bluuebunny/crossref_metadata_2025 huggingface dataset:
Nocturnal Hemodialysis Leads to Improvement in Physical Performance in Comparison with Conventional Hemodialysis
Authors: Dam Manouk , Weijs Peter J. M. , van Ittersum Frans J. , Hoekstra Tiny , Douma Caroline E. , van Jaarsveld Brigit C.
Published: December 2022

End-stage kidney disease patients treated with conventional hemodialysis (CHD) are known to have impaired physical performance and protein-energy wasting (PEW). Nocturnal hemodialysis (NHD) was shown to improve clinical outcomes, but the evidence is limited on physical performance and PEW. We investigate whether NHD improves physical performance and PEW. This prospective, multicenter, non-randomized cohort study compared patients who changed from CHD (2–4 times/week 3–5 h) to NHD (2–3 times/week 7–8 h), with patients who continued CHD. The primary outcome was physical performance at 3, 6 and 12 months, assessed with the short physical performance battery (SPPB). Secondary outcomes were a 6-minute walk test (6MWT), physical activity monitor, handgrip muscle strength, KDQOL-SF physical component score (PCS) and LAPAQ physical activity questionnaire. PEW was assessed with a dietary record, dual-energy X-ray absorptiometry, bioelectrical impedance spectroscopy and subjective global assessment (SGA). Linear mixed models were used to analyze the differences between groups. This study included 33 patients on CHD and 32 who converted to NHD (mean age 55 ± 15.3). No significant difference was found in the SPPB after 1-year of NHD compared to CHD (+0.24, [95% confidence interval −0.51 to 0.99], p = 0.53). Scores of 6MWT, PCS and SGA improved (+54.3 [95%CI 7.78 to 100.8], p = 0.02; +5.61 [−0.51 to 10.7], p = 0.03; +0.71 [0.36 to 1.05], p < 0.001; resp.) in NHD patients, no changes were found in other parameters. We conclude that NHD patients did not experience an improved SPPB score compared to CHD patients; they did obtain an improved walking distance and self-reported PCS as well as SGA after 1-year of NHD, which might be related to the younger age of these patients.
Modulation of Oxidative Stress and Antioxidant Response by Different Polyphenol Supplements in Five-a-Side Football Players
Authors: Carrera-Quintanar Lucrecia , Funes Lorena , Herranz-López María , Vicente-Salar Néstor , Bonet-García Raul , Blasco-Peris Carles , Micol Vicente , Pons Antoni , Roche Enrique
Published: December 2022

Oxidative stress is associated with playing soccer. The objective of the present report was to study the influence of different polyphenolic antioxidant-rich beverages in five-a-side/futsal players. The study was performed with a no supplemented control group (CG) and two supplemented groups with an almond-based beverage (AB) and the same beverage fortified with Lippia citriodora extract (AB + LE). At day 22, participants played a friendly futsal game. Blood extractions were performed at the beginning of intervention (day 1), before and after match (day 22) to determine oxidative stress markers and antioxidant enzyme activities in plasma, neutrophils and peripheral blood mononuclear cells (PBMCs). Malondialdehyde increased significantly in controls after the match in neutrophils, PBMCs and plasma compared to pre-match. Protein carbonyls also increased after the match in plasma in CG. In addition, malondialdehyde levels in neutrophils were significantly lower in the supplemented groups compared to controls. Post-match samples showed significant increases in neutrophil antioxidant activities in CG. Supplemented groups displayed variable results regarding neutrophil antioxidant activities, with superoxide dismutase activity significantly lower than in controls. Finally, post-match myeloperoxidase activity increased significantly in controls compared to pre-match and supplemented groups. In conclusion, polyphenolic antioxidant and anti-inflammatory supplements could be instrumental for optimal recovery after high intensity futsal games.
Synergistic and Antibiofilm Effects of the Essential Oil from Croton conduplicatus (Euphorbiaceae) against Methicillin-Resistant Staphylococcus aureus
Authors: Oliveira Genil Dantas de , Rocha Wilma Raianny Vieira da , Rodrigues José Filipe Bacalhau , Alves Harley da Silva
Published: December 2022

Bacterial resistance refers to the ability of bacteria to resist the action of some antibiotics due to the development of adaptation and resistance mechanisms. It is a serious public health problem, especially for diseases caused by opportunistic bacteria. In this context, the search for new drugs, used alone or in combination, appears as an alternative for the treatment of microbial infections, and natural products, such as essential oils, are important in this process due to their structural diversity, which increases the probability for antimicrobial action. The objective of this study was to extract and identify the chemical components of the essential oil from Croton conduplicatus (EOCC), to evaluate the antimicrobial activity, to investigate the effect of the interaction between the EOCC and different antibiotics and to evaluate its antibiofilm potential. The EOCC was obtained by hydrodistillation. Based on chemical characterisation, 70 compounds were identified, with 1.8 cineole (13.15%), p-cymene (10.68%), caryophyllene (9.73%) and spathulenol (6.36%) being the major constituents. The minimum inhibitory concentration (MIC) values of EOCC were 256 and 512 µg mL−1 for methicillin-sensitive and -resistant Staphylococcus aureus strains (MSSA and MRSA), respectively. The combinations of EOCC with the antibiotics oxacillin and ampicillin were synergistic (OXA/EOCC and AMP/EOCC combined decreased the OXA MIC and AMP MIC to 0.5 and 0.25 for MSSA, respectively, and OXA/EOCC and AMP/EOCC combined decreased the OXA MIC and the AMP MIC to 1 and 0.5 for MRSA, respectively) and could modify the resistance profile of MSSA and MRSA strains. The results indicated that EOCC was also able to partially inhibit biofilm formation. Our study presents important information about the chemical composition of EOCC and its antimicrobial potential and provides a reference to determine the mechanisms of action of EOCC and its use in pharmaceutical formulations.
New Ferulic Acid and Amino Acid Derivatives with Increased Cosmeceutical and Pharmaceutical Potential
Authors: Janus Ewa , Pinheiro Luan Ramalho , Nowak Anna , Kucharska Edyta , Świątek Ewelina , Podolak Natalia , Perużyńska Magdalena , Piotrowska Katarzyna , Duchnik Wiktoria , Kucharski Łukasz , Klimowicz Adam
Published: December 2022

