Search results for: high performance concrete (HPC)

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

Procedia PDF Downloads 222

Authors: Jae Soo Do, Kyoung-Seok Kim

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Radical changes in the industrial environment, and spectacular developments of IT have changed the current of managements from people-centered to technology- or IT-centered. Interpersonal emotion exchanges have long become insipid and interactive services have also come as mechanical reactions. This study offers various concepts for the emotional labor based on traditional studies on emotional labor. Especially the present day, on which human emotions are subject to being served as machinized thing, is the time when the study on human emotions comes momentous. Precedent researches on emotional labors commonly and basically dealt with the relationship between the active group who performs actions and the passive group who is done with the action. This study focuses on the passive group and tries to offer a new perspective of 'liquid emotion' as a defence mechanism for the passive group from the external environment. Especially, this addresses a concrete discussion on directions of following studies on the liquid labor as a newly suggested perspective.

Keywords: emotion labor, surface acting, deep acting, liquid emotion

Procedia PDF Downloads 349

Authors: Sri Sharath Kulkarni, Pauline Janssen, Alberto Berardi, Bastiaan Dickhoff, Sander van Gessel

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Blending is a common process in the production of pharmaceutical dosage forms where the high shear is used to obtain a homogenous dosage. The shear required can lead to uncontrolled attrition of excipients and affect API’s. This has an impact on the performance of the formulation as this can alter the structure of the mixture. Therefore, it is important to understand the driving mechanisms for attrition. The aim of this study was to increase the fundamental understanding of the attrition behavior of excipients. Attrition behavior of the excipients was evaluated using a high shear blender (Procept Form-8, Zele, Belgium). Twelve pure excipients are tested, with morphologies varying from crystalline (sieved), granulated to spray dried (round to fibrous). Furthermore, materials include lactose, microcrystalline cellulose (MCC), di-calcium phosphate (DCP), and mannitol. The rotational speed of the blender was set at 1370 rpm to have the highest shear with a Froude (Fr) number 9. Varying blending times of 2-10 min were used. Subsequently, after blending, the excipients were analyzed for changes in particle size distribution (PSD). This was determined (n = 3) by dry laser diffraction (Helos/KR, Sympatec, Germany). Attrition was found to be a surface phenomenon which occurs in the first minutes of the high shear blending process. An increase of blending time above 2 mins showed no change in particle size distribution. Material chemistry was identified as a key driver for differences in the attrition behavior between different excipients. This is mainly related to the proneness to fragmentation, which is known to be higher for materials such as DCP and mannitol compared to lactose and MCC. Secondly, morphology also was identified as a driver of the degree of attrition. Granular products consisting of irregular surfaces showed the highest reduction in particle size. This is due to the weak solid bonds created between the primary particles during the granulation process. Granular DCP and mannitol show a reduction of 80-90% in x10(µm) compared to a 20-30% drop for granular lactose (monohydrate and anhydrous). Apart from the granular lactose, all the remaining morphologies of lactose (spray dried-round, sieved-tomahawk, milled) show little change in particle size. Similar observations have been made for spray-dried fibrous MCC. All these morphologies have little irregular or sharp surfaces and thereby are less prone to fragmentation. Therefore, products containing brittle materials such as mannitol and DCP are more prone to fragmentation when exposed to shear. Granular products with irregular surfaces lead to an increase in attrition. While spherical, crystalline, or fibrous morphologies show reduced impact during high shear blending. These changes in size will affect the functionality attributes of the formulation, such as flow, API homogeneity, tableting, formation of dust, etc. Hence it is important for formulators to fully understand the excipients to make the right choices.

Keywords: attrition, blending, continuous manufacturing, excipients, lactose, microcrystalline cellulose, shear

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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Borosilicate-crown (BK7) glass has found broad application in the optic and automotive industries and the growing demands for nanometric surface finishes is becoming a necessity in such applications. Thus, it has become paramount to optimize the parameters influencing the surface roughness of this precision lens. The research was carried out on a 4-axes Nanoform 250 precision lathe machine with an ultra-high precision grinding spindle. The experiment varied the machining parameters of feed rate, wheel speed and depth of cut at three levels for different combinations using Box Behnken design of experiment and the resulting surface roughness values were measured using a Taylor Hobson Dimension XL optical profiler. Acoustic emission monitoring technique was applied at a high sampling rate to monitor the machining process while further signal processing and feature extraction methods were implemented to generate the input to a neural network algorithm. This paper highlights the training and development of a back propagation neural network prediction algorithm through careful selection of parameters and the result show a better classification accuracy when compared to a previously developed response surface model with very similar machining parameters. Hence artificial neural network algorithms provide better surface roughness prediction accuracy in the ultra-high precision grinding of BK7 glass.

