bluuebunny/crossref_metadata_2025 huggingface dataset:
Survival Characteristics and Transcriptomic Analyses Reveal the Adaptive Response of the Aquatic Pathogen Non-O1/O139 Vibrio cholerae to Starvation Stress
Authors: Gao Xiaojian , Zhang Zirui , Qian Qieqi , Chen Qiyun , Gu Shuwen , Li Jie , Zhang Yingjie , Wu Congcong , Jiang Qun , Zhang Xiaojun
Published: May 2022

Non-O1/O139
V. cholerae
is a causal agent of vibriosis that can be subject to nutrient insufficiency and cause high rates of mortality in aquatic animals. However, its molecular mechanisms of survival in response to starvation stress have been investigated only partially.
Microsurgical treatment of posterior inferior cerebellar aneurysms based on angioarchitecture supplemented by high-resolution vessel wall MRI: a case series report
Authors: Yang Zixiao , Song Jianping , Quan Kai , Li Peiliang , An Qingzhu , Shi Yuan , Liu Peixi , Yu Guo , Tian Yanlong , Zhou Liangfu , Zhu Wei
Published: May 2022

Background

Surgical treatment of posterior inferior cerebellar artery (PICA) aneurysms is challenging because many are nonsaccular and atherosclerotic. We report our tailored approach to PICA aneurysms, which is based on angioarchitecture supplemented by high-resolution vessel wall MRI (HR-VW MRI) findings.

Methods

From March 2010 to September 2020, 27 patients with 29 PICA aneurysms underwent surgical treatment in our institution. Since October 2016, HR-VW MRI has been used for aneurysmal wall assessment. Clinical characteristics, radiological data and surgical outcomes were analysed.

Results

Nineteen proximal PICA aneurysms (vertebral artery (VA), P1, P2 and P3) were treated using the far-lateral approach. Ten distal PICA aneurysms (P4, P5) were treated using the suboccipital midline approach. Direct clipping or clip reconstruction was achieved in 19 aneurysms. Ten were trapped in conjunction with extracranial–intracranial or intracranial–intracranial bypass, including three occipital artery-PICA reimplantations, three PICA-VA reimplantations, two PICA-PICA side-to-side anastomoses, one PICA-PICA reimplantation and one PICA-PICA reanastomosis. All aneurysms were eventually completely obliterated and all bypasses remained patent. At the last follow-up, 26 patients (96.2%) achieved a good outcome (modified Rankin Scale score <3). Eight patients underwent HR-VW MRI. Among these, the six aneurysms with focal wall enhancement required bypass and the two with negative enhancement were successfully clipped.

Conclusion

PICA aneurysms have a higher frequency of complex features such as large or giant size and fusiform or dissecting morphology. Favourable outcomes were achieved with individualised microsurgical strategies based on angioarchitecture. HR-VW MRI may be used as a promising technique to predict aneurysmal atherosclerosis.
Enhanced reduction of nitrobenzene derivatives using reusable Ni nanoparticles supported on multi-layered poly(1,2-phenylenediamine)-coated layered double hydroxides
Authors: Babamoradi Jamshid , Ghorbani-Vaghei Ramin , Alavinia Sedigheh
Published: May 2022

Recently, nanomaterials with layered double hydroxide (LDH) cores have been the subject of intense research regarding their promising applications in organic synthesis. In this study, nitrobenzene reduction is investigated by designing and synthesizing a novel LDH-based heterogeneous catalyst containing a nickel-1,2-phenylenediamine complex. The Cu–Zn–Al LDH was functionalized with copolymer bearing a glycidyl methacrylate (GMA) linkage that makes it suitable for grafting with 1,2-phenylenediamine. Overall, the synthesized LDH@MPS-GMA-PDA-Ni was found to be a highly efficient heterogeneous nanocatalyst that can catalyze nitroarene reduction with high yields under mild conditions.
Extremal Betti numbers of symbolic powers of two-dimensional squarefree monomial ideals
Authors: Quang Lôc Nguyên , Công Minh Nguyên , Thi Thuy Phan
Published: May 2022

Let [Formula: see text] be a two-dimensional squarefree monomial ideal in a polynomial ring [Formula: see text], where [Formula: see text] is a field. In this paper, we give explicit formulas for the extremal Betti numbers of the [Formula: see text]th symbolic power of [Formula: see text] for all [Formula: see text]. As a consequence, we characterize the rings [Formula: see text] which are pseudo-Gorenstein as sense of Ene et al. [Pseudo-Gorenstein and level Hibi rings, J. Algebra 431 (2015) 138–161]. We also provide a complete classification for the level property of the second symbolic power [Formula: see text]. In particular, we obtain a new algebraic-property of the unknown Moore graph of degree 57.
Enterprise Financial Risk Early Warning Using BP Neural Network Under Internet of Things and Rough Set Theory
Authors: Zhang Huang , Luo Yonghui
Published: May 2022

