Performance Index Research Articles

Breast Ultrasound Computer-Aided Diagnosis System Based on Mass Irregularity Features in Frequency Domain

Our study develops a computer-aided diagnosis (CAD) system for breast ultrasound by presenting an innovative frequency domain technique for extracting mass irregularity features, thereby significantly boosting tumor classification accuracy. The experimental data consists of 5252 ultrasound breast tumor images, including 2745 benign tumors and 2507 malignant tumors. A Support Vector Machine was employed to classify the tumor as either benign or malignant, and the effectiveness of the proposed features set in distinguishing malignant masses from benign ones was validated. For the constructed CAD system, the performance indices’ accuracy, sensitivity, specificity, PPV, and NPV were 92.91%, 89.94%, 91.38%, 90.29%, and 91.45%, respectively, and the area index in the ROC analysis (AUC) was 0.924, demonstrating our method’s superiority over traditional spatial gray level dependence (SGLD), the ratio of depth to width, the count of depressions, and orientation features. Therefore, the constructed CAD system with the proposed features will be able to provide a precise and quick distinction between benign and malignant breast tumors with minimal training time in clinical settings.

Population Dynamics of Nile Tilapia (Oreochromis niloticus, Linnaeus.1758) from Khashm El-Girba Reservoir, Atbara River, Eastern Sudan

This study was conducted to assess the population parameters of Nile tilapia, Oreochromis niloticus, in the Khashm El-Girba Dam Reservoir in Eastern Sudan. Fish samples were collected from December 2019 to November 2020. Length-frequency data were collected from 1,671 specimens ranging from 5.1 to 34.2 cm in total length (TL). Analysis of the population parameters was determined using the ELEFAN I routine and the FiSAT II software computer program revealed that the estimated the Von Bertalanffy growth parameters were as follows: asymptotic length (L∞ = 36.75 cm), growth rate (K = 0.650 year -1) and age at length zero (t0 = -0.629) and the growth performance index (Φ') was calculated at 2.943. The instantaneous total mortality (Z), natural mortality (M), and fishing mortality (F) rates were determined using the length-converted catch curve and empirical models. The values obtained were Z = 2.38 year -1, M = 1.22 year -1, and F = 1.16 year -1, respectively. The exploitation rate (E) of the Nile tilapia was calculated at 0.49 year -1. The size at first capture (Lc) was estimated at 15.64 cm, which is slightly greater than the size at first maturity (Lm = 14.5 cm) and longevity (Tmax) was found to be 4.62 years. These findings indicate that the stock of the Nile tilapia population in Khashm El-Girba reservoir is overexploited, and that monitoring and management practices need to be employed to maintain the stocks at the optimum exploitation level.

Embracing Green Foreign Direct Investment in a Journey toward Global Sustainable Economy: An Empirical Approach Using Statistical Analysis

In particular, the link between green foreign direct investments (GFDI) and environmental performance (EP) is the focus of this study’s empirical analysis of the effects of GFDI on environmental sustainability. According to measurements like the environmental performance index (EPI) and indicators like health and ecosystem preservation (HLT and ECO), the results show that bigger GFDI sizes benefit environmental performance. Using a variety of econometric approaches, this result is derived using a worldwide sample that includes European nations from 2001 to 2023. Even after adding more explanatory factors and using a variety of econometric techniques, these results hold up well. Furthermore, the research explores the immediate and long-term impacts of GFDI on EP, emphasizing that the relationship between GFDI and EP becomes increasingly evident with time. Additionally, research will investigate how different transmission mechanisms allow green FDI to influence environmental sustainability. These results highlight how GFDI may be used to support industry environmental sustainability.

LNG storage tanks 9% Ni steel weld inspection via phased-coherent TFM and SVD enhancement

