Enhancing hydrological insight: isotopic methods revealing groundwater-surface water interactions in the Lower Quang Tri River Group, Vietnam.

The Lower Quang Tri River Group, situated in central Vietnam, faces a myriad of challenges, notably the decline in groundwater levels and the salinisation of both groundwater and surface water, significantly impacting water availability for domestic, agricultural, and industrial purposes. To address these pressing concerns, this study adopts a comprehensive methodology integrating hydrogeological measurements, isotopic techniques, and chemical analyses of various water sources, including local precipitation, surface water bodies, reservoirs, and groundwater samples. Utilising the deuterium and oxygen-18 signatures (δ2H and δ18O) in water molecules as environmental tracers for the assessment of base flow and water sources enables a nuanced understanding of the intricate interaction between surface water and groundwater. Research findings elucidate that during the dry season, groundwater recharge primarily stems from water in the reservoirs over approximately seven months. Base flow contributes between 80 and 85 % of streamflow during the rainy season, escalating to 100 % during the dry season. The mean travelling time of the base flow is estimated at 120 ± 10 days using the sine curve model developed by Rodgers et al. The insights gleaned from this study are poised to play a pivotal role in guiding the local water resources managers in licensing for the exploitation of a right quantities of groundwater as sustainable management strategies in the region.

Experimental and computational study of binary mixture ethanolamine and 2-amino-2-methyl-1-propanol.

The present work involves experimental and computational investigations into the density of pure and mixed states of ethanolamine (ET) and 2-amino-2-methyl-1-propanol (AMP) under a pressure of 1 atm and temperatures ranging from 293.15 K to 333.15 K The density data were used to derive the excess molar volume, thermal expansion coefficient, and isothermal coefficient of pressure excess molar enthalpy. The Redlich-Kister equation was employed to calculate the excess molar and its accompanying coefficients. In the gas phase, density functional theory (DFT) was utilized to explore the most stable structures of ET … ET, AMP … AMP, and the ET … AMP mixture. Molecular dynamics simulation (MD) was used to calculate the structural properties of these mixtures in the liquid phase. Radial distribution function (RDFs) combined distribution function (CDF) and spatial distribution function (SDF) in different mole fractions calculated in the liquid phase. The intramolecular and intermolecular interactions of ethanolamine and AMP were obtained using the radial distribution function in different molar fractions. It was found that the ethanolamine molecule has a greater tendency to form intramolecular hydrogen bonds, while the AMP molecule has a greater tendency to form intermolecular hydrogen bonds.

Semantic units: organizing knowledge graphs into semantically meaningful units of representation.

BACKGROUND: In today's landscape of data management, the importance of knowledge graphs and ontologies is escalating as critical mechanisms aligned with the FAIR Guiding Principles-ensuring data and metadata are Findable, Accessible, Interoperable, and Reusable. We discuss three challenges that may hinder the effective exploitation of the full potential of FAIR knowledge graphs. RESULTS: We introduce "semantic units" as a conceptual solution, although currently exemplified only in a limited prototype. Semantic units structure a knowledge graph into identifiable and semantically meaningful subgraphs by adding another layer of triples on top of the conventional data layer. Semantic units and their subgraphs are represented by their own resource that instantiates a corresponding semantic unit class. We distinguish statement and compound units as basic categories of semantic units. A statement unit is the smallest, independent proposition that is semantically meaningful for a human reader. Depending on the relation of its underlying proposition, it consists of one or more triples. Organizing a knowledge graph into statement units results in a partition of the graph, with each triple belonging to exactly one statement unit. A compound unit, on the other hand, is a semantically meaningful collection of statement and compound units that form larger subgraphs. Some semantic units organize the graph into different levels of representational granularity, others orthogonally into different types of granularity trees or different frames of reference, structuring and organizing the knowledge graph into partially overlapping, partially enclosed subgraphs, each of which can be referenced by its own resource. CONCLUSIONS: Semantic units, applicable in RDF/OWL and labeled property graphs, offer support for making statements about statements and facilitate graph-alignment, subgraph-matching, knowledge graph profiling, and for management of access restrictions to sensitive data. Additionally, we argue that organizing the graph into semantic units promotes the differentiation of ontological and discursive information, and that it also supports the differentiation of multiple frames of reference within the graph.

Developing a Novel Ontology for Cybersecurity in Internet of Medical Things-Enabled Remote Patient Monitoring.

