation and interpretation of the vitality surrounding the waterfront rail transit station area in Chongqing. The study found that (1) the spatial vitality in the vicinity of waterfront rail transit stations is correlated with the waterfront's functional zoning and the intensity of development. Stations situated in waterfront residential and public spaces are more likely to experience a convergence of people, whereas those located in waterfront industrial areas exhibit lower levels of vitality. (2) Effective transportation accessibility plays a pivotal role in maintaining a steady flow of passengers and facilitating their movement. However, the three-dimensionality of urban space in mountainous regions is a notable challenge, leading to some stations experiencing limited accessibility. This underscores the importance of enhancing the optimization of walking space, particularly the access routes from the station to the waterfront area. (3) The density of spatial facilities around waterfront stations in old urban areas lags behind the population's needs, indicating a need to strengthen the allocation of relevant land and resources in these areas.

Keywords: rail transit station, waterfront, influence area, spatial vitality, urban vitality

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Authors: Yen-Luan Chen

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Maintenance has a great impact on the capacity of production and on the quality of the products, and therefore, it deserves continuous improvement. Maintenance procedure done before a failure is called preventive maintenance (PM). Sequential PM, which specifies that a system should be maintained at a sequence of intervals with unequal lengths, is one of the commonly used PM policies. This article proposes a generalized sequential PM policy for a system subject to shocks with imperfect maintenance and random working time. The shocks arrive according to a non-homogeneous Poisson process (NHPP) with varied intensity function in each maintenance interval. As a shock occurs, the system suffers two types of failures with number-dependent probabilities: type-I (minor) failure, which is rectified by a minimal repair, and type-II (catastrophic) failure, which is removed by a corrective maintenance (CM). The imperfect maintenance is carried out to improve the system failure characteristic due to the altered shock process. The sequential preventive maintenance-last (PML) policy is defined as that the system is maintained before any CM occurs at a planned time Ti or at the completion of a working time in the i-th maintenance interval, whichever occurs last. At the N-th maintenance, the system is replaced rather than maintained. This article first takes up the sequential PML policy with random working time and imperfect maintenance in reliability engineering. The optimal preventive maintenance schedule that minimizes the mean cost rate of a replacement cycle is derived analytically and determined in terms of its existence and uniqueness. The proposed models provide a general framework for analyzing the maintenance policies in reliability theory.

Keywords: optimization, preventive maintenance, random working time, minimal repair, replacement, reliability

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Authors: Bita Payami-Shabestari, Dariush Eslami

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The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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Authors: Hyeonkyeong Yang, Minseok Son, Taekbeom Yoo, Woojin Park

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Human error is the most salient contributing factor to railway accidents. To reduce the frequency of human errors, many researchers and train designers have adopted ergonomic design principles for designing display-control layout in rail cab. There exist a number of approaches for designing the display control layout based on optimization methods. However, the ergonomically optimized layout design may not be the best design for train drivers, since the drivers have their own mental models based on their experiences. Consequently, the drivers may prefer the existing display-control layout design over the optimal design, and even show better driving performance using the existing design compared to that using the optimal design. Thus, in addition to ergonomic design principles, train drivers’ mental models also need to be considered for designing display-control layout in rail cab. This paper developed an ergonomic assessment system of display-control layout design, and an interactive layout design system that can generate design alternatives and calculate ergonomic assessment score in real-time. The design alternatives generated from the interactive layout design system may not include the optimal design from the ergonomics point of view. However, the system’s strength is that it considers train drivers’ mental models, which can help generate alternatives that are more friendly and easier to use for train drivers. Also, with the developed system, non-experts in ergonomics, such as train drivers, can refine the design alternatives and improve ergonomic assessment score in real-time.

Keywords: display-control layout design, interactive layout design system, mental model, train drivers

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Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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Authors: Natalia Moreno-Castellanos, Amaia Rodriguez, Gema Frühbeck

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Introduction: In adipocytes, the cytoskeleton undergoes important expression and distribution in adipocytes rearrangements during adipogenesis and in obesity. Indeed, a role for these proteins in the regulation of adipocyte differentiation and response to insulin has been demonstrated. Recently, septins have been considered as new components of the cytoskeletal network that interact with other cytoskeletal elements (actin and tubulin) profoundly modifying their dynamics. However, these proteins have not been characterized as yet in adipose tissue. In this work, were examined the cellular, molecular and functional features of a member of this family, septin 11 (SEPT11), in adipocytes and evaluated the impact of obesity on the expression of this protein in human adipose tissue. Methods: Adipose gene and protein expression levels of SEPT11 were analysed in human samples. SEPT11 distribution was evaluated by immunocytochemistry, electronic microscopy, and subcellular fractionation techniques. GST-pull down, immunoprecipitation and a Yeast-Two Hybrid (Y2H) screening were used to identify the SEPT11 interactome. Gene silencing was employed to assess the role of SEPT11 in the regulation of insulin signaling and lipid metabolism in adipocytes. Results: SEPT11 is expressed in human adipocytes, and its levels increased in both omental and subcutaneous adipose tissue in obesity, with SEPT11 mRNA content positively correlating with parameters of insulin resistance in subcutaneous fat. In non-stimulated adipocytes, SEPT11 immunoreactivity showed a ring-like distribution at the cell surface and associated to caveolae. Biochemical analyses showed that SEPT11 interacted with the main component of caveolae, caveolin-1 (CAV1) as well as with the fatty acid-binding protein, FABP5. Notably, the three proteins redistributed and co-localized at the surface of lipid droplets upon exposure of adipocytes to oleate. In this line, SEPT11 silencing in 3T3-L1 adipocytes impaired insulin signaling and decreased insulin-induced lipogenesis. Conclusions: Those findings demonstrate that SEPT11 is a novel component of the adipocyte cytoskeleton that plays an important role in the regulation of lipid traffic, metabolism and can thus represent a potential biomarker of insulin resistance in obesity in adipocytes through its interaction with both CAV1 and FABP5.

