bluuebunny/crossref_metadata_2025 huggingface dataset:
The Frequency-Response Approach to the Design of a Mechanical Servo
Authors: Helm H. A.
Published: July 2022

The frequency-response method of analysis has proved extremely valuable in the design of electronic feedback systems. This paper illustrates the application of this method to the design of completely mechanical systems. Basic relations between the mechanical elements are pointed out and the necessary feedback concepts are developed for mechanical systems. These concepts are illustrated by the actual step-by-step design of an automatic contour-following lathe using entirely mechanical, hydraulic, and pneumatic control elements.
Application of Frequency-Analysis Techniques to Hydraulic Control Systems
Authors: Hall A. C.
Published: July 2022

Hydraulic control systems, while inherently nonlinear, under many conditions can be studied by means of a linear approximation. Performance may be predicted by this approximation with reasonable accuracy provided the change in fluid flow during a transient is small compared to the steady-state value of the flow. A valve-motor control system is studied by linear analysis and the frequency-response characteristic obtained. The transfer function of this system is of the third order if the servomotor load is a mass. Expressions for the damping ratio, natural frequency, and sensitivity are obtained.
Synthesis of Optimum Feedback Systems Satisfying a Power Limitation
Authors: Westcott J. H.
Published: July 2022

The paper describes two methods of synthesizing feedback systems in which stability considerations are qualified by an overriding limit on power demand. The three basic requirements for either method are (a) a spectral density function of input signals, (b) a transfer function of fixed elements (i.e., basic elements essential for the performance of the task), and (c) the maximum rating of the power source. Examples are given. In one method the form of the stabilizing means has to be specified. The criterion, that the mean-square error be a minimum subject to the power limitation, is applied. This gives as a result the optimum design parameters of the specified stabilizing means. The other method, based upon the same criterion, uses a variational principle. A solution by this method gives a stabilizing means for the system which, within the specified power limit, cannot be improved. One example of this method illustrates the desirability of allowing a finite time delay between the input and the output of a feedback system.
Recent Advances in Nonlinear Servo Theory
Authors: Loeb J. M.
Published: July 2022

This paper concerns the so-called “filtered nonlinear servos,” i.e., servos where the signal undergoes a filtering effect from a linear part of the device. “Hereditary phenomena,” such as Coulomb friction, gear backlash, and so on, are dealt with. A general stability criterion is derived, and it is shown how the Nyquist criterion appears as a particular case. The criterion indicates whether or not a servo is liable to hunt, but it is still necessary to state whether or not the possible hunting will have a limited amplitude. An approach to this problem is sketched and it is shown how the first results may be considered as quantitatively valid for quasi-linear systems. Some conclusions previously derived by assuming the transfer functions to be analytic appear as a limiting case of the present results.
The Use of Zeros and Poles for Frequency Response or Transient Response
Authors: Evans W. R.
Published: July 2022

The characteristic equation of a control system is often of the form 1/KG(s) + 1 = 0, in which G(s) is (s − q1) (s − q2)… /(s − p1) (s − p2)… Each factor of G(s), such as (s − p1), is a complex variable which can be plotted as a vector in the s-plane from the pole p1 to the point s. The complex product G(s) is itself a vector whose magnitude is the product of magnitudes and whose angle is the sum of the angles of its factors. Frequency response is computed directly for s points along the jω-axis. In order to find the roots of 1/KG(s) = −1, the locus of s is sketched, where for each point on this locus the total angle of G(s) is equal to 180 deg; a point on this locus is then a root if K = 1/|G(s)|. For given initial conditions the Laplace transform permits the transient response of the system to be written directly.
Equilibrium Behavior of a Tethered Autogyro: Application in Extended Flight and Power Generation
Authors: McConnell Jonathan , Das Tuhin
Published: July 2022

In this article, we study the characteristics of steady autorotation of a tethered autogyro. The phenomenon of autorotation refers to the natural spinning of a rotor in a wind field. We explore the viability of tethered autogyros as unmanned aerial vehicles (UAVs) for long-duration and energy efficient hovering applications, such as in monitoring or surveillance. The tether provides mooring and can be used to power the rotor and to transmit wind power to the ground when suitable. This is a novel application of autorotation. It requires a generalized formulation and modeling of autorotation, beyond what is reported in the literature. We adopt a model-based approach where the blade element momentum (BEM) method and catenary mechanics are used to model the aerodynamics and the tether, respectively. The resulting model is highly nonlinear and numerical methods are proposed to solve for the equilibria. The model is validated against existing simulation and experimental results in the literature. It is extended to incorporate new features that are pertinent to our application, such as low rotor speeds, regenerative torque for power generation, combining catenary mechanics with aerodynamics, and varying atmospheric conditions with altitude. We characterize the autorotational equilibria over a range of operating conditions involving multiple independent variables. The analysis reveals an optimal operating range of the tip speed ratio of the autogyro under equilibrium. It also indicates the possibility of power generation in large autogyros stationed at high altitudes.
Kurtosis analysis of sounds from down-the-hole pile installation and the implications for marine mammal auditory impairment
Authors: Guan Shane , Brookens Tiffini , Miner Robert
Published: July 2022

