Long-term assessment of collagenase treatment for Dupuytren’s contracture:A 10-year follow-up study

BACKGROUND Enzymatic fasciotomy with collagenase clostridium histolyticum(CCH)has revolutionized the treatment for Dupuytren’s contracture(DC).Despite its benefits,the long-term outcomes remain unclear.This study presented a comprehensive 10-year follow-up assessment of the enduring effects of CCH on patients with DC.AIM To compare the short-term(12 wk)and long-term(10 years)outcomes on CCH treatment in patients with DC.METHODS A cohort of 45 patients was treated with CCH at the metacarpophalangeal(MCP)joint and the proximal interphalangeal(PIP)joint and underwent systematic reevaluation.The study adhered to multicenter trial protocols,and assessments were conducted at 12 wk,7 years,and 10 years post-surgery.RESULTS Thirty-seven patients completed the 10-year follow-up.At 10 years,patients treated at the PIP joint exhibited a 100%recurrence.However,patients treated at the MCP joint only showed a 50%recurrence.Patient satisfaction varied,with a lower satisfaction reported in PIP joint cases.Recurrence exceeding 20 degrees on the total passive extension deficit was observed,indicating a challenge for sustained efficacy.Significant differences were noted between outcomes at the 7-year and 10-year intervals.CONCLUSION CCH demonstrated sustained efficacy when applied to the MCP joint.However,caution is warranted for CCH treatment at the PIP joint due to a high level of recurrence and low patient satisfaction.Re-intervention is needed within a decade of treatment.

Long-term outcomes of endoscopic submucosal dissection for undifferentiated type early gastric cancer over 2 cm with R0 resection

BACKGROUND Endoscopic submucosal dissection(ESD)for over 2 cm in size undifferentiated type(UD type)early gastric cancer(EGC)confined to the mucosa is not only challenging,but also long-term outcomes are not well known.AIM To evaluate the long-term outcomes of ESD done for UD type EGCs confined to the mucosa over 2 cm in size and compare the results with those where the lesions were less than 2 cm.METHODS 143 patients with UD type EGC confirmed on histology after ESD at a tertiary hospital were reviewed.Cases with synchronous and metachronous lesions and a case with emergency surgery after ESD were excluded.A total of 137 cases were enrolled.79 cases who underwent R0 resection were divided into 2 cm or less(group A)and over 2 cm(group B)in size.RESULTS Among 79 patients who underwent R0 resection,the number in group A and B were 51 and 28,respectively.The mean follow-up period(SD)was 79.71±45.42 months.There was a local recurrence in group A(1/51,2%)and group B(1/28,3.6%)respectively.This patient in group A underwent surgery while the patient in group B underwent repeated ESD with no further recurrences in both patients.There was no regional lymph node metastasis,distant metastasis,and deaths in both groups.With R0 resection strategy for ESD on lesions over 2 cm,20.4%(28/137)of patients were able to avoid surgery compared with expanded indication.CONCLUSION If R0 resection is achieved by ESD,UD type EGCs over 2 cm also showed good and similar clinical outcomes as compared to lesions less than 2 cm when followed for over 5 years.With R0 resection strategy,several patients can avoid surgery.

Modeling injection-induced fault slip using long short-term memory networks

Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault.This can be due to subsurface(geo)engineering activities such as fluid injections and geologic disposal of nuclear waste.Such activities are expected to rise in the future making it necessary to assess their short-and long-term safety.Here,a new machine learning(ML)approach to model pore pressure and fault displacements in response to high-pressure fluid injection cycles is developed.The focus is on fault behavior near the injection borehole.To capture the temporal dependencies in the data,long short-term memory(LSTM)networks are utilized.To prevent error accumulation within the forecast window,four critical measures to train a robust LSTM model for predicting fault response are highlighted:(i)setting an appropriate value of LSTM lag,(ii)calibrating the LSTM cell dimension,(iii)learning rate reduction during weight optimization,and(iv)not adopting an independent injection cycle as a validation set.Several numerical experiments were conducted,which demonstrated that the ML model can capture peaks in pressure and associated fault displacement that accompany an increase in fluid injection.The model also captured the decay in pressure and displacement during the injection shut-in period.Further,the ability of an ML model to highlight key changes in fault hydromechanical activation processes was investigated,which shows that ML can be used to monitor risk of fault activation and leakage during high pressure fluid injections.

