bluuebunny/crossref_metadata_2025 huggingface dataset:
Advanced Time-Frequency Methods for ECG Waves Recognition
Authors: Zyout Ala’a , Alquran Hiam , Mustafa Wan Azani , Alqudah Ali Mohammad
Published: January 2023

ECG wave recognition is one of the new topics where only one of the ECG beat waves (P-QRS-T) was used to detect heart diseases. Normal, tachycardia, and bradycardia heart rhythm are hard to detect using either time-domain or frequency-domain features solely, and a time-frequency analysis is required to extract representative features. This paper studies the performance of two different spectrum representations, iris-spectrogram and scalogram, for different ECG beat waves in terms of recognition of normal, tachycardia, and bradycardia classes. These two different spectra are then sent to two different deep convolutional neural networks (CNN), i.e., Resnet101 and ShuffleNet, for deep feature extraction and classification. The results show that the best accuracy for detection of beats rhythm was using ResNet101 and scalogram of T-wave with an accuracy of 98.3%, while accuracy was 94.4% for detection using iris-spectrogram using also ResNet101 and QRS-Wave. Finally, based on these results we note that using deep features from time-frequency representation using one wave of ECG beat we can accurately detect basic rhythms such as normal, tachycardia, and bradycardia.
The Neoplastic Side of the Abdominal Wall: A Comprehensive Pictorial Essay of Benign and Malignant Neoplasms
Authors: Porrello Giorgia , Cannella Roberto , Alvarez-Hornia Pérez Eduardo , Brancatelli Giuseppe , Vernuccio Federica
Published: January 2023

Abdominal wall neoplasms are usually benign and, in the majority of these cases, no further work-up or treatment is indicated. The percentage of malignant abdominal neoplasms, however, is not negligible. Radiologists play a pivotal role in identifying imaging features that should favor malignancy, including larger lesion size, edema, neurovascular involvement, and peripheral or inhomogeneous dynamic enhancement, thus indicating to the clinician the need for further work-up. Histopathology is the reference standard for the characterization of abdominal wall neoplasms. In patients undergoing surgery, radiological assessment is needed to guide the surgeon by providing a comprehensive anatomic guide of the tumor extension. We present a pictorial review of benign and malignant abdominal wall neoplasms that can be encountered on radiological examinations, with a main focus on CT and MRI features that help in narrowing the differential diagnosis.
Polycystic Ovary Syndrome, Subclinical Hypothyroidism, the Cut-Off Value of Thyroid Stimulating Hormone; Is There a Link? Findings of a Population-Based Study
Authors: Rojhani Ehsan , Rahmati Maryam , Firouzi Faegheh , Saei Ghare Naz Marzieh , Azizi Fereidoun , Ramezani Tehrani Fahimeh
Published: January 2023

Despite solid evidence regarding the association of over-hypothyroidism with polycystic ovary syndrome (PCOS), the relationship between PCOS and subclinical hypothyroidism (SCH) is still a topic of debate. In the present population-based study, we aimed to assess if there is a difference between PCOS and the control group regarding the upper reference limit of thyroid stimulating hormone (TSH). We also aimed to identify the prevalence of SCH in women with PCOS compared to controls. This study was conducted on data collected in the Iranian PCOS prevalence study and the Khuzestan PCOS prevalence study. Participants that met our eligibility criteria were categorized into two groups: PCOS (n = 207) and control (n = 644). Quantile and logistic regression models were used to explore the effect of PCOS status on TSH cut-off values and SCH, respectively. The 95 percentiles of TSH were not significantly different in the PCOS group compared to control ones (6.12 and 6.56 microU/mL, respectively). There was no statistically significant association between PCOS status and SCH (OR adjusted: 1.40; 95%CI: 0.79, 2.50; p = 0.2). The prevalence of SCH and the upper reference limit of TSH were not significantly different in PCOS and controls. Investigation of SCH in women with PCOS might be questionable.
The Role of CRP POC Testing in the Fight against Antibiotic Overuse in European Primary Care: Recommendations from a European Expert Panel
Authors: Gentile Ivan , Schiano Moriello Nicola , Hopstaken Rogier , Llor Carl , Melbye Hasse , Senn Oliver
Published: January 2023

Tackling antibiotic resistance represents one of the major challenges in modern medicine, and limiting antibiotics’ overuse represents the first step in this fight. Most antibiotics are prescribed in primary care settings, and lower respiratory tract infections (LRTIs) are one of the most common indications for their prescription. An expert panel conducted an extensive report on C-reactive protein point-of-care (CRP POC) testing in the evaluation of LRTIs and its usefulness to limit antibiotic prescriptions. The expert panel stated that CRP POC testing is a potentially useful tool to limit antibiotic prescriptions for LRTI in a community setting. CRP POC must be used in conjunction with other strategies such as improved communication skills and the use of other molecular POC testing. Potential barriers to the adoption of CRP POC testing are financial and logistical issues. Moreover, the efficacy in limiting antibiotic prescriptions could be hampered by the fact that, in some countries, patients may gain access to antibiotics even without a prescription. Through the realization of a better reimbursement structure, the inclusion in standardized procedures in local guidelines, and better patient education, CRP point-of-care testing can represent a cornerstone in the fight against antimicrobial resistance.
The Clinical Impact of Metagenomic Next-Generation Sequencing (mNGS) Test in Hospitalized Patients with Suspected Sepsis: A Multicenter Prospective Study
Authors: Zuo Yi-Hui , Wu Yi-Xing , Hu Wei-Ping , Chen Yan , Li Yu-Ping , Song Zhen-Ju , Luo Zhe , Ju Min-Jie , Shi Min-Hua , Xu Shu-Yun , Zhou Hua , Li Xiang , Jie Zhi-Jun , Liu Xue-Dong , Zhang Jing
Published: January 2023