ABSTRACT 9% Ni steel is commonly utilised in liquefied natural gas storage tanks due to its strong resistance to corrosion and oxidation. However, the welds in these tanks are prone to serious defects, necessitating thorough non-destructive testing. Unfortunately, when inspecting nickel-based alloy welds using phased array ultrasonic testing (PAUT) technology the ultrasonic waves are scattered and attenuated because of the coarse columnar grains. To address this challenge, this paper introduces a based on SVD enhancement directivity corrected circular coherence factor weighted TFM imaging algorithm (SVD-DC-CCF). Initially, the CCF matrix is corrected by the directivity and energy attenuation compensation factors, then weighted with the TFM pixel point amplitude. Subsequently, the weighted amplitude matrix undergoes singular value decomposition (SVD), followed by the establishment of an enhancement factor to reconstruct the amplitude matrix. The proposed algorithm is evaluated through experiments on three types of defects in a 30.0 mm thick 9% Ni steel T-shaped fillet weld test block. Results demonstrate superior signal-to-noise ratio (SNR) and enhanced image resolution. Compared to TFM results, the SNR increases by 4.97 dB, 4.25 dB, and 4.96 dB, respectively, while the array performance index (API) decreases by 9.80%, 34.39%, and 22.22%, respectively.

Research on Non-Destructive Quality Detection of Sunflower Seeds Based on Terahertz Imaging Technology.

The variety and content of high-quality proteins in sunflower seeds are higher than those in other cereals. However, sunflower seeds can suffer from abnormalities, such as breakage and deformity, during planting and harvesting, which hinder the development of the sunflower seed industry. Traditional methods such as manual sensory and machine sorting are highly subjective and cannot detect the internal characteristics of sunflower seeds. The development of spectral imaging technology has facilitated the application of terahertz waves in the quality inspection of sunflower seeds, owing to its advantages of non-destructive penetration and fast imaging. This paper proposes a novel terahertz image classification model, MobileViT-E, which is trained and validated on a self-constructed dataset of sunflower seeds. The results show that the overall recognition accuracy of the proposed model can reach 96.30%, which is 4.85%, 3%, 7.84% and 1.86% higher than those of the ResNet-50, EfficientNeT, MobileOne and MobileViT models, respectively. At the same time, the performance indices such as the recognition accuracy, the recall and the F1-score values are also effectively improved. Therefore, the MobileViT-E model proposed in this study can improve the classification and identification of normal, damaged and deformed sunflower seeds, and provide technical support for the non-destructive detection of sunflower seed quality.

Inference of single-cell network using mutual information for scRNA-seq data analysis

BackgroundWith the advance in single-cell RNA sequencing (scRNA-seq) technology, deriving inherent biological system information from expression profiles at a single-cell resolution has become possible. It has been known that network modeling by estimating the associations between genes could better reveal dynamic changes in biological systems. However, accurately constructing a single-cell network (SCN) to capture the network architecture of each cell and further explore cell-to-cell heterogeneity remains challenging.ResultsWe introduce SINUM, a method for constructing the SIngle-cell Network Using Mutual information, which estimates mutual information between any two genes from scRNA-seq data to determine whether they are dependent or independent in a specific cell. Experiments on various scRNA-seq datasets with different cell numbers based on eight performance indexes (e.g., adjusted rand index and F-measure index) validated the accuracy and robustness of SINUM in cell type identification, superior to the state-of-the-art SCN inference method. Additionally, the SINUM SCNs exhibit high overlap with the human interactome and possess the scale-free property.ConclusionsSINUM presents a view of biological systems at the network level to detect cell-type marker genes/gene pairs and investigate time-dependent changes in gene associations during embryo development. Codes for SINUM are freely available at https://github.com/SysMednet/SINUM.

Evaluation of fibrous feed ingredients alternatives to oat hulls as a source of feed structure in broiler diets

This study aimed to evaluate several fibrous feed ingredients as potential substitutes for oat hulls (OH), assessing their efficacy in providing structural integrity to broiler feeds. A total of 4,160 day-old male Ross-308 broilers were allocated to eight dietary treatments, including a control group (CON) without additional fiber supplementation and 7 diets where 3% of the wheat content was replaced by either OH, soy hulls (SH), beet pulp (BP), carob bean (CB), wheat straw (WS), rice hulls (RH), or wheat bran (WB). The experimental design followed a complete randomized block design with 10 pens per treatment and 52 birds each. Growth performance and gut development indices were monitored, and the coefficients of total tract apparent retention (CTTAR) of nutrients were measured at 28 d. The OH improved feed conversion ratio (FCR) during the entire growth period (1-36 d) compared to the CON, SH, CB, WS, RH, and WB (P < 0.05). Conversely, BP diets reduced the final BW and ADFI compared to OH (P < 0.05) but were not different from the CON (P > 0.05). However, the FCR in birds fed with BP was similar to OH but lower than the CON group. In addition, BP-fed birds had higher CTTAR of ether extract and non-starch polysaccharides and relative weight of empty proventriculus and gizzard to BW at 14 and 28 d compared to CON. The WS, RH, and WB yielded similar final BW to OH and CON but higher FCR (P < 0.05). The CB, on the other hand, resulted in the highest FCR when contrasted with the other substitutes and CON (P < 0.05). Finding an alternative to OH with comparable benefits remains a challenge, with WS, RH, and WB showing similar final BW but inferior FCR to OH, and BP showing similar FCR but lower BW and ADFI.

