bluuebunny/crossref_metadata_2025 huggingface dataset:
A Systematic Review of Methodology Used in Studies Aimed at Creating Charts of Fetal Brain Structures
Authors: Donadono Vera , Cavallaro Angelo , Roberts Nia W. , Ioannou Christos , Papageorghiou Aris T. , Napolitano Raffaele
Published: May 2021

Ultrasound-based assessment of the fetal nervous system is routinely recommended at the time of the mid-trimester anatomy scan or at different gestations based on clinical indications. This review evaluates the methodological quality of studies aimed at creating charts for fetal brain structures obtained by ultrasound, as poor methodology could explain substantial variability in percentiles reported. Electronic databases (MEDLINE, EMBASE, Cochrane Library, and Web of Science) were searched from January 1970 to January 2021 to select studies on singleton fetuses, where the main aim was to construct charts on one or more clinically relevant structures obtained in the axial plane: parieto-occipital fissure, Sylvian fissure, anterior ventricle, posterior ventricle, transcerebellar diameter, and cisterna magna. Studies were scored against 29 predefined methodological quality criteria to identify the risk of bias. In total, 42 studies met the inclusion criteria, providing data for 45,626 fetuses. Substantial heterogeneity was identified in the methodological quality of included studies, and this may explain the high variability in centiles reported. In 80% of the studies, a high risk of bias was found in more than 50% of the domains scored. In conclusion, charts to be used in clinical practice and research should have an optimal study design in order to minimise the risk of bias and to allow comparison between different studies. We propose to use charts from studies with the highest methodological quality.
Significance of Lung Ultrasound in Patients with Suspected COVID-19 Infection at Hospital Admission
Authors: Gutsche Holger , Lesser Thomas G. , Wolfram Frank , Doenst Torsten
Published: May 2021

With a lung ultrasound (LUS) the typical findings are interstitial pneumonia. COVID-19 pneumonia is often manifested in sub-pleural areas, which is preferably detected by sonography. An RT-PCR test cannot always ensure a safe differentiation of COVID-19- and non-diseased cases. Clinically challenging is that a reliable and time efficient decision regarding COVID-19 suspects requiring isolation. Therefore, this study was aimed at evaluating the significance of LUS in symptomatic patients with COVID-19 suspicion at hospital admission. A total of 101 patients admitted to a suspect ward with COVID-19-typical symptoms were assessed. All patients received prospectively a standardized LUS at admission. Patients were classified as LUS-positive and -negative cases based on a specific LUS score. The RT-PCR test in combination with the clinical findings served as a reference. Correctly classified were 14/15 COVID-19 diseased suspects as LUS-positive (sensitivity: 93.3%). Twenty-seven out of 61 non-positive cases were classified as false positive with LUS (specificity: 55.7%). In 34/35 patients who were assessed as LUS negative, no COVID-19 disease was detected during the hospitalization. The PPV and NPV of the LUS were 34.1% and 97.1%. LUS is a valuable tool in symptomatic patients for the assessment of COVID-19-disease. The high negative predictive value of LUS is helpful to rule out the disease.
Application of the Interaction between Tissue Immunohistochemistry Staining and Clinicopathological Factors for Evaluating the Risk of Oral Cancer Progression by Hierarchical Clustering Analysis: A Case-Control Study in a Taiwanese Population
Authors: Wang Hui-Ching , Chou Meng-Chun , Wu Chun-Chieh , Chan Leong-Perng , Moi Sin-Hua , Pan Mei-Ren , Liu Ta-Chih , Yang Cheng-Hong
Published: May 2021

The aim of this single-center case-control study is to investigate the feasibility and accuracy of oral cancer protein risk stratification (OCPRS) to analyze the risk of cancer progression. All patients diagnosed with oral cancer in Taiwan, between 2012 and 2014, and who underwent surgical intervention were selected for the study. The tissue was further processed for immunohistochemistry (IHC) for 21 target proteins. Analyses were performed using the results of IHC staining, clinicopathological characteristics, and survival outcomes. Novel stratifications with a hierarchical clustering approach and combinations were applied using the Cox proportional hazard regression model. Of the 163 participants recruited, 102 patients were analyzed, and OCPRS successfully identified patients with different progression-free survival (PFS) profiles in high-risk (53 subjects) versus low-risk (49 subjects) groups (p = 0.012). OCPRS was composed of cytoplasmic PLK1, phosphoMet, and SGK2 IHC staining. After controlling for the influence of clinicopathological features, high-risk patients were 2.33 times more likely to experience cancer progression than low-risk patients (p = 0.020). In the multivariate model, patients with extranodal extension (HR = 2.66, p = 0.045) demonstrated a significantly increased risk for disease progression. Risk stratification with OCPRS provided distinct PFS groups for patients with oral cancer after surgical intervention. OCPRS appears suitable for routine clinical use for progression and prognosis estimation.
Shear Wave Elastography in the Detection of Sinusoidal Obstruction Syndrome in Adult Patients Undergoing Allogenic Hematopoietic Stem Cell Transplantation
Authors: Schulz Marten , Vuong Lam Giang , Müller Hans Peter , Maibier Martin , Tacke Frank , Blau Igor Wolfgang , Wree Alexander
Published: May 2021

