bluuebunny/crossref_metadata_2025 huggingface dataset:
Promising Novel Method of Acetylation Modification for Regulating Fatty Acid Metabolism in Brassica napus L.
Authors: Jia Xiaojiang , Xiong Xinghua , Chen Hao , Xiao Gang , Cheng Qian , Zhang Zhenqian
Published: March 2022

In this study, lysine acetylation analysis was conducted using two Brassica napus near-isogenic lines, HOCR and LOCR, containing high and low oleic acid contents, respectively, to explore this relationship. Proteins showing differences in quantitative information between the B. napus lines were identified in lysine acetylation analysis, and KEGG pathways were analyzed, yielding 45 enriched proteins, most of which are involved in carbon fixation in photosynthetic organisms, photosynthesis, ascorbate and aldarate metabolism, and glycolysis. Potential key genes related to fatty acid metabolisms were determined. To further explore the effect of acetylation modification on fatty acid metabolisms, the acyl-ACP3 related gene BnaACP363K was cloned, and a base mutation at No.63 was changed via overlapping primer PCR method. This study is the first to demonstrate that acetylation modification can regulate oleic acid metabolisms, which provides a promising approach for the study of the molecular mechanism of oleic acid in rapeseed.
Preclinical Development of Bioengineered Allografts Derived from Decellularized Human Diaphragm
Authors: Barbon Silvia , Stocco Elena , Contran Martina , Facchin Federico , Boscolo-Berto Rafael , Todros Silvia , Sandrin Deborah , Romanato Filippo , Pavan Piero , Macchi Veronica , Vindigni Vincenzo , Bassetto Franco , De Caro Raffaele , Porzionato Andrea
Published: March 2022

Volumetric muscle loss (VML) is the traumatic/surgical loss of skeletal muscle, causing aesthetic damage and functional impairment. Suboptimal current surgical treatments are driving research towards the development of optimised regenerative therapies. The grafting of bioengineered scaffolds derived from decellularized skeletal muscle may be a valid option to promote structural and functional healing. In this work, a cellular human diaphragm was considered as a scaffold material for VML treatment. Decellularization occurred through four detergent-enzymatic protocols involving (1) sodium dodecyl sulfate (SDS), (2) SDS + TergitolTM, (3) sodium deoxycholate, and (4) TergitolTM. After decellularization, cells, DNA (≤50 ng/mg of tissue), and muscle fibres were efficiently removed, with the preservation of collagen/elastin and 60%–70% of the glycosaminoglycan component. The detergent-enzymatic treatments did not affect the expression of specific extracellular matrix markers (Collagen I and IV, Laminin), while causing the loss of HLA-DR expression to produce non-immunogenic grafts. Adipose-derived stem cells grown by indirect co-culture with decellularized samples maintained 80%–90% viability, demonstrating the biosafety of the scaffolds. Overall, the tested protocols were quite equivalent, with the patches treated by SDS + TergitolTM showing better collagen preservation. After subcutaneous implant in Balb/c mice, these acellular diaphragmatic grafts did not elicit a severe immune reaction, integrating with the host tissue.
Novel Biomarkers Detected by Proteomics Predict Death and Cardiovascular Events in Hemodialysis Patients
Authors: Wu Ping-Hsun , Glerup Rie Io , Svensson My Hanna Sofia , Eriksson Niclas , Christensen Jeppe Hagstrup , Laval Philip de , Soveri Inga , Westerlund Magnus , Linde Torbjörn , Ljunggren Östen , Fellström Bengt
Published: March 2022

End-stage kidney disease increases mortality and the risk of cardiovascular (CV) disease. It is crucial to explore novel biomarkers to predict CV disease in the complex setting of patients receiving hemodialysis (HD). This study investigated the association between 92 targeted proteins with all-cause death, CV death, and composite vascular events (CVEs) in HD patients. From December 2010 to March 2011, 331 HD patients were included and followed prospectively for 5 years. Serum was analyzed for 92 CV-related proteins using Proseek Multiplex Cardiovascular I panel, a high-sensitivity assay based on proximity extension assay (PEA) technology. The association between biomarkers and all-cause death, CV death, and CVEs was evaluated using Cox-regression analyses. Of the PEA-based proteins, we identified 20 proteins associated with risk of all-cause death, 7 proteins associated with risk of CV death, and 17 proteins associated with risk of CVEs, independent of established risk factors. Interleukin-8 (IL-8), T-cell immunoglobulin and mucin domain 1 (TIM-1), and C-C motif chemokine 20 (CCL20) were associated with increased risk of all-cause death, CV death, and CVE in multivariable-adjusted models. Stem cell factor (SCF) and Galanin peptides (GAL) were associated with both decreased risk of all-cause death and CV death. In conclusion, IL-8, TIM-1, and CCL20 predicted death and CV outcomes in HD patients. Novel findings were that SCF and GAL were associated with a lower risk of all-cause death and CV death. The SCF warrants further study with regard to its possible biological effect in HD patients.
Safety and Efficacy of Embolization with Microspheres in Chronic Refractory Inflammatory Shoulder Pain: A Pilot Monocentric Study on 15 Patients
Authors: Gremen Emeric , Frandon Julien , Lateur Gabriel , Finas Mathieu , Rodière Mathieu , Horteur Clément , Benassayag Michaël , Thony Frédéric , Pailhe Régis , Ghelfi Julien
Published: March 2022

