Validation Procedure Research Articles

Prediction of Snatch and Clean and Jerk Performance From Physical Performance Measures in Elite Male Weightlifters.

Sandau, I and Kipp, K. Prediction of snatch and clean and jerk performance from physical performance measures in elite male weightlifters. J Strength Cond Res XX(X): 000-000, 2024-This study aimed to build a valid model to predict maximal weightlifting competition performance using ordinary least squares linear regression (OLR) and penalized (Ridge) linear regression (penLR) in 29 elite male weightlifters. One repetition maximum (1RM) or 3RM test results of assistant exercises were used as predictors. Maximal performance data of competition and assistant exercises were collected during a macrocycle in preparation for a competition. One repetition maximum snatch pull, 3RM back squat, 1RM overhead press, and body mass were used to predict the 1RM snatch; and 1RM clean pull, 3RM front squat, 1RM overhead press, and body mass were used to predict the 1RM clean and jerk. Model validation was performed using cross-validation (CV) and external validation (EV; random unknown dataset) for the coefficient of determination and root mean square error (RMSE). Results revealed that penLR models present more plausible output in the relative importance of highly correlated predictors. Of note, the 1RM snatch pull is the most relevant predictor for the 1RM snatch, whereas the 1RM clean pull and 3RM front squat are the most relevant predictors for the 1RM clean and jerk. Validation-based absolute predictive error (RMSE) ranged between ≈ 3-9 kg for the 1RM snatch and ≈ 3-7 kg for the 1RM clean and jerk, depending on the model (OLR vs. penLR) and validation procedure (CV vs. EV). In conclusion, penLR models should be used over OLR models to analyze highly correlated predictors because of more plausible model coefficients and smaller predictive errors.

Handshake of deep eutectic solvent and ionic liquid: Two liquid-liquid microextraction procedures for plant analysis

Plants are subjects of interest due to the secondary metabolites in their extracts which are promising as new pharmaceuticals. Phytochemistry do not have united system of sample preparation or analysis still due to different structure of plant cells, wide broad range of chemical properties and concentrations of bioactive compounds. Such challenges can be addressed in a green chemistry manner using new approaches through smart materials in routine monitoring and researches. Liquid smart materials, such as ionic liquids (ILs) and deep eutectic solvents (DESs) are attractive due to flexible properties, lots of extraction approaches, recycle potential, and direct compatibility with powerful analytical methods.In this study DES-based microextraction procedure with pH-switching was developed. Four choline chloride DESs were suggested as selective extraction phases for polar compounds from acetonitrile extracts. Method was successfully tested on four plants (Iris sibirica L., Hypericum perforatum L., Scutellaria baicalensis G, Citrus reticulata B.). Developed procedure was optimized and validated for the choline chloride – urea (1:2 mol/mol) DES that demonstrated better results in extraction. LOD for rutin was found as 0.05 mg ml−1. For low-polar compound, imidazolium ionic liquid-based dispersive liquid-liquid microextraction procedure was developed. 1-hexyl-3-methylimidazolium salts have demonstrated desired selectivity. The main factors influencing the extraction efficiency have been identified and optimized by design of experiment on two model plants (Iris sibirica L. and Scutellaria baicalensis G.). Validation procedures were done for thymol. LOD for thymol was found as 0.021 mg ml−1.The methods were compared with each other and traditional methanol extraction. The selectivity of the smart materials supports each other, usage of such extraction phases provides same or better results as obtained with methanol.

Biological Patch in the Repair of Rotator Cuff Tears: Functional and Clinical Evaluation of Twenty-Three Cases with a Mean Follow-Up of Six Years.