Background: Metagenomic Next Generation Sequencing (mNGS) has the potential to detect pathogens rapidly. We aimed to assess the diagnostic performance of mNGS in hospitalized patients with suspected sepsis and evaluate its role in guiding antimicrobial therapy. Methods: A multicenter, prospective cohort study was performed. We enrolled patients with suspected sepsis, collected clinical characteristics and blood samples, and recorded the 30-day survival. Diagnostic efficacy of mNGS test and blood culture was compared, and the clinical impact of mNGS on antibiotic regimen modification was analyzed. Results: A total of 277 patients were enrolled, and 162 were diagnosed with sepsis. The mortality was 44.8% (121/270). The mNGS test exhibited shorter turn-out time (27.0 (26.0, 29.0) vs. 96.0 (72.0, 140.3) hours, p < 0.001) and higher sensitivity (90.5% vs. 36.0%, p < 0.001) compared with blood culture, especially for fungal infections. The mNGS test showed better performance for patients with mild symptoms, prior antibiotic use, and early stage of infection than blood culture, and was capable of guiding antibiotic regimen modification and improving prognosis. Higher reads of pathogens detected by mNGS were related to 30-day mortality (p = 0.002). Conclusions: Blood mNGS testing might be helpful for early etiological diagnosis of patients with suspected sepsis, guiding the antibiotic regimen modification and improving prognosis.
Prognostic Role of CD200 in Acute Lymphoblastic Leukemia Patients
Authors: Khalil Mohamed , Elsharkawy Nahla , Elmawardy Mona Mohsen , Ayoub Mahmoud Aly
Published: January 2023

Background: Overexpression of CD200 in ALL patients indicates that it may be useful in the characterization of leukemia initiating cells (LIC). We aim at investigating the expression pattern of CD200 on leukemic B cells and the correlation of CD200 expression with various clinical and laboratory findings in 62 newly diagnosed acute lymphoblastic leukemia patients. Methods: All patients were subjected to full history taking, a thorough clinical examination, and laboratory investigations, which included complete blood count (CBC), BM aspiration, immunophenotyping of blast cells, and CD200 expression. Results: There is a higher statistically significant mean value of CD200 expression among the cases (66.15 ± 23.08) than the control group (0.37 ± 0.2) (p value ≤ 0.001). CD200 expression shows a significant correlation with total leucocytic count and hemoglobin level (p = 0.001, 0.03, respectively). Conclusions: This study showed that CD200 expression was expressed in 100% of the patients. Correlations between CD200 expression and different laboratory data of patients revealed that there was an impact of CD200 on different diagnostic findings. After the follow-up of the patients, we found that the use of PRISM function of the software could add value to the detection of minimal residual disease.
Utilisation of 3D Printing in the Manufacturing of an Anthropomorphic Paediatric Head Phantom for the Optimisation of Scanning Parameters in CT
Authors: Jusufbegović Merim , Pandžić Adi , Busuladžić Mustafa , Čiva Lejla M. , Gazibegović-Busuladžić Azra , Šehić Adnan , Vegar-Zubović Sandra , Jašić Rahima , Beganović Adnan
Published: January 2023

Computed tomography (CT) is a diagnostic imaging process that uses ionising radiation to obtain information about the interior anatomic structure of the human body. Considering that the medical use of ionising radiation implies exposing patients to radiation that may lead to unwanted stochastic effects and that those effects are less probable at lower doses, optimising imaging protocols is of great importance. In this paper, we used an assembled 3D-printed infant head phantom and matched its image quality parameters with those obtained for a commercially available adult head phantom using the imaging protocol dedicated for adult patients. In accordance with the results, an optimised scanning protocol was designed which resulted in dose reductions for paediatric patients while keeping image quality at an adequate level.
3D Reconstruction of Wrist Bones from C-Arm Fluoroscopy Using Planar Markers
Authors: Shrestha Pragyan , Xie Chun , Shishido Hidehiko , Yoshii Yuichi , Kitahara Itaru
Published: January 2023

In orthopedic surgeries, such as osteotomy and osteosynthesis, an intraoperative 3D reconstruction of the bone would enable surgeons to quickly assess the fracture reduction procedure with preoperative planning. Scanners equipped with such functionality are often more expensive than a conventional C-arm fluoroscopy device. Moreover, a C-arm fluoroscopy device is commonly available in many orthopedic facilities. Based on the widespread use of such equipment, this paper proposes a method to reconstruct the 3D structure of bone with a conventional C-arm fluoroscopy device. We focus on wrist bones as the target of reconstruction in this research as this will facilitate a flexible imaging scheme. Planar markers are attached to the target object and are tracked in the fluoroscopic image for C-arm pose estimation. The initial calibration of the device is conducted using a checkerboard pattern. In general, reconstruction algorithms are sensitive to geometric calibration errors. To assess the practicality of the method for reconstruction, a simulation study demonstrating the effect of checkerboard thickness and spherical marker size on reconstruction quality was conducted.
Distributed Motion Planning for Multiple Quadrotors in Presence of Wind Gusts
Authors: Abichandani Pramod , Lobo Deepan , Muralidharan Meghna , Runk Nathan , McIntyre William , Bucci Donald , Benson Hande
Published: January 2023

