Formal Analysis Research Articles

Criminalising looting in wartime: International and national experiences

The relevance of this research topic is conditioned by the increasing number of cases of looting during armed conflicts, which requires the improvement of legal mechanisms for criminalising this act. Even though looting is recognised as a war crime at the international level, there are significant differences in approaches to its criminalisation and the determination of liability for such acts in national legal systems. This creates the risk of ambiguous interpretation of legal norms in judicial practice and complicates the administration of justice. The purpose of this study was to analyse the global and national experiences with the criminalisation of looting during armed conflicts, using the cases of Bosnia and Herzegovina, Sierra Leone, and Ukraine, as well as to formulate recommendations for improving Ukraine’s national legislation in this area. The study employed the methods of comparative legal analysis, formal legal analysis, and case law analysis. The study compared the criminal law provisions and approaches of different countries to the prosecution of pillage, specifically the concepts of “military necessity” and “spoils of war”. The findings of the study showed that the absence of clear legal definitions and criteria for assessing “military necessity” and “gravity of the violation” complicates prosecution for this crime and creates risks of abuse. The study revealed major differences in approaches to the criminalisation of looting, particularly in determining the scope and conditions of liability. The practical value of this study lies in its recommendations for harmonising Ukrainian legislation with international standards. It was suggested that a separate law be drafted to define the mechanisms for criminalising looting during armed conflicts, to establish clear criteria for assessing military necessity, and to unify approaches to judicial practice. This will help to increase the effectiveness of investigations and prosecutions of this type of war crime and strengthen Ukraine’s legal framework in armed conflict

EMAKAS: An efficient three-factor mutual authentication and key-agreement scheme for IoT environment

The adoption of IoT in healthcare revolutionizes remote patient monitoring and healthcare efficiency. Yet, it brings notable security and privacy challenges, particularly in resource-constrained environment. We propose a secure and efficient three-factor lightweight mutual authentication and key agreement scheme, designed for IoT-based smart healthcare systems, addressing these critical concerns. The scheme employs a fuzzy extractor, a one-way hash function, Elliptic Curve Discrete Logarithm and XOR operations for efficient cryptographic transformations, creating a robust framework for secure data handling. The scheme's design focuses on security and privacy while minimizing computational demands, making it ideal for resource-constrained IoT devices. We utilized both informal and formal security analyses to validate our scheme, employing the Random Oracle Model (ROM), Scyther tool and Burrows-Abadi-Needham (BAN) logic. The security and performance analysis showed that our scheme offers more security features across 15 defined criteria with minimal communication and computational costs compared to other related schemes. The scheme is not only robust against security threats but also practical for implementation in IoT healthcare environment, offering a solution for secure IoT communication by achieving mutual authentication and key agreement with minimized computational requirements.

Video Art and Collective Memory in Turkey

The aim of this article is to present and study contemporary video practices since the 2000s in Turkey through the representation of time and collective memory. The article features the four video artists who have structured the video art scene in Turkey: Ali Kazma, Halil Altındere, Erkan Özgen and Seza Paker. This research addresses two interconnected issues: firstly, the purpose is to examine how the distinct technical parameters of video production shape a synthesized temporality. This inquiry naturally gives rise to a secondary purpose: in what manner does this constructed temporality facilitate the exploration of memory and historical discourse? The hypothesis is that the video image, both as a technical artifact and a conceptual construct, inherently possesses its unique framework for temporal construction, thereby actively contributing to novel reinterpretations of collective memory and historiography The methodology involves conducting a formal analysis of the video content. This approach focuses on examining the visual elements, composition, use of color, sound, editing techniques, and overall aesthetics of the video to gain deeper insights into its artistic significance and meaning. By employing formal analysis, the aim of this article is to decipher the visual language employed by the video artists and uncover nuanced layers of interpretation.

