Quality Threshold Research Articles

Metabolomic and enzymatic markers reveal critical air exposure threshold for Crassostrea hongkongensis quality

Metabolomic and enzymatic markers reveal critical air exposure threshold for Crassostrea hongkongensis quality

Linking summer nutrition to behavior and performance of black‐tailed deer

AbstractMany large‐herbivore populations are regulated at least in part by bottom‐up forces, and thus relationships between herbivores and their habitat are of fundamental importance to wildlife managers. Variation in nutritional resources—and how herbivores respond to that variation—influences rates of nutrient intake, which directly affect nutritional condition, pregnancy rates, timing of parturition, offspring birth mass, and survival. Accordingly, nutrition‐focused research holds great potential for uncovering the mechanisms that govern population performance of large herbivores and for assessing the nature and magnitude of bottom‐up limitations. We quantified relationships between the foodscape (i.e., spatiotemporal variation in forage quality and abundance) in southwestern Oregon, USA, and black‐tailed deer (Odocoileus hemionus columbianus) behavior and performance, with a focus on the influence of maternal nutrition on fawn survival. We hypothesized that black‐tailed deer performance (i.e., fawn birth mass and survival) is influenced by the availability of high‐quality forage during spring and summer and patterns of foodscape use exhibited by individual deer. From 2016–2023 we monitored movement and survival of adult female black‐tailed deer and their offspring. We also conducted intensive vegetation sampling and used generalized additive modeling to map the foodscape available to deer in spring and summer. Suitable forage biomass (i.e., maximum biomass of forage that together exceeded quality thresholds for supporting one fawn) was highly variable across space and time, and our top foodscape model explained 70% of the variation in suitable biomass (adjusted R2 = 0.70). We observed a strong, positive relationship between use of the foodscape by maternal females prior to parturition and fawn birth mass. Although maternal foodscape use after parturition did not influence the probability of fawn survival, survival increased with increasing birth mass. These results suggest that the effects of nutrition on fawn survival in our study system are indirectly mediated by maternal behavior (i.e., use of the foodscape) and the corresponding effects on birth mass of fawns. Our study adds to a growing body of literature supporting a fundamental link between foodscape use and population performance of large herbivores. Wildlife managers can use the dynamic models we developed to assess habitat quality and to make quantitative predictions about how different management actions (e.g., forest thinning) are likely to influence habitat quality and performance of black‐tailed deer.

Small amounts of misassembly can have disproportionate effects on pangenome-based metagenomic analyses.

Individual genes from microbiomes can drive host-level phenotypes. To help identify such candidate genes, several recent tools estimate microbial gene copy numbers directly from metagenomes. These tools rely on alignments to pangenomes, which in turn are derived from the set of all individual genomes from one species. While large-scale metagenomic assembly efforts have made pangenome estimates more complete, mixed communities can also introduce contamination into assemblies, and it is unknown how robust pangenome-based metagenomic analyses are to these errors. To gain insight into this problem, we re-analyzed a case-control study of the gut microbiome in cirrhosis, focusing on commensal Clostridia previously implicated in this disease. We tested for differentially prevalent genes in the Lachnospiraceae , then investigated which were likely to be contaminants using sequence similarity searches. Out of 86 differentially prevalent genes, we found that 33 (38%) were probably contaminants originating in taxa such as Veillonella and Haemophilus , unrelated genera that were independently correlated with disease status. Our results demonstrate that even small amounts of contamination in metagenome assemblies, below typical quality thresholds, can threaten to overwhelm gene-level metagenomic analyses. However, we also show that such contaminants can be accurately identified using a method based on gene-to-species correlation. After removing these contaminants, we observe that several flagellar motility gene clusters in the Lachnospira eligens pangenome are associated with cirrhosis status. We have integrated our analyses into an analysis and visualization pipeline, PanSweep, that can automatically identify cases where pangenome contamination may bias the results of gene-resolved analyses.