IoT has seen remarkable growth, particularly in healthcare, leading to the rise of IoMT. IoMT integrates medical devices for real-time data analysis and transmission but faces challenges in data security and interoperability. This research identifies a significant gap in the existing literature regarding a comprehensive ontology for vulnerabilities in medical IoT devices. This paper proposes a fundamental domain ontology named MIoT (Medical Internet of Things) ontology, focusing on cybersecurity in IoMT (Internet of Medical Things), particularly in remote patient monitoring settings. This research will refer to similar-looking acronyms, IoMT and MIoT ontology. It is important to distinguish between the two. IoMT is a collection of various medical devices and their applications within the research domain. On the other hand, MIoT ontology refers to the proposed ontology that defines various concepts, roles, and individuals. MIoT ontology utilizes the knowledge engineering methodology outlined in Ontology Development 101, along with the structured life cycle, and establishes semantic interoperability among medical devices to secure IoMT assets from vulnerabilities and cyberattacks. By defining key concepts and relationships, it becomes easier to understand and analyze the complex network of information within the IoMT. The MIoT ontology captures essential key terms and security-related entities for future extensions. A conceptual model is derived from the MIoT ontology and validated through a case study. Furthermore, this paper outlines a roadmap for future research, highlighting potential impacts on security automation in healthcare applications.

Fundamental drying and agglomeration experiments with bio-fraction and refuse derived fuel for the development of pyrolysis reactor feed.

The EU's circular economy concept necessitates increasing the recycling ratio of municipal solid wastes. There are many existing mechanical-biological processing plants in Hungary for the preparation of residual municipal solid wastes (RMSWs). The two most important products of these plants are the bio-fraction and the refuse derived fuel (RDF). Currently, there are problems with both of these material streams in Hungary, since most of the bio-fraction is still landfilled, and the local thermal utilisation of the RDF has not been implemented yet. The high moisture content of the produced bio-fraction and RDF causes difficulties for the downstream operations; therefore, there is recent engineering interest in drying and agglomeration of these materials. The authors have carried out systematic and parallel drying and briquetting experimental series to study the effect of the material, material composition, mass (volume or surface) of the material, particle size distribution and pre-treatment with a cutting mill on drying intensity in a 1 m3 oven and their effect on briquettability by a laboratory briquette press. The initial slope of the relative moisture loss as function of time was determined. Process engineering design methods of convective hot air-drying can be further developed taking into account the research results. Results can be used for the design of the feed of a pyrolysis reactor once reactor experiments have provided the optimal feed requirements.

Techno-environmental analysis to valorize the secondary energy resources from refuse-derived fuel-based waste to energy plant.

The present study quantifies the environmental and sustainability impacts associated with municipal solid waste management (MSWM) in India which plays a vital environmental issue in recent times. The upsurge in population has resulted in massive waste generation, leading to a concerning rise in the level of greenhouse gas (GHG) emissions. Therefore, the sustainable management of MSW has been discussed and highlights the conversion of MSW into refuse-derived fuel (RDF) to identify its potential for generating electricity in waste-to-energy (WtE) plants. The life cycle assessment (LCA) study has been done to identify and compare the environmental impacts associated with different scenarios (SC) as SC1: landfilling without energy recovery, SC2: open burning and SC3: processing of RDF in WtE plant by considering the nine impact categories from the inventory data obtained over a period of 12 consecutive months (Jan 2021-Jan 2022). The results exhibited that the global warming potential caused by emissions of GHG are in the order of SC1 (1188 kg CO2 eq) > SC2 (752 kg CO2 eq) > SC3 (332 kg CO2 eq), respectively from 1 t of MSW. It is concluded that the WtE plant can help in the reduction of environmental issues, strengthening the capacity of electricity generation and improving the aesthetic view of the city which is socially acceptable as well. Thus, WtE technology can help in achieving sustainable development goal 12 to regenerate the sustainable secondary resources for the twenty-first century and minimize global climate change.

Electronic Health Record and Semantic Issues Using Fast Healthcare Interoperability Resources: Systematic Mapping Review.

