bluuebunny/crossref_metadata_2025 huggingface dataset:
In Situ Compensation Method for Precise Integral SQUID Magnetometry of Miniscule Biological, Chemical, and Powder Specimens Requiring the Use of Capsules
Authors: Gas Katarzyna , Sawicki Maciej
Published: January 2022

Steadily growing interest in magnetic characterization of organic compounds for therapeutic purposes or of other irregularly shaped specimens calls for refinements of experimental methodology to satisfy experimental challenges. Encapsulation in capsules remains the method of choice, but its applicability in precise magnetometry is limited. This is particularly true for minute specimens in the single milligram range as they are outweighed by the capsules and are subject to large alignment errors. We present here a completely new experimental methodology that permits 30-fold in situ reduction of the signal of capsules by substantially restoring the symmetry of the sample holder that is otherwise broken by the presence of the capsule. In practical terms it means that the standard 30 mg capsule is seen by the magnetometer as approximately a 1 mg object, effectively opening the window for precise magnetometry of single milligram specimens. The method is shown to work down to 1.8 K and in the whole range of the magnetic fields. The method is demonstrated and validated using the reciprocal space option of MPMS-SQUID magnetometers; however, it can be easily incorporated in any magnetometer that can accommodate straw sample holders (i.e., the VSM-SQUID). Importantly, the improved sensitivity is accomplished relying only on the standard accessories and data reduction method provided by the SQUID manufacturer, eliminating the need for elaborate raw data manipulations.
The Effects of Core Machining Configurations on the Mechanical Properties of Cores and Sandwich Structures
Authors: Qin Zhiwen , Wei Lili , Zhang Mingming , Zhang Rui , Ji Xiang , Song Xiaofei , Qiang Shengguan
Published: January 2022

Composite sandwich structures are widely used in the fields of aviation, marine, and energy due to their high specific stiffness and design flexibility. Improving the mechanical properties of the cores is significant to the strength, modulus, and stability of composite sandwich structures. Two kinds of core machining configurations were designed by combining thin grooves, perforated holes, and thick contour cuts as well as non-machining plain cores. The cores and sandwich structures with these configurations were fabricated using a vacuum-assistant infusion process. Static tensile, compressive, shear, and peeling tests were conducted on the infused cores and sandwich structures. The results showed that the tensile, compressive, and shear moduli, and compressive strength of the infused cores can be greatly improved. The tensile strength changed negligibly due to stress concentration induced by irregular foam cell and the shear-lag phenomenon of the resin column/foam interface. The shear strength of the infused cores increased slightly. The thick contour cuts and perforated holes can greatly improve the face sheet/core peel capacity of the sandwich structures, whereas the thin grooves can moderately improve the peel capacity. Both infused cores with the designed machining configurations exhibited positive effects on the compressive, tensile, and shear moduli, and compressive strength, considering the material costs. The study provides a comprehensive and quantitative insight into the effects of core machining configurations on mechanical properties of infused cores and composite sandwich structures.
Impurity-Induced Magnetization of Graphene
Authors: Inglot Michał , Szczepański Tomasz
Published: January 2022

We present a model of impurity-induced magnetization of graphene assuming that the main source of graphene magnetization is related to impurity states with a localized spin. The analysis of solutions of the Schrödinger equation for electrons near the Dirac point has been performed using the model of massless fermions. For a single impurity, the solution of Schrödinger’s equation is a linear combination of Bessel functions. We found resonance energy levels of the non-magnetic impurity. The magnetic moment of impurity with a localized spin was accounted for the calculation of graphene magnetization using the Green’s function formalism. The spatial distribution of induced magnetization for a single impurity is obtained. The energy of resonance states was also calculated as a function of interaction. This energy is depending on the impurity potential and the coupling constant of interaction.
Simulation of the Peritectic Phase Transition in Fe-C Alloys
Authors: Fang Hui , Tang Qianyu , Zhang Qingyu , Fan Yiming , Pan Shiyan , Rettenmayr Markus , Zhu Mingfang
Published: January 2022

In this work, a multi-phase cellular automaton (CA) model is extended for the quantitative simulation of peritectic phase transition. First, the effects of cooling rate/supersaturation and temperature on the peritectic transformation kinetics in Fe-C alloys are investigated by utilizing the present CA model. The CA simulations show that supersaturations in the parent phases (liquid and δ-ferrite) increase the L/γ interface growth velocity remarkably, but tinily for the δ/γ interface migration velocity. There exists a transition supersaturation for isothermal transformations, at which the growth rates of the two interfaces are equal. The transition supersaturation is found to increase with decreasing temperature. Microstructural evolution at different cooling rates during peritectic transformation is simulated using the experimental conditions. At low cooling rates, the δ/γ interface propagates at a higher velocity than the L/γ interface. At high cooling rates, however, the γ-phase grows more into the L-phase with a cellular morphology. Then, the proposed CA model is applied to simulate the microstructural evolution during peritectic reaction. It is observed that the γ-phase propagates along the L/δ interface and finally encircles the δ-phase. Meanwhile, the intervenient γ-phase grows in thickness through peritectic transformation. The CA simulations are compared reasonably well with the experimental data and analytical calculations.
An Open-Source Low-Cost Imaging System Plug-In for Pheromone Traps Aiding Remote Insect Pest Population Monitoring in Fruit Crops
Authors: Schrader Mark Jacob , Smytheman Peter , Beers Elizabeth H. , Khot Lav R.
Published: January 2022

