Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

Analysis on the turning point of dynamic in-plane compressive strength for a plain weave composite

Experimental investigations on dynamic in-plane compressive behavior of a plain weave composite were performed using the split Hopkinson pressure bar. A quantitative criterion for calculating the constant strain rate of composites was established. Then the upper limit of strain rate, restricted by stress equilibrium and constant loading rate, was rationally estimated and confirmed by tests. Within the achievable range of 0.001/s-895/s, it was found that the strength increased first and subsequently decreased as the strain rate increased. This feature was also reflected by the turning point(579/s) of the bilinear model for strength prediction. The transition in failure mechanism, from local opening damage to completely splitting destruction, was mainly responsible for such strain rate effects. And three major failure modes were summarized under microscopic observations: fiber fracture, inter-fiber fracture, and interface delamination. Finally, by introducing a nonlinear damage variable, a simplified ZWT model was developed to characterize the dynamic mechanical response. Excellent agreement was shown between the experimental and simulated results.

High-sensitive state perception method for inverter-fed machine turn insulation based on FrFT-Mel

Amidst the swift advancement of new power systems and electric vehicles,inverter-fed machines have progressively materialized as a pivotal apparatus for efficient energy conversion.Stator winding turn insulation failure is the root cause of inverter-fed machine breakdown.The online monitoring of turn insulation health can detect potential safety risks promptly,but faces the challenge of weak characteristics of turn insulation degradation.This study proposes an innovative method to evaluate the turn insulation state of inverter-fed machines by utilizing the fractional Fourier transform with a Mel filter(FrFT-Mel).First,the sensitivity of the high-frequency(HF)switching oscillation current to variations in turn insulation was analyzed within the fractional domain.Subsequently,an improved Mel filter is introduced,and its structure and parameters are specifically designed based on the features intrinsic to the common-mode impedance resonance point of the electrical machine.Finally,an evaluation index was proposed for the turn insulation state of inverter-fed machines.Experimental results on a 3kW permanent magnet synchronous machine(PMSM)demonstrate that the proposed FrFT-Mel method significantly enhances the sensitivity of turn insulation state perception by approximately five times,compared to the traditional Fourier transform method.

Evolution and Prospects of Russia’s“Turn to the East”

With the escalation of the Ukraine crisis,Russia’s policy of“Turn to the East”has evolved into“Turn to the Non-West”at an accelerated pace.Involving both a shift of focus in diplomacy and economics and the“de-Westernization”in financial and ideological areas,it has become a strategy to break through Western diplomatic and economic blockade.The transition will continue in the medium term,but adjustments or twists and turns are likely under the influence of internal and external factors.

DER SPATIAL TURN IN DEN KLASSISCHEN ALTERTUMSWISSENSCHAFTEN(UND SPEZIELL IN DER EPIGRAPHIK)

Since the 1990s the so-called spatial turn has brought back space and topography into the discussion within historical studies,particular ancient studies.This survey reviews current trends and developments within the field and offers some perspectives on possible future developments related to space,material,objects,their agency,and frames.

TURNING LIGNIN INTO VALUABLE PRODUCTS

In a study published in Nature Catalysis on May 28,Chinese scientists unveiled a nove l approach to transforming lignin,a major component of woody biomass,into valuable chemical products(doi:10.1038/s41929-024-01165-w).This discovery could pave the way for more sustainable and efficient use of renewable resources.

Numerical Study of a Three-Dimensional Laminar Flow in a Rectangular Channel with a 180-Degree Sharp Turn

This study presents a numerical analysis of three-dimensional steady laminar flow in a rectangular channel with a 180-degree sharp turn. The Navier-Stokes equations are solved by using finite difference method for Re = 900. Three-dimensional streamlines and limiting streamlines on wall surface are used to analyze the three-dimensional flow characteristics. Topological theory is applied to limiting streamlines on inner walls of the channel and two-dimensional streamlines at several cross sections. It is also shown that the flow impinges on the end wall of turn and the secondary flow is induced by the curvature in the sharp turn.

