Search results for: multi-criteria selection

Authors: Zunnu Raen Akhtar, U. Irshad, M. Majid

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Due to the widespread cultivation of transgenic cotton, intense selection pressure resulted in resistant allele in pink bollworm, Pectinophora gossypiella (Gelechiidae: Lepidoptera). A resistant strain of pink bollworm against transgenic cotton has become a challenge to Integrated Resistance Management (IRM) in the World. Laboratory and field studies were conducted to determine the resistant strains of pink bollworm by performing bioassay, extracting the DNA, conducting PCR of both laboratory as well as field collected pink bollworms to observe the developed resistance. In all of the studies, two Bt varieties FH-142 and FH-118 expressing Cry1Ac compared to non-Bt (Control) were tested against pink bollworm. In the laboratory, bioassay results showed that there was no significant mortality difference between Bt and non-Bt varieties. Similar mortality percentage was observed in transgenic and non-transgenic (control) variety. Insects which were survived after bioassay, as well as those collected from the Bt cotton fields, were selected for further molecular studies. DNA extraction followed by PCR was conducted to check the resistant strains in pink bollworm. In field studies, we also observed the population dynamics of pink boll worms on Bt as compared to non-Bt varieties. Laboratory and field studies confirmed that resistant strains occurs in Pakistani Bt cotton fields. Different strategies should be adopted to combat that serious prevailing resistance issues.

Keywords: transgenic cotton, resistance, pectinophora gossypiella, , integrated resistance management (IRM), polymerase chain reaction (PCR)

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Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

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Authors: Kate Benedicta Amenador, Dianjian Wang, Bright Nkrumah

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This extensive bibliometric study explores the dynamic influence of artificial intelligence in the field of English as a Foreign Language (EFL) between 2012 and 2024. The study, which examined 4,500 articles from Google Scholar, Modern Language Association Linguistics Abstracts, Web of Science, Scopus, Researchgate, and library genesis databases, indicates that AI integration in EFL is on the rise. This notable increase is ascribed to a variety of transformative events, including increased academic funding for higher education and the COVID-19 epidemic. The results of the study identify leading contributors, prominent authors, publishers and sources, with the United States, China and the United Kingdom emerging as key contributors. The co-occurrence analysis of key terms reveals five clusters highlighting patterns in AI-enhanced language instruction and learning, including evaluation strategies, educational technology, learning motivation, EFL teaching aspects, and learner feedback. The study also discusses the impact of various AIs in enhancing EFL writing skills with software such as Grammarly, Quilbot, and Chatgpt. The current study recognizes limitations in database selection and linguistic constraints. Nevertheless, the results provide useful insights for educators, researchers and policymakers, inspiring and guiding a cross-disciplinary collaboration and creative pedagogical techniques and approaches to teaching and learning in the future.

Keywords: artificial intelligence, bibliometrics study, VOSviewer visualization, English as a foreign language

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Authors: D. Karibasavaraja, Ramesh M.R., Sufiyan Ahmed, Noyonika M.R., Sameeksha A. V., Mamatha J., Samiksha S. Urs

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This research paper gives an overview of the experimental analysis of natural fibers with polymer composite. The whole world is concerned about conserving the environment. Henceforth, the demand for natural and decomposable materials is increasing. The application of natural fibers is widely used in aerospace for manufacturing aircraft bodies, and ship construction in navy fields. Based on the literature review, researchers and scientists are replacing synthetic fibers with natural fibers. The selection of these fibers mainly depends on lightweight, easily available, and economical and has its own physical and chemical properties and many other properties that make them a fine quality fiber. The pineapple fiber has desirable properties of good mechanical strength, high cellulose content, and fiber length. Hybrid composite was prepared using different proportions of pineapple fiber and banana fiber, and their ratios were varied in 90% polypropylene mixed with 5% banana fiber and 5% pineapple fiber, 85% polypropylene mixed with 7.5% banana fiber and 7.5% pineapple fiber and 80% polypropylene mixed with 10% banana fiber and 10% pineapple fiber. By impact experimental analysis, we concluded that the combination of 90% polypropylene and 5% banana fiber and 5% pineapple fiber exhibits a higher toughness value with mechanical strength. We also conducted scanning electron microscopy (SEM) analysis which showed better fiber orientation bonding between the banana and pineapple fibers with polypropylene composites. The main aim of the present research is to evaluate the properties of pineapple fiber and banana fiber reinforced with hybrid polypropylene composites.