Ferulic acid (FA) has been widely used in the pharmaceutical and cosmetics industry due to its, inter alia, antioxidant, antiaging and anti-inflammatory effects This compound added to cosmetic preparations can protect skin because of its photoprotective activity. However, the usefulness of FA as a therapeutic agent is limited due to its low solubility and bioavailability. The paper presents the synthesis, identification, and physicochemical properties of new FA derivatives with propyl esters of three amino acids, glycine (GPr[FA]), L-leucine (LPr[FA]), and L-proline (PPr[FA]). The NMR and FTIR spectroscopy, DSC, and TG analysis were used as analytical methods. Moreover, water solubility of the new conjugates was compared with the parent acid. Both ferulic acid and its conjugates were introduced into hydrogel and emulsion, and the resulting formulations were evaluated for stability. Additionally, in vitro penetration of all studied compounds from both formulations and for comparative purposes using Franz diffusion cells was evaluated from the solution in 70% (v/v) ethanol. Finally, cytotoxicity against murine fibroblasts L929 was tested. All of the analyzed compounds permeated pig skin and accumulated in it. LPr[FA] and PPr[FA] were characterized by much better permeability compared to the parent ferulic acid. Additionally, it was shown that all the analyzed derivatives are characterized by high antioxidant activity and lack of cytotoxicity. Therefore, they can be considered as an interesting alternative to be applied in dermatologic and cosmetic preparations.
Storage Life Prediction of Rubber Products Based on Step Stress Accelerated Aging and Intelligent Algorithm
Authors: Guo Xiaohui , Yuan Xiaojing , Liu Guangyong , Hou Genliang , Zhang Ze
Published: December 2022

Compared with the constant stress accelerated aging test, the step stress accelerated aging test reduces the accelerated aging test time by increasing the aging temperature step by step to obtain the aging failure life of rubber in a shorter time, but its data processing method is not mature enough. In this paper, a simplified step is proposed to process the step stress accelerated aging data. The identification of the acceleration factor is transformed into an optimization problem to avoid the error accumulation problem caused by fitting the data at each temperature. Considering the non-Arrhenius phenomenon in the rubber aging process, a modified Arrhenius equation was used to extrapolate the acceleration factor at low temperatures to calculate the prediction curves for the degradation of polyurethane rubber properties at low temperatures. The life prediction results of the constant stress accelerated aging test and step stress accelerated aging test were compared, and the dispersion coefficient between the two results was between 0.9 and 1. The results obtained by the two methods were in good agreement, which proved the correctness and feasibility of the method used in this paper.
Modeling of Single-Process 3D-Printed Piezoelectric Sensors with Resistive Electrodes: The Low-Pass Filtering Effect
Authors: Košir Tilen , Slavič Janko
Published: December 2022

Three-dimensional printing by material extrusion enables the production of fully functional dynamic piezoelectric sensors in a single process. Because the complete product is finished without additional processes or assembly steps, single-process manufacturing opens up new possibilities in the field of smart dynamic structures. However, due to material limitations, the 3D-printed piezoelectric sensors contain electrodes with significantly higher electrical resistance than classical piezoelectric sensors. The continuous distribution of the capacitance of the piezoelectric layer and the resistance of the electrodes results in low-pass filtering of the collected charge. Consequently, the usable frequency range of 3D-printed piezoelectric sensors is limited not only by the structural properties but also by the electrical properties. This research introduces an analytical model for determining the usable frequency range of a 3D-printed piezoelectric sensor with resistive electrodes. The model was used to determine the low-pass cutoff frequency and thus the usable frequency range of the 3D-printed piezoelectric sensor. The low-pass electrical cutoff frequency of the 3D-printed piezoelectric sensor was also experimentally investigated and good agreement was found with the analytical model. Based on this research, it is possible to design the electrical and dynamic characteristics of 3D-printed piezoelectric sensors. This research opens new possibilities for the design of future intelligent dynamic systems 3D printed in a single process.
Data-Augmented Manifold Learning Thermography for Defect Detection and Evaluation of Polymer Composites
Authors: Liu Kaixin , Wang Fumin , He Yuxiang , Liu Yi , Yang Jianguo , Yao Yuan
Published: December 2022

