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We introduce a Retrieval-Augmented Generation (RAG) system for translating user questions into accurate federated SPARQL queries over bioinformatics knowledge graphs (KGs) leveraging Large Language Models (LLMs). To enhance accuracy and reduce hallucinations in query generation, our system utilises metadata from the KGs, including query examples and schema information, and incorporates a validation step to correct generated queries. The system is available online at chat.expasy.org.

Background. In the last decades, several life science resources have structured data using the same framework and made these accessible using the same query language to facilitate interoperability. Knowledge graphs have seen increased adoption in bioinformatics due to their advantages for representing data in a generic graph format. For example, yummydata.org catalogs more than 60 knowledge graphs accessible through SPARQL, a technical query language. Although SPARQL allows powerful, expressive queries, even across physically distributed knowledge graphs, formulating such queries is a challenge for most users. Therefore, to guide users in retrieving the relevant data, many of these resources provide representative examples. These examples can also be an important source of information for machine learning, if a sufficiently large number of examples are provided and published in a common, machine-readable and standardized format across different resources. Findings. We introduce a large collection of human-written natural language questions and their corresponding SPARQL queries over federated bioinformatics knowledge graphs (KGs) collected for several years across different research groups at the SIB Swiss Institute of Bioinformatics. The collection comprises more than 1000 example questions and queries, including 65 federated queries. We propose a methodology to uniformly represent the examples with minimal metadata, based on existing standards. Furthermore, we introduce an extensive set of open-source applications, including query graph visualizations and smart query editors, easily reusable by KG maintainers who adopt the proposed methodology. Conclusions. We encourage the community to adopt and extend the proposed methodology, towards richer KG metadata and improved Semantic Web services.

Integrated access and backhaul (IAB) technology is a flexible solution for network densification. IAB nodes can also be deployed in moving nodes such as buses and trains, i.e., mobile IAB (mIAB). As mIAB nodes can move around the coverage area, the connection between mIAB nodes and their parent macro base stations (BSs), IAB donor, is sometimes required to change in order to keep an acceptable backhaul link, the so called topology adaptation (TA). The change from one IAB donor to another may strongly impact the system load distribution, possibly causing unsatisfactory backhaul service due to the lack of radio resources. Based on this, TA should consider both backhaul link quality and traffic load. In this work, we propose a load balancing algorithm based on TA for IAB networks, and compare it with an approach in which TA is triggered based on reference signal received power (RSRP) only. The results show that our proposed algorithm improves the passengers worst connections throughput in uplink (UL) and, more modestly, also in downlink (DL), without impairing the pedestrian quality of service (QoS) significantly., Comment: Paper submitted to Journal of Communication and Information Systems (JCIS)

As the number of user equipments increases in fifth generation (5G) and beyond, it is desired to densify the cellular network with auxiliary nodes assisting the base stations. Examples of these nodes are integrated access and backhaul (IAB) nodes, network-controlled repeaters (NCRs) and reconfigurable intelligent surfaces (RISs). In this context, this work presents a system level overview of these three nodes. Moreover, this work evaluates through simulations the impact of network planning aiming at enhancing the performance of a network used to cover an outdoor sport event. We show that, in the considered scenario, in general, IAB nodes provide an improved signal to interference-plus-noise ratio and throughput, compared to NCRs and RISs. However, there are situations where NCR outperforms IAB due to higher level of interference caused by the latter. Finally, we show that the deployment of these nodes in unmanned aerial vehicles (UAVs) also achieves performance gains due to their aerial mobility. However, UAV constraints related to aerial deployment may prevent these nodes from reaching results as good as the ones achieved by their stationary deployment., Comment: Paper submitted to IEEE Systems Journal