Stance of numerous leadership styles and their effect on teaching to sustain academic performance at the high school level

The present study focused on three leadership, autocratic, democratic, and Laissez-faire, to sustain high school academic performance. To accomplish this, we used quantitative survey method and employed convenient sampling technique to collect data from 358 high school teachers/educators in various regions of Multan, Punjab, Pakistan. Data collection consisted of administering a survey questionnaire that used a five-point Likert Scale. The questionnaire included four variables: one dependent variable, sustained academic Performance, and three independent variables: Autocratic Leadership, Democratic Leadership, and Laissez-faire Leadership. Following data collection, Cronbach's alpha was used to assess the questionnaire's reliability, while the Kolmogorov-Smirnov test was utilized to confirm the normality of the data. Formal statistical analysis included conducting a correlation study to ascertain the association between Autocratic Leadership, Democratic Leadership, and Laissez-faire Leadership with SAP and the impact of each independent variable on the dependent variable. CFA and SEM were conducted using Linear Structural Relations (LISREL) 8.80. These tests were used to identify relationships and differences among the study participants' opinions. The findings indicate that democratic leadership has a highly positive impact, and autocratic leadership has a moderate impact on sustaining academic performance. In contrast, the laissez-faire leadership style has the lowest impact on sustaining academic performance. Based on the study's findings, it is recommended that school teachers/educators should use a combination of democratic and authoritarian leadership styles in their classes to promote cooperation, student participation, ownership in the learning process and leading to their exceptional performance. Furthermore, the findings suggest that schools should actively promote teacher involvement in administrative tasks and decision-making. Ultimately, by integrating the advantages of both types, it is possible to cultivate a comprehensive educational experience that promotes scholarly achievement and equips students with the necessary skills to tackle future problems.

A stochastic Galerkin lattice Boltzmann method for incompressible fluid flows with uncertainties

Efficient modeling and simulation of uncertainties in computational fluid dynamics (CFD) remains a crucial challenge. In this paper, we present the first stochastic Galerkin (SG) lattice Boltzmann method (LBM) built upon the generalized polynomial chaos (gPC). The proposed method offers an efficient and accurate approach that depicts the propagation of uncertainties in stochastic incompressible flows. Formal analysis shows that the SG LBM preserves the correct Chapman–Enskog asymptotics and recovers the corresponding macroscopic fluid equations. Numerical experiments, including the Taylor–Green vortex flow, lid-driven cavity flow, and isentropic vortex convection, are presented to validate the solution algorithm. The results demonstrate that the SG LBM achieves the expected spectral convergence and the computational cost is significantly reduced compared to the sampling-based non-intrusive approaches, e.g., the routinely used Monte Carlo method. We obtain a speedup factor of 5.72 compared to Monte Carlo sampling in a randomized two-dimensional Taylor–Green vortex flow test case. By leveraging the accuracy and flexibility of LBM and the efficiency of gPC-based SG, the proposed SG LBM provides a powerful framework for uncertainty quantification in CFD practice.

Masculinity and Homosociality in Western Cinema: Taking Close (2022) as a Case Study

Masculinity and homosociality in Western cinema undergo continuous evolution, transitioning from the construction of traditional ideals to contemporary, more diverse expressions, thereby presenting challenges and deconstructions. To contribute to the theorization of masculinity and homosociality in Western films, this study examines Lukas Dhont's Close to analyze how masculinity and homosociality are represented and negotiated to reproduce gender structures and heteronormative ideologies, and offer implications for future film presentations. Employing textual and formal analyses, along with relevant theories of masculinity and homosociality, this paper identifies different forms of masculinities embodied in hierarchical and horizontal homosociality. In doing so, this paper finds that homosociality provides space for some masculinities to assert and solidify their dominance while relegating others to subordinated or marginalized positions. The dynamic shifts in masculinity also correspondingly affect homosocial dynamics. Further exploration is warranted in presenting and constructing positive narratives surrounding non-hegemonic masculinity and horizontal homosociality, so that a diverse, anti-homophobic, and gender equality-supporting masculinity on screen may have the potential to achieve hegemony.

Decentralized Federated Recommendation with Privacy-aware Structured Client-level Graph

