Hasil untuk "Engineering"

Yashuai Wu, Ruiyang Yin, Wenjing Tian et al.

Umami taste in lager beer not only determined body fullness and the backbone of aftertaste, but also affected the controllability and interpretability of flavor expression across the entire brewing process. Based on stage-wise sampling, peptidomic profiles were established on wort fermentation day 0, day 1, day 3, and day 9. A total of 25,592 peptides were identified by reversed-phase liquid chromatography–quadrupole time-of-flight mass spectrometry (RPLC-QTOF-MS). Molecular informatics screening was performed using UMPred-FRL (a feature representation learning-based meta-predictor for umami peptides) and TastePeptides-Meta (a one-stop platform for taste peptides and prediction models), yielding 7255 potential umami peptides. From these, 145 peptides were further selected for molecular docking. In addition, 6 representative umami peptides were selected for receptor-level validation and structural analysis. Mechanistically, the umami receptor taste receptor type 1 member 1/taste receptor type 1 member 3 (T1R1/T1R3) belonged to class C G protein-coupled receptor (GPCR) and relied on the extracellular Venus flytrap (VFT) domain for ligand capture. Ligand-induced VFT conformational convergence transmitted changes to the transmembrane region and triggered signal transduction. Docking and energy decomposition indicated that the ionic group primarily contributed to orientation and anchoring. Salt-bridge or hydrogen-bond networks were formed around Lys228, Arg240, Glu206, Asp210, Asn141, and Gln138, thereby reducing conformational freedom. Meanwhile, hydrophobic side chains obtained major binding gains within a hydrophobic microenvironment formed by Val135, Ile137, Leu165, Tyr166, Trp78, and His79. These results reflected a synergistic mode in which charge pairing enabled positioning and hydro-phobic complementarity promoted VFT closure. To experimentally confirm sensory relevance, 6 representative peptides were individually spiked into 4 brewing-stage beer samples, which produced a clear stratification pattern across stages. Notably, peptides with favorable docking-derived binding propensity did not necessarily enhance umami perception, and several longer peptides showed persistent negative sensory shifts, supporting that binding affinity alone could not be treated as a proxy for perceived umami in the beer matrix. At the node level, the cumulative abundance of umami peptides showed a significant positive correlation with umami scores, with a Pearson correlation coefficient of r = 0.963 and <i>p</i> = 0.037. This result indicated good linear consistency between umami peptide content and the upward shift in umami taste in lager beer. Umami peptide clusters were further proposed as a more appropriate functional unit, and an umami peptide cluster database spanning the full process was constructed. This database provided a reusable resource for process control and flavor prediction.

C. J. Horwell, S. Ravenhall, R. Clarkson et al.

Abstract Volcanic eruptions produce plumes of ash, gas and aerosols that present a risk to aviation at all standard flight levels. Here, we investigate atmospheric dispersal of volcanic emissions, whether and how they infiltrate aircraft, and whether ground-level public health exposure thresholds can be related to the pressurised cabin environment. We then review the limited evidence for physical and mental health, and behavioural impacts, resulting from volcanic emissions entering aircraft. Serious health risks are considered low for healthy individuals, but respiratory irritation is likely for a high exposure scenario to sulfur dioxide (SO2). Asthmatics are particularly sensitive to SO2, with even relatively low, short exposures, potentially resulting in severe respiratory impacts. Negative group behaviours are not expected but individual distress is possible. Communicating this evidence to the aviation industry may result in more informed decision-making on flightpath alterations and triggering of emergency protocols, both before and during volcanic emission encounters.

Tamer Eliyan, Ali Saeed Almuflih, Z. M. S. Elbarbary et al.

The new horizons for HVDC systems and their applications has intensified the research in HVDC protection systems. The HVDC circuit breakers (CB) has been the center of the protection systems with vacuum interrupters (VIs) showcasing a great potential for application as a part of HVDC-CBs. However, VIs still face the problem of arc-reignition with limited studies in this area. This paper tends to address this problem by investigating the impact of the parameters of VI and the shunt L-C branch upon the re-ignition occurrence during switching process. An HVDC testing system and VI-based HVDC-CB were modeled using ATP software. The testing included investigation of the impact of the rate of rise of dielectric strength (RRDS) of VI, the type of LC circuit either active or passive and its timing of injection. The results showed that active L-C circuits demanded a longer delay time before insertion to avoid re-ignitions and the increase in RRDS reduced the reignitions. The main contributions of this paper include; investigating the arc re-ignition in VI-based HVDC-CB; analyzing the combined effect of the VI and L-C parameters upon those reignitions and providing a co-relation between the re-ignition occurrence and these parameters. That co-relation is used to define the most suitable delay time for LC circuit to avoid re-ignitions. The co-relation shows that the delay time is inversely co-related to the RRDS and directly-correlated to active LC types with lower values for passive L-C. This was applied to the simulation results and showed agreement with that co-relation.