In this paper, an enterprise financial risk indicator system is established to warn about the financial risk of enterprises. First, the related knowledge of financial risk and its measurement is introduced. Next, the financial risk indicator system of small- and medium-sized enterprises (SMEs) is established based on back propagation neural network (BPNN). The rough set theory is adopted to simplify the indicator. Finally, the BPNN model is used to predict the financial situation of SMEs. The results show that in the 490th iteration, the performance of the BPNN-based financial risk early warning system for SMEs can reach the optimal and meet the accuracy requirements of initialization. The error of the enterprise financial risk early warning model converges to the target error, so the calculation result is credible. The actual output after training is close to the expected output. By judging the actual output value, it can be known that the financial risk status of SMEs in 2016, 2017 and 2018 is of low alarm. This exploration has a certain preventive effect on the financial risk of enterprises and provides a basis for the rapid development of enterprises.
An Enhanced Term Weighted Question Embedding for Visual Question Answering
Authors: Manmadhan Sruthy , Kovoor Binsu C
Published: May 2022

Visual Question Answering (VQA) is a multi-modal AI-complete task of answering natural language questions about images. Literature solved VQA with a three-phase pipeline: image and question featurisation, multi-modal feature fusion and answer generation or prediction. Most of the works have given attention to the second phase, where multi-modal features get combined ignoring the effect of individual input features. This work investigates VQA’s natural language question embedding phase by proposing a new question featurisation framework based on Supervised Term Weighting (STW) schemes. In addition, two new STW schemes integrating text semantics, qf.cos and tf.rf.sim, have been introduced to boost the framework’s performance. A series of tests on the DAQUAR VQA dataset is used to compare the new system to conventional pre-trained word embedding. Over the past few years, STW schemes have been commonly used in text classification research. In light of this, tests are carried out to verify the effectiveness of the two newly proposed STW schemes in the general text classification task.
Global dynamics and bifurcation analysis of an insect-borne plant disease model with two transmission routes
Authors: Zhang Fumin , Qiu Zhipeng , Huang Aijun , Cheng Yan , Fan Guihong
Published: May 2022

Huanglongbing (HLB) is a plant disease mainly spread by the insect-borne citrus psyllid. It is the most destructive citrus pathosystem worldwide. To understand the impact of sexual transmission on HLB dynamics, we propose a host–vector–HLB compartment model incorporating two transmission routes. The basic reproduction number [Formula: see text] is derived. Various interventions of the disease are assessed. We also investigate the effect of different incidence functions to simulate sexual transmission. For the case of sublinear incidence functions, the disease-free equilibrium is globally asymptotically stable (GAS) provided [Formula: see text]. For mass action incidence of sexual transmission, the endemic equilibrium is GAS provided [Formula: see text]. However, under nonlinear incidence, it is proved that the model may exhibit backward bifurcation. Theoretical and numerical studies reveal that (i) different forces of infection between heterosexual psyllids in the model may have a distinct impact on disease dynamics; (ii) sensitivity analysis shows that for [Formula: see text], the transmission rate between host and vector is more sensitive parameter than that between heterosexual psyllids; (iii) if the sexual transmission is ignored, the disease burden is likely to be underestimated in comparison with realistic scenarios; (iv) in the absence of chemical insecticides, the combined use of yellow sticky traps and injection of nutrient solutions can be more effective in suppressing the spread of HLB. These findings provide valuable insights for public policymakers to determine the long-term viability of implemented HLB management strategies and highlight the urgency of finding sustainable HLB solutions.
Unequal-order grey model with the difference information and its application
Authors: Tu Leping , Chen Yan , Wu Lifeng
Published: May 2022

According to the principle of minimum information, new information priority, and difference information, most existing grey forecast models and their improvement are inconsistent with the grey theory. Therefore, a novel discrete multivariable grey model with unequal fractional-order accumulation is proposed. To improve the accuracy and stability of the model, an optimization algorithm for unequal fractional-order is proposed. The proposed model and algorithm are evaluated with four actual cases. The results show that the novel model has better performance and the proposed unequal fractional-order accumulation operator is better than other existing accumulation operators. Considering the energy consumption, the carbon dioxide emissions in the USA have been forecasted to decrease but remain at a high level by using the novel discrete multivariable grey model. Reducing energy consumption is conducive to reducing carbon dioxide emissions.
Carbonaceous residues in the Southern Uplands accretionary prism of Ireland and Scotland
Authors: Schito Andrea , Muirhead David , Parnell John
Published: May 2022

Carbonaceous residues occur in mudstones and turbidites of the Lower Paleozoic accretionary prism in Ireland and Scotland (Longford-Down, Southern Uplands). The accretionary prism was host to fluid migration during both the Lower Paleozoic and Carboniferous–Triassic, so the age of the carbonaceous fluids is uncertain. Raman spectroscopy data for the carbonaceous residues in the Lower Paleozoic rocks indicate palaeotemperatures similar to those measured in their host rocks, and much higher than those in the Carboniferous cover rocks or in residues in the cover rocks. These data show that residues in the prism rocks are of Lower Paleozoic age, and were not contributed by younger mineralizing fluids. The residues represent hydrocarbons generated from source rocks in the prism that were part of the Ordovician–Silurian deposits of the Iapetus Ocean.
IoTRepair: Flexible Fault Handling in Diverse IoT Deployments
Authors: Norris Michael , Celik Z. Berkay , Venkatesh Prasanna , Zhao Shulin , McDaniel Patrick , Sivasubramaniam Anand , Tan Gang
Published: May 2022