Purpose: Musculoskeletal (MSK) embolization is emerging in tendinopathy treatment. The objective of this study was to assess the efficacy and safety of MSK embolization with microspheres in the treatment of chronic shoulder pain. Patients and methods: This retrospective monocentric study included patients with chronic shoulder pain resistant to 6 months or more of conventional therapies who were treated with MSK embolization between 2017 and 2021. Embolization was performed using calibrated 100–250 µm microspheres. Clinical success was defined as pain reduction, i.e., a decrease in the visual analogue scale (VAS) pain score of ≥50% at 3 months after MSK embolization as compared to baseline. Adverse events were collected. Results: Fifteen patients (11 women, 4 men) were included, with a median age of 50.3 years (IQR: 46.7–54.5). The median duration of symptoms was 26.6 months (20.6–39.8). The median VAS pain scores were 7.0 (7.0–8.0) at baseline, 6.0 (3.5–7.0) at 1 month, 5.0 (4.5–6.5) and 5.0 (3.0–7.4) at 3 months and 6 months (p = 0.002). Three patients (20%) reported clinical success at 3 months. Three patients experienced minor complications after embolization (paresthesia, n = 2; transient osteo-medullary edema, n = 1) and two patients had moderate complications (transient skin ischemia). Conclusion: MSK embolization with microspheres for treatment of refractory chronic shoulder pain showed moderate results in terms of clinical success and safety.
Robust PVC Identification by Fusing Expert System and Deep Learning
Authors: Cai Zhipeng , Wang Tiantian , Shen Yumin , Xing Yantao , Yan Ruqiang , Li Jianqing , Liu Chengyu
Published: March 2022

Premature ventricular contraction (PVC) is one of the common ventricular arrhythmias, which may cause stroke or sudden cardiac death. Automatic long-term electrocardiogram (ECG) analysis algorithms could provide diagnosis suggestion and even early warning for physicians. However, they are mutually exclusive in terms of robustness, generalization and low complexity. In this study, a novel PVC recognition algorithm that combines deep learning-based heartbeat template clusterer and expert system-based heartbeat classifier is proposed. A long short-term memory-based auto-encoder (LSTM-AE) network was used to extract features from ECG heartbeats for K-means clustering. Thus, the templates were constructed and determined based on clustering results. Finally, the PVC heartbeats were recognized based on a combination of multiple rules, including template matching and rhythm characteristics. Three quantitative parameters, sensitivity (Se), positive predictive value (P+) and accuracy (ACC), were used to evaluate the performances of the proposed method on the MIT-BIH Arrhythmia database and the St. Petersburg Institute of Cardiological Technics database. Se on the two test databases was 87.51% and 87.92%, respectively; P+ was 92.47% and 93.18%, respectively; and ACC was 98.63% and 97.89%, respectively. The PVC scores on the third China Physiological Signal Challenge 2020 training set and hidden test set were 36,256 and 46,706, respectively, which could rank first in the open-source codes. The results showed that the combination strategy of expert system and deep learning can provide new insights for robust and generalized PVC identification from long-term single-lead ECG recordings.
Review of Label-Free Monitoring of Bacteria: From Challenging Practical Applications to Basic Research Perspectives
Authors: Péter Beatrix , Farkas Eniko , Kurunczi Sandor , Szittner Zoltán , Bősze Szilvia , Ramsden Jeremy J. , Szekacs Inna , Horvath Robert
Published: March 2022

Novel biosensors already provide a fast way to detect the adhesion of whole bacteria (or parts of them), biofilm formation, and the effect of antibiotics. Moreover, the detection sensitivities of recent sensor technologies are large enough to investigate molecular-scale biological processes. Usually, these measurements can be performed in real time without using labeling. Despite these excellent capabilities summarized in the present work, the application of novel, label-free sensor technologies in basic biological research is still rare; the literature is dominated by heuristic work, mostly monitoring the presence and amount of a given analyte. The aims of this review are (i) to give an overview of the present status of label-free biosensors in bacteria monitoring, and (ii) to summarize potential novel directions with biological relevancies to initiate future development. Optical, mechanical, and electrical sensing technologies are all discussed with their detailed capabilities in bacteria monitoring. In order to review potential future applications of the outlined techniques in bacteria research, we summarize the most important kinetic processes relevant to the adhesion and survival of bacterial cells. These processes are potential targets of kinetic investigations employing modern label-free technologies in order to reveal new fundamental aspects. Resistance to antibacterials and to other antimicrobial agents, the most important biological mechanisms in bacterial adhesion and strategies to control adhesion, as well as bacteria-mammalian host cell interactions are all discussed with key relevancies to the future development and applications of biosensors.
Antibiotic Therapy in Integrated Oncology and Palliative Cancer Care: An Observational Study
Authors: Moen Martine Kjølberg , Løhre Erik Torbjørn , Jakobsen Gunnhild , Thronæs Morten , Klepstad Pål
Published: March 2022