Hepatic sinusoidal obstruction syndrome (SOS), also known as veno-occlusive disease (VOD) can be a life-threatening complication after hematopoietic stem cell transplantation (HSCT). Diagnosis is often difficult and traditionally based on clinical parameters. Shear wave elastography (SWE) is a modern non-invasive liver stiffness measurement technique using ultrasound. In this monocentric study, we evaluated the role of SWE in diagnosing SOS/VOD in 63 adult patients undergoing HSCT from February 2020 to August 2020 in real world settings. Three patients developed SOS/VOD. This was accompanied by an increase in shear wave velocity in all three patients, indicating that this method may contribute to establishing the diagnosis SOS/VOD after HSCT.
Hepatobiliary Scintigraphy and Glass 90Y Radioembolization with Personalized Dosimetry: Dynamic Changes in Treated and Nontreated Liver
Authors: Allimant Carole , Deshayes Emmanuel , Kafrouni Marilyne , Santoro Lore , de Verbizier Delphine , Fourcade Marjolaine , Cassinotto Christophe , Hermida Margaux , Guillot Chloé , Mariano-Goulart Denis , Guiu Boris
Published: May 2021

Background: The functional changes that occur over time in the liver following 90Y-radioembolization (RE) using personalized dosimetry (PD) remain to be investigated. Methods: November 2016–October 2019: we retrospectively included hepatocellular carcinoma (HCC) patients treated by 90Y-glass RE using PD, who underwent hepatobiliary scintigraphy (HBS) at baseline and at 15 days, 1, 2, 3, and 6 months after RE. Results: There were 16 patients with unilobar disease (100%) included, and 64 HBS were performed. Whole liver function significantly decreased over time. The loss was maximal at 2 weeks: −32% (p = 0.002) and remained below baseline at 1 (−15%; p = 0.002), 2 (−25%; p < 0.001), and 3 months (−16%; p = 0.027). No radioembolization-induced liver disease was observed. Treated liver function strongly decreased to reach −64% (p < 0.001) at 2 months. Nontreated liver function decreased at 2 weeks (−21%; p = 0.027) and remained below baseline before reaching +20% (p = 0.002) and +59% (p < 0.001) at 3 and 6 months, respectively. Volumetric and functional changes exhibited parallel evolutions in the treated livers (p = 0.01) but independent evolutions in the nontreated livers (p = 0.08). Conclusion: RE using PD induces significant regional changes in liver function over time. As early as 15 days following RE, both the treated and nontreated livers showed a decreased function. Nontreated liver function recovered after 3 months and greatly increased afterwards.
Improvement of Contact Tracing with Citizen’s Distributed Risk Maps
Authors: Rebollo Miguel , Benito Rosa María , Losada Juan Carlos , Galeano Javier
Published: May 2021

The rapid spread of COVID-19 has demonstrated the need for accurate information to contain its diffusion. Technological solutions are a complement that can help citizens to be informed about the risk in their environment. Although measures such as contact traceability have been successful in some countries, their use raises society’s resistance. This paper proposes a variation of the consensus processes in directed networks to create a risk map of a determined area. The process shares information with trusted contacts: people we would notify in the case of being infected. When the process converges, each participant would have obtained the risk map for the selected zone. The results are compared with the pilot project’s impact testing of the Spanish contact tracing app (RadarCOVID). The paper also depicts the results combining both strategies: contact tracing to detect potential infections and risk maps to avoid movements into conflictive areas. Although some works affirm that contact tracing apps need 60% of users to control the propagation, our results indicate that a 40% could be enough. On the other hand, the elaboration of risk maps could work with only 20% of active installations, but the effect is to delay the propagation instead of reducing the contagion. With both active strategies, this methodology is able to significantly reduce infected people with fewer participants.
Introduction to the Physics of Ionic Conduction in Narrow Biological and Artificial Channels
Authors: Luchinsky Dmitry G. , McClintock Peter V. E.
Published: May 2021

“There is plenty of room at the bottom” [...]
How Important Is Future Teachers’ “Connectedness to Nature”? Adaptation and Validation of the Connectedness to Nature Scale
Authors: Anđić Dunja , Šuperina Lorena
Published: May 2021

The teacher plays a key role in fostering sustainability and implementing Education for Sustainable Development at school. This paper presents a study aimed at adapting and validating a shorter version of the Connectedness to Nature Scale (CNS) to measure student future teachers’ connectedness to nature. The scale has been translated into Croatian in an abbreviated form and applied to a specific sample of students from the Faculty of Teacher Education in Rijeka, Croatia (N = 138). One of the tasks was to examine whether there are statistically significant differences among students regarding their membership in eco-associations and previous participation in an Environmental Education/Education for Sustainable Development (EE/ESD) course. A special research objective was to determine the extent to which the current education and membership in an eco-association explain the connectedness to nature. In addition to the indicated research limitations, the results confirmed the significant measured characteristics of the scale. Education has so far proved to be a predictor of connectedness to nature. Additionally, the results showed that membership in an eco-association is a predictor of connectedness to nature. Based on the obtained results, it is possible to conclude that the connectedness to nature must be further explored, especially in the context of the initial education of future teachers, as a possible prerequisite for a successful practice of Education for Sustainable Development in schools.
Detailed Analysis on Generating the Range Image for LiDAR Point Cloud Processing
Authors: Wu Tao , Fu Hao , Liu Bokai , Xue Hanzhang , Ren Ruike , Tu Zhiming
Published: May 2021

