Complex Type Research Articles

QORAQALPOG‘ISTON OYKONIMLARINING GRAMMATIK TUZILISHI

In toponymy, the analysis of toponyms based on their grammatical structure allows us to determine their semantic features and lexical basis. The article highlights simple and complex types of oikonyms of Karakalpakstan based on their grammatical structure. The functional and semantic properties of affixes in territorial geographical names are revealed.

Stress Prediction Processes of Metal Pressure-Bearing Complex Components in Thermal Power Plants Based on Machine Learning

The real-time stress assessment of metal pressure components is one of the key factors in ensuring the safe operation of thermal power plants. To address the challenge of real-time prediction of stress in the key areas of complex special-shaped metal pressure-bearing components in a certain domestic 300 MW thermal power plant, three typical complex metal pressure-bearing components, the main steam pipe tee (MSPT), the steam drum downcomer joint (DDJ) and the header ligament (HL), were taken as research objects. The stress distribution of the three complex metal pressure-bearing components under different conditions was analyzed through the finite element method, and the stress results at the dangerous points were used as samples to establish training sample data. Subsequently, different machine learning methods were employed to train the sample data. The training results indicate that neural networks (NNs) and the Auto-Sklearn Regression (ASR) models can accurately predict the stress of the key parts of complex metal pressure-bearing components in real time. The ASR method demonstrates better performance in stress prediction of the main steam pipe tee, with a prediction accuracy of ≥96%. The NN model shows better prediction for the header ligament, with a prediction accuracy of ≥94%. These research findings provide effective support for the high-temperature lifespan assessment and safe operation of thermal power plants.

A Study of Knowledge Graph and IoT Integration-Based Anomalous Event Tracking Method for Digital Platforms

In digital platforms, abnormal events involve multiple data sources and complex information types, and the difficulty of tracking them increases due to the similarity and interaction between components, operations, and user behavior. Therefore, in order to achieve precise tracking and efficient processing of abnormal events, and thereby improve the stability and security of the platform, a digital platform abnormal event tracking method based on a knowledge graph is proposed. First, using data mining and association rule techniques, abnormal event data in the digital platform are effectively collected and integrated. Subsequently, the data are input into a model that integrates residual atrous convolutional neural networks and conditional random fields to achieve precise identification of key entities. On the basis of entity recognition, the correlation between entities is extracted and a knowledge graph architecture for abnormal events is constructed, providing a solid foundation for subsequent deep analysis. Through a visual interface, the knowledge graph of abnormal events can be intuitively displayed, making it easy for users to quickly understand the full picture of the event. At the same time, the knowledge graph subgraph matching algorithm is adopted, combined with flow graph indexing and optimal matching sequence, to achieve accurate tracking and recognition of abnormal events. The experimental results show that this method can effectively track abnormal events in the digital platform. The first detection time is relatively short, with a mishandling time of 8.3[Formula: see text]s and data duplication of 7.9[Formula: see text]s. The continuous tracking time is long, with a security vulnerability of 50[Formula: see text]min. The false alarm rate is low, with the highest being 2.1% for data duplication, and the false miss rate is also low, with the highest being 0.8% for mishandling. This method can identify the number of abnormal events, which helps to understand the stability and health status of the platform. By timely and effectively preventing abnormal events, the frequency of their occurrence can be reduced, and the overall security and stability of the platform can be improved.

Mitochondrial Dysfunction in HFpEF: Potential Interventions Through Exercise.

HFpEF is a prevalent and complex type of heart failure. The concurrent presence of conditions such as obesity, hypertension, hyperglycemia, and hyperlipidemia significantly increase the risk of developing HFpEF. Mitochondria, often referred to as the powerhouses of the cell, are crucial in maintaining cellular functions, including ATP production, intracellular Ca2+ regulation, reactive oxygen species generation and clearance, and the regulation of apoptosis. Exercise plays a vital role in preserving mitochondrial homeostasis, thereby protecting the cardiovascular system from acute stress, and is a fundamental component in maintaining cardiovascular health. In this study, we review the mitochondrial dysfunction underlying the development and progression of HFpEF. Given the pivotal role of exercise in modulating cardiovascular diseases, we particularly focus on exercise as a potential therapeutic strategy for improving mitochondrial function. Graphical abstract Note: This picture was created with BioRender.com.