Decision-making for antibiotic therapy in palliative cancer care implies avoiding futile interventions and to identify patients who benefit from treatment. We evaluated patient-reported outcome-measures (PROMs), physiological findings, and survival in palliative cancer care patients hospitalized with an infection. All acute admissions during one year, directly to a University Hospital unit that provided integrated services, were included. Serious infection was defined as a need to start intravenous antibiotics. PROMs, clinical and paraclinical variables, and survival were obtained. Sixty-two of 257 patients received intravenous antibiotic treatment. PROMs were generally similar in the infection group and the non-infection group, both in respect to intensities at admission and improvements during the stay. There were more physiological and paraclinical deviations at admission in patients in the infection group. These deviations improved during the stay. Survival was not poorer in the infection group compared to the non-infection group. Patients in integrated cancer care were as likely to be put on intravenous antibiotics but had longer survival. In integrated oncology and palliative cancer services, patients with an infection had similar outcomes as those without an infection. This argues that the use of intravenous antibiotics is appropriate in many patients admitted to palliative care.
Mass Cytometric Analysis of Early-Stage Mycosis Fungoides
Authors: Guo Nannan , Jia Li , Out-Luiting Coby , Miranda Noel F. C. C. de , Willemze Rein , Koning Frits , Vermeer Maarten , Quint Koen
Published: March 2022

Mycosis fungoides (MF) is the most common subtype of cutaneous T-cell lymphoma. Early-stage disease is characterized by superficial infiltrates of small- to medium-sized atypical epidermotropic T lymphocytes that are clonal related. Nevertheless, the percentage of atypical T cells is low with many admixed reactive immune cells. Despite earlier studies, the composition and spatial characteristics of the cutaneous lymphocytic infiltrate has been incompletely characterized. Here, we applied mass cytometry to profile the immune system in skin biopsies of patients with early-stage MF and in normal skin from healthy individuals. Single-cell suspensions were prepared and labeled with a 43-antibody panel, and data were acquired on a Helios mass cytometer. Unbiased hierarchical clustering of the data identified the major immune lineages and heterogeneity therein. This revealed patient-unique cell clusters in both the CD4+ and myeloid cell compartments but also phenotypically distinct cell clusters that were shared by most patients. To characterize the immune compartment in the tissue context, we developed a 36-antibody panel and performed imaging mass cytometry on MF skin tissue. This visualized the structure of MF skin and the distribution of CD4+ T cells, regulatory T cells, CD8+ T cells, malignant T cells, and various myeloid cell subsets. We observed clusters of CD4+ T cells and multiple types of dendritic cells (DCs) identified through differential expression of CD11c, CD1a, and CD1c in the dermis. These results indicated substantial heterogeneity in the composition of the local immune infiltrate but suggest a prominent role for clustered CD4–DC interactions in disease pathogenesis. Probably, the local inhibition of such interactions may constitute an efficient treatment modality.
Metabolic Reprogramming and Its Relationship to Survival in Hepatocellular Carcinoma
Authors: Wang Qingqing , Tan Yexiong , Jiang Tianyi , Wang Xiaolin , Li Qi , Li Yanli , Dong Liwei , Liu Xinyu , Xu Guowang
Published: March 2022

Hepatocarcinogenesis is frequently accompanied by substantial metabolic reprogramming to maximize the growth and proliferation of cancer cells. In this study, we carried out a comprehensive study of metabolomics and lipidomics profiles combined with gene expression analysis to characterize the metabolic reprogramming in hepatocellular carcinoma (HCC). Compared with adjacent noncancerous liver tissue, the enhanced aerobic glycolysis and de novo lipogenesis (DNL) and the repressed urea cycle were underscored in HCC tissue. Furthermore, multiscale embedded correlation analysis was performed to construct differential correlation networks and reveal pathologically relevant molecule modules. The obtained hub nodes were further screened according to the maximum biochemical diversity and the least intraclass correlation. Finally, a panel of ornithine, FFA 18:1, PC O-32:1 and TG (18:1_17:1_18:2) was generated to achieve the prognostic risk stratification of HCC patients (p < 0.001 by log-rank test). Altogether, our findings suggest that the metabolic dysfunctions of HCC detected via metabolomics and lipidomics would contribute to a better understanding of clinical relevance of hepatic metabolic reprogramming and provide potential sources for the identification of therapeutic targets and the discovery of biomarkers.
Evaluation of Antibiotic-Based Selection Methods for Camelina sativa Stable Transformants
Authors: Ontiveros-Cisneros Abraham , Moss Oliver , Van Moerkercke Alex , Van Aken Olivier
Published: March 2022

