bluuebunny/crossref_metadata_2025 huggingface dataset:
Compressor Maps and Coupling: Symmetry, Geometry, and Universality
Authors: Iwrey Benjamin , Johnson Paul K.
Published: October 2022

The predecessor of this paper (GT2021-60012) introduced the Symmetry (S’-) framework of compressor map representation. This framework exhibits a natural simplicity of expression in comparison with the common BETA framework, enables relatively simple coupling of an arbitrary number of maps in series, and posits a novel instability mechanism termed “snap equilibrium.” A one-dimensional numerical simulation is constructed to simulate snap equilibrium and its associated hysteresis, exactly as predicted in the S’-framework by inspecting the maps at their interface. Both two-map and three-map snap equilibria are simulated, the latter demonstrating that snap equilibrium may be triggered between two maps by the presence of a third.

The geometrical structure of the S’-framework is then explored in depth. Any given constant-geometry map can be expressed completely as either of two related vector fields — inlet-exit and input-output — in the corrected speed-corrected flow abstract space. The geometry of these vector fields is examined, and the nature of speedlines themselves is reinterpreted. The possibility of breaking a given map into its constituent maps is explored. Finally, a set of features common to all constant-geometry maps is identified in corrected speed-corrected flow space, and their implications are discussed.
New Concept for Design in Turbomachinery Applications using Full RANS Gradient Methodology
Authors: Del Rio Armando , Casartelli Ernesto , Fleischli Benno , Mangani Luca
Published: October 2022

Centrifugal compressors are mainly designed with the best efficiency point in mind and the focus oriented towards the impeller. The vaned diffuser geometry is usually developed using simple shapes, such as prismatic blades or wedges, which are unable to account for the flow distortion at the impeller outlet. Investigations of diffuser modifications using CFD during the design phase can help to extend the operating range. In order to assess the effect of such modifications, simulations in off-design conditions need to be performed. Accurate predictions of local flow structures at such conditions require a robust flow solver with mixing-plane interfaces and advanced turbulence modelling capabilities. In recent years diffuser modifications were performed mainly based on manual trial-and-error approaches and show considerable potential for improvements. To accelerate the process and allow automation, which is crucial in industrial applications, it is suggested to use an adjoint-based optimization algorithm for diffuser shape design. In this work a discrete adjoint solver implemented into a robust pressure-based CFD framework was used. While many optimization studies follow the frozen-turbulence approach, which essentially ignores the dependency of the sensitivity on the turbulence quantities, the present adjoint solver fully includes such effects. Automatic differentiation even allows for flexibility with respect to the choice of turbulence model: Any model available in the primal solver can also be used in the adjoint solver. In this particular case the k-ε EWT model was used, since it shows good convergence behavior and is capable of predicting the machine characteristic even at off-design conditions. Mesh morphing was realized via the Free Form Deformation method, which provides stable mesh deformation and offers a simple and fast set-up procedure. Several optimizations were conducted for the RWTH Aachen “Radiver” centrifugal compressor case with vaned diffuser. It was shown that an optimization strategy using a multi-operating-point approach, considering part- and overload conditions, is capable of improving the peak efficiency as well as the overall shape of the machine characteristic.
Investigation of Impeller Backface Cavity Flowfield Using CFD and a One-Dimensional Flow Solver
Authors: Erdem E. , Sertcakan M. C. , Sal S. , Dogu Y. , Yalcinkaya A.
Published: October 2022

This article aims at the investigation of impeller backface cavity flowfield using Computational Fluid Dynamics (CFD) and one-dimensional flow solver for a representative backface cavity. For initial validation the test rig data from Hart and Turner [5 and 6] is employed at various leakage flows and inlet swirl ratios. For impeller backface cavity in consideration, rather than covering a wide range of impeller leakage flows, which is irrelevant for engine operations, different rotational speeds representing different phases of engine running conditions are varied. The cavity flowfield is composed of two flows entering the cavity, impeller leakage and Compressor Discharge Pressure (CDP) seal leakage flows. The flowfield displays the dominant character of torques induced by the stator and the rotor for the majority of the cavity, towards the lower radii radially inward flow starts to gain swirl and when CDP seal leakage flow mixes with this flow, swirl ratios reach nearly unity. A fraction of mixture flow leaves the cavity thru the outlet and remaining circulates at bottom left corner and gets pumped up by the backface surface.
Design Sensitivity of a 1-1/2 Stage Unshrouded High Work Turbine Using Very-Large Eddy Simulations
Authors: Gonzalez-Martino Ignacio
Published: October 2022

A numerical study has been conducted to assess the performance sensitivity of a 1-1/2 stage turbine to variations in design or operating conditions. The impact of the rotor tip gap, blade and vane fillets, and upstream boundary layer turbulence are assessed with respect to a baseline model and a comprehensive set of experimental data. Global stage performance, radial distribution of relevant quantities such as pressure and turning angles, as well as unsteady pressure distributions in the planes between rows were available as reference data.

