Information Database Research Articles

A geospatial approach for dynamic on-road emission through open-access floating car data

Abstract This paper presents a geospatial approach for quantifying street-level on-road emissions of carbon dioxide (CO2), nitrogen oxides (NOx), and carbon monoxide (CO). By leveraging an existing open-access database of real-time congestion information derived from floating car data, we tested three methods to map high-resolution dynamic traffic emissions. To demonstrate the robustness and accuracy of the methods, we showcased results for summer workdays and winter weekends in the Helsinki Metropolitan Area (HMA). The three methods employed include (1) a physics-based relation known as the macroscopic fundamental diagram, (2) a data-driven input-adaptive generalized linear model (GLM), and (3) their ensemble (ENS). These methods estimated traffic density with satisfactory accuracy (R 2 = 0.60–0.88, sMAPE = 31%–68%). Utilizing speed-dependent emission factors retrieved from a European database, the results compared favorably against the downscaled national emission inventory, particularly for CO2 (R 2 = 0.70–0.77). Among the three methods, GLM exhibited the best overall performance in the HMA, while ENS provided a robust upscaling solution. The modeled emissions exhibited dynamic diurnal and spatial behavior, influenced by different functional road classes, fleet compositions and congestion patterns. Congestion-induced emissions were calculated to account for up to 10% of the total vehicular emissions. Furthermore, to anticipate the forthcoming transportation transformation, we calculated emission changes under scenarios with various penetration rates of connected and autonomous vehicles (CAVs) using this geospatial approach. The introduction of CAVs could result in emission reductions of 3%–14% owing to congestion improvements.

Risk prediction of computer investment database information management system based on machine learning algorithms

In recent years, with the continuous development of the financial market, the risk prediction of computer investment database information management systems (IMS) has high practical value. At present, there are risk issues in the information management system, which may cause drawbacks to investment data processing. To address these issues, this article used Machine Learning (ML) algorithms to analyze the risk prediction of computer investment database IMS. This article introduced and utilized typical Self-Organizing Map (SOM) and Artificial Neural Network (ANN) combination algorithms, regression algorithms, and Gradient Boosting Decision Tree (GBDT) algorithms to compare and analyze the prediction accuracy of these three algorithms. This article found that the GBDT algorithm has the highest prediction accuracy. Through a large amount of experimental data, it has been proven that the average testing accuracy using regression algorithms was 3.5% higher than that using neural network algorithms. It was found that the average test accuracy using the GBDT algorithm was 7.2% higher than the average test accuracy using the regression algorithm. The study also explores the combination of physiological and behavioral data collected by wearable devices to provide more comprehensive risk assessment and decision support, which provides an important reference for the optimization of enterprise risk management. Through this innovative data source integration, this paper provides a new perspective for the application and development of machine learning algorithms in computer investment database IMS.

Surrogate modelling of surface roughness for asphalt pavements using artificial neural networks: a mechanistic-empirical approach

ABSTRACT Pavement surface smoothness (or roughness) is crucial for traffic safety, driving comfort, and fuel efficiency. As a widely applied roughness indicator, an accurate forecasting of the International Roughness Index (IRI) and its deterioration is essential for the design, maintenance, and management of asphalt pavements. Previous studies have used field measurement data or AASHTOWare Pavement ME Design simulations for the development of machine learning (ML) models to streamline the IRI modelling. However, these models frequently lack the accuracy and robustness of the measurement data or high-fidelity computational simulations they are intended to surrogate. To address this issue, we employed a new adaptive sampling technique to generate an informative yet efficient pavement damage database from Pavement ME simulations. Utilising Artificial Neural Networks (ANNs), we engineered two types of surrogate ML models: (a) Model I, an ANN-based IRI predictive model, and (b) Model II, a hybrid model combining ANN-based predictions of rutting, fatigue damage, and thermal cracking with closed-form relationships between these indicators and IRI. Our findings show that Model II outperforms Model I in IRI modelling accuracy both globally and locally. Moreover, Model II matches IRI simulations of Pavement ME while providing enhanced efficiency and adaptability to a broader spectrum of design considerations.

Characterization and genomic analysis of the highly virulent Acinetobacter baumannii ST1791 strain dominating in Anhui, China.