This work demonstrates distributed motion planning for multi-rotor unmanned aerial vehicle in a windy outdoor environment. The motion planning is modeled as a receding horizon mixed integer nonlinear programming (RH-MINLP) problem. Each quadrotor solves an RH-MINLP to generate its time-optimal speed profile along a minimum snap spline path while satisfying constraints on kinematics, dynamics, communication connectivity, and collision avoidance. The presence of wind disturbances causes the motion planner to continuously regenerate new motion plans, thereby significantly increasing the computational time and possibly leading to safety violations. Control Barrier Functions (CBFs) are used for assist in collision avoidance in the face of wind disturbances while alleviating the need to recalculate the motion plans continually. The RH-MINLPs are solved using a novel combination of heuristic and optimal methods, namely Simulated Annealing and interior-point methods, respectively, to handle discrete variables and nonlinearities in real-time feasibly. The framework is validated in simulations featuring up to 50 quadrotors and Hardware-in-the-loop (HWIL) experiments, followed by outdoor field tests featuring up to 6 DJI M100 quadrotors. Results demonstrate (1) fast online motion planning for outdoor communication-centric multi-quadrotor operations and (2) the utility of CBFs in providing effective motion plans.
The Effects of Spatial Resolution and Resampling on the Classification Accuracy of Wetland Vegetation Species and Ground Objects: A Study Based on High Spatial Resolution UAV Images
Authors: Chen Jianjun , Chen Zizhen , Huang Renjie , You Haotian , Han Xiaowen , Yue Tao , Zhou Guoqing
Published: January 2023

When employing remote sensing images, it is challenging to classify vegetation species and ground objects due to the abundance of wetland vegetation species and the high fragmentation of ground objects. Remote sensing images are classified primarily according to their spatial resolution, which significantly impacts the classification accuracy of vegetation species and ground objects. However, there are still some areas for improvement in the study of the effects of spatial resolution and resampling on the classification results. The study area in this paper was the core zone of the Huixian Karst National Wetland Park in Guilin, Guangxi, China. The aerial images (Am) with different spatial resolutions were obtained by utilizing the UAV platform, and resampled images (An) with different spatial resolutions were obtained by utilizing the pixel aggregation method. In order to evaluate the impact of spatial resolutions and resampling on the classification accuracy, the Am and the An were utilized for the classification of vegetation species and ground objects based on the geographic object-based image analysis (GEOBIA) method in addition to various machine learning classifiers. The results showed that: (1) In multi-scale images, both the optimal scale parameter (SP) and the processing time decreased as the spatial resolution diminished in the multi-resolution segmentation process. At the same spatial resolution, the SP of the An was greater than that of the Am. (2) In the case of the Am and the An, the appropriate feature variables were different, and the spectral and texture features in the An were more significant than those in the Am. (3) The classification results of various classifiers in the case of the Am and the An exhibited similar trends for spatial resolutions ranging from 1.2 to 5.9 cm, where the overall classification accuracy increased and then decreased in accordance with the decrease in spatial resolution. Moreover, the classification accuracy of the Am was higher than that of the An. (4) When vegetation species and ground objects were classified at different spatial scales, the classification accuracy differed between the Am and the An.
Reconciling Registration Policies for Unmanned Aircraft with Unmanned Aircraft Ownership Characteristics
Authors: Henderson Isaac Levi
Published: January 2023

Registration of unmanned aircraft is a common policy around the world and forms part of the International Civil Aviation Organisation’s model regulations for unmanned aircraft. This study conducts a review of the various registration policies that have been implemented amongst advanced economies to find commonalities and differences. New Zealand is then used as a case study. The country does not currently have registration of unmanned aircraft; however, their Ministry of Transport has put forward the idea of implementing a registration scheme. As part of this case study, the ownership characteristics of 919 New Zealand unmanned aircraft users were collected using an online survey. The results highlight that personally owned aircraft tend to only be used by their owner, with the number of users being lower than the number of aircraft. For organisationally owned aircraft, there are multiple users per aircraft; however, these users tend to only be employees of the organisation. These findings suggest that for New Zealand, the best way to implement a registration scheme would be to register users and organisations rather than individual aircraft. While specific to New Zealand, these findings also prompt the need for future research worldwide to see whether registration schemes reconcile with ownership data.
Gamification in a News English Course
Authors: Wang Yi-Chien
Published: January 2023