Sounds from down-the-hole pile installation contain both impulsive and non-impulsive components. Kurtosis values (β) were determined for two datasets to investigate the impulsiveness of piling sounds. When the hammer struck the pile(s), β was 21–30 at 10 m and approximately 10 at 200 m. When the hammer was used for drilling without contacting the pile, β was 4–6 at all distances. These findings suggest that a simple dichotomy of classifying sounds as impulsive or non-impulsive may be overly simplistic for assessing marine mammal auditory impacts and studies investigating the impacts from complex sound fields are needed.
Mismatched ligand density enables ordered assembly of mixed-dimensional, cross-species materials
Authors: Li Tongtao , Xia Xiuyang , Wu Guanhong , Cai Qingfu , Lyu Xuanyu , Ning Jing , Wang Jing , Kuang Min , Yang Yuchi , Pica Ciamarra Massimo , Ni Ran , Yang Dong , Dong Angang
Published: July 2022

The ordered coassembly of mixed-dimensional species—such as zero-dimensional (0D) nanocrystals and 2D microscale nanosheets—is commonly deemed impracticable, as phase separation almost invariably occurs. Here, by manipulating the ligand grafting density, we achieve ordered coassembly of 0D nanocrystals and 2D nanosheets under standard solvent evaporation conditions, resulting in macroscopic, freestanding hybrid-dimensional superlattices with both out-of-plane and in-plane order. The key to suppressing the notorious phase separation lies in hydrophobizing nanosheets with molecular ligands identical to those of nanocrystals but having substantially lower grafting density. The mismatched ligand density endows the two mixed-dimensional components with a molecular recognition-like capability, driving the spontaneous organization of densely capped nanocrystals at the interlayers of sparsely grafted nanosheets. Theoretical calculations reveal that the intercalation of nanocrystals can substantially reduce the short-range repulsions of ligand-grafted nanosheets and is therefore energetically favorable, while subsequent ligand-ligand van der Waals attractions induce the in-plane order and kinetically stabilize the laminate superlattice structure.
Feedback of aggregate patient-reported outcomes (PROs) data to clinicians and hospital end users: findings from an Australian codesign workshop process
Authors: Ryan Olivia Francis , Hancock Shaun L , Marion Violet , Kelly Paulette , Kilkenny Monique F , Clissold Benjamin , Gunzburg Penina , Cooke Shae , Guy Lauren , Sanders Lauren , Breen Sibilah , Cadilhac Dominique A
Published: July 2022

Objectives

Patient-reported outcomes (PROs) are increasingly used to measure the patient’s perspective of their outcomes following healthcare interventions. The aim of this study was to determine the preferred formats for reporting service-level PROs data to clinicians, researchers and managers to support greater utility of these data to improve healthcare and patient outcomes.

Setting

Healthcare professionals receiving PRO data feedback at the health service level.

Participants

An interdisciplinary Project Working Group comprised of clinicians participated in three workshops to codesign reporting templates of summarised PRO data (modified Rankin Scale, EuroQol Five Dimension Descriptive System, EuroQol Visual Analogue Scale and Hospital Anxiety and Depression Scale) using a modified Delphi process. An electronic survey was then distributed to short list the preferred templates among a broad sample of clinical end users. A final workshop was undertaken with the Project Working Group to review results and reach consensus on the final templates.

Primary and secondary outcome measures

The recommendation of preferred PRO summary data feedback templates and guiding principles for reporting aggregate PRO data to clinicians was the primary outcome. A secondary outcome was the identification of perceived barriers and enablers to the use of PRO data in hospitals. For each outcome measure, quantitative and qualitative data were summarised.

Results

31 Working Group members (19 stroke, 2 psychology, 1 pharmacy, 9 researchers) participated in the workshops, where 25/55 templates were shortlisted for wider assessment. The survey was completed by 114 end users. Strongest preferences were identified for bar charts (37/82 votes, 45%) and stacked bar charts (37/91 votes, 41%). At the final workshop, recommendations to enhance communication of PROs data for comparing health service performance were made including tailoring feedback to professional roles and use of case-mix adjustment to ensure fair comparisons.

Conclusions

Our research provides guidance on PROs reporting for optimising data interpretation and comparing hospital performance.
Xpert Ultra stool testing to diagnose tuberculosis in children in Ethiopia and Indonesia: a model-based cost-effectiveness analysis
Authors: Mafirakureva Nyashadzaishe , Klinkenberg Eveline , Spruijt Ineke , Levy Jens , Shaweno Debebe , de Haas Petra , Kaswandani Nastiti , Bedru Ahmed , Triasih Rina , Gebremichael Melaku , Dodd Peter J , Tiemersma Edine W
Published: July 2022

Objectives

The WHO currently recommends stool testing using GeneXpert MTB/Rif (Xpert) for the diagnosis of paediatric tuberculosis (TB). The simple one-step (SOS) stool method enables processing for Xpert testing at the primary healthcare (PHC) level. We modelled the impact and cost-effectiveness of implementing the SOS stool method at PHC for the diagnosis of paediatric TB in Ethiopia and Indonesia, compared with the standard of care.

