bluuebunny/crossref_metadata_2025 huggingface dataset:
Local search algorithms on the Stable Marriage Problem: Experimental Studies
Authors: Gelain M.  , Pini M.S.  , Rossi F.  , Venable K.B.  , Walsh T.
Published: February 2025

The stable marriage problem (SM) has a wide variety of practical applications, ranging from matching resident doctors to hospitals, to matching students to schools, or more generally to any two-sided market. In the classical formulation, n men and n women express their preferences over the members of the other sex. Solving an SM means finding a stable marriage: a matching of men to women with no blocking pair. A blocking pair consists of a man and a woman who are not married to each other but both prefer each other to their partners. It is possible to find a male-optimal (resp., female-optimal) stable marriage in polynomial time. However, it is sometimes desirable to find stable marriages without favoring a group at the expenses of the other one. In this paper we present a local search approach to find stable marriages. Our experiments show that the number of steps grows as little as O(nlog(n)). We also show empirically that the proposed algorithm samples very well the set of all stable marriages of a given SM, thus providing a fair and efficient approach to generate stable marriages.
The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks
Authors: Kwisthout Johan H.P.  , Bodlaender Hans L.  , van der Gaag L.C.
Published: February 2025

Algorithms for probabilistic inference in Bayesian networks are known to have running times that are worst-case exponential in the size of the network. For networks with a moralised graph of bounded treewidth, however, these algorithms take a time which is linear in the network's size. In this paper, we show that under the assumption of the Exponential Time Hypothesis (ETH), small treewidth of the moralised graph actually is a necessary condition for a Bayesian network to render inference efficient by an algorithm accepting arbitrary instances. We thus show that no algorithm can exist that performs inference on arbitrary Bayesian networks of unbounded treewidth in polynomial time, unless the ETH fails.
Constraint-Based Controller Synthesis in Non-Deterministic and Partially Observable Domains
Authors: Pralet Cédric  , Verfaillie Gérard  , Lemaître Michel  , Infantes Guillaume
Published: February 2025

Controller synthesis consists in automatically building controllers taking as inputs observation data and returning outputs guaranteeing that the controlled system satisfies some desired properties. In system specification, these properties may be safety properties specifying that some conditions must always hold. In planning, they express that the evolution of the controlled system must terminate in a goal state. In this paper, we propose a generic approach able to synthesize memoryless or finite-memory controllers for both safety-oriented and goal-oriented control problems. This approach relaxes some restrictive assumptions made by existing work on controller synthesis with non-determinism and partial observability and is shown to induce potentially significant gains. The proposed “Simulate and Branch” algorithm consists in exploring the possible evolutions of the controlled system and in adding new control elements when uncovered states are discovered. The approach developed is constraint-based in the sense that control problems are formulated using the flexibility of constraint programming languages and that our implementation uses the Gecode constraint programming library.
Contract Search: Heuristic Search under Node Expansion Constraints
Authors: Aine Sandip  , Chakrabarti P.P.  , Kumar Rajeev
Published: February 2025

In this work, we present a heuristic search technique (Contract Search) which can be automatically adapted for a specified node expansion limitation. We analyze the node expansion properties of best first search and propose a probabilistic model (rank profile) to characterize heuristic search under restricted expansions. We identify the basic properties of the rank profile and establish its relation with the search space configuration. In Contract Search, we use the rank profile model to formulate an optimal strategy to choose level dependent restriction bounds maximizing the probability of obtaining the goal node under the specified contract. Experimental comparison with anytime search techniques like ARA* and beam search shows that Contract Search outperforms these techniques over a range of constraint specifications.
ISAC – Instance-Specific Algorithm Configuration
Authors: Kadioglu Serdar  , Malitsky Yuri  , Sellmann Meinolf  , Tierney Kevin
Published: February 2025

We present a new method for instance-specific algorithm configuration (ISAC). It is based on the integration of the algorithm configuration system GGA and the recently proposed stochastic offline programming paradigm. ISAC is provided a solver with categorical, ordinal, and/or continuous parameters, a training benchmark set of input instances for that solver, and an algorithm that computes a feature vector that characterizes any given instance. ISAC then provides high quality parameter settings for any new input instance. Experiments on a variety of different constrained optimization and constraint satisfaction solvers show that automatic algorithm configuration vastly outperforms manual tuning. Moreover, we show that instance-specific tuning frequently leads to significant speed-ups over instance-oblivious configurations.
Multi Grain Sentiment Analysis using Collective Classification
Authors: Shivashankar S.  , Ravindran B.
Published: February 2025

