Variation In Performance Research Articles

Multi-omics dataset of individual variations in growth performance of large yellow croaker

Large yellow croaker (Larimichthys crocea) is a highly economically important marine fish species in China. However, substantial individual variations in growth performance have emerged as a limiting factor for the sustainable development of the large yellow croaker industry. Gut microbiota plays a crucial role in fish growth and development by regulating metabolic processes. To explore these dynamics, we employed metagenomics, transcriptomics, and untargeted metabolomics to comprehensively analyze the structure of the intestinal microbiome and its relationship with intestinal metabolism and host gene expression. We constructed association models for “gut microbiota–differentially expressed genes”, “differentially expressed genes–metabolites,” and “gut microbiota–metabolites.” Sequencing data and LC–MS/MS raw data have been deposited in NCBI and MetaboLights databases for public access. Our findings offer critical insights into the molecular mechanisms underlying growth variations in L. crocea and provide valuable data for the selective breeding of improved strains.

Preserving the Past: A Dynamic Analysis of Heritage Tourism and Land Conservation in Mamluk Cairo

Historic urban cities face increasing pressure from tourism, necessitating sophisticated approaches to visitor management that protect both heritage values and local communities. The current study develops new sustainable metrics—sustainable visitor capacity (SVC) and Sustainable Visitation Index (SVI)—to provide a multifaceted assessment of heritage destination management beyond simple visitor volume calculations. The SVC considers operating hours, site capacity, and walking time, while the SVI holistically evaluates time efficiency, spatial distribution, and physical comfort. Applying these metrics to seven routes through the historic Mamluk monuments revealed significant variations in sustainability performance, with SVI scores ranging from 48.9 at Al-Ṣalῑba/Al-Sayyida Zaynab Streets to 92.8 at Northern Al-Mu’izz Street. The findings demonstrate that while the recommended daily visitor capacity ranges from 1286 to 2182 visitors across different routes, actual visitation frequently exceeds these thresholds, particularly in commercial zones. Geographic analyses and on-site studies identified the integration of tourist activities with commercial, residential, and religious uses as a critical factor contributing to overcrowding, especially evident in areas like Al-Ṣalῑba Street, where low SVI scores reflect challenges with unorganized markets and local congestion. The study offers site-specific recommendations for heritage managers, focusing on dynamic visitor management systems and zoning strategies that consider the dual function of these historic corridors as both tourist attractions and vital local thoroughfares. This research provides heritage managers with practical tools to quantify and enhance the sustainability of visitor experiences while preserving site integrity within complex urban heritage contexts.

Age-related biomechanical variations in vertical jumping and sprinting performance among basketball players

IntroductionThis study aims to investigate age-related differences in physical performance metrics, specifically vertical jumping and sprinting capabilities, between young (average age 12.5) and senior (average age 23.2) male basketball players.MethodsPerformance metrics were assessed through standardised tests measuring jump height and sprint times, alongside force production during eccentric and concentric phases of jumping movement.ResultsKey findings show that senior players outperform younger athletes in both sprint times and jump heights, attributed to greater physical maturation and neuromuscular development. However, contraction times and phase durations were similar across both age groups, indicating that strength improvements do not affect fundamental movement timing.DiscussionThese results highlight the importance of age-specific training programs that focus on developing explosive power for younger players and optimising performance while minimising injury risk for seniors. The study provides valuable insights and recommendations for tailoring training strategies to athletes' developmental stages and suggests that further research is needed to explore effective interventions for enhancing physical performance across the lifespan.

Surface and Electrochemical Performance Variations of 2205 Duplex Stainless Steel in Multistep Surface Processing

Surface and Electrochemical Performance Variations of 2205 Duplex Stainless Steel in Multistep Surface Processing

Is there any skill in daily global precipitation forecasts over the Maritime Continent?

