bluuebunny/crossref_metadata_2025 huggingface dataset:
A Rotational Invariant Neural Network for Electrical Impedance Tomography Imaging without Reference Voltage: RF-REIM-NET
Authors: Rixen Jöran , Eliasson Benedikt , Hentze Benjamin , Muders Thomas , Putensen Christian , Leonhardt Steffen , Ngo Chuong
Published: March 2022

Background: Electrical Impedance Tomography (EIT) is a radiation-free technique for image reconstruction. However, as the inverse problem of EIT is non-linear and ill-posed, the reconstruction of sharp conductivity images poses a major problem. With the emergence of artificial neural networks (ANN), their application in EIT has recently gained interest. Methodology: We propose an ANN that can solve the inverse problem without the presence of a reference voltage. At the end of the ANN, we reused the dense layers multiple times, considering that the EIT exhibits rotational symmetries in a circular domain. To avoid bias in training data, the conductivity range used in the simulations was greater than expected in measurements. We also propose a new method that creates new data samples from existing training data. Results: We show that our ANN is more robust with respect to noise compared with the analytical Gauss–Newton approach. The reconstruction results for EIT phantom tank measurements are also clearer, as ringing artefacts are less pronounced. To evaluate the performance of the ANN under real-world conditions, we perform reconstructions on an experimental pig study with computed tomography for comparison. Conclusions: Our proposed ANN can reconstruct EIT images without the need of a reference voltage.
Deep Learning Segmentation in 2D X-ray Images and Non-Rigid Registration in Multi-Modality Images of Coronary Arteries
Authors: Park Taeyong , Khang Seungwoo , Jeong Heeryeol , Koo Kyoyeong , Lee Jeongjin , Shin Juneseuk , Kang Ho Chul
Published: March 2022

X-ray angiography is commonly used in the diagnosis and treatment of coronary artery disease with the advantage of visualization of the inside of blood vessels in real-time. However, it has several disadvantages that occur in the acquisition process, which causes inconvenience and difficulty. Here, we propose a novel segmentation and nonrigid registration method to provide useful real-time assistive images and information. A convolutional neural network is used for the segmentation of coronary arteries in 2D X-ray angiography acquired from various angles in real-time. To compensate for errors that occur during the 2D X-ray angiography acquisition process, 3D CT angiography is used to analyze the topological structure. A novel energy function-based 3D deformation and optimization is utilized to implement real-time registration. We evaluated the proposed method for 50 series from 38 patients by comparing the ground truth. The proposed segmentation method showed that Precision, Recall, and F1 score were 0.7563, 0.6922, and 0.7176 for all vessels, 0.8542, 0.6003, and 0.7035 for markers, and 0.8897, 0.6389, and 0.7386 for bifurcation points, respectively. In the nonrigid registration method, the average distance of 0.8705, 1.06, and 1. 5706 mm for all vessels, markers, and bifurcation points was achieved. The overall process execution time was 0.179 s.
Feature Paper Special Issue for Editorial Board Members (EBMs) of Diseases
Authors: Battino Maurizio
Published: March 2022

When you are part of a community, especially a scientific one, you are required to contribute significantly to its welfare, because the community as a whole represents each individual within it and, in turn, determines the wellbeing of the participants themselves [...]
Age Assessment in Children and Adolescents by Measuring the Open Apices in Teeth: A New Sardinian Formula
Authors: Spinas Enrico , Melis Giorgia , Zerman Nicoletta , De Luca Stefano , Cameriere Roberto
Published: March 2022

Age estimation in children is fundamental in both clinical and forensic fields. The aim of this study was to evaluate the accuracy of the Cameriere’s European and Italian formulae for age estimation in Sardinian children and adolescents, a genetically isolated population. A sample of 202 orthopantomograms of healthy Sardinian children and adolescents (100 females and 102 males) aged between 6 and 17 years was retrospectively evaluated. The seven left mandibular teeth were assessed with the Cameriere’s European and Italian formulae. The teeth with closed apex (N0) were counted and, in the teeth with open apex, the distance between the inner sides was calculated. All variables showed a significant and negative correlation with age except N0 and g. Sex (g), the variables s, N0, and the first-order interaction between them, contributed substantially to the age measurement (p < 0.001). Although the value of x5 had a low prediction level, it generated the following multiple linear regression formula, specific for the Sardinian sample: Age = 10.372 + 0.469 g + 0.810 N0 − 1.079 s − 0.398 s ∙ N0 − 0.326 × 5. Only the Sardinian and European formulae allowed to obtain an acceptable interclass agreement (both the lower and upper >0.7). The results showed that the European formula could be accurate for assessing age in this sample of children and adolescents.
Learning about Pesticide Use Adapted from Ethnoscience as a Contribution to Green and Sustainable Chemistry Education
Authors: Zidny Robby , Eilks Ingo
Published: March 2022