IoT devices can be used to complete a wide array of physical tasks, but due to factors such as low computational resources and distributed physical deployment, they are susceptible to a wide array of faulty behaviors. Many devices deployed in homes, vehicles, industrial sites, and hospitals carry a great risk of damage to property, harm to a person, or breach of security if they behave faultily. We propose a general fault handling system named IoTRepair, which shows promising results for effectiveness with limited latency and power overhead in an IoT environment. IoTRepair dynamically organizes and customizes fault-handling techniques to address the unique problems associated with heterogeneous IoT deployments. We evaluate IoTRepair by creating a physical implementation mirroring a typical home environment to motivate the effectiveness of this system. Our evaluation showed that each of our fault-handling functions could be completed within 100 milliseconds after fault identification, which is a fraction of the time that state-of-the-art fault-identification methods take (measured in minutes). The power overhead is equally small, with the computation and device action consuming less than 30 milliwatts. This evaluation shows that IoTRepair not only can be deployed in a physical system, but offers significant benefits at a low overhead.
Multimodal Optimization of Edge Server Placement Considering System Response Time
Authors: Zhang Xinglin , Zhang Jinyi , Peng Chaoqun , Wang Xiumin
Published: May 2022

Mobile edge computing (MEC)deploys computing and storage resources close to mobile devices, enabling resource demanding applications to run on mobile devices with short network latency. In the past few years, large numbers of research works focused on the research hotspots in MEC, such as computation offloading and energy efficiency. However, few researchers have investigated the deployment of edge servers. On the one hand, blindly deploying numerous edge servers will result in a large amount of capital expenditure. On the other hand, the deployment of edge servers is a multimodal problem that should provide decision makers with multiple deployment options to deal with the impact of unmeasured real-world factors. Considering these factors, we study themultimodal optimization problem of edge server placement (MESP)with the goal of minimizing the average system response time in this work. Regarding the difficulty of the MESP problem, we propose a heuristic algorithm that combines particle swarm optimization and niching technology to obtain a set of competitive placement solutions. Extensive experiments over a real-world dataset show that the proposed algorithm can significantly reduce the system response time.
Regenerating myofiber directs Tregs and Th17 responses in inflamed muscle through the intrinsic TGF-β signaling-mediated IL-6 production
Authors: Huang Tao , Huang JingWen , Liao ZhaoHong , Lan HaiQiang , Jian XiaoTing , Gu RuiCai , Ouyang Jun , Hu Jijie , Liao Hua
Published: May 2022

Myofiber mediates muscle inflammatory response through activating the intrinsic TGF-β signaling. The specific TGF-β signaling activation contributes to myofiber IL-6 production and directs muscle-specific Th17 and Treg cell responses
Empagliflozin Ameliorates Diabetic Cardiomyopathy via Attenuating Oxidative Stress and Improving Mitochondrial Function
Authors: Wang Jinwu , Huang Xinyuan , Liu Hanjie , Chen Yuhang , Li Peipei , Liu Lingling , Li Jiashen , Ren Yangxi , Huang Junping , Xiong Erya , Tian Zhijie , Dai Xiaozhen
Published: May 2022

Diabetic cardiomyopathy (DCM) is considered to be a critical contributor to the development of heart failure. Empagliflozin (EMPA), a sodium-glucose cotransporter 2 inhibitor, has been shown to prevent cardiovascular events and reduce the incidence of heart failure in randomized clinical trials. However, the mechanism of how EMPA prevents DCM is poorly understood. To study the potential mechanisms involved in the therapeutic effects of EMPA, we assessed the protective effects of EMPA on myocardial injury in type 2 diabetic db/db mice and H9C2 cardiomyocytes. 9–10-week-old male db/db mice were treated with EMPA (10 mg/kg) via oral gavage daily for 20 weeks. Afterward, cardiac function of treated mice was evaluated by echocardiography, and pathological changes in heart tissues were determined by histopathological examination and western blot assay. EMPA markedly reduced blood glucose levels, improved insulin tolerance, and enhanced insulin sensitivity of db/db mice. In addition, EMPA significantly prevented cardiac dysfunction, inhibited cardiac hypertrophy and fibrosis, and reduced glycogen deposition in heart tissues. Furthermore, EMPA improved diabetes-induced oxidative stress and mitochondrial dysfunction in both heart tissues of db/db mice and palmitate exposed H9C2 cells. EMPA significantly increased the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream genetic targets in cardiac tissue of type 2 diabetic db/db mice and H9C2 cells. EMPA also downregulated the expression of mitochondrial fission-related proteins and upregulated the expression of mitochondrial fusion-related proteins. Collectively, these findings indicate that EMPA may prevent DCM via attenuating oxidative stress and improving mitochondrial function in heart tissue.
Resource Optimization in MEC-Assisted Multirobot Cooperation Systems
Authors: Qiu Lanxin , Zhang Yi , Wang Yanbo , Shen Yineng , Yuan Jiantao , Yin Rui
Published: May 2022