BACKGROUND: The increasing use of electronic health records and the Internet of Things has led to interoperability issues at different levels (structural and semantic). Standards are important not only for successfully exchanging data but also for appropriately interpreting them (semantic interoperability). Thus, to facilitate the semantic interoperability of data exchanged in health care, considerable resources have been deployed to improve the quality of shared clinical data by structuring and mapping them to the Fast Healthcare Interoperability Resources (FHIR) standard. OBJECTIVE: The aims of this study are 2-fold: to inventory the studies on FHIR semantic interoperability resources and terminologies and to identify and classify the approaches and contributions proposed in these studies. METHODS: A systematic mapping review (SMR) was conducted using 10 electronic databases as sources of information for inventory and review studies published during 2012 to 2022 on the development and improvement of semantic interoperability using the FHIR standard. RESULTS: A total of 70 FHIR studies were selected and analyzed to identify FHIR resource types and terminologies from a semantic perspective. The proposed semantic approaches were classified into 6 categories, namely mapping (31/126, 24.6%), terminology services (18/126, 14.3%), resource description framework or web ontology language-based proposals (24/126, 19%), annotation proposals (18/126, 14.3%), machine learning (ML) and natural language processing (NLP) proposals (20/126, 15.9%), and ontology-based proposals (15/126, 11.9%). From 2012 to 2022, there has been continued research in 6 categories of approaches as well as in new and emerging annotations and ML and NLP proposals. This SMR also classifies the contributions of the selected studies into 5 categories: framework or architecture proposals, model proposals, technique proposals, comparison services, and tool proposals. The most frequent type of contribution is the proposal of a framework or architecture to enable semantic interoperability. CONCLUSIONS: This SMR provides a classification of the different solutions proposed to address semantic interoperability using FHIR at different levels: collecting, extracting and annotating data, modeling electronic health record data from legacy systems, and applying transformation and mapping to FHIR models and terminologies. The use of ML and NLP for unstructured data is promising and has been applied to specific use case scenarios. In addition, terminology services are needed to accelerate their use and adoption; furthermore, techniques and tools to automate annotation and ontology comparison should help reduce human interaction.

Case-Reported Data Management Methodology Using an RDF Data Model for Building a Multicenter Clinical Registry.

In multicenter clinical research, case-reported clinical data are managed for each research project. Participating institutions manage the mapping between standardized codes and in-house codes. To use the data extracted from electronic medical records in case report forms, it is necessary to pay attention to the gap in the semantic hierarchy. Managing mapping information between in-house and standardized codes is centralized in Resource Description Framework (RDF) stores. The relationship between standardized and in-house codes is described in RDF and stored in RDF stores. RESTful APIs for accessing RDF stores in SPARQL was developed and verified. The relationship between standardized codes and in-house codes of pharmaceuticals was expressed in RDF triples. As a +result of the operational verification of the implemented APIs, it was confirmed that data management with knowledge bases expressed in RDF graphs is possible. The ability to dynamically modify mapping definitions enables flexible data management and ease of operational restrictions.

Assessing resolvability, parsability, and consistency of RDF resources: a use case in rare diseases.

INTRODUCTION: Healthcare data and the knowledge gleaned from it play a key role in improving the health of current and future patients. These knowledge sources are regularly represented as 'linked' resources based on the Resource Description Framework (RDF). Making resources 'linkable' to facilitate their interoperability is especially important in the rare-disease domain, where health resources are scattered and scarce. However, to benefit from using RDF, resources need to be of good quality. Based on existing metrics, we aim to assess the quality of RDF resources related to rare diseases and provide recommendations for their improvement. METHODS: Sixteen resources of relevance for the rare-disease domain were selected: two schemas, three metadatasets, and eleven ontologies. These resources were tested on six objective metrics regarding resolvability, parsability, and consistency. Any URI that failed the test based on any of the six metrics was recorded as an error. The error count and percentage of each tested resource were recorded. The assessment results were represented in RDF, using the Data Quality Vocabulary schema. RESULTS: For three out of the six metrics, the assessment revealed quality issues. Eleven resources have non-resolvable URIs with proportion to all URIs ranging from 0.1% (6/6,712) in the Anatomical Therapeutic Chemical Classification to 13.7% (17/124) in the WikiPathways Ontology; seven resources have undefined URIs; and two resources have incorrectly used properties of the 'owl:ObjectProperty' type. Individual errors were examined to generate suggestions for the development of high-quality RDF resources, including the tested resources. CONCLUSION: We assessed the resolvability, parsability, and consistency of RDF resources in the rare-disease domain, and determined the extent of these types of errors that potentially affect interoperability. The qualitative investigation on these errors reveals how they can be avoided. All findings serve as valuable input for the development of a guideline for creating high-quality RDF resources, thereby enhancing the interoperability of biomedical resources.

