Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

The W transform and its improved methods for time-frequency analysis of seismic data

The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region,we have proposed a W transform method,in which the instantaneous frequency is introduced as a parameter into the linear transformation,and the analysis time window is constructed which matches the instantaneous frequency of the seismic data.In this paper,the W transform method is compared with the Wigner-Ville distribution(WVD),a typical nonlinear time-frequency analysis method.The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet,while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing,because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter.Therefore,the W transform can be benchmarked directly by the WVD method.We summarize the development of the W transform and three improved methods in recent years,and elaborate on the evolution of the standard W transform,the chirp-modulated W transform,the fractional-order W transform,and the linear canonical W transform.Through three application examples of W transform in fluvial sand body identification and reservoir prediction,it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra.

Corrigendum to“Migration pattern of a population of Barn Swallows(Hirundo rustica)breeding in East Asian tropical region”[Avian Res.15(2024)100192]

The authors regret that the caption of Fig.4 should be replaced as below.

A reliability-oriented genetic algorithm-levenberg marquardt model for leak risk assessment based on time-frequency features

Since leaks in high-pressure pipelines transporting crude oil can cause severe economic losses,a reliable leak risk assessment can assist in developing an effective pipeline maintenance plan and avoiding unexpected incidents.The fast and accurate leak detection methods are essential for maintaining pipeline safety in pipeline reliability engineering.Current oil pipeline leakage signals are insufficient for feature extraction,while the training time for traditional leakage prediction models is too long.A new leak detection method is proposed based on time-frequency features and the Genetic Algorithm-Levenberg Marquardt(GA-LM)classification model for predicting the leakage status of oil pipelines.The signal that has been processed is transformed to the time and frequency domain,allowing full expression of the original signal.The traditional Back Propagation(BP)neural network is optimized by the Genetic Algorithm(GA)and Levenberg Marquardt(LM)algorithms.The results show that the recognition effect of a combined feature parameter is superior to that of a single feature parameter.The Accuracy,Precision,Recall,and F1score of the GA-LM model is 95%,93.5%,96.7%,and 95.1%,respectively,which proves that the GA-LM model has a good predictive effect and excellent stability for positive and negative samples.The proposed GA-LM model can obviously reduce training time and improve recognition efficiency.In addition,considering that a large number of samples are required for model training,a wavelet threshold method is proposed to generate sample data with higher reliability.The research results can provide an effective theoretical and technical reference for the leakage risk assessment of the actual oil pipelines.

Clinical manifestation,lifestyle,and treatment patterns of chronic erosive gastritis:A multicenter real-world study in China

BACKGROUND Although chronic erosive gastritis(CEG)is common,its clinical characteristics have not been fully elucidated.The lack of consensus regarding its treatment has resulted in varied treatment regimens.AIM To explore the clinical characteristics,treatment patterns,and short-term outcomes in CEG patients in China.METHODS We recruited patients with chronic non-atrophic or mild-to-moderate atrophic gastritis with erosion based on endoscopy and pathology.Patients and treating physicians completed a questionnaire regarding history,endoscopic findings,and treatment plans as well as a follow-up questionnaire to investigate changes in symptoms after 4 wk of treatment.RESULTS Three thousand five hundred sixty-three patients from 42 centers across 24 cities in China were included.Epigastric pain(68.0%),abdominal distension(62.6%),and postprandial fullness(47.5%)were the most common presenting symptoms.Gastritis was classified as chronic non-atrophic in 69.9%of patients.Among those with erosive lesions,72.1%of patients had lesions in the antrum,51.0%had multiple lesions,and 67.3%had superficial flat lesions.In patients with epigastric pain,the combination of a mucosal protective agent(MPA)and proton pump inhibitor was more effective.For those with postprandial fullness,acid regurgitation,early satiety,or nausea,a MPA appeared more promising.CONCLUSION CEG is a multifactorial disease which is common in Asian patients and has non-specific symptoms.Gastroscopy may play a major role in its detection and diagnosis.Treatment should be individualized based on symptom profile.

