bluuebunny/crossref_metadata_2025 huggingface dataset:
An Improved Smart Meta-Superconductor MgB2
Authors: Zhao Xiaopeng , Hai Qingyu , Shi Miao , Chen Honggang , Li Yongbo , Qi Yao
Published: July 2022

Increasing and improving the critical transition temperature (TC), current density (JC) and the Meissner effect (HC) of conventional superconductors are the most important problems in superconductivity research, but progress has been slow for many years. In this study, by introducing the p-n junction nanostructured electroluminescent inhomogeneous phase with a red wavelength to realize energy injection, we found the improved property of smart meta-superconductors MgB2, the critical transition temperature TC increases by 0.8 K, the current density JC increases by 37%, and the diamagnetism of the Meissner effect HC also significantly improved, compared with pure MgB2. Compared with the previous yttrium oxide inhomogeneous phase, the p-n junction has a higher luminescence intensity, a longer stable life and simpler external field requirements. The coupling between superconducting electrons and surface plasmon polaritons may be explained by this phenomenon. The realization of smart meta-superconductor by the electroluminescent inhomogeneous phase provides a new way to improve the performance of superconductors.
Tetracycline Removal by Hercynite-Biochar from the Co-Pyrolysis of Red Mud-Steel Slag-Sludge
Authors: Zhou Xian , Chen Xia , Han Wei , Han Yi , Guo Mengxin , Peng Ziling , Fan Zeyu , Shi Yan , Wan Sha
Published: July 2022

The sludge-derived biochar is considered an effective emerging contaminants adsorbent for wastewater treatment. In this paper, red mud and steel slag (RMSS) was used for improving sludge dewaterability and enhancing the sludge-derived biochar adsorption capacity. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and a scanning electron microscope (SEM) were employed to comprehensively characterize the mineral composition, functional group, and morphology of the adsorbent. RMSS was able to improve the sludge dewatering performance by providing a skeleton structure to promote drainage and Fe(III) to decrease the Zeta potential. The dosage of 20 mg/g RMSS was able to reduce the specific resistance to filtration (SRF) and the Zeta potential of sludge from 1.57 × 1013 m/kg and −19.56 mV to 0.79 × 1013 m/kg and −9.10 mV, respectively. The co-pyrolysis of RMSS and sludge (2:8) induced the formation of biochar containing FeAl2O4 (PS80). The PS80 exhibited a large surface area (46.40 m2/g) and high tetracycline (TC) removal capacity (98.87 mg/g) when combined with H2O2 (PS80-H2O2). The adsorption process of TC onto PS80 and PS80-H2O2 was well described by the pseudo-first-order and pseudo-second-order kinetic model, indicating physisorption and chemisorption behavior. The results indicated that co-pyrolysis of RMSS sludge PS80-H2O2 could enhance the biochar adsorption capacity of TC, attributable to the degradation by ·OH generated by the heterogeneous Fenton reaction of FeAl2O4 and H2O2, the release of adsorbed sites, and the improvement of the biochar pore structure. This study proposed a novel method for the use of RMSS to dewater sludge as well as to induce the formation of FeAl2O4 in biochar with effective TC removal by providing a Fe and Al source, achieving a waste-to-resource strategy for the integrated management of industrial solid waste and sewage sludge.
Hyperelastic Microcantilever AFM: Efficient Detection Mechanism Based on Principal Parametric Resonance
Authors: Alibakhshi Amin , Rahmanian Sasan , Dastjerdi Shahriar , Malikan Mohammad , Karami Behrouz , Akgöz Bekir , Civalek Ömer
Published: July 2022

The impetus of writing this paper is to propose an efficient detection mechanism to scan the surface profile of a micro-sample using cantilever-based atomic force microscopy (AFM), operating in non-contact mode. In order to implement this scheme, the principal parametric resonance characteristics of the resonator are employed, benefiting from the bifurcation-based sensing mechanism. It is assumed that the microcantilever is made from a hyperelastic material, providing large deformation under small excitation amplitude. A nonlinear strain energy function is proposed to capture the elastic energy stored in the flexible component of the device. The tip–sample interaction is modeled based on the van der Waals non-contact force. The nonlinear equation governing the AFM’s dynamics is established using the extended Hamilton’s principle, obeying the Euler–Bernoulli beam theory. As a result, the vibration behavior of the system is introduced by a nonlinear equation having a time-dependent boundary condition. To capture the steady-state numerical response of the system, a developed Galerkin method is utilized to discretize the partial differential equation to a set of nonlinear ordinary differential equations (ODE) that are solved by the combination of shooting and arc-length continuation method. The output reveals that while the resonator is set to be operating near twice the fundamental natural frequency, the response amplitude undergoes a significant drop to the trivial stable branch as the sample’s profile experiences depression in the order of the picometer. According to the performed sensitivity analysis, the proposed working principle based on principal parametric resonance is recommended to design AFMs with ultra-high detection resolution for surface profile scanning.
Long-Term Adherence to a Mediterranean Diet 1-Year after Completion of the MedLey Study
Authors: Murphy Karen J. , Dyer Kathryn A. , Hyde Belinda , Davis Courtney R. , Bracci Ella L. , Woodman Richard J. , Hodgson Jonathan M.
Published: July 2022

