bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comprehensive Review of Surface Modification Techniques for Enhancing the Biocompatibility of 3D-Printed Titanium Implants
Authors: Long Shuai , Zhu Jiang , Jing Yiwan , He Si , Cheng Lijia , Shi Zheng
Published: November 2023

The advent of three-dimensional (3D) printing technology has revolutionized the production of customized titanium (Ti) alloy implants. The success rate of implantation and the long-term functionality of these implants depend not only on design and material selection but also on their surface properties. Surface modification techniques play a pivotal role in improving the biocompatibility, osseointegration, and overall performance of 3D-printed Ti alloy implants. Hence, the primary objective of this review is to comprehensively elucidate various strategies employed for surface modification to enhance the performance of 3D-printed Ti alloy implants. This review encompasses both conventional and advanced surface modification techniques, which include physical–mechanical methods, chemical modification methods, bioconvergence modification technology, and the functional composite method. Furthermore, it explores the distinct advantages and limitations associated with each of these methods. In the future, efforts in surface modification will be geared towards achieving precise control over implant surface morphology, enhancing osteogenic capabilities, and augmenting antimicrobial functionality. This will enable the development of surfaces with multifunctional properties and personalized designs. By continuously exploring and developing innovative surface modification techniques, we anticipate that implant performance can be further elevated, paving the way for groundbreaking advancements in the field of biomedical engineering.
A Complete Review of Automatic Detection, Segmentation, and Quantification of Neovascularization in Optical Coherence Tomography Angiography Images
Authors: Tun Yar Zar , Aimmanee Pakinee
Published: November 2023

Optical coherence tomography (OCT) is revolutionizing the way we assess eye complications such as diabetic retinopathy (DR) and age-related macular degeneration (AMD). With its ability to provide layer-by-layer information on the retina, OCT enables the early detection of abnormalities emerging underneath the retinal surface. The latest advancement in this field, OCT angiography (OCTA), takes this to the next level by providing detailed vascular information without requiring dye injections. One of the most significant indicators of DR and AMD is neovascularization, the abnormal growth of unhealthy vessels. In this work, the techniques and algorithms used for the automatic detection, classification, and segmentation of neovascularization in OCTA images are explored. From image processing to machine learning and deep learning, works related to automated image analysis of neovascularization are summarized from different points of view. The problems and future work of each method are also discussed.
Susceptibility of Ocular Surface Bacteria to Various Antibiotic Agents in a Romanian Ophthalmology Clinic
Authors: Ghita Aurelian Mihai , Iliescu Daniela Adriana , Ghita Ana Cristina , Ilie Larisa Adriana
Published: November 2023

Periodic assessment of bacterial contamination is necessary as it allows proper guidance in cases of eye infections through the use of appropriate antibiotics. Due to the extensive use of antibiotic treatment, many strains of the microbiota that cause infections are resistant to the usual ophthalmic antibiotics. The present study provides an updated assessment of the susceptibility of Gram-positive and Gram-negative bacteria found on the ocular surface to the most commonly used antibiotic agents in patients undergoing cataract surgery. A total of 993 patients were included in the study with ages between 44 and 98 years old. Conjunctival cultures were collected 7 days before cataract surgery. The response of Gram-positive and Gram-negative bacteria to various antibiotic classes, such as glycopeptides, cephalosporins, carbapenems, fluoroquinolones, aminoglycosides, phenicols, tetracyclines, rifamycins, macrolides and penicillins, was assessed. From the tested antibiotics, vancomycin had 97.8% efficacy on Gram-positive bacteria. In the cephalosporin category, we observed a high level of resistance of the cefuroxime for both Gram-positive and negative bacteria. Antibiotics that have more than 90% efficacy on Gram-positive bacteria are meropenem, imipenem, netilmicin, amikacin and rifampicin. On Gram-negative bacteria, we found 100% efficacy of all tested fluoroquinolones, i.e., aminoglycosides (except for tobramycin), doxycycline, azithromycin, clarithromycin and chloramphenicol. The current study illustrates patterns of increased resistance in certain bacteria present on the ocular surface to some of the commonly used antibiotics in ophthalmological clinical practice. One such revealing example is cefuroxime, which has been highly used as an intracameral antibiotic for the prevention of bacterial endophthalmitis after cataract surgery.
Postoperative Seizure Prophylaxis in Meningioma Resection: A Systematic Review and Meta-Analysis
Authors: Batista Sávio , Bertani Raphael , Palavani Lucca B. , de Barros Oliveira Leonardo , Borges Pedro , Koester Stefan W. , Paiva Wellingson Silva
Published: November 2023