Combination of dura turning-over and decompressive craniectomy： a new pattern of surgery for cerebral infarction caused by craniocerebral gunshot injury

Background:Craniocerebral gunshot injury refers to a wound caused by a bullet passing through or lodged in brain tissue,resulting in the loss of function of a certain area or other fatal damage to the human brain.Craniocerebral gunshot injury is usually life-threatening and is very common in modern warfare,accounting for the majority of battle casualties.Most of the patients suffer from acute cerebral infarction caused by vascular injury.Lack of early and solid battlefield emergency medical interference adds to the risk of death among the wounded.Case presentation:We present a 24-year-old man who was shot with a shotgun from a distance of 15m in an accidental injury.Forty-seven grape shots were found on his body surface by physical examination.A computed tomography(CT)scan demonstrated large areas of low-density shadows in his right parietal lobe and right temporal lobe with the midline shifting to the left side 2 days later.Afterwards,the patient was transferred to our emergency medical center at Changzheng Hospital in Shanghai.Cranial computed tomography angiography(CTA)showed a high-density shadow in the initial part of the right middle cerebral artery.The branches after the initial part were obliterated.Prompt medical attention and decompressive craniotomy(DC)surgery contributed to the final recovery from cerebral infarction of this patient.Conclusion:Bullets can penetrate or be lodged in the brain,causing intracranial hypertension.The bullets lodged in the brain can result in stenosis and embolism of a cerebral artery,causing acute cerebral infarction.Combining dura turning-over surgery with DC surgery can not only decrease intracranial pressure,which can increase the blood supply for hypertension-induced vessel stenosis,but also help vessels outside the dura mater grow into ischemic areas of the cerebral cortex.However,this new pattern of surgery needs further support from evidence-based medicine.

NC code generation for laser assisted turn-mill of various type of clovers and square section members

Laser assisted turning （LAT） is one of the advanced machining technologies, which uses laser power to heat the surface of a workpiece before the material is removed. It has several advantages of low manufacturing costs, high productivity and high qualities to machine difficult-to-cut materials such as silicon nitride, muUite, zirconia and Ni. A large part of studies on LAT have been focused on a round bar. With increasing demands for high quality products and high performance engineering system, the researches on LAT for clover and square section members are necessary. But, these workpieces are impossible to be machined on conventional CNC lathe and to generate NC code with current CAM softwares. As a basic research for combining LAT with a tilting index table type 5-axis machining center, i.e. laser assisted turn-mill, a new method is suggested to generate NC code that can process various types of clover and square section members through development of C＋＋ program.

A Study on Effects of Turn-over Technology on the Quality of Jinmudan Oolong Tea

This paper reported the effect of oolong tea processing procedure of turn-over on quality of the Jinmudan Oolong tea,including taste components and volatile compounds.The content of the water extractable solids was gradually increased,but the content of amino acid decreased and then increased,and the content of the soluble sugar and tea polyphenols increased after the first turn-over processing.The major volatiles of the three tested Jinmudan Oolong tea samples were nerolidolcistrans,α-farnesene,palmitic acid,indole and 9,12,15-octadecatrienoicacid and methyl ester.The sensory evaluation results showed that an appropriate increase in the number of turn-over was helpful to quality of the Jinmudan Oolong tea.

Integral Event-Triggered Attack-Resilient Control of Aircraft-on-Ground Synergistic Turning System With Uncertain Tire Cornering Stiffness

This article proposes an integral-based event-triggered attack-resilient control method for the aircraft-on-ground(AoG) synergistic turning system with uncertain tire cornering stiffness under stochastic deception attacks. First, a novel AoG synergistic turning model is established with synergistic reverse steering of the front and main wheels to decrease the steering angle of the AoG fuselage, thus reducing the steady-state error when it follows a path with some large curvature. Considering that the tire cornering stiffness of the front and main wheels vary during steering, a dynamical observer is designed to adaptively identify them and estimate the system state at the same time.Then, an integral-based event-triggered mechanism(I-ETM) is synthesized to reduce the transmission frequency at the observerto-controller end, where stochastic deception attacks may occur at any time with a stochastic probability. Moreover, an attackresilient controller is designed to guarantee that the closed-loop system is robust L2-stable under stochastic attacks and external disturbances. A co-design method is provided to get feasible solutions for the observer, controller, and I-ETM simultaneously. An optimization program is further presented to make a tradeoff between the robustness of the control scheme and the saving of communication resources. Finally, the low-and high-probability stochastic deception attacks are considered in the simulations. The results have illustrated that the AoG synergistic turning system with the proposed control method follows a path with some large curvature well under stochastic deception attacks. Furthermore,compared with the static event-triggered mechanisms, the proposed I-ETM has demonstrated its superiority in saving communication resources.

