bluuebunny/crossref_metadata_2025 huggingface dataset:
Lipid Droplets from Plants and Microalgae: Characteristics, Extractions, and Applications
Authors: Xu Kaiwei , Zou Wen , Peng Biao , Guo Chao , Zou Xiaotong
Published: April 2023

Plant and algal LDs are gaining popularity as a promising non-chemical technology for the production of lipids and oils. In general, these organelles are composed of a neutral lipid core surrounded by a phospholipid monolayer and various surface-associated proteins. Many studies have shown that LDs are involved in numerous biological processes such as lipid trafficking and signaling, membrane remodeling, and intercellular organelle communications. To fully exploit the potential of LDs for scientific research and commercial applications, it is important to develop suitable extraction processes that preserve their properties and functions. However, research on LD extraction strategies is limited. This review first describes recent progress in understanding the characteristics of LDs, and then systematically introduces LD extraction strategies. Finally, the potential functions and applications of LDs in various fields are discussed. Overall, this review provides valuable insights into the properties and functions of LDs, as well as potential approaches for their extraction and utilization. It is hoped that these findings will inspire further research and innovation in the field of LD-based technology.
Molecular Characterization Related to Ovary Early Development Mechanisms after Eyestalk Ablation in Exopalaemon carinicauda
Authors: Jia Shaoting , Li Jitao , Lv Jianjian , Ren Xianyun , Wang Jiajia , Wang Qiong , Liu Ping , Li Jian
Published: April 2023

Eyestalk ablation is an effective method to promote ovarian development in crustaceans. Herein, we performed transcriptome sequencing of ovary and hepatopancreas tissues after eyestalk ablation in Exopalaemon carinicauda to identify genes related to ovarian development. Our analyses led to the identification of 97,383 unigenes and 190,757 transcripts, with an average N50 length of 1757 bp. In the ovary, four pathways related to oogenesis and three related to oocyte rapid growth were enriched. In the hepatopancreas, two vitellogenesis-associated transcripts were identified. Furthermore, short time-series expression miner (STEM) and gene ontology (GO) enrichment analyses revealed five terms related to gamete generation. In addition, two-color fluorescent in situ hybridization results suggested that dmrt1 might play a vital role in oogenesis during the early stage of ovarian development. Overall, our insights should support future studies focusing on investigating oogenesis and ovarian development in E. carinicauda.
Prostate Cancer: From Molecular Imaging to Immunological and Target Therapies
Authors: Filippi Luca , Chiaravalloti Agostino
Published: April 2023

Prostate cancer (PCa) is one of the most common malignancies and a leading cause of cancer-related deaths, affecting a million people worldwide with a particularly high burden in countries with a low human development index [...]
Ouabain Reverts CUS-Induced Disruption of the HPA Axis and Avoids Long-Term Spatial Memory Deficits
Authors: Leite Jacqueline Alves , Orellana Ana Maria , Andreotti Diana Zukas , Matumoto Amanda Midori , de Souza Ports` Natacha Medeiros , de Sá Lima Larissa , Kawamoto Elisa Mitiko , Munhoz Carolina Demarchi , Scavone Cristoforo
Published: April 2023

Ouabain (OUA) is a cardiotonic steroid that modulates Na+, K+ -ATPase activity. OUA has been identified as an endogenous substance that is present in human plasma, and it has been shown to be associated with the response to acute stress in both animals and humans. Chronic stress is a major aggravating factor in psychiatric disorders, including depression and anxiety. The present work investigates the effects of the intermittent administration of OUA (1.8 μg/kg) during the chronic unpredictable stress (CUS) protocol in a rat’s central nervous system (CNS). The results suggest that the intermittent OUA treatment reversed CUS-induced HPA axis hyperactivity through a reduction in (i) glucocorticoids levels, (ii) CRH-CRHR1 expression, and by decreasing neuroinflammation with a reduction in iNOS activity, without interfering with the expression of antioxidant enzymes. These changes in both the hypothalamus and hippocampus may reflect in the rapid extinction of aversive memory. The present data demonstrate the ability of OUA to modulate the HPA axis, as well as to revert CUS-induced long-term spatial memory deficits.
Energy Consumption Analysis Using Weighted Energy Index and Energy Modeling for a Hotel Building
Authors: Permana Indra , Wang Fujen , Agharid Alya Penta , Rakshit Dibakar , Luo Jianhui
Published: April 2023

Energy consumption is an essential and vital issue for commercial hotel buildings. Regulations and codes are commonly used to regulate the energy usage of the building. However, the energy index used to evaluate energy performance does not include the usage of hotel buildings for different service purposes. This study utilizes a comprehensive approach involving data collection, field measurement, regression analysis, and building energy modeling to investigate the energy performance in hotel buildings. The study finds that ambient temperature and occupancy rate are key factors in energy consumption, resulting in a weighted energy index for public areas and guest rooms with an R-square of 0.8314 and 0.9184, respectively. The measurement data are also used to perform the energy modeling, and the data are validated. Studies on different regions, occupancy, orientation, window-to-wall ratios, and U-values are evaluated and simulated to determine the energy consumption, which might be useful for the hotel building design phase. In addition, it also evaluates the energy-saving potential, including chilled and condenser water temperature, COP, and indoor temperature settings. The study finds that implementing various studies could result in significant energy consumption and savings, with higher chilled water and lower condenser water temperature having a particularly prominent impact. The study concludes that energy modeling approaches can be useful tools for identifying and implementing energy-saving strategies.
Seismic Behavior of UHPC-Filled Rectangular Steel Tube Columns Incorporating Local Buckling
Authors: Yan Yanxiang , Yan Yu , Wang Yansong , Cai Heng , Zhu Yaorui
Published: April 2023

