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 adh...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.展开更多
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 over...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.展开更多
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 spi...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.展开更多
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.Com...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.展开更多
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 b...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.展开更多
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 influ...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.展开更多
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 curren...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.展开更多
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, respectivel...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.展开更多
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-Pet...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.展开更多
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 betw...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.展开更多
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 equilibriu...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.展开更多
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 algor...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.展开更多
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 th...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.展开更多
Datasets with the imbalanced class distribution are difficult to handle with the standard classification algorithms.In supervised learning,dealing with the problem of class imbalance is still considered to be a challe...Datasets with the imbalanced class distribution are difficult to handle with the standard classification algorithms.In supervised learning,dealing with the problem of class imbalance is still considered to be a challenging research problem.Various machine learning techniques are designed to operate on balanced datasets;therefore,the state of the art,different undersampling,over-sampling and hybrid strategies have been proposed to deal with the problem of imbalanced datasets,but highly skewed datasets still pose the problem of generalization and noise generation during resampling.To overcome these problems,this paper proposes amajority clusteringmodel for classification of imbalanced datasets known as MCBC-SMOTE(Majority Clustering for balanced Classification-SMOTE).The model provides a method to convert the problem of binary classification into a multi-class problem.In the proposed algorithm,the number of clusters for themajority class is calculated using the elbow method and the minority class is over-sampled as an average of clustered majority classes to generate a symmetrical class distribution.The proposed technique is cost-effective,reduces the problem of noise generation and successfully disables the imbalances present in between and within classes.The results of the evaluations on diverse real datasets proved to provide better classification results as compared to state of the art existing methodologies based on several performance metrics.展开更多
Brain angiotensinⅡ(ANGⅡ)as a pleiotropic player:Mental disorders have been commonly associated with an imbalance in many neurotransmitter systems,such as dopamine,glutamate,and gamma-aminobutyric acid.Considering th...Brain angiotensinⅡ(ANGⅡ)as a pleiotropic player:Mental disorders have been commonly associated with an imbalance in many neurotransmitter systems,such as dopamine,glutamate,and gamma-aminobutyric acid.Considering the complexity of brain functioning,all components of the neurovascular unit should be considered in studies for a better comprehension of the physiopathology and possible therapeutics.展开更多
As a promising edge learning framework in future 6G networks,federated learning(FL)faces a number of technical challenges due to the heterogeneous network environment and diversified user behaviors.Data imbalance is o...As a promising edge learning framework in future 6G networks,federated learning(FL)faces a number of technical challenges due to the heterogeneous network environment and diversified user behaviors.Data imbalance is one of these challenges that can significantly degrade the learning efficiency.To deal with data imbalance issue,this work proposes a new learning framework,called clustered federated learning with weighted model aggregation(weighted CFL).Compared with traditional FL,our weighted CFL adaptively clusters the participating edge devices based on the cosine similarity of their local gradients at each training iteration,and then performs weighted per-cluster model aggregation.Therein,the similarity threshold for clustering is adaptive over iterations in response to the time-varying divergence of local gradients.Moreover,the weights for per-cluster model aggregation are adjusted according to the data balance feature so as to speed up the convergence rate.Experimental results show that the proposed weighted CFL achieves a faster model convergence rate and greater learning accuracy than benchmark methods under the imbalanced data scenario.展开更多
With the rise of internet facilities,a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the ba...With the rise of internet facilities,a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction.However,the fraud cases have also increased causing the loss of money to the consumers.Hence,an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time.Generally,the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem.In this research work,an online transaction fraud detection system using deep learning has been proposed which can handle class imbalance problem by applying algorithm-level methods which modify the learning of the model to focus more on the minority class i.e.,fraud transactions.A novel loss function named Weighted Hard-Reduced Focal Loss(WH-RFL)has been proposed which has achieved maximum fraud detection rate i.e.,True PositiveRate(TPR)at the cost of misclassification of few genuine transactions as high TPR is preferred over a high True Negative Rate(TNR)in fraud detection system and same has been demonstrated using three publicly available imbalanced transactional datasets.Also,Thresholding has been applied to optimize the decision threshold using cross-validation to detect maximum number of frauds and it has been demonstrated by the experimental results that the selection of the right thresholding method with deep learning yields better results.展开更多
