Evidential Information Research Articles

Veterinary Evidence: moving forward

Unrecognised and unknown information needs can significantly impact on the quality of decision making, advice, and patient care. In the practice of veterinary medicine, additional information may be required in one or more of epidemiology, diagnosis, treatment, prognosis, control (risk reduction), and prevention (risk avoidance), in order to optimise patient care. Veterinary Evidence publishes Knowledge Summaries, which aim to answer a specific and focused clinical query by appraising the best available evidence published in peer-reviewed scientific journals. By presenting the evidence in a structured and easily digestible format, Knowledge Summaries enable veterinary professionals to stay informed and apply the best available evidence to their decision-making. To assist in the identification of unrecognised deficits and the generation of clinical queries Veterinary Evidence has developed a list of common conditions for each species, alongside the different categories of information. The aim is to prompt and support the generation of new clinical queries in a more systematic format. This resource sits alongside our species-based lists of clinical queries that have already been suggested by practicing veterinarians, veterinary nurses, and other paraprofessionals (see veterinaryevidence.org/index.php/ve/clinical-queries). We hope readers and prospective authors will use these resources to generate new clinical queries or as a starting point for writing their own Knowledge Summaries. Most of the papers published in Veterinary Evidence are Knowledge Summaries, but the journal has always accepted and will continue to accept and encourage other types of reviews and original research that provide evidence to inform clinical practice. For example, in this issue we have published a commentary paper by Professor Jonathan Elliott regarding the processes and evidence required for the registration of veterinary medicinal products which provides some important insights and debate into the publication of evidential information (Elliott, 2024). A Knowledge Summary may not always be the best format to synthesise and summarise evidence on a multifaceted topic; scoping reviews, systematic reviews, or narrative reviews maybe more appropriate. Munn et al. (2018) provide a useful account of scoping reviews and how they differ from traditional literature and systematic reviews. In particular, we are keen to receive articles on artificial intelligence applications, sustainability, and quality improvement in clinical practice, as the impact and importance of these topics grows. We are also making some changes to the presentation of Knowledge Summaries in Veterinary Evidence, to help readers more easily understand the details and context of the summarised evidence. In order to support everyone in appraising and understanding quantitative clinical studies, we will be publishing a glossary and guidance on basic statistical terms and tests on the journal website.

A new distance measure between two basic probability assignments based on penalty coefficient

Uncertainty information processing is a challenging topic in information science. Dempster-Shafer evidence theory shows excellent performance when dealing with uncertainty in information representation, fusion, and processing. The measurement of the distance between the basic probability assignments (BPA) in Dempster-Shafer evidence theory is a powerful tool that deals with uncertainty in evidential information processing. Most of the existing methods are based on the difference in the assessment of evidential degree for different hypotheses, with a notable example Belief-Jensen-Shannon (BJS) divergence. However, these methods ignore the information that is carried by different units in the power sets that represent the hypotheses, i.e., the difference on the hypotheses themselves that include in the evidential degree assessment of different BPA should be considered in the distance measurement. Therefore, in this paper, a novel method grounded in BJS divergence and incorporating a penalty coefficient to rectify the distance between basic probability assignments is proposed. This methodology showcases commendable properties, including symmetry, boundedness, and adherence to the triangle inequality. To demonstrate the efficiency of the proposed distance measurement method between BPAs, we apply it to two common-used machine learning data sets: Iris data set and Dry Beans data set. Compared to the represented existing evidence distance measurement approaches, the proposed method yields superior performance in both data sets with respect to classification accuracy.

Leveraging generative AI for clinical evidence synthesis needs to ensure trustworthiness

Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence. The rapid growth of medical evidence, which can be obtained from various sources, poses a challenge in collecting, appraising, and synthesizing the evidential information. Recent advancements in generative AI, exemplified by large language models, hold promise in facilitating the arduous task. However, developing accountable, fair, and inclusive models remains a complicated undertaking. In this perspective, we discuss the trustworthiness of generative AI in the context of automated summarization of medical evidence.

