bluuebunny/crossref_metadata_2025 huggingface dataset:
Design, Heat Transfer, and Visualization of the Milli-Reactor by CFD and ANN
Authors: Liu Hanyang , Wang Chenfeng , Wang Rijie , Yang Xiaoxia
Published: November 2022

This paper proposes a milli-reactor design method incorporating reactor runaway criteria. Based on Computational Fluid Dynamic (CFD) simulation, neural networks are applied to obtain the optimal reactor structure according to the target reaction requirements. Varma’s theory, the critical Nusselt number for stable operation of the flow reactor, is derived. Inserts of the multi-blade structure are designed and investigated to enhance mixing and heat transfer performance. The flow field and heat transfer capacities are obtained by CFD calculations in the range of Re 50–1800. The internal components increase the heat transfer performance up to 21 times, and the pressure drop up to 16 times. The inclined angle of the blade is recommended to be 45°, which can effectively improve heat transfer without generating excessive pressure drop. By partial least squares regression (PLS) analysis, Re and the number of blades are the most critical factors affecting heat transfer, and the five blades and smaller tilt angles are recommended. The CFD calculation results are in good agreement with the Particle Image Velocimetry (PIV) experimental results.
Purification, Structural Elucidation, and Anticancerous Properties of a Novel Flavonoid from Flowers of Leucas indica
Authors: Sowjanya Muthyam , Venkata Sandeep Bhagavathula , Venkaiah Kaduru , Dirisala Vijaya R. , Reddy Malapati Hanuma , Pradeepkiran Jangampalli Adi , Sainath Sri Bhashyam
Published: November 2022

Previously, we showed that the crude methanol extracts of Leucas indica flowers exhibited antioxidant properties and in the current study, crude methanol flower extracts of L. indica showed anticancerous properties as evidenced cytotoxicity (MTT assay test) against the selected cancerous cell lines HeLa, HCT116, HL-60, and MCF-7. Therefore, further analysis was performed to isolate and purify the bioactive compound using activity-guided repeated fractionation of the methanol extract by silica gel column chromatography. After collection of different fractions, all the fractions were subjected to TLC analysis and the fractions which yielded the same compounds on TLC were further analyzed for physicochemical and spectroscopic analyses, e.g., UV, IR, 1H NMR, 13C NMR, COSY, HSQC, and mass spectroscopy. The bioactive compound isolated was elucidated as 6-hydroxy-3-(4-hydroxyphenyl)-7-(3,4,5-trihydroxy-6-)(hydroxymethyl)tetrahydro-2H-pyran-2yl)-4H-chromen-4-one. Based on the antioxidant and anticancerous properties, L. indica might be a promising source of useful natural products and the newly bioactive compound might offer opportunities to develop new anticancerous drugs.
Periodontal Therapy Using Bioactive Glasses: A Review
Authors: Nicholson John W.
Published: November 2022

This paper reviews the use of bioactive glasses as materials for periodontal repair. Periodontal disease causes bone loss, resulting in tooth loosening and eventual tooth loss. However, it can be reversed using bioactive glass, typically the original 45S5 formulation (Bioglass®) at the defect site. This is done either by plcing bioactive glass granules or a bioactive glass putty at the defect. This stimulates bone repair and causes the defect to disappear. Another use of bioactive glass in periodontics is to repair so-called furcation defects, i.e., bone loss due to infection at the intersection of the roots in multi-rooted teeth. This treatment also gives good clinical outcomes. Finally, bioactive glass has been used to improve outcomes with metallic implants. This involves either placing bioactive glass granules into the defect prior to inserting the metal implant, or coating the implant with bioactive glass to improve the likelihood of osseointegration. This needs the glass to be formulated so that it does not crack or debond from the metal. This approach has been very successful, and bioactive glass coatings perform better than those made from hydroxyapatite.
The Description of the Liturgy of the Presanctified Gifts in the Typikon of Mâr Saba, a Reminiscence of Byzantinisation?
Authors: Fittipaldi Diego Rodrigo
Published: November 2022

This article deals with the description of the Liturgy of the Presanctified Gifts in the Byzantine liturgical book known as the Typikon of Mâr Saba. This description is well preserved from its oldest known Greek testimonies until at least the 13th century. It is notable that this liturgical celebration is the only one depicted in the book that involves the Eucharist. In the article, some partially unedited fragments of the Greek text of three testimonies are presented and analysed, and some reflections and questions are collected at the end in an attempt to shed light on the historical development of this text, which is crucial to our understanding of the history of Byzantine liturgy.
Development of a 4-DoF Active Upper Limb Orthosis
Authors: Durante Francesco , Raparelli Terenziano , Zobel Pierluigi Beomonte
Published: November 2022

In this paper, the designs and manufacturing process of a powered upper limb orthosis are presented. The orthosis is an exoskeleton worn on one arm by the user and fixed to the trunk. The orthosis’ architecture, design, and manufacturing process are presented and discussed. Estimations of the ranges of movement related to daily living activities are presented. The preliminary tests to verify the functionality of the design show encouraging results.
Global Moho Gravity Inversion from GOCE Data: Updates and Convergence Assessment of the GEMMA Model Algorithm
Authors: Rossi Lorenzo , Lu Biao , Reguzzoni Mirko , Sampietro Daniele , Fadel Islam , van der Meijde Mark
Published: November 2022