Very-large eddy simulations using time-marching Lattice-Boltzmann methods are performed here to analyze in detail the compressible and highly turbulent flow features. In the present work, the complete 1-1/2 stage turbine with time-accurate moving rotor geometry has been simulated. This means that no blade reduction technique or almost-periodic flow hypothesis have been used in the simulation. This will help in providing a better understanding of the complex mechanisms occurring in the turbine channel, for the different numerical models. Moreover, thorough comparisons to experimental data will help in validating the numerical approach for future similar turbomachinery cases.
About the bosonic decays of heavy Higgs states in the (N)MSSM
Authors: Domingo Florian , Paßehr Sebastian
Published: October 2022

The heavy, doublet-dominated Higgs bosons expected in Two-Higgs-Doublet-Model-like extensions of the Standard Model are obvious targets for searches at high-energy colliders, and considerable activity in this sense is currently employed in analyzing the results of the Large Hadron Collider. For sufficiently heavy states, the $$SU(2)_\textrm{L}$$

S
U

(
2
)

L

symmetry drastically constrains the decays of these new scalars. In models that contain only additional Higgs doublets, fermionic decay channels are expected to dominate, although some bosonic modes may lead to cleaner signals. The situation is very different if the Higgs sector is further extended by singlet states and the singlet-dominated scalars are kinematically accessible, in which case the Higgs-to-Higgs widths may even become dominant. Yet, a quantitative interpretation of the experimental data in terms of a specific model also runs through the control of radiative corrections in this model. In this paper, we examine the bosonic decays of the heavy, doublet-dominated Higgs states in the MSSM and the NMSSM at full one-loop order, insisting on the impact of the $$SU(2)_\textrm{L}$$

S
U

(
2
)

L

symmetry and the effects of infrared type, in particular, the emergence of sizable non-resonant contributions to the three-boson final states.
Coincident gauge for static spherical field configurations in symmetric teleparallel gravity
Authors: Bahamonde Sebastián , Järv Laur
Published: October 2022

In symmetric teleparallel gravities, where the independent connection is characterized by nonmetricity while curvature and torsion are zero, it is possible to find a coordinate system whereby the connection vanishes globally and covariant derivatives reduce to partial derivatives – the coincident gauge. In this paper we derive general transformation rules into the coincident gauge for spacetime configurations where the both the metric and connection are static and spherically symmetric, and write out the respective form of the coincident gauge metrics. Taking different options in fixing the freedom in the connection allowed by the symmetry and the field equations, the Schwarzschild metric in the coincident gauge can take for instance the Cartesian, Kerr–Schild, and diagonal (isotropic-like) forms, while the BBMB black hole metric in symmetric teleparallel scalar–tensor theory a certain diagonal form fits the coincident gauge requirements but the Cartesian and Kerr–Schild forms do not. Different connections imply different value for the boundary term which could in principle be physically relevant, but simple arguments about the coincident gauge do not seem to be sufficient to fix the connection uniquely. As a byproduct of the investigation we also point out that only a particular subset of static spherically symmetric connections has vanishing nonmetricity in the Minkowski limit.
Observational constraints on the fractal cosmology
Authors: Asghari Mahnaz , Sheykhi Ahmad
Published: October 2022

In this paper, we explore a fractal model of the universe proposed by Calcagni (J High Energy Phys 03:120, 2010) for a power-counting renormalizable field theory living in a fractal spacetime. Considering a timelike fractal profile, we derived field equations in fractal cosmology, in order to explore the structure formation and the expansion history in fractal universe. Numerical investigations based on matter power spectra diagrams report higher structure growth in fractal cosmology, being in contrast to local galaxy surveys. Additionally, according to the evolution of Hubble parameter diagrams, it can be understood that Hubble constant would decrease in fractal cosmology, which is also incompatible with low redshift estimations of $$H_0$$

H
0

. So, concerning primary numerical studies, it seems that fractal cosmology is not capable to alleviate the tensions between local and global observational probes. Then, in pursuance of more accurate results, we constrain the fractal cosmology by observational data, including Planck cosmic microwave background (CMB), weak lensing, supernovae, baryon acoustic oscillations (BAO), and redshift-space distortions (RSD) data. The derived constraints on fractal dimension $$\beta $$
β
indicate that there is no considerable deviation from standard model of cosmology.
A Semi-Analytical Finite Element Framework for Lamb Waves in Soft Compressible Plates Considering Strain Stiffening Effect
Authors: Patra Asesh Kumar , Sharma Atul Kumar , Joglekar D. M. , Joglekar M. M.
Published: October 2022