Camelina sativa (Camelina) is an oilseed crop that in recent years has gained importance due to its closeness to the plant model organism Arabidopsis thaliana (Arabidopsis), its low agronomical requirements, and the ability to grow under temperate conditions. To explore all the agronomical and biotechnological possibilities of this crop, it is important to evaluate the usability of the molecular procedures currently available for plants. One of the main tools for plant genetic modification and genetic studies is stable plant transformation. In the case of Arabidopsis, as well as Camelina, floral dipping is the easiest and most used method, which is followed by a selection for stable transformants. Commonly used selection methods for Camelina involve Discosoma sp. red protein (DsRed) fluorescence screening. However, many widely used plant transformation vector systems, for example those used in Arabidopsis and grasses, rely on antibiotic resistance selection. In this study, we evaluated the usability of different antibiotics including kanamycin (Kan), hygromycin (Hyg) and BASTA, and propose optimised protocols for selecting T1 and subsequent generation Camelina transformants, as well as crossing of Camelina lines expressing different transgenes. Finally, we also showed that overexpression of genes encoding enzymes from the seco-iridoid pathway of Catharanthus roseus using Hyg or BASTA-based expression constructs could be successfully achieved in Camelina, demonstrating the potential of these methods for metabolic engineering. Overall, in this study we show an efficient way to sterilize seeds, handle and perform selection of Camelina for use with transformation vectors designed for Arabidopsis thaliana. We also demonstrate a successful method to cross Camelina sativa and provide qRT-PCR results to prove its effectiveness.
NXN Gene Epigenetic Changes in an Adult Neurogenesis Model of Alzheimer’s Disease
Authors: Blanco-Luquin Idoia , Acha Blanca , Urdánoz-Casado Amaya , Gómez-Orte Eva , Roldan Miren , Pérez-Rodríguez Diego R. , Cabello Juan , Mendioroz Maite
Published: March 2022

In view of the proven link between adult hippocampal neurogenesis (AHN) and learning and memory impairment, we generated a straightforward adult neurogenesis in vitro model to recapitulate DNA methylation marks in the context of Alzheimer’s disease (AD). Neural progenitor cells (NPCs) were differentiated for 29 days and Aβ peptide 1–42 was added. mRNA expression of Neuronal Differentiation 1 (NEUROD1), Neural Cell Adhesion Molecule 1 (NCAM1), Tubulin Beta 3 Class III (TUBB3), RNA Binding Fox-1 Homolog 3 (RBFOX3), Calbindin 1 (CALB1), and Glial Fibrillary Acidic Protein (GFAP) was determined by RT-qPCR to characterize the culture and framed within the multistep process of AHN. Hippocampal DNA methylation marks previously identified in Contactin-Associated Protein 1 (CNTNAP1), SEPT5-GP1BB Readthrough (SEPT5-GP1BB), T-Box Transcription Factor 5 (TBX5), and Nucleoredoxin (NXN) genes were profiled by bisulfite pyrosequencing or bisulfite cloning sequencing; mRNA expression was also measured. NXN outlined a peak of DNA methylation overlapping type 3 neuroblasts. Aβ-treated NPCs showed transient decreases of mRNA expression for SEPT5-GP1BB and NXN on day 9 or 19 and an increase in DNA methylation on day 29 for NXN. NXN and SEPT5-GP1BB may reflect alterations detected in the brain of AD human patients, broadening our understanding of this disease.
The Promising Therapeutic and Preventive Properties of Anthocyanidins/Anthocyanins on Prostate Cancer
Authors: Mottaghipisheh Javad , Doustimotlagh Amir Hossein , Irajie Cambyz , Tanideh Nader , Barzegar Alireza , Iraji Aida
Published: March 2022

As water-soluble flavonoid derivatives, anthocyanidins and anthocyanins are the plants pigments mostly rich in berries, pomegranate, grapes, and dark color fruits. Many bioactivity properties of these advantageous phytochemicals have been reported; among them, their significant abilities in the suppression of tumor cells are of the promising therapeutic features, which have recently attracted great attention. The prostate malignancy, is considered the 2nd fatal and the most distributed cancer type in men worldwide. The present study was designated to gather the preclinical and clinical studies evaluating potencies of anthocyanidins/anthocyanins for the treatment and prevention of this cancer type for the first time. In general, findings confirm that the anthocyanins (especifically cyanidin-3-O-glucoside) indicated higher activity against prostatic neoplasms compared to their correlated anthocyanidins (e.g., delphinidin); in which potent anti-inflammatory, apoptosis, and anti-proliferative activities were analyzed. Complementary anti-prostate cancer assessment of diverse naturally occurred anthocyanidins/anthocyanins and their synthetically optimized derivatives through preclinical experiments and eventually confirmed by clinical trials can promisingly lead to discover natural-based chemotherapeutic drug options.
Therapeutic Anti-Depressant Potential of Microbial GABA Produced by Lactobacillus rhamnosus Strains for GABAergic Signaling Restoration and Inhibition of Addiction-Induced HPA Axis Hyperactivity
Authors: Tette Fernanda-Marie , Kwofie Samuel K. , Wilson Michael D.
Published: March 2022

The role of the microbiota–gut–brain (MGB) axis in mood regulation and depression treatment has gained attention in recent years, as evidenced by the growing number of animal and human studies that have reported the anti-depressive and associated gamma-aminobutyric acid-ergic (GABAergic) effects of probiotics developed from Lactobacillus rhamnosus bacterial strains in the gut microbiome. The depressive states attenuated by these probiotics in patients suffering from clinical depression also characterize the severe and relapse-inducing withdrawal phase of the addiction cycle, which has been found to arise from the intoxication-enabled hyperregulation of the hypothalamic–pituitary–adrenal (HPA) axis, the body’s major stress response system, and a corresponding attenuation of its main inhibitory system, the gamma-aminobutyric acid (GABA) signaling system. Therefore, the use of probiotics in the treatment of general cases of depression provides hope for a novel therapeutic approach to withdrawal depression remediation. This review discusses potential therapeutic avenues by which probiotic application of Lactobacillus rhamnosus strains can be used to restore the central GABAergic activity responsible for attenuating the depression-inducing HPA axis hyperactivity in addiction withdrawal. Also, information is provided on brain GABAergic signaling from other known GABA-producing strains of gut microbiota.
Electrical and Structural Properties of CVD-Graphene Oxidized Using KMnO4/H2SO4 Solution
Authors: Choi Jin-Seok , Im Ki-Sik , Lee Tae-Kyun , Choi Yeo-Jin , An Sung-Jin
Published: March 2022