Mediterranean populations enjoy the health benefits of a Mediterranean diet (MedDiet), but is it feasible to implement such a pattern beyond the Mediterranean region? The MedLey trial, a 6-month MedDiet intervention vs habitual diet in older Australians, demonstrated that the participants could maintain high adherence to a MedDiet for 6 months. The MedDiet resulted in improved systolic blood pressure (BP), endothelial dilatation, oxidative stress, and plasma triglycerides in comparison with the habitual diet. We sought to determine if 12 months after finishing the MedLey study, the participants maintained their adherence to the MedDiet principles and whether the reduction in the cardiovascular disease (CVD) risk factors that were seen in the trial were sustained. Participants completed a food frequency questionnaire, and a 15-point MedDiet adherence score (MDAS; greater score = greater adherence) was calculated. Home BP was measured over 6 days, BMI was assessed, and fasting plasma triglycerides were measured. The data were analysed using intention-to-treat linear mixed effects models with a group × time interaction term, comparing data at baseline, 2, 4, and 18 months (12 months post-trial). At 18 months (12 months after finishing the MedLey study), the MedDiet group had a MDAS of 7.9 ± 0.3, compared to 9.6 ± 0.2 at 4 months (p < 0.0001), and 6.7 ± 0.2 (p < 0.0001), at baseline. The MDAS in the HabDiet group remained unchanged over the 18-month period (18 months 6.9 ± 0.3, 4 months 6.9 ± 0.2, baseline 6.7 ± 0.2). In the MedDiet group, the consumption of olive oil, legumes, fish, and vegetables remained higher (p < 0.01, compared with baseline) and discretionary food consumption remained lower (p = 0.02) at 18 months. These data show that some MedDiet principles could be adhered to for 12 months after finishing the MedLey trial. However, improvements in cardiometabolic health markers, including BP and plasma triglycerides, were not sustained. The results indicate that further dietary support for behaviour change may be beneficial to maintaining high adherence and metabolic benefits of the MedDiet.
Indexing of Fatty Acids in Poultry Meat for Its Characterization in Healthy Human Nutrition: A Comprehensive Application of the Scientific Literature and New Proposals
Authors: Dal Bosco Alessandro , Cartoni Mancinelli Alice , Vaudo Gaetano , Cavallo Massimiliano , Castellini Cesare , Mattioli Simona
Published: July 2022

Chicken meat is becoming the most consumed in the world for both economic and nutritional reasons; regarding the latter, the lipid profile may play positive or negative roles in the prevention and treatment of diseases. In this study, we define the state of the art of lipid-based nutritional indexes and used the lipid content and fatty acid profile (both qualitative and quantitative) of breast meat of two poultry genotypes with different growth rates and meat traits. Further, we summarize and review the definitions, implications, and applications of nutritional indexes used in recent years and others of our own design to provide a useful tool to researchers working in the field of meat quality (not only in poultry) to select the most appropriate index for their own scientific purposes. All indexes show advantages and disadvantages; hence, a rational choice should be applied to consider the nutritional effect of meat on human health and for a possible assessment of the most suitable rearing systems (genotype, feeding, farming system or postmortem handling).
Helicobacter pylori CagA Protein Regulating the Biological Characteristics of Gastric Cancer through the miR-155-5p/SMAD2/SP1 axis
Authors: Wu Leilei , Jiang Fei , Shen Xiaobing
Published: July 2022

Helicobacter pylori (Hp) is a grade Ι carcinogen of gastric cancer (GC), and its high infection rate seriously affects human health. Cytotoxin-associated gene A (CagA) plays a key role in the carcinogenesis of Hp as one of its main virulence factors. miR-155-5p is abnormally expressed in patients with GC, associated with the occurrence and development of cancer. However, little is known about the association between CagA and miR-155-5p. (1) Background: This study explored the association and mechanism of CagA and miR-155-5p in GC. (2) Methods: The CagA sequence was obtained from the NCBI. After sequence optimization, it was connected to the pcDNA3.1 vector to construct a CagA eukaryotic expression plasmid (pcDNA-CagA). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to investigate the expression of miR-155-5p and CagA in GC cells. The function of CagA on GC cells was detected by CCK8, wound healing, and Transwell assays. Similarly, the function of miR-155-5p was also studied through the above functional experiments after the miR-155-5p overexpression and knockdown models had successfully been constructed. The associations among CagA, miR-155-5p, and SMAD2/SP1 were evaluated using RNA immunoprecipitation (RIP) and rescue experiments. (3) Results: The expression of miR-155-5p was significantly reduced in GC cells, and the expression of miR-155-5p was further reduced after CagA induction. Both overexpressed CagA and knockdown miR-155-5p cell models enhanced malignant transformation, whereas overexpressed miR-155-5p inhibited malignant transformation in vitro. The function of miR-155-5p on GC cells could be influenced by CagA. We also found that the influence of miR-155-5p on SMAD2 and SP1 could be regulated by CagA. (4) Conclusions: CagA potentially regulates the biological function of GC cells through the miR-155-5p/SMAD2/SP1 axis. miR-155-5p could be a therapeutic target for GC related to CagA.
Genetic Characterization of Staphylococcus aureus, Staphylococcus argenteus, and Coagulase-Negative Staphylococci Colonizing Oral Cavity and Hand of Healthy Adults in Northern Japan
Authors: Hirose Mina , Aung Meiji Soe , Fujita Yusuke , Kato Taisei , Hirose Yukito , Yahata Shoko , Fukuda Atsushi , Saitoh Masato , Urushibara Noriko , Kobayashi Nobumichi
Published: July 2022