Background: Seizures in the early postoperative period may impair patient recovery and increase the risk of complications. The aim of this study is to determine whether there is any advantage in postoperative seizure prophylaxis following meningioma resection. Methods: This systematic review was conducted in accordance with PRISMA guidelines. PUBMED, Web of Science, Embase, Science Direct, and Cochrane were searched for papers until April 2023. Results: Among nine studies, a total of 3249 patients were evaluated, of which 984 patients received antiepileptic drugs (AEDs). No significant difference was observed in the frequency of seizure events between patients who were treated with antiepileptic drugs (AEDs) and those who were not. (RR 1.22, 95% CI 0.66 to 2.40; I2 = 57%). Postoperative seizures occurred in 5% (95% CI: 1% to 9%) within the early time period (<7 days), and 9% (95% CI: 1% to 17%) in the late time period (>7 days), with significant heterogeneity between the studies (I2 = 91% and 97%, respectively). In seizure-naive patients, the rate of postoperative seizures was 2% (95% CI: 0% to 6%) in the early period and increased to 6% (95% CI: 0% to 15%) in the late period. High heterogeneity led to the use of random-effects models in all analyses. Conclusions: The current evidence does not provide sufficient support for the effectiveness of prophylactic AED medications in preventing postoperative seizures in patients undergoing meningioma resection. This underscores the importance of considering diagnostic criteria and conducting individual patient analysis to guide clinical decision-making in this context.
Cloud-Based Quad Deep Ensemble Framework for the Detection of COVID-19 Omicron and Delta Variants
Authors: Tiwari Ravi Shekhar , Dandabani Lakshmi , Das Tapan Kumar , Khan Surbhi Bhatia , Basheer Shakila , Alqahtani Mohammed S.
Published: November 2023

The mortality rates of patients contracting the Omicron and Delta variants of COVID-19 are very high, and COVID-19 is the worst variant of COVID. Hence, our objective is to detect COVID-19 Omicron and Delta variants from lung CT-scan images. We designed a unique ensemble model that combines the CNN architecture of a deep neural network—Capsule Network (CapsNet)—and pre-trained architectures, i.e., VGG-16, DenseNet-121, and Inception-v3, to produce a reliable and robust model for diagnosing Omicron and Delta variant data. Despite the solo model’s remarkable accuracy, it can often be difficult to accept its results. The ensemble model, on the other hand, operates according to the scientific tenet of combining the majority votes of various models. The adoption of the transfer learning model in our work is to benefit from previously learned parameters and lower data-hunger architecture. Likewise, CapsNet performs consistently regardless of positional changes, size changes, and changes in the orientation of the input image. The proposed ensemble model produced an accuracy of 99.93%, an AUC of 0.999 and a precision of 99.9%. Finally, the framework is deployed in a local cloud web application so that the diagnosis of these particular variants can be accomplished remotely.
Long COVID and Physical Therapy: A Systematic Review
Authors: Sánchez-García Juan Carlos , Reinoso-Cobo Andrés , Piqueras-Sola Beatriz , Cortés-Martín Jonathan , Menor-Rodríguez María José , Alabau-Dasi Raquel , Rodríguez-Blanque Raquel
Published: November 2023

Prolonged COVID is a persistent condition following the initial COVID-19 infection, which is characterized by a variety of symptoms that may include fatigue, muscle pain, sleep disturbances, “brain fog”, respiratory, cardiovascular, digestive, neurological and dermatological symptoms. Physical therapy has been identified as a crucial aspect of the management of patients with long COVID, as it can help improve symptoms and overall physical function. The investigation of long COVID poses significant challenges due to the diversity and variability of symptoms, lack of clear diagnostic criteria, and limited understanding of the underlying mechanisms. The aim of this study is to conduct a systematic review of studies conducted in patients with long COVID in conjunction with interventions targeting respiratory function, particularly involving physical activity. To this end, we conducted a systematic review to analyze studies conducted on treatment programs for long COVID based on some form of physical activity. The protocol of the review was registered in the PROSPERO website, and the databases PubMed, Scopus, CINAHL and WOS were searched. Of the 62 initial articles, six were included in the review. The results obtained have positive implications for the advancement of physical activity as a therapeutic intervention for individuals with long COVID-19 and the conceptualization of evidence-based treatment protocols. Statistically significant results have been observed in studies of at least 6 weeks duration, in which inspiratory muscle training exercises are proposed. Further research is needed to better understand long COVID and develop effective treatment strategies.
On the Proper Computation of the Hausman Test Statistic in Standard Linear Panel Data Models: Some Clarifications and New Results
Authors: Le Gallo Julie , Sénégas Marc-Alexandre
Published: November 2023

We provide new analytical results for the implementation of the Hausman specification test statistic in a standard panel data model, comparing the version based on the estimators computed from the untransformed random effects model specification under Feasible Generalized Least Squares and the one computed from the quasi-demeaned model estimated by Ordinary Least Squares. We show that the quasi-demeaned model cannot provide a reliable magnitude when implementing the Hausman test in a finite sample setting, although it is the most common approach used to produce the test statistic in econometric software. The difference between the Hausman statistics computed under the two methods can be substantial and even lead to opposite conclusions for the test of orthogonality between the regressors and the individual-specific effects. Furthermore, this difference remains important even with large cross-sectional dimensions as it mainly depends on the within-between structure of the regressors and on the presence of a significant correlation between the individual effects and the covariates in the data. We propose to supplement the test outcomes that are provided in the main econometric software packages with some metrics to address the issue at hand.
A Systematic Literature Review on Artificial Intelligence and Explainable Artificial Intelligence for Visual Quality Assurance in Manufacturing
Authors: Hoffmann Rudolf , Reich Christoph
Published: November 2023