Keywords: toughness, fracture, impact strength, banana fibers, pineapple fibers, tensile strength, SEM analysis

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Authors: Anjela Koblischka-Veneva, Michael Koblischka

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In this contribution, the transmission-Kikuchi diffrac-tion (TKD, or sometimes called t-EBSD) is applied to bulk, melt-grown YBa2Cu3O7 (YBCO) superconductors prepared by the MTMG (melt-textured melt-grown) technique and the infiltration (IG) growth technique. TEM slices required for the analysis were prepared by means of focused ion-beam (FIB) milling using mechanically polished sample surfaces, which enable a proper selection of the in-teresting regions for investigations. The required optical transparency was reached by an additional polishing step of the resulting surfaces using FIB-Ga-ion and Ar-ion milling. The improved spatial resolution of TKD enabled the investigation of the tiny Y2BaCuO5 (Y-211) particles having a diameter of about 50-100 nm embedded within the YBCO matrix and of other added secondary phase particles. With the TKD technique, the microstructural properties of the YBCO matrix are studied in detail. It is observed that the matrix shows effects of stress/strain, depending on the size and distribution of the embedded particles, which are important for providing additional flux pinning centers in such superconducting bulk samples. Using the Kernel average misorientation (KAM) maps, the strain induced in the superconducting matrix around the particles, which increases the flux pinning effectivity, can be clearly revealed. This type of analysis of the EBSD/TKD data is, therefore, also important for other material systems, where nanoparticles are embedded in a matrix.

Keywords: electron backscatter Diffraction, transmission Kikuchi diffraction, SEM, YBCO, microstructure, nanoparticles

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Authors: Ravindra Raju, Vidhu Kampurath

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For smooth transition of the power from the engine to the transmission system, a clutch is used. In agricultural tractors, friction clutches are widely used in power transmission applications. To transmit the maximum torque in friction clutches, selection of materials is one of the important tasks. The present used material for friction disc is Asbestos, Ceramic etc. In this study, analysis is performed using composites materials. The composite materials are considered due to their high strength to weight ratio. Composite materials like kevlar49, kevlar 29U were used in the study. The paper presents a systematic approach to optimize the structural and thermal characteristics of the clutch friction pad. A single plate clutch is modeled using Creo 2.0 software and analyzed using ANSYS. Thermal analysis considers the reduction of heat generated between the friction surfaces and reducing the temperature rise during the steady state period. Structural analysis is done to minimize the stresses developed as a result of the loading contact between friction surfaces. Also, modal analysis is done to optimize the natural frequency of the friction plate to avoid being in resonance with the engine frequency range. The analysis carried out on ANSYS workbench to get the foremost appropriate friction material for clutch. From the analyzed results stress, strain / total deformation values and natural frequency of the materials were compared for all the composite materials and the best one was taken out. For the study purpose, specifications of the clutch are obtained from the MF1035 (47KW) Tractor model.

Keywords: ANSYS, clutch, composite materials, creo

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Authors: Dwi Retno Sri Ambarwati