We report the electrical properties of graphene grown via chemical vapor deposition (CVD-graphene) and oxidized using a KMnO4/dilute H2SO4 mixture. CVD-graphene was successfully oxidized without any pores or peeling off from the substrates. When the H2SO4 concentration was increased, the electrical resistance of the oxidized graphene (OG) increased. In particular, OG-20 shows a nonlinear current–voltage curve similar to that of a diode owing to direct tunneling through the interfaces between the nanosized sp2 and sp3 regions. The changes in electrical properties occurred because of structural evolution. As the H2SO4 concentration increased, the number of oxygen functional groups (epoxide/hydroxyl and carboxyl groups) in the OG increased. In addition, a reduction in the average distance between defects in the OG was determined using Raman spectroscopy. Oxidation using a KMnO4/dilute H2SO4 mixture results in CVD-graphene with modified electrical properties for graphene-based applications.
Evaluation of a Multi-Mode-Transceiver for Enhanced UAV Visibility and Connectivity in Mixed ATM/UTM Contexts
Authors: Schelle Alexander , Völk Florian , Schwarz Robert T. , Knopp Andreas , Stütz Peter
Published: March 2022

Visibility and communication are the essential pillars for safe flight operations in dense airspaces. Small Unmanned Aerial Vehicles (UAVs) of the order of up to 25 kg are increasingly being used at airports as a cost-effective alternative for maintenance and calibration work. However, the joint operation of manned and unmanned aircraft in busy airspaces poses a major challenge. Due to the small diameter of such UAVs, the established principle of “see and avoid” is difficult or even impossible to implement, especially during take-off and landing. For this reason, a certified Mode A/C/S transponder supporting ADS-B was extended with an embedded system and a cellular interface to realize a Multi-Mode-Transceiver (MMT). Integrated into a UAV, the MMT can provide aircraft visibility in the context of traditional manned Air Traffic Management (ATM) and future UAS Traffic Management (UTM) at the same time. This multimodal communication approach was investigated in flight test campaigns with two commercially available UAS that were connected to an experimental UTM with a simulated controlled airspace. The results confirm the safety gain of the multimodal cooperative approach. Furthermore, the collaborative interface with ATC enables the digital transmission of transponder codes, entry clearances and emergency procedures without the need for a voice radio communication. However, the parallel operation of both radio technologies in a confined space requires modifications to the transmission power and alignment of the radio antennas to avoid mutual interference. Furthermore, different reference planes of barometric altitude measurement in manned and unmanned aviation pose additional challenges that need to be addressed.
Upper-Ocean Processes Controlling the Near-Surface Temperature in the Western Gulf of Mexico from a Multidecadal Numerical Simulation
Authors: Zheng Yangxing , Bourassa Mark , Dukhovskoy Dmitry , Ali M.
Published: March 2022

The upper-ocean processes controlling the near-surface layer temperature in the western Gulf of Mexico (GOM) are examined by estimating the contributing terms in the heat equation based on a 54-year simulation of an eddy-resolving HYbrid Coordinate Ocean Model (HYCOM). An eddy-active region defined by large surface eddy kinetic energy, representing the Loop Current eddies (LCEs) primary trajectory region, is selected for analysis. Both observations and the simulation reveal that the mean net surface heat flux cools the northern GOM and warms the southern GOM. Mean horizontal heat advection contributes to an overall cooling in the eddy-active region. Mean vertical heat advection has a strong seasonal variability associated with the strong seasonal cycle of the mixed layer process: winters tend to have a strong downward heat advection in the eddy-active region and a strong upward heat advection in the rest of the western GOM, while summers tend to have a weak advective heat flux. The downwelling (upwelling) is primarily due to the dominant anticyclonic (cyclonic) wind stress curl. Mean eddy heat flux convergence contributes to the overall warming in the upper ocean of the western GOM. Diffusive flux is not small across the thermocline, and it is expected to have an insignificant influence on the near-surface temperature.
A Multi-Entity Knowledge Joint Extraction Method of Communication Equipment Faults for Industrial IoT
Authors: Liang Kun , Zhou Baoxian , Zhang Yiying , He Yeshen , Guo Xiaoyan , Zhang Bo
Published: March 2022