This note describes the development of a plug-in imaging system for pheromone delta traps used in pest population monitoring. The plug-in comprises an RGB imaging sensor integrated with a microcontroller unit and associated hardware for optimized power usage and data capture. The plug-in can be attached to the top of a modified delta trap to realize periodic image capture of the trap liner (17.8 cm × 17.8 cm). As configured, the captured images are stored on a microSD card with ~0.01 cm2 pixel−1 spatial resolution. The plug-in hardware is configured to conserve power, as it enters in sleep mode during idle operation. Twenty traps with plug-in units were constructed and evaluated in the 2020 field season for codling moth (Cydia pomonella) population monitoring in a research study. The units reliably captured images at daily interval over the course of two weeks with a 350 mAh DC power source. The captured images provided the temporal population dynamics of codling moths, which would otherwise be achieved through daily manual trap monitoring. The system’s build cost is about $33 per unit, and it has potential for scaling to commercial applications through Internet of Things-enabled technologies integration.
A p−V Diagram Based Fault Identification for Compressor Valve by Means of Linear Discrimination Analysis
Authors: Li Xueying , Ren Peng , Zhang Zhe , Jia Xiaohan , Peng Xueyuan
Published: January 2022

The pressure-volume diagram (p−V diagram) is an established method for analyzing the thermodynamic process in the cylinder of a reciprocating compressor as well as the fault of its core components including valves. The failure of suction/discharge valves is the most common cause of unscheduled shutdowns, and undetected failure may lead to catastrophic accidents. Although researchers have investigated fault classification by various estimation techniques and case studies, few have looked deeper into the barriers and pathways to realize the level determination of faults. The initial stage of valve failure is characterized in the form of mild leakage; if this is identified at this period, more serious accidents can be prevented. This study proposes a fault diagnosis and severity estimation method of the reciprocating compressor valve by virtue of features extracted from the p−V diagram. Four-dimensional characteristic variables consisting of the pressure ratio, process angle coefficient, area coefficient, and process index coefficient are extracted from the p−V diagram. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were applied to establish the diagnostic model, where PCA realizes feature amplification and projection, then LDA implements feature dimensionality reduction and failure prediction. The method was validated by the diagnosis of various levels of severity of valve leakage in a reciprocating compressor, and further, applied in the diagnosis of two actual faults: Mild leakage caused by the cracked valve plate in a reciprocating compressor, and serious leakage caused by the deformed valve in a hydraulically driven piston compressor for a hydrogen refueling station (HRS).
The Origins and the Current Applications of Microfluidics-Based Magnetic Cell Separation Technologies
Authors: Civelekoglu Ozgun , Frazier A. Bruno , Sarioglu A. Fatih
Published: January 2022

The magnetic separation of cells based on certain traits has a wide range of applications in microbiology, immunology, oncology, and hematology. Compared to bulk separation, performing magnetophoresis at micro scale presents advantages such as precise control of the environment, larger magnetic gradients in miniaturized dimensions, operational simplicity, system portability, high-throughput analysis, and lower costs. Since the first integration of magnetophoresis and microfluidics, many different approaches have been proposed to magnetically separate cells from suspensions at the micro scale. This review paper aims to provide an overview of the origins of microfluidic devices for magnetic cell separation and the recent technologies and applications grouped by the targeted cell types. For each application, exemplary experimental methods and results are discussed.
Consensus Control of Leaderless and Leader-Following Coupled PDE-ODEs Modeled Multi-Agent Systems
Authors: Ni Xu , Yi Kejia , Jiang Yiming , Zhang Ancai , Yang Chengdong
Published: January 2022

This paper discusses consensus control of nonlinear coupled parabolic PDE-ODE-based multi-agent systems (PDE-ODEMASs). First, a consensus controller of leaderless PDE-ODEMASs is designed. Based on a Lyapunov-based approach, coupling strengths are obtained for leaderless PDE-ODEMASs to achieve leaderless consensus. Furthermore, a consensus controller in the leader-following PDE-ODEMAS is designed and the corresponding coupling strengths are obtained to ensure the leader-following consensus. Two examples show the effectiveness of the proposed methods.
Forecasting the Hydrogen Demand in China: A System Dynamics Approach
Authors: Huang Jingsi , Li Wei , Wu Xiangyu
Published: January 2022

Many countries, including China, have implemented supporting policies to promote the commercialized application of green hydrogen and hydrogen fuel cells. In this study, a system dynamics (SD) model is proposed to study the evolution of hydrogen demand in China from the petroleum refining industry, the synthetic ammonia industry, and the vehicle market. In the model, the impact from the macro-environment, hydrogen fuel supply, and construction of hydrogen facilities is considered to combine in incentives for supporting policies. To further formulate the competitive relationship in the vehicle market, the Lotka–Volterra (LV) approach is adopted. The model is verified using published data from 2003 to 2017. The model is also used to forecast China’s hydrogen demand up to the year of 2030 under three different scenarios. Finally, some forward-looking guidance is provided to policy makers according to the forecasting results.
ReRec: A Divide-and-Conquer Approach to Recommendation Based on Repeat Purchase Behaviors of Users in Community E-Commerce
Authors: Wu Jun , Li Yuanyuan , Shi Li , Yang Liping , Niu Xiaxia , Zhang Wen
Published: January 2022