This paper presents a numerical study on the static behavior and cyclic behavior of UHPC-filled steel tube (UHPCFST) columns. A novel fiber element model is developed based on the effective distribution width method to consider the influence of local buckling. The parameters of the descending branch of the stress–strain curve of constrained concrete have been modified and proposed according to the existing experimental results. Thereafter, the impact parameter analysis of the seismic performance of UHPCFST columns under the pseudo static load is conducted, and the strength of steel and UHPC, width–thickness ratio, length–diameter ratio and axial compression ratio are considered. The results indicate that the proposed fiber element model can accurately predict the static and cyclic nonlinear behaviors of the UHPCFST columns. The bearing capacity and the post-peak ductility of UHPCFST columns can be overestimated, such as neglecting the local buckling of the steel tube, which will lead to the insecurity of structures.
Analysis of Building Retrofit, Ventilation, and Filtration Measures for Indoor Air Quality in a Real School Context: A Case Study in Korea
Authors: Sung Ho Jin , Kim Sean Hay , Kim Hyunsuk
Published: April 2023

While many school retrofits in Korea tend to focus on energy savings, some school operation practices and policies in the field may cause indoor air quality issues. This study aims to analyze the indoor air quality impact when selected measures of the energy retrofit package are applied to classrooms in a real operation context with actual airflow and contaminant transport characteristics. The selected measures included replacement of envelope windows/doors/hallway-side windows, more airtight enclosures as a byproduct of adding envelope insulation, ventilation systems and air purifiers under various operating conditions, and natural ventilation. Actual classrooms with the ages of 10, 20, and 80 years were selected. Their CONTAM base models were calibrated with the measured airflow and contaminant transport variables per American Society for Testing and Materials (ASTM) D5157. The near-open-air hallways and frequent door opening made ambient PM2.5 in the hallways, which initially originated from outdoors, flow into the classrooms. Therefore, the infiltrations and penetrations from hallways to classrooms should also be secured along with those via the envelope. When the enclosures’ airtightness is enhanced, mechanical ventilation and filtration should be in operation. Specifically, they should operate independently from school energy demand reduction policy. Installing a high-efficiency filter can help a situation when mechanical ventilation needs to run at a reduced volume. Natural ventilation, as intended for energy savings, should be introduced only when the outdoor conditions are desirable and should be supplemented with a high-capacity air purifier to maintain stable indoor concentrations.
Finite Element Analysis of Shear Reinforcing of Reinforced Concrete Beams with Carbon Fiber Reinforced Polymer Grid-Strengthened Engineering Cementitious Composite
Authors: Sharifi Ghalehnoei Mohammadsina , Javanmardi Ahad , Izadifar Mohammadreza , Ukrainczyk Neven , Koenders Eduardus
Published: April 2023

This study investigates the shear behavior of reinforced concrete (RC) beams that have been strengthened using carbon fiber reinforced polymer (CFRP) grids with engineered cementitious composite (ECC) through finite element (FE) analysis. The analysis includes twelve simply supported and continuous beams strengthened with different parameters such as CFRP sheets, CFRP grid cross-sectional area, and CFRP grid size. To conduct the analysis, FE models of the RC beams were created and analyzed using ABAQUS software. Research results show that the strengthened RC beams with CFRP grids and ECC had approx. 30–50% higher shear capacity than reference RC beams. The composite action of CFRP grids with the ECCs also showed a significant ability to limit diagonal cracks and prevent the degradation of the bending stiffness of the RC beams. Furthermore, this study calculated the shear capacity of the strengthened beams using an analytical model and compared it with the numerical analysis results. The analytical equations showed only a 4% difference from the numerical results, indicating that the analytical model can be used in practice.
Comprehensive Studies on the Role of Small Aliphatic Alcohols in the Direct Synthesis of Hydrogen Peroxide with a Combination of Solvent Step and In Situ FTIR-ATR Experiments
Authors: Reinsdorf Ole , Eränen Kari , Salmi Tapio
Published: April 2023

A combination of transient methods in a laboratory-scale trickle bed reactor and attenuated total reflection (ATR)-infrared spectroscopy was applied to gain insight into the reaction mechanism of the direct synthesis of hydrogen peroxide (DSHP) on a commercial 5 %Pd/C catalyst, with water and methanol used as solvents. During the transient studies, after the switch from water to methanol, an oscillatory pattern was observed in which methoxy and hydroxymethyl species were observed prior to the peroxide species. From the specific position and the maxima in the intensities of these species over time, an augmented reaction scheme for the DSHP in methanol was proposed, in which methanol can form hydroxymethyl species which act as co-catalysts to reduce absorbed oxygen species.
Sensitivity of Papilledema as a Sign of Increased Intracranial Pressure
Authors: Krahulik David , Hrabalek Lumir , Blazek Filip , Halaj Matej , Slachta Marek , Klaskova Eva , Maresova Klara
Published: April 2023