Steam gasification of char derived from refuse-derived fuel pyrolysis: adsorption behaviour in phenol solutions.

The increasing waste generation trends resulted in growing attention to the technologies that aim to reduce or prevent landfilling. The pyrolysis and gasification of refuse-derived fuel (RDF) allow waste to be turned into new raw materials, like pyrolysis gas and syngas. However, the wet gas cleaning processes result in the production of highly contaminated liquid waste. Phenolic compounds are common constituents of this wastewater and often appear in the wastewater of other industries as well. In this research, the laboratory-scale steam gasification of an RDF char was performed to produce syngas and adsorbent simultaneously. The RDF was previously pyrolyzed at 700 °C maximum temperature in a Hungarian pyrolysis pilot plant with approximately 120 kg h-1 capacity. In this thermal waste processing plant, the pyrolysis gas is already utilised by burning, but currently, the char ends up in landfills. The gasification of char samples was examined with different steam-to-carbon ratios (0.56, 0.84, and 1.12) and duration (30, 60, and 120 min) at 900 °C. Following gasification, the phenol removal capability of the solid by-products was investigated. The results show that its composition and energetic properties make the produced syngas more suitable to use as a raw material in the chemical industry rather than a fuel. At lower concentrations, the effectiveness of the solid by-product for phenol removal was comparable to commercial activated carbon. These are promising results about producing activated carbon from waste without any chemical treatment.

Shape Expressions (ShEx) schemas for the FHIR R5 specification.

This work continues along a visionary path of using Semantic Web standards such as RDF and ShEx to make healthcare data easier to integrate for research and leading-edge patient care. The work extends the ability to use ShEx schemas to validate FHIR RDF data, thereby enhancing the semantic web ecosystem for working with FHIR and non-FHIR data using the same ShEx validation framework. It updates FHIR's ShEx schemas to fix outstanding issues and reflect changes in the definition of FHIR RDF. In addition, it experiments with expressing FHIRPath constraints (which are not captured in the XML or JSON schemas) in ShEx schemas. These extended ShEx schemas were incorporated into the FHIR R5 specification and used to successfully validate FHIR R5 examples that are included with the FHIR specification, revealing several errors in the examples.

Structural and Electromagnetic Signatures of Anatase and Rutile NTs and Sheets in Three Different Water Models under Different Temperature Conditions.

Experimental studies of TiO2 nanotubes have been conducted for nearly three decades and have revealed the remarkable advantages of this material. Research based on computer simulations is much rarer, with research using density functional theory (DFT) being the most significant in this field. It should be noted, however, that this approach has significant limitations when studying the macroscopic properties of nanostructures such as nanosheets and nanotubes. An alternative with great potential has emerged: classical molecular dynamics simulations (MD). MD Simulations offer the possibility to study macroscopic properties such as the density of phonon states (PDOS), power spectra, infrared spectrum, water absorption and others. From this point of view, the present study focuses on the distinction between the phases of anatase and rutile TiO2. The LAMMPS package is used to study both the structural properties by applying the radial distribution function (RDF) and the electromagnetic properties of these phases. Our efforts are focused on exploring the effect of temperature on the vibrational properties of TiO2 anatase nanotubes and an in-depth analysis of how the phononic softening phenomenon affects TiO2 nanostructures to improve the fundamental understanding in different dimensions and morphological configurations. A careful evaluation of the stability of TiO2 nanolamines and nanotubes at different temperatures is performed, as well as the adsorption of water on the nanosurface of TiO2, using three different water models.

Cultural gems linked open data: Mapping culture and intangible heritage in European cities.

The recovery and resilience of the cultural and creative sectors after the COVID-19 pandemic is a current topic with priority for the European Commission. Cultural gems is a crowdsourced web platform managed by the Joint Research Centre of the European Commission aimed at creating community-led maps as well as a common repository for cultural and creative places across European cities and towns. More than 130,000 physical locations and online cultural activities in more than 300 European cities and towns are currently tracked by the application. The main objective of Cultural gems consists in raising a holistic vision of European culture, reinforcing a sense of belonging to a common European cultural space. This data article describes the ontology developed for Cultural gems, adopted to represent the domain of knowledge of the application by means of FAIR (Findable, Accessible, Interoperable, Reusable) principles and following the paradigms of Linked Open Data (LOD). We provide an overview of this dataset, and describe the ontology model, along with the services used to access and consume the data.