Quoc Cuong Ngo, Nicole McConnell, Mohammod Abdul Motin et al.

Objective: A change in handwriting is an early sign of Parkinson&#x2019;s disease (PD). However, significant inter-person differences in handwriting make it difficult to identify pathological handwriting, especially in the early stages. This paper reports the testing of NeuroDiag, a software-based medical device, for the automated detection of PD using handwriting patterns. NeuroDiag is designed to direct the user to perform six drawing and writing tasks, and the recordings are then uploaded onto a server for analysis. Kinematic information and pen pressure of handwriting are extracted and used as baseline parameters. NeuroDiag was trained based on 26 PD patients in the early stage of the disease and 26 matching controls. Methods: Twenty-three people with PD (PPD) in their early stage of the disease, 25 age-matched healthy controls (AMC), and 7 young healthy controls were recruited for this study. Under the supervision of a consultant neurologist or their nurse, the participants used NeuroDiag. The reports were generated in real-time and tabulated by an independent observer. Results: The participants were able to use NeuroDiag without assistance. The handwriting data was successfully uploaded to the server where the report was automatically generated in real-time. There were significant differences in the writing speed between PPD and AMC (P&#x003C;0.001). NeuroDiag showed 86.96&#x0025; sensitivity and 76.92&#x0025; specificity in differentiating PPD from those without PD. Conclusion: In this work, we tested the reliability of NeuroDiag in differentiating between PPD and AMC for real-time applications. The results show that NeuroDiag has the potential to be used to assist neurologists and for telehealth applications. Clinical and Translational Impact Statement &#x2014; This pre-clinical study shows the feasibility of developing a community-wide screening program for Parkinson&#x2019;s disease using automated handwriting analysis software, NeuroDiag.

Al Amin Biswas

Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited due to the transparency issue, which is considered a significant obstacle. To achieve the trust of end users, it is necessary to explain the AI models' output. Therefore, explainable AI (XAI) has become apparent as a potential solution by providing transparent explanations of the AI models' output. In this review paper, the primary aim is to review articles that are mainly related to machine learning (ML) or deep learning (DL) based human disease diagnoses, and the model's decision-making process is explained by XAI techniques. To do that, two journal databases (Scopus and the IEEE Xplore Digital Library) were thoroughly searched using a few predetermined relevant keywords. The PRISMA guidelines have been followed to determine the papers for the final analysis, where studies that did not meet the requirements were eliminated. Finally, 90 Q1 journal articles are selected for in-depth analysis, covering several XAI techniques. Then, the summarization of the several findings has been presented, and appropriate responses to the proposed research questions have been outlined. In addition, several challenges related to XAI in the case of human disease diagnosis and future research directions in this sector are presented.

Ajay Dadhich, Jaideep Patel, Rovin Tiwari et al.

Mind-wandering (MW) is when an individual’s concentration drifts away from the task or activity. Researchers found a greater variability in electroencephalogram (EEG) signals due to MW. Collecting more nuanced information from raw EEG data to examine the harmful effects of MW is time-consuming. This study proposes a multi-resolution assessment of EEG signals using the flexible analytic wavelet transform (FAWT). The FAWT algorithm decomposes raw EEG data into more representative sub-bands (SBs). Several statistical characteristics are derived from the obtained SBs, and the effects of MW during meditation on the EEG signals are investigated. A set of significant characteristics is chosen and fed into the machine learning modules using a 10-fold validation approach to detect MW subjects automatically. Our proposed framework attained the highest classification accuracy of 92.41%, the highest sensitivity of 93.56%, and the highest specificity of 91.97%. The proposed framework can be used to design a suitable brain-computer interface (BCI) system to reduce MW and increase meditation depth for holistic and long-term health in society.

Qizhi Xie, Song Cui, Peilin Cheng et al.

