bluuebunny/crossref_metadata_2025 huggingface dataset:
Defense Inducers Mediated Mitigation of Bacterial Canker in Tomato through Alteration in Oxidative Stress Markers
Authors: Tripathi Ruchi , Vishunavat Karuna , Tewari Rashmi , Kumar Sumit , Minkina Tatiana , De Corato Ugo , Keswani Chetan
Published: November 2022

The bacterial canker disease of tomato caused by Clavibacter michiganensis subsp. michiganensis (Cmm) has been reported to adversely affect the tomato cultivation in the NE hilly regions of India. Defense inducers such as salicylic acid (SA), isonicotinic acid (INA), benzothiadiazole (BTH) and lysozyme were used as prophylactic and curative sprays at different concentrations to test their efficacy in inducing resistance in tomato plants against Cmm under protected conditions. The induced resistance was studied through the alteration in the activities of oxidative stress marker enzymes (PAL, PO, PPO, TPC and PR-2 protein), hydrogen peroxide formation in leaf tissues and lignin accumulation in stem tissues, as well as through the reduction in disease severity under glasshouse conditions. The results of the present study revealed that the enzymatic activity, hydrogen peroxide formation and lignin production were significantly higher in the BTH (500 ppm)-treated leaves than in those observed in the control. The lowest disease incidence was recorded when BTH was applied as a prophylactic spray (27.88%) in comparison to being applied as a curative spray (53.62%), thereby suggesting that a defense inducer, BTH, shows antibacterial activity against Cmm, reduces disease incidence severity and induces defense responses in the tomato plant.
Responses of Rhizosphere Bacterial and Fungal Communities to the Long-Term Continuous Monoculture of Water Oat
Authors: Wu Gang , Yu Feifei , Yuan Manman , Wang Jiabao , Liu Chuang , He Weizhu , Ge Zhihuan , Sun Yixiang , Liu Yuan
Published: November 2022

As an cultivated aquatic vegetable, the long-term continuous monocropping of water oat results in the frequent occurrence of diseases, the deterioration of ecological system and decreased quality of water oat. In this study, real-time quantitative PCR (qPCR) and Illumina high-throughput sequencing were used to determine the dynamic changes in bacterial and fungal communities in rhizosphere soil under continuous cropping of water oat for 1, 5, 10, 15 and 20 years (Y1, Y5, Y10, Y15 and Y20), and soil properties and enzyme activities were also determined. Results showed that the contents of soil organic carbon (SOC), total nitrogen (TN), alkali-hydrolyzable nitrogen (AN), available phosphorus (AP) and the activities of four soil enzymes increased in Y5 and Y10 and then decreased in Y15 and Y20. Spearman correlation analysis identified SOC, TN, AP and AN as the main factors that affect the four enzyme activities. The qPCR results showed that there was no significant difference in bacterial abundance between the different planting years, while the fungal abundance first increased and then decreased. The long-term continuous planting of water oat (Y15 and Y20) significantly reduced the operational taxonomic unit numbers and the Shannon, Chao1, and ACE indices of rhizosphere bacteria and fungi. The bacterial and fungal community compositions were markedly affected by the continuous planting year. The relative abundances of Bacteroidetes and Firmicutes decreased significantly in Y10 and Bacteroidetes increased significantly in Y15. Relative abundances of dominated Mortierellomycota and Ascomycota phyla increased with the continuous cropping years, while Rozellomycota presented the opposite trend. The AK, AN, and SOC were the main factors that changed the bacterial community, while AK and AP significantly shifted the fungal community. Thus, long-term continuous planting of water oat resulted in the deterioration of soil nutrients and microbial communities. The results provided a reference for the remediation of soil under continuous water oat planting and sustainable development of water oat industry.
Effect of Different Nutritional Education Based on Healthy Eating Index for HemoDialysis Patients on Dietary Quality and Muscle Mass
Authors: Chen Yun-Han , Liu Wan-Lin , Duong Tuyen Van , Wong Te-Chih , Chen Hsi-Hsien , Chen Tso-Hsiao , Hsu Yung-Ho , Peng Sheng-Jeng , Yang Shwu-Huey
Published: November 2022

Background: Hemodialysis patients are at high risk of muscle loss as a result of aging and disease, and combined with inadequate dietary intake. The Healthy Eating Index for HemoDialysis patients (HEI-HD) was developed to assess the dietary quality of hemodialysis patients. The purposes of this study were to examine the effects of different nutritional education models using HEI-HD-based education on dietary quality and muscle mass in hemodialysis patients. Methods: A quasi-experimental study was conducted from May 2019 to April 2021, with four groups, including no course for patients and nurses (Non-C), course for nurses (CN), course for patients (CP), and course for patients and nurses (CPN). The courses were delivered by registered dietitians. The data of 94 patients were collected and analyzed at baseline, after 2 months of intervention, and 2 months follow-up, including demographics, body composition, 3-day dietary records, and hemodialysis dietary knowledge. The HEI-HD index score was calculated. Results: Patients aged 58.3 ± 10.1 years. The dietary quality change in the CPN group was improved as compared with the Non-C group (−3.4 ± 9.5 vs. 3.0 ± 5.5, 0.04). The skeletal muscle mass of the Non-C group at intervention was also significantly lower than baseline, but the CPN group was not. Conclusions: The HEI-HD-based nutritional education for both patients and nurses showed a positive effect on improving the dietary quality and maintaining muscle mass in hemodialysis patients.
Effects of Additional Dietary Fiber Supplements on Pregnant Women with Gestational Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Studies
Authors: Sun Jihan , Wang Jinjing , Ma Wenqing , Miao Miao , Sun Guiju
Published: November 2022