Since its discovery in 1909, the Moho was routinely studied by seismological methods. However, from the 1950s, a possible alternative was introduced by gravimetric inversion. Thanks to satellite gravity missions launched from the beginning of the 21st century, a global inversion became feasible, e.g., leading to the computation of the GEMMA model in 2012. This model was computed inverting the GOCE second radial derivatives of the anomalous potential by a Wiener filter, which was applied in the spherical harmonic domain, considering a two-layer model with lateral and vertical density variations. Moreover, seismic information was introduced in the inversion to deal with the joint estimation/correction of both density and geometry of the crustal model. This study aims at revising the GEMMA algorithm from the theoretical point of view, introducing a cleaner formalization and studying the used approximations more thoroughly. The updates are on: (1) the management of the approximations due to the forward operator linearization required for the inversion; (2) the regularization of spherical harmonic coefficients in the inversion by proper modelling the Moho signal and the gravity error covariances; (3) the inclusion of additional parameters and their regularization in the Least Squares adjustment to correct the density model by exploiting seismic information. Thanks to these updates, a significant improvement from the computational point of view is achieved too, thus the convergence of the iterative solution and the differences with respect to the previous algorithm can be assessed by closed-loop tests, showing the algorithm performance in retrieving the simulated “true” Moho.
Comparative Study of Marine Ranching Recognition in Multi-Temporal High-Resolution Remote Sensing Images Based on DeepLab-v3+ and U-Net
Authors: Chen Yanlin , He Guojin , Yin Ranyu , Zheng Kaiyuan , Wang Guizhou
Published: November 2022

The recognition and monitoring of marine ranching help to determine the type, spatial distribution and dynamic change of marine life, as well as promote the rational utilization of marine resources and marine ecological environment protection, which has important research significance and application value. In the study of marine ranching recognition based on high-resolution remote sensing images, the convolutional neural network (CNN)-based deep learning method, which can adapt to different water environments, can be used to identify multi-scale targets and restore the boundaries of extraction results with high accuracy. However, research based on deep learning still has problems such as rarely considering the feature complexity of marine ranching and inadequate discussion of model generalization for multi-temporal images. In this paper, we construct a multi-temporal dataset that describes multiple features of marine ranching to explore the recognition and generalization ability of the semantic segmentation models DeepLab-v3+ and U-Net (used in large-area marine ranching) based on GF-1 remote sensing images with a 2 m spatial resolution. Through experiments, we find that the F-score of the U-Net extraction results from multi-temporal test images is basically stable at more than 90%, while the F-score of DeepLab-v3+ fluctuates around 80%. The results show that, compared with DeepLab-v3+, U-Net has a stronger recognition and generalization ability for marine ranching. U-Net can identify floating raft aquaculture areas at different growing stages and distinguish between cage aquaculture areas with different colors but similar morphological characteristics.
Automatic Detection of the Explosive Activity of the Mt. Etna Volcano through Doppler Radar Monitoring
Authors: Giammello Giuseppe , Firetto Carlino Marco , Coltelli Mauro
Published: November 2022

Improving the capability to detect volcanic explosive activity could be strategic for the task of a volcano observatory to inform civil protection authorities and air traffic controllers. The detection of explosive volcanic activity can be done in real time and also under bad visibility conditions by using the radar remote sensing technique. Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV-OE) installed an S-band pulse Doppler radar in a shelter located at about 3 km south of the active volcanic vents in order to enhance the Etna volcano’s surveillance. Here, we describe the realisation of a system that exploits such device, aimed at continuously monitoring the explosive eruptive activity at the Mt. Etna summit craters through an automatic processing flow of the radar data. We analysed the signals recorded during 23 eruptive episodes that occurred at the Etna South-East Crater during the second half of 2021; these episodes were characterised by an opening Strombolian activity and the subsequent evolution into a lava fountain. To identify the onset of both volcanic phenomena, empirical thresholds of radar time series were extracted with the help of thermal and visible images acquired by the INGV-OE cameras’ network. The resulting monitoring tool automatically operates 24/7 for volcanic surveillance, providing real-time data to the INGV-OE control room.
MSA-MOT: Multi-Stage Association for 3D Multimodality Multi-Object Tracking
Authors: Zhu Ziming , Nie Jiahao , Wu Han , He Zhiwei , Gao Mingyu
Published: November 2022

Three-dimensional multimodality multi-object tracking has attracted great attention due to the use of complementary information. However, such a framework generally adopts a one-stage association approach, which fails to perform precise matching between detections and tracklets, and, thus, cannot robustly track objects in complex scenes. To address this matching problem caused by one-stage association, we propose a novel multi-stage association method, which consists of a hierarchical matching module and a customized track management module. Specifically, the hierarchical matching module defines the reliability of the objects by associating multimodal detections, and matches detections with trajectories based on the reliability in turn, which increases the utilization of true detections, and, thus, guides accurate association. Then, based on the reliability of the trajectories provided by the matching module, the customized track management module sets maximum missing frames with differences for tracks, which decreases the number of identity switches of the same object and, thus, further improves the association accuracy. By using the proposed multi-stage association method, we develop a tracker called MSA-MOT for the 3D multi-object tracking task, alleviating the inherent matching problem in one-stage association. Extensive experiments are conducted on the challenging KITTI benchmark, and the results show that our tracker outperforms the previous state-of-the-art methods in terms of both accuracy and speed. Moreover, the ablation and exploration analysis results demonstrate the effectiveness of the proposed multi-stage association method.
Force-Sensorless Identification and Classification of Tissue Biomechanical Parameters for Robot-Assisted Palpation
Authors: Gutierrez-Giles Alejandro , Padilla-Castañeda Miguel A. , Alvarez-Icaza Luis , Gutierrez-Herrera Enoch
Published: November 2022