Our study evaluates the sensitivity of papilledema as a sign of high intracranial pressure in children. Patients younger than 18 years old, diagnosed with increased ICP, and who had received dilated fundus examination between 2019 and 2021 were retrospectively reviewed. Factors including the patient’s age, sex, aetiology, duration of signs or symptoms, intracranial pressure (ICP), and presence of papilledema were evaluated. We included 39 patients in this study, whose mean age was 6.7 years. The 31 patients without papilledema had a mean age of 5.7 years, and 8 patients (20%) with papilledema had a mean age of 10.4 (p < 0.037). The mean duration of signs or symptoms was nine weeks in patients without papilledema and seven weeks in those with papilledema (p = 0.410). The leading causes of increased ICP with papilledema were supratentorial tumor (12.5%), infratentorial tumor (33.3%), and hydrocephalus (20%) (p = 0.479). Papilledema was statistically significantly more common in older patients. We found no statistical significance between sex, diagnosis, and symptoms. The relatively low incidence of papilledema (20%) in our study shows that papilledema’s absence does not ensure the absence of increased ICP, especially in younger patients.
School-Based Circuit Training Intervention Improves Local Muscular Endurance in Primary School Students: A Randomized Controlled Trial
Authors: Stojanović Nikola , Stupar Dušan , Marković Miroslav , Trajković Nebojša , Aleksić Dragana , Pašić Goran , Koničanin Admira , Zadražnik Marko , Stojanović Toplica
Published: April 2023

Background: This study aimed to explore the effectiveness of a 12-week circuit training program in improving local muscular endurance in normal-weighted primary school students. Methods: The study involved a parallel-group randomized trial with 606 primary school boys assigned to an experimental or a control group. The participants underwent a 12-week circuit training program that involved multi-joint, total-body workouts using body weight, resistance bands, and medicine ball exercises. The study measured the participants’ local muscular endurance during sit-ups, dynamic trunk extensions on a Roman bench (DTE), and push-ups. Results: After adjusting for the baseline, the treatment–grade interaction was significant for sit-ups (F = 7.74, p < 0.001, ηp2 = 0.04), DTE (F = 6.49, p < 0.001, ηp2 = 0.03), and push-ups (F = 9.22, p < 0.001, ηp2 = 0.05), where the experimental treatment was more beneficial than the control. The treatment effect seemed to vary depending on the individual’s baseline local muscle endurance capacity. As the baseline local muscular endurance values increased, the treatment and grade effects became less beneficial. Conclusion: A 12-week circuit training program involving body weight, resistance bands, and medicine ball exercises suits school-based programs and can improve local muscular endurance in normal-weighted primary school boys. The experimental treatment was more effective than the control, and the individual baseline muscular endurance should be considered when designing training programs.
Pediatric Hepatic Angiosarcoma (PHAS) and Vinyl Chloride—A Ghost of the Past May Loom over East Palestine, OH, and beyond: A Critical Commentary
Authors: Sergi Consolato M.
Published: April 2023

Road accidents are not infrequent everywhere in the world, but when they involve poisonous and dangerous chemical compounds, they represent a hazard and an issue for public health. In this commentary, we briefly review a recent East Palestine event and one of the chemicals primarily involved with a predisposition to initiate a carcinogenetic process. The author reviewed, as a consultant, numerous chemical compounds for the International Agency for Research on Cancer, a trusted agency of the World Health Organization. Something is looming over the territories of East Palestine, Ohio, United States, draining water from the soil. We speculate that there is a dark and opprobrious fate for this area of the United States due to the potential increase in cases of pediatric hepatic angiosarcoma, which will also be revised in this commentary.
Pitfalls in the Diagnosis and Management of Hypercortisolism (Cushing Syndrome) in Humans; A Review of the Laboratory Medicine Perspective
Authors: Flowers Kade C. , Shipman Kate E.
Published: April 2023

Biochemical confirmation of a diagnosis of hypercortisolism (Cushing syndrome) is vital to direct further investigations, especially given the overlap with non-autonomous conditions, such as pseudo-Cushing, and the morbidity associated with missed diagnoses. A limited narrative review was performed focusing on the laboratory perspective of the pitfalls of making a biochemical diagnosis of hypercortisolism in those presenting with presumed Cushing syndrome. Although analytically less specific, immunoassays remain cheap, quick, and reliable in most situations. Understanding cortisol metabolism can help with patient preparation, specimen selection (e.g., consideration of urine or saliva for those with possible elevations of cortisol binding globulin concentration), and method selection (e.g., mass spectrometry if there is a high risk of abnormal metabolites). Although more specific methods may be less sensitive, this can be managed. The reduction in cost and increasing ease of use makes techniques such as urine steroid profiles and salivary cortisone of interest in future pathway development. In conclusion, the limitations of current assays, particularly if well understood, do not impede diagnosis in most cases. However, in complex or borderline cases, there are other techniques to consider to aid in the confirmation of hypercortisolism.
Natural Language Processing for Breast Imaging: A Systematic Review
Authors: Diab Kareem Mahmoud , Deng Jamie , Wu Yusen , Yesha Yelena , Collado-Mesa Fernando , Nguyen Phuong
Published: April 2023

