bluuebunny/crossref_metadata_2025 huggingface dataset:
Nitrous oxide emissions from productive and degraded potato fields in the Fraser Valley delta of British Columbia
Authors: Chizen Chantel J. , Krzic Maja , Black T. Andrew , Jassal Rachhpal S. , Smukler Sean M.
Published: May 2022

Soil nitrous oxide (N2O) emissions and potato yield were evaluated under 0, 90, and 120 kg N ha−1 fertilizer rates and two planting dates, at productive and degraded fields in the Fraser Valley delta. During the growing season, N2O emissions were comparable among N fertilizer rates. Following November rainfall, N2O emissions increased by three times with 120 kg N ha−1. In the degraded field, yield did not respond to the increasing N fertilizer rates. These findings suggest that lower N fertilizer rates, especially in fields with degraded soils, can lower N2O emissions from British Columbia potato production.
ANALYSIS OF GLOBAL VALUE CHAIN PARTICIPATION AND WORKERS’ WAGES IN THAILAND: A MICRO-LEVEL ANALYSIS
Authors: KORWATANASAKUL UPALAT , BAEK YOUNGMIN , MAJOE ADAM
Published: May 2022

This study examines the relationship between global value chain (GVC) participation and workers’ wages and the disparities in wage benefits from GVC participation. It employs a pseudo-panel approach to treat endogeneity biases, utilizing pseudo-panel data constructed from the Thai Labour Force Survey, 1995–2011. The results show that GVC participation, on average, induces higher hourly wages through forward and backward linkages. Although forward linkages inclusively and positively affect workers’ wages, the wage benefits of backward linkages accrue to particular demographic groups. Therefore, government policies must be designed to promote GVC participation, particularly forward linkages, and support disadvantaged demographic groups facing disproportionate wage effects.
ON THE EFFECTS OF OIL PRICE SHOCKS ON KOREA’S TRADE BALANCE WITH ITS TOP THREE PARTNERS: A STRUCTURAL VAR ANALYSIS
Authors: RAN SHUANG , BAEK JUNGHO
Published: May 2022

The primary contribution of this paper is to investigate the impacts that three components of oil shocks – oil supply shocks, aggregate demand shocks, and oil-specific demand shocks – have on three measures of Korea’s trade balances – oil, non-oil, and total trade balances – with its top three trading partners – China, the United States and Japan. We reveal that aggregate demand shocks have the greatest impact on Korea’s trade balances, while oil supply shocks have negligible impacts. Additionally, the overall impact of the three oil shocks on Korea’s trade balances with its top three partners appears to rely on the response of the non-oil trade balance.
Energy contents of stringy charged black hole in general relativity and teleparallel gravity
Authors: Mourad M. F. , Abdelgaber M.
Published: May 2022

In the framework of general relativity (GR) and teleparallel equivalent to GR (TEGR), we investigate the energy–momentum localization of a stringy charged black hole by using Bergman–Thompson’s prescription and the Papapetrou’s prescription. Moreover, we investigate the gravitational energy–momentum (GEM) in TEGR. Our results are consistent with the results of previous studies. Finally, we calculate the GEM flux and gravitational center of mass in TEGR.
SDN Framework for Mitigating Time-Based Delay Attack
Authors: Ramani Sagar V. , Jhaveri Rutvij H.
Published: May 2022

Due to recent cyberattacks on the Cyber-Physical Systems, the traditional security schemes face difficulties in dealing with such attacks as the attackers nowadays have adopted many intelligent mechanisms involving advanced information and communication technologies to launch attacks. This recent type of attack provides a significant impact on the resiliency of the software-defined networks. In this paper, we present a real-time delay attack on fault-resilient software-defined networks. The main objective of the time delay attack is to reduce the resiliency in the SDN-RM by adding a delay in the LLDP packets in the OpenFlow Switch. This addition of delay causes degradation in the network performance resulting in a low success rate in the SDN-RM mechanisms. In this paper, we present a machine learning-based detection system for detecting the attacks. The integration of machine learning techniques with network resilience solutions can effectively address the issue of predicting and classifying the LLDP packets that are delayed at a particular switch. Another issue is the detection of the malicious switch at the controller side which results in the improvement of the resiliency in SDN-RM. We propose a machine learning solution to detect the anomalies that are present in the topology and can be detected at the controller side. We use machine learning models such as k-nearest neighbors, support vector machines (SVM), Random Forest, and decision trees to detect the poisonous switches. The delay-based time attack detection system (DTA-DS) helps the controller to take a reactive decision to improve resilience by detecting poisonous network switches. With the help of the preventive approach, we achieve high-fault resiliency in fault resilient-based software-defined networks.
A numerical invariant of oriented links
Authors: Zhang Kai , Yang Zhiqing
Published: May 2022

In this paper, the authors obtain a numerical invariant [Formula: see text] of oriented links. It satisfies a non-homogeneous skein relation, and [Formula: see text] is additive under the connected sum operation. We give an obstruction for two links to be 6-equivalent, derived from this numerical invariant.
A Blockchain-Based Framework for Transparent, Secure, and Verifiable Online Examination System
Authors: Sadayapillai Banupriya , Kottursamy Kottilingam
Published: May 2022