Research on Low Voltage Series Arc Fault Prediction Method Based on Multidimensional Time-Frequency Domain Characteristics

The load types in low-voltage distribution systems are diverse.Some loads have current signals that are similar to series fault arcs,making it difficult to effectively detect fault arcs during their occurrence and sustained combustion,which can easily lead to serious electrical fire accidents.To address this issue,this paper establishes a fault arc prototype experimental platform,selects multiple commonly used loads for fault arc experiments,and collects data in both normal and fault states.By analyzing waveform characteristics and selecting fault discrimination feature indicators,corresponding feature values are extracted for qualitative analysis to explore changes in timefrequency characteristics of current before and after faults.Multiple features are then selected to form a multidimensional feature vector space to effectively reduce arc misjudgments and construct a fault discrimination feature database.Based on this,a fault arc hazard prediction model is built using random forests.The model’s multiple hyperparameters are simultaneously optimized through grid search,aiming tominimize node information entropy and complete model training,thereby enhancing model robustness and generalization ability.Through experimental verification,the proposed method accurately predicts and classifies fault arcs of different load types,with an average accuracy at least 1%higher than that of the commonly used fault predictionmethods compared in the paper.

Surface Patterning of Metal Zinc Electrode with an In‑Region Zincophilic Interface for High‑Rate and Long‑Cycle‑Life Zinc Metal Anode

The undesirable dendrite growth induced by non-planar zinc(Zn)deposition and low Coulombic efficiency resulting from severe side reactions have been long-standing challenges for metallic Zn anodes and substantially impede the practical application of rechargeable aqueous Zn metal batteries(ZMBs).Herein,we present a strategy for achieving a high-rate and long-cycle-life Zn metal anode by patterning Zn foil surfaces and endowing a Zn-Indium(Zn-In)interface in the microchannels.The accumulation of electrons in the microchannel and the zincophilicity of the Zn-In interface promote preferential heteroepitaxial Zn deposition in the microchannel region and enhance the tolerance of the electrode at high current densities.Meanwhile,electron aggregation accelerates the dissolution of non-(002)plane Zn atoms on the array surface,thereby directing the subsequent homoepitaxial Zn deposition on the array surface.Consequently,the planar dendrite-free Zn deposition and long-term cycling stability are achieved(5,050 h at 10.0 mA cm^(−2) and 27,000 cycles at 20.0 mA cm^(−2)).Furthermore,a Zn/I_(2) full cell assembled by pairing with such an anode can maintain good stability for 3,500 cycles at 5.0 C,demonstrating the application potential of the as-prepared ZnIn anode for high-performance aqueous ZMBs.

Venous Doppler flow patterns,venous congestion,heart disease and renal dysfunction:A complex liaison

The World Journal of Cardiology published an article written by Kuwahara et al that we take the pleasure to comment on.We focused our attention on venous congestion.In intensive care settings,it is now widely accepted that venous congestion is an important clinical feature worthy of investigation.Evaluating venous Doppler profile abnormalities at multiple sites could suggest adequate treatment and monitor its efficacy.Renal dysfunction could trigger or worsen fluid overload in heart disease,and cardio-renal syndrome is a well-characterized spectrum of disorders describing the complex interactions between heart and kidney diseases.Fluid overload and venous congestion,including renal venous hypertension,are major determinants of acute and chronic renal dysfunction arising in heart disease.Organ congestion from venous hypertension could be involved in the development of organ injury in several clinical situations,such as critical diseases,congestive heart failure,and chronic kidney disease.Ultrasonography and abnormal Doppler flow patterns diagnose clinically significant systemic venous congestion.Cardiologists and nephrologists might use this valuable,noninvasive,bedside diagnostic tool to establish fluid status and guide clinical choices.