The multidrug-resistant Acinetobacter baumannii clonal complex 92 is spreading worldwide due to its high-frequency gene mutation and recombination, posing a significant threat to global medical and health safety. Between November 2021 and April 2022, a total of 132 clinical A. baumannii isolates were collected from a tertiary hospital in China. Their growth ability and virulence of these isolates were assessed using growth curve analyses and the Galleria mellonella infection model. The genetic characteristics of the isolates were further examined through whole-genome sequencing. ST1791O/ST2P isolates represented the largest proportion of isolates in our collection and exhibited the highest growth rate and strongest virulence among all sequence types (STs) analyzed. Whole-genome sequences from 14,159 clinical isolates were collected from the National Center for Biotechnology Information database, and only nine ST1791O/ST2P isolates were detected. Comparative genomic analysis revealed that ST1791O/ST2P carried 11 unique genes, 5 of which were located within the capsular polysaccharide synthesis (cps) gene cluster. Single nucleotide polymorphisms (SNPs) between ST1791O/ST2P and other isolates were primarily found in the cps gene cluster. Among the other isolates, ST195O/ST2P and ST208O/ST2P exhibited the smallest SNP differences from ST1791O/ST2P, while ST195O/ST2P and ST1486O/ST2P had high homology. The ST1791O/ST2P strain in Anhui, China, displayed significant homology with ST195O/ST2P, ST208O/ST2P, and ST1486O/ST2P isolates. Compared to other isolates in this study, ST1791O/ST2P exhibited strong growth ability and virulence. Therefore, preventing the further spread of ST1791O/ST2P should be a top public health priority.

Developing and validating a content quality evaluation tool for cancer mobile applications

IntroductionCancer remains a leading cause of death, underscoring the importance of reliable health apps. This study aims to design and validate a content quality evaluation tool for cancer mobile applications ensuring they provide standard services and features to users.MethodThis descriptive-analytical study was conducted in steps including identifying mobile application contents, designing and validating evaluation tool. Studies published until February 19, 2023, in PubMed, Web of Science, Scopus, and Scientific Information Database (SID) databases, as well as mobile applications in Myket, Bazaar, and Google Play, were searched. Data extraction and expert panel validation followed, leading to four expert sessions to design the tool. Nineteen oncologists, health information management and medical informatics specialties were included in the study as a research community. The tool’s face validity, content validity and reliability were assessed using CVR (Content Validity Ratio), CVI (Content Validity Index), and Cronbach’s alpha respectively.ResultsOut of 242 initial search results in databases and 125 mobile applications in app stores, 25 articles and 20 mobile applications included based on the search limits. The designed tools consist of 8 main themes (prevention, diagnosis, treatment, follow-up, education, communication, requests/order and other) with 43 question items. All items received scores above 0.79 in CVI and 0.42 in CVR, leading to their approval and the reliability of the tool was accepted with a score of 0.967.ConclusionEvaluating cancer mobile applications can be very helpful in developing useful and supportive mobile apps, and assist health policymakers in identifying and recommending high-quality cancer-related apps. This will enable patients to choose the most suitable apps, enhancing the quality of cancer care.

PATHOGENETIC MECHANISMS OF PAPILLEDEMA DEVELOPMENT ON PREECLAMPSIA

Preeclampsia is a multisystem disease that can include cardiovascular changes, hematological disorders, liver and kidney failure, cerebral and visual symptoms. Currently, the presence of papilledema in preeclampsia characterizes the disease as severe. However, it is likely that the presence of papilledema does not always characterize vasogenic cerebral edema with increased intracranial pressure. The formation of blurred borders and papilledema may also be associated with impaired autoregulation in the head of the optic disc due to increased blood pressure and the presence of endothelial dysfunction in preeclampsia. It is also important to differentiate the true papilledema from the pseudopapilledema. The study carried out a detailed systematic analysis of modern domestic and foreign literature, devoted to the pathogenetic mechanisms of papilledema development in preeclampsia. The study used such information databases as: eLibrary, PubMed, Scopus, Cochrane Library, MEDLINE for the period from 2015 to May 2024. This literature review presents possible pathogenetic mechanisms of the development of papilledema against on preeclampsia, as well as modern approaches to the differential diagnosis of papilledema from pseudopapilledema. Further study of the pathogenetic mechanisms of papilledema development in hypertensive pregnancy disorders is necessary to identify high-risk patients and optimize their management and treatment tactics.