Studies examining the link between gamification and News English learning are scant. This study explored the effects of a gamified learning activity using the card games, slides, and learning sheets (CSCL) model on News English learning performance through a quasi-experimental mixed-methods study design. Pretests and post-tests and students’ self-reflections were employed to determine the students’ learning performance and responses to the activity. Gamification significantly and positively affected the experimental group’s (EG) News English learning performance, with the learning performance of both lower and higher achievers improving significantly. Furthermore, the EG participants regarded the activity to be a fun and interactive hands-on experience. Gamification was considered useful for content comprehension and vocabulary acquisition. The mechanisms through which the activity affected News English learning were analyzed, and implications for gamification application in News English and further research are presented.
Innovative Higher Education Approaches for Power System Courses
Authors: Bompard Ettore , Estebsari Abouzar , Mazza Andrea , Pons Enrico , Solida Lorenzo
Published: January 2023

Higher education plays a crucial role in modern society and in emerging energy systems, due to the rising complexity of the phenomena and the interplay among various layers (physical, cyber, social and economic). To cope with this context, universities need to develop new visions and tools for education and training. Real-time simulation (RTS) is emerging as a novel and effective approach to analyzing power system aspects, and this characteristic can be effectively used in power system courses. Hence, after the presentation of the basics about the RTS, the paper will show the advantages of employing RTS for teaching activities. Finally, two examples of didactic activities involving RTS at Politecnico di Torino will be presented. In fact, RTS is part of both multi-disciplinary projects (where students with different backgrounds can face the issues affecting the protection and control of power systems) and the course “Electrical systems and safety”, where RTS is used to study the behavior of voltage transformers in saturation.
Investigating the User Interface Design Frameworks of Current Mobile Learning Applications: A Systematic Review
Authors: Ahmad Faudzi Masyura , Che Cob Zaihisma , Omar Ridha , Sharudin Sharul Azim , Ghazali Masitah
Published: January 2023

Online learning has replaced traditional face-to-face classroom instruction in the educational system. Learning via mobile, or mobile learning, is one of the solutions that most learners use since it is less expensive and easier to adopt on the go. However, in addition to hindering information transfer, issues such as small screen size and bad interface design can also make learning more cognitively demanding. This paper presents a systematic literature review on the user interface design of mobile learning applications based on the preferred reporting items for systematic reviews and meta-analyses approach. Articles selected for this study were published after the COVID-19 outbreak, between 2020 and 2022. The goal of this research was to outline the current user interface design criteria and guidelines applied when designing a mobile learning application and explore how these factors affect the learner’s cognitive load. It also aimed to identify potential research gaps and future opportunities in the creation of a UID guideline/framework for mobile learning. The findings of this study may be used as a guideline for designers, developers, educators, instructors, and others who are interested in creating a mobile learning application that provides learners with an effective knowledge and mobile learning experience.
A Skin Disease Classification Model Based on DenseNet and ConvNeXt Fusion
Authors: Wei Mingjun , Wu Qiwei , Ji Hongyu , Wang Jingkun , Lyu Tao , Liu Jinyun , Zhao Li
Published: January 2023

Skin disease is one of the most common diseases. Due to the intricate categories of skin diseases, their symptoms being very similar in the early stage, and the lesion samples being extremely unbalanced, their classification is challenging. At the same time, under the conditions of limited data, the generalization ability of a single reliable convolutional neural network model is weak, the feature extraction ability is insufficient, and the classification accuracy is low. Therefore, in this paper, we proposed a convolutional neural network model for skin disease classification based on model fusion. Through model fusion, deep and shallow feature fusion, and the introduction of an attention module, the feature extraction capacity of the model was strengthened. In addition, a series of works such as model pre-training, data augmentation, and parameter fine-tuning were conducted to upgrade the classification performance of the model. The experimental results showed that when working on our private dataset dominated by acne-like skin diseases, our proposed model outperformed the two baseline models of DenseNet201 and ConvNeXt_L by 4.42% and 3.66%, respectively. On the public HAM10000 dataset, the accuracy and f1-score of the proposed model were 95.29% and 89.99%, respectively, which also achieved good results compared with other state-of-the-art models.
Saliency Detection Based on Low-Level and High-Level Features via Manifold-Space Ranking
Authors: Li Xiaoli , Liu Yunpeng , Zhao Huaici
Published: January 2023

Saliency detection as an active research direction in image understanding and analysis has been studied extensively. In this paper, to improve the accuracy of saliency detection, we propose an efficient unsupervised salient object detection method. The first step of our method is that we extract local low-level features of each superpixel after segmenting the image into different scale parts, which helps to locate the approximate locations of salient objects. Then, we use convolutional neural networks to extract high-level, semantically rich features as complementary features of each superpixel, and low-level features, as well as high-level features of each superpixel, are incorporated into a new feature vector to measure the distance between different superpixels. The last step is that we use a manifold space-ranking method to calculate the saliency of each superpixel. Extensive experiments over four challenging datasets indicate that the proposed method surpasses state-of-the-art methods and is closer to the ground truth.
An Ensemble Learning Approach for Reversible Data Hiding in Encrypted Images with Fibonacci Transform
Authors: Panchikkil Shaiju , Vegesana Siva Priya , Manikandan V. M. , Donta Praveen Kumar , Maddikunta Praveen Kumar Reddy , Gadekallu Thippa Reddy
Published: January 2023