To address the need of coverage enhancement in the fifth generation (5G) of wireless cellular telecommunications, while taking into account possible bottlenecks related to deploying fiber based backhaul (e.g., required cost and time), the 3rd generation partnership project (3GPP) proposed in Release 18 the concept of network-controlled repeaters (NCRs). NCRs enhance previous radio frequency (RF) repeaters by exploring beamforming transmissions controlled by the network through side control information. In this context, this paper introduces the concept of NCR. Furthermore, we present a system level model that allows the performance evaluation of an NCR-assisted network. Finally, we evaluate the network deployment impact on the performance of NCR-assisted networks. As we show, with proper network planning, NCRs can boost the signal to interference-plus-noise ratio (SINR) of the user equipments (UEs) in a poor coverage of a macro base station. Furthermore, celledge UEs and uplink (UL) communications are the ones that benefit the most from the presence of NCRs., Comment: Paper accepted for publication in the conference proceedings of "19th International Symposium on Wireless Communication Systems" (ISWCS)

In fifth generation (5G) wireless cellular networks, millimeter wave spectrum opens room for several potential improvements in throughput, reliability, latency, among other aspects. However, it also brings challenges, such as a higher influence of blockage which may significantly limit the coverage. In this context, network-controlled repeaters (NCRs) are network nodes with low complexity that represent a technique to overcome coverage problems. In this paper, we introduce the NCR concept and study its performance gains and deployment options. Particularly, presenting the main specifications of NCR as agreed in 3rd generation partnership project (3GPP) Rel-18, we analyze different NCR deployments in an urban scenario and compare its performance with alternative deployments. As demonstrated, with a proper network planning and beamforming design, NCR is an attractive solution to cover blind spots the base stations (BSs) may have., Comment: Submmited to IEEE Communications Standards Magazine

Millimeter wave (mmWave) and sub-THz communications, foreseen for sixth generation (6G), suffer from high propagation losses which affect the network coverage. To address this point, smart entities such as network-controlled repeaters (NCRs) have been considered as cost-efficient solutions for coverage extension. NCRs, which have been standardized in 3rd generation partnership project Release 18, are radio frequency repeaters with beamforming capability controlled by the network through side control information. Another challenge raised by the adoption of high frequency bands is the use of large bandwidths. Here, a common configuration is to divide a large frequency band into multiple smaller subbands. In this context, we consider a scenario with NCRs where signaling related to measurements used for radio resource management is transmitted in one subband centered at frequency $f_c$ and data transmission is performed at a different frequency $f_c + \Delta f$ based on the measurements taken at $f_c$. Here, a challenge is that the array radiation pattern can be frequency dependent and, therefore, lead to beam misalignment, called beam squinting. We characterize beam squinting in the context of subband operation and propose a solution where the beam patterns to be employed at a given subband can be adjusted/compensated to mitigate beam squinting. Our results show that, without compensation, the perceived signal to interference-plus-noise ratio (SINR) and so the throughput can be substantially decreased due to beam squinting. However, with our proposed compensation method, the system is able to support NCR subband signaling operation with similar performance as if signaling and data were transmitted at the same frequency., Comment: Submitted to IEEE Transactions on Vehicular Technology

The recent success of Large Language Models (LLM) in a wide range of Natural Language Processing applications opens the path towards novel Question Answering Systems over Knowledge Graphs leveraging LLMs. However, one of the main obstacles preventing their implementation is the scarcity of training data for the task of translating questions into corresponding SPARQL queries, particularly in the case of domain-specific KGs. To overcome this challenge, in this study, we evaluate several strategies for fine-tuning the OpenLlama LLM for question answering over life science knowledge graphs. In particular, we propose an end-to-end data augmentation approach for extending a set of existing queries over a given knowledge graph towards a larger dataset of semantically enriched question-to-SPARQL query pairs, enabling fine-tuning even for datasets where these pairs are scarce. In this context, we also investigate the role of semantic "clues" in the queries, such as meaningful variable names and inline comments. Finally, we evaluate our approach over the real-world Bgee gene expression knowledge graph and we show that semantic clues can improve model performance by up to 33% compared to a baseline with random variable names and no comments included., Comment: To appear in Proceedings of SWAT4HCLS 2024: Semantic Web Tools and Applications for Healthcare and Life Sciences