The Industrial Internet of Things (IIoT) deploys massive communication devices for information collection and process control. Once it reaches failure, it will seriously affect the operation of the industrial system. This paper proposes a new method for multi-entity knowledge joint extraction (MEKJE) of IIoT communication equipment faults. This method constructs a multi-task tightly coupled model of fault entity and relationship extraction. We use it to implement word embedding and bidirectional semantic capture to generate computable text vectors. At the same time, a multi-entity segmentation method is proposed, which uses noise filtering to distinguish the multi-fault relationship of single corpus. We constructed a dataset of communication failures in power IIoT and conducted experiments. The experimental results show that the method performs best in tests with the Faulty Text dataset and the CLUENER dataset. In particular, the model achieves an F1 value of 78.6% in the evaluation of relationship extraction for multiple entities, and a significant improvement of 5–8% in its accuracy and recall. It enables effective mapping and accurate extraction of fault knowledge data.
Design of Compact Complex Impedance Transformer with Frequency and Terminal Impedance Tunability
Authors: Liu Hongmei , Guo Yongquan , Wang Xinshuo , Fang Shaojun , Wang Zhongbao
Published: March 2022

In the paper, a compact complex impedance transformer (CIT) composed of the cascading of three varactors loaded coupled lines and two variable shunt susceptances was proposed. Highly flexible tunability functions including only frequency tunable, only impedance tunable, and both frequency and impedance tunable can be achieved by tuning the capacitance of two types of varactors and the value of the susceptance. Design equations were derived using the even–odd mode analysis and examples are given for descripting the design procedures. For validation, a prototype was designed and fabricated. During measurement, three cases were exhibited. When the termination impedance was fixed, the measured center frequency can be tuned in the range of 1.1–2.1 GHz (62.5%). When the frequency was determined, different terminal impedances can be matched by the prototype. The function of frequency tunable at different terminal impedances is also trated by the measured results. After comparison, the potential of the proposed CIT for applications in radio frequency front-end were demonstrated.
Applying AI Tools for Modeling, Predicting and Managing the White Wine Fermentation Process
Authors: Florea Adrian , Sipos Anca , Stoisor Melisa-Cristina
Published: March 2022

This paper reveals two of the challenges faced by Romania and proposes a sustainable and simple solution for its wine industry. First, substantial areas with vineyards that may produce qualitative wine, and second, the very low digitalization rate of industrial sectors. More precisely, this work proposes a solution for digitalizing the fermentation process of white wine, allowing it to be adapted for other control techniques (i.e., knowledge-based systems, intelligent control). Our method consists of implementing a pre-trained multi-layer perceptron neural network, using genetic algorithms capable of predicting the concentration of alcohol and the amount of substrate at a certain point in time that starts from the initial configuration of the fermentation process. The purpose of predicting these process features is to obtain information about status variables so that the process can be automatically driven. The main advantage of our application is to help experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors. After comprehensive simulations using experimental data obtained from previous fermentation processes, we concluded that a configuration that is close to the optimal one, for which the prediction accuracy is high, is a neural network (NN) having an input layer with neurons for temperature, time, initial substrate concentration, and the biomass concentration, a hidden layer with 10 neurons, and an output layer with 2 neurons representing the alcohol and substrate concentration, respectively. The best results were obtained with a pre-trained NN, using a genetic algorithm (GA) with a population of 50 individuals for 20 generations, a crossover probability of 0.9, and a probability of mutation of 0.5 that uniformly decreases depending on the generations, based on a beta coefficient of 0.3 and an elitist selection method. In the case of a data set with a larger number of variables, which also contains data regarding pH and CO2, the prediction accuracy is even higher, leading to the conclusion that a larger data set positively influences the performance of the neural network. Furthermore, methods based on artificial intelligence applications like neural networks, along with various heuristic optimization methods such as genetic algorithms, are essential if hardware sensors cannot be used, or if direct measurements cannot be made.
The Measurement, Application, and Effect of Oxygen in Microbial Fermentations: Focusing on Methane and Carboxylate Production
Authors: Magdalena Jose Antonio , Angenent Largus T. , Usack Joseph G.
Published: March 2022

Oxygen is considered detrimental to anaerobic fermentation processes by many practitioners. However, deliberate oxygen sparging has been used successfully for decades to remove H2S in anaerobic digestion (AD) systems. Moreover, microaeration techniques during AD have shown that small doses of oxygen may enhance process performance and promote the in situ degradation of recalcitrant compounds. However, existing oxygen dosing techniques are imprecise, which has led to inconsistent results between studies. At the same time, real-time oxygen fluxes cannot be reliably quantified due to the complexity of most bioreactor systems. Thus, there is a pressing need for robust monitoring and process control in applications where oxygen serves as an operating parameter or an experimental variable. This review summarizes and evaluates the available methodologies for oxygen measurement and dosing as they pertain to anaerobic microbiomes. The historical use of (micro-)aeration in anaerobic digestion and its potential role in other anaerobic fermentation processes are critiqued in detail. This critique also provides insights into the effects of oxygen on these microbiomes. Our assessment suggests that oxygen dosing, when implemented in a controlled and quantifiable manner, could serve as an effective tool for bioprocess engineers to further manipulate anaerobic microbiomes for either bioenergy or biochemical production.
Early Smoke Detection Based on Improved YOLO-PCA Network
Authors: Masoom S. Muhammad , Zhang Qixing , Dai Peiwen , Jia Yang , Zhang Yongming , Zhu Jiping , Wang Jinjun
Published: March 2022