The efficacy of different types and doses of dietary fiber supplementation in the treatment of gestational diabetes (GDM) remains controversial. The purpose of this study is to investigate the effect of dietary fiber on blood glucose control in pregnant women with gestational diabetes mellitus, and further observe the effect on their blood lipids and pregnancy outcomes. We searched on Web of Science, PubMed, Embase, Scopus, and Cochrane, and included several articles on additional fortification with dietary fiber for gestational diabetes interventions. This meta-analysis included 8 trials. We found that additional dietary fiber supplements significantly reduced fasting glucose (Hedges’g = −0.3; 95% CI [−0.49, −0.1]), two-hour postprandial glucose (Hedges’g = −0.69; 95% CI [−0.88, −0.51]), glycated hemoglobin (Hedges’g = −0.5; 95% CI [−0.68, −0.31]), TC (Hedges’g = −0.44; 95% CI [−0.69, −0.19]), TG (Hedges’g = −0.3; 95% CI [−0.4, −0.2]) and LDL-C (Hedges’g = −0.48; 95% CI [−0.63, −0.33]). It also significantly reduced preterm delivery (Hedges’g = 0.4, 95% CI [0.19~0.84]), cesarean delivery (Hedges’g = 0.6; 95% CI [0.37~0.97]), fetal distress (Hedges’g = 0.51; 95% CI [0.22~1.19]), and neonatal weight (Hedges’g = −0.17; 95% CI [−0.27~−0.07]). In a subgroup analysis comparing dietary fiber type and dose, insoluble dietary fiber was more effective than soluble dietary fiber in reducing fasting glucose (Hedges’g = −0.44; 95% CI [−0.52, −0.35]). ≥12 g fiber per day may be more effective in improving glycemic lipid and pregnancy outcomes than <12 g/day, but the difference was not statistically significant. In conclusion, our meta-analysis showed that dietary fiber supplementation significantly improved glycolipid metabolism and pregnancy outcomes in gestational diabetes. Dietary fiber may be considered adjunctive therapy for gestational diabetes, and an additional supplement with insoluble dietary fiber is more recommended for those with poor fasting glucose. However, more high-quality studies are needed on the further effect of fiber type and the dose-effect relationship.
Association between Dietary Habits, Food Attitudes, and Food Security Status of US Adults since March 2020: A Cross-Sectional Online Study
Authors: Bin Zarah Aljazi , Schneider Sydney T , Andrade Jeanette Mary
Published: November 2022

Since COVID-19, global reports indicate changes in dietary habits and food security status of the population. As a follow-up to an earlier study conducted in 2020, the purpose of this online cross-sectional study was to examine food security and food attitudes and their subsequent impact on dietary habits since March 2020 and potential associations with demographics, health characteristics and lifestyle habits on dietary habits. Participants (n = 2036) responded to a 71-item online survey conducted between February–March 2022. Frequency counts and percentages were tabulated, and multivariate linear regressions were conducted to examine associations. Results showed that most participants indicated no change in dietary habits (45.9–88.8%) for the listed food and beverage items. A significant positive association for food attitudes scores (1.11, 95% CI 0.93 to 1.29; p < 0.001) and food security scores (0.53, 95% CI 0.35 to 0.71; p < 0.001) on total dietary habits was found. Further, significant positive associations were seen with various health characteristics such as medical conditions (p = 0.01) and lifestyle habits such as preparing meals at home (p < 0.001). A negative association was observed with females on total dietary habits (p < 0.001). It is necessary to encourage adults in the US to maintain the positive dietary and lifestyle habits they acquired since March 2020 in their daily living. Future studies should investigate the impact these habits have on their health long-term and sustained positive dietary and lifestyle habits.
Optimization of Pulsed Electric-Field-Based Total Polyphenols’ Extraction from Elaeagnus pungens ‘Limelight’ Leaves Using Hydroethanolic Mixtures
Authors: Pappas Vasileios M. , Palaiogiannis Dimitrios , Athanasiadis Vassilis , Chatzimitakos Theodoros , Bozinou Eleni , Makris Dimitris P. , Lalas Stavros I.
Published: November 2022

In this study, the use of pulsed electric field (PEF) for the extraction of polyphenols from mature Elaeagnus pungens ‘Limelight’ leaves is discussed. Optimization of the main parameters that affect the extraction process was carried out. More specifically, the composition of the solvent (ethanol, water, and mixtures of the two at a 25% v/v step gradient) and the main PEF-related parameters (i.e., pulse duration, pulse period, and electric field intensity) was optimized. The obtained extracts were examined for their polyphenol content with the Folin–Ciocalteu assay and individual polyphenols were also assessed with high-performance liquid chromatography. The extracts obtained with PEF were compared to the extract compared without PEF, in terms of total polyphenols. According to the results, the optimum extraction parameters were found to be a pulse duration of 10 μs, a pulse period of 1000 μs, and an electric field intensity of 0.85 kV cm−1 after 20 min of extraction. The optimum solvent was found to be the 50% (v/v) ethanol/water mixture. The extract prepared under the optimum conditions was found to contain 58% more polyphenols compared with the extract prepared without PEF. Moreover, an increase of up to 92% was recorded for specific polyphenols. Based on the above, it was evidenced that the examined parameters influenced the recovery of polyphenols, suggesting that such parameters should be also examined in similar studies, in order to maximize the extraction yield of polyphenols.
Solubilization and Controlled Release Strategy of Poorly Water-Soluble Drugs
Authors: Peña M. A.
Published: November 2022