The use of evidence in criminal proceedings as a component of the evidetiary process

The article is devoted to elucidating the essence and content of the use of evidence, as well as to justifying the identification of such a category as a separate component of evidentiary process in criminal proceedings. It was found that despite the absence of the category "use of evidence” among the provisions of Part 2 of Art. 91 of the Criminal Procedure Code of Ukraine, the term is used by the legislator in a number of articles of the current CPC of Ukraine. The positions of domestic scientists regarding the essence of the use of evidence were analyzed. It was found that the majority of doctrinal definitions of this term boil down to the understanding of the use of evidence as the manipulation of it (evidence, their procedural sources, evidentiary information) for the performance of intermediate and final tasks (that is, the achievement of certain positive results) in criminal proceedings.
 Based on the study of the provisions of the current legislation and doctrinal sources, it was established that evidence is used by justifying, making, and implementing decisions in criminal proceedings. The following forms of evidence use are singled out: procedural decisions, decisions on submitting evidence to the court and substantiating legal positions with them, on submitting motions and complaints during the pre-trial investigation, tactical decisions of the prosecution and other subjects of evidence. The general mechanism of making the listed decisions and the place of use of evidence in the system of components of evidentiary activity are considered.
 The use of evidence is defined as a component of the evidentiary process, a set of logical and instrumental operations consisting in justifying with evidence (evidential information), making and implementing decisions by the subject of proof in order to fulfill their own tasks in criminal proceedings.
 Further research prospects in the analyzed field are related to the scientific and theoretical study of the essence, types and mechanism of decision­making in criminal proceedings as a form of evidence use.

Мотивационная речь: специфика функционирования речевого жанра

The study aims to describe the speech genre of “motivational speech” in English-speaking motivational discourse. The relevance and scientific novelty of the research are determined by the need to construct the definition of motivational discourse, to clarify its discursive intention and strategy, and to study and describe its genre specificity. The article distinguishes between the concepts of motivation and impact and their respective discourses based on the addressee type (particularlyaddressable, targeting a specific communication partner, and generally addressable, oriented towards an abstract addressee), as well as based on the subject types that depend on the individual’s chosen “achievement motivation” strategy – either striving for success or avoiding failure. The analysis of motivational speeches demonstrated their thematic heterogeneity and varying degrees of formalization, ranging from rigid and soft formalization genres to free genres. The study identified eight main types of motivational speeches differentiated according to their basic intention and addressee concept, and determined their compositional structure. Furthermore, the research established characteristic features of this genre, such as the incorporation of storytelling, humor, different types of evidential information, emotive lexis and syntax, as well as the use of the so called “inclusive language”.

CD-BFT: Canonical Decomposition-Based Belief Functions Transformation in Possibility Theory.

Based on subjective possibilistic semantics, an agent's subjective probability mass function is dominated by a qualitative Possibility Mass Function (PossMF), which can also be transformed into a unique consonant mass function. However, the existing transformation method cannot maintain the consistency of combination rules, i.e., fusing PossMFs and consonant mass functions with same information content, respectively, the results no longer maintain the reversible transformation. To address the above issue, a novel belief functions transformation is proposed, which can be interpreted based on both Smets' canonical decomposition and Pichon's canonical decomposition. The proposed method is validated based on consistency of combination rules, the least commitment principle, and its application in the fusion of information. In addition, based on the two canonical decompositions, we extend the transformation to possibilistic belief structure, and offer a new perspective of relationship between possibilistic information and evidential information.