Knowledge-based employees are the inexhaustible motive force for the sustainable development of modern enterprises. Being consistent with the psychological expectation of knowledge-based employees is conducive to stim...Knowledge-based employees are the inexhaustible motive force for the sustainable development of modern enterprises. Being consistent with the psychological expectation of knowledge-based employees is conducive to stimulating the intrinsic motivation of knowledge-based employees and promoting the innovation performance of enterprises. Based on 175 valid questionnaires,the analysis shows that the knowledge about employees' psychological contract can be divided into two-dimension, transactional or relational dimension. Both of them are independent to each other.The correlation analysis shows that the transactional psychological contract and relational psychological contract have positive correlation with team performance and organization performance.At the same time, the team performance and organization performance have positive correlation. Regression analysis shows that compared with relational psychological contract,transactional psychological contract can promote team performance and organizational performance more effectively. Both two psychological contracts can mediate the organizational performance by virtue of team performance.展开更多
BACKGROUND The role of oxidative stress in the pathogenesis of colorectal carcinoma(CRC)has garnered considerable interest recently.Specific oxidative factors have been implicated in the pathogenesis of adenomatous po...BACKGROUND The role of oxidative stress in the pathogenesis of colorectal carcinoma(CRC)has garnered considerable interest recently.Specific oxidative factors have been implicated in the pathogenesis of adenomatous polyps and ultimately adenocarcinoma.AIM To evaluate the effect of oxidative imbalance as quantified by specific serological markers in the development of sporadic colon adenocarcinoma.METHODS A total of 170 patients that underwent endoscopy of the lower gastrointestinal tract in a tertiary center within 3 years were included in the study.They were allocated in three groups;those with sporadic colon adenocarcinoma(n=56,32.9%),those with colonic polyps(n=33,19.4%)and healthy controls(n=81,47.7%).All patients were evaluated for oxidant activity and antioxidant capacity with serum measurements of specific markers such as vitamins A,25(OH)D3,E,C,B12,folic acid,glutathione,selenium(Se),zinc(Zn),free iron(Fe^(2+)),and malondialdehyde and results were compared between groups.RESULTS Serum levels of vitamins C,E,D,Se,Zn,vitamin B12 and total antioxidant capacity were significantly lower in the combined neoplasia/polyp group than in the control group(P=0.002,P=0.009,P<0.001,P<0.001,P<0.001,P=0.020 and P<0.001,correspondingly).Increased levels of vitamin E(P=0.004),vitamin D(P<0.001),Se(P<0.001)and Zn(P<0.001)seem to bestow a protective effect on the development of CRC.For vitamin D(P<0.001)and Zn(P=0.036),this effect seems to extend to the development of colon polyps as well.On the other hand,elevated serum levels of malondialdehyde are associated with a higher risk of CRC(OR=2.09 compared to controls,P=0.004).Regarding colonic polyp development,increased concentrations of vitaminΑand Fe^(2+) are associated with a higher risk,whereas lower levels of malondialdehyde with a lower risk.CONCLUSION Increased oxidative stress may play an important role in the pathogenesis and progression of CRC.Antioxidants’presence may exert a protective effect in the very early stages of colon carcinogenesis.展开更多
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 fact...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.展开更多
基金the High-Performance Computing Platform of Beijing University of Chemical Technology(BUCT)for supporting this papersupported by the Fundamental Research Funds for the Central Universities(JD2319)+2 种基金the CNOOC Technical Cooperation Project(ZX2022ZCTYF7612)the National Natural Science Foundation of China(51775029,52004014)the Chinese Universities Scientific Fund(XK2020-04)。
文摘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.
基金The authors would like to extend their gratitude to Universiti Teknologi PETRONAS (Malaysia)for funding this research through grant number (015LA0-037).
文摘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.
基金supported by the National Natural Science Foundation of China,Nos.81070996 (to ZW) and 815 72151 (to XYH)Shaanxi Provincial Key R&D Program,Nos.2020ZDLSF02-05 (to ZW),2021ZDLSF02-10 (to XYH)。
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(Grant No.32200940)Science and Technology Bureau of Nantong(Grant Nos.JC2020101,JC2021085)Municipal Health Commission of Nantong(Grant No.MA2020019).
文摘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.
文摘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.
文摘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.
基金National Institutes of Health,Grant/Award Number:R01NS079792UNTHSC Seed Grants,Grant/Award Number:RI10015 and RI10039
文摘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.
文摘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.
基金partially supported by the National Natural Science Foundation of China (51874325)the Science Foundation of China University of PetroleumBeijing (2462021BJRC009)。
文摘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.
文摘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.
文摘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.
文摘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.
基金This research was supported by Taif University Researchers Supporting Project number(TURSP-2020/254),Taif University,Taif,Saudi Arabia.
文摘Datasets with the imbalanced class distribution are difficult to handle with the standard classification algorithms.In supervised learning,dealing with the problem of class imbalance is still considered to be a challenging research problem.Various machine learning techniques are designed to operate on balanced datasets;therefore,the state of the art,different undersampling,over-sampling and hybrid strategies have been proposed to deal with the problem of imbalanced datasets,but highly skewed datasets still pose the problem of generalization and noise generation during resampling.To overcome these problems,this paper proposes amajority clusteringmodel for classification of imbalanced datasets known as MCBC-SMOTE(Majority Clustering for balanced Classification-SMOTE).The model provides a method to convert the problem of binary classification into a multi-class problem.In the proposed algorithm,the number of clusters for themajority class is calculated using the elbow method and the minority class is over-sampled as an average of clustered majority classes to generate a symmetrical class distribution.The proposed technique is cost-effective,reduces the problem of noise generation and successfully disables the imbalances present in between and within classes.The results of the evaluations on diverse real datasets proved to provide better classification results as compared to state of the art existing methodologies based on several performance metrics.