A theoretical and deep learning hybrid model for predicting surface roughness of diamond-turned polycrystalline materials

Polycrystalline materials are extensively employed in industry.Its surface roughness significantly affects the working performance.Material defects,particularly grain boundaries,have a great impact on the achieved surface roughness of polycrystalline materials.However,it is difficult to establish a purely theoretical model for surface roughness with consideration of the grain boundary effect using conventional analytical methods.In this work,a theoretical and deep learning hybrid model for predicting the surface roughness of diamond-turned polycrystalline materials is proposed.The kinematic–dynamic roughness component in relation to the tool profile duplication effect,work material plastic side flow,relative vibration between the diamond tool and workpiece,etc,is theoretically calculated.The material-defect roughness component is modeled with a cascade forward neural network.In the neural network,the ratio of maximum undeformed chip thickness to cutting edge radius RT S,work material properties(misorientation angle θ_(g) and grain size d_(g)),and spindle rotation speed n s are configured as input variables.The material-defect roughness component is set as the output variable.To validate the developed model,polycrystalline copper with a gradient distribution of grains prepared by friction stir processing is machined with various processing parameters and different diamond tools.Compared with the previously developed model,obvious improvement in the prediction accuracy is observed with this hybrid prediction model.Based on this model,the influences of different factors on the surface roughness of polycrystalline materials are discussed.The influencing mechanism of the misorientation angle and grain size is quantitatively analyzed.Two fracture modes,including transcrystalline and intercrystalline fractures at different RTS values,are observed.Meanwhile,optimal processing parameters are obtained with a simulated annealing algorithm.Cutting experiments are performed with the optimal parameters,and a flat surface finish with Sa 1.314 nm is finally achieved.The developed model and corresponding new findings in this work are beneficial for accurately predicting the surface roughness of polycrystalline materials and understanding the impacting mechanism of material defects in diamond turning.

Effects of Snow Cover on Alfalfa Overw intering and Turning Green

In order to investigate the effect of snow cover on alfalfa overwintering and turning green,6 different alfalfa varieties( including Longmu806,Gongnong No. 1,Aohan,Wega 7F,WL319 HQ,Caoyuan No. 3) were used as plant materials. There were 4 treatments in this study include snow-cover of 0,30%,70% and natural snow-cover( used as control). Nutrient content and antioxidant enzyme activity of root were measured before and after overwintering period. The rate of plant returning green and growth rate after greening were also measured after turning green. The result showed that the snow cover was the guarantee of alfalfa safely overwintering and turning green. The 54. 5-77. 9 cm snowfall was the optimum thickness of snow for safe overwintering. Alfalfa improved the overwintering ability by enhancing the root nutrients and antioxidant enzyme activity,and it was affected by snow cover. In addition total nitrogen and soluble sugar increased by 61% and 60% respectively,soluble protein reduced by8%,SOD and CAT reduced by 20% and 9% respectively than that before the overwintering under 70% of natural snow-cover. There were differences between overwintering ability of 6 different alfalfa varieties,in which Caoyuan No. 3 has more grass production and Wega 7F has stronger overwintering ability.

Good or Evil,Both or Neither——An Analysis of the Governess in The Turn of the Screw

Henry James’ novella The Turn of the Screw has drawn much attention from critics, and the discussion mainly dwells on the ghosts’ existence or the governess’ sexual desire repression, which result in the children’s tragedy.This paper tries to approach the story from a new perspective. In accordance with James’ theory of "unity" and "roundness",this paper avoids the judgment on the governess of being simply good or evil,but focuses on the analysis of the process of being protective to persecutive.