Multi grain sentiment analysis is the task of simultaneously classifying sentiment expressed at different levels of granularity, as opposed to single level at a time. Models built for multi grain sentiment analysis assume fully labeled corpus at fine grained level or coarse grained level or both. Huge amount of online reviews are not fully labeled at any of the levels, but are partially labeled at both the levels. We propose a multi grain collective classification framework to not only exploit the information available at all the levels but also use intra dependencies at each level and inter dependencies between the levels. We demonstrate empirically that the proposed framework enables better performance at both the levels compared to baseline approaches.
Towards (Probabilistic) Argumentation for Jury-based Dispute Resolution
Authors: Dung Phan Minh  , Thang Phan Minh
Published: February 2025

We propose an argumentation framework for modelling jury-based dispute resolution where the dispute parties present their arguments before a judge and a jury. While the judge as the arbiter of law determines the legal permissibility of the presented arguments the jurors as triers of facts determine their probable weights. Such a framework is based on two key components: classical argumentation frameworks containing legally permissible arguments and probabilistic spaces assigning probable weights to arguments. A juror's probability space is represented by a set of possible worlds coupled with a probabilistic measure computed by assumption-based argumentation framework using grounded semantics.
Lower Bounds on Argument Verification in Computational Dialectic
Authors: Vreeswijk Gerard
Published: February 2025

An argument may be considered sound (“admissible” or “RSA-compliable” in informal logic) if it is well-formed and fulfills a number of reasonable semantic criteria. When agents exchange arguments, not all incoming arguments are sound.
An Experimental Comparison of Use Case Models Understanding by Novice and High Knowledge Users
Authors: Mustafa Balsam A.
Published: February 2025

Use cases were introduced into the Unified Modeling Language to capture the functional requirements in object oriented systems development. This work reports the results of comparing two controlled experiments conducted on use case models with different subjects, in which the effect of use case format on users understanding of systems requirements is assessed. Replication with subjects of different knowledge in use case technique allowed us to investigate whether subjects experience play any role in the comprehension of use case models. The results of the controlled experiments showed that for the comprehension tasks, which required only surface understanding of the Use Case model, the provision of diagrams along with the textual use case descriptions significantly improved comprehension performance of both novice and high knowledge users. However, diagrams had no effect on users performance in the deep understanding tasks. Moreover, there was no evidence that prior experience with use cases has influenced subject's performance in surface and deep understanding tasks in familiar and unfamiliar application domains.
Multi-Level Product Line Customization
Authors: Elsner Christoph  , Schwanninger Christa  , Schröder-Preikschat Wolgang  , Lohmann Daniel
Published: February 2025

Managing and developing a set of software products jointly using a software product line approach has achieved significant productivity and quality gain in the last decade. More and more, product lines now are becoming themselves entities that are sold and bought in the software supply chain. Customers build more specialized product lines on top of them or derive themselves the concrete products. As customers have different requirements, whole product lines now may vary depending on customer needs—they need to be customized. Current approaches going beyond the scope of one product line do not provide appropriate means for customization. They either are tailored to specific implementation techniques, only regard customization on few levels (e.g., only source code level), or imply a lot of manual effort for performing the customization.
Semantic Analysis of Sentences: The Estonian Experience
Authors: Õim Haldur  , Orav Heili  , Kahusk Neeme  , Taremaa Piia
Published: February 2025

This paper describes the work done on computational semantics of Estonian simple sentences. Main attention is paid to inferring knowledge from text. Differences from widely used FrameNet is discussed.
An Audio System of Electronic Texts for the Visually Impaired and Perception of Different Speech Rates by the Blind and the Sighted
Authors: Mihkla Meelis  , Hein Indrek  , Kiissel Indrek  , Orusaar Margit  , Räpp Artur
Published: February 2025

This work presents the audio system of electronic texts and audio books, designed for the visually impaired people, helping them read the news, newspapers, magazines and books and listen to audio books over the Internet. Considered are the possibilities of use and the functional range of the system. For selection of various speech rates perception tests were arranged for the blind and those sighted. The perception tests revealed that the so-called trained blind prefer to listen to the speech of a higher rate than the sighted or the blind, lacking the experience of daily use of computer.
Internet Commentators as Dialogue Participants: Coherence Achieved through Membership Categorization
Authors: Hennoste Tiit  , Gerassimenko Olga  , Kasterpalu Riina  , Koit Mare  , Laanesoo Kirsi  , Oja Anni  , Rääbis Andriela  , Strandson Krista
Published: February 2025

We are studying how an inherent dialogue structure is formed by the conglomeration of an Internet opinion article as a source text and its anonymous comments. We are using methods of conversation analysis and membership categorization analysis, originally intended for the analysis of coherent spoken dialogues. A source text and its comments can be considered as dialogue acts and commentators turn out to be dialogue participants. Every commentator can react to the source text or to some of the previous comments. A dialogue is formed by occurring a ‘bunch’ of many micro-dialogues. On the other hand, the commentators are categorizing themselves as well as agents of the source text. As a result, an additional structure layer is formed. The coherence of turns is also structured non-linearly.
Human-Computer Interaction in Estonian: Collection and Analysis of Simulated Dialogues
Authors: Pärkson Siiri
Published: February 2025

