bluuebunny/crossref_metadata_2025 huggingface dataset:
Attributes of Bi-Directional Turbomachinery for Pumped Thermal Energy Storage
Authors: Chiapperi J. D. , Greitzer E. M. , Tan C. S.
Published: September 2022

In this paper, we (i) present a methodology for determining the aerodynamic performance of bi-directional turbomachines for pumped thermal energy storage, i.e., turbomachines designed to operate as a compressor in one direction, and then as a turbine in the opposite direction, (ii) carry out performance computations for such turbomachines, and (iii) propose principles for conceptual design of these devices. Focus is placed on using the energy storage cycle not only to identify the novel requirements placed on bi-directional turbomachines but also to estimate the effect of these requirements on the efficiency of the energy storage process. In particular, the difference between aerodynamic loading in forward and in backward operation causes the blading to work at incidences leading to the performance below maximum efficiency, resulting in a lower round-trip efficiency. The description of the design principles includes determination of the number of stages, definition of nondimensional parameters for blading selection, and optimization of two-dimensional blading for bi-directional operation. The assessment of stage count shows the relationship between relative Mach number, pressure ratio, and round-trip efficiency. The nondimensional parameters are assessed through a bi-directional analogue to existing “Smith charts,” for the efficiency of single-direction turbomachines, as a function of camber and stagger. The blade shape evaluation and optimization show how the blade profile can be modified to address the requirements of a bi-directional turbomachine, enabling an increase in round-trip efficiency of two percentage points compared to a baseline double circular arc configuration.
Development of Translucent Design Philosophy for the Cyclic Pattern Design of Fan Outlet Guide Vanes
Authors: Kulkarni Davendu , di Mare Luca
Published: September 2022

The fan systems of typical high bypass civil engines encounter strong flow distortions originating in the intake and the bypass duct. These flow distortions cause the fan stage operation point to vary from its design intent, thus reducing the fan stage performance and increasing low engine-order fan blade forcing. A cyclic pattern design for the fan Outlet Guide Vanes (OGV) can be effectively used to recover the fan stage performance and to control its system-level aeromechanical behavior. This paper presents the development of an OGV pattern design philosophy using the numerical experimentation technique. Multiple fan-intake unsteady computational fluid dynamic computations are conducted by clocking the circumferential pressure profile at the fan exit. The study revealed that a mild, low-harmonic fan back pressure profile with a suitable clocking position is able to improve the fan rotor efficiency and reduce the first engine order (1EO) fan forcing simultaneously. Such a profile can be generated by designing a cyclic OGV pattern that allows the bifurcation potential fields of controlled intensity and phase to pass through the OGV blade row, thus termed the translucent design philosophy. Further, a sensitivity study is performed to assess the effects of simultaneous distortions upstream and downstream of the fan. The study showed that a correctly clocked intra-stage static pressure profile can consistently improve both the performance and aeromechanical behavior of fan systems having different intake lengths and at different flight conditions. The implementation of the proposed translucent design philosophy in a new OGV pattern design tool is discussed.
Numerical Investigation of Near-Tip Modifications for a Highly Loaded Low-Speed Rotor Under the Influence of Double Leakage
Authors: Eckel Jannik , von Jeinsen Philipp , Gümmer Volker
Published: September 2022

This paper numerically investigates the flow field in the tip region of a highly loaded axial low-speed compressor rotor. The rotor in focus is of a hybrid blade configuration, featuring a tandem profile in the mid-span region and single blade profiles near the endwalls. The simulated 1.5-stage configuration also consists of a single row inlet guide vane (IGV) and a tandem stator. Due to high loading coefficients (Ψ = 0.58) in combination with moderate flow coefficients (ϕ = 0.58), double leakage of the tip leakage vortex plays a major role at all operating conditions. As already shown in the past, double leakage is a stability influencing dominant flow phenomenon in compressor rotors and influencing that can be the key to an efficient working range enhancement on compressor stages. This work introduces a simple and powerful method of enhancing the working range for low-speed rotors under the influence of double leakage. It is shown, that modifications to the pressure side (ps) shape of rotor tip profiles can influence the interaction of the tip leakage vortex with the adjacent blade, comparable to the effects of casing treatments. These unconventional blade shapes result from the transformations from tandem blade configurations to hybrid blades near the endwalls. The resulting single blade profile close to the tip features a convex profile element (an increase in local thickness, called the “belly”), which significantly influences the local static pressure gradients. This unusual pressure-side profiling can change mass flow over the tip and, by correct positioning, may reduce the amount of double leakage and, consequently, increase the rotor’s efficient working range. This work presents the geometry definitions for the hybrid blade single-segments, a detailed analysis of the impact on design and off-design operating conditions together with their underlying flow phenomena, and finally proposes design guidelines for the blade-tip geometries of highly loaded rotors under the influence of double leakage.
Thermal Performance of Car Radiator Operated by Al2O3–Ethylene Glycol/Water-Based Nanofluids: A Computational Fluid Dynamics Study
Authors: Ghimire Rahul , Mehta Pankaj , Aryal Nischal , Sah Daya Ram , Adhikari Surya Prasad
Published: September 2022