Range images are commonly used representations for 3D LiDAR point cloud in the field of autonomous driving. The approach of generating a range image is generally regarded as a standard approach. However, there do exist two different types of approaches to generating the range image: In one approach, the row of the range image is defined as the laser ID, and in the other approach, the row is defined as the elevation angle. We named the first approach Projection By Laser ID (PBID), and the second approach Projection By Elevation Angle (PBEA). Few previous works have paid attention to the difference of these two approaches. In this work, we quantitatively analyze these two different approaches. Experimental results show that the PBEA approach can obtain much smaller quantization errors than PBID, and should be the preferred choice in reconstruction-related tasks. If PBID is chosen for use in recognition-related tasks, then we have to tolerate its larger quantization error.
Analysis of Dual-Band Direction of Arrival Estimation in Multipath Scenarios
Authors: Cidronali Alessandro , Ciervo Edoardo , Collodi Giovanni , Maddio Stefano , Passafiume Marco , Pelosi Giuseppe
Published: May 2021

The present paper analyzes the performance of localization systems, based on dual-band Direction of Arrival (DoA) approach, in multi-path affected scenarios. The implemented DoA estimation, which belongs to the so-called Space and Frequency Division Multiple Access (SFDMA) technique, takes advantage of the use of two uncorrelated communication carrier frequencies, as already demonstrated by the authors. Starting from these results, this paper provides, first, the methodology followed to describe the localization system in the proposed simulation environment, and, as a second step, describes how multi-path effects may be taken into account through a set of full-wave simulations. The latter follows an approach based on the two-ray model. The validation of the proposed approach is demonstrated by simulations over a wide range of virtual scenarios. The analysis of the results highlights the ability of the proposed approach to describe multi-path effects and confirms enhancements in DoA estimation as experimentally evaluated by the same authors. To further assess the performance of the aforementioned simulation environment, a comparison between simulated and measured results was carried out, confirming the capability to predict DoA performance.
Resilience Evaluation of Multi-Path Routing against Network Attacks and Failures
Authors: An Hyok , Na Yoonjong , Lee Heejo , Perrig Adrian
Published: May 2021

The current state of security and availability of the Internet is far from being commensurate with its importance. The number and strength of DDoS attacks conducted at the network layer have been steadily increasing. However, the single path (SP) routing used in today’s Internet lacks a mitigation scheme to rapidly recover from network attacks or link failure. In case of a link failure occurs, it can take several minutes until failover. In contrast, multi-path routing can take advantage of multiple alternative paths and rapidly switch to another working path. According to the level of available path control, we classfy the multi-path routing into two types, first-hop multi-path (FMP) and multi-hop multi-path (MMP) routing. Although FMP routing supported by networks, such as SD-WAN, shows marginal improvements over the current SP routing of the Internet, MMP routing supported by a global Internet architecture provides strong improvement under network attacks and link failure. MMP routing enables changing to alternate paths to mitigate the network problem in other hops, which cannot be controlled by FMP routing. To show this comparison with practical outcome, we evaluate network performance in terms of latency and loss rate to show that MMP routing can mitigate Internet hazards and provide high availability on global networks by 18 participating ASes in six countries. Our evaluation of global networks shows that, if network attacks or failures occur in other autonomous systems (ASes) that FMP routing cannot avoid, it is feasible to deal with such problems by switching to alternative paths by using MMP routing. When the global evaluation is under a transit-link DDoS attack, the loss rates of FMP that pass the transit-link are affected significantly by a transit-link DDoS attack, but the other alternative MMP paths show stable status under the DDoS attack with proper operation.
Intelligent Mirai Malware Detection for IoT Nodes
Authors: Palla Tarun Ganesh , Tayeb Shahab
Published: May 2021

The advancement in recent IoT devices has led to catastrophic attacks on the devices resulting in breaches in user privacy and exhausting resources of various organizations, so that users and organizations expend increased time and money. One such harmful malware is Mirai, which has created worldwide recognition by impacting the digital world. There are several ways to detect Mirai, but the Machine Learning approach has proved to be accurate and reliable in detecting malware. In this research, a novel-based approach of detecting Mirai using Machine Learning Algorithm is proposed and implemented in Matlab and Python. To evaluate the proposed approaches, Mirai and Benign datasets are considered and training is performed on the dataset comprised of a Training set, Cross-Validation set and Test set using Artificial Neural Network (ANN) consisting of neurons in the hidden layer, which provides consistent accuracy, precision, recall and F-1 score. In this research, an accurate number of hidden layers and neurons are chosen to avoid the problem of Overfitting. This research provides a comparative analysis between ANN and Random Forest models of the dataset formed by merging Mirai and benign datasets of the Mirai malware detection pertaining to seven IoT devices. The dataset used in this research is “N-BaIoT” dataset, which represents data in the features infected by Mirai Malware. The results are found to be accurate and reliable as the best performance was achieved with an accuracy of 92.8% and False Negative rate of 0.3% and F-1 score of 0.99. The expected outcomes of this project, include major findings towards cost-effective Learning solutions in detecting Mirai Malware strains.
On Channel Estimation in LTE-Based Downlink Narrowband Internet of Things Systems
Authors: Jewel Md Khalid Hossain , Zakariyya Rabiu Sale , Lin Fujiang
Published: May 2021