This paper investigates the elastic wave propagation through soft materials that are being subjected to finite deformations. The nonlinear elastic and linearized incremental theories have been exploited to formulate governing wave equations and elastic moduli in Lagrangian space. Semi-analytical finite element (SAFE) method, a numerical approach has been formulated for computing dispersive relations of guided waves in compressible hyper-elastic plates. This framework requires finite element discretization of the cross section of the waveguide and harmonic exponential function assumes the motion along the wave propagation direction. Here, explicit phase velocity results have been shown for soft materials with a prominent stiffening effect by employing the Gent model, and these results are analyzed for elastic wave propagation through compressible materials. It has been noticed that Lamb waves have a strong dependence on the frequency-thickness product, prestretch, and direction of wave propagation. Moreover, with the strain stiffening effect, the dependence becomes stronger, especially for fundamental symmetric and anti-symmetric modes. The numerical results display that at certain prestretch the Gent material encounter snap-through instability resulting from geometrical and material nonlinearities. The influence of material properties like Gent constant and direction of wave propagation on snap-through instability has been discussed. The proposed SAFE framework reveals that finite deformations can affect elastic wave propagation through stiffness and compressibility.
Enhancing Youth Self-Regulation Through Wearable Apps: Increasing Usage Through Participatory Design in Low Income Youth
Authors: Persa Nicholas , Anderson Craig G. , Martinez Richard , Collins Max , Anderson-Coto Maria J. , Squire Kurt D.
Published: October 2022

Managing attention, progressing towards goals, and monitoring behaviors are elements of self-regulation (SR). SR applications based on contemplative practices such as breath counting have demonstrated gains in field studies but have failed to engage youth without coercion. Prior research generated behavioral and neurological changes, but was disliked by youth. This three-part study includes a participatory design workshop, application redesign, and subsequent field deployment to understand how wearable devices can support self-regulation. Twenty-seven youth designed activities that revealed interest in and models of self-regulation that became part of a smartwatch app. Researchers revisited and redesign the application based on youth feedback, and then released the redesigned application (some of whom participated in workshops, some of whom did not). Redesigning the application to be responsive to youth needs resulted in higher levels of satisfaction than previously observed. Youth also used this application more often and reported higher use. Three design tensions persisted: (1) Breath counting applications as attention grabbing vs. attention cultivating and (2) breath counting activities as a relaxation activity vs. a mental workout, and (3) exposing youth to meditation and breath counting as a strategy for developing healthy minds vs. an institutionalized or compulsory required action. Activity occupied positions along these continua, which creates associated challenges for researchers. A fruitful design space exists for researchers to integrate attention focusing into activities that youth value, which can include stress reduction or mindfulness training, but also could be simply to improve their academic work.
Algorithms and Data Structures for Hyperedge Queries
Authors: Bertrand Jules , Dufossé Fanny , Singh Somesh , Uçar Bora
Published: October 2022

We consider the problem of querying the existence of hyperedges in hypergraphs. More formally, given a hypergraph, we need to answer queries of the form: “Does the following set of vertices form a hyperedge in the given hypergraph?” Our aim is to set up data structures based on hashing to answer these queries as fast as possible. We propose an adaptation of a well-known perfect hashing approach for the problem at hand. We analyze the space and runtime complexity of the proposed approach and experimentally compare it with the state-of-the-art hashing-based solutions. Experiments demonstrate the efficiency of the proposed approach with respect to the state-of-the-art.
Threat-Based Simulation of Data Exfiltration Toward Mitigating Multiple Ransomware Extortions
Authors: Mundt Michael , Baier Harald
Published: October 2022

Network-based attacks and their mitigation are of increasing importance in our ever-connected world. Often network-based attacks address valuable data, which the attacker either encrypts to extort ransom or steals to make money reselling, or both. After the infamous WannaCry and NotPetya ransomware attacks in 2017, companies stepped up their cyber defenses. More emphasis was placed on backup and recovery processes so that even when files were destroyed, organizations had copies for quick recovery. However, cyber criminals have also adapted their methods. Instead of simply encrypting files, double extortion ransomware now exfiltrates the data first, before encrypting it. As a consequence, the early detection and prevention of data exfiltration is one of today’s major challenges of institutions connected to the Internet. If attempts to illegal data exfiltration are successfully detected, the attacked institution should address a probable subsequent encryption attack step as well. In particular, valuable business assets must be checked for unauthorized access and need to be protected. However, due to the bulk of network traffic and persistent data, automation is a key requirement to successfully defend contemporary threats. The main goal of this article is to present a concept and its initial evaluation to achieve automation of data exfiltration mitigation in a targeted manner. Our concept consists of two main steps. Based on recognized international approaches used in cyber threat intelligence, an automatic procedure on the base of the MITRE Adversarial Tactics, Techniques Common Knowledge (ATT&CK) framework for deriving current threats with respect to data exfiltration is presented in the first place. In the spirit of the Digital Threats: Research and Practice (DTRAP) forum, a practical approach is chosen in addition to the theory in this manner. Our evaluation reveals that we are able to automatically identify the most relevant recent risks of unauthorized data exfiltration. In our second step, we present the design of a simulation gear based on the attacks extracted from the MITRE ATT&CK framework. The aim is to simulate the greatest threats before they actually occur in the operational environment. The strict focus on the threats of data exfiltration characterizes our solution and makes our approach an ideal addition to existing solutions. We provide an evaluation of this initial simulation concept and its underlying technology for the implementation to show that we are on the right track.
Evaluating the Robustness of Click Models to Policy Distributional Shift
Authors: Deffayet Romain , Renders Jean-Michel , de Rijke Maarten
Published: October 2022

Many click models have been proposed to interpret logs of natural interactions with search engines and extract unbiased information for evaluation or learning. The experimental set-up used to evaluate them typically involves measuring two metrics, namely the test perplexity for click prediction and nDCG for relevance estimation. In both cases, the data used for training and testing is assumed to be collected using the same ranking policy. We question this assumption.