Existing studies have made a great endeavor in predicting users’ potential interests in items by modeling user preferences and item characteristics. As an important indicator of users’ satisfaction and loyalty, repeat purchase behavior is a promising perspective to extract insightful information for community e-commerce. However, the repeated purchase behaviors of users have not yet been thoroughly studied. To fill in this research gap from the perspective of repeated purchase behavior and improve the process of generation of candidate recommended items this research proposed a novel approach called ReRec (Repeat purchase Recommender) for real-life applications. Specifically, the proposed ReRec approach comprises two components: the first is to model the repeat purchase behaviors of different types of users and the second is to recommend items to users based on their repeat purchase behaviors of different types. The extensive experiments are conducted on a real dataset collected from a community e-commerce platform, and the performance of our model has improved at least about 13.6% compared with the state-of-the-art techniques in recommending online items (measured by F-measure). Specifically, for active users, with w=1 and NUA∈5,25, the results of ReRec show a significant improvement (at least 50%) in recommendation. With α and σ as 0.75 and 0.2284, respectively, the proposed ReRec for unactive users is also superior to (at least 13.6%) the evaluation indicators of traditional Item CF when NUB∈6, 25. To the best of our knowledge, this paper is the first to study recommendations in community e-commerce.
Taming Hyperchaos with Exact Spectral Derivative Discretization Finite Difference Discretization of a Conformable Fractional Derivative Financial System with Market Confidence and Ethics Risk
Authors: Clemence-Mkhope Dominic P. , Gibson Gregory A.
Published: January 2022

Four discrete models, using the exact spectral derivative discretization finite difference (ESDDFD) method, are proposed for a chaotic five-dimensional, conformable fractional derivative financial system incorporating ethics and market confidence. Since the system considered was recently studied using the conformable Euler finite difference (CEFD) method and found to be hyperchaotic, and the CEFD method was recently shown to be valid only at fractional index α=1, the source of the hyperchaos is in question. Through numerical experiments, illustration is presented that the hyperchaos previously detected is, in part, an artifact of the CEFD method, as it is absent from the ESDDFD models.
Extremophilic Fungi from Marine Environments: Underexplored Sources of Antitumor, Anti-Infective and Other Biologically Active Agents
Authors: Giddings Lesley-Ann , Newman David J.
Published: January 2022

Marine environments are underexplored terrains containing fungi that produce a diversity of natural products given unique environmental pressures and nutrients. While bacteria are commonly the most studied microorganism for natural products in the marine world, marine fungi are also abundant but remain an untapped source of bioactive metabolites. Given that their terrestrial counterparts have been a source of many blockbuster antitumor agents and anti-infectives, including camptothecin, the penicillins, and cyclosporin A, marine fungi also have the potential to produce new chemical scaffolds as leads to potential drugs. Fungi are more phylogenetically diverse than bacteria and have larger genomes that contain many silent biosynthetic gene clusters involved in making bioactive compounds. However, less than 5% of all known fungi have been cultivated under standard laboratory conditions. While the number of reported natural products from marine fungi is steadily increasing, their number is still significantly lower compared to those reported from their bacterial counterparts. Herein, we discuss many varied cytotoxic and anti-infective fungal metabolites isolated from extreme marine environments, including symbiotic associations as well as extreme pressures, temperatures, salinity, and light. We also discuss cultivation strategies that can be used to produce new bioactive metabolites or increase their production. This review presents a large number of reported structures though, at times, only a few of a large number of related structures are shown.
Metabolomic Analysis of Carbohydrate and Amino Acid Changes Induced by Hypoxia in Naked Mole-Rat Brain and Liver
Authors: Cheng Hang , Qin Yiming (Amy) , Dhillon Rashpal , Dowell James , Denu John M. , Pamenter Matthew E.
Published: January 2022

Hypoxia poses a major physiological challenge for mammals and has significant impacts on cellular and systemic metabolism. As with many other small rodents, naked mole-rats (NMRs; Heterocephalus glaber), who are among the most hypoxia-tolerant mammals, respond to hypoxia by supressing energy demand (i.e., through a reduction in metabolic rate mediated by a variety of cell- and tissue-level strategies), and altering metabolic fuel use to rely primarily on carbohydrates. However, little is known regarding specific metabolite changes that underlie these responses. We hypothesized that NMR tissues utilize multiple strategies in responding to acute hypoxia, including the modulation of signalling pathways to reduce anabolism and reprogram carbohydrate metabolism. To address this question, we evaluated changes of 64 metabolites in NMR brain and liver following in vivo hypoxia exposure (7% O2, 4 h). We also examined changes in matched tissues from similarly treated hypoxia-intolerant mice. We report that, following exposure to in vivo hypoxia: (1) phenylalanine, tyrosine and tryptophan anabolism are supressed both in NMR brain and liver; (2) carbohydrate metabolism is reprogramed in NMR brain and liver, but in a divergent manner; (3) redox state is significantly altered in NMR brain; and (4) the AMP/ATP ratio is elevated in liver. Overall, our results suggest that hypoxia induces significant metabolic remodelling in NMR brain and liver via alterations of multiple metabolic pathways.
Abnormal Iron and Lipid Metabolism Mediated Ferroptosis in Kidney Diseases and Its Therapeutic Potential
Authors: Zhang Xiaoqin , Li Xiaogang
Published: January 2022