Efficient Tomato Disease Detection Using MaxMin-Diffusion Mechanism and Lightweight Techniques

This paper proposes a disease detection model based on the maxmin-diffusion mechanism, aimed at improving the accuracy and robustness of disease detection tasks in the agricultural field. With the development of smart agriculture, automated disease detection has become one of the key tasks driving agricultural modernization. Traditional disease detection models often suffer from significant accuracy loss and robustness issues when dealing with complex disease types and dynamically changing time-series data. To address these problems, this paper introduces the maxmin-diffusion mechanism, which dynamically adjusts attention weights to enhance the model’s focus on key disease regions while suppressing interference from irrelevant areas, significantly improving the segmentation accuracy of disease regions. Through a series of experiments, the proposed model demonstrates outstanding performance across various disease detection tasks. For bacterial spot disease detection, the model achieves a precision of 0.98, recall of 0.95, accuracy of 0.96, and mIoU of 0.96, indicating that it can efficiently and accurately identify disease regions even in complex backgrounds. Compared to traditional self-attention and CBAM mechanisms, the maxmin-diffusion mechanism shows significant advantages in fine-grained feature extraction and time-series data processing, particularly in the recognition of dynamically changing disease regions, where it exhibits higher detection accuracy and robustness. Furthermore, the model underwent lightweight optimization, enabling the proposed disease detection model to not only achieve high-precision detection but also run efficiently on resource-constrained mobile devices. This provides strong technical support for the application of smart agriculture.

Evolving Immunotherapy Strategies in Gastrointestinal Neuroendocrine Neoplasms.

Treatment for neuroendocrine neoplasms (NENs) is tailored to the tumor's site of origin, grade, and differentiation. NENs are categorized into two main types: well-differentiated neuroendocrine tumors (NETs), which tend to grow more slowly and are less aggressive, and poorly differentiated neuroendocrine carcinomas (NECs), which are highly aggressive and harder to treat. Treatment options for NETs range from somatostatin analogues and mTOR inhibitors to peptide receptor radionuclide therapy (PRRT) with Lutetium-177 dotatate. In cases where the disease progresses more rapidly, cytotoxic chemotherapy may also be considered. In contrast, chemotherapy plays a central role in treating NECs, often following protocols similar to those used for small cell lung cancer. Exciting progress is being made in the development of new therapies for NENs. Inspired by the success of immunotherapy in other cancers, clinical trials have begun to explore its potential in NENs. Early findings suggest that immune checkpoint inhibitors (ICIs) may offer benefits, especially in patients with higher-grade NETs and NECs. However, because NENs have an immunologically "cold" tumor microenvironment-meaning they are less likely to trigger an immune response-new strategies are needed to boost ICI efficacy. To overcome this challenge, researchers are exploring innovative approaches, such as combining dual ICIs or pairing ICIs with other therapeutic agents to make the tumors more responsive to immune attack. Moreover, there is growing enthusiasm for cutting-edge therapies designed to enhance the immune system's ability to recognize and destroy cancer cells. These include bispecific T cell engagers, chimeric antigen receptor T cells, tumor-infiltrating lymphocytes, oncolytic viruses, and cancer vaccines. While their effectiveness in NENs is still being studied, these approaches hold considerable promise, offering new hope for patients with this challenging and complex cancer type.

Bis(diiminate)-Supported Bimetallic Complexes: Tri-Coordinated Zinc for Nitrile and Carbodiimide Hydroboration.

We report the synthesis and characterization of bis(diiminate)-supported tricoordinated zinc complexes (1-4) and demonstrate the catalytic activity of one representative compound in the hydroboration of nitriles and carbodiimides using pinacolborane (HBpin). Experimental and theoretical studies were performed to elucidate the reaction mechanism. Our findings indicate that the hydroboration reaction initiates with the formation of a tricoordinated zinc hydride intermediate, followed by the subsequent attack of nitriles and carbodiimides. This leads to the formation of a four-membered metallacycle before the release of the diborylated amine. This work provides access to new types of zinc complexes and highlights its effectiveness in the hydroboration of nitriles and carbodiimides, offering a milder alternative to existing reduction methods.