Recommendation models are deployed in a variety of commercial applications to provide personalized services for users. However, most of them rely on the users’ original rating records that are often collected by a centralized server for model training, which may cause privacy issues. Recently, some centralized federated recommendation models are proposed for the protection of users’ privacy, which however requires a server for coordination in the whole process of model training. As a response, we propose a novel privacy-aware decentralized federated recommendation (DFedRec) model, which is lossless compared with the traditional model in recommendation performance and is thus more accurate than other models in this line. Specifically, we design a privacy-aware structured client-level graph for the sharing of the model parameters in the process of model training, which is a one-stone-two-bird strategy, i.e., it protects users’ privacy via some randomly sampled fake entries and reduces the communication cost by sharing the model parameters only with the related neighboring users. With the help of the privacy-aware structured client-level graph, we propose two novel collaborative training mechanisms in the setting without a server, including a batch algorithm DFedRec(b) and a stochastic one DFedRec(s), where the former requires the anonymity mechanism while the latter does not. They are both equivalent to probabilistic matrix factorization trained in a centralized server and are thus lossless. We then provide formal analysis of privacy guarantee of our methods and conduct extensive empirical studies on three public datasets with explicit feedback, which show the effectiveness of our DFedRec, i.e., it is privacy aware, communication efficient, and lossless.

The creative city’s swan song? The individualisation of the music scene in Bologna, UNESCO City of Music

This paper extends the debate on medium-sized cities as active designers of place-specific neoliberal identities by reporting relevant findings from Bologna, European Capital of Culture in 2000 and a UNESCO City of Music since 2006. The study identifies the formal relationships of collaboration among local musicians as a relevant proxy to discuss the individualisation of the pop-rock music scene and its variations between 1978 and 2019. For this purpose, formal Social Network Analysis is combined with semi-structured interview analysis and archival research. The findings reveal decreased levels of social cohesion among artists and establishes a link between growing individualisation in the local music scene and an increasing tourist-orientation in the city.

HCFAIUN: A novel hyperelliptic curve and fuzzy extractor-based authentication for secure data transmission in IoT-based UAV networks

IoT-based UAV networks comprise interconnected UAVs outfitted with sensors and microcontrollers to simplify data exchange in environments such as smart cities. In light of open-access communication landscapes, IoT-based UAV networks could pose security challenges, encompassing authentication vulnerabilities and the inadvertent disclosure of location and other confidential information to unauthorised parties. Henceforth, we have proposed a lightweight and secure authentication protocol: Hyperelliptic Curve and Fuzzy Extractor based Authentication in IoT-based UAV networks (HCFAIUN) leveraging Hyperelliptic Curve Cryptography(HCC), Fuzzy Extractor (FE), XOR operations and hash functions. HCC's maximum key size is 80 bits, differing from the 160-bit requirement of the elliptic curve, making it apt for UAVs with limited resources. The proposed scheme utilises biometrics traits of users to avoid exposing data from stealing smart devices using FE. This protocol facilitates the mutual authentication of users and UAVs, allowing them to exchange a session key for secure communication. The Hyperelliptic Curve (HC) scalar multiplication protects the user's private key from attackers, even in public channels. The obfuscation identity of the user and UAVs generated through the hash function and timestamp makes the external user and UAV anonymous. The efficacy of this proposed framework is examined using the Scyther verification tool and Random oracle model-based formal analysis, and informal analysis is also discussed, which validates its robustness against well-known potential physical and logical attacks. The performance analysis shows that the HCFAIUN scheme has lower computation, communication, and storage costs, i.e., 3.832 ms and 1456 bits and 1128 bits, respectively, compared to existing schemes.

Single sample-oriented attribute reduction for rule learning with formal concept analysis

As an effective tool for data mining, formal concept analysis can yield interpretable decision rules using attribute reduction. Currently, existing reduction methods within the framework of formal concept analysis result in all samples sharing the same conditional attributes, thereby overlooking the distinctions between rules extracted from different samples. To address this problem, we present a novel attribute reduction method for single samples. For this purpose, a single sample-oriented reduction framework is established by incorporating a discernibility attribute vector and an algorithm for calculating reducts based on the matrix representation of the discernibility attribute vector. Furthermore, the process of obtaining a new reduct from the original reduct is discussed by considering incremental learning. Given that attributes included in reducts are crucial conditions for decision-making, intent-minimal granular rules are generated through attribute reduction, and a reduction-based method for measuring the completeness of the rule set is discussed. Finally, to accomplish the classification task, a minimal rule-based classification model (MRCM) is proposed. The experimental results show that the MRCM has the same classification ability as the unreduced rules, and the rules with higher completeness tend to exhibit better classification performance.

Photovoice for leveraging traditional, complementary, and integrative medicine amongst black adults to improve sleep health and overall health.