The goal of online examination is to ensure convenience, scalability, expanded reach, and customization. Despite the popularity of online exams, there have been some demonstrations against using them. The existing system is vulnerable and faces failures like question paper leakage, answer deception, trying to forge scorecards, difficulty in ensuring the integrity and consistency of scorecards by the exam board, and so on. Blockchain technology is the greatest and unsurpassed option for continuous authentication, confidentiality, and reliability. A blockchain-based framework for an online examination system is proposed to collect, register, and maintain a growing list of records using cryptography. It is also a peer-to-peer system that manages or stores time-stamped transactions such that no one can alter them. The proposed model combines time lock and multi-signature techniques and ensures the encrypted questions are locked till the exam starts, candidates’ answers are not altered, and scorecards are not manipulated. The system is open to the public, and the system’s processes are transparent. The costs associated are analyzed with the suggested solution’s on-chain and off-chain evaluation.
The Limitations of Optimization from Samples
Authors: Balkanski Eric , Rubinstein Aviad , Singer Yaron
Published: May 2022

In this article, we consider the following question: Can we optimize objective functions from the training data we use to learn them? We formalize this question through a novel framework we call
optimization from samples
(
OPS
). In
OPS
, we are given sampled values of a function drawn from some distribution and the objective is to optimize the function under some constraint.

While there are interesting classes of functions that can be optimized from samples, our main result is an impossibility. We show that there are classes of functions that are statistically learnable and optimizable, but for which no reasonable approximation for optimization from samples is achievable. In particular, our main result shows that there is no constant factor approximation for maximizing coverage functions under a cardinality constraint using polynomially-many samples drawn from any distribution.

We also show tight approximation guarantees for maximization under a cardinality constraint of several interesting classes of functions including unit-demand, additive, and general monotone submodular functions, as well as a constant factor approximation for monotone submodular functions with bounded curvature.
Bayesian Hypothesis Testing Illustrated: An Introduction for Software Engineering Researchers
Authors: Erdogmus Hakan
Published: May 2022

Bayesian data analysis is gaining traction in many fields, including empirical studies in software engineering. Bayesian approaches provide many advantages over traditional, or frequentist, data analysis, but the mechanics often remain opaque to beginners due to the underlying computational complexity. Introductory articles, while successful in explaining the theory and principles, fail to provide a totally transparent operationalization. To address this gap, this tutorial provides a step-by-step illustration of Bayesian hypothesis testing in the context of software engineering research using a fully developed example and in comparison to the frequentist hypothesis testing approach. It shows how Bayesian analysis can help build evidence over time incrementally through a family of experiments. It also discusses chief advantages and disadvantages in an applied manner. A
figshare
package is provided for reproducing all calculations.
Personal Space in Human-Robot Interaction at Work: Effect of Room Size and Working Memory Load
Authors: Leichtmann Benedikt , Lottermoser Albrecht , Berger Julia , Nitsch Verena
Published: May 2022

A recent literature review on personal space in human-robot interaction identified a research gap for the influence of contextual factors. At the same time, psychological research on interpersonal distancing and theoretical considerations based on compensatory control models suggest the importance of considering these factors in robot path planning. To address this gap, we tested the effect of room size and working memory load on participants’ comfort distance toward an approaching robot. In a preregistered 3 × 2 within-subject design,
N
= 72 participants were approached by a mobile manufacturing robot in a corridor with varying room size and with and without a cognitive secondary task. As dependent variables, comfort distance, arousal, and perceived control were measured. While room size and working memory load had no significant direct effect on comfort distance, participants felt higher arousal and lower control in smaller rooms and in conditions with high working memory load, which in turn caused larger comfort distances (indirect effect). With experience, comfort distances decreased. Based on the indirect effects, future studies should test the effect of more extreme manipulations on comfort distances. Robots should adapt their path planning by keeping larger distances toward human workers in stressful environments to avoid discomfort.
The glycosaminoglycan interactome 2.0
Authors: Vallet Sylvain D. , Berthollier Coline , Ricard-Blum Sylvie
Published: May 2022

Glycosaminoglycans (GAGs) are complex linear polysaccharides, which are covalently attached to core proteins (except for hyaluronan) to form proteoglycans. They play key roles in the organization of the extracellular matrix, and at the cell surface where they contribute to the regulation of cell signaling and of cell adhesion. To explore the mechanisms and pathways underlying their functions, we have generated an expanded dataset of 4,290 interactions corresponding to 3,464 unique GAG-binding proteins, four times more than the first version of the GAG interactome (Vallet, Clerc, and Ricard-Blum. J Histochem Cytochem 69: 93–104, 2021). The increased size of the GAG network is mostly due to the addition of GAG-binding proteins captured from cell lysates and biological fluids by affinity chromatography and identified by mass spectrometry. We review here the interaction repertoire of natural GAGs and of synthetic sulfated hyaluronan, the specificity and molecular functions of GAG-binding proteins, and the biological processes and pathways they are involved in. This dataset is also used to investigate the differences between proteins binding to iduronic acid-containing GAGs (dermatan sulfate and heparin/heparan sulfate) and those interacting with GAGs lacking iduronic acid (chondroitin sulfate, hyaluronan, and keratan sulfate).
Key amino acids alter activity and trafficking of a well-conserved olfactory receptor
Authors: Xu Jiaojiao , Pluznick Jennifer L.
Published: May 2022

