Toughening ultrastrong low-density steel by textured δ-ferrite lamellas

By both the Charpy V-notched impact and the projectile tests, we here investigated the dynamic fracture behavior of a recently developed ultrastrong lightweight steel comprising a hierarchical martensitic matrix, dispersed ultra-fine-retained austenite grains and oriented δ-ferrite lamellas, the latter being due to high Al and Si contents employed for low-density design. This steel shows a superior combination of specific ultimate tensile strength and impact toughness to other ultrastrong steels and has successfully arrested a real steel-cored bullet shot. These are attributed to the densely textured δ-ferrite lamellas that can deflect the propagating cracks until they are trapped and enclosed besides austenite-to-martensite transformation crack closure, leading to more energy consumed before failure. These results suggest a new pathway for toughening ultrastrong lightweight steels.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

2-D Modeling and Calculations of Stratospheric Ozone and Influences of Convection, Diffusion, and Time

An engineering system approach of 2-D cylindrical model of transient mass balance calculations of ozone and other concerned chemicals along with fourteen photolysis, ozone-generating and ozone-depleting chemical reaction equations was developed, validated, and used for studying the ozone concentrations, distribution and peak of the layer, ozone depletion and total ozone abundance in the stratosphere. The calculated ozone concentrations and profile at both the Equator and a 60˚N location were found to follow closely with the measured data. The calculated average ozone concentration was within 1% of the measured average, and the deviation of ozone profiles was within 14%. The monthly evolution of stratospheric ozone concentrations and distribution above the Equator was studied with results discussed in details. The influences of slow air movement in both altitudinal and radial directions on ozone concentrations and profile in the stratosphere were explored and discussed. Parametric studies of the influences of gas diffusivities of ozone DO3 and active atomic oxygen DO on ozone concentrations and distributions were also studied and delineated. Having both influences through physical diffusion and chemical reactions, the diffusivity (and diffusion) of atomic oxygen DO was found to be more sensitive and important than that of ozone DO3 on ozone concentrations and distribution. The 2-D ozone model present in this paper for stratospheric ozone and its layer and depletion is shown to be robust, convenient, efficient, and executable for analyzing the complex ozone phenomena in the stratosphere. .

Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learning to predict software bugs,but a more precise and general approach is needed.Accurate bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning methods.However,these studies are not generalized and efficient when extended to other datasets.Therefore,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems.The methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a model.Four National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were combined.It reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

Novelty of Different Distance Approach for Multi-Criteria Decision-Making Challenges Using q-Rung Vague Sets

In this article,multiple attribute decision-making problems are solved using the vague normal set(VNS).It is possible to generalize the vague set(VS)and q-rung fuzzy set(FS)into the q-rung vague set(VS).A log q-rung normal vague weighted averaging(log q-rung NVWA),a log q-rung normal vague weighted geometric(log q-rung NVWG),a log generalized q-rung normal vague weighted averaging(log Gq-rung NVWA),and a log generalized q-rungnormal vagueweightedgeometric(logGq-rungNVWG)operator are discussed in this article.Adescription is provided of the scoring function,accuracy function and operational laws of the log q-rung VS.The algorithms underlying these functions are also described.A numerical example is provided to extend the Euclidean distance and the Humming distance.Additionally,idempotency,boundedness,commutativity,and monotonicity of the log q-rung VS are examined as they facilitate recognizing the optimal alternative more quickly and help clarify conceptualization.We chose five anemia patients with four types of symptoms including seizures,emotional shock or hysteria,brain cause,and high fever,who had either retrograde amnesia,anterograde amnesia,transient global amnesia,post-traumatic amnesia,or infantile amnesia.Natural numbers q are used to express the results of the models.To demonstrate the effectiveness and accuracy of the models we are investigating,we compare several existing models with those that have been developed.