Keywords: acoustic emission technique, artificial neural network, surface roughness, ultra-high precision grinding

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Authors: M. Ciminello, I. Dimino, S. Ameduri, A. Concilio

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Improving aircraft's efficiency is one of the key elements of Aeronautics. Modern aircraft possess many advanced functions, such as good transportation capability, high Mach number, high flight altitude, and increasing rate of climb. However, no aircraft has a possibility to reach all of this optimized performance in a single airframe configuration. The aircraft aerodynamic efficiency varies considerably depending on the specific mission and on environmental conditions within which the aircraft must operate. Structures that morph their shape in response to their surroundings may at first seem like the stuff of science fiction, but take a look at nature and lots of examples of plants and animals that adapt to their environment would arise. In order to ensure both the controllable and the static robustness of such complex structural systems, a monitoring network is aimed at verifying the effectiveness of the given control commands together with the elastic response. In order to achieve this kind of information, the use of FBG sensors network is, in this project, proposed. The sensor network is able to measure morphing structures shape which may show large, global displacements due to non-standard architectures and materials adopted. Chord -wise variations may allow setting and chasing the best layout as a function of the particular and transforming reference state, always targeting best aerodynamic performance. The reason why an optical sensor solution has been selected is that while keeping a few of the contraindication of the classical systems (like cabling, continuous deployment, and so on), fibre optic sensors may lead to a dramatic reduction of the wires mass and weight thanks to an extreme multiplexing capability. Furthermore, the use of the ‘light’ as ‘information carrier’, permits dealing with nimbler, non-shielded wires, and avoids any kind of interference with the on-board instrumentation. The FBG-based transducers, herein presented, aim at monitoring the actual shape of adaptive trailing edge. Compared to conventional systems, these transducers allow more fail-safe measurements, by taking advantage of a supporting structure, hosting FBG, whose properties may be tailored depending on the architectural requirements and structural constraints, acting as strain modulator. The direct strain may, in fact, be difficult because of the large deformations occurring in morphing elements. A modulation transducer is then necessary to keep the measured strain inside the allowed range. In this application, chord-wise transducer device is a cantilevered beam sliding trough the spars and copying the camber line of the ATE ribs. FBG sensors array position are dimensioned and integrated along the path. A theoretical model describing the system behavior is implemented. To validate the design, experiments are then carried out with the purpose of estimating the functions between rib rotation and measured strain.

Keywords: fiber optic sensor, morphing structures, strain sensor, shape reconstruction

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Authors: Nikhil Jain, Yang Xu, Bin Yu

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The material behavior of graphene, a single layer of carbon lattice, is extremely sensitive to its dielectric environment. We demonstrate improvement in electronic performance of graphene nanowire interconnects with full encapsulation by lattice-matching, chemically inert, 2D layered insulator hexagonal boron nitride (h- BN). A novel layer-based transfer technique is developed to construct the h-BN/MLG/h-BN heterostructures. The encapsulated graphene wires are characterized and compared with that on SiO2 or h-BN substrate without passivating h-BN layer. Significant improvements in maximum current-carrying density, breakdown threshold, and power density in encapsulated graphene wires are observed. These critical improvements are achieved without compromising the carrier transport characteristics in graphene. Furthermore, graphene wires exhibit electrical behavior less insensitive to ambient conditions, as compared with the non-passivated ones. Overall, h-BN/graphene/h- BN heterostructure presents a robust material platform towards the implementation of high-speed carbon-based interconnects.

Keywords: two-dimensional nanosheet, graphene, hexagonal boron nitride, heterostructure, interconnects

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Amina Ottozbeer, Nazanin Derakhshan

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Emotion regulation, a transdiagnostic process, is often impaired in individuals with high trait anxiety due to compromised executive functioning and attentional control. Recent research underscores the importance of studying individual differences and contextual factors in understanding the adaptability of emotion regulation processes, particularly in those with high trait anxiety. Prior studies have emphasized the role of self-efficacy in promoting positive cognitive flexibility outcomes and mitigating executive function impairments in highly anxious individuals. Accordingly, the objective of this study was to examine the moderating influence of attentional control, cognitive flexibility, and self-efficacy on the relationship between trait anxiety and emotion regulation. Using a correlational design, an online study was conducted with a sample of 82 participants (mean age: 22 years). Self-report questionnaires measured individual difference variables. The Classic Stroop Task assessed attentional control as an objective measure of cognitive flexibility . The findings revealed three significant interactions. Firstly, high cognitive flexibility and self-efficacy were linked to reduced expressive suppression in individuals with low trait anxiety. Secondly, elevations in cognitive flexibility and self-efficacy were associated with increased suppression in those with high trait anxiety. Thirdly, high trait anxiety was associated with reduced attentional control. The results suggest that typically adaptive processes can yield different outcomes in highly anxious populations, highlighting the need to explore additional variables that could alter the impact of cognitive flexibility and self-efficacy on emotion regulation in individuals with high anxiety. These findings have significant clinical implications, emphasizing the need to consider individual differences in emotion regulation and trait anxiety to inform more effective psychological treatments.