Important downstream tasks based on click models involve evaluating a different policy than the training policy, i.e., click models need to operate under
policy distributional shift
. We show that click models are sensitive to it. This can severely hinder their performance on the targeted task: conventional evaluation metrics cannot guarantee that a click model will perform equally well under distributional shift.

In order to more reliably predict click model performance under policy distributional shift, we propose a new evaluation protocol. It allows us to compare the relative robustness of six types of click models under various shifts, training configurations and downstream tasks. We obtain insights into the factors that worsen the sensitivity to policy distributional shift, and formulate guidelines to mitigate the risks of deploying policies based on click models.
The Effect of Allograft Inflammatory Factor-1 on Inflammation, Oxidative Stress, and Autophagy via miR-34a/ATG4B Pathway in Diabetic Kidney Disease
Authors: Jianbing Hao , Xiaotian Liu , Jie Tang , Xueying Chang , Honge Jin , Bo Zhu , Lirong Hao , Lei Zhang
Published: October 2022

Increasing evidence suggests that disorders of inflammation, oxidative stress, and autophagy contribute to the pathogenesis of diabetic kidney disease (DKD). This study attempted to clarify the effect of allograft inflammatory factor-1 (AIF-1), miR-34a, and ATG4B on inflammation, oxidative stress, and autophagy in DKD both in vitro and in vivo experiments. In vivo, it was found that the levels of AIF-1, miR-34a, oxidative stress, and inflammatory factors were significantly increased in blood and urine samples of DKD patients and mouse models and correlated with the level of urinary protein. In vitro, it was also found that the expressions of AIF-1, miR-34a, ROS, and inflammatory factors were increased, while ATG4B and other autophagy related proteins were decreased in human renal glomerular endothelial cells (HRGECs) cultured with high concentration glucose medium (30 mmol/L). When AIF-1 gene was overexpressed, the levels of miR-34a, ROS, and inflammatory factors were significantly upregulated, and autophagy-related proteins such as ATG4B were downregulated, while downregulation of AIF-1 gene had the opposite effect. In addition, miR-34a inhibited the expression of ATG4B and autophagy-related proteins and increased the levels of ROS and inflammation. Furthermore, the result of luciferase reporter assay suggested that ATG4B was the target gene of miR-34a. When ATG4B gene was overexpressed, the level of autophagy was upregulated, and inflammatory factors were downregulated. Conversely, when ATG4B gene was inhibited, the level of autophagy was downregulated, and inflammatory factors were upregulated. Then, autophagy inducers inhibited the levels of inflammation and ROS, whereas autophagy inhibitors had the opposite function in HRGECs induced by glucose (30 mmol/L). In conclusion, the above data suggested that AIF-1 regulated the levels of inflammation, oxidative stress, and autophagy in HRGECs via miR-34a/ATG4B pathway to contribute to the pathogenesis of diabetic kidney disease.
Machine Learning-Based Two-Stage Task Offloading Optimization for Power Distribution Internet of Things
Authors: He Chenzidu , Wu Yuanyuan , Huang Mengxing , Feng Siling , Shu Feng
Published: October 2022

The increase in the number of services in the power distribution grid leads to a massive increase in task data. Power distribution internet of things (PDIoT) is the specific application of internet of things (IoT) in the power distribution grid. By deploying a large number of PDIoT devices, the voltage, active power, reactive power, and harmonic parameters are collected to support distribution grid services such as fault identification and status detection. Therefore, PDIoT utilizes massive devices to collect and offload tasks to the edge server through 5G network for real-time data processing. However, how to dynamically select edge servers and channels to meet the energy-efficient and low-latency task offloading requirements of PDIoT devices still faces several technical challenges such as task offloading decisions coupling among devices, unobtainable global state information, as well as interrelation of various quality of service (QoS) metrics such as energy efficiency and delay. To this end, we firstly construct a joint optimization problem to maximize the weighted difference between energy efficiency and delay of devices in PDIoT. Then, the joint optimization problem is decomposed into a large-timescale server selection problem and a small-timescale channel selection problem. Next, we propose an ML-based two-stage task offloading algorithm, where the large-timescale problem is solved by two-side matching in the first stage, and the small-timescale problem is solved by adaptive

ε

-greedy learning in the second stage. Finally, simulation results show that compared with the task offloading delay-first matching algorithm and the matching theory-based task offloading strategy, the proposed algorithm performs superior in terms of energy efficiency and delay.
FAPA: Transferable Adversarial Attacks Based on Foreground Attention
Authors: Yang Zhifei , Li Wenmin , Gao Fei , Wen Qiaoyan
Published: October 2022

