bluuebunny/crossref_metadata_2025 huggingface dataset:
ARTERIAL HYPERTENSION AND WAR, WHAT TO EXPECT?
Authors: Kravchenko A.M.
Published: August 2023

The aim. To conduct an analysis and generalize scientific publications on the influence of war factors on morbidity indicators and the clinical course of arterial hypertension.

Materials and methods. An analysis and generalization of scientific research and publications on the specifics of morbidity among military personnel and the population affected by war has been conducted. The following methods were utilized: a systematic approach, bibliosemantic analysis, and analytical methods.

Results: The article focuses on the influence of war factors on the incidence rates and clinical course of arterial hypertension in both military personnel and the civilian population. Through a review of historical data and modern scientific sources, the study examines the long-term effects of stress factors on the development of hypertension, the peculiarities of its clinical manifestations, and the potential for predicting complications in individuals affected by military operations. The impact of nervous tension is particularly evident among frontline soldiers, as hypertension is observed, on average, 3-4 times more frequently compared to soldiers in the rear. The article emphasizes the clear correlation between the frequency of arterial hypertension in servicemen and the duration of their frontline deployment.

Conclusion. Severe mental trauma and negative emotions, experienced by both military personnel and the civilian population during war, can not only contribute to an increased incidence of hypertension but also lead to a significant rise in the occurrence of the disease in young individuals, with severe clinical manifestations expected.
CPA Evolution: Curriculum revision for Higher Education
Authors: Bilbeisi Khamis M
Published: August 2023

Recent proposals from the National Association of States Board of Accountancy and the American Institute of Certified Public Accountants aim to modify the CPA license model to reflect the knowledge and abilities that new CPAs will need both now and in the future. The Uniform CPA Examination has recently undergone its most significant modification in many years thanks to the CPA Evolution project. This article discusses the exam's revised structure and content, evaluates the anticipated effects of those changes on accounting education, and explains how colleges will need to modify their curricula to meet the new exam core Plus requirements.

Today's accountants and the accounting industry require different technical capabilities than they did even a few years ago. For the accounting profession to advance, proficiency in technology, data analytics, risk management, and IT governance are becoming crucial competencies. The joint CPA Evolution project of the AICPA and NASBA acknowledges the rapidly evolving abilities and competences needed by today's CPAs. The quick development of technical advancements, such as data analytics, robots, and artificial intelligence, among others, is significantly altering the way CPAs do their business. Additionally, this report illustrates the constraints that the COVID-19 placed on the world's environment and economy. The CPA profession is changing, and data from IPEDS and responses from participating U.S. universities and public accounting companies enable us to assess the effects of this change on both the supply and demand of new accounting. The public accounting firms have started to fill the technology and data analytics talent gaps among accounting recruits by hiring non-accounting staff, according to the AICPA's 2021 Accounting Graduate Supply and Demand Report, which includes a survey of the hiring practices of public accounting firms. According to the research, new hires of master's graduates increased by 2% in 2020, despite a 10% decline in the total hiring of new accounting graduates.
The added value of costing social and behavior change interventions
Authors:   Breakthrough RESEARCH
Published: August 2023

This brief provides an overview of how investment in high-quality costing of social and behavior change (SBC) interventions can benefit the work of government ministries, donors, program implementers, and technical specialists. It also introduces the Breakthrough RESEARCH “Guidelines for Costing of Social and Behavior Change Health Interventions” that can be utilized to plan for and optimize such investment. With the support of the U.S. Agency for International Development (USAID), Breakthrough RESEARCH is developing a body of SBC cost-related evidence and tools that emphasize the value of investing in high-quality SBC programming and research and evaluation.
Using audience segmentation approaches to inform integrated family planning and maternal health programs in Niger
Authors:   Breakthrough RESEARCH
Published: August 2023

Understanding the specific behavioral determinants and barriers to health-seeking for reproductive and maternal health services is critical to developing social and behavior change (SBC) programs that can best address the needs of the community. Effective SBC interventions can incorporate audience segmentation, the practice of dividing an audience into subgroups based on demographic, psychographic, and/or behavioral factors to develop tailored SBC approaches that are most likely to resonate with each audience subgroup. This brief presents study results of audience profiles for women of reproductive age in Niger with a focus on three reproductive and maternal health behaviors. It is intended to inform integrated SBC activities implemented by the USAID-funded Resilience in the Sahel Enhanced (RISE) II partners to improve health outcomes.
A structural and provider behavior change approach to enhancing respectful, integrative, responsive care for hospitalized young children (0–24 months) in Kenya
Authors:   Breakthrough RESEARCH
Published: August 2023

This brief describes a co-creation process and a resulting provider behavior change intervention approach that can be adapted to similar low- and middle-income hospital contexts. It offers policy and program managers details around each intervention component, linking to an accompanying provider orientation PowerPoint and other training materials/job aids. Finally, it recommends a few lessons to guide those interested in engaging in a similar co-creation and implementation approach.
Evidence from the implementation of a social accountability approach to improve family planning services: Perspectives from community members and health workers in Togo
Authors:   Breakthrough RESEARCH
Published: August 2023

