bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation and Characterization of Plasma-Derived Fibrin Hydrogels Modified by Alginate di-Aldehyde
Authors: Sanz-Horta Raúl , Matesanz Ana , Jorcano José Luis , Velasco Diego , Acedo Pablo , Gallardo Alberto , Reinecke Helmut , Elvira Carlos
Published: April 2022

Fibrin hydrogels are one of the most popular scaffolds used in tissue engineering due to their excellent biological properties. Special attention should be paid to the use of human plasma-derived fibrin hydrogels as a 3D scaffold in the production of autologous skin grafts, skeletal muscle regeneration and bone tissue repair. However, mechanical weakness and rapid degradation, which causes plasma-derived fibrin matrices to shrink significantly, prompted us to improve their stability. In our study, plasma-derived fibrin was chemically bonded to oxidized alginate (alginate di-aldehyde, ADA) at 10%, 20%, 50% and 80% oxidation, by Schiff base formation, to produce natural hydrogels for tissue engineering applications. First, gelling time studies showed that the degree of ADA oxidation inhibits fibrin polymerization, which we associate with fiber increment and decreased fiber density; moreover, the storage modulus increased when increasing the final volume of CaCl2 (1% w/v) from 80 µL to 200 µL per milliliter of hydrogel. The contraction was similar in matrices with and without human primary fibroblasts (hFBs). In addition, proliferation studies with encapsulated hFBs showed an increment in cell viability in hydrogels with ADA at 10% oxidation at days 1 and 3 with 80 µL of CaCl2; by increasing this compound (CaCl2), the proliferation does not significantly increase until day 7. In the presence of 10% alginate oxidation, the proliferation results are similar to the control, in contrast to the sample with 20% oxidation whose proliferation decreases. Finally, the viability studies showed that the hFB morphology was maintained regardless of the degree of oxidation used; however, the quantity of CaCl2 influences the spread of the hFBs.
A New Hypothetical Concept in Metabolic Understanding of Cardiac Fibrosis: Glycolysis Combined with TGF-β and KLF5 Signaling
Authors: Methatham Thanachai , Nagai Ryozo , Aizawa Kenichi
Published: April 2022

The accumulation of fibrosis in cardiac tissues is one of the leading causes of heart failure. The principal cellular effectors in cardiac fibrosis are activated fibroblasts and myofibroblasts, which serve as the primary source of matrix proteins. TGF-β signaling pathways play a prominent role in cardiac fibrosis. The control of TGF-β by KLF5 in cardiac fibrosis has been demonstrated for modulating cardiovascular remodeling. Since the expression of KLF5 is reduced, the accumulation of fibrosis diminishes. Because the molecular mechanism of fibrosis is still being explored, there are currently few options for effectively reducing or reversing it. Studying metabolic alterations is considered an essential process that supports the explanation of fibrosis in a variety of organs and especially the glycolysis alteration in the heart. However, the interplay among the main factors involved in fibrosis pathogenesis, namely TGF-β, KLF5, and the metabolic process in glycolysis, is still indistinct. In this review, we explain what we know about cardiac fibroblasts and how they could help with heart repair. Moreover, we hypothesize and summarize the knowledge trend on the molecular mechanism of TGF-β, KLF5, the role of the glycolysis pathway in fibrosis, and present the future therapy of cardiac fibrosis. These studies may target therapies that could become important strategies for fibrosis reduction in the future.
YY2 Promotes Osteoblast Differentiation by Upregulating Osterix Transcriptional Activity
Authors: Piao Meiyu , Lee Sung Ho , Kim Myeong Ji , Kim Hyung Sik , Lee Kwang Youl
Published: April 2022

Yin Yang 2 (YY2) is a paralog of YY1, a well-known multifunctional transcription factor containing a C-terminal zinc finger domain. Although the role of YY1 in various biological processes, such as the cell cycle, cell differentiation and tissue development, is well established, the function of YY2 has not been fully determined. In this study, we investigated the functional role of YY2 during osteoblast differentiation. YY2 overexpression and knockdown increased and decreased osteoblast differentiation, respectively, in BMP4-induced C2C12 cells. Mechanistically, YY2 overexpression increased the mRNA and protein levels of Osterix (Osx), whereas YY2 knockdown had the opposite effect. To investigate whether YY2 regulates Osx transcription, the effect of YY2 overexpression and knockdown on Osx promoter activity was evaluated. YY2 overexpression significantly increased Osx promoter activity in a dose-dependent manner, whereas YY2 knockdown had the opposite effect. Furthermore, vectors containing deletion and point mutations were constructed to specify the regulation site. Both the Y1 and Y2 sites were responsible for YY2-mediated Osx promoter activation. These results indicate that YY2 is a positive regulator of osteoblast differentiation that functions by upregulating the promoter activity of Osx, a representative osteogenic transcription factor in C2C12 cells.
PPAR-Targeted Therapies in the Treatment of Non-Alcoholic Fatty Liver Disease in Diabetic Patients
Authors: Lange Naomi F. , Graf Vanessa , Caussy Cyrielle , Dufour Jean-François
Published: April 2022