The processes of solubilization and controlled release of drugs that are poorly soluble in water are highly relevant in drug preformulation studies in pharmaceutical development [...]
Core Switch Using Optically Induced Long-Period Gratings
Authors: Fernandes Gil M. , Rocha Ana M. , Facão Margarida
Published: November 2022

We propose and theoretically demonstrate an optically induced long-period gratings (OLPGs) based core switching technique for multi-core fibers (MCFs). This switching technique is fully reconfigurable in terms of signal wavelength and input–output fiber cores. The switching window and its efficiency can be adjusted by changing the peak power and the shape of the pump pulses, respectively. Switching efficiencies of 76% were found. Furthermore, we also show that the switched signal can be reshaped by tuning the shape of the pump pulses.
Physiological Performance of Mimosa pudica L. under Different Light Quality and Photoperiods
Authors: Kumar Deepak , Singh Hanwant , Bhatt Upma , Sharma Jyotshana , Sharma Shubhangani , Soni Vineet
Published: November 2022

In the present study, we examined the light quality and photoperiod-dependent physiological performance of Mimosa pudica. Plants were grown in pots under white, blue, green and red-light compositions under 12 h per day (12/12 h) and 24 h per day (24/0 h) for 12 days. After 12 days, the physiological parameters’ morphology, fresh weight, chlorophyll fluorescence and biochemical analyses, which include antioxidants, lipid peroxidation, pigment content and carbohydrate content were also measured. Necrosis was found in red, blue and green light and the plant was senesced at the end of the experiment. The blue 24-h light period showed the highest pigment and antioxidant content, whereas the lowest was observed in green light conditions. The OJIP curve was complete in white light, hence it was not completely formed in red, blue and green light. The phenomenological parameters also fluctuated in different light conditions. Photosynthesis ultimately results in starch content, which was highest in blue light and lowest in red light. Different monochromatic light qualities inhibited plant growth by reducing the activity of photosynthetic apparatus in plants. White light was more effective in driving photosynthesis and promoting the plant growth, while green and red light showed a suppressive effect on plants’ growth. The 24 h photoperiod was also accompanied by various spectra to reduce the plants’ growth. The results clearly indicate that the photoperiod and light spectrum must be considered before growing plants in a greenhouse.
Medicinal Plant Preparations Administered by Botswana Traditional Health Practitioners for Treatment of Worm Infections Show Anthelmintic Activities
Authors: Dube Mthandazo , Raphane Boingotlo , Sethebe Bongani , Seputhe Nkaelang , Tiroyakgosi Tsholofelo , Imming Peter , Häberli Cécile , Keiser Jennifer , Arnold Norbert , Andrae-Marobela Kerstin
Published: November 2022

Schistosomiasis and soil-transmitted helminths are some of the priority neglected tropical diseases (NTDs) targeted for elimination by the World Health Organization (WHO). They are prevalent in Botswana and although Botswana has begun mass drug administration with the hope of eliminating soil-transmitted helminths as a public health problem, the prevalence of schistosomiasis does not meet the threshold required to warrant large-scale interventions. Although Botswana has a modern healthcare system, many people in Botswana rely on traditional medicine to treat worm infections and schistosomiasis. In this study, ten plant species used by traditional health practitioners against worm infections were collected and tested against Ancylostoma ceylanicum (zoonotic hookworm), Heligmosomoides polygyrus (roundworm of rodents), Necator americanus (New World hookworm), Schistosoma mansoni (blood fluke) [adult and newly transformed schistosomula (NTS)], Strongyloides ratti (threadworm) and Trichuris muris (nematode parasite of mice) in vitro. Extracts of two plants, Laphangium luteoalbum and Commiphora pyaracanthoides, displayed promising anthelmintic activity against NTS and adult S. mansoni, respectively. L. luteoalbum displayed 85.4% activity at 1 μg/mL against NTS, while C. pyracanthoides displayed 78.5% activity against adult S. mansoni at 10 μg/mL.
Assessment of a Formulation Containing a Castanea sativa Shells Extract on Skin Face Parameters: In Vivo Evaluation
Authors: Silva Ana Margarida , Costa Paulo C. , Delerue-Matos Cristina , Rodrigues Francisca
Published: November 2022