Setting

All children (age <15 years) presenting with presumptive TB at primary healthcare or hospital level in Ethiopia and Indonesia.

Primary outcome

Cost-effectiveness estimated as incremental costs compared with incremental disability-adjusted life-years (DALYs) saved.

Methods

Decision tree modelling was used to represent pathways of patient care and referral. We based model parameters on ongoing studies and surveillance, systematic literature review, and expert opinion. We estimated costs using data available publicly and obtained through in-country expert consultations. Health outcomes were based on modelled mortality and discounted life-years lost.

Results

The intervention increased the sensitivity of TB diagnosis by 19–25% in both countries leading to a 14–20% relative reduction in mortality. Under the intervention, fewer children seeking care at PHC were referred (or self-referred) to higher levels of care; the number of children initiating anti-TB treatment (ATT) increased by 18–25%; and more children (85%) initiated ATT at PHC level. Costs increased under the intervention compared with a base case using smear microscopy in the standard of care resulting in incremental cost-effectiveness ratios of US$132 and US$94 per DALY averted in Ethiopia and Indonesia, respectively. At a cost-effectiveness threshold of 0.5×gross domestic product per capita, the projected probability of the intervention being cost-effective in Ethiopia and Indonesia was 87% and 96%, respectively. The intervention remained cost-effective under sensitivity analyses.

Conclusions

The addition of the SOS stool method to national algorithms for diagnosing TB in children is likely to be cost-effective in both Ethiopia and Indonesia.
Does an increase in physiological indexes predict better cognitive performance: the PhyCog randomised cross-over protocol in type 2 diabetes
Authors: Magnon Valentin , Dutheil Frederic , Tauveron Igor , Mille Jordan , Baker Julien S , Brusseau Valentin , Silvert Laetitia , Izaute Marie , Vallet Guillaume T
Published: July 2022

Introduction

There has been a growing interest towards cognitive-training programmes to improve cognition and prevent cognitive impairment despite discrepant findings. Physical activity has been recognised in maintaining or improving cognitive ability. Based on a psychoneurophysiological approach, physiological indexes should partly determine neuronal dynamics and influence cognition as any effects of cognitive training. This study’s primary aim was to examine if improved physiological indexes predict improved cognitive variables in the context of a clinical intervention programme for type 2 diabetes (T2D).

Method and analysis

PhyCog will be a 22-week randomised controlled trial comparing cognitive performance between three arms: (1) physical activity (1 month), a 15-day wash-out, then cognitive training (1 month), (2) cognitive training (1 month), a 15-day wash-out and physical activity (1 month), and (3) an active breathing condition (psychoeducation and resonance frequency breathing for 1 month), then a 15-day wash-out, and combined physical activity and cognitive training (1 month), allowing to determine the most effective intervention to prevent cognitive impairment associated with T2D. All participants will be observed for 3 months following the intervention. The study will include a total of 81 patients with T2D.

Cognitive performance and physiological variables will be assessed at baseline (week 0—W0), during the washout (W5, 72–96 hours after week 4), at the end of the intervention (W10), and at the end of the follow-up (W22). The main variables of interest will be executive function, memory and attention. Physiological testing will involve allostatic load such as heart rate variability, microcirculation, cortisol and dehydroepiandrosterone sulfate levels. Sociodemographic and body composition will also be a consideration. Assessors will all be blinded to outcomes. To test the primary hypothesis, the relationship between improvement in physiological variables and improvement in cognitive variables (executive, memory and attention) will be collected.

Ethics and dissemination

This protocol was approved by the Est III French Ethics Committee (2020-A03228-31). Results will be published in peer-reviewed journals.

Trial registration number

NCT04915339.
An Efficient Semi-Supervised Framework with Multi-Task and Curriculum Learning for Medical Image Segmentation
Authors: Wang Kaiping , Wang Yan , Zhan Bo , Yang Yujie , Zu Chen , Wu Xi , Zhou Jiliu , Nie Dong , Zhou Luping
Published: July 2022

A practical problem in supervised deep learning for medical image segmentation is the lack of labeled data which is expensive and time-consuming to acquire. In contrast, there is a considerable amount of unlabeled data available in the clinic. To make better use of the unlabeled data and improve the generalization on limited labeled data, in this paper, a novel semi-supervised segmentation method via multi-task curriculum learning is presented. Here, curriculum learning means that when training the network, simpler knowledge is preferentially learned to assist the learning of more difficult knowledge. Concretely, our framework consists of a main segmentation task and two auxiliary tasks, i.e. the feature regression task and target detection task. The two auxiliary tasks predict some relatively simpler image-level attributes and bounding boxes as the pseudo labels for the main segmentation task, enforcing the pixel-level segmentation result to match the distribution of these pseudo labels. In addition, to solve the problem of class imbalance in the images, a bounding-box-based attention (BBA) module is embedded, enabling the segmentation network to concern more about the target region rather than the background. Furthermore, to alleviate the adverse effects caused by the possible deviation of pseudo labels, error tolerance mechanisms are also adopted in the auxiliary tasks, including inequality constraint and bounding-box amplification. Our method is validated on ACDC2017 and PROMISE12 datasets. Experimental results demonstrate that compared with the full supervision method and state-of-the-art semi-supervised methods, our method yields a much better segmentation performance on a small labeled dataset. Code is available at https://github.com/DeepMedLab/MTCL .
Study of midrapidity pt distributions of identified charged particles in Xe+Xe collisions at (snn)1/2 = 5.44TeV using non-extensive Tsallis statistics with transverse flow
Authors: Olimov Khusniddin K. , Liu Fu-Hu , Musaev Kobil A. , Olimov Kosim , Shodmonov Maratbek Z. , Fedosimova Anastasiya I. , Lebedev Igor A. , Kanokova Shakhnoza Z. , Tukhtaev Boburbek J. , Yuldashev Bekhzod S.
Published: July 2022