Peroxisome proliferator-activated receptors (PPAR), ligand-activated transcription factors of the nuclear hormone receptor superfamily, have been identified as key metabolic regulators in the liver, skeletal muscle, and adipose tissue, among others. As a leading cause of liver disease worldwide, non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) cause a significant burden worldwide and therapeutic strategies are needed. This review provides an overview of the evidence on PPAR-targeted treatment of NAFLD and NASH in individuals with type 2 diabetes mellitus. We considered current evidence from clinical trials and observational studies as well as the impact of treatment on comorbid metabolic conditions such as obesity, dyslipidemia, and cardiovascular disease. Future areas of research, such as possible sexually dimorphic effects of PPAR-targeted therapies, are briefly reviewed.
Lignocellulosic Biomass Waste-Derived Cellulose Nanocrystals and Carbon Nanomaterials: A Review
Authors: Magagula Lindokuhle Precious , Masemola Clinton Michael , Ballim Muhammed As’ad , Tetana Zikhona Nobuntu , Moloto Nosipho , Linganiso Ella Cebisa
Published: April 2022

Rapid population and economic growth, excessive use of fossil fuels, and climate change have contributed to a serious turn towards environmental management and sustainability. The agricultural sector is a big contributor to (lignocellulosic) waste, which accumulates in landfills and ultimately gets burned, polluting the environment. In response to the current climate-change crisis, policymakers and researchers are, respectively, encouraging and seeking ways of creating value-added products from generated waste. Recently, agricultural waste has been regularly appearing in articles communicating the production of a range of carbon and polymeric materials worldwide. The extraction of cellulose nanocrystals (CNCs) and carbon quantum dots (CQDs) from biomass waste partially occupies some of the waste-recycling and management space. Further, the new materials generated from this waste promise to be effective and competitive in emerging markets. This short review summarizes recent work in the area of CNCs and CQDs synthesised from biomass waste. Synthesis methods, properties, and prospective application of these materials are summarized. Current challenges and the benefits of using biomass waste are also discussed.
Root Exposure to 5-Aminolevulinic Acid (ALA) Affects Leaf Element Accumulation, Isoprene Emission, Phytohormonal Balance, and Photosynthesis of Salt-Stressed Arundo donax
Authors: Brilli Federico , Pignattelli Sara , Baraldi Rita , Neri Luisa , Pollastri Susanna , Gonnelli Cristina , Giovannelli Alessio , Loreto Francesco , Cocozza Claudia
Published: April 2022

Arundo donax has been recognized as a promising crop for biomass production on marginal lands due to its superior productivity and stress tolerance. However, salt stress negatively impacts A. donax growth and photosynthesis. In this study, we tested whether the tolerance of A. donax to salinity stress can be enhanced by the addition of 5-aminolevulinic acid (ALA), a known promoter of plant growth and abiotic stress tolerance. Our results indicated that root exposure to ALA increased the ALA levels in leaves along the A. donax plant profile. ALA enhanced Na+ accumulation in the roots of salt-stressed plants and, at the same time, lowered Na+ concentration in leaves, while a reduced callose amount was found in the root tissue. ALA also improved the photosynthetic performance of salt-stressed apical leaves by stimulating stomatal opening and preventing an increase in the ratio between abscisic acid (ABA) and indol-3-acetic acid (IAA), without affecting leaf methanol emission and plant growth. Supply of ALA to the roots reduced isoprene fluxes from leaves of non-stressed plants, while it sustained isoprene fluxes along the profile of salt-stressed A. donax. Thus, ALA likely interacted with the methylerythritol 4-phosphate (MEP) pathway and modulate the synthesis of either ABA or isoprene under stressful conditions. Overall, our study highlights the effectiveness of ALA supply through soil fertirrigation in preserving the young apical developing leaves from the detrimental effects of salt stress, thus helping of A. donax to cope with salinity and favoring the recovery of the whole plant once the stress is removed.
Adenylate Kinase Isozyme 3 Regulates Mitochondrial Energy Metabolism and Knockout Alters HeLa Cell Metabolism
Authors: Fujisawa Koichi , Wakazaki Maina , Matsuzaki Aya , Matsumoto Toshihiko , Yamamoto Naoki , Noma Takafumi , Takami Taro
Published: April 2022

The balance between oxidative phosphorylation and glycolysis is important for cancer cell growth and survival, and changes in energy metabolism are an emerging therapeutic target. Adenylate kinase (AK) regulates adenine nucleotide metabolism, maintaining intracellular nucleotide metabolic homeostasis. In this study, we focused on AK3, the isozyme localized in the mitochondrial matrix that reversibly mediates the following reaction: Mg2+ GTP + AMP ⇌ Mg2+ GDP + ADP. Additionally, we analyzed AK3-knockout (KO) HeLa cells, which showed reduced proliferation and were detected at an increased number in the G1 phase. A metabolomic analysis showed decreased ATP; increased glycolytic metabolites such as glucose 6 phosphate (G6P), fructose 6 phosphate (F6P), and phosphoenolpyruvate (PEP); and decreased levels of tricarboxylic acid (TCA) cycle metabolites in AK3KO cells. An intracellular ATP evaluation of AK3KO HeLa cells transfected with ATeam plasmid, an ATP sensor, showed decreased whole cell levels. Levels of mitochondrial DNA (mtDNA), a complementary response to mitochondrial failure, were increased in AK3KO HeLa cells. Oxidative stress levels increased with changes in gene expression, evidenced as an increase in related enzymes such as superoxide dismutase 2 (SOD2) and SOD3. Phosphoenolpyruvate carboxykinase 2 (PCK2) expression and PEP levels increased, whereas PCK2 inhibition affected AK3KO HeLa cells more than wild-type (WT) cells. Therefore, we concluded that increased PCK2 expression may be complementary to increased GDP, which was found to be deficient through AK3KO. This study demonstrated the importance of AK3 in mitochondrial matrix energy metabolism.
A New Human Platelet Lysate for Mesenchymal Stem Cell Production Compliant with Good Manufacturing Practice Conditions Preserves the Chemical Characteristics and Biological Activity of Lyo-Secretome Isolated by Ultrafiltration
Authors: Mareschi Katia , Banche Niclot Alessia Giovanna Santa , Marini Elena , Bari Elia , Labanca Luciana , Lucania Graziella , Ferrero Ivana , Perteghella Sara , Torre Maria Luisa , Fagioli Franca
Published: April 2022