Natural Language Processing (NLP) has gained prominence in diagnostic radiology, offering a promising tool for improving breast imaging triage, diagnosis, lesion characterization, and treatment management in breast cancer and other breast diseases. This review provides a comprehensive overview of recent advances in NLP for breast imaging, covering the main techniques and applications in this field. Specifically, we discuss various NLP methods used to extract relevant information from clinical notes, radiology reports, and pathology reports and their potential impact on the accuracy and efficiency of breast imaging. In addition, we reviewed the state-of-the-art in NLP-based decision support systems for breast imaging, highlighting the challenges and opportunities of NLP applications for breast imaging in the future. Overall, this review underscores the potential of NLP in enhancing breast imaging care and offers insights for clinicians and researchers interested in this exciting and rapidly evolving field.
A Lossless-Recovery Secret Distribution Scheme Based on QR Codes
Authors: Pan Jeng-Shyang , Liu Tao , Yan  Bin , Yang  Hong-Mei , Chu Shu-Chuan
Published: April 2023

The visual cryptography scheme (VCS) distributes a secret to several images that can enhance the secure transmission of that secret. Quick response (QR) codes are widespread. VCS can be used to improve their secure transmission. Some schemes recover QR codes with many errors. This paper uses a distribution mechanism to achieve the error-free recovery of QR codes. An error-correction codeword (ECC) is used to divide the QR code into different areas. Every area is a key, and they are distributed to n shares. The loss of any share will make the reconstructed QR code impossible to decode normally. Stacking all shares can recover the secret QR code losslessly. Based on some experiments, the proposed scheme is relatively safe. The proposed scheme can restore a secret QR code without errors, and it is effective and feasible.
Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree
Authors: Wang Fenghua , Kooij Robert E.
Published: April 2023

Network controllability and its robustness have been widely studied. However, analytical methods to calculate network controllability with respect to node in- and out-degree targeted removals are currently lacking. This paper develops methods, based on generating functions for the in- and out-degree distributions, to approximate the minimum number of driver nodes needed to control directed networks, during node in- and out-degree targeted removals. By validating the proposed methods on synthetic and real-world networks, we show that our methods work reasonably well. Moreover, when the fraction of the removed nodes is below 10% the analytical results of random removals can also be used to predict the results of targeted node removals.
An Innovative Approach to Analyze Financial Contagion Using Causality-Based Complex Network and Value at Risk
Authors: Dong Yiqi , Dong Zuoji
Published: April 2023

In this paper, we propose a new approach to analyze financial contagion using a causality-based complex network and value-at-risk (VaR). We innovatively combine the use of VaR and an expected shortfall (ES)-based causality network with impulse response analysis to discover features of financial contagion. We improve the current research methods by building a Granger causality network on VaR and ES and using conclusions drawn from network analysis as a foundational step before impulse response analysis. First of all, we select 30 stock indices that are very well-known globally and collect their trading data. After calculating the risk indicators of VaR and ES, we perform the Granger causality test on them and then build networks based on their respective Granger causality square matrix. Next, we examine the networks’ topological features to discover different degrees of risk transmission among all stock indices in the system. Lastly, we identify the most and the least active stock indices in the risk transmission network and conduct impulse response analysis on them. We discover that BSESN (India S&P BSE SENSEX) is the most risk-sensitive stock index as its VaR significantly increases by 0.03–0.04% and its ES jumps even more, by 0.07–0.08%, in response to an impulse from a few key stock indices. We also find that either PSI20 or XU100 is the most risk-proof stock index, depending on whether we choose VaR or ES as a risk indicator.
Bridging the Gap between Medical Tabular Data and NLP Predictive Models: A Fuzzy-Logic-Based Textualization Approach
Authors: Mugisha Chérubin , Paik Incheon
Published: April 2023

The increasing use of electronic health records (EHRs) generates a vast amount of data, which can be leveraged for predictive modeling and improving patient outcomes. However, EHR data are typically mixtures of structured and unstructured data, which presents two major challenges. While several studies have focused on using machine learning models to predict patient outcomes, these models often require data to be in a structured format, which may lead to the loss of important information. On the other hand, unstructured data, such as narrative reports, can be noisy and challenging for natural language processing applications and interoperability. Therefore, there is a need to bridge the gap between structured EHR data and NLP-based predictive models. In this paper, we propose a fuzzy-logic-based pipeline that generates medical narratives from structured EHR data and evaluates its performance in predicting patient outcomes. The pipeline includes a feature selection operation and a reasoning and inference function that generates medical narratives. We then extensively evaluate the generated narratives using transformer-based NLP models for a patient-outcome-prediction task. We furthermore assess the interpretability of the generated text using Shapley values. Our approach has demonstrated comparable performance to the benchmark baseline models with an F1-score of 93.7%, while exhibiting slightly improved results in terms of recall. The model demonstrated proficiency in the preservation of information and interpretability inherited from nuanced and structured narratives. To the best of our knowledge, this is the first study to demonstrate the ability to transform tabular data into text to apply NLP for a prediction task.
Accelerating Fuzzy Actor–Critic Learning via Suboptimal Knowledge for a Multi-Agent Tracking Problem
Authors: Wang Xiao , Ma Zhe , Mao Lei , Sun Kewu , Huang Xuhui , Fan Changchao , Li Jiake
Published: April 2023