The spread of methicillin resistance and virulence among staphylococci in the community poses a public health concern. In this study, we investigated the prevalence of Staphylococcus species colonizing the oral cavity and hand (skin) of healthy university students and their phenotypic and genetic characteristics in northern Japan. Among a total of 332 subjects, 6 and 110 methicillin-resistant and susceptible Staphylococcus aureus (MRSA and MSSA, respectively) isolates were recovered from 105 subjects. MRSA isolates were genotyped as CC5, CC8, CC45, and CC59 with SCCmec-IIa or IV, among which an isolate of ST6562 (single-locus variant of ST8) harbored SCCmec-IVa, PVL genes and ACME-I, which are the same traits as the USA300 clone. ST1223 S. argenteus was isolated from the oral cavity and hand of a single student. Coagulase-negative Staphylococcus (CoNS) was recovered from 154 subjects (172 isolates), and classified into 17 species, with S. capitis being the most common (38%), followed by S. warneri (24%) and S. epidermidis (15%), including nine mecA-positive isolates. S. capitis was differentiated into seven clusters/subclusters, and genetic factors associated with the NRCS-A clone (nsr, tarJ, ebh) were detected in 10–21% of isolates. The colonization of the USA300-like MRSA variant and S. capitis with the traits of the NRCS-A clone in healthy individuals was noteworthy.
Investigation of Machine Learning Methods for Prediction of Measured Values of Atmospheric Channel for Hybrid FSO/RF System
Authors: Lapčák Maroš , Ovseník Ľuboš , Oravec Jakub , Zdravecký Norbert
Published: July 2022

This research paper addresses the problems of fiberless optical communication, known as free space optics, in predicting RSSI (Received Signal Strength Indicator) parameters necessary for hard switching in a hybrid FSO/RF (Free Space Optics/Radio Frequency) system. This parameter is used to determine the intensity of the transmitted signal (in our case, a light beam) from one FSO head to another. Since we want to achieve almost 100% reliability, it is important to know the parameters of the transmission environment for the FSO and RF lines. Each of them has its limitations and, as a result, a weather monitoring station is required. The FSO is mostly affected by fog and the concentration of particles in the air, while the RF line is affected by rain and snow. It is precisely due to these influences that it is necessary (based on the mentioned RSSI parameter) to switch using the hard switching method from the primary FSO line to the backup RF line by correctly predicting this value. If the value of the RSSI parameter falls below the critical level—42 dBm—the system automatically switches to the backup RF line. There are several ways we can predict this parameter. One of them is machine learning methods such as decision trees. Our research focused on the prediction of the RSSI parameter, the methods of decision trees and decision trees using the AdaBoost regressor. Since we want to correctly predict the RSSI parameter, it is also necessary to choose the right way to predict it based on the recorded weather conditions. If we want to correctly use the hard switching method in hybrid FSO/RF systems, it is necessary to choose the correct method of predicting the RSSI parameter, which serves as an indicator for switching from the primary FSO line to the secondary RF line. Therefore, we decided to investigate methods of machine learning—the decision tree and the decision tree with the use of an AdaBoost Regressor. The main benefit of this paper is the improvement of existing machine learning methods (decision trees and decision trees using the AdaBoost regressor) for the correct prediction of the RSSI parameter for the needs of hard switching in a hybrid FSO/RF system. The method chosen in this manuscript has very good results. As can be seen in the attached graphs, over a longer period and using correctly selected training data, it is possible to achieve ideal results for the prediction of the RSSI parameter. The tables also show the effectiveness of the prediction, and the fact that it is best to train on either the first- or third-minute data. In the future, it would be appropriate to implement weather prediction or to consider other methods, such as random forests or neural networks.
The Investigation of Underwater Wireless Optical Communication Links Using the Total Reflection at the Air-Water Interface in the Presence of Waves
Authors: Lv Zhijian , He Gui , Yang Hang , Chen Rui , Li Yuxin , Zhang Wenwei , Qiu Chengfeng , Liu Zhaojun
Published: July 2022

With the development of underwater exploration, underwater networking is in urgent demand. At present, underwater wireless optical communication (UWOC) is primarily based on line-of-sight (LOS) communication links. However, the underwater environment is so complicated that LOS communication links are easily affected by a couple of factors such as air bubbles, turbidity, oceanic turbulence, and so on. We put forward novel UWOC links using the total reflection at the air-water interface, which can mitigate those phenomena. This paper aims to investigate a UWOC link based on the total reflection at the air-water interface. In our work, we achieved the maximum data rate of 300 Mb/s and a bit error rate (BER) of 3.10 × 10−3 under the forward error correction (FEC) with the total reflection angle of 7°. Furthermore, we verified the performance of the total reflection-based UWOC links at the air-water interface in the presence of waves and evaluated the impact on the UWOC links when the frequency and amplitude of the waves varied.
Photoacoustic Detection of Pollutants Emitted by Transportation System for Use in Automotive Industry
Authors: Vafaie Reza Hadjiaghaie , Pour Roya Shafiei , Mohammadzadeh Ardashir , Asad Jihad H. , Mosavi Amir
Published: July 2022