Quality assurance (QA) plays a crucial role in manufacturing to ensure that products meet their specifications. However, manual QA processes are costly and time-consuming, thereby making artificial intelligence (AI) an attractive solution for automation and expert support. In particular, convolutional neural networks (CNNs) have gained a lot of interest in visual inspection. Next to AI methods, the explainable artificial intelligence (XAI) systems, which achieve transparency and interpretability by providing insights into the decision-making process of the AI, are interesting methods for achieveing quality inspections in manufacturing processes. In this study, we conducted a systematic literature review (SLR) to explore AI and XAI approaches for visual QA (VQA) in manufacturing. Our objective was to assess the current state of the art and identify research gaps in this context. Our findings revealed that AI-based systems predominantly focused on visual quality control (VQC) for defect detection. Research addressing VQA practices, like process optimization, predictive maintenance, or root cause analysis, are more rare. Least often cited are papers that utilize XAI methods. In conclusion, this survey emphasizes the importance and potential of AI and XAI in VQA across various industries. By integrating XAI, organizations can enhance model transparency, interpretability, and trust in AI systems. Overall, leveraging AI and XAI improves VQA practices and decision-making in industries.
gemV-tool: A Comprehensive Soft Error Reliability Estimation Tool for Design Space Exploration
Authors: So Hwisoo , Ko Yohan , Jung Jinhyo , Lee Kyoungwoo , Shrivastava Aviral
Published: November 2023

With aggressive technology scaling, soft errors have become a major threat in modern computing systems. Several techniques have been proposed in the literature and implemented in actual devices as countermeasures to this problem. However, their effectiveness in ensuring error-free computing cannot be ascertained without an accurate reliability estimation methodology. This can be achieved by using the vulnerability metric: the probability of system failure as a function of the time the program data are exposed to transient faults. In this work, we present a gemV-tool, a comprehensive toolset for estimating system vulnerability, based on the cycle-accurate gem5 simulator. The three main characteristics of the gemV-tool are: (i) fine-grained modeling: vulnerability modeling at a fine-grained granularity through the use of RTL abstraction; (ii) accurate modeling: accurate vulnerability calculation of speculatively executed instructions; and (iii) comprehensive modeling: vulnerability estimation of all the sequential elements in the out-of-order processor core. We validated our vulnerability models through extensive fault injection campaigns with <3% correlation error and 90% statistical confidence. Using the gemV-tool, we made the following observations: (i) the vulnerability of two microarchitectural configurations with similar performance can differ by 82%; (ii) the vulnerability of a processor can vary by more than 10×, depending on the implemented algorithm; and (iii) the vulnerability of each component in the processor varies significantly, depending on the ISA of the processor.
Sparse Microwave Imaging Algorithm Based on L1/2 Threshold Iteration and an Approximate Observation Operator
Authors: Gao Zhiqi , Li Xin , Huang Pingping , Xu Wei , Tan Weixian
Published: November 2023

Aiming at the problems of synthetic-aperture radar (SAR), such as high sampling rate and vulnerability to noise interference in imaging, a sparse reconstruction algorithm based on approximate observation and L1/2 threshold iteration is proposed in this paper. To solve the problem of the large dimension and high computational complexity of the measurement matrix, a sparse reconstruction model based on approximate observation is constructed, and a threshold iterative algorithm to rapidly solve the L1/2 regularization problem is introduced, which can realize sparse signal reconstruction with fewer sampling data and quickly solve the problem. The simulation results of point targets and the measured data of spaceborne SAR show that compared with the traditional matched filtering algorithm and L1 threshold algorithm based on a two-step iteration, the proposed sparse reconstruction algorithm has a faster iteration speed and improves the image quality.
Addressing Body Image Disturbance through Metaverse-Related Technologies: A Systematic Review
Authors: Perez Moises , Pineda-Rafols Adriana , Egea-Romero Maria Pilar , Gonzalez-Moreno Maria , Rincon Esther
Published: November 2023

There is an increasing awareness about body image disturbance and eating disorders which calls for a multidisciplinary approach. The usefulness of new technologies for improving body image distortion has been addressed in the scientific literature, but has not included current strategies such as Metaverse-related technologies. Seemingly, this is the first systematic review which focuses on the efficacy of Metaverse-related technologies in reducing body image disturbance related to eating disorders like Anorexia nervosa and Bulimia nervosa. The main objective of this study was to review the scientific studies published in the last decade to answer the following three questions: (1) Are Metaverse-related technologies useful in mitigating body image disturbance in patients diagnosed with Anorexia nervosa and Bulimia nervosa? (2) What are the advantages and disadvantages? (3) Are the patients satisfied after using this kind of technology? The results obtained were that 80% of the included studies found metaverse-related technologies useful for the improvement in body image disturbance, in addition to various advantages, such as a decrease in eating disorder symptomatology. Whereas patient satisfaction was only evaluated in 20% of the included studies, with the majority of patients evaluating the use of metaverse-related technologies positively. We will conduct a systematic review of the peer-reviewed literature from EBSCO Discovery Service, and Web of Science (WOS), following the PRISMA statements. Only Journal articles published from 2013 to the present, written in the English language, will be reviewed. The findings are expected to offer valuable insights for the development of novel approaches for the improvement in body image disturbance in healthcare settings.
An RGB Pseudo-Colorization Method for Filtering of Multi-Source Graphical Data
Authors: Kubiak Ireneusz , Przybysz Artur
Published: November 2023