Multi-agent differential games usually include tracking policies and escaping policies. To obtain the proper policies in unknown environments, agents can learn through reinforcement learning. This typically requires a large amount of interaction with the environment, which is time-consuming and inefficient. However, if one can obtain an estimated model based on some prior knowledge, the control policy can be obtained based on suboptimal knowledge. Although there exists an error between the estimated model and the environment, the suboptimal guided policy will avoid unnecessary exploration; thus, the learning process can be significantly accelerated. Facing the problem of tracking policy optimization for multiple pursuers, this study proposed a new form of fuzzy actor–critic learning algorithm based on suboptimal knowledge (SK-FACL). In the SK-FACL, the information about the environment that can be obtained is abstracted as an estimated model, and the suboptimal guided policy is calculated based on the Apollonius circle. The guided policy is combined with the fuzzy actor–critic learning algorithm, improving the learning efficiency. Considering the ground game of two pursuers and one evader, the experimental results verified the advantages of the SK-FACL in reducing tracking error, adapting model error and adapting to sudden changes made by the evader compared with pure knowledge control and the pure fuzzy actor–critic learning algorithm.
Does Technology Orientation Determine Innovation Performance through Digital Innovation? A Glimpse of the Electronic Industry in the Digital Economy
Authors: Nassani Abdelmohsen A. , Grigorescu Adriana , Yousaf Zahid , Condrea Elena , Javed Asad , Haffar Mohamed
Published: April 2023

This study aims to explore the impact of technology orientation on innovation performance in the electronic industry operating in the digital economy. This study also investigates the mediating role of digital innovation (a special type of innovation that is based on digital technologies) in the relationship between technology orientation and innovation performance. Primary data, based on perception, was collected from operational managers of electronic firms. Correlation and regression analyses were used to test the direct relationship among digital innovation, innovation performance, and technology orientation. The stepwise regression model was used to check the indirect relationship (mediation analysis). Findings revealed that technology orientation is a major predictor of innovation performance in the electronic industry. Results show that digital innovation acts as a bridge between technology orientation and innovation performance. This study investigates the nexus of technology orientation, digital innovation, and innovation performance in electronic firms. This study contextualizes electronic firms for the achievement of innovation performance through digitalization and technology orientation, which is a dire need of the current decade.
Research on Identification and Location of Charging Ports of Multiple Electric Vehicles Based on SFLDLC-CBAM-YOLOV7-Tinp-CTMA
Authors: Quan Pengkun , Lou Ya’nan , Lin Haoyu , Liang Zhuo , Wei Dongbo , Di Shichun
Published: April 2023

With the gradual maturity of autonomous driving and automatic parking technology, electric vehicle charging is moving towards automation. The charging port (CP) location is an important basis for realizing automatic charging. Existing CP identification algorithms are only suitable for a single vehicle model with poor universality. Therefore, this paper proposes a set of methods that can identify the CPs of various vehicle types. The recognition process is divided into a rough positioning stage (RPS) and a precise positioning stage (PPS). In this study, the data sets corresponding to four types of vehicle CPs under different environments are established. In the RPS, the characteristic information of the CP is obtained based on the combination of convolutional block attention module (CBAM) and YOLOV7-tinp, and its position information is calculated using the similar projection relationship. For the PPS, this paper proposes a data enhancement method based on similar feature location to determine the label category (SFLDLC). The CBAM-YOLOV7-tinp is used to identify the feature location information, and the cluster template matching algorithm (CTMA) is used to obtain the accurate feature location and tag type, and the EPnP algorithm is used to calculate the location and posture (LP) information. The results of the LP solution are used to provide the position coordinates of the CP relative to the robot base. Finally, the AUBO-i10 robot is used to complete the experimental test. The corresponding results show that the average positioning errors (x, y, z, rx, ry, and rz) of the CP are 0.64 mm, 0.88 mm, 1.24 mm, 1.19 degrees, 1.00 degrees, and 0.57 degrees, respectively, and the integrated insertion success rate is 94.25%. Therefore, the algorithm proposed in this paper can efficiently and accurately identify and locate various types of CP and meet the actual plugging requirements.
A Recommendation Algorithm Combining Local and Global Interest Features
Authors: Song Xiaoyuan , Qin Jiwei , Ren Qiulin
Published: April 2023