Background: Rotator cuff (RC) repair leads to less than optimal results when dealing with massive lesions, so the use of scaffolds as biological support has been proposed to improve RC repair site biology. The present study aims to evaluate the clinical and radiographical outcomes of a series of patients suffering from massive or irreparable RC tears treated with patch (porcine or human scaffolds) repair (augmentation or bridging). Methods: Twenty-three patients with a minimum follow-up of 24 months were subjectively, clinically, and radiographically assessed before and after surgery. Three different patient-related outcome measurements (PROMs) (American Shoulder and Elbow Surgeons score, Constant score, visual analog scale) were used for the subjective and clinical evaluation, while plain radiographs and magnetic resonance imaging where employed for radiographical follow-up. Results: Regardless of the technique (augmentation or bridging) or type of scaffold (porcine or human) employed, at follow-up, all patients experienced a statistically significant improvement in all PROMs and clinically. Conclusions: Patch repair represents a valid salvage procedure in massive or irreparable RC tears, improving the quality of life and eventually delaying the need for prosthetic replacement.

Validation and Verification of Computational Model for the Numerical Simulation of the Operational Principle of a Submerged Horizontal Plate Device

This study describes the validation and verification of a two-dimensional numerical wave channel with a Submerged Horizontal Plate (SHP). The SHP is a fixed, submerged structure with a dual function: it acts as a breakwater and as a wave energy converter. To carry out the validation and verification procedures for the computational modeling, experimental and numerical results obtained from the literature were used. A relative error of 2.14% for the maximum axial velocity below the SHP was obtained in the validation, while an average absolute error of 0.0043 m/s for the axial velocity variation below the SHP was identified in the verification. Therefore, it can be inferred that the validation and verification stages were carried out successfully. So, the model is suitable for the numerical simulation of the operational principle of the SHP, both on a laboratory scale and on a real scale, allowing the investigation of its fluid dynamic behavior.

Dataset on the Validation and Standardization of the Questionnaire for the Self-Assessment of Service-Learning Experiences in Higher Education (QaSLu)

This dataset shows the original validation and standardization of the Questionnaire for the Self-Assessment of Service-Learning Experiences in Higher Education (QaSLu). The QaSLu is the first instrument to measure university service-learning (USL), validated following a strict qualitative and quantitative process by a sample of experts in USL and generating rating scales for different profiles of professors. The Delphi method was used for the qualitative validation by 16 academic experts, who evaluated the relevance and clarity of the items. After two consultation rounds, 45 items were qualitatively validated, generating the QaSLu-45. Then, 118 instructors from 43 universities took part as the sample in the quantitative validation procedure. Quantitative validation was carried out through goodness-of-fit measures using confirmatory factor analysis and the final configuration optimized using one-factor robust exploratory factor analysis, determining the most optimal version of the questionnaire under the law of parsimony, the QaSLu-27, with only 27 items and better psychometric properties. Finally, rating scales were calculated to compare different profiles of USL professors. These findings offer a valid, strong, and trustworthy instrument. The QaSLu-27 may be helpful for the design of USL experiences, in addition to facilitating the assessment of such programs to enhance teaching and learning processes.

The recovery cycle of excitability assessed by a conventional electrodiagnostic machine: A study in healthy volunteers and in Charcot-Marie-Tooth 1A patients

ObjectiveTo validate the ‘paired pulses’ technique with a conventional electrodiagnostic machine (CEM) for studying the axonal excitability recovery cycle (ERC). MethodsPaired pulses, with a variable inter-stimulus interval, were delivered at the wrist along the median nerve. The CEM repeatability was verified in a group of 15 healthy volunteers (test/retest analysis). ERC was then applied in 40 healthy volunteers and 10 patients with Charcot-Marie-Tooth type 1A (CMT1A), using both the threshold tracking (TT) reference method and CEM (basal condition, during and after ischemia). ResultsCEM parameters evaluating absolute refractory and supernormal periods were reproducible (interclass correlation coefficient > 0.75). CEM results were consistent with TT method and literature data. In CMT1A, refractory and superexcitable periods were significantly reduced. According to receiving operator characteristic analysis, the CEM supernormal period area was the most relevant parameter for discriminating CMT1A from healthy volunteers (area under the curve = 0.98). ConclusionsCEM was a valid procedure for studying ERC. CMT1A patients exhibited ERC alterations due to modifications in passive membrane properties and of nodal ion channel distribution resulting from demyelination. SignificanceStudying ERC with CEM could be performed in routine practice in patients with peripheral neuropathies to provide information on motor axonal excitability.