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Recently, the traditional architecture were getting lost, replaced by modern architecture. The existence of many traditional houses often changing the function and change the values in an effort to adjust to the modern lifestyle, whereas the spiritual background of traditional architectural design is very specific and be the basis for consideration in the construction of the building, both in terms of determining the location of the building, the direction toward building, the spatial pattern and organization of space, zoning, hierarchical space, building form, ornamentation, the selection of building materials, and so on. The changes in function and form will transformed the spiritual values contained in it, because the architecture affects human behavior and reflects the culture. The traditional architecture views the architecture as a concept that has different tendencies in terms of orientation, shape, and attitude toward nature that tends to harmony with the social environment and local culture. The concept of the spirit of place made the architecture looks familiar, not arrogant and give a positive value to the surrounding environment. Every culture has a traditional architecture that full of spiritual values, although in the simplest form. Humans can learn about human values and local wisdom through the positive values that contained in traditional architecture, the desire to balance themselves with nature and the environment, not overbearing, strict adherence to the prevailing norms, openness in public life and intimacy family life that form a harmonious in life. The great and the wise value of traditional architecture should be revived in modern architecture that tends to ignore the spiritual values and more concerned with the functional and aesthetic pleasure, by combining the noble values of traditional architecture into modern architecture.

Keywords: architecture, combining noble values, local wisdom, traditional architecture

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Authors: Niloofar Fariborzi, Hamzeh Alipour, Kourosh Azizi, Neda Eskandarzade, Abozar Ghorbani

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The family Parvoviridae consists of a large diversity of single-stranded DNA viruses, which cause mild to severe diseases in both vertebrates and invertebrates. The Parvoviridae are classified into three subfamilies: Parvovirinae infect vertebrates, Densovirinae infects invertebrates, while Hamaparovirinae infects both vertebrates and invertebrates. Except for the NS1 region, which is the prime criterion for phylogeny analysis, other parts of the parvoviruses genome, such as UTRs, are diverse even among closely related viruses or within the same genus. It is believed that host switching in parvoviruses may be related to genetic changes in regions other than NS1; therefore, whole-genome screening is valuable for studying parvoviruses' host-virus interactions. The aim of this study was to analyze genome organization and phylogeny of the complete genome sequence of the 132 Paroviridae family members, focusing on viruses that infect invertebrates. The maximum and minimum divergence within each subfamily belonged to Densovirinae and Parvovirinae, respectively. The greatest evolutionary divergence was between Hamaparovirinae and Parvovirinae. Unclassified viruses were mostly from Parovirinae and had the highest divergence to densoviruses and the lowest divergence to Parovirinae viruses. In a phylogenetic tree, all hamparoviruses were found in the center of densoviruses, with the exception of Syngnathid Ichthamaparvovirus 1 (NC_055527), which was positioned between two Parvovirinae members (NC _022089 and NC_038544). The proximity of hamparoviruses members to some densoviruses strengthens the possibility that densoviruses may be the ancestors of hamaparoviruses or vice versa. Therefore, examination and phylogeny analysis of the whole genome is necessary to understand Parvoviridae family host selection.

Keywords: densoviruses, parvoviridae, bioinformatics, phylogeny

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Authors: Zekun Lin, Xun Li

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Silicon photonics has gained much interest and extensive research for a promising aspect for fabricating compact, high-speed and low-cost photonic devices compatible with complementary metal-oxide-semiconductor (CMOS) process. Despite the remarkable progress made on the development of silicon photonics, high-performance, cost-effective, and reliable silicon laser sources are still missing. In this work, we present a 1550 nm III-V/silicon laser design with stable single-mode lasing property and robust and high-efficiency vertical coupling. The InP cavity consists of two uniform Bragg grating sections at sides for mode selection and feedback, as well as a central second-order grating for surface emission. A grating coupler is etched on the SOI waveguide by which the light coupling between the parallel III-V and SOI is reached vertically rather than by evanescent wave coupling. Laser characteristic is simulated and optimized by the traveling-wave model (TWM) and a Green’s function analysis as well as a 2D finite difference time domain (FDTD) method for the coupling process. The simulation results show that single-mode lasing with SMSR better than 48dB is achievable, and the threshold current is less than 15mA with a slope efficiency of around 0.13W/A. The coupling efficiency is larger than 42% and possesses a high tolerance with less than 10% reduction for 10 um horizontal or 15 um vertical dislocation. The design can be realized by standard flip-chip bonding techniques without co-fabrication of III-V and silicon or precise alignment.