Due to the ability of knowledge graph to effectively solve the sparsity problem of collaborative filtering, knowledge graph (KG) has been widely studied and applied as auxiliary information in the field of recommendation systems. However, existing KG-based recommendation methods mainly focus on learning its representation from the neighborhood of target items, ignoring the influence of other items on the target item. The learning focuses on the local feature representation of the target item, which is not sufficient to effectively explore the user’s preference degree for the target item. To address the above issues, in this paper, an approach combining users’ local interest features with global interest features (KGG) is proposed to efficiently explore the user’s preference level for the target item, which learns the user’s local interest features and global interest features for target item through Knowledge Graph Convolutional Network and Generative Adversarial Network (GAN). Specifically, this paper first utilizes the Knowledge Graph Convolutional Network to mine related attributes on the knowledge graph to effectively capture item correlations and obtain the local feature representation of the target item, then uses the matrix factorization method to learn the user’s local interest features for target items. Secondly, it uses GAN to learn the user’s global interest features for target items from the implicit interaction matrix. Finally, a linear fusion layer is designed to effectively fuse the user’s local and global interests towards target items to obtain the final click prediction. Experimental results on three real datasets show that the proposed method not only effectively integrates the user’s local and global interests but also further alleviates the problem of data sparsity. Compared with the current baselines for knowledge graph-based systems, the KGG method achieves a maximum improvement of 8.1% and 7.6% in AUC and ACC, respectively.
Transient Frequency Estimation Methods for the Fast Frequency Response in Converter Control
Authors: Pfendler Anna , Steppan Rafael , Hanson Jutta
Published: April 2023

In an interconnected power system, frequency control and stability are of vital importance and indicators of system-wide active power balance. The shutdown of conventional power plants leads to faster frequency changes and a steeper frequency gradient due to reduced system inertia. For this reason, the importance of electrical frequency estimation methods is increasing, among others, as an input for the control of converter-based generation plants. The aim of this work is to implement, compare, and analyze the robustness of the Phase-Locked-Loop and Zero-Crossing, Gauss–Newton, and recursive Gauss–Newton methods in time-domain simulations in Matlab/Simulink. The parameters of these methods are tuned for different scenarios in a medium-voltage testbench. The sensitive parameters of the frequency estimation methods show a linear correlation to the magnitude of the active power imbalance so a simple implementation can be designed for simulations. With the linearized parameter calculation for the frequency estimation methods, the local frequency as an input for converter control is used for the fast frequency response of a full power converter, which counteracts frequency deviations in the power system. Finally, two different implementations of the fast frequency response are compared. The Zero-Crossing Method shows the best robustness and the Phase-Locked Loop achieves the absolute best result.
Real-Time Detection of Nickel Plated Punched Steel Strip Parameters Based on Improved Circle Fitting Algorithm
Authors: Cao Binfang , Li Jianqi , Liang Yincong , Sun Xuan , Li Weihao
Published: April 2023

Nickel-plated punched steel strip is a product obtained by punching holes on the surface of cold-rolled white sheet steel strip and then electrochemical nickel plating. It is necessary to make accurate and fast detection of punching circle parameters, since it is of crucial importance to ensuring the quality of nickel-plated punched steel strips. Accordingly, in this article, an improved circle fitting algorithm of nickel-plated punched steel strip is proposed. Firstly, the least squares fitting is performed to obtain the circle center and radius dataset by iterative algorithm with different values for the initial point positions and intervals. Then, the mean shift algorithm is used to optimize the results after iteration, and the segmented fitted circle centers are all concentrated around the true circle center to obtain the best radius and center coordinates. Finally, comparison experiments with different numbers of circular holes and verification experiments with nickel-plated punched steel strips are carried out. As the results show, the algorithm proposed in this article is more robust than the least squares algorithm in detecting multiple circles and has better real-time performance than the Hough transform. Therefore, it can meet the industrial production needs with high accuracy and real-time requirements, such as nickel-plated punched steel strips.
Selection of Saccharomyces cerevisiae Isolates from Helan Mountain in China for Wine Production
Authors: Hu Lanlan , Ji Xueao , Li Jiacong , Jia Yangyang , Wang Xiaohong , Zhang Xiuyan
Published: April 2023

S. cerevisiae strains were isolated and identified from vineyards and the spontaneous fermentation must at the eastern foot of Helan Mountain in China, and their oenological properties and fermentation abilities were analyzed. From the total of 199 S. cerevisiae strains isolated and identified, 14 isolates (F4-13, F5-7, F5-9, F5-12, F5-18, F5-19, F5-21, F6-8, F6-23, F9-23, SXY-4, HT-10, ZXY-17, MXY-19) exhibited excellent tolerance to sugar, SO2, and ethanol. Among the isolates, the strain F4-13 exhibited the better oenological properties, with low H2S production (+), suitable flocculation ability (58.74%), and reducing-L-malic acid ability (49.07%), and generated high contents of polyphenol, anthocyanin, tannin, terpenes, and higher alcohols, which contributed to the improvement of the red fruity and floral traits of the wines. The obtained results provide a strategy for the selection of indigenous S. cerevisiae for wine fermentation to produce high-quality wine with regional characteristics.
Effects of Four Critical Gene Deletions in Saccharomyces cerevisiae on Fusel Alcohols during Red Wine Fermentation
Authors: Yan Tongshuai , Wang Zexiang , Zhou Haoyang , He Jiaojiao , Zhou Shishui
Published: April 2023