This study analyzed the heat transfer potential of nanofluids (suspension of Al2O3 nanoparticles in 60:40 mixtures of ethylene glycol and water by volume) compared to the base fluid by modeling the flow in both laminar and turbulent flow regimes in a flat tube of a radiator using both single-phase and Eulerian–Eulerian multiphase approaches of computational fluid dynamics (CFD) simulation. Nusselt number is calculated by varying the Reynolds number for both the models and compared with the theoretical correlations and the experimental data available in the literature. The effect of change in volumetric concentrations, inlet velocities, inlet temperatures, and particle sizes on the heat transfer performance parameters of nanofluids was evaluated. The multiphase approach showed a 5–45% greater increase in Nusselt number than the single-phase approach for the same volume fraction up to 1% and thereafter multiphase approach showed an even higher Nusselt number. The multiphase model revealed that raising the volume fraction up to 2% increases the Nusselt number of nanofluid by approximately thrice that of the base fluid but after that further increase in volume fraction does not show any significant increment. With the increase in Reynolds number, the Nusselt number, as well as surface heat transfer coefficient, increased for both laminar and turbulent flow regimes. Skin friction coefficient, pressure drop across inlet and outlet, and pumping power required increased slightly with the increase in volume fractions. Also, on varying the nanoparticle size, superior performance was observed at the particle size of 25 nm.
Experimental Research on Heat Transfer Performance of CO2 Tube Bundle Falling Film Evaporator
Authors: Liu Zhongyan , Zhang Hao , Sun Dahan , Jin Xu , Zheng Shuang , Zhang Xin
Published: September 2022

CO2 is a promising refrigerant substitute, and falling film evaporator is widely used in high-capacity heat pump systems. In this article, a CO2 heat pump experimental device is built. According to experimental parameters, a CO2 falling film heat exchanger is fabricated. The falling film heat exchanger is used in heat pump evaporator, and its heat transfer characteristics are analyzed and tested. The outer diameter of the heat exchanger is 219 mm, outer diameter of the inner tube is 15.88 mm, and total outer surface area of the inner tube is 0.58 m2. Number of internal tubes was 12, each with a length of 0.97 m. During the test, change of heat transfer coefficient of each tube was analyzed when evaporation temperature, CO2 mass flowrate, and heat flow density changed. The influence of the position of heat exchange tube inside falling film evaporator on heat transfer coefficient is analyzed. The order of heat transfer coefficient of internal heat exchange tube is obtained. Finally, database of CO2 falling film evaporator is established. Through data sorting, heat exchange correlation formula is obtained. The deviation of 90% data in database is less than 5%. Heat exchange correlation formula has good accuracy.
Quantum phase transition dynamics in the two-dimensional transverse-field Ising model
Authors: Schmitt Markus , Rams Marek M. , Dziarmaga Jacek , Heyl Markus , Zurek Wojciech H.
Published: September 2022

The quantum Kibble-Zurek mechanism (QKZM) predicts universal dynamical behavior near the quantum phase transitions (QPTs). It is now well understood for the one-dimensional quantum matter. Higher-dimensional systems, however, remain a challenge, complicated by the fundamentally different character of the associated QPTs and their underlying conformal field theories. In this work, we take the first steps toward theoretical exploration of the QKZM in two dimensions for interacting quantum matter. We study the dynamical crossing of the QPT in the paradigmatic Ising model by a joint effort of modern state-of-the-art numerical methods, including artificial neural networks and tensor networks. As a central result, we quantify universal QKZM behavior close to the QPT. We also note that, upon traversing further into the ferromagnetic regime, deviations from the QKZM prediction appear. We explain the observed behavior by proposing an extended QKZM taking into account spectral information as well as phase ordering. Our work provides a testing platform for higher-dimensional quantum simulators.
The nonconducting W434F mutant adopts upon membrane depolarization an inactivated-like state that differs from wild-type Shaker-IR potassium channels
Authors: Coonen Laura , Martinez-Morales Evelyn , Van De Sande Dieter V. , Snyders Dirk J. , Cortes D. Marien , Cuello Luis G. , Labro Alain J.
Published: September 2022