This study shows how students can learn about green and sustainable chemistry by using the knowledge perspective of a local indigenous culture as a starting point. This learning approach encourages students to learn chemistry by connecting culture with learning about green chemistry. The cultural context selects the use of a phytochemical agent (d-limonene) from a local plant (Citrus grandis), which is a traditional botanical pesticide that is used by the Baduy tribe in Western Java, Indonesia. A simple low-cost extraction method that uses a kitchen microwave was chosen to introduce modern green extraction methods to learners. This facilitates the students’ ability to evaluate the “greenness” of this method, as compared to more conventional extraction methods, such as Soxhlet and steam distillation. The learning activities were conducted during the COVID-19 pandemic with the help of an online learning management system (SPADA) and Google Meet. The students’ feedback and selected results are discussed below.
GIReSiMCo: A Learning Model to Scaffold Students’ Science Process Skills and Biology Cognitive Learning Outcomes
Authors: Senisum Maria , Susilo Herawati , Suwono Hadi , Ibrohim
Published: March 2022

The discovery of new knowledge is inseparable from the process of determining whether that applies science process skills (SPS). Science process skills are essential for students to develop science. This study aimed to determine the effect of the GIReSiMCo (Guided Inquiry, Reading, Sharing, Mind Mapping, and Communication) learning model as a new guided inquiry on students’ SPS and cognitive learning outcomes. A quasi-experimental research design was applied in biology classrooms at seven senior high schools for one semester. One hundred and twenty-six eleventh-grade students who were interested in mathematics and natural sciences were selected as the research sample. In this study, the application of the GIReSiMCo learning model was compared to that of a guided inquiry model, the Reading Mind Mapping Sharing (RMS) model, and traditional learning models. The two dependent variables are science process skills and cognitive learning outcomes. The data collection instrument for the two variables is in the form of an essay test. The reliability of the instrument test was 0.75 for cognitive learning outcomes, and 0.68 for SPS. The dependent variable data were analyzed using the ANCOVA test. The result showed that the GIReSiMCo learning model had a higher impact on students’ cognitive performance and SPS, compared to the traditional learning models. In short, the GIReSiMCo learning model can enhance students’ SPS and cognitive learning outcomes. The GIReSiMCo as a student-centered learning model is recommended in Biology learning.
Explaining the Factors Affecting Students’ Attitudes to Using Online Learning (Madrasati Platform) during COVID-19
Authors: Almaiah Mohammed , Hajjej Fahima , Lutfi Abdalwali , Al-Khasawneh Ahmad , Shehab Rami , Al-Otaibi Shaha , Alrawad Mahmaod
Published: March 2022

This study aims to investigate students’ perceptions about the Madrasati platform as well as to identify the crucial factors that could influence the adoption of the Madrasati platform. Online quantitative survey method was employed to collect the data. SEM modelling method was adopted to analyze the hypotheses in the research model. The findings of the study indicate system quality, service quality and content quality, technology infrastructure, awareness, university management support, security concerns and training have a primary role in increasing the usage of the Madrasati platform in Saudi Arabia. The findings indicate that all factors have a significant influence on Madrasati platform-adoption among students. This research contributes to the body of knowledge and Madrasati platform-adoption practices. Likewise, it may help facilitate and promote the usage of Madrasati platform among students in Saudi universities.
Detection of Impurity Rate of Machine-Picked Cotton Based on Improved Canny Operator
Authors: Zhang Chengliang , Li Tianhui , Li Jianyu
Published: March 2022

Aiming at the real-time detection of the impurity rate in machine-picked cotton processing, a detection method for the impurity rate in machine-picked cotton was proposed based on an improved Canny operator. According to the characteristics of different saturations between cotton and impurities, the impurities were separated by extracting the image S channel. Due to problems existing in the traditional Canny operator’s edge detection, the Gaussian filter was replaced by employing mean filtering and nonlocal mean denoising, which could effectively remove the noise in the image. A YOLO V5 neural network was used to classify and identify the impurities after segmentation, and the densities of various impurities were measured. The volume–weight (V–W) model was established to solve the impurity rate based on mass. Compared with a single thread, the data processing time was shortened by 43.65%, and the frame rate was effectively improved by using multithread technology. By solving the average value of the impurity rate, the anti-interference performance of the algorithm was enhanced, and has the characteristics of real-time detection and stability. This method solved the problems of low speed, poor real-time detection, and ease of interference, and can be used to guide the cotton production process.
A Novel Adaptive East–West Interface for a Heterogeneous and Distributed SDN Network
Authors: Hoang Nam-Thang , Nguyen Hai-Nam , Tran Hai-Anh , Souihi Sami
Published: March 2022

In the years since its initiation, the software-defined network paradigm has evolved into a distinguished networking technology by causing a revolution in separating the control logic from physical devices and centralizing software-based controllers. Despite its indisputable benefits compared with the traditional network, the SDN raises the challenge of scalability with its physically centralized control. The only potential solution is to transform it into physically distributed SDN control. However, this solution requires the interoperability between SDN controllers, and the consistency of network state being distributed across these controllers. Although some east–west interfaces that help SDN controllers exchange network information have been released, they reveal several drawbacks. First, they cannot support a heterogeneous SDN system where SDN controllers are developed by different providers. Secondly, their consistency solution is simple in disregarding the tradeoff between the consistency level and the performance of SDN networks. This paper proposes an east–west interface, called SINA, to provide the interoperability of a heterogeneous and distributed SDN network. In addition, a novel reinforcement-learning-based consistency algorithm is introduced for an adaptive, quorum-based replication mechanism. The experimental results showed that SINA successfully connects heterogeneous and distributed SDN domains and balances the consistency and network performance.
Novel Approach and Methods for Optimizing Highly Sensitive Low Noise Amplifier CMOS IC Design for Congested RF Environments
Authors: Chung Jooik , Iliadis Agis A.
Published: March 2022