The midrapidity transverse momentum [Formula: see text] distributions of the charged pions and kaons, protons, and antiprotons, measured by ALICE Collaboration at nine centrality groups of Xe[Formula: see text]Xe collisions at [Formula: see text], have been reproduced quite well using simultaneous (combined) minimum [Formula: see text] fits with the simple (non-consistent) as well as thermodynamically consistent Tsallis function with included transverse flow. The parameters [Formula: see text], [Formula: see text], and [Formula: see text] extracted in this work using both consistent and non-consistent Tsallis function with included transverse flow demonstrate the similar dependencies on collision centrality [Formula: see text]. The obtained non-extensivity parameter [Formula: see text] values decrease systematically for all studied particle species with increasing Xe[Formula: see text]Xe collision centrality, indicating an increase in degree of system thermalization with increasing centrality of heavy-ion collisions. The average transverse flow velocity demonstrates significantly different growth rates in regions [Formula: see text] and [Formula: see text], and parameter [Formula: see text] stays constant within uncertainties in [Formula: see text] range in Xe[Formula: see text]Xe collisions at [Formula: see text]. It is argued that [Formula: see text] could possibly be a threshold border value for a crossover transition from a dense hadronic state to the QGP phase (or mixed phase of QGP and hadrons) in Xe[Formula: see text]Xe collisions at [Formula: see text]. Depletion (enhancement) of [Formula: see text] ratio at low [Formula: see text] (intermediate [Formula: see text]) has been observed in this work in Xe[Formula: see text]Xe collisions at [Formula: see text], which agrees with the similar results of ALICE Collaboration obtained recently in high-energy Xe[Formula: see text]Xe and [Formula: see text] collisions at the LHC. Analyzing and reflecting the extracted [Formula: see text] versus [Formula: see text] and [Formula: see text] versus [Formula: see text] dependencies, we have verified that the depletion (enhancement) of baryon-to-meson ratio at low [Formula: see text] (intermediate [Formula: see text]) values with increasing [Formula: see text] is due to radial flow effects.
Hawking radiation of charged massive particle and tunneling from Kerr–Newman–de Sitter black hole
Authors: Niranjan Singh S. , Singh T. Ibungochouba , Meitei I. Ablu , Singh Aheibam Keshwarjit
Published: July 2022

The semiclassical tunneling technique proposed by Parikh and Wilczek to study Hawking radiation of static and stationary black holes has been extensively used to investigate the Hawking radiation of different types of black holes. In this paper, the geodesic equation of charged massive particle and the massless particle are obtained by using the Lagrangian analysis. The geodesic equations of charged massive particle and massless particle are determined uniformly and consistently. Based on the geodesic equation, the Hawking radiation of the charged massive particle is investigated near the event horizon of Kerr–Newman–de Sitter black hole. By finding the imaginary part of the action of charged massive particle, the Hawking temperature and the tunneling probability of charged massive particle across the event horizon of KNdS black hole are obtained. The finding of this paper is a development for Parikh–Wilczek’s tunneling technique.
A New Network Pruning Framework Based on Rewind
Authors: Yu Haoran , Zhang Weiwei , Zhou Hongbo , Ma Xin
Published: July 2022

Model pruning is one of the main methods of deep neural network model compression. However, the existing model pruning methods are inefficient, there is still a lot of redundancy in the network, and the pruning has a great impact on the accuracy. In addition, the traditional pruning process usually needs to fine-tune the network to restore accuracy, and fine-tuning has a limited effect on accuracy recovery, so it is difficult to achieve a high level of accuracy. In this paper, we propose a new neural network pruning framework: the channel sparsity is realized by introducing a scale factor, and the sparse network is pruned by setting a global threshold, which greatly improves the efficiency of pruning. After pruning, this paper proposes a rewind method to restore the accuracy, that is, save the weight after training, and then reload it on the network for training to restore the accuracy. In addition, we also study the best rewind point of the three networks. The experimental results show that our method significantly reduces the number of parameters and FLOPs without affecting or even improving the accuracy, and the rewind method proposed by us achieves a better accuracy recovery effect than fine-tuning. At the same time, we find that the epoch with the highest accuracy is the best rewind point, and the accuracy is the highest after saving its corresponding weight and retraining the model.
An Optimal Dead Time Compensator Design for Nonsquare Process with Disturbance Rejection
Authors: Roy Neelbrata , Sengupta Anindita , Sutradhar Ashoke
Published: July 2022