This brief summarizes findings from Breakthrough RESEARCH's formative qualitative evaluation of a social accountability approach implemented in and around the city of Lomé, Togo to strengthen family planning (FP) services. It is intended to inform FP programs implemented by the USAID-funded West Africa Breakthrough ACTION (WABA) and AmplifyPF projects to further improve FP related outcomes. This brief provides an overview of the social accountability approach and describes the enabling factors and challenges associated with implementation as well as perceived outcomes related to the effectiveness of the social accountability approach to improve FP service delivery at the community level, at the facility, and in terms of client and provider interactions. The brief concludes with strategies to leverage these findings to improve implementation to achieve increased FP client satisfaction service utilization.
Young and Old Sugar Apple (Annona squamosa Linn) Leaf Extracts As an Aedes aegypti Larva Insecticide
Authors: Khair Abdul , Noraida Noraida
Published: August 2023

Vector-borne diseases are still a health problem in some tropical countries. One vector-borne disease is Dengue Hemorrhagic Fever (DHF). DHF never decreases and even tends to continue to increase, and many cause deaths in children, 90% of them attack children under 15 years. DHF cases in 2018 amounted to 65,602 cases, with 467 deaths (CFR = 0.71%). The behavior of holding water in various places such as tubs and tendons indirectly creates a breeding place for Aedes aegypti mosquitoes. The use of chemicals as insecticides can cause the death of non-target animals, environmental pollution, and the occurrence of vector resistance to insecticides. Therefore it is necessary to do other methods including the use of vegetable insecticides. Sugar apple leaves can be used to kill Aedes aegypti larvae. Sugar apple leaves will obtain throughout the year. The purpose of this study is to know the ability of young and old sugar apple leaves to kill Aedes aegypti larvae. This type of research is a posttest only control group design. The study sample was part of the Aedes aegypti larvae on the final instar III. The experiment to kill Aedes aegypti larvae use two types of sugar apple leaf extract, namely young and old sugar apple leaves with nine treatments four replications. Each treatment consisted of 25 larvae. The research results show There was no significant difference in the number of dead larvae using either extracts from young sugar apple leaves or old sugar apple leaves. LC90 of sugar apple leaf extract was between 0.05632 to 0.08324% and the effective residual age at LC90 (0.06568%) with the death of Aedes aegypti larvae was 92% over 24 hours (1 day).
Analysis of Obesity And Axillary Lymph Nodes on Mammography
Authors: Akdogan Gemici Aysegul , Bayram Ersoy , Gultekin Nigar , Inci Ercan
Published: August 2023

Fat-infiltrated lymph nodes mostly seen on mammograms (MG) of the elderly and obese women. We analyzed the fat infiltration of lymph nodes for its potential use in estimating body mass index (BMI). 2D digital MG of 157 women assessed by one breast radiologist and one radiology resident. For each patient, the largest lymph node chosen as the index by analyzing the medial, lateral oblique (MLO) views. The width and length of the node and the hilum, the cortex, and the Hilo-cortical ratio (HCR) were measured. Breast density was categorized according to the ACR BI-RADS 4th edition and divided into two groups as dense and non-dense. Obesity was defined as BMI ≥ 30 kg/m2, overweight as BMI
Polubowne załatwienie sprawy w postępowaniu administracyjnym
Authors: Ura Paulina
Published: August 2023

Organy administracji publicznej w sprawach, których charakter na to pozwala, dążą do polubownego rozstrzygnięcia kwestii spornych oraz ustalenia praw i obowiązków będących przedmiotem postępowania. Celem niniejszego opracowania jest przedstawienie problematyki związanej z polubownym załatwieniem spraw w postępowaniu administracyjnym z uwzględnieniem roli organu w dążeniu do polubownego rozstrzygania kwestii spornych oraz do polubownego ustalania praw i obowiązków stron postępowania będących przedmiotem postępowania administracyjnego. Zasadę polubownego załatwiania spraw konkretyzują w szczególności dwie instytucje procesowe – ugoda administracyjna i mediacja.
Dopuszczalność zawarcia umowy darowizny na wypadek śmierci w świetle orzecznictwa i poglądów doktryny
Authors: Nowak-Dziwina Olga
Published: August 2023

Umowa darowizny na wypadek śmierci nie jest wprost uregulowana w polskich aktach prawnych. Od wielu lat w literaturze prawniczej toczy się dyskusja na temat dopuszczalności jej zawarcia. Odpowiedź na pytanie czy w polskim porządku prawnym możliwe jest zawarcie jej w sposób waży i skuteczny zależy przede wszystkim od znalezienia odpowiedzi na pytanie czy należy klasyfikować ją jako czynność prawną inter vivos czy mortis causa. Zagadnienie to może mieć istotne znaczenie praktyczne. Sąd Najwyższy w 2013 r. podjął uchwałę, w której uznał, że dopuszczalne jest zawarcie umowy darowizny na wypadek śmierci, jeżeli jej przedmiotem są konkretne rzeczy lub prawa, a umowa nie jest sprzeczna z zasadami współżycia społecznego. Pogląd ten znalazł wśród przedstawicieli doktryny zarówno swoich zwolenników, jak i przeciwników.
Oświadczyny jako oferta
Authors: Czop Katarzyna
Published: August 2023