Artificial colorization (pseudo-colorization) is a commonly used method to improve the readability of images obtained from sources (sensors) that do not reflect the original color of the object of observation (e.g., X-ray). It is designed to draw the observer’s attention to the important details of the analyzed image (e.g., disease changes in medical imaging). Analogous needs occur in the process of assessing the emission security (EMSEC) of imaging devices used to process classified information, which is made on the basis of the analysis of images reproduced from compromising emanations related to the operation of these devices. The presence of many graphic elements in an image may reduce the level of perception of the information contained in it. Such images may be very noisy or contain overlapping graphic symbols, the source of which is devices processing graphic information operating in close proximity to each other. The use of various types of measures enabling data filtration at various stages of their processing, e.g., the use of a directional antenna, frequency filtering, point filtering or contextual contrast modification, does not always prove effective. The solution to the filtration problem is the pseudo-colorization of the image. However, the image colorization used based on the typical “Hot”, “Radar” or “Cold” color palettes does not meet the requirements for filtering graphic data from many sources. It is necessary to use a filter that will allow the sharp cut-off of graphic data at the border between the background and the graphic symbol. For the pseudo-colorization process itself, the exponential function as a function of transforming the amplitudes of image pixels from the gray color space to the RGB color space is sufficient. However, the smooth transition of the function shape from zero values to values greater than zero results in a low efficiency of filtering graphic data from noise. In this article, a method of filtering an image based on the pseudo-colorization of its content, i.e., reproduction of a compromising emanation signal level in the RGB value of image pixel color components, was proposed. A quadratic function was proposed as the transformation function. The higher effectiveness of the method based on the use of a square function (compared to the exponential function) was shown by conducting tests on many images, some of which are presented in this article. The proposed solution is a universal approach and can be used in various fields related to image analysis and the need for their filtration. Its universality is related to the possibility of changing function parameters affecting its position on the value axis from 0 to 255, its width, its minimum and its maximum value for each RGB channel.
USV Search Mission Planning Methodology for Lost Target Rescue on Sea
Authors: Zhang Han , Huang Yanyan , Qin Hucheng , Geng Ze
Published: November 2023

Quick and efficient mission planning is essential in maritime search and rescue (SAR). This includes defining the search area and developing an effective strategy. The task is fraught with challenges due to the difficulty of determining location information and the impact of complex meteorological environments. The primary objective of SAR mission planning is the rapid deployment of unmanned surface vehicles (USVs) to the incident area. While many planning algorithms prioritize the shortest route, there’s a lack of mission planning measures that maximize SAR effectiveness. In addition, the joint deployment of USVs increases the success rate compared to individual operations. Therefore, this paper presents a task assignment framework for USVs in SAR missions that considers the probability of success and time constraints. USVs are used to search for lost targets, and the framework consists of the following three modules: (1) a module for predicting the location of the overboard target to be rescued; (2) a module for modeling the probability of mission success; (3) a module for assigning search tasks to USVs. The framework first analyzes the search area. Then, it predicts the target location with a stochastic particle method, which incorporates marine environment forecast data to update the mission target location. To improve the scientific nature of USV search and rescue mission plans, an evaluation model is developed to assess mission capability. Simulation experiments and task scheme analysis validate its effectiveness.
Cyclic Appearance and Disappearance of Aerosol Nucleation in the Boundary Layer of Drops of Volatile Liquid
Authors: Scheunemann Patrick , Jermy Mark , Stephenson Paul
Published: November 2023

The cyclic appearance and disappearance of nucleation was observed in the boundary layer of drops of 1,3-propanediol, 1,2-propanediol, and glycerol, close to the boiling point and exposed to a cooler airflow. Although continuous nucleation has previously been widely observed, the cyclic nature of the phenomenon observed here is unusual. It was observed in experiments with free-falling drops and fixed drops in an upflow of air. To investigate this unexpected phenomenon further, the phenomenon was reproduced in two finite volume models. The first model used 1D potential flow solutions to approximate the airflow around the spherical windward face of the droplet. The second model used CFD to model the airflow. Both models used classical nucleation theory, the Stefan–Fuchs model of droplet growth by condensation, mass transfer by evaporation, diffusion, convection, and heat transfer by diffusion and convection. Despite several simplifications, the most important being the assumption that the drop has a uniform temperature, both models predict the frequency of nucleation to be better than the order of magnitude. These models also predict the experimentally observed power law dependence of nucleation frequency on air speed. It is proposed that the cyclic nature of the phenomenon is caused by the following process: the depletion of condensable vapour around the freshly nucleated aerosol due to condensation onto the aerosol results in reduced supersaturation, which stops further nucleation, and then the replenishment of this vapour by diffusion and convection from the parent drop, with nucleation of aerosol recommencing when the supersaturation has recovered sufficiently—then, the repetition of these steps in a cycle. It is proposed that the process depends mostly on the maximum saturation ratio in the boundary layer, which itself is determined by four key dimensionless numbers: the Lewis number, the Peclet number, the Reynolds number, and the ratio of the vapour pressure of the condensable compound at drop surface temperature to the vapour pressure of the same species at ambient temperature. A practical application of the phenomenon may be as a means of validation of thermo-fluid models, which include nucleation.
Nuclear Energy and Financial Development for a Clean Environment: Examining the N-Shaped Environmental Kuznets Curve Hypothesis in Top Nuclear Energy-Consuming Countries
Authors: Jóźwik Bartosz , Gürsoy Samet , Doğan Mesut
Published: November 2023