In this study, we elucidate factors that regulate the trafficking and activity of a well-conserved olfactory receptor (OR), olfactory receptor 558 (Olfr558), and its human ortholog olfactory receptor 51E1 (OR51E1). Results indicate that butyrate activates Olfr558/OR51E1 leading to the production of cAMP, and evokes Ca2+ influx. We also find olfactory G protein (Golf) increases cAMP production induced by Olfr558/OR51E1 activation but does not affect trafficking. Given the 93% sequence identity between OR51E1 and Olfr558, it is surprising to note that OR51E1 has significantly more surface expression yet similar total protein expression. We find that replacing the Olfr558 N-terminus with that of OR51E1 significantly increases trafficking; in contrast, there is no change in surface expression conferred by the OR51E1 TM2, TM3, or TM4 domains. A previous analysis of human OR51E1 single nucleotide polymorphisms (SNPs) identified an A156T mutant primarily found in South Asia as the most abundant (albeit still rare). We find that the OR51E1 A156T mutant has reduced surface expression and cAMP production without a change in total protein expression. In sum, this study of a well-conserved olfactory receptor identifies both protein regions and specific amino acid residues that play key roles in protein trafficking and also elucidates common effects of Golf on the regulation of both the human and murine OR.
mRatBN7.2: familiar and unfamiliar features of a new rat genome reference assembly
Authors: de Jong Tristan V. , Chen Hao , Brashear Wesley A. , Kochan Kelli J. , Hillhouse Andrew E. , Zhu Yaming , Dhande Isha S. , Hudson Elizabeth A. , Sumlut Mary H. , Smith Melissa L. , Kalbfleisch Theodore S. , Doris Peter A.
Published: May 2022

Rat genomic tools have been slower to emerge than for those of humans and mice and have remained less thorough and comprehensive. The arrival of a new and improved rat reference genome, mRatBN7.2, in late 2020 is a welcome event. This assembly, like predecessor rat reference assemblies, is derived from an inbred Brown Norway rat. In this “user” survey we hope to provide other users of this assembly some insight into its characteristics and some assessment of its improvements as well as a few caveats that arise from the unique aspects of this assembly. mRatBN7.2 was generated by the Wellcome Sanger Institute as part of the large Vertebrate Genomes Project. This rat assembly has now joined human, mouse, chicken, and zebrafish in the National Center for Biotechnology Information (NCBI)’s Genome Reference Consortium, which provides ongoing curation of the assembly. Here we examine the technical procedures by which the assembly was created and assess how this assembly constitutes an improvement over its predecessor. We also indicate the technical limitations affecting the assembly, providing illustrations of how these limitations arise and the impact that results for this reference assembly.
New Degree‐Based Topological Indices of Toroidal Polyhex Graph by Means of M‐Polynomial
Authors: Afzal Farkhanda , Zeeshan Mohammad , Afzal Deeba , Munawar Sufian , Thapa Dhan Kumari , Mirza Alina
Published: May 2022

Graph theory is the principal field of mathematics. In this manuscript, we have discussed the toroidal polyhex graph. Some new indices such as reduced reciprocal randic, arithmetic geometric, SK, SK1, SK2 indices, First Zagrab, the general sum‐connectivity, SCIλ, and the forgotten index have been used. We have computed the closed form of topological indices of toroidal polyhex graph via M‐Polynomial.
Automatic Detection of Epilepsy Based on Entropy Feature Fusion and Convolutional Neural Network
Authors: Sun Yongxin , Chen Xiaojuan
Published: May 2022

Epilepsy is a neurological disorder, caused by various genetic and acquired factors. Electroencephalogram (EEG) is an important means of diagnosis for epilepsy. Aiming at the low efficiency of clinical artificial diagnosis of epilepsy signals, this paper proposes an automatic detection algorithm for epilepsy based on multifeature fusion and convolutional neural network. Firstly, in order to retain the spatial information between multiple adjacent channels, a two-dimensional Eigen matrix is constructed from one-dimensional eigenvectors according to the electrode distribution diagram. According to the feature matrix, sample entropy SE, permutation entropy PE, and fuzzy entropy FE were used for feature extraction. The combined entropy feature is taken as the input information of three-dimensional convolutional neural network, and the automatic detection of epilepsy is realized by convolutional neural network algorithm. Epilepsy detection experiments were performed in CHB-MIT and TUH datasets, respectively. Experimental results show that the performance of the algorithm based on spatial multifeature fusion and convolutional neural network achieves excellent results.
An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSD
Authors: Peng Dongxiao
Published: May 2022

