bluuebunny/crossref_metadata_2025 huggingface dataset:
Parameter Calibration of Xinjiang Paperbark Walnut Kernels by Discrete Element Simulation
Authors: Zhou Binnan , Zuo Yi , Hou Lixia
Published: February 2023

To solve the problem of the lack of an accurate model for mechanized transportation and grading of walnut kernels, this paper took the shelled walnut kernels as the research object and calibrated the parameters of the discrete element model of walnut cracking kernels with the discrete element simulation software EDEM. The physical parameters of cracking kernels were measured by experiments, and the Hertz–Mindlin model was used to simulate the repose angle of cracking kernels. The contact parameters, such as the particle collision recovery coefficient, the static friction coefficient, and the rolling friction coefficient, were determined by the two-level factor test, steepest ascent test, and response surface test, respectively. Subsequently, the Hertz–Mindlin model with bonding contact was exploited to conduct the simulation of cracking kernels bending test based on the calibrated contact parameters. Finally, the normal contact stiffness, tangential contact stiffness, critical tangential force, and normal force of cracking kernels were determined by response surface analysis. It was shown that the relative error between the simulated values and the experiment results was 3.00 ± 1.31%. These results indicated that the calibrated parameter values are reliable, and could be used for the mechanized transportation and grading of walnut kernels.
Application of Computational Intelligence Methods in Agricultural Soil–Machine Interaction: A Review
Authors: Badgujar Chetan , Das Sanjoy , Figueroa Dania Martinez , Flippo Daniel
Published: February 2023

Rapid advancements in technology, particularly in soil tools and agricultural machinery, have led to the proliferation of mechanized agriculture. The interaction between such tools/machines and soil is a complex, dynamic process. The modeling of this interactive process is essential for reducing energy requirements, excessive soil pulverization, and soil compaction, thereby leading to sustainable crop production. Traditional methods that rely on simplistic physics-based models are not often the best approach. Computational intelligence-based approaches are an attractive alternative to traditional methods. These methods are highly versatile, can handle various forms of data, and are adaptive in nature. Recent years have witnessed a surge in adapting such methods in all domains of engineering, including agriculture. These applications leverage not only classical computational intelligence methods, but also emergent ones, such as deep learning. Although classical methods have routinely been applied to the soil–machine interaction studies, the field is yet to harness the more recent developments in computational intelligence. The purpose of this review article is twofold. Firstly, it provides an in-depth description of classical computational intelligence methods, including their underlying theoretical basis, along with a survey of their use in soil–machine interaction research. Hence, it serves as a concise and systematic reference for practicing engineers as well as researchers in this field. Next, this article provides an outline of various emergent methods in computational intelligence, with the aim of introducing state-of-the-art methods to the interested reader and motivating their application in soil–machine interaction research.
Construction and Test of Baler Feed Rate Detection Model Based on Power Monitoring
Authors: Liu Huaiyu , Gao Ning , Meng Zhijun , Zhang Anqi , Wen Changkai , Li Hanqing , Zhang Jing
Published: February 2023

The existing methods of measuring the baler feed rate seldom consider the influence of machine vibration on the sensor signal during field operation, which leads to the low detection accuracy and poor stability of feeding quantity detection. We established a feed rate detection model of a baler based on power monitoring of the pickup platform. Through the dynamic analysis of the pickup platform, the functional relationship between the working power of the pickup platform and the feed rate was constructed. A power monitoring system of the pickup platform was developed, and the model construction experiment of the working power and the feed rate was performed. The influence mechanism of different running speeds on the torque noise signal of the power input shaft of the pickup platform was explored. The frequency of the noise signal was mainly concentrated at 0.5–6 Hz and 9–13 Hz employing a fast Fourier transform, and the noise signal was eliminated by the frequency-domain-filtering method. The function model of working power and feed rate of the pickup platform was established based on signal processing, and the determination coefficient R2 of the model was 0.9796. The field experiment results show that when the feed rate of the baler is between 1.6 and 4.88 kg/s, the determination coefficient R2 and RMSE between the actual and predicted feed rate are 0.989 and 0.2, respectively. The relative error range of feed-rate prediction is −9.37–8.77%, which indicates that the model has high detection accuracy and good stability and meets the requirements of feed-rate monitoring of a baler in field operation.
Capsaicinoid Content in the Pericarp and Placenta of Bolilla Peppers (Capsicum annuum L.) throughout the Ripening of the Fruit at Two Different Stages of Plant Maturation
Authors: Vázquez-Espinosa Mercedes , Álvarez-Romero María , González-de-Peredo Ana V. , Ruíz-Rodríguez Ana , Ferreiro-González Marta , Barbero Gerardo F. , Palma Miguel
Published: February 2023