Keywords: III-V/silicon integration, silicon photonics, single mode laser, vertical coupling

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Authors: Xinyuan Zou, Qihui Tang, Shujian Wang, Yulin Huang, Jie Gui, Xiangping Liu, Gang Liu, Yanqiang Tao

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Childhood trauma can have a long-lasting influence on individuals and contribute to mental disorders, including depression and anxiety. The current study aimed to explore the symptomatic and developmental patterns of depression, anxiety, and stress among adolescents who have suffered from childhood trauma. A total of 3,598 college students (female = 1,617 (44.94%), Mean Age = 19.68, SD Age = 1.35) in China completed the Childhood Trauma Questionnaire (CTQ) and the Depression, Anxiety, and Stress Scales (DASS-21), and 2,337 participants met the selection standard based on the cut-off scores of the CTQ. The symptomatic network and directed acyclic graph (DAG) network approaches were used. The results revealed that males reported experiencing significantly more physical abuse, physical neglect, emotional neglect, and sexual abuse compared to females. However, females scored significantly higher than males on all items of DASS-21, except for “Worthless”. No significant difference between the two genders was observed in the network structure and global strength. Meanwhile, among all participants, “Down-hearted” and “Agitated” appeared to be the most interconnected symptoms, the bridge symptoms in the symptom network, as well as the most vital symptoms in the DAG network. Apart from that, “No-relax” also served as the most prominent symptom in the DAG network. The results suggested that intervention targeted at assisting adolescents in developing more adaptive coping strategies with stress and regulating emotion could benefit the alleviation of comorbid depression, anxiety, and stress.

Keywords: symptom network, childhood trauma, depression, anxiety, stress

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Authors: Trevor R. Higgins

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The aim of this study was to compare muscle activation of the latissimus dorsi between pin-loaded machine (Lat Pull Down), resistance band (Lat Pull Down) and body-weight (Chin Up) exercises. A convenient sample of male college students with >2 years resistance training experience volunteered for the study. A paired t-test with repeated measures designs was carried out on results from EMG analysis. EMG analysis was conducted with Trigno wireless sensors (Delsys) placed laterally on the latissimus dorsi (left and right) of each participant. By conventional criteria the two-tailed P value suggested that differences between pin-loaded and body-weight was not significantly different (p = 0.93) and differences between pin-loaded and resistance band was not significantly different (p = 0.17) in muscle activity. In relation to conventional criteria the two-tailed P value suggested differences between body-weight and resistance band was not quite significantly different (p = 0.06) in muscle activity. However, effect size trends indicated that both body-weight and pin-loaded exercises where more effective in stimulating muscle electrical activity than a resistance band with male college athletes with >2 years resistance training experience. Although, resistance bands have increased in popularity in health and fitness centres, that for well-trained participants, they may not be effective in stimulating muscles of the latissimus dorsi. Therefore, when considering equipment and exercise selection for experienced resistance training participants pin-loaded machines and body-weight should be prescribed.

Keywords: pin-loaded, resistance bands, body weight, EMG analysis

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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: Rania E. Ramadan

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Dental esthetics is subjective, can be reported by the dentist and not noticed by the patient. However, if there is any imperfection seen by both the dentist and the patient, it is considered as an unesthetic like white and/or brown spot lesions. Many patients nowadays have been concerned about dental esthetics. Esthetic rehabilitation of anterior teeth and even maxillary premolars aid a lot in patients’ satisfaction of their smile consequently, gaining positive psychological impact for the patients. Many cases need esthetic rehabilitation such as diastema closure, spaced teeth and masking discolored teeth. Dental fluorosis and enamel hypo calcification can be presented as white and/or brown spot lesions. There are many treatment options for the management of these spotted teeth. Treatment options range from bleaching, microabrasion, direct composite restorations, porcelain veneers, and complete coverage crowns. The selection of certain options depends on many factors: the patient’s age, socioeconomic status and the severity of the lesion. In this clinical report, a 22-year-old male patient has been presented to the Department of Prosthodontics in Alexandria University, Egypt. His chief complaint was, “I was unpleased by white and brown spots in my teeth and I want to close the space between the two maxillary central.” Upon medical history, clinical examination, diagnostic photographs, and digital smile design by Exocad software, lithium disilicate veneers were chosen as the treatment of choice in maxillary anterior and first premolars.