Recently, we proposed a Good Manufacturing Practice (GMP)-compliant production process for freeze-dried mesenchymal stem cell (MSC)-secretome (lyo-secretome): after serum starvation, the cell supernatant was collected, and the secretome was concentrated by ultrafiltration and freeze-dried, obtaining a standardized ready-to-use and stable powder. In this work, we modified the type of human platelet lysate (HPL) used as an MSC culture supplement during the lyo-secretome production process: the aim was to verify whether this change had an impact on product quality and also whether this new procedure could be validated according to GMP, proving the process robustness. MSCs were cultured with two HPLs: the standard previously validated one (HPL-E) and the new one (HPL-S). From the same pool of platelets, two batches of HPL were obtained: HPL-E (by repeated freezing and thawing cycles) and HPL-S (by adding Ca-gluconate to form a clot and its subsequent mechanical wringing). Bone marrow MSCs from three donors were separately cultured with the two HPLs until the third passage and then employed to produce lyo-secretome. The following indicators were selected to evaluate the process performance: (i) the lyo-secretome quantitative composition (in lipids and proteins), (ii) the EVs size distribution, and (iii) anti-elastase and (iv) immunomodulant activity as potency tests. The new HPL supplementation for MSCs culture induced only a few minimal changes in protein/lipid content and EVs size distribution; despite this, it did not significantly influence biological activity. The donor intrinsic MSCs variability in secretome secretion instead strongly affected the quality of the finished product and could be mitigated by concentrating the final product to reach a determined protein (and lipid) concentration. In conclusion, the modification of the type of HPL in the MSCs culture during lyo-secretome production induces only minimal changes in the composition but not in the potency, and therefore, the new procedure can be validated according to GMP.
Zebrafish as a Model for Neurological Disorders
Authors: Soussi-Yanicostas Nadia
Published: April 2022

Over the past two decades, the simplicity and the versatility of the zebrafish (Danio rerio) have helped make it one of the main animal models used to address an increasing number of issues, from fundamental research to clinical investigations, drug discovery [...]
Enhancement in Electrical and Thermal Properties of LDPE with Al2O3 and h-BN as Nanofiller
Authors: He Lijuan , Ye Zhanzheng , Zeng Junji , Yang Xiong , Li Dawei , Yang Xiangyu , Chen Yu , Huang Yuewu
Published: April 2022

Low-density polyethylene (LDPE) has excellent dielectric properties and is extensively used in electrical equipment. Hexagonal boron nitride (h-BN) is similar to a graphite-layered structure, and alumina fiber (Al2O3) has high-temperature resistance and a strong performance. Herein, we prepared Al2O3-h-BN/LDPE nanocomposites by using LDPE as the matrix material and h-BN and Al2O3 as the fillers. The influence of different doping contents and the mass ratio of Al2O3 and h-BN (1:1) to LDPE on the electrical properties and thermal conductivity of the nanocomposites was examined. The results showed that the suppression effect on space charge was the most obvious and average. The charge density was the lowest and had the minimum decay rate when the doping content was 2%. The breakdown strength of the film reached the maximum value of 340.1 kV/mm, which was 12.3% higher than that of the pure LDPE (302.8 kV/mm). The thermal diffusivity of the composite sample was also higher than that of the single h-BN-doped sample when the content of h-BN and Al2O3 was 7%. The thermal conductivity was 59.3% higher than that of the pure LDPE sample and 20% higher than that of h-BN/LDPE.
Effect of Long-Term Aging on the Microstructural Evolution in a P91 Steel
Authors: Zhao Hongchang , Wang Zixi , Han Xi , Wang Mingjia
Published: April 2022

The precipitation and growth mechanism of the Laves phase and the coarsening behaviors of Laves phase, M23C6 and MX carbonitrides have been emphatically investigated in P91 steel at 625 °C under different aging conditions. After long-term aging at 625 °C (>1500 h), it was observed that the Laves phase grew rapidly in the region near the M23C6 carbide once precipitated, and further gradually completed the engulfment process until the M23C6 carbide particles disappeared. Furthermore, a new crystallographic orientation relationship between M23C6 carbides and Laves phase has been observed at 625 °C for 5000 h, which is {0001}Laves∥{111}M23C6, <112¯1>Laves∥ <011>M23C6. The coarsening behaviors of Laves phase, M23C6 carbides and MX carbonitrides have been emphatically investigated, conforming to the existing ripening model of multicomponent alloys. The coarsening rates for the Laves phase, M23C6 and MX have values of ~32.2 (≥5000 h), 5.3 and 0.6 nm/h1/3, respectively.
A Review of the Effects of Raw Material Compositions and Steam Curing Regimes on the Performance and Microstructure of Precast Concrete
Authors: Zhou Yucheng , Zhan Yijian , Zhu Mintao , Wang Shengyi , Liu Juanhong , Ning Ning
Published: April 2022