Voltage-gated K
+
(Kv) channels mediate the flow of K
+
across the cell membrane by regulating the conductive state of their activation gate (AG). Several Kv channels display slow C-type inactivation, a process whereby their selectivity filter (SF) becomes less or nonconductive. It has been proposed that, in the fast inactivation-removed Shaker-IR channel, the W434F mutation epitomizes the C-type inactivated state because it functionally accelerates this process. By introducing another pore mutation that prevents AG closure, P475D, we found a way to record ionic currents of the Shaker-IR-W434F-P475D mutant at hyperpolarized membrane potentials as the W434F-mutant SF recovers from its inactivated state. This W434F conductive state lost its high K
+
over Na
+
selectivity, and even NMDG
+
can permeate, features not observed in a wild-type SF. This indicates that, at least during recovery from inactivation, the W434F-mutant SF transitions to a widened and noncationic specific conformation.
A flexible electronic strain sensor for the real-time monitoring of tumor regression
Authors: Abramson Alex , Chan Carmel T. , Khan Yasser , Mermin-Bunnell Alana , Matsuhisa Naoji , Fong Robyn , Shad Rohan , Hiesinger William , Mallick Parag , Gambhir Sanjiv Sam , Bao Zhenan
Published: September 2022

Assessing the efficacy of cancer therapeutics in mouse models is a critical step in treatment development. However, low-resolution measurement tools and small sample sizes make determining drug efficacy in vivo a difficult and time-intensive task. Here, we present a commercially scalable wearable electronic strain sensor that automates the in vivo testing of cancer therapeutics by continuously monitoring the micrometer-scale progression or regression of subcutaneously implanted tumors at the minute time scale. In two in vivo cancer mouse models, our sensor discerned differences in tumor volume dynamics between drug- and vehicle-treated tumors within 5 hours following therapy initiation. These short-term regression measurements were validated through histology, and caliper and bioluminescence measurements taken over weeklong treatment periods demonstrated the correlation with longer-term treatment response. We anticipate that real-time tumor regression datasets could help expedite and automate the process of screening cancer therapies in vivo.
Ketogenic diet uncovers differential metabolic plasticity of brain cells
Authors: Düking Tim , Spieth Lena , Berghoff Stefan A. , Piepkorn Lars , Schmidke Annika M. , Mitkovski Miso , Kannaiyan Nirmal , Hosang Leon , Scholz Patricia , Shaib Ali H. , Schneider Lennart V. , Hesse Dörte , Ruhwedel Torben , Sun Ting , Linhoff Lisa , Trevisiol Andrea , Köhler Susanne , Pastor Adrian Marti , Misgeld Thomas , Sereda Michael , Hassouna Imam , Rossner Moritz J. , Odoardi Francesca , Ischebeck Till , de Hoz Livia , Hirrlinger Johannes , Jahn Olaf , Saher Gesine
Published: September 2022

To maintain homeostasis, the body, including the brain, reprograms its metabolism in response to altered nutrition or disease. However, the consequences of these challenges for the energy metabolism of the different brain cell types remain unknown. Here, we generated a proteome atlas of the major central nervous system (CNS) cell types from young and adult mice, after feeding the therapeutically relevant low-carbohydrate, high-fat ketogenic diet (KD) and during neuroinflammation. Under steady-state conditions, CNS cell types prefer distinct modes of energy metabolism. Unexpectedly, the comparison with KD revealed distinct cell type–specific strategies to manage the altered availability of energy metabolites. Astrocytes and neurons but not oligodendrocytes demonstrated metabolic plasticity. Moreover, inflammatory demyelinating disease changed the neuronal metabolic signature in a similar direction as KD. Together, these findings highlight the importance of the metabolic cross-talk between CNS cells and between the periphery and the brain to manage altered nutrition and neurological disease.
Deep learning reveals predictive sequence concepts within immune repertoires to immunotherapy
Authors: Sidhom John-William , Oliveira Giacomo , Ross-MacDonald Petra , Wind-Rotolo Megan , Wu Catherine J. , Pardoll Drew M. , Baras Alexander S.
Published: September 2022

T cell receptor (TCR) sequencing has been used to characterize the immune response to cancer. However, most analyses have been restricted to quantitative measures such as clonality that do not leverage the complementarity-determining region 3 (CDR3) sequence. We use DeepTCR, a framework of deep learning algorithms, to reveal sequence concepts that are predictive of response to immunotherapy. We demonstrate that DeepTCR can predict response and use the model to infer the antigenic specificities of the predictive signature and their unique dynamics during therapy. The predictive signature of nonresponse is associated with high frequencies of TCRs predicted to recognize tumor-specific antigens, and these tumor-specific TCRs undergo a higher degree of dynamic changes on therapy in nonresponders versus responders. These results are consistent with a biological model where the hallmark of nonresponders is an accumulation of tumor-specific T cells that undergo turnover on therapy, possibly because of the dysfunctional state of these T cells in nonresponders.
Unemployment and insecure housing are linked to less successful treatment for depression
Authors: Saul Helen , Gursul Deniz , Hoskin Lauren , Buckman Joshua
Published: September 2022

The study

Buckman JEJ, Saunders R, Stott J, et al. Socioeconomic indicators of treatment prognosis for adults with depression: a systematic review and individual patient data meta-analysis.JAMA Psychiatry2022;79:5.