This paper discusses an experiment series in the course of which so-called simulated dialogues in Estonian were collected in human-computer interaction. The subjects were asked to test a program, which interacted with a person in written Estonian, which gave information about cinema, TV listings, weather, politics or flights. In reality another person (so-called Wizard of Oz) answered the subject's questions via Internet. I will introduce the Wizard of Oz interface. All the experiments have been recorded in a log file; on the basis of this information the analysis of dialogues takes place. I primarily concentrate on a repair type occurred in dialogues, which based on the conversational analysis is called other-initiated repair. I look for language rules (patterns) which have been followed to produce the utterances. This research is one step closer to the aim to create a computer program, which provides users with the information in the most convenient and pleasant way.
Taking Advantage of Semantics in Recommendation Systems
Authors: Codina Victor  , Ceccaroni Luigi
Published: February 2025

Recommendation systems leverage product and community information to target products to consumers. Researchers have developed collaborative recommendation systems, content-based recommendation systems and a few hybrid systems. We propose a semantic framework to overcome common limitations of current systems. We present a system whose representations of items and user-profiles are based on concept taxonomies in order to provide personalized recommendation and services. The recommender incorporates semantics to enhance (1) user modeling by applying a domain-based inference method, and (2) recommendation by applying a semantic-similarity method. We show that semantics can often be used to overcome information scarcity. Experiments on movie-data from Netflix show that systems incorporating semantics produce significantly better quality recommendations than content-based ones.
Applying I-Fuzzy Partitions to Represent Sets of Fuzzy Partitions
Authors: Torra Vicenç  , Min Ji-Hee
Published: February 2025

I-fuzzy partitions have been defined to represent uncertainty on the clustering process. They are based on interval type-2 fuzzy sets, also known as Atanassov's intuitionistic fuzzy sets.
Encoding Basic Arithmetic Operations for SAT-Solvers
Authors: Béjar Ramón  , Fernández Cèsar  , Guitart Francesc
Published: February 2025

In this paper we start an investigation to check the best we can do with SAT encodings for solving two important hard arithmetic problems, integer factorization and discrete logarithm. Given the current success of using SAT encodings for solving problems with linear arithmetic constraints, studying the suitability of SAT for solving non-linear arithmetic problems was a natural step. However, our results indicate that these two problems are extremely hard for state-of-the-art SAT solvers, so they are good benchmarks for the research community interested in finding good SAT encodings for practical constraints.
Argumentation-based Example Interchange for Multiagent Induction
Authors: Ontañón Santiago  , Plaza Enric
Published: February 2025

Argumentation can be used by a group of agents to discuss about the validity of hypotheses. In this paper we propose an argumentation-based frame-work for multiagent induction, where two agents learn separately from individual training sets, and then engage in an argumentation process in order to converge to a common hypothesis about the data. The result is a multiagent induction strategy in which the agents minimize the set of examples that they have to exchange (using argumentation) in order to converge to a shared hypothesis. The proposed strategy works for any induction algorithm which expresses the hypothesis as a set of rules. We show that the strategy converges to a hypothesis indistinguishable in training set accuracy from that learned by a centralized strategy.
Discovering the visual patterns elicited by human scan-path
Authors: Carbone Andrea
Published: February 2025

In this work we present a biologically motivated framework for the modelling of the visual scene exploration preference. We aim at capturing the statistical patterns that are elicited by the subjective visual selection and reproduce them via a computational system. The low level visual features are encoded through the projection of the image patches on a learned basis of linear filters reproducing the typical response properties of the primary visual cortex (V1) receptive fields of mammals. The resulting training set is typically high-dimensional and sparse. We exploit the sparse structure by clustering together patterns of channel activation which are similar on the basis of a binary activation map and finally deriving a pooling over the set of the original linear filters in terms of active (on) and non-active (off) channels for each cluster. The system has been tested on a dataset of natural images by comparing the fixation density maps recorded from human subjects observing the pictures and the saliency maps computed by our system obtaining promising results.
Dealing with the dynamics of proof-standard in argumentation-based decision aiding
Authors: Ouerdane Wassila  , Maudet Nicolas  , Tsoukias Alexis
Published: February 2025

Usually, in argumentation, the proof-standards that are used are fixed a priori by the procedure. However decision-aiding is a context where these may be modified dynamically during the process, depending on the responses of the client. The expert indeed needs to adapt and refine its choice of an appropriate method of aggregation, so that it fits the preference model inferred from the interaction. In this paper we examine how this aspect can be handled in an argumentation-based decision-aiding framework. The first contribution of the paper is conceptual: the notion of a concept lattice based on simple properties and allowing to navigate among the different proof-standards is put forward. We then show how this can be integrated within the Carneades model while still preserving its essential properties; and illustrates our proposal with a detailed example.
Temporal Dimensions in Rules Modelling
Authors: Palmirani Monica  , Governatori Guido  , Contissa Giuseppe
Published: February 2025