Use of ultra-low contrast dose CT aortography for the management of aortic aneurysmal disease

PurposeComputed tomography aortography (CTA) is used in the assessment of aortic pathologies and planning of surgical intervention. However, its dependence on iodinated contrast can result in development of contrast-induced acute kidney injury (CI-AKI). The potential concern of CI-AKI has spurred research into the potential of administration of low contrast volumes in CTA investigations while maintaining overall diagnostic appeal. Several studies have shown that CTA using contrast volumes as low as 30 mL (equivalent to 10.5 g of iodine) can still yield scans of diagnostic quality. We present a retrospective pilot study to evaluate the feasibility of utilising an ultra-low volume of iodinated intravenous contrast in a population of patients with severe renal insufficiency with referral from our vascular surgery unit for CTA evaluation of the thoracic and abdominal aorta.MethodsThis retrospective pilot study examined 12 CTA scans performed with 20 mLs of iodinated contrast and assessed image quality with both quantitative and qualitative markers. All scans were performed on a Siemens SOMATOM Force dual-source CT scanner. Quantitative assessment values were measured via attenuation values at eight aortoiliac locations and used to calculate a signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) at each location. Qualitative analysis of image quality and viability for surgical intervention was obtained from subjective clinical assessment by an interventional radiologist and vascular surgeon.ResultsObtained quantitative assessment values included mean attenuation 189.9 HU, mean SNR 9.6 and mean CNR 8.0. All 12 scans demonstrated individual mean SNR values above predetermined quality thresholds while only five scans produced individual mean CNR values above threshold. Eleven of 12 scans were determined to be of sufficient quality for diagnosis and planning of surgical intervention.ConclusionsOur results suggest that CTA utilising an ultra-low contrast dose of 20 mLs (6 g iodine) yields scans of diagnostic quality for therapeutic decision-making in vascular surgical intervention.

Quality evaluation of French guidelines in primary care infectious disease: An AGREE II assessment.

Antibiotic prescription, its nature and its duration are a very common decision-making situation in primary care practice. Clinical practice guidelines (CPGs) are regularly emitted by various organisations on this topic. Our goal is to run a quality appraisal of the current French guidelines, for the most common primary care infectious pathologies. We collected all primary care CPGs that are currently prevailing in France through a systematic review of the french website Antibioclic®. For each of these guidelines, a quality assessment was run by 3 independent reviewers, by means of the Appraisal of Guidelines for REsearch & Evaluation II instrument. The main outcome was a 'reliability score', defined as the sum of the scores in domains 'rigour of development' and 'editorial independence'. To be considered 'reliable', the CPG had to reach a 60% threshold in these two domains. Secondary outcomes were as follows: global quality score of CPGs, number and ratio of CPGs for which a systematic review has been conducted during its conception. Over the 43 CPGs that have been assessed, none reached the 60%-threshold as to the reliability score. Only one CPG (2.33%) gets an over-60% quality assessment in the domain of rigour of development (D3), whereas three CPGs (6.98%) reach this threshold in the domain of editorial independence (D6). One CPG (2.33%) met the quality threshold of 60% as to overall assessment. Rigour of development and editorial independence are the domains that obtained the lowest average score, respectively, 11% and 21%. Overall assessment received an average score of 29%. A systematic review of the literature was mentioned for 10 CPGs (23.26%). There is a lack of quality in the development process of the current French guidelines in primary care infectiology. This process should be reconsidered, with higher insistence as to its quality.

Evaluating the Readability, Credibility, and Quality of Spanish-Language Online Educational Resources for Knee Arthroplasty: Implications for Patient Education and Health Disparities.