The accuracy of English pronunciation is the key index to evaluate the quality of English teaching. Correct pronunciation and smooth language flow are the expectations of every student for English learning. Aiming at the poor effect and slow speed of the original SSD (Single Shot MultiBox Detector) algorithm in English teaching pronunciation detection, this paper proposes a clustering and improved SSD algorithm for English teaching pronunciation detection and recognition. The algorithm improves the concept module to enhance the feature extraction ability of the network and improve the detection speed. Meanwhile, it integrates multiscale features to realize multilayer multiplexing and equalization of features, so as to improve the detection effect of small target sound. This algorithm extracts more features by introducing channel attention mechanism, which increases the detection accuracy while reducing computation. In order to optimize the network’s ability to extract target location information, K-means clustering method is used to set the default parameters that are more in line with the characteristics of target samples. The experimental results showed that the proposed algorithm can accurately evaluate the pronunciation quality of reading aloud, so as to effectively reflect the oral English level of the reader.
Scrutinizing Deleterious Nonsynonymous SNPs and Their Effect on Human POLD1 Gene
Authors: Bappy Md. Nazmul Islam , Roy Anindita , Rabbi Md Gulam Rabbany , Jahan Nusrat , Chowdhury Fahmida Akther , Hoque Syeda Farjana , Sajib Emran Hossain , Khan Parvez , Hossain Ferdaus Mohd Altaf , Zinnah Kazi Md. Ali
Published: May 2022

POLD1 (DNA polymerase delta 1, catalytic subunit) is a protein-coding gene that encodes the large catalytic subunit (POLD1/p125) of the DNA polymerase delta (Polδ) complex. The consequence of missense or nonsynonymous SNPs (nsSNPs), which occur in the coding region of a specific gene, is the replacement of single amino acid. It may also change the structure, stability, and/or functions of the protein. Mutation in the POLD1 gene is associated with autosomal dominant predisposition to colonic adenomatous polyps, colon cancer, endometrial cancer (EDMC), breast cancer, and brain tumors. These de novo mutations in the POLD1 gene also result in autosomal dominant MDPL syndrome (mandibular hypoplasia, deafness, progeroid features, and lipodystrophy). In this study, genetic variations of POLD1 which may affect the structure and/or function were analyzed using different types of bioinformatics tools. A total of 17038 nsSNPs for POLD1 were collected from the NCBI database, among which 1317 were missense variants. Out of all missense nsSNPs, 28 were found to be deleterious functionally and structurally. Among these deleterious nsSNPs, 23 showed a conservation scale of >5, 2 were predicted to be associated with binding site formation, and one acted as a posttranslational modification site. All of them were involved in coil, extracellular structures, or helix formation, and some cause the change in size, charge, and hydrophobicity.
Evaluating Gas-Oil Ratio Behavior of Unconventional Wells in the Uinta Basin
Authors: Zhao Yajie , Nohavitza Jack , Williams Ryan , Yu Wei , Liu Chuxi , Ganjdanesh Reza , Sepehrnoori Kamy
Published: May 2022

On account of low matrix permeability and porosity, the fluid phase behavior in tight oil reservoirs significantly differs from the conventional plays, which increases the challenges of evaluating the well performance and providing reliable production prediction. One of the most important efforts is to investigate the behavior of unconventional well gas-to-oil ratio (GOR). The growth trend of GOR is always considered as a principal reference to modify the production strategies and enhance the well productivity. In this paper, long-term GOR (20 years) behavior of an unconventional well model was evaluated by a set of comprehensive sensitivity studies. This model’s dimensions and reservoir properties are based on information of the Altamont-Bluebell field in the Uinta Basin. The simulation results established a general framework for interpreting the GOR behavior. Key drivers such as completion designs, reservoir, and fracture properties are investigated. This study provides some key insights into the GOR behaviors, such as the high sensitivity of the hydraulic fracture properties, including fracture conductivity and effective fracture half-length. The GOR behavior could be considerably different on various conductivity values or fracture lengths, resulting from the conductivity impact of phase movement and the pressure transition along the fracture. The fracture design factors like drawdown scenario and cluster spacing also play indispensable roles in impacting the GOR response, where a less aggressive drawdown rate can help to delay the GOR increase at an early stage; a widening spacing also can mitigate the rise of GOR and keep it at low value during the whole production period. The impact from natural fractures is also examined and discussed for the first time, including the effect of natural fracture numbers and conductivity, where the latter variable is considered as a more effective contributor to the GOR prediction. The findings presented in this work promote a better understanding of the GOR behaviors in tight oil reservoirs. Results and discussion in this paper allow a more accurate forecasting production to improve the reservoir management efficiency and provide multiple valuable insights to guide the field development in future projects.
Numerical Analysis of Subgrade Behavior under a Dynamic Maglev Train Load
Authors: Wang Wubin , Deng Zhixing , Li Yandong , Huang Zhichao , Niu Yunbin , Xie Kang
Published: May 2022