Typically legal reasoning involves multiple temporal dimensions. The contribution of this work is to extend LKIF-rules (LKIF is a proposed mark-up language designed for legal documents and legal knowledge in ESTRELLA Project [3]) with temporal dimensions. We propose an XML-schema to model the various aspects of the temporal dimensions in legal domain, and we discuss the design choices. We illustrate the use of the temporal dimensions in rules with the help of real life examples.
Update Legal Documents Using Hierarchical Ranking Models and Word Clustering
Authors: Pham Minh Quang Nhat  , Nguyen Minh Le  , Shimazu Akira
Published: February 2025

Our research addresses the task of updating legal documents when new information emerges. In this paper, we employ a hierarchical ranking model to the task of updating legal documents. Word clustering features are incorporated to the ranking models to exploit semantic relations between words. Experimental results on legal data built from the United States Code show that the hierarchical ranking model with word clustering outperforms baseline methods using Vector Space Model, and word cluster-based features are effective features for the task.
Case Frames as Contextual Mappings to Case Law in BestPortal
Authors: Hoekstra Rinke  , Lodder Arno  , van Harmelen Frank
Published: February 2025

This paper introduces case frames as a way to provide a more meaningful structure to vocabulary mappings used to bridge the gap between laymen and legal descriptions of court proceedings. Case frames both reduce the ambiguity of queries, and improve the ability of users to formulate good quality queries. We extend the BestMap ontology with a formalisation of case frame based mappings in OWL 2, present a new version of BestPortal, and show how case frames impact retrieval results compared to simple contextual mappings and a direct fulltext search.
Cell differentiation in noisy random Boolean network
Authors: Barbieri A.  , Villani M.  , Serra R.  , Kauffman S.A.  , Colacci A.
Published: February 2025

The dynamics of genetic regulatory networks are often affected by stochastic noise, due to the small number of molecules involved in some reactions. The role of these fluctuations is analyzed in a discrete model of gene regulatory networks, i.e. that of noisy random Boolean networks. By relating the asymptotic states of the noisy system to the different cell types, we show how the main features of the important process of cell differentiation can be described by assuming that the noise level changes as differentiation proceeds. Differentiation is seen as a series of transitions from an asymptotic state in which the system can wander among many states under the action of noise to other asymptotic states in which the system can reach fewer and fewer states. This model easily describes the fact that multi-potent cells can stochastically differentiate along various routes. We show here that the process can also be controlled (as it happens in the embryo growth) so that it is possible to determine the final fully differentiated state of the cell. This is achieved by forcing some genes, which are called here “swithces”, to take constant values, in a way which mimicks the influence of external signals, and by simoultaneously varying the noise level in the cell.
Analysing Security Protocols using CSP
Authors: Lowe Gavin
Published: February 2025

In this chapter we describe an approach to analysing security protocols using the process algebra CSP and the model checker FDR. The basic approach is to build a CSP model of a small system running the protocol, together with the most general intruder who can interact with the protocol. We then use the model checker FDR to explore the state space, looking for insecure states. In the second half of the chapter, we extend this approach so as to be able to analyse an arbitrary system running the protocol.
Low-cost RFID Tags as IPv6 Nodes in the Internet of Things
Authors: Dominikus Sandra  , Gross Hannes  , Aigner Manfred  , Kraxberger Stefan
Published: February 2025

RFID tags can no longer be treated as pure bar-code substitute as their functional capabilities increase rapidly. Many of them are able to store and compute data, or hold sensors. The data flow in the EPCglobal network, which was created for “traditional” low-cost tags, does only work one-way: from tags to a couple of servers where data for the tags is stored and can be accessed by other readers or servers. To draw advantage from the increased functionality of the tags it will become important to have a two-way end-to-end communication between servers and tags, e.g. to remotely change data on the tags.
Putting Public Governance Innovation into Perspective: From Administrative Reform to Innovation Discourse
Authors: Caiden Gerald E.  , Puniha Pushpinder S.
Published: February 2025

The current push for innovation in governance repeats a familiar historical pattern as societies grapple with fast changing circumstances. It begins with administrative reforms to improve the performance of public authorities, moves invariably on to changes in public policy that take into account the benefits to the ruled as well as the rulers in pursuit of good governance, then involves the more difficult task of wider institutional reform, and finally requires institutional innovation to complete the cycle of modernization. This is the continuing struggle to overcome the dysfunctions of bureaucratization and to inject creativity into the ever-increasing complex process of conducting the public's business. The imperative arises from the gap between results obtained and rising expectations. While the process is somewhat consistent, the substance changes radically over time as public leaders try to catch up with advances in other fields of knowledge despite lagging outcomes as people resist change. Hence in governance, reforms and overhauls often disappoint as traditional arrangements persist beyond their time.
Internal Simulation in a Bimodal System
Authors: Johnsson Magnus  , Gil David  , Hesslow Germund  , Balkenius Christian
Published: February 2025