Keywords: caveolae, lipid metabolism, obesity, septins

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Authors: Rajiv Kumar Srivastava

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Manufacturing of complex products such as automobiles and computers requires a very large number of parts and sub-assemblies. The design of mechanisms for delivery of these materials to the point of assembly is an important manufacturing system and supply chain challenge. Different approaches to this problem have been evolved for assembly lines designed to make large volumes of standardized products. However, contemporary assembly systems are required to concurrently produce a variety of products using approaches such as mixed model production, and at times even mass customization. In this paper we examine the material supply approaches for variety production in moderate to large volumes. The conventional approach for material delivery to high volume assembly lines is to supply and stock materials line-side. However for certain materials, especially when the same or similar items are used along the line, it is more convenient to supply materials in kits. Kitting becomes more preferable when lines concurrently produce multiple products in mixed model mode, since space requirements could increase as product/ part variety increases. At times such kits may travel along with the product, while in some situations it may be better to have delivery and station-specific kits rather than product-based kits. Further, in some mass customization situations it may even be better to have a single delivery and assembly station, to which an entire kit is delivered for fitment, rather than a normal assembly line. Finally, in low-moderate volume assembly such as in engineered machinery, it may be logistically more economical to gather materials in an order-specific kit prior to launching final assembly. We have studied material supply mechanisms to support assembly systems as observed in case studies of firms with different combinations of volume and variety/ customization. It is found that the appropriate approach tends to be a hybrid between direct line supply and different kitting modes, with the best mix being a function of the manufacturing and supply chain environment, as well as space and handling considerations. In our continuing work we are studying these scenarios further, through the use of descriptive models and progressing towards prescriptive models to help achieve the optimal approach, capturing the trade-offs between inventory, material handling, space, and efficient line supply.

Keywords: assembly systems, kitting, material supply, variety production

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Authors: He Li

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Around the mid-1980s, Confucianism was reintroduced into China from Taiwan and Hong Kong as a result of China’s policies of reform and openness. Since then, the revival of neo-Confucianism in mainland China has accelerated and become a crucial component of the public intellectual sphere. The term xinrujia or xinruxue, loosely translated as “neo-Confucianism,” is increasingly understood as an intellectual and cultural phenomenon of the last four decades. The Confucian scholarship is in the process of restoration. This paper examines the Chinese intellectual discourse on Confucianism and democracy and places it in comparative and theoretical perspectives. With China’s rise and surge of populism in the West, particularly in the US, the leading political values of Confucianism could increasingly shape both China and the world at large. This state of affairs points to the need for more systematic efforts to assess the discourse on neo-Confucianism and its implications for China’s transformation. A number of scholars in the camp of neo-Confucianism maintain that some elements of Confucianism are not only compatible with democratic values and institutions but actually promote liberal democracy. They refer to it as Confucian democracy. By contrast, others either view Confucianism as a roadblock to democracy or envision that a convergence of democracy with Confucian values could result in a new hybrid system. The paper traces the complex interplay between Confucianism and democracy. It explores ideological differences between neo-Confucianism and liberal democracy and ascertains whether certain features of neo-Confucianism possess an affinity for the authoritarian political system. In addition to printed materials such as books and journal articles, a selection of articles from the website entitled Confucianism in China will be analyzed. The selection of this website is due to the fact that it is the leading website run by Chinese scholars focusing on neo-Confucianism. Another reason for selecting this website is its accessibility and availability. In the past few years, quite a few websites, left or right, were shut down by the authorities, but this website remains open. This paper explores the core components, dynamics, and implications of neo-Confucianism. My paper is divided into three parts. The first one discusses the origins of neo-Confucianism. The second section reviews the intellectual discourse among Chinese scholars on Confucian democracy. The third one explores the implications of the Chinese intellectual discourse on neo-Confucianism. Recently, liberal democracy has entered more conflict with official ideology. This paper, which is based on my extensive interviews in China prior to the pandemic and analysis of the primary sources in Chinese, will lay the foundation for a chapter on neo-Confucianism and democracy in my next book-length manuscript, tentatively entitled Chinese Intellectual Discourse on Democracy.