Information Granule Based Uncertainty Measure of Fuzzy Evidential Distribution

Quantifying the uncertainty of information distributions containing randomness, imprecision and fuzziness is the premise of processing them. A useful information representation in the field of intelligent computing is the information granule, which optimizes data from the perspective of specificity and coverage. We introduce information granularity into evidential information and model the Basic Probability Assignment (BPA) as a weighted information granules model. Based on the proposed model, a new uncertainty measure of BPA is derived from the quality evaluation of granules. In addition, the proposed measure is extended to fuzzy evidential information distributions. When the Fuzzy BPA (FBPA) degenerates into the Probability Mass Function (ProbMF) and Possibility Mass Function (PossMF), the proposed method degenerates to Gini entropy and Yager's specificity measure, respectively. We use a refined belief structure to interpret the meaning of FBPA in the transfer belief model, and verify the validity of the proposed method by properties analysis and numerical examples. The concept of information granule is used for the first time to model focal set and beliefs. Compared with Shannon entropy-based information measures, the proposed method provides a novel perspective on the relationship between randomness, imprecision, and fuzziness in FBPA.

Fractal-based basic probability assignment: A transient mass function

Effectively measuring the information content of Basic Probability Assignments (BPA) is a crucial prerequisite for addressing uncertain information within the framework of Dempster-Shafer theory. In previous research, uncertainty and dissimilarity measures for BPAs were often treated separately to counteract the impact of incomplete mutual exclusion between focal elements. In this paper, we introduce a Transient Mass Function (TMF) based on the process of pignistic probability transformation to forge a link between probabilistic and evidential information. As a transient state of BPA, the TMF not only considers the structural features of the focal element but also maintains its numerical content. Carrying out probabilistic information measures on the TMF is equivalent to performing belief information measures on the original BPA. Finally, validated by numerical simulations, TMF provides a unified and effective metric framework for evidential information.

Traditional uses, phytochemistry and therapeutic efficacy of Cassava (Manihot esculenta Crantz) - A Review

The usage of naturally available resources by humans for gratifying different requirements is an age-old custom. This is because natural products provide indispensable facilities in the form of nutritional, economic, social, medicinal aspects and many more. Cassava (Manihot esculenta Crantz) has been used as an herbal medicine by different groups of ethnic people. Besides having medicinal prospect, this plant is commonly used as a source of nutrition for humans and animals in tropical regions. However, conduction of more studies to see if there is chemical, microbiological, and/or clinical evidence, from a scientific perspective, of their effectiveness for those ailments. Therefore, this review was conducted to summarize the traditional uses, to understand the phytochemistry and identify the possible correlation between bioactive compounds and corresponding pharmacological properties. A systematic and detailed literature search has been undertaken for the study by using standard search engines like Google Scholar, PubMed, SciFinder, Research Gate and Science Direct. The evidential information was then assembled to present the manuscript with separate sections. From the literature search, it came into focus that Cassava contains various secondary metabolites which exhibits some notable pharmacological activities like antioxidant, antiradical, anticancer, antibacterial, antifungal, antidiarrheal, analgesic and pesticidal activity. The biological activities established by cassava provide insight into its usagthe e in traditional medicinal systems. But an intricate and thorough review appears to be deficient on M. esculenta. Therefore, this review has summarized the studies investigating about the traditional uses, phytochemistry, bioactive compounds and therapeutic efficacy of M. esculenta. The significance of this review is aimed at a better understanding of the novel applications and further considerations for more logical and scientific evaluation. We hope this study will further aid in the development of research on this area to identify a new generation of natural source-based treatments that will help meet the growing consumer demand for safe, sustainable, and natural treatments.

A Crime Scene Reconstruction for Digital Forensic Analysis

The abundance of digital data within modern vehicles makes digital vehicle forensics (DVF) a promising subfield of digital forensics (DF), with significant potential for investigations. In this research, the authors apply DVF methodology to a SUV, simulating a real case by extracting and analyzing the data in the period leading up to an incident to evaluate the effectiveness of DVF in solving crime. The authors employ DVF approach to extract data to reveal evidential information for judicial evaluation and verdict. This data helped determine whether the incident represented an accident or an act of crime. This simulated case and the assumptions supported by the DVF evidence provides a compelling example of how law enforcement agencies can leverage DVF to collect and present evidence to relevant authorities. This form of forensics can assist government in planning for and regulating the deployment of DVF data, the judiciary in assessing the nature and admissibility of evidence, and vehicle manufacturers in complying with the regulations relating to the harvesting and retrieval of data.