In photoacoustic spectroscopy, the signal is inversely proportional to the resonant cell volume. Photoacoustic spectroscopy (PAS) is an absorption spectroscopy technique that is suitable for detecting gases at low concentrations. This desirable feature has created a growing interest in miniaturizing PA cells in recent years. In this paper, a simulation of a miniaturized H-type photoacoustic cell consisting of two buffer holes and a resonator was performed in order to detect CO, NH3, NO, and CH4 pollutants. These gases are the main components of the air pollutants that are produced by the automotive industry. The linear forms of the continuity, Navier–Stokes equations, and the energy equation were solved using the finite element method in a gaseous medium. The generated pressure could be measured by a MEMS sensor. Photoacoustic spectroscopy has proven to be a sensitive method for detecting pollutant gases. The objectives of the measurements were: determining the proper position of the pressure gauge sensor; measuring the frequency response; measuring the frequency response changes at different temperatures; studying the local velocity at the resonant frequency; and calculating the quality factor. The acoustic quality coefficient, acoustic response (pressure), local velocity, frequency response, and the effect of different temperatures on the frequency response were investigated. A frequency response measurement represents the fact that different gases have different resonance frequencies, for which CO and NO gases had values of 23.131 kHz and 23.329 kHz, respectively. The difference between these gases was 200 Hz. NH3 and CH4 gases with values of 21.206 kHz and 21.106 kHz were separable with a difference of 100 Hz. In addition, CO and NO gases had a difference of 2000 Hz compared to NH3 and CH4, which indicates the characteristic fingerprint of the designed cell in the detection of different gases. Better access to high-frequency acoustic signals was the goal of the presented model in this paper.
Security of Optical Beam Splitter in Quantum Key Distribution
Authors: Li Dong-Dong , Tang Yan-Lin , Zhao Yu-Kang , Zhou Lei , Zhao Yong , Tang Shi-Biao
Published: July 2022

The optical beam splitter is an essential device used for decoding in quantum key distribution. The impact of optical beam splitters on the security of quantum key distribution was studied, and it was found that the realistic device characteristics closely influence the error rate introduced by the wavelength-dependent attack on optical beam splitters. A countermeasure, combining device selection and error rate over-threshold alarms, is proposed to protect against such attacks. Beam splitters made of mirror coatings are recommended, and the variation of splitting ratio should be restricted to lower than 1 dB at 1260–1700 nm. For the partial attack scenario where the eavesdropper attacks only a portion of the quantum signal, a modified secure key rate formula is proposed to eliminate the revealed information of the attacked portion. Numerical results show that the QKD system adopting this countermeasure exhibits good performance with a secure key rate of over 10 kbps at 100 km and a maximum transmission distance of over 150 km, with only a small difference from the no-attack scenario. Additionally, a countermeasure to monitor the light intensity of different wavelengths is proposed to protect against the wavelength-dependent attack on optical beam splitters.
Phytochemical Composition, Antioxidant, Antibacterial, and Enzyme Inhibitory Activities of Various Organic Extracts from Apocynum hendersonii (Hook.f.) Woodson
Authors: Abubakar Aminu Shehu , Huang Xiaoyu , Birhanie Ziggiju Mesenbet , Gao Gang , Feng Xinkang , Yu Chunming , Chen Ping , Chen Jikang , Chen Kunmei , Wang Xiaofei , Zhu Aiguo
Published: July 2022

Apocynum hendersonii is a traditional medicinal plant used primarily as tea. It has a potential health benefit from its rich bioactive substances. This study investigated the reactivity of solvents of different polarities (ethanol, ethyl acetate, n-hexane, methanol, and water) extracts of the A. hendersonii leaf. The phytochemical composition of the extracts was evaluated using a Fourier Transform Infrared spectrophotometer (FT-IR), Gas Chromatography-Mass Spectrometry (GC-MS), UHPLC-MS, and Higher Performance Liquid Chromatography (HPLC). The result revealed the presence of medicinally important bioactive constituents, including phenols, flavonoids, and polysaccharides. Methanol extracts exhibited the highest flavonoid contents (20.11 ± 0.85 mg QE/g DW) and the second-highest in terms of phenolic (9.25 ± 0.03 mg GAE/g DW) and polysaccharide (119.66 ± 2.65 mg GE/g DW). It also had the highest antioxidant capacity with 60.30 ± 0.52% and 4.60 ± 0.02 µmol Fe2+ per g DW based on a 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay and ferric reducing antioxidant power (FRAP), respectively. Ethanol extract displayed the maximum antibacterial action against Gram-negative and Gram-positive bacteria and the highest inhibition activity against the enzymes tyrosinase and acetylcholinesterase, followed by methanol extract. The principal component analysis revealed a positive correlation between the constituents, bioactivities, and extracts. The overall result showed A. hendersonii as a rich natural source of antimicrobial and antioxidant bioactive compounds and may be used for future applications in pharmaceuticals and food industries.
Identification of Novel Broad-Spectrum Leaf Rust Resistance Sources from Khapli Wheat Landraces
Authors: Raghunandan K. , Tanwar Jatin , Patil Shivanagouda N. , Chandra Ajay Kumar , Tyagi Sandhya , Agarwal Priyanka , Mallick Niharika , Murukan Niranjana , Kumari Jyoti , Sahu Tanmaya Kumar , Jacob Sherry R. , Kumar Atul , Yadav Suresh , Nyamgoud Sneha , Vinod  , Singh Amit Kumar , Jha Shailendra Kumar
Published: July 2022