Deep learning models are vulnerable to attacks by adversarial examples. However, current studies are mainly limited to generating adversarial examples for specific models, and the migration of adversarial examples between different models is rarely studied. At the same time, in only studies, it is not considered that adding disturbance to the position of the image can improve the migration of adversarial examples better. As the main part of the picture, the model should give more weight to the foreground information in the recognition. Will adding more perturbations to the foreground information of the image result in a higher transfer attack rate? This paper focuses on the above problems, and proposes the FAPA algorithm, which first selects the foreground information of the image through the DINO framework, then uses the foreground information to generate M, and then uses PNA to generate the perturbation required for the whole picture. In order to show that our method attaches importance to the foreground information, we give a greater weight to the perturbation corresponding to the foreground information, and a smaller weight to the rest of the image. Finally, we optimize the generated perturbation through the gradient generated by the dual attack framework. In order to demonstrate the effectiveness of our method, we have conducted relevant comparative experiments. During the experiment, we used the three white-box ViTs models to attack the six black-box ViTs models and the three black-box CNNs models. In the transferable attack of ViTs models, the average attack success rate of our algorithm reaches 64.19%, which is much higher than 21.12% of the FGSM algorithm. In the transferable attack of CNN models, the average attack success rate of our algorithm reaches 48.07%, which is also higher than 18.65% of the FGSM algorithm. By integrating ViTs and CNNs models, the attack success rate of transfer of our algorithm reaches 56.13%, which is higher than 1.18% of the dual attack framework we refer to.
Fault Diagnosis of Rotating Machinery Based on Evolutionary Convolutional Neural Network
Authors: Bai Yihao , Cheng Weidong , Wen Weigang , Liu Yang
Published: October 2022

This paper proposes a fault diagnosis method for rotating machinery based on evolutionary convolutional neural network (ECNN). With the time-frequency images as the network input, with the help of the global optimization ability of the genetic algorithm, the structure of the convolutional neural network can evolve autonomously, and the adaptive configuration of the structural hyperparameters for the target task is realized. In this paper, the proposed method is verified by the measured signal of the planetary gearbox. The results show that the proposed method is helpful to obtain a convolutional neural network structure with better performance and achieve higher fault diagnosis accuracy.
Improvement of Fish Growth and Metabolism by Oligosaccharide Prebiotic Supplement
Authors: Xu Wei , Lutz Charles Greg , Taylor Christopher M. , Ortega Miriam Contin
Published: October 2022

Finfish aquaculture is expected to continue to benefit from significantly improved fish diets, which are the source of energy to support the growth and health of fish. Strategies to enhance the transformation rate of dietary energy and protein to fish growth are greatly desired by fish culturists. Prebiotic compounds can be used as supplements to human, animal, and fish diets to populate beneficial bacteria in the gut. The goal of the present study is to identify low-cost prebiotic compounds with high efficacy in increasing the absorption of food nutrients by fish. Several oligosaccharides were evaluated as prebiotics in Nile tilapia (Oreochromis niloticus), one of the most widely cultured species in the world. Several parameters of the fish on different diets were evaluated, including feed conversion ratios (FCRs), enzymatic activities, expression of growth-related genes, and the gut microbiome. Two age groups of fish (30 days old and 90 days old) were used in this study. The results indicated that the addition of xylooligosaccharide (XOS), galactooligosaccharide (GOS), or XOS and GOS combination to the basic fish diet significantly decreased the feed conversion ratio (FCR) of the fish in both age groups. Both XOS and GOS decreased the FCR of 30-day-old fish by 34.4% compared to the fish on the control diet. In the 90-day-old fish group, XOS and GOS decreased the FCR by 11.9%, while the combination of the two prebiotics led to a 20.2% decrease in FCR compared to the control group. The application of XOS and GOS also elevated the production of glutathione-related enzymes and the enzymatic activity of glutathione peroxidase (GPX), indicating the enhancement of antioxidation processes in fish. These improvements were associated with significant changes in the fish gut microbiota. The abundance of Clostridium ruminantium, Brevinema andersonii, Shewanella amazonensis, Reyranella massiliensis, and Chitinilyticum aquatile were upregulated by XOS and GOS supplements. The findings of the present study suggested that the prebiotics would be more effective when they were applied to the younger fish, and the application of multiple oligosaccharide prebiotic compounds could result in a greater growth enhancement. The identified bacteria can be potentially used as probiotic supplements in the future to improve fish growth and feeding efficiency and ultimately reduce the cost of tilapia aquaculture.
Tardive Dyskinesia Development, Superoxide Dismutase Levels, and Relevant Genetic Polymorphisms
Authors: Uludag Kadir , Wang Dong Mei , Zhang Xiang Yang
Published: October 2022