Slovak database of speech affected by neurodegenerative diseases

A new Slovak speech database EWA-DB was created for research purposes aimed at early detection of neurodegenerative diseases from speech. It contains 1649 speakers performing various speech and language tasks, such as sustained vowel phonation, diadochokinesis, naming and picture description. The sample of speakers consists of individuals with Alzheimer’s disease, mild cognitive impairment, Parkinson’s disease, and healthy controls. In this article we describe the EWA-DB development process, the language and speech task selection, patient and healthy control recruitment, as well as the testing and recording protocol. The structure and content of the database and file formats are described in detail. We assume that the presented database could be suitable for the development of automatic systems predicting the diagnoses of Alzheimer’s disease, mild cognitive impairment, and Parkinson’s disease from language and speech features.

Specific PCR primer designed from genome data for rapid detection of Fusarium oxysporum f. sp. cubense tropical race 4 in the Cavendish banana.

Fusarium wilt caused by Fusarium oxysporum f. sp. cubense (Foc) tropical race 4 (TR4) severely affects banana production worldwide. Thus, specific PCR primers have been developed to rapidly diagnose and monitor Foc TR4-related fusarium wilt outbreaks in bananas. However, evaluation of these primers revealed room for improvement in the accuracy. This study aimed to design highly specific PCR primers based on genome data for Foc TR4 downloaded from the National Center for Biotechnology Information database. The specificity of the primers was assessed using Foc TR4, Foc races 1 and 2, and 15 other formae speciales strains. The utility of the primers was verified by correctly detecting Foc TR4 in 7 out of 86 isolates of Fusarium spp. obtained from banana farms in the Philippines. The primers allowed for rapid detection in experimentally diseased tissues. We concluded that this novel primer set enables the simplified diagnosis of fusarium wilt caused by Foc TR4 in bananas.

Critical Thinking and L2 Learning in the Persian Context: A Meta-analysis

Correlational studies are one of the rich literatures in Iranian English as a Foreign Language (EFL) studies. In the present study, an attempt is made to provide a systematic review of the correlational studies of Critical Thinking (CT) and Second Language (L2) conducted in Iran. The studies were retrieved from both English and Persian indexing sources such as Google Scholar, Noormags, Civilica, and the Scientific Information Database (SID). Thus, the gray literature was not included. The risk of bias in this systematic review was considered and computed. This review followed the fixed stages of the statistical systematic review, and 77 effect sizes out of 53 published studies were identified. After eliminating seven outliers, 70 studies were included in the meta-analysis (N=9,120). The findings uncovered that CT and EFL learning had a remarkable relationship in Iran. The results covered that language proficiency is complex and requires further investigation and distinct L2 learning-related skills were moderators among the included studies. Based on the findings, EFL learners of Master of Arts (M.A.) levels showed higher associations with CT. Since this meta-analysis can be considered one of the pioneers in internationalizing CT in EFL education, this study might be a cornerstone for subsequent steps in the teaching and research of CT in Iranian EFL educational fields. However, the high heterogeneity and potential publication bias underscore the need for cautious interpretation and further research.

Interactive virtual reality environments and emotions: a systematic review

Emotions influence the way people react in different contexts. Virtual reality (VR) makes it possible to generate environments that can resemble a real experience. These concepts were taken as the basis of the review, focusing on the use of VR on emotions. The search for information was carried out in the Scopus database (179) and other sources of information (17), and the selection criteria were applied to 196 results, such as the user’s interaction with the environment and the application of a software development of VR applications, resulting in the analysis of 16 studies. Unity was found to be used in 81.25% of the articles, HTC Vive appears in 37.5% of the research. The minimum time of application of the experience is 1-min contrasting with the maximum time of 30 min. Only theories of emotions were mentioned in 18.75% of the articles, most of the research uses VR to influence users (56.25%) and with the indicators only 1 article coincides with ISO 25000.

National trends in surgical treatment and clinical outcomes among patients with aneurysmal subarachnoid hemorrhage in the Republic of Korea.