AbstractThe presence of and spatial variation in daily precipitation forecast skill from a global deterministic Numerical Weather Prediction (NWP) model is explored over the Maritime Continent (MC). Location specificity and the variation of forecast performance with topographic height were of primary interest. The localised Fractions Skill Score (LFSS) was used alongside one well‐known derivative, the Skilful Spatial Scale (SSS). In this study a new temporal factorisation, the Lead Time Potential (LTP), is introduced and applied. It was found that whilst scores can be high, these do not necessarily imply useful skill. This is because of the impact of observed frequency of occurrence or base rate f in the 0.5 + f/2 useful skill criterion which underpins the SSS and LTP. For regions with high rainfall, such as the MC, it is not uncommon for f → 1, especially for modest thresholds, such that 0.5 + f/2 → 1. This means that even a near‐perfect score is not associated with any useful skill. Thus, if f/2 is ignored, the scales with useful skill are either considered as being smaller than they are, or worse, suggesting there is useful skill when there is none. The new LTP identifies many locations where useful skill is present up to seven days ahead. Typhoons are associated with some of the highest scores and skill, whereas persistence over land can be locally as skilful as the model forecast, though model forecasts show larger regions with better (lower) SSS and better (higher) LTP.

Time-of-day effects on physical performance and perceptual responses in Brazilian Jiu-Jitsu athletes

ABSTRACT This study investigated how the time of day affects physical performance and perceptual responses in Brazilian Jiu-Jitsu (BJJ) athletes. Given the significance of circadian rhythms on athletic capabilities, we aimed to determine whether performance variations occur across different times of the day (morning, 10:00–11:00h; afternoon, 14:00–15:00h; and evening, 18:00–19:00h) and if these effects differ by sex. In total, 23 BJJ athletes (9 females, 14 males) participated in this study. The athletes performed physical tests including the maximal isometric handgrip strength test (HGS), Kimono Grip Strength Endurance Test (KGST), and a BJJ-specific test (BJJST) in the morning, afternoon, and evening. Perceptual responses (RPE) were also collected before the BJJST. Results showed enhanced physical performance in the evening for most tests, including increased HGS and superior performance in the KGST and BJJST for both sexes (p < 0.05). No significant differences were observed in perceptual responses (RPE) or between sexes (p > 0.05). We conclude that BJJ athletes generally perform better in the evening compared to other times of the day, with notable improvements in HSG and specific BJJ tests. The study highlights the importance of aligning training schedules with an athlete’s circadian rhythm to optimize performance, leading to more efficient training sessions and improved long-term performance outcomes.

Profit and Reliability Analysis of a Gas Production Unit with the Concept of Optimal Age Replacement Policy: A Copula Approach

Abstract This paper presents a comparative study of reliability analysis of a gas production plant, before and after applying optimal age replacement policy for a specific machine. The gas production plant has six machines connected in the series configuration a sulfur (S) shaft, coal pit, reaction furnace, sulfur separation machine, adiabatic reactor, and cooling machine. Here, the optimal age replacement policy has been applied to the cooling machine as this machine is working under a wear-out period, i.e., it has completed its prescribed age (say T) and is still operational. Two different situations have been discussed to analyze the performance variation of the system (i) when the model is working with high risk because the cooling machine is operational even after completion of its prescribed age (ii) when the old cooling machine is replaced by a new one after completing the age, T. The failure of any machine can cause the model failure. Additionally, a situation of employee walkout is also considered a responsible factor for model failure. Supplementary variable technique and copula methodology have been applied to solve the Markov model.

A standardised comparison of chest and percutaneous drainage catheters to evaluate the applicability of the ‘French’ sizing units

A variety of medical specialities undertake percutaneous drainage but understanding of device performance outside radiology is often limited. Furthermore, the current catheter sizing using the “French” measurement of outer diameter is unhelpful; it does not reflect the internal diameter and gives no information on flow rate. To illustrate this and to improve catheter selection, notably for chest drainage, we assessed the variation of drain performance under standardised conditions. Internal diameter and flow rates of 6Fr.-12Fr. drainage catheters from 8 manufacturers were tested to ISO 10555-1 standard: Internal diameters were measured with Meyer calibrated pin-gauges. Flow rates were calculated over a period of 30s after achieving steady state. Evaluation demonstrated a wide range of internal diameters for the 6Fr., 8Fr., 10Fr. and 12Fr. catheters. Mean measurements were 1.49 mm (SD:0.07), 1.90 mm (SD:0.10), 2.43 mm (SD:0.11) and 2.64 mm (SD:0.03) respectively. Mean flow rates were 128 mL/min (SD:37.6), 207 mL/min (SD: 55.1), 291 mL/min (SD:36.7) and 303 mL/min (SD:20.2) respectively. There was such variance that there was overlap between catheters of different size: thin-walled 10Fr. drains performed better than 12Fr. “Seldinger” chest drains. Better understanding of drain characteristics and better declaration of performance data by manufacturers are required to allow optimum drain choice for individual patients and optimum outcomes.