We define a random walk of a particle in $\mathbb{R}^3$ where the space is rotating. The particle is not glued to the space and will collide with it at random times, resulting in changes in its velocity and direction. After many collisions, the random walk starts to have some asymptotic behaviors inherited from the movement of space. The paper will find the limit movement of the particle, and explain how the randomness of the random walk gives rise to the particle asymptotic deterministic movement., Comment: 16 pages, 3 figures

With their exceptional natural language processing capabilities, tools based on Large Language Models (LLMs) like ChatGPT and Co-Pilot have swiftly become indispensable resources in the software developer's toolkit. While recent studies suggest the potential productivity gains these tools can unlock, users still encounter drawbacks, such as generic or incorrect answers. Additionally, the pursuit of improved responses often leads to extensive prompt engineering efforts, diverting valuable time from writing code that delivers actual value. To address these challenges, a new breed of tools, built atop LLMs, is emerging. These tools aim to mitigate drawbacks by employing techniques like fine-tuning or enriching user prompts with contextualized information. In this paper, we delve into the lessons learned by a software development team venturing into the creation of such a contextualized LLM-based application, using retrieval-based techniques, called CodeBuddy. Over a four-month period, the team, despite lacking prior professional experience in LLM-based applications, built the product from scratch. Following the initial product release, we engaged with the development team responsible for the code generative components. Through interviews and analysis of the application's issue tracker, we uncover various intriguing challenges that teams working on LLM-based applications might encounter. For instance, we found three main group of lessons: LLM-based lessons, User-based lessons, and Technical lessons. By understanding these lessons, software development teams could become better prepared to build LLM-based applications.

This work presents a novel methodology for analysis and control of nonlinear fluid systems using neural networks. The approach is demonstrated on four different study cases being the Lorenz system, a modified version of the Kuramoto-Sivashinsky equation, a streamwise-periodic 2D channel flow, and a confined cylinder flow. Neural networks are trained as models to capture the complex system dynamics and estimate equilibrium points through a Newton method, enabled by backpropagation. These neural network surrogate models (NNSMs) are leveraged to train a second neural network, which is designed to act as a stabilizing closed-loop controller. The training process employs a recurrent approach, whereby the NNSM and the neural network controller (NNC) are chained in closed loop along a finite time horizon. By cycling through phases of combined random open-loop actuation and closed-loop control, an iterative training process is introduced to overcome the lack of data near equilibrium points. This approach improves the accuracy of the models in the most critical region for achieving stabilization. Through the use of L1 regularization within loss functions, the NNSMs can also guide optimal sensor placement, reducing the number of sensors from an initial candidate set. The datasets produced during the iterative training process are also leveraged for conducting a linear stability analysis through a modified dynamic mode decomposition approach. The results demonstrate the effectiveness of computationally inexpensive neural networks in modeling, controlling, and enabling stability analysis of nonlinear systems, providing insights into the system behaviour and offering potential for stabilization of complex fluid systems., Comment: 30 pages, 22 figures, under consideration for publication

In this work we analyze mathematically the consequences and effectiveness of strategies to control an epidemic in the framework of classical SEIR models with multiple parallel infectious stages. We define the mathematical concept of a control strategy, showing that it implies turning classic epidemiological models into systems of non-autonomous differential equations. The analysis of these non-autonomous systems is based on the two main results obtained in this work: the first establishes a condition that implies a dynamic without epidemic outbreaks; the second establishes a maximum value for the susceptible population associated to the fixed points that are attractors, moreover, we proof that any trajectory converges to some of these attractors. An important consequence of this last result is the existence of an insurmountable limit on the number of infected individuals after the end of a given control strategy. This restriction can only be mitigated by changing the maximum value of susceptible population associated to the system attractors, which could only be done with permanent control action, that is, without returning to normality. Another interesting result of our work is to show how the moment to start and the way how the control strategy ends strongly impacts the asymptotic value for the total number of infected individuals. We illustrate our analysis and results in a SEIR model (with two or three parallel stages) applied to describe the COVID-19 epidemic., Comment: 39 Pages, 10 Figures, 3 Tables, Preprint Article