Peppers are a very popular ingredient in many dishes, either as the fruit itself or as derived products. They are not only consumed because of their organoleptic characteristics, but also because of their high content of bioactive compounds. The aim of this work was to determine the optimal time to harvest the Bolilla pepper, based on the capsaicinoid concentration in the pericarp and placenta at two different plant maturities (young and adult), in order to maximize their potential biological properties. In the case of the pericarp, the maximum capsaicinoid concentration was reached at 30 days post-anthesis (dpa) (with values of 1565.98 and 2158.82 µmol/kg, for the young and adult plant, respectively), while in the placenta it was registered at 41 dpa with greater values (5898.12 and 2349.67 µmol/kg). In either case, from that moment on, there was a drastic reduction in the capsaicinoid content. With regard to the capsaicinoid content levels in the pericarp, this was greater in older plants, while the placenta presented greater content in younger plants, which is of considerable importance from an economic point of view. This work allows a better selection of the final product, taking full advantage of its beneficial effects on health and taste, which would be very interesting for analytical laboratories or industries.
Utilization of Prickly Pear Peels Flour as a Natural Source of Minerals, Dietary Fiber and Antioxidants: Effect on Cakes Production
Authors: El-Beltagi Hossam S. , Ahmed Abdelrahman R. , Mohamed Heba I. , Al-Otaibi Hala Hazam , Ramadan Khaled M. A. , Elkatry Haiam O.
Published: February 2023

Prickly pear peel makes up around half of the fruit and is typically thrown away, creating an environmental issue. Due to its high bioactive chemical content, prickly pear peel can easily be used as a functional and nutraceutical ingredient in several food recipes, such as baked products. This study’s objective was to determine whether prickly pear peel flour (PPPF) could successfully be combined (5, 10, and 15%) with wheat flour to make cakes, by analyzing the physical and chemical characteristics of the cakes and performing a descriptive sensory analysis. Prickly pear peel flour contains high amounts of fiber, ash, carbohydrate, phenolic, flavonoid compounds, or antioxidant activity. In addition, PPPF contains high amounts of magnesium, calcium, sodium and potassium. The ethanolic extract of prickly pear peel revealed the presence of 11 phenolic compounds using UPLC-MS/MS. The main constituents in the peel extract were isorhamnetin (27.1%), eucomic acid (19.6%), kaempferol (14.07%), 3-O-Methylquercetin (13.7%), Feruloyl-D-glucose (10.01%) and piscidic acid (8.89%). Results showed that adding PPPF significantly enhanced the amount of fibers, total polyphenols, flavonoids and minerals in the cakes prepared by the addition of 5, 10 and 15% PPPF as compared to the control cake. Moreover, the addition of different levels of PPPF increased antioxidant activity (DPPH and ABTS%) and decreased thiobarbituric acid reactive substances (TBARS) in cakes as compared to the control cake. The descriptive sensory analysis ultimately revealed that cakes made with 10% prickly pear flour received a higher score for their smell, taste or color. In conclusion, prickly pear peel has antioxidant potential and contains biochemical compounds that can be utilized in the enhancement of functional foods and also help to reduce the waste accumulation that causes environmental issues.
Improving Classification Performance in Credit Card Fraud Detection by Using New Data Augmentation
Authors: Strelcenia Emilija , Prakoonwit Simant
Published: February 2023

In many industrialized and developing nations, credit cards are one of the most widely used methods of payment for online transactions. Credit card invention has streamlined, facilitated, and enhanced internet transactions. It has, however, also given criminals more opportunities to commit fraud, which has raised the rate of fraud. Credit card fraud has a concerning global impact; many businesses and ordinary users have lost millions of US dollars as a result. Since there is a large number of transactions, many businesses and organizations rely heavily on applying machine learning techniques to automatically classify or identify fraudulent transactions. As the performance of machine learning techniques greatly depends on the quality of the training data, the imbalance in the data is not a trivial issue. In general, only a small percentage of fraudulent transactions are presented in the data. This greatly affects the performance of machine learning classifiers. In order to deal with the rarity of fraudulent occurrences, this paper investigates a variety of data augmentation techniques to address the imbalanced data problem and introduces a new data augmentation model, K-CGAN, for credit card fraud detection. A number of the main classification techniques are then used to evaluate the performance of the augmentation techniques. These results show that B-SMOTE, K-CGAN, and SMOTE have the highest Precision and Recall compared with other augmentation methods. Among those, K-CGAN has the highest F1 Score and Accuracy.
Ovariectomy in Mouflons (Ovis aries) in the Field: Application of Innovative Surgical and Anaesthesiological Techniques
Authors: Cicirelli Vincenzo , Carbonari Alice , Burgio Matteo , Giannini Francesca , Rizzo Annalisa
Published: February 2023

This report describes an innovative technique of ovariectomy useful for the birth control in the mouflon population. Thirteen female mouflons in reproductive age were submitted to ovariectomy via midline and left flank, using the AESCULAP CAIMAN® Seal and Cut device. The CAIMAN® was useful for clamping the ovary, stapling the vessels, and cutting in one stroke, thus reducing the surgery times. The day after the gonadectomy all animals were mobilized to another enclosure. In this study, no intraoperative and post-operative complications were observed, and all animals were gonadectomized without side effects. This study sets the guidelines for the surgical sterilization of mouflons in the field using anesthetic protocols and high-quality surgical procedures.
Effect of High Efficiency Digestion and Utilization of Organic Iron Made by Saccharomyces cerevisiae on Antioxidation and Caecum Microflora in Weaned Piglets
Authors: Zeng Yan , Jiang Liwen , Zhou Bingyu , Liu Yubo , Wang Lingang , Hu Zhijin , Wang Chunping , Tang Zhiru
Published: February 2023