Reversible data hiding (RDH) is an active area of research in the field of information security. In RDH, a secret can be embedded inside a cover medium. Unlike other data-hiding schemes, RDH becomes important in applications that demand recovery of the cover without any deformation, along with recovery of the hidden secret. In this paper, a new RDH scheme is proposed for performing reversible data hiding in encrypted images using a Fibonacci transform with an ensemble learning method. In the proposed scheme, the data hider encrypts the original image and performs further data hiding. During data hiding, the encrypted image is partitioned into non-overlapping blocks, with each block considered one-by-one. The selected block undergoes a series of Fibonacci transforms during data hiding. The number of Fibonacci transforms required on a selected block is determined by the integer value that the data hider wants to embed. On the receiver side, message extraction and image restoration are performed with the help of the ensemble learning method. The receiver will try to perform all possible Fibonacci transforms and decrypt the blocks. The recovered block is identified with the help of trained machine-learning models. The novelty of the scheme lies in (1) retaining the encrypted pixel intensities unaltered while hiding the data. Almost every RDH scheme described in the literature alters the encrypted pixel intensities to embed the data, which represents a security concern for the encryption algorithm; (2) Introducing an efficient means of recovery through an ensemble model framework. The majority of votes from the different trained models guarantee the correct recovery of the cover image. The proposed scheme enables reduction in the bit error rate during message extraction and contributes to ensuring the suitability of the scheme in areas such as medical image transmission and cloud computing. The results obtained from experiments undertaken show that the proposed RDH scheme was able to attain an improved payload capacity of 0.0625 bits per pixel, outperforming many related RDH schemes with complete reversibility.
Packet Loss Optimization in Router Forwarding Tasks Based on the Particle Swarm Algorithm
Authors: Ghani Rana Fareed , Al-Jobouri Laith
Published: January 2023

Software-defined networks (SDNs) are computer networks where parameters and devices are configured by software. Recently, artificial intelligence aspects have been used for SDN programs for various applications, including packet classification and forwarding according to the quality of service (QoS) requirements. The main problem is that when packets from different applications pass through computer networks, they have different QoS criteria. To meet the requirements of packets, routers classify these packets, add them to multiple weighting queue systems, and forward them according to their priorities. Multiple queue systems in routers usually use a class-based weighted round-robin (CBWRR) scheduling algorithm with pre-configured fixed weights for each priority queue. The problem is that the intensity of traffic in general and of each packet class occasionally changes. Therefore, in this work, we suggest using the particle swarm optimization algorithm to find the optimal weights for the weighted fair round-robin algorithm (WFRR) by considering the variable densities of the traffic. This work presents a framework to simulate router operations by determining the weights and schedule packets and forwarding them. The proposed algorithm to optimize the weights is compared with the conventional WFRR algorithm, and the results show that the particle swarm optimization for the weighted round-robin algorithm is more efficient than WFRR, especially in high-intensity traffic. Moreover, the average packet-loss ratio does not exceed 7%, and the proposed algorithms are better than the conventional CBWRR algorithm and the related work results.
Acknowledgment to the Reviewers of Epidemiologia in 2022
Authors:   Epidemiologia Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Effects of Extreme Drought and Heat Events on Leaf Metabolome of Black Alder (Alnus glutinosa L.) Growing at Neighboring Sites with Different Water Availability
Authors: Zhu Lijun , Liao Zhengqiao , Liu Lei , Du Baoguo
Published: January 2023

Riparian tree species are thought to be sensitive to the more frequent and intensive drought and heat events that are projected to occur in the future. However, compared to waterlogging, information about the responses of these tree species to water limitation and heat is still scare. Black alder (Alnus glutinosa L.) is a riparian tree species with significant ecological and economic importance in Europe. In the present study, we investigated the physiological responses of black alder (Alnus glutinosa L.) to different water availabilities growing at neighboring sites. Compared to trees with unlimited water source, trees with a limited water source had 20% lower leaf hydration, 39% less H2O2 contents, and 34% lower dehydroascorbate reductase activities. Concurrent with dramatically accumulated glutathione and phenolic compounds, leaf glutathione contents were two times higher in trees with limited water than in trees with sufficient water. Limited water availability also resulted in increased abundances of sugars, sugar acids, and polyols. Serine, alanine, as well as soluble protein related to nitrogen metabolism were also accumulated under limited water conditions. In contrast to sulfate, leaf phosphate contents were significantly increased under limited water. No significant effects of water conditions on malondialdehyde and ascorbate contents and fatty acid abundances were observed. The present study improves our understanding of the physiological responses of black alder to different water conditions. Our findings highlight this riparian species is at least to some extent resistant to future drought with a well-regulated system including antioxidative and metabolic processes and its potential as an admixture candidate for afforestation in either water-logged or dry areas, particularly in nitrogen limited habitats.
Evaluation of Plant Growth and Potential of Carbon Storage in the Restored Mangrove of an Abandoned Pond in Lubuk Kertang, North Sumatra, Indonesia
Authors: Amelia Rizka , Basyuni Mohammad , Alfinsyahri Alfinsyahri , Sulistiyono Nurdin , Slamet Bejo , Bimantara Yuntha , Harahap Salma Safrina Hashilah , Harahap Mikrajni , Harahap Insar Maulid , Al Mustaniroh Shofiyah Sabilah , Sasmito Sigit D. , Arifanti Virni Budi
Published: January 2023