Infrared thermography techniques with thermographic data analysis have been widely applied to non-destructive tests and evaluations of subsurface defects in practical composite materials. However, the performance of these methods is still restricted by limited informative images and difficulties in feature extraction caused by inhomogeneous backgrounds and noise. In this work, a novel generative manifold learning thermography (GMLT) is proposed for defect detection and the evaluation of composites. Specifically, the spectral normalized generative adversarial networks serve as an image augmentation strategy to learn the thermal image distribution, thereby generating virtual images to enrich the dataset. Subsequently, the manifold learning method is employed for the unsupervised dimensionality reduction in all images. Finally, the partial least squares regression is presented to extract the explicit mapping of manifold learning for defect visualization. Moreover, probability density maps and quantitative metrics are proposed to evaluate and explain the obtained defect detection performance. Experimental results on carbon fiber-reinforced polymers demonstrate the superiorities of GMLT, compared with other methods.
Effect of Tannin Furanic Polymer in Comparison to Its Mimosa Tannin Extract on the Growth of Bacteria and White-Rot Fungi
Authors: Eckardt Jonas , Tondi Gianluca , Fanchin Genny , Lach Alexander , Junker Robert R.
Published: December 2022

Tannins are well-known to protect plants from bacteria and fungi, but nothing is known about its effects on microorganisms once they are copolymerized. Therefore, a study was conducted to evaluate the effect of a tannin–furanic polymer in comparison with industrial mimosa tannin extract on the in vitro growth of two strains of bacteria, Bacillaceae and Pseudomanadaceae, and two white-rot fungi, Trametes versicolor and Agrocybe aegerita. Results have highlighted that the tannin polymer did not inhibit the growth of tested bacteria and even favored the growth of Bacillaceae without extra glucose. The growth of both fungi was enhanced by mimosa tannin and its polymer at low concentrations (<1%), while concentrations above 10% had a growth-inhibiting effect, which was slightly less strong for the polymer compared to the tannin against Trametes versicolor. These findings highlighted that tannin–furanic polymers can be tolerated by certain microorganisms at low concentration and that their inhibitory effect is similar or slightly lower than that of the pristine tannin extract.
Enhancing the Spun Yarn Properties by Controlling Fiber Stress Distribution in the Spinning Triangle with Rotary Heterogeneous Contact Surfaces
Authors: Liu Yingcun , Ge Can , Su Ziyi , Chen Ze , Gao Chong , Gong Haoran , Xu Weilin , Xu Duo , Liu Keshuai
Published: December 2022

Control of tension distribution in the spinning triangle region that can facilitate fiber motion and transfer is highly desirable for high quality yarn production. Here, the key mechanisms and a mechanical model of gradient regulation of fiber tension and motion with rotary heterogeneous contact surfaces were theoretically analyzed. The linear velocity gradient, effected on a fiber strand using rotary heterogeneous contact surfaces, could balance and stabilize the structure and stress distribution of spinning triangle area, which could capture exposed fiber to reduce hairiness formation and enhance the internal and external fiber transfer to strengthen the fiber utilization rate. Then, varied yarns spun without and with the rotary grooved and rotary heterogeneous contact surfaces were tested to compare the property improvement for verifying above-mentioned theory. The hairiness, irregularity, and tensity of the yarns spun with rotary heterogeneous contact surfaces spun yarns were significantly improved compared to other spun yarns, which effectively corresponded well to the theoretical analysis. Based on this spinning method, this effective, low energy-consuming, easy spinning apparatus can be used with varied fiber materials for high-quality yarn production.
The Potential of Visible Spectroscopy as a Tool for the In-Line Monitoring of Lignin Methylolation
Authors: Gonçalves Sofia , Martins Jorge , Paiva Nádia T. , Paiva Diana , Carvalho Luísa H. , Magalhães Fernão D.
Published: December 2022

Out of the 50 to 70 million tons of lignin that are produced annually, only 1 to 2% are used for value-added products. Currently, 90% of the total market of this compound corresponds to lignosulphonates (LS). The most successful industrial attempts to use lignin for wood adhesives rely on using it as a partial substitute in phenol–formaldehyde or urea–formaldehyde resins. However, lignin’s aromatic ring presents a low number of reactive sites. Several methods have been proposed to improve its reactivity, such as prior methylolation with formaldehyde. Off-line methods are commonly applied to monitor this reaction’s progress, but this introduces a significant delay in the analysis. This study proposes a new method for in-line monitoring of the methylolation reaction using visible spectroscopy. In order to monitor the reaction progress, principal component analysis was applied to the spectra, and the obtained scores were analyzed. When these results were plotted against those obtained by the off-line methods, a satisfactory regression was obtained at 50 °C (R2 = 0.97) and 60 °C (R2 = 0.98) for two different LS samples. Therefore, it was concluded that visible spectroscopy is a promising technique for studying lignin methylolation.
Multifunctional Nanoparticles as High-Efficient Targeted Hypericin System for Theranostic Melanoma
Authors: de Morais Flávia Amanda Pedroso , De Oliveira Ana Carolina Vieira , Balbinot Rodolfo Bento , Lazarin-Bidóia Danielle , Ueda-Nakamura Tânia , de Oliveira Silva Sueli , da Silva Souza Campanholi Katieli , da Silva Junior Ranulfo Combuca , Gonçalves Renato Sonchini , Caetano Wilker , Nakamura Celso Vataru
Published: December 2022