The summer solstice is the turning point when light and temperature affect the growth of trees

The interaction between light and temperature is known to influence the seasonal growth of trees.Traditional studies on"light"primarily focus on day length,specifically short day(SD)or long day(LD)conditions.However,little research has been conducted on the process of transitioning between SD and LD conditions.

Technique for Multi-Pass Turning Optimization Based on Gaussian Quantum-Behaved Bat Algorithm

The multi-pass turning operation is one of the most commonly used machining methods in manufacturing field.The main objective of this operation is to minimize the unit production cost.This paper proposes a Gaussian quantum-behaved bat algorithm(GQBA)to solve the problem of multi-pass turning operation.The proposed algorithm mainly includes the following two improvements.The first improvement is to incorporate the current optimal positions of quantum bats and the global best position into the stochastic attractor to facilitate population diversification.The second improvement is to use a Gaussian distribution instead of the uniform distribution to update the positions of the quantum-behaved bats,thus performing a more accurate search and avoiding premature convergence.The performance of the presented GQBA is demonstrated through numerical benchmark functions and amulti-pass turning operation problem.Thirteen classical benchmark functions are utilized in the comparison experiments,and the experimental results for accuracy and convergence speed demonstrate that,in most cases,the GQBA can provide a better search capability than other algorithms.Furthermore,GQBA is applied to an optimization problem formulti-pass turning,which is designed tominimize the production cost while considering many practical machining constraints in the machining process.The experimental results indicate that the GQBA outperforms other comparison algorithms in terms of cost reduction,which proves the effectiveness of the GQBA.

Predicting Βeta-Turns and Βeta-Turn Types Using a Novel Over-Sampling Approach

β-turn is one of the most important reverse turns because of its role in protein folding. Many computational methods have been studied for predicting β-turns and β-turn types. However, due to the imbalanced dataset, the performance is still inadequate. In this study, we proposed a novel over-sampling technique FOST to deal with the class-imbalance problem. Experimental results on three standard benchmark datasets showed that our method is comparable with state-of-the-art methods. In addition, we applied our algorithm to five benchmark datasets from UCI Machine Learning Repository and achieved significant improvement in G-mean and Sensitivity. It means that our method is also effective for various imbalanced data other than β-turns and β-turn types.

Status of research on non-conventional technology assisted single-point diamond turning

With the increasing use of difficult-to-machine materials in aerospace applications,machining requirements are becoming ever more rigorous.However,traditional single-point diamond turning(SPDT)can cause surface damage and tool wear.Thus,it is difficult for SPDT to meet the processing requirements,and it has significant limitations.Research indicates that supplementing SPDT with unconventional techniques can,importantly,solve problems due to the high cutting forces and poor surface quality for difficult-to-machine materials.This paper first introduces SPDT and reviews research into unconventional techniques for use with SPDT.The machining mechanism is discussed,and the main advantages and disadvantages of various methods are investigated.Second,hybrid SPDT is briefly described,which encompasses ultrasonic-vibration magnetic-field SPDT,ultrasonic-vibration laser SPDT,and ultrasonic-vibration cold-plasma SPDT.Compared with the traditional SPDT method,hybrid SPDT produces a better optical surface quality.The current status of research into unconventional techniques to supplement SPDT is then summarized.Finally,future development trends and the application prospects of unconventional assisted SPDT are discussed.

Design of a coated thinly clad chalcogenide long-period fiber grating refractive index sensor based on dual-peak resonance near the phase matching turning point

A novel method for designing chalcogenide long-period fiber grating(LPFG) sensors based on the dual-peak resonance effect of the LPFG near the phase matching turning point(PMTP) is presented. Refractive index sensing in a high-refractive-index chalcogenide fiber is achieved with a coated thinly clad film. The dual-peak resonant characteristics near the PMTP and the refractive index sensing properties of the LPFG are analyzed first by the phase-matching condition of the LPFG. The effects of film parameters and cladding radius on the sensitivity of refractive index sensing are further discussed. The sensor is optimized by selecting the appropriate film parameters and cladding radius. Simulation results show that the ambient refractive index sensitivity of a dual-peak coated thinly clad chalcogenide LPFG at the PMTP can be 2400 nm/RIU, which is significantly higher than that of non-optimized gratings. It has great application potential in the field of chemical sensing and biosensors.