Keywords: attentional control, trait anxiety, emotional dysregulation, transdiagnostic, individual differences

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Authors: Nadia Hammouda, Kamel Belmokre

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Organic coatings are widely employed in the corrosion protection of most metal surfaces, particularly steel. They provide a barrier against corrosive species present in the environment, due to their high resistance to oxygen, water and ions transport. This study focuses on the evaluation of corrosion protection performance of epoxy paint on the carbon steel surface in sea water by Electrochemical Impedance Spectroscopy (EIS). The electrochemical behavior of painted surface was estimated by EIS parameters that contained paint film resistance, paint film capacitance and double layer capacitance. On the basis of calculation using EIS spectrums it was observed that pore resistance (Rpore) decreased with the appearance of doubled layer capacitance (Cdl) due to the electrolyte penetration through the film. This was further confirmed by the decrease of diffusion resistance (Rd) which was also the indicator of the deterioration of paint film protectiveness.

Keywords: epoxy paints, carbon steel, electrochemical impedance spectroscopy, corrosion mechanisms, sea water

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Authors: Enrique Claver Cortés, Bartolomé Marco Lajara, Eduardo Sánchez García, Pedro Seva Larrosa, Encarnación Manresa Marhuenda, Lorena Ruiz Fernández, Esther Poveda Pareja

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In recent decades, the analysis of the effects of clustering as an essential factor for the development of innovations and the competitiveness of enterprises has raised great interest in different areas. Nowadays, companies have access to almost all tangible and intangible resources located and/or developed in any country in the world. However, despite the obvious advantages that this situation entails for companies, their geographical location has shown itself, increasingly clearly, to be a fundamental factor that positively influences their innovative performance and competitiveness. Industrial clusters could represent a unique level of analysis, positioned between the individual company and the industry, which makes them an ideal unit of analysis to determine the effects derived from company membership of a cluster. Also, the absorptive capacity (hereinafter 'AC') can mediate the process of innovation development by companies located in a cluster. The transformation and exploitation of knowledge could have a mediating effect between knowledge acquisition and innovative performance. The main objective of this work is to determine the key factors that affect the degree of generation and use of knowledge from the environment by companies and, consequently, their innovative performance and competitiveness. The elements analyzed are the companies' membership of a cluster and the AC. To this end, 30 most relevant papers published on this subject in the "Web of Science" database have been reviewed. Our findings show that, within a cluster, the knowledge coming from the companies' environment can significantly influence their innovative performance and competitiveness, although in this relationship, the degree of access and exploitation of the companies to this knowledge plays a fundamental role, which depends on a series of elements both internal and external to the company.

Keywords: absorptive capacity, clusters, innovation, knowledge

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Authors: C. Hernandez-Garcia, P. Adderley, D. Bullard, J. Grames, M. A. Mamun, G. Palacios-Serrano, M. Poelker, M. Stutzman, R. Suleiman, Y. Wang, , S. Zhang

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High-energy nuclear physics experiments performed at the Jefferson Lab (JLab) Continuous Electron Beam Accelerator Facility require a beam of spin-polarized ps-long electron bunches. The electron beam is generated when a circularly polarized laser beam illuminates a GaAs semiconductor photocathode biased at hundreds of kV dc inside an ultra-high vacuum chamber. The photocathode is mounted on highly polished stainless steel electrodes electrically isolated by means of a conical-shape ceramic insulator that extends into the vacuum chamber, serving as the cathode electrode support structure. The assembly is known as a dc photogun, which has to simultaneously meet the following criteria: high voltage to manage space charge forces within the electron bunch, ultra-high vacuum conditions to preserve the photocathode quantum efficiency, no field emission to prevent gas load when field emitted electrons impact the vacuum chamber, and finally no voltage breakdown for robust operation. Over the past decade, JLab has tested and implemented the use of inverted geometry ceramic insulators connected to commercial high voltage cables to operate a photogun at 200kV dc with a 10 cm long insulator, and a larger version at 300kV dc with 20 cm long insulator. Plans to develop a third photogun operating at 400kV dc to meet the stringent requirements of the proposed International Linear Collider are underway at JLab, utilizing even larger inverted insulators. This contribution describes approaches that have been successful in solving challenging problems related to breakdown and field emission, such as triple-point junction screening electrodes, mechanical polishing to achieve mirror-like surface finish and high voltage conditioning procedures with Kr gas to extinguish field emission.