Biotin, spermine, and folic acid were covalently linked to the F127 copolymer to obtain a new drug delivery system designed for HY-loaded PDT treatment against B16F10 cells. Chemical structures and binders quantification were performed by spectroscopy and spectrophotometric techniques (1NMR, HABA/Avidin reagent, fluorescamine assay). Critical micelle concentration, critical micelle temperature, size, polydispersity, and zeta potential indicate the hydrophobicity of the binders can influence the physicochemical parameters. Spermine-modified micelles showed fewer changes in their physical and chemical parameters than the F127 micelles without modification. Furthermore, zeta potential measurements suggest an increase in the physical stability of these carrier systems. The phototherapeutic potential was demonstrated using hypericin-loaded formulation against B16F10 cells, which shows that the combination of the binders on F127 copolymer micelles enhances the photosensitizer uptake and potentializes the photodynamic activity.
Synthesis and Characterization of Polyethylene Glycol-Grafted Photoreactive Polyethylene Glycols for Antibiofouling Applications
Authors: Othman Mahmoud H. , Ito Yoshihiro , Akimoto Jun
Published: December 2022

Notably, antibiofouling is an important and predominant technique adopted to improve the surfaces of biomaterials. In this study, polyethylene glycol-grafted polyethylene glycols bearing azidophenyl groups were synthesized and immobilized on polystyrene surfaces via photoirradiation. The prepared polymers were found to be highly soluble in water, and photoimmobilization with fluorescent proteins was confirmed based on micropatterning using a photomask. These polymers suppressed nonspecific interactions between proteins and cells on the substrate. Considering that photoimmobilization can be adopted for the covalent bond modification of various surfaces, the developed water-soluble and highly antibiofouling polymers appear to be useful in biomaterial preparation.
Research on Pressure Control of an Electro-Hydraulic Servo System Based on Sliding-Mode Variable-Structure Direct Torque Control
Authors: Liu Rongsheng , Wang Zekai , Jia Pengshuo , Yan Guishan , Zhang Tiangui , Jia Chunyu , Chen Gexin
Published: December 2022

Taking a direct-drive volume control (DDVC) electro-hydraulic servo system as the research object and aiming at the problems of the servo motor torque fluctuation, high-precision system pressure control, and dynamic response of the system, based on traditional motor direct torque control (DTC), a motor direct torque control method based on a sliding-mode variable structure is proposed to control the system pressure. The motor torque loop is part of the inner control loop and has a rapid dynamic response speed, resulting in higher pressure control accuracy. A nonlinear mathematical model was established for the DDVC electro-hydraulic servo system. The switch meter hysteresis controller in the traditional DTC system was replaced with space vector pulse-width modulation technology. Then, the PID control module in space vector modulation technology was replaced with high-order sliding-mode variable-structure control. Through the coupling relationship between the electric machine and the constant-displacement pump, the pressure can be controlled with high precision using motor torque control. Finally, using the MATLAB/Simulink simulation platform and the DDVC electro-hydraulic servo system simulation model, the proposed theoretical approach to torque control was verified on the basis of simulations and experiments, and the performance with regard to pressure control in the hydraulic system was observed. The simulation and experimental results show that the designed torque control is able to effectively reduce the motor torque fluctuation and improve the dynamic response characteristics of the system. The system pressure control is superior to traditional pressure control methods based on speed regulation, and it has higher control accuracy and a better dynamic response.
ELISA Based Immunoreactivity Reduction of Soy Allergens through Thermal Processing
Authors: Ravindran Akshaya , Ramaswamy Hosahalli S.
Published: December 2022

Allergens are proteins and are, therefore, likely to be denatured when subjected to thermal treatment. Traditional cooking has so far been able to reduce allergen sensitivity by around 70–90%. This study was aimed at evaluating the effect of a broad range of thermal treatments on the reduction of soy immunoreactivity (IR) in a 5% slurry using a sandwich ELISA technique. Cooking at 100 °C (10–60 min) and different thermal processing conditions, such as in commercial sterilization (with a process lethality (Fo) between 3 and 5 min) and selected severe thermal processing conditions (Fo > 5 and up to 23 min) were used in the study to evaluate their influence on allergen IR. Based on an IR comparison with an internal soy allergen standard, the allergen concentration in the untreated soy sample was calculated to be equivalent to 333 mg/kg (ppm). Cooking conditions only reduced the IR sensitivity to about 10 mg/kg (~1.5 log reductions), while the thermal processing treatments lowered the allergen IR up to 23 × 10−3 mg/kg (or 23 ppb) (>4 log reductions). FTIR analysis indicated significant changes in protein structure resulting from the thermal processing treatments, with a higher degree of allergen reduction corresponding with a higher value of random coil percentages. The influence of process severity on color and rheological properties was, however, minimal.
Processing and Properties Analysis of Grain Foods
Authors: Li Yonghui , Wu Xiaorong
Published: December 2022

Foods from grains and grain-derived ingredients are among the most important energy and nutrient source for humans [...]
Fuel Cell Systems for Maritime: A Review of Research Development, Commercial Products, Applications, and Perspectives
Authors: Elkafas Ahmed G. , Rivarolo Massimo , Gadducci Eleonora , Magistri Loredana , Massardo Aristide F.
Published: December 2022