In this paper, the effects of steam curing conditions on concrete properties and microstructural characteristics are reviewed, and technical approaches such as appropriate raw material compositions and curing regimes are explored. Moreover, the environmental effects of precast concrete are evaluated. The main conclusion is that steam curing can improve the early strength of concrete, but thermal damage, shrinkage cracking, delayed ettringite formation (DEF), and other factors cause the later strength to increase more slowly or even deteriorate. Accordingly, it is necessary to undertake methods for improvement: (1) Adopt a lot of high-activity mineral admixture + a few low-activity mineral admixture combinations to ensure that the early strength of concrete meets the standard while allowing the subsequent development of concrete hydration to ensure durability. (2) Control the precuring time and temperature gradient of the concrete to allow the initial structure of the concrete to form. (3) Use effective secondary curing, such as soaking in an aqueous solution of limestone, in addition to standard curing to further improve the compactness of concrete. Moreover, the replacement of cement with less than 30% mineral admixtures in steam-cured concrete should be promoted to alleviate the environmental hazards caused by excessive CO2 emissions.
Cytotoxic Alkylynols of the Sponge Cribrochalina vasculum: Structure, Synthetic Analogs and SAR Studies
Authors: Kovalerchik Dimitry , Zovko Ana , Hååg Petra , Sierakowiak Adam , Viktorsson Kristina , Lewensohn Rolf , Ilan Micha , Carmeli Shmuel
Published: April 2022

A series of twenty-three linear and branched chain mono acetylene lipids were isolated from the Caribbean Sea sponge Cribrochalina vasculum. Seventeen of the compounds, 1–17, are new, while six, 18–23, were previously characterized from the same sponge. Some of the new acetylene-3-hydroxy alkanes 1, 6, 7, 8, 10 were tested for selective cytotoxicity in non-small cell lung carcinoma (NSCLC) cells over WI-38 normal diploid lung fibroblasts. Compound 7, presented clear tumor selective activity while, 1 and 8, showed selectivity at lower doses and 6 and 10, were not active towards NSCLC cells at all. The earlier reported selective cytotoxicity of some acetylene-3-hydroxy alkanes (scal-18 and 23), in NSCLC cells and/or other tumor cell types were also confirmed for 19, 20 and 22. To further study the structure activity relationships (SAR) of this group of compounds, we synthesized several derivatives of acetylene-3-hydroxy alkanes, rac-18, scal-S-18, R-18, rac-27, rac-32, R-32, S-32, rac-33, rac-41, rac-42, rac-43, rac-45, rac-48 and rac-49, along with other 3-substituted derivatives, rac-35, rac-36, rac-37, rac-38, rac-39 and rac-40, and assessed their cytotoxic activity against NSCLC cells and diploid fibroblasts. SAR studies revealed that the alcohol moiety at position 3 and its absolute R configuration both were essential for the tumor cell line selective activity while for its cytotoxic magnitude the alkyl chain length and branching were of less significance.
Reconfigurable Metalens with Phase-Change Switching between Beam Acceleration and Rotation for 3D Depth Imaging
Authors: Ma Zhiyuan , Dong Siyu , Dun Xiong , Wei Zeyong , Wang Zhanshan , Cheng Xinbin
Published: April 2022

Depth imaging is very important for many emerging technologies, such as artificial intelligence, driverless vehicles and facial recognition. However, all these applications demand compact and low-power systems that are beyond the capabilities of most state-of-art depth cameras. Recently, metasurface-based depth imaging that exploits point spread function (PSF) engineering has been demonstrated to be miniaturized and single shot without requiring active illumination or multiple viewpoint exposures. A pair of spatially adjacent metalenses with an extended depth-of-field (EDOF) PSF and a depth-sensitive double-helix PSF (DH-PSF) were used, using the former metalens to reconstruct clear images of each depth and the latter to accurately estimate depth. However, due to these two metalenses being non-coaxial, parallax in capturing scenes is inevitable, which would limit the depth precision and field of view. In this work, a bifunctional reconfigurable metalens for 3D depth imaging was proposed by dynamically switching between EDOF-PSF and DH-PSF. Specifically, a polarization-independent metalens working at 1550 nm with a compact 1 mm2 aperture was realized, which can generate a focused accelerating beam and a focused rotating beam at the phase transition of crystalline and amorphous Ge2Sb2Te5 (GST), respectively. Combined with the deconvolution algorithm, we demonstrated the good capabilities of scene reconstruction and depth imaging using a theoretical simulation and achieved a depth measurement error of only 3.42%.
Latest Advancements in Micro Nano Molding Technologies—Process Developments and Optimization, Materials, Applications, Key Enabling Technologies
Authors: Tosello Guido
Published: April 2022

Micro and nano molding technologies are continuously being developed due to enduring trends such as increasing miniaturization and the higher functional integration of products, devices and systems [...]
Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor
Authors: Yamagishi Shunsei , Jing Lei
Published: April 2022