文摘Brain angiotensinⅡ(ANGⅡ)as a pleiotropic player:Mental disorders have been commonly associated with an imbalance in many neurotransmitter systems,such as dopamine,glutamate,and gamma-aminobutyric acid.Considering the complexity of brain functioning,all components of the neurovascular unit should be considered in studies for a better comprehension of the physiopathology and possible therapeutics.
文摘As a promising edge learning framework in future 6G networks,federated learning(FL)faces a number of technical challenges due to the heterogeneous network environment and diversified user behaviors.Data imbalance is one of these challenges that can significantly degrade the learning efficiency.To deal with data imbalance issue,this work proposes a new learning framework,called clustered federated learning with weighted model aggregation(weighted CFL).Compared with traditional FL,our weighted CFL adaptively clusters the participating edge devices based on the cosine similarity of their local gradients at each training iteration,and then performs weighted per-cluster model aggregation.Therein,the similarity threshold for clustering is adaptive over iterations in response to the time-varying divergence of local gradients.Moreover,the weights for per-cluster model aggregation are adjusted according to the data balance feature so as to speed up the convergence rate.Experimental results show that the proposed weighted CFL achieves a faster model convergence rate and greater learning accuracy than benchmark methods under the imbalanced data scenario.
基金This research was supported by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(P0012724,The Competency Development Program for Industry Specialist)and the Soonchunhyang University Research Fund.
文摘With the rise of internet facilities,a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction.However,the fraud cases have also increased causing the loss of money to the consumers.Hence,an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time.Generally,the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem.In this research work,an online transaction fraud detection system using deep learning has been proposed which can handle class imbalance problem by applying algorithm-level methods which modify the learning of the model to focus more on the minority class i.e.,fraud transactions.A novel loss function named Weighted Hard-Reduced Focal Loss(WH-RFL)has been proposed which has achieved maximum fraud detection rate i.e.,True PositiveRate(TPR)at the cost of misclassification of few genuine transactions as high TPR is preferred over a high True Negative Rate(TNR)in fraud detection system and same has been demonstrated using three publicly available imbalanced transactional datasets.Also,Thresholding has been applied to optimize the decision threshold using cross-validation to detect maximum number of frauds and it has been demonstrated by the experimental results that the selection of the right thresholding method with deep learning yields better results.
基金Fundamental Research Funds for the Central Universities,China(No.17D111004)
文摘Knowledge-based employees are the inexhaustible motive force for the sustainable development of modern enterprises. Being consistent with the psychological expectation of knowledge-based employees is conducive to stimulating the intrinsic motivation of knowledge-based employees and promoting the innovation performance of enterprises. Based on 175 valid questionnaires,the analysis shows that the knowledge about employees' psychological contract can be divided into two-dimension, transactional or relational dimension. Both of them are independent to each other.The correlation analysis shows that the transactional psychological contract and relational psychological contract have positive correlation with team performance and organization performance.At the same time, the team performance and organization performance have positive correlation. Regression analysis shows that compared with relational psychological contract,transactional psychological contract can promote team performance and organizational performance more effectively. Both two psychological contracts can mediate the organizational performance by virtue of team performance.
文摘BACKGROUND The role of oxidative stress in the pathogenesis of colorectal carcinoma(CRC)has garnered considerable interest recently.Specific oxidative factors have been implicated in the pathogenesis of adenomatous polyps and ultimately adenocarcinoma.AIM To evaluate the effect of oxidative imbalance as quantified by specific serological markers in the development of sporadic colon adenocarcinoma.METHODS A total of 170 patients that underwent endoscopy of the lower gastrointestinal tract in a tertiary center within 3 years were included in the study.They were allocated in three groups;those with sporadic colon adenocarcinoma(n=56,32.9%),those with colonic polyps(n=33,19.4%)and healthy controls(n=81,47.7%).All patients were evaluated for oxidant activity and antioxidant capacity with serum measurements of specific markers such as vitamins A,25(OH)D3,E,C,B12,folic acid,glutathione,selenium(Se),zinc(Zn),free iron(Fe^(2+)),and malondialdehyde and results were compared between groups.RESULTS Serum levels of vitamins C,E,D,Se,Zn,vitamin B12 and total antioxidant capacity were significantly lower in the combined neoplasia/polyp group than in the control group(P=0.002,P=0.009,P<0.001,P<0.001,P<0.001,P=0.020 and P<0.001,correspondingly).Increased levels of vitamin E(P=0.004),vitamin D(P<0.001),Se(P<0.001)and Zn(P<0.001)seem to bestow a protective effect on the development of CRC.For vitamin D(P<0.001)and Zn(P=0.036),this effect seems to extend to the development of colon polyps as well.On the other hand,elevated serum levels of malondialdehyde are associated with a higher risk of CRC(OR=2.09 compared to controls,P=0.004).Regarding colonic polyp development,increased concentrations of vitaminΑand Fe^(2+) are associated with a higher risk,whereas lower levels of malondialdehyde with a lower risk.CONCLUSION Increased oxidative stress may play an important role in the pathogenesis and progression of CRC.Antioxidants’presence may exert a protective effect in the very early stages of colon carcinogenesis.
基金This study was supported by the Beijing Natural Science Foundation(7192114).
文摘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.