Medium‐low‐speed maglevs are increasingly used in the urban rail transit industry because of their advantages, such as low noise and low energy consumption. In this study, a finite element analysis of the responses of the subgrade that supports a medium‐low‐speed maglev structure under a dynamic maglev load is presented. First, the finite element analysis considers a low‐lying structure with different elastic moduli. Then, the attenuation laws of the dynamic stress and dynamic deformation for different depth ranges of the subgrade under the rail beam are analyzed. In addition, the magnitude of the influence of the dynamic load is clarified. The results lead to a recommendation of a base bed thickness of 1.5 m, graded gravel or group A filler as the surface layer of filler, and gravel soil as the bottom layer. This study provides theoretical support for the construction design of a subgrade structure under the rail beam of a low‐lying maglev line.
Analytical Solution for Consolidation of Vertical Drains‐Impervious Piles with Multiple Composite Foundations under Nonuniform Initial Pore Pressure and Time‐Dependent Well Resistance
Authors: Zhang Yuguo , Zhao Yamin
Published: May 2022

For the vertical drains‐impervious pile multiple composite foundation consolidation problem, the effects of nonuniform distribution of initial pore pressure, variation of well resistance with time, and combined radial and vertical seepage in the soil are considered, and a consolidation control equation based on the assumption of equal strain is established based on the axisymmetric model. The analytical solution method is used to give an analytical solution for the consolidation of multiple composite foundations with vertical drains‐impervious piles with trapezoidal, rectangular, positive triangle, and inverted triangular distribution of initial pore pressure. The reasonableness of the solution of this study is verified by degradation analysis. According to the solution of the study, the consolidation properties of the multicomposite foundation were analyzed. The results show that the initial pore pressure is faster to consolidate with trapezoidal distribution than with rectangular distribution, the slowest to consolidate with positive triangular distribution, and the fastest to consolidate with inverted triangular distribution, and the larger the initial pore pressure value at the base of the soil layer, the slower the consolidation; the consolidation rate of the foundation all decreases with the increase of the well resistance factor, and the change of the well resistance mainly has an important influence on the later consolidation of the foundation; the vertical permeability coefficient of the soil has a greater influence on the consolidation of the foundation at the initial stage when the foundation thickness is small, and the vertical permeability coefficient of the soil has greater influence on the consolidation of the foundation at the later stage when the foundation thickness is large; the consolidation rate of foundation increases with the increase of replacement rate of impervious pile, compression modulus, and vertical permeability coefficient of soil. Compared with the single pile foundation, the multicomposite foundation can significantly improve the consolidation rate of foundation.
Influence of Dual-Credit Policy on the R&D Cooperation Mode of Chinese Auto Industry
Authors: He Qing , Zhao Hua
Published: May 2022

The dual-credit policy is regarded as an important measure in the postsubsidy era of energy conservation and emission reduction in the auto industry and is concerned with all aspects of society. In this paper, a research and development cooperation model of the duopoly supply chain between suppliers and manufacturers in the automotive industry is constructed, and the influence of the double integral policy on the research and development cooperation between suppliers and manufacturers in the automotive industry is discussed based on the power perspective theory in the supply chain. The results show that cooperation is more effective than noncooperation in promoting both parties’ R&D investment in fuel economy, as well as the fuel economy of the final product. The government should encourage R&D cooperation in the upstream and downstream of the supply chain of the automotive industry. The influence on the R&D cooperation between the supplier and the manufacturer was the combined effect of fuel consumption saving. The government’s intention to formulate a dual-credit policy to guide the R&D cooperation behavior in the auto industry supply chain should consider not only the impact of credit unit price but also the public’ consciousness of fuel saving and environmental protection. The combined effect of fuel consumption saving on the R&D cooperation led by different powers, which meant that the government was aiming to encourage R&D cooperation, should consider different situations in the auto industry supply chain to formulate the dual-credit policy to adjust the supply and demand relationship of the dual-credit policy to affect the credit unit price, thus affecting the combined effect of fuel consumption saving, encouraging R&D cooperation in the auto industry supply chain, and realizing energy conservation and emission reduction.
A Systematic Review and Network Meta-Analysis about the Efficacy and Safety of Tripterygium wilfordii Hook F in Rheumatoid Arthritis
Authors: Wang Hai-long , Zhao Qi , Li Wei , Zhu Hua-chao , Lv Liu , Zhu Zhen-hong , Wang Xi-xi , Yang Zheng-zheng , Ma Yu-cao , Liu Ming-xuan , Wang Yi-wen , Lai Hezheng , Liu Chun-ping , Yang Yu-zheng
Published: May 2022