In this paper, we researched Pedestrian Dead Reckoning (PDR) with one foot-mounted IMU sensor. The issues of PDR are magnetism noise and accumulated error due to the noise included in acceleration and gyro data. Two methods are proposed in this paper. First is the gait-phase-estimation method with pitch angle for the Zero Velocity Update algorithm. Second is a method for avoiding accumulated errors by updating the roll and pitch angles with acceleration. The two experiments were conducted to examine the error of gait-phase estimation and distance estimations. The relative error of distance was about 7.40% in the case of walking straight and about 12.27% in the case of a shifting travel direction.
Development of Functional Composite Cu(II)-Polyoxometalate/PLA with Antimicrobial Properties
Authors: Duvanova Ella , Krasnou Illia , Krumme Andres , Mikli Valdek , Radio Serhii , Rozantsev Georgiy M. , Karpichev Yevgen
Published: April 2022

Novel composite self-disinfecting films of polylactic acid (PLA) filled with nanosized particles of double sodium–copper(II) paratungstate B Na2Cu3(CuOH)2[W12O40(OH)2]·32H2O (POM) were developed. The solvent casting (POM/PLA film) and solvent-free melt extrusion methods (Extr. POM/PLA film) were applied for film preparation. The copper (II) ion release to water from both types of the films after 10 days at different temperatures demonstrated that the PLA matrix acts as a diffusion barrier, and the resulting concentration of released copper in water at room temperature remained low, at 0.79% for POM/PLA film and 0.51% for Extr. POM/PLA film. The POM-containing films reveals a significant inhibitory effect against E. coli ATCC 25922 in the agar diffusion test. The numbers of CFUs in washes of the films after incubation for 24 h were found to be 3.6 log CFU mL–1 (POM/PLA film) and 4.1 log CFU mL–1 (Extr. POM/PLA film). The films combine the antibacterial properties of POM and a bio-based polymer matrix, which makes them a prospective coating material for applications in hospital indoor environments. Excellent thermal stability of POM gives a technological advantage for industrial manufacturing to allow the processing of novel composite material in the solvent free (molten) state.
Composition of Fatty Acids in Bone Marrow of Red Deer from Various Ecosystems and Different Categories
Authors: Steiner-Bogdaszewska Żaneta , Tajchman Katarzyna , Domaradzki Piotr , Florek Mariusz
Published: April 2022

In this study, the influence of the living conditions of red deer (Cervus elaphus) fawns (wild vs. farmed) and effect of the category of free-living animals (fawns vs. does) on the fatty acid (FA) profile of the leg bone marrow was assessed. The composition of FAs in the deer bone marrow was determined by the gas chromatography method. In all groups, oleic acid (18:1 c9) was the most abundant in deer bone marrow and comprised of approximately 37% of total FAs. The bone marrow of young wild deer was characterized by a significantly (p < 0.001) higher fat content and saturated FAs proportion, while farmed fawns contained more moisture (p < 0.005) and fat-free dry matter (p < 0.001), as well as more monounsaturated FAs cis branched-chain FAs and monounsaturated FAs trans (p < 0.001). Although no significant (p > 0.05) differences were found between fawns, in terms of partial sums of PUFA, a significantly (p < 0.001) higher level of the sum of n-3 and n-6 FAs and more favorable n-6/n-3 ratio in the bone marrow of wild fawns were determined. In general, the legs of wild fawns were better prepared for wintering than farmed ones. In turn, comparing the category-related FAs composition in the bone marrow of free-living animals, a more favorable profile was observed in the adult (does) than in the young (fawns) animals, as the bone marrow of the wild does was characterized by significantly (p < 0.001) lower percentages of saturated FAs and a higher percentage of monounsaturated FAs cis.
Identification and Characterization of a Novel Endo-β-1,4-Xylanase from Streptomyces sp. T7 and Its Application in Xylo-Oligosaccharide Production
Authors: Li Yumei , Zhang Xinxin , Lu Chunwen , Lu Peng , Yin Chongxu , Ye Zhengmao , Huang Zhaosong
Published: April 2022

A xylanase-producing strain, identified as Streptomyces sp. T7, was isolated from soil by our lab. The endo-β-1,4-xylanase (xynST7) gene was found in the genome sequence of strain T7, which was cloned and expressed in Escherichia coli. XynST7 belonged to the glycoside hydrolase family 10, with a molecular mass of approximately 47 kDa. The optimum pH and temperature of XynST7 were pH 6.0 and 60 °C, respectively, and it showed wide pH and temperature adaptability and stability, retaining more than half of its enzyme activity between pH 5.0 and 11.0 below 80 °C. XynST7 showed only endo-β-1,4-xylanase activity without cellulase- or β-xylosidase activity, and it showed maximal hydrolysis for corncob xylan in all the test substrates. Then, XynST7 was used for the production of xylo-oligosaccharides (XOSs) by hydrolyzing xylan extracted from raw corncobs. The maximum yield of the XOS was 8.61 ± 0.13 mg/mL using 15 U/mL of XynST7 and 1.5% corncob xylan after 10 h of incubation at 60 °C. The resulting hydrolysate products mainly consisted of xylobiose and xylotriose. These data indicated that XynST7 might by a promising tool for various industrial applications.
Cannabinoid CB1 Receptor Involvement in the Actions of CBD on Anxiety and Coping Behaviors in Mice
Authors: Austrich-Olivares Amaya , García-Gutiérrez María Salud , Illescas Lucía , Gasparyan Ani , Manzanares Jorge
Published: April 2022