In the last years, the demand for new eco-friendly ingredients has increased on the cosmetic market. Consumers are more aware of sustainable principles and, simultaneously, more conscious regarding the skin aging process. Chestnut (Castanea sativa) shells are a food by-product produced in high quantities in Europe. This waste has been described as a rich source of phenolic compounds with skin biological effects, such as antioxidant, antiradical, and anti-inflammatory activities. Despite the huge number of assays reporting the richness of chestnut shell extracts in bioactive compounds as well as the development of cosmetic formulations containing these extracts, no in vivo assays have assessed their clinical efficacy in human volunteers. The aim of this study was to evaluate the effect on skin face parameters of a formulation containing a chestnut shell extract in human volunteers (n = 22) who applied the product twice per day, for 56 days. For that, biophysical techniques, including Corneometer®, Cutometer®, and PrimosPremium, were employed, allowing the quantification of skin hydration and firmness, as well as of wrinkles’ depth and volume and wrinkles’ skin roughness. The results demonstrated that the formulation led to a slight decrease in roughness and wrinkles’ depth, although no significant differences with respect to a placebo were observed. In addition, a clear improvement of skin hydration was achieved (t0 = 54.00 Arbitrary Units (A.U.) and t56 = 58.62 A.U.). In contrast to the placebo, the active formulation increased skin firmness up to 31.76% in 50.00% of the volunteers, but without significant differences with respect to the placebo, probably due to the short period of treatment. A long-term use of the product is recommended to possibly observe significant differences in all parameters.
Inactivation of Clostridium Spores in Honey with Supercritical CO2 and in Combination with Essential Oils
Authors: Dacal-Gutiérrez Alejandro , Tirado Diego F. , Calvo Lourdes
Published: November 2022

The presence of tens of Clostridium botulinum spores per gram of honey can cause infantile botulism. Thermal treatment is insufficient to inactivate these resistant forms. This study explored the effectiveness of supercritical CO2 (scCO2) on its own and combined with lemon (LEO), clove (CLEO), and cinnamon (CEO) essential oils on the inactivation of Clostridium sporogenes (CECT 553) as a surrogate of Clostridium botulinum. In water, the degree of inactivation at 10 MPa after 60 min increased with the increasing temperature, reducing the population by 90% at 40 °C and by 99.7% at 80 °C. In contrast, when applied to honey, scCO2 did not inactivate Clostridium spores satisfactorily at temperatures below 70 °C, which was related to the protective effect of honey. Meanwhile, scCO2 modified with CEO (<0.4% mass) improved the inactivation degree, with a 1.3-log reduction achieved at 60 °C. With this same mixture, a reduction of 3.7 logs was accomplished in a derivative with 70% moisture. Honey was very sensitive to the temperature of the applied CO2. The obtained product could be used as a novel food, food ingredient, cosmetic, or medicine.
Plant Extraction in Water: Towards Highly Efficient Industrial Applications
Authors: Gallina Lorenzo , Cravotto Christian , Capaldi Giorgio , Grillo Giorgio , Cravotto Giancarlo
Published: November 2022

Since the beginning of this century, the world has experienced a growing need for enabling techniques and more environmentally friendly protocols that can facilitate more rational industrial production. Scientists are faced with the major challenges of global warming and safeguarding water and food quality. Organic solvents are still widely used and seem to be hard to replace, despite their enormous environmental and toxicological impact. The development of water-based strategies for the extraction of primary and secondary metabolites from plants on a laboratory scale is well documented, with several intensified processes being able to maximize the extraction power of water. Technologies, such as ultrasound, hydrodynamic cavitation, microwaves and pressurized reactors that achieve subcritical water conditions can dramatically increase extraction rates and yields. In addition, significant synergistic effects have been observed when using combined techniques. Due to the limited penetration depth of microwaves and ultrasonic waves, scaling up entails changes to reactor design. Nevertheless, the rich academic literature from laboratory-scale investigations may contribute to the engineering work involved in maximizing mass/energy transfer. In this article, we provide an overview of current and innovative techniques for solid-liquid extraction in water for industrial applications, where continuous and semi-continuous processes can meet the high demands for productivity, profitability and quality.
Using Artificial Neural Network Application in Modeling the Mechanical Properties of Loading Position and Storage Duration of Pear Fruit
Authors: Cevher Elçin Yeşiloğlu , Yıldırım Demet
Published: November 2022

In the study, rupture energy values of Deveci and Abate Fetel pear fruits were predicted using artificial neural network (ANN). This research aimed to develop a simple, accurate, rapid, and economic model for harvest/post-harvest loss of efficiently predicting rupture energy values of Deveci and Abate Fetel pear fruits. The breaking energy of the pears was examined in terms of storage time and loading position. The experiments were carried out in two stages, with samples kept in cold storage immediately after harvest and 30 days later. Rupture energy values were estimated using four different single and multi-layer ANN models. Four different model results obtained using Levenberg–Marquardt, Scaled Conjugate Gradient, and resilient backpropagation training algorithms were compared with the calculated values. Statistical parameters such as R2, RMSE, MAE, and MSE were used to evaluate the performance of the methods. The best-performing model was obtained in network structure 5-1 that used three inputs: the highest R2 value (0.90) and the lowest square of the root error (0.018), and the MAE (0.093).
Preparation and Magneto-Structural Investigation of Nanocrystalline CoMn-Based Heusler Alloy Glass-Coated Microwires
Authors: Salaheldeen Mohamed , Talaat Ahmed , Ipatov Mihail , Zhukova Valentina , Zhukov Arcady
Published: November 2022