The inchworm in-pipe robot has the advantages of stable support, low walking resistance, and high flexibility. However, the gait motion of in-pipe robots relies on the precise coordination of three motors, which greatly increases the complexity of control. To solve this problem, an inchworm in-pipe robot based on a multi-cam combination is proposed. The robot needs only one motor to achieve active support and bidirectional crawling for the pipe wall, mainly used for detecting straight pipelines, such as the main drainage pipeline. In order to obtain the periodic motion law and characteristics of the inchworm in-pipe robot, structure design, constraint analysis, and dynamic simulation were carried out on the robot. Finally, the principle prototype was tested in the transparent pipe, the test results indicate that the robot can achieve bidirectional creep under a single motor drive, which can simplify the control of gait motion for inchworm in-pipe robots. The average displacement errors for horizontal walking and vertical walking are 2.0&#x0025; and 11.3&#x0025;, respectively, due to factors such as gravity. Therefore, the robot can achieve a more accurate step distance in the horizontal pipe.

Alejandra Rodríguez, Teresa Gea, Xavier Font

Biosurfactants are being proposed as a substitute for surfactants in the framework of a circular economy strategy. Sophorolipids (SL) are a type of biosurfactant produced by yeast that can be produced through submerged or solid-state fermentation (SSF) processes. Even though sophorolipids are being produced at full scale, through submerged fermentations, environmental and technoeconomic information regarding its production through SSF is unavailable. An inventory of data necessary to perform preliminary economic and environmental assessments is presented in this study. Data was obtained from three SSF processes at 22-L reactor volume and from two SSF processes at 100-L reactor volume, using winterization oil cake and molasses as substrates, wheat straw as support material, and Starmerella bombicola as SL producing yeast. The effect of increasing the operation scale was assessed. Besides presenting parameters such as inoculum production, initial mass of substrates, and airflow requirements; process emissions (NH3, Volatile Organic Compounds, N2O, SH2 and CH4) and the biogas potential of the spent fermentation solids were also presented.

Yanghuan Zhang, Xin Wei, Wei Zhang et al.

In this investigation, mechanical grinding was applied to fabricating the Mg-based alloys La7Sm3Mg80Ni10 + 5 wt.% M (M = None, TiO2, La2O3) (named La7Sm3Mg80Ni10–5 M (M = None, TiO2, La2O3)). The result reveals that the structures of as-milled alloys consist of amorphous and nanocrystalline. The particle sizes of the added M (M = TiO2, La2O3) alloys obviously diminish in comparison with the M = None specimen, suggesting that the catalysts TiO2 and La2O3 can enhance the grinding efficiency. What's more, the additives TiO2 and La2O3 observably improve the activation performance and reaction kinetics of the composite. The time required by releasing 3 wt.% hydrogen at 553, 573 and 593 K is 988, 553 and 419 s for the M= None sample, and 578, 352 and 286 s for the M = TiO2 composite, and 594, 366, 301 s for the La2O3 containing alloy, respectively. The absolute value of hydrogenation enthalpy change |ΔH| of the M (M = None, TiO2, La2O3) alloys is 77.13, 74.28 and 75.28 kJ/mol. Furthermore, the addition of catalysts reduces the hydrogen desorption activation energy (Eade).

Gorjanc Dunja Šajn, Bras Ana, Novak Boštjan

Nonwovens represent a part of technical textiles that are used for clothing (“cloth tech”). Nonwovens are also used in the footwear industry mainly for functional purposes, where the aesthetic properties are not of great importance. They are mainly used for support and reinforcement of footwear. All three groups of textiles are used for footwear, i.e. woven fabrics, knitted fabrics and nonwovens that are produced directly from fibres, yarns or threads mainly from chemical fibres and in a small proportion from natural fibres.

Ali Davoodi, Homayoun H. Zadeh, Morteza Daliri Joupari et al.

Plasma surface treatment has a wide range of applications in biomedicine. In the present study, flat polylactic acid (PLA) films were treated with oxygen and nitrogen, low-pressure, non-thermal plasma. The water contact angle of the PLA films dramatically decreased from 67° in the untreated surface to 34° and 38° in surfaces treated with nitrogen and oxygen plasma, respectively. Conversely, after the plasma treatment, the surface free energy of the films increased considerably from 45.73 mN/m to 66.51 mN/m. The hydrophilicity potential variations following the plasma treatment were measured by the x-ray photoelectron spectroscopy examination of polar functional groups. Furthermore, surface changes after plasma treatment were examined using atomic force microscopy. The MTT assay showed no changes in cell viability cytotoxicity following the PLA films’ plasma treatment. Moreover, as evidenced by SEM analysis, plasma treatment was found to promote cell growth and adhesion to polymer surfaces. The results were suggestive of modifications due to the PLA’s plasma treatment that may enhance the biological properties of PLA as a scaffold.