The ambitious targets set by the International Maritime Organization for reducing greenhouse gas emissions from shipping require radical actions by all relevant stakeholders. In this context, the interest in high efficiency and low emissions (even zero in the case of hydrogen) fuel cell technology for maritime applications has been rising during the last decade, pushing the research developed by academia and industries. This paper aims to present a comparative review of the fuel cell systems suitable for the maritime field, focusing on PEMFC and SOFC technologies. This choice is due to the spread of these fuel cell types concerning the other ones in the maritime field. The following issues are analyzed in detail: (i) the main characteristics of fuel cell systems; (ii) the available technology suppliers; (iii) international policies for fuel cells onboard ships; (iv) past and ongoing projects at the international level that aim to assess fuel cell applications in the maritime industry; (v) the possibility to apply fuel cell systems on different ship types. This review aims to be a reference and a guide to state both the limitations and the developing potential of fuel cell systems for different maritime applications.
Correlation Research between Asymmetry Coefficient of Gondola Car Body and Stress Distribution of Cross Bearer Weld
Authors: Liu Wenfei , Zhang Li , Bi Chen , Gao Zhixiong , Pu Xiongtao
Published: December 2022

In order to find out the root cause of cross bearer welds’ cracks in general-purpose gondola cars, the relationship between asymmetric structure and stress distribution is studied in this paper. Firstly, the concept of asymmetry coefficient and stress distribution cluster is proposed, and the asymmetric coefficients’ calculation methods of independent and dependent variables are given, respectively, in two-dimensional space. Secondly, according to the different positions of side column 1 and side column 2, 30 local models are established, the cross bearer weld stresses are extracted after finite element simulation, and the stress distribution clusters of cross bearer weld stresses are formed. Finally, the asymmetry coefficients of the side columns are calculated, and the correlation between the positions of the side columns and the weld stresses is studied using the methods of Pearson correlation coefficient and complex correlation coefficient. The results show that the correlation between the stress of cross bearer weld 2 and the positions of the side columns is much higher than that between the stress of cross bearer weld 1 and the positions of the side columns. Meanwhile, it shows that the method presented in this paper is feasible and effective for the analysis and research of asymmetric structures. These combined with the calculation method of the correlation coefficient.
Nonlinear Dynamic Process Monitoring Using Canonical Variate Kernel Analysis
Authors: Li Simin , Yang Shuang-hua , Cao Yi
Published: December 2022

Most industrial systems today are nonlinear and dynamic. Traditional fault detection techniques show their limits because they can hardly extract both nonlinear and dynamic features simultaneously. Canonical variate analysis (CVA) shows its excellent monitoring performance in fault detection for dynamic processes but is not applicable to nonlinear processes. Inspired by the CVA method, a novel nonlinear dynamic process monitoring method, namely, the “canonical variate kernel analysis” (CVKA), is proposed in this work. The way to extract nonlinear features is different from a traditional kernel canonical variate analysis (KCVA). In a sequential structure, the new approach firstly extracts the linear dynamic features from the data through the CVA method, followed by a kernel principal component analysis to extract nonlinear features from the CVA residual space. The new CVKA method is then applied to a TE process case study, proving the excellent performance of CVKA compared to other common approaches in dynamic nonlinear process monitoring for TE-like processes.
Novel Semisynthetic Betulinic Acid−Triazole Hybrids with In Vitro Antiproliferative Potential
Authors: Nistor Gabriela , Mioc Alexandra , Mioc Marius , Balan-Porcarasu Mihaela , Ghiulai Roxana , Racoviceanu Roxana , Avram Ștefana , Prodea Alexandra , Semenescu Alexandra , Milan Andreea , Dehelean Cristina , Șoica Codruța
Published: December 2022

Betulinic acid, BA, is a lupane derivative that has caught the interest of researchers due to the wide variety of pharmacological properties it exhibits towards tumor cells. Because of their prospective increased anti−proliferative efficacy and improved pharmacological profile, BA derivatives continue to be described in the scientific literature. The current work was conducted in order to determine the antiproliferative activity, under an in vitro environment of the newly developed 1,2,4−triazole derivatives of BA. The compounds and their reaction intermediates were tested on three cancer cell lines, namely RPMI−7951 human malignant melanoma, HT−29 colorectal adenocarcinoma, A549 lung carcinoma, and healthy cell line (HaCaT human keratinocytes). BA−triazole derivatives 4a and 4b revealed lower IC50 values in almost all cases when compared to their precursors, exhibiting the highest cytotoxicity against the RPMI−7951 cell line (IC50: 18.8 μM for 4a and 20.7 μM for 4b). Further biological assessment of these compounds executed on the most affected cell line revealed a mitochondrial level induced apoptotic mechanism where both compounds inhibited mitochondrial respiration in RPMI−7951 cells. Furthermore, the triazole−BA derivatives caused a significant decrease of the anti−apoptotic Bcl−2 gene expression, while increasing the pro−apoptotic BAX gene’s expression.
Automatic XML Extraction from Word and Formatting of E-Book Formats: Insight into the Open Source Academic Publishing Suite (OS-APS)
Authors: Borchert Carsten , Cozatl Roberto , Eichler Frederik , Hoffmann Astrid , Putnings Markus
Published: December 2022