Keywords: electron guns, high voltage techniques, insulators, vacuum insulation

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Authors: M. Bolacali

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The aim of the study is to determine the effect of immunocastration vaccine administration at different doses on fattening performance of feedlot Holstein bulls. Bopriva® is a vaccine that stimulates the animals' own immune system to produce specific antibodies against gonadotropin releasing factor (GnRF). Ninety four Holstein male calves (309.5 ± 2.58 kg body live weight and 267 d-old) assigned to the 4 treatments. Control group; 1 mL of 0.9% saline solution was subcutaneously injected to intact bulls on 1st and 60th days of the feedlot as placebo. On the same days of the feedlot, Bopriva® at two doses of 1 mL and 1 mL for Trial-1 group, 1.5 mL, and 1.5 mL for Trial-2 group, 1.5 mL, and 1 mL for Trial-3 group were subcutaneously injected to bulls. The study was conducted in a private establishment in the Sirvan district of Siirt province and lasted 180 days. The animals were weighed at the beginning of fattening and at 30-day intervals to determine their live weights at various periods. The statistical analysis for normal distribution data of the treatment groups was carried out with the general linear model procedure of SPSS software. The fattening initial live weight in Control, Trial-1, Trial-2 and Trial-3 groups was respectively 309.21, 306.62, 312.11, and 315.39 kg. The fattening final live weight was respectively 560.88, 536.67, 548.56, and 548.25 kg. The daily live weight gain during the trial was respectively 1.40, 1.28, 1.31, and 1.29 kg/day. The cold carcass yield was respectively 51.59%, 50.32%, 50.85%, and 50.77%. Immunocastration vaccine administration at different doses did not affect the live weights and cold carcass yields of Holstein male calves reared under intensive conditions (P > 0.05). However, it was determined to reduce fattening performance between 61-120 days (P < 0.05) and 1-180 days (P < 0.01). In addition, it was determined that the best performance among the vaccine-treated groups occurred in the group administered a 1.5 mL of vaccine on the 1st and 60th study days. In animals, castration is used to control fertility, aggressive and sexual behaviors. As a result, the fact that stress is induced by physical castration in animals and active immunization against GnRF maintains performance by maximizing welfare in bulls improves carcass and meat quality and controls unwanted sexual and aggressive behavior. Considering such features, it may be suggested that immunocastration vaccine with Bopriva® can be administered as a 1.5 mL dose on the 1st and 60th days of the fattening period in Holstein bulls.

Keywords: anti-GnRF, fattening, growth, immunocastration

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Authors: Ebuka Valentine Iroha, Tsunemi Watanabe, Satoshi Tsuchiya

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Project management practices play an important role in construction project performance and are one of project managers' essential key performance indicators. Previous studies have explored the poor performance of the construction industry, with project delays and cost overruns identified to contribute largely to numerous abandoned projects. These challenges are attributed to insufficient project management practices and a lack of utilization of project managers. The actual causes of inadequate project management practices and underutilization of project managers have been rarely discussed. This study tends to bridge the gap by identifying and assessing the actual causes of insufficient project management practices and underutilization of project managers. This study differs from past studies investigating the causes of poor performance by using institutional analysis methods to identify and analyze the factors influencing project management practices and proper utilization of project managers. Based on a comprehensive literature review, this study identified some factors embedded in the construction industry that influence the institutional environment and weaken the laws and regulations. These factors were used as the basis for semi-structured interview questions to investigate their impacts on project management practices and project managers. The data collected were coded into a four-level framework for institutional analysis. This method was used to analyze the interrelationships between the identified embedded factors, institutional laws and regulations, and construction organizations to understand how these influences result in the underutilization of project managers. The study found that the underutilization of project managers consists of two subsystems, including underutilization and lowering commitment. The first subsystem, corruption, political influence, religious and tribal discrimination, and organizational culture, were found to affect the institutional structure. These embedded factors weaken the industry’s governance mechanism, forcing project managers to prioritize corrupt practices over project demands. The ineffectiveness of the existing laws and regulations worsens the situation, supporting unfair working conditions and contributing to the underperformance of project managers. This situation leads to the development of the second subsystem, which is characterized by a lack of opportunities for career development and minimal incentives within construction organizations. The findings provide significant potential for addressing systemic challenges in the construction industry, particularly the underutilization of project managers and enhancing organizational support measures to improve project management practices and mitigate the adverse effects of corruption.