Mangrove forest in Lubuk Kertang Village, West Brandan sub-district has been converted around 20 ha annually (1996–2016) into various non-forest land use. Rehabilitation can be a solution to restore the condition of the ecosystem so that it can resume its ecological and economic functions. This paper discusses the evaluation of mangrove rehabilitation carried out by planting 6000 propagules in December 2015 and 5000 seedlings in May 2016 with Rhizophora apiculata species in abandoned ponds. Monitoring was carried out every 6 months from 2016 to 2022. In the restored area, 11 true mangrove species and 3 associated mangrove species were found. The percentage of plants that survived after seven years was 69.42% for planting using propagules and 86.38% for planting with seedlings. The total biomass carbon stocks stored by 7-year-old plants using propagules was 51.18 Mg ha−1, while the carbon stored by planting using seedlings was 56.79 Mg ha−1. Soil carbon stocks at the planted site with propagules were 506.89 ± 250.74 MgC ha−1, and at the planted site with seedlings were 461.85 ± 102.23 MgC ha−1. The total ecosystem carbon stocks (including aboveground carbon) in the planted site using propagules were 558.07 MgC ha−1, while planting using seedlings were 518.64 MgC ha−1. The dataset and findings on the carbon storage evaluation of mangrove rehabilitation will be useful for blue carbon research community and policymakers in the context of the climate change mitigation strategy for Indonesia.
Variability in Snowpack Isotopic Composition between Open and Forested Areas in the West Siberian Forest Steppe
Authors: Pershin Dmitry , Malygina Natalia , Chernykh Dmitry , Biryukov Roman , Zolotov Dmitry , Lubenets Lilia
Published: January 2023

The stable water isotopes in snow (primarily 18O and 2H) are widely used for tracing hydrological and ecological processes. However, isotopic signatures of snow can be significantly modified by topography and land cover. This study assesses spatial and temporal variability of the bulk snowpack isotopic composition (δ18O, δ2H, d-excess) between forested (pine and birch) and open areas in the West Siberian forest steppes. Isotopic samples were collected over the peak snow accumulation in 2017–2019. The snow isotopic composition within forested areas differed from open steppes, mainly in reducing d-excess (1.6‰ on average). We did not find a significant effect of canopy interception on snow enrichment in heavier isotopes. Snowpack in the pine forests was even lighter by 3.6‰ for δ2H compared to open areas, probably, due to low energy inputs and interception capacity. Additionally, snow depth significantly influenced the isotopic composition spatial variability. As snow depth increased, δ18O and δ2H values decreased due to conservation within the snowpack and less influence of sublimation and moisture exchange with the soil. However, this pattern was only evident in winters with below-average snow depth. Therefore, taking into account snow depth spatial and seasonal variability is advisable when applying the isotopic methods.
Polyculture of Pacific White Shrimp Litopenaeus vannamei (Boone) and Red Seaweed Gracilaria birdiae (Greville) under Different Densities
Authors: Henry-Silva Gustavo Gonzaga , Alves Joseanna , Flickinger Dallas , Gomes-Rebouças Renata , Bessa-Junior Ambrosio
Published: January 2023

The present study evaluated a polyculture system with Pacific white shrimp (Litopenaeus vannamei) and the macroalga Gracilaria birdiae and its potential to remove nutrients. The experimental design consisted of a shrimp monoculture of 100 animals/m2 (T0) and three multitrophic cultures with L. vannamei (100 animals/m2) and with G. birdiae at densities of 500 (T500), 1000 (T1000), and 2000 (T2000) g/m2. Nitrogen and phosphorus concentrations decreased at the beginning of the experiment in the treatments with macroalgae, but this reduction was not maintained throughout the cultivation period. The stable values of G. birdiae biomass were perhaps related to the high turbidity of the water. There was an increase in shrimp biomass during cultivation, which reached the final individual averages of 7.5 g (T0), 7.6 g (T500), 5.9 g (T1000), and 7.5 g (T2000), with no significant differences between treatments. Nevertheless, the absence of macroalgae growth provides no added profit for the producer. Thus, there is no economic advantage in using G. birdiae in an integrated multitrophic system with L. vannamei at a high density and conditions of high water turbidity.
Review on the Antiviral Organic Agents against Fish Rhabdoviruses
Authors: Sun Shuang-Shuang , Ma Shi-Wei , Li Jun , Zhang Qin , Zhou Guang-Zhou
Published: January 2023

Fish rhabdoviruses are harmful single-stranded RNA viruses with high mortality rates which cause considerable economic losses in aquaculture. It is imperative to explore and develop new antiviral compounds against them. In recent years, in addition to inorganic antiviral substances, more than 50 different organic compounds have been confirmed to be effective in the prevention and treatment of rhabdovirus infection and its dissemination in fish. The main types of extracts or agents and their trial designs are here considered for review. This review reveals the reported antiviral activities of extracts from organisms, proteins, lipids, polysaccharides, nucleic acids, coumarin derivatives, arctigenin derivatives, and other antiviral organic molecules against fish rhabdoviruses, respectively. Additionally, their antiviral mechanisms of action include direct virucidal effects, inhibiting virus-induced host cell apoptosis, the blocking of the viral replication cycle, affecting gene expression and innate antiviral immune responses, and so on. This review also gives perspectives on how to comprehensively explore the potential applications of the candidate molecules, which lay the foundation for the future development of new compounds or strategies for the prevention and control of fish rhabdoviruses in aquaculture.
The Effects of Buoyancy on Laminar Heat Transfer Rates to Supercritical CO2 in Vertical Upward Flows
Authors: Viswanathan Krishnamoorthy , Krishnamoorthy Gautham
Published: January 2023