RP-CAD for Lipid Quantification: Systematic Method Development and Intensified LNP Process Characterization.

Lipid nanoparticles (LNPs) and their versatile nucleic acid payloads bear great potential as delivery systems. Despite their complex lipid composition, their quality is primarily judged by particle characteristics and nucleic acid encapsulation. In this study, we present a holistic reversed-phase (RP)-charged aerosol detection (CAD)-based method developed for commonly used LNP formulations, allowing for intensified LNP and process characterization. We used an experimental approach for power function value (PFV) optimization termed exploratory calibration, providing a single PFV (1.3) in an appropriate linearity range for all six lipids. Followed by the procedure of method calibration and validation, linearity (10-400 ng, R2 > 0.996), precision, accuracy, and robustness were effectively proven. To complement the commonly determined LNP attributes and to evaluate the process performance across LNP processing, the developed RP-CAD method was applied in a process parameter study varying the total flow rate (TFR) during microfluidic mixing. The RP-CAD method revealed a constant lipid molar ratio across processing but identified deviations in the theoretical lipid content and general lipid loss, which were both, however, entirely TFR-independent. The deviations in lipid content could be successfully traced back to the lipid stock solution preparation. In contrast, the observed lipid loss was attributable to the small-scale dialysis following microfluidic mixing. Overall, this study establishes a foundation for employing RP-CAD for lipid quantification throughout LNP processing, and it highlights the potential to extend its applicability to other LNPs, process parameter studies, or processes such as cross-flow filtration.

Is Seeing Believing? A Practitioner's Perspective on High-Dimensional Statistical Inference in Cancer Genomics Studies.

Variable selection methods have been extensively developed for and applied to cancer genomics data to identify important omics features associated with complex disease traits, including cancer outcomes. However, the reliability and reproducibility of the findings are in question if valid inferential procedures are not available to quantify the uncertainty of the findings. In this article, we provide a gentle but systematic review of high-dimensional frequentist and Bayesian inferential tools under sparse models which can yield uncertainty quantification measures, including confidence (or Bayesian credible) intervals, p values and false discovery rates (FDR). Connections in high-dimensional inferences between the two realms have been fully exploited under the "unpenalized loss function + penalty term" formulation for regularization methods and the "likelihood function × shrinkage prior" framework for regularized Bayesian analysis. In particular, we advocate for robust Bayesian variable selection in cancer genomics studies due to its ability to accommodate disease heterogeneity in the form of heavy-tailed errors and structured sparsity while providing valid statistical inference. The numerical results show that robust Bayesian analysis incorporating exact sparsity has yielded not only superior estimation and identification results but also valid Bayesian credible intervals under nominal coverage probabilities compared with alternative methods, especially in the presence of heavy-tailed model errors and outliers.

Developing Service Line Inventories: Guidance for Utilities With Limited Lead Lines

Key TakeawaysIn the United States, all community and nontransient noncommunity water systems are required to submit an inventory describing the location and makeup of all service lines in their service areas.While the material can be designated as lead, galvanized requiring replacement, nonlead, or unknown, the last two designations require additional steps to be taken in the proposed Lead and Copper Rule Improvements (LCRI).Some utilities have few or no lead service lines, and this inventory requirement, issued by the US Environmental Protection Agency (EPA), may be burdensome to those utilities.This article demonstrates the methodology in EPA's proposed LCRI for verification of construction material, and an alternate validation procedure is proposed.