Features of evidentiary information in civil proceedings regarding land property disputes, the object of which is agricultural land

The article discusses certain aspects of evidence used by the parties to the civil process, the subject of which is the resolution of property disputes related to land relations in relation to agricultural land.
 In the process of scientific research, the authors turn to legal concepts of “evidence”, “data”, “evidential information” that are well-established in procedural science, providing them with a procedural and legal characteristic through the prism of property legal relations.
 The article reveals the characteristics of the land lease agreement as the primary source of basic evidence, which is an integral part of the evidence system in the category of cases under study. In this regard, it is noted that the land lease agreement is by far the most common basis for the emergence of lease land legal relations and the form of their fixation, the object of which is an agricultural land plot.
 The article contains the author's definition of the concept of proof in the field of property disputes related to land relations, the subject of which is a lease relationship with respect to agricultural land. In addition, the authors give a definition of the term "evidence" in the field of property disputes related to land relations (land property disputes), which should be defined as specific data contained in the procedural form of various evidence confirming or refuting the presence of a violated, unrecognized or disputed property right of a person, which is connected with the right of ownership or use of a particular land plot. At the same time, the evidentiary value of such a legal category as “evidence” contained in the information from the State Register of Individuals-Taxpayers of the State Fiscal Service of Ukraine was analyzed through the prism of the requirements of the Tax Code of Ukraine, which determine the specific tax obligations of the tenant of the land plot.
 This scientific work is based on the jurisprudence of the Supreme Court, which reveals and fixes certain aspects that are not regulated by land legislation regarding the property liability of the parties to the lease agreement, the grounds for collecting debt from the rent and terminating such a transaction by terminating it.

Evidential network‐based system reliability assessment by fusing multi‐source evidential information

AbstractExpert knowledge is an important information source for reliability assessment of those systems with limited time‐to‐failure data. For a better understanding of the degradation profiles of systems, multiple experts are oftentimes invited to express their judgments and the associated uncertainties on the reliability‐related measures of the system. Evidential variables, as an alternative of uncertainty quantification, have been extensively used in expert systems to quantify the epistemic uncertainty of the elicited expertise. When eliciting the reliability‐related information by evidential variables, experts only need to express the possible ranges of reliability‐related measures and their associated probabilities. Such a type of information well caters to the experts’ elicitation process. In this article, an evidential network (EN)‐based reliability assessment method is put forth by fusing multi‐source evidential information. The proposed method mainly contains three steps. In the first place, the multi‐source evidential information related to all components is elicited from experts in the form of evidential variables. Next, the evidential variable of the component reliability is assessed via a constrained optimization model by treating all pieces of multi‐source evidential information as constraints. The component reliability results are transformed into pieces of mass functions of the components’ states under the theory of belief functions. The system reliability‐box and the reliability‐box over time are, therefore, calculated by the EN model by inputting all mass functions of components’ states. A pipeline system and a chip cutting system are exemplified to examine the effectiveness of the proposed method.

Рецензия на книгу: Гричин С. В. Авторизационная модель научного текста: монография. – Новосибирск: Изд-во НГТУ, 2020. – 292 с.