Narrowband Internet of Things (NB-IoT) systems were specified by 3GPP in release 13 as a low power wide area network (LPWAN) technology to operate with a very narrow bandwidth of 180 kHz only. Due to fragile radio signal operating conditions (where a signal is weaker than noise), NB-IoT channel status becomes highly complex. Therefore, an effective and low complexity channel estimation will perform a significant role in the receiver operation. The linear minimum mean square error (LMMSE) scheme is very effective in estimating the channel but introduces massive complexity because of having complex matrix inversion. In this paper, we first derive the analytical model of the signal for long-term evolution (LTE)-based NB-IoT downlink systems and propose a reduced complexity LMMSE channel estimation for the downlink NB-IoT systems by applying singular value decomposition (SVD) technique along with partitioning the whole channel matrix into small submatrices. Furthermore, we apply the overlap banded technique to optimize the performance of the proposed channel estimator. As a result of exploiting several submatrices instead of a larger channel matrix, the operational complexity is significantly optimized. Lastly, we propose a polyphase filter structure for implementing the interpolation procedure instead of the conventional interpolation method to further optimize the performance and complexity of the proposed channel estimator further. The performance of the proposed technique has been justified by the mean square error (MSE), bit error rate (BER), and instantaneous throughput for the related signal-to-noise ratio (SNR). The system complexity is verified by the number of complex multiplications used. Simulation evaluations indicate that with the sacrifice of negligible performance, the proposed modified LMMSE technique along with the proposed interpolation possesses a good balance between the performance and the system complexity that could help the proposed techniques to be applied successfully in the low complexity NB-IoT systems.
A Survey on Computational Intelligence Applications in Distribution Network Optimization
Authors: Vukobratović Marko , Marić Predrag , Horvat Goran , Balkić Zoran , Sučić Stjepan
Published: May 2021

This paper aims to present carefully selected scientific papers that have pushed the boundaries in the application of advanced computational intelligence–based methods in power engineering, mainly in optimal power system management. Contemporary development of the Smart Grid and detailed framework for power grid digitalization enabled the real and efficient application of advanced optimization algorithms presented in this paper. Papers that are not directly related to Smart Grid management are also considered, since they solve the partial challenges of planning and development with metaheuristic procedures, and according to the authors, they are highly applicable and represent a fundamental starting point for wider application. This paper covers papers and research whose results are reproducible and can be realized in production-grade software. The emphasis of the paper is on the considerate and impartial way of providing a concise overview of the methods for solving technical challenges within the accepted Smart Grid architecture. The paper is the result of many years of research and commitment to this field and represents the foundation for present research and development.
Bearing Fault Classification Using Ensemble Empirical Mode Decomposition and Convolutional Neural Network
Authors: Nishat Toma Rafia , Kim Cheol-Hong , Kim Jong-Myon
Published: May 2021

Condition monitoring is used to track the unavoidable phases of rolling element bearings in an induction motor (IM) to ensure reliable operation in domestic and industrial machinery. The convolutional neural network (CNN) has been used as an effective tool to recognize and classify multiple rolling bearing faults in recent times. Due to the nonlinear and nonstationary nature of vibration signals, it is quite difficult to achieve high classification accuracy when directly using the original signal as the input of a convolution neural network. To evaluate the fault characteristics, ensemble empirical mode decomposition (EEMD) is implemented to decompose the signal into multiple intrinsic mode functions (IMFs) in this work. Then, based on the kurtosis value, insignificant IMFs are filtered out and the original signal is reconstructed with the rest of the IMFs so that the reconstructed signal contains the fault characteristics. After that, the 1-D reconstructed vibration signal is converted into a 2-D image using a continuous wavelet transform with information from the damage frequency band. This also transfers the signal into a time-frequency domain and reduces the nonstationary effects of the vibration signal. Finally, the generated images of various fault conditions, which possess a discriminative pattern relative to the types of faults, are used to train an appropriate CNN model. Additionally, with the reconstructed signal, two different methods are used to create an image to compare with our proposed image creation approach. The vibration signal is collected from a self-designed testbed containing multiple bearings of different fault conditions. Two other conventional CNN architectures are compared with our proposed model. Based on the results obtained, it can be concluded that the image generated with fault signatures not only accurately classifies multiple faults with CNN but can also be considered as a reliable and stable method for the diagnosis of fault bearings.
FPGA Implementation of High-Efficiency ECC Point Multiplication Circuit
Authors: Zhao Xia , Li Bing , Zhang Lin , Wang Yazhou , Zhang Yan , Chen Rui
Published: May 2021