With prevalent utilization of multirobot cooperation (MRC) systems, people pay more attention to improve the system performance. Among them, the energy consumption and implementation latency of MRC systems are major concerns, and mobile edge computing (MEC) provides a potential way to solve these problems. Therefore, how to leverage MEC to get the balance between computing and communication consumption in MRC systems needs to be investigated urgently. In this paper, a MRC system deployed to accomplish multiple time-critical tasks by MEC technology is studied. The proposed MRC system includes a powerful master robot (MR) and several slave robots (SRs). As a scheduler, MR is responsible for allocating tasks to SRs and has more computing power. SRs are robots with sensors that interact with the environment. In this paper, we propose a strategy for task allocation and resource management in MRC systems. The results show that the proposed scheme can effectively reduce the total energy consumption in SRs.
Zengye Decoction Attenuated Severe Acute Pancreatitis Complicated with Acute Kidney Injury by Modulating the Gut Microbiome and Serum Amino Acid Metabolome
Authors: Dai Xiao-Yu , Hu Qian , Yao Jia-Qi , Wu Xiao-Jia , Miao Yi-Fan , Li Juan , Wan Mei-Hua , Tang Wen-Fu
Published: May 2022

Objective. To explore the effect and underlying mechanism of Zengye decoction (ZYD), a traditional formula from China, on the severe acute pancreatitis (SAP) rat model with acute kidney injury (AKI). Methods. The SAP-AKI model was induced by 3.5% sodium taurocholate. Rats were treated with normal saline or ZYD twice and sacrificed at 36 h after modeling. Amylase, lipase, creatinine, blood urea nitrogen, kidney injury molecule 1(KIM-1), and multiple organs’ pathological examinations were used to assess the protective effect of ZYD. Gut microbiome detected by 16S rRNA sequencing analysis and serum amino acid metabolome analyzed by liquid chromatography-mass spectrometry explained the underlying mechanism. The Spearman correlation analysis presented the relationship between microflora and metabolites. Results. ZYD significantly decreased KIM-1(

P
<
0.05

) and the pathological score of the pancreas (

P
<
0.05

), colon (

P
<
0.05

), and kidney (

P
<
0.05

). Meanwhile, ZYD shifted the overall gut microbial structure (β-diversity, ANOSIM R = 0.14,

P
=
0.025

) and altered the microbial compositions. Notably, ZYD reduced the potentially pathogenic bacteria—Bacteroidetes, Clostridiales vadin BB60 group, and uncultured_Clostridiales_bacterium, but promoted the short-chain fatty acid (SCFA) producers—Erysipelotrichaceae, Bifidobacterium, Lactobacillus, and Moryella (all

P
<
0.05

). Moreover, principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA) presented a remarkable change in amino acid metabolome after SAP-AKI induction and an apparent regulation by ZYD treatment (R2Y 0.878,

P
=
0.01

; Q2 0.531,

P
=
0.01

). Spearman’s correlation analysis suggested that gut bacteria likely influenced serum metabolites levels (absolute r > 0.4 and FDR

P
<
0.02

). Conclusions. ZYD attenuated SAP-AKI by modulating the gut microbiome and serum amino acid metabolome, which may be a promising adjuvant treatment.
Potentially Inappropriate Medications Use among Older Adults with Comorbid Diabetes and Hypertension in an Ambulatory Care Setting
Authors: Alwhaibi Monira
Published: May 2022

Objective. This study aims to estimate the prevalence of PIMs use and its associated factors among older adults with comorbid diabetes and hypertension. Methods. A cross-sectional retrospective study was used, including 1,853 older adults (age ≥65 years) with diabetes and hypertension who visited an ambulatory care setting. The study objectives were to estimate the prevalence and factors associated with PIMs use based on the 2019 American Geriatric Society (AGS) Beers criteria. Results. Almost one out of two individuals had PIMs used, with the average number of medications taken being seven. The most commonly prescribed PIMs were the use of gastrointestinal and endocrine medications. High risk of PIMs use was among those with ischemic heart disease, anxiety, and polypharmacy. Conclusions. Given the higher PIMs use among older adults with diabetes and hypertension comorbidities, tailored strategies and interventions to minimize PIMs use in this population are warranted.
The Key Technology of Wireless Sensor Network and Its Application in the Internet of Things
Authors: Zhang Yao , Cai Wanxiong
Published: May 2022

At present, sensor networks and the Internet of Things have made rapid development and received more and more attention. Wireless sensor network technology is widely applied in many industries. As an important part of IoT sensor layer, it is an important infrastructure for IoT development. The purpose of this paper is to enhance the existing wireless sensor networks on the basis of existing technologies for better application in IoT. In this article, we introduce the structural features, key techniques, and some specific applications of wireless sensor networks in the IoT. Secondly, this paper studies and analyzes the principle of the cell membrane algorithm and its own characteristics. Aiming at the problem of energy constraint in wireless sensor network, an energy equilibrium clustering algorithm based on the cell membrane optimization algorithm is proposed in order to realize energy balance of nodes and distribution of network cluster heads. This algorithm divides the nodes by concentration and energy factors and divides them into globally balanced clusters by combining distance factors, which can well solve the problems of uneven distribution of cluster heads and unbalanced global power usage in sensor networks. On the basis of a lot of previous researches, this paper presents a QoS model, which is based on the routing protocol, clustering protocol, and data fusion scheme discussed in this paper. Through analysis and experiments, it is proved that this scheme improves energy consumption and flexibility by 78% compared with the previous one and achieves better network performance.
[Retracted] A Novel Multicriteria Decision‐Making Approach for Einstein Weighted Average Operator under Pythagorean Fuzzy Hypersoft Environment
Authors: Sunthrayuth Pongsakorn , Jarad Fahd , Majdoubi Jihen , Zulqarnain Rana Muhammad , Iampan Aiyared , Siddique Imran
Published: May 2022