Average adults are recommended to have 7-8 h of sleep. However insufficient sleep (IS defined as <7 h/nightly) is associated with increased risk of chronic diseases such as cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM). Traditional, complementary, and integrative medicine (TCIM), a burgeoning area of research and practice, leverages both modern and traditional approaches to improve health. Despite TCIM's recognition as a tool to improve sleep and related outcomes, there is a gap in literature in addressing its impact among black individuals, who experience a disproportionate burden of IS and chronic disease. This qualitative study aimed to increase understanding of TCIM practices to overcome IS and overall health in black communities. Using photovoice methodology, a qualitative tool which applies community-engaged principles to produce culturally informed results through interviews and digital media, consented participants were recruited from Miami, Florida and (1) instructed to capture images over one week that communicated their TCIM to improve sleep and overall health on their mobile device; (2) interviewed using individual, semi-structured procedures to add "voice" to the "photos" they captured for ~20 min; and (3) invited to participate in follow-up focus groups for refined discussion and data triangulation for ~1.5 h. Both individual and focus group interviews were conducted over Zoom with recordings transcribed for formal content analysis using Nvivo software. The sample included N = 25 diverse US black individuals (M = 37, SD = 13, range 21-57). Approximately a quarter of the sample were unemployed (N = 7) and majority were women (N = 21). Results highlighted five themes including: (1) natural wellness (sleep supplements, comfort beverages, aromatherapy, herbalism, outdoors); (2) self-care (self-maintenance, physical activity, spatial comfort); (3) leisure (pet support, play); (4) mental stimulation (mindfulness, reading); and (5) spiritual wellness (faith-based practices). Study results elucidate the heterogeneity of diverse US black individuals regarding sociocultural knowledge, beliefs, and behaviors. Addressing IS in black communities requires a comprehensive strategy that integrates cultural sensitivity, family and community dynamics, education, mental health support, and informed policymaking. Future studies should consider how sleep health literacy, stress appraisal, and coping strategies may vary by race/ethnicity for tailored intervention.

DIDS: A distributed inference framework with dynamic scheduling capability

Distributed inference is a promising solution for deploying Deep Neural Network (DNN) applications in resource-constrained edge environments. However, due to the complexity and variability of edge scenarios, efficiently completing DNN inference remains challenging. While previous works have made significant progress in various aspects such as partition strategy, device diversity, and memory overhead, few consider the impact of environmental dynamics, particularly environmental workloads. This oversight renders existing solutions impractical. In this study, we propose DIDS, a distributed inference framework with dynamic scheduling capability that considers environmental dynamics. We first conduct a formal analysis of distributed inference and design two basic scheduling strategies: Re-Partition and Complete-Push. Then we introduce Dynamic Push, a runtime scheduler based on Complete-Push that aims to mitigate the impact of environmental workloads through runtime scheduling. The evaluation results show that DIDS can achieve up to 3.7x speedup compared to static distributed inference, in addition, DIDS is also able to achieve significant improvement compared to the state-of-the-art method.

Enhancing Trust in Transactive Energy with Individually Linkable Pseudonymous Trading Using Smart Contracts

The transactive energy market (TEM) is a recent development in energy management that enables prosumers to trade directly, promising many environmental and economic benefits. Prosumer trading necessitates sharing information to facilitate transactions. Additionally, many TEMs propose using blockchains to manage auctions and store transactions. These facts introduce privacy concerns: consumption data, trading history, and other identifying information pose risks to users if leaked. Anonymity by trading under a pseudonym is commonly presented as a solution; however, this creates risks for market participants: scammed users will not have recourse, and users with innocent malfunctions may be banned from trading. We propose the Individually Linkable Pseudonymous Trading Scheme (ILPTS), which enables users to trade under a pseudonym, protecting their identity, while a smart contract monitors reputations and can temporarily deanonymize a user, ensuring market integrity. ILPTS was developed in stages. Examination of existing TEM literature was performed to identify desirable features. Analysis of cryptography literature was performed to identify techniques that may confer certain features. It was found through formal analysis that ILPTS adheres to identified design goals, improves upon existing solutions, and resists common attacks against TEMs. Future work includes software simulation and on-device implementation to further verify security and feasibility.