Pedestrian flow through exit:Study focused on evacuation pattern

Experiments are conducted on the evacuation rate of pedestrians through exits with queued evacuation pattern and random evacuation pattern. The experimental results show that the flow rate of pedestrians is larger with the random evacuation pattern than with the queued evacuation pattern. Therefore, the exit width calculated based on the minimum evacuation clear width for every 100 persons, which is on the assumption that the pedestrians pass through the exit in one queue or several queues, is conservative. The number of people crossing the exit simultaneously is greater in the random evacuation experiments than in the queued evacuation experiments, and the time interval between the front row and rear row of people is shortened in large-exit conditions when pedestrians evacuate randomly. The difference between the flow rate with a queued evacuation pattern and the flow rate with a random evacuation pattern is related to the surplus width of the exit, which is greater than the total width of all accommodated people streams. Two dimensionless quantities are defined to explore this relationship. It is found that the difference in flow rate between the two evacuation patterns is stable at a low level when the surplus width of the exit is no more than 45% of the width of a single pedestrian stream. There is a great difference between the flow rate with the queued evacuation pattern and the flow rate with the random evacuation pattern in a scenario with a larger surplus width of the exit. Meanwhile, the pedestrians crowd extraordinarily at the exit in these conditions as well, since the number of pedestrians who want to evacuate through exit simultaneously greatly exceeds the accommodated level. Therefore, the surplus width of exit should be limited especially in the narrow exit condition, and the relationship between the two dimensionless quantities mentioned above could provide the basis to some extent.

A divergent pattern in functional connectivity: a transdiagnostic perspective

Functional magnetic resonance imaging(fMRI)is a popular tool used to investigate not only how the brain responds to specific stimuli during sensorimotor or cognitive tasks,but also brain activity at rest.The physics beyond this approach is based on the analysis of the blood oxygenation level-dependent signal.

Pig Reproductive and Respiratory Syndrome Virus (PRRSV) Does Not Attach to Boar Sperm;It Affects Only the Velocity Pattern and the Mobility Pattern

The purpose of the study was to evaluate the sperm viability of semen infected with PRRSV viral particles, observing the effect of the Virus on the motility of boar sperm. The work was carried out at the FMVZ-BUAP Genetics and Reproduction Laboratory. 5 stallions were used. Each sample contained 1 × 106 sperm, the PRRS virus strain was ATCC-VR-2332 (0, 102, 104 and 106 copies of RNA/mL in triplicate), it was observed daily at the CASA;Hamilton Thorne®. Cells with MT (P < 0.05) on days 1, 3, 5, 7 and 10 of evaluation with 201 ± 7.3, 167 ± 10.1, 165 ± 14.6, 134 ± 8.2 and 120 ± 8.8, respectively. The % MP between control and virus concentrations (P ≥ 0.05). The LCV on day 1 and 7 PI at 10X2 and 10X6 (P < 0.05) vs control. In the Correlation Matrix, where it is observed that there is a correlation between VSL and VAP, VSL and VCL, VCL and ALH, VAP with ALH. There is a correlation of VSL and ALH, STR and ALH. In this study there were (P ≤ 0.01) in the VCL, in the concentrations (102) 162.81 ± 10.65 and (106) 177.12 ± 5.77 vs 193.04 ± 4.62 of control. This indicates that altering these parameters would be related to fertility and the PRRS virus affects the LCV. Regarding the VSL, it was observed that the sperm infected with viruses 102, 104 and 106 of 48.00 ± 3.38, 49.88 ± 1.83 and 50.55 ± 2.24 Vs. 56.66 ± 1.68 of control respectively, the control would have greater possibilities of fertilizing the oocyte. In this study, it was found (P ≤ 0.01) in the VAP with 102 of 77.26 ± 5.16, 104 with 83.35 ± 2.41 and 106 with 81.29 ± 3.14 vs the control with 90.56 ± 2.07. Regarding the ALH there is (P < 0.05) a 104 with 8.70 ± .26 and 106 with 9.64 ± 0.23 vs control 8.50 ± 0.27. The presence of different concentrations of PRRSV in boar semen induces changes in different types of sperm motility. Infection of ejaculates with the PRRS virus affects sperm motility on days 1, 3, 5, 7, and 10 post-infections.