This work aims to establish an optimal design of the Smith dead-time compensator for a nonsquare multivariable system with a transfer function matrix containing first-order dead time elements. The scheme has a set point tracking controller along with disturbance rejection using an optimal estimator. An inverse signal from the estimator eliminates the disturbance. The proposed method significantly improves the disturbance rejection and performance index compared to the other established methods. The common evolutionary algorithms such as the grey wolf optimization technique and teaching learning based algorithm have been used to tune the controllers.
Inter-Turn Short-Circuit Faults Detection and Monitoring of Induction Machines Using WPT-Fuzzy Logic Approach Based on Online Condition
Authors: Indiran Raja Rajeswari , Stonier Albert Alexander
Published: July 2022

This paper proposes an efficient fuzzy logic-based fault detection scheme for diagnosing the inter-turn short-circuit (ITSC) faults in induction motors (IMs). The proposed approach utilizes the fast Fourier transforms (FFTs) and wavelet packet transform (WPT) for this detection of fault. To improve the efficiency and secure the operation, the proposed approach is detecting the fault in online manner. The WPT is utilized to extract the stator current signal into time-frequency domain characteristics. The variation in the amplitude of the vibration spectrum at different characteristic frequencies by FFT is utilized to identify the stator ITSC. The vibration signal is dignified by a MEMS accelerometer. The performance of the fuzzy logic fault detector (FLFD) for online condition is monitored with stator current, vibration and input speed. The performance of the proposed approach is performed at MATLAB/Simulink working site, and then the performance is compared to other existing works. The accuracy, precision, recall and specificity of the proposed approach are analyzed. Similarly, the statistical measures like root mean square error (RMSE), mean absolute percentage error (MAPE), mean bias error (MBE) and consumption time are analyzed.
Improved Read/Write Stability-Based Level Shift 5T Ternary SRAM Cell Design Using Enhanced Gate Diffusion Input BWGCNTFET
Authors: Suneel Kumar Gopavaram , Mamatha Gannera
Published: July 2022

Nowadays, CNTFET introduced the complexity of SRAM design along with the stability. To overcome these complexities, an enhanced Gate Diffusion Input technique-based Ballistic wrap gate CNTFET (EGDI-BWGCNTFET) technology with ternary static random-access memory (T-SRAM) is proposed in this paper. The aim of the proposed technique is “to give higher stability with less stagnant power consumption, voltage drop and store appropriate read/write value of the SRAM cells”. Here, level shift 5T ternary SRAM cell design using Enhanced Gate Diffusion Input Ballistic wrap gate CNTFET (level shift EGDI-BWGCNTFET 5T-ternary SRAM) is proposed for improving read and write stability. It uses two cross-coupled EGDI-BWGCNTFET ternary inverter, which is used for data storage elements along with one access transistor which is connected with bit line (BL) and word line (WL) with minimum supply voltage resulting in leakage current that is decreased. By this, proposed method reduces delay in the write cycles and read cycles. It provides good read static noise margin (RSNM) and controls precharge voltage. The proposed level shift EGDI-BWGCNTFET 5T-ternary SRAM is done in HSPICE platform. The performance of the proposed level shift EGDI-BWGCNTFET 5T-ternary SRAM design is measured in terms of lower Read Delay 23.25%, 22.94%, 18.38%, 23.97%, lower Write Delay 33.92%, 28.94%, 42.83%, 31.98% compared with the existing methods, such as 8T CNTFET-Ternary SRAM, 24T CNTFET-2Ternary SRAM, 18T CNTFET-Ternary SRAM and 17T CNTFET-Ternary SRAM, respectively.
Generation of C++ Code from Isabelle/HOL Specification
Authors: Jiang Dongchen , Xu Bo
Published: July 2022

Automatic code generation plays an important role in ensuring the reliability and correctness of software programs. Reliable programs can be obtained automatically from verified program specifications by code generators. The target languages of the existing code generators are mainly functional languages, which are relatively less used than C/C[Formula: see text]. As C/C[Formula: see text] is widely used in the industry and many fundamental software facilities and the correctness verification of C/C[Formula: see text] programs is difficult and cumbersome, this paper provides an automatic conversion framework that allows to generate C[Formula: see text] implementation from verified Isabelle/HOL specifications. The framework is characterized by combining the verification convenience of Isabelle/HOL and the efficiency of C[Formula: see text]. Since the correctness of the functional Isabelle/HOL specification can be guaranteed by interactive proofs, the correctness of the relevant generated C[Formula: see text] implementation can also be maintained.
Synthesis of Li1.2Mn0.54Ni0.13Co0.13O2 Nanorods by a Facile Self-Template Method and their Electrochemical Performances
Authors: Wang Jinjin , Wang Xinlu , Feng Qingnan , Shao Chenglong , Liu Guixia , Yu Wensheng , Dong Xiangting , Wang Jinxian
Published: July 2022