The anxiolytic and antidepressant properties of cannabidiol (CBD) have been evaluated in several studies. However, the molecular mechanisms involved in these actions remain unclear. A total of 130 male mice were used. CBD’s ability to modulate emotional disturbances (anxiety and depressive-like behaviors) was evaluated at different doses in wild-type (CD1; 10, 20 and 30 mg/kg; i.p.) and knockout (CB1KO, CB2KO; GPR55KO; 20 mg/kg) mice. Moreover, CBD effects (20 mg/kg; i.p.) were evaluated in mice previously treated with the CB1r-antagonist SR141716A (2mg/kg; i.p.). Relative gene expression analyses of Cnr1 and Cnr2, Gpr55 and GABA(A)α2 and γ2 receptor subunits were performed in the amygdala (AMY) and hippocampus (HIPP) of CD1 mice. CBD (10 and 20 mg/kg) showed anxiolytic and antidepressant actions in CD1 mice, being more effective at 20 mg/kg. Its administration did not induce anxiolytic actions in CB1KO mice, contrary to CB2KO and GPR55KO. In all of them, the lack of cannabinoid receptors did not modify the antidepressant activity of CBD. Interestingly, the administration of the CB1r antagonist SR141716A blocked the anxiolytic-like activity of CBD. Real-time PCR studies revealed a significant reduction in Cnr1 and GABA(A)α2 and γ2 gene expression in the HIPP and AMY of CD1 mice treated with CBD. Opposite changes were observed in the Cnr2. Indeed, Gpr55 was increased in the AMY and reduced in the HIPP. CB1r appears to play a relevant role in modulating the anxiolytic actions of CBD. Moreover, this study revealed that CBD also modified the gene expression of GABA(A) subunits α2 and γ2 and CB1r, CB2r and GPR55, in a dose- and brain-region-dependent manner, supporting a multimodal mechanism of action for CBD.
Adaptive Leader-Following Consensus Tracking Control of Multiple UAVs Subject to Deception Attacks
Authors: Mu Xiufeng , Yan Shen
Published: April 2022

This article is concerned with the problem of leader-following consensus tracking control for multi-unmanned aerial vehicle (UAV) systems under deception attacks and actuator saturation. While guaranteeing the expected control performance, a novel adaptive event-triggered scheme (AETS) is developed to reduce the frequency of data transmission among UAVs and reduce the release of redundant data, where the adaptive threshold can be adjusted online according to the dynamic error instead of giving a default value. With the help of a new Lyapunov function, sufficient conditions and security criteria are developed to ensure that all following UAVs could reach secure consensus asymptotically with a leader UAV. Lastly, an illustrative example is presented to validate the effectiveness of the designed method.
The Role of Environmental Water and Reedbed Condition on the Response of Phragmites australis Reedbeds to Flooding
Authors: Higgisson William , Cobb Adrian , Tschierschke Alica , Dyer Fiona
Published: April 2022

Globally, wetlands have experienced significant declines in area and condition. Reedbeds are a key attribute of many wetlands and are typically composed of Phragmites australis (common reed), a globally distributed emergent aquatic perennial grass. Environmental water is increasingly used to support functioning river and floodplain ecosystems, including reedbeds, where maintaining wetland vegetation condition is a common objective. Drone-based remote sensing allows for the consistent collection of high-quality data in locations such as wetlands where access is limited. We used unoccupied aerial vehicles (UAVs) and convolutional neural networks (CNNs) to estimate the cover of Phragmites australis and examine the role of reedbed condition and prior environmental watering in the response of reedbeds to flooding. Data were collected from a large inland reedbed in semi-arid western New South Wales, Australia between October 2019 and March 2021 using UAVs and processed using CNNs. Prior to the flood event, sites that had received environmental water had a significantly greater cover of Phragmites australis. The sites that were not managed with environmental water had very low cover (<1%) of reeds prior to the flood event and transitioned from a Critical condition to a Poor or Medium condition following flooding. Using UAVs and CNNs we demonstrated the role environmental water plays in filling the gaps between large flood events and maintaining the condition and resilience of reedbeds.
Manifestation of Spiral Structures under the Action of Upper Ocean Currents
Authors: Shomina Olga , Danilicheva Olga , Tarasova Tatiana , Kapustin Ivan
Published: April 2022

The traditional approach to the interpretation of spirals observed in radar, optical and radiometric panoramas of a sea surface is based on equating the outer spiral scale with the scale of a manifesting eddy, but the validity of this approach has been poorly studied. Using the maximum cross-correlation (MCC) method for multispectral satellite images containing a spiral structure, we found a significant discrepancy between the structures of horizontal velocity fields and the geometrical characteristics of spiral structures in each band. Each velocity field demonstrated a pair of points of zero velocity with a km-scale difference between their positions in different bands. In order to describe the observed features, an analytical description of the upper-ocean current composed of a spiral eddy and of a homogeneous drift (related, in particular, to wind forcing) is proposed. This simple model states that the spiral characteristics and the position of the spiral center depend on a drift current even when the genuine characteristics of the marine eddy are fixed. The studied example shows that the diameter of an eddy core may significantly (2–3 times) differ from the outer scale of the spiral, which demonstrates the incorrectness of the traditional approach of spiral structures interpretation.
LLNet: A Fusion Classification Network for Land Localization in Real-World Scenarios
Authors: Chang Kun , Yan Li
Published: April 2022