Objective. This study aims to evaluate the efficacy of various conventional synthetic DMARDs, including Tripterygium wilfordii Hook F (TwHF) for treating rheumatoid arthritis (RA) by network meta-analysis. Methods. We retrieved the related literature from online databases and supplemented it by using a manual retrieval method. Data was extracted from the literature and analyzed with STATA software. Results. A total of 21 trials (5,039 participants) were identified. Assessment of ACR20 response found that TwHF combined with methotrexate (MTX) had the greatest probability for being the best treatment option among the treatments involved, while TwHF used singly was second only to TwHF combined with MTX. Assessment of ACR50 response found that TwHF combined with MTX ranked second in all treatment options after cyclosporine A (CsA) combined with leflunomide (LEF) and TwHF alone, followed by TwHF combined with MTX. Assessment of ACR70 response found that CsA combined with LEF ranked first, TwHF combined with LEF ranked second, TwHF combined with MTX ranked third, and TwHF used singly ranked fourth. In the safety analysis, TwHF had the least probability of adverse event occurrence, followed by TwHF combined with MTX, which ranked first and second, respectively. Conclusion. Compared with the current csDMARDs for treating RA, the efficacy of TwHF was clear, and TwHF combined with MTX performed well under various endpoints. In the future, large, rigorous, and high-quality RCTs are still needed to confirm the benefits of TwHF therapy on RA.
Morphological and Physiological Characterization of Cassava Genotypes on Dry Land of Ultisol Soil in Indonesia
Authors: Diaguna Ridwan , Suwarto  , Santosa Edi , Hartono Arief , Pramuhadi Gatot , Nuryartono Nunung , Yusfiandayani Roza , Prartono Tri
Published: May 2022

Indonesia has a large cassava diversity, but the tolerant cultivars on drought areas have not been well recorded. Candidate mapping can begin with morphological and physiological characterization. This study aimed to map cassava’s genetic diversity, determining the key phenotype to distinguish genotypes, physiological adaptation, and high-yield candidates under environmental stress. A total of 29 genotypes were clustered into 5 groups. A specific group for genotype from same site was not found. The differences and relations among genotypes were very clear, demonstrating cassava’s genetic diversity in Indonesia. The key group characteristics are upward petiole orientation (G1), nine lobes (G2), prominent foliar scars (G3), winding lobe (G4), and elliptic-lanceolate (G5). A total of 19 genotypes had a number of storage root >10 storage roots, 20 genotypes had a weight of storage root >2 kg/plant, and 3 genotypes had >4 kg/plant. Morphological and physiological trait determination is relevant to contribute to high-yield cassava breeding in dry areas. The morphological characteristics of well-adapted plants were plant height, lobe characteristics, and petiole orientation, while the physiological traits were chlorophyll index, transpiration rate, and photosynthesis rate.
Effect of Solar Drying and Vinegar Pretreatment on the Antioxidant Properties and Bioactive Compounds of Sliced Ginger
Authors: Amoah Roseline Esi , Kalakandan Sureshkumar , Wireko-Manu Faustina Dufie , Oduro Ibok , Saalia Firibu Kwesi , Ellis William Otoo , Krishnamoorrthy Srinivasan
Published: May 2022

A comparison of concrete solar dryer (CSD) to stainless steel solar dryer (SSSD) in terms of the effect of drying and 10% vinegar pretreatment on antioxidant activities of ginger rhizome using 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity method, Ferric Reducing Antioxidant Power (FRAP) Assay, and total antioxidant methods was investigated. The effect of the two solar dryers and open-sun drying (OSD) on bioactive compound composition of the 10% vinegar pretreated sliced ginger using ethanol and aqueous extracts with GCMS/MS identification was also evaluated. The antioxidant activities of ethanol and aqueous extract of the 10% vinegar pretreated ginger using FRAP, DPPH, and total antioxidant methods were all higher than that of the dried samples, with CSD having the highest antioxidant activities among the dried methods. Drying reduced the main bioactive compound, which is gingerol, from 47.97% in the fresh sample to 32.49% in the OSD sample. The CSD sample demonstrated close likeness to the fresh sample with regard to retaining the highest gingerol and α-zingiberene. Hence, CSD can be adopted for commercial processing of ginger to reduce postharvest losses of the crop.
Live-Imaging Analysis of Target Vessels and Nitric Oxide Production Associated with Gosha-Jinki-Gan and Keishi-Bukuryo-Gan: Two Herbal Preparations with Clinically Proven Blood Flow-Improving Effects but with Different Traditional Clinical Indicative Patterns
Authors: Hirayama Aki , Tomita Tsutomu , Nishida Takashi , Nagano Yumiko
Published: May 2022

Gosha-jinki-gan (GJG) and Keishi-bukuryo-gan (KBG) are Kampo traditional herbal prescriptions used for different clinical patterns (sho) that improve blood flow. The pharmacological basis of the therapeutic choice remains unclear, although the clinical reliance of this pattern-based therapy is widely proven. We aimed to investigate their effects on microcirculation and nitric oxide (NO) kinetics using a live-imaging system to provide evidence for this. Live-imaging was performed in murine subcutaneous vessels and rat mesentery. In the subcutaneous vessels, we analyzed the effects of both drugs on the vessel diameter, blood flow velocity, and volume in the arteries, arterioles, and capillaries. In the rat mesentery, we induced the “oketsu” blood stasis using a stack of thin vinylidene chloride films and examined the effect on NO production using a fluorescent diaminofluorescein-2 diacetate. Following dissolution in hot water, 300 mg/kg of both drugs were administered intragastrically via a transesophageal catheter. Live-imaging analysis of subcutaneous blood flow revealed the different effects of GJG and KBG on their target vessels and effect onset. GJG targeted the capillaries and progressively increased the blood flow velocity and rate at 30–120 min after administration. No vasodilation or increased blood flow in the arteries and arterioles occurred. In contrast, KBG increased the diameter of the arterioles and arteries at 30–90 min after administration, and increased blood flow velocity and rate in arteries and arterioles. In a model of oketsu blood stasis in the mesenteric arteries, KBG increased the NO production from the vascular endothelial cells with dilatation of the arteriolar diameter. GJG improved blood flow mainly in the capillaries. Endothelial NO production decreased after GJG administration. The empirical treatment choice between GJG and KBG is based on the difference in target vessels and NO action and provides a pharmacological basis for therapy based on traditional medicine.
Artificial Intelligence-based Blockchain Technology for Skin Cancer Investigation Complemented with Dietary Assessment and Recommendation using Correlation Analysis in Elder Individuals
Authors: Mann Suman , Balyan Archana , Rohilla Vinita , Gupta Deepa , Gupta Zatin , Rahmani Abdul Wahab
Published: May 2022