Spanish-speaking individuals may experience language-based disparities related to elective orthopaedic procedures. Because patients often seek online health information, we assessed the readability, credibility, and quality of Spanish-language educational websites for knee arthroplasty. We queried "Google," "Yahoo," and "Bing" using the term "reemplazo de rodilla" (knee replacement in Spanish) and extracted the top 50 websites per search engine. Websites were categorized by information source (physician/community hospital, university/academic, other) and presence of HONcode certification. Information was assessed for readability (Fernández-Huerta formula), credibility (Journal of the American Medical Association benchmark criteria), and quality (Brief DISCERN tool); scores were compared between the categories. A total of 77 unique websites were included (40.3% physician/community hospital, 35.1% university/academic). The median readability score was 59.4 (10th to 12th-grade reading level); no websites achieved the recommended level of ≤6th grade. The median Journal of the American Medical Association benchmark score was 2 (interquartile range 1 to 3), with only 7.8% of websites meeting all criteria. The median Brief DISCERN score was 16 (interquartile range 12 to 20), with 50.7% meeting the threshold for good quality. University/academic websites had better readability (P = 0.02) and credibility (P = 0.002) but similar quality (P > 0.05) compared with physician/community hospital websites. In addition, HONcode-certified websites had better quality scores (P = 0.045) but similar readability and credibility (P > 0.05) compared with noncertified websites. We identified limitations in readability, credibility, and quality of Spanish-language online educational resources for knee arthroplasty. Healthcare providers should be aware of these patient education barriers when counseling patients, and efforts should be made to support the online information needs of Spanish-speaking orthopaedic patients and mitigate language-based disparities.

The existing conditions of distribution parameters of physical and chemical factors of salt pond land on the Coast of Palang District, Tuban Regency, Indonesia

The purpose of this study was to determine the distribution value of physical and chemical factors that affect salt pond land. We employed a method to assess the current state of salt ponds in coastal regions. We conducted this study in Palang District, Tuban Regency, from May 1 to June 1, 2024. This research method involves various methods, including remote sensing and geographic information systems (GIS), to map and analyze land conditions. We will use data from satellite imagery and field measurements to evaluate the physical and chemical parameters for the development of salt ponds. Based on the research data, we have established that the physical and chemical parameters of salt pond land on the coast of Palang District, such as salt table height, seeding place, main embankment, intermediate embankment, pH, and pond bottom, are in good condition and meet the requirements for salt pond land development. In conclusion, the chemical parameters show that the quality of water and soil in salt ponds is still within acceptable limits, although there are several locations that show values approaching the standard quality threshold. We recommend implementing sustainable management practices in the development of salt ponds, which include periodic monitoring of physical and chemical parameters, further research on the impacts of climate change, and collaboration between government, academics, and communities in managing sustainable salt ponds and formulating policies that support the development of the salt industry in coastal areas.

‘Bad Jobs’ in Europe: Derivation and Analysis of a Wellbeing-Related Job Quality Threshold

‘Bad Jobs’ in Europe: Derivation and Analysis of a Wellbeing-Related Job Quality Threshold

Generative Haplotype Prediction Outperforms Statistical Methods for Small Variant Detection in NGS Data

Abstract Motivation Detection of germline variants in next-generation sequencing data is an essential component of modern genomics analysis. Variant detection tools typically rely on statistical algorithms such as de Bruijn graphs or Hidden Markov Models, and are often coupled with heuristic techniques and thresholds to maximize accuracy. Despite significant progress in recent years, current methods still generate thousands of false positive detections in a typical human whole genome, creating a significant manual review burden. Results We introduce a new approach that replaces the handcrafted statistical techniques of previous methods with a single deep generative model. Using a standard transformer-based encoder and double-decoder architecture, our model learns to construct diploid germline haplotypes in a generative fashion identical to modern Large Language Models (LLMs). We train our model on 37 Whole Genome Sequences (WGS) from Genome-in-a-Bottle samples, and demonstrate that our method learns to produce accurate haplotypes with correct phase and genotype for all classes of small variants. We compare our method, called Jenever, to FreeBayes, GATK HaplotypeCaller, Clair3 and DeepVariant, and demonstrate that our method has superior overall accuracy compared to other methods. At F1-maximizing quality thresholds, our model delivers the highest sensitivity, precision, and the fewest genotyping errors for insertion and deletion variants. For single nucleotide variants our model demonstrates the highest sensitivity but at somewhat lower precision, and achieves the highest overall F1 score among all callers we tested. Availability and Implementation Jenever is implemented as a python-based command line tool. Source code is available at https://github.com/ARUP-NGS/jenever/

Nexus between natural resource endowments and economic growth in selected African countries