Development and characteristics of a low rare-earth containing magnesium alloy with high strength-ductility synergy

In this study,we successfully developed a low RE containing Mg-3Y-2Gd-1Nd-0.5Zr(wt%)alloy with high strength-ductility synergy by combined processes of hot extrusion,hot rolling and ageing.This alloy exhibits an excellent strength-ductility balance(UTS of 345±2.0 MPa,TYS of 301±5.0 MPa and EL of 9.2±1.9%),which is better than that of many Mg-RE wrought alloys with higher RE concentration and even comparable to that of 6061 Al wrought alloy.A long-range chain-like structure consisting ofβphase,βH phase,βM phase and zig-zag atomic columns is observed for the first time in the studied alloy.The combined process of hot extrusion and hot rolling boosts the formation of deformed grains and low angle grain boundaries,and makes the deformed grains dominate in the alloy strengthening.Under this circumstance,the following ageing generates a novel heterogeneous structure comprising the long-range chain-like structure with broad interparticle spacing and the spacious precipitate-free zones in the deformed grains,which plays a key role in the concurrent strengthening and toughening of the alloy.The present study demonstrates that the deformed grains with long-range chain-like structures and precipitate-free zones is desirable microstructure for the low RE containing Mg alloys to achieve high strength-ductility synergy.

Voice Response Questionnaire System for Speaker Recognition Using Biometric Authentication Interface

The use of voice to perform biometric authentication is an importanttechnological development,because it is a non-invasive identification methodand does not require special hardware,so it is less likely to arouse user disgust.This study tries to apply the voice recognition technology to the speech-driveninteractive voice response questionnaire system aiming to upgrade the traditionalspeech system to an intelligent voice response questionnaire network so that thenew device may offer enterprises more precise data for customer relationshipmanagement(CRM).The intelligence-type voice response gadget is becominga new mobile channel at the current time,with functions of the questionnaireto be built in for the convenience of collecting information on local preferencesthat can be used for localized promotion and publicity.Authors of this study propose a framework using voice recognition and intelligent analysis models to identify target customers through voice messages gathered in the voice response questionnaire system;that is,transforming the traditional speech system to anintelligent voice complex.The speaker recognition system discussed hereemploys volume as the acoustic feature in endpoint detection as the computationload is usually low in this method.To correct two types of errors found in the endpoint detection practice because of ambient noise,this study suggests ways toimprove the situation.First,to reach high accuracy,this study follows a dynamictime warping(DTW)based method to gain speaker identification.Second,it isdevoted to avoiding any errors in endpoint detection by filtering noise from voicesignals before getting recognition and deleting any test utterances that might negatively affect the results of recognition.It is hoped that by so doing the recognitionrate is improved.According to the experimental results,the method proposed inthis research has a high recognition rate,whether it is on personal-level or industrial-level computers,and can reach the practical application standard.Therefore,the voice management system in this research can be regarded as Virtual customerservice staff to use.

Federated Feature Concatenate Method for Heterogeneous Computing in Federated Learning

Federated learning is an emerging machine learning techniquethat enables clients to collaboratively train a deep learning model withoutuploading raw data to the aggregation server. Each client may be equippedwith different computing resources for model training. The client equippedwith a lower computing capability requires more time for model training,resulting in a prolonged training time in federated learning. Moreover, it mayfail to train the entire model because of the out-of-memory issue. This studyaims to tackle these problems and propose the federated feature concatenate(FedFC) method for federated learning considering heterogeneous clients.FedFC leverages the model splitting and feature concatenate for offloadinga portion of the training loads from clients to the aggregation server. Eachclient in FedFC can collaboratively train a model with different cutting layers.Therefore, the specific features learned in the deeper layer of the serversidemodel are more identical for the data class classification. Accordingly,FedFC can reduce the computation loading for the resource-constrainedclient and accelerate the convergence time. The performance effectiveness isverified by considering different dataset scenarios, such as data and classimbalance for the participant clients in the experiments. The performanceimpacts of different cutting layers are evaluated during the model training.The experimental results show that the co-adapted features have a criticalimpact on the adequate classification of the deep learning model. Overall,FedFC not only shortens the convergence time, but also improves the bestaccuracy by up to 5.9% and 14.5% when compared to conventional federatedlearning and splitfed, respectively. In conclusion, the proposed approach isfeasible and effective for heterogeneous clients in federated learning.