Organic iron is expected to replace inorganic iron used in diets as an iron source. Organic iron possesses high absorption efficiency and low fecal iron excretion. This study aims to study the effect of organic iron produced by Saccharomyces cerevisiae (yeast iron) on digestion, utilization, antioxidation and caecum microflora in weaned piglets. In total, 20 piglets that had been weaned after 28 days were divided into 4 groups, each of which followed a different basal diet. The basal diet of each of these 4 groups contained, respectively, 104 mg/kg iron (ferrous sulfate, CON), 84 mg/kg iron (yeast iron, LSC), 104 mg/kg iron (yeast iron, MSC) or 124 mg/kg iron (yeast iron, HSC). This experiment lasted 35 d. The apparent digestibility of iron in LSC, MSC and HMS was higher than that in CON (p < 0.01) and the fecal iron content in LSC, MSC and HMS was lower than that in CON (p < 0.01). Serum iron contents in LSC, MSC and HMS were higher than that in CON (p < 0.01). The iron contents of the heart, lungs, liver, kidney and left gluteus muscle in the MSC and HMS groups were higher than that in CON and LSC (p < 0.05). Serum catalase, glutathione peroxidase, superoxide dismutase activity, superoxide anion, glutathione, hydroxyl free radical scavenging rate, total antioxidant capacity, and liver superoxide anion clearance rate and peroxidase in MSC and HMS were higher than that in CON and LSC (p < 0.05). The contents of nitric oxide and peroxide of the weaned piglets in MSC and HMS were lower than that in CON and LSC (p < 0.05). The abundance of Firmicutes, Blautia and Peptococcus in LSC, HSC and MSC was higher than that in CON (p < 0.01). The abundance of Lactobacillus in CON and LSC was higher than that in MSC and HSC (p < 0.01). The abundance of Acinetobacter, Streptococcus and Prevotella in LSC, MSC and HSC was lower than that in CON (p < 0.01). The results suggested that a diet containing 84 mg/kg iron of yeast iron has the same effect as a diet containing 104 mg/kg iron of ferric sulfate, and that a diet containing 104 or 124 mg/kg iron of yeast iron is superior to a diet containing 104 mg/kg iron of ferric sulfate.
Fattening Iberian Pigs Indoors vs. Outdoors: Production Performance and Market Value
Authors: Horrillo Andrés , Gaspar Paula , Muñoz Ángel , Escribano Miguel , González Elena
Published: February 2023

The current Quality Standard regulating the Iberian pig provides for various differentiated farming systems subject to the type of management implemented and the breed of the pigs. This study attempts to analyse the differences between two of these production systems, i.e., the outdoor and the indoor rearing systems by comparing the main technical and economic factors of six farms, three operating under each system, in order to ascertain the most profitable production system. This analysis is based on the information provided by the farm owners. It also evaluates the impact that the COVID-19 pandemic outbreak had on profitability. The results show that both systems spend the same resources on animal feed, which represents nearly 60% of the expense, with the price of purchase of piglets representing 30–32% of the total; however, there are differences in the cost of labour, which is higher in the outdoor variant. In economic terms, outdoor farms obtained a higher gross margin than indoor farms did. Although their production costs are higher, these are offset with larger incomes due to the higher market price of the pigs at the time of slaughter. Lastly, all the farms under study reveal large financial losses on account of COVID-19, given that there was a general decrease in the revenues due to the decrease in the selling price of the pigs, which seems to be the most determinant factor for the economic profits made by these kinds of farms.
Determination of the Binding Epitope of an Anti-Mouse CCR9 Monoclonal Antibody (C9Mab-24) Using the 1× Alanine and 2× Alanine-Substitution Method
Authors: Kobayashi Hiyori , Asano Teizo , Tanaka Tomohiro , Suzuki Hiroyuki , Kaneko Mika K. , Kato Yukinari
Published: February 2023

C-C chemokine receptor 9 (CCR9) is a receptor for C-C-chemokine ligand 25 (CCL25). CCR9 is crucial in the chemotaxis of immune cells and inflammatory responses. Moreover, CCR9 is highly expressed in tumors, including several solid tumors and T-cell acute lymphoblastic leukemia. Several preclinical studies have shown that anti-CCR9 monoclonal antibodies (mAbs) exert antitumor activity. Therefore, CCR9 is an attractive target for tumor therapy. In this study, we conducted the epitope mapping of an anti-mouse CCR9 (mCCR9) mAb, C9Mab-24 (rat IgG2a, kappa), using the 1× alanine (1× Ala)- and 2× alanine (2× Ala)-substitution methods via enzyme-linked immunosorbent assay. We first performed the 1× Ala-substitution method using one alanine-substituted peptides of the mCCR9 N-terminus (amino acids 1–19). C9Mab-24 did not recognize two peptides (F14A and F17A), indicating that Phe14 and Phe17 are critical for C9Mab-24-binding to mCCR9. Furthermore, we conducted the 2× Ala-substitution method using two consecutive alanine-substituted peptides of the mCCR9 N-terminus, and showed that C9Mab-24 did not react with four peptides (M13A–F14A, F14A–D15A, D16A–F17A, and F17A–S18A), indicating that 13-MFDDFS-18 is involved in C9Mab-24-binding to mCCR9. Overall, combining, the 1× Ala- or 2× Ala-scanning methods could be useful for understanding for target–antibody interaction.
Antibodies, B Cell Responses and Immune Responses to SARS-CoV-2 Infections
Authors: Martinez-Sobrido Luis , Kobie James J.
Published: February 2023