The authentication of Internet of Things (IoT) devices based on the Physical Unclonable Function (PUF) is widely adopted in the information security domain. However, the leakage of PUF responses in an authentication system reduces its privacy and security. To improve its security, we can utilize the Elliptic Curve Cryptography (ECC) algorithm with different key lengths to encrypt the PUF response arbitrarily. Point multiplication is the most time-consuming operation in ECC because of its complex calculation process, which seriously affects the efficiency of the PUF response encryption. In order to solve this problem, a point multiplier based on binary field with reconfigurable key lengths of 233, 283, 409 and 571 is designed in this paper. In our method, by reusing the underlying computing units, the resources needed for point multiplication are effectively reduced. What it is more innovative is that double point multiplication operations with a key length of less than 283 bits can be performed simultaneously in the elaborate designed point multiplication circuit, which can effectively speed up the encryption process of ECC. The circuit is implemented on Xilinx Virtex-6 FPGA. The experiment results show the single point multiplication times of 233, 283, 409 and 571 key lengths are 19.33, 22.36, 41.36 and 56.5 μs, respectively, under the clock frequency of 135 MHz. In addition, it only needs 19.33 μs to perform two-point multiplication operations when the key length is 233 bits at the same time. When the key length is 283 bits, the point multiplication operation can be performed twice in 22.36 μs.
Performance Analysis of Multihop Underground Magnetic Induction Communication
Authors: Ishtiaq Mariam , Hwang Seung-Hoon
Published: May 2021

Magnetic induction (MI) is a promising solution for realizing wireless underground sensor networks (WUSNs) for many applications such as smart agriculture, surveillance, and environmental monitoring. In this study, a practical deployment model for a multihop MI-WUSN was developed, and its end-to-end performance was evaluated in terms of the signal-to-noise ratio, channel capacity, and bit error rate. We considered a multihop MI-WUSN and evaluated its end-to-end statistical performance for two scenarios pertaining to the hop state: (1) independent and identical distribution (IID) and (2) independent and non-identical distribution (INID). We derived analytical expressions for the performance evaluation and analysis of both scenarios by varying the number of hops and channel conditions. Our extensive numerical results show that asymptotic performance bounds can be obtained for the IID of hops. An analysis of the INID of hops yielded practical results that can facilitate decisive optimisation trade-offs and that can help reduce the system design overhead.
Evaluation of Modelling and Simulation Strategies to Investigate the Mechanical Integrity of a Battery Cell Using Finite Element Methods
Authors: Kulkarni Shraddha Suhas , Vysoudil Filip , Vietor Thomas
Published: May 2021

The mechanical integrity of a lithium ion battery cell can be evaluated using finite element (FE) simulation techniques. In this study, different FE modelling approaches including heterogeneous, homogeneous, hybrid and sandwich methods are presented and analysed. The basic capabilities of the FE-methods and their suitability to simulate a real mechanical safety test procedures on battery cells are investigated by performing a simulation of a spherical indentation test on a sample pouch cell. For each modelling approach, one battery cell model was created. In order to observe the system behaviour, relevant parametric studies involving coefficient of friction and failure strain of separator were performed. This studied showed that these parameters can influence the maximum force and the point of failure of the cell. Furthermore, the influence of an anisotropic separator on the results was also investigated. The advantages and disadvantages of each modelling approach are discussed and a simplified approach with a partial cell modelling is suggested to further reduce the simulation time and complexity.
Comparative Analysis of Carbon Capture and Storage Finance Gaps and the Social Cost of Carbon
Authors: Harker Steele Amanda , Warner Travis , Vikara Derek , Guinan Allison , Balash Peter
Published: May 2021

This paper evaluates how changes in economic market and policy conditions, including the establishment of a per-unit tax on unabated emissions of carbon dioxide (CO2) set equal to estimates of the social cost of carbon (SCC), influence the economics of carbon capture and storage (CCS) for two hypothetical power generation facilities located in the United States. Data are provided from modified versions of models and resources created and managed by the National Energy Technology Laboratory. Changes in economic market and policy conditions are evaluated over a series of scenarios in which differences in the levelized cost of electricity (LCOE) provide estimates of the financial gap necessary to overcome for CCS to be considered the cost-minimizing choice for each power generation facility type considered. Results suggest that for the coal and natural gas power generation facilities considered, a per-unit tax set equal to an SCC exceeding $123 per metric ton of CO2 (/tCO2) emitted (2018 dollars) and $167/tCO2 emitted, respectively, in combination with current Section 45Q tax credits, yields investment in CCS as the cost-minimizing choice; SCC values as low as $58/tCO2 and $98/tCO2 can make CCS the cost-minimizing choice with additional support policies (e.g., free transportation and storage options).
Electric Drivetrain Optimization for a Commercial Fleet with Different Degrees of Electrical Machine Commonality
Authors: Lu Meng , Domingues-Olavarría Gabriel , Márquez-Fernández Francisco J. , Fyhr Pontus , Alaküla Mats
Published: May 2021