Unusual capitate fracture with dorsal shearing pattern and concomitant carpometacarpal dislocation with a 6-year follow-up:A case report

BACKGROUND Isolated capitate fractures are rare carpal fractures.Following high-energy injuries,capitate fractures are usually associated with other carpal fractures or ligament injuries.The management of capitate fractures depends on the fracture pattern.Here,we report an unusual capitate fracture with a dorsal shearing pattern and concomitant carpometacarpal dislocation,with a 6-year follow-up.To the best of our knowledge,this fracture pattern and surgical management have not been previously reported.CASE SUMMARY A 28-year-old man presented with left-hand volar tenderness and decreased grip strength that persisted for one month after a traffic accident.Radiography showed a distal capitate fracture with carpometacarpal joint incongruence.Computed tomography(CT)revealed a distal capitate fracture with carpometacarpal joint dislocation.The distal fragment was rotated by 90°in the sagittal plane,and an oblique shearing fracture pattern was noted.Open reduction and internal fixation(ORIF)with a locking plate were performed using the dorsal approach.The imaging studies performed 3 mo and 6 years following surgery revealed a healed fracture,and the Disabilities of the Arm,Shoulder,and Hand and visual analog scale scores were significantly improved.CONCLUSION CT can detect capitate fractures with dorsal shearing pattern and concomitant carpometacarpal dislocation.ORIF using a locking plate are possible.

Fabrication of High Color Rendering Index White Light Emitting Diodes from Gold Nanoclusters

We demonstrated gold nanoclusters as color tunable emissive light converters for the application of white light emitting diodes (WLEDs). A blue LED providing 460 nm to excite gold nanoclusters mixed with UV curable material generates broad bandwidth emission at the visible range. Increasing the amount of gold nanoclusters, the correlated color temperature of WLEDs tuned from cold white to warm white, and also results in the variation of color rendering index (CRI). The highest CRI in the experiment is 92.

Impact of gut–brain interaction in emerging neurological disorders

The central nervous system(CNS)is a reservoir of immune privilege.Specialized immune glial cells are responsible for maintenance and defense against foreign invaders.The blood–brain barrier(BBB)prevents detrimental pathogens and potentially overreactive immune cells from entering the periphery.When the double-edged neuroinflammatory response is overloaded,it no longer has the protective function of promoting neuroregeneration.Notably,microbiota and its derivatives may emerge as pathogen-associated molecular patterns of brain pathology,causing microbiome–gut–brain axis dysregulation from the bottom-up.When dysbiosis of the gastrointestinal flora leads to subsequent alterations in BBB permeability,peripheral immune cells are recruited to the brain.This results in amplification of neuroinflammatory circuits in the brain,which eventually leads to specific neurological disorders.Aggressive treatment strategies for gastrointestinal disorders may protect against specific immune responses to gastrointestinal disorders,which can lead to potential protective effects in the CNS.Accordingly,this study investigated the mutual effects of microbiota and the gut–brain axis,which may provide targeting strategies for future disease treatment.

Effects of Different Cations on the Flocculation and Sedimentation of Static Fine-Grained

Natural water bodies mostly contain cations,and the type and content of these cations are the main factors affecting the flocculation of fine-grained cohesive sediments and the floc sedimentation rate at the interface between clear and turbid water.From the microscopic aspect,this study examined the changing patterns of porosity and the fractal dimension of the flocs of fine-grained cohesive sediments.Sedimentation experiments under different sediment contents and electrolyte conditions were conducted,and microscopic images of the flocs were analysed using Image-Pro Plus(IPP)and MATLAB based on the fractal theory.From the macroscopic aspect,this study experimentally investigated the flocculation and sedimentation of fine-grained cohesive sediments and proposed a sedimentation rate equation by introducing an ion concentration-related parameter into an existing sedimentation rate equation(stagnation zone)based on the adsorption isotherm equation.The equation proposed in this study was validated with measured data.The calculated values were in good agreement with the measured values,with a relative error of 16%.The findings of this study provide a reference for further research on the flocculation and sedimentation of fine-grained cohesive sediments in different water bodies.