The experts used the Pythagorean fuzzy hypersoft set (PFHSS) in their research to discourse ambiguous and vague information in decision‐making processes. The aggregation operator (AO) plays a prominent part in the sensitivity of the two forefront loops and eliminates anxiety from that perception. The PFHSS is the most influential and operative extension of the Pythagorean fuzzy soft set (PFSS), which handles the subparameterized values of alternatives. It is also a generalized form of Intuitionistic fuzzy hypersoft set (IFHSS) that provides better and more accurate assessments in the decision‐making (DM) process. In this work, we present some operational laws for Pythagorean fuzzy hypersoft numbers (PFHSNs) and then formulate Pythagorean fuzzy hypersoft Einstein weighted average (PFHSEWA) operator based on developed operational laws. We discuss essential features such as idempotency, boundedness, and homogeneity for the proposed PFHSEWA operator. Furthermore, a DM approach has been developed based on the built‐in operator to address multicriteria decision‐making (MCDM) issues. A numerical case study of decision‐making problems in real‐life agricultural farming is considered to validate the settled technique’s dominance and applicability. The consequences display that the planned model is more operative and consistent to handle inexact data based on PFHSS.
Maxillary Expansion: A Comparison of Damon Self‐Ligating Bracket Therapy with MARPE and PAOO
Authors: Alsayegh Eman , Balut Nasib , Ferguson Donald J. , Makki Laith , Wilcko Thomas , Hansa Ismaeel , Vaid Nikhilesh R.
Published: May 2022

Purpose. The aim of this study was to investigate arch parameters and dentoalveolar changes from pretreatment to posttreatment by comparing the Miniscrew Assisted Rapid Palatal Expansion (MARPE), Periodontally Accelerated Osteogenic Orthodontics (PAOO), and Damon self‐ligating bracket therapies. Materials and Methods. Seventy‐nine patients underwent maxillary expansion followed by or in conjunction with Damon (n = 23), PAOO (n = 28), and MARPE (n = 28) therapies. Nine maxillary dental arch parameters were compared at pretreatment, posttreatment as well as, increments of treatment change. Measurements were made on STL study casts using 3Shape Ortho Analyzer 3D scanner software. Results. All groups showed significant posterior width increase in the molar area. The mean increase in inter‐molar distance was more than 8X greater in MARPE group compared to Damon and more than 4X greater compared to PAOO. MARPE showed significantly greater increments of change in inter‐molar width and palatal vault area Conclusions. All groups showed a significant width increase in the canine and molar area. MARPE showed the greatest increase in inter‐molar width, followed by PAOO and Damon. MARPE was the only group to show a significant increase in palatal vault area.
Insulin Resistance and Biological Aging: The Role of Body Mass, Waist Circumference, and Inflammation
Authors: Tucker Larry A.
Published: May 2022

The purpose of this investigation was to evaluate the association between insulin resistance and biological aging in a randomly selected sample of 2,596 U.S. women and men. Another key objective was to examine the extent to which the insulin resistance and biological aging association was influenced by differences in body mass, waist circumference, and systemic inflammation. Biological aging was indexed using the length of leukocyte telomeres. The homeostatic model assessment (HOMA) was employed to index insulin resistance. The body mass index (BMI) was used to represent body mass independent of height. Waist circumference was used to assess abdominal adiposity, and C‐reactive protein (CRP) was measured to index body‐wide inflammation. Insulin resistance and telomere length were both treated as continuous variables. Results revealed that insulin resistance was related significantly with cellular aging, after adjusting for several demographic covariates (F = 5.7, P = 0.0234). The association remained significant after controlling for multiple demographic and lifestyle covariates together (F = 4.6, P = 0.0410). However, after controlling for BMI, along with the other covariates, insulin resistance was no longer associated with biological aging (F = 2.1, P = 0.1573). After adjusting for differences in waist circumference, along with the demographic and lifestyle covariates, but not BMI, the relationship between insulin resistance and biological aging was negated further (F = 1.5, P = 0.2283). Adjusting for CRP with the demographic and lifestyle covariates, but not BMI or waist circumference, weakened the relationship (F = 4.0, P = 0.0552). Evidently, if all adults in the U.S. had the same BMI or waist circumference, there would not be a relationship between insulin resistance and telomere length. It appears that insulin resistance accounts for differences in biological aging mainly because of differences in BMI and waist circumference, especially the latter.
Centrally Extended α‐Homoderivations on Prime and Semiprime Rings
Authors: El-Soufi Mahmoud M. , Ghareeb A.
Published: May 2022

We present a new type of mappings called centrally extended α‐homoderivations of a ring ℜ (i.e., a map H from ℜ into ℜ which satisfies H(x + y) − H(x) − H(y) ∈ Z(ℜ) and H(xy) − H(x)H(y) − H(x)α(y) − α(x)H(y) ∈ Z(ℜ) for any x, y ∈ ℜ) where α is a mapping of ℜ and discuss the relationship between these mappings and other related mappings. Also, we study their effect on the center of a ring, and we give several outcomes on the commutativity of the ring.
Reducing the Possibility of Ruin by Maximizing the Survival Function for the Insurance Company’s Portfolio
Authors: Komunte Masoud , Kasumo Christian , Masanja Verdiana Grace
Published: May 2022