This research aims to reassess the impact of nuclear energy consumption and financial development on environmental quality using annual data from 1993 to 2019 for 11 countries with the highest nuclear energy consumption. Additionally, the study seeks to test the validity of the N-shaped EKC hypothesis. The findings of this study indicate a long-term cointegration relationship between the variables. According to the PCSE model results, increased nuclear energy consumption among the top 11 countries leads to decreased carbon emissions. Furthermore, the study reveals an N-shaped relationship between economic growth and environmental degradation. There is a strong recommendation for enhancing investments and grants directed towards research and development endeavours to identify and implement innovative solutions to reduce carbon emissions and improve environmental quality, particularly in less technologically advanced countries. Such efforts could include allocating more substantial funding to new technologies and encouraging collaborations between academic institutions and industry. Furthermore, considering regulatory adjustments like the liberalization of the energy market with the pro-ecological initiatives mainly carried out by public utilities is crucial as part of a comprehensive strategy to address environmental challenges.
A Comprehensive Multicriteria Evaluation Approach for Alternative Marine Fuels
Authors: Strantzali Eleni , Livanos Georgios A. , Aravossis Konstantinos
Published: November 2023

In the last decade, shipping decarbonization has accelerated rapidly in response to the regulatory framework. Shifting toward alternative marine fuel options is the subject of extensive study from stakeholders and researchers. This study attempts to propose a decision support model for alternative fuel evaluation. The decision-making process is multidimensional, comprising economic, technical, environmental, and social aspects, and has been carried out with the aid of the outranking multicriteria methodology, Promethee II. The approach is based on a comprehensive list of 11 criteria and 25 sub-criteria, covering all the crucial aspects. The weighting criteria process postulates the viewpoints of six stakeholder categories, including all the stakeholders’ preferences: shipowners, fuel suppliers, industry and engine manufacturers, academics, banks and the public. The results demonstrated that although LNG, MGO and HFO are classified in the highest positions, there are renewable options that also appear in high-ranking positions in most categories and especially among academics, banks, the public and in the combined case scenario. The commercially available options of drop-in biofuels, bio and e-LNG, fossil and bio methanol were ranked in these high positions. This approach offers insight into the assessment and selection of alternative marine fuel options, providing an incentive for strategic planning.
Research on the Control Method of the PV Grid-Connected Inverter under an Asymmetrical Power Grid Fault
Authors: Tian Shiji , Lu Min , Wang Ruikang , Liu Di’an
Published: November 2023

The negative-sequence current component and harmonic components generated when an asymmetrical fault occurs in the power grid seriously affect the normal operation of the photovoltaic (PV) grid-connected inverter. In order to suppress the negative-sequence current component and the harmonic component of the grid-connected current, and to meet the normal grid-connected operation requirements of the PV grid-connected inverter when asymmetrical faults occur in the grid, this paper proposes the proportional integral double-resonant (PI-DR) current controller, which consists of the PI controller and double-resonant controllers. The PI-DR current controller can directly control the negative-sequence current component and the grid-connected current harmonic component in the output current in the forward synchronous rotating coordinate system, without decomposing the positive and negative sequence currents. The PI-DR current controller ensures that the PV grid-connected inverter can realize normal grid-connected operation and improves the quality of the power when an asymmetrical fault occurs in the power grid. MATLAB/Simulink experiments show that the PI-DR current controller can improve the dynamic characteristics of the PV grid-connected inverter and improve the operating capability of the system when an asymmetrical fault occurs in the power grid.
A Regression Framework for Energy Consumption in Smart Cities with Encoder-Decoder Recurrent Neural Networks
Authors: Carrera Berny , Kim Kwanho
Published: November 2023

Currently, a smart city should ideally be environmentally friendly and sustainable, and energy management is one method to monitor sustainable use. This research project investigates the potential for a “smart city” to improve energy management by enabling the adoption of various types of intelligent technology to improve the energy sustainability of a city’s infrastructure and operational efficiency. In addition, the South Korean smart city region of Songdo serves as the inspiration for this case study. In the first module of the proposed framework, we place a strong emphasis on the data capabilities necessary to generate energy statistics for each of the numerous structures. In the second phase of the procedure, we employ the collected data to conduct a data analysis of the energy behavior within the microcities, from which we derive characteristics. In the third module, we construct baseline regressors to assess the proposed model’s varying degrees of efficacy. Finally, we present a method for building an energy prediction model using a deep learning regression model to solve the problem of 48-hour-ahead energy consumption forecasting. The recommended model is preferable to other models in terms of R2, MAE, and RMSE, according to the study’s findings.
Nutrient Levels, Bioactive Metabolite Contents, and Antioxidant Capacities of Faba Beans as Affected by Dehulling
Authors: Choi Yu-Mi , Yoon Hyemyeong , Shin Myoung-Jae , Lee Sukyeung , Yi Jungyoon , Jeon Young-ah , Wang Xiaohan , Desta Kebede Taye
Published: November 2023