MSCFS-RP: A Colored-Petri-Net-Based Analysis Model for Master–Slave Cloud File Systems with Replication Pipelining

As a typical information system, a cloud file system enables the storage, retrieval, and management of data on remote servers or server clusters. The reliable design of such systems is critical to ensure the security of data and availability of services. However, designing correct-by-construction systems is challenging due to the complexity of and concurrency inherent in cloud file systems. Further, existing works on cloud file system analysis often focus on specific systems or lack formal modeling and verification, leading to potential design flaws and security vulnerabilities. To address these issues, we propose MSCFS-RP, which is a formal analysis model based on colored Petri nets. Leveraging the strengths of colored Petri nets in representing diverse information types with colored tokens and defining explicit rules for concurrent interactions, our model captures the writing and reading processes of clients, meta servers, and clusters. With strong formalism and support for verification using CPN Tools, we rigorously evaluate key properties such as replication consistency under various scenarios. The results demonstrate that MSCFS-RP satisfies these properties, validating its effectiveness and trustworthiness in managing information within cloud storage systems.

Trends and predictors of reporting social determinants of health in shoulder surgery

IntroductionThe role of social determinants of health (SDH) in patient outcomes, quality of life, and overall well-being has been well documented. However, the inclusion of these variables in randomized control trials (RCTs) remains limited; thus, the extent of generalizability from such trials is brought into question. The purpose of this study is to explore the rates of reporting SDH variables in RCTs focused on shoulder surgery from the past decade. MethodsThe PubMed database was searched for RCTs with a focus on shoulder surgery from 2013-2023. Duplicates, responses to the editor, biomechanical studies, and non-shoulder studies were excluded. Each article was reviewed and data pertaining to patient demographics, socioeconomic covariates. Journal of publication was recorded, and studies from the five most common journals were analyzed. These journals were the Journal of Shoulder and Elbow Surgery (JSES), the Journal of Bone and Joint Surgery (JBJS), the American Journal of Sports Medicine (AJSM), the Bone and Joint Journal (BJJ), and The Journal of the American Medical Association (JAMA). Multivariate logistic regression was performed to determine the independent effect of study characteristics on the reporting rates of SDH. ResultsA total of 255 articles were reviewed. Of these, 93.3% and 90.2% of articles reviewed reported age and sex, respectively. Employment status was reported in 11.8% of articles. Fewer than 10% reported race, ethnicity, income, insurance, and housing, with even less performing formal analyses on these variables. Studies that were conducted in the United States (US), multicenter, had a sample size 251+, and had a combination of public and private funding were significantly more likely to report on race and ethnicity. Reporting employment status was significantly associated with being European-based, multicenter, sample size 251+, double-blinded, and published in AJSM, Newer studies were significantly less likely to report education. Only publication in AJSM was significant for reporting income. Study intervention and topic were not significant for any SDH reporting. DiscussionThis data reflects how small of a proportion of RCTs report and analyze on SDH variables. These findings reflect a need for future RCTs to accurately report SDH variables that influence outcomes, such as race, ethnicity, education, employment, income, housing status, and insurance.. ConclusionsSDH are infrequently reported and analyzed in RCTs pertaining to shoulder surgery. Academic medical journals should incorporate guidelines to encourage studies to include such variables and enable the assessment of outcomes to apply to a broader population.

“Is this where the Jew butchered that poor woman?”: antisemitism in Eddie Campbell’s and Alan Moore’s From Hell

ABSTRACT By using formal analysis and investigating the history related to the emigration of East End Jews in London, I discuss antisemitism in From Hell. From Hell provides various visual and verbal coordinates to suggest that the birth of the 20th century will bring antisemitic values and rhetoric which will, in turn, contribute to the Holocaust. In that way, Sir William Gull (or Jack the Ripper) is not just midwifing the twentieth century to bring upon a continuation of the patriarchy, but he also assists in the creation of the Shoah.

Fuzzy object-induced network three-way concept lattice and its attribute reduction

Concept cognition and knowledge discovery under network data combine formal concept analysis with complex network analysis. However, in real life, network data is uncertain due to some limitations. Fuzzy sets are a powerful tool to deal with uncertainty and imprecision. Therefore, this paper focuses on concept-cognitive learning in fuzzy network formal contexts. Fuzzy object-induced network three-way concept (network OEF-concept) lattices and their properties are mainly investigated. In addition, three fuzzy network weaken-concepts are proposed. As the real data is too large, attribute reduction can simplify concept-cognitive learning by removing redundant attributes. Thus, the paper proposes attribute reduction methods that can keep the concept lattice structure isomorphic and the set of extents of granular concepts unchanged. Finally, an example is given to show the attribute reduction process of a fuzzy network three-way concept lattice. Attribute reduction experiments are conducted on nine datasets, and the results prove the feasibility of attribute reduction.