Ferroptosis is a newly identified form of regulated cell death driven by iron-dependent phospholipid peroxidation and oxidative stress. Ferroptosis has distinct biological and morphology characteristics, such as shrunken mitochondria when compared to other known regulated cell deaths. The regulation of ferroptosis includes different molecular mechanisms and multiple cellular metabolic pathways, including glutathione/glutathione peroxidase 4(GPX4) signaling pathways, which are involved in the amino acid metabolism and the activation of GPX4; iron metabolic signaling pathways, which are involved in the regulation of iron import/export and the storage/release of intracellular iron through iron-regulatory proteins (IRPs), and lipid metabolic signaling pathways, which are involved in the metabolism of unsaturated fatty acids in cell membranes. Ferroptosis plays an essential role in the pathology of various kidneys diseases, including acute kidney injury (AKI), chronic kidney disease (CKD), autosomal dominant polycystic kidney disease (ADPKD), and renal cell carcinoma (RCC). Targeting ferroptosis with its inducers/initiators and inhibitors can modulate the progression of kidney diseases in animal models. In this review, we discuss the characteristics of ferroptosis and the ferroptosis-based mechanisms, highlighting the potential role of the main ferroptosis-associated metabolic pathways in the treatment and prevention of various kidney diseases.
High-Efficiency Expression and Purification of DNAJB6b Based on the pH-Modulation of Solubility and Denaturant-Modulation of Size
Authors: Linse Sara
Published: January 2022

The chaperone DNAJB6b delays amyloid formation by suppressing the nucleation of amyloid fibrils and increases the solubility of amyloid-prone proteins. These dual effects on kinetics and equilibrium are related to the unusually high chemical potential of DNAJB6b in solution. As a consequence, the chaperone alone forms highly polydisperse oligomers, whereas in a mixture with an amyloid-forming protein or peptide it may form co-aggregates to gain a reduced chemical potential, thus enabling the amyloid peptide to increase its chemical potential leading to enhanced solubility of the peptide. Understanding such action at the level of molecular driving forces and detailed structures requires access to highly pure and sequence homogeneous DNAJB6b with no sequence extension. We therefore outline here an expression and purification protocol of the protein “as is” with no tags leading to very high levels of pure protein based on its physicochemical properties, including size and charge. The versatility of the protocol is demonstrated through the expression of an isotope labelled protein and seven variants, and the purification of three of these. The activity of the protein is bench-marked using aggregation assays. Two of the variants are used to produce a palette of fluorescent DNAJB6b labelled at an engineered N- or C-terminal cysteine.
Novel Antifungal Dimers from the Roots of Taiwania cryptomerioides
Authors: Cheng Ming-Jen , Wu Ming-Der , Chang Chao-Lin , Chang Hsun-Shuo , Chyu Chiou-Fung , Kuo Yueh-Hsiung
Published: January 2022

Five new dimer compounds, namely Taiwaniacryptodimers A–E (1–5), were isolated from the methanol extract of the roots of Taiwania cryptomerioides. Their structures were established by mean of spectroscopic analysis and comparison of NMR data with those of known analogues. Their antifungal activities were also evaluated. Our results indicated that metabolites 1, 2, 4, and 5 displayed moderate antifungal activities against Aspergillus niger, Penicillium italicum, Candida albicans, and Saccharomyces cerevisiae.
Study on Synergistic Antioxidant Effect of Typical Functional Components of Hydroethanolic Leaf Extract from Ginkgo Biloba In Vitro
Authors: Zhang Lihu , Zhu Chunyi , Liu Xiaoqing , Su Erzheng , Cao Fuliang , Zhao Linguo
Published: January 2022

The predicted anti-oxidation is related to apoptosis, proliferation, lipid metabolism, cell differentiation, and immune response. There are some differences in the antioxidant capacity of the four typical components of ginkgo biloba extract (EGb) including ginkgo flavone (GF), ginkgolide (G), procyanidins (OPC), and organic acids (OA), and any two members of them can exhibit apparent synergistic effects. The order of DPPH scavenging ability was: OPC > GF > OA > G. The scavenging ability of procyanidins was close to that of VC; the scavenging capacity of ABTS was GF > OPC > OA > G. The GF:OPC (1:9) showed the best synergism in scavenging DPPH and ABTS radicals. The 193 kinds of small molecules reported in EGb were obtained by analyzing the properties of EGb. In order to construct a corresponding biological activity target set, molecular docking and the network pharmacology method were employed to build the molecular action mechanism network of a compound target, and the main biological functions and signaling pathways involved with their antioxidant activities were predicted. The results displayed that the top ten compounds which belonged to the two broad categories, ginkgo flavonoids and proanthocyanidins, could interact closely with several important target proteins (CASP3, SOD2, MAPK1, HSPA4, and NQO1). This would be expected to lay a theoretical foundation for the deep development of Ginkgo biloba extract.
Effect of Calmodulin-like Gene (CML) Overexpression on Stilbene Biosynthesis in Cell Cultures of Vitis amurensis Rupr.
Authors: Aleynova Olga A. , Suprun Andrey R. , Ananev Alexey A. , Nityagovsky Nikolay N. , Ogneva Zlata V. , Dubrovina Alexandra S. , Kiselev Konstantin V.
Published: January 2022