Wheat leaf rust caused by Puccinia triticina Eriks is an important disease that causes yield losses of up to 40% in susceptible varieties. Tetraploid emmer wheat (T. turgidum ssp. Dicoccum), commonly called Khapli wheat in India, is known to have evolved from wild emmer (Triticum turgidum var. dicoccoides), and harbors a good number of leaf rust resistance genes. In the present study, we are reporting on the screening of one hundred and twenty-three dicoccum wheat germplasm accessions against the leaf rust pathotype 77-5. Among these, an average of 45.50% of the germplasms were resistant, 46.74% were susceptible, and 8.53% had mesothetic reactions. Further, selected germplasm lines with accession numbers IC138898, IC47022, IC535116, IC535133, IC535139, IC551396, and IC534144 showed high level of resistance against the eighteen prevalent pathotypes. The infection type varied from “;”, “;N”, “;N1” to “;NC”. PCR-based analysis of the resistant dicoccum lines with SSR marker gwm508 linked to the Lr53 gene, a leaf rust resistance gene effective against all the prevalent pathotypes of leaf rust in India and identified from a T. turgidum var. dicoccoides germplasm, indicated that Lr53 is not present in the selected accessions. Moreover, we have also generated 35K SNP genotyping data of seven lines and the susceptible control, Mandsaur Local, to study their relationships. The GDIRT tool based on homozygous genotypic differences revealed that the seven genotypes are unique to each other and may carry different resistance genes for leaf rust.
A Global Model Study of Plasma Chemistry and Propulsion Parameters of a Gridded Ion Thruster Using Argon as Propellant
Authors: Magaldi Bernardo , Karnopp Júlia , da Silva Sobrinho Argemiro , Pessoa Rodrigo
Published: July 2022

This work reports on the (zero-dimensional) global model study of argon plasma chemistry for a cylindrical thruster based on inductively coupled plasma (ICP) whose output has a system of two grids polarized with each other with direct current potential. The global model developed is based on particle and energy balance equations, where the latter considers both charged and neutral species. Thus, the model allows the determination of the neutral gas temperature. Finally, this study also investigated the role of excited species in plasma chemistry especially in the ions production and its implications for propulsion parameters, such as thrust. For this, the study was carried out in two different scenarios: (1) one taking into account the metastable species Arr and Arp (multi-step ionization), and (2) the other without these species (single-step ionization). Results indicates a distinct behavior of electron temperature with radiofrequency (RF) power for the investigated cases. On the other hand, the gas temperature is almost the same for investigated power range of up to 900 W. Concern propulsion analysis, a thrust of 40 mN at 450 W was verified for case (1), which represents a remarkable thrust value for electric thrusters.
A Silicone Resin Coating with Water-Repellency and Anti-Fouling Properties for Wood Protection
Authors: Ding Zehao , Lin Wensheng , Yang Wenbin , Chen Hanxian , Zhang Xinxiang
Published: July 2022

The strong hygroscopicity of wood greatly shortens its service life. Here, a simple impregnation modification approach was used to construct superhydrophobic silicone resin coatings on wood surfaces. Briefly, with hydrofluorosilicone oil (HFSO), tetramethyl tetravinyl cyclotetrasiloxane (V4), and hydrophobic SiO2 from industrial production as raw materials, superhydrophobic wood samples (water contact angle ~160.8°, sliding angle ~3.6°) can be obtained by simply dipping the wood in the HFSO/V4/SiO2 modifier solutions. As a result, the superhydrophobic silicone resin coating constructed on the wood surface still has good water repellency after finger touching, tape peeling, and sandpaper abrasion. When the mass ratio of HFSO to V4 is 2:1, the water absorption of the resulting wood after soaking in water for 24 h is only 29.2%. Further, the resulting superhydrophobic wood shows excellent anti-fouling properties. Finally, we believe that the impregnation modification method proposed in this study can be applied to the protection of cellulose substrates.
Reversible Metal Ion/Complex Binding to Chitin Controlled by Ligand, Redox, and Photochemical Reactions and Active Movement of Chitin on Aquatic Arthropods
Authors: Fränzle Stefan , Blind Felix
Published: July 2022