In the modern world, due to the usage of high-power chemical-based cosmetics, climate change, and other major factors, skin cancer has been increasing among individuals. Skin cancer is considered as the most common malignant disorder, and there are more than a million cases being recorded with this disease every year. Extensive studies have already been performed to identify the risk factors and causative agents for skin cancer, including lifestyle changes and eatery patterns among individuals. The most common type of skin cancer is classified into basal cell carcinoma and squamous cell carcinoma. The researcher intends to conduct the research with the primary goal of determining the important factors in blockchain technology in the treatment of skin cancer in senior people. The application of new technologies such as blockchain has enabled offering better promises to health care professionals in addressing skin cancer in a more effective manner. These tools supported in evaluating the nature and severity of psoriasis has been regarded as much support for health care professionals in detecting skin cancer and offer better health care guidance for better living. The detection of melanomas supports the patient in enhancing the prognosis and support in discriminating between the melanomas and less impact lesions. The blockchain-based classification system offers more benefits and reduces the cost of detecting skin cancer in an effective manner. It also helps the medical professionals by assisting them in developing a custom diet plan for each patient on the basis of their health records and food intake. The researchers are focused on applying both the primary data sources and secondary data sources for performing the study. A detailed questionnaire is designed, and it is shared with the participants through university hospitals, support groups, etc. so as to gather the information. Nearly 156 respondents were chosen through nonprobability sampling, and the information was collected. The researcher performs critical descriptive analysis, and correlation analysis is performed to understand the overall association between the variables. The researchers intend to perform the study with the basic goal of understanding the critical factors in blockchain technology in skin cancer for elderly individuals. The major factors involved are enhanced data privacy, support in forecasting patterns, and enhanced medical services to patients complemented with personalized dietary assessment and recommendations. The result demonstrates that artificial intelligence-based blockchain technology allows for the efficient processing of huge amounts of data in order to complete the assigned task and correctly determine and predict the model.
Investigation into the Reliability and Encryption Performance of Wireless Signal Transmission by Network Coding Combined with Blockchain in Natural Disaster Scenarios
Authors: Li Ju , Shang Fengjun
Published: May 2022

To enhance the reliability and encryption of unmanned aerial vehicle (UAV) wireless signals in natural disaster scenarios, firstly, the present work analyzes the current wireless signal transmission mode of UAV. In addition, it discusses the efficient network coding of wireless signal transmission model and blockchain with strong encryption ability. Secondly, the signal transmission model of network coding is explored. Finally, the network coding wireless signal transmission model is combined with the blockchain wireless signal transmission model to realize efficient and encrypted data transmission. The research results show that the network coding wireless signal transmission model combined with blockchain technology realizes the maximum difference of network coding wireless signal transmission rate of 1.5 Mb/s. The model also encrypts the data in the simulation scenario of natural disasters through blockchain technology. After encryption, the data protection effect of the transmission model is significantly improved and meets the requirements of standard data transmission. Meanwhile, the wireless signal transmission model can reduce the resource occupation rate in the process of data transmission and improve the success rate and universality of data transmission in natural disaster scenarios. The probability of data being successfully protected in disaster is more than 90%. The results provide technical support for the stable transmission of wireless signals in natural disaster scenarios and provide a reference for improving the reliability and encryption of wireless signal transmission.
The Promotion Effect of the Improved ISCA Model on the Application of Accounting Informatization in Small- and Medium-Sized Enterprises in the Cloud Computing Environment
Authors: Meng Lamei
Published: May 2022

Cloud computing has played a strong role in promoting the accounting informatization of small and medium-sized enterprises, which is helpful to accelerate the construction of accounting informatization. In order to improve the accounting informatization construction effect of small and medium-sized enterprises, this paper proposes an improved ISCA accounting informatization model based on cloud computing and proposes a semisupervised clustering method of accounting information based on the minimum prototype cluster to classify accounting information. Moreover, this paper uses labeled samples to measure the compactness and purity of clusters and guide the splitting of clusters and constructs a corresponding intelligent model structure. The research shows that the improved ISCA model proposed in this paper has a very obvious effect on the improvement of application of accounting informatization in small- and medium-sized enterprises in the cloud computing environment.
hsa_circ_0001955 Promotes Colorectal Cancer Progression by Regulating miR-583/FGF21 Axis
Authors: Gao Xuefeng , Yin Junfeng , Yao Ying
Published: May 2022