Legume dehulling often removes anti-nutrients while improving nutritional quality. However, the process may reduce the levels of other health-promoting metabolites. This study investigated the effect of dehulling on major nutrients, bioactive metabolites, and antioxidant activities using 22 faba bean cultivars typically grown in different parts of the world. The faba bean cultivars differed significantly in all the parameters assessed. Crude fiber (CFC), dietary fiber (DFC), crude protein, and crude fat contents were in the ranges of 5.24–10.56, 16.17–25.15, 19.83–30.90, and 0.79–1.94% in the whole seeds and 0.96–1.59, 4.14–9.50, 22.47–36.61, and 1.13–2.07% in the dehulled seeds, respectively. Moreover, fatty acids including palmitic acid, stearic acid, oleic acid, linoleic acid, and linolenic acid, bioactive metabolites including total phenol (TPC), total saponin (TSC), and total tannin (TTC) contents, and antioxidant activities including ABTS•+-scavenging activity, ferric antioxidant power (FRAP), and DPPH•-scavenging activity also showed significant variations. Dehulling significantly reduced DFC (55.09–79.30%), CFC (69.61–87.52%), and TTC (1.70–66.99%) in all the faba bean cultivars while increasing total protein content (9.31–17.69%). Dehulling also increased the total fat content (3.02–48.13%) in all the cultivars except Giant Three Seeded, a Japanese cultivar, which showed a 12.62% decrease. In contrast, dehulling exhibited varying results on fatty acids, TPC, TSC, and antioxidant activities among the faba bean cultivars. Accordingly, three cultivars: Primus from Hungary, Levens Marschbohne from Germany, and Ascott from France, exhibited simultaneous increases in nutritional levels after dehulling. Domasna-2 from Macedonia, Abawi# 1 from Peru, Seville from the United Kingdom, and Large Mazandran from Iran, on the other hand, exhibited marked reductions in nutritional levels, functional metabolites, and antioxidant activities. In general, our findings indicated that dehulling reduces crude fiber, dietary fiber, and tannin levels while increasing protein and fat contents in faba beans. However, fatty acids, phenolic content, and antioxidant activity may not be equally affected by dehulling and, therefore, specific genotypes should be inspected.
Physicochemical, Microbiological, and Toxicological Characterization of Pâté Prepared from the Meat and Liver of Bullfrog (Aquarana catesbeiana) Carcasses
Authors: Magalhães Luiz Rogério G. , Moebus Victor F. , Castagna Airton A. , Aronovich Marcos , Coutinho Carlos Eduardo R. , Favotto Saida , Piasentier Edi , Keller Luiz A. M. , Mesquita Eliana F. M.
Published: November 2023

The development of balanced, healthy, ready-to-consume, and easy-to-prepare products has led to the development of new food technologies. Despite their high commercial value, bullfrog (Aquarana catesbeiana) carcasses result in low yields, with the thighs being the most marketed in comparison to other carcass portions. In this sense, liver pâté is a traditional food consumed worldwide, mainly in European countries, and may be prepared by incorporating bullfrog meat by-products and certain viscera. In this context, the aim of the present study was to develop a pâté product based on a mixture comprising 50% grounded bullfrog torso meat and 50% liver paste, with each treatment incorporating 10% liver paste increments, totaling five final mixtures. The nutritional compositions and physicochemical, microbiological, and toxicological characteristics of each mixture were assessed. The dry matter percentage of the prepared product was determined to be 27.00%, while mineral content was 1.45%, lipid content was 4.00%, and total protein content was 20.00%. Finally, microbiological counts were in agreement with current food safety regulations. The developed pâté serves as a standard, recycling underused industrial materials, adding value to the production chain at low operational costs, creating a more accessible market, and promoting the popularization of this type of meat.
The Leptospermum scoparium (Mānuka)-Specific Nectar and Honey Compound 3,6,7-Trimethyllumazine (LepteridineTM) That Inhibits Matrix Metalloproteinase 9 (MMP-9) Activity
Authors: Lin Bin , Nair Smitha , Fellner Daniel M. J. , Nasef Noha Ahmed , Singh Harjinder , Negron Leonardo , Goldstone David C. , Brimble Margaret A. , Gerrard Juliet A. , Domigan Laura , Evans Jackie C. , Stephens Jonathan M. , Merry Troy L. , Loomes Kerry M.
Published: November 2023