An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction

With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service quality.Traffic volume is an influential parameter for planning and operating traffic structures.This study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning process.The fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal relationships.Firstly,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition model.The second aspect involves predicting traffic volume using the long short-term memory algorithm.Next,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent optimization.Finally,the fusion of the obtained results leads to a final traffic volume prediction.The experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and R-squared.The achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the competing.These findings highlight the accuracy of traffic pattern prediction.Consequently,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.

State-of-health estimation for fast-charging lithium-ion batteries based on a short charge curve using graph convolutional and long short-term memory networks

A fast-charging policy is widely employed to alleviate the inconvenience caused by the extended charging time of electric vehicles. However, fast charging exacerbates battery degradation and shortens battery lifespan. In addition, there is still a lack of tailored health estimations for fast-charging batteries;most existing methods are applicable at lower charging rates. This paper proposes a novel method for estimating the health of lithium-ion batteries, which is tailored for multi-stage constant current-constant voltage fast-charging policies. Initially, short charging segments are extracted by monitoring current switches,followed by deriving voltage sequences using interpolation techniques. Subsequently, a graph generation layer is used to transform the voltage sequence into graphical data. Furthermore, the integration of a graph convolution network with a long short-term memory network enables the extraction of information related to inter-node message transmission, capturing the key local and temporal features during the battery degradation process. Finally, this method is confirmed by utilizing aging data from 185 cells and 81 distinct fast-charging policies. The 4-minute charging duration achieves a balance between high accuracy in estimating battery state of health and low data requirements, with mean absolute errors and root mean square errors of 0.34% and 0.66%, respectively.

Integrating Transformer and Bidirectional Long Short-Term Memory for Intelligent Breast Cancer Detection from Histopathology Biopsy Images

Breast cancer is a significant threat to the global population,affecting not only women but also a threat to the entire population.With recent advancements in digital pathology,Eosin and hematoxylin images provide enhanced clarity in examiningmicroscopic features of breast tissues based on their staining properties.Early cancer detection facilitates the quickening of the therapeutic process,thereby increasing survival rates.The analysis made by medical professionals,especially pathologists,is time-consuming and challenging,and there arises a need for automated breast cancer detection systems.The upcoming artificial intelligence platforms,especially deep learning models,play an important role in image diagnosis and prediction.Initially,the histopathology biopsy images are taken from standard data sources.Further,the gathered images are given as input to the Multi-Scale Dilated Vision Transformer,where the essential features are acquired.Subsequently,the features are subjected to the Bidirectional Long Short-Term Memory(Bi-LSTM)for classifying the breast cancer disorder.The efficacy of the model is evaluated using divergent metrics.When compared with other methods,the proposed work reveals that it offers impressive results for detection.

Long-Term Mortality of Children with Congenital Heart Disease Admitted to the Departmental University Hospital of Borgou/Alibori from 2011 to 2022

Background: Congenital heart disease is a public health issue due to its incidence and mortality rate. The aim of this study was to investigate the long-term mortality of children with congenital heart disease admitted to the Departmental University Hospital of Borgou/Alibori (CHUD-B/A) from 2011 to 2022. Methods: This descriptive longitudinal study with analytical aims covered 11 years (April 1, 2011 to December 31, 2022). It consisted of a review of the records of children under 15 years of age with echocardiographically confirmed congenital heart disease. This was followed by an interview with the parents to assess the children’s current condition. Data were entered using Kobocollect software and analyzed using R Studio 4.2.2. software. Results: A total of 143 complete files were retained. The median age at diagnosis was 14 months (IIQ: Q1 = 4;Q3 = 60) with a range of 2 days and 175 months, and the sex-ratio (M/F) was 0.96. Left-to-right shunts were the most frequent cardiopathy group (62.9%). Only 35 children (24.5%) benefited from restorative treatment. The mortality rate was 31.5%. Median survival under the maximum bias assumption was 114 months and 216 months under the assumption of minimum bias. Survival was significantly better in children with right-to-left shunts (p = 0.0049) under the assumption of minimum bias. The death risk factors were: age at diagnosis less than 12 months (aHR = 7.58;95% CI = 3.36 - 17.24;p Conclusion: The long-term mortality of congenital heart disease is high and favoured by the absence of restorative treatment. Local correction of congenital heart disease and medical follow-up will help to reduce this mortality.