W artykule omówiono instytucje oświadczyn z perspektywy prawa cywilnego. Ukazano cechy oświadczyn przemawiające za uznaniem ich za ofertę w rozumieniu Kodeksu cywilnego oraz postarano się przeanalizować orzecznictwo i poglądy przedstawicieli nauki odnoszące się do tej problematyki. Celem publikacji jest przybliżenie zagadnienia związanego z charakterem oświadczyn na kanwie prawa cywilnego.
The effect of age on the severity of dry mouth occurring in patients receiving high dose radioactive iodine treatment
Authors: ERATİLLA Veysel , KAPLAN İhsan
Published: August 2023

Aims: Dry mouth of individuals causes many oral discomforts and undesirable conditions. In order to prevent such an undesirable situation from occurring, it is aimed to complete the Radioactive Iodine Therapy (RAI) treatment with less damage by mastering all possible factors. In our study, we aimed to find the level of the effect of the age factor.

Methods: In this study, we included patients who received high-dose radioactive iodine treatment after total thyroidectomy for differentiated thyroid cancer and were hospitalized in our clinic. These patients were selected among the patients who applied to our hospital between 2021-2022. We specifically focused on patients who reported dry mouth and obtained salivary gland scintigraphies of their submandibular glands. Afterwards, we looked at the ratio of the age of the patients with the level of dry mouth. We analyzed the collected data using statistical methods.

Results: The data analysis was performed using the Chi-square (χ2) test and the Spearman correlation test to examine the relationship between age and the severity of dry mouth in patients undergoing high-dose RAI treatment for thyroid cancer. Our hypotheses were two-sided, and statistical significance was considered at p-values ≤0.05. The results of our analysis revealed that there was no significant direct correlation between age and the severity of dry mouth in the patients. This suggests that age is not a determining factor for the occurrence or severity of dry mouth in individuals receiving high-dose RAI treatment.

Conclusion: In our study, it was concluded that the age factor alone was not a determining factor in terms of the severity of dry mouth. Therefore, it is important to consider additional factors and potential underlying causes when evaluating and managing dry mouth in patients receiving high-dose RAI therapy for thyroid cancer.
Perceptions of finger-amputated hand appearance and its effects on social life from the perspectives of affected and unaffected individuals
Authors: ASFUROĞLU Zeynel Mert , ESKANDARİ Metin Manouchehr
Published: August 2023

Aims: Traumatic finger amputation leads to dysfunction and disfigurement of the hand. Hand disfigurements can affect the social lives of affected individuals. The purpose of this study was to investigate affected and unaffected individuals' perceptions of finger-amputated hand appearance and its effects on social life.

Methods: A group of 26 finger-amputated individuals completed a questionnaire assessing the impact of their hand appearance on their social lives and rated their hand appearance using a visual analogue scale (VAS). Hand photographs of members of this group were shown to 50 unaffected individuals, who were asked to rate their appearance using the VAS and complete a questionnaire assessing their reactions to similar hands encountered during daily life.

Results: In the patient group, the mean VAS and questionnaire scores were 5.1±2 (range: 1–10), and 60.3±17 (range: 31–94), respectively. In the assessor group, the mean VAS score for all 26 hand photographs was 7.1±2 (range: 3–9) and the mean questionnaire score was 83.6±11 (range: 56–100). While the patients' and assessors' VAS scores were significantly correlated for each hand photograph (r=0.511, p=0.008), in total, 21 of the 26 VAS scores were lower for the patient than assessor group. The VAS and questionnaire scores in the patient group improved significantly with time since amputation (p =.00 and p=0.011, respectively).

Conclusion: The self-evaluation results of the affected group were worse than those of the unaffected group in terms of perceptions of appearance and the resultant effects on their social lives. We conclude that individuals without finger-amputated hands perceived hand disfigurements less negatively than affected patients. This knowledge may aid the psychosocial support of patients with hand anomalies.
Analysis of the relationship between clinical features, treatment options and recurrence of patients diagnosed with anogenital warts
Authors: DEMİRCİ SAADET Elif , İNAL Halil Gürdal , SEÇKİN Bedreddin , AKARSU Süleyman
Published: August 2023

Aims: Our study aimed to describe the demographic and clinical characteristics of patients with anogenital warts and to investigate the relationship between treatment options and recurrence.