This article is a review of the book The Evidential Model of a Scientific Text by Sergey Grichin. The monograph describes evidentiality, one of the leading discursive categories of a scientific text. Grichin answers the questions: How does new knowledge emerge? How is it converted into a text? How does the dialogue between the author and his predecessors come about? Answering these questions, Grichin substantiates the status of evidentiality as a universal text-forming category. This category reflects all cognitive actions of the author of the text, so the study of evidentiality requires a complex, interdisciplinary approach. In the reviewed book, this approach is represented by the synthesis of functional stylistics, cognitive linguistics, discourse analysis, psychology and logic. The author of the monograph fully and clearly formulates the research methodology and defines the key concepts: evidential sense, evidential unit, evidential indicators, etc. Grichin establishes the extra-linguistic factors influencing the representation of evidential meanings in a scientific text, and describes the linguistic units for expressing these meanings. The correlation between the category of evidentiality and the category of certainty / uncertainty is shown. Regularities in the perception of evidential information by the addressee are defined. The novelty of the research lies in the fact that the category of evidentiality is presented as an integrative, multifactor model, which takes into account extralinguistic (discursive) and linguistic factors of communicative and cognitive activity of the author of the text. The scientific significance of the developed model is ensured by the fact that Grichin interprets evidentiality in a wider and deeper way than it was accepted in traditional linguistics (traditionally evidentiality is understood as referring to the source of someone else’s speech). The monograph considers evidentiality as a multifactorial category, which is a tool for structuring scientific discourse. The evidentiality model is developed by Grichin on the basis of the analysis of vast material, which includes more than 300 texts in 13 branches of science. To check the validity of the concept, journalistic and colloquial (dialectal) texts are used in addition to scientific texts. The regularities of the addressee’s perception of evidential senses are analysed by means of experimental methods. The reviewers note the value of the monograph for speech studies, in particular: development of a cognitive and discursive method of scientific text analysis; identification of new extralinguistic factors of scientific communication; establishment of mechanisms of generation and perception of scientific texts.

Risk-Aware Path Planning for Unmanned Aerial Systems in a Spreading Wildfire

Path planning for small unmanned aerial systems (SUAS) in the presence of poorly understood and dynamic obstacles is a challenging problem: for example, flight over a spreading wildfire. Evidential information fusion is used to estimate the current wildfire state and the resulting heat aura at flight level. This approach accounts for ignorance, which is a result of conflict among sensors operating in a harsh environment and a computational forecasting agent that uses a fire evolution model of inadequate accuracy. An SUAS is employed to visit locations of high conflict to provide additional situational awareness. Flight-level heat aura is modeled as a keepout zone with probabilistic boundaries for SUAS path planning. A novel unsupervised classification algorithm is developed to identify distinct obstacle boundaries within the estimated heat aura. Path planning is posed as a chance-constrained optimal control problem, which is transcribed to a nonlinear program via pseudospectral discretization. The results show that this approach can yield a family of solutions that elicit the risk associated with each mission design, and the appropriate choice of risk can aid in the generation of “keyhole paths.”

Transformation of Expert Activities in the Age of Digitalization

Digitalization of forensic science is primarily associated with ensuring the reliability of digital information as evidence. And here it is important to pay attention to the creation of regulatory rules for using methods of obtaining, research and use of electronic evidential information and its inviolability throughout court proceedings.

Therapeutic Potential of Functional MRI in the Squamous Cell Cancer of Head and Neck.

Magnetic Resonance Imaging (MRI) is frequently employed for the assessment of therapy in head and neck squamous cell carcinoma patients. Nonetheless, this technique has its limitations, the most apparent being the inability to differentiate between after therapy effects and the reoccurrence of tumor cells. This review was carried out to demonstrate the role of operative MRI in the treatment of head and neck squamous cell carcinoma patients, as well as the analysis of various methods like diffusion, perfusion, and spectroscopy when used in conjugation. Techniques such as diffusion-weighted imaging can augment the reliability of the detection of the main tumor site and local lymphatic nodes post-treatment. It was observed that diffusion is the most facile of the methods in question and can be easily implemented in follow-up sessions after therapy, though the evidential information is sometimes insufficient to validate. Perfusion factors may become elevated in the proliferation of tumors or their reoccurrence, but they are not employed for their accuracy in clinical settings. Spectroscopy methods pose some potential, but the case is the same as diffusion; insufficient data cannot be deemed enough to validate its application. These operative MRI methods can significantly help in the initial discernment of disease, thereby resulting in an improved therapeutic approach in patients. Prospective studies are necessary to layout standard specifications for using operative MRI in routine clinical applications.