Background optimization of powder electron diffraction for implementation of the e-PDF technique and study of the local structure of iron oxide nanocrystals.

The local structural characterization of iron oxide nanoparticles is explored using a total scattering analysis method known as pair distribution function (PDF) (also known as reduced density function) analysis. The PDF profiles are derived from background-corrected powder electron diffraction patterns (the e-PDF technique). Due to the strong Coulombic interaction between the electron beam and the sample, electron diffraction generally leads to multiple scattering, causing redistribution of intensities towards higher scattering angles and an increased background in the diffraction profile. In addition to this, the electron-specimen interaction gives rise to an undesirable inelastic scattering signal that contributes primarily to the background. The present work demonstrates the efficacy of a pre-treatment of the underlying complex background function, which is a combination of both incoherent multiple and inelastic scatterings that cannot be identical for different electron beam energies. Therefore, two different background subtraction approaches are proposed for the electron diffraction patterns acquired at 80 kV and 300 kV beam energies. From the least-square refinement (small-box modelling), both approaches are found to be very promising, leading to a successful implementation of the e-PDF technique to study the local structure of the considered nanomaterial.

A comparison of approaches to accessing existing biological and chemical relational databases via SPARQL.

Current biological and chemical research is increasingly dependent on the reusability of previously acquired data, which typically come from various sources. Consequently, there is a growing need for database systems and databases stored in them to be interoperable with each other. One of the possible solutions to address this issue is to use systems based on Semantic Web technologies, namely on the Resource Description Framework (RDF) to express data and on the SPARQL query language to retrieve the data. Many existing biological and chemical databases are stored in the form of a relational database (RDB). Converting a relational database into the RDF form and storing it in a native RDF database system may not be desirable in many cases. It may be necessary to preserve the original database form, and having two versions of the same data may not be convenient. A solution may be to use a system mapping the relational database to the RDF form. Such a system keeps data in their original relational form and translates incoming SPARQL queries to equivalent SQL queries, which are evaluated by a relational-database system. This review compares different RDB-to-RDF mapping systems with a primary focus on those that can be used free of charge. In addition, it compares different approaches to expressing RDB-to-RDF mappings. The review shows that these systems represent a viable method providing sufficient performance. Their real-life performance is demonstrated on data and queries coming from the neXtProt project.

Mapping the SPHN Dataset to FHIR.

Several European health data research initiatives aim to make health data FAIR for research and healthcare, and supply their national communities with coordinated data models, infrastructures, and tools. We present a first map of the Swiss Personalized Healthcare Network dataset to Fast Healthcare Interoperability Resources (FHIR®). All concepts could be mapped using 22 FHIR resources and three datatypes. Deeper analyses will follow before creating a FHIR specification, to potentially enable data conversion and exchange between research networks.

Automated approach for quality assessment of RDF resources.

INTRODUCTION: The Semantic Web community provides a common Resource Description Framework (RDF) that allows representation of resources such that they can be linked. To maximize the potential of linked data - machine-actionable interlinked resources on the Web - a certain level of quality of RDF resources should be established, particularly in the biomedical domain in which concepts are complex and high-quality biomedical ontologies are in high demand. However, it is unclear which quality metrics for RDF resources exist that can be automated, which is required given the multitude of RDF resources. Therefore, we aim to determine these metrics and demonstrate an automated approach to assess such metrics of RDF resources. METHODS: An initial set of metrics are identified through literature, standards, and existing tooling. Of these, metrics are selected that fulfil these criteria: (1) objective; (2) automatable; and (3) foundational. Selected metrics are represented in RDF and semantically aligned to existing standards. These metrics are then implemented in an open-source tool. To demonstrate the tool, eight commonly used RDF resources were assessed, including data models in the healthcare domain (HL7 RIM, HL7 FHIR, CDISC CDASH), ontologies (DCT, SIO, FOAF, ORDO), and a metadata profile (GRDDL). RESULTS: Six objective metrics are identified in 3 categories: Resolvability (1), Parsability (1), and Consistency (4), and represented in RDF. The tool demonstrates that these metrics can be automated, and application in the healthcare domain shows non-resolvable URIs (ranging from 0.3% to 97%) among all eight resources and undefined URIs in HL7 RIM, and FHIR. In the tested resources no errors were found for parsability and the other three consistency metrics for correct usage of classes and properties. CONCLUSION: We extracted six objective and automatable metrics from literature, as the foundational quality requirements of RDF resources to maximize the potential of linked data. Automated tooling to assess resources has shown to be effective to identify quality issues that must be avoided. This approach can be expanded to incorporate more automatable metrics so as to reflect additional quality dimensions with the assessment tool implementing more metrics.