Tardive dyskinesia (TD) is a prevalent movement disorder that significantly impacts patients with schizophrenia (SCZ) due to extended exposure to antipsychotics (AP). Several genetic polymorphisms, including superoxide dismutase (SOD) and DRD3 9ser, have been suggested as explanations why some patients suffer from TD. Methods. A PubMed search was used to search relevant articles using the following keywords: “Tardive Dyskinesia and Superoxide Dismutase”. Fifty-eight articles were retrieved. Among them, 16 were included in this review. Results. Overall, 58 studies were retrieved from PubMed. Most studies investigated the association between TD and the SOD-related polymorphisms. In addition, previous studies reported an association between TD occurrence and other genetic polymorphisms. Conclusion. This study found that the risk of TD is associated with altered SOD levels and several genetic polymorphisms, including VAL 66 Met and DRD3 9ser.
Imaging Evaluation of Insertion Point Accuracy in Retrograde Intramedullary Femoral Nailing
Authors: He Miao , Tian Shanshan , Liu Jian , Deng Xu , Xiang Jiangxia
Published: October 2022

Objective. When compared with visual retrograde intramedullary nail placement in the femur, fluoroscopic retrograde intramedullary nail placement in the femur improved the accuracy of insertion. Methods. Ninety‐six patients treated with retrograde intramedullary nailing of the femur for femoral fracture were included in this retrospective case‐control study, including 48 patients treated with nailing under direct vision and 48 patients treated with nailing under fluoroscopy. Influencing factors potentially associated with the deviation of the needle insertion point on the coronal and sagittal planes (including the needle insertion method, use of limited open reduction, side, intramedullary nail diameter, mechanism of injury, and fracture classification) were analyzed univariately; then, the variables with a p value < 0.20 on univariate analysis were included in the linear regression equation to assess the independent factors associated with needle insertion point deviation. Results. On the coronal plane, the insertion point deviation in the visual nail placement group (1.11 ± 4.08 mm) was not significantly different (p = 0.13) from that in the fluoroscopic nail placement group (−0.44 ± 3.48 mm); on the sagittal plane, the insertion point deviation in the visual nail placement group (4.91 ± 4.67 mm) was significantly greater than that in the fluoroscopic nail placement group (2.08 ± 2.97 mm) (p < 0.01). Visual nail placement was a risk factor for insertion point deviation on the sagittal plane compared with fluoroscopic nail placement (β = −0.84, p < 0.01). Conclusion. Compared with visual nail placement, fluoroscopic nail placement improves the accuracy of insertion on the sagittal plane, with no difference between the two methods on the coronal plane. These findings indicate that surgeons should exercise more caution when placing nails under direct vision.
Methodological Approach for Optimizing Production of Oxygen by Adsorption of Nitrogen from Air using Zeolite Li-LSX
Authors: Al-Yousuf Marwa , Almilly Raghad F. , Kamil Riyadh
Published: October 2022

This research investigates the optimum operating conditions related to the adsorption of nitrogen gas from ambient air on zeolite Li-LSX to produce oxygen gas by the pressure-vacuum swing adsorption process. Experiments were performed using a column (4 cm inside diameter and 17 cm length) packed with different heights of packing (h) of zeolite (9, 12, and 16 cm) from 0.4 to 0.8 mm diameter pellets. At each packing height, different flow rates (f) (2, 4, 6, 8, and 10 L·min−1) for different input pressures (

p

) (0.5, 1, 1.5, 2, and 2.5 bar) were used to detect their effects on the purity of produced oxygen as percentage volume of the outlet air stream. The results showed that the purity of produced oxygen increased with increasing packing height, pressure, and flowrate to a specific limit. The maximum purity obtained was 73.15% at 16 cm packing height, 2.5 bar input pressure, and 6 L·min−1 inlet flowrate, and the productivity was equal to 18 mmol·(Kg·s)−1 at these conditions. A response surface methodology was used to determine the most influential variables and their interactions. The results confirmed the strong effects of the input pressure, the packing height, and to a lesser extent, the flowrate. A quadratic model was predicted based on the experimental result and assessed statistically. The impacts of quadratic terms in the model were in the order: of

p
∗
p
>
p
∗
h
>
p
∗
f

. The model was applied to predict the operating conditions of 95% purity of oxygen.
Three-Parameter Twin τ2 Strength Theory for Brittle Materials under Multiaxial Stress State and Its Application
Authors: Meng Jinzhu , Chen Sili , Meng Tiantian , Wang Junxiang , Zhang Jingyu
Published: October 2022

The strength failure of brittle materials under complex stress is an important problem. Herein, we propose a novel three-parameter twin τ2 strength theory considering the influence of hydrostatic pressure and normal stress on the principal shear-stress surface, derive a mathematical expression for the strength theory, and compare the theoretical predictions under several stress states with existing experimental data. The results show that different ultimate stress ratios, α and β, correspond to different strength theories for brittle materials. The principal stress σ1 increases gradually with an increase in σ2 (=σ3) under the stress state σ1 > σ2 = σ3; σ1 (=σ2) increases gradually with an increase in σ3 under the stress state σ1 = σ2 > σ3. Furthermore, the biaxial compressive strength is considerably higher than the uniaxial compressive strength under the biaxial compressive stress for σ1 > 0, σ2 > 0, and σ3 = 0. When σ3 is fixed and σ2 is relatively small under the stress states of σ1 > 0, σ2 > 0, and σ3 > 0, the maximum principal stress σ1 increases with the increasing σ2. When σ2 is relatively large and as σ1 gradually decreases with the increasing σ2, the effect law of intermediate principal stress σ2 is obtained.
A Financial Risk Early Warning of Listed Companies Based on PCA and BP Neural Network
Authors: Zhang Chen , Zhou Xinmiao , Wang Jiaqing
Published: October 2022