Stilbenes are plant phenolics known to rapidly accumulate in grapevine and other plants in response to injury or pathogen attack and to exhibit a great variety of healing beneficial effects. It has previously been shown that several calmodulin-like protein (CML) genes were highly up-regulated in cell cultures of wild-growing grapevine Vitis amurensis Rupr. in response to stilbene-modulating conditions, such as stress hormones, UV-C, and stilbene precursors. Both CML functions and stilbene biosynthesis regulation are still poorly understood. In this study, we investigated the effect of overexpression of five VaCML genes on stilbene and biomass accumulation in the transformed cell cultures of V. amurensis. We obtained 16 transgenic cell lines transformed with the VaCML52, VaCML65, VaCML86, VaCML93, and VaCML95 genes (3–4 independent lines per gene) under the control of the double CaMV 35S promoter. HPLC-MS analysis showed that overexpression of the VaCML65 led to a considerable and consistent increase in the content of stilbenes of 3.8–23.7 times in all transformed lines in comparison with the control calli, while biomass accumulation was not affected. Transformation of the V. amurensis cells with other analyzed VaCML genes did not lead to a consistent and considerable effect on stilbene biosynthesis in the cell lines. The results indicate that the VaCML65 gene is implicated in the signaling pathway regulating stilbene biosynthesis as a strong positive regulator and can be useful in viticulture and winemaking for obtaining grape cultivars with a high content of stilbenes and stress resistance.
Continuous LED Lighting Enhances Yield and Nutritional Value of Four Genotypes of Brassicaceae Microgreens
Authors: Shibaeva Tatjana G. , Sherudilo Elena G. , Rubaeva Alexandra A. , Titov Alexander F.
Published: January 2022

The effect of continuous lighting (CL, 24 h) and light spectrum on growth and nutritional quality of arugula (Eruca sativa), broccoli (Brassica oleracea var. italic), mizuna (Brassica rapa. var. nipposinica), and radish (Raphanus sativus var. radicula) were investigated in growth chambers under light-emitting diode (LED) and fluorescent lighting. Microgreens were grown under four combinations of two photoperiods (16 h and 24 h) providing daily light integral (DLI) of 15.6 and 23.3 mol m−2 day−1, correspondingly) with two light spectra: LED lamps and fluorescent lamps (FLU). The results show that fresh and dry weights as well as leaf mass per area and robust index of harvested arugula, broccoli, mizuna, and radish seedlings were significantly higher under CL compared to 16 h photoperiod regardless of light quality. There were no visible signs of leaf photodamage. In all CL-treated plants higher chlorophyll a/b and carotenoid-to-chlorophyll ratios were observed in all plants except mizuna. CL treatment was beneficial for anthocyanin, flavonoid, and proline accumulation. Higher activities of antioxidant enzymes (catalase, superoxide dismutase, ascorbate peroxidase, and guaiacol peroxidase) were also observed in CL-treated plants. In most cases, the effects were more pronounced under LED lighting. These results indicate that plants under mild oxidative stress induced by CL accumulated more non-enzymatic antioxidants and increased the activities of antioxidant enzymes. This added nutritional value to microgreens that are used as functional foods providing health benefits. We suggest that for arugula, broccoli, mizuna, and radish, an LED CL production strategy is possible and can have economic and nutritional benefits.
A Water Surface Contaminants Monitoring Method Based on Airborne Depth Reasoning
Authors: Luo Wei , Han Wenlong , Fu Ping , Wang Huijuan , Zhao Yunfeng , Liu Ke , Liu Yuyan , Zhao Zihui , Zhu Mengxu , Xu Ruopeng , Wei Guosheng
Published: January 2022

Water surface plastic pollution turns out to be a global issue, having aroused rising attention worldwide. How to monitor water surface plastic waste in real time and accurately collect and analyze the relevant numerical data has become a hotspot in water environment research. (1) Background: Over the past few years, unmanned aerial vehicles (UAVs) have been progressively adopted to conduct studies on the monitoring of water surface plastic waste. On the whole, the monitored data are stored in the UAVS to be subsequently retrieved and analyzed, thereby probably causing the loss of real-time information and hindering the whole monitoring process from being fully automated. (2) Methods: An investigation was conducted on the relationship, function and relevant mechanism between various types of plastic waste in the water surface system. On that basis, this study built a deep learning-based lightweight water surface plastic waste detection model, which was capable of automatically detecting and locating different water surface plastic waste. Moreover, a UAV platform-based edge computing architecture was built. (3) Results: The delay of return task data and UAV energy consumption were effectively reduced, and computing and network resources were optimally allocated. (4) Conclusions: The UAV platform based on airborne depth reasoning is expected to be the mainstream means of water environment monitoring in the future.
Electrodeformation of White Blood Cells Enriched with Gold Nanoparticles
Authors: Hallfors Nicholas G. , Teo Jeremy C. M. , Bertone Peter M. , Joshi Chakra P. , Orozaliev Ajymurat , Martin Matthew N. , Isakovic A. F.
Published: January 2022