TRAF2 and RIPK1 redundantly mediate classical NFκB signaling by TNFR1 and CD95-type death receptors

This study suggests a modified model of TNFR1-induced complex I-mediated NFκB signaling. Evaluation of a panel of five tumor cell lines (HCT116-PIK3CAmut, SK-MEL-23, HeLa-RIPK3, HT29, D10) with TRAF2 knockout revealed in two cell lines (HT29, HeLa-RIPK3) a sensitizing effect for death receptor-induced necroptosis and in one cell line (D10) a mild sensitization for TNFR1-induced apoptosis. TRAF2 deficiency inhibited death receptor-induced classical NFκB-mediated production of IL-8 only in a subset of cell lines and only partly. TRAF5, furthermore, failed to improve DR-induced NFκB signaling in HCT116-PIK3CAmut and HCT116-PIK3CAmut-TRAF2KO cells. These findings argue for a non-obligatory role of TRAF2 in death receptor-induced classical NFκB signaling. Similar as in TRAF2-deficient cells, TNF- and CD95L-induced NFκB signaling was found to be only poorly affected in RIPK1KO cells and in cells treated with the RIPK1-specific PROTAC LD4172. Intriguingly, however, death receptor-induced NFκB signaling was completely inhibited in HCT116-PIK3CAmut cells double deficient for TRAF2 and RIPK1 and in TRAF2-deficient cells treated with LD4172. Moreover, with exception of recruitment of TRADD, acting upstream to TRAF2 and parallel to RIPK1, TNFR1 signaling complex formation was abrogated in TRAF2-RIPK1 DKO cells. Based on our findings, two distinguishable types of TNFR1-interacting complexes promote TNF-induced NFκB signaling: First, a TRADD-TRAF2/cIAP utilizing complex Ia which becomes evident in RIPK1-deficient cells. Second, a non-modified RIPK1 utilizing complex Ib which acts in TRADD- or TRAF2-deficient cells. Complex Ia and Ib may furthermore interact and cooperate to ubiquitinate RIPK1 resulting in a modified complex Ia/b preventing complex Ia and Ib to convert to the established TNFR1-induced cytotoxic complexes IIa and IIb.

Identification of novel triazolylquinoxaline-based metal complexes supported by experimental and virtual screenings.

The formation of novel complexes from so far non-investigated ligands and different metal centers is important for the development of new functional materials such as (photo)catalysts or biologically active compounds. Still, promising strategies to quickly and systematically investigate the complexation behavior of selected ligands are rare. We developed an NMR-based screening approach to monitor changes within reaction mixtures containing metals and ligands on a small scale via a simple but reliable protocol. Based on the obtained data, we could draw conclusions on the formation of 2-(1',2',3'-triazol-1'yl)quinoxaline-based transition metal complexes. The NMR screening results obtained were confirmed by the repetition of selected experiments on a large scale, and wherever possible, the type of complex obtained was evaluated by crystal structure elucidation. We could show the versatile complexation of the selected ligands with copper, gold, and silver in a bridging, chelating, or monodentate manner. The calculated theoretical properties supported the experimental results and enabled initial in silico predictions of similar compounds before conducting the complexation experiments and structural analyses.

Structure of Hydrothermally Stable Acid Sites and their Catalytic Role in P-Modified ZSM-5 Zeolite Revealed by Solid-State NMR Spectroscopy.

The ZSM-5 zeolite is the key active component in high-severity fluid catalytic cracking (FCC) catalysts and is routinely activated by phosphorus compounds in industrial production. To date, however, the detailed structure and function of the introduced phosphorus still remain ambiguous, which hampers the rational design of highly efficient catalysts. In this work, using advanced solid-state NMR techniques, we have quantitatively identified a total of seven types of P-containing complexes in P-modified ZSM-5 zeolite and clearly revealed their structure, location, and catalytic role. The experimental findings indicate that the introduced phosphorus can stabilize a portion of the aluminum atoms in the lattice by forming an energetically favorable framework-bound Si-OH-Al-O-P structure inside the zeolite channels, preserving more acidic bridging hydroxyl groups under the working conditions of the catalyst. Besides, two other types of hydrothermally stable phosphoric acid species (H3PO4 and H4P2O7) captured by neighboring silanol groups (H3PO4···HO-Si(SiO4)3 and H4P2O7···HO-Si(SiO4)3) are identified. For the FCC process, the framework-bound Si-OH-Al-O-P structure is proven to be the active site in the conversion of the FCC reactant, while the two phosphoric acid species can promote the yield of C2-C4 olefins.