Lithium-rich manganese-based oxides have become one of the widely studied cathode materials for lithium-ion batteries due to their high-energy density, relatively low price and environmental friendliness. Herein, we propose a simple self-template route to prepare [Formula: see text][Formula: see text][Formula: see text][Formula: see text]O2 nanorods using rod-like Mn2O3 as templates. Besides, the effect of calcination temperature on the morphology and electrochemical properties of the electrode materials was investigated. [Formula: see text][Formula: see text][Formula: see text][Formula: see text]O2 nanorods as the cathode exhibit initial capacity of 251.4 mAh gt1 at 0.1 C and capacity retention rate of 67.9% after 200 cycles, which can be attributed to the enhanced layered structural stability, lower charge transfer resistance and shorter lithium-ion transport pathway.
Evaluating the Risk and Complexity of Pluvial Flood Damage in the U.S.
Authors: Tonn Gina , Czajkowski Jeffrey
Published: July 2022

Flood hazard in the U.S. is typically separated into two categories: storm surge and inland. Inland flooding is frequently represented as fluvial, stemming from overflow of rivers and streams. However, significant inland flood risk also exists in the form of pluvial flooding, resulting from ponding of water, and often occurring due to insufficient drainage in urban areas. Pluvial flood risk can be complex to model and is often not shown on floodplain maps, leading to significant uninsured risk. While pluvial and fluvial flooding are sometimes lumped together for purposes of modeling, insurance, and risk management, we hypothesize that key differences exist in damage associated with these types of inland flooding. We investigate and quantify these differences through study of three datasets: (i) Tropical cyclone (TC) flood insurance claims; (ii) non-Tropical Cyclone (non-TC) flood insurance claims; and (iii) Hurricane Harvey flood insurance claims in the Houston area. From our data analyses, we find that fluvial claims involve greater damage on average and are more likely to occur within the mapped Special Flood Hazard Area (i.e., 100-year floodplain) than pluvial claims. However, pluvial flooding is more frequent overall being the cause of 74% of TC and 60% of non-TC flood insurance claims in the U.S. TC floods have a higher percentage of pluvial flood insurance claims and higher average pluvial damage than non-TC floods. Analysis of Hurricane Harvey claims shows that zip codes with higher-than-expected losses tend to have high percentages of pluvial claims. Pluvial flooding and its local nuances exhibit the potential to reduce the accuracy of catastrophe models of expected flood damage.
Mechanical degradation mechanism of rock under seismic disturbance stress
Authors: Pan Yisha , Wang Chongyang , Wang Yidi
Published: July 2022

During the action of periodic seismic disturbance stress, the rock mass surrounding buried structures will show fatigue damage owing to cyclic loading. To explore the fatigue characteristics and mechanical degradation mechanism of this process, fatigue loading and uniaxial compression tests were carried out on gypsum samples. The conclusions are as follows. With increasing seismic wave amplitude, the stress loading and unloading velocity gradually increases, and the opening of the stress–strain hysteresis loop gradually increases. With increasing seismic wave frequency, the dip angle of hysteresis loops gradually inclines to the

σ

-axis (where

σ

is stress), and the variation amplitude of hysteresis loops on the

ε

-axis (where

ε

is strain) decreases gradually. This shows that the greater the amplitude of the seismic wave and the lower the frequency, the greater the damage to rock. Under seismic wave disturbance, with increasing number of disturbances, the original cracks in the sample gradually spread and infiltrate the rock, and secondary cracks gradually develop, indicating that the physical and mechanical properties of the rock gradually deteriorate. There is a strong correlation between the acoustic emission of samples and the stages of the stress–time curve for uniaxial compression. According to the acoustic emission characteristics, the stress–time curve can be divided into four stages: the initial loading stage, the stable crack growth stage, the unstable crack growth to failure stage and the post-peak stage. Compared with the sample before fatigue, the peak strain decreases significantly and the impact energy index increases significantly after fatigue loading. This indicates that some original cracks in the sample are compressed under seismic disturbance, the brittleness of the sample is enhanced and the rockburst tendency is greatly enhanced.
Global Fisheries Science Documents Human Impacts on Oceans: The Sea Around Us Serves Civil Society in the Twenty-First Century
Authors: Zeller Dirk , Palomares Maria L.D. , Pauly Daniel
Published: July 2022

Fishing provides the world with an important component of its food supply, but it also negatively impacts the biodiversity of marine and freshwater ecosystems, especially when industrial fishing is involved. To mitigate these impacts, civil society needs access to fisheries data (i.e., catches and catch-derived indicators of these impacts). Such data, however, must be more comprehensive than the official fisheries statistics supplied to the Food and Agriculture Organization of the United Nations (FAO) by its member countries, which shape public policy in spite of their deficiencies, notably underestimating small-scale fisheries. This article documents the creation, based on the geographically coarse FAO data, of a database and website ( https://www.seaaroundus.org ) that provides free reconstructed (i.e., corrected) catch data by ecosystem, country, species, gear type, commercial value, etc., to any interested person, along with catch-derived indicators from 1950 to the near present for the entire world.
Analysis and Design of Cooperative Control Solutions for Electrical Systems of Laser CNC Machines
Authors: Shao Shufeng
Published: July 2022