Keywords: construction industry, project management, poor performance, embedded factors, project managers underutilization

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Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

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Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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Authors: Khadidja Mahdi, Salaheddine Doumandji

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Among the natural enemies that reduce populations of the tomato leaf miner studied in experimental plots of National High school of agriculture (ENSA, Algeria, 36° 40’ à 36° 43’ N.; 3° 08’ à 3° 12’ E.), larval ectoparasites. Three larval ectoparasites are reported in this study namely Necrinmus Sp. and two species of indeterminate Chalcidae (Chalcidae Sp. 1 and 2). These species have significantly reduced the effectives of Tuta absoluta. The results for the parasitism of eggs, larval instars and pupae of Tuta absoluta on the open field tomato in the experimental plots of ENSA show high levels of parasite eggs with 25%. With 94.7%, the first larval instar (L1) is the most parasites. The second instar (L2) undergoes the action of parasitoids least 60%. Instars L3 and L4 and pupae remain unharmed.

Keywords: tuta absoluta, larval ectoparasites, tomato, ensa, Algeria

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Authors: Amal M. Alrayes, Hayat M. Ali

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Since the beginning of distance education with the rapid evolution of technology, the social network plays a vital role in the educational process to enforce the interaction been the learners and teachers. There are many Web 2.0 technologies, services and tools designed for educational purposes. This research aims to investigate instructors’ acceptance towards web-based learning systems in higher educational institutes in Kingdom of Bahrain. Questionnaire is used to investigate the instructors’ usage of Web 2.0 and the factors affecting their acceptance. The results confirm that instructors had high accessibility to such technologies. However, patterns of use were complex. Whilst most expressed interest in using online technologies to support learning activities, learners seemed cautious about other values associated with web-based system, such as the shared construction of knowledge in a public format. The research concludes that there are main factors that affect instructors’ adoption which are security, performance expectation, perceived benefits, subjective norm, and perceived usefulness.

Keywords: Web 2.0, higher education, acceptance, students' perception

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Authors: Thanapat Chaireongsirikul, Apichit Svang-Ariyaskul

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An analysis of mass balance, energy performance, and environmental impact assessment were performed to evaluate bioethanol production in Thailand. Thailand is an agricultural country. Thai government plans to increase the use of alternative energy to 20 percent by 2022. One of the primary campaigns is to promote a bioethanol production from abundant biomass resources such as bitter cassava, molasses and sugarcane. The bioethanol production is composed of three stages: cultivation, pretreatment, and bioethanol conversion. All of mass, material, fuel, and energy were calculated to determine the environmental impact of three types of bioethanol production: bioethanol production from cassava (CBP), bioethanol production from molasses (MBP), and bioethanol production from rice straw (RBP). The results showed that bioethanol production from cassava has the best environmental performance. CBP contributes less impact when compared to the other processes.

Keywords: bioethanol production, biofuel, LCA, chemical engineering

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Authors: Aneesh Babu, S. P. Anusha

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A dynamic signal control system combines traditional traffic lights with an array of sensors to intelligently control vehicle and pedestrian traffic. The present study focus on evaluating the performance of dynamic signal control systems for mixed traffic conditions. Data collected from four different approaches to a typical four-legged signalized intersection at Trivandrum city in the Kerala state of India is used for the study. Performance of three other dynamic signal control methods, namely (i) Non-sequential method (ii) Webster design for consecutive signal cycle using flow as input, and (iii) dynamic signal control using RFID delay as input, were evaluated. The evaluation of the dynamic signal control systems was carried out using a calibrated VISSIM microsimulation model. Python programming was used to integrate the dynamic signal control algorithm through the COM interface in VISSIM. The intersection delay obtained from different dynamic signal control methods was compared with the delay obtained from fixed signal control. Based on the study results, it was observed that the intersection delay was reduced significantly by using dynamic signal control methods. The dynamic signal control method using delay from RFID sensors resulted in a higher percentage reduction in delay and hence is a suitable choice for implementation under mixed traffic conditions. The developed dynamic signal control strategies can be implemented in ITS applications under mixed traffic conditions.

Keywords: dynamic signal control, intersection delay, mixed traffic conditions, RFID sensors

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Authors: Julia B. Kischkat, Charlie D. Waters

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This research aims to understand the factors that may affect the survival and productivity of Pacific salmonids through two components. The first component is lab-based and aims to improve high-performance liquid chromatography to better quantify vitamin deficiencies such as thiamine. The lab work is conducted at the National Oceanic and Atmospheric Administration (NOAA) Ted Stevens Marine Research Institute in Juneau, Alaska. Deficiencies in thiamine have been shown to reduce the survival of salmonids at early life stages. The second component involves the analysis of a 22-year data set of migration timing of juvenile Coho Salmon, Dolly Varden, Steelhead, and returning adult Steelhead at Little Port Walter, Alaska. The statistical analysis quantifies their migration fluctuations and whether they correlate to various environmental conditions such as temperature, salinity, and precipitation.