The implementation of robotic systems for minimally invasive surgery and medical procedures is an active topic of research in recent years. One of the most common procedures is the palpation of soft tissues to identify their mechanical characteristics. In particular, it is very useful to identify the tissue’s stiffness or equivalently its elasticity coefficient. However, this identification relies on the existence of a force sensor or a tactile sensor mounted at the tip of the robot, as well as on measuring the robot velocity. For some applications it would be desirable to identify the biomechanical characteristics of soft tissues without the need for a force/tactile nor velocity sensors. An estimation of such quantities can be obtained by a model-based state observer for which the inputs are only the robot joint positions and its commanded joint torques. The estimated velocities and forces can then be employed for closed-loop force control, force reflection, and mechanical parameters estimation. In this work, a closed-loop force control is proposed based on the estimated contact forces to avoid any tissue damage. Then, the information from the estimated forces and velocities is used in a least squares estimator of the mechanical parameters. Moreover, the estimated biomechanical parameters are employed in a Bayesian classifier to provide further help for the physician to make a diagnosis. We have found that a combination of the parameters of both linear and nonlinear viscoelastic models provide better classification results: 0% misclassifications against 50% when using a linear model, and 3.12% when using only a nonlinear model, for the case in which the samples have very similar mechanical properties.
Phytochemical and Biological Characterization of the Fractions of the Aqueous and Ethanolic Extracts of Parthenium hysterophorus
Authors: Alfaro Jiménez Miguel A. , Zugasti Cruz Alejandro , Silva Belmares Sonia Y. , Ascacio Valdés Juan A. , Sierra Rivera Crystel A.
Published: November 2022

In this study, the fractions of the aqueous (AE) and ethanolic (EE) crude extracts of Parthenium hysterophorus were evaluated for their phytochemical composition, cytotoxic, and antioxidant activity. The two extracts were subjected to a fractionation by vacuum liquid chromatography, obtaining seven fractions for each extract. These fractions were evaluated for the presence of phenolic compounds by reverse phase high performance liquid chromatography coupled to mass spectrometer (RP-HPLC-MS) analysis. Their cytotoxic activity was tested with a hemolysis assay. The antioxidant activity was evaluated with the Trolox equivalent antioxidant capacity (TEAC), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and hydroxyl radical (–OH) scavenging assays. In addition, the effect of the fractions on the activity of the antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT), from human erythrocytes, was evaluated. The phytochemical screening by RP-HPLC-MS mainly showed the presence of flavonoids and hydroxycinnamic acids. The hemolysis assay exhibited a low cytotoxic activity by the fractions of the AE, but the fractions of the EE exhibited a hemolytic effect. The fractions of the AE and EE showed significant antioxidant activity to inhibit radicals in the three radical scavenging assays. Moreover, only some fractions of the AE showed a significant increase in the activity of the SOD enzyme, while the activity of CAT exhibited a significant increase by the fractions of the two extracts. The fractions of the AE and EE of P. hysterophorus have phytochemicals with antioxidant activity to inhibit radicals and increase the activity of in vitro antioxidant enzymes.
Box–Behnken Design Based Development of UV-Reversed Phase High Performance Liquid Chromatographic Method for Determination of Ascorbic Acid in Tablet Formulations
Authors: Azmi Syed Najmul Hejaz , Al Hoqani Umaima , Al Mamari Juhaina Obaid Said , Al Mamari Buthaina Mohamed Salim , Al Jassasi Balaqis Sultan Ali Rashid , Al Rubaiai Aziza Saleh Saif , Rahman Nafisur , Nasir Mohd , Haque Sk Manirul , Khan Shah Alam , Ahmed Qamar Uddin , Zakaria Zainul Amiruddin
Published: November 2022

A simple, sensitive, accurate and inexpensive UV-reversed-phase high-performance liquid chromatographic method was developed for the determination of ascorbic acid in tablet formulations. The method was based on the separation of ascorbic acid using a mobile phase of an acetonitrile-NaH2PO4-H3PO4 buffer solution (pH = 3) (5:95 v/v) with a UV detection wavelength of 245 nm and a flow rate of 0.8 mL min−1 at ambient column temperature. The variables of the proposed method, such as acetonitrile fraction (%), flow rate (mL min−1) and column temperature (°C), were optimized on the peak area by response surface methodology via the Box–Behnken design. The mobile phase was passed isocratically, and the separation of ascorbic acid was performed at the retention time of 4.1 min. A calibration graph was obtained and found to be linear in the concentration range of 10–180 µg mL−1. The method suitability was assessed and an asymmetry factor of 1.15 was obtained. The proposed method was successfully applied for the determination of ascorbic acid in tablet formulations and statistically compared with the results of the reference method. The performance of the proposed method was excellent and in agreement with the reference method. The recovery percentage of the proposed and reference methods was in the range of 99.98–100.04% and showed compliance (100 ± 2%) with regulatory guidelines.
A Fuzzy Rule-Based System to Infer Subjective Noise Annoyance Using an Experimental Wireless Acoustic Sensor Network
Authors: Fernandez-Prieto Jose-Angel , Canada-Bago Joaquin , Birkel Ulrich
Published: November 2022