Buoyancy effects in vertical, upward laminar flows can result in an augmentation in heat transfer rates to supercritical CO2 (sCO2) near its pseudocritical temperature (TPC). This is in contrast to corresponding flows in the turbulent regime, or laminar sCO2 flows (with minimum buoyancy effects), where a deterioration in heat transfer near TPC, followed by a recovery phase, have been observed. To exploit these sCO2 heat transfer enhancement characteristics and improve heat exchange efficiencies, the location of the TPC pinch point and the variables controlling these buoyancy effects need to be identified. To fill this void, numerical simulations of sCO2 (at inlet: 8.2 MPa, 265 K) in vertical circular tubes of diameters (D) 0.2–2 mm, heated with constant wall heat fluxes (Q) of 1–4 kW/m2) and inlet Reynolds numbers (Re) of 100, 400, were carried out. The tube lengths were varied to maintain an exit temperature of 320 K (TPC~309 K). The results indicated that buoyancy-augmented laminar heat transfer rates may be expected when Gr/Re2.7 > 10−4 (Gr = Grashof number). A modified Nusselt number correlation in terms of (Gr/Re) is proposed and is observed to fit the observed variations within a mean absolute percentage error < 15%, in most regions.
Advanced Glycation End Products and Nitrosamines in Sausages Influenced by Processing Parameters, Food Additives and Fat during Thermal Processing
Authors: Lu Jingnan , Li Mingyu , Shen Mingyue , Xie Jianhua , Xie Mingyong
Published: January 2023

Advanced glycation end products (AGEs) and nitrosamines (NAs) in sausage are associated with pathogenic and carcinogenic risks. However, the multiple reaction parameters affecting the production of AGEs and NAs during sausage processing remain unclear. This experiment evaluated the effects of processing parameters, food additives and fat ratios on the formation of AGEs and NAs in sausages. The results showed a 2–3-fold increase in Nε-(carboxymethyl)lysine (CML) and Nε-(carboxyethyl)lysine (CEL) when the sausage processing temperature was increased from 90 °C to 130 °C, and N-nitrosodimethylamine (NDEA) increased from 3.68 ng/g to 6.41 ng/g. The addition of salt inhibited the formation of AGEs and NAs, and the inhibitory ability of 2 g/100 g of salt was 63.6% for CML and 36.5% for N-nitrosodimethylamine (NDMA). The addition of 10 mg/kg nitrite to sausages reduced CML formation by 43.9%, however, nitrite had a significant contribution to the formation of NAs. The addition of fat only slightly contributed to the production of CML. In addition, the relationship between α-dicarbonyl compounds and the formation of AGEs was investigated by measuring the changes in α-dicarbonyl compounds in sausages. The results showed two trends of AGEs and α-dicarbonyl compounds: AGEs increased with the increase in α-dicarbonyl compounds and AGE level increased but α-dicarbonyl compound level decreased.
Progress in the Conversion of Ginsenoside Rb1 into Minor Ginsenosides Using β-Glucosidases
Authors: Zhu Hongrong , Zhang Rui , Huang Zunxi , Zhou Junpei
Published: January 2023

In recent years, minor ginsenosides have received increasing attention due to their outstanding biological activities, yet they are of extremely low content in wild ginseng. Ginsenoside Rb1, which accounts for 20% of the total ginsenosides, is commonly used as a precursor to produce minor ginsenosides via β-glucosidases. To date, many research groups have used different approaches to obtain β-glucosidases that can hydrolyze ginsenoside Rb1. This paper provides a compilation and analysis of relevant literature published mainly in the last decade, focusing on enzymatic hydrolysis pathways, enzymatic characteristics and molecular mechanisms of ginsenoside Rb1 hydrolysis by β-glucosidases. Based on this, it can be concluded that: (1) The β-glucosidases that convert ginsenoside Rb1 are mainly derived from bacteria and fungi and are classified as glycoside hydrolase (GH) families 1 and 3, which hydrolyze ginsenoside Rb1 mainly through the six pathways. (2) Almost all of these β-glucosidases are acidic and neutral enzymes with molecular masses ranging from 44–230 kDa. Furthermore, the different enzymes vary widely in terms of their optimal temperature, degradation products and kinetics. (3) In contrast to the GH1 β-glucosidases, the GH3 β-glucosidases that convert Rb1 show close sequence-function relationships. Mutations affecting the substrate binding site might alter the catalytic efficiency of enzymes and yield different prosapogenins. Further studies should focus on elucidating molecular mechanisms and improving overall performances of β-glucosidases for better application in food and pharmaceutical industries.
Genetic Dissection and Germplasm Selection of the Low Crude Fiber Component in Brassica napus L. Shoots
Authors: Shi Rui , Pang Chengke , Wu Xu , Zhao Xiaozhen , Chen Feng , Zhang Wei , Sun Chengming , Fu Sanxiong , Hu Maolong , Zhang Jiefu , Wang Xiaodong
Published: January 2023