Due to resource constraints, most Diamond Open Access journals publish fewer than 25 articles per year, and 75% of journals are not able to provide their content in XML and HTML, primarily providing only PDFs. In order to keep up with larger commercial publishers, a high degree of automation and streamlining of processes is necessary. The Open Source Academic Publishing Suite (OS-APS) project, funded by the German Federal Ministry of Education and Research, aims to achieve this. OS-APS automatically extracts the underlying XML from Word manuscripts and offers optimization and export options in various formats (PDF, HTML, EPUB). The professional corporate design, e.g., of the PDFs, is managed automatically using templates or creating one’s own using a Template Development Kit. OS-APS will also connect to scholarly-led and community-driven publishing platforms such as Open Journal Systems (OJS), Open Monograph Press (OMP), and DSpace: the software will be able to be integrated into a wide range of publication processes, whether at small, low-resource commercial Open Access Publishers, or institutional and Diamond Open Access Publishers.
Changes in the Structure of the Snow Cover of Hansbreen (S Spitsbergen) Derived from Repeated High-Frequency Radio-Echo Sounding
Authors: Kachniarz Kamil , Grabiec Mariusz , Ignatiuk Dariusz , Laska Michał , Luks Bartłomiej
Published: December 2022

This paper explores the potential of ground-penetrating radar (GPR) monitoring for an advanced understanding of snow cover processes and structure. For this purpose, the study uses the Hansbreen (SW Spitsbergen) records that are among the longest and the most comprehensive snow-cover GPR monitoring records available on Svalbard. While snow depth (HS) is frequently the only feature derived from high-frequency radio-echo sounding (RES), this study also offers an analysis of the physical characteristics (grain shape, size, hardness, and density) of the snow cover structure. We demonstrate that, based on GPR data (800 MHz) and a single snow pit, it is possible to extrapolate the detailed features of snow cover to the accumulation area. Field studies (snow pits and RES) were conducted at the end of selected accumulation seasons in the period 2008–2019, under dry snow conditions and HS close to the maximum. The paper shows that although the snow cover structure varies in space and from season to season, a single snow pit site can represent the entire center line of the accumulation zone. Numerous hard layers (HLs) (up to 30% of the snow column) were observed that reflect progressive climate change, but there is no trend in quantity, thickness, or percentage contribution in total snow depth in the study period. HLs with strong crystal bonds create a “framework” in the snowpack, which reduces compaction and, consequently, the ice formation layers slow down the rate of snowpack metamorphosis. The extrapolation of snow pit data through radar profiling is a novel solution that can improve spatial recognition of snow cover characteristics and the accuracy of calculation of snow water equivalent (SWE).
Multi-Level Data Analyses in the Gajevo Landslide Research, Croatia
Authors: Podolszki Laszlo , Miklin Luka , Kosović Ivan , Gulam Vlatko
Published: December 2022

The Gajevo landslide is located in a hilly area of northern Croatia, where numerous landslides endanger and damage houses, roads, water systems, and power lines. Nevertheless, available landslide data are relatively scarce. Therefore, the Gajevo landslide location was chosen for detailed research and the development of a typical landslide model for this area. During initial research, the geographical and geological settings were reviewed and historical orthophotos were analysed. Due to the complexity and vulnerability of the area, the location required detailed investigations and the integration of multi-level data: remote (based on high-resolution LiDAR data) and field landslide mapping were performed and a map of the landslide area was developed. Precipitation data were reviewed, while shallow boreholes with material sampling and geophysical measurements provided information on material characteristics and 3D (depth) insight. As a result, knowledge was gained about material resistivity and composition along with the depth of sliding surfaces, and an engineering geological map of the Gajevo landslide area with the landslide and directly endangered areas marked was developed to be used by the local community in landslide risk assessment. As it is reasonable to expect that an extreme rainfall event will occur in combination with snowmelt in the coming years, resulting in the reactivation of Gajevo landslide, further research and continuous landslide monitoring are recommended.
Electrolyte-Gated Graphene Field Effect Transistor-Based Ca2+ Detection Aided by Machine Learning
Authors: Zhang Rong , Hao Tiantian , Hu Shihui , Wang Kaiyang , Ren Shuhui , Tian Ziwei , Jia Yunfang
Published: December 2022

Flexible electrolyte-gated graphene field effect transistors (Eg-GFETs) are widely developed as sensors because of fast response, versatility and low-cost. However, their sensitivities and responding ranges are often altered by different gate voltages. These bias-voltage-induced uncertainties are an obstacle in the development of Eg-GFETs. To shield from this risk, a machine-learning-algorithm-based LgGFETs’ data analyzing method is studied in this work by using Ca2+ detection as a proof-of-concept. For the as-prepared Eg-GFET-Ca2+ sensors, their transfer and output features are first measured. Then, eight regression models are trained with the use of different machine learning algorithms, including linear regression, support vector machine, decision tree and random forest, etc. Then, the optimized model is obtained with the random-forest-method-treated transfer curves. Finally, the proposed method is applied to determine Ca2+ concentration in a calibration-free way, and it is found that the relation between the estimated and real Ca2+ concentrations is close-to y = x. Accordingly, we think the proposed method may not only provide an accurate result but also simplify the traditional calibration step in using Eg-GFET sensors.
Application of Variational Mode Decomposition and Whale Optimization Algorithm to Laser Ultrasonic Signal Denoising
Authors: Mao Xing , Yang Quan , Wang Xiaocheng , Li Jingdong
Published: December 2022