Keywords: flourosis, ceramic veneers, case report, diastema closure

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Authors: A. Khodabakhshi, A. Mortazavi

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Accurate determination of rock mass deformation modulus, as an important design parameter, is one of the most controversial issues in most engineering projects. A 3D numerical model of standard plate load test (PLT) using the FLAC3D code was carried to investigate the mechanism governing the test process. Five objectives were the focus of this study. The first goal was to employ 3D modeling in the interpretation of PLT conducted at the Bazoft dam site, Iran. The second objective was to investigate the effect of displacements measuring depth from the loading plates on the calculated moduli. The magnitude of rock mass deformation modulus calculated from PLT depends on anchor depth, and in practice, this may be a cause of error in the selection of realistic deformation modulus for the rock mass. The third goal of the study was to investigate the effect of testing plate diameter on the calculated modulus. Moreover, a comparison of the calculated modulus from ISRM formula, numerical modeling and calculated modulus from the actual PLT carried out at right abutment of the Bazoft dam site was another objective of the study. Finally, the effect of plastic strains on the calculated moduli in each of the loading-unloading cycles for three loading plates was investigated. The geometry, material properties, and boundary conditions on the constructed 3D model were selected based on the in-situ conditions of PLT at Bazoft dam site. A good agreement was achieved between numerical model results and the field tests results.

Keywords: deformation modulus, numerical model, plate loading test, rock mass

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Authors: Anamitra Ghosh, Neeladri Paul

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The present work aims at investigating material combinations and thereby improvising an optimized design of liner-mother plate arrangement and that of the stone box, such that it has low cost, high weldability, sufficiently capable of withstanding the increased amount of corrosive shear and bending loads, and having reduced thermal expansion coefficient at temperatures close to 1000 degrees Celsius. All the above factors have been preliminarily examined using a computational approach via ANSYS Thermo-Structural Computation, a commercial software that uses the Finite Element Method to analyze the response of simulated design specimens of liner-mother plate arrangement and the stone box, to varied bending, shear, and thermal loads as well as to determine the temperature gradients developed across various surfaces of the designs. Finally, the optimized structural designs of the liner-mother plate arrangement and that of the stone box with improved material and better structural and thermal properties are selected via trial-and-error method. The final improvised design is therefore considered to enhance the overall life and reliability of a Direct Charge Transfer Chute that transfers and segregates the hot sinter onto the cooler in a sinter plant.

Keywords: shear, bending, thermal, sinter, simulated, optimized, charge, transfer, chute, expansion, computational, corrosive, stone box, liner, mother plate, arrangement, material

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Authors: J. C. Cabanillas-Noris, M. I. Martínez-Hernández, I. León-Monzón

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The selection of diffractive events in the ALICE experiment during the first data taking period (RUN-I) of the Large Hadron Collider (LHC) was limited by the range over which rapidity gaps occur. It would be possible to achieve better measurements by expanding the range in which the production of particles can be detected. For this purpose, the ALICE Diffractive (AD0) detector has been installed and commissioned for the second phase (RUN-II). Any new detector should be able to take the data synchronously with all other detectors and be operated through the ALICE central systems. One of the key elements that must be developed for the AD0 detector is the Detector Control System (DCS). The DCS must be designed to operate safely and correctly this detector. Furthermore, the DCS must also provide optimum operating conditions for the acquisition and storage of physics data and ensure these are of the highest quality. The operation of AD0 implies the configuration of about 200 parameters, from electronics settings and power supply levels to the archiving of operating conditions data and the generation of safety alerts. It also includes the automation of procedures to get the AD0 detector ready for taking data in the appropriate conditions for the different run types in ALICE. The performance of AD0 detector depends on a certain number of parameters such as the nominal voltages for each photomultiplier tube (PMT), their threshold levels to accept or reject the incoming pulses, the definition of triggers, etc. All these parameters define the efficiency of AD0 and they have to be monitored and controlled through AD0 DCS. Finally, AD0 DCS provides the operator with multiple interfaces to execute these tasks. They are realized as operating panels and scripts running in the background. These features are implemented on a SCADA software platform as a distributed control system which integrates to the global control system of the ALICE experiment.