3,6,7-trimethyllumazine (Lepteridine™) is a newly discovered natural pteridine derivative unique to Mānuka (Leptospermum scoparium) nectar and honey, with no previously reported biological activity. Pteridine derivative-based medicines, such as methotrexate, are used to treat auto-immune and inflammatory diseases, and Mānuka honey reportedly possesses anti-inflammatory properties and is used topically as a wound dressing. MMP-9 is a potential candidate protein target as it is upregulated in recalcitrant wounds and intestinal inflammation. Using gelatin zymography, 40 μg/mL LepteridineTM inhibited the gelatinase activities of both pro- (22%, p < 0.0001) and activated (59%, p < 0.01) MMP-9 forms. By comparison, LepteridineTM exerted modest (~10%) inhibition against a chromogenic peptide substrate and no effect against a fluorogenic peptide substrate. These findings suggest that LepteridineTM may not interact within the catalytic domain of MMP-9 and exerts a negligible effect on the active site hydrolysis of small soluble peptide substrates. Instead, the findings implicate fibronectin II domain interactions by LepteridineTM which impair gelatinase activity, possibly through perturbed tethering of MMP-9 to the gelatin matrix. Molecular modelling analyses were equivocal over interactions at the S1′ pocket versus the fibronectin II domain, while molecular dynamic calculations indicated rapid exchange kinetics. No significant degradation of synthetic or natural LepteridineTM in Mānuka honey occurred during simulated gastrointestinal digestion. MMP-9 regulates skin and gastrointestinal inflammatory responses and extracellular matrix remodelling. These results potentially implicate LepteridineTM bioactivity in Mānuka honey’s reported beneficial effects on wound healing via topical application and anti-inflammatory actions in gastrointestinal disorder models via oral consumption.
Evolution of the Critically Endangered Green Sawfish Pristis zijsron (Rhinopristiformes, Pristidae), Inferred from the Whole Mitochondrial Genome
Authors: Wang Chen , Ye Peiyuan , Pillans Richard , Chen Xiao , Wang Junjie , Feutry Pierre
Published: November 2023

The green sawfish Pristis zijsron (Bleeker, 1851), a species of sawfish in the family Pristidae (Rhinopristiformes), mainly inhabits the Indo-West Pacific region. In this study, the complete mitochondrial genome of the critically endangered green sawfish is first described. The length of the genome is 16,804 bp, with a nucleotide composition of 32.0% A, 24.8% C, 13.1% G, and 30.0% T. It contains 37 genes in the typical gene order of fish. Two start (GTG and ATG) and two stop (TAG and TAA/T-) codons are found in the thirteen protein-coding genes. The 22 tRNA genes range from 67 bp (tRNA-Ser) to 75 bp (tRNA-Leu). The ratio of nonsynonymous substitution (Ka) and synonymous substitution (Ks) indicates that the family Pristidae are suffering a purifying selection. The reconstruction of Bayesian inference and the maximum likelihood phylogenetic tree show the same topological structure, and the family Pristidae is a monophyletic group with strong posterior probability. Pristis zijsron and P. pectinata form a sister group in the terminal clade. And the divergence time of Rhinopristiformes show that P. zijsron and P. pectinata diverged as two separate species in about Paleogene 31.53 Mya. Complete mitochondrial genomes of all five sawfishes have been published and phylogenetic relationships have been analyzed. The results of our study will provide base molecular information for subsequent research (e.g., distribution, conservation, phylogenetics, etc.) on this endangered group.
Is the Concept of Solastalgia Meaningful to Pacific Communities Experiencing Mental Health Distress Due to Climate Change? An Initial Exploration
Authors: Tupou Trish , Tiatia-Siau Jemaima , Newport Christina , Langridge Fiona , Tiatia Suelaki
Published: November 2023

The critical inquiry is how Pacific communities themselves characterize mental distress as a result of climate change. If not solastalgia, what more suitable terms might they use? This viewpoint article aims to initiate a discourse using solastalgia as the focus for the Pacific by 1. providing a definition of solastalgia; 2. examining its application in Pacific research; 3. presenting limitations of solastalgia; and 4. assessing its appropriateness for Pacific communities. There is a dearth of research using solastalgia, particularly within Pacific communities. The Pacific region’s diverse contexts may already possess terms that effectively convey place-based distress that solastalgia attempts to describe. However, the authors found that solastalgia holds limited utility in the Pacific region, primarily based on a review of the literature, which involved keyword searches in Google Scholar such as solastalgia, mental health, mental distress, wellbeing, climate change, environmental distress, displacement, and Indigenous and Pacific peoples. More importantly, the concept is limited in capturing Pacific experiences of land loss due to climate change events, particularly, as the Pacific imbues land with profound significance, intertwined with culture, identity, and wellbeing. Land loss equates to a loss of culture, identity, wellbeing, and kinship in most Pacific contexts. It is apparent that broader and more holistic approaches are required.
The Impact of Monetary Policy on the U.S. Stock Market since the COVID-19 Pandemic
Authors: Thorbecke Willem
Published: November 2023