A Portfolio Selection Method Based on Pattern Matching with Dual Information of Direction and Distance

Pattern matching method is one of the classic classifications of existing online portfolio selection strategies. This article aims to study the key aspects of this method—measurement of similarity and selection of similarity sets, and proposes a Portfolio Selection Method based on Pattern Matching with Dual Information of Direction and Distance (PMDI). By studying different combination methods of indicators such as Euclidean distance, Chebyshev distance, and correlation coefficient, important information such as direction and distance in stock historical price information is extracted, thereby filtering out the similarity set required for pattern matching based investment portfolio selection algorithms. A large number of experiments conducted on two datasets of real stock markets have shown that PMDI outperforms other algorithms in balancing income and risk. Therefore, it is suitable for the financial environment in the real world.

Study on Epidemiological Profile, Clinical Profile, and Angiographic Patterns in Acute Coronary Syndrome Patients in a Tertiary Health Care Center in Haryana

Background: Cardiovascular diseases are the leading cause of death in India, with coronary artery disease (CAD) accounting for a majority of the deaths. There are few large registries on acute coronary syndrome (ACS) from India. Our aim is to study the clinical and epidemiological profile of ACS PATIENTS presenting to our institute, including their angiographic features. Methods: This hospital-based observational, single tertiary care center, prospective study was conducted on patients admitted in the Department of Cardiology at a tertiary care center in Haryana. The study included 400 patients aged greater than 18 years who were admitted with the diagnosis of ACS, and it was carried out for 1 year. The epidemiological profile, clinical history, risk factors, electrocardiogram findings, and angiographic pattern were studied and analyzed with appropriate statistical tools. Results: The mean age of the study population was 55.12 ± 11.78 years. Male and female ratio was 2.4:1. The majority of the patients came from rural background (80%);24% of the patients were illiterate. Smoking was the most common risk factor (51.5%) in our study population followed by hypertension (40%) and diabetes (28%). Unstable angina was the most common type of ACS, which was found in 68.25% of patients. Premature CAD was found in 27.8% of patients and obstructive CAD was found in 63% of patients. Coronary angiography revealed that 39% had single vessel disease (SVD), 23.5% had double vessel disease (DVD), and 27.5% had triple vessel disease (TVD). LAD was more commonly involved, followed by RCA and LCX. Within the first 24 hours, 67% of patients sought medical assistance and only 38.5% received definitive treatment, suggesting a delay in seeking definitive treatment in our study population. Conclusion: The study suggests that unstable angina is the most common form of ACS in the study population, which is mostly of rural background with significant delay in seeking medical help. Smoking is the most common risk factor in the study population.

Pattern of Referral of Obstetric Patients at a Tertiary Care Hospital in Southern Nigeria

Background: Health challenges that are difficult to manage at primary health centres should be referred to secondary health facilities, and if untreated, to the tertiary hospitals. A good referral should include the patient’s biography, such as age, gender, tribe, religion, occupation, medical history, the reason for the referral, treatments received, and clinical diagnosis. Objectives: To evaluate the referral patterns, indications for referrals, and feto-maternal outcomes for obstetric patients who were referred to the University of Port Harcourt Teaching Hospital. Materials and Methods: A prospective study of patients admitted to the Obstetric unit from January 1, 2021, to December 31, 2022. Data was collected from patients while on admission or clinic visits and recorded in an excel spread sheet. Data was analyzed with the Statistical Package for Social Sciences (SPSS) version 25. Results: Of the 3469 patients were admitted to the obstetric unit, 1476 and 1993 were admitted in 2021 and 2022, respectively. Most (70.35%) of the patients were in the 20-34 years age group, parity 1-4 was the most frequent (66.49%), while 85.39% of patients were booked. 10.46% of the booked patients were referred from other facilities, whereas 89.54% of patients were booked at our facility from the onset. Most common indications of referrals were previous caesarean section (CS) at term (40.09%) and hypertensive disorders of pregnancy (17.59%). The outcome for 2021 indicated 17 maternal deaths, 132 fetal deaths and 1010 live births, giving maternal mortality ratio (MMR) as 1810.44 per 100,000 live births and perinatal mortality ratio (PMR) of 130.7 per 1000 births respectively. In 2022, there were 17 maternal deaths, 130 fetal deaths and 1297 deliveries, giving a MMR of 1399 per 100,000 live births and a PMR of 100.2 per 1000 births. Conclusion: The pattern of referral among obstetric patients in this study shows that a lot of the patients do not get adequate care at the lower cadre of the referral system, hence adequate facilities should be made available in primary and secondary health centres to tackle obstetric emergencies.