Africa began implementing the Sustainable Development Goals (SDGs) in 2015 emphasizing on sustainable management and effective use of natural capital to spur economic growth (Goals 12, 14, and 15). This study using World Bank data sets from 46 African countries selected for the years 2000 to 2022, examined the nexus between natural resource endowments and economic growth in Africa. We used the system generalized method of moments (sys-GMM) and dynamic panel threshold regression (DPTR) to analyze the data. The findings of the two-step sys-GMM estimation using 'xtabond2' revealed that when the institutional quality variable is added and excluded from the model, natural resource dependence negatively impacts economic growth, but the impact is greater when the institution is excluded. In the estimation of the interaction variable of natural resource dependence and institutional variable included in the model, natural resource dependence positively impacts economic growth. The results of the DPTR using "xthenreg" showed that when the threshold value of natural resource dependence is ≤ 1.73% of gross domestic product, natural resource dependence has a positive impact on economic growth and a negative impact when the threshold value is above 1.73%. Similarly, when the institutional quality threshold is ≤ 0.277, natural resources dependence impacts economic growth negatively; above the threshold (0.277), the impact is positive. In conclusion, natural resource endowment is a curse with no or low-quality institutions and a blessing with high-quality institutions. Thus, building strong institutions and proper utilization of natural resources helps to minimize the adverse impact of resource endowments on economic growth.

Electrocardiogram Signal Compression Using Deep Convolutional Autoencoder with Constant Error and Flexible Compression Rate

ObjectivesElectrocardiogram (ECG) signals are beneficial for diagnosing cardiac diseases. The cardiac patients' life quality likely increases with continuous or long-period recording and monitoring of ECG signals, leading to better and early diagnosis of disease and heart attacks. However, continuous ECG recording necessitates high data rates and storage, which means high costs. Therefore, ECG compression is a handy concept that facilitates continuous monitoring of ECG signals. Deep neural networks open up new horizons for compression and also for ECG compression by providing high compression rates and quality. Although they bring constant compression ratios with better average quality, the compression quality of individual samples is not guaranteed, which may lead to misdiagnoses. This study aims to investigate the effect of compression quality on the diagnoses and to develop a deep neural network-based compression strategy that guarantees a quality-bound in return for varying compression ratios.Materials and methodsThe effect of the compression quality on the arrhythmia diagnoses is tested by comparing the performance of the deep learning-based ECG classifier on the original ECG recordings and the distorted recordings using a lossy compression algorithm with different compression error levels. Then, a compression error upper limit is calculated in terms of normalized percent root mean square difference (PRDN) error, which also coincides with the findings of the previous studies in the literature. Lastly, to enable deep learning in ECG compression, a single encoder-multi-decoder convolutional autoencoder architecture, and multiple quantization levels are proposed to guarantee a desired upper limit on the error rate.ResultsThe efficiency of the proposed method is demonstrated on a popular benchmark data set for ECG compression methods using a transfer learning approach. The PRDN error is fixed to various values, and the average compression rates are reported. An average of 13.019:1 compression is achieved for a 10% PRDN error rate, assessed as a fair quality threshold for reconstruction error. It has also been shown that the compression model has a runtime that can be run in real-time on wearable devices such as commercial smartwatches.ConclusionThis study proposes a deep learning-based ECG compression algorithm that guarantees a desired upper limit on the compression error. This model may facilitate an eHealth solution for continuous monitoring of ECG signals of individuals, especially cardiac patients.