In order to further improve the collaborative control efficiency of the electrical system of the laser CNC machine tool, an electrical system based on the ultrafast laser CNC machine tool is proposed. The design of the collaborative control scheme is discussed from three aspects: the overall control scheme design, hardware structure design, and control software implementation of the electrical system of the laser numerical control machine tool. The experimental results show that the length of the metal sheet processed by the electrical system of the laser CNC machine tool is 5.3 cm and the width is about 3.6 cm, and the actual processing aperture size will also change according to the set number of variable radius turns, and more precise processing can be enabled in the online test. The research results show that this electrical collaborative control system scheme has strong practicability and feasibility. With the help of system upgrades and optimization, the efficient integration of laser processing technology and numerical control technology can be better achieved. It should be noted that the machining process of the machine tool is also required to make in-depth improvements, which can maximize the operating efficiency and machining accuracy of the electrical system of the CNC machine tool. The laser CNC machine tool researched and developed in this paper verifies the rationality and feasibility of the collaborative control scheme through practical experiments, which can meet the processing requirements and realize the integration of laser processing technology and numerical control technology. High machining efficiency and machining accuracy.
Design and Implementation of College Japanese Teaching Interactive System Based on Moodle Platform
Authors: Yang Jing
Published: July 2022

In order to make college Japanese teaching better adapt to the pace and process of the rapid development of society and enable contemporary college students to better apply and practice it, this study has built a college Japanese teaching interactive system based on Moodle platform to analyze the current situation of college Japanese education and teaching; by integrating the Moodle platform online teaching mode into the conventional teaching mode, we evaluate and analyze the demand data of the college Japanese teaching system under the two different teaching modes; it can be clearly seen that the application of Moodle platform online teaching mode can enable teachers and students or students to think together, work together to solve problems, more actively promote students’ independent interaction, communication, exchange, and discussion with others, greatly improve students’ enthusiasm for autonomous learning, and enable students to receive higher quality education and teaching.
Multiobjective Optimization Management of Construction Engineering Based on Ant Colony Algorithm
Authors: Liang Xuejie
Published: July 2022

In order to solve the problems of extensive management, the construction stage often faces the extension of construction period, excessive cost, and large amount of carbon emission and this paper proposes a multiobjective optimization management method of construction engineering based on ant colony algorithm. Firstly, taking the installation process of laminated plate components as an example, this paper combs the construction process and the consumption types of labor, materials, machinery, or equipment in each process in detail. Then, combined with the idea of multiobjective optimization, the multiobjective optimization mathematical model of construction process is constructed, and the construction data obtained from field investigation are summarized and analyzed to obtain the cost, construction period, and carbon emission of each process under different execution modes. The experimental results show that the ant colony algorithm is used to find the comprehensive optimal process execution mode combination of “cost duration carbon emission.” After optimization, the installation cost of laminated plate components is reduced by 1.55%, the construction period is reduced by 3.52%, and the carbon emission is reduced by 7.36%. The feasibility and rationality of multiobjective optimization in this paper are verified by experiments, which can effectively guide the optimization management of construction process.
Insulator Semantic Segmentation in Aerial Images Based on Multiscale Feature Fusion
Authors: Cui Zheng , Yang Chunxi , Wang Sen
Published: July 2022

As one of the important components in the transmission line, the insulator is related to the safe and reliable operation of the entire transmission line. Aerial images are characterized by complex backgrounds, multiple pseudotargets, and low signal‐to‐noise ratios. Rapid and accurate localization of insulators in aerial images is a critical and challenging task in automatic inspection of transmission lines. Most insulator localization methods suffer from the loss of target edge detail information and large amount of model parameters. To solve these problems, this paper adopts an Encoder‐Decoder architecture, called ED‐Net, to realize end‐to‐end intelligent and accurate identification of insulators in aerial images. Firstly, Initial Module and CA‐Bottleneck which are used to extract features from images to generate finer feature maps are proposed in the Encoder path. Meanwhile, global average pooling is used to preserve the maximum receptive field. Secondly, in the Decoder path, Refinement Boundary Module and Asymmetric Convolution Module are given to perform boundary optimization on the feature map, which are generated by the Encoder path. Finally, the Attention Feature Fusion Module is introduced into the Decoder path to combine high‐level features with low‐level features better and reduce the gap between features of different levels. The proposed model architecture keeps a suitable balance between the model parameters and insulator segmentation performance on insulator test datasets. Specifically, for a 512 × 512 input image, 95.12% mean intersection over union is achieved on the insulator test datasets with different environments and model parameters size being only 13.61 M. Compared with the current state‐of‐the‐art semantic segmentation methods, the results show that the proposed method has higher efficient and accuracy.
[Retracted] Selection of the Male or Female Sex in Chronic Unpredictable Mild Stress‐Induced Animal Models of Depression
Authors: Jiang Shuo , Lin Ling , Guan Lihua , Wu Youming
Published: July 2022