In this work, we have successfully fabricated nanocrystalline Co2MnSi Heusler alloy glass-coated microwires with a metallic nucleus diameter (dnuclei) 10.2 ± 0.1 μm and total diameter 22.2 ± 0.1 μm by the Taylor–Ulitovsky technique for the first time. Magnetic and structural investigations have been performed to clarify the basic magneto-structural properties of the Co2MnSi glass-coated microwires. XRD showed a well-defined crystalline structure with a lattice parameter a = 5.62 Å. The room temperature magnetic behavior showed a strong in-plane magnetocrystalline anisotropy parallel to the microwire axis. The M-H loops showed unique thermal stability with temperature where the coercivity (Hc) and normalized magnetic remanence exhibited roughly stable tendency with temperature. Moreover, quite soft magnetic behavior has been observed with values of coercivity of the order of Hc = 7 ± 2 Oe. Zero field cooling and field cooling (ZFC-FC) magnetization curves displayed notable irreversible magnetic dependence, where a blocking temperature (TB = 150 K) has been observed. The internal stresses generated during the fabrication process induced a different magnetic phase and is responsible for the irreversibility behavior. Moreover, high Curie temperature has been reported (Tc ≈ 985 K) with unique magnetic behavior at a wide range of temperature and magnetic fields, making it a promising candidate in magnetic sensing and spintronic applications.
The Lean-Branch-and-Bound Structure Effectiveness in Enhancing the Logistic Stowage Methodology for the Regular Shapes
Authors: Abed Ahmed M. , Seddek Laila F.
Published: November 2022

An excellent e-commerce logistic cycle is based on reducing the delivery time to satisfy customers, accelerating the distribution chain activities at each delivery station, increasing the transported stowage objects for mobilization parallelograms containers to ingest most orders, and reducing the unused area. Because the stowage steps are considered an NP-complexity, the authors introduce the Oriented Stowage Map (OSM) using one of the heuristic methods (i.e., the camel algorithm) that are programmed by the C-sharp software to be easily managed via the Internet of Things (IoT), which is embedded in the distribution chain. The authors called it Oriented Stowage’s Map by Camel algorithm “OSM-CA”. This methodology is considered one of the mat-heuristic approaches (i.e., decomposition metaheuristics) because we resorted to using mathematical steps (branch-and-bound). The OSM-CA reduces transport costs by 7% and delivery time by 14%. Additionally, it shows superiority over the solo Ant-colony for stowage less than 50 boxes by 10% and over the solo camel algorithm by 27%, while for more than 50 boxes, the OSM-CA superiority by 30% over the ant colony, and 17% over the camel algorithm. Creating the map in the proposed way takes 70% less time than using mathematical models, especially for a large number of orders, more than 200.
Inhibition of Necroptosis in Acute Pancreatitis: Screening for RIPK1 Inhibitors
Authors: Yao Jiaqi , Luo Yalan , Liu Xiaojun , Wu Ping , Wang Yin , Liu Yan , Chen Hailong , Wen Qingping
Published: November 2022

This work utilizes the anthraquinone (AQ) database to identify potential inhibitors of the RIPK1 protein for developing medicines targeting AP-associated necroptosis. Screening for necroptosis-related genes that play a crucial role in AP is based on the GEO and GSEA databases. An optimum AQ for receptor-interacting protein kinase 1 (RIPK1) inhibition was virtually screened using the Discovery Studio 2019 tool, with a previously described RIPK1 inhibitor (necrostatin-1) as a reference ligand. Using LibDock and CDOCKER molecular docking, an AQ that robustly binds to RIPK1 was identified. The DOCKTHOR web server was used to calculate the ligand–receptor binding energy. The pharmacological properties and toxicity of potential AQ were evaluated using the ADME module and ProTox-II web server. The stability of ligand–receptor complexes was examined using molecular dynamics (MD) simulation. All 12 AQs showed solid binding activity to RIPK1, 5 of which were superior to necrostatin-1. Rheochrysin and Aloe-Emodin-8-O-Beta-D-Glucopyranoside (A8G) were safe RIPK1 inhibitors based on pharmacological characterization and toxicity studies. Additionally, the potential energy of the candidate AQs with RIPK1 was greater than that of the reference ligand, necrostatin-1. MD simulations also showed that the candidate AQs could bind stably to RIPK1 in the natural environment. Rheochrysin and A8G are safe and effective anthraquinones that inhibit the RIPK1 protein. This research takes a first step toward developing RIPK1 inhibitors by screening AQs that have the potential to be more effective than the reference ligand necrostatin-1.
A Decision-Making Model for Predicting Technology Adoption Success
Authors: Tahriri Farzad , Mousavi Maryam , Galavi Hadi , Sorooshian Shahryar
Published: November 2022

Advanced manufacturing technology (AMT) has the potential to significantly improve manufacturing performance and boost competitiveness in the global market. Investment in AMT remains a promising but potentially risky venture due to the numerous factors that must be considered before the full benefits of implementing a new technology can be realized. To respond to the reported risks and uncertainties, such as those revealed in the recent industrial revolution, it is very important to identify and classify the critical factors that can influence the success of AMT adoption early in the planning stage. Based on an extensive review of relevant literature, 32 critical factors are identified and classified into ten categories in this paper. A new multiple-input single-output (MISO) model is developed by combining the fuzzy Delphi method (FDM) and the fuzzy inference system (FIS) based on the objectives defined. The FDM is used to determine the critical factors, and the FIS addresses the general fuzzy multi-attribute decision-making (MADM) problem in order to evaluate and predict the percentage of AMT adoption success with an existing system. The model is validated using a numerical test bed, and the results show that the model is a proper tool for risk management in AMT implementation.
Causal Plot: Causal-Based Fault Diagnosis Method Based on Causal Analysis
Authors: Uchida Yoshiaki , Fujiwara Koichi , Saito Tatsuki , Osaka Taketsugu
Published: November 2022