In this study, changes in treatment methods and patient prognosis were analyzed using a Korean nationwide medical insurance information database. Patients with subarachnoid hemorrhage who received surgical treatment for cerebral aneurysm from 2005 to 2020 were included. The specific surgery type was classified using the surgical code and according to whether stents were used. Yearly trends in mortality rates and poor prognosis, using tracheostomy as proxy, were analyzed by a simple regression analysis. A multistep logistic regression analysis was performed to evaluate the risk factors of mortality and poor prognosis. Overall, 83,587 patients were included. Females were predominant (64.5%). Microsurgical clip usage rate decreased by approximately two-thirds from 78.8% in 2005 to 24.4% in 2020. Contrarily, endovascular treatment proportion gradually increased, and stent-assisted coil embolization rate surpassed microsurgical clip usage rate in 2020 (24.6% vs. 24.4%). In the multivariate analysis, endovascular treatment correlated positively with 3-month mortality (hazard ratio [HR]: 1.13, 95% confidence interval [CI]: 1.07-1.19, P<0.0001), although correlated negatively with poor prognosis (tracheostomy) (HR: 0.93, 95% CI: 0.89-0.98, P=0.0050). According to the treatment trend analysis, during the 16 years studied, for patients with subarachnoid hemorrhage due to ruptured cerebral aneurysm, the endovascular treatment rate increased rapidly and stent-assisted coil embolization rate surpassed that of microsurgical clip ligation. Diversification of treatment methods has led to a decrease in mortality and improved prognosis.

Proper name in a normative scientific text

INTRODUCTION. The ability of a proper name to reflect both subject information and multifaceted background information puts it on a par with the main carrier of scientific knowledge – a term. In the study of linguistic expression of knowledge, the question of the role and place of onomastic vocabulary in the content of school education becomes relevant. The purpose of the study is to analyze the qualitative composition, quantitative parameters and nature of the relationship of proper names in the structure of existing educational texts, which will allow us to formulate requirements for the organization of the onomastic content of newly created texts.MATERIALS AND METHODS. The research material was an array of proper names extracted by the method of continuous sampling from the texts of textbooks and programs on all subjects of general secondary education in the late 1980s – early 2000s. When processing the obtained material, presented in the Database format, analytical, comparative, field methods, elements of the statistical method were used. RESULTS AND DISCUSSION. The total number and composition of onomastic units in educational texts were determined, the frequency and prevalence rates of these units were established, the core and peripheral components of this onomastic space were distinguished, the ratio of recurring and single onyms was revealed, their role in expressing subject knowledge was characterized, and the conditions for the optimal organization of educational onomastic space were formulated.CONCLUSION. The obtained data provide an idea of the volume and nature of the onomastic fragment of the generally binding scientific knowledge reflected in the normative scientific texts of the analyzed era. These results create the basis for the implementation of a systematic approach to the organization of onomastic vocabulary within the framework of normative scientific texts. Comparison of the obtained data with data from other time periods will allow us to determine the onomastic invariant and variable elements in different time concepts of the composition of basic onomastic knowledge.

Cryptanalysis and Improvement to the Quantum Private Query Protocol for Enhancing Database Privacy

Abstract In order to protect the privacy of query user and database, some QKD-based quantum private query (QPQ) protocols were proposed. One example is the protocol proposed by Zhou et al., in which the user makes initial quantum states and derives the key bit by comparing the initial quantum state and the outcome state returned from the database by ctrl or shift mode instead of announcing&amp;#xD;two non-orthogonal qubits as others which may leak part secret information. In some extent, the security of the database and the privacy of the user are strengthened. Unfortunately, we find that in this protocol, the dishonest user can obtain, utilizing unambiguous state discrimination, much more database information than that is analyzed in Zhou et al.’s original research. To strengthen the database security, we improved the mentioned protocol by modifying the information returned by the database in various ways. The analysis indicates that the security of the improved protocols is greatly enhanced.

Association between metabolic syndrome and chronic obstructive pulmonary disease development in young individuals: a nationwide cohort study