Effects of different dietary energy and protein levels and sex on growth performance,carcass characteristics and meat quality of F1 Angus x Chinese Xiangxi yellow cattle

Background:The experiment evaluated the effect of nutrition levels and sex on the growth performance,carcass characteristics and meat quality of F1 Angus × Chinese Xiangxi yellow cattle.Methods:During the background period of 184 d,23 steers and 24 heifers were fed the same ration,then put into a2×2×2 factorial arrangement under two levels of- dietary energy(TON:70/80%DM),protein(CP:11.9/14.3%DM)and sex(S:male/female) during the finishing phase of 146 d.The treatments were-(1) high energy/low protein(HELP),(2) high energy/high protein(HEHP),(3) low energy/low protein(LELP) and(4) low energy/high protein(LEHP).Each treatment used 6 steers and 6 heifers,except for HELP- 5 steers and 6 heifers.Results:Growth rate and final carcass weight were unaffected by dietary energy and protein levels or by sex.Compared with the LE diet group,the HE group had significantly lower dry matter intake(DMI,6.76 vs.7.48 kg DM/d),greater chest girth increments(46.1 vs.36.8 cm),higher carcass fat(19.9 vs.16.3%) and intramuscular fat content(29.9 vs.22.8%DM).The HE group also had improved yields of top and medium top grade commercial meat cuts(39.9 vs.36.5%).The dressing percentage was higher for the HP group than the LP group(53.4 vs.54.9%).Steers had a greater length increment(9.0 vs.8.3 cm),but lower carcass fat content(16.8 vs.19.4%) than heifers.The meat quality traits(shear force value,drip loss,cooking loss and water holding capacity) were not affected by treatments or sex,averaging 3.14 kg,2.5,31.5 and 52.9%,respectively.The nutritive profiles(both fatty and amino acid composition) were not influenced by the energy or protein levels or by sex.Conclusions:The dietary energy and protein levels and sex significantly influenced the carcass characteristics and chemical composition of meat but not thegrowth performance,meat quality traits and nutritive profiles.

Development of micro milling force model and cutting parameter optimization

Taking the minimum chip thickness effect,cutter deflection,and spindle run-out into account,a micro milling force model and a method to determine the optimal micro milling parameters were developed.The micro milling force model was derived as a function of the cutting coefficients and the instantaneous projected cutting area that was determined based on the machining parameters and the rotation trajectory of the cutter edges.When an allowable micro cutter deflection is defined,the maximum allowable cutting force can be determined.The optimal machining parameters can then be computed based on the cutting force model for better machining efficiency and accuracy.To verify the proposed cutting force model and the method to determine the optimal cutting parameters,micro-milling experiments were conducted,and the results show the feasibility and effectiveness of the model and method.

Relationship between vitamin D deficiency and cardiovascular disease

Epidemiological studies have found that low 25-hydroxyvitamin D levels may be associated with coronary risk factors and adverse cardiovascular outcomes.Additionally,vitamin D deficiency causes an increase in parathyroid hormone,which increases insulin resistance and is associated with diabetes,hypertension,inflammation,and increased cardiovascular risk.In this review,we analyze the association between vitamin D supplementation and the reduction in cardiovascular disease.The role of vitamin D deficiency in cardiovascular morbidity and mortality is still controversial,and larger scale,randomized placebo controlled trials are needed to investigate whether oral vitamin D supplementation can reduce cardiovascular risk.Given the low cost,safety,and demonstrated benefit of higher 25-hydroxyvitamin D levels,vitamin D supplementation should become a public health priority for combating common and costly chronic cardiovascular diseases.

Detection of Lactobacillus acidophilus in Fermented Material by Real-time Fluorescent Quantitative PCR

The species distinctive PCR primer of Lactobacillus acidophilus( L. acidophilus) was designed according to 16 S rRNA gene sequences of common Lactobacillus species in fermented material. Bacterial genome DNA of separated L. acidophilus in fermented sample was taken as template,and L. acidophilus in fermented material was conducted the quantitative determination by real-time quantitative PCR( RT-PCR). Analysis on RT-PCR results shown that contents of L. acidophilus in the test sample reached 1. 5 billion CFU / g. Test results shown that contents of L. acidophilus in fermented material could be detected accurately by the established RT-PCR method in the test,indicating that the established RT-PCR method could be applied to the detection of L. acidophilus in fermented material.