PENGEMBANGAN PEMBALUT BUNGA TELANG BERBASIS NANOTECHNOLOGY DAN AKURASI DALAM DETEKSI DINI KETUBAN PECAH DINI

The incidence of premature rupture of membranes (PROM) reaches 12.3% of total births throughout the world. Efforts to detect early KPD still face problems, namely the use of litmus paper which is small in size and there are no regulations regarding its use, so a tool is needed that has the same function as litmus paper in detecting amniotic fluid which can be used and used by pregnant women independently. The study aimed to develop nanotechnology-based butterfly pea flower pads in early detection of PROM. The research method used is Quasy Experimental, with purposive sampling technique, using an observation sheet. The sanitary napkin design is designed with a telang flower indicator for PROM detection with a sanitary napkin length of 22 cm and a width of 7 cm. Testing was carried out on 30 pregnant women in Jati District, Blora Regency, at January 20 to February 19, 2024. Statistical analysis uses Anova, Multiple Comparison test and Tukey's Difference Test. The research results obtained accuracy, sensitivity and specificity values ​​of 100%. Sanitary napkins do not cause irritation to the skin, have an ideal absorbency of 10x the initial weight, a chlorine concentration of 1.8 ppm with a total of 39 bacterial colonies which is still below the quality threshold for sanitary napkins. The study concluded that butterfly pea flower sanitary napkin products can accurately replace litmus paper as an indicator for early detection of PROM.

Paris air quality monitoring for the 2024 Olympics and Paralympics: focus on air pollutants and pollen

BackgroundExposure to air pollution can affect the health of individuals with respiratory disease, but may also impede the health and performance of athletes. This is potentially relevant for people travelling...

A high resolution hydrodynamic-biogeochemical-oyster-filtration model predicts that the presence of oysters (Crassostrea virginica) can improve, or reduce, water quality depending upon oyster abundance and location

The eastern oyster (Crassostrea virginica) provides numerous ecosystem services such as building reef habitat, clarifying the water by filtering seston, and reducing excess nitrogen when their biodeposits are denitrified. Some of these ecosystem services have been extensively studied using two-dimensional and three-dimensional (3D) models. Yet, the relationship between oyster abundance, their filtration and biodeposition rates, and associated water quality metrics has not been estimated with high-resolution models that include biodeposit resuspension as well as simulation of 3D processes in the sub-tributaries where oysters are abundant. To undertake these estimates, a 3D Regional Ocean Modeling System (ROMS) framework, comprised of a coupled hydrodynamic-water quality model with an oyster filtration and biodeposition sub-model, was implemented over a fine-resolution model grid (120–150 m) of the Choptank River on the eastern shore of Chesapeake Bay, U.S.A. After validation with data from 20 cruises between May and September 2010, the model was used to predict seven variables associated with water quality in simulations with zero, recent, and 50x recent abundances of oysters. Results indicated that improvement in the seven water quality variables differed in response to the abundance of oysters and between regions in the Choptank River. In line with expectations, the water quality metrics improved with increasing oyster abundance in the shallow and retentive sub-tributaries of Broad and Harris Creeks. In contrast, in the deeper and more flushed mainstem of the Choptank River, some water quality metrics deteriorated when recent abundances of oysters were added to the model compared to the simulation with zero oysters and the same metrics improved when oyster abundances were increased by 50x. Overall, model results indicated that the many complex physical and biogeochemical processes that influence the effect of oysters on water quality resulted in differing responses to oysters across different systems. In addition, this study introduces a high-resolution, predictive tool that could be used to estimate the number of oysters needed to meet water quality thresholds in specific systems in support of ecosystem management.

One third of African rivers fail to meet the ’good ambient water quality’ nutrient targets

The ambition of Sustainable Development Goal (SDG) target 6.3 is to improve global water quality by 2030. SDG indicator 6.3.2 monitors progress towards this target by assessing water bodies against ‘good’ ambient water quality criteria, with nutrients (nitrogen and phosphorus) as part of the key metrics. However, large data gaps present a fundamental challenge, especially for Africa on how to assess the progress being made with respect to both the current and desired future situations. Here, a continental water quality model for Africa is presented to simulate river sediment load, Total Nitrogen (TN) and Total Phosphorus (TP) loads and concentrations. Furthermore, critical areas and hotspots of TN and TP pollution are mapped for the period 2017 – 2019, in relation to the United Nations Environment Programme (UNEP) target thresholds used for the assessment of SDG indicator 6.3.2. Utilizing the UNEP’s criteria, which designates a water body as having “good ambient water quality” if 80% or more of its monitored values meet their targets, it is estimated that 44 % and 15 % of African rivers fail to meet the set water quality thresholds for simulated TP and TN, respectively. When synthesizing data for both TP and TN, 34 % of the rivers do not qualify as having “good ambient water quality”. Geographically, the most pronounced nutrient pollution hotspots were in North Africa, Niger River Delta, Nile River basin, Congo River basin and specific zones in Southern Africa. These areas correlate with regions characterized by high inputs of fertilizers, manure and wastewater discharge.