At present, the prevalence of electric vehicles is increasing continuously. In particular, there are promising applications for commercial vehicles transferring from conventional to full electric, due to lower operating costs and stricter emission regulations. Thus, cost analysis from the fleet perspective becomes important. The study of cost competitiveness of different drivetrain designs is necessary to evaluate the fleet cost variance for different degrees of electrical machine commonality. This paper presents a methodology to find a preliminary powertrain design that minimizes the Total Cost of Ownership (TCO) for an entire fleet of electric commercial vehicles while fulfilling the performance requirements of each vehicle type. This methodology is based on scalable electric machine models, and particle swarm is used as the main optimization algorithm. The results show that the total cost penalty incurred when sharing the same electrical machine is small, therefore, there is a cost saving potential in higher degrees of electrical machine commonality.
Enhanced Biogas Production by Ligninolytic Strain Enterobacter hormaechei KA3 for Anaerobic Digestion of Corn Straw
Authors: Zhang Qing , Zhang Jing , Zhao Shuai , Song Peizhi , Chen Yanli , Liu Pu , Mao Chunlan , Li Xiangkai
Published: May 2021

Lignin-feeding insect gut is a natural ligninolytic microbial bank for the sustainable conversion of crop straw to biogas. However, limited studies have been done on highly efficient microbes. Here, an efficient ligninolytic strain Enterobacter hormaechei KA3 was isolated from the gut microbiomes of lignin-feeding Hypomeces squamosus Fabricius, and its effects on lignin degradation and anaerobic digestion were investigated. No research has been reported. Results showed that strain KA3 had better lignin-degrading ability for corn straw with a higher lignin-degrading rate (32.05%) and lignin peroxidase activity (585.2 U/L). Furthermore, the highest cumulative biogas yield (59.19 L/kg-VS) and methane yield (14.76 L/kg-VS) were obtained for KA3 inoculation, which increased by 20% and 31%, respectively, compared to CK. Higher removal rates of COD, TS, and vs. of 41.6%, 43.11%, and 66.59% were also found. Moreover, microbial community diversity increased as digestion time prolonged in TG, and bacteria were more diverse than archaea. The dominant genus taxon, for methanogens, was Methanosate in TG, while in CK was Methanosarcina. For bacteria, dominant taxa were similar for all groups, which were Solibacillus and Clostridium. Therefore, strain KA3 improved the methane conversion of the substrate. This study could provide a new microbial resource and practical application base for lignin degradation.
Voltage-Gain Design and Efficiency Optimization of Series/Series-Parallel Inductive Power Transfer System Considering Misalignment Issue
Authors: Yang Libin , Zong Ming , Li Chunlai
Published: May 2021

Compensation is key to an inductive power transfer (IPT) system in terms of voltage transfer function and efficiency optimization. Basic compensation is simple, but not suitable, for the achievement of variable load-independent voltage-gains without changing the design of the loosely-coupled transformer (LCT). On the other hand, higher-order compensation circuits enable greater design freedom to achieve variable load-independent voltage-gains while keeping the LCT unchanged, but it requires a variety of compensation components, especially the inductive components, which incur significant copper and core losses. This paper proposes a comprehensive design of the series/series-parallel (S/SP) IPT system. The design methodology for variable load-independent voltage-gains is studied to keep the LCT unchanged and achieve zero phase angle input over the whole load range. Design consideration includes the effect of misalignment issue on the voltage-gain and, thus, a design criteria can be derived to ensure an acceptable sensitivity to the misalignment when taking efficiency optimization. The experimental results are presented for verification.
Rejuvenated Brewer’s Spent Grain: EverVita Ingredients as Game-Changers in Fibre-Enriched Bread
Authors: Sahin Aylin W. , Atzler Jonas Joachim , Valdeperez Daniel , Münch Steffen , Cattaneo Giacomo , O’Riordan Patrick , Arendt Elke K.
Published: May 2021

Brewer’s spent grain (BSG) is the main side-stream of brewing. BSG is a potential source for nutritionally enriched cereal products due to its high content of fibre and protein. Two novel ingredients originating from BSG, EverVita FIBRA (EVF) and EverVita PRO (EVP), were incorporated into bread in two addition levels to achieve a ‘source of fibre’ (3 g/100 g) and a ‘high in fibre’ (6 g/100 g) nutrition claim for the breads. The impact of those two ingredients on dough and bread quality as well as on nutritional value was investigated and compared to baker’s flour (C1) and wholemeal flour (C2) breads. The addition of EVF performed outstandingly well in the bread system achieving high specific volumes (3.72–4.66 mL/g), a soft crumb texture (4.77–9.03 N) and a crumb structure comparable with C1. Furthermore, EVF barely restricted gluten network development and did not influence dough rheology. EVP increased the dough resistance (+150%) compared to C1 which led to a lower specific volume (2.17–4.38 mL/g) and a harder crumb (6.25–36.36 N). However, EVP increased the nutritional value of the breads by increasing protein content (+36%) and protein quality by elevating the amount of indispensable amino acids. Furthermore, a decrease in predicted glycaemic index by 26% was achieved and microbial shelf life was extended by up to 3 days. Although both ingredients originated from the same BSG, their impact on bread characteristics and nutritional value varied. EVF and EVP can be considered as game-changers in the development of bread fortified with BSG, increasing nutritional value, and promoting sustainability.
Effect of Microwave Maceration and SO2 Free Vinification on Volatile Composition of Red Wines
Authors: Muñoz García Raquel , Oliver Simancas Rodrigo , Díaz-Maroto María Consuelo , Alañón Pardo María Elena , Pérez-Coello María Soledad
Published: May 2021