Fault diagnosis is crucial for realizing safe process operation when a fault occurs. Multivariate statistical process control (MSPC) has widely been adopted for fault detection in real processes, and contribution plots based on MSPC are a well-known fault diagnosis method, but it does not always correctly diagnose the causes of faults. This study proposes a new fault diagnosis method based on the causality between process variables and a monitored index for fault detection, which is referred to as a causal plot. The proposed causal plot utilizes a linear non-Gaussian acyclic model (LiNGAM), which is a data-driven causal inference algorithm. LiNGAM estimates a causal structure only from data. In the proposed causal plot, the causality of a monitored index of fault detection methods, in addition to process variables, is estimated with LiNGAM when a fault is detected with the monitored index. The process variables having significant causal relationships with the monitored indexes are identified as causes of faults. In this study, the proposed causal plot was applied to fault diagnosis problems of a vinyl acetate monomer (VAM) manufacturing process. The application results showed that the proposed causal plot diagnosed appropriate causes of faults even when conventional contribution plots could not do the same. In addition, we discuss the effects of the presence of a recycle flow on fault diagnosis results based on the analysis result of the VAM process. The proposed causal plot contributes to realizing safe and efficient process operations.
Filling Process Optimization through Modifications in Machine Settings
Authors: Cui Yanmei , Zhang Xupeng , Luo Jing
Published: November 2022

In this paper, a mathematical model is developed for the modified settings of an automatic filling machine to minimize the filling time of orders for different volumes of dairy product and flavors. The linear programming model is solved using the Simplex method to find an optimal solution to the optimization problem. The results of the model are used for sequencing the processing of orders using one-dimensional rules with the aim of obtaining an optimal sequence for the most valued performance measure. The comparative analysis of the one-dimensional rules showed that Shortest Processing Time (SPT) is better than the other rules for minimization of the average time past due. Additionally, the results of the model for the new machine settings, when compared with previous similar studies, yielded encouraging results.
Pricing European Currency Options with High-Frequency Data
Authors: Le Thi , Hoque Ariful
Published: November 2022

Technological innovation has changed the financial market significantly with the increasing application of high-frequency data in research and practice. This study examines the performance of intraday implied volatility (IV) in estimating currency options prices. Options quotations at a different trading time, such as the opening period, midday period and closing period of a trading day with one-month, two months’ and three months’ maturity, are employed to compute intraday IV for pricing currency options. We use the Mincer–Zarnowitz regression test to analyse the volatility forecast power of IV for three different forecast horizons (within a week, one week and one month). Intraday IV’s capability in estimating currency options price is measured by the mean squared error, mean absolute error and mean absolute percentage error measure. The empirical findings show that intraday IV is the key to accurately forecasting volatility and estimating currency options prices precisely. Moreover, IV at the closing period of the beginning of the week contains crucial information for options price estimation. Furthermore, the shorter maturity intraday IV is suitable for pricing options for a shorter horizon. In comparison, the intraday IV based on the longer maturity options subsumes appropriate information to price options with higher accuracy for the longer horizon. Our paper proposes a new approach to accurately pricing currency options using high-frequency data.
Upper Ocean Responses to the Tropical Cyclones Ida and Felicia (2021) in the Gulf of Mexico and the Eastern North Pacific
Authors: Neun Sebastian , Jacob Jan , Wurl Oliver
Published: November 2022

Tropical cyclones (TCs) are a significant component of ocean–atmosphere interactions and the climate system. These interactions determine both the development and strength of TCs, as well as various biogeochemical processes in the upper oceans, including vertical mixing and primary production. We investigated the impact of the TCs Felicia and Ida that emerged in 2021 in the eastern North Pacific and the Gulf of Mexico, respectively, using satellite observations of sea-surface temperature (SST) and surface chlorophyll a (chl-a) concentrations, and vertical profiles of temperature and salinity derived from Argo floats. Observations differed between the two study areas. Cooling of SST associated with TC Ida was observed throughout the Gulf of Mexico (<0.5 °C), except for warming in a region off the Mexican coast east of Ida’s track (by about 0.5 °C). The passing of TC Felicia cooled SST in the eastern region (15°N, 115°W) and a central region (15°N, 125°W) by 0.5 °C and 0.36 °C, respectively. The passing of the TCs caused enhanced vertical mixing of the upper ocean layer in the Gulf of Mexico, with a deepening of the mixed layers from 38 m to 68 m (TC Ida). In contrast, the mixed layer in the eastern North Pacific decreased from 50 m to 20 m. For the eastern North Pacific, mixing could be related to an increase in surface chl-a and thus enhanced phytoplankton biomass was observed for 2 months after the passing of TC Felicia with a chl-a increase of 0.15 mg m−3. In the Gulf of Mexico, however, TC Ida caused the injection of a coastal phytoplankton bloom into the open Gulf, resting for more than a month after the cyclone had passed. Our findings contribute to the understanding of potential SST cooling, destratification, and enhanced primary production due to the passage of TCs in two distinct ocean regions, i.e., the open eastern North Pacific and the semi-enclosed Gulf of Mexico.
The Initial Performance Evaluation of Mixed Multi-Frequency Undifferenced and Uncombined BDS-2/3 Precise Point Positioning under Urban Environmental Conditions
Authors: Yang Fuxin , Zheng Chuanlei , Zhang Jie , Sun Zhiguo , Li Liang , Zhao Lin
Published: November 2022