Lane localization is one of the core tasks in an autonomous driving system. It receives the visual information collected by the camera and the lane marks and road edges information outputted from the perception module and gives lane index for the subsequent decision module. Traditional rule-based lane localization methods using navigation maps can only be effective in regular road scenarios and have poor generalization ability. High-Definition Map (HD map) was originally thought to solve the lane localization problem, but due to the regulations of the relevant departments, HD map is currently not allowed to be used in autonomous driving systems. In addition, many multi-sensor fusion methods have been proposed to solve the lane localization problem. However, due to the extremely strict safety requirements of autonomous driving systems, these well-designed solutions make it difficult to meet the requirements in terms of robustness, efficiency, and stability. To solve these problems, we innovatively define the lane localization task as a classification problem. First, to better utilize the perceptual information outputted from the perceptual model, we design an image-generating method that projects the perceptual information onto a new image and ensures that our model can learn the perceptual features wisely. Second, to better fuse the perceptual and visual information, we propose a fusion structure deep learning neural network named LLNet to address the lane localization problem in an end-to-end manner. Finally, to ensure the generalization ability, robustness, and stability of LLNet, we conduct extensive comparison experiments on a large-scale real-world dataset, with a total mileage of over 400 km. The experiments show that our approach remarkably outperforms the deep learning classification baselines. In the discussion part of this paper, we give a comprehensive and detailed elaboration for the effectiveness of various designs in our LLNet. To our knowledge, LLNet is the first lane localization method based entirely on deep learning. LLNet is added to the self-driving suite for a kind of mass production vehicle that will be available in the summer of 2022, with an expected sales volume more than 300,000.
A Fast Inference Vision Transformer for Automatic Pavement Image Classification and Its Visual Interpretation Method
Authors: Chen Yihan , Gu Xingyu , Liu Zhen , Liang Jia
Published: April 2022

Traditional automatic pavement distress detection methods using convolutional neural networks (CNNs) require a great deal of time and resources for computing and are poor in terms of interpretability. Therefore, inspired by the successful application of Transformer architecture in natural language processing (NLP) tasks, a novel Transformer method called LeViT was introduced for automatic asphalt pavement image classification. LeViT consists of convolutional layers, transformer stages where Multi-layer Perception (MLP) and multi-head self-attention blocks alternate using the residual connection, and two classifier heads. To conduct the proposed methods, three different sources of pavement image datasets and pre-trained weights based on ImageNet were attained. The performance of the proposed model was compared with six state-of-the-art (SOTA) deep learning models. All of them were trained based on transfer learning strategy. Compared to the tested SOTA methods, LeViT has less than 1/8 of the parameters of the original Vision Transformer (ViT) and 1/2 of ResNet and InceptionNet. Experimental results show that after training for 100 epochs with a 16 batch-size, the proposed method acquired 91.56% accuracy, 91.72% precision, 91.56% recall, and 91.45% F1-score in the Chinese asphalt pavement dataset and 99.17% accuracy, 99.19% precision, 99.17% recall, and 99.17% F1-score in the German asphalt pavement dataset, which is the best performance among all the tested SOTA models. Moreover, it shows superiority in inference speed (86 ms/step), which is approximately 25% of the original ViT method and 80% of some prevailing CNN-based models, including DenseNet, VGG, and ResNet. Overall, the proposed method can achieve competitive performance with fewer computation costs. In addition, a visualization method combining Grad-CAM and Attention Rollout was proposed to analyze the classification results and explore what has been learned in every MLP and attention block of LeViT, which improved the interpretability of the proposed pavement image classification model.
Short Range Pipe Guided Wave Testing Using SH0 Plane Wave Imaging for Improved Quantification Accuracy
Authors: Szlaszynski Filip , Lowe Michael J. S. , Huthwaite Peter
Published: April 2022

Detection and criticality assessment of defects appearing in inaccessible locations in pipelines pose a great challenge for many industries. Inspection methods which allow for remote defect detection and accurate characterisation are needed. Guided wave testing (GWT) is capable of screening large lengths of pipes from a single device position, however it provides very limited individual feature characterisation. This paper adapts Plane Wave Imaging (PWI) to pipe GWT to improve defect characterization for inspection in nearby locations such as a few metres from the transducers. PWI performance is evaluated using finite element (FE) and experimental studies, and it is compared to other popular synthetic focusing imaging techniques. The study is concerned with part-circumferential part-depth planar cracks. It is shown that PWI achieves superior resolution compared to the common source method (CSM) and comparable resolution to the total focusing method (TFM). The techniques involving plane wave acquisition (PWI and CSM) are found to substantially outperform methods based on full matrix capture (FMC) in terms of signal-to-noise ratio (SNR). Therefore, it is concluded that PWI which achieves good resolution and high SNR is a more attractive choice for pipe GWT, compared to other considered techniques. Subsequently, a novel PWI transduction setup is proposed, and it is shown to suppresses the transmission of unwanted S0 mode, which further improves SNR of PWI.
Contrastive Learning for Image Registration in Visual Teach and Repeat Navigation
Authors: Rozsypálek Zdeněk , Broughton George , Linder Pavel , Rouček Tomáš , Blaha Jan , Mentzl Leonard , Kusumam Keerthy , Krajník Tomáš
Published: April 2022