Construction and Reactivity of Benzimidazole‐Modified Thiolate‐Bridged Diiron Complexes with Different Electronic Structures

Thiolate‐bridged diiron complexes have drawn extensive attention due to their wide applications in the biomimetic simulation for the structure and function of various metalloenzymes and the related bioinspired catalysis. Through the introduction of the functional subunit into the bridging thiolate ligands, the resulting thiolate‐bridged diiron complexes with different geometric and electronic structures can exhibit distinct reactivity. Herein, we utilize a half‐sandwich type of mononuclear iron complex as the reaction precursor to construct two novel thiolate‐bridged diiron complexes featuring the benzimidazole moiety through the oxidative dimerization strategy. X‐ray diffraction analysis reveals the two thiolate ligands containing the benzimidazole group in a syn arrangement bridge the two iron centers through the sulfur and nitrogen atoms. Furthermore, Mössbauer spectroscopy and computational studies suggest two complexes both possess two low‐spin FeIII ions, but adopt different magnetic couplings to give different electronic structures. Notably, difference in geometric and electronic structures between two complexes results in the distinct reactivity toward the azide species.

Penetrating Orbital Injury: A Narrative Review for Emergency Clinicians.

Penetrating orbit injury is a rare but complex and life-threatening occurrence that may easily be overlooked. Management in the emergency department requires an early multidisciplinary approach but still lacks standard guidelines. This narrative review aims to provide a systematic approach to the management of penetrating orbital injuries for emergency clinicians. Mortality and morbidity are significant due to the orbit's proximity to numerous anatomical structures. Complications may be infectious, ocular, or cerebro-vascular. Their incidence depends on the mechanism of injury, entry point, and object's characteristics such as its shape, composition, and velocity. Non-occult cases are often associated with medial orbital rim or medial eyelid penetration, whereas occult cases mainly present with trivial lateral eyelid injury and could be overlooked. Radiological workup consists of computed tomography or magnetic resonance according to the object's composition. Treatment in the emergency department focuses on initial resuscitation, broad-spectrum antibiotics, and tetanus immunization. Subsequently, early removal of the foreign object in a controlled environment and other specific treatments must be discussed with a multidisciplinary team. Penetrating orbital injury is an uncommon but complex type of head trauma that may be challenging to diagnose. Systematic and multidisciplinary management in the emergency department is crucial to improve overall prognosis.

Integration of Natural Language Processing (NLP) in MongoDB NoSQL: A New Era of Efficient Text Data Management

Advancements in computing power enable efficient management of large and complex datasets, leading to growing importance in big data analytics. This is evidenced in the progress demonstrated by word embedding’s in creating extensive index files of interconnected entities. Digital collections, which represent layered textual structures and multimodal communication annotations—ranging from linguistic to gestural data—point out the complexity of modern datasets. Evolving data forms call for new techniques for effective storage and management of data forms to be used in NLP applications. This paper analyzes six distinct Database Management Systems (DBMS) that will help in understanding optimum methods for dealing with the complex data types. Specifically, the paper looks into the areas of tokenization, semantic analysis, named entity recognition, sentiment analysis, text classification, and information retrieval. These were found to not be dominant in all tasks. We thus propose a web-based multi-database management system MDBMS that integrates specialized databases in various paradigms; this is scalable and adaptive. This MDBMS model integrates the strengths of different systems to meet the needs of heterogeneous datasets in NLP applications.

View from above: Farmland infrastructure and its impacts on agricultural landscapes

<p>Agricultural landscapes are shaped by the interaction between natural elements and human activities. The development of farmland infrastructure has directly added man-made objects or indirectly altered the production capacity, thereby impacting these landscapes. Earth Observation (EO), primarily satellite imagery, plays a crucial role in observing and monitoring the Earth’s surface and provides a valuable tool for understanding the pattern and structure of agricultural landscapes by offering information on land cover types. However, due to the varied and complex types, shapes, sizes, and functionalities of farmland infrastructure, the approaches and methods for observing its characteristics are limited. This limitation further obstructs the understanding of its impacts on agricultural landscapes. In this paper, we summarize the challenges and opportunities in exploring farmland infrastructure using EO and aim to comprehensively understand the interaction between natural elements and human activities in shaping agricultural landscapes.</p>

Homologous metal-organic complexes reconstructed oxy-hydroxide heterostructures as efficient oxygen evolution electrocatalysts.