This work details the optimization and evaluation of a CMOS low-noise amplifier by developing a new algorithm for the gm/ID approach and combining with a modified figure of merit index method. The amplifier includes on-chip matching elements (such as IC inductors) for resonance at the targeted frequencies. The simulation results of the optimized LNA model showed scattering parameter S21 = 19.91 dB, noise figure NF = 3.54 dB and excellent linearity for third-order intermodulation parameter IIP3 = 5.89 dBm for the targeted frequency of f0 = 2.4 GHz.
Deep-Forest-Based Encrypted Malicious Traffic Detection
Authors: Zhang Xueqin , Zhao Min , Wang Jiyuan , Li Shuang , Zhou Yue , Zhu Shinan
Published: March 2022

The SSL/TLS protocol is widely used in data encryption transmission. Aiming at the problem of detecting SSL/TLS-encrypted malicious traffic with small-scale and unbalanced training data, a deep-forest-based detection method called DF-IDS is proposed in this paper. According to the characteristics of SSL/TSL protocol, the network traffic was split into sessions according to the 5-tuple information. Each session was then transformed into a two-dimensional traffic image as the input of a deep-learning classifier. In order to avoid information loss and improve the detection efficiency, the multi-grained cascade forest (gcForest) framework was simplified with only cascade structure, which was named cascade forest (CaForest). By integrating random forest and extra trees in the CaForest framework, an end-to-end high-precision detector for small-scale and unbalanced SSL/TSL encrypted malicious traffic was realized. Compared with other deep-learning-based methods, the experimental results showed that the detection rate of DF-IDS was 6.87% to 29.5% higher than that of other methods on a small-scale and unbalanced dataset. The advantage of DF-IDS was more obvious in the multi-classification case.
A Partial-Reconfiguration-Enabled HW/SW Co-Design Benchmark for LTE Applications
Authors: Hosseinghorban Ali , Kumar Akash
Published: March 2022

Rapid and continuous evolution in telecommunication standards and applications has increased the demand for a platform with high parallelization capability, high flexibility, and low power consumption. FPGAs are known platforms that can provide all these requirements. However, the evaluation of approaches, architectures, and scheduling policies in this era requires a suitable and open-source benchmark suite that runs on FPGA. This paper harnesses high-level synthesis tools to implement high-performance, resource-efficient, and easy-maintenance kernels for FPGAs. We provide various implementations of each kernel of PHY-Bench and WiBench, which are the most well-known benchmark suites for telecommunication applications on FPGAs. We analyze the execution time and power consumption of different kernels on ARM processors and FPGA. We have made all sources and documentation public for the benefit of the research community. The codes are flexible, and all kernels can easily be regenerated for different sizes. The results show that the FPGA can increase the speed by up to 19.4 times. Furthermore, we show that the power consumption of the FPGA can be reduced by up to 45% by partially reconfiguring a kernel that fits the size of the input data instead of using a large kernel that supports all inputs. We also show that partial reconfiguration can improve the execution time for processing a sub-frame in the uplink application by 33% compared to an FPGA-based approach without partial reconfiguration.
Real-Time Fault Location Using the Retardation Method
Authors: Nabwani Moneer , Suleymanov Michael , Pinhasi Yosef , Yahalom Asher
Published: March 2022

A new method for short-circuit fault location is proposed. The method is based on instantaneous signal measurement and its first and second derivatives, which are the novel elements of the current approach. The derivatives allow associating a precise time stamp to the occurrence of the fault. Due to retardation phenomena, the difference between the times in which a signal is registered in two detectors can be used to locate the fault. We offer several mathematical models to describe the fault. Although a description of faults in terms of a lumped circuit is useful for elucidating the methods for detecting the fault, this description will not suffice to describe the fault signal propagation; hence, a distributed models is needed, which is given in terms of the telegraph equations. Those equations were used to derive a transmission line transfer function, and an exact analytical description of the fault signal propagating in the transmission line was obtained. The analytical solution was verified both by numerical simulations and experimentally.
Immune System Programming: A Machine Learning Approach Based on Artificial Immune Systems Enhanced by Local Search
Authors: Mabrouk Emad , Raslan Yara , Hedar Abdel-Rahman
Published: March 2022