Laser ultrasound signal echoes are easily drowned out by the surrounding environmental noise in industrial field applications, and it is worthwhile to study methods of retaining the weak ultrasound signal during signal processing. To address this problem, this paper proposes to adopt the parameters optimized by the whale optimization algorithm to the variational mode decomposition (VMD) of laser ultrasound signals. The optimized parameters can avoid the frequency mixing and incomplete noise separation caused by the choice of artificial VMD parameters. The Hausdorff distance is applied in the process of reconstructing the signal to help accurately select the relevant modes and improve the signal-to-noise ratio. Simulation and experimental results show that the proposed method is feasible and effective compared with the other three available denoising methods.
STC-NLSTMNet: An Improved Human Activity Recognition Method Using Convolutional Neural Network with NLSTM from WiFi CSI
Authors: Islam Md Shafiqul , Jannat Mir Kanon Ara , Hossain Mohammad Nahid , Kim Woo-Su , Lee Soo-Wook , Yang Sung-Hyun
Published: December 2022

Human activity recognition (HAR) has emerged as a significant area of research due to its numerous possible applications, including ambient assisted living, healthcare, abnormal behaviour detection, etc. Recently, HAR using WiFi channel state information (CSI) has become a predominant and unique approach in indoor environments compared to others (i.e., sensor and vision) due to its privacy-preserving qualities, thereby eliminating the need to carry additional devices and providing flexibility of capture motions in both line-of-sight (LOS) and non-line-of-sight (NLOS) settings. Existing deep learning (DL)-based HAR approaches usually extract either temporal or spatial features and lack adequate means to integrate and utilize the two simultaneously, making it challenging to recognize different activities accurately. Motivated by this, we propose a novel DL-based model named spatio-temporal convolution with nested long short-term memory (STC-NLSTMNet), with the ability to extract spatial and temporal features concurrently and automatically recognize human activity with very high accuracy. The proposed STC-NLSTMNet model is mainly comprised of depthwise separable convolution (DS-Conv) blocks, feature attention module (FAM) and NLSTM. The DS-Conv blocks extract the spatial features from the CSI signal and add feature attention modules (FAM) to draw attention to the most essential features. These robust features are fed into NLSTM as inputs to explore the hidden intrinsic temporal features in CSI signals. The proposed STC-NLSTMNet model is evaluated using two publicly available datasets: Multi-environment and StanWiFi. The experimental results revealed that the STC-NLSTMNet model achieved activity recognition accuracies of 98.20% and 99.88% on Multi-environment and StanWiFi datasets, respectively. Its activity recognition performance is also compared with other existing approaches and our proposed STC-NLSTMNet model significantly improves the activity recognition accuracies by 4% and 1.88%, respectively, compared to the best existing method.
Misalignment-Resilient Propagation Model for Underwater Optical Wireless Links
Authors: Araújo João H. , Tavares Joana S. , Marques Veridiano M. , Salgado Henrique M. , Pessoa Luís M.
Published: December 2022

This paper proposes a multiple-lens receiver scheme to increase the misalignment tolerance of an underwater optical wireless communications link between an autonomous underwater vehicle (AUV) and a sensor plane. An accurate model of photon propagation based on the Monte Carlo simulation is presented which accounts for the lens(es) photon refraction at the sensor interface and angular misalignment between the emitter and receiver. The results show that the ideal divergence of the beam of the emitter is around 15° for a 1 m transmission length, increasing to 22° for a shorter distance of 0.5 m but being independent of the water turbidity. In addition, it is concluded that a seven-lense scheme is approximately three times more tolerant to offset than a single lens. A random forest machine learning algorithm is also assessed for its suitability to estimate the offset and angle of the AUV in relation to the fixed sensor, based on the power distribution of each lens, in real time. The algorithm is able to estimate the offset and angular misalignment with a mean square error of 5 mm (6 mm) and 0.157 rad (0.174 rad) for a distance between the transmitter and receiver of 1 m and 0.5 m, respectively.
Development and Testing of a Compact Autorefractor Based on Double-Pass Imaging
Authors: Emmerich Linus , Ohlendorf Arne , Leube Alexander , Suchkov Nikolai , Wahl Siegfried
Published: December 2022

Autorefraction is an objective way to determine the refractive error of the eye, without the need for feedback by the patient or a well-educated practitioner. To make refractive measurements more accessible in the background of the growing prevalence of myopia, a compact autorefractor was built, containing only few optical components and relying on double-pass imaging and the physical properties of the point-spread function and digital image processing instead. A method was developed to analyze spherical defocus as well as the defocus and angle of astigmatism. The device was tested using calibrator eye models in a range of ± 15 D spherical defocus and −3 D astigmatic defocus. Reliable results could be achieved across the whole measurement range, with only a small increase in deviation toward high values of refractive errors, showing the feasibility of a PSF-based approach for a compact and low-cost solution for objective measurements of refractive error.
High Quality Coal Foreign Object Image Generation Method Based on StyleGAN-DSAD
Authors: Cao Xiangang , Wei Hengyang , Wang Peng , Zhang Chiyu , Huang Shikai , Li Hu
Published: December 2022