Methods: The data of patients who were admitted to the dermatology, urology, and gynecology outpatient clinics between 2010 and 2021, and diagnosed with anogenital warts were retrospectively analyzed. Demographic characteristics of the patients, presence of other sexually transmitted diseases, anatomical distribution of warts, number of anatomical regions and warts, frequency of recurrence, type of treatment before the first recurrence, and follow-up periods were documented. Statistical analysis was performed and the results were evaluated at a 95% confidence interval and p
The initial psychological impact of the COVID-19 pandemic on healthcare professionals in a children's hospital
Authors: ÖZTÜRK Betül , AÇIKEL Sadettin Burak , GÜNGÖR Ali , GÜNEYLİOĞLU Muhammed Mustafa , YARADILMIŞ Raziye Merve , BODUR İlknur , TEKELİ Aysun , AKCA ÇAĞLAR Ayla , GÖKTUĞ Aytaç , TUYGUN Nilden , KARACAN Can Demir
Published: August 2023

Aims: The pandemic has had devastating effects across the world particularly on healthcare professionals. We assessed anxiety and depression with somatization to discover the psychological effects of the pandemic.

Methods: 250 healthcare workers in a tertiary pediatric teaching hospital were asked to respond to the questionnaire between 1 and 30 June 2020 and the responses were assessed via three scales including the Patient Health Questionnaire 9 (PHQ-9), the General Anxiety Disorder 7 (GAD-7) and the Somatosensory Amplification Scale (SSAS).

Results: A total of 242 participants responded (response rate 97%); 29% of the participants reported moderate or severe anxiety while 49% reported moderate or more severe depression. There was no significant difference between the degrees of depression and moderate to severe anxiety through different professions (p= 0.480, p=0.384, respectively). Somatization was significantly lower in doctors and higher in female participants (p=0.001). Participants with chronic diseases and ones that had a dependent relative were at higher risk for anxiety and depression.

Conclusion: Most of the healthcare workers had depression and anxiety in the beginning of the pandemic, and it was independent of gender, profession, or workplace. Healthcare professionals with chronic diseases and dependent relatives are at risk for severe depression.
The impact of gastroenterology fellowship involvement on the ERCP outcomes
Authors: CANKURTARAN Rasim Eren , GÜVEN İbrahim Ethem , ÇAĞIR Yavuz , TASKİN Edanur , ERSOY Osman
Published: August 2023

Aims: This study aimed whether the companionship of the gastroenterology fellowships to operators performing high-volume ERCP, would adversely affect the safety and success of the procedure.

Methods: This retrospective observational study included 964 patients with naïve papilla who underwent ERCP between February 2019 and May 2022. Procedures with fellowship involvement were compared with procedures performed only by the expert operator in terms of cannulation success, procedure time, cannulation time, unintended PD cannulation, difficult cannulation, cannulation techniques, and post-procedure adverse events.

Results: The two groups were similar in terms of procedure difficulty, successful cannulation in the first session, overall successful canulation, unintended PD cannulation, difficult cannulation rates, and cannulation techniques. The median procedure time was significantly higher in the fellowship involvement group compared to the other group (p=0.008). There was no difference between the two groups in terms of adverse events after the procedure (p>0.05). Procedure difficulty were found an independent risk factor of adverse events in the multivariate analysis (Odds ratio: 2.3; 95% Cl 1.4-3.6; p
The success of volumetric means ADC in predicting MGMT promoter hypermethylation in glioblastomas
Authors: KORKMAZ Serhat , DEMIREL Emin
Published: August 2023

Aims: This study aimed to investigate the relationship between volumetric mean ADC values and MGMT promoter hypermethylation status in glioblastoma (GB) patients segmented into perilesional edema area, solid tumor area, and necrosis area.

Methods: The 212 GB patients in the University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) dataset were retrieved from the Cancer Imaging Archive (TCIA). The mean volumetric ADC value was calculated in patients with shared segmentation data in the UCSF-PDGM dataset. The difference in mean volumetric ADC value was investigated in patients divided into groups based on MGMT promoter hypermethylation (MGMT+/ MGMT-).

Results: Of the patients in our study, 125 (59.0%) were male. The median age of the patients was 62 years (26-94). MGMT promoter hypermethylation was observed in 152 (71.7%) patients. Mean Survival was calculated as 574.14±345.57 days in the MGMT+ group and 484.68±301.71 days in MGMT- group. According to volumetric mean ADC values, a difference was observed in the solid tumor and perilesional edema areas according to MGMT promoter hypermethylation (p1.14 in ADC measurements from the edema area with 72% sensitivity and 90% specificity. MGMT+ group could be determined with a sensitivity of 88% and specificity of 69% with a cut-off value of >1.01 in ADC measurements from the solid tumor area.