Tuning the diffusion constant to optimize the readout of positional information of spatial concentration patterns

Positional information encoded in spatial concentration patterns is crucial for the development of multicellular organisms.However,it is still unclear how such information is affected by the physically dissipative diffusion process.Here we study one-dimensional patterning systems with analytical derivation and numerical simulations.We find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration patterns.Specifically,there exists an optimal diffusion constant that maximizes the positional information.Moreover,we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

Temporal and spatial evolution of global major grain trade patterns

The complex and volatile international landscape has significantly impacted global grain supply security. This study uses a complex network analysis model to examine the evolution and trends of the global major grain trade from 1990 to 2020, focusing on network topology, centrality ranking, and community structure. There are three major findings. First, the global major grain trade network has expanded in scale, with a growing emphasis on diversification and balance. During the study period, the United States, Canada, China, and Brazil were the core nodes of the network. Grain-exporting countries were mainly situated in Asia, the Americas, and Europe, and importing countries in Asia, Africa, and Europe. Second, a significant increase in the number of high centrality countries with high export capacity occurred, benefiting from natural advantages such as fertile land and favorable climates. Third, the main global grain trade network is divided into four communities, with the Americas-Europe community being the largest and most widespread. The formation of the community pattern was influenced by geographic proximity, driven by the core exporting countries. Therefore, the world needs to enhance the existing trade model, promote the multi-polarization of the grain trade network, and establish a global vision for the future community. Countries and regions should participate actively in global grain trade security governance and institutional reform, expand trade links with other countries, and optimize import and export policies to reduce trade risks.

Dissolvable temporary barrier:a novel paradigm for flexible hydrogel patterning in organ-on-a-chip models

A combination of hydrogels and microfluidics allows the construction of biomimetic three-dimensional(3D)tissue models in vitro,which are also known as organ-on-a-chipmodels.The hydrogel patterningwith awell-controlled spatial distribution is typically achieved by embedding sophisticated microstructures to act as a boundary.However,these physical barriers inevitably expose cells/tissues to a less physiologically relevant microenvironment than in vivo conditions.Herein,we present a novel dissolvable temporary barrier(DTB)strategy that allows robust and flexible hydrogel patterning with great freedom of design and desirable flow stimuli for cellular hydrogels.The key aspect of this approach is the patterning of a water-soluble rigid barrier as a guiding path for the hydrogel using stencil printing technology,followed by a barrier-free medium perfusion after the dissolution of the DTB.Single and multiple tissue compartments with different geometries can be established using either straight or curved DTB structures.The effectiveness of this strategy is further validated by generating a 3D vascular network through vasculogenesis and angiogenesis using a vascularized microtumor model.As a new proof-of-concept in vasculature-on-a-chip,DTB enables seamless contact between the hydrogel and the culture medium in closed microdevices,which is an improved protocol for the fabrication ofmultiorgan chips.Therefore,we expect it to serve as a promising paradigm for organ-on-a-chip devices for the development of tumor vascularization and drug evaluation in the future preclinical studies.