APPLICATION OF WAVELET TRANSFORM ON DIAGNOSIS AND PREDICTION OF MILLING CHATTER

In order to avoid the accuracy deterioration or tool damage caused by milling chatter, it is necessary to have an efficient and reliable diagnosis system that can on-line predict/detect the occur-rence of chatter. The diagnosis/predicting system proposed is to on-line process and analysis the vi-bration signals of the milling machine measured by accelerometers. According to the analysis results, the system will be able to detect/predict the occurrence of the chatter. The diagnosis algorithm is, first, collecting both the normal signals and chatter signals from milling processes, and then, converting the signals through wavelet transform and fast Fourier transform (FFT). Since the converted chatter sig-nals exhibit different characteristics from the normal signals, through defining the characteristic val-ues, such as root-mean-square value, max value, and ratio of peak value to root-mean-square value, etc, a diagnosis reference library that contains the distribution of these characteristic values is built for diagnosis. When a diagnosis is executing, the characteristic value of the measured signals is con-trasted with the diagnosis reference. The approach index which shows the possibility of occurrence of milling chatter will, then, be calculated through the diagnosis system. Cutting experiments are con-ducted to verify the proposed diagnosis system. The results show the success of early chatter detecting for the system.

Correlation between growth differentiation factor-15 and collagen metabolism indicators in patients with myocardial infarction and heart failure

BackgroundGrowth 区别因素(GDF )-15, 转变生长因素贝它总科的一个分叉的成员确实看起来响应试验性的压力超载和心失败(HF ) 的前进起来调整。HF 经常在心肌的梗塞(MI ) 以后发展，贡献更坏的结果。学习是在 HF.MethodsThe 学习的不同阶段估计在与骨胶原周转有关的 GDF-15 层次和标记之间的关联的这的目的由 179 个病人的一个队组成，包括稳定的心绞痛病人( AP 组， n = 50 )，没有 HF 的旧 MI 病人( OMI 组， n = 56 )，有 HF 的旧 MI 病人( OMI-HF 组， n = 38 )并且正常控制组( n = 35 )。包括 precollagen 反映骨胶原的合成和降级率的两指示物我N终端肽( PINP )，类型我骨胶原carboxy终端肽( ICTP )， precollagen III N终端肽( PIIINP )和 GDF-15 用连接酶的 inmunosorbent assay.ResultsThe 血浆 GDF-15 水平被测量在 OMI-HF 组是更高的( 1373.4 &#x000b1 ；275.4 ng/L ) 比 OMI 组(1036.1 &#x000b1；248.6 ng/L ) ， AP 组(784.6 &#x000b1；222.4 ng/L ) 并且控制组(483.8 &#x000b1；186.4 ng/L )(P &#x0003c；0.001 ) 。骨胶原周转的指示物(ICTP， PINP， PIIINP ) 与控制相比在 OMI-HF 组增加的所有组织(3.03 &#x000b1；1.02 &#x000b5； g/L 对 2.08 &#x000b1；0.95 &#x000b5； g/L， 22.2 &#x000b1；6.6 &#x000b5； g/L 对 16.7 &#x000b1；5.1 &#x000b5； g/L 和 13.2 &#x000b1；7.9 &#x000b5； g/L 对 6.4 &#x000b1；2.1 &#x000b5； g/L 分别地；P &#x0003c；0.01 ) 。GDF-15 断然与 ICTP 和 PIIINP 相关(r = 0.302， P &#x0003c；0.001 并且 r = 0.206， P = 0.006，分别地) 。GDF-15 断然相关到心脏舒张的指示物 E/Em 和左 atrial 迫使的 echocardiographic (r = 0.349 并且 r = 0.358 分别地；P &#x0003c；0.01 ) ，并且相反地相关到收缩指示物左室的喷射部分和山峰的一般水准收缩心肌的速度(Sm )(r =&#x02212； 0.623 并且 r =&#x02212； 0.365 分别地；P &#x0003c；0.01 ).ConclusionPlasma GDF-15 与类型的指示物被联系我和 III 骨胶原周转。

Si-Based Anode Materials for Li-Ion Batteries:A Mini Review

Si has been considered as one of the most attractive anode materials for Li-ion batteries(LIBs) because of its high gravimetric and volumetric capacity. Importantly, it is also abundant, cheap, and environmentally benign. In this review, we summarized the recent progress in developments of Si anode materials. First, the electrochemical reaction and failure are outlined, and then, we summarized various methods for improving the battery performance, including those of nanostructuring, alloying, forming hierarchic structures, and using suitable binders. We hope that this review can be of benefit to more intensive investigation of Si-based anode materials.