How does the Dunning-Kruger effect happen in creativity? The creative self-concept matters

The Dunning-Kruger effect refers to the tendency of unskilled individuals to overestimate their abilities while skilled individuals tend to underestimate themselves. The purpose of this study is to investigate the existence of the Dunning-Kruger effect in creativity and identify its key determinants. Using the cue-utilization framework, we explored how inaccurate metacognitive judgments result from creative self-concept, compared to those who can accurately evaluate themselves. Two hundred and ten university students completed an Alternative Uses Task (AUT) and evaluated their performance with self- and comparative judgments, then they reported the creative self-concept. The study conducted a two-step clustering analysis based on individuals' creative performance, judgments, and Bias Index of metacognitive judgments, and identified four distinct groups: 'skilled but underestimate' (SU group), 'unskilled but aware' (UA group), 'skilled and aware' (SA group), and 'unskilled and overestimate' (UO group). The SU and UO groups were typical examples of the Dunning-Kruger effect. Using binary logistic regression analysis, we found that high creative self-concept enabled skilled individuals to assess their creativity accurately, while it caused unskilled individuals to overestimate their creativity. This study identified the Dunning-Kruger effect in creativity while also offering new insights into the underlying mechanism of the Dunning-Kruger effect.

Evaluation of a solar-driven adsorption desalination system for Brazilian semiarid region

In this study, the effect of using a hybrid solar thermal-activated adsorption desalination system for brackish water is evaluated under the climatic conditions of the Brazilian semiarid region. The proposed theoretical model utilizes climatic data from the meteorological station in Campina Grande, PB, and adsorptive kinetics data of Fuji Davison RD 260 silica gel to predict the performance indices of the specific daily water production (SDWP), specific cooling power (SCP), and coefficient of performance (COP) performance coefficients over a characteristic day. The SDWP value of 6.26 m3/ton, SCP ranging from 50 to 300 W/kg, and an average COP of 0.5 were obtained, considering variations in global horizontal irradiance in the ACDS system and transient ambient temperature. It was observed that both the production of desalinated water and the refrigeration effect increase with the rise in daily solar irradiance. The variation in the number of solar collectors used in the system and their optimality, as well as the variation in the salinity index of the feed source, impacted the evaluated performance coefficients.

A new solution for tackling mismatching losses in solar PV array via image encryption

Solar photovoltaic systems may undergo changes in power generation due to environmental factors such as partial shadowing, resulting in losses due to mismatch. This can ultimately lead to a decrease in the efficiency of the system's power conversion. While current solutions are both cost-effective and efficient, there is potential for novel approaches to further enhance system performance by improving consistency, power production, and minimizing mismatch losses. To address these limitations, this paper proposes the utilization of a highly efficient generalized Arnold's cat Map technique, commonly used in the image encryption process, to reconfigure the PV array. The effectiveness of these proposed approaches is evaluated in a MATLAB Simulink environment, specifically for a symmetrical (8x8) PV array, under various benchmark conditions such as Long wide; Short wide, Long Narrow, and Short Narrow shading conditions. The results obtained from these evaluations are then compared to prominent strategies such as Total-cross-tied and the recently reported Chaotic Baker's Map reconfiguration techniques. Furthermore, extensive analysis is conducted using different performance indices to gain a comprehensive understanding of the proposed approaches.

Reinforcement Q-learning algorithm for H∞ tracking control of discrete-time Markov jump systems

In this paper, the H ∞ tracking control problem of linear discrete-time Markov jump systems is studied by using the data-based reinforcement learning method. Specifically, a new performance index function is established by using Markov chain and weighted sum technique, and thus the tracking game algebraic Riccati equation with weight vector and discount factor is obtained. A Q-learning algorithm is proposed to solve the tracking game algebra Riccati equation problem online without knowing the information of the system model. In addition, the convergence analysis of the algorithm is given, and it is proved that the added probing noise will not bias the algorithm. Finally, two simulation examples are given to verify the effectiveness of the proposed algorithm.