Recent Advances in Patterning Strategies for Full‑Color Perovskite Light‑Emitting Diodes

Metal halide perovskites have emerged as promising light-emitting materials for next-generation displays owing to their remarkable material characteristics including broad color tunability,pure color emission with remarkably narrow bandwidths,high quantum yield,and solution processability.Despite recent advances have pushed the luminance efficiency of monochromic perovskite light-emitting diodes(PeLEDs)to their theoretical limits,their current fabrication using the spincoating process poses limitations for fabrication of full-color displays.To integrate PeLEDs into full-color display panels,it is crucial to pattern red–green–blue(RGB)perovskite pixels,while mitigating issues such as cross-contamination and reductions in luminous efficiency.Herein,we present state-of-the-art patterning technologies for the development of full-color PeLEDs.First,we highlight recent advances in the development of efficient PeLEDs.Second,we discuss various patterning techniques of MPHs(i.e.,photolithography,inkjet printing,electron beam lithography and laserassisted lithography,electrohydrodynamic jet printing,thermal evaporation,and transfer printing)for fabrication of RGB pixelated displays.These patterning techniques can be classified into two distinct approaches:in situ crystallization patterning using perovskite precursors and patterning of colloidal perovskite nanocrystals.This review highlights advancements and limitations in patterning techniques for PeLEDs,paving the way for integrating PeLEDs into full-color panels.

Spatiotemporal pattern of climate change in the China-Myanmar Economic Corridor from 1901 to 2018

The China-Myanmar Economic Corridor(CMEC) is an important part of China's Belt and Road Initiative and an important area for global ecology and biodiversity. In this study, the annual and seasonal spatiotemporal patterns of temperature and precipitation in the CMEC over the past century were investigated using linear tendency estimation, the Mann-Kendall mutation test, the T-test, and wavelet analysis based on the monthly mean climatic data from 1901 to 2018 released by the Climatic Research Unit(CRU) of the University of East Anglia, UK. The results show that the CMEC demonstrated a trend of warming and drying over the past 100 years, and the rate of change in Myanmar was stronger than that in Yunnan Province of China. The warming rate was 0.039 ℃/10a. Precipitation decreased at a rate of -6.1 mm/10a. From the perspective of spatial distribution, temperature was high in the central and southern, low in the north of the CMEC, and the high-temperature centers were mainly distributed in the southern plain and river valley. Precipitation decreased from west to east and from south to north of the CMEC. From the perspective of the rate of change, warming was stronger in central and northern CMEC than in southern and northeastern CMEC. The rate of precipitation decline was stronger in the central and western regions than in the eastern region. This study provides a scientific reference for the CMEC to address climate change and ensure sustainable social and economic development and ecological security.

Prophylactic Pattern Scanning Laser Retinal Photocoagulation for Diabetic Retinopathy in Spontaneously Diabetic Torii Fatty Rats: Preliminary Experimental Results

Research Background and Purpose: The number of diabetic patients is rapidly increasing, making it crucial to find methods to prevent diabetic retinopathy (DR), a leading cause of blindness. We investigated the effects of prophylactic pattern scanning laser retinal photocoagulation on DR development in Spontaneously Diabetic Torii (SDT) fatty rats as a new prevention approach. Methods: Photocoagulation was applied to the right eyes of 8-week-old Spontaneously Diabetic Torii (SDT) fatty rats, with the left eyes serving as untreated controls. Electroretinography at 9 and 39 weeks of age and pathological examinations, including immunohistochemistry for vascular endothelial growth factor and glial fibrillary acidic protein at 24 and 40 weeks of age, were performed on both eyes. Results: There were no significant differences in amplitude and prolongation of the OP waves between the right and left eyes in SDT fatty rats at 39 weeks of age. Similarly, no significant differences in pathology and immunohistochemistry were observed between the right and left eyes in SDT fatty rats at 24 and 40 weeks of age. Conclusion: Prophylactic pattern scanning retinal laser photocoagulation did not affect the development of diabetic retinopathy in SDT fatty rats.