We present a bimodal model able to internally simulate expected sequences of perceptions within a modality likely to follow the last sensory experience. Simultaneously reasonable perceptual expectations are elicited in the other modality. Our model is based on the novel Associative Self-Organizing Map (A-SOM), which develops a representation of the input space as well as learns to associate its activity with the (possibly time delayed) activities of an arbitrary number of other neural networks. The model was trained on sequences of inputs and the trained model was able to simulate appropriate sequences of activity patterns in the absence of sensory input for several epochs in both modalities. The simulation results are very encouraging and confirms the abilities of the A-SOM to serve in a multimodal system capable of internal simulation of perceptions and of cross-modal expectations.
Fast Distributed Process Creation with the XMOS XS1 Architecture
Authors: Hanlon James  , Hollis Simon J.
Published: February 2025

The provision of mechanisms for processor allocation in current distributed parallel programming models is very limited. This makes difficult, or even prohibits, the expression of a large class of programs which require a run-time assessment of their required resources. This includes programs whose structure is irregular, composite or unbounded. Efficient allocation of processors requires a process creation mechanism able to initiate and terminate remote computations quickly. This paper presents the design, demonstration and analysis of an explicit mechanism to do this, implemented on the XMOS XS1 architecture, as a foundation for a more dynamic scheme. It shows that process creation can be made efficient so that it incurs only a fractional overhead of the total runtime and that it can be combined naturally with recursion to enable rapid distribution of computations over a system.
SystemVerilogCSP: Modeling Digital Asynchronous Circuits Using SystemVerilog Interfaces
Authors: Saifhashemi Arash  , Beerel Peter A.
Published: February 2025

This paper describes how to model channel-based digital asynchronous circuits using SystemVerilog interfaces that implement CSP-like communication events. The interfaces enable explicit handshaking of channel wires as well as abstract CSP events. This enables abstract connections between modules that are described at different levels of abstraction facilitating both verification and design. We explain how to model one-to-one, one-to-many, one-to-any, any-to-one and synchronised channels. Moreover, we describe how to split communication actions into multiple parts to model more accurately less concurrent handshaking protocols that are commonly found in many asynchronous pipelines.
On Some Best Practices in Large-Scale Ontology Development: The Chronious Ontology Suite as a Case Study
Authors: Schneider Luc  , Brochhausen Mathias  , Koepsell David
Published: February 2025

Domain ontologies that are created without reference to, or not based upon an upper ontology will undermine future ontology development both within and among domains. Applied ontologies based on sound design principles and theoretical foundations provide advantages compared to ontologies neglecting ontological analysis. In this paper we demonstrate the economic pay-offs of applying these principles to the development of ontology-driven systems. We focus on three topics: reuse of pre-existing resources, modularization of ontologies into separable and reusable components, and harmonization of ontologies and knowledge management systems and ex ante harmonization. We show, using cases from the medical and pharmaceutical domains, how rigorous and methodical use of an upper ontology built upon realist principles better enables parametric adaptation to future objects, cross-ontology interoperability, and accommodates objects of both scientific and social importance. More importantly, the application of those principles leads to a streamed-lined development process of ontologies and ontology-driven systems.
9. Measurement and Imaging of Free and Total Zinc in Biological Specimens
Authors: Thompson Richard B.  , Fierke Carol A.  , Frederickson Christopher J.  , McCall Keith A.  , McCranor Bryan J.  , Penner-Hahn James E.
Published: February 2025

Numerous methods have proven useful in the study of zinc in biological systems. This chapter briefly reviews several methods for determining and imaging zinc, particularly in aqueous solutions, cells, and tissues. The sections are written for bioscientists who are potentially interested in a method but may have little experience with it. The methods include fluorescent stains for zinc, fluorescence-based biosensors, X-ray fluorescence, determination of zinc binding affinity, and fiber optic biosensors. For each method the principle and background are described, followed by a brief summary of the procedure and typical results, and concluding with the advantages and disadvantages of each method.
10. Immunobiology and Hematology of Zinc
Authors: Rosenkranz Eva  , Prasad Ananda  , Rink Lothar
Published: February 2025

The essentiality of the trace element zinc is anchored in its role as a cofactor in a number of enzymes and in its function as a signaling molecule. Among other cell systems, the immune system requires zinc for adequate functionality. Not only zinc deprivation but also exceedingly high zinc levels result in immune dysfunction, depicting the significance of a regulated zinc homeostasis for the immune response. Disturbances of zinc homeostasis affect multiple aspects of the immune system, including hematopoiesis, innate immunity, adaptive immune response and processes involved in immune regulation. Zinc deficiency impairs the development of lymphocyte progenitors and modifies the differentiation of cells of the innate immune system. Furthermore, immune cell function is adversely affected during zinc deprivation, resulting in compromised lymphocyte immune reaction combined with dysregulated innate immune responses. Consequently, the development and progression of various infections and diseases is influenced by alterations in the zinc homeostasis. For several decades, the immunobiology of zinc has been studied. This chapter aims to discuss the overall impact of zinc on the immune system.
16. Zinc and Ageing
Authors: Mocchegiani Eugenio  , Malavolta Marco
Published: February 2025