With the full operation of the global BeiDou navigation satellite system (BDS-3), positioning performance can be further enhanced by BDS-3 combined with the regional BeiDou navigation satellite system (BDS-2). However, due to satellite signals being out of lock and the limited visibility of satellites, the traditional multi-frequency BDS-2/3 precise point positioning (PPP) model is unable to maintain great positioning performance under urban environmental conditions. In this study, a mixed multi-frequency undifferenced and uncombined (UDUC) BDS-2/3 PPP model is presented to improve the positioning performance under urban environmental conditions by making full use of B1I, B1C, B2I, B2a, and B3I signals from all visible BDS satellites. In this model, BDS satellites with single-, dual-, triple- and quad-frequency observations all can participate in PPP. The static and kinematic experiments were carried out using the mixed multi-frequency UDUC BDS-2/3 PPP model to fully assess the positioning performance under urban environmental conditions with comparisons to the multi-frequency model. The static experiments indicated that the mixed multi-frequency UDUC BDS-2/3 PPP could continuously achieve decimeter-level positioning accuracy at a cut-off elevation angle of 40°, but part of the BDS-3 PPP would lose resolution due to limited visible satellites. Furthermore, the initial kinematic vehicle experiment showed that mixed multi-frequency UDUC BDS-2/3 PPP had better satellite geometry and more observation redundancy than the traditional multi-frequency model. Compared with the traditional multi-frequency BDS-2/3 model, the positioning accuracy of the mixed multi-frequency model was improved by 51.6, 35.5, and 39.1%, respectively, in east, north, and up directions. The convergence time was shortened by 40%.
Online Boosting-Based Target Identification among Similar Appearance for Person-Following Robots
Authors: Algabri Redhwan , Choi Mun-Taek
Published: November 2022

It is challenging for a mobile robot to follow a specific target person in a dynamic environment, comprising people wearing similar-colored clothes and having the same or similar height. This study describes a novel framework for a person identification model that identifies a target person by merging multiple features into a single joint feature online. The proposed framework exploits the deep learning output to extract four features for tracking the target person without prior knowledge making it generalizable and more robust. A modified intersection over union between the current frame and the last frame is proposed as a feature to distinguish people, in addition to color, height, and location. To improve the performance of target identification in a dynamic environment, an online boosting method was adapted by continuously updating the features in every frame. Through extensive real-life experiments, the effectiveness of the proposed method was demonstrated by showing experimental results that it outperformed the previous methods.
A Secure LEACH-PRO Protocol Based on Blockchain
Authors: Aljumaie Ghada Sultan , Alhakami Wajdi
Published: November 2022

Wireless Sensor Networks (WSNs) are becoming more popular for many applications due to their convenient services. However, sensor nodes may suffer from significant security flaws, leading researchers to propose authentication schemes to protect WSNs. Although these authentication protocols significantly fulfill the required protection, security enhancement with less energy consumption is essential to preserve the availability of resources and secure better performance. In 2020, Youssef et al. suggested a scheme called Enhanced Probabilistic Cluster Head Selection (LEACH-PRO) to extend the sensors’ lifetime in WSNs. This paper introduces a new variant of the LEACH-PRO protocol by adopting the blockchain security technique to protect WSNs. The proposed protocol (SLEACH-PRO) performs a decentralized authentication mechanism by applying a blockchain to multiple base stations to avoid system and performance degradation in the event of a station failure. The security analysis of the SLEACH-PRO is performed using Burrows–Abadi–Needham (BAN) logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. Moreover, the SLEACH-PRO is evaluated and compared to related protocols in terms of computational cost and security level based on its resistance against several attacks. The comparison results showed that the SLEACH-PRO protocol is more secure and requires less computational cost compared to other related protocols.
Emotional Effects in Object Recognition by the Visually Impaired People in Grocery Shopping
Authors: Balconi Michela , Acconito Carlotta , Angioletti Laura
Published: November 2022

To date, neuroscientific literature on consumption patterns of specific categories of consumers, such as people with disability, is still scarce. This study explored the implicit emotional consumer experience of visually impaired (VI) consumers in-store. A group of VI and a control group explored three different product shelves and manipulated target products during a real supermarket shopping experience. Autonomic (SCL, skin conductance level; SCR, skin conductance response; HR, heart rate; PVA, pulse volume amplitude; BVP, blood volume pulse), behavioural and self-report data were collected in relation to three phases of the in-store shopping experience: (i) identification of a product (recognition accuracy, ACC, and reaction times, RTs); (ii) style of product purchase (predominant sense used for shelf exploration, store spatial representation, and ability to orientate themselves); (iii) consumers experience itself, underlying their emotional experience. In the VI group, higher levels of disorientation, difficulty in finding products, and repeating the route independently were discovered. ACC and RTs also varied by product type. VI also showed significantly higher PVA values compared to the control. For some specific categories (pasta category), PVA correlates negatively with time to recognition and positively with simplicity in finding products in the entire sample. In conclusion, VI emotional and cognitive experience of grocery shopping as stressful and frustrating and has a greater cognitive investment, which is mirrored by the activation of a larger autonomic response compared to the control group. Nevertheless, VI ability to search and recognise a specific product is not so different from people without visual impairment.
Shared Autonomous Vehicles Competing with Shared Electric Bicycles: A Stated-Preference Analysis
Authors: Lee Sungwon , Farmer Devon , Kim Jooyoung , Kim Hyun
Published: November 2022