Financial risk, as one of the most influential and destructive risks in business, will make enterprises unable to escape the fate of bankruptcy if not warned and prevented in time. In the paper, we conducted research on the financial risk early warning of listed companies. A total of 250 companies were randomly selected from the Chinese A-share market from 2019 to 2021. By building the 26 financial indicators of listed companies and constructing the PCA-BP neural network, we compared the financial risk early warning effects among PCA-BPNN, SVM, and Logistic. It is found that the financial data processed by PCA can better adapt to the financial risk early warning model. The PCA-BPNN model improved the prediction accuracy of the financial risk early warning, which has strong generalization ability for the prediction of financial risk. Research findings have certain reference significance for precise judgment on the financial risk of companies.
Research on the Revenue Management of Network Video Platform Based on Game Theory
Authors: Li Beibei , Li Huayi
Published: October 2022

To study how the network video platform can improve revenue and optimize the revenue structure, we construct an asymmetric competition model between free and paid platforms based on game theory, and the impact of the positive and negative cross-network externalities and program differentiation on platform’s competition and revenue are analyzed. The results show that changes in the relative relationship of positive and negative cross-network externalities may lead to free platform exiting the consumer market or paid platform exiting the advertising market. Only when the ratio of positive and negative cross-network externalities is moderate, the free and paid platform coexist, and the greater the difference of program, the greater the possibility of coexistence. With the effect of the positive and negative cross-networks externalities, the multi-revenue structure of the payment mode is not always better than the single revenue structure of the free platform. In addition, the impact of the positive and negative cross-network externalities and program differentiation on the revenue of free and paid platforms are nonlinear. If the platform wants to achieve greater revenue through the adjustment of revenue structure, it should fully consider the relative relationship of positive and negative cross-network externalities and program differentiation, otherwise it may bring losses.
Research on Stratum Identification Method Based on TBM Tunneling Characteristic Parameters
Authors: Wu Wei , Guo Jingbo , Li Jie , Sun Ji , Qi Haoran , Chen Ximing
Published: October 2022

In order to obtain continuous stratum information during TBM tunneling, using TBM tunneling parameters, stratum recognition is carried out through the K‐nearest neighbor model, and the model is improved by the entropy weight method to improve the stratum recognition rate. By analyzing the correlation between TBM tunneling characteristic parameters and stratum, the tunneling characteristic parameter vector which is most sensitive to the stratum is obtained by sensitivity analysis, and the stratum recognition model based on the K‐nearest neighbor algorithm is established. Aiming at the problem that the model has a large error in complex formation recognition, a formation recognition model based on the entropy weight K‐nearest neighbor algorithm is established, and the wrong data of the K‐nearest neighbor model is recalculated. The recognition rate of the stratum in the new model is increased from 90.95% to 98.55%. The results show that the K‐nearest neighbor model has a better recognition effect for the interval with single stratum distribution, and the recognition rate of entropy weight K‐nearest neighbor model for complex stratum is significantly improved, which provides an effective method to obtain stratum information by using tunneling characteristic parameters.
Perfectionism and Emotional Intelligence: A Person-Centered Approach
Authors: Vicent María , Sanmartín Ricardo , Cargua-García Nancy Isabel , García-Fernández José Manuel
Published: October 2022

This study examined the relationship between perfectionistic concerns (PC) and perfectionistic strivings (PS) with the subcomponents of emotional intelligence (EI) through a latent class person-centered approach. A sample of 1582 Ecuadorian adolescents (619 females) aged from 12 to 18 was employed. The trait meta-mood scale-24 (TMMS-24) and the child and adolescent perfectionism scale (CAPS) were used, respectively, for assessing three subcomponents of EI (i.e., emotional attention, emotional clarity, and mood repair) and two perfectionist dimensions (PC and PS). A three-class solution (High perfectionism, moderate perfectionism, and nonperfectionism) was identified by using latent class analysis. High perfectionism significantly scored higher on emotional attention in comparison with the moderate and nonperfectionism classes, with small and moderate effect sizes. Overall, results suggest that people with high perfectionism might be at greater risk of developing maladaptive emotional self-regulation strategies, such as rumination, because of their tendency to excessively attend their negative mood states.
In Silico and In Vitro Studies on the Mechanisms of Chinese Medicine Formula (Yiqi Jianpi Jiedu Formula) in the Treatment of Hepatocellular Carcinoma
Authors: Wu Zhulin , Kang Jianyuan , Tan Wanjun , Wei Chunshan , He Li , Jiang Xiaoyan , Peng Lisheng
Published: October 2022