Coronaviruses (CoV) are enveloped, positive-sense, single-stranded RNA viruses responsible for causing seasonal, mild respiratory disease in humans [...]
Editorial for Special Issue “Antimicrobial Therapy in Intensive Care Unit”
Authors: Paramythiotou Elizabeth , Routsi Christina
Published: February 2023

Life-threatening infections, either as the initial reason for an admission to the intensive care unit (ICU) or acquired in the ICU, are especially common among critically ill patients [...]
Genetic Organization of Acquired Antimicrobial Resistance Genes and Detection of Resistance-Mediating Mutations in a Gallibacterium anatis Isolate from a Calf Suffering from a Respiratory Tract Infection
Authors: Schink Anne-Kathrin , Hanke Dennis , Semmler Torsten , Roschanski Nicole , Schwarz Stefan
Published: February 2023

Gallibacterium (G.) anatis isolates associated with respiratory diseases in calves and harboring acquired antimicrobial resistance genes have been described in Belgium. The aim of this study was to analyze the genetic organization of acquired resistance genes in the G. anatis isolate IMT49310 from a German calf suffering from a respiratory tract infection. The isolate was submitted to antimicrobial susceptibility testing, and a closed genome was obtained by a hybrid assembly of Illumina MiSeq short-reads and MinION long-reads. Isolate IMT49310 showed elevated MIC values for macrolides, aminoglycosides, florfenicol, tetracyclines, and trimethoprim/sulfamethoxazole. The acquired resistance genes catA1, floR, aadA1, aadB, aphA1, strA, tet(M), tet(B), erm(B), and sul2 were identified within three resistance gene regions in the genome, some of which were associated with IS elements, such as ISVsa5-like or IS15DII. Furthermore, nucleotide exchanges within the QRDRs of gyrA and parC, resulting in amino acid exchanges S83F and D87A in GyrA and S80I in ParC, were identified. Even if the role in the pathogenesis of respiratory tract infections in cattle needs to be further investigated, the identification of a G. anatis isolate with reduced susceptibility to regularly used antimicrobial agents in cases of fatal bovine respiratory tract infections is worrisome, and such isolates might also act as a reservoir for antimicrobial resistance genes.
Dimensional Error Compensation Based on Data-Driven Sliding Mode Terminal Iterative Learning Control for CNC Batch Grinding
Authors: Chen Tiantian , Tian Xincheng
Published: February 2023

Dimensional error of workpiece is an important index that indicts the grinding accuracy of machine tools. Conventional error compensation strategies focus on modeling one or several error factors for a particular CNC machining type, which are time consuming and costly. Based on data-driven sliding mode terminal iterative learning control, a new dimensional error compensation method is proposed in this paper. The compensation algorithm based on an iterative sliding surface and an objective function is established using the terminal experimental data. A modified NC program is fed to the machine tool to push the workpiece dimension towards desired. The theoretical analysis and experimental results show the proposed compensation method can effectively improve the batch grinding accuracy of the machine tool, which shows good perspective in manufacturing industry.
Acoustic Voice and Speech Biomarkers of Treatment Status during Hospitalization for Acute Decompensated Heart Failure
Authors: Murton Olivia M. , Dec G. William , Hillman Robert E. , Majmudar Maulik D. , Steiner Johannes , Guttag John V. , Mehta Daryush D.
Published: February 2023

This study investigates acoustic voice and speech features as biomarkers for acute decompensated heart failure (ADHF), a serious escalation of heart failure symptoms including breathlessness and fatigue. ADHF-related systemic fluid accumulation in the lungs and laryngeal tissues is hypothesized to affect phonation and respiration for speech. A set of daily spoken recordings from 52 patients undergoing inpatient ADHF treatment was analyzed to identify voice and speech biomarkers for ADHF and to examine the trajectory of biomarkers during treatment. Results indicated that speakers produce more stable phonation, a more creaky voice, faster speech rates, and longer phrases after ADHF treatment compared to their pre-treatment voices. This project builds on work to develop a method of monitoring ADHF using speech biomarkers and presents a more detailed understanding of relevant voice and speech features.
Non-Toxic Natural Additives to Improve the Electrical Conductivity and Viscosity of Polycaprolactone for Melt Electrospinning
Authors: Kim Jee Woo , Park Seongho , Park Kyungsoon , Kim Byung-Kwon
Published: February 2023