Information graphs and their use for Bayesian network graph construction

In this paper, we present the information graph (IG) formalism, which provides a precise account of the interplay between deductive and abductive inference and causal and evidential information, where ‘deduction’ is used for defeasible ‘forward’ inference. IGs formalise analyses performed by domain experts in the informal reasoning tools they are familiar with, such as mind maps used in crime analysis. Based on principles for reasoning with causal and evidential information given the evidence, we impose constraints on the inferences that may be performed with IGs. Our IG-formalism is intended to facilitate the construction of formal representations within AI systems by serving as an intermediary formalism between analyses performed using informal reasoning tools and formalisms that allow for formal evaluation. In this paper, we investigate the use of the IG-formalism as an intermediary formalism in facilitating Bayesian network (BN) graph construction. We propose a structured approach for automatically constructing from an IG a directed BN graph, together with qualitative constraints on the probability distribution represented by the BN. Moreover, we prove a number of formal properties of our approach and identify assumptions under which the construction of an initial BN graph can be fully automated.

Unsupervised isolation of abnormal process variables using sparse autoencoders

Isolation of abnormal changes in process variables is an integral component of fault diagnosis, as it provides evidential information for determining the root cause of a detected abnormal event. This task is challenging when the approach to diagnosis does not incorporate knowledge of the process’ nominal behavior, but is instead established solely on historical process data. Though isolation of abnormal changes in variables may be facilitated by including historical process data for faults that have been previously diagnosed, inconclusive results will remain for unfamiliar faults. This paper presents a method for isolating abnormal changes in process variables with an autoencoder (AE) - a type of neural network configured for latent projection — and without prior knowledge of nominal process behavior or faults. The AE is optimized with nominal process data as well as a sparsity constraint to produce a sparse network. Probing into the sparse AE allows one to gain insight into the correlations that exist among the process variables during normal process operation. Movements in the AE’s reconstruction space are interrogated alongside the acquired knowledge to isolate the abnormal changes in process variables. The method is demonstrated with a simulation of a nonlinear triple tank process, and is shown to isolate abnormal changes in variables for both simple and complex faults.

Evidentiality, Modality, and Speech Acts

Evidential constructions have two main semantic effects: They contribute information about an individual's source of evidence, and they potentially modify the force of a sentence. In this article, I review the at-issue status of the evidential information, the indexical and anaphoric properties of evidentials, their force-modifying effect, and the connection throughout to epistemic modality. In some languages, evidentials occur as part of the grammatical morphology, but evidential information can be expressed through a variety of constructions across languages. As such, the study of evidentiality highlights the important role of cross-linguistic semantics and the collaboration between language typology and linguistic semantics.

КРИМИНАЛИСТИЧЕСКОЕ МЫШЛЕНИЕ СЛЕДОВАТЕЛЯ КАК ИНТЕЛЛЕКТУАЛЬНЫЙ ФАКТОР ЭФФЕКТИВНОСТИ ПРИ ПРОИЗВОДСТВЕ ОСМОТРА МЕСТА ПРОИСШЕСТВИЯ

The fight against crime in modern conditions of technical progress, requires from law-enforcement bodies of the Russian Federation not only considerable financial cost, physical and moral strength of the officials, carrying out disclosure and investigation of crimes, but also the tremendous intellectual scope of work to ensure the planning and organization of investigation of criminal cases. As shows the analysis of the investigative practice, in most cases, non-obvious crimes are difficult to investigate, the investigator here is experiencing not only a lack of guidance and evidential information about facts and results of an event, but also prone to superficial conclusions and stereotyped (typical) thinking. All this affects the quality and efficiency of the solution of tasks of criminal proceedings. The article attempts to consider the theoretical and methodological foundations of the intellectual support of the investigation of crimes. The author, based on existing scientific works and research by scientists in this field, offers a subjective approach to the concept, meaning and system of forensic thinking in the investigation of criminal cases. Particular attention is paid to the complex of elements that make up the forensic thinking system. The values and functions of the elements of the forensic thinking system are revealed, the particular tasks of each element are considered based on the informational conditions of the investigation. The article also highlights, according to the author, the key elements of the application of forensic thinking during the production of the inspection of the scene.