BackgroundThe association between metabolic syndrome (MetS) and chronic obstructive pulmonary disease (COPD) has not been studied well, particularly in young individuals. We investigated the risk of COPD development in young individuals based on MetS and its components.MethodsWe used the Korean National Health Information Database to identify 6,891,400 individuals aged 20–39 years who participated in the national health check-up service between 2009 and 2012. Then, we identified individuals with MetS and investigated COPD development based on health insurance claims. Cox proportional hazard regression models were used to calculate the adjusted hazard ratio (aHR) for the risk of COPD development.ResultsDuring a mean follow-up period of 8.35 years, 13,784 individuals were newly diagnosed with COPD. MetS was associated with an increased risk of COPD (aHR, 1.18; 95% confidence interval [CI], 1.11–1.24). Among the MetS components, except for hyperglycemia, abdominal obesity (aHR, 1.27; 95% CI, 1.19–1.34), hypertension (aHR, 1.05; 95% CI, 1.01–1.10), hypertriglyceridemia (aHR, 1.11; 95% CI, 1.07–1.16), and low high-density lipoprotein cholesterol levels (aHR, 1.16; 95% CI, 1.11–1.22) were significantly associated with COPD development. A higher number of MetS components correlated with an increased risk of COPD development, with the highest risk observed when all five MetS components were present (aHR, 1.55; 95% CI, 1.28–1.87).ConclusionMetS was associated with COPD development in young individuals. The risk of COPD development increased along with the increasing number of MetS components. These findings suggest that careful monitoring for COPD development is necessary in young individuals with MetS, especially those with multiple components of MetS.

Development and validation of a dynamic nomogram for predicting in-hospital mortality in patients with gastrointestinal bleeding: a retrospective cohort study in the intensive care unit

The study aims to develop and validate a predictive model for effectively predicting in-hospital mortality in patients admitted to the intensive care unit due to Gastrointestinal bleeding (GIB). A retrospective cohort study was conducted, including data from patients in the Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD) and Medical Information Mart for Intensive Care-IV Database (MIMIC-IV) with a diagnosis of GIB. Patients from the eICU-CRD were randomly allocated into both development and validation sets, and those from MIMIC-IV were assigned as an external validation group. Multivariate logistic regression was employed to create a predictive model, which was depicted as a nomogram. This study included a total of 2929 patients with GIB from the eICU-CRD and 718 patients from the MIMIC-IV. To access the dynamic nomogram, please use the following link: https://kangzou.shinyapps.io/DynNomapp_GIB/. The area under the receiver operating characteristic curve for the nomogram was 0.893 in the development set, 0.860 in the internal validation set, and 0.781 in the external validation set. The mortality rate was 25.7% in the high-risk group (nomogram scores > 101.974) and 2.8% in the low-risk group (nomogram scores ≤ 101.974). The nomogram exhibited excellent discrimination, calibration, and clinical utility in predicting in-hospital mortality among patients admitted to the intensive care unit with GIB.

A seventeen-year, population-based study to identify dynamic patterns of interfering neck pain and its burden in South Korea

AimThe aim of this study were to introduce a profile of a nationwide cohort for patients with neck pain and to identify the patterns of recurrent neck pain over time. MethodsHealth insurance data for 1,127,323 patients (43.5 ± 11.5 years, 60.8% females) with neck pain in 2010 were extracted from the National Health Information Database of South Korea. Data on the duration and frequency of neck pain and the number of healthcare visits recorded between 2002 and 2018 were screened and used for descriptive analysis. ResultsDuring the study period, patients experienced 4.1 episodes of neck pain, and 74% of patients experienced multiple episodes. The duration of one episode was 12.1 ± 35.7 days. Following each episode, more than 73% of patients experienced a subsequent episode of neck pain. As patients experienced more episodes, the recurrence rate increased gradually from 73% to 80%, and subsequent episodes occurred in a shorter time and lasted longer with a higher number of healthcare visits, compared to a preceding episode. ConclusionThe study highlighted the dynamic pattern of interfering neck pain, with episodes occurring more frequently and lasting longer over time. Early intensive management with a long-term follow-up is recommended to prevent a dynamic pattern of interfering neck pain.

A indústria brasileira de private equity: Market timing para desinvestimento pós IPO

This is a descriptive, quantitative study that used as a database information from Equity Investment Funds (EIF) and records of 49 companies supported by Private Equity (PE) and Venture Capital (VC) in Brazil, between the years 2000 and 2020, which carried out an IPO and were fully divested. The results show that 2.7 years is the approximate time for total divestment - close to the 3 years of the US market, in addition to the fact that when the shares held by the PE/VC Funds were fully divested, the prices of the shares were higher than the prices at the IPO and, finally, that the exits resulted in positive abnormal returns for investors. Therefore, this study brings contributions to society and to the Applied Social Sciences, as it is innovative in measuring the Market Timing of divestment in the PE/VC industry in Brazil, as well as filling a gap in the internal literature and perhaps assisting researchers interested in further exploring this subject.