Understanding the factors that affect the uptake of emerging transport modes is critical for understanding if and how they will be used once they are implemented. In this study, we undertook a stated-preference analysis to understand the factors that affect the use of shared autonomous vehicles and shared personal mobility (micromobility) as competing modes on a university campus in Korea. We applied a binary logit model, which included time and cost variables as well as the perceptions of convenience (in-car congestion and availability) and safety. For autonomous vehicles, the cost- and time-related demand elasticities were estimated to be −0.45 and −0.25, respectively, while the cost elasticity for shared electric bicycles was −0.42. The elasticities of perceived convenience (availability) and safety for the shared electric bicycle system were estimated to be 0.72 and 0.29, respectively. Finally, the elasticity for perceived convenience (in-car congestion) of the shared autonomous vehicle was 0.42. Our results show that there is an innate preference for shared autonomous vehicles when these are compared to shared personal mobility, and that the effect of subjective variables (convenience and safety) on the use of emerging transport modes is as important as traditional cost and time variables.
Detecting the Turn on of Vehicle Brake Lights to Prevent Collisions in Highway Tunnels
Authors: Kim JongBae
Published: November 2022

This paper proposes a method of detecting driving vehicles, estimating the distance, and detecting whether the brake lights of the detected vehicles are turned on or not to prevent vehicle collision accidents in highway tunnels. In general, it is difficult to determine whether the front vehicle brake lights are turned on due to various lights installed in a highway tunnel, reflections on the surface of vehicles, movement of high-speed vehicles, and air pollution. Since driving vehicles turn on headlights in highway tunnels, it is difficult to detect whether the vehicle brake lights are on or not through color and brightness change analysis in the brake light area only with a single image. Therefore, there is a need for a method of detecting whether the vehicle brake lights are turned on by using a sustainable change obtained from image sequences and estimated distance information. In the proposed method, a deep convolutional neural network(DCNN) is used to detect vehicles, and inverse perspective mapping is used to estimate the distance. Then, a long short-term memory (LSTM) Network that can analyze temporal continuity information is used to detect whether the brake lights of the detected vehicles are turned on. The proposed method detects whether or not the vehicle brake lights are turned on by learning the long-term dependence of the detected vehicles and the estimated distances in an image sequence. Experiments on the proposed method in highway tunnels show that the detection accuracy of whether the front vehicle brake lights are turned on or not is 90.6%, and collision accidents between vehicles can be prevented in highway tunnels.
Estimation of Carbon Emissions from Tourism Transport and Analysis of Its Influencing Factors in Dunhuang
Authors: Yang Gengxia , Jia Liang
Published: November 2022

Traffic carbon emissions have a non-negligible impact on global climate change. Effective estimation and control of carbon emissions from tourism transport will contribute to the reduction in the amount of global carbon emissions. Based on the panel data of Dunhuang in western China from 2010 to 2019, the process analysis method was used to estimate the carbon emissions from tourism traffic of Dunhuang. By establishing the Kaya identity of tourism traffic carbon emissions, the LMDI decomposition method was used to reveal the contribution of different factors to the change in tourism traffic carbon emissions. The results showed that the impact of tourism traffic carbon emissions was diversified; we found three main factors of promoting carbon emissions, namely the number of tourists, tourism expenditure per capita, and energy consumption per unit of passenger turnover. However, the contribution of tourism activities to GDP, passenger turnover per unit of GDP, and energy structure largely inhibited the increase in carbon emissions.
Exploring the Use of Tobacco Waste as a Metal Ion Adsorbent and Substrate for Sulphate-Reducing Bacteria during the Treatment of Acid Mine Drainage
Authors: Dovorogwa Hamlton , Harding Kevin
Published: November 2022

Treatment of acid mine drainage (AMD) was successfully demonstrated using tobacco waste (dust and stem) as a metal cation adsorbent, pH modifier and carbon source for sulphate-reducing bacteria (SRB). Synthetic and industrial AMD wastewaters were used in batch adsorption and SRB facilitated bioremediation experiments. Up to absorbent loading of 80 g/L, metal removal increased. However, increases above 160 g/L did not offer a proportional increase. At an adsorbent loading of 80 g/L, the highest metal removals of 38, 41, 31 and 43% for iron, nickel, copper and zinc respectively were achieved. The iron data fitted well to the Langmuir adsorption isotherm while the Sips adsorption isotherm better-described nickel, copper and zinc adsorption to tobacco waste. SRBs used were able to use tobacco waste as a carbon source while reducing sulphates to metal sulphides in acid mine drainage. In the presence of SRBs, metal removals by both adsorption and sulphide precipitation were 95, 97, 70 and 93% for iron, nickel, copper and zinc, respectively. Copper, however, demonstrated lower removal yields in both adsorption and bioremediation. Bioremediation improved acid mine drainage pH by 2.05 units. The exponential decay function could model both the metal and sulphate removal perfectly. It was concluded that tobacco waste can be confidently used as an adsorbent and carbon source for sulphate-reducing bacteria while facilitating AMD biological treatment.