In this paper, the intention was to reduce the possibility of ruin in the insurance company by maximizing its survival function. This paper uses a perturbed classical risk process as the basic model. The basic model was later compounded by refinancing and return on investment. The Hamilton–Jacobi–Bellman equation and integro‐differential equation of Volterra type were obtained. The Volterra integro‐differential equation for the survival function of the insurance company was converted to a third‐order ordinary differential equation which was later converted into a system of first‐order ordinary differential equations. This system was then solved numerically using the fourth‐order Runge‐Kutta method. The results show that the survival function increases with the increase in the intensity of the counting process but decreases with an increase in the instantaneous rate of stock return and return volatility. This is due to the fact that the insurance company faces more risk. Thus, this paper suggests that in this situation, more investments should be made in risk‐free assets.
Rebalancing Docked Bicycle Sharing System with Approximate Dynamic Programming and Reinforcement Learning
Authors: Seo Young-Hyun , Kim Dong-Kyu , Kang Seungmo , Byon Young-Ji , Kho Seung-Young
Published: May 2022

The bicycle, an active transportation mode, has received increasing attention as an alternative in urban environments worldwide. However, effectively managing the stock levels of rental bicycles at each station is challenging as demand levels vary with time, particularly when users are allowed to return bicycles at any station. There is a need for system-wide management of bicycle stock levels by transporting available bicycles from one station to another. In this study, a bicycle rebalancing model based on a Markov decision process (MDP) is developed using a real-time dynamic programming method and reinforcement learning considering dynamic system characteristics. The pickup and return demands are stochastic and continuously changing. As a result, the proposed framework suggests the best operation option every 10 min based on the realized system variables and future demands predicted by the random forest method, minimizing the expected unmet demand. Moreover, we adopt custom prioritizing strategies to reduce the number of action candidates for the operator and the computational complexity for practicality in the MDP framework. Numerical experiments demonstrate that the proposed model outperforms existing methods, such as short-term rebalancing and static lookahead policies. Among the suggested prioritizing strategies, focusing on stations with a larger error in demand prediction was found to be the most effective. Additionally, the effects of various safety buffers were examined.
Quantum Density Functional Theory Studies on Additive Hydration of Tuftsin Tetrapeptide
Authors: Yogeswari B. , Tamilselvan K. S. , Thanikaikarasan S. , Dayanand Lal N. , Anandaram Harishchander , Madhusudhanan J. , Karthik R. , Batu Areda
Published: May 2022

Density functional B3LYP method has been used to study the molecular properties of the tuftsin tetrapeptide (threonine‐lysine‐proline‐arginine) and its retro form (arginine‐proline‐lysine‐threonine). The influence of single water molecule on the conformations and relative stabilities of solvated tuftsin complexes has been studied by placing the water molecule at the individual amino acid residues of both the tuftsin complexes. The contribution of four water molecules to the system energetics of tuftsin complexes has also been analyzed. The conformational changes occurred in the solvated tuftsin complexes have been explored through their dihedral angles. The tuftsin is found to be sensitive to structural changes, and our results indicate that water‐tuftsin hydrogen bonds (H‐bonds), in addition to intramolecular H‐bonds, stabilize the β‐turn structure with H‐bonds between threonine and arginine residues of tuftsin. Difference in the stability of the hydrated complexes is confined to the amino acid residues at which the water molecule is attached to tuftsin. The interaction energy calculations have been used to investigate the strength of the intermolecular H‐bond interactions. The AIM theory and NBO analysis were employed to survey the H‐bonding patterns in hydrated tuftsin complexes. The maximum ellipticity value (0.129) is noted for the Cα‐H (Arg)…O (W) interaction in Tuftsin…4W complex which indicates the higher chance of structural deformation under external perturbations. The interactions between oxygen lone pairs in water and C‐H antibond orbitals of tuftsin and retro tuftsin complexes exist with E(2) in the range of 4.03‐5.7 and 3.59‐4.14 kcal/mol, respectively.
Independent Innovation Incentive Mechanism of the National Independent Innovation Demonstration Zone of China Based on Evolutionary Game
Authors: Du Peijie , Tian Kang , Wang Yanrong
Published: May 2022

Considering the reward and punishment mechanism of the management committee and the complexity of innovation path selection of high‐tech and general enterprises, this paper constructs an evolutionary game model of independent innovation incentive mechanism in the National Independent Innovation Demonstration Zone of China. Meanwhile, the equilibrium points of the strategy selection are solved for the three. In addition, this paper adopts numerical simulation to analyze the influence of each decision variable on different players’ strategic selections. The results show that (1) the initial willingness of the management committee, high‐tech and general enterprises has different influences on each other, and these factors such as independent innovation cost, technology spillover coefficient, and patent royalty significantly affect the strategic selection of enterprises; (2) the reward and punishment mechanism of the management committee can enhance the innovation willingness of high‐tech and general enterprises, in which these punitive measures can promote further the independent innovation of the two; (3) the greater the innovation subsidy provided by the management committee to high‐tech enterprises, the heavier the punishment for general enterprises, and the better the effect of independent innovation incentives. The results can provide theoretical guidance and practical reference for the management committee to formulate the independent innovation incentive policies in the National Independent Innovation Demonstration Zone.
Topological Optimum Approach for Improving Indicators for Agricultural Sustainability
Authors: Khan Waseem Asghar
Published: May 2022