LaMPost: AI Writing Assistance for Adults with Dyslexia Using Large Language Models

The natural language capabilities demonstrated by large language models (LLMs) highlight an opportunity for new writing support tools that address the varied needs of people with dyslexia. We present LaMPost, a prototype email editor that draws upon our understanding of these needs to motivate AI-powered writing features, such as outlining main ideas, generating a subject line, suggesting changes, and rewriting a selection. We evaluated LaMPost with 19 adults with dyslexia, identifying promising routes for further exploration (such as the popular “rewrite” and “subject line” features), while also finding that the current generation of LLMs may not yet meet the accuracy and quality thresholds to be useful for writers with dyslexia. In addition, knowledge of the AI did not alter participants’ perception of the system nor their feelings of autonomy, expression, and self-efficacy when writing emails. Our findings provide insight into the benefits and drawbacks of LLMs as writing support for adults with dyslexia, and they offer a foundation to build upon in future research.

Whole-genome sequencing for antimicrobial surveillance: species-specific quality thresholds and data evaluation from the network of the European Union Reference Laboratory for Antimicrobial Resistance genomic proficiency tests of 2021 and 2022.

As antimicrobial resistance (AMR) surveillance shifts to genomics, ensuring the quality of whole-genome sequencing (WGS) data produced across laboratories is critical. Participation in genomic proficiency tests (GPTs) not only increases individual laboratories' WGS capacity but also provides a unique opportunity to improve species-specific thresholds for WGS quality control (QC) by repeated resequencing of distinct isolates. Here, we present the results of the EU Reference Laboratory for Antimicrobial Resistance (EURL-AR) network GPTs of 2021 and 2022, which included 25 EU national reference laboratories (NLRs). A total of 392 genomes from 12 AMR-bacteria were evaluated based on WGS QC metrics. Two percent (n = 9) of the data were excluded, due to contamination, and 11% (n = 41) of the remaining genomes were identified as outliers in at least one QC metric and excluded from computation of the adjusted QC thresholds (AQT). Two QC metric correlation groups were identified through linear regression. Eight percent (n = 28) of the submitted genomes, from 11 laboratories, failed one or more of the AQTs. However, only three laboratories (12%) were identified as underperformers, failing across AQTs for uncorrelated QC metrics in at least two genomes. Finally, new species-specific thresholds for "N50" and "number of contigs > 200 bp" are presented for guidance in routine laboratory QC. The continued participation of NRLs in GPTs will reveal WGS workflow flaws and improve AMR surveillance data. GPT data will continue to contribute to the development of reliable species-specific thresholds for routine WGS QC, standardizing sequencing data QC and ensure inter- and intranational laboratory comparability.IMPORTANCEIllumina next-generation sequencing is an integral part of antimicrobial resistance (AMR) surveillance and the most widely used whole-genome sequencing (WGS) platform. The high-throughput, relative low-cost, high discriminatory power, and rapid turnaround time of WGS compared to classical biochemical methods means the technology will likely remain a fundamental tool in AMR surveillance and public health. In this study, we present the current level of WGS capacity among national reference laboratories in the EU Reference Laboratory for AMR network, summarizing applied methodology and statistically evaluating the quality of the obtained sequence data. These findings provide the basis for setting new and revised thresholds for quality metrics used in routine WGS, which have previously been arbitrarily defined. In addition, underperforming participants are identified and encouraged to evaluate their workflows to produce reliable results.