Ageing is an inevitable biological process with gradual and spontaneous biochemical and physiological changes and increased susceptibility to diseases. Nutritional zinc may remodel these change with subsequent healthy ageing, because zinc improves the inflammatory/immune response as shown by “in vitro” and “in vivo” studies. However, in ageing, the zinc daily dietary intake is reduced than that one recommended by the RDA. Many causes can be involved: among them, inadequate mastication, psychosocial factors, drugs interactions, altered cellular processes [zinc transporters and Metallothioneins (MT)]. These processes are very relevant because the intracellular zinc homeostasis is regulated by buffering MT and zinc transporters assigning to zinc a role of “second messenger”. Physiological zinc supplementation in elderly improves these functions with however contradictory data. Therefore, the choice of old subjects for zinc supplementation has to be better considered in relation to the specific genetic background of MT and IL-6, because the latter is involved both in MTmRNA and in intracellular zinc homeostasis. The genetic variations of IL-6 -174G/C locus when associated with those ones of MT1A +647A/C locus are useful tools for the choice of old people for zinc supplementation because improving the inflammatory/immune response, suggesting the relevance of zinc-MT gene interaction for healthy ageing and longevity.
17. Zinc and Atherosclerosis: Clinical Observations and Potential Mechanisms
Authors: Foster Meika  , Samman Samir
Published: February 2025

Zinc is an essential nutrient that is required for a broad range of biological functions. The potential exists for zinc to impact on chronic disease. The aims of this chapter are twofold: firstly to evaluate the epidemiological and clinical data that report on zinc status and atherosclerosis in humans, and secondly to determine the potential mechanisms of the interaction of zinc with atherosclerosis risk factors. There are conflicting reports of the relationship between atherosclerosis and zinc status, as assessed by dietary intake of zinc and/or the measurement of zinc concentrations in healthy and diseased tissues. The balance of epidemiological studies points to an association between zinc deficiency and atherosclerosis however the studies are hampered by the lack of a decisive biomarker of zinc status. Clinical trials are mainly of zinc supplementation, and these show a decrease in plasma high-density lipoprotein cholesterol concentrations leading to an increased risk of heart disease. Impaired zinc homeostasis has been associated with increased levels of oxidative stress and the induction of widespread genomic and proteomic changes that relate to cardiovascular disease. Potential mechanisms of the influence of zinc on atherogenesis studied in rodent models and in cell culture include its interaction with a wide range of cellular redox and inflammatory processes, such as NF-kB, NO, PPAR, and PKC signalling pathways. In conclusion, zinc is likely to be involved in atherogenesis through its interactions with lipoprotein metabolism, inflammation and oxidative stress. Further progress will be made when improved methods of measuring zinc status are developed.
20. Zinc and Mental Health
Authors: Szewczyk Bernadeta  , Pilc Andrzej  , Nowak Gabriel
Published: February 2025

Depression is a chronic recurring illness that is associated with significant disability, morbidity and mortality. Depression is twice as prevalent in women as men and the risk factor for prenatal depression and postpartum depression is similar to the risk factor for depression in general. Attention deficit hyperactivity disorder (ADHD) is a developmental disease, characterized by overactivity, impulsivity and inattentiveness. ADHD affects about 5-9% of children aged between 5 and 14 years and 2-3 times as many boys as girls. The presence of ADHD in childhood is a major risk of the development of neurobehavioral disorder in adults. Despite the intensive research of both diseases, the exact mechanisms involved in the pathophysiology and treatment of depression or ADHD is still unknown.
Probabilistic Appearance-based Mapping and Localization using the Feature Stability Histogram
Authors: Bacca Bladimir  , Salví Joaquím  , Cufí Xavier
Published: February 2025

Appearance-based methods for mapping and localization have gained increasing attention in recent years. The strength of these models lies in their ability to represent the environment through high-level image features. However, the environment illumination, occlusions and walking people have a negative impact on these approaches. This paper presents a probabilistic appearance-based mapping and localization approach which uses the Feature Stability Histogram to update the environment appearance continuously and extract the more stable features in the environment. Our proposed method uses these stable features as successive appearance measurements to update the posterior probabilities incrementally on a topological map using a Rao-Blackwellized particle filter. Our algorithm considers omnidirectional images and laser data as measure of the environment appearance. Our approach was evaluated on a robot in a dataset collected along various seasons and time of day.
Towards a Biologically Inspired Question-Answering Neural Architecture
Authors: Monner Derek  , Reggia James A.
Published: February 2025