Early detection of smoke having indistinguishable pixel intensities in digital images is a difficult task. To better maintain fire surveillance, early smoke detection is crucial. To solve the problem, we have integrated the principal component analysis (PCA) as a pre-processing module with the improved version of You Only Look Once (YOLOv3). The ordinary YOLOv3 structure has been improved after inserting one extra detection scale at stride-4 specifically to detect immense small smoke instances in the wild. The improved network design establishes a sequential relation between feature maps of lower spatial information and fine-grained semantic information in up-sampled maps via skip connections and concatenation operations. The testing of the improved model is carried out on self-prepared smoke datasets. In digital images, the smoke instances are captured in various complicated environments, for example, the mountains and fog in the background. A principal component analysis (PCA) helps in useful features selection and abandons the involvement of redundant features in the testing of the trained network hence, overcoming the latency at inference stage. In addition, to process small smoke images as positive samples during training, new sizes of anchors are calculated on small smoke data at a specified Intersection over Union (IoU) threshold. The experimental results show the improvement in precision rate, recall rate, and mean harmonic (F1-score) by 2.67, 3.06, and 5.59 percentages. The respective improvements in average precision (AP) and mean average precision (mAP) are 1.66 and 2.78 percentages.
From Darcy Equation to Darcy Paradox
Authors: Di Nucci Carmine , Celli Daniele
Published: March 2022

This theoretical paper focuses on the single-phase fluid flow through a granular porous medium. The emphasis is on the Darcy flow regime (without free boundary) of a linear viscous fluid in a saturated, deformable, homogeneous porous medium. The approach is developed at the Darcy scale (also referred to as macroscale or phenomenological scale). Within this framework, some discrete aspects of the flow model are highlighted, the governing equations are revisited, the thermodynamic state functions are reconsidered, and the Darcy paradox is presented. The Darcy paradox is illustrated for the isoshoric-isothermal flow of a viscous fluid in the liquid state, in a homogenous porous medium. After some remarks about the intrinsic assumption of this kind of flow, the governing equations are reduced to a well-known parabolic equation. According to this equation, infinitesimal pressure disturbances diffuse at an infinite speed. To remove this paradox, a mathematical model, based on the elementary scales method, is employed.
Barriers and Facilitators to Screening for Cognitive Impairment in Australian Rural Health Services: A Pilot Study
Authors: MacDermott Sean , McKechnie Rebecca , LoGiudice Dina , Morgan Debra , Blackberry Irene
Published: March 2022

Australian National standards recommend routine screening for all adults over 65 years by health organisations that provide care for patients with cognitive impairment. Despite this, screening rates are low and, when implemented, screening is often not done well. This qualitative pilot study investigates barriers and facilitators to cognitive screening for older people in rural and regional Victoria, Australia. Focus groups and interviews were undertaken with staff across two health services. Data were analysed via thematic analysis and contextualized within the i-PARIHS framework. Key facilitators of screening included legislation, staff buy-in, clinical experience, appropriate training, and interorganisational relationships. Collaborative implementation processes, time, and workloads were considerations in a recently accredited tertiary care setting. Lack of specialist services, familiarity with patients, and infrastructural issues may be barriers exacerbated in rural settings. In lieu of rural specialist services, interorganisational relationships should be leveraged to facilitate referring ‘outwards’ rather than ‘upwards’.
Producing Cherry Tomatoes in Urban Agriculture
Authors: Richardson Matthew L. , Arlotta Caitlin G.
Published: March 2022

Agriculture in urban and urbanizing areas will be increasingly critical to enhancing food security and food sovereignty, creating income, strengthening social interactions, and improving health outcomes in cities. We used three roofs, a hydroponic system, an aquaponic system, and field rows in an urban environment to grow six dwarf tomato cultivars: ‘Micro Tom’, ‘Red Robin’, ‘Sweet ‘n’ Neat’, ‘Terenzo’, ‘Tiny Tim’, and ‘Tumbler.’ We measured the marketable yield and non-marketable yield, mass of non-marketable tomatoes exhibiting defects, and the content of 12 mineral nutrients in fruits. We found the productivity often varied among cultivars within a cropping system. ‘Terenzo’ and ‘Tumbler’ were always some of the most productive cultivars, whereas ‘Micro Tom’ was normally among the least productive cultivars. The production from ‘Red Robin’, ‘Tiny Tim’, and ‘Sweat ‘n’ Neat’ was more variable, sometimes producing high, moderate, or low mass. The mineral content was especially variable across the cultivars and we did not identify cultivars that were consistently high or low in mineral content across systems, indicating that the mineral content was highly influenced by a genotype x environment interaction. The amount of 5 minerals differed across cultivars in aquaponics, 9 differed in hydroponics, and 6–12 differed in the roof systems. A high-yielding cultivar should be selected first and production methods can then be modified to maximize the nutrient content.
Predicting Terrorism in Europe with Remote Sensing, Spatial Statistics, and Machine Learning
Authors: Buffa Caleb , Sagan Vasit , Brunner Gregory , Phillips Zachary
Published: March 2022