Comparing carbon agronomic footprint and sequestration in Central American coffee agroforestry systems and assessing trade-offs with economic returns.

Agricultural systems are both emitters of greenhouse gases and have the potential to sequester carbon, especially agroforestry systems. Coffee agroforestry systems offer a wide range of intensities of use of agricultural inputs and densities and management of shade trees. We assessed the agronomic carbon footprint (up to farm gate) and modelled the carbon sequestration of a range of coffee agroforestry systems across 180 farms in Costa Rica and Guatemala. The agronomic carbon footprint included upstream, direct and indirect processes associated with chemical and organic fertiliser use and energy consumption (excluding processing of cherries). Carbon sequestration was modelled using the CAF2021 model a processed based model of the C, N and water dynamics specifically designed for coffee agroforestry systems. The carbon footprint per kg of coffee cherries was significantly and positively related to the level of nitrogen inputs. Modelled changes in C stocks i.e. carbon sequestration was significantly and positively related to the Leaf Area Index (LAI) of the trees, and the levels of nitrogen inputs. Increasing nitrogen inputs per hectare was positively associated with emission per kg as nitrogen efficiency varied significantly across the sample. The net carbon balance, defined as sequestration minus CO2e emissions was also positively related to shade tree LAI but negatively with yield and N application. Carbon positive farms were characterized by shade cover over 60%, but low yields and low net income. However, farms that were close to carbon neutral had higher yields and higher net income, with shade levels of about 50% cover, while carbon negative farms which had shade cover averaging 40%. Nevertheless, farms showed a large variation in performance with all combinations of positive and negative for carbon balance and net income. However, among the farms with a positive net income, those with a positive carbon balance had a significantly lower net income than those that were carbon negative (i.e. net emitters). This confirms the economic trade-off for farmers seeking to maximise these two goals. If farmers are expected to generate positive carbon balances and potentially to offset emissions higher in the supply chain, then they should receive economic support to compensate continued on-farm carbon accumulation.

Microstructural Assessment of Molybdenum Disulfide Coatings Using Nanoindentation Hardness.

MoS2 coatings are used extensively in aerospace and defense applications due to their ultralow friction and high wear resistance. Burnished and resin-bonded MoS2 coatings are commonly used in these applications due to simplicity in deposition and history of use, despite issues with consistency in coating properties and performance. Physical vapor deposition (PVD) of MoS2 thin films has emerged as a process alternative in the past 50 years, promising far greater control over film structure and composition but at a greater cost. Despite PVD's benefits, hesitance to adoption persists in high-consequence applications, not only due to increased costs but variability in resulting coating properties. These variations in properties and subsequent performance are in part due to the complexity of the PVD process and the sensitive interplay between coating process-structure-property relationships. This work aims to demystify the remaining uncertainties of the process-structure-property relationships in PVD MoS2. The microstructure and mechanical and tribological properties of 61 different PVD pure MoS2 coatings are examined herein. Emphasis has been placed on developing performance-based (i.e., hardness, modulus) metrics that can assess microstructural changes (density, orientation, and crystallinity) and be utilized to accelerate process development and coating optimization. Relationships established within suggest that nanoindentation hardness can be used to infer coating performance (i.e., wear rate) and properties (i.e., density, crystalline texture, and stoichiometry). Furthermore, this work demonstrates that PVD MoS2 coatings close to the theoretical density of MoS2 consistently have the best tribological performance and can be reliably identified by their hardness.

Machine learning-based 28-day mortality prediction model for elderly neurocritically Ill patients.

The growing population of elderly neurocritically ill patients highlights the need for effective prognosis prediction tools. This study aims to develop and validate machine learning (ML) models for predicting 28-day mortality in intensive care units (ICUs). Data were extracted from the Medical Information Mart for Intensive Care IV(MIMIC-IV) database, focusing on elderly neurocritical ill patients with ICU stays ≥ 24 h. The cohort was split into 70 % for training and 30 % for internal validation. We analyzed 58 variables, including demographics, vital signs, medications, lab results, comorbidities, and medical scores, using Lasso regression to identify predictors of 28-day mortality. Seven ML algorithms were evaluated, and the best model was validated with data from Guizhou Medical University Affiliated Hospital. A log-rank test was used to assess survival differences in Kaplan-Meier curves. Shapley Additive Explanations (SHAP) were used to interpret the best model, while subgroup analysis identified variations in model performance across different populations. The study included 1,773 elderly neurocritically ill patients, with a 28-day mortality rate of 28.6 %. The Light Gradient Boosting Machine (LightGBM) outperformed other models, achieving an area under the curve (AUC) of 0.896 in internal validation and 0.812 in external validation. Kaplan-Meier analysis showed that higher LightGBM prediction scores correlated with lower survival probabilities. Key predictors identified through SHAP analysis included partial pressure of arterial carbon dioxide (PaCO2), Acute physiology and chronic health evaluation II (APACHE II), white blood cell count, age, and lactate. The LightGBM model demonstrated consistent performance across various subgroups. The LightGBM model effectively predicts 28-day mortality risk in elderly neurocritically ill patients, aiding clinicians in management and resource allocation. Its reliable performance across diverse subgroups underscores its clinical utility.