Though question-answering systems like IBM's Watson are undoubtedly impressive, their errors are often baffling and inscrutable to onlookers, suggesting that the strategies they use are far different than those that humans employ. Desiring a more biologically inspired approach, we investigate the extent to which a neural network can develop a functional grasp of language by observing question/answer pairs. We present a neural network model that takes questions, as speech-sound sequences, about a visual environment, and learns to answer them with grounded predicate-based meanings. The model must learn to 1) segment morphemes, words, and phrases from the speech stream, 2) map the intended referents from the speech signal onto objects in the environment, 3) comprehend simple questions, recognizing what information the question is asking for, and 4) find and supply that information. Model evaluations suggest that the grounding and question-answering parts of the problem are significantly more demanding than interpreting the speech input.
Access to Symbolization and Associativity Mechanisms in a Model of Conscious and Unconscious Processes
Authors: Wedemann Roseli S.  , de Carvalho Luís Alfredo V.  , Donangelo Raul
Published: February 2025

We have previously described aspects of neurotic mental pathology, in terms of its relation to memory function and proposed a neural network model, whereby neurotic behavior is described as an associative memory process. Modules corresponding to sensory and symbolic memories interact, representing unconscious and conscious mental processes. Our main contribution with respect to current work regarding machine models of consciousness is to propose a neuronal associative memory mechanism that describes conscious and unconscious memory activity, based on Freud's description of neurosis, which illustrates how access to symbolization mechanisms is essential for consciousness. We modeled memory access dynamics by the Boltzmann machine (BM) and Generalized Simulated Annealing (GSA) and investigated the effects of using both on network associativity.
Supervised State Mapping of Clustered GraphESN States
Authors: Gallicchio Claudio  , Micheli Alessio
Published: February 2025

Graph Echo State Network (GraphESN) is an efficient neural network model that extends the applicability of Reservoir Computing to the processing of graphs. The untrained reservoir encodes input graphs into isomorphic structured states. In this paper we propose a novel and supervised approach for adaptively weight the relevance of the states of the vertices in the input graphs for the output computation in classification tasks. To this aim, local average computations on partitions of the state space, obtained using the Neural Gas algorithm, are combined according to the target information. The effectiveness of the proposed approach is shown on real-world tasks from Cheminformatics.
A VLSI neuromorphic device for implementing spike-based neural networks
Authors: Indiveri Giacomo  , Chicca Elisabetta
Published: February 2025

We present a neuromorphic VLSI device which comprises hybrid analog/digital circuits for implementing networks of spiking neurons. Each neuron integrates input currents from a row of multiple analog synaptic circuit. The synapses integrate incoming spikes, and produce output currents which have temporal dynamics analogous to those of biological post synaptic currents. The VLSI device can be used to implement real-time models of cortical networks, as well as real-time learning and classification tasks. We describe the chip architecture and the analog circuits used to implement the neurons and synapses. We describe the functionality of these circuits and present experimental results demonstrating the network level functionality.
EUR-Lex: Towards a Common Legal Portal
Authors: Breedstraet Els
Published: February 2025

An overview of current scenario going on at EU level in the EUR-Lex portal anticipating future trends and directions of this relevant official information source is given by this contribution. The current status of the EU portal is briefly outlined. All changes and adjustments implemented in the new EUR-Lex system are analyzed focusing the attention on the user-friendliness, accessing options, searching functionalities, personalization, interaction of other websites and users. The new EUR-Lex will go live in 2012; its transformation into a unique juridical portal containing all steps of the legislative procedure and the jurisprudence and providing access to national legislation will consistently enhance the role of EUR-Lex as a fundamental tool for stakeholders for deeply getting in touch with everyday EU institutions activities and results.
High Automated Integration of Ontologies on the Basis of Extendable Thesaurus
Authors: Shishaev Maxim  , Lomov Pavel
Published: February 2025

The technique of automatic ontology integration on the level of alignment has been developed. The technique is oriented for information search in heterogeneous resources. The thesaurus, which is result of integration, is used for translation search queries in term of particular ontologies. The technology is based on use of the weighed relation of association which is modified during use of the integrated ontology. It allows to avoid attraction of experts in the course of integration of ontologies and, thereby, to raise level of automation of the given process.
A Small Experiment on Mining Memeplexes
Authors: Laansalu-Veskioja Karin  , Veskioja Tarmo
Published: February 2025

A set of memes were extracted from a knowledge-exchange chain experiment to investigate the communication and exchange of information in physics classes. Meme change patterns were analysed using two approaches. First, meme similarity matrix was created using a similarity measure, a Võhandu maximum correlation path/tree (similar to a minimum spanning tree approach on an inverted scale) was computed, the tree was partitioned using Võhandu partitioning rules. Second, a monotone systems minus technique algorithm was used to reorder memes and to partition the ordering. The two approaches gave roughly similar partitioning of memes into possible memeplexes.
Extending UML Profiles to Model Integrity Constraints in SQL Databases
Authors: Eessaar Erki  , Aaberg Erko
Published: February 2025