Multidimensional Representation of Semantic Relations between Physical Theories, Fundamental Constants and Units of Measurement with Formal Concept Analysis

We propose several hierarchical graphs that represent the semantic relations between physical theories, their fundamental constants and units of measurement. We begin with an alternative representation of Zel’manov’s cube of fundamental constants as a concept lattice. We then propose the inclusion of a new fundamental constant, Milgrom’s critical acceleration, and discuss the implications of such analysis. We then look for the same fundamental constants in a graph that relates magnitudes and units of measurement in the International System of Units. This exercise shows the potential of visualizing hierarchical networks as a tool to better comprehend the symmetries, interrelations and dependencies of physical magnitudes, units and theories. New regimes of application may be deduced, as well as an interesting reflection on our ontologies and corresponding theoretical objects.

Energy management in gyms microgrid: Nonlinear control of stationary bikes and treadmills with parallel rectifiers and AC/DC conversion

This article presents the complete design of a nonlinear control system for multiple stationary bikes connected to a mechanical energy conversion system equipped with squirrel cage induction generators (SIGs) linked to AC/DC converters. The primary objective of this study is to investigate the feasibility of powering multiple treadmills using the DC bus via DC/AC converters. The novelty of our approach lies in the integration of a new strategy of control system to achieve multiple control objectives within a gym microgrid environment, and an energy management algorithm to ensure the energy flow between intermittent generation and the considered, somewhat random, demand. The system is composed of several subsystems: i) stationary bikes connected to the DC bus via inverters acting as intermittent power sources; ii) a Li-ion battery-based energy storage system interfaced through a Buck-Boost converter; iii) electromechanical loads, including treadmills, powered by DC/AC converters, in addition to other DC loads. The main control objectives are as follows: a) each stationary bike extracts energy from the DC network by regulating the torque applied by the athlete, ensuring that the torque follows the reference torque; b) the treadmill’s speed must follow the reference generated based on the athlete’s condition; c) ensuring the protection of the energy storage system by monitoring its current and voltage; d) all mentioned objectives are achieved while maintaining the DC bus voltage at a reference value. To achieve these objectives, a nonlinear control approach based on Lyapunov theory is used to design the controllers. A formal analysis is conducted to assess the performance of the studied system. The system’s performance is demonstrated using the MATLAB/Simulink environment. Numerous simulations demonstrate that every control objective is achieved. Specifically, the system maintained the DC bus voltage at 500 V with a maximum deviation of 1 V, and the treadmill speed followed the reference within a margin of 0.1 m/s.

Common Financial Market of the EAEU: Concept, Structure and Problems of Formation

Aim. The purpose of the study is to substantiate the concept and structure of the common financial market of the Eurasian Economic Union, highlight the problems of its formation and ways to solve them. Tasks. The objectives of the study are: review and analysis of the definitions of the common financial market in the legal framework of the Eurasian Economic Union; highlighting key aspects of the development of the common financial market; defining its structure, problems of formation, proposing ways to solve them.Methods. Methods were used: institutional analysis, comparative analysis, system analysis to substantiate aspects of the formation and structure of the common financial market of the Eurasian Economic Union. The method of formal logical analysis was also used to clarify the concepts of the common financial market in various acts of the integration level.Results. Firstly, at the level of the Eurasian Economic Union, the concept and criteria of a common financial market have been established.Secondly, a broad and narrow understanding of the structure of the common financial market in the context of Eurasian integration is highlighted.Thirdly, the key aspects of the development of the common financial market are: expanding the range and accessibility of financial services; ensuring the rights of consumers of financial services and investors; security and transparency of financial services.Fourthly, the problems of forming a common financial market are highlighted, including the different levels of development of the markets of the integration member states, the weak sector of the securities and investment markets.Conclusions. The common financial market is part of Eurasian integration, the processes of formation of such a market are components of integration processes. The structure of the general financial market in the narrow sense includes the banking and insurance services sector, the securities market sector, and the relations between these sectors. A broad understanding of the structure of the general financial market additionally includes the tax, budget and currency areas.