Depression is a serious public health problem and an important factor leading to disease‐related disability. Influenced by many factors, such as psychological, hormonal, and genetic factors, the incidence rate of depression in females is approximately two times that in males. However, in preclinical neuroscience research, the selection of the animals’ sex for use in depression models has been controversial. At present, in most preclinical studies, the animals generally chosen in depression models have been male rodents rather than female rodents. It remains doubtful whether the data obtained from male animals can be generalized to female animals. The performance of female animals in preclinical studies of depression has been inconclusive. Based on a review of a large number of original studies in the PubMed database, it was found that although male rodents are more commonly used in the study of depression, the use of female animals also shows good modeling of depression and has its advantages. The influence of the animals’ sex in the chronic unpredictable mild stress (CUMS) model needs further research.
Simulation Training Auxiliary Model Based on Neural Network and Virtual Reality Technology
Authors: Liu Wei
Published: July 2022

Training simulators have been gradually evolving in the direction of software, virtualization, networking, and multiplatform in recent years, with the continuous development of hardware and software technologies, particularly the maturity of VR (Virtual Reality) related technologies. The network intrusion program allows remote hackers to take control of the system, posing a serious threat to the network and computer security. As a result, this paper proposes a VR-based ID (intrusion detection) simulation training system. This paper proposes an ID model based on CNN (Convolutional Neural Networks) and LSTM to address these issues (Long Short-term Memory Networks). This model oversamples data from unbalanced data sets, reducing the difference in category data and thus improving the ID model’s performance and existing detection methods to compensate for the flaw. 3DSMAX technology is used to simulate the process visualization scene, as well as some key equipment models and signal transmission simulations, during the system design and implementation process. The experimental results show that CNN LSTM outperforms BP, and the overall evaluation index F1 has significantly improved, particularly the F1 index of D4. CNN LSTM outperforms GA (genetic algorithm) by 12.75 percent and BP by 14.07 percent. The system essentially accomplishes the anticipated simulation training goal, and the simulation training effect is impressive.
Transmembrane Transporter Sema3D Serves as a Tumor Suppressor in Localized Clear Cell Renal Cell Carcinoma
Authors: Xie Ruiyang , Wu Jie , Shang Bingqing , Cao Chuanzhen , Bi Xingang , Shi Hongzhe , Shou Jianzhong , Guan Youyan
Published: July 2022

Background. The transmembrane transporter Sema3D is a vital molecule involved in axon guidance and carcinogenesis of variant malignancies. However, the relationship between Sema3D and clear cell renal cell carcinoma (ccRCC) is barely reported and remains unclear. Methods. Sema3D expression and the connection of clinical and histological characteristics were first analyzed with transcriptome data in the TCGA repository. We then located and examined the Sema3D expression in ccRCC patients by using immunofluorescence staining in the tissue microarray. The prognostic value of Sema3D in localized ccRCC was evaluated by Cox proportional hazard analysis. Functional and gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to describe the potential mechanisms of Sema3D in ccRCC. Correlation analysis between Sema3D and tumor-infiltrating lymphocytes was calculated by ssGSEA. Results. In 86 ccRCC patients, Sema3D mRNA and protein expression were downregulated in tumor tissues than the para-tumor tissues, and Sema3D was dominantly expressed in the extracellular space. Low expression of Sema3D was associated with advanced tumor stage, advanced histological grade, and poor prognosis in ccRCC. In the subgroup analysis of 81 localized ccRCC patients, Sema3D expression level was an independent protective prognostic factor for overall survival (OS) (HR = 0.125,

p
=
0.043

). Coagulation, complement, estrogen response, and KRAS signaling hallmark gene sets were identified as Sema3D-related signaling pathways. The expression level of Sema3D was significantly correlated with a high abundance of several immune cells (neutrophils, eosinophils, and T helper cells). Conclusions. Transmembrane transporter Sema3D is an efficient prognostic biomarker for localized ccRCC patients, by playing the role of tumor suppressor in ccRCC. Sema3D can be a novel therapeutic target for ccRCC.
An Efficient Method for Detecting Supernodes Using Reversible Summary Data Structures in the Distributed Monitoring Systems
Authors: Zhou Aiping , Qian Jin
Published: July 2022

Supernode detection has many applications in detecting network attacks, assisting resource allocation, etc. As 5G/IoT networks constantly grow, big network traffic brings a great challenge to collect massive traffic data in compact and real-time way. Previous works focus on detecting supernodes in a measurement point, while only a few works consider it in the distributed monitoring system. Moreover, they are not able to measure two types of node cardinalities simultaneously and reconstruct labels of supernodes efficiently due to large calculation and memory cost. To address these problems, we propose a novel reversible and distributed traffic summarization called RDS to simultaneously measure source and destination cardinalities for detecting supernodes in the distributed monitoring system. The basic idea of our approach is that each monitor generates a summary data structure using the coming packets and sends the summary data structure to the controller; then, the controller aggregates the received summary data structures, estimates node cardinalities, and reconstructs labels of supernodes according to the aggregated summary data structure. The experimental results based on real network traffic demonstrate that the proposed approach can detect up to 96% supernodes with a low memory requirement in comparison with state-of-the-art approaches.