Development of a Novel Retinal Surgery Robot Based on Spatial Variable Remote Center-of-Motion Mechanism

Abstract This article reports the design, modeling, and experiments of a novel retinal surgery robot based on spatial variable remote center-of-motion (RCM) mechanism. The general design criteria for parallel mechanisms are proposed, and the planar five-bar mechanisms are evaluated and selected. The planar-spatial evolution process, including the parallel connection of the planar mechanism and the equivalent substitution of joints, is adopted to develop a spatial variable RCM mechanism and then the robot. The mobility and singularity of the robot are analyzed, and the forward/inverse kinematics and workspace are modeled. Dimension optimization is conducted based on a comprehensive performance indicator that characterizes the motion range of linear actuators and the global dexterity performance index of robot. The prototyped robot is fabricated and assembled, and the kinematic calibration is performed. The position error of end-effector is within 34 μm, and both the position error and deviation of the RCM point are within 23 μm. The robot is demonstrated to reach the desired position and execute the RCM motion with high precision simultaneously.

Synthetic Grafts in Anterior Cruciate Ligament Reconstruction Surgery in Professional Female Handball Players-A Viable Option?

Anterior cruciate ligament (ACR) rupture is a frequent injury in professional sports players. We conducted a retrospective cohort study, including 41 professional female handball players, undergoing ACR reconstruction surgery, using a Ligament Advanced Reinforcement System (LARS) graft (n = 12) or a Soft Tissue (ST) graft (n = 29). After return-to-play, the patients were asked to take a survey, reporting subjective and objective performance indexes before the injury and after return-to-play. Time from surgery to first practice and to return-to-play were significantly shorter in the LARS group (3.92 ± 1.14 vs. 6.93 ± 2.19 months, p < 0.001 and 4.71 ± 1.2 vs. 8.81 ± 2.9, respectively). While there was no difference between postoperative mean time on court, number of goals/match, number of matches played at 6 months return-to-play and 50 m, 100 m and gate-to-gate sprint times, there was a significantly greater increase in preoperative times in the ST group than in the LARS group (1.45 ± 1.05 s vs. 0.21 ± 0.58 s slower than preoperatively, p < 0.001 for 50 m; 1.09 ± 0.95 s vs. 0.08 ± 1 s, p = 0.01 for 100 m; 1.66 ± 1 s vs. 0.21 ± 0.66 s for gate-to-gate). In conclusion, LARS grafts provide a faster recovery time and better functional outcome, significantly impacting the performance of professional handball players.

Winners and losers in US marine aquaculture under climate change

Abstract Mariculture will be important to meeting global seafood food demand in the coming decades. Yet, the threat of climate change—such as rising ocean temperatures—on mariculture performance remains uncertain. This is particularly true at small spatial scales relevant to most producers. Additionally, mariculture is often limited by regulations that impose restrictions on production, creating potential hurdles for anticipating and adapting to climate change. We focus on mariculture performance in the United States (U.S.), where state and federal policies and exposure to climate change vary substantially and likely interact. We map a current and future mariculture performance index by combining the first high resolution downscaled (0.083°) climate outputs for U.S. waters, species-specific physiological requirements, and policy restrictions. We find high current performance that will increase under warming oceans, with spatial variation that will amplify existing regional differences. Generally, performance will increase in the north and decrease in the south. While the permitting process is not intentionally climate-forward, permitted species outperformed taxon averages, yet state policies often limit production of seaweeds and finfishes, which perform well. Thus, we sit at a critical juncture where the U.S. could capitalize on its seemingly favorable environmental conditions through re-alignment of regulations to support portfolio diversification to include climate-resilient species.

The Optimal Experimental Design for Exponentiated Frech’et Lifetime Products

In many manufacturing industries, the lifetime performance index CL is utilized to assess the manufacturing process performance for products following some lifetime distributions and subjecting them to progressive type I interval censoring. This paper aims to explore the sampling design required to achieve a specified level of significance and test power for products with lifetimes following the Exponentiated Frech’et distribution. Since lifetime distribution is an asymmetrical probability distribution, this investigation is related to the topic of asymmetrical probability distributions and applications in various fields. When the termination time is fixed but the number of intervals is variable, the optimal number of inspection intervals and sample sizes yielding the minimized total experimental costs are determined and tabulated. When the termination time is varying, the optimal number of inspection intervals, sample sizes, and equal interval lengths achieving the minimum total experimental costs are determined and tabulated. Optimal parameter values are displayed in tabular form for feasible applications for users. Additionally, a practical example is provided to illustrate how this sampling design can be used to collect data by using the optimal setup of parameters, followed by a testing procedure to assess the capability of the production process.