This study evaluates the effect of microwave treatment in grape maceration at laboratory scale on the content of free and glycosidically bound varietal compounds of must and wines and on the overall aroma of wines produced with and without SO2. The volatile compounds were extracted by solid phase extraction and analyzed by gas chromatography–mass spectrometry, carrying out a sensory evaluation of wines by quantitative descriptive analysis. Microwave treatment significantly increased the free and bound fraction of most varietal compounds in the must. Wines from microwave maceration showed faster fermentation kinetics and shorter lag phase, resulting in an increase in some volatile compounds of sensory relevance. The absence of SO2 caused a decrease in concentration of some volatile compounds, mainly fatty acids and esters. The sensory assessment of wines from microwave treatment was higher than the control wine, especially in wines without SO2, which had higher scores in the “red berry” and “floral” odor attributes and a more intense aroma. This indicates that the pre-fermentative treatment of grapes with microwaves could be used to increase the wine aroma and to reduce the occurrence of SO2.
Chemometric Comparison of High-Pressure Processing and Thermal Pasteurization: The Nutritive, Sensory, and Microbial Quality of Smoothies
Authors: Škegro Marko , Putnik Predrag , Bursać Kovačević Danijela , Kovač Ana Petra , Salkić Lidija , Čanak Iva , Frece Jadranka , Zavadlav Sandra , Ježek Damir
Published: May 2021

This study investigated the status of bioactive compounds (phenolic compounds, carotenoids, and vitamin C), changes in color performance, and microbiological quality in smoothies preserved by high-pressure processing (HP) and thermal pasteurization (P) during cold storage at 4 °C for 21 days. Chemometric tools were used to select relevant variables that represent the most useful information for the fast and accurate quality assessment of smoothies. HP was performed at 350 and 450 MPa for 5 and 15 min at room temperature, respectively, while P was performed at 85 °C for 7 min. Smoothies were prepared by blending juices of apple (50%, v/v), carrot (20%, v/v), chokeberry (5%, v/v), Indian banana puree (10%, w/v), and almond drink (15%, v/v). The results obtained indicated that lower pressures with a shorter duration of HP showed higher levels of bioactive compounds in the smoothies, compared to the control samples. Compared to P, the HP samples exhibited a greater stability of bioactive compounds during shelf life. HP was found to be highly effective in reducing the native microflora of the smoothies, without subsequent microbial activation during storage. This study demonstrated the usefulness of the chemometric approach in interpreting complex datasets for the effective quality assessment of smoothies treated with different preservation technologies.
Risk of Global External Cereals Supply under the Background of the COVID-19 Pandemic: Based on the Perspective of Trade Network
Authors: Zhang Chao , Yang Yanzhao , Feng Zhiming , Xiao Chiwei , Lang Tingting , Du Wenpeng , Liu Ying
Published: May 2021

International food trade is an integral part of the food system, and the COVID-19 pandemic has exposed the fragility of external food supplies. Based on the perspective of cereals trade networks (CTN), the pandemic risk is combined with the trade intensity between countries, and an assessment model of cereals external supply risk is constructed that includes external dependence index (EDI), import concentration, and risk of COVID-19 from import countries index (RICI). The results show that: (1) the global main CTN have typical scale-free characteristics, and seven communities are detected under the influence of the core countries; (2) about 60%, 50%, and 70% of countries face risks of medium and above (high and very high) external dependence, concentration of imports, and COVID-19 in the country of origin, respectively. Under the influence of the pandemic, the risk of global external cereal supply index (RECSI) has increased by 65%, and the USA-CAN communities show the highest risk index; (3) the countries with a very high risk are mainly the Pacific island countries and the Latin American and African countries. In addition, Japan, Mexico, South Korea, and 80% of the net food-importing developing countries are at high or very high RECSI levels. Approximately 50% of countries belong to the compound risk type, and many export countries belong to the RICI risk type; (4) global external food supply is subjected to multiple potential threats such as trade interruption, “price crisis”, and “payment dilemma”. The geographical proximity of community members and the geographical proximity of the pandemic risk is superimposed, increasing the regional risk of external food supply; and (5) this study confirms that the food-exporting countries should avoid the adoption of food export restriction measures and can prevent potential external supply risks from the dimensions of maintaining global food liquidity and promoting diversification of import sources. We believe that our assessment model of cereals external supply risk comprises a useful method for investigations regarding the international CTN or global food crisis under the background of the pandemic.
Down-Regulation of FAD2-1 Gene Expression Alters Lysophospholipid Composition in the Endosperm of Rice Grain and Influences Starch Properties
Authors: Luo Jixun , Liu Lei , Konik-Rose Christine , Tian Lijun , Singh Surinder , Howitt Crispin A. , Li Zhongyi , Liu Qing
Published: May 2021