Conclusion: Volumetric ADC measurements from the perilesional edema and solid tumor areas revealed higher ADC values in the MGMT+ group.
Chapter 2. Neuro-Symbolic RDF and Description Logic Reasoners: The State-Of-The-Art and Challenges
Authors: Singh Gunjan , Bhatia Sumit , Mutharaju Raghava
Published: August 2023

Ontologies are used in various domains, with RDF and OWL being prominent standards for ontology development. RDF is favored for its simplicity and flexibility, while OWL enables detailed domain knowledge representation. However, as ontologies grow larger and more expressive, reasoning complexity increases, and traditional reasoners struggle to perform efficiently. Despite optimization efforts, scalability remains an issue. Additionally, advancements in automated knowledge base construction have created large and expressive ontologies that are often noisy and inconsistent, posing further challenges for conventional reasoners. To address these challenges, researchers have explored neuro-symbolic approaches that combine neural networks’ learning capabilities with symbolic systems’ reasoning abilities. In this chapter, we provide an overview of the existing literature in the field of neuro-symbolic deductive reasoning supported by RDF(S), the description logics EL and ALC, and OWL 2 RL, discussing the techniques employed, the tasks they address, and other relevant efforts in this area.
Chapter 3. Architectural Patterns for Neuro-Symbolic AI
Authors: ten Teije Annette , van Harmelen Frank
Published: August 2023

We propose a set of architectural patterns that describe a large variety of neuro-symbolic systems. As in other areas of computer science (knowledge engineering, software engineering, ontology engineering, process mining and others), such design patterns provide a unified vocabulary to describe a large variety of systems, help to systematise the literature, clarify which combinations of techniques serve which purposes, and encourage re-use of software components. We have validated our set of compositional design patterns against a large body of recent literature, and we apply them to a number of systems described in the different sections of this volume. Sections 1.1-1.7 of this chapter are based on our earlier publications [1] and [2], the new contributions of this chapter are in section 1.5 and 1.6.
Chapter 7. Neural-Symbolic Interaction and Co-Evolving
Authors: Tan Bowen , Hao Shibo , Xing Eric , Hu Zhiting
Published: August 2023

Symbolic knowledge is vital in various human cognitive functions, including reasoning, skill acquisition, and communication. Its integration is also essential for creating AI with human-like capabilities, such as robustness, creativity, and interpretability. Nevertheless, current machine learning approaches still dominantly emphasize learning from large data sets, struggling to effectively and scalably incorporate symbolic knowledge. This leads to fundamental limitations, such as brittle results when faced with complex or novel concepts, and difficulty in understanding or explaining the decision processes of models. Past attempts at integrating symbolic information with neural networks frequently rely on manually created knowledge bases that are defined in specific configurations, thereby impeding their generalizability to new applications and domains. This chapter seeks to introduce interaction and co-evolving mechanisms between neural models and symbolic knowledge bases. It starts from constructing a panoramic learning framework for learning with all experiences (data, rules, knowledge graphs, etc.). Subsequently, it delves into a novel inversion problem of extracting symbolic knowledge from black-box neural models. Finally, based on the components mentioned above, the chapter will explore a blueprint of a lifelong neural-symbolic system that accommodates human intervention.
Chapter 8. Neuro-Causal Models
Authors: Aragam Bryon , Ravikumar Pradeep
Published: August 2023

This chapter proposes neuro-causal models, a novel neuro-symbolic model architecture that uses a synthesis of deep generative models and causal graphical models to automatically infer higher level symbolic information from lower level “raw features”, while also allowing for rich relationships among the symbolic variables. Neuro-causal models retain the flexibility of modern deep neural network architectures while simultaneously capturing statistical semantics such as identifiability and causality, which are important to discuss ideal, target representations and their tradeoffs. We consider a general setting for this problem: No assumptions are placed on these relationships, and the number of hidden variables, their state spaces, and their relationships are presumed unknown. The primary objective is to provide explicit conditions under which all of this can be recovered uniquely, and to develop practical algorithms for learning these representations from data.
Chapter 11. Autodidactic and Coachable Neural Architectures
Authors: Michael Loizos
Published: August 2023

The prediction made by a learned model is rarely the end outcome of interest to a given agent. In most real-life scenarios, a certain policy is applied on the model’s prediction and on some relevant context to reach a decision. It is the (possibly temporally distant) effects of this decision that bring value to the agent. Moreover, it is those effects, and not the model’s prediction, that need to be evaluated as far as the agent’s satisfaction is concerned. The formalization of such scenarios naturally raises certain questions: How should a learned model be integrated with a policy to reach decisions? How should the learned model be trained and evaluated in the presence of such a policy? How is the training affected in terms of the type of access that one has on the policy? How can the policy be represented and updated in a way that is cognitively compatible with a human, so that it offers an explainable layer of reasoning on top of the learned model? This chapter offers a high-level overview of past work on the integration of modular reasoning with autodidactic learning and with user-driven coaching, as it applies on neural-symbolic architectures that combine sequentially a neural module with an arbitrary symbolically represented (and possibly non-differentiable) policy. In this context, the chapter offers responses to the questions above when the policy can be reasoned with only in a deductive manner, or in a deductive and an abductive manner. It further discusses how the policy can be learned / updated in an elaboration-tolerant and cognitively-light manner through machine coaching, and highlights the connections of the dialectical coaching process with the central role that argumentation plays in human reasoning.
Chapter 17. Approximate Answering of Graph Queries
Authors: Cochez Michael , Alivanistos Dimitrios , Arakelyan Erik , Berrendorf Max , Daza Daniel , Galkin Mikhail , Minervini Pasquale , Niepert Mathias , Ren Hongyu
Published: August 2023