Keywords: AD0, ALICE, DCS, LHC

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Authors: Mohammad Tipu Sultan, Farzana Sharmin, Ke Xue

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Social media create a better opportunity for travelers to search for travel information, select destination and share their personal experiences of the travel. This study proposes a framework which describes the relationships between social media, and positive or negative tourism experience sharing impact on destination choice. To find out new trends of travelers behavioral intention, we propose an extended theoretical model, the Theory of Reasoned Action (TRA). We conducted a survey to analyze three external factors, subjective norms, and positive and negative experience influence on travel destination choice. Structural questionnaire analysis was employed to confirm the proposed research hypothesis within the relationship between consumer influences on the shared experience of social media. The results of the study confirm that sharing positive experiences influence the positive effect of destination choice, while negative experiences decrease the destination selection option. The results indicate that attitudes, subjective norms are passively influenced by shared experience. Moreover, we find that sharing live pictures of travel experiences through social media helps to reduce negative perceptions of the destination brand. This research contribution is useable to the research field as a new determination factor and the findings could be used by destination organization management (DMO) to enhancing their tourism promotion through social media.

Keywords: destination choice, tourism experience sharing, Theory of Reasoned Action, TRA, social media

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Umego Chukwudi T., Ntui Valentine O., Uyoh Edak A.

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Phosphorus (P) deficiency has been identified as a major hindrance to rice production the world over. Eleven (11) rice genotypes predominantly used by local farmers in Nigeria were studied for their responses to P deficient conditions. The characterization was based on morpho-physiologic parameters. The genotypes were screened using a hydroponic system in a modified Hoagland’s solution. Morphological and physiologic parameters, including Plant height (PH), number of tillers per plant, shoot dry weight (SDW), shoot phosphate concentration (SPC), and chlorophyll content, were recorded after exposure to three levels of phosphate concentration (0µM, 400 µM, and 800 µM). The data obtained were subjected to analysis of variance (ANOVA), and the means were separated using least significance difference tests. The results obtained showed that P starvation caused a significant (p≤0.05) reduction in PH, SDW, and tillering and also triggered a significant (p≤0.05) increase in root length among the genotypes. The Pearsons correlation coefficient was used to estimate the relationships among studied parameters, and a significant negative correlation was observed between plant height and root length. FARO63 was identified as a highly tolerant genotype to P deficiency with a low (0.24) SPC and higher (4.81) phosphate utilization efficiency (PUE). This study has identified FARO63 as a true tolerant genotype to Phosphate deficiency, which will be useful in breeding for phosphate deficiency tolerance in rice and thus combating food insecurity.

Keywords: phosphate deficiency, rice genotypes, hydroponic system, food security

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Michael Zimba

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A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency sub-band of the DWT of the suspicious image thereby leaving valuable information in the other three sub-bands, the proposed algorithm simultaneously extracts features from all the four sub-bands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates.

Keywords: affine transformation, discrete wavelet transform, radix sort, SATS

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Authors: Merzak Siham, Benguerine Zohra, Si Tayeb Fatima, Bouzian Chaimaa Affaf, Jou Siham, Belkessam Nafissa