The foundation of machine learning is to enable computers to automatically solve certain problems. One of the main tools for achieving this goal is genetic programming (GP), which was developed from the genetic algorithm to expand its scope in machine learning. Although many studies have been conducted on GP, there are many questions about the disruption effect of the main GP breeding operators, i.e., crossover and mutation. Moreover, this method often suffers from high computational costs when implemented in some complex applications. This paper presents the meta-heuristics programming framework to create new practical machine learning tools alternative to the GP method. Furthermore, the immune system programming with local search (ISPLS) algorithm is composed from the proposed framework to enhance the classical artificial immune system algorithm with the tree data structure to deal with machine learning applications. The ISPLS method uses a set of breeding procedures over a tree space with gradual changes in order to surmount the defects of GP, especially the high disruptions of its basic operations. The efficiency of the proposed ISPLS method was proven through several numerical experiments, including promising results for symbolic regression, 6-bit multiplexer and 3-bit even-parity problems.
Trust in the U.S. Government and Its Health Agencies in the Time of COVID-19
Authors: Geisterfer-Black Maraika , Niemi Taylor , Neier Leonie , Rodwin Victor G.
Published: March 2022

This article examines the factors affecting Americans’ trust in their federal government and its health agencies during the COVID-19 public health crisis. More specifically, we examine the evolution of Americans’ trust in their government and health system and how, in the context of the COVID-19 pandemic response, it has been affected by multiple factors. Several academic journals, government policy recommendations and public health polls were evaluated to understand the public’s trust in the federal government and its health institutions. Public trust in institutions during a global pandemic is essential in influencing adherence to a pandemic response (both non-pharmaceutical and medical interventions). Americans’ trust in institutions is built and maintained by a variety of factors. We focus on: political polarization and involvement, media influence and health communications, history of systemic racism and socioeconomic inequalities, and pandemic fatigue. Based on the interplay of these factors, we conclude with recommendations for future pandemic response strategies.
Impact of COVID-19 on Food Security in Ethiopia
Authors: Zhang Wenqin , Persoz Léo , Hakiza Sandrine , Biru Loza , Girmatsion Lemlem
Published: March 2022

Since the outbreak of COVID-19, its effects on different aspects of life have been subject to much research, including food security, a domain that has been of special concern in many low-income countries. Ethiopia has been facing many challenges related to food security for decades via drought, famine, and conflict. Within this context, this case study assessed the impact of the COVID-19 pandemic on food security in Ethiopia. Results show that the ongoing pandemic has negatively impacted different regions and at-risk groups in a heterogeneous manner. This has been mainly through disruptions in the Ethiopian food value chain and the relative failure of social security programmes to address the losses generated by COVID-19. The population in the capital city, Addis Ababa, was able to maintain the same level of food security despite income losses caused by the COVID-19 pandemic. However, at-risk groups such as refugees, internally displaced persons (IDPs), and conflict affected regions were seen to suffer significantly from food insecurity exacerbated by COVID-19. Furthermore, this paper particularly emphasizes the importance of considering contextual factors other than COVID-19, such as conflicts or climate change, when discussing the state of food security in Ethiopia.
Changes in the Microbial Community and Biogenic Amine Content in Rapeseed Meal during Fermentation with an Antimicrobial Combination of Lactic Acid Bacteria Strains
Authors: Bartkiene Elena , Gruzauskas Romas , Ruzauskas Modestas , Zokaityte Egle , Starkute Vytaute , Klupsaite Dovile , Vadopalas Laurynas , Badaras Sarunas , Özogul Fatih
Published: March 2022

The aim of this study was to evaluate the microbial changes and biogenic amine (BA) formation in rapeseed meal (RP) during fermentation with a bacterial starter combination of Lactiplantibacillus plantarum-LUHS122 and -LUHS135, Lacticaseibacillus casei-LUHS210, Lentilactobacillus farraginis-LUHS206, Pediococcus acidilactici-LUHS29, and Liquorilactobacillus uvarum-LUHS245. Sampling was carried out after 12 h and 7, 14, 21, and 28 days of cultivation under conditions of constant changes to the substrate, with a change frequency of 12 h. The highest lactic acid bacteria (LAB) and yeast/mould counts were established in RP fermented for 14 days (8.29 and 4.34 log10 CFU/g, respectively); however, the lowest total enterobacteria count was found in RP fermented for 12 h (3.52 log10 CFU/g). Further metagenomic analysis showed that Lactobacillus spp. were the most prevalent species in fermented RP. The changes in microbial community in RP led to differences in BA formation. Putrescine and phenylethylamine were found in all fermented RP samples, while the contents of some other amines increased with prolonged fermentation. Finally, the use of combined fermentation could ensure Lactobacillus spp. domination; however, other parameters should be controlled due to the formation of undesirable compounds.
Extreme Winds Alter Influence of Fuels and Topography on Megafire Burn Severity in Seasonal Temperate Rainforests under Record Fuel Aridity
Authors: Evers Cody , Holz Andrés , Busby Sebastian , Nielsen-Pincus Max
Published: March 2022