Visual teach and repeat navigation (VT&R) is popular in robotics thanks to its simplicity and versatility. It enables mobile robots equipped with a camera to traverse learned paths without the need to create globally consistent metric maps. Although teach and repeat frameworks have been reported to be relatively robust to changing environments, they still struggle with day-to-night and seasonal changes. This paper aims to find the horizontal displacement between prerecorded and currently perceived images required to steer a robot towards the previously traversed path. We employ a fully convolutional neural network to obtain dense representations of the images that are robust to changes in the environment and variations in illumination. The proposed model achieves state-of-the-art performance on multiple datasets with seasonal and day/night variations. In addition, our experiments show that it is possible to use the model to generate additional training examples that can be used to further improve the original model’s robustness. We also conducted a real-world experiment on a mobile robot to demonstrate the suitability of our method for VT&R.
Sparse Damage Detection with Complex Group Lasso and Adaptive Complex Group Lasso
Authors: Dimopoulos Vasileios , Desmet Wim , Deckers Elke
Published: April 2022

Sparsity-based methods have recently come to the foreground of damage detection applications posing a robust and efficient alternative for traditional approaches. At the same time, low-frequency inspection is known to enable global monitoring with waves propagating over large distances. In this paper, a single sensor complex Group Lasso methodology for the problem of structural defect localization by means of compressive sensing and complex low-frequency response functions is presented. The complex Group Lasso methodology is evaluated on composite plates with induced scatterers. An adaptive setting of the methodology is also proposed to further enhance resolution. Results from both approaches are compared with a full-array, super-resolution MUSIC technique of the same signal model. Both algorithms are shown to demonstrate high and competitive performance.
Deep Reinforcement Learning-Based Resource Allocation for Satellite Internet of Things with Diverse QoS Guarantee
Authors: Tang Siqi , Pan Zhisong , Hu Guyu , Wu Yang , Li Yunbo
Published: April 2022

Large-scale terminals’ various QoS requirements are key challenges confronting the resource allocation of Satellite Internet of Things (S-IoT). This paper presents a deep reinforcement learning-based online channel allocation and power control algorithm in an S-IoT uplink scenario. The intelligent agent determines the transmission channel and power simultaneously based on contextual information. Furthermore, the weighted normalized reward concerning success rate, power efficiency, and QoS requirement is adopted to balance the performance between increasing resource efficiency and meeting QoS requirements. Finally, a practical deployment mechanism based on transfer learning is proposed to promote onboard training efficiency and to reduce computation consumption of the training process. The simulation demonstrates that the proposed method can balance the success rate and power efficiency with QoS requirement guaranteed. For S-IoT’s normal operation condition, the proposed method can improve the power efficiency by 60.91% and 144.44% compared with GA and DRL_RA, while its power efficiency is only 4.55% lower than that of DRL-EERA. In addition, this method can be transferred and deployed to a space environment by merely 100 onboard training steps.
Applications of Online UV-Vis Spectrophotometer for Drinking Water Quality Monitoring and Process Control: A Review
Authors: Shi Zhining , Chow Christopher W. K. , Fabris Rolando , Liu Jixue , Jin Bo
Published: April 2022

Water quality monitoring is an essential component of water quality management for water utilities for managing the drinking water supply. Online UV-Vis spectrophotometers are becoming popular choices for online water quality monitoring and process control, as they are reagent free, do not require sample pre-treatments and can provide continuous measurements. The advantages of the online UV-Vis sensors are that they can capture events and allow quicker responses to water quality changes compared to conventional water quality monitoring. This review summarizes the applications of online UV-Vis spectrophotometers for drinking water quality management in the last two decades. Water quality measurements can be performed directly using the built-in generic algorithms of the online UV-Vis instruments, including absorbance at 254 nm (UV254), colour, dissolved organic carbon (DOC), total organic carbon (TOC), turbidity and nitrate. To enhance the usability of this technique by providing a higher level of operations intelligence, the UV-Vis spectra combined with chemometrics approach offers simplicity, flexibility and applicability. The use of anomaly detection and an early warning was also discussed for drinking water quality monitoring at the source or in the distribution system. As most of the online UV-Vis instruments studies in the drinking water field were conducted at the laboratory- and pilot-scale, future work is needed for industrial-scale evaluation with ab appropriate validation methodology. Issues and potential solutions associated with online instruments for water quality monitoring have been provided. Current technique development outcomes indicate that future research and development work is needed for the integration of early warnings and real-time water treatment process control systems using the online UV-Vis spectrophotometers as part of the water quality management system.
A Real-Time Effectiveness Evaluation Method for Remote Sensing Satellite Clusters on Moving Targets
Authors: Li Zhi , Dong Yunfeng , Li Peiyun , Li Hongjue , Liew Yingjia
Published: April 2022

Recently, remote sensing satellites have become increasingly important in the Earth observation field as their temporal, spatial, and spectral resolutions have improved. Subsequently, the quantitative evaluation of remote sensing satellites has received considerable attention. The quantitative evaluation method is conventionally based on simulation, but it has a speed-accuracy trade-off. In this paper, a real-time evaluation model architecture for remote sensing satellite clusters is proposed. Firstly, a multi-physical field coupling simulation model of the satellite cluster to observe moving targets is established. Aside from considering the repercussions of on-board resource constraints, it also considers the consequences of the imaging’s uncertainty effects on observation results. Secondly, a moving target observation indicator system is developed, which reflects the satellite cluster’s actual effectiveness in orbit. Meanwhile, an indicator screening method using correlation analysis is proposed to improve the independence of the indicator system. Thirdly, a neural network is designed and trained for stakeholders to realize a rapid evaluation. Different network structures and parameters are comprehensively studied to determine the optimized neural network model. Finally, based on the experiments carried out, the proposed neural network evaluation model can generate real-time, high-quality evaluation results. Hence, the validity of our proposed approach is substantiated.