It is imperative to investigate more cost-effective, long-lasting, efficient, and reliable non-noble metal electrocatalysts for the oxygen evolution reaction (OER) in hydrogen production via water splitting. Metal-organic complexes have been extensively researched and utilized for this purpose, yet their transformation in this process remains intriguing and underexplored. To enable a comprehensive comparison, we synthesized three types of metal-organic complexes with varying morphologies using the same raw material. Specifically, monocrystalline and lamella Fe-Co metal-organic frameworks (MOFs), along with Fe-Co metal-organic gels (MOGs), were created using p-Phthalic acid (PTA) as a ligand to facilitate the oxygen evolution reaction in a 1M KOH solution. The overpotential (η10) of MOF nanosheets (MOF-NSs) was 286mV at 10mAcm-2 under 1M KOH, while that of MOGs was 297mV, and MOF single crystals (MOF-SCs) exhibited an overpotential (η10) of 346mV. Density-functional theory (DFT) calculations demonstrated that the formation of FeOOH/CoOOH heterostructures reduced adsorption energy barriers and accelerated the rate-determining step, thereby improving the overall catalytic performance of OER. Hence, the structural reconstruction approach can be leveraged to develop and fabricate high-performance OER electrocatalysts in energy and related applications.

Structural Maintenance of Chromosomes Complexes.

The Structural Maintenance of Chromosomes (SMC) protein complexes are DNA-binding molecular machines required to shape chromosomes into functional units and to safeguard the genome through cell division. These ring-shaped multi-subunit protein complexes, which are present in all kingdoms of life, achieve this by organizing chromosomes in three-dimensional space. Mechanistically, the SMC complexes hydrolyze ATP to either stably entrap DNA molecules within their lumen, or rapidly reel DNA into large loops, which allow them to link two stretches of DNA in cis or trans. In this chapter, the canonical structure of the SMC complexes is first introduced, followed by a description of the composition and general functions of the main types of eukaryotic and prokaryotic SMC complexes. Thereafter, the current model for how SMC complexes perform in vitro DNA loop extrusion is presented. Lastly, chromosome loop formation by SMC complexes is introduced, and how the DNA loopextrusion mechanism contributes to chromosome looping by SMC complexes in cells is discussed.

Expanded Uses of the Dorsal Nasal Flap: Redefining the Nasal Reconstruction Algorithm.

Defects of the nose present complex reconstructive challenges to the plastic surgeon. We present our experience with using the dorsal nasal flap (DNF) to provide a durable reconstruction even in sizable defects that would otherwise be considered necessitating a paramedian forehead flap. We conducted a retrospective chart review of patients who underwent reconstruction by DNF following resection of skin cancers on the nose. Six flap-type modifications are described: limited, standard, double, combined, extended, and readvanced. From 2015 to 2021, a total of 51 patients underwent DNF reconstruction. The most frequently used flap types were the limited or standard configurations. There is a general trend of utilizing increasingly complex flap types to reconstruct larger defect sizes, as depicted in our reconstructive algorithm. There were no flap losses. Our study expands the indications of the DNF and redefines the nasal reconstruction algorithm. However, our proposition is not absolute in that one must consider tissue pliability and the location of the defect.

Structural complexity of glyphosate and aminomethylphosphonate metal complexes.

Small differences in the structure and subsequent reactivity of glyphosate complexes can have a highly consequential impact due to the enormous quantities of glyphosate used globally. The gas phase metal speciation of glyphosate and its abundant metabolite, aminomethylphosphonic acid (AMPA), were determined using cross-platform electrospray ionisation ion mobility mass spectrometry. Monomeric [M + L - H]+ complexes, and both larger, and/or higher order clusters formed with divalent metals (M = Mg2+, Ca2+, Sr2+, Ba2+, Mn2+, Co2+, Cu2+, and Zn2+; and L = glyphosate and AMPA). Complexation occurred at more than one ligand donor site for [M + L - H]+, resulting in multidentate complexes. The type of complex depended on M, with central positions maximizing the interactions of the M with donor sites of the L preferred. The isomers were separated by ion mobility and experimental collisional cross sections (N2CCSexp) were derived for all isolated species. An energy threshold DFT approach located the structural families and potential lowest energy forms; these were found to be consistent with confirmed condensed phase (reported crystal structures) and gas phase structures (via infrared multiple photon dissociation, IRMPD). Theoretical nitrogen collisional cross sections (N2CCScalc) of these confirmed structures tended to underestimate the N2CCSexp for both [M + glyphosate - H]+ and [M + AMPA - H]+ complexes. Underestimation ranged between 1-20%, and was not uniform between species. By comparison, helium collisional cross sections (HeCCSexp and HeCCScalc) were in better agreement (within 1-3%). These findings suggest further refinements are needed to collisional cross section modelling for metal containing species, in particular for nitrogen drift gas.