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Introduction: Medicinal plants, particularly spices, are essential for pharmacological research due to their health benefits. This study focuses on Curcuma longa, a spice recognized for its therapeutic properties. Materials and Methods: This study is based on a thorough search conducted on Google Scholar, PubMed, and ScienceDirect. From an initial selection of 25 articles, five were chosen to extract relevant information on Curcuma longa. Results and Discussions: Clinical studies have indicated that curcumin is well tolerated at doses up to 12 g/day. Its anti-rheumatic efficacy was compared to phenylbutazone in 18 individuals. Each participant received a daily dose of either 1200 mg of curcumin or 300 mg of phenylbutazone for 2 weeks. Curcumin was well tolerated at this dose and demonstrated activity comparable to phenylbutazone. Additionally, a study on 62 patients showed that curcumin sustainably relieved symptoms without toxicity. Its effects included reduced itching, lesions, and pain. In ten volunteers, administering 500 mg of curcumin for seven days resulted in a 33% decrease in lipid peroxidation, a 29% increase in HDL cholesterol, and a 12% decrease in total cholesterol. It is important to note that curcumin is a potent, selective inhibitor of phosphorylase kinase, an increased marker in psoriasis. Conclusion: Curcumin is promising as a future drug for various diseases, but its bioavailability must be improved through techniques such as nano encapsulation. Additionally, exploring chemical derivatives of curcumin could lead to more potent and targeted molecules.

Keywords: turmeric, spice, medicinal plants, pharmacological activities.

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Authors: Sadia Suri Kashif, Raheeda Fatima, Maqsood Ahmed Khan

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Purpose of the study: The objective of this research was to determine the perception of Pakistani physicians (whether primary care, specialists or residents) in Karachi, being one of the largest and highly populated cities of Pakistan, regarding clinical approaches towards diet, exercise, and therapy in obese patients. This research determines their understanding of obesity and employability of obesity management in their daily practices. Research methodology: This is a questionnaire-based survey. A minimum of 300 questionnaires (N=300) were distributed and filled by practicing physicians in a random selection of medical setups in Karachi. Randomly 246 physicians responded to the survey. The survey tested their views regarding weight management, importance of general awareness and their strategies to control weight. Results: In the first part of survey the physicians responded to almost 66% regarding the seriousness of obesity management with advising diet modification, physical exercise and decreasing calorie intake; 57% failed to employ Body Mass Index and Waist Hip Ratio as weight measurement tools in their daily practice; 50% disagreed on using pharmacotherapy as an option; 67% were not sure about the proper dosage and indication of anti-obesity medication while almost same disagreed on using surgical options for management of obesity; 83.3% physicians agreed on the increased obesity pandemic in Pakistan. Conclusion: The findings indicate that there is a gap between awareness and knowledge among Pakistani practicing physicians regarding pharmacotherapy for obesity. There is a need to frequently update latest guidelines to help manage this condition, which is becoming more prevalent in our country day by day. Physicians should be obligated to use updated knowledge for managing obesity.

Keywords: obesity, physicians, BMI, weight management, obesity awareness

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Authors: Chao Xu

Abstract:

Selecting ground motion intensity measures reasonably is one of the very important issues to affect the input ground motions selecting and the reliability of vulnerability analysis results. In this paper, inelastic spectral displacement is used as an alternative intensity measure to characterize the ground motion damage potential. The inelastic spectral displacement is calculated based modal pushover analysis and inelastic spectral displacement based incremental dynamic analysis is developed. Probability seismic demand analysis of a six story and an eleven story RC frame are carried out through cloud analysis and advanced incremental dynamic analysis. The sufficiency and efficiency of inelastic spectral displacement are investigated by means of regression and residual analysis, and compared with elastic spectral displacement. Vulnerability curves are developed based on inelastic spectral displacement. The study shows that inelastic spectral displacement reflects the impact of different frequency components with periods larger than fundamental period on inelastic structural response. The damage potential of ground motion on structures with fundamental period prolonging caused by structural soften can be caught by inelastic spectral displacement. To be compared with elastic spectral displacement, inelastic spectral displacement is a more sufficient and efficient intensity measure, which reduces the uncertainty of vulnerability analysis and the impact of input ground motion selection on vulnerability analysis result.