The elasticity of white blood cells (WBCs) provides valuable insight into the condition of the cells themselves, the presence of some diseases, as well as immune system activity. In this work, we describe a novel process of refined control of WBCs’ elasticity through a combined use of gold nanoparticles (AuNPs) and the microelectrode array device. The capture and controlled deformation of gold nanoparticles enriched white blood cells in vitro are demonstrated and quantified. Gold nanoparticles enhance the effect of electrically induced deformation and make the DEP-related processes more controllable.
Biomass-Derived Carbon/Sulfur Composite Cathodes with Multiwalled Carbon Nanotube Coatings for Li-S Batteries
Authors: Han Lina , Li Zemin , Feng Yang , Wang Lijiang , Li Bowen , Lei Zijie , Wang Wenyan , Huang Weiwei
Published: January 2022

Lithium sulfur (Li-S) batteries stand out among many new batteries for their high energy density. However, the intermediate charge–discharge product dissolves easily into the electrolyte to produce a shuttle effect, which is a key factor limiting the rapid development of Li-S batteries. Among the various materials used to solve the challenges related to pure sulfur cathodes, biomass derived carbon materials are getting wider research attention. In this work, we report on the fabrication of cathode materials for Li-S batteries based on composites of sulfur and biomass-derived porous ramie carbon (RC), which are coated with multiwalled carbon nanotubes (MWCNTs). RC can not only adsorb polysulfide in its pores, but also provide conductive channels. At the same time, the MWCNTs coating further reduces the dissolution of polysulfides into the electrolyte and weakens the shuttle effect. The sulfur loading rate of RC is 66.3 wt.%. As a result, the initial discharge capacity of the battery is 1325.6 mAh·g−1 at 0.1 C long cycle, and it can still maintain 812.5 mAh·g−1 after 500 cycles. This work proposes an effective double protection strategy for the development of advanced Li-S batteries.
Intra Articular Ozone Modulates Inflammation and Has Anabolic Effect on Knee Osteoarthritis: IL-6 and IGF-1 as Pro-Inflammatory and Anabolic Biomarkers
Authors: Fernández-Cuadros Marcos E. , Pérez-Moro Olga S. , Albaladejo-Florín María J. , Tobar-Izquierdo María M. , Magaña-Sánchez Amelia , Jiménez-Cuevas Patricia , Rodríguez-de-Cía Javier
Published: January 2022

Objectives: (1) to demonstrate the anti-inflammatory and anabolic effect of Ozone by determining in serum samples the biochemical levels of IL-6 and IGF-1 in knee osteoarthritis (OA) patients in a real world rehabilitation setting; (2) to differentiate Ozone effect in diabetic (DM)/obese and non-DM/non-obese patients; (3) to evaluate clinical effectiveness by visual analog scale (VAS) and WOMAC scale, and biochemical effect by C-reactive protein (CRP), uric acid and erythrocyte sedimentation rate (ESR). Material and methods: 65 patients with knee OA Kellgren Lawrence (KL) grade 2 or more were analyzed in a retrospective observational study. The study ran from January 2018 to September 2021. Inclusion criteria: (a) patients 18 years or older; (b) with knee OA KL 2° or more; (c) biochemical analysis before-and-after treatment; (d) pain more than 3 on VAS. Exclusion Criteria: (a) previous knee surgery; (b) favism; (c) pregnancy; (d) any other disease that originates lack of collaboration for infiltration. Primary Outcome variables: (a) IL-6; (b) IGF-1 in diabetes mellitus (DM)/obese and non-DM/non-obese patients; both before-and-after Ozone treatment. Secondary Outcome variables: (a) CRP, (b) ESR, (c) uric acid, (d) VAS pain, (e) WOMAC pain, function and stiffness. Ozone protocol consisted of four sessions (once a week) of an intra-articular infiltration of 20 mL (20 µg/mL concentration) of a gas mixture of Oxygen-Ozone 95-5% (produced by Ozone generator Ozonosan-α Plus®). For biochemical evaluation, SNIBE MAGLUMI ™ IL-6 (CLIA) and SNIBE MAGLUMI ™ IGF-1 (CLIA) kits were used. CRP and uric acid were analyzed by a Abbott Alinity c kit; and ESR was evaluated by DIESSE VES MATIC CUBE 30. Results: There is a linear correlation between age and OA severity. IL-6 decreased both in DM and non-DM patients and in all OA KL grades (from 2.70 to 1.59 pg/mL). IGF-1 decreased in total group (OA + DM + obesity) from 112.09 to 107.19 ng/mL. When only non-DM/non-obese knee OA patients were analyzed, Ozone improved IGF-1 levels (from 100.17 to 102.03 ng/mL). Ozone decreased CRP, ESR, uric acid, and improved VAS pain, WOMAC pain, function and stiffness (p < 0.05). Conclusions: Ozone is a valid option for the management of knee osteoarthritis in a real world rehabilitation setting, because of its anti-inflammatory, metabolic and anabolic properties. Ozone tends to downregulate pro-inflammatory IL-6 cytokine. Ozone has a metabolic/hypoglycemic effect on obese/diabetic knee osteoarthritis patients by reducing IGF-1. Ozone has an anabolic effect on non-diabetic/non-obese patients by improving IGF-1. Ozone reduces other biomarkers of inflammation (CRP, ESR and uric acid) and improves, pain, function and quality of life.
Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm
Authors: Nasirahmadi Abozar , Hensel Oliver
Published: January 2022