There is strong adsorption of metal ions and their complexes to chitin, which depends on both the oxidation and complexation states of many of the said elements (whereas others display chemical reactions detectable via electrochemical methods while being retained by chitin); thus, ad- and desorption at ambient water concentrations (often in the nMol/L range) are controlled by the presence and photochemical properties (concerning Eu and probably U and Ag) of mainly biogenic organic matter (both DOC and POC, and DON). With chitin forming the outer hull of mobile organisms (animals), this biopolymer is expected to take part in metal distribution in aquatic (limnetic and riverine) ecosystems. Having studied the attachment of many different elements to both crayfish and grafted (marine shrimp) chitin, with the highest accumulations observed in Bi, V, Ni, and LREEs, one should consider secondary biochemical transformations which take place at different water and sediment levels. After chitin had been embedded into sediment, methanogenesis (which requires Ni), Bi, and Sb biomethylations and photodesorption in the illuminated water column will occur if there are appropriate organics, causing the vertical separation of Eu from other REEs, at least during the daytime. Eutrophication will enhance both the production and especially the photooxidation rates of organics in water because phosphorylated sugars and lipids are formed quantitatively within min P, which enter water and undergo Eu-mediated photooxidation much more readily. Another biopolymer, gelatin, acts as an inert matrix-enhancing organic photooxidation product via Eu, producing chemical waves, indicating autocatalysis upon light impact. From the redox-related photodesorption of metal analytes from chitin, both sensors and devices for (light-assisted) electrochemical energy conversion are being developed by our workgroup. The electrochemical determination of adsorption thermodynamics on chitin is thus directly linked to its applications in environmental monitoring and technology.
A Multi-Regional Collaborative Optimization Model of Emergency Medical Materials for Responding to COVID-19
Authors: Wang Yanyan , Zhu Xiaoxin
Published: July 2022

Medical materials are the most important, fundamental resources necessary for emergency relief of major infectious disease disasters. The scientific and optimal allocation of emergency medical materials is the key to reducing casualties and losses in epidemic regions, and to improving the effectiveness and efficiency of rescue operations. In response to the cross-border characteristics of major infectious diseases, the imbalance of material storage, and the differences of supply across regions, a multi-objective optimization model for a multi-regional collaborative allocation of emergency medical materials was developed. Then, an improved adaptive genetic algorithm (IAGA) was designed and applied to solve the proposed model. Finally, a case study of the collaborative response to the COVID-19 epidemic in the Yangtze River Delta of China was conducted for model verification. The results show that collaborative allocation can improve the material satisfaction rate at demand points, especially under peak demand pressure during the early stage of the response, and can meet all material needs at all demand points in the shortest possible amount of time. The proposed model can achieve the effective integration and mutual sharing of emergency materials across regions, and improve the efficiency of emergency material utilization and rescue efforts. The material allocation scheme considers the difference coefficients in different regions, which is conducive to enhancing the flexibility of decision-making and the practical applicability of collaborative allocation operations. A comparative analysis of the algorithms shows that the proposed IAGA is an effective method for managing large-scale multi-regional emergency material allocation optimization problems, as it has higher solving efficiency, better convergence, and stronger stability.
In-Depth Understanding of ICD Completion Technology Working Principle
Authors: Pinilla Andres , Stanko Milan , Asuaje Miguel , Ratkovich Nicolás
Published: July 2022

The rate-controlled production (RCP) inflow control devices (ICDs) are valves placed in the lower completion of oil and gas wells, capable of autonomously controlling the reservoir inflow. This completion technology self-regulates the inflow of undesired phases, such as water, by choking the flow after the breakthrough event, thus improving the recovery factor and reducing water production. In this context, this article presents a numerical study that describes the working principle of RCP valves based on a computational fluid dynamics (CFD) analysis. The numerical models are based on the conservation equations of fluid flow, the volume of fluid (VOF) multiphase flow model, and the dynamic fluid body interaction (DFBI) model to simulate the valve’s movement caused by its interaction with the flow. This study demonstrates the possibility of studying RCP valves alone or coupled with the whole completion assembly and reservoir rock. The difference in the valve efficiency after considering the entire completion assembly and reservoir rock is 19% less compared with the stand-alone analysis of the valve. Finally, this study provides a deep understanding of the fluid dynamics near the wellbore, the completion assembly, and the RCP valves, along with its chocking, which could be helpful to future researchers interested in improving multiphase flow efficiency in subsurface processes.
Like a Fierce God: Reenvisioning the Enemy in the Legend of Empress Jingū in the Wake of the Mongol Invasions
Authors: Simpson Emily B.
Published: July 2022

The legend of Empress Jingū’s conquest of the Korean peninsula is well-known for its many divine elements. However, the legend’s successful conquest of a foreign enemy has also been key to its longevity. In particular, the Mongol Invasions of the late thirteenth century inspired a renaissance of the Jingū legend in the fourteenth, with the addition of several new motifs. One such motif is Jinrin, a red demon with multiple heads and immense power from the continent who threatens Japan before being slain by Jingū’s husband Emperor Chūai. In this paper, I argue that the Jinrin motif plays an important role in reenvisioning Jingū’s conquest as a war against evil. Though Jinrin may have antecedents in the Buddhist Canon and Japanese mythology, this “fierce god” emerges in the medieval Hachiman tradition in origin narratives and later in regional kagura. Jinrin serves as a visual representation of the threat of the Korean kingdoms and an opportunity for Chūai’s heroism and honorable death, creating a clear juxtaposition between a depraved Korean peninsula and an ethical Japan. Thus, Jinrin provides a vibrant example of how the belief in Japan as land of the gods (shinkoku shisō) galvanized a reinterpretation of Japan, its world, and its history.
An Improved Spatiotemporal Weighted Mean Temperature Model over Europe Based on the Nonlinear Least Squares Estimation Method
Authors: Zhang Bingbing , Wang Zhengtao , Li Wang , Jiang Wei , Shen Yi , Zhang Yan , Zhang Shike , Tian Kunjun
Published: July 2022