To read the full NIHR Alert, go to:https://evidence.nihr.ac.uk/alert/unemployment-insecure-housing-linked-less-successful-depression-treatment/
Is there a mitochondrial DNA haplogroup connection between osteoarthritis and elite athletes? A narrative review
Authors: Martel-Pelletier Johanne , Pelletier Jean-Pierre
Published: September 2022

Elite athletes are at greater risk of joint injuries linked to the subsequent risk of developing osteoarthritis (OA). Genetic factors such as mitochondrial (mt) DNA haplogroups have been associated with the incidence/progression of OA and athletic performance. This review highlights an area not yet addressed: is there a common pattern in the mtDNA haplogroups for OA occurrence in individuals and elite athletes of populations of the same descent? Haplotypes J and T confer a decreased risk of OA in Caucasian/European descent, while H and U increase this risk. Both J and T haplogroups are under-represented in Caucasian/European individuals and endurance athletes with OA, but power athletes showed a greater percentage of the J haplogroup. Caucasian/European endurance athletes had a higher percentage of haplogroup H, which is associated with increased athletic performance. In a Chinese population, haplogroup G appears to increase OA susceptibility and is over-represented in Japanese endurance athletes. In contrast, in Koreans, haplogroup B had a higher frequency of individuals with OA but was under-represented in the endurance athlete population. For Caucasian endurance athletes, it would be interesting to evaluate if those carrying haplotype H would be at an increased risk of accelerated OA, as well as the haplogroup G in Chinese and Japanese endurance athletes. The reverse might be studied for the Korean descent for haplogroup B. Knowledge of such genetic data could be used as a preliminary diagnosis to identify individuals at high risk of OA, adding prognostic information and assisting in personalising the early management of both populations.
On the reduction of instability of label propagation algorithm
Authors: Yazdani Maryam , Moeini Ali , Mazoochi Mojtaba , Rahmani Farzaneh , Rabiei Leila
Published: September 2022

Label propagation algorithm is widely used for community detection in a network due to its linear time complexity. It also does not need any predefined information such as the number of communities. However, the results of this algorithm are not stable because of the randomness strategy used in its propagation process. In this paper, a modification on label propagation strategy is proposed in which labels are propagated based on nodes importance defined by their positions and popularity among neighbors. The proposed strategy is an updating process which reduces the instability of the label propagation algorithm. Experiments on real-world and synthetic networks show that the proposed method improves accuracy in terms of modularity, NMI and ARI. Also, the method has an acceptable execution time.
ALGORITHM FOR THE SOLUTION OF NONLINEAR VARIABLE-ORDER PANTOGRAPH FRACTIONAL INTEGRO-DIFFERENTIAL EQUATIONS USING HAAR METHOD
Authors: SHAH KAMAL , AMIN ROHUL , ALI GAUHAR , MLAIKI NABIL , ABDELJAWAD THABET
Published: September 2022

This research work is related to establish a powerful algorithm for the computation of numerical solution to nonlinear variable order integro-differential equations (VO-IDEs). The adopted procedure is based on the Haar Wavelet Method (HWM) to compute the required numerical solution to the proposed problem. Further, in the considered problem, a proportional-type delay term is involved, which is also known as the pantograph equation. For a physical problem to investigate the computational purposes, we need to first ensure its existence. For this purpose, we utilize classical fixed results given by Banach and Schauder to establish the sufficient conditions for existence of at least one approximate solution to the proposed problem. Two pertinent examples are given, where the error analysis is also recorded.
Graph Distances for Determining Entities Relationships: A Topological Approach to Fraud Detection
Authors: Calabuig J. M. , Falciani H. , Sapena A. Ferrer , Raffi L. M. García , Pérez E. A. Sánchez
Published: September 2022

A new model for the control of financial processes based on metric graphs is presented. Our motivation has its roots in the current interest in finding effective algorithms to detect and classify relations among elements of a social network. For example, the analysis of a set of companies working for a given public administration or other figures in which automatic fraud detection systems are needed. Given a set [Formula: see text] and a proximity function [Formula: see text], we define a new metric for [Formula: see text] by considering a path distance in [Formula: see text] that is considered as a graph. We analyze the properties of such a distance, and several procedures for defining the initial proximity matrix [Formula: see text]. Using this formalism, we state our main idea regarding fraud detection: financial fraud can be detected because it produces a meaningful local change of density in the metric space defined in this way.
Bardeen compact stars in modified f(R) gravity with conformal motion
Authors: Farasat Shamir M. , Rashid Aisha
Published: September 2022

The main emphasis of this paper is to find the viable solutions of Einstein Maxwell field equations of compact star in context of modified [Formula: see text] theory of gravity. Two different models of modified [Formula: see text] gravity are considered. In particular, we choose isotropic matter distribution and Bardeen’s model for compact star to find the boundary conditions as an exterior space-time geometry. We use the conformal Killing geometry to compute the metric potentials. We discuss the behavior of energy density and pressure distribution for both models. Moreover, we analyze different physical properties such as behavior of energy density and pressure, equilibrium conditions, equation of state parameters, causality conditions and adiabatic index. It is noticed that both [Formula: see text] gravity models are suitable and provide viable results with Bardeen geometry.
On Kähler structures of Taub-Nut and kerr spaces
Authors: Kelekçi̇ Özgür
Published: September 2022