Crucial impact of spectrum calculation on energy and daylighting performance of glazing windows

The rapid advancement of spectrally selective materials has enabled the development of smart windows that can regulate different bands of solar radiation. However, existing methods for calculating spectral properties vary, leading to inconsistent results when evaluating their light-electricity-heat-color performance. Therefore, this paper presents five methods for calculating window spectral properties, intending to compare and identify the most effective approach for assessing building thermal performance, energy efficiency, and daylighting. The methods focus primarily on the solar spectrum input and the glazing spectrum response. The solar spectrum inputs include the Beijing local solar spectrum, ASTM G173-03, and ISO 9845 (methods S1 to S3), and the glazing spectrum response methods differ based on whether they account for spectral selectivity and the choice of spectral weighting functions (methods S3 to S5). The findings reveal that variations in solar spectrum input have a minimal effect on window performance, while differences in glazing spectral response calculations significantly impact results. It is particularly evident in thermochromic windows, where discrepancies in energy efficiency, specifically in lighting load, can reach up to 67.21 %, and variations in dynamic daylighting performance, specifically in Useful Daylight Illuminance (UDI) below 500 lx, can be as high as 28.27 %. To provide more accurate assessment results of glazing windows, this study recommends using the spectral calculation method S1, which incorporates the local solar spectrum and applies the standard luminous efficiency function to the glazing spectrum response. This paper highlights that further refinement of spectral calculation methods will enhance their utility for performance evaluation and guide the reverse design of innovative window features.

Feed efficiency and resilience in dairy ewes subjected to a nutritional challenge.

It is currently uncertain how selection of more efficient animals might impact other traits such as resilience (which, in this context, is defined as the ability of an animal to sustain or revert quickly to its previous production level and health status after a disturbance), especially in small ruminants. However, improving, or at least maintaining, resilience is of utmost importance to ensure livestock production in the face of external perturbances, which are expected to become more prevalent in the near future due to climate change and global instability. This study was conducted to investigate whether a nutritional challenge consisting of animals receiving only 70% of their voluntary feed intake (DMI) for 26 d, might differentially affect the response of high- and low-feed efficiency (FE) sheep. To meet this aim, residual feed intake (RFI), as a proxy of FE, was calculated in 40 lactating ewes fed a total mixed ration ad libitum. Using the RFI values, the ewes with the highest (H-FE; n = 8) and the lowest (L-FE; n = 8) FE were selected and subjected to the nutritional challenge. After the feed restriction, all sheep were again fed ad libitum for a further 25 d. Temporal patterns of variation in animal performance, ruminal fermentation and blood and milk metabolites in response to, and recovery from, the underfeeding were examined in H-FE versus L-FE. More efficient ewes (H-FE) tended to eat less than less efficient ewes (L-FE) for the same level of production. Linear regressions for DMI and milk yield data showed that time-series response to the challenge was comparable in L-FE and H-FE. Despite temporal changes due to underfeeding, both FE divergent groups displayed a similar response to, and recovery from, the challenge with no significant differences in the temporal patterns of variation of the parameters analyzed, except for a tendency to higher plasma glucose in the L-FE ewes. These results challenge the general hypothesis that more efficient animals would be less resilient, but further research is still needed on the relationship and possible trade-offs between high efficiency and resilience.

Evaluation of artificial intelligence-based autosegmentation for a high-performance cone-beam computed tomography imaging system in the pelvic region.