Weighted average temperature (Tm) plays a crucial role in global navigation satellite system (GNSS) precipitable water vapor (PWV) retrieval. Aiming at the poor applicability of the existing Tm models in Europe, in the article, we used observations from 48 radiosonde stations over Europe from 2014 to 2020 to establish a weighted average temperature model in Europe (ETm) by the nonlinear least squares estimation method. The ETm model takes into account factors such as ground temperature, water vapor pressure, latitude, and their annual variation, semiannual variation and diurnal variation. Taking the Tm obtained from the radiosonde data by the integration method in 2021 as the reference value, the accuracy of the ETm model was evaluated and compared with the commonly used Bevis model, ETmPoly model, and GPT2w model. The results of the 48 modeled stations showed that the mean bias and root mean square (RMS) values of the ETm model were 0.06 and 2.85 K, respectively, which were 21.7%, 11.5%, and 31.8% higher than the Bevis, ETmPoly, and GPT2w-1 (1° × 1° resolution) models, respectively. In addition, the radiosonde data of 12 non-modeling stations over Europe in 2021 were selected to participate in the model accuracy validation. The mean bias and RMS values of the ETm model were –0.07 and 2.87 K, respectively. Compared with the Bevis, ETmPoly, and GPT2w-1 models, the accuracy (in terms of RMS values) increased by 20.5%, 10.6%, and 35.2%, respectively. Finally, to further verify the superiority of the ETm model, the ETm model, and other Tm models were applied to the GNSS PWV calculation. The ETm model had mean RMSPWV and RMSPWV/PWV values of 0.17 mm and 1.03%, respectively, which were less than other Tm models. Therefore, the ETm model has essential applications in GNSS PWV over Europe.
Recognition Method of Massage Techniques Based on Attention Mechanism and Convolutional Long Short-Term Memory Neural Network
Authors: Zhu Shengding , Lei Jingtao , Chen Dongdong
Published: July 2022

Identifying the massage techniques of the masseuse is a prerequisite for guiding robotic massage. It is difficult to recognize multiple consecutive massage maps with a time series for current human action recognition algorithms. To solve the problem, a method combining a convolutional neural network, long-term neural network, and attention mechanism is proposed to identify the massage techniques in this paper. First, the pressure distribution massage map is collected by a massage glove, and the data are enhanced by the conditional variational auto-encoder. Then, the features of the massage map group in the spatial domain and timing domain are extracted through the convolutional neural network and the long- and short-term memory neural network, respectively. The attention mechanism is introduced into the neural network, giving each massage map a different weight value to enhance the network extraction of data features. Finally, the massage haptic dataset is collected by a massage data acquisition system. The experimental results show that a classification accuracy of 100% is achieved. The results demonstrate that the proposed method could identify sequential massage maps, improve the network overfitting phenomenon, and enhance the network generalization ability effectively.
A Machine Learning Approach for Movement Monitoring in Clustered Workplaces to Control COVID-19 Based on Geofencing and Fusion of Wi-Fi and Magnetic Field Metrics
Authors: Abd El-Haleem Ahmed M. , Mohamed Noor El-Deen M. , Abdelhakam Mostafa M. , Elmesalawy Mahmoud M.
Published: July 2022

The ubiquitous existence of COVID-19 has required the management of congested areas such as workplaces. As a result, the use of a variety of inspiring tools to deal with the spread of COVID-19 has been required, including internet of things, artificial intelligence (AI), machine learning (ML), and geofencing technologies. In this work, an efficient approach based on the use of ML and geofencing technology is proposed to monitor and control the density of persons in workplaces during working hours. In particular, the workplace environment is divided into a number of geofences in which each person is associated with a set of geofences that make up their own cluster using a dynamic user-centric clustering scheme. Different metrics are used to generate a unique geofence digital signature (GDS) such as Wi-Fi basic service set identifier, Wi-Fi received signal strength indication, and magnetic field data, which can be collected using the person’s smartphone. Then, these metrics are utilized by different ML techniques to generate the GDS for each indoor geofence and each building geofence as well as to detect whether the person is in their cluster. In addition, a Layered-Architecture Geofence Division method is considered to reduce the processing overhead at the person’s smartphone. Our experimental results demonstrate that the proposed approach can perform well in a real workplace environment. The results show that the system accuracy is about 98.25% in indoor geofences and 76% in building geofences.
IoT-Based Monitoring System Applied to Aeroponics Greenhouse
Authors: Méndez-Guzmán Hugo A. , Padilla-Medina José A. , Martínez-Nolasco Coral , Martinez-Nolasco Juan J. , Barranco-Gutiérrez Alejandro I. , Contreras-Medina Luis M. , Leon-Rodriguez Miguel
Published: July 2022