Objective. Hsa_circ_0001955 presents significant upregulation in colorectal cancer (CRC) tissues. However, its role in CRC remains unclear. Thus, we attempted to clarify functions of hsa_circ_0001955 on CRC. Methods. qRT-PCR was performed to examine hsa_circ_0001955, miR-583, and FGF21 levels. Western blotting was conducted to measure FGF21 protein expression. CCK-8, flow cytometry, and Ki-67 immunohistochemical staining and TUNEL assays were conducted to assess proliferation and apoptosis in vitro and in vivo, respectively. Cell invasion and migration were assessed by Transwell assay. Tumor-bearing mouse model and HE staining were used to assess inflammatory injury. Luciferase reporter system and RNA pull-down were conducted to evaluate the regulation between miR-583 and hsa_circ_0001955 or FGF21. Results. We found that hsa_circ_0001955 showed characteristics of upregulated circRNA in CRC. Further analysis indicated that hsa_circ_0001955 elevation facilitated CRC cell malignancy in vitro and promoted tumor growth in vivo. Furthermore, hsa_circ_0001955 was a miR-583 sponge and FGF21 was directly targeted by miR-583. In addition, we found that downregulation of miR-583 promoted hsa_circ_0001955-mediated CRC cell malignancy in vitro. In contrast, FGF21 elevation promoted miR-583-regulated CRC cell malignancy in vitro. Conclusion. We demonstrated that hsa_circ_0001955 facilitated CRC progression via miR-583/FGF21 axis, suggesting that hsa_circ_0001955 may provide a novel insight for therapy of CRC.
Prognostic Prediction Using the Clinical Data and Ultrasomics-Based Model in Acute Respiratory Distress Syndrome (ARDS) Combined with Acute Kidney Injury (AKI)
Authors: Cai Xing , Li Jing , Qin Ping , An Peng , Yang Hao , Zuo MingYan , Wang Jinsong
Published: May 2022

Objective. A model was constructed based on clinical and ultrasomics features to predict the prognosis of patients in the respiratory intensive unit (RICU) who had acute respiratory distress syndrome (ARDS) combined with acute kidney injury (AKI). AKI ensues after ARDS in RICU ordinarily. The prognostic prediction tool was further developed on this basis. Methods. We collected clinical and ultrasonic data from 145 patients who had ARDS combined with AKI and received continuous renal replacement therapy (CRRT) in the RICU of Xiangyang Hospital of Traditional Chinese Medicine from March 2016 to November 2019. The patients were divided into the survival group (n = 51) and the death group (n = 94), depending on the treatment outcome. The training set (n = 102) and the testing set (n = 43) were established based on patient data. The clinical and ultrasomics features and the CRRT parameters were compared between the two groups. The influence factors of death were analyzed by logistic regression, and four predictive models were established. The predictive performance of 4 models was compared using the R Software 4.1.3. The decision curve analysis graphs were drawn using the R language to determine the net benefit of each. Result. Univariate analysis was conducted in the training set. The following risk factors for poor prognosis were identified: age, concurrent cancers, sequential organ failure assessment score (SOFA), number of organ dysfunctions, positive cumulative fluid balance at 72 h, time from ICU admission to CRRT, mean arterial pressure, oxygenation index, and gray-level size zone matrix, GLSZM (SumEntropy.239/SmallDependenceHighGrayLevelEmphasis.314/Maximum.327/Variance.338) (

P
<
0.05

). Four models were built based on the above factors: clinical model, CRRT model, ultrasomics-based model, and combination model. Comparison using the MedCalc software indicated that the best predictive performance achieved with the combination model. The decision curve analysis also suggested that the combination model had the highest net benefit. Similar results were reported after validation on the testing set. Conclusion. The prognosis of ARDS patients combined with AKI is usually poor. The combination model based on clinical and ultrasomics features had the highest predictive performance. This model can be used to improve the clinical outcome and prognosis.
Experimental Study on the Aeolian Sand Solidification via MICP Technique
Authors: Zhou Yijun , Chen Yulong
Published: May 2022

This study solidifies the aeolian sand by microbial-induced carbonate precipitation (MICP) technique. The effects of cementation solution with different concentrations, particle size, and grouting batches are examined via the bender element, unconfined compressive test, and scanning electron microscope (SEM). The bender element results show that the wave speed of loose aeolian sand is 200 m/s; however, after solidification of the aeolian sand, the speed of P-wave is about 450-600 m/s and S-wave is about 350-500 m/s. Additionally, the unconfined compressive strength (UCS) results indicate that when the concentration of cementation solution is 0.75 mol/L, the UCS of biosolidified sand sample is the highest. Then, compared with the aeolian sand with original grade, the particles ranging from 0.1 to 0.4 mm have a better cementation effect. Moreover, the UCS of biosolidified sand samples increases along with the grouting batch. From the SEM images, it can be seen that when the grouting batch reaches to five times, the particles are almost completely covered by CaCO3 crystals compared with the three batches and four batches.