UML is a general-purpose visual modeling language that can be adapted by creating profiles based on its built-in extension mechanism. There exist UML profiles for modeling the logical design of SQL databases. The profiles allow developers to create model elements that correspond to SQL language elements. In case of many integrity constraints, developers have to manually specify the implementation of the constraint in a model. It complicates the creation of the models and the use of the models to generate final code that does not need elaboration. In this paper, we propose to extend UML SQL database design profiles with stereotypes that correspond to domain-independent database design patterns about integrity constraints to raise the abstraction level of models and facilitate generation of code that implements integrity constraints. We also present the results of an experiment about extending a UML SQL database design profile.
Myofibroblasts: Origins and Regulation of Phenotype by Mechanical Signaling
Authors: Darby Ian A.  , Hinz Boris  , Desmoulière Alexis
Published: February 2025

Myofibroblasts are responsible for contraction of granulation tissue in skin wounds. They are also present in many pathological situations, derived either from local cells in the tissue or from circulating precursor or stem cells. Because of their important role in pathological scarring and fibrosis, as well as a role in for cancer-associated myofibroblasts in tumor growth, much interest centres on the factors that regulate their differentiation and survival. Myofibroblast phenotype is regulated by the microenvironment of damaged tissue, including growth factors, the extracellular matrix, mechanical stress and mechanical signaling to which they are subjected.
Embryonic Stem Cells, a Promise of Therapeutic Applications
Authors: Lemaitre Gilles  , Baldeschi Christine
Published: February 2025

Stem cells are valuable tools for the study of developmental biology, drug discovery and modeling and understanding disease, and they also show great potential for the development of stem-cell-based therapies. Stem cells and their derivatives do indeed form the basis of therapies for treating a select number of diseases, including hematopoietic stem cell transplants for bone marrow diseases and the use of epithelial stem-cell-based treatments for corneal disorders and burns. Recent studies reveal that regenerative medicine is in transit to clinical trials include the use of human embryonic stem cell (hESC) derivatives to treat macular degeneration, stroke and amyotrophic lateral sclerosis. The hESC have two essential characteristics: the unlimited proliferation capacity and pluripotency, which was the ability to differentiate into any cell type of the human body. By their self-renewal capacity and the ability to differentiate for example into neurons or keratinocytes, it can be imagine to prepare a bank of allogenic cells derived from hESCs to treat patients. The current challenge is the transition from bench to bedside.
Adipose Stromal/Stem Cell and Cardiovascular Repair
Authors: Planat-Benard Valérie  , Casteilla Louis
Published: February 2025

Post-infarction heart failure is closely associated with a major loss of differentiated cardiomyocytes consecutive to ischemia, which cannot be overcome by the poor renewal of cardiac cells in the heart. This has led many investigators to develop various strategies for cell-based therapy to improve defective contractile performance and heart function. Although indirect beneficial effects can be expected from various mechanisms, such as improvement of tissue perfusion, tissue contractility recovery or paracrine secretions, a definitive treatment requires neocardiogenesis in order to repopulate the ischemic area. The concept of cell plasticity opened new perspectives in this field, suggesting a possible use of different adult cells with the aim to achieving cell transdifferentiation towards cardiomyocytes when placed in an appropriate in vivo context. Among the sources of adult stem or progenitor cells for cardiomyocyte regeneration, cells derived from adipose tissue are now being investigated, including at the clinical level. According to several reports, the transplantation of these cells is associated with a functional benefit, which however cannot only be explained by transdifferentiation regardless of the underlined mechanisms. The purpose of this chapter is to discuss, in a critical view, the direct and indirect effects of stromal cells derived from adipose tissue on heart regeneration.
Chondrogenic Differentiation of Human Bone Marrow-Derived Mesenchymal Stem Cells
Authors: Cucchiarini Magali  , Madry Henning
Published: February 2025

Bone marrow-derived mesenchymal stem cells, a subpopulation of the marrow compartment, have remarkable properties that make them an attractive source of cells for regenerative medicine. MSCs are capable of self-renewal, stemness maintenance, and differentiation in cells forming various mesodermal tissues under specific conditions of induction (cartilage, bone, fat, muscle, meniscus, tendons, ligaments, stromal connective tissue). They exhibit homing properties that allow them to migrate toward sites of damage where they exert their reparative effects via the synthesis of different bioactive factors. MSCs have also been reported for their immunosuppressive activities and absence of tumorigenicity. For these reasons, MSCs represent a promising source of transplantable cells to reinforce the natural healing response in patients with disorders of the musculoskeletal system, especially of the articular cartilage that has an intrinsic limited capacity for regeneration.