Polycaprolactone (PCL) is biodegradable and non-toxic, making it an eco-friendly polymer with various medical applications. In order to increase the stability of PCL used in the field of medical applications, it is necessary to be able to produce fibers with a melt electrospinning method that does not use toxic hydrophobic solvents. However, PCL has very high viscosity and low conductivity, making melt electrospinning difficult. This study presents natural additives enabling the solvent-free melt electrospinning of PCL, wherein the physical properties (i.e., conductivity and viscosity) of the additive-mixed PCL are analyzed. Among the natural additives added to PCL, 7 wt% gallic acid increased conductivity by 81 times and decreased viscosity by 1/8526 times, showing the best results. We believe that our study, improving the physical properties of melt PCL by adding natural additives, will be of great help to the development of the melt electrospinning method of PCL.
Lightweight Micro-Expression Recognition on Composite Database
Authors: Ab Razak Nur Aishah , Sahran Shahnorbanun
Published: February 2023

The potential of leveraging micro-expression in various areas such as security, health care and education has intensified interests in this area. Unlike facial expression, micro-expression is subtle and occurs rapidly, making it imperceptible. Micro-expression recognition (MER) on composite dataset following Micro-Expression Grand Challenge 2019 protocol is an ongoing research area with challenges stemming from demographic variety of the samples as well as small and imbalanced dataset. However, most micro-expression recognition (MER) approaches today are complex and require computationally expensive pre-processing but result in average performance. This work will demonstrate how transfer learning from a larger and varied macro-expression database (FER 2013) in a lightweight deep learning network before fine-tuning on the composite dataset can achieve high MER performance using only static images as input. The imbalanced dataset problem is redefined as an algorithm tuning problem instead of data engineering and generation problem to lighten the pre-processing steps. The proposed MER model is developed from truncated EfficientNet-B0 model consisting of 15 layers with only 867k parameters. A simple algorithm tuning that manipulates the loss function to place more importance on minority classes is suggested to deal with the imbalanced dataset. Experimental results using Leave-One-Subject-Out cross-validation on the composite dataset show substantial performance increase compared to the state-of-the-art models.
A Comprehensive Classification Method for the Pore Permeability of Deep-Mine Sandstone Used to Guide Grouting
Authors: Li Yanzhi , Qiao Weiguo , Yang Xuxu , Wu Yue , Li Xungang , Zhang Shuai
Published: February 2023

One type of seepage water that is difficult to plug by grouting is the water exuding through the pores of sandstone in deep underground engineering. Aiming at this problem, this paper collected deep-mine sandstone samples from the Southwest Shandong coalfield, studied the sandstone pore structure and its influential factors by casting thin slices, scanning electron microscopy, mercury intrusion and physical property tests, and selected five representative permeability classification indicators: permeability, porosity, average pore throat radius, comprehensive diagenetic coefficient and sorting coefficient. According to these five indicators, the pore permeability of all the sandstone samples was divided into four subcategories (I1, I2, II1, and II2) from the perspective of grouting. I1 has medium pores and medium pore throats that can be filled with ultrafine cement-based slurries; I2 has medium-small pores and fine pore throats; II1 has medium-small pores and fine pore throats or small pores and microthroats; both I2 and II1 can be filled with chemical slurries; and II2 has micropores and microthroats that cannot be grouted. This case study provides a reference for the classification and evaluation of the pore permeability of sandstone for grouting and lays a foundation for classified permeation grouting and subsequent pore-expanding permeation grouting.
Special Issue on Precision Technologies and Novel Farming Practices to Reduce Chemical Inputs in Agriculture
Authors: Grella Marco , Marucco Paolo , Llop Jordi , Gioelli Fabrizio
Published: February 2023

The sustainability of agriculture is a key point to feed human population in the future [...]
In-Process Tool Condition Forecasting of Drilling CFRP/Ti Stacks Based on ResNet and LSTM Network
Authors: Jiang Zhenxi , Wang Fuji , Zeng Debiao , Zhu Shaowei , Fu Rao
Published: February 2023

Tool condition forecasting (TCF) is a key technology for continuous drilling of CFRP/Ti stacks, as the tool wear is always rapid and severe, which may further induce unexpected drilling quality issues. However, for drilling CFRP/Ti stacks, the cutting spindle power and vibration signals change are complex, influenced by many factors due to the different materials properties. The TCF for drilling CFRP/Ti stacks remains challenging, as the sensitive features are difficult to extract, which decide the accuracy and robustness. Aiming to monitor and forecast tool wear of drilling CFRP/Ti stacks, an in-process TCF method based on residual neural network (ResNet) and long short-term memory (LSTM) network has been proposed in this paper. Using the cutting spindle power and vibration signals preprocessed by the proposed method, the LSTM network with the ResNet-based model integrated can forecast tool-wear values of the next drilling holes. A case study demonstrated the effectiveness of TCF, where the results using raw measured signals and preprocessed datasets are tested for comparison. The mean absolute error (MAE) using raw signals is 45.01 μm, which is 2.20 times bigger than that using preprocess signals. With the proposed method, the data preprocessing for drilling CFRP/Ti stacks can improve the tool-wear forecasting accuracy to MAE 20.43μm level, which meets the demand for online TCF.
Nanotechnology to the Rescue: Therapeutic Strategies Based on Brown Algae for Neurodegenerative Diseases
Authors: Gonçalves Anabela , Fernandes Mário , Lima Margarida , Gomes João Pedro , Silva Filipa , Castro Sara , Sampaio Filipa , Gomes Andreia Castro
Published: February 2023