Identification of urban street trees for green belt development for optimizing pollution mitigation in Delhi, India.

The current study evaluated the effects of air pollution on selected street trees in the National Capital Territory during the pre- and post-monsoon seasons to identify the optimally suitable tree for green belt development in Delhi. The identification was performed by measuring the air pollution tolerance index (APTI), anticipated performance index (API), dust-capturing capacity (DCC) and proline content on the trees. The APTI of street trees of Delhi varied significantly among different tree species (F11,88.91 = 47.18, p < 0.05), experimental sites (F3,12.52 = 6.65, p < 0.001) and between seasons (F1,31.12 = 16.51, p < 0.001), emphasizing the relationships between trees and other types of variables such as the climate and level of pollution, among other factors. This variability emphasizes the need to choose trees to use for urban greening in the improvement of air quality in different environments within cities. Ascorbic acid (AA) concentration and relative water content (RWC) had a strong influence on APTI with an extremely significant moderate positive correlation between AA concentration and APTI (r = 0.65, p < 0.001) along with RWC and APTI (r = 0.52, p < 0.001), indicating that higher levels of AA concentration and RWC are linked to increased air pollution tolerance. The PCA bi-plot indicates AA has poor positive loading coefficients with PC1 explaining 29.49% of the total variance in the dataset. The highest APTI was recorded in Azadirachta indica (22.01), Leucaena leucocephala (20.65), Morus alba (20.62), Ficus religiosa (20.61) and Ficus benghalensis (19.61), irrespective of sites and seasons. Similarly, based on API grading, F. religiosa and F. benghalensis were identified as excellent API grade 6 (81-90%), A. indica and Alstonia scholaris as very good API grade 5 (71-80%), M. alba, Pongamia pinnata and Monoon longifolium as good API grade 4 (61-70%) and Plumeria alba as moderate API grade 3 (51-60%) in different streets of Delhi. As these plants are indigenous to the region and hold significant socio-economic and aesthetic significance in Indian societies, they are advisable for avenue plantations as part of various government initiatives to support environmental sustainability.

EFFECT OF FREEZE-DRIED SUPER RED DRAGON FRUIT ANTHOCYANIN DISCLOSING SOLUTION ON DENTAL PLAQUE INDEX

Background: Accumulation of dental plaque can cause of dental and oral health problems such as caries and periodontitis. Dental plaque is colorless so it is difficult to see visually. Super red dragon fruit can be an alternative disclosing solution because it contains. Objectives: The purpose of this research was to determine the content and the effect of anthocyanin disclosing solution freeze dry super red dragon fruit on dental plaque index. Methods: This research is a type of the Experimental Laboratory and Quasi Experimental design research with post-test control group design method. Thirty samples were used and there were three treatment groups: the application of aquadest, super red dragon fruit disclosing solution, and synthetic disclosing solution. Super red dragon fruit freeze dry was tested for antioxidants and tested total anthocyanin levels using the pH difference method at Unjani Pharmaceutical Laboratory. Research on plaque index examination was carried out in the Integrated Dentistry Laboratory Unjani. Dental plaque index assessment is measured using PHPI (Patient Hygiene Performance Index) method. Data were analyzed using Kruskall Wallis and Mann-Whitney tests (p&lt;0.05). Results: The results showed an anthocyanin content of 9.0764 mg/100 g and a significant difference in the anthocyanin disclosing solution freeze dry treatment of super red dragon fruit on the dental plaque index with a value of p = 0.000. Conclusion: In conclusion this research indicates that the freeze-dried super red dragon fruit disclosing solution contains anthocyanin and has an effect on the dental plaque index. This shows the potential of anthocyanin disclosing solution freeze dry super red dragon fruit can be used to detect and control dental plaque, but further research is needed to determine the length of time attached to anthocyanin disclosing solution super red dragon fruit to the tooth surface