Knowledge graphs (KGs) are inherently incomplete because of incomplete world knowledge and bias in what is the input to the KG. Additionally, world knowledge constantly expands and evolves, making existing facts deprecated or introducing new ones. However, we would still want to be able to answer queries as if the graph were complete. In this chapter, we will give an overview of several methods which have been proposed to answer queries in such a setting. We will first provide an overview of the different query types which can be supported by these methods and datasets typically used for evaluation, as well as an insight into their limitations. Then, we give an overview of the different approaches and describe them in terms of expressiveness, supported graph types, and inference capabilities.
Chapter 18. Enhancing Case-Based Reasoning with Neural Networks
Authors: Leake David , Wilkerson Zachary , Ye Xiaomeng , Crandall David J.
Published: August 2023

Integrations of case-based reasoning (CBR) with neural approaches are appealing because of their complimentary characteristics. This chapter presents research on neuro-symbolic integrations to support CBR, to reduce knowledge engineering and improve performance for CBR systems. It summarizes three strands of research: First, on extracting features for case retrieval from deep neural networks to use in concert with expert-generated features, second, on applying neural networks to learn to adapt the solutions of retrieved cases to fit new situations, and third, on harmonizing similarity learning with case adaptation learning, in order to focus retrieval on adaptable cases. It summarizes strengths, weaknesses and tradeoffs of these approaches, and points to future challenges for neuro-CBR integrations.
Chapter 20. Neuro-Symbolic Architectures for Combinatorial Problems in Structured Output Spaces
Authors: Nandwani Yatin , Mausam  , Singla Parag
Published: August 2023

Recently there has been a lot of focus on developing deep learning models for symbolic reasoning tasks. One such task involves solving combinatorial problems, which can be viewed as instances of a constraint satisfaction problem, albeit with unknown constraints. The task of the neural model is then to discover the unknown constraints using the training data consisting of many solved instances. There are broadly two approaches for learning the unknown constraints: the first approach creates a purely neural model that maps an input puzzle directly to its solution, thereby representing the constraints implicitly in the model’s weights [1, 2, 3], and the second approach invokes a symbolic reasoner, such as an Integer Linear Program (ILP) solver, learning the constraints explicitly in the solver’s language, e.g., linear inequalities for an ILP solver [4, 5]. In this chapter, we discuss about both the implicit and explicit approaches. In the implicit approach, we review three neural architectures for solving combinatorial problems, viz., Neural Logic Machines (NLM) [2], Recurrent Relational Networks (RRN) [1], and its extensions proposed by Nandwani et al. [3] to tackle output space invariance (solving 16×16 sudoku after training on 9×9 sudokus). Under the second approach having explicit representation of constraints, we present two methods (CombOptNet [5] and ILP–Loss[4]) for end-to-end training of a Neural-ILP architecture: a neuro–symbolic model where a neural perception layer is followed by an ILP layer to represent reasoning. CombOptNet proposed by Paulus et al. [5] trains slowly owing to a call to an ILP solver in each learning iteration. On the other hand, ILP–Loss proposed by Nandwani et al. [4] is solver–free during training and thus much more scalable. In the end, we present specific experiments from [3] and [4] that compare the different methods discussed in this chapter.
Chapter 26. Combining Sub-Symbolic and Symbolic Methods for Explainability
Authors: Himmelhuber Anna , Grimm Stephan , Joblin Mitchell , Zillner Sonja , Runkler Thomas
Published: August 2023

Many important real-world data sets come in the form of graphs or networks, including social networks, knowledge graphs, protein-interaction networks, the World Wide Web and many more. Graph neural networks (GNNs) are connectionist models that capture the dependence structure induced by links via message passing between the nodes of graphs. Similarly to other connectionist models, GNNs lack transparency in their decision-making. Since the unprecedented levels of performance of such AI methods lead to increasing use in the daily life of humans, there is an emerging need to understand the decision-making process of such systems. While symbolic methods such as inductive logic learning come with explainability, they perform best when dealing with relatively small and precise data. Sub-symbolic methods such as graph neural networks are able to handle large datasets, have a higher tolerance to noise in real world data, generally have high computing performance and are easier to scale up. We aim to develop a hybrid method by combining GNNs, sub-symbolic explainer methods and inductive logic learning. This enables human-centric and causal explanations through extracting symbolic explanations from identified decision drivers and enriching them with available background knowledge. With this method, high-accuracy sub-symbolic predictions come with symbolic-level explanations, and the preliminary evaluation results reported show an effective solution for the performance vs. explainability trade-off. The evaluation is done on a chemical use case and an industrial cybersecurity use case.
Chapter 27. Explaining CNNs Using Knowledge Extraction and Graph Analysis
Authors: Horta Vitor A.C. , Mileo Alessandra
Published: August 2023