Keywords: vulnerability, probability seismic demand analysis, ground motion intensity measure, sufficiency, efficiency, inelastic time history analysis

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Authors: Sifriyani Sifriyani, I Nyoman Budiantara, Sri Haryatmi, Gunardi Gunardi

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East Java Province has a first rank as a province that has the most counties and cities in Indonesia and has the largest population. In 2015, the population reached 38.847.561 million, this figure showed a very high population growth. High population growth is feared to lead to increase the levels of unemployment. In this study, the researchers mapped and modeled the unemployment rate with 6 variables that were supposed to influence. Modeling was done by nonparametric geographically weighted regression methods with truncated spline approach. This method was chosen because spline method is a flexible method, these models tend to look for its own estimation. In this modeling, there were point knots, the point that showed the changes of data. The selection of the optimum point knots was done by selecting the most minimun value of Generalized Cross Validation (GCV). Based on the research, 6 variables were declared to affect the level of unemployment in eastern Java. They were the percentage of population that is educated above high school, the rate of economic growth, the population density, the investment ratio of total labor force, the regional minimum wage and the ratio of the number of big industry and medium scale industry from the work force. The nonparametric geographically weighted regression models with truncated spline approach had a coefficient of determination 98.95% and the value of MSE equal to 0.0047.

Keywords: East Java, nonparametric geographically weighted regression, spatial, spline approach, unemployed rate

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Authors: J. Kazior, A. Szewczyk-Nykiel, T. Pieczonka, M. Laska

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Aluminium alloys are an important class of engineering materials for structural applications. This is due to the fact that these alloys have many interesting properties, namely, low density, high ratio of strength to density, good thermal and electrical conductivity, good corrosion resistance as well as extensive capabilities for shaping processes. In case of classical PM technology a particular attention should be paid to the selection of appropriate parameters of compacting and sintering processes and to keeping them. The latter need arises from the high sensitivity of aluminium based alloy powders on any fluctuation of technological parameters, in particular those related to the temperature-time profile and gas flow. Only then the desired sintered compacts with residual porosity may be produced. Except high mechanical properties, the other profitable properties of almost fully dense sintered components could be expected. Among them is corrosion resistance, rarely investigated on PM aluminium alloys. Thus, in the current study the Alumix 431/D commercial, press-ready grade powder was used for this purpose. Sintered compacts made of it in different conditions (isothermal sintering temperature, gas flow rate) were subjected to corrosion experiments in 0,1 M and 0,5 M NaCl solutions. The potentiodynamic curves were used to establish parameters characterising the corrosion resistance of sintered Alumix 431/D powder, namely, the corrosion potential, the corrosion current density, the polarization resistance, the breakdown potential. The highest value of polarization resistance, the lowest value of corrosion current density and the most positive corrosion potential was obtained for Alumix431/D powder sintered at 600°C and for highest protective gas flow rate.

Keywords: aluminium alloys, sintering, corrosion resistance, industry

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Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: A. Aslihan Gokaltun, Ali Tuncel

Abstract:

The unique properties of capillary electrochromatography (CEC) such as high performance, high selectivity, low consumption of both reagents and analytes ensure this technique an attractive one for the separation of biomolecules including nucleosides and nucleotides, peptides, proteins, carbohydrates. Monoliths have become a well-established separation media for CEC in the format that can be compared to a single large 'particle' that does not include interparticular voids. Convective flow through the pores of monolith significantly accelerates the rate of mass transfer and enables a substantial increase in the speed of the separation. In this work, we propose a new approach for the preparation of cationic monolithic stationary phase for capillary electrochromatography. Instead of utilizing a charge bearing monomer during polymerization, the desired charge-bearing group is generated on the capillary monolith after polymerization by using the reactive moiety of the monolithic support via one-pot, simple reaction. Optimized monolithic column compensates the disadvantages of frequently used reversed phases, which are difficult for separation of polar solutes. Rapid separation and high column efficiencies are achieved for the separation of neutral analytes, nucleic acid bases and nucleosides in reversed phase mode. Capillary monolith showed satisfactory hydrodynamic permeability and mechanical stability with relative standard deviation (RSD) values below 2 %. A new promising, reactive support that has a 'ligand selection flexibility' due to its reactive functionality represent a new family of separation media for CEC.

Keywords: biomolecules, capillary electrochromatography, cationic monolith, neutral analytes

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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