Keywords: climate change, smolt timing, phenology, migration timing, salmon, time series analysis, ecology, chemistry, fisheries science

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Authors: Seyed Mahdi Rafiaei

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In this investigation, red emitting Eu³⁺ doped YVO₄ nano-phosphors have been synthesized via the facile combustion method using isobutyl nitrite and urea fuels, individually. Field-emission scanning electron microscope (FE-SEM) images, high resolution transmission electron microscope (TEM) images and X-ray diffraction (XRD) spectra reveal that the mentioned fuels can be used successfully to synthesis YVO₄: Eu³⁺ nano-particles. Interestingly, the fuels have a large effect on the size and morphology of nano-phosphors as well as luminescence properties. Noteworthy the use of isobutyl nitrite provides an average particle size of 65 nm, while the employment of urea, results in the formation of larger particles and also provides higher photoluminescence emission intensity. The improved luminescence performance is attributed to the condition of chemical reaction via the combustion synthesis and the size of synthesized phosphors.

Keywords: phosphors, combustion, fuels, luminescence, nanostructure

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Authors: Kageeporn Wongpreedee, Bongkot Phichaikamjornwut, Duangkhae Bootkul

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The technique of stone in place casting had been established in jewelry production for two decades. However, the process were not widely used since it was limited to precious stones with high hardness and high stabililty at high temperature. This experiment were tested on tourmaline which is semi-precious gemstone having less hardness and less stability comparing to precious stones. The experiment were designed into two parts. The first part is to understand the phenomena of tourmaline under the heating conditions. Natural tourmaline stones were investigated and compared inclusions inside stones tested at temperature of 500 °C, 600 °C, and 700 °C. The second part is to cast the treated tourmaline with ion-implanation under the stones in place casting conditions. The results showed that stones were able to tolerate as much as at 700 °C showing the growths of inclusions inside the stones. The second part of this experiment were compared tourmaline with ion-implantation and natural tourmaline using on stones in place casting process at different stone setting types. The results showed that the cracks and inclustions of both treat and natural tourmaline with stones in place casting were propagate due to high stress of metal contractions. The stones with ion-implatation were more likely tolerate to cracks and inclusion propagations inside the stones.

Keywords: stone in place casting, tourmaline, ion implantation, metal contraction

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Authors: Adeniran K. Ademuwagun, Alastair Allen

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The relationship dependence between RSS and distance in an enclosed environment is an important consideration because it is a factor that can influence the reliability of any localization algorithm founded on RSS. Several algorithms effectively reduce the variance of RSS to improve localization or accuracy performance. Our proposed algorithm essentially avoids this pitfall and consequently, its high adaptability in the face of erratic radio signal. Using 3 anchors in close proximity of each other, we are able to establish that RSS can be used as reliable indicator for localization with an acceptable degree of accuracy. Inherent in this concept, is the ability for each prospective anchor to validate (guarantee) the position or the proximity of the other 2 anchors involved in the localization and vice versa. This procedure ensures that the uncertainties of radio signals due to multipath effects in enclosed environments are minimized. A major driver of this idea is the implicit topological relationship among sensors due to raw radio signal strength. The algorithm is an area based algorithm; however, it does not trade accuracy for precision (i.e the size of the returned area).

Keywords: anchor nodes, centroid algorithm, communication graph, radio signal strength

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Authors: Anmar Dulaimi, Hassan Al Nageim, Felicite Ruddock, Linda Seton

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Fast-curing cold bituminous emulsion mixture (CBEM) including active filler from high calcium fly ash (HCFA) and waste material (LJMU-A2) has been developed in this study. This will overcome the difficulties related with the use of hot mix asphalt such as greenhouse gases emissions and problems in keeping the temperature when transporting long distance. The aim of this study is to employ petrographic examinations using scanning electron microscopy (SEM) for characterizing the hydrates microstructure, in a new binary blended cement filler (BBCF) system. The new BBCF has been used as a replacement to traditional mineral filler in cold bituminous emulsion mixtures (CBEMs), comprises supplementary cementitious materials containing high calcium fly ash (HCFA) and a waste material (LJMU-A2). SEM analysis demonstrated the formation of hydrates after varying curing ages within the BBCF. The accelerated activation of HCFA by LJMU-A2 within the BBCF was revealed and as a consequence early and later stiffness was developed in novel CBEM.