Over the last few years, several works have been conducted on the design and development of wireless acoustic sensor networks (WASNs) to monitor acoustic noise levels and create noise maps. The information provided by these WASNs is based on the equivalent noise pressure level over time T (Leq,T), which is used to assess the objective noise level. According to some authors, noise annoyance is an inherently vague and uncertain concept, and Leq,T does not provide any information about subjective annoyance to humans. Some fuzzy models have been proposed to model subjective annoyance. However, the use of fuzzy rule-based systems (FRBS) that have been adapted to acoustic sensor node resource limitations in real WASN to provide the degree of subjective noise annoyance in real-time remains a largely unexplored region. In this paper, we present the design and implementation of an FRBS that enables the sensor nodes of a real WASN deployed in the city of Linares (Jaen), Spain to infer the degree of subjective noise annoyance in real-time. The hardware used for the sensor nodes is a commercial model, Arduino Due. The results demonstrate that the sensor nodes have sufficient processing capacity and memory to infer the subjective annoyance in real-time, and the system can correctly detect situations that can be considered more annoying by humans.
Selected Payback Statistical Contributions to Matrix/Linear Algebra: Some Counterflowing Conceptualizations
Authors: Griffith Daniel A.
Published: November 2022

Matrix/linear algebra continues bestowing benefits on theoretical and applied statistics, a practice it began decades ago (re Fisher used the word matrix in a 1941 publication), through a myriad of contributions, from recognition of a suite of matrix properties relevant to statistical concepts, to matrix specifications of linear and nonlinear techniques. Consequently, focused parts of matrix algebra are topics of several statistics books and journal articles. Contributions mostly have been unidirectional, from matrix/linear algebra to statistics. Nevertheless, statistics offers great potential for making this interface a bidirectional exchange point, the theme of this review paper. Not surprisingly, regression, the workhorse of statistics, provides one tool for such historically based recompence. Another prominent one is the mathematical matrix theory eigenfunction abstraction. A third is special matrix operations, such as Kronecker sums and products. A fourth is multivariable calculus linkages, especially arcane matrix/vector operators as well as the Jacobian term associated with variable transformations. A fifth, and the final idea this paper treats, is random matrices/vectors within the context of simulation, particularly for correlated data. These are the five prospectively reviewed discipline of statistics subjects capable of informing, inspiring, or otherwise furnishing insight to the far more general world of linear algebra.
Accounting for China’s Net Carbon Emissions and Research on the Realization Path of Carbon Neutralization Based on Ecosystem Carbon Sinks
Authors: Wang Nuo , Zhao Yuxiang , Song Tao , Zou Xinling , Wang Erdan , Du Shuai
Published: November 2022

Carbon sinks are an important way to achieve carbon neutrality. In this study, carbon emissions in each year from 2019 to 2060 were predicted by constructing the LEAP (Long-range Energy Alternatives Planning System)-China model. The ecosystem carbon sinks in five representative years of 2012, 2017, 2019, 2030, and 2060 were predicted by reviewing related literature to calculate China’s net carbon emission accounts in these five key years and to quantitatively analyze the path to achieving carbon neutrality in China. The results show that China’s annual carbon emissions will peak in 2028, with a peak of 10.27 billion tons of carbon dioxide; that they will then decrease year by year to 7227 million tons of carbon dioxide in 2060; and that the ecosystem carbon sinks generated by land use are more stable, with a total of approximately 5.5 billion tons of carbon dioxide. To achieve carbon neutrality, a dependence only on ecosystem carbon sinks is insufficient. National energy conservation, voluntary emission reduction by enterprises, and a reliance on new energy and new technologies are needed to ensure the final implementation of China’s carbon neutrality strategy.
High-Quality Development Evaluation and Spatial Evolution Analysis of Urban Agglomerations in the Middle Reaches of the Yangtze River
Authors: Xie Zhongqi , Zhang Ying , Fang Zhiqiang
Published: November 2022

Urban agglomeration in the middle reaches of the Yangtze River is key to the rise of central China, and an important engine for the high-quality development of the Yangtze River economic belt. Research on urban agglomeration in the middle reaches of the Yangtze River focuses mainly on economic development, ecological environment, and innovation. Few studies focus on evaluation combining development levels. This study uses the entropy weight TOPSIS method to build an urban high-quality development level indicator system with “innovation, coordination, greenness, openness, and sharing” as the indicators, comprehensively measuring the high-quality development level of 31 cities in the middle reaches of the Yangtze River from 2010 to 2019 and analyzing the evolution of spatial distribution and autocorrelation. The results show that the high-quality development level of the urban agglomeration in the middle reaches of the Yangtze River varies greatly, and fluctuations are significant. The spatial distribution also shows an evolution from belt-shaped agglomeration to point-shaped diffusion distribution, and the spatial autocorrelation shows a negative correlation. Finally, this paper proposes suggestions to promote high-quality development from three aspects: system coordination, industry coordination, and sustainability.
Climate Change and Inflation in Eastern and Southern Africa
Authors: Odongo Maureen Teresa , Misati Roseline Nyakerario , Kamau Anne Wangari , Kisingu Kethi Ngoka
Published: November 2022