Nearly 0.8 million hectares of land were burned in the North American Pacific Northwest (PNW) over two weeks under record-breaking fuel aridity and winds during the extraordinary 2020 fire season, representing a rare example of megafires in forests west of the Cascade Mountains. We quantified the relative influence of weather, vegetation, and topography on patterns of high burn severity (>75% tree mortality) among five synchronous megafires in the western Cascade Mountains. Despite the conventional wisdom in climate-limited fire regimes that regional drivers (e.g., extreme aridity, and synoptic winds) overwhelm local controls on vegetation mortality patterns (e.g., vegetation structure and topography), we hypothesized that local controls remain important influences on burn severity patterns in these rugged forested landscapes. To study these influences, we developed remotely sensed fire extent and burn severity maps for two distinct weather periods, thereby isolating the effect of extreme east winds on drivers of burn severity. Our results confirm that wind was the major driver of the 2020 megafires, but also that both vegetation structure and topography significantly affect burn severity patterns even under extreme fuel aridity and winds. Early-seral forests primarily concentrated on private lands, burned more severely than their older and taller counterparts, over the entire megafire event regardless of topography. Meanwhile, mature stands burned severely only under extreme winds and especially on steeper slopes. Although climate change and land-use legacies may prime temperate rainforests to burn more frequently and at higher severities than has been historically observed, our work suggests that future high-severity megafires are only likely to occur during coinciding periods of heat, fuel aridity, and extreme winds.
Characterization of Taste Compounds and Sensory Evaluation of Soup Cooked with Sheep Tail Fat and Prickly Ash
Authors: Huang Yan , Pu Dandan , Hao Zhilin , Liang Li , Zhao Jing , Tang Yizhuang , Zhang Yuyu
Published: March 2022

Sheep tail fat and prickly ash play an important role in improving the umami taste of mutton soup. In this work, the effects of prickly ash on key taste compounds in stewed sheep tail fat soup were investigated. Results showed that the taste intensity of sheep tail fat soup cooked with 0.2% prickly ash increased significantly. The concentration of organic acids and free amino acids in sheep tail fat soup significantly increased with the addition of prickly ash. The concentration of succinic acid (2.637 to 4.580 mg/g) and Thr (2.558 to 12.466 mg/g) increased the most among organic acids and amino acids, respectively. Spearman’s correlation analysis elucidated that seven taste compounds were positively correlated (correlation coefficient > 0.7) with the overall taste intensity of the soup sample including Thr, Asp, oxalic acid, lactic acid, citric acid, succinic acid, and ascorbic acid. Additional experiments and quantitative descriptive analysis further confirmed that Asp, lactic acid and citric acid were the key taste compounds to improve saltiness and umami taste in sheep tail fat soup with prickly ash.
Identifying Quality Protein Maize Inbred Lines for Improved Nutritional Value of Maize in Southern Africa
Authors: Amegbor Isaac , van Biljon Angeline , Shargie Nemera , Tarekegne Amsal , Labuschagne Maryke
Published: March 2022

Malnutrition, as a result of deficiency in essential nutrients in cereal food products and consumption of a poorly balanced diet, is a major challenge facing millions of people in developing countries. However, developing maize inbred lines that are high yielding with enhanced nutritional traits for hybrid development remains a challenge. This study evaluated 40 inbred lines: 26 quality protein maize (QPM) lines, nine non-QPM lines, and five checks (three QPM lines and two non-QPM lines) in four optimum environments in Zimbabwe and South Africa. The objective of the study was to identify good-quality QPM inbred lines for future hybrid breeding efforts in order to increase the nutritional value of maize. The QPM lines had a lower protein content (7% lower) than that of the non-QPM lines but had 1.9 times more tryptophan and double the quality index. The lysine- and tryptophan-poor α-zein protein fraction was 41% lower in QPM than in non-QPM, with a subsequent increase in γ-zein. There was significant variation within the QPM inbred lines for all measured quality characteristics, indicating that the best lines can be selected from this material without a yield penalty. QPM lines that had both high protein and tryptophan levels, which can be used as parents for highly nutritious hybrids, were identified.
Food Availability in Different Food Environments Surrounding Schools in a Vulnerable Urban Area of Santiago, Chile: Exploring Socioeconomic Determinants
Authors: Pinheiro Anna Christina , Quintiliano-Scarpelli Daiana , Flores Jacqueline Araneda , Álvarez Claudio , Suárez-Reyes Mónica , Palacios José Luis , Quevedo Tito Pizarro , de Oliveira Maria Rita Marques
Published: March 2022

The analysis of the food environment is used to identify areas with gaps in the availability of healthy foods and can be used as a public policy assessment tool. In recent decades, Chile has implemented several strategies and regulations to improve food environments, with encouraging results. Little is known about the scope of these measures in socially vulnerable environments. This study is part of a project that seeks to build an integrated intervention model for healthy school environments in a vulnerable area of Santiago, Chile. The objective of this study was to evaluate the availability of healthy and unhealthy foods around schools and the relationship between it and socioeconomic determinants of the school community in the Chilean context. A cross-sectional study to measure the food environment of informal markets (street food), formal markets (stores), and institutions (schools) was conducted in and around 12 schools (100 m surrounding schools) in a vulnerable urban area of Santiago, Chile. A lack of healthy foods was observed, which was related to some socio-economic determinants and the multidimensional poverty was the most relevant. The diagnosis of food environments around schools can represent an important target for governments to implement policies focused at improving the availability of healthy foods.
Antimicrobial Activity of Red Alga Flour (Gelidium sp.) and Its Effect on Quality Retention of Scomber scombrus during Refrigerated Storage
Authors: Miranda José M. , Trigo Marcos , Barros-Velázquez Jorge , Aubourg Santiago P.
Published: March 2022