Digitalization has impacted agricultural and food production systems, and makes application of technologies and advanced data processing techniques in agricultural field possible. Digital farming aims to use available information from agricultural assets to solve several existing challenges for addressing food security, climate protection, and resource management. However, the agricultural sector is complex, dynamic, and requires sophisticated management systems. The digital approaches are expected to provide more optimization and further decision-making supports. Digital twin in agriculture is a virtual representation of a farm with great potential for enhancing productivity and efficiency while declining energy usage and losses. This review describes the state-of-the-art of digital twin concepts along with different digital technologies and techniques in agricultural contexts. It presents a general framework of digital twins in soil, irrigation, robotics, farm machineries, and food post-harvest processing in agricultural field. Data recording, modeling including artificial intelligence, big data, simulation, analysis, prediction, and communication aspects (e.g., Internet of Things, wireless technologies) of digital twin in agriculture are discussed. Digital twin systems can support farmers as a next generation of digitalization paradigm by continuous and real-time monitoring of physical world (farm) and updating the state of virtual world.
Rich Structural Index for Stereoscopic Image Quality Assessment
Authors: Zhang Hua , Hu Xinwen , Gou Ruoyun , Zhang Lingjun , Zheng Bolun , Shen Zhuonan
Published: January 2022

The human visual system (HVS), affected by viewing distance when perceiving the stereo image information, is of great significance to study of stereoscopic image quality assessment. Many methods of stereoscopic image quality assessment do not have comprehensive consideration for human visual perception characteristics. In accordance with this, we propose a Rich Structural Index (RSI) for Stereoscopic Image objective Quality Assessment (SIQA) method based on multi-scale perception characteristics. To begin with, we put the stereo pair into the image pyramid based on Contrast Sensitivity Function (CSF) to obtain sensitive images of different resolution. Then, we obtain local Luminance and Structural Index (LSI) in a locally adaptive manner on gradient maps which consider the luminance masking and contrast masking. At the same time we use Singular Value Decomposition (SVD) to obtain the Sharpness and Intrinsic Structural Index (SISI) to effectively capture the changes introduced in the image (due to distortion). Meanwhile, considering the disparity edge structures, we use gradient cross-mapping algorithm to obtain Depth Texture Structural Index (DTSI). After that, we apply the standard deviation method for the above results to obtain contrast index of reference and distortion components. Finally, for the loss caused by the randomness of the parameters, we use Support Vector Machine Regression based on Genetic Algorithm (GA-SVR) training to obtain the final quality score. We conducted a comprehensive evaluation with state-of-the-art methods on four open databases. The experimental results show that the proposed method has stable performance and strong competitive advantage.
Design and Implementation of Charge Pump Phase-Locked Loop Frequency Source Based on GaAs pHEMT Process
Authors: Zhao Ranran , Zhang Yuming , Lv Hongliang , Wu Yue
Published: January 2022

This paper realized a charge pump phase locked loop (CPPLL) frequency source circuit based on 0.15 μm Win GaAs pHEMT process. In this paper, an improved fully differential edge-triggered frequency discriminator (PFD) and an improved differential structure charge pump (CP) are proposed respectively. In addition, a low noise voltage-controlled oscillator (VCO) and a static 64:1 frequency divider is realized. Finally, the phase locked loop (PLL) is realized by cascading each module. Measurement results show that the output signal frequency of the proposed CPPLL is 3.584 GHz–4.021 GHz, the phase noise at the frequency offset of 1 MHz is −117.82 dBc/Hz, and the maximum output power is 4.34 dBm. The chip area is 2701 μm × 3381 μm, and the power consumption is 181 mw.
Low-Cost Force Sensors Embedded in Physical Human–Machine Interfaces: Concept, Exemplary Realization on Upper-Body Exoskeleton, and Validation
Authors: Hoffmann Niclas , Ersoysal Samet , Prokop Gilbert , Hoefer Matthias , Weidner Robert
Published: January 2022

In modern times, the collaboration between humans and machines increasingly rises, combining their respective benefits. The direct physical support causes interaction forces in human–machine interfaces, whereas their form determines both the effectiveness and comfort of the collaboration. However, their correct detection requires various sensor characteristics and remains challenging. Thus, this paper presents a developed low-cost sensor pad working with a silicone capsule and a piezoresistive pressure sensor. Its measurement accuracy is validated in both an isolated testing environment and a laboratory study with four test subjects (gender-balanced), and an application integrated in interfaces of an active upper-body exoskeleton. In the material-testing machine, it becomes apparent that the sensor pad generally features the capability of reliably determining normal forces on its surface until a certain threshold. This is also proven in the real application, where the measurement data of three sensor pads spatially embedded in the exoskeletal interface are compared to the data of an installed multi-axis load cell and a high-resolution flexible pressure map. Here, the consideration of three sensor pads potentially enables detection of exoskeletal support on the upper arm as well as “poor” fit conditions such as uneven pressure distributions that recommend immediate system adjustments for ergonomic improvements.
T/R RF Switch with 150 ns Switching Time and over 100 dBc IMD for Wideband Mobile Applications in Thick Oxide SOI Process
Authors: Rikan Behnam S. , Kim David , Choi Kyung-Duk , Hejazi Arash , Yoo Joon-Mo , Pu YoungGun , Kim Seokkee , Huh Hyungki , Jung Yeonjae , Lee Kang-Yoon
Published: January 2022