Small quantities of lipids accumulate in the white rice grains. These are grouped into non-starch lipid and starch lipid fractions that affect starch properties through association with starch. Lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE) are two major lipid classes in the two fractions. Using high-oleic rice grains, we investigated the fatty-acid composition in flour and starch by LC-MS and evaluated its impact on starch properties. In the wild-type grain, nearly 50% of fatty acids in LPC and LPE were palmitic acid (C16:0), over 20% linoleic acid (C18:2) and less than 10% oleic acid (C18:1). In the high-oleic rice grain, C18:1 increased at the expense of C18:2 and C16:0. The compositional changes in starch lipids suggest that LPC and LPE are transported to an amyloplast with an origin from endoplasmic reticulum-derived PC and PE during endosperm development. The high-dissociation temperature of the amylose-lipid complex (ALC) and restricted starch swelling power in the high-oleic rice starch indicates that the stability of the ALC involving C18:1 is higher than that of C18:2 and C16:0. This study provides insight into the lipid deposition and starch properties of rice grains with optimized fatty-acid composition.
Films Based on Thermoplastic Starch Blended with Pine Resin Derivatives for Food Packaging
Authors: Pavon Cristina , Aldas Miguel , López-Martínez Juan , Hernández-Fernández Joaquín , Arrieta Marina Patricia
Published: May 2021

Completely biobased and biodegradable thermoplastic starch (TPS) based materials with a tunable performance were prepared for food packaging applications. Five blends were prepared by blending TPS with 10 wt%. of different pine resins derivatives: gum rosin (GR), disproportionated gum rosin (RD), maleic anhydride-modified gum rosin (CM), pentaerythritol ester of gum rosin (LF), and glycerol ester of gum rosin (UG). The materials were characterized in terms of thermo-mechanical behavior, surface wettability, color performance, water absorption, X-ray diffraction pattern, and disintegration under composting conditions. It was determined that pine resin derivatives increase the hydrophobicity of TPS and also increase the elastic component of TPS which stiffen the TPS structure. The water uptake study revealed that GR and LF were able to decrease the water absorption of TPS, while the rest of the resins kept the water uptake ability. X-ray diffraction analyses revealed that GR, CM, and RD restrain the aging of TPS after 24 months of aging. Finally, all TPS-resin blends were disintegrated under composting conditions during the thermophilic incubation period (90 days). Because of the TPS-resin blend’s performance, the prepared materials are suitable for biodegradable rigid food packaging applications.
Sweet Talk: A Qualitative Study Exploring Attitudes towards Sugar, Sweeteners and Sweet-Tasting Foods in the United Kingdom
Authors: Tang Claudia S. , Mars Monica , James Janet , de Graaf Kees , Appleton Katherine M.
Published: May 2021

Worldwide initiatives currently aim to reduce free sugar intakes, but success will depend on consumer attitudes towards sugar and the alternatives. This work aimed to explore attitudes towards sugar, sweeteners and sweet-tasting foods, towards consumption and related policies, in a sample of the general public of the UK. Focus groups and interviews were conducted with 34 adults (7 males, ages: 18–65 years). Thematic analysis identified six themes: ‘Value’ (e.g., pleasure, emotions), ‘Angle’ (e.g., disinterest), ‘Personal Relevance’ (to be concerned and/or change one’s own behavior), ‘Personal Responsibility’ (one has an active relationship with these food items), ‘Understanding’ (the acquisition, comprehension and application of information) and ‘It’s Not Up to Me’ (a passive approach, because intake is subjected to other factors). Both positive and negative attitudes towards sugar, sweeteners and sweet-tasting foods were expressed in all themes. Participants also reported varied engagement with and motivations towards all food items, with implications for intakes. Suggested challenges and potential strategies for reducing free sugar intakes highlighted the need for differing approaches. Future work should assess associations between attitudes and intakes. For greatest population benefit, evidence of the dominant attitudes in those in greatest need of reduced free sugar intakes would be of value.
A Milk Foodomics Investigation into the Effect of Pseudomonas fluorescens Growth under Cold Chain Conditions
Authors: Bellassi Paolo , Rocchetti Gabriele , Morelli Lorenzo , Senizza Biancamaria , Lucini Luigi , Cappa Fabrizio
Published: May 2021

Pseudomonas fluorescens is a psychrotrophic species associated with milk spoilage because of its lipolytic and proteolytic activities. Consequently, monitoring P. fluorescens or its antecedent activity in milk is critical to preventing quality defects of the product and minimizing food waste. Therefore, in this study, untargeted metabolomics and peptidomics were used to identify the changes in milk related to P. fluorescens activity by simulating the low-temperature conditions usually found in milk during the cold chain. Both unsupervised and supervised multivariate statistical approaches showed a clear effect caused by the P. fluorescens inoculation on milk samples. Our results showed that the levels of phosphatidylglycerophosphates and glycerophospholipids were directly related to the level of contamination. In addition, our metabolomic approach allowed us to detect lipid and protein degradation products that were directly correlated with the degradative metabolism of P. fluorescens. Peptidomics corroborated the proteolytic propensity of P. fluorescens-contaminated milk, but with lower sensitivity. The results obtained from this study provide insights into the alterations related to P. fluorescens 39 contamination, both pre and post heat treatment. This approach could represent a potential tool to retrospectively understand the actual quality of milk under cold chain storage conditions, either before or after heat treatments.