Transcriptome analysis for the identification of spot blotch responsive genes and miRNAs in wheat

Spot blotch caused by Bipolaris sorokiniana is one of the most devastating foliar diseases of wheat particularly in South Asian countries including India, Nepal, Bangladesh etc. In the present study, using whole genome transcriptome sequencing data from two contrasting genotypes for spot blotch disease (one resistant and the other susceptible), at three time points after inoculation, we identified a large number of differentially expressed genes (DEGs) and many microRNAs (miRNAs) with their target genes (in silico). The mean number of reads in six libraries were 39.8 millions with a range of 32.1–44.9 million reads per library. The reads from resistant and susceptible genotypes were aligned. The aligned reads had a mean of 32.4 million with a range of 25.0–37.1 million reads. The raw data were deposited into the National Center for Biotechnology Information (NCBI) database under the SRA accession number PRJNA1182498. The DEGs included 5294 upregulated and 4383 downregulated genes. Functional annotation and enrichment analysis showed that the main pathways enriched for the DEGs included photosynthesis-antenna proteins, MAPK signaling pathways, plant-pathogen interactions, circadian rhythm-plant, etc. These DEGs mainly encoded proteins with leucine rich repeat (LRR) domain, F-box-like domain, non-specific serine/threonine-protein kinases (S/TPK), wall-associated receptor kinases (WAKs), etc. Many DEGs also belonged to the following families of transcription factors (TFs): ERF, NAC, WRKY, GRAS, MYB etc. Few DEGs were also associated with pathogenesis related (PR) proteins including PR 1.1, PR 1.2, PR 1.17 and PR 1.19. The results of the present study may be utilized by plant breeders, geneticists and bioinformatician for further research.

Assessment of Metaliteracy Competencies Among Library Professionals in Indian Institutes of Technology

The digital revolution has reshaped academic libraries, requiring new skills from library professionals. This study explores how library professionals at Indian Institutes of Technology (IITs) are adapting to this change through their metaliteracy skills. By surveying 144 library professionals across IITs, we uncovered a complex process of digital adaptation and professional growth. Our findings reveal that most professionals are confidently entering the digital era, with three-quarters showing proficiency in basic digital tools. However, beneath this digital fluency lies a more intricate picture. While many excel in traditional tasks like database management and information retrieval − 65% reported high proficiency – there is notable reluctance when engaging with emerging technologies and cybersecurity challenges. Surprisingly, gender significantly influenced how professionals approached information evaluation and synthesis. Experience, though important for many metaliteracy skills, seemed less relevant in addressing modern concerns such as privacy protection and detecting misinformation. One of the most revealing findings is the gap between competence and teaching ability: although many professionals possess strong technical skills, only 31.5% feel confident in teaching these skills to others. This highlights the urgent need for targeted professional development that considers both gender dynamics and varying experience levels. By shedding light on these patterns, our study offers a pathway to reinforce the digital infrastructure of India’s leading technical institutions, ensuring library professionals can guide future researchers through an increasingly complex information landscape. Our findings not only enhance our understanding of metaliteracy in academic libraries but also provide practical insights for designing training programs to address these gaps. Ultimately, this work contributes to the broader discussion on digital transformation in academic libraries and the evolving role of library professionals in the digital age.

An Extensive Review of Leaching Models for the Forecasting and Integrated Management of Surface and Groundwater Quality

The present study reviews leachate models useful for proactive and rehab actions to safeguard surface and subsurface soft water, which have become even more scarce. Integrated management plans of water basins are of crucial importance since intensively cultivated areas are adding huge quantities of fertilizers to the soil, affecting surface water basins and groundwater. Aquifers are progressively being nitrified on account of the nitrogen-based fertilizer surplus, rendering water for human consumption not potable. Well-tested solute leaching models, standalone or part of a model package, provide rapid site-specific estimates of the leaching potential of chemical agents, mostly nitrates, below the root zone of crops and the impact of leaching toward groundwater. Most of the models examined were process-based or conceptual approaches. Nonetheless, empirical prediction models, though rather simplistic and therefore not preferrable, demonstrate certain advantages, such as less demanding extensive calibration database information requirements, which in many cases are unavailable, not to mention a stochastic approach and the involvement of artificial intelligence (AI). Models were categorized according to the porous medium and agents to be monitored. Integrated packages of nutrient models are irreplaceable elements for extensive catchments to monitor the terrestrial nitrogen-balanced cycle and to contribute to policy making as regards soft water management.