Excessive fusel alcohols in red wine will bring an uncomfortable bitterness and generate an intoxicating effect, which affects the quality and attractivity of the red wine. In order to achieve better regulation of fusel alcohols in red wine, strains with LEU1 and PDC5 deletions were constructed, and seven engineered yeast strains based on THI3 and BAT2 deletions were applied to red wine fermentation to dissect the effects of four critical genes on fusel alcohols during wine fermentation. The fermentation results of these recombinant strains showed that the deletion of THI3 increased the contents of n-propanol, isobutanol, and isoamyl alcohol by 48.46%, 42.01%, and 7.84%, respectively; the deletion of BAT2 decreased isoamyl alcohol and isobutanol by 32.81% and 44.91%; the deletion of PDC5 and LEU1 decreased isoamyl alcohol by 40.21% and 68.28%, while increased isobutanol by 24.31% and 142%, respectively; the deletion of THI3 exerted a negative influence on the reduction of isoamyl alcohol caused by BAT2 or PDC5 deletion; the deletion of THI3 and PDC5 had a synergistic effect on the increase of isobutanol, while BAT2 and PDC5 deletion presented no additive property to the decrease of isoamyl alcohol. Hence, it is concluded that either BAT2, PDC5, or LEU1 deletion can effectively decrease fusel alcohols, especially isoamyl alcohol, which provides an important reference for the control of fusel alcohols in red wine.
Correction: Haddad, R.K.; Harun, Z. Development of a Novel Quantitative Risk Assessment Tool for UK Road Tunnels. Fire 2023, 6, 65
Authors: Haddad Razieh Khaksari , Harun Zambri
Published: April 2023

In the original publication [...]
Probabilistic Wildfire Risk Assessment and Modernization Transitions: The Case of Greece
Authors: Troumbis Andreas Y. , Gaganis Cleo Maria , Sideropoulos Haralambos
Published: April 2023

Wildfire is the primary cause of deforestation in fire-prone environments, disrupting the forest transition process generated by multiple social-ecological drivers of modernization. Given the positive feedback between climate change and wildfire-driven deforestation, it seems necessary to abstract the primary- or micro-characteristics of wildfire event(s) and focus on the general behavior of the phenomenon across time and space. This paper intends to couple wildfire self-organizing criticality theory (SOC) and modernization statistics to propose a verisimilar explanation of the phenomenon’s evolution in the past decades and a prediction of its trends in Greece. We use power law distributions of the fire frequency–magnitude relationship to estimate the basic SOC parameters and the Weibull reliability method to calculate large-size wildfires’ conditional probability as a time function. We use automatic linear modeling to search for the most accurate relationship between wildfire metrics and the best subset of modernization predictors. The discussion concentrates on reframing the political debate on fire prevention vs. suppression, its flaws and limitations, and the core challenges for adopting more efficient wildfire management policies in Greece.
Transcriptional Profiling of Populations in the Clam Ruditapes decussatus Suggests Genetically Determined Differentiation in Gene Expression along Parallel Temperature Gradients and between Races of the Atlantic Ocean and West Mediterranean Sea
Authors: Saavedra Carlos , Milan Massimo , Leite Ricardo B. , Cordero David , Patarnello Tomaso , Cancela M. Leonor , Bargelloni Luca
Published: April 2023

Ongoing ocean warming due to climate change poses new challenges for marine life and its exploitation. We have used transcriptomics to find genetically based responses to increased temperature in natural populations of the marine clam Ruditapes decussatus, which lives along parallel thermal gradients in southern Europe. Clams of the Atlantic and West Mediterranean races were collected in northern (cool) and a southern (warm) localities. The animals were kept in running seawater in the warm, southern Atlantic locality for a 15-week period. During this period, water temperature was raised to typical southern European summer values. After this period, an expression profile was obtained for a total of 34 clams and 11,025 probes by means of an oligonucleotide microarray. We found distinct transcriptional patterns for each population based on a total of 552 differentially expressed genes (DEGs), indicating innate differences which probably have a genetic basis. Race and latitude contributed significantly to gene expression differences, with very different sets of DEGs. A gene ontology analysis showed that races differed mainly in the genes involved in ribosomal function and protein biosynthesis, while genes related to glutathione metabolism and ATP synthesis in the mitochondria were the most outstanding with respect to north/south transcriptional differences.
Fingerprint of Characteristic Saffron Compounds as Novel Standardization of Commercial Crocus sativus Extracts
Authors: Mena-García Adal , Herrero-Gutiérrez Diego , Sanz María L. , Díez-Municio Marina , Ruiz-Matute Ana I.
Published: April 2023