Background. The goal of this study is to improve the topological efficiency of agricultural production in Saudi Arabia’s allocated agriculture area. Method. The data envelopment analysis (DEA) topology was adopted to efficiently identify agricultural land utilization from 2009 to 2013. Results. According to the constant return to scale (CRS) topology, the area may be reduced by 8.7831667 percent in 2009, resulting in a given optimal crop yield scenario. Similarly, the area may be reduced by 3.9425506 percent in 2010 to attain a given optimum crop production topology, by 4.0198591 percent in 2011 to achieve the same amount of crop production, and by 1.0621519 percent in 2012 to attain the desired level of crop output. The topology of crop production could increase by 5.1334182 percent while retaining quality, according to the variable return to scale (VRS) topology while maintaining the same assigned area. Conclusion. Also using the linear programming approach to reproduce the results of CRS and VRS models.
Meso-Analysis of Recycled Coarse Aggregate Self-Compacting Concrete on the Basis of Random Aggregate Model
Authors: Gao Songpu , Liu Qing , Han Fengxia , Guo Zhongyan , Yang Jianping , Ren Jianwei
Published: May 2022

The purpose of this paper is to explore the numerical simulation of damage process and results of a new environmentally friendly material, recycled coarse aggregate self-compacting concrete (RCASCC). Random aggregate model of mesoscopic viewpoint was used for the experimental simulation of RCASCC. Results show that the specimens with 50% substitution rate exhibited the best performance among the specimens (i.e., with rates of 25%, 50%, 75%, and 100%). The stress-strain curves after dimensionless treatment were fitted using the uniaxial compressive principal equation of concrete with control parameters a = 0.9 and b = 11, and the fitting degree of the curve was relatively good. Meanwhile, the change process of internal cracking was shown intuitively. The crack expansion process became more obvious in the specimens and beams with a high substitution rate of RCA. The simulation results of the bending process of RCASCC beams analyzed by the concrete damaged plasticity (CDP) model and extended finite element (XFEM) were compared with the test results. Both simulation results validated the applicability of the CDP model and XFEM in the mechanical tests of RCASCC and can provide valuable reference for future research on the mechanical properties of recycled aggregate self-compacting concrete.
Identification of m6A‐Related lncRNA to Predict the Prognosis of Patients with Hepatocellular Carcinoma
Authors: Yang Hao , Yang Hong , Zhang Wei , Wang Juping , Sun Liping , Gao Juan , Zhao Haiping , Wang Zhenfei
Published: May 2022

Hepatocellular carcinoma (HCC) is the third leading cause of cancer‐related death worldwide. In the past decades, HCC treatment has achieved great progress; however, the overall prognosis remains poor. Therefore, it is the need of the hour to identify new prognostic biomarkers which can advance our understanding related to the underlying molecular mechanism of adverse prognosis and apply them to clinical work in prognosis prediction. In the present study, data of 576 HCC patients and 292 normal control cases from TCGA and ICGC databases were enrolled to our bioinformatic analysis. SNHG1 and SNHG3 were identified as overlapping genes in TCGA and ICGC databases using Pearson correlation analysis and univariate Cox regression analysis. Further, we used the median of the SNHG1 and SNHG3 expression values as the cutoff values to define the HCC patient groups with high or low expression level. The subsequent analysis revealed that abnormal high expression of SNHG1 or SNHG3 affected the immune infiltration patterns and the crosstalk among immune cells. Moreover, high expression of SNHG1 or SNHG3 resulted in drug resistant to AKT inhibitor VII, bexarotene, bicalutamide, dasatinib, erlotinib, and gefitinib. In addition, lower tumor neoantigen burden was observed in high SNHG1 or SNHG3 group. Further, we found significant relation between the aberrant upregulation of SNHG1 and SNHG3 in tumor grade and stage. We established a nomogram to systematically predict the 5‐ and 8‐year overall survival of liver cancer patients with good accuracy. Finally, the in vitro assays suggest that SNHG1 and SNHG3 promote the proliferative, migratory, and invasive abilities of HCC cells.
Application of Spatial Digital Information Fusion Technology in Information Processing of National Traditional Sports
Authors: Fu Xiang , Zhang Ye , Qin Ling
Published: May 2022

The rapid development of digital informatization has led to an increasing degree of reliance on informatization in various industries. Similarly, the development of national traditional sports is also inseparable from the support of information technology. In order to improve the informatization development of national traditional sports, this paper studies the fusion process of multisource vector image data and proposes an adjustment and merging algorithm based on topological relationship and shape correction for the mismatched points that constitute entities with the same name. The algorithm is based on topological relationship. The shape of the adjustment and merging algorithm is modified, and finally, a set of national traditional sports information processing system is constructed by combining the digital information fusion technology. Experiments have proved that the method of national traditional sports information processing based on digital information fusion technology proposed in this paper is effective and can play a good role in the digital development of national traditional sports.
Weighted Gene Co-Expression Network Analysis to Identify Potential Biological Processes and Key Genes in COVID-19-Related Stroke
Authors: Cen Gengyu , Liu Liuyu , Wang Jun , Wang Xue , Chen Shijian , Song Yiting , Liang Zhijian
Published: May 2022