Keywords: China, confucius, confucianism, neo-confucianism, democracy

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Authors: Hansraj Bookun, Angela Tan, Rachel Xuan, Linheng Zhao, Kejia Wang, Animesh Singla, David Kim, Christopher Loupos

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Introduction: Incisional wound complications in vascular surgery patients represent a significant clinical and econometric burden of morbidity and mortality. The objective of this study was to trial the feasibility of applying the Prevena negative pressure incision management system as a routine dressing in patients who had undergone arterial surgery. Conventionally, Prevena has been applied to groin incisions, but this study features applications on multiple wound sites such as the thigh or major amputation stumps. Method: This was a cross-sectional observational, single-centre case series of 12 patients who had undergone major vascular surgery. Their wounds were managed with the Prevena system being applied either intra-operatively or on the first post-operative day. Demographic and operative details were collated as well as the length of stay and complication rates. Results: There were 9 males (75%) with mean age of 66 years and the comorbid burden was as follows: ischaemic heart disease (92%), diabetes (42%), hypertension (100%), stage 4 or greater kidney impairment (17%) and current or ex-smoking (83%). The main indications were acute ischaemia (33%), claudication (25%), and gangrene (17%). There were single instances of an occluded popliteal artery aneurysm, diabetic foot infection, and rest pain. The majority of patients (50%) had hybrid operations with iliofemoral endarterectomies, patch arterioplasties, and further peripheral endovascular treatment. There were 4 complex arterial bypass operations and 2 major amputations. The mean length of stay was 17 ± 10 days, with a range of 4 to 35 days. A single complication, in the form of a lymphocoele, was encountered in the context of an iliofemoral endarterectomy and patch arterioplasty. This was managed conservatively. There were no deaths. Discussion: The Prevena wound management system shows that in conjunction with safe vascular surgery, absolute wound complication rates remain low and that it remains a valuable adjunct in the treatment of vasculopaths.

Keywords: wound care, negative pressure, vascular surgery, closed incision

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Authors: Umme Hani, Mohammed Rahmatulla, Mohammed Ghazwani, Ali Alqahtani, Yahya Alhamhoom

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Background and introduction: Neratinib is a potent anticancer drug used for the treatment of breast cancer. It is poorly soluble at higher pH, which tends to minimize the therapeutic effects in the lower gastrointestinal tract (GIT) leading to poor bioavailability. An attempt has been made to prepare and develop a gastro-retentive system of Neratinib to improve the drug bioavailability in the GIT by enhancing the gastric retention time. Materials and methods: In the present study a three-factor at two-level (23) factorial design based optimization was used to inspect the effects of three independent variables (factors) such as sodium alginate (A), sodium bicarbonate (B) and sodium citrate (C) on the dependent variables like in vitro gelation, in vitro floating, water uptake and percentage drug release. Results: All the formulations showed pH in the range 6.7 ±0.25 to 7.4 ±0.24, percentage drug content was observed to be 96.3±0.27 to 99.5 ±0.28%, in vitro gelation observed as gelation immediate remains for an extended period. Percentage of water uptake was in the range between 9.01±0.15 to 31.01±0.25%, floating lag time was estimated form 7±0.39 to 57±0.36 sec. F4 and F5 showed floating even after 12hrs. All formulations showed a release of around 90% drug release within 12hr. It was observed that the selected independent variables affect the dependent variables. Conclusion: The developed system may be a promising and alternative approach to augment gastric retention of drugs and enhances the therapeutic efficacy of the drug.

Keywords: neratinib, 2³ factorial design, sodium alginate, floating, in situ gelling system

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Authors: Shahbaz Abbas, Lin Han Chiang Hsieh

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The significant population growth and climate change issues have contributed to the natural resources depletion and their sustainability in the future. Manufacturing industries have a substantial impact on every country’s economy, but the sustainability of the industrial resources is challenging, and the policymakers have been developing the possible solutions to manage the sustainability of industrial resources such as raw material, energy, water, and industrial supply chain. In order to address these challenges, nexus approach is one of the optimization and modelling techniques in the recent sustainable environmental research. The interactions between the nexus components acknowledge that all components are dependent upon each other, and they are interrelated; therefore, their sustainability is also associated with each other. In addition, the nexus concept does not only provide the resources sustainability but also environmental sustainability can be achieved through nexus approach by utilizing the industrial waste as a resource for the industrial processes. Based on energy-water nexus, this study has developed a resource-energy-water for the sugar industry to understand the interactions between sugarcane, energy, and water towards the sustainable sugar industry. In particular, the focus of the research is the Taiwanese sugar industry; however, the same approach can be adapted worldwide to optimize the sustainability of sugar industries. It has been concluded that there are significant interactions between sugarcane, energy consumption, and water consumption in the sugar industry to manage the scarcity of resources in the future. The interactions between sugarcane and energy also deliver a mechanism to reuse the sugar industrial waste as a source of energy, consequently validating industrial and environmental sustainability. The desired outcomes from the nexus can be achieved with the modifications in the policy and regulations of Taiwanese industrial sector.

Keywords: energy-water nexus, environmental sustainability, industrial sustainability, natural resource management

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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