Background: Brassica napus is one of the most important oil crops in the world, and B. napus shoots are nutrient-rich fresh vegetables. The crude fiber (CF) component is one of the most important factors affecting the taste quality of B. napus shoots, but the factors underlying the desirable low-CF trait remain poorly understood. Methods: In this study, a high-density single-nucleotide polymorphism (SNP) map was used to map quantitative trait loci (QTLs) for five CF-related traits in a recombinant inbred population. Results: A total of 49 QTLs were obtained in four environments, including eleven, twelve, eight, twelve and six QTLs for content of neutral detergent fiber, acid detergent fiber, acid detergent lignin, hemicellulose and cellulose, respectively. The phenotypic variation explained by single QTL ranged from 4.62% to 14.76%. Eight of these QTLs were further integrated into four unique QTLs, which controlled two different traits simultaneously. Five CF-component-related candidate genes were identified, among which BnaC03g07110D and BnaC07g21271D were considered to be the most likely candidate genes. In addition, five lines with low CF content were selected, which can be used as excellent germplasm resources in breeding. Conclusions: The QTLs identified in this study will contribute to our understanding of the genetic mechanism of CF and can be used as targets for reducing CF content in B. napus shoots. In addition, this study also provided excellent germplasm resources for low CF content breeding.
Role of Microorganisms in the Development of Quality during the Fermentation of Salted White Herring (Ilisha elongata)
Authors: Wu Jiajia , Mao Haiping , Dai Zhiyuan
Published: January 2023

Salted white herring (Ilisha elongata) is a popular fish product in the coastal region of China. The complex endogenous enzymes and microbial action determine the quality of a traditionally salted herring. In order to investigate the role of microorganisms in the quality formation of salted herring, three groups for different salting processes were established: traditional salted (TS), non-starter salted (NS), and starter culture salted (SS). The predominant microorganism in each processing group was Staphylococcus spp., as inferred by next-generation sequencing data. Different physicochemical parameters were obtained in each of the three processing groups (TCA-soluble peptide (trichloroacetic acid-soluble peptide), TVB-N (Total volatile basic nitrogen), and TBA values (thiobarbituric acid-reactive substance)). The TS group had the maximum level of total biogenic amines, while the SS group had the lowest. A strong positive correlation was found between Staphylococcus and 14 aromatic compounds, of which 5 were odor-active compounds that created fishy, grassy, fatty, and fruity flavors. Shewanella may produce trimethylamine, which is responsible for the salted herrings’ fishy, salty, and deteriorating flavor. The findings demonstrated that autochthonous strains of Staphylococcus saprophyticus M90–61 were useful in improving product quality because they adapted quickly to the high osmotic environment.
‘Nutritional Footprint’ in the Food, Meals and HoReCa Sectors: A Review
Authors: Zarzo Inmaculada , Soler Carla , Fernandez-Zamudio Maria-Angeles , Pina Tatiana , Barco Héctor , Soriano Jose M.
Published: January 2023

Nowadays, the food industry is integrating environmental, social, and health parameters to increase its sustainable impact. To do this, they are using new tools to calculate the potential efficiency of nutritional products with lower levels of environmental impact. One of these tools is called the ‘nutritional footprint’, created by Wuppertal Institute for Climate, Environment and Energy GmbH. This study aims to review this concept and clarify its historical development, its use in several sectors of the food industry, and its transformation from a manual to an online tool. Results reflected that it is a suitable indicator that integrates nutritional, environmental, and social-economic dimensions to help the decision-making process in the procurement of more sustainable products and, although it is limited to Germany due to the use of the national standard nutritional intakes of Germany, its importance lies in the fact that is a promising instrument to promote environmental sustainability in the context of food, meals, and the hotel, restaurant and catering (HoReCa) sectors.
Coffee Consumption during the COVID Pandemic in a Portuguese Sample: An Online Exploratory Study
Authors: Batista Patrícia , Afonso Anabela , Monteiro Maria João , Pintado Manuela , Oliveira-Silva Patrícia
Published: January 2023

Background: Coffee is one of the most consumed beverages worldwide and is part of the Portuguese lifestyles. This study aims to describe coffee consumption during the COVID-19 pandemic, the change in consumption, the relation between work and familiar pressure during the COVID-19 pandemic and coffee consumption, and the reasons for this consumption pattern. Methods: This is a cross-sectional study conducted by an online questionnaire (n = 463) between March and June 2020. During the data collection phase, information about coffee consumption and socio-demographic characteristics were gathered. Results: All respondents were and are coffee consumers. The coffee average intake before the COVID-19 pandemic was 2.40 ± 0.84 cups of coffee per day, and the average consumption during the COVID-19 confinement was 2.68 ± 0.88 cups. Consumption increased during the COVID-19 pandemic, but a correlation between the consumption changes and the familiar or work pressure was not found. The general reasons for the increase in the coffee consumption were “social/cultural” (27%), “the search for energy “boost”” (22.9%), “to feel awake” (22.7%), “to deal with stress” (22.7%) and “the taste” (21.8%). Conclusions: The results suggest the ever-increasing popularity of coffee consumption. Respondents also highlighted that some situations make them more prone to consume coffee consumption, such as when they face stress and the need to control tiredness. The COVID pandemic depleted a change in behaviors.
Acknowledgment to the Reviewers of Forecasting in 2022
Authors:   Forecasting Editorial Office
Published: January 2023

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