This study analyzes the dynamics of key climate change indicators and their implications on food prices in Eastern and Southern African Countries. The study uses descriptive and quantitative analysis of monthly data covering ten countries over the period 2001 to 2020. The descriptive analysis reveals that the sampled countries have experienced various climate change events with increasing intensity in the last two decades. Additionally, three of the countries in the sample ranked in the list of countries most affected by extreme weather events in 2019 are at risk of either frequent events or rare but extraordinary catastrophes. The quantitative analysis showed that supply shocks measured using rainfall amounts and imported food price inflation are the main determinants of food inflation, whereas oil prices, subsidies, and imported inflation are the key determinants of overall inflation. At a macro level, the analysis shows that all countries have various climate change policy initiatives in place but are still vulnerable to climate change risks. This implies a need for sector-specific climate change policy options that are most effective. In addition, the adoption of renewable sources of power such as wind and solar and appropriate irrigation practices is important.
Soil Quality Index of Young and Differently Managed Almond Orchards under Mediterranean Conditions
Authors: Mirás-Avalos José Manuel , Marco Pedro , Sánchez Sergio , Bielsa Beatriz , Rubio Cabetas María José , González Vicente
Published: November 2022

Sustainable agriculture has drawn attention to the maintenance and enhancement of soil health. However, research on soil quality has been carried out mainly in field crops and, to a lesser extent, in mature orchards, neglecting the relevance of assessing the soil quality status in the first years of tree plantations. Therefore, the aim of this study was to assess the soil quality index of young almond orchards located in marginal lands and managed under different practices. The survey was carried out in the Teruel Province (Northeast Spain), in three almond orchards: Alacón (2 years old, 0.75 ha, rainfed, conventionally managed), San Martín (1 year old, 0.4 ha, irrigated, organically managed), and Valdealgorfa (6 years old, 0.2 ha, rainfed, organically managed). The composite soil samples were taken from three spots within each orchard. To determine the soil quality index, four main soil functions were considered: filtering and buffering, nutrient supply, water relations, and crop limitation. The soil quality indices were 0.55, 0.75, and 0.54 for Alacón, San Martín, and Valdealgorfa orchards, respectively. These values suggested that the evaluated soils are adequate for almond production, although they require management actions to improve their quality (for instance, the application of organic amendments) and increase the sustainability of these agroecosystems. Furthermore, this work provides a framework for the assessment of the soil quality in tree orchards at a young stage.
Comprehensive Evaluation of Sustainable Development of Entrepreneurship Education in Chinese Universities Using Entropy–TOPSIS Method
Authors: Cai Xu , Zhao Lei , Bai Xuchen , Yang Zihan , Jiang Yujia , Wang Peng , Huang Zhaoxin
Published: November 2022

A comprehensive evaluation is important for the sustainable development of entrepreneurship education in colleges and universities. Specifically, evaluating entrepreneurship education in colleges and universities from the perspective of teachers, as stakeholders of entrepreneurship education in colleges and universities, can provide a basis for decision making to improve the quality of entrepreneurship education. Using the improved entropy–TOPSIS method, this study selects 35 indicators from five aspects, namely, curriculum systems, organizational leadership, faculty construction, teaching management, and an institutional guarantee, to establish a sustainable and comprehensive evaluation framework for entrepreneurship education in colleges and universities. Survey data from a questionnaire of college teachers in 11 provinces (cities) in China’s Yangtze River economic zone are used. The objective is to propose a framework that enables a comprehensive evaluation of the sustainability of entrepreneurship education and to develop a new evaluation method that highlights the challenges in evaluating the sustainability of entrepreneurship education, including the selection and effective measurement of the evaluation criteria. The study provides a scientific basis and support for decision making on the optimal reform of entrepreneurship education, faculty allocation, and education methods in Chinese universities and contributes to the realization of the goal of sustainable development of entrepreneurship education in universities.
Artichoke By-Products Valorization for Phenols-Enriched Fresh Egg Pasta: A Sustainable Food Design Project
Authors: Amoriello Tiziana , Mellara Francesco , Ruggeri Stefania , Ciorba Roberto , Ceccarelli Danilo , Ciccoritti Roberto
Published: November 2022