A Prospective Study on Evaluating the Long-Term Effects of Childhood Vaccination from Birth to 13 Years Old in Kuwait

Background: To prevent infectious diseases and deaths of children, vaccinations play a crucial role in public health strategies in Kuwait. However, it remained uncertain to demonstrate the potential long-term health outcomes of vaccination, including neurodevelopmental disorders (NDD) and autism. This study aimed to evaluate the long-term health outcomes of vaccination among Kuwait children from birth to thirteen years old. Objectives: This study included the significant objectives: (1) to compare long-term health effects, including chronic and acute conditions for unvaccinated, partially vaccinated, and vaccinated children, and (2) to evaluate the association of vaccination with the neurodevelopmental disorders (NDD) and autism, and the preventable illnesses. Methods: This prospective study involved a sample of 976 children from Kuwait based on mothers’ reporting. Data collection about the vaccination status of children and various health outcomes relevant to chronic and acute illnesses was performed based on structured questionnaires through an online survey. However, participants were classified into unvaccinated (n = 40), partially vaccinated (n = 222), and fully vaccinated (n = 714). Statistical analyses, including the chi-square test, Odds Ratios (OR), 95% Confidence Interval (CI), and logistic regression, were performed using SAS (Version 9.4) to determine the associations between vaccination status and health outcomes among children. Results: The study disclosed that vaccinated children showed an increased diagnosis of chronic (allergic rhinitis, allergies, autism spectrum, eczema, neuro-developmental disorders, learning disability, ADHD, and any chronic condition) and acute (whooping cough, pneumonia, rubella, hepatitis A or B, measles, mumps, meningitis, influenza, rotavirus, cancer, chronic fatigue, Crohn’s disease, inflammatory bowel disease, conduct disorder, diabetes type 1 or 2, rheumatoid arthritis, obesity, seizures, hearing loss, polio, diphtheria, tetanus, and depression) illnesses than unvaccinated children. The fully vaccinated children showed an increased prevalence of influenza diagnosis, while partially vaccinated children were more likely to be diagnosed with rheumatoid arthritis than unvaccinated children. In contrast, unvaccinated were more likely to have been diagnosed with chickenpox and encephalopathy than fully and partially vaccinated. Males with chronic and acute conditions had a lower incidence of allergies and pneumonia, respectively, whereas females had a reduced prevalence of acute illnesses, such as whooping cough, inflammatory bowel disease, and hepatitis A or B among vaccinated (n = 936;combination of partially vaccinated and fully vaccinated) children. Regarding medication use and health service applications, vaccinated children were more likely to use medications for fever, antibiotics, and allergies. In addition, they showed an increased rate of sick visits and emergency visits in the past twelve months. On the other hand, factors like age (2 - 5 years, 6 - 9 years, and 10 - 13 years), birth type (cesarian), and mother suffering during pregnancy (gestational diabetes) were significantly associated with NDD (learning disability, autism spectrum, and attention deficient hyperactivity disorder) in the adjusted analysis. In the interaction model of age and birth type, age (6 - 9 years;OR 5.3, 95% CI: 1.1, 25.3) and mother suffering (gestational diabetes;OR 2.5, 95% CI: 1.2, 5.2) during pregnancy were associated with NDD. Conclusion: The findings of this study showed that there are some cases where the infection rate is higher among the vaccinated compared to unvaccinated children, or there are no significant differences between the two groups in Kuwait. Upon controlling the factors in the interaction model, the age of 6 to 9 years and gestational diabetic mothers during pregnancy were associated with the synergistic increment of odds with NDD. These data findings are recommended to verify a larger and diverse group of samples to optimize the vaccination on health outcomes in Kuwait children.