Aerothermal performance of two-pass channel with tilted grater-baffles

Aerothermal performances of four two-pass channels enhanced by tilted 90° or 60° grater-baffles with one- or two-rows of perforation are studied. Aerothermal impacts of baffle attack angle and perforation row-number on Nusselt number (Nu) distribution, friction factor (f), and aerothermal performance index (API) are cross examined. Cold streams from duct core are confluent in oval dimples to eject through inclined grater-baffle as impinging jets that diminish boundary layers at stagnation spots and augment core-to-wall mixings, leading to significant heat transfer enhancements (HTE). Heat transfer data reveals that the HTE impact increases and decreases with perforation-row number and Reynolds number (Re) respectively. With the sectional vortical flows tripped by the 60° grater-baffles, both Nu and f are raised from those with the 90° baffles. The Nusselt numbers and friction factors for the two-pass channel enhanced by the inclined 60° baffles with two perforation rows are elevated to 4.64–4.95and 33.67–34.16 times Dittus-Boelter correlation and Blasius equation levels, giving rise to the API in the range of 1.67 and 1.43 at Re between 5000 and 15,000. Empirical correlations of regional average Nu and channel average f for the four two-pass baffled channels are devised to assist engineering applications.

Assessment of short and long-term pozzolanic activity of natural pozzolans using machine learning approaches

This investigation introduces the optimal performance models for predicting the compressive strength (CS) and pozzolanic activity index (PAI) by comparing the machine learning models. The machine learning models, i.e., multilinear regression (MLR), support vector machine (SVM), gaussian process regression (GPR), decision tree (DT), random forest (RF), and gene expression programming (GEP) have been trained (TRN) and tested (TST) by 28 and 7 data points. For the first time, the SiO2, Al2O3, Fe2O3, SiO2 +Al2O3 +Fe2O3, reactive SiO2, Blaine specific surface area, and specific gravity have been used as input variables to compute the CS, and 28 days PAI (28PAI), and 90 days PAI (90PAI) of the natural pozzolans. The multicollinearity analysis showed the SiO2, Al2O3, Fe2O3, SiO2 +Al2O3 +Fe2O3, reactive SiO2, and specific gravity have problematic multicollinearity (variance inflation factor – VIF > 10). Therefore, the root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (R), performance index (PI), and variance accounted for (VAF) metrics have been implemented to evaluate the model's performance and multicollinearity impact. From the comparison of models, it has been recorded that model GPR outperformed the MLR, SVM, DT, RF, and GEP models in predicting CS (PI = 1.29, VAF = 71.31, R = 0.8473, MAE = 0.9390 MPa), 28PAI (PI = 1.87, VAF = 94.88, R = 0.9744, MAE = 0.7295 %), and 90PAI (PI = 1.72, VAF = 88.11, R = 0.9393, MAE = 1.2444 %) in the TST phase, close to ideal values. The score, generalizability. Wilcoxon test, uncertainty analysis, Anderson-daring test, and accuracy metrics have confirmed the superiority of GPR models in predicting CS, 28PAI, and 90PAI of natural pozzolans.

Technique description and outcome evaluation of Thoroughbred racehorses following soft palate thermocautery performed under standing sedation.

Palatal dysfunction (PD), which encompasses palatal instability (PI) and intermittent dorsal displacement of the soft palate, is the most common performance-limiting upper respiratory tract obstruction in young Thoroughbred racehorses. Soft palate thermocautery (SPT) performed under general anaesthesia is a routinely performed procedure for PD in some countries, but the procedure for and outcome of SPT performed under standing sedation has not been published. (1) To describe a technique for SPT performed under standing sedation; and (2) to assess post-operative performance in horses compared to controls using the Racing Post rating (RPR), British Horseracing Authority official rating (OR), Performance Index and Earnings. Retrospective case series. Medical records were reviewed for all horses that had SPT performed under standing sedation following topical and local infusion of lidocaine hydrochloride into the rostral soft palate, and that were identified to have PI by overground endoscopy. Two matched controls were identified for each case. The median RPR, OR, Performance Index and Earnings for the three pre-operative and three post-operative races were compared. No significant differences were identified between the SPT (n=23) and Control groups (n=46) for baseline characteristics or outcomes. Retrospective study design, small sample size. No significant differences in racing performance were identified between horses that had SPT performed under standing sedation and controls.