More healthy and sustainable food are nowadays desirable to improve human health and protect the planet’s resources. From this perspective, the aim of this study is to investigate artichoke (Cynara scolymus L.) by-products as a potential source of phenolic compounds and to use these compounds to design new fresh egg pasta formulation. Sustainable extraction was carried out using ultrasound-assisted extraction (UAE) and chemometric techniques, such as the Response Surface Methodology (RSM). UAE process parameters (temperature and time) and solvent composition (ethanol aqueous mixtures) were optimized using a three-level Box–Behnken design, in order to carry out the maximum yield in phenols. Under the optimal conditions (temperature: 60 °C; time: 60 min; solvent: 50% ethanol:water), the amount of phenolics (TPC) was 22.4 ± 0.2 mg GAE g−1 d.w., characterized mainly by dicaffeoylquinic acid (32.8 ± 0.6 mg CAE g−1 d.w.) and chlorogenic acid (14.1 ± 0.2 mg CAE g−1 d.w.). Hence, the polyphenols extract was used as an ingredient to design a new formulation of functional fresh egg pasta. Four recipes with soft wheat and semolina (P1 and P2) and with soft wheat alone (P3 and P4) were prepared. Compared with control pastas (P1 and P3), the enriched ones (P2 and P4) showed a higher polyphenol content, especially for P4 (1.86 ± 0.03 mg GAE g−1 d.w. for P1, 2.05 ± 0.02 mg GAE g−1 d.w. for P2, 1.92 ± 0.03 mg GAE g−1 d.w. for P3, 2.04 ± 0.02 mg GAE g−1 d.w. for P4). A high decrease in TPC was observed as a result of the cooking process, especially for the two control formulations (−71% for P1 and −70% for P3) in comparison with P2 (−64%) and P4 (−55%). At last, to assess the antimicrobial effect of artichoke by-products on fresh pasta and to monitor its spoilage, we used image analysis. Corresponding to a higher TPC content, P2 and P4 showed an extended shelf life of 16% and 33%, respectively, probably due to the antioxidant activity of artichoke. The new fresh egg pasta enriched with polyphenols extracted from artichoke by-products showed very good nutritional and technological characteristics, even after cooking, confirming the good potentiality of artichoke by-products in the design of new, healthy, and sustainable food products.
Evaluating Enterprise Resource Planning (ERP) Implementation for Sustainable Supply Chain Management
Authors: Qureshi Mohamed Rafik Noor Mohamed
Published: November 2022

Enterprise Resource Planning (ERP) plays a vital role in an organization’s growth and sustainability in the supply chain. ERP implementations have a mix of critical success factors (CSFs) that are very important. Hence, it is essential to study the CSFs, their mutual influence and their severity in terms of prioritization for the I4.0. The goal of the current study is to identify CSFs for ERP implementations, as well as their interdependence and ranking. The CSFs of ERP deployment were discovered by a thorough analysis of the literature and subsequent input from a group of subject matter experts. Using the interpretive structural modeling (ISM) method, the shortlisted CSFs were modeled, and after that, the matrice d’ impacts croises multiplication appliqué an classement (MICMAC) analysis was used to classify them. The interpretative ranking technique was used to carry out the subsequent prioritization and ranking (IRP). In the present research, the modeling of CSFs for successful ERP implementations was carried out to accomplish much-needed sustainability in the supply chain. The result revealed the three top-ranked CSFs for successful ERP implementations: “Top management support”, “Change management” and “Business process reengineering.” This research can help practicing managers prepare an ERP implementation plan to accomplish sustainability in SCM. Each CSF’s role can be studied in terms of the mutual relationships for its control. This research can also help in prioritizing strategies for optimizing the resources required for ERP implementations.
Development of Meso- and Macro-Pore Carbonization Technology from Biochar in Treating the Stumps of Representative Trees in Taiwan
Authors: Lee Shih-Chi , Kitamura Yutaka , Chien Chuan-Chi , Cheng Chun-Shen , Cheng Jen-Hao , Tsai Shu-Hsien , Hsieh Chin-Cheng
Published: November 2022

This study uses the tree stumps of the three representative trees in Taiwan (Leucaena leucocephala, Syzygium samarangense, and Ziziphus jujuba) as the material source and recyclable oyster shell powder as an activator. A carbonization process for upgrading and recycling the tree stumps was developed with our homemade, digital-controlled, energy-saving carbonization system. First, the tree stumps are carbonized at a medium temperature of 500 °C and then heated to 900 °C for high-temperature carbonization, followed by the activation procedure as required. With our method, we can produce biochar with a high proportion of fixed carbon and a high proportion of meso- and macropores while maximizing the yield of wood vinegar. The specific surface area of the meso- and macropores can reach up to 70 m2/g or more. The effect of different activation materials on the pore characteristics and specific surface area of biochar was carefully examined. It was found that both KOH and oyster shell powder is the ideal activator for producing biochar with a high proportion of meso- and macropores. The FTIR spectrum, CEC, and contents of the ordinary elements and heavy metals of the biochar were also reported. It is clear from the FTIR data that the absorption peaks of the overall spectrum of the three types of biochar after carbonization at high temperature are cleaner than those of biochar carbonized at low temperature. This research can promote the recycling of agricultural residues, enhance soil carbon sequestration, preserve fertilizers, and suppress diseases and pests, moving towards approaching the goal of net-zero carbon emissions.
Review of Recent Developments in Microgrid Energy Management Strategies
Authors: Shafiullah Md , Refat Akib Mostabe , Haque Md Ershadul , Chowdhury Dewan Mabrur Hasan , Hossain Md Sanower , Alharbi Abdullah G. , Alam Md Shafiul , Ali Amjad , Hossain Shorab
Published: November 2022