A Trajectory Privacy Protection Method to Resist Long-Term Observation Attacks

Users face the threat of trajectory privacy leakage when using location-based service applications, especially when their behavior is collected and stored for a long period of time. This accumulated information is exploited by opponents, greatly increasing the risk of trajectory privacy leakage. This attack method is called a long-term observation attack. On the premise of ensuring lower time overhead and higher cache contribution rate, the existing methods cannot utilize cache to answer subsequent queries while also resisting long-term observation attacks. So this article proposes a trajectory privacy protection method to resist long-term observation attacks. This method combines caching technology and improves the existing differential privacy mechanism, while incorporating randomization factors that are difficult for attackers to recognize after long-term observation to enhance privacy. Search for locations in the cache of both the mobile client and edge server that can replace the user’s actual location. If there are replacement users in the cache, the query results can be obtained more quickly. Simultaneously obfuscating the spatiotemporal correlation of actual trajectories by generating confusion regions. If it does not exist, the obfuscated location generation method that resists long-term observation attacks is executed to generate the real anonymous area and send it to the service provider. The above steps can comprehensively protect the user’s trajectory privacy. The experimental results show that this method can protect user trajectories from long-term observation attacks while ensuring low time overhead and a high cache contribution rate.

Photoelectric State with Long-Term Relaxation in CdTe:(Ag, Cu, Cd) and Sb2Se3:Se Photovoltaic Films

The results of an experimental study of long-term relaxation of the photoelectret state of polycrystalline CdTe:(Ag, Cu, Cd) and Sb2Se3:Se films with an anomalous photovoltaic property are presented. In such films, the residual photovoltage is caused by the separation of photocarriers by the built-in electrostatic field of the near-surface region of space charges and their asymmetric capture by deep levels of impurities or complexes, including impurity atoms and intrinsic defects, both in the bulk and on the surface of crystal grains. It has been shown that in activated films, a two-step exponential temporary relaxation of the initial photovoltage of the order of VAPV ≈ (500-600) V is detected, and only 10% of it experiences long-term relaxation (t ≈ 100-120 min).

“Long-term care”概念辨析

Long-term care（LTC）在国外最早是以救济贫穷个人或家庭为目标。随着人口结构、家庭结构以及社会结构的变化,要求医疗护理模式作出相应的调整,也使LTC的存在有了更充分的理由,因此LTC是社会发展到一定时期的必然产物。迄今为止,我国学术界对＂long-term care＂的中文翻译问题依然没有统一的看法。因此,很有必要就此展开深入研究和讨论。笔者将全面辨析和讨论“long-termcare”概念，并在此基础上探讨“long-termcare”的中文翻译问题，从而进一步廓清“long-termcare”的涵义。

一种基于long short-term memory的唇语识别方法

唇动视觉信息是说话内容的重要载体。受嘴唇外观、背景信息和说话习惯等影响,即使说话者说相同的内容,唇动视觉信息也会相差很大。为解决唇语视觉信息多样性的问题,提出一种基于long short-term memory(LSTM)的新的唇语识别方法。以往大多数的方法从嘴唇外表信息入手。本方法用嘴唇关键点坐标描述嘴唇形变信息作为唇语视频的特征,它具有类内一致性和类间区分性的特点。然后利用LSTM对特征进行时序编码,它能学习具有区分性和泛化性的空间-时序特征。在公开的唇语数据集GRID、MIRACL-VC和Oulu VS上对本方法做了针对分割的单词或短语的说话者独立的唇语识别评估。在GRID和MIRACL-VC上,本方法的准确率比传统方法至少高30%;在Oulu VS上,本方法的准确率接近于最优结果。以上实验结果表明,本文提出的基于LSTM的唇语识别方法有效地解决了唇语视觉信息多样性的问题。

Mid-long Term Optimal Dispatching Method of Hydro-thermal Power System Considering Scheduled Maintenance

在中长期水火发电调度中考虑检修计划的影响是目前中长期水火发电调度面临的难题。利用现代整数代数建模技术，建立发电计划和检修计划协调优化的多场景调度模型。在该模型中，鉴于设备检修计划的连续性，在预测场景树的基础上，将场景节点划分成不同的场景，通过节点和场景关联矩阵，实现多场景下设备检修模型的构建。同时，鉴于中长期调度计划中发电计划和检修计划对时段间隔要求的不同，分别设置电量相关节点和电力相关节点，实现中长期发电计划和检修计划的协调。上述模型是一个大规模混合整数线性规划（mixed integer linear programming，MILP）问题，采用商用MILP求解器进行求解。大规模实际水火电系统的实例分析结果表明，所提模型和方法是可行、有效的。

Carbon Sequestration in Soil Humic Substances Under Long-Term Fertilization in a Wheat-Maize System from North China

The changes in humic substances （HS） is fundamental in detecting soil carbon sequestration mechanisms in natural and cultivated environments. Based on a long-term trial, the amounts of water dissolved substances （WSS）, humic acid （HA）, fulvic acid （FA） and humin （HU） were determined to explore the impact of long-term fertilization on HS. Increases in the amounts of WSS, HA, FA and HU were significant different among the treatments with manure. A significant correlation was found between the increased soil organic carbon （SOC） and HS （R^2=0.98, P〈0.01）. The change in the E4/E6 ratio was significantly correlated with the increased SOC （R2=0.88, P〈0.01）, HA （R^2=0.91, P〈0.01）, FA （R^2=0.91, P〈0.01） and HU （R^2=0.88, P〈0.01）. The cluster was mainly divided into two parts as manure fertilization and inorganic fertilization, based on the increases in HA, FA and HU. These results suggest that long term fertilization with manure favours carbon sequestration in HS and is mainly stabilized as HU, while the HA becomes more aliphatic. We conclude that increases in SOC can be linked to changes in the molecular characteristics of HS fractions under long term fertilization.

Long-term effects of early antibiotic intervention on blood parameters,apparent nutrient digestibility, and fecal microbial fermentation profile in pigs with different dietary protein levels

Backgroud： This study aimed to determine the effects of early antibiotic intervention（EAI） on subsequent blood parameters, apparent nutrient digestibility, and fecal fermentation profile in pigs with different dietary crude protein（CP） levels. Eighteen litters of piglets（total 212） were randomly allocated to 2 groups and were fed a creep feed diet with or without in-feed antibiotics（olaquindox, oxytetracycline calcium and kitasamycin） from postnatal d 7 to d 42. On d 42, the piglets within the control or antibiotic group were mixed, respectively, and then further randomly assigned to a normal-（20%, 18%, and 14% CP from d 42 to d 77, d 77 to d 120, and d 120 to d 185,respectively） or a low-CP diet（16%, 14%, and 10% CP from d 42 to d 77, d 77 to d 120, and d 120 to d 185,respectively）, generating 4 groups. On d 77（short-term） and d 185（long-term）, serum and fecal samples were obtained for blood parameters, microbial composition and microbial metabolism analysis.Results： EAI increased（P 〈 0.05） albumin and glucose concentrations in low-CP diet on d 77, and increased（P 〈 0.05） urea concentration in normal-CP diet. On d 185, EAI increased（P 〈 0.05） globulin concentration in normal-CP diets, but decreased glucose concentration. For nutrient digestibility, EAI increased（P 〈 0.05）digestibility of CP on d 77. For fecal microbiota, the EAI as well as low-CP diet decreased（P 〈 0.05） E. coli count on d 77. For fecal metabolites, on d 77, EAI decreased（P 〈 0.05） total amines concentration but increased skatole concentration in low-CP diet. On d 185, the EAI increased（P 〈 0.05） putrescine and total amines concentrations in low-CP diets but reduced（P 〈 0.05） in the normal-CP diets. The low-CP diet decreased the concentrations of these compounds.Conclusions： Collectively, these results indicate that EAI has short-term effects on the blood parameters and fecal microbial fermentation profile. The effects of EAI varied between CP levels, which was characterized by the significant alteration of glucose and putrescine concentration.

Long-term survival after liver transplantation for alcoholic liver disease

Currently,alcoholic cirrhosis is the second leading indication for liver transplantation in the United States and Europe.The quality of life and survival after a liver transplantation(LT)in patients with alcoholic liver disease(ALD)are similar to those in patients with other cirrhosis etiologies.The alcoholic relapse rate after a LT varies from 10%-50%,and these relapse patients are the ones who present a reduced long-term survival,mainly due to cardiovascular diseases and the onset of de novo neoplasms,including lung and upper aerodigestive tract.Nearly 40%of ALD recipients resume smoking and resume it early post-LT.Therefore,our pre-and post-LT follow-up efforts regarding ALD should be focused not only on alcoholic relapse but also on treating and avoiding other modifiable risk factors such as tobacco.The psychiatric and psychosocial pre-LT evaluation and the post-LT follow-up with physicians,psychiatrists and addiction specialists are important for reversing these problems because these professionals help to identify patients at risk for relapse as well as those patients who have relapsed,thus enabling responsive actions.