Explainable Artificial Intelligence (XAI) has recently become an active research field due to the need for transparency and accountability when deploying AI models for high-stake decision making. Despite state-of-the-art Convolutional Neural Networks (CNNs) have achieved great performance in computer vision, understanding their decision processes, especially when a mistake occurs, is still a known challenge. The research direction presented in this chapter stems from the idea that combining knowledge with deep representations can be the key to more transparent decision making. Specifically, we have proposed a graph representation, called co-activation graph, that can be used as an intermediate representation between knowledge encoded within a trained CNNs with the semantics contained in external knowledge bases. Given a trained CNN, in this chapter we first show how a co-activation graph can be created and exploited to generate global insights for the inner-workings of the deep model. Then, we illustrate in detail how background knowledge from external knowledge bases can be connected to the graph in order to generate textual local factual and counterfactual explanations based on semantic attributes. Our results indicate that graph analysis approaches such as community analysis, node centrality and link prediction applied to co-activation graphs can reveal important insights into how CNNs work and enable both global and local semantic explanations for Deep Learning models. At the end of the chapter we will discuss interesting research directions that are being investigated in the area of using knowledge graphs and graph analysis for explainability of deep learning models.
Chapter 28. Effective Reasoning over Neural Networks Using Łukasiewicz Logic
Authors: Preto Sandro , Finger Marcelo
Published: August 2023

In this chapter, we present a research line whose aim is to represent neural networks in Łukasiewicz Infinitely-valued Logic (Ł∞) so that one might reason about such neural networks by means of logical machinery. We focus on a class of neural networks with inputs and outputs in the unit interval [0,1] concentrating the study on the ones that compute piecewise linear functions, which is not a strong constraint since such functions may densely approximate any continuous function. For that, we introduce the concept of representation modulo satisfiability, that enlarges the representational power of Ł∞. We derive an algorithm for building such representations, which terminates in polynomial time as long as the input is given in a suitable format. As applications of representation modulo satisfiability, we proceed by showing how properties of neural networks, such as reachability and robustness, may be encoded in Ł∞, giving rise to formal verification techniques. Finally, we present a case study where some formal verifications are performed in real-world neural network.
Numerical analysis of the stressed-deformed state of a tubular element under thermal loading
Authors: Maksimyuk Yuriy , Martyniuk Ivan , Kozak Oleksandr , Maksimyuk Oleksandr
Published: August 2023

In articles [2-5] solving relations and the block iteration method algorithm for solving linear and nonlinear equations by the semi-analytical finite element method for curvilinear heterogeneous prismatic bodies are implemented. In article [1], a numerical study of the convergence of the solution was performed, a wide range of test problems for bodies with smoothly and abruptly changing physical and geometric characteristics in elastic and elastic-plastic settings were considered. In [6], to confirm the reliability of the results obtained on the basis of the semi-analytical method of finite elements, the effectiveness of the application of this approach for the calculation of curvilinear inhomogeneous prismatic objects is shown. Solving control problems of the theory of elasticity, thermoelasticity, and thermoplasticity, as well as shape change problems, makes it possible to draw a conclusion about the reliability of the results of the research of a selected class of objects based on the developed methodology and implements its application program package.

In this paper, using the methodology outlined in the above works, the results of the numerical solution of the problem, which have an applied value, were presented. The stress-strain state of a tubular element with a rectangular cutout under conditions of thermoforce loading was studied. As a rule, solving similar problems is carried out in a flat setting without taking into account the bending load. This approach greatly simplifies the formulation of the problem, but leads to very significant errors in the results. At zero value of the bending load, a good agreement of the planar and spatial solutions is observed. The presence of a bending load leads to deviation of the curves from their initial position. The maximum discrepancy of the results is almost 50%.

The analysis of this structure from the standpoint of the spatial problem of thermoplasticity, which ensures taking into account the dependence of the physical and mechanical characteristics of the material on temperature and taking into account the bending load on the section of the cut, allowed us to reveal the real features of its deformation.
Influence of polymer aggregate reinforcement on the dynamics of three-layer cylindrical structure of elliptical cross-section
Authors: Gaidaichuk Viktor , Kotenko Kostyantyn , Lazareva Maryna
Published: August 2023

The dynamic behavior of a three-layer cylindrical structure of normal elliptical cross-section with a discrete polymer filler under internal non-stationary loading was investigated. A finite element model of the structure was created and calculations of normal deflections  and normal stresses  of its bearing layers were performed using a software and calculation complex Fimap with NX Nastran. The values of deflections and stresses of the specified layers in the absence and presence of reinforcement of the polymer aggregate structure at the ratio of elasticity of the material of bearing layers and aggregate are given E1,2/Et=500.

Reinforcement of polymer aggregate with metal stiffening ribs significantly affects the dynamic behavior of the three-layer cylindrical structure. The presence of this factor synchronized the stress-strain layer of the bearing layers of the structure, reduced the values of normal deflections and stresses of the bearing layers of the cylindrical three-layer structure. The effectiveness of reinforcement of polymer aggregate is confirmed by other materials, which indicates the feasibility of the practical use of such a constructive measure.
Inspection of war-damaged buildings and structures by the example of urban settlement Borodianka
Authors: Molodid Oleksandr , Kovalchuk Oleksandr , Skochko Volodymyr , Plokhuta Ruslana , Molodid Olena , Musiiaka Ivan
Published: August 2023

Inthe first 100 days of the full-scale armed aggression of Russia's armed forces against Ukraine, more than 1600 rocket strikes were carried out, not including other shelling.In this regard, numerous buildings and structures suffered various damages.