Application of validated UV-Vis spectrophotometry-colorimetric methods for specific quantification of deferiprone in the development of iron-responsive nanoparticle loaded into dissolvingmicroneedle.

Deferiprone (DFP) is one of the iron-chelating agents used in iron overload therapy for patients with ß-thalassemia major (ß-TM). However, the use of DFP is limited as it experiences a first-pass effect and can potentially cause iron deficiency due to uncontrolled release. Therefore, iron-responsive (NP-IR) DFP nanoparticle innovation was developed to control DFP release. A dissolving microneedle system (NP-IR-DMNs) was used to maximize DFP release. However, in support of this development, validation of analytical methods using spectrophotometry and colorimetrics was carried out. UV-Vis spectrophotometry is an approach that is easy to use, practical, and more cost-effective than others. The DFP levels were determined in normal and iron-overloaded medium solutions with 1%, 2%, and 4% concentrations. In addition, DFP levels were also measured in rat plasma using the colorimetric method with the addition of FeCl3 reagent to increase sensitivity for the detection of the analyte. The procedures used as guidelines in the validation procedure are The International Council for Harmonization (ICH). As a result, all linear correlation values of medium and plasma ≥ 0.999 were obtained. The LOQ levels obtained were 0.55µg/mL, 0.44µg/mL, 0.42µg/mL, 0.52µg/mL, and 1.01µg/mL in plasma, 1% FeSO4, 2% FeSO4, 4% FeSO4, and normal media, respectively. The accuracy and precision were confirmed valid, as all values were within the requirements and did not change during dilution. Then, this approach was successfully applied to determine the levels of DFP in NP-IR integrated into DMNs.

Training set optimization is a feasible alternative for perennial orphan crop domestication and germplasm management: an Acrocomia aculeata example.

Orphan perennial native species are gaining importance as sustainability in agriculture becomes crucial to mitigate climate change. Nevertheless, issues related to the undomesticated status and lack of improved germplasm impede the evolution of formal agricultural initiatives. Acrocomia aculeata - a neotropical palm with potential for oil production - is an example. Breeding efforts can aid the species to reach its full potential and increase market competitiveness. Here, we present genomic information and training set optimization as alternatives to boost orphan perennial native species breeding using Acrocomia aculeata as an example. Furthermore, we compared three SNP calling methods and, for the first time, presented the prediction accuracies of three yield-related traits. We collected data for two years from 201 wild individuals. These trees were genotyped, and three references were used for SNP calling: the oil palm genome, de novo sequencing, and the A. aculeata transcriptome. The traits analyzed were fruit dry mass (FDM), pulp dry mass (PDM), and pulp oil content (OC). We compared the predictive ability of GBLUP and BayesB models in cross- and real validation procedures. Afterwards, we tested several optimization criteria regarding consistency and the ability to provide the optimized training set that yielded less risk in both targeted and untargeted scenarios. Using the oil palm genome as a reference and GBLUP models had better results for the genomic prediction of FDM, OC, and PDM (prediction accuracies of 0.46, 0.45, and 0.39, respectively). Using the criteria PEV, r-score and core collection methodology provides risk-averse decisions. Training set optimization is an alternative to improve decision-making while leveraging genomic information as a cost-saving tool to accelerate plant domestication and breeding. The optimized training set can be used as a reference for the characterization of native species populations, aiding in decisions involving germplasm collection and construction of breeding populations.