Long Short-Term Memory Recurrent Neural Network-Based Acoustic Model Using Connectionist Temporal Classification on a Large-Scale Training Corpus

A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.

Evolution of interfacial dislocation networks during long term thermal aging in Ni-based single crystal superalloy DD5

Interfacial dislocations found in single crystal superalloys after long term thermal aging have an important effect on mechanical properties. Long term thermal aging tests for DD5 single crystal superalloy were carried out at 1,100 ℃ for 20, 100, 200, 500 and 1000 h, and then cooled by air. The effect of long term thermal aging on the dislocation networks at the γ/γ' interfaces was investigated by FE-SEM. Results showed that during the long term thermal aging at 1,100 ℃, misfit dislocations formed firstly and then reorientation in the(001) interfacial planes occurred. Different types of square or rectangular dislocation network form by dislocation reaction. Square dislocation networks consisting of four groups of dislocations can transform into octagonal dislocation networks, and then form another square dislocation network by dislocation reaction. Rectangular dislocation networks can also transform into hexagonal dislocation networks. The interfacial dislocation networks promote the γ' phase rafting process. The dislocation networks spacings become smaller and smaller, leading to the effective lattice misfit increasing from-0.10% to-0.32%.

Carbon sequestration rate,nitrogen use efficiency and rice yield responses to long-term substitution of chemical fertilizer by organic manure in a rice–rice cropping system

Combined application of chemical fertilizers with organic amendments was recommended as a strategy for improving yield,soil carbon storage,and nutrient use efficiency.However,how the long-term substitution of chemical fertilizer with organic manure affects rice yield,carbon sequestration rate(CSR),and nitrogen use efficiency(NUE)while ensuring environmental safety remains unclear.This study assessed the long-term effect of substituting chemical fertilizer with organic manure on rice yield,CSR,and NUE.It also determined the optimum substitution ratio in the acidic soil of southern China.The treatments were:(i)NPK0,unfertilized control;(ii)NPK1,100%chemical nitrogen,phosphorus,and potassium fertilizer;(iii)NPKM1,70%chemical NPK fertilizer and 30%organic manure;(iv)NPKM2,50%chemical NPK fertilizer and 50%organic manure;and(v)NPKM3,30%chemical NPK fertilizer and 70%organic manure.Milk vetch and pig manure were sources of manure for early and late rice seasons,respectively.The result showed that SOC content was higher in NPKM1,NPKM2,and NPKM3 treatments than in NPK0 and NPK1 treatments.The carbon sequestration rate increased by 140,160,and 280%under NPKM1,NPKM2,and NPKM3 treatments,respectively,compared to NPK1 treatment.Grain yield was 86.1,93.1,93.6,and 96.5%higher under NPK1,NPKM1,NPKM2,and NPKM3 treatments,respectively,compared to NPK0 treatment.The NUE in NPKM1,NPKM2,and NPKM3 treatments was higher as compared to NPK1 treatment for both rice seasons.Redundancy analysis revealed close positive relationships of CSR with C input,total N,soil C:N ratio,catalase,and humic acids,whereas NUE was closely related to grain yield,grain N content,and phenol oxidase.Furthermore,CSR and NUE negatively correlated with humin acid and soil C:P and N:P ratios.The technique for order of preference by similarity to ideal solution(TOPSIS)showed that NPKM3 treatment was the optimum strategy for improving CSR and NUE.Therefore,substituting 70%of chemical fertilizer with organic manure could be the best management option for increasing CSR and NUE in the paddy fields of southern China.

Tool Health Condition Recognition Method for High Speed Milling of Titanium Alloy Based on Principal Component Analysis (PCA) and Long Short Term Memory (LSTM)

The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cutter at the right time.In order to recognize the health condition of the milling cutter,a method based on the long short term memory(LSTM)was proposed to recognize tool health state in this paper.The various signals collected in the tool wear experiments were analyzed by time-domain statistics,and then the extracted data were generated by principal component analysis(PCA)method.The preprocessed data extracted by PCA is transmitted to the LSTM model for recognition.Compared with back propagation neural network(BPNN)and support vector machine(SVM),the proposed method can effectively utilize the time-domain regulation in the data to achieve higher recognition speed and accuracy.