In the last decades, marine macroalgae have drawn attention mainly because of their bioactive constituents. Most brown algae are distributed over coastal areas of the Atlantic Ocean, Mediterranean Sea, Aegean Sea and Black Sea, and their composition varies with endogenous and exogenous factors. Phlorotannins, fatty acids, sterols and carbohydrates are some of the compounds responsible for biological activities related to cytotoxic, antiviral, antifungal, antibacterial, antidiabetic, antioxidant and anti-inflammatory potential. In this review we seek to highlight some of the compounds responsible for these last two biological activities, which have enormous importance for the management of neurodegenerative diseases, such as Alzheimer and Parkinson’s, with neuroinflammation and oxidative stress as hallmarks. However, one of the major problems associated with treating these diseases is the highly selective blood-brain-barrier, which can be overcome with nanocarriers used as delivery systems. Weighing the risks, benefits and toxicity of the used nanoparticles is nevertheless important. We also discuss zebrafish as an upcoming adequate biological model for in vivo screening of risks and benefits of such treatment strategies. This review aims to enable researchers working in the exploitation of these macroalgae and in the use of nanocarriers to potentiate the controlled delivery of bioactive compounds.
The Influence of Emotional and Cognitive Factors on Limb Laterality Discrimination in Women with Fibromyalgia Syndrome: A Cross-Sectional Study Secondary Analysis
Authors: Riquelme-Aguado Víctor , Gil-Crujera Antonio , Fernández-Carnero Josué , Cuenca-Martínez Ferran , Klett Guillermo Baviano , Esquer Francisco Gómez
Published: February 2023

Previous scientific evidence has shown that patients with fibromyalgia syndrome (FMS) have alterations in the body schema. There have also been findings regarding the influence of psychological factors on pain, as well as evidence that patients with FMS have difficulty performing laterality discrimination tasks. The main objective of this study was to evaluate whether emotional and cognitive factors influence the limb laterality discrimination task in women with FMS. Seventeen of the participants were healthy female controls, and the other seventeen were women diagnosed with FMS. The main outcome measures were laterality discrimination, anxiety symptoms, depression symptoms, pain catastrophizing, and fear-related movement. The main analysis showed that patients with FMS had longer reaction times for laterality discrimination in hands (hand 20 images, p < 0.031; hands 50 images p < 0.013). In the secondary analysis, FMS patients showed emotional (anxiety (p < 0.0001); depression (p < 0.0001)) and cognitive (pain catastrophizing (p < 0.0001); fear-related movement (p < 0.0001)) disorders compared with healthy subjects. There was no correlation between limb laterality discrimination and psychological variables. In conclusion, patients with FMS showed impaired laterality discrimination, but psychological variables were not influenced. This could be due to the implicit nature of the task.
Polyacrylonitrile-Derived Carbon Nanocoating for Long-Life High-Power Phosphate Electrodes
Authors: Nazarov Eugene E. , Tyablikov Oleg A. , Nikitina Victoria A. , Antipov Evgeny V. , Fedotov Stanislav S.
Published: February 2023

Carbon-coating proved an efficient and reliable strategy to increase the power capabilities and lifetime of phosphate-based positive electrode materials for Li-ion batteries. In this work, we provide a systematic study on the influence of polyacrylonitrile-(PAN)-derived carbon coating on electrochemical properties of the nanosized Li-rich Li1+δ(Fe0.5Mn0.5)1−δPO4 (Li-rich LFMP) cathode material, as well as the characterization of carbon-coated composites by means of Raman spectroscopy for the determination of carbon graphitization degree, DF-STEM and STEM-EELS for the estimation of carbon layer thickness, uniformity and compositional homogeneity of the conductive layer respectively, and impedance spectroscopy for the determination of charge transfer resistances of the resulted composite electrodes in Li-based cells. Using PAN as a carbon coating precursor enables significantly enhancing the cycling stability of Li-rich LFMP/C compared to those conventionally obtained with the glucose precursor: up to 40% at high current loads of 5–10C retaining about 78 ± 2% of capacity after 1000 cycles. Varying the PAN-derived carbon content in the composites allows controlling the electrochemical response of the material triggering either a high-capacity or a high-power performance.
Assessment of Rural Vulnerability to Sand and Dust Storms in Iran
Authors: Darvishi Boloorani Ali , Soleimani Masoud , Neysani Samany Najmeh , Bakhtiari Mohsen , Qareqani Masomeh , Papi Ramin , Mirzaei Saham
Published: February 2023

Climate-related hazards such as sand and dust storms (SDS) have various impacts on human health, socio-economy, environment, and agroecosystems. Iran has been severely affected by domestic and external SDS during the last two decades. Considering the fragile economy of Iran’s rural areas and the strong dependence of livelihood on agroecosystems, SDS cause serious damage to human communities. Therefore, there is an urgent need to conduct a vulnerability assessment for developing SDS risk mitigation plans. In this study, various components of SDS vulnerability were formulated through a geographic information system (GIS)-based integrated assessment approach using composite indicators. By implementing a GIS multiple-criteria decision analysis (GIS-MCDA) model using socioeconomic and remote sensing data, a map of rural vulnerability to SDS was produced. Our results show that about 37% of Iran’s rural areas have experienced high and very high levels of vulnerability to SDS. Rural areas in the southeast and south of Iran, especially Sistan and Baluchestan and Hormozgan provinces are more vulnerable to SDS. The findings of this study provide a basis for developing SDS disaster risk-reduction plans and enabling the authorities to prioritize SDS mitigation policies at the provincial administrative scale in Iran.
Dominance Patterns Specified by the Ideal Gas Equation: Example of Examining Simultaneous Multivariate Relation with Scale Analysis Approach
Authors: Tu Juqing , Yuan Dian , Lu Er
Published: February 2023