Regression Models for Tree Volume Prediction in Pinus Wallichiana Stands of South Western Himalayan Region of Kashmir

This study focuses on assessing tree species diversity and evaluating the efficacy of both linear and non-linear regression models for predicting tree volume. The research was conducted in the slopes of the Pir Panjal range within the Shopian Forest Division, situated in the South-Western Himalayan Region of Kashmir. Data on Pinus wallichiana stands, including diameter at breast height (D) and tree height (H), were meticulously collected using appropriate measurement instruments. Employing a multi-stage sampling technique, ten plots of uniform size (10m x 10m) were selected across 20 blocks, and subsequently, 25 trees were randomly chosen from each plot. Six different linear and non-linear regression equations were fitted to the data, and the most suitable equation was identified for volume estimation. To evaluate the performance of the fitted regression models, metrics such as R-squared (R²), adjusted R², root-mean-square error (RMSE), and Theil’s U statistic were employed. Additionally, validation procedures involved using the half-split approach and the Chow test. Upon analysis, it was determined that when employing diameter (D) and considering the joint effectof diameter and height (D2H (I)) as independent variables, the linear model (V=-1.41+15.12D) and power model (V=2.301 I0.502), quadratic model (V=1.8726+0.663 I- 0.011 I²) with highest R², lowest RMSE and Theil’s U statistic respectively, emerged as the most suitable for volume estimation, demonstrating superior accuracy compared to alternative models. Consequently, our findings extend beyond academic inquiry, offering practical implications for sustainable forest management and planning in the Western Himalayan Regions of Kashmir. By providing robust volume estimation models tailored to Pinus wallichiana stands, our study equips forest managers and policymakers with essential tools for informed decision-making.

Antibiotic resistance challenge: evaluating anthraquinones as rifampicin monooxygenase inhibitors through integrated bioinformatics analysis

ObjectiveAntibiotic resistance poses a pressing and crucial global public health challenge, leading to significant clinical and health-related consequences. Substantial evidence highlights the pivotal involvement of rifampicin monooxygenase (RIFMO) in the context of antibiotic resistance. Hence, inhibiting RIFMO could offer potential in the treatment of various infections. Anthraquinones, a group of organic compounds, have shown promise in addressing tuberculosis. This study employed integrated bioinformatics approaches to evaluate the potential inhibitory effects of a selection of anthraquinones on RIFMO. The findings were subsequently compared with those of rifampicin (RIF), serving as a positive control inhibitor.MethodsThe AutoDock 4.0 tool assessed the binding free energy between 21 anthraquinones and the RIFMO catalytic cleft. The ligands were ranked based on the most favorable scores derived from ΔGbinding. The docking analyses for the highest-ranked anthraquinone and RIF underwent a cross-validation process. This validation procedure utilized the SwissDock server and the Schrödinger Maestro docking software. Molecular dynamics simulations were conducted to scrutinize the stability of the backbone atoms in free RIFMO, RIFMO-RIF, and RIFMO complexed with the top-ranked anthraquinone throughout a 100-ns computer simulation. The Discovery Studio Visualizer tool visualized interactions between RIFMO residues and ligands. An evaluation of the pharmacokinetics and toxicity profiles of the tested compounds was also conducted.ResultsFive anthraquinones were indicated with ΔGbinding scores less than − 10 kcal/mol. Hypericin emerged as the most potent RIFMO inhibitor, boasting a ΔGbinding score and inhibition constant value of − 12.11 kcal/mol and 798.99 pM, respectively. The agreement across AutoDock 4.0, SwissDock, and Schrödinger Maestro results highlighted hypericin’s notable binding affinity to the RIFMO catalytic cleft. The RIFMO-hypericin complex achieved stability after a 70-ns computer simulation, exhibiting a root-mean-square deviation of 0.55 nm. Oral bioavailability analysis revealed that all anthraquinones except hypericin, sennidin A, and sennidin B may be suitable for oral administration. Furthermore, the carcinogenicity prediction analysis indicated a favorable safety profile for all examined anthraquinones.ConclusionInhibiting RIFMO, particularly with anthraquinones such as hypericin, holds promise as a potential therapeutic strategy for infectious diseases.

A predictive model for stunting among children under the age of three.