Keywords: cold bituminous emulsion mixtures, indirect tensile stiffness modulus, scanning electron microscopy (SEM), and high calcium fly ash

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Authors: Seyed-Ali Sadegh-Zadeh, Mahboobe Bahrami, Sahar Ahmadi, Seyed-Yaser Mousavi, Hamed Atashbar, Amir M. Hajiyavand

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This paper presents an investigation into the concept of neural reshaping, which is crucial for achieving strong artificial intelligence through the development of AI algorithms with very high plasticity. By examining the plasticity of both human and artificial neural networks, the study uncovers groundbreaking insights into how these systems adapt to new experiences and situations, ultimately highlighting the potential for creating advanced AI systems that closely mimic human intelligence. The uniqueness of this paper lies in its comprehensive analysis of the neural reshaping process in both human and artificial intelligence systems. This comparative approach enables a deeper understanding of the fundamental principles of neural plasticity, thus shedding light on the limitations and untapped potential of both human and AI learning capabilities. By emphasizing the importance of neural reshaping in the quest for strong AI, the study underscores the need for developing AI algorithms with exceptional adaptability and plasticity. The paper's findings have significant implications for the future of AI research and development. By identifying the core principles of neural reshaping, this research can guide the design of next-generation AI technologies that can enhance human and artificial intelligence alike. These advancements will be instrumental in creating a new era of AI systems with unparalleled capabilities, paving the way for improved decision-making, problem-solving, and overall cognitive performance. In conclusion, this paper makes a substantial contribution by investigating the concept of neural reshaping and its importance for achieving strong AI. Through its in-depth exploration of neural plasticity in both human and artificial neural networks, the study unveils vital insights that can inform the development of innovative AI technologies with high adaptability and potential for enhancing human and AI capabilities alike.

Keywords: neural plasticity, brain adaptation, artificial intelligence, learning, cognitive reshaping

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Authors: Deepak K. Gupta, T. R. Ravindran

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Holographic Optical Tweezers (HOTs) in general use iterative algorithms such as weighted Gerchberg-Saxton (WGS) to generate multiple traps, which produce traps with 99% uniformity theoretically. But in experiments, it is the phase response of the spatial light modulator (SLM) which ultimately determines the efficiency, uniformity, and quality of the trap spots. In general, SLMs show a nonlinear phase response behavior, and they may even have asymmetric phase modulation depth before and after π. This affects the resolution with which the gray levels are addressed before and after π, leading to a degraded trap performance. We present a method to optimize the SLM for a linear phase response behavior along with a symmetric phase modulation depth around π. Further, we optimize the SLM for its varying phase response over different spatial regions by optimizing the brightness/contrast and gamma of the hologram in different subsections. We show the effect of the optimization on an array of trap spots resulting in improved efficiency and uniformity. We also calculate the spot sharpness metric and trap performance metric and show a tightly focused spot with reduced aberration. The trap performance is compared by calculating the trap stiffness of a trapped particle in a given trap spot before and after aberration correction. The trap stiffness is found to improve by 200% after the optimization.

Keywords: spatial light modulator, optical trapping, aberration, phase modulation

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Authors: Mohammad Erfan Doraki, Mohammad Salehi

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In this study, to evaluate the performance of Baseboard and Panel radiators with thermal comfort coefficient, A room with specific dimensions was modeled with Ansys fluent and DesignBuilder, then calculated the speed and temperature parameters in different parts of the room in two modes of using Panel and Baseboard radiators and it turned out that use of Baseboard radiators has a more uniform temperature and speed distribution, but in a Panel radiator, the room is warmer. Then, by calculating the thermal comfort indices, It was shown that using a Panel radiator is a more favorable environment and using a Baseboard radiator is a more uniform environment in terms of thermal comfort.

Keywords: Radiator, Baseboard, optimal, comfort coefficient, heat

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Authors: Kaoutar Zellat, Tahar Kadri

Abstract:

The purpose of new aseismic techniques is to provide an additional means of energy dissipation, thereby reducing the transmitted acceleration into the superstructure. In order to demonstrate the effectiveness of aseismic bearings technique and understand the behavior of seismically isolated bridges by such devices a three-span continuous deck bridge made of reinforced concrete is considered. The bridge is modeled as a discrete model and the relative displacements of the isolation bearing are crucial from the design point of view of isolation system and separation joints at the abutment level. The systems presented here are passive control systems and the results of some important experimental tests are also included. The results show that the base shear in the piers is significantly reduced for the isolated system as compared to the non isolated system in the both directions of the bridge. This indicates that the use of aseismic systems is effective in reducing the earthquake response of the bridge.