In this paper, we study the Kählerian nature of Taub-NUT and Kerr spaces which are gravitational instanton and black hole solutions in general relativity. We show that Euclidean Taub-NUT metric is hyper-Kähler with respect to the usual almost complex structures by employing an alternative explicit coframe, and Euclidean Kerr metric is globally conformally Kähler. We also show that conformally scaled Euclidean Kerr space admits a Kähler structure by applying a conformal scaling factor stemming from the Lee-form of the original metric or alternatively a factor coming from self-dual part of the Weyl tensor [Formula: see text].
The Darboux trihedrons of timelike surfaces in the Lorentzian 3-space
Authors: Li Yanlin , Mazlum Sümeyye Gür , Şenyurt Süleyman
Published: September 2022

The parameter curves [Formula: see text] and [Formula: see text] intersecting under the angle [Formula: see text] on a timelike surface and any curve [Formula: see text] passing through the same point with these curves have six different cases according to their causal characters. In this study, the Darboux trihedrons of these three curves and the Darboux instantaneous rotation vectors of these trihedrons are separately calculated for each of these six cases, and the relationships between these vectors are given. In addition, some theorems and results have been obtained on this surface. Besides, the special cases where the parameter curves [Formula: see text] and [Formula: see text] intersect perpendicularly are examined and these cases are compared with previous studies.
Multifluid cosmology in f(G) gravity
Authors: Munyeshyaka Albert , Ayirwanda Abraham , Twagirayezu Fidele , Murorunkwere Beatrice , Ntahompagaze Joseph
Published: September 2022

The treatment of (1+3)-covariant perturbation in a multifluid cosmology with the consideration of [Formula: see text] gravity, [Formula: see text] being the Gauss–Bonnet term, is done in this paper. We define a set of covariant and gauge-invariant variables to describe density, velocity and entropy perturbations for both the total matter and component fluids. We then use different techniques such as scalar decomposition, harmonic decomposition, quasi-static approximation together with the redshift transformation to get simplified perturbation equations for analysis. We then discuss a number of interesting applications like the case where the universe is filled with a mixture of radiation and Gauss–Bonnet fluids as well as dust with Gauss–Bonnet fluids for both short- and long-wavelength limits. Considering polynomial [Formula: see text] model, we get numerical solutions of energy density perturbations and show that they decay with increase in redshift. This feature shows that under [Formula: see text] gravity, specifically under the considered [Formula: see text] model, one expects that the formation of the structure in the late Universe is enhanced.
Design of a Robust MAC Protocol for LoRa
Authors: Ahmar Absar-Ul-Haque , Aras Emekcan , Nguyen Thien Duc , Michiels Sam , Joosen Wouter , Hughes Danny
Published: September 2022

Low-power wide-area networks enable large-scale deployments of low-power wireless devices. LoRaWAN is a long-range wireless technology that has emerged as a low-power and low data rate solution to support Internet of Things applications. Although LoRaWAN provides a low-power and cost-efficient networking solution, recent literature shows that it performs poorly in terms of reliability and security in dense deployments due to the uncoordinated (ALOHA-based) nature of the MAC (medium access control) protocol. Furthermore, LoRaWAN is not robust against selective jamming attacks. This article proposes CRAM: a time-synchronized cryptographic frequency hopping MAC protocol designed for the LoRa physical layer. CRAM reduces the contention by fairly exploiting the available frequency space and maximizes the entropy of the channel hopping algorithm. We develop a large physical testbed and a simulator to thoroughly evaluate the proposed protocol. Our evaluations show that CRAM significantly improves reliability and scalability and increases channel utilization while making selective jamming difficult to perform compared to the standard LoRaWAN protocol.
Extended Residual Power Series Algorithm for Boundary Value Problems
Authors: Qayyum Mubashir , Fatima Qursam , Sohail Muhammad , El-Zahar Essam R. , Gokul K. C.
Published: September 2022

In this article, modification of the residual power series method (RPSM) is proposed for higher order boundary value problems (BVPs). The proposed algorithm is tested against various linear and nonlinear BVPs of orders nine up to thirteen. For the efficiency check of RPSM, obtained series solutions are compared with other available results in the literature. Analysis indicates that RPSM is better in terms of accuracy as compared to other mentioned schemes. As RPSM is applicable to BVPs without linearization, discretization, and perturbation, hence practically it is the best suitable solution tool for more complex BVPs in science and engineering.
Antidepressant Effect of Ketamine on Inflammation-Mediated Cytokine Dysregulation in Adults with Treatment-Resistant Depression: Rapid Systematic Review
Authors: Sukhram Shiryn D. , Yilmaz Grozdena , Gu Jianying
Published: September 2022