Food supplements based on saffron (Crocus sativus L.) dried stigma extracts are widely consumed due to their multiple bioactive properties. Saffron extract (SE) standardization is of crucial importance, as it determines the reproducibility of the product quality and is essential for the evaluation of its bioactive effect and safety. Although SEs are commonly standardized considering their safranal content, the lack of specificity of the official methods may give inaccurate measurements. In addition to the development of more precise methodologies, the evaluation of alternative saffron components, such as crocins and picrocrocin, for standardization purposes would also be of interest. Thus, in this study, qualitative and quantitative information regarding picrocrocin and crocin isomers of different commercial saffron extracts was first obtained by a validated methodology using liquid chromatography (HPLC) coupled to diode array (DAD) and mass spectrometer (MS) detectors. Principal component analysis (PCA) was applied to gain insight into the compositional variability and natural grouping of SE. These studies suggested the potential use of the relative content of crocin isomers and trans-/cis-crocins and trans-4 GG/picrocrocin ratios as novel criteria for SE standardization. Their reproducibility and stability under controlled storage conditions for 36 months was demonstrated in a commercial standardized SE (affron®).
Towards Sustainable and Nutritionally Enhanced Flatbreads from Sprouted Sorghum, Tapioca, and Cowpea Climate-Resilient Crops
Authors: Marchini Mia , Paciulli Maria , Broccardo Lorenza , Tuccio Maria Grazia , Scazzina Francesca , Cirlini Martina , Carini Eleonora
Published: April 2023

This study aimed to develop high-quality flatbreads for low-income countries by using composite flours from climate-resilient crops, i.e., sprouted sorghum, tapioca, and cowpea, as partial alternatives to imported wheat. Through the experimental design, several flatbread prototypes were developed that maximized the content of sprouted sorghum and cowpea flours and minimized the content of wholewheat flour. Three of them were chosen based on the best textural, nutritional (highest intake of energy, proteins, and micronutrients—iron, zinc and vitamin A), and economic (cheapest in Sierra Leone, Tanzania, Burundi, and Togo) features. The physicochemical properties, in vitro starch digestibility, total phenolic content, antioxidant capacity, and sensory acceptability were also measured for the samples. The experimental flatbreads showed lower rapidly digestible starch and higher resistant starch contents than the control (100% wholewheat based), and were also richer in phenolic content and higher in antioxidant activity. Moreover, one of the prototypes was perceived to be as acceptable as the control for texture and flavour properties. The ranking test, performed after explaining the nature of the samples, revealed that the flatbread meeting the nutritional criteria was the preferred one. Overall, the use of composite flour from climate-resilient crops was proven to be an efficient strategy to obtain high-quality flatbread.
Encapsulation of Sorghum Leaf Red Dye: Biological and Physicochemical Properties and Effect on Stability
Authors: Serrano Carmo , Sapata Margarida , Oliveira M. Conceição , Soares Andreia , Pereira Carla , Abreu Rui M. V. , Barros Lillian
Published: April 2023

The encapsulation of the 3-deoxyanthocyanidins (3-DXA) red dye, extracted from sorghum (Sorghum bicolor L.) leaves, was explored for food application. The extracts showed antioxidant activity at concentrations ranging from 803 to 1210 μg mL−1 and did not reveal anti-inflammatory or cytotoxic properties, indicating their potential for food application. Encapsulation was performed with two carrier agents (maltodextrin and Arabic gum) in different proportions (1:1, 2:1 and 1.5:2.5 (w/w)). The microparticles produced by freeze-drying and spray-drying were studied according to the concentration of the dye, the encapsulation efficiency, the process yield, the solubility and the colour of the powders. The dye extracts are released from the microparticles at different pHs. The variation in ratio composition of the 3-DXA encapsulation was assessed by principal component analysis (PCA) using data from ten physicochemical parameters. The results indicated that the maltodextrin at the 2:1 ratio had a higher dye concentration and total phenolic content (TPC) at pH 6. This ratio was selected to produce the microparticles by freeze-drying and spray-drying, and the particles were used in the temperature stability tests at pH 6. The results suggest that the freeze-drying process offers better protection to 3-DXA, with a degradation percentage of 22% during the heating period (80 °C for 18 h), compared to the non-encapsulated dye (48%). However, there were no significant differences between the two polymeric agents. The non-encapsulated 3-DXA was evaluated as control and lost 48% of the total colour with the same treatment. Red dyes from sorghum leaf by-products may constitute promising ingredients for the food industry and increase the value of this crop.
Multiplicative Noise Removal and Contrast Enhancement for SAR Images Based on a Total Fractional-Order Variation Model
Authors: Zhou Yamei , Li Yao , Guo Zhichang , Wu Boying , Zhang Dazhi
Published: April 2023

In this paper, we propose a total fractional-order variation model for multiplicative noise removal and contrast enhancement of real SAR images. Inspired by the high dynamic intensity range of SAR images, the full content of the SAR images is preserved by normalizing the original data in this model. Then, we propose a degradation model based on the nonlinear transformation to adjust the intensity of image pixel values. With MAP estimator, a corresponding fidelity term is introduced into the model, which is beneficial for contrast enhancement and bias correction in the denoising process. For the regularization term, a gray level indicator is used as a weighted matrix to make the model adaptive. We first apply the scalar auxiliary variable algorithm to solve the proposed model and prove the convergence of the algorithm. By virtue of the discrete Fourier transform (DFT), the model is solved by an iterative scheme in the frequency domain. Experimental results show that the proposed model can enhance the contrast of natural and SAR images while removing multiplicative noise.