Green Innovation and Energy Efficiency: Moderating Effect of Institutional Quality Based on the Threshold Model

AbstractRecent studies demonstrated that green innovation and environment-related technologies reduce energy intensity and improve energy efficiency, contributing to the reduction of carbon emissions. However, the existing studies employ linear estimation methods to examine the relationship between green innovation and energy intensity and do not consider the indirect implications of institutional quality for the effect of green technology on energy intensity. Institutional quality is found to be an essential driver of innovation, and countries may need to achieve at least a minimum level of institutional quality to promote green innovation and improve their energy intensity. To test this hypothesis, this paper examines the relationship between energy intensity and green innovation using a panel dataset from 72 countries between 1996 and 2017 and a panel threshold model when institutional quality is considered a threshold variable. The findings highlight that green innovation reduces the energy intensity if and only if countries surpass a certain threshold of institutional quality. Therefore, countries need to improve their institutional quality to promote green innovation and benefit from green technologies in improving their energy intensity.

Urea Cocrystals as a Potential Fertilizer for Turfgrass: Responses of ‘Tifway’ Hybrid Bermudagrass and Nitrogen Release Behavior

Urea cocrystal materials are a potential fertilizer source that has shown to decrease environmental nitrogen losses. Novel nitrogen (N)-containing urea cocrystal fertilizers, CaSO4·4urea (UC1) and Ca(H2PO4)2·4urea (UC2), were synthesized using the mechanochemical method to form stable urea cocrystals to be tested as a fertilizer source for turfgrass. The objectives of this study were to 1) evaluate the response of ‘Tifway’ hybrid bermudagrass (Cynodon dactylon × C. traansvalensis Burt Davy) to N fertilization by urea cocrystals and traditional coated urea products (MU·PCU, methylene urea, urea, polymer-coated urea; PCU, polymer-coated urea, urea) supplied at two rates at the beginning of two, 10-week study periods conducted under a greenhouse setting and 2) investigate N release behavior of urea and two cocrystal products using a rapid water release test. In the turfgrass response study conducted in the greenhouse, improved turfgrass quality above the minimum quality threshold was observed when averaging across all products. For normalized difference vegetation index (NDVI), cocrystal outperformed all other products in the summer study and both cocrystal products outperformed the traditional product (MU·PCU) in the winter study. Further, both cocrystal products showed favorable growth responses compared with the commercial products provided by positive clipping production and vertical extension rates. In the nitrogen release experiment, a rapid water release test revealed the N release peak of urea was significantly higher than both UC1 and UC2. Furthermore, significantly higher N was leached from urea (15% loss) compared with both UC1 and UC2 (≈8% loss). Results from both studies provide evidence supporting suitability of urea cocrystal application on bermudagrass and potential as a slow-release fertilizer source through sustained turfgrass vigor, growth, decreased N release peak, and decreased leaching losses.

DEVELOPMENT AND RESEARCH OF SOFTWARE SOLUTION FOR BUSINESS PROCESS MODEL CORRECTNESS ANALYSIS USING MACHINE LEARNING

Poorly designed business process models are a source of errors and the subsequent costs associated with these errors, such as monetary costs, lost time, or even some harmful impact on people or the environment if the erroneous business process models are associated with critical industries. The BPM (Business Process Management) lifecycle usually consists of designing, implementing, monitoring, and controlling the business process execution, but it lacks continuous quality control of the created BPMN (Business Process Model and Notation) models. Thus, this paper considers the problem of business process models classification based on their correctness, which solution will ensure quality control of the designed business process models. Thus, this study aims to improve the quality of business process models by developing a software solution for business process models classification based on their correctness. The subject of the study is the process of business process models classification based on their correctness, which uses quality measures and thresholds, usually, complexity measures. The subject of the study is a software solution for business process models classification based on their correctness. Therefore, in this study, the algorithm to solve the problem of BPMN models classification using logistic regression, interface complexity, and modularity measures is proposed, the software requirements are determined, the software development tools are selected, the software for business process models classification based on their correctness is designed, the corresponding software components are developed, the use of a software solution for solving the problem of business process models classification based on their correctness is demonstrated, the obtained results are analyzed and discussed. The developed software indicates high performance of BPMN models classification based on their correctness, achieving high accuracy (99.14 %), precision (99.88 %), recall (99.23 %), and F-score (99.56 %), highlighting the high performance of modeling errors detection.