Background. Major depressive disorder (MDD) and treatment-resistant depression (TRD) represent a global source of societal and health burden. To advise proper management of inflammation-related depression among TRD patients, it is important to identify therapeutic clinical treatments. A key factor is related to proinflammatory cytokines such as interleukin- (IL-) 1β, IL-6, and tumor necrosis factor- (TNF-) α which have been implicated in the pathogenesis of depressive symptoms in MDD patients. Ketamine may provide an anti-inflammatory therapeutic strategy by targeting proinflammatory pathways associated with depressive disorders, which may be exacerbated in the ageing population with TRD. Objective. Despite a burgeoning body of literature demonstrating that inflammation is linked to TRD, there is still a lack of comprehensive research on the relationship between proinflammatory biomarkers and ketamine’s antidepressant effect on TRD patients. Method. The Cochrane Library and PubMed/MEDLINE databases were systematically searched from inception up to February 1, 2022, adopting broad inclusion criteria to assess clinical topics related to the impact of ketamine on inflammatory cytokines in TRD patients. The present work is in compliance with the World Health Organization Rapid Review Guide. Results. Five out of the seven studies examined in this review show that ketamine infusion may reduce depressive symptoms with a quick start of effect on TRD patients. Based on the Montgomery-Åsberg Depression Rating Scale (MADRS) and Hamilton Depression Rating Scale (HAM-D) scores, the overall response rate for ketamine was 56%; that is, 56% of those treated with ketamine had MADRS/HAM-D scores decreased by at least 50%. Conclusions. While the anti-inflammatory effects of ketamine modulate specific proinflammatory cytokines, its rapid antidepressant effect on TRD patients remains inconsistent. However, our study findings can provide a reliable basis for future research on how to improve systemic inflammatory immune disorders and mental health. We suggest that ketamine infusion may be part of a comprehensive treatment approach in TRD patients with elevated levels of depression-specific inflammatory biomarkers.
Some Results about Weak UP‐algebras
Authors: Chaudhry Muhammad Anwar , Fahad Asfand , Qureshi Muhammad Imran , Riasat Urwa
Published: September 2022

We introduce a new class of algebras, weak UP‐algebras, briefly written as WUP‐algebras, as a wider class than the classes of UP‐algebras and KU‐algebras. We investigate fundamental aspects including maximal elements, branches and the subalgebra consisting of maximal elements of a WUP‐algebra. We also study regular congruences on a WUP‐algebra as well as the corresponding quotient WUP‐algebras. We prove that the congruence generated from the branches of a WUP‐algebra is regular and the corresponding quotient algebra χ/q is isomorphic to the WUP‐algebra Max(χ), the subalgebra of χ consisting of its maximal elements.
Enterprise Financial Early Warning Based on Improved Whale Optimization Algorithm: Optimize the Perspective with Indicators
Authors: Li Bowei , Di Mengzui , Wei Zikun , Qiao Hong , Li Xuzhao
Published: September 2022

The key to solving the problem of redundant financial indicators in addressing financial warning issues is to reduce the dimensionality of the original financial indicators. This paper proposes a model based on the whale optimization algorithm with mixed strategy (IWOA) combined with support vector machine (SVM), namely, the IWOA-SVM early warning model, which simultaneously performs index optimization and dimensionality reduction, and financial risk early warning identification. This paper takes a total of 302 enterprises specially treated in Shanghai and Shenzhen stock exchanges and normal enterprises of the same specification as the research samples to design the model. The results show that the improved whale optimization algorithm has better optimization speed and accuracy and improves the search ability of the original algorithm for the optimal solution. Compared with other dimensionality reduction methods, the IWOA-SVM model has the lowest index dimension after dimensionality reduction and has more excellent recognition effect. The dimensionality reduction results have certain universality for different classifiers, which provides a new idea for the selection of indicators for financial early warning.
Diverse Soliton Structures of the (
2
+
1
)-Dimensional Nonlinear Electrical Transmission Line Equation
Authors: Li Peng-Fei , Wang Kang-Jia
Published: September 2022

In this work, the (

2
+
1

)-dimensional nonlinear electrical transmission line equation (NETLE) is investigated by applying three recent technologies, namely, the variational approach, Hamiltonian approach, and energy balance approach. Diverse exact soliton solutions such as the bright, bright-like, kinky bright, bright-dark soliton, and periodic soliton solutions are successfully constructed. The outlines of the different solutions are shown in the form of the 3-D plot with the help of the Wolfram Mathematica. It reveals that the used methods are concise and effective and are expected to provide some inspiration for the study of travelling wave solutions of the PDEs in physics.
[Retracted] The English Teaching Methods in the Field of Public Health in Colleges and Universities Based on Artificial Intelligence Technology
Authors: Li Shan
Published: September 2022

Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities to continuously optimize the English teaching system. This technology can help colleges and universities to carry out English education in the field of public health and can improve the overall quality of English teaching in colleges and universities. Artificial intelligence technology is related to the optimization of English teaching environment in colleges and universities. At the same time, artificial intelligence technology also affects the development of society and the future of the country. Artificial intelligence technology provides more accurate data resources for English teaching in the field of public health in colleges and universities. It also provides rich and reliable educational technology means for teachers. This technology improves the scientific nature of English education in the field of public health in colleges and universities. This paper comprehensively uses a variety of methods such as case empirical analysis and qualitative analysis to analyze the application mode of artificial intelligence technology in English teaching. This paper closely integrates artificial intelligence technology with English education in the field of public health in colleges and universities. College English teaching methods, teachers’ personal factors, and teacher‐student relationship will all have an impact on students’ health. This paper makes a comprehensive analysis of the theoretical basis and actual situation of English teaching in colleges and universities, and then constructs an innovative system of English education in the field of public health in colleges and universities. Based on this, the text adopts a structured analysis method to conduct an in‐depth analysis of the application mode of artificial intelligence technology. This paper analyzes in detail the opportunities and challenges faced by the development of public health education in colleges and universities. At the same time, this paper also summarizes the objective laws of the development of public health education, and then comprehensively analyzes the impact of artificial intelligence technology on the English education model in colleges and universities.
Analysis of Multifactor Influence Model on Energy Dissipation Rate of Rough-Strips Energy Dissipator in the Spillway Bend
Authors: Zhang Honghong , Mu Zhenwei , Fan Fan , Li Fanqi
Published: September 2022

The rough-strips energy dissipator (R-SED) is applied to the bottom of the spillway bend and can play the role of energy dissipation and flow stabilization. In this study, based on 18 sets of orthogonal tests and the principle of dimensional analysis, a multifactor influence model of R-SED’s energy dissipation rate was proposed. A dimensionless factor k was introduced, which can reflect the comprehensive characteristics of the geometric dimensions of R-SEDs. The multifactor influence model of the energy dissipation rate considered nine factors, including bend radius of curvature Rc, bend width B, flow velocity of the bend inlet

v

, R-SED’s average height hL, R-SED’s arrangement angle θ, R-SED’s arrangement spacing ∆L, fluid density ρ, dynamic viscosity coefficient μ, and gravitational acceleration

g

. The residual sum of squares of the model (RSS) was 6.6% and the correlation coefficient R was 83.2% (>80%), indicating the universality and feasibility of the model. The independent variables of the multifactor model of the energy dissipation rate were ranked according to the Pearson value in descending order: (ΔL/Rc) > (θ) > (B/Rc) > (hL/Rc) > (1/Fr2). This indicates that R-SEDs’ layout parameters showed larger effects on the multifactor model of the energy dissipation rate, compared with the engineering layout parameters of the spillway. The maximum relative error between the predicted value of the multifactor model and the measured value of the validation group was 6.28%, indicating good agreement. In the orthogonal tests, scenario 5 had the highest energy dissipation rate (44.83%) with k = 0.023; scenario 16 had the largest k value (0.043), with an energy dissipation rate of 40.78%. The multifactor influence model of R-SEDs’ energy dissipation rate proposed in this paper was a semi-theoretical and semi-empirical calculation formula, which can provide reference and support for similar practical engineering designs.
An Optimization Approach considering Passengers’ Space-Time Requirements for Bus Bridging Service under URT Disruption
Authors: Shao Lihua , Song Liying
Published: September 2022

Rapid urbanization and growth of population in megacities generate severe pressures on urban rail transit (URT) system. The quantity and frequency of disruptive events have increased significantly, which might have obvious adverse impacts. A large number of passengers are stranded at disrupted URT station when a disruptive event occurs. One essential solution for passenger evacuation is the bus bridging service. This paper is aimed at addressing the passenger evacuation problem caused by a disruptive event in the URT network, by proposing a bus bridging service model considering the passengers’ space-time requirements. The model is proposed to minimize the waiting time of passengers and considers factors including bus service capacity limitations, bus stop parking capacity, and the maximum bridging time limit of a single bus. Buses are assumed to provide bridging service on either the local bus route or the direct bus route. The optimal routes and scheduling plans of bridging bus are designed. The model is applied to an example of a disruptive event in Shanghai URT line 9. The results of this example show that the proposed model is capable of reducing the waiting time of passengers and the number of buses used by 3.2% and 24.7%, compared with the traditional bus bridging service. Further analysis of the example shows that it is not a cost-effective solution to reserve a large number of buses for URT disruption. Decision-makers should comprehensively trade off between passengers’ space-time demands and monetary costs of bus bridging service.
Experimental Study on Calculation Method of Drainage Capacity of Drainage Facilities Affected by Overtopping on Artificial Island
Authors: Ge Long-zai , Chen Han-bao , Liu Hai-yuan
Published: September 2022