Wen Liu, Fumio Yamazaki, Yoshihisa Maruyama

A series of earthquakes hit Kumamoto Prefecture, Japan, continuously over a period of two days in April 2016. The earthquakes caused many landslides and numerous surface ruptures. In this study, two sets of the pre- and post-event airborne Lidar data were applied to detect landslides along the Futagawa fault. First, the horizontal displacements caused by the crustal displacements were removed by a subpixel registration. Then, the vertical displacements were calculated by averaging the vertical differences in 100-m grids. The erosions and depositions in the corrected vertical differences were extracted using the thresholding method. Slope information was applied to remove the vertical differences caused by collapsed buildings. Then, the linked depositions were identified from the erosions according to the aspect information. Finally, the erosion and its linked deposition were identified as a landslide. The results were verified using truth data from field surveys and image interpretation. Both the pair of digital surface models acquired over a short period and the pair of digital terrain models acquired over a 10-year period showed good potential for detecting 70% of landslides.

Xiaoqing Gu, Cong Zhang, Tongguang Ni

The rule-based fuzzy systems have successfully applied for numerous medical data classification problems. However, structuring the concise and interpretable fuzzy rules with good classification performance is still a big challenge. To address this issue, a novel feature selection and rule generation integrated learning for Takagi-Sugeno-Kang fuzzy system (called FSRG-IL-TSK) in this paper. FSRG-IL-TSK represents feature selection, structure identification and parameter learning into a Bayesian model, and uses the sequential importance resampling (SIR) algorithm to obtain the optimal parameters simultaneously, including the optimal features for each fuzzy rule, number of rules, and antecedent/consequent parameter of rules. Due to an integrated learning mechanism, it can select a small set of useful features and obtain a small number of rules. The effectiveness and advantages of FSRG-IL-TSK are validated experimentally on real-world medical data classification tasks.

Ahmed Rady, Daniel Guyer, William Kirk et al.

The sprouting of potato tubers during storage is a significant problem that suppresses obtaining high quality seeds or fried products. In this study, the potential of fusing data obtained from visible (VIS)/near-infrared (NIR) spectroscopic and hyperspectral imaging systems was investigated, to improve the prediction of primordial leaf count as a significant sign for tubers sprouting. Electronic and lab measurements were conducted on whole tubers of Frito Lay 1879 (FL1879) and Russet Norkotah (R.Norkotah) potato cultivars. The interval partial least squares (IPLS) technique was adopted to extract the most effective wavelengths for both systems. Linear regression was utilized using partial least squares regression (PLSR), and the best calibration model was chosen using four-fold cross-validation. Then the prediction models were obtained using separate test data sets. Prediction results were enhanced compared with those obtained from individual systems&rsquo; models. The values of the correlation coefficient (the ratio between performance to deviation, or r(RPD)) were 0.95(3.01) and 0.9s6(3.55) for FL1879 and R.Norkotah, respectively, which represented a feasible improvement by 6.7%(35.6%) and 24.7%(136.7%) for FL1879 and R.Norkotah, respectively. The proposed study shows the possibility of building a rapid, noninvasive, and accurate system or device that requires minimal or no sample preparation to track the sprouting activity of stored potato tubers.

Ika Rinawati Dyah, Puspita Sari Diana, Pujotomo Darminto et al.

Using synthetic dyes causes bad impact on the environment. But using natural dyes has several problems such as fade, slight colour variations and takes longer time. In order to solve that problems, it is needed to develop instant natural dyes. This study aims to design instant natural dyes to fulfill needs of batik artisans that having minimal environmental impact as well as having minimal cost. This study use green quality function deployment II method. This study involve voice of customer identification, calculation gap, the determination of characteristic of technical, making the house of quality (HOQ), life cycle assessment (formulation of green house & green the matrix), life cycle cost (formulation of cost house, the preparation of cost the matrix) and concept comparison house (CCH). Based on voice of customer, natural dyes that will be developed is red colour. Red natural dyes extracted from root of Morinda citrifolia and Ceriops candolleana. In this research, there are two alternatives of natural dyes namely powders and liquid natural dyes. The result of this study is powder natural dyes selected because of lower environmental impact and user operational cost.

Belma Zengin Kurt

Bu çalışmada, sinnamaldehitin 9yeni schiff bazı sentezlenmiş ve bu bileşiklerin 2,2-difenil-1-pikrilhidrazil radikal söndürücü kapasitesi(DPPH), Troloks eşdeğeri antioksidankapasitesi (ABTS) ve bakır (II)iyonu indirgeyici antioksidan kapasitesi (CUPRAC) olmak üzere üç farklıyöntemle antioksidan aktivite özellikleri incelenmiştir. Bu bileşiklerin içinde(2,3-dihidroksibenziliden)amino)fenil)-5-fenilpenta-2,4-dien-1-on(4c) bileşiği her üç yönteme göre oldukça etkin bir şekilde antioksidanözellik göstermiştir. Ayrıca sentezlenen bileşiklerin yapı aktivite ilişkisiincelenerek bileşiklerin sahip oldukları grupların antioksidan aktiviteyi hangiyönde etkilediği ortaya konulmuştur.