In this study, we analyze the relationship between human population growth and economic dynamics. To do so, we present a modified version of the Verhulst model and the Solow model, which together simulate population dynamics and the role of economic variables in capital accumulation. The model incorporates support and foraging functions, which participate in the dynamic relationship between population growth and the creation and destruction of carrying capacity. The validity of the model is demonstrated using empirical data., Comment: 28 pages, 9 figures, Preprint Article

This work investigates interference mitigation techniques in multi-user multiple input multiple output (MU-MIMO) Intelligent Reflecting Surface (IRS)-aided networks, focusing on the base station end. Two methods of precoder design based on block diagonalization are proposed. The first method does not consider the interference caused by the IRS, seeking to mitigate only the multi-user interference. The second method mitigates both the IRS-caused interference and the multi-user interference. A comparison between both methods within an no-IRS MU-MIMO network with strong direct links is provided. The results show that, although in some circumstances IRS interference can be neglected, treating it can improve system capacity and provide higher spectral efficiency, Comment: 5 pages, 4 figures, submitted to XLI BRAZILIAN SYMPOSIUM ON TELECOMMUNICATIONS AND SIGNAL PROCESSING - SBrT 2023

Heterogeneous networks have been studied as one of the enablers of network densification. These studies have been intensified to overcome some drawbacks related to propagation in millimeter waves (mmWaves), such as severe path and penetration losses. One of the promising heterogeneous nodes is network-controlled repeater (NCR). It was proposed by the 3rd generation partnership project (3GPP) in Release 18 as a candidate solution to enhance network coverage. In this context, this work performs a system level evaluation to analyze the performance improvement that an NCR can cause in its serving cell as well as its interference impact on neighbor cells. Particularly, the results show a considerable improvement on the performance of user equipments (UEs) served by the NCR, while neighbor UEs that receive the NCR signal as interference are negatively impacted, but not enough to suffer from outage., Comment: Submitted to XLI Brazilian Symposium on Telecommunications and Signal Processing (SBrT)

In this paper, we present work in progress on the role of artificial intelligence (AI) chatbots, such as ChatGPT, in facilitating data access to federated knowledge graphs. In particular, we provide examples from the field of bioinformatics, to illustrate the potential use of Conversational AI to describe datasets, as well as generate and explain (federated) queries across datasets for the benefit of domain experts.

Third order equations, which describe spherical surfaces (ss) or pseudospherical surfaces (pss), of the form \[ \nu\,z_{t}-\lambda\,z_{xxt}=A(z,z_{x},z_{xx})\,z_{xxx}+B(z,z_{x},z_{xx}) \] with $\nu$, $\lambda$ $\in$ $\mathbb{R}$, $\nu^2+\lambda^2\neq 0$, are considered. These equations are equivalent to the structure equations of a metric with Gaussian curvature $K=1$ or $K=-1$, respectively. Alternatively they can be seen as the compatibility condition of an associated $\mathfrak{su}(2)$-valued or $\mathfrak{sl}(2,\mathbb{R})$-valued linear problem, also referred to as a zero curvature representation. Under certain assumptions we obtain an explicit classification for equations of the considered form that describe ss or pss, in terms of some arbitrary differentiable functions. Several examples of such equations, which describe also a number of already known equations, are provided by suitably choosing the arbitrary functions.