The drainage capacity design of offshore artificial island and inland urban drainage facilities have a great differences in the boundary conditions involved. Therefore, in order to ensure the safety and reliability of the drainage facilities of the Shenzhen-Zhongshan channel’s East artificial island under extreme weather conditions, the coastline of the Southwest open section of the artificial island is identified as a subject for carrying out the research study. This island is affected by offshore waves and the superposition of rainstorms, therefore the calculation method of drainage capacity of artificial island drainage facilities is demonstrated in the article. Through the physical model testing based on soft computing techniques, some recommendations are suggested for preserving the environment, where the optimization schemes are meeting the design requirements of wave and landscape based on correlations between them. Secondly, the adjustment of drainage capacity is suggested to analyze the overtopping of waves on the island and then the final scheme meeting the drainage capacity is obtained. By introducing the comprehensive influence coefficient

k

of overtopping volume and current velocity caused by overtopping under the action of superimposed waves, a new calculation method and simple calculation formula suitable for the drainage capacity in the artificial island are proposed. The proposed method is verified by the drainage capacity test results of the southeast shoreline. The results show that the proposed method has good accuracy and can provide reference for the design and estimation of drainage capacity of similar projects to preserve the environment. The research results based on mathematical problems in engineering not only solve the practical problems of major projects of Shenzhen China channel but also provide valuable inputs for similar projects.
Mechanisms of Banxia Xiexin Decoction Underlying Chronic Atrophic Gastritis via Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulations
Authors: Chang Cheng , Feng Weiqi , Sun Min , Yu Xiaowen , Sun Zhiguang
Published: September 2022

Chronic atrophic gastritis (CAG) is a common chronically digestive disease which is notoriously characterized by atrophy of the epithelium and glands of the gastric mucosa, reduced number, thinning of the gastric mucosa, thickening of the mucosal base, or pyloric glandular hyperplasia and intestinal glandular hyperplasia, or with atypical hyperplasia. Banxia Xiexin decoction (BXD) has been applied for two thousand years and is considered an effective therapy for functional dyspepsia, gastroesophageal reflux disease and colon cancer. In this current study, to probe into the underlying mechanism of BXD on CAG, network pharmacology was conducted to collect druggable ingredients and predicted targets of BXD and the CAG-associated targets were harvested to take intersection with druggable ingredients from BXD predicted targets to obtain potential critical action targets. Subsequently, GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were conducted to elucidate the underlying mechanisms and roles from the perspective of overall pathways and cellular functions. Eventually, molecular docking integrated with molecular dynamics simulations was conducted to further investigate the mechanism of action of BXD active ingredients on CAG from drug molecule-target interactions and to provide a theoretical basis for BXD drug development.
Improvement and Experimental Explore on Coordinated Control of Kinematic Mechanism of FDM 3D Printer
Authors: Li Guozhu
Published: September 2022

As the main component of the 3D printing industry, the fused deposition process covers all aspects of the industry with its advantages of low R&D investment, high practicability, and open source programs. However, due to process problems, problems have arisen in terms of printing efficiency and molding quality. To this end, we designed a large-scale multinozzle FDM printing device using the high-current fused deposition (FDM) printing principle. The defects of small size, slow printing speed, and low precision are deeply studied, and the machine structure is optimized according to the structural strength analysis. In this paper, the theoretical design and static analysis of the overall mechanical part of the large-scale FDM device are carried out, and then, the selection of the movement organization structure and movement method is theoretically analyzed. A modular flow chart is designed for the control system to coordinate and control the parallel and precise operation of multiple nozzles, and the relationship function between the main controller, power driver, and heating module is designed. By modifying the firmware parameter command, we can find out the optimal method running on the platform and discuss the function usage of the slicing software in detail. According to the current problems of FDM printing equipment, various factors affecting printing speed were analyzed from the perspective of printing accuracy, and the process parameters of 3D printer were studied through orthogonal experiments. Speed, nozzle temperature, idling speed, and fill rate were studied, and the relationship between factors affecting printing speed and printing accuracy was obtained. Use a simple model print to measure the overall performance of your product. The stability of the system is verified by short-term and long-term printing tests. The analysis results show that the forming performance and stability of the large-scale FDM are improved significantly.
Construction and Practice of English Writing Model Based on Random Matrix
Authors: Chen Fengping , Guo Xuan
Published: September 2022

Writing is an indispensable part of English comprehensive ability. It can test learners’ ability in viewpoint content, text organization, language use, and so on. In view of the many problems existing in the English writing of contemporary primary and middle school students, high school students and even college students, this paper proposes an English writing model based on random matrix. This method collects the necessary English vocabulary information through the English word database and combines the M-P law and the density spectrum value of the hybrid matrix to accurately locate students’ writing needs, clarify their writing needs, identify, and construct dynamic English compositions. The random matrix is used to judge and test the English level threshold of different students, so as to get the abnormal use of words when students write. By comparing the predicted data of students’ abnormal vocabulary with the accurate vocabulary data, different students’ writing ability is judged, and corresponding suggestions are given, and qualified writing formats are provided. The experimental results show that the English writing model based on random matrix has strong learning ability and judgment, and can better achieve one-to-one targeted teaching.