Climate science involves various functional relations and needs to investigate the dominance or relative importance of the variables in their relation. In our previous studies, we examined several problems in which causal relations are established, showing how the dependent quantity is affected by two or more independent variables. With linear fitting, the relative contributions of the variables to the variation of the quantity are compared. In this study, we examine constraint relation, which is a simultaneous multivariate relation, with all variables in the relation being equal in position. The relation can generally be nonlinear. To be convenient for examining the dominance, plane equation fitting can be used to linearize the relation. The equation of state for ideal dry air is investigated as a simple case of the relation. For this special case, a linearized relation can be obtained from both the fitting and the derivation. The scale analysis tool used in dynamic meteorology is applied here for the dominance analysis. Through comparing the scales of the terms, we can simplify the equation. The simplified relations correspond, respectively, to Charle’s law, Boyle’s law, and Gay-Lussac’s law. The geographical preferences of the different dominance patterns are exhibited. In addition, when considering the change of the variable that is smallest in scale, we can identify which factor is the dominator. The ideal gas law is intentionally chosen as the example, since the relation is simple in form, and the results of dominance can be deduced analytically. A comparison demonstrates that the methods used here for the dominance analysis are reliable.
Statistical Inference of Truncated Cauchy Power-Inverted Topp–Leone Distribution under Hybrid Censored Scheme with Applications
Authors: Mohamed Rania A. H. , Elgarhy Mohammed , Alabdulhadi Manal H. , Almetwally Ehab M. , Radwan Taha
Published: February 2023

In this article, a new two-parameter model called the truncated Cauchy power-inverted Topp–Leone (TCP-ITL) is constructed by merging the truncated Cauchy power -G (TCP-G) family with the inverted Topp–Leone (ITL) distribution. Some structural properties of the newly suggested model are obtained. Different types of entropies are proposed under the TCP-ITL distribution. Under the complete and hybrid censored data, the maximum likelihood (ML), maximum product of spacing (MPSP), and Bayesian estimate approaches are explored. A simulation study is developed to test the proposed distribution’s restricted sample attributes. In the majority of cases, the numerical data revealed that the Bayesian estimates provided more accurate outcomes than the equivalent alternative estimates. The adaptability of the proposed approach is proven using examples from dependability, medicine, and engineering. A real-world data set is utilized to demonstrate the potential of the TCP-ITL distribution in comparison to other well-known distributions. The results of the model selection revealed that the proposed distribution is the best choice for the data sets under consideration.
Impact of R&D on the Innovation of Products and Processes in Latin Countries
Authors: Ortiz Henriquez Rodrigo Esteban , Crespo Fernando , Geldes Cristian , Alves Ferreira Tiago , Castillo-Vergara Mauricio
Published: February 2023

According to the literature on innovation, several vital factors or determinants favor innovation in companies. In the case of R&D, significant advances have been made in the last two decades, which have enriched our understanding of its impact on various innovation outcomes. However, due to a lack of data availability, its study is difficult to address in emerging markets. This is why, using microdata from 5588 firms, we investigate the relationship between R&D investment and the impact on product and process innovations in different Latin American countries. We contribute to the literature by employing a machine learning methodology and comparing its results to a traditional innovation model. Our findings demonstrate the behavior of both product and process innovation methods.
Increased Enzymatic Activity of Acetylcholinesterase Indicates the Severity of the Sterile Inflammation and Predicts Patient Outcome following Traumatic Injury
Authors: Zivkovic Aleksandar R. , Paul Georgina M. , Hofer Stefan , Schmidt Karsten , Brenner Thorsten , Weigand Markus A. , Decker Sebastian O.
Published: February 2023

Traumatic injury induces sterile inflammation, an immune response often associated with severe organ dysfunction. The cholinergic system acts as an anti-inflammatory in injured patients. Acetylcholinesterase (AChE), an enzyme responsible for the hydrolysis of acetylcholine, plays an essential role in controlling cholinergic activity. We hypothesized that a change in the AChE activity might indicate the severity of the traumatic injury. This study included 82 injured patients with an Injury Severity Score (ISS) of 4 or above and 40 individuals without injuries. Bedside-measured AChE was obtained on hospital arrival, followed by a second measurement 4–12 h later. C-reactive protein (CRP), white blood cell count (WBCC), and Sequential Organ Failure Assessment (SOFA) score were simultaneously collected. Injured patients showed an early and sustained increase in AChE activity. CRP remained unaffected at hospital admission and increased subsequently. Initially elevated WBCC recovered 4–12 h later. AChE activity directly correlated with the ISS and SOFA scores and predicted the length of ICU stay when measured at hospital admission. An early and sustained increase in AChE activity correlated with the injury severity and could predict the length of ICU stay in injured patients, rendering this assay a complementary diagnostic and prognostic tool at the hand of the attending clinician in the emergency unit.
Acid Ceramidase Deficiency: Bridging Gaps between Clinical Presentation, Mouse Models, and Future Therapeutic Interventions
Authors: Kleynerman Annie , Rybova Jitka , Faber Mary L. , McKillop William M. , Levade Thierry , Medin Jeffrey A.
Published: February 2023