The purpose of this research was to explore the underlying biological processes causing coronavirus disease 2019- (COVID-19-) related stroke. The Gene Expression Omnibus (GEO) database was utilized to obtain four COVID-19 datasets and two stroke datasets. Thereafter, we identified key modules via weighted gene co-expression network analysis, following which COVID-19- and stroke-related crucial modules were crossed to identify the common genes of COVID-19-related stroke. The common genes were intersected with the stroke-related hub genes screened via Cytoscape software to discover the critical genes associated with COVID-19-related stroke. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for common genes associated with COVID-19-related stroke, and the Reactome database was used to annotate and visualize the pathways involved in the key genes. Two COVID-19-related crucial modules and one stroke-related crucial module were identified. Subsequently, the top five genes were screened as hub genes after visualizing the genes of stroke-related critical module using Cytoscape. By intersecting the COVID-19- and stroke-related crucial modules, 28 common genes for COVID-19-related stroke were identified. ITGA2B and ITGB3 have been further identified as crucial genes of COVID-19-related stroke. Functional enrichment analysis indicated that both ITGA2B and ITGB3 were involved in integrin signaling and the response to elevated platelet cytosolic Ca2+, thus regulating platelet activation, extracellular matrix- (ECM-) receptor interaction, the PI3K-Akt signaling pathway, and hematopoietic cell lineage. Therefore, platelet activation, ECM-receptor interaction, PI3K-Akt signaling pathway, and hematopoietic cell lineage may represent the potential biological processes associated with COVID-19-related stroke, and ITGA2B and ITGB3 may be potential intervention targets for COVID-19-related stroke.
Metaverse, SED Model, and New Theory of Value
Authors: Wang Jianguo , Wang Tongsan , Shi Yuna , Xu Diwei , Chen Yutian , Wu Jie
Published: May 2022

The metaverse concept constructs a virtual world parallel to the real world. The social economic dynamics (SED) model establishes a systematic model for social economic dynamics simulation that integrates macroeconomy and microeconomy based on modeling mechanism of the new theory of value by analogy with Newtonian mechanics and the modeling approach of Agent‐based computational economics. This article describes the SED model’s modeling mechanisms, modeling rules, and behavior equations. At the same time, this article introduces the methods, testing standards, and some typical cases about using the SED model to generate the economic digital twin systems. By doing so, we hope to demonstrate that the method of computer simulation experiment based on the SED model is a scientific empirical method, which has more advantages than the existing empirical research methods in economics. The SED model, which can be fully used to form an economic engine and construct a virtual economic system by digital twin method, can be integrated with the extant physical engine in the metaverse concept to build a virtual world consisting of physics, economy, culture, and politics that is close to and coexists with reality.
APU‐Net: An Attention Mechanism Parallel U‐Net for Lung Tumor Segmentation
Authors: Zhou Tao , Dong YaLi , Lu HuiLing , Zheng XiaoMin , Qiu Shi , Hou SenBao
Published: May 2022

Lung cancer is one of the malignant tumors with high morbidity and mortality, and lung nodules are the early stages of lung cancer. The symptoms of pulmonary nodules are not obvious in the clinic, and the optimal treatment time is missed due to the missed diagnosis in the clinic. A parallel U‐Net network called APU‐Net is proposed. Firstly, two parallel U‐Net networks are used to extract the features of different modalities. Among them, the subnetwork UNet_B extracts the CT image features, and the subnetwork UNet_A consists of two encoders to extract the PET/CT and PET image features. Secondly, multimodal feature extraction blocks are used to extract features for PET/CT and PET images in UNet_B network. Thirdly, a hybrid attention mechanism is added to the encoding paths of the UNet_A and UNet_B. Finally, a multiscale feature aggregation block is used for extracting feature maps of different scales of decoding path. On the lung tumor 18FDGPET/CT multimodal medical images dataset, experiments’ results show that the DSC, Recall, VOE, and RVD coefficients of APU‐Net are 96.86%, 97.53%, 3.18%, and 3.29%, respectively. APU‐Net can improve the segmentation accuracy of the adhesion between the lesion of complex shape and the normal tissue. This has positive significance for computer‐aided diagnosis.
Measuring the Total‐Factor Green Efficiency in China’s Industrial Sectors: A Parametric Approach
Authors: Wang Zhenghuan
Published: May 2022

At present, China’s industrial economy is facing a severe problem of green transformation, so the measurement of total‐factor green efficiency has become one of the research hot spots. Combining Shephard’s distance function and metafrontier model, this study constructs a parametric total‐factor green efficiency model in consideration of technology heterogeneity. Stochastic metafrontier analysis, which controls individual effects, is used to estimate metafrontier green efficiency. This study calculates the green efficiency of Chinese industrial sectors. Results show that there are significant differences in metafrontier green efficiency between high‐ and low‐emission groups, and the efficiency level of the low‐emission group is systematically higher than that of the high‐emission group. Compared with pooled green efficiency and existing studies without considering technology heterogeneity, the metafrontier green efficiency is more intuitive and realistic. In order to achieve green industrial growth, this study suggests that the government should implement heterogeneous energy conservation and emission reduction policies for high‐ and low‐emission groups, especially to encourage carbon‐intensive industries to improve the use of existing group technologies, and to promote technology diffusion and spillover between high‐ and low‐emission groups. Based on the reliable measurement of green efficiency, green productivity might be reliably explored as well in the future.