A novel ring-gantry cone-beam computed tomography (CBCT) imaging system shows improved image quality compared to its conventional version, but its effect on autosegmentation is unknown. This study evaluates the impact of this high-performance CBCT on autosegmentation performance, inter-observer variability, contour correction times and delineation confidence, compared to the conventional CBCT. Twenty prostate cancer patients were enrolled in this prospective clinical study. Per patient, one pair of high-performance CBCT and conventional CBCT scans was included. Three observers manually corrected contours generated by the artificial intelligence (AI) model for prostate, seminal vesicles, bladder, rectum and bowel. Differences between AI-based and manual corrected contours were quantified using Dice Similarity Coefficient (DSC) and 95th percentile of Hausdorff distance (HD95). Autosegmentation performance and interobserver variation were compared using a random effects model; correction times and confidence scores using a paired t-test and Wilcoxon signed-rank test, respectively. Autosegmentation performance showed small, but statistically insignificant differences. Interobserver variability, assessed by the intraclass correlation coefficient, was significantly different across most organs, but these were considered clinically irrelevant (maximum difference=0.08). Mean contour correction times were similar for both CBCT systems (11:03 versus 11:12min; p=0.66). Delineation confidence scores were significantly higher with the high-performance CBCT scans for prostate, seminal vesicles and rectum (4.5 versus 3.5, 4.3 versus 3.5, 4.8 versus 4.3; all p<0.001). The high-performance CBCT did not (clinically) improve autosegmentation performance, inter-observer variability or contour correction time compared to conventional CBCT. However, it clearly enhanced user confidence in organ delineation for prostate, seminal vesicles and rectum.

British Society of Gastroenterology National Evaluation of Colonoscopy Quality: Findings from the National Endoscopy Database.

Analysis of national colonoscopy quality using automatically uploaded data from a national database, including exploring performance variation. Data on all colonoscopies performed in the UK 01/03/2019-29/02/2020 and recorded in the National Endoscopy Database were analysed. Unadjusted key performance indicators were calculated and proportions of endoscopists achieving national standards were determined. Regression models tested associations between case-mix (patient age, sex, indication) and colonoscopy quality. Endoscopist factors (specialty, annual procedure numbers, withdrawal times) were added to case-mix adjusted models, with results presented as adjusted odds ratios (aOR) with 95% confidence intervals. 592,764 colonoscopies were analysed. Rates of caecal intubation (93.5%, 95% CI 93.4-93.6), polyp detection (37.3%, 95% CI 37.2-37.4), and moderate/severe patient discomfort (4.8%, 95% CI 4.7-4.8) had all improved since the 2011 national audit (p<0.01 for all). 63.9% of endoscopists met all minimum standards for caecal intubation, polyp detection, and discomfort, but only 46.4% did so among those performing fewer than 100 colonoscopies annually. Overall, surgeons recorded lower caecal intubation and polyp detection rates than gastroenterologists (p<0.01); however, those performing over 100 annual colonoscopies achieved KPIs similar to gastroenterologists. Endoscopists with longer withdrawal times were almost twice as likely to identify polyps (aOR 1.9, 95% CI 1.7-2.2) and detected more large polyps (aOR 1.6, 95% CI 1.3-2.0). UK colonoscopy quality has improved, yet almost 40% of endoscopists still fell short of minimum standards. Variation in quality was strongly associated with endoscopist procedure volumes; mandating minimum annual procedures and emphasising longer withdrawal times could improve overall quality.

Evaluating the Flexural Strengthening Performance of Concrete Beams Reinforced with Fiber-Enhanced Spray Materials

This study examined the compressive and tensile strengths of spray-applied strengthening materials and the flexural performance of concrete beams reinforced using these materials to assess the effectiveness of spray-based reinforcement techniques. The findings revealed substantial variations in performance influenced by fiber type, dosage, and casting method. Key factors affecting performance included fiber dispersion and bond strength within the spray-applied layer. The PE (polyethylene) fibers exhibited stable performance, while PVA (polyvinyl alcohol) fibers experienced significant degradation due to moisture absorption. These results offer valuable insights for optimizing the design and application of fiber-reinforced concrete, advancing repair and reinforcement methods in the construction sector.

IoT-Based Energy Meter for Remote Monitoring and Managements of Power Consumption

Real-time monitoring of several parameters such as the current and the rated power is provided by this design. Users become more conscious of their consumption with specifications based on recorded data using this design. Additionally, it enables users to quickly identify abnormal issues such as spikes that result in device failure. Also, this design offers remote access to received data by cloud platforms with mobile applications. This study evaluates the performance of an Energy Monitoring distributed among 17 electrical devices in three houses over a period of 30 days. The design demonstrated high accuracy and minimal error in its readings for the related devices with effectively capturing detailed energy consumption values. Based on results, the analysis of power and current efficiency at different power levels reveals notable performance variations. House 1 runs efficiently at low power levels; yet, efficiency levels indicate higher power levels with (96% ,97%) power and current reading efficiency respectively. House 2's efficiency at medium power displays more pronounced inefficiencies than House 1's, although it still keeps its current efficiency constant with (90% ,97%) power and current reading efficiency respectively. House 3 demonstrates that it is ideally adapted to handle high power levels, exhibiting the highest overall efficiency in high power conditions with (97% ,98%) power and current reading efficiency respectively. The extra power in every case shows how well help users to use this design with the extra reading power for other devices or reducing house power to reduce in electrical bill cost.

Systematic benchmarking of deep-learning methods for tertiary RNA structure prediction.

The 3D structure of RNA critically influences its functionality, and understanding this structure is vital for deciphering RNA biology. Experimental methods for determining RNA structures are labour-intensive, expensive, and time-consuming. Computational approaches have emerged as valuable tools, leveraging physics-based-principles and machine learning to predict RNA structures rapidly. Despite advancements, the accuracy of computational methods remains modest, especially when compared to protein structure prediction. Deep learning methods, while successful in protein structure prediction, have shown some promise for RNA structure prediction as well, but face unique challenges. This study systematically benchmarks state-of-the-art deep learning methods for RNA structure prediction across diverse datasets. Our aim is to identify factors influencing performance variation, such as RNA family diversity, sequence length, RNA type, multiple sequence alignment (MSA) quality, and deep learning model architecture. We show that generally ML-based methods perform much better than non-ML methods on most RNA targets, although the performance difference isn't substantial when working with unseen novel or synthetic RNAs. The quality of the MSA and secondary structure prediction both play an important role and most methods aren't able to predict non-Watson-Crick pairs in the RNAs. Overall among the automated 3D RNA structure prediction methods, DeepFoldRNA has the best prediction results followed by DRFold as the second best method. Finally, we also suggest possible mitigations to improve the quality of the prediction for future method development.

Evaluating the performance of the EUMETSAT H SAF H35 fractional snow-covered area product over the Tibetan Plateau

Background and aims This study evaluates the performance of the H35 fractional snow-covered area (fSCA) product over the Tibetan Plateau (TP) from May 2019 to December 2021. The H35 product, derived from AVHRR satellite data, provides daily fSCA estimates at a resolution of 0.01°. The aim of this work is to assess the accuracy and reliability of this product in capturing snow cover dynamics over a significant period. Methods Validation of the H35 product uses a high-resolution, cloud-free snow cover dataset derived from long-term MODIS data, ensuring temporal consistency and high accuracy. Statistical metrics, including probability of detection (POD), false alarm ratio (FAR), and accuracy (ACC), were employed to assess the product's performance. Results The results reveal seasonal variations in performance, with POD values reaching a peak of 0.91 during the winter months. The FAR shows an inverse trend, while the overall ACC values remain consistently high, indicating reliable performance across the study period. Conclusions This study contributes to the understanding of snow cover dynamics over the TP and highlights the significance of validating satellite-derived products for hydrological studies. The consistently high accuracy of the H35 product underscores its potential for use in monitoring snow cover in the region.

Cost-Effective Laser Powder Bed Fusion of Ti-6Al-4V Grade 5: The Effect of Expanding Powder Size Distribution on Mechanical Performance

This study aims to assess the feasibility of expanding the powder size distribution (PSD) of Ti-6Al-4V grade 5 powder for LPBF to achieve cost reduction. Parameter optimization to minimize the degradation of mechanical properties due to the expanded particle size distribution was conducted. Mechanical tests for specimens built using optimized parameters revealed minor reductions in strength: 3.9% in tensile yield strength, 1.1% in compressive strength, 5.5% in shear strength, and 4.5% in bearing yield strength—all of which complied with MMPDS standards. Statistical analysis, using the Anderson–Darling test, demonstrated stable mechanical performance and minimal variation between the original and expanded PSDs. These results highlight the potential of an expanded PSD to achieve cost reductions while maintaining compliance with industry standards, offering a practical solution for LPBF applications in cost-sensitive and high-performance industries.