This study analyzed the antimicrobial effect of aqueous extracts of flour obtained from red alga (Gelidium sp.) both in vitro, against most common food pathogenic and spoilage bacteria, and in a food model system during the chilled storage of Atlantic mackerel (Scomber scombrus). Results of in vitro assays allowed the conclusion that the aqueous flour extracts have antimicrobial activity against Gram-negative bacteria such as Enterobacteriaceae (Escherichia coli, Enterobacter aerogenes, and Klebsiella pneumoniae) and proteobacteria (Vibrio alginolyticus), and against Gram-positive bacteria such as Bacillus cereus and B. subtilis. In the food model study, different concentrations of the flour extract were present in the icing medium, microbial and chemical analyses being carried out in fish muscle at different storage times. An inhibitory effect (p < 0.05) on microbial growth (aerobes, psychrotrophs, Enterobacteriaceae, and proteolytic and lipolytic bacteria) and on chemical quality indices (pH, total volatile amines, and trimethylamine) was concluded. This effect was more pronounced when the flour extract concentration in the ice increased and at advanced storage times. This study provides a first approach to the beneficial use of flour of the alga Gelidium as a new preserving strategy for chilled fish.
Fish Liver Discards as a Source of Long-Chain Omega-3 Polyunsaturated Fatty Acids
Authors: Jacobsen Charlotte , Warncke Simone Andrea , Hansen Sussie Hjorth , Sørensen Ann-Dorit Moltke
Published: March 2022

The intake of omega-3 polyunsaturated fatty acids (PUFA) of the average consumer is generally low, and products such as fish oils high in omega-3 PUFA have become popular dietary supplements. There is a need for more sources of omega-3 PUFA to cover the increasing demand. This study investigated whether livers from different lean fish species could be a potential new source of oils rich in omega-3 PUFA. The seasonal variation in lipid content, fatty acid composition, peroxide value and free fatty acid content (FFA) of livers from cod, hake, ling, coalfish and monkfish was determined, and the effect of storage conditions on the fishing vessel (ice vs frozen) was studied. Generally, the lipid content and composition of the livers from the five fish species varied similarly during the two years of the sampling period, with significantly lower values in spring (March, April) and higher values in fall (October, November). Storage conditions were found to have no significant effect on the quality and oil composition. Monkfish livers were less suitable for production of omega-3 oil due to their lower lipid and EPA content as well as higher FFA levels. Coalfish had higher fluctuations in oil composition during the sampling period, which potentially makes a standardised quality difficult to obtain. Cod, hake and ling were the most suitable species for fish liver oil production.
Brassinosteroid Accelerates Wound Healing of Potato Tubers by Activation of Reactive Oxygen Metabolism and Phenylpropanoid Metabolism
Authors: Han Ye , Yang Ruirui , Zhang Xuejiao , Wang Qihui , Wang Bin , Zheng Xiaoyuan , Li Yongcai , Prusky Dov , Bi Yang
Published: March 2022

Wound healing could effectively reduce the decay rate of potato tubers after harvest, but it took a long time to form typical and complete healing structures. Brassinosteroid (BR), as a sterol hormone, is important for enhancing plant resistance to abiotic and biotic stresses. However, it has not been reported that if BR affects wound healing of potato tubers. In the present study, we observed that BR played a positive role in the accumulation of lignin and suberin polyphenolic (SPP) at the wounds, and effectively reduced the weight loss and disease index of potato tubers (cv. Atlantic) during healing. At the end of healing, the weight loss and disease index of BR group was 30.8% and 23.1% lower than the control, respectively. Furthermore, BR activated the expression of StPAL, St4CL, StCAD genes and related enzyme activities in phenylpropanoid metabolism, and promoted the synthesis of lignin precursors and phenolic acids at the wound site, mainly by inducing the synthesis of caffeic acid, sinapic acid and cinnamyl alcohol. Meanwhile, the expression of StNOX was induced and the production of O2− and H2O2 was promoted, which mediated oxidative crosslinking of above phenolic acids and lignin precursors to form SPP and lignin. In addition, the expression level of StPOD was partially increased. In contrast, the inhibitor brassinazole inhibited phenylpropanoid metabolism and reactive oxygen metabolism, and demonstrated the function of BR hormone in healing in reverse. Taken together, the activation of reactive oxygen metabolism and phenylpropanoid metabolism by BR could accelerate the wound healing of potato tubers.
Improvement of Intramuscular Fat in longissimus Muscle of Finishing Thai Crossbred Black Pigs by Perilla Cake Supplementation in a Low-Lysine Diet
Authors: Sringarm Korawan , Chaiwang Niraporn , Wattanakul Watcharapong , Mahinchai Prapas , Satsook Apinya , Norkeaw Rakkiat , Seel-audom Mintra , Moonmanee Tossapol , Mekchay Supamit , Sommano Sarana Rose , Ruksiriwanich Warintorn , Rachtanapun Pornchai , Jantanasakulwong Kittisak , Arjin Chaiwat
Published: March 2022