Background, enhancing interoperability of bioinformatics knowledge bases is a high priority requirement to maximize data reusability, and thus increase their utility such as the return on investment for biomedical research. A knowledge base may provide useful information for life scientists and other knowledge bases, but it only acquires exchange value once the knowledge base is (re)used, and without interoperability the utility lies dormant. Results, in this article, we discuss several approaches to boost interoperability depending on the interoperable parts. The findings are driven by several real-world scenario examples that were mostly implemented by Bgee, a well-established gene expression database. To better justify the findings are transferable, for each Bgee interoperability experience, we also highlight similar implementations by major bioinformatics knowledge bases. Moreover, we discuss ten general main lessons learnt. These lessons can be applied in the context of any bioinformatics knowledge base to foster data reusability. Conclusions, this work provides pragmatic methods and transferable skills to promote reusability of bioinformatics knowledge bases by focusing on interoperability.

Hydropower is a renewable, controllable, and flexible source of electricity. These are instrumental features to support decarbonization efforts, as an enabler of non-controllable and variable sources of renewable electricity. Sometimes hydropower is accompanied by other services provided by multipurpose reservoirs, such as water supply, irrigation, navigation, flood control and recreation. Despite all these benefits, hydropower can be a polarizing issue. A large sample of projects with poor planning and execution provides numerous arguments for its opponents. Large and complex projects frequently suffer overcost and delays. The direct impacts are related to the disruption of river ecosystems and surrounding habitats due to the flooding of large areas, and the fragmentation of rivers caused by the construction of dams and the reduction of sediment transport that impoverishes aquatic life. People displacement and compensation are always a complex issue. Hydropower projects can also cause indirect impacts, such as additional deforestation related to the construction of workers' villages, access roads and transmission lines. Finally, reservoirs may also become a significant source of methane emission, especially in tropical areas. This paper offers an analytical approach for sustainable hydropower planning at the river basin scale called HERA: Hydropower and Environmental Resource Assessment. Built on three main components, namely geoprocessing, engineering, and optimization, HERA screens and compares hydropower development alternatives to guarantee social and environmental objectives while maximizing mentioned economic benefits. It was designed to encourage a transparent and participatory hydropower planning process from the early stages. Experience has shown this approach increases the chances of better and balanced outcomes. A case study is presented in the Ogooue river basin in Gabon.

Deploying access and backhaul as wireless links, a.k.a. integrated access and backhaul (IAB), is envisioned as a viable approach to enable flexible and dense networks. Even further, mobile IAB (mIAB) is a candidate solution to enhance the connectivity of user equipments (UEs) moving together. In this context, different of other works from the literature, the present work overviews the basis for the deployment of mIAB by presenting: 1) the current status of IAB standardization in the fifth generation (5G) new radio (NR); 2) a new taxonomy for state-of-the-art works regarding fixed IAB and mIAB; 3) an extensive performance analysis of mIAB based on simulation results; and 4) open challenges and potential future prospects of mIAB. Specifically, the proposed taxonomy classifies IAB works according to different perspectives and categorizes mIAB works according to the type of mobility. For each type of mobility, the main studied topics are presented. Regarding the performance evaluation, we consider an urban macro scenario where mIAB nodes are deployed in buses in order to improve the passengers connection. The results show that, compared to other network architectures, the deployment of mIAB nodes remarkably improves the passengers throughput and latency in both downlink and uplink., Comment: Submitted to "IEEE Access"

Today's international corporations such as BASF, a leading company in the crop protection industry, produce and consume more and more data that are often fragmented and accessible through Web APIs. In addition, part of the proprietary and public data of BASF's interest are stored in triple stores and accessible with the SPARQL query language. Homogenizing the data access modes and the underlying semantics of the data without modifying or replicating the original data sources become important requirements to achieve data integration and interoperability. In this work, we propose a federated data integration architecture within an industrial setup, that relies on an ontology-based data access method. Our performance evaluation in terms of query response time showed that most queries can be answered in under 1 second.