The grid integration of microgrids and the selection of energy management systems (EMS) based on robustness and energy efficiency in terms of generation, storage, and distribution are becoming more challenging with rising electrical power demand. The problems regarding exploring renewable energy resources with efficient and durable energy storage systems demand side management and sustainable solutions to microgrid development to maintain the power system’s stability and security. This article mainly focuses on the overview of the recent developments of microgrid EMS within the control strategies and the implementation challenges of the microgrid. First, it provides energy management strategies for the major microgrid components, including load, generation, and energy storage systems. Then, it presents the different optimization approaches employed for microgrid energy management, such as classical, metaheuristic, and artificial intelligence. Moreover, this article sheds light on the major implementation challenges of microgrids. Overall, this article provides interactive guidelines for researchers to assist them in deciding on their future research.
Independent Innovation or Secondary Innovation: The Moderating of Network Embedded Innovation
Authors: Cao Bing , Han Zishu , Liang Ling , Liu Yuanyuan , Wang Jialiang , Xie Jiaping
Published: November 2022

Based on the provincial data of China’s high-tech industries from 2009 to 2019, this paper constructs a stepwise regression to analyze the effect of innovation inputs, independent and secondary innovation, and innovation value, while being mediated and moderated by innovation ability and innovation network, respectively. We found that in general, innovation inputs had a significant positive direct effect on innovation valuation: a one unit increase of independent innovation increased 0.60 units of innovation valuation, and a one unit increase of secondary innovation input increased 0.78 units of innovation valuation. Innovation ability was found to be a partial mediator for independent innovation (0.74), and a complete mediator for secondary innovation (0.90). Finally, the innovation network showed significant moderating effects in both innovation input methods. Empirical research indicates that China is entering an era shifting from secondary innovation to independent innovation, and Chinese high-tech companies should focus on independent innovation.
Predicting the Impact of Construction Rework Cost Using an Ensemble Classifier
Authors: Mostofi Fatemeh , Toğan Vedat , Ayözen Yunus Emre , Behzat Tokdemir Onur
Published: November 2022

Predicting construction cost of rework (COR) allows for the advanced planning and prompt implementation of appropriate countermeasures. Studies have addressed the causation and different impacts of COR but have not yet developed the robust cost predictors required to detect rare construction rework items with a high-cost impact. In this study, two ensemble learning methods (soft and hard voting classifiers) are utilized for nonconformance construction reports (NCRs) and compared with the literature on nine machine learning (ML) approaches. The ensemble voting classifiers leverage the advantage of the ML approaches, creating a robust estimator that is responsive to underrepresented high-cost impact classes. The results demonstrate the improved performance of the adopted ensemble voting classifiers in terms of accuracy for different cost impact classes. The developed COR impact predictor increases the reliability and accuracy of the cost estimation, enabling dynamic cost variation analysis and thus improving cost-based decision making.
Research on Prediction of Coal Sample Deformation Based on Acoustic-Emission Sensitive Index
Authors: Wang Man , Zhang Jianguo , Jia Bing , Du Weihang , Chen Zhaofan , Liu Shuaitao
Published: November 2022

Establishing the relationship between the deformation of coal samples and acoustic emission response is the basis for the deformation prediction of coal samples. Using a combination of laboratory tests and theoretical analysis, acoustic emission tests of the uniaxial loading process were conducted on coal samples in the study area and the test results were analyzed, focusing on the rule of variation of acoustic emission counts with loading time. Based on the analysis of stress, strain, time, and acoustic-emission parameters variation, the relationship between the deformation of coal samples and acoustic emission response was established and analyzed. The analysis results show that during the loading process, the acoustic emission counts show the characteristics of stage changes, which can be divided into three stages: the initial stage with sporadic acoustic emission events, the middle stage with a stable increase of acoustic emission events, and the final stage with the rapid increase of acoustic emission events. This stage division has good consistency with the deformation stages of coal samples. Moreover, the acoustic emission counts have obvious and easily identifiable characteristics of changes in the deformation process of coal samples. The acoustic emission count can be used as a sensitive indicator in this study area to predict the deformation of coal samples. It provides a reference for the application of acoustic-emission prediction technology in this study area, which is important to improve the accuracy of geohazard prediction.
Customer Satisfaction in e-Commerce during the COVID-19 Pandemic
Authors: Ilieva Galina , Yankova Tania , Klisarova Stanislava , Dzhabarova Yulia
Published: November 2022

The declared state of emergency and the measures taken against the spread of coronavirus by governments have increased Internet shopping. All companies, regardless of size and type of business activity, had to adapt their business models to the new circumstances through transformation of their business processes and offering products or services tailored to the changing customer behavior. This study aims to analyze the peculiarities of online sales during the COVID-19 health crisis via the integration of classic and modern data analysis methods. The purpose of the paper is to identify the main factors determining user behavior and examine their impact on customer satisfaction in e-commerce. The survey method and structural equation modeling (SEM) were used to recognize the dependencies between variables from the online users’ perspective. The satisfaction determinants indicated and described in the paper affect differently the perceived value for the customers. As this value is subjective and dynamic, this study developed a reliable system for e-commerce factor evaluation. Using the proposed methodology, companies can constantly monitor and assess indicators influencing customer satisfaction and gain awareness of consumer behavior’s dynamics in online shopping. e-commerce marketers can employ the obtained results to decide how to organize order execution and optimize supply chains. Identifying the most important components of the e-commerce value, managers of online retailers can better run online sales platforms, increase customer loyalty, and thus, improve company’s online performance.
FDG-PET/MRI for Nonoperative Management of Rectal Cancer: A Prospective Pilot Study
Authors: Ince Semra , Itani Malak , Henke Lauren E. , Smith Radhika K. , Wise Paul E. , Mutch Matthew G. , Glasgow Sean C. , Silviera Matthew L. , Pedersen Katrina S. , Hunt Steven R. , Kim Hyun , Fraum Tyler J.
Published: November 2022