In light of the global effort to eradicate stunting in childhood, the objective of this research endeavor was to assess the prevalence of stunting and associated factors, simultaneously construct and validate a risk prediction model for stunting among children under the age of three in Shenzhen, China. Using the stratified random sampling method, we selected 9,581 children under the age of three for research and analysis. The dataset underwent a random allocation into training and validation sets, adhering to a 8:2 split ratio. Within the training set, a combined approach of LASSO regression analysis and binary logistic regression analysis was implemented to identify and select the predictive variables for the model. Subsequently, model construction was conducted in the training set, encompassing model evaluation, visualization, and internal validation procedures. Finally, to assess the model's generalizability, external validation was performed using the validation set. A total of 684 (7.14%) had phenotypes of stunt. Utilizing a combined approach of LASSO regression and logistic regression, key predictors of stunting among children under three years of age were identified, including sex, age in months, mother's education, father's age, birth order, feeding patterns, delivery mode, average daily parent-child reading time, average time spent in child-parent interactions, and average daily outdoor time. These variables were subsequently employed to develop a comprehensive prediction model for childhood stunting. A nomogram model was constructed based on these factors, demonstrating excellent consistency and accuracy. Calibration curves validated the agreement between the nomogram predictions and actual observations. Furthermore, ROC and DCA analyses indicated the strong predictive performance of the nomograms. The developed model for forecasting stunt risk, which integrates a spectrum of variables. This analytical framework presents actionable intelligence to medical professionals, laying down a foundational framework and a pivot for the conception and execution of preemptive strategies and therapeutic interventions.

Evaluating a novel method for vitamin A analysis in an observational study of the UAE's obese population

Vitamin A plays a critical role in various biological functions, including vision, cellular differentiation, and immune regulation. However, accurately assessing its status, particularly in obese individuals, presents challenges due to potential alterations in metabolism and distribution. This study utilized Liquid Chromatography–Tandem Mass Spectrometry (LC–MS/MS) methodology to precisely measure serum vitamin A concentrations in population of UAE. The methodology's reliability and precision, as demonstrated through validation procedures, underscore its potential utility in clinical settings. Employing the Multiple Reaction Monitoring mode of positive ion electrospray ionization, the LC–MS/MS system achieves a limit of detection (LOD) of 0.48 ng/mL in serum, while adhering to FDA-US regulations for accuracy and compliance. A key aspect of this study was the application of LC–MS/MS to assess vitamin A status in an obese population within UAE. By employing a diverse cohort of 452 Emirati participants, including 277 individuals from a randomized controlled trial who were assessed at baseline and at 6th month, and 175 healthy individuals aged 18–82 assessed at baseline, this study explores the relationship between obesity and vitamin A levels, shedding light on potential implications for health and well-being. It was an observational study based on a new vitamin A method and participants were asked to eat vitamin A rich foods. The robust performance of the LC–MS/MS methodology positions it as a valuable tool for clinical research. By accurately quantifying vitamin A levels in human serum, this methodology opens avenues for advancing our understanding of vitamin A physiology and its implications for health, particularly in obese populations. In summary, this LC–MS/MS methodology presents a potent tool for clinical studies, providing reliable, specific, and robust detection of vitamin A in human serum, thus, opening a new frontier for advancing our understanding of vitamin A related physiology and health in the obese population.

An Efficient and Cost-effective Modified Carbon Paste Electrodes for Diltiazem Hydrochloride Determination in Tablets