This study was conducted to find out the effects of perilla cake (PC) supplementation in a low-lysine diet on Thai crossbred finishing pigs’ productivity, carcass and meat quality, and fatty acid composition. For six weeks, a total of 21 barrows of finishing pigs were fed with three dietary treatments (T1: basal diet, T2: 2.5 percent PC supplementation in a low-lysine diet, and T3: 4.5 percent PC supplementation in a low-lysine diet). The results show that the intramuscular fat and marbling score was significantly increased by T2 and T3. On the other hand, it was found that the boiling loss and shear force value were significantly decreased by T2 and T3 (p < 0.05). In a low-lysine diet, dietary PC supplementation caused a significant increase in malondialdehyde levels in meat (p < 0.05) compared with the basal diet. It was also shown that alpha-linolenic acid level in backfat and the longissimus thoracis et lumborum muscle was increased considerably by T2 and T3. Therefore, supplementing PC in a low-lysine diet may be an alternative strategy for improving the meat quality of late-phase pigs.
Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS
Authors: Tufariello Maria , Pati Sandra , Palombi Lorenzo , Grieco Francesco , Losito Ilario
Published: March 2022

This review takes a snapshot of the main multivariate statistical techniques and methods used to process data on the concentrations of wine volatile molecules extracted by means of solid phase micro-extraction and analyzed using GC-MS. Hypothesis test, exploratory analysis, regression models, and unsupervised and supervised pattern recognition methods are illustrated and discussed. Several applications in the wine volatolomic sector are described to highlight different interactions among the various matrix components and volatiles. In addition, the use of Artificial Intelligence-based methods is discussed as an innovative class of methods for validating wine varietal authenticity and geographical traceability.
Utilisation of Amaranth and Finger Millet as Ingredients in Wheat Dough and Bread for Increased Agro-Food Biodiversity
Authors: Onyango Calvin , Luvitaa Susan Karenya , Lagat Kibet , Hüsken Alexandra , Smit Inga , Schmidt Marcus
Published: March 2022

Amaranth and finger millet are important food security crops in Africa but show poor bread making ability, even in composite wheat breads. Malting and steaming are promising approaches to improve composite bread quality, which have not been fully explored yet. Therefore, in this study, wheat was blended with native, steamed or malted finger millet or amaranth in the ratio of 70:30. Wheat/native amaranth (WHE-NAM) and wheat/malted amaranth (WHE-MAM) had longer dough development times and higher dough stabilities, water absorption capacities and farinograph quality numbers than wheat/steamed amaranth (WHE-SAM), wheat/native finger millet (WHE-NFM), wheat/steamed finger millet (WHE-SFM) or wheat/malted finger millet (WHE-MFM). The WHE-NAM and WHE-MAM breads had lower crumb firmness and chewiness, higher resilience and cohesiveness and lighter colours than WHE-NFM, WHE-SFM and WHE-MFM. Starch and protein digestibility of composite breads were not different (p > 0.05) from each other and ranged between 95–98% and 83–91%, respectively. Composite breads had higher ash (1.9–2.5 g/100 g), dietary fibre (5.7–7.1 g/100 g), phenolic acid (60–122 mg/100 g) and phytate contents (551–669 mg/100 g) than wheat bread (ash 1.6 g/100 g; dietary fibre 4.5 g/100 g; phenolic acids 59 mg/100 g; phytate 170 mg/100 g). The WHE-NAM and WHE-MAM breads possessed the best crumb texture and nutritional profile among the composite breads.
Osteological Collections of the National Museum in Brazil: Challenges and New Perspectives for a Historical Collection
Authors: Mendes Paulo Vítor , Silva Hilton P. , Bastos Murilo , Bittar Victor , Reis Silvia , Rodrigues-Carvalho Claudia
Published: March 2022

The National Museum of the Federal University of Rio de Janeiro (NM-UFRJ), Brazil, suffered a serious fire in 2018, resulting in the loss or severe damage of many collections. The human osteological collection, also affected, was one of the largest and oldest in the country, holding over two thousand entries from prehistoric to historic sites, including some international donations. The oldest remains were those of “Luzia”, dating to 11.5 thousand years. While part of the collection was recovered from the debris, the bones were mostly warped and damaged by the fire, making the possibility of identification uncertain. Therefore, this collection is now inadequate for regular forensic and bioarchaeological studies. Considering the need for the construction of a new human osteological collection, especially with forensic perspectives, we conducted a survey of Brazilian national and local (capitals of the Southeast region) legislation, regarding donation and institutionalization of human remains for scientific collections and ossuaries, considering the potential ethics and logistics aspects. Results suggest that legislation generally treats human remains studies and collections as an issue of lesser importance Thus, private donations may become the simplest way to receive human remains, even though they are generally age biased. We conclude that it is necessary to broaden legal and ethical discussions in order to build contemporary human bone collections with proper scientific potential for the needs of society.
Fixed-Time Fractional-Order Global Sliding Mode Control for Nonholonomic Mobile Robot Systems under External Disturbances
Authors: Labbadi Moussa , Boubaker Sahbi , Djemai Mohamed , Mekni Souad Kamel , Bekrar Abdelghani
Published: March 2022