Objective. Traditional Chinese medicine (TCM) is an important part of the comprehensive treatment of hepatocellular carcinoma (HCC), and Chinese materia medica formulas with the effect of “Yiqi Jianpi” (replenishing qi and strengthening spleen) or “Jiedu” (removing toxicity) have been proved to be effective in treating HCC. However, mechanisms of these formulas in treating HCC remain unclear. In this paper, our goal is to explore the antitumor activity and its molecular mechanisms of Yiqi Jianpi Jiedu (YQJPJD) formula against HCC. Methods. The bioactive ingredients and targets of YQJPJD formula and HCC targets were screened by five Chinese materia medicas and two disease databases, respectively. The network pharmacology was utilized to construct the relationship network between YQJPJD formula and HCC, and the mechanisms were predicted by the protein-protein interaction (PPI) network, pathway enrichment analysis, bioinformatics, and molecular docking. Numerous in vitro assays were performed to verify the effect of YQJPJD formula on HCC cells, cancer-associated targets, and PI3K/Akt pathway. Results. The network relationship between YQJPJD formula and HCC suggested that YQJPJD formula mainly regulated the potential therapeutic targets of HCC by several key bioactive ingredients (e.g., quercetin, luteolin, baicalein, and wogonin). PPI network, bioinformatics, and molecular docking analyses displayed that YQJPJD formula may play an anti-HCC effect through key targets such as MAPK3, RAC1, and RHOA. Additionally, pathway analysis demonstrated that YQJPJD formula could play an anti-HCC effect via multiple pathways (e.g., PI3K-Akt and hepatitis B). Experimental results showed that YQJPJD formula could effectively inhibit the proliferation, migration, and invasion of HCC cells and promote HCC cell apoptosis in a concentration-dependent manner. Moreover, YQJPJD formula could decrease the mRNA expression of β-catenin, MAPK3, and RHOA and the protein expression of phosphorylated PI3K and Akt. Conclusion. YQJPJD formula mainly exerts its anti-HCC effect through multiple bioactive ingredients represented by quercetin, as well as multiple pathways and targets represented by PI3K/Akt pathway, β-catenin, MAPK3, and RHOA.
Residual Strain Monitoring and Dynamic Characteristics of Hybrid Hollow Square Tube with Metal–FRP–Metal Sandwich Walls
Authors: Li Zhao , Liu Mingyao , Wang Jintao , Ke Wei
Published: October 2022

In order to design and fabricate a novel hollow square tube (HST) for ram structure in machine tools, the hybrid HST with sandwich walls based on steel skins and unidirectional carbon fiber-reinforced polymer (CFRP) composite core is proposed. A detailed co-cured fabrication method with embedded fiber Bragg grating (FBG) sensors for residual strains/stresses determination in a hybrid metal–composite structure is presented. Results reveal that the hybrid HST has undergone complex residual strain history, and the strain rate is about 10 times the cooling rate. The tensile strains in the dwell stage transform into compressive strains in the cooling stage due to the mismatch of the coefficients of thermal expansion of the steel plates and the CFRP composite. A comparison of the residual strains in the cooling phase obtained by FBG sensors with those obtained by theoretical calculation is carried out. Furthermore, the dynamic characteristics of the hybrid HST and the steel HST are tested. The results showed that the damping of the hybrid HST is 586% higher than that of the steel HST, while the hybrid HST has a lower first natural frequency (4.6% reduction) and mass (15.9% weight reduction). The influence of co-cure temperature and cooling rate on the size and state of the residual strains is analyzed, which might be helpful to guide the manufacturing of sandwich structures in machine tools. This novel hybrid HST may be used for online health monitoring and safety evaluation to build intelligent machine tools structures.
Aristotle’s Metaphysics Z as First Philosophy
Authors: Meister Samuel
Published: October 2022

Discussions of Aristotle’s Metaphysics Z tend to treat it either as an independent treatise on substance and essence or as preliminary to the main conclusions of the Metaphysics. I argue instead that Z is central to Aristotle’s project of first philosophy in the Metaphysics: the first philosopher seeks the first causes of being qua being, especially substances, and in Z Aristotle establishes that essences or forms are the first causes of being of perceptible substances. I also argue that the centrality of Z to first philosophy is compatible with its status as theology.
The Gramophone Industry and Chinese Records in Pre-war Singapore: Global Network and Local Consumption
Authors: Goh Song Wei
Published: October 2022

This paper presents the history of the gramophone industry and Chinese records in pre-war Singapore, through exploring the position of Singapore in the global commercial networks of transnational gramophone enterprises, and the local consumption of Chinese music records. At the turn of the twentieth century, the emergence of gramophone companies in the United States and European countries enabled Chinese opera and music in different regional languages to be manufactured into records, and consumed as commodities by Chinese communities all around the globe. Shaped by multiple routes of trade and cultural connections, the Chinese records sold in Singapore were of diverse historical origins and regional languages that catered to the different Chinese dialect groups. By the 1920s and 1930s, the popularization of gramophones and Chinese records had engendered an unprecedented sonic experience in Singapore.