The inclusion of the Internet of Things (IoT) in greenhouses has become a fundamental tool for improving cultivation systems, offering information relevant to the greenhouse manager for decision making in search of optimum yield. This article presents a monitoring system applied to an aeroponic greenhouse based on an IoT architecture that provides user information on the status of the climatic variables and the appearance of the crop in addition to managing the irrigation timing and the frequency of visual inspection using an application developed for Android mobile devices called Aeroponics Monitor. The proposed IoT architecture consists of four layers: a device layer, fog layer, cloud layer and application layer. Once the information about the monitored variables is obtained by the sensors of the device layer, the fog layer processes it and transfers it to the Thingspeak and Firebase servers. In the cloud layer, Thingspeak analyzes the information from the variables monitored in the greenhouse through its IoT analytic tools to generate historical data and visualizations of their behavior, as well as an analysis of the system’s operating status. Firebase, on the other hand, is used as a database to store the results of the processing of the images taken in the fog layer for the supervision of the leaves and roots. The results of the analysis of the information of the monitored variables and of the processing of the images are presented in the developed app, with the objective of visualizing the state of the crop and to know the function of the monitoring system in the event of a possible lack of electricity or a service line failure in the fog layer and to avoid the loss of information. With the information about the temperature of the plant leaf and the relative humidity inside the greenhouse, the vapor pressure deficit (VPD) in the cloud layer is calculated; the VPD values are available on the Thingspeak server and in the developed app. Additionally, an analysis of the VPD is presented that demonstrates a water deficiency from the transplanting of the seedling to the cultivation chamber. The IoT architecture presented in this paper represents a potential tool for the study of aeroponic farming systems through IoT-assisted monitoring.
Secure Spectrum Access, Routing, and Hybrid Beamforming in an Edge-Enabled mmWave Massive MIMO CRN-Based Internet of Connected Vehicle (IoCV) Environments
Authors: Pari Deepanramkumar , Natarajan Jaisankar
Published: July 2022

A cognitive radio network (CRN) is integrated with the Internet of Connected Vehicles (IoCV) in order to address spectrum scarcity and communication reliability issues. However, it is limited, possessing less throughput, a low packet delivery ratio, high latency, and high mobility in the spectrum. In this research study, the existing issues are addressed by proposing a 6G cognitive radio network–Internet of connected vehicles (6GCRN–IoCV) approach. Initially, all the entities such as secondary users (SUs), primary users (PUs), and pedestrians are authenticated in blockchain to ensure security. The edge-assisted roadside units (ERSU) initiate clustering only for authenticated SUs using the improved DBSCAN algorithm in consideration of several metrics. The ERSU then generates an intersection-aware map using the spatial and temporal-based logistic regression algorithm (STLR) to reduce collisions in the intersection. The spectrum utilization is improved by performing spectrum sensing in which all the SUs involved in spectrum sensing use lightweight convolutional neural networks (Lite-CNN) in consideration of several metrics and provide the sensing report to the fusion center (FC) in an encrypted manner to reduce the spectrum scarcity and security issues. The communications between the SUs are necessary to avoid risks in the IoCV environment. Hence, optimal routing is performed using the Dingo Optimization Algorithm (DOA), which increases throughput and packet delivery ratio. Finally, communication reliability is enhanced by performing hybrid beamforming, and this exploits the multi-agent-based categorical Deep-Q Network (categorical DQN), which increases spectral efficiency based on its adaptive intelligent behavior. The proposed study is simulated using the SUMO and OMNeT++ simulation tools and the performances are validated with existing works using several performance metrics. The result of the simulation shows that the proposed work performs better than the existing approaches.
Plant Tissue Modelling Using Power-Law Filters
Authors: Gadallah Samar I. , Ghoneim Mohamed S. , Elwakil Ahmed S. , Said Lobna A. , Madian Ahmed H. , Radwan Ahmed G.
Published: July 2022

Impedance spectroscopy has became an essential non-invasive tool for quality assessment measurements of the biochemical and biophysical changes in plant tissues. The electrical behaviour of biological tissues can be captured by fitting its bio-impedance data to a suitable circuit model. This paper investigates the use of power-law filters in circuit modelling of bio-impedance. The proposed models are fitted to experimental data obtained from eight different fruit types using a meta-heuristic optimization method (the Water Cycle Algorithm (WCA)). Impedance measurements are obtained using a Biologic SP150 electrochemical station, and the percentage error between the actual impedance and the fitted models’ impedance are reported. It is found that a circuit model consisting of a combination of two second-order power-law low-pass filters shows the least fitting error.
3D Measurement Method for Saturated Highlight Characteristics on Surface of Fuel Nozzle
Authors: Li Yeni , Hou Liang , Chen Yun
Published: July 2022

Saturated highlights on metal surfaces reduce the detection accuracy of fuel nozzles. In this paper, we propose an image inpainting method with a saturated highlight based on the statistics of similar patches used in prior segmentation of the subregion. The sequence image acquisition is based on the shape from focus in the five-axis platform. By our method, the focus measure (FM) operator and the window size are evaluated using the sharpness evaluation curve and calculating time. We observe that the detection accuracy is improved when the highlight area is filled by the highlight-free area within the same segmentation region. There are fewer deviation points in the three-dimensional (3D) point cloud that are extracted from the sequence images. The inlet circle and the outlet circle of the fuel nozzle are both detected by the two-dimensional (2D) Hough Transform (HT) method. Our experiments show that the method yields better results in 3D detection of the key parameters of fuel nozzles with the saturated highlight characteristics.