Ni(II)‐Directed Supramolecular Metallogel: Stimuli Responsiveness and Semiconducting Device Fabrication

AbstractMetal‐organic gels (MOGs) are a type of supramolecular complex that have become highly intriguing due to their synergistic combination of inorganic and organic elements. We report the synthesis and characterization of a Ni‐directed supramolecular gel using chiral amino acid L–DOPA (3,4‐dihydroxy phenylalanine) containing ligand, which coordinates with Ni(II) to form metal‐organic gels with exceptional properties. The functional Ni(II)‐gel was synthesized by heating nickel(II) acetate hexahydrate and the L–DOPA containing ligand in DMSO at 70 °C. The rheological tests have verified the gel with its mechanical stability, while a SEM image has shown a spherical aggregate morphology. The gel is photo‐responsive in nature and exhibits gel to sol transformation upon adsorption of toxic gases like NH3 or H2S. Notably, electrical conductivity of the gel was observed in electronic metal‐semiconductor (MS) junctions’ devices with a measured conductivity of 0.9×10−6 Sm−1. These devices also exhibited Schottky barrier diode characteristics, underscoring the multifunctional potential of the Ni(II)‐gel.

Évaluation des dysarthries et des apraxies de la parole : quelles approches ?

Context. In clinical practice, acquired motor speech disorders (MSDs), dysarthria and/or apraxia of speech (AoS) are mainly assessed using a perceptual approach. This approach remains dominant despite the biases associated with phonemic restoration and the subjectivity of the listener's internal representations. Furthermore, there is a lack of international consensus on the main diagnostic criteria for AoS. Several of these features are shared with dysarthria, which also often coexists with AoS (Duffy, 2019). In this context, the assessment of MSDs for differential diagnosis is a major challenge. Aims. This article provides an overview of the studies resulting from our PhD thesis. The aim of the thesis was to examine the contribution of the perceptual, acoustic and cognitive approaches to the assessment of dysarthria and AoS for the diagnosis and characterisation of these MSDs. Methods. Three studies were conducted on 4 groups of speakers: neurotypical, pathological speakers with AoS, hypokinetic dysarthria in Parkinson's disease, and mixed flaccid-spastic dysarthria in amyotrophic lateral sclerosis. These studies, partly based on the MonPaGe-2.0.s corpus (Fougeron et al., 2018 ; Laganaro et al., 2021 ; Pernon et al., 2020), focused on each of the following assessment approaches: (i) a multi-judge auditory-perceptual classification task of MSDs, (ii) a discrete phonetic-acoustic analysis by speech dimension of the speakers with the lowest and highest accuracy rates in (i), (iii) a dual-task paradigm evaluating the effects of attentional and executive demands on speech and non-verbal tasks in neurotypical speakers. Results. There was little difference between the perceptual and acoustic assessment approaches in diagnosing MSDs. The perceptual approach failed to diagnose very mild MSDs. The acoustic approach provided a quantified characterisation of MSDs profiles on average across three speech dimensions assessed by the MonPaGe-2.0.s tool, as in the study of perceptual classification of MSDs. The bidirectional dual-task effects showed that the mode of presentation of the stimuli and their modality, the type of speech task and the attentional demand of the non-verbal tasks had to be taken into account when developing and interpreting dual-task performance. These three studies found differences depending on the speech task. Conclusion. In addition to considering the speech dimensions involved in speech tasks, a more precise examination of their cognitive-motor demands on speech (type of speech task, phonetic and linguistic complexity of the corpus, speech production condition) refines the differential diagnosis of MSDs and improves their characterisation during assessment.