Using the developed "Methodology of surveying and registration of its results", surveyors developed a procedure for surveying many buildings and structures in a short period.

KNUCA (Kyiv National University of Construction and Architecture) specialists inspected multi-apartment, communal, and administrative buildings in the Borodiankavillageinthe Kyiv region.Based on the results of the surveys, damage to buildings was systematized depending on their causes, namely explosions, and their impact on structures – explosive shock wave, fire, and bullet or shrapnel damage.

The direct damage caused by the explosive shock wave included: destruction, cracking, distortion, and declination from the axis of symmetry, damage to window glasses and frames, for brick structures: knocking out (individual bricks or sections of the wall), protrusion (indentation) and displacement of masonry elements, cracks in masonry and spilling of seams between building elements.The direct damage to structures from shrapnel and bullet injuries includes: through holes, splinters, damage to coatings and the roofing layer, jamming of structures, et cetera.The direct damage to structures caused by thermal effectsincludes fire damage, including irreversible thermal elongation of reinforcement and destruction of concrete; damage to the finishing layers; destruction of window and door frames and their filling; the collapse of the roof; destruction of wooden walls and ceilings.

KNUCA specialists established that buildings suffer significant damage and destruction when an aerial bomb hits. The most destructive effect is the damage caused by multiple launch rocket systems (MLRS), artillery weapons, and tanks. However, buildings (building structures) suffer minor damage when hit by Armory Personnel Carriers (APVs) and small arms.
Impact of geometric parameters and physical-mechanical properties of the internal bearing layer on the dynamic transient processes of the three-layer hemispherical shell
Authors: Gaidaichuk Viktor , Mamedov Alirza , Kotenko Kostyantyn
Published: August 2023

The effect of geometrical parameters and physical-mechanical properties of the internal bearing layer of a three-layer spherical structure on its dynamic behavior under internal impulse loading was investigated. A finite-element model of the structure was created and calculations of normal deflections and normal stresses of its bearing layers were performed using the Fimap with NX Nastran software and calculation complex. Options for reducing the negative impact of inefficient design solutions are considered.

Geometric parameters and physical and mechanical properties of the internal bearing layer of the shell structure under internal impulse loading are significant.

An effective factor of stability to dynamic influences of layered shell structures is the provision of optimal ratios of geometric parameters and physical and mechanical characteristics of the materials of their bearing layers and polymer aggregate.
Numerical study of the parametric optimization of the forced oscillation frequencies of the shell of a minimal surface on a trapezoidal contour under thermal and power loading
Authors: Ivanchenko Hryhoriy , Koshevyi Oleksandr , Koshevyi Oleksandr , Grigoryеva Lyudmyla
Published: August 2023

This research paper discusses various methods and approaches to the optimal design of structures. Methods for solving the optimization problem can be divided into two large groups. The first group includes methods that are based on the use of the necessary conditions for the extremes of the objective function. The second group consists of mathematical programming methods: linear, convex, dynamic programming, and random search. In mathematical terms, optimal design problems are optimization problems - the search for an extremum of the objective function and the values of the parameters at which the extremum is achieved. The choice of the optimality criterion is one of the main problems of optimal design. The most widely developed problems are those that have the optimization criterion of weight or volume of the structure while satisfying the conditions of strength, rigidity and stability.

Optimal design problemsare also divided into three large groups. The first group is parametric optimization problems, which involve the optimization of one or more parameters, called design variables, to minimize or maximize the objective function. The second group is topological optimization, in which unnecessary material is discarded, where the Mises stress is zero, thereby minimizing the objective function. The third group is optimization of the shape of the object under study, when the shape corresponds to internal forces, the shell with the smallest area is modeled on a given cone (shells of minimal surfaces), as well as methods of applied geometry, where the surface shape is modeled for a certain load.

To perform the parametric optimization of the forced vibrations of the shell of the minimum surface on a trapezoidal contour, the objective function is the weight of the spatial structure. The variables in the parametric optimization problem are the thickness of the finite elements from 1 to 100 mm. The structure constraint is imposed on the first forced oscillation frequency of 0.250 Hz. This type of problem is used to prevent resonance from process equipment that can affect the natural frequencies of the structure under external load.Subject of this study is an interesting applied problem for construction mechanics, as it is the first time to display the application of two types of optimization on one research object.

The results of a numerical study of the parametric optimization of the minimum surface shell on a trapezoidal cage under thermal power loading.  The parametric optimization helped to reduce the weight of the shell by 13.4%, which is 1810 kg of sheet steel. The first forced oscillation frequency meets the constraint of the optimization calculation. We constructed 10 forced vibration frequency shapes of the shell before and after optimization, and also presented the distribution of the shell thickness after the optimization calculation.