This paper presents a fast-switching Transmit/Receive (T/R) Single-Pole-Double-Throw (SPDT) Radio Frequency (RF) switch. Thorough analyses have been conducted to choose the optimum number of stacks, transistor sizes, gate and body voltages, to satisfy the required specifications. This switch applies six stacks of series and shunt transistors as big as 3.9 mm/160 nm and 0.75 mm/160 nm, respectively. A negative charge pump and a voltage booster generate the negative and boosted control voltages to improve the harmonics and to keep Inter-Modulation Distortion (IMD) performance of the switch over 100 dBc. A Low Drop-Out (LDO) regulator limits the boosted voltage in Absolute Maximum Rating (AMR) conditions and improves the switch performance for Process, Voltage and Temperature (PVT) variations. To reduce the size, a dense custom-made capacitor consisting of different types of capacitors has been presented where they have been placed over each other in layout considering the Design Rule Checks (DRC) and applied in negative charge pump, voltage booster and LDO. This switch has been fabricated and tested in a 90 nm Silicon-on-Insulator (SOI) process. The second and third IMD for all specified blockers remain over 100 dBc and the switching time as fast as 150 ns has been achieved. The Insertion Loss (IL) and isolation at 2.7 GHz are −0.17 dB and −33 dB, respectively. This design consumes 145 uA from supply voltage range of 1.65 V to 1.95 V and occupies 440 × 472 µm2 of die area.
Slow Time-Varying Batch Process Quality Prediction Based on Batch Augmentation Analysis
Authors: Zhao Luping , Huang Xin
Published: January 2022

In this paper, focusing on the slow time-varying characteristics, a series of works have been conducted to implement an accurate quality prediction for batch processes. To deal with the time-varying characteristics along the batch direction, sliding windows can be constructed. Then, the start-up process is identified and the whole process is divided into two modes according to the steady-state identification. In the most important mode, the process data matrix, used to establish the regression model of the current batch, is expanded to involve the process data of previous batches, which is called batch augmentation. Thus, the process data of previous batches, which have an important influence on the quality of the current batch, will be identified and form a new batch augmentation matrix for modeling using the partial least squares (PLS) method. Moreover, considering the multiphase characteristic, batch augmentation analysis and modeling is conducted within each phase. Finally, the proposed method is applied to a typical batch process, the injection molding process. The quality prediction results are compared with those of the traditional quality prediction method based on PLS and the ridge regression method under the proposed batch augmentation analysis framework. The conclusion is obtained that the proposed method based on the batch augmentation analysis is superior.
A Low-Cost Multi-Sensor Data Acquisition System for Fault Detection in Fused Deposition Modelling
Authors: Kumar Satish , Kolekar Tushar , Patil Shruti , Bongale Arunkumar , Kotecha Ketan , Zaguia Atef , Prakash Chander
Published: January 2022

Fused deposition modelling (FDM)-based 3D printing is a trending technology in the era of Industry 4.0 that manufactures products in layer-by-layer form. It shows remarkable benefits such as rapid prototyping, cost-effectiveness, flexibility, and a sustainable manufacturing approach. Along with such advantages, a few defects occur in FDM products during the printing stage. Diagnosing defects occurring during 3D printing is a challenging task. Proper data acquisition and monitoring systems need to be developed for effective fault diagnosis. In this paper, the authors proposed a low-cost multi-sensor data acquisition system (DAQ) for detecting various faults in 3D printed products. The data acquisition system was developed using an Arduino micro-controller that collects real-time multi-sensor signals using vibration, current, and sound sensors. The different types of fault conditions are referred to introduce various defects in 3D products to analyze the effect of the fault conditions on the captured sensor data. Time and frequency domain analyses were performed on captured data to create feature vectors by selecting the chi-square method, and the most significant features were selected to train the CNN model. The K-means cluster algorithm was used for data clustering purposes, and the bell curve or normal distribution curve was used to define individual sensor threshold values under normal conditions. The CNN model was used to classify the normal and fault condition data, which gave an accuracy of around 94%, by evaluating the model performance based on recall, precision, and F1 score.
A Comparison of the External and Internal Demands Imposed during Conditioning Training and Match-Play in Semi-Professional and Development Female Netball Players
Authors: Wood Tandia G. , Scanlan Aaron T. , Minett Geoffrey M. , Kelly Vincent G.
Published: January 2022

This case series, team-based study aimed to compare the demands imposed during conditioning training and match-play in netball players. Female netball players competing at semi-professional (n = 9, age: 22.2 ± 3.8 years) and development (n = 9, age: 22.3 ± 2.9 years) levels had their internal (rating of perceived exertion (RPE)) and external (relative PlayerLoad (PL) in total and in the forwards, sideways, and vertical vectors) loads measured during conditioning-based training sessions and matches in a season. Demand variables were compared between conditioning and match-play across all players and according to position in each playing level. Conditioning training imposed higher relative PL in total and in each vector compared to match-play in semi-professional and development players (small to large effects). In contrast, RPE was significantly (p = 0.006) higher during match-play than conditioning training in semi-professional and development players (medium effects). Furthermore, according to playing position, significantly higher relative PL variables were evident during conditioning training than match-play in wing attack and goalkeeper semi-professional players and in goal attack, goal shooter, goal keeper, and goal defence development players. These results suggest conditioning training practices elicit adequate external intensities but inadequate internal intensities relative to match-play across positions in semi-professional and development netball players.