Development of binary classification models for grouping hydroxylated polychlorinated biphenyls into active and inactive thyroid hormone receptor agonists.

Some adverse effects of hydroxylated polychlorinated biphenyls (OH-PCBs) in humans are presumed to be initiated via thyroid hormone receptor (TR) binding. Due to the trial-and-error approach adopted for OH-PCB selection in previous studies, experiments designed to test the TR binding hypothesis mostly utilized inactive OH-PCBs, leading to considerable waste of time, effort and other material resources. In this paper, linear discriminant analysis (LDA) and binary logistic regression (LR) were used to develop classification models to group OH-PCBs into active and inactive TR agonists using radial distribution function (RDF) descriptors as predictor variables. The classifications made by both LDA and LR models on the training set compounds resulted in an accuracy of 84.3%, sensitivity of 72.2% and specificity of 90.9%. The areas under the ROC curves, constructed with the training set data, were found to be 0.872 and 0.880 for LDA and LR models, respectively. External validation of the models revealed that 76.5% of the test set compounds were correctly classified by both LDA and LR models. These findings suggest that the two models reported in this paper are good and reliable for classifying OH-PCB congeners into active and inactive TR agonists.

CASBERT: BERT-based retrieval for compositely annotated biosimulation model entities.

Maximising FAIRness of biosimulation models requires a comprehensive description of model entities such as reactions, variables, and components. The COmputational Modeling in BIology NEtwork (COMBINE) community encourages the use of Resource Description Framework with composite annotations that semantically involve ontologies to ensure completeness and accuracy. These annotations facilitate scientists to find models or detailed information to inform further reuse, such as model composition, reproduction, and curation. SPARQL has been recommended as a key standard to access semantic annotation with RDF, which helps get entities precisely. However, SPARQL is unsuitable for most repository users who explore biosimulation models freely without adequate knowledge of ontologies, RDF structure, and SPARQL syntax. We propose here a text-based information retrieval approach, CASBERT, that is easy to use and can present candidates of relevant entities from models across a repository's contents. CASBERT adapts Bidirectional Encoder Representations from Transformers (BERT), where each composite annotation about an entity is converted into an entity embedding for subsequent storage in a list of entity embeddings. For entity lookup, a query is transformed to a query embedding and compared to the entity embeddings, and then the entities are displayed in order based on their similarity. The list structure makes it possible to implement CASBERT as an efficient search engine product, with inexpensive addition, modification, and insertion of entity embedding. To demonstrate and test CASBERT, we created a dataset for testing from the Physiome Model Repository and a static export of the BioModels database consisting of query-entities pairs. Measured using Mean Average Precision and Mean Reciprocal Rank, we found that our approach can perform better than the traditional bag-of-words method.

Improvement of energy recovery potential of wet-refuse-derived fuel through bio-drying process.

This paper proposes novel wet-refuse-derived fuel (Wet-RDF) bio-drying process with the variation of initial organic substrate and moisture content. The bio-drying was carried out using 0.3 m3 lysimeter aerated continuously at different rates. Two conditions of Wet-RDF feedstock tested included: Experiment A ‒ 37% organic substrate and 58% moisture content with an initial heating value of 2,889 kcal/kg; and Experiment B ‒ 28% organic substrate and 35% moisture content with an initial heating value of 4,174 kcal/kg. The bio-drying was performed in both experiments under negative ventilation mode and non-ventilation mode, the ventilation mode was set at the aeration rates of 0.2 m3/kg/day and 0.4 m3/kg/day. The results suggest that the optimum aeration rate was 0.4 m3/kg/day, achieving a 30% moisture reduction and a 60% heating value increase from their initial values. As a result, the improved wet-RDF qualified for the local cement industry's standard in terms of heating value.