Farber disease (FD) and spinal muscular atrophy with progressive myoclonic epilepsy (SMA-PME) are ultra-rare, autosomal-recessive, acid ceramidase (ACDase) deficiency disorders caused by ASAH1 gene mutations. Currently, 73 different mutations in the ASAH1 gene have been described in humans. These mutations lead to reduced ACDase activity and ceramide (Cer) accumulation in many tissues. Presenting as divergent clinical phenotypes, the symptoms of FD vary depending on central nervous system (CNS) involvement and severity. Classic signs of FD include, but are not limited to, a hoarse voice, distended joints, and lipogranulomas found subcutaneously and in other tissues. Patients with SMA-PME lack the most prominent clinical signs seen in FD. Instead, they demonstrate muscle weakness, tremors, and myoclonic epilepsy. Several ACDase-deficient mouse models have been developed to help elucidate the complex consequences of Cer accumulation. In this review, we compare clinical reports on FD patients and experimental descriptions of ACDase-deficient mouse models. We also discuss clinical presentations, potential therapeutic strategies, and future directions for the study of FD and SMA-PME.
Exploring the Temporal Patterns of Dynamic Information Flow during Attention Network Test (ANT)
Authors: Duan Keyi , Xie Songyun , Zhang Xin , Xie Xinzhou , Cui Yujie , Liu Ruizhen , Xu Jian
Published: February 2023

The attentional processes are conceptualized as a system of anatomical brain areas involving three specialized networks of alerting, orienting and executive control, each of which has been proven to have a relation with specified time-frequency oscillations through electrophysiological techniques. Nevertheless, at present, it is still unclear how the idea of these three independent attention networks is reflected in the specific short-time topology propagation of the brain, assembled with complexity and precision. In this study, we investigated the temporal patterns of dynamic information flow in each attention network via electroencephalograph (EEG)-based analysis. A modified version of the attention network test (ANT) with an EEG recording was adopted to probe the dynamic topology propagation in the three attention networks. First, the event-related potentials (ERP) analysis was used to extract sub-stage networks corresponding to the role of each attention network. Then, the dynamic network model of each attention network was constructed by post hoc test between conditions followed by the short-time-windows fitting model and brain network construction. We found that the alerting involved long-range interaction among the prefrontal cortex and posterior cortex of brain. The orienting elicited more sparse information flow after the target onset in the frequency band 1–30 Hz, and the executive control contained complex top-down control originating from the frontal cortex of the brain. Moreover, the switch of the activated regions in the associated time courses was elicited in attention networks contributing to diverse processing stages, which further extends our knowledge of the mechanism of attention networks.
The Divergent Effects of the Public’s Sense of Power on Donation Intention
Authors: Yuan Yanpeng , Li Pingping , Ju Fanghui
Published: February 2023

Studies of the relationship between individuals’ sense of power and donation intention have inconsistent findings. Classifying donor intention into two types, this study explored the mechanism through which a sense of power affects donation intention. Using a three-wave time-lagged survey of 1200 people, this study found that situational prevention focus mediates the positive effect of a sense of power on avoidance-based donation intention, and situational promotion focus mediates the positive effect of a sense of power on improvement-based donation intention. Furthermore, a strong perceived ethical climate strengthens the effects of a sense of power. These findings have practical implications for increasing charitable giving and improving the development of charitable programs.
Social-Emotional Development of Children in Asia: A Systematic Review
Authors: Yong Geok Har , Lin Mei-Hua , Toh Teck-Hock , Marsh Nigel V.
Published: February 2023

There has been growing interest in the social-emotional development of children. However, the social-emotional development of children in Asia remains a knowledge gap. This systematic review identifies and summarizes existing studies on children’s social-emotional development in Asia. We conducted a systematic review using the Guidelines for Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). We reviewed 45 studies that met the inclusion criteria, and they were from 12 Asian countries, primarily the East Asia region (China and Hong Kong). Most of the studies were cross-sectional in design (n = 28, 62.2%). Six themes emerged, including (a) social-emotional development (overall) (n = 24, 53.3%); (b) social competence (n = 7, 15.6%); (c) emotional development (n = 5, 11.1%); (d) social-emotional learning (n = 3, 6.7%); (e) problem behavior (n = 3, 6.7%); (f) self-regulation (n = 2, 4.4%); and (g) both social-emotional learning and problem behavior (n = 1, 2.2%). The findings highlighted the paucity of studies, the need for examining more diverse variables in a similar population, and the low quality of intervention studies in social-emotional research in Asia. Research gaps indicate the need for more social-emotional and ethnocultural studies in other Asian regions. Parent and teacher knowledge of children’s social-emotional functioning should be examined more closely in future research.