Keywords: aseismic bearings, bridge isolation, bridge, seismic response

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Authors: Fadime Eryılmaz Pehlivan

Abstract:

Anthocyanins are important plant pigments having roles in many physiological and ecological functions; that are controlled by numerous regulatory factors. The accumulation of anthocyanins in Z. mays cause the plants stems to exhibit red coloration when encountering gradually increasing copper treatments (1, 5, and 10 mM of Cu in a period of 5 days) on maize seedlings. Stress injury was measured in terms of chlorophyll (a and b), carotenoid and anthocyanin contents, malondialdehyde (MDA), hydrogen peroxide (H2O2). Carotenoid and anthocyanin contents dramatically increased by increasing concentrations of Cu stress. MDA and H2O2 levels were found to significantly increase at high Cu treatments (5 and 10 mM of Cu). Chlorophyll content was observed to be highest at 1 mM Cu and then decreased at 5 and 10 mM of Cu. In addition, significant increases were determined in the activities of catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR) and ascorbate peroxidase (APX) under high Cu concentrations, while glutathione S-transferase (GST) and peroxidase (POX) activities showed no change. Treatments above 5 and 10 mM of Cu triggered copper stress in maize seedlings. The results of this study provide evidence that maize seedlings represent a high tolerance to gradually increasing copper treatments. Improved copper tolerance may relate to high anthocyanin, and carotenoid content besides antioxidant enzyme activity may improve the metal chelating ability of anthocyanin pigments. Data presented in this study may also contribute to a better understanding of phytoremediation studies in maize exposed to high copper contenting soils.

Keywords: anthocyanin, copper, maize , antioxidant

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Authors: Widya Anggraini Pamungkas, Rosana Budi Setyawati, Awaludin Fitroh Rifai, Candra Pangesti Setiawan, Anatta Wahyu Budiiman, Inayati, Joko Waluyo, Sunu Herwi Pranolo

Abstract:

The increase in LPG consumption in Indonesia is not balanced with the amount of supply. The high demand for LPG due to the success of the government's kerosene-to-LPG conversion program and the Covid-19 pandemic in 2020 led to an increase in LPG consumption in the household sector and caused Indonesia's trade balance to experience a deficit. The high consumption of LPG encourages the need for alternative fuels as a substitute or which aims to substitute LPG; one of the materials that can be used is Dimethyl Ether (DME). Dimethyl ether (DME) is an organic compound with the chemical formula CH 3. OCH 3 has a high cetane number and has characteristics similar to LPG. DME can be produced from various sources, such as coal, biomass and natural gas. Based on the economic analysis conducted at 10% IRR, coal has the largest NPV of Rp. 20,034,837,497,241 with a payback period of 3.86 years, then biomass with an NPV of Rp. 10,401,526,072,850 and a payback period of 5.16. the latter is natural gas with an NPV of IDR 7,401,272,559,191 and a payback period of 6.17 years. Of the three sources of raw materials used, if the sensitivity is calculated using the selling price of DME equal to the selling price of LPG, it will get an NPV value that is greater than the NPV value when using the current DME price. The advantages of coal as a raw material for DME are not only because it is profitable, namely: low price and abundant resources, but has high greenhouse gas emissions.

Keywords: LPG, DME, coal, biomass, natural gas

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Authors: Muhammad Tahir Hassan, Stas Burek, Muhammad Asif, Mohamed Emad

Abstract:

Industrial sector in Pakistan accounts for 25% of total energy consumption in the country. The performance of this sector has been severely affected due to the adverse effect of current energy crises in the country. Energy conservation potentials of Pakistan’s industrial sectors through energy management can save wasted energy which would ultimately leads to economic and environmental benefits. However due to lack of financial incentives of energy efficiency and absence of energy benchmarking within same industrial sectors are some of the main challenges in the implementation of energy management. In Pakistan, this area has not been adequately explored, and there is a lack of focus on the need for industrial energy efficiency and proper management. The main objective of this research is to evaluate the current energy management performance of Pakistani industrial sector and empirical investigation of the existence of various barriers to industrial energy efficiency. Data was collected from the respondents of 192 small and medium-sized enterprises (SME’s) of Pakistan i.e. foundries, textile, plastic industries, light engineering, auto and spare parts and ceramic manufacturers and analysed using Statistical Package for the Social Sciences (SPSS) software. Current energy management performance of manufacturing SME’s in Pakistan has been evaluated by employing two significant indicators, ‘Energy Management Matrix’ and ‘pay-off criteria’, with modified approach. Using the energy management matrix, energy management profiles of overall industry and the individual sectors have been drawn to assess the energy management performance and identify the weak and strong areas as well. Results reveal that, energy management practices in overall surveyed industries are at very low level. Energy management profiles drawn against each sector suggest that performance of textile sector is better among all the surveyed manufacturing SME’s. The empirical barriers to industrial energy efficiency have also been ranked according to the overall responses. The results further reveal that there is a significant relationship exists among the industrial size, sector type and nature of barriers to industrial energy efficiency for the manufacturing SME’s in Pakistan. The findings of this study may help the industries and policy makers in Pakistan to formulate a sustainable energy policy to support industrial energy efficiency keeping in view the actual existing energy efficiency scenario in the industrial sector.

Keywords: barriers, energy conservation, energy management profile, environment, manufacturing SME's of Pakistan

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