The present study addresses the problem of fixed-time stabilization (FTS) of mobile robots (MRs). The study’s distinguishing aspects are that the system under examination is subjected to external disturbances, and the system states are pushed to zero in a finite time. This paper suggests new control techniques for chained-form nonholonomic systems (CFNS) subjected to disturbances. First, a switching fractional-order (FO) control approach is proposed for a first-order subsystem (FOS) of an MR under complex disturbances. Secondly, an FO generic global sliding mode control approach is designed for the second-order system (SOS) of the MR in the presence of disturbances. The suggested sliding manifold for the SOS of the MR guarantees global system stability and reduces the chattering problem during control operations. A conventional quadratic Lyapunov function (QLF) is used to converge to the origin in a finite time (FnT). Through this study, a stabilizer for an MR in the presence of disturbances based on an FO switching time-varying controller that can stabilize immeasurable states in a fixed time is proposed. Finally, three case simulations are provided to demonstrate the efficacy of the control strategy proposed in this work against external disturbances.
High-Energy Photon Attenuation Properties of Lead-Free and Self-Healing Poly (Vinyl Alcohol) (PVA) Hydrogels: Numerical Determination and Simulation
Authors: Pianpanit Theerasarn , Saenboonruang Kiadtisak
Published: March 2022

This work numerically determined high-energy photon shielding properties of self-healing poly(vinyl alcohol) (PVA) hydrogels containing lead-free, heavy-metal compounds, namely, bismuth oxide (Bi2O3), tungsten oxide (WO3), and barium sulfate (BaSO4), through XCOM software packages. In order to understand the dependencies of the shielding properties of the hydrogels on filler contents and photon energies, the filler contents added to the hydrogels were varied from 0–40 wt.% and the photon energies were varied from 0.001–5 MeV. The results, which were verified for their reliability and correctness with those obtained from PHITS (Particle and Heavy Ion Transport code System), indicated that overall shielding performances, which included the mass attenuation coefficients (µm), the linear attenuation coefficient (µ), the half-value layer (HVL), and the lead equivalence (Pbeq), of the hydrogels improved with increasing filler contents but generally decreased with increasing photon energies. Among the three compounds investigated in this work, Bi2O3/PVA hydrogels exhibited the highest photon attenuation capabilities, determined at the same filler content and photon energy, mainly due to its highest atomic number of Bi and the highest density of Bi2O3 in comparison with other elements and compounds. Furthermore, due to possible reduction in self-healing and mechanical properties of the hydrogels with excessive filler contents, the least content of fillers providing a 10-mm sample with the required Pbeq value of 0.5 mmPb was investigated. The determination revealed that only the hydrogel containing at least 36 wt.% of Bi2O3 exhibited the Pbeq values greater than 0.5 mmPb for all photon energies of 0.05, 0.08, and 0.1 MeV (common X-ray energies in general nuclear facilities). The overall outcomes of the work promisingly implied the potential of PVA hydrogels to be used as novel and potent X-ray and gamma shielding materials with the additional self-healing and nonlead properties.
Application of Sol–Gels Modified with Natural Plants Extracts as Stationary Phases in Open-Tubular Capillary Electrochromatography
Authors: Svobodová Jana , Mikšík Ivan
Published: March 2022

Ethanol extracts of three widely growing plants were added to silica sol–gel solutions, which were subsequently applied as wall surface modifiers in inner quartz capillaries. Modified capillaries were used for open-tubular capillary electrochromatographic separation of nucleotides and amino groups containing biological compounds (neurotransmitters, amino acids and oligopeptides). The experiments were performed at physiological pH 7.40, and eventual changes of effective mobilities were calculated. Specific compounds characteristic for each plant were tested as sol–gel additives as well, and thus-modified capillaries were used for the separations of the same analytes under identical conditions. The aim of this study was to find out possible interactions between physiological compounds and extracts of freely available plants anchorded in the sol-gel stationary phase in the flowing system. Even though the amount of the modifier in each capillary is very small, basic statistical evaluation showed some not negligible changes in effective mobility of tested analytes. These changes were bigger than ±5% for separations of nucleotides in capillaries with curcuma, Moringa or the mixture of synthetic additives as the sol-gel aditive, and for separations of amino compounds where these changes varying by additive, analyte by analyte.
Changes in Psychological Distress in Five Groups of Welfare State Service Workers over a Nine-Year Period
Authors: Geirdal Amy K. Østertun , Nerdrum Per , Høglend Per Andreas , Bonsaksen Tore
Published: March 2022

Health and social care workers are exposed to varying degrees of stress in their work, which may be reflected in their trajectories of psychological distress during the education program and the first years in the job. The aim of this study was to add to the knowledge concerned with the long-term development of psychological distress in five groups of welfare state service workers in Norway. The study included 1612 individuals. Psychological distress was measured with General Health Questionnaire-12 at four occasions from the start of the education program to 6 years post-graduation (nine year follow-up period). Results of linear mixed models (LMM) for repeated measures showed that psychological distress changed significantly over time in the social work professional groups. At the start of the education program, the lowest and highest levels of psychological distress were found among the child welfare and social workers, respectively. Six years post-graduation, social workers had become less distressed and child welfare workers had become more distressed. No significant change pattern for psychological distress was found among any of the health care professional groups.