Experimental manipulation of temperature reduce ectoparasites in nests of blue tits (Cyanistes caeruleus)

Several models predict changes in the distributions and incidences of diseases associated with climate change. However, studies that investigate how microclimatic changes may affect host?parasite relationships are scarce. Here, we experimentally increased the temperature in blue tit Cyanistes caeruleus nest boxes during their breeding season to determine its effects on the parasitic abundance (i.e. of nestdwelling ectoparasites, blood-sucking flying insects and hemoparasites) in nests and the host condition of nestlings and adults. The temperature was increased using heat mats placed underneath the nest material, which resulted in an average temperature increase of 3ºC and a reduction in relative humidity of about six units. The abundance of mites Dermanyssus gallinoides and blowfly pupae Protocalliphora azurea was significantly reduced in heated nest boxes. Although not statistically significant, a lower prevalence of flea larvae Ceratophyllus gallinae was also found in heated nests. However, heat treatment did not affect hemoparasite infection of adult blue tits or the body condition of adult and nestling blue tits. In conclusion, heat treatment in blue tit nests reduced nest-dwelling ectoparasites yet without any apparent benefit for the host.Ministerio de Economía, Comercio y Empres

Explainable automatic industrial carbon footprint estimation from bank transaction classification using natural language processing

Concerns about the effect of greenhouse gases have motivated the development of certification protocols to quantify the industrial carbon footprint (cf). These protocols are manual, work-intensive, and expensive. All of the above have led to a shift towards automatic data-driven approaches to estimate the cf, including Machine Learning (ml) solutions. Unfortunately, as in other sectors of interest, the decision-making processes involved in these solutions lack transