A method for establishing a bearing residual life prediction model for process enhancement equipment based on rotor imbalance response analysis

A rotating packed bed is a typical chemical process enhancement equipment that can strengthen micromixing and mass transfer.During the operation of the rotating packed bed,the nonreactants and products irregularly adhere to the wire mesh packing in the rotor,thus resulting in an imbalance in the vibration of the rotor,which may cause serious damage to the bearing and material leakage.This study proposes a model prediction for estimating the bearing residual life of a rotating packed bed based on rotor imbalance response analysis.This method is used to determine the influence of the mass on the imbalance in the vibration of the rotor on bearing damage.The major influence on rotor vibration was found to be exerted by the imbalanced mass and its distribution radius,as revealed by the results of orthogonal experiments.Through implementing finite element analysis,the imbalance response curve for the rotating packed bed rotor was obtained,and a correlation among rotor imbalance mass,distribution radius of imbalance mass,and bearing residue life was established via data fitting.The predicted value of the bearing life can be used as the reference basis for an early safety warning of a rotating packed bed to effectively avoid accidents.

IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,etc.In terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic.It is challenging to identify a specific attack due to complex features and data imbalance issues.To address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced data.First,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,etc.Second,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic anchors.Third,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority attacks.Fourth,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network traffic.Finally,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep features.Detailed experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and NSL-KDD.An explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

Photobiomodulation provides neuroprotection through regulating mitochondrial fission imbalance in the subacute phase of spinal cord injury

Increasing evidence indicates that mitochonarial lission imbalance plays an important role in derayed neuronal cell death. Our previous study round that photo biomodulation improved the motor function of rats with spinal cord injury.However,the precise mechanism remains unclear.To investigate the effect of photo biomodulation on mitochondrial fission imbalance after spinal cord injury,in this study,we treated rat models of spinal co rd injury with 60-minute photo biomodulation(810 nm,150 mW) every day for 14 consecutive days.Transmission electron microscopy results confirmed the swollen and fragmented alte rations of mitochondrial morphology in neurons in acute(1 day) and subacute(7 and 14 days) phases.Photo biomodulation alleviated mitochondrial fission imbalance in spinal cord tissue in the subacute phase,reduced neuronal cell death,and improved rat posterior limb motor function in a time-dependent manner.These findings suggest that photobiomodulation targets neuronal mitochondria,alleviates mitochondrial fission imbalance-induced neuronal apoptosis,and thereby promotes the motor function recovery of rats with spinal cord injury.

Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more complex.The existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s performance.We analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream classification.Precision, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority classes.The study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

Pharmacological effects of denervated muscle atrophy due to metabolic imbalance in different periods

Denervation-induced skeletal muscle atrophy can potentially cause the decline in the quality of life of patients and an increased risk of mortality.Complex pathophysiological mechanisms with dynamic alterations have been documented in skeletal muscle atrophy resulting from innervation loss.Hence,an in-depth comprehension of the key mechanisms and molecules governing skeletal muscle atrophy at varying stages,along with targeted treatment and protection,becomes essential for effective atrophy management.Our preliminary research categorizes the skeletal muscle atrophy process into four stages using microarray analysis.This review extensively discusses the pathways and molecules potentially implicated in regulating the four stages of denervation and muscle atrophy.Notably,drugs targeting the reactivare oxygen species stage and the inflammation stage assume critical roles.Timely intervention during the initial atrophy stages can expedite protection against skeletal muscle atrophy.Additionally,pharmaceutical intervention in the ubiquitin-proteasome pathway associated with atrophy and autophagy lysosomes can effectively slow down skeletal muscle atrophy.Key molecules within this stage encompass MuRF1,MAFbx,LC3II,p62/SQSTM1,etc.This review also compiles a profile of drugs with protective effects against skeletal muscle atrophy at distinct postdenervation stages,thereby augmenting the evidence base for denervation-induced skeletal muscle atrophy treatment.

Attenuate Class Imbalance Problem for Pneumonia Diagnosis Using Ensemble Parallel Stacked Pre-Trained Models

Pneumonia is an acute lung infection that has caused many fatalitiesglobally. Radiologists often employ chest X-rays to identify pneumoniasince they are presently the most effective imaging method for this purpose.Computer-aided diagnosis of pneumonia using deep learning techniques iswidely used due to its effectiveness and performance. In the proposed method,the Synthetic Minority Oversampling Technique (SMOTE) approach is usedto eliminate the class imbalance in the X-ray dataset. To compensate forthe paucity of accessible data, pre-trained transfer learning is used, and anensemble Convolutional Neural Network (CNN) model is developed. Theensemble model consists of all possible combinations of the MobileNetv2,Visual Geometry Group (VGG16), and DenseNet169 models. MobileNetV2and DenseNet169 performed well in the Single classifier model, with anaccuracy of 94%, while the ensemble model (MobileNetV2+DenseNet169)achieved an accuracy of 96.9%. Using the data synchronous parallel modelin Distributed Tensorflow, the training process accelerated performance by98.6% and outperformed other conventional approaches.

Correlation between cognitive impairment and metabolic imbalance of gut microbiota in patients with schizophrenia

BACKGROUND The gut microbiome interacts with the central nervous system through the gutbrain axis,and this interaction involves neuronal,endocrine,and immune mechanisms,among others,which allow the microbiota to influence and respond to a variety of behavioral and mental conditions.AIM To explore the correlation between cognitive impairment and gut microbiota imbalance in patients with schizophrenia.METHODS A total of 498 untreated patients with schizophrenia admitted to our hospital from July 2020 to July 2022 were selected as the case group,while 498 healthy volunteers who underwent physical examinations at our hospital during the same period were selected as a control group.Fluorescence in situ hybridization was employed to determine the total number of bacteria in the feces of the two groups.The cognitive function test package was used to assess the score of cognitive function in each dimension.Then,the relationship between gut microbiota and cognitive function was analyzed.RESULTS There were statistically significant differences in the relative abundance of gut microbiota at both phylum and class levels between the case group and the control group.In addition,the scores of cognitive function,such as attention/alertness and learning ability,were significantly lower in the case group than in the control group(all P<0.05).The cognitive function was positively correlated with Actinomycetota,Bacteroidota,Euryarchaeota,Fusobacteria,Pseudomonadota,and Saccharibacteria,while negatively correlated with Bacillota,Tenericutes,and Verrucomicrobia at the phylum level.While at the class level,the cognitive function was positively correlated with Class Actinobacteria,Bacteroidia,Betaproteobacteria,Proteobacteria,Blastomycetes,and Gammaproteobacteria,while negatively correlated with Bacilli,Clostridia,Coriobacteriia,and Verrucomicrobiae.CONCLUSION There is a relationship between the metabolic results of gut microbiota and cognitive function in patients with schizophrenia.When imbalances occur in the gut microbiota of patients,it leads to more severe cognitive impairment.

Co-effect of Demand-control-support Model and Effort-reward Imbalance Model on Depression Risk Estimation in Humans: Findings from Henan Province of China

Objective To investigate the co-effect of Demand-control-support （DCS） model and Effort-reward Imbalance （ERI） model on the risk estimation of depression in humans in comparison with the effects when they are used respectively. Methods A total of 3 632 males and 1 706 females from 13 factories and companies in Henan province were recruited in this cross-sectional study. Perceived job stress was evaluated with the Job Content Questionnaire and Effort-Reward Imbalance Questionnaire （Chinese version）. Depressive symptoms were assessed by using the Center for Epidemiological Studies Depression Scale （CES-D）. Results DC （demands/job control ratio） and ERI were shown to be independently associated with depressive symptoms. The outcome of low social support and overcommitment were similar. High DC and low social support （SS）, high ERI and high overcommitment, and high DC and high ERI posed greater risks of depressive symptoms than each of them did alone. ERI model and SS model seem to be effective in estimating the risk of depressive symptoms if they are used respectively. Conclusion The DC had better performance when it was used in combination with low SS. The effect on physical demands was better than on psychological demands. The combination of DCS and ERI models could improve the risk estimate of depressive symptoms in humans.

Endocrine milieu and erectile dysfunction： is oestradio-testosterone imbalance, a risk factor in the elderly？

Oestrogens are not exclusive to the female gender but occur in moderate circulating levels of 25-70 pg ml^-1 in men, compared to 44- 153 pg ml^-1 in women. Arising from aromatisation of testosterone （T）, oestrogen is considered to have many opposing physiological functions and the progressive T decline in the aging male is associated with relative and/or absolute increase in serum oestradiol （E2）. Sexual disinterest and erectile dysfunction （ED） in the elderly may well be due to pathophysiological E2-T imbalance; the altered hormonal ratio may also explain the higher incidence of ED in hyperestrogenism or following exposure to environmental/plant oestrogens.

China’s financial conundrum and global imbalances

China’s financial conundrum arises from two sources: (1) its large trade (saving) surplus results in a currency mismatch because it is an immature creditor that cannot lend in its own currency. Instead foreign currency claims (largely dollars) build up within domestic financial institutions. And (2) economists – both American and Chinese – mistakenly attribute the surpluses to an undervalued renminbi. To placate the United States, the result is a gradual appreciation of the renminbi against the dollar of 6% or more per year. This predictable appreciation since 2004, and the fall in US interest rates since mid 2007, not only attracts hot money inflows but inhibits private capital outflows from financing China’s huge trade surplus. This one-way bet in the foreign exchange markets can no longer be offset by relatively low interest rates in China compared to the United States, as had been the case in 2005-06. Thus, the People’s Bank of China (PBOC) now must intervene heavily to prevent the renminbi from ratcheting upwards – and so becomes the country’s sole international financial intermediary. Despite massive efforts by the PBOC to sterilize the monetary consequences of the reserve buildup, inflation in China is increasing, with excess liquidity that spills over into the world economy. China has been transformed from a deflationary force on American and European price levels into an inflationary one. Because of the currency mismatch, floating the RMB is neither feasible nor desirable – and a higher RMB would not reduce China’s trade surplus. Instead, monetary control and normal private-sector finance for the trade surplus require a return to a credibly fixed nominal yuan/dollar rate similar to that which existed between 1995 and 2004. But for any newly reset yuan/dollar rate to be credible as a monetary anchor, foreign "China bashing" to get the RMB up must end. Currency stabilization would allow the PBOC to regain monetary control and quash inflation. Only then can the Chinese government take decisive steps to reduce the trade (saving) surplus by tax cuts, increased social expenditures, and higher dividend payouts. But as long as the economy remains overheated, the government hesitates to take these trade-surplus-reduction measures because of their near-term inflationary consequences.

Redox imbalance stress in diabetes mellitus: Role of the polyol pathway

In diabetes mellitus, the polyol pathway is highly active and consumes approximately 30% glucose in the body. This pathway contains 2 reactions catalyzed by aldose reductase(AR) and sorbitol dehydrogenase, respectively. AR reduces glucose to sorbitol at the expense of NADPH, while sorbitol dehydrogenase converts sorbitol to fructose at the expense of NAD+, leading to NADH production. Consumption of NADPH, accumulation of sorbitol, and generation of fructose and NADH have all been implicated in the pathogenesis of diabetes and its complications. In this review, the roles of this pathway in NADH/NAD+redox imbalance stress and oxidative stress in diabetes are highlighted. A potential intervention using nicotinamide riboside to restore redox balance as an approach to fighting diabetes is also discussed.

High-performance compensation scheme for frequency-dependent IQ imbalances in OFDM transmitter and receiver

An efficient compensation scheme combining a timedomain Gaussian elimination（GE） channel estimator and a frequency-domain GE equalizer is proposed for orthogonal frequency division multiplexing（OFDM） systems with frequencydependent in-phase and quadrature-phase（IQ） imbalances at both transmitter and receiver.Compared with the traditional least square and least mean square compensation schemes,the proposed compensation scheme achieves the same bit error rate as the ideal IQ branches by using only two training OFDM symbols instead of about 20 OFDM symbols.

General characteristics of patients with electrolyte imbalance admitted to emergency department

BACKGROUND:Fluid and electrolyte balance is a key concept to understand for maintaining homeostasis,and for a successful treatment of many metabolic disorders.There are various regulating mechanisms for the equilibrium of electrolytes in organisms.Disorders of these mechanisms result in electrolyte imbalances that may be life-threatening clinical conditions.In this study we defined the electrolyte imbalance characteristics of patients admitted to our emergency department.METHODS:This study was conducted in the Emergency Department(ED) of Uludag University Faculty of Medicine,and included 996 patients over 18 years of age.All patients had electrolyte imbalance,with various etiologies other than traumatic origin.Demographic and clinical parameters were collected after obtaining informed consent from the patients.The ethical committee of the university approved this study.RESULTS:The mean age of the patients was 59.28±16.79,and 55%of the patients were male.The common symptoms of the patients were dyspnea(14.7%),fever(13.7%),and systemic deterioration(11.9%);but the most and least frequent electrolyte imbalances were hyponatremia and hypermagnesemia,respectively.Most frequent findings in physical examination were confusion(14%),edema(10%) and rales(9%);and most frequent pathological findings in ECG were tachycardia in24%,and atrial fibrillation in 7%of the patients.Most frequent comorbidity was malignancy(39%).Most frequent diagnoses in the patients were sepsis(11%),pneumonia(9%),and acute renal failure(7%).CONCLUSIONS:Electrolyte imbalances are of particular importance in the treatment of ED patients.Therefore,ED physicians must be acknowledged of their fluid-electrolyte balance dynamics and general characteristics.

Spinal pedicle subtraction osteotomy for fixed sagittal imbalance patients

In addressing spinal sagittal imbalance through a posterior approach, the surgeon now may choose from among a variety of osteotomy techniques. Posterior column osteotomies such as the facetectomy or Ponte or Smith-Petersen osteotomy provide the least correction, but can be used at multiple levels with minimal blood loss and a lower operative risk. Pedicle subtraction osteotomies provide nearly 3 times the per-level correction of Ponte/Smith-Petersen osteotomies; however, they carry increased technical demands, longer operative time, and greater blood loss and associated significant morbidity, including neurological injury. The literature focusing on pedicle subtraction osteotomy for fixed sagittal imbalance patients is reviewed. The longterm overall outcomes, surgical tips to reduce the complications and suggestions for their proper application are also provided.

Th17/Treg Imbalance in Malignant Pleural Effusion

Both T helper IL-17-producing cells （Thl7 cells） and regulatory T cells （Tregs） have been found to be increased in malignant pleural effusion （MPE）. However, the possible imbalance between Thl7 cells and Tregs, as well as the association of.Thl7/Treg and Thl/Th2 cells in MPE remains to be elucidated. The objective of the present study was to investigate the distribution of Th 17 cells in relation to Tregs, as well as Thl/Th2 balance in MPE. The number ofThl7, Tregs, Thl, and Th2 cells in MPE and peripheral blood was determined by using flow cytometry. The relationship among the number of Thl7, Tregs, Thl, and Th2 cells was explored. It was found that the number of Thl7, Tregs, Thl, and Th2 cells was all increased in MPE as compared with the corresponding peripheral blood. The number of Thl7 cells was correlated negatively with Tregs in MPE, but not in blood. Thl7 cells and Thl7/Treg ratio were positively, and Tregs were negatively, correlated with Thl cells, but not with either Th2 cells or Th1/Th2 ratio in MPE. This study supports earlier data that both Thl7 cells and Treg are present at higher frequencies in MPE than in the autologous blood. For the first time, we show that Thl7/Treg imbalance exists in MPE.

Ensemble-based active learning for class imbalance problem

In medical diagnosis, the problem of class imbalance is popular. Though there are abundant unlabeled data, it is very difficult and expensive to get labeled ones. In this paper, an ensemble-based active learning algorithm is proposed to address the class imbalance problem. The artificial data are created according to the distribution of the training dataset to make the ensemble diverse, and the random subspace re-sampling method is used to reduce the data dimension. In selecting member classifiers based on misclassification cost estimation, the minority class is assigned with higher weights for misclassification costs, while each testing sample has a variable penalty factor to induce the ensemble to correct current error. In our experiments with UCI disease datasets, instead of classification accuracy, F-value and G-means are used as the evaluation rule. Compared with other ensemble methods, our method shows best performance, and needs less labeled samples.