This study predicts the presence or absence of terrorism in Europe on a previously unexplored spatial scale. Dependent variables consist of satellite imagery and socio-environmental data. Five machine learning models were evaluated over the following binary classification problem: the presence or absence of historical attacks within hexagonal-grid cells of 25 square kilometers. Four spatial statistics were conducted to assess the validity of the results and improve our inferential understanding of spatial processes among terror attacks. This analysis resulted in a Random Forest model that achieves 0.99 accuracy in predicting the presence or absence of terrorism at a spatial resolution of approximately 5 km. The results were validated by robust F1 and average precision scores of 0.96 and 0.97, respectively. Additionally, statistical analysis revealed spatial differences between separatists and all other terrorist types. This work concludes that remote sensing, machine learning, and spatial techniques are important and valuable methods for providing insight into terrorist activity and behavior.
Is One-Way Multi-Station Feasible? Influence of Value and Cost on Travel Intention of Urban Agglomeration in the Guangdong–Hong Kong–Macao Greater Bay Area
Authors: Su Haiyang , Chen Chaolong
Published: March 2022

Regional tourism with urban agglomeration as the spatial carrier has become one of the flow characteristics of many tourists. Tourists visiting multiple cities at one time will certainly gain more value than visiting one city, but they will also pay more costs, thus affecting their emotions and willingness to travel. But the mechanism and theoretical boundaries have not been clarified. Based on the cognitive–affective–behavioral attitude model and the customer-delivered-value model, this paper takes the tourism destination tourists of the Guangdong–Hong Kong–Macao Greater Bay Area urban agglomeration as samples to explore the influence mechanism of tourists’ perceived functional value, social value and knowledge value on positive emotion and travel intention, and to test the moderating mediating effect of monetary cost, energy cost and psychological cost on positive emotion. Social value and knowledge value positively affect travel intention. Functional value, knowledge value and social value positively affect positive emotion, and positive emotion positively affect travel intention. Positive emotion plays a complete mediating role between functional value, social value and travel intention, and plays a partial mediating role between knowledge value and travel intention. Monetary cost, energy cost and psychological cost respectively moderate the mediating effect of positive emotion between functional value and travel intention. Psychological cost moderates the mediating effect of positive emotion between social value and travel intention. Monetary cost and psychological cost respectively moderate the mediating effect of positive emotion between knowledge value and travel intention. Differences in the impact of consumers’ perceived value at different levels on positive emotion and travel intentions. It opens up the differences in the effects of the interaction of different levels of perceived value and different types of perceived cost on positive emotion. From an empirical point of view, it is proved that the tourism boutique line design based on multicity destination combination in China is feasible as a method to promote tourism integration and regional tourism brand building. It also puts forward the management enlightenment of regional tourism integration and regional tourism brand building from the perspectives of enterprises, front-line service personnel, residents and government.
A Knowledge Discovery Method for Landslide Monitoring Based on K-Core Decomposition and the Louvain Algorithm
Authors: Wang Ping , Deng Xingdong , Liu Yang , Guo Liang , Zhu Jun , Fu Lin , Xie Yakun , Li Weilian , Lai Jianbo
Published: March 2022

Landslide monitoring plays an important role in predicting, forecasting and preventing landslides. Quantitative explorations at the subject level and fine-scale knowledge in landslide monitoring research can be used to provide information and references for landslide monitoring status analysis and disaster management. In the context of the large amount of network information, it is difficult to clearly determine and display the domain topic hierarchy and knowledge structure. This paper proposes a landslide monitoring knowledge discovery method that combines K-core decomposition and Louvain algorithms. In this method, author keywords are used as nodes to construct a weighted co-occurrence network, and a pruning standard value is defined as K. The K-core approach is used to decompose the network into subgraphs. Combined with the unsupervised Louvain algorithm, subgraphs are divided into different topic communities by setting a modularity change threshold, which is used to establish a topic hierarchy and identify fine-scale knowledge related to landslide monitoring. Based on the Web of Science, a comparative experiment involving the above method and a high-frequency keyword subgraph method for landslide monitoring knowledge discovery is performed. The results show that the run time of the proposed method is significantly less than that of the traditional method.
Biosynthesis of Fungal Natural Products Involving Two Separate Pathway Crosstalk
Authors: Dai Guangzhi , Shen Qiyao , Zhang Youming , Bian Xiaoying
Published: March 2022

Fungal natural products (NPs) usually possess complicated structures, exhibit satisfactory bioactivities, and are an outstanding source of drug leads, such as the cholesterol-lowering drug lovastatin and the immunosuppressive drug mycophenolic acid. The fungal NPs biosynthetic genes are always arranged within one single biosynthetic gene cluster (BGC). However, a rare but fascinating phenomenon that a crosstalk between two separate BGCs is indispensable to some fungal dimeric NPs biosynthesis has attracted increasing attention. The hybridization of two separate BGCs not only increases the structural complexity and chemical diversity of fungal NPs, but also expands the scope of bioactivities. More importantly, the underlying mechanism for this hybridization process is poorly understood and needs further exploration, especially the determination of BGCs for each building block construction and the identification of enzyme(s) catalyzing the two biosynthetic precursors coupling processes such as Diels–Alder cycloaddition and Michael addition. In this review, we summarized the fungal NPs produced by functional crosstalk of two discrete BGCs, and highlighted their biosynthetic processes, which might shed new light on genome mining for fungal NPs with unprecedented frameworks, and provide valuable insights into the investigation of mysterious biosynthetic mechanisms of fungal dimeric NPs which are constructed by collaboration of two separate BGCs.