Ednawati Rainarli, Arif Romadhan

Abstrak— Prediksi kemenangan atlet adalah hal yang harus dilakukan oleh pelatih ketika memutuskan pemain  yang akan diturunkan dalam suatu pertandingan. Banyaknya faktor-faktor yang mempengaruhi kemenangan atlet membuat keputusan tersebut tidak mudah untuk ditentukan. Dalam penelitian ini akan dilakukan perbandingan dari penggunaan metode Simple Logistic Classifier (SLC) dengan Support Vector Machine (SVM)  dalam memprediksi kemenangan atlet berdasarkan data kesehatan dan data latihan fisik. Data yang digunakan diambil dari 28 cabang olahraga perorangan. Rata-rata akurasi SLC dan SVM masing-masing diperoleh sebesar 80% dan 88%, sedangkan rata-rata kecepatan pemrosesan metode SLC dan SVM adalah 1,6 detik dan 0,2 detik.  Hal ini menunjukkan bahwa penggunaan metode SVM lebih unggul daripada SLC, baik dari segi kecepatan maupun dari nilai akurasi yang dihasilkan. Selain pengujian akurasi, dilakukan pula pengujian terhadap 24 fitur yang digunakan dalam proses klasifikasi.  Hasilnya diketahui bahwa pengurangan fitur melalui tahap seleksi mengakibatkan penurunan nilai akurasi. Berdasarkan hal tersebut disimpulkan bahwa semua fitur yang digunakan dalam penelitian ini adalah fitur yang berpengaruh dalam penentuan prediksi kemenangan atlet.   Kata Kunci— Prediksi, Simple Logistic Classifier, Sports Data Mining, Support Vector Machine Abstract— A coach must be able to select which athlete has a good prospect of winning a game.  There are a lot of aspects which influence the athlete in winning a game, so it's not easy by coach to decide it.This research would compare Simple Logistic Classifier (SLC) and Support Vector Machine (SVM) usage applied to predict winning game of athlete based on health and physical condition record.  The data get from 28 sports. The accuracy of SLC and SVM are 80% and 88% meanwhile processing times of SLC and SVM method are 1.6 seconds dan 0.2 seconds.The result shows the SVM usage superior to the SLC both of speed process and the value of accuracy.  There were also testing of 24 features used in the classifications process. Based on the test,  features selection process can cause decreasing the accuracy value. This result concludes that all features used in this research influence the determination of a victory athletes prediction.  Keywords— Prediction, Simple Logistic Classifier, Sports Data Mining, Support Vector Machine

Aqsa Yousaf, Muhammad Nawaz Tahir, Abdul Rauf et al.

The title compound, [Ag(C9H10NO3)]n, is a polymeric silver(I) complex of l-tyrosine. The AgI atom is connected to N and O atoms of two different l-tyrosine ligands in an almost linear arrangement, with an Ni—Ag—O1 bond angle of 173.4 (2)° [symmetry code: (i) x + 1, y, z]. The Ag—Ni and Ag—O bond lengths are 2.156 (5) and 2.162 (4) Å, respectively. The polymeric chains extend along the crystallographic a axis. Strong hydrogen bonds of the N—H...O and O—H...O types and additional C—H...O interactions connect these chains into a double-layer polymeric network in the ab plane.

Thalles Evangelista Fernandes de Souza, Emanuel Flávio Campos Costa, Marcos Fábio Porto de Aguiar

É tendência mundial a incorporação de diversas facilidades nas edificações multifamiliares, tais como elevadores, internet predial, sistema de segurança eletrônica, poço profundo, gerador elétrico de emergência, dentre outras. Tais facilidades possuem um custo de manutenção, e este custo é repassado aos condôminos através da taxa condominial. Atualmente, muitos desses moradores de edifícios multifamiliares se queixam dos valores cobrados para a taxa condominial. Em diversos casos, o valor da taxa é superior ao valor do aluguel do imóvel. A proposta do presente trabalho é a de desenvolver uma ferramenta para auxiliar os condôminos, síndicos, compradores e locatários de imóveis residenciais, na previsão do valor da taxa condominial e apontar quais as principais variáveis influenciantes na formação desse valor, tendo como referência o mercado imobiliário de Fortaleza(CE).

Equipo Editorial