An Analysis of Public Service Structural Imbalances in Rural China

Rectifying the structural imbalance between the provision of and demand for rural public services can effectively boost the efficiency of public funds utilization and the level of public service provision. Based on the findings of a field survey, this article presents a summary of the structural imbalance between the provision of and demand for rural public services. This paper holds that the structural imbalance is primarily reflected in the dislocation between provision and demand, the unsuitable mode of provision, the monolithic provision mechanism, the excessive focus on construction at the expense of governance and the overemphasis of counties and townships at the cost of villages. Such structural imbalance is principally because of the limited financial strength of government at the grass-roots level due to treasury centralization and the over-dependence of public services on special funds allocated by government at or above provincial level.

Primary logistics planning of oil products under the imbalance of supply and demand

This paper intends to complete the primary logistics planning of oil products under the imbalance of supply and demand. An integrated mathematical programming model is developed to simultaneously find the balance between supply and demand, and optimize the logistics scheme. The model takes minimum logistics cost and resource adjustment cost as the objective function, and takes supply and demand capacity, transportation capacity, mass balance, and resource adjustment rules as constraints.Three adjustment rules are considered in the model, including resource adjustment within oil suppliers,within oil consumers, and between oil consumers. The model is tested on a large-scale primary logistics of a state-owned petroleum enterprise, involving 37 affiliated refineries, 31 procurement departments,286 market depots and dedicated consumers. After the unified optimization, the supply and demand imbalance is eased by 97% and the total cost is saved by 7%, which proves the effectiveness and applicability of the proposed model.

Intervention of the Mahuang Lianqiao Chixiaodou decoction on immune imbalance in atopic dermatitis-like model mice

Objective:To explore the potential mechanism of intervention on the immune imbalance of atopic dermatitis(AD) by studying the effects of Mahuang Lianqiao Chixiaodou decoction(MLCD) on skin damage and inflammation factors in an AD-like mouse model.Methods:Ninety-six male BALB/c mice were divided into normal,model,positive control(mometasone furoate),and traditional Chinese medicine treatment(MLCD) groups by a random number table.2,4-dinitrofluorobenzene was used to induce AD-like mice in all groups except the normal group.The treatment or intervention was administered for seven consecutive days on days 4,18,32,and 39.The mRNA relative expressions of interleukin-4(IL-4),IL-10,interferon-γ(IFN-γ),thymic stromal lymphopoietin(TSLP),and the TSLP receptor(TSLPR) were measured using quantitative real-time polymerase chain reaction,and the serum immunoglobulin E,IL-4,IL-10,and IFN-γ levels were detected using enzyme-linked immunosorbent assay.Results:Compared with the normal group,the hematoxylin-eosin staining of the skin lesions of the mice in the model group was significantly thickened on days 11,25,and 39.Compared with the model group,the epidermal thickness of the positive control group was significantly alleviated on day 39(P <.001),and that of the MLCD group was significantly improved on days 25 and 39(P <.001).Compared with the four observation time points,MLCD had the best treatment effect on day 39 of the experiment and significantly improved the skin damage performance and relieved pathological lesions.On day 39,compared with the model group,MLCD downregulated the skin mRNA relative expressions of IL-4(P=.009),TSLP(P=.030),and TSLPR(P <.001),and reduced the mouse serum levels of IL-4(P=.003).For other serum indicators,no significant difference was observed between the model and MLCD groups.Conclusion:MLCD improved AD-like mice skin damage by regulating the Th1/Th2 immune imbalance.

Detecting Power Imbalance in Multi-Cylinder Inline Diesel Engine Genset

A model of fuel injection adjustment for balancing the 4-stroke six cylinder diesel engine coupling geneset is developed by detecting imbalance in operating engine by the frequency analysis of the crankshaft＇s speed variation. In this work, the crankshaft is considered to be a rigid body, so that the variation of its angular speed could be directly correlated to the total gas-pressure torque. By analyzing only the lower harmonic orders, the speed variation spectrum can filter out the distortions produced by the dynamic response of the crankshaft. The information carried by these harmonic orders permits to establish correlations between measurements and the average gas pressure torque of the engine, and to detect imbalance and identify faulty cylinders. Detailed experimental reading are taken on diesel engine coupling genset on the test bed of Greaves Cotton Ltd Pane, India.