Inflation in 2021 and 2022 grew much faster than the Federal Reserve expected. The Fed downplayed inflation in 2021 and then increased the federal funds rate by 500 basis points between March 2022 and May 2023. This paper investigates how this unprecedented tightening has impacted the stock market. To do so, it estimates a fully specified multi-factor model that measures the exposure of 53 assets to monetary policy surprises over the 1994 to 2019 period. It then uses the monetary policy betas to gauge investors’ beliefs about monetary policy between 2020 and 2023. The results indicate that changing perceptions about monetary policy multiplied uncertainty and stock market volatility.
Multi-Scale Road Matching Based on the Summation Product of Orientation and Distance and Shape Descriptors
Authors: Sun Ying , Lu Yuefeng , Ding Ziqi , Wen Qiao , Li Jing , Liu Yanru , Yao Kaizhong
Published: November 2023

Most commonly used road-based homonymous entity matching algorithms are only applicable to the same scale, and are weak in recognizing the one-to-many and many-to-many types that are common in matching at different scales. This paper explores model matching for multi-scale road data. By considering the sources of various scales and landmark datasets, as well as the spatial relationships between the selected objects and the detailed features of the entities, we propose an improved matching metric, the summation product of orientation and distance (SOD), combined with the shape descriptor based on feature point vectors, the shape area descriptor based on the minimum convex hull, and three other indicators, to establish multiple multi-scale road matching models. Through experiments, the comprehensive road matching model that combines SOD, orientation, distance and length is selected in this paper. When matching the road dataset with a scale of 1:50,000 and 1:10,000, the precision, recall, and F-score of the matching result of this model reached 97.31%, 94.33%, and 95.8%, respectively. In the case that the scale of the two datasets did not differ much, we concluded that the model can be used for matching between large-scale road datasets.
Integrated Transcriptome and Metabolomics to Reveal the Mechanism of Adipose Mesenchymal Stem Cells in Treating Liver Fibrosis
Authors: Liu Haifeng , Wang Xinmiao , Deng Hongchuan , Huang Haocheng , Liu Yifan , Zhong Zhijun , Shen Liuhong , Cao Suizhong , Ma Xiaoping , Zhou Ziyao , Chen Dechun , Peng Guangneng
Published: November 2023

Liver fibrosis (LF) is a late-stage process observed in various chronic liver diseases with bile and retinol metabolism closely associated with it. Adipose-derived mesenchymal stem cells (ADMSCs) have shown significant therapeutic potential in treating LF. In this study, the transplantation of ADMSCs was applied to a CCl4-induced LF model to investigate its molecular mechanism through a multi-omics joint analysis. The findings reveal that ADMSCs effectively reduced levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), gamma-glutamyltransferase (GGT), Interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and α-Smooth muscle actin (α-SMA), thereby mitigating liver lesions, preventing liver parenchymal necrosis, and improving liver collagen deposition. Furthermore, 4751 differentially expressed genes (DEGs) and 270 differentially expressed metabolites (DMs) were detected via transcriptome and metabolomics analysis. Conjoint analysis showed that ADMSCs up-regulated the expression of Cyp7a1, Baat, Cyp27a1, Adh7, Slco1a4, Aldh1a1, and Adh7 genes to promote primary bile acids (TCDCA: Taurochenodeoxycholic acid; GCDCA: Glycochenodeoxycholic acid; GCA: glycocholic acid, TCA: Taurocholic acid) synthesis, secretion and retinol metabolism. This suggests that ADMSCs play a therapeutic role in maintaining bile acid (BA) homeostasis and correcting disturbances in retinol metabolism.
Formoterol Exerts Anti-Cancer Effects Modulating Oxidative Stress and Epithelial-Mesenchymal Transition Processes in Cigarette Smoke Extract Exposed Lung Adenocarcinoma Cells
Authors: Ferraro Maria , Di Vincenzo Serena , Lazzara Valentina , Pinto Paola , Patella Bernardo , Inguanta Rosalinda , Bruno Andreina , Pace Elisabetta
Published: November 2023

Lung cancer frequently affects patients with Chronic Obstructive Pulmonary Disease (COPD). Cigarette smoke (CS) fosters cancer progression by increasing oxidative stress and by modulating epithelial-mesenchymal transition (EMT) processes in cancer cells. Formoterol (FO), a long-acting β2-agonist widely used for the treatment of COPD, exerts antioxidant activities. This study explored in a lung adenocarcinoma cell line (A549) whether FO counteracted the effects of cigarette smoke extract (CSE) relative to oxidative stress, inflammation, EMT processes, and cell migration and proliferation. A549 was stimulated with CSE and FO, ROS were evaluated by flow-cytometry and by nanostructured electrochemical sensor, EMT markers were evaluated by flow-cytometry and Real-Time PCR, IL-8 was evaluated by ELISA, cell migration was assessed by scratch and phalloidin test, and cell proliferation was assessed by clonogenic assay. CSE significantly increased the production of ROS, IL-8 release, cell migration and proliferation, and SNAIL1 expression but significantly decreased E-cadherin expression. FO reverted all these phenomena in CSE-stimulated A549 cells. The present study provides intriguing evidence that FO may exert anti-cancer effects by reverting oxidative stress, inflammation, and EMT markers induced by CS. These findings must be validated in future clinical studies to support FO as a valuable add-on treatment for lung cancer management.