Research on coal foreign object detection based on deep learning is of great significance to safe, efficient, and green production of coal mines. However, the foreign object image dataset is scarce due to collection conditions, which brings an enormous challenge to coal foreign object detection. To achieve augmentation of foreign object datasets, a high-quality coal foreign object image generation method based on improved StyleGAN is proposed. Firstly, the dual self-attention module is introduced into the generator to strengthen the long-distance dependence of features between spatial and channel, refine the details of the generated images, accurately distinguish the front background information, and improve the quality of the generated images. Secondly, the depthwise separable convolution is introduced into the discriminator to solve the problem of low efficiency caused by the large number of parameters of multi-stage convolutional networks, to realize the lightweight model, and to accelerate the training speed. Experimental results show that the improved model has significant advantages over several classical GANS and original StyleGAN in terms of quality and diversity of the generated images, with an average improvement of 2.52 in IS and a decrease of 5.80 in FID for each category. As for the model complexity, the parameters and training time of the improved model are reduced to 44.6% and 58.8% of the original model without affecting the generated images quality. Finally, the results of applying different data augmentation methods to the foreign object detection task show that our image generation method is more effective than the traditional methods, and that, under the optimal conditions, it improves APbox by 5.8% and APmask by 4.5%.
Energy-Saving Optimization Method of Urban Rail Transit Based on Improved Differential Evolution Algorithm
Authors: Lu Guancheng , He Deqiang , Zhang Jinlai
Published: December 2022

The transformation of railway infrastructure and traction equipment is an ideal way to realize energy savings of urban rail transit trains. However, upgrading railway infrastructure and traction equipment is a high investment and difficult process. To produce energy-savings in the urban rail transit system without changing the existing infrastructure, we propose an energy-saving optimization method by optimizing the traction curve of the train. Firstly, after analyzing the relationship between the idle distance and running energy-savings, an optimization method of traction energy-savings based on the combination of the inertia motion and energy optimization is established by taking the maximum idle distance as the objective; and the maximum allowable running speed, passenger comfort, train timetable, maximum allowable acceleration and kinematics equation as constraints. Secondly, a solution method based on the combination of the adaptive dynamic multimodal differential evolution algorithm and the Q learning algorithm is applied to solve the optimization model of energy-savings. Finally, numeric experiments are conducted to verify the proposed method. Extensive experiments demonstrate the effectiveness of the proposed method. The results show that the method has significant energy-saving properties, saving energy by about 11.2%.
Electrocatalytic Platform Based on Silver-Doped Sugar Apple-like Cupric Oxide Embedded Functionalized Carbon Nanotubes for Nanomolar Detection of Acetaminophen (APAP)
Authors: Balram Deepak , Lian Kuang-Yow , Sebastian Neethu
Published: December 2022

Economical and nanomolar-level determination of the analgesic drug, acetaminophen (APAP), is reported in this work. A novel ternary nanocomposite based on silver-doped sugar apple-like cupric oxide (CuO)-decorated amine-functionalized multi-walled carbon nanotubes (fCNTs) was sonochemically prepared. CuO nanoparticles were synthesized based on the ascorbic acid-mediated low-temperature method, and sidewall functionalization of CNTs was carried out. Important characterizations of the synthesized materials were analyzed using SEM, TEM, HAADF-STEM, elemental mapping, EDX, lattice fringes, SAED pattern, XRD, EIS, UV-Vis, micro-Raman spectroscopy, and FTIR. It was noted the sonochemically prepared nanocomposite diligently fabricated on screen-printed carbon electrode showcased outstanding electrocatalytic performance towards APAP determination. The APAP sensor exhibited ultra-low limit of detection of 4 nM, wide linear concentration ranges of 0.02–3.77 and 3.77–90.02 μM, and high sensitivity of 30.45 μA μM−1 cm−2. Moreover, further evaluation of the sensor’s performance based on electrochemical experiments showcased outstanding selectivity, stability, reproducibility, and repeatability. Further, excellent practical feasibility of the proposed APAP sensor was affirmed with excellent recovery larger than 96.86% and a maximum RSD of 3.67%.
Thickness Measurement at High Lift-Off for Underwater Corroded Iron-Steel Structures Using a Magnetic Sensor Probe
Authors: Adachi Shoya , Hayashi Minoru , Kawakami Taisei , Ando Yuto , Wang Jin , Sakai Kenji , Kiwa Toshihiko , Ishikawa Toshiyuki , Tsukada Keiji
Published: December 2022

Infrastructure facilities that were built approximately half a century ago have rapidly aged. Steel sheet piles, the inspection object in this study, are severely corroded, resulting in cave-in damages at wharfs. To solve such a problem, non-destructive inspection techniques are required. We previously demonstrated plate thickness measurement using extremely low-frequency eddy current testing. However, when the steel sheet piles are located in water, shellfish adhere to their surface, causing a lift-off of several tens of millimeters. Therefore, this large lift-off hinders the thickness measurement owing to fluctuations of magnetic signals. In this study, sensor probes with different coil diameters were prototyped and the optimum size for measuring steel sheet piles at high lift-off was investigated. Using the probes, the magnetic field was applied with a lift-off range from 0 to 80 mm, and the intensity and phase of the detected magnetic field were analyzed. Subsequently, by increasing the probe diameter, a good sensitivity was obtained for the thickness estimation with a lift-off of up to 60 mm. Moreover, these probes were used to measure the thickness of actual steel sheet piles, and measurements were successfully obtained at a high lift-off.