Nonoperative management (NOM) is increasingly utilized for rectal cancer patients with a clinical complete response (cCR) following total neoadjuvant therapy (TNT). The objective of this pilot study was to determine whether FDG-PET/MRI alters clinical response assessments among stage I-III rectal cancer patients undergoing TNT followed by NOM, relative to MRI alone. This prospective study included 14 subjects with new rectal cancer diagnoses. Imaging consisted of FDG-PET/MRI for initial staging, post-TNT restaging, and surveillance during NOM. Two independent readers assessed treatment response on MRI followed by FDG-PET/MRI. Inter-reader differences were resolved by consensus review. The reference standard for post-TNT restaging consisted of surgical pathology or clinical follow-up. 7/14 subjects completed post-TNT restaging FDG-PET/MRIs. 5/7 subjects had evidence of residual disease and underwent total mesorectal excision; 2/7 subjects had initial cCR with no evidence of disease after 12 months of NOM. FDG-PET/MRI assessments of cCR status at post-TNT restaging had an accuracy of 100%, compared with 71% for MRI alone, as FDG-PET detected residual tumor in 2 more subjects. Inter-reader agreement for cCR status on FDG-PET/MRI was moderate (kappa, 0.56). FDG-PET provided added value in 82% (9/11) of restaging/surveillance scans. Our preliminary data indicate that FDG-PET/MRI can detect more residual disease after TNT than MRI alone, with the FDG-PET component providing added value in most restaging/surveillance scans.
A New Recombinant Multiepitope Chimeric Protein of Leptospira interrogans Is a Promising Marker for the Serodiagnosis of Leptospirosis
Authors: Fernandes Luis G. V. , Avelar Kátia E. S. , Romero Eliete C. , Heinemann Marcos B. , Kirchgatter Karin , Nascimento Ana L. T. O.
Published: November 2022

The zoonotic disease leptospirosis is caused by pathogenic species of the genus Leptospira and was recently included in the list of Neglected Diseases by the World Health Organization. Leptospirosis burden is estimated to have over a million human cases and cause 60 thousand deaths annually, in addition to its economic impact and veterinary concern. The microscopic agglutination test (MAT), recommended by the World Health Organization, exhibits reduced sensitivity at the beginning of the disease, in addition to being technically difficult. New recombinant antigens are being pursued for rapid and specific serodiagnostic tests, especially in the initial phase of the disease, and chimeric multiepitope proteins are a strategy with a great potential to be implemented in serology. Based on previous subproteomic results, we designed a synthetic construct comprising 10 conserved leptospiral surface antigens, and the recombinant protein was purified and evaluated regarding its diagnostic potential. The protein termed rChi2 was recognized by antibodies in serum from patients both at the onset (MAT−) and in the convalescent (MAT+) phase in 75 and 82% of responders, respectively. In addition, rChi2 immunization in hamsters elicited a strong humoral response, and anti-rChi2 antibodies recognized several immobilized intact Leptospira species, validating its potential as an early, broad, and cross-reactive diagnostic test.
Quality and Integrated Service Delivery: A Cross-Sectional Study of the Effects of Malaria and Antenatal Service Quality on Malaria Intervention Use in Sub-Saharan Africa
Authors: Lee Elizabeth H. , Mancuso James D. , Koehlmoos Tracey , Stewart V. Ann , Bennett Jason W. , Olsen Cara
Published: November 2022

Using regionally linked facility and household surveys, we measured the quality of integrated antenatal care and malaria in pregnancy services in Kenya, Namibia, Senegal, and Tanzania. We examined country heterogeneities for the association of integrated antenatal and malaria service quality scores with insecticide-treated bed net (ITN) use in pregnant women and children under-five and intermittent preventive treatment in pregnancy (IPTp-2) uptake. Malaria in pregnancy service quality was low overall. Our findings suggest modest, positive associations between malaria in pregnancy quality and ITN use and IPTp-2 uptake across pooled models and for most studied countries, with evidence of heterogeneity in the strength of associations and relevant confounding factors. Antenatal care quality generally was not associated with the study outcomes, although a positive interaction with malaria in pregnancy quality was present for pooled ITN use models. The improved quality of malaria services delivered during formal antenatal care can help address low coverage and usage rates of preventive malaria interventions in pregnancy and childhood. Study findings may be used to target quality improvement efforts at the sub-national level. Study methods may be adapted to identify low-performing facilities for intervention and adaption to other areas of care, such as HIV/AIDS, child immunizations, and postnatal care.