Background and Objective: This study presented new sensitive and selective modified carbon paste (MCPE) potentiometric sensors modified with different ion pairs for the determination of the antihypertensive drug diltiazem hydrochloride (DTM-HCl) in biological fluids, pharmaceutical preparations, and in its pure form. Methods: Plasticizers, ion pair type, ion pair content, response time, temperature, and pH were just a few of the experimental factors evaluated that were found to affect electrode efficiency. The two electrodes that show the best sensitivity were prepared by mixing diltiazem-tetraphenyl borate (DTM-TPB) ion pair, graphite, and TCP or o-NPOE as a plasticizer. Result: Over the concentration ranges of 1.0x10-5–1.0x10-2, the produced electrodes I and II demonstrated monovalent Nernstian responses of 55.7±0.902 and 57.6±0.451 mV decade-1. The selectivity property of the suggested electrodes was used to study the interference ions. The concentration of DTM-HCl in pharmaceutical formulations and biological fluids was measured using these modified electrodes. During the validation procedure, metrics like linearity, accuracy, precision, limit of detection, limit of quantification, and specificity were used. Conclusion: The obtained results showed good agreement with the HPLC technique as indicated by the F and t-test values and can conclude the possibility of using this potentiometric method in the routine analysis of DTM-HCl.

Transvaginal uterine niche repair: surgical technique and outcome.

A uterine niche after caesarean section may play a role in secondary infertility. The transvaginal approach is a newly developed minimally invasive surgical technique for repairing a uterine isthmocele. To report on the feasibility, effectiveness, and safety of the transvaginal uterine niche repair. The technique is demonstrated in a live-surgery video. A retrospective chart review involving all patients with secondary infertility who underwent a transvaginal uterine niche repair in Ziekenhuis Oost-Limburg between August 2019 and July 2022 was conducted. We compared the pre- and postoperative residual myometrial thickness as a primary surgical outcome measurement. The pregnancy ratio and the peri- and postoperative complications were also reported. A total of 26 patients underwent a transvaginal uterine niche repair with an average operation time of 44 minutes. No major surgical complications were reported. 23 patients (88%) had good postoperative myometrial integrity, while 3 patients had a partial or complete postoperative recurrence of the uterine niche. The average pre- and postoperative myometrial thicknesses were 1.6 mm and 6.4 mm respectively. 64% of patients desiring pregnancy became pregnant after the transvaginal niche repair. There were no obstetric complications reported. A transvaginal approach is a safe and effective technique for uterine niche repair. It offers good results in re-establishing myometrial integrity and may favour fertility outcomes. It represents a valid minimal invasive procedure for patients with a very thin residual myometrial thickness and secondary infertility without leaving a visual scar.

Verification and Validation of CFD analysis for 1/7th scale model of APR1400 for CVAP

This paper presents a methodology for analyzing the internal flow of the APR1400 Reactor Vessel Internals (RVI) using Computational Fluid Dynamics (CFD). The Comprehensive Vibration Assessment Program (CVAP) is performed to verify the structural integrity of reactor internals for flow-induced vibrations prior to the commercial operation of nuclear power plants. To classify the APR1400 as a valid prototype, it is necessary to demonstrate through successful CVAP that there are no adverse effects. In this study, CFD is used to calculate the local velocity and flow distribution to generate the forcing functions caused by turbulent flow for analysis programs in the CVAP. The Verification &Validation (V&V) procedure recommended by the American Society of Mechanical Engineers (ASME) is performed to verify the accuracy of CFD based on reliability, and it is compared with tests on a scale model. This paper provides valuable insights into the analysis and V&V process for CVAP using CFD, which can help ensure the safe and reliable operation of nuclear power plants.

Pengaruh Teknologi Human Resource Information System (HRIS) terhadap kinerja karyawan pada Kantor Cabang Utama Pos Bandung

This research aims to determine the effect of Human Resource Information System (HRIS) technology on employee performance. This research uses a descriptive approach with a quantitative approach. Analyze causal relationships using hypothesis testing. Data was collected through distributing questionnaires. All 54 employees of KCU Pos Bandung were the population in this study. Data analysis uses validity, reliability, normality and simple linear regression test procedures, correlation coefficients, determining factors and hypothesis testing. The research results show that HRIS Technology influences employee performance at KCU Pos Bandung

Forest therapy in Italy: proposal of a standard procedure for validation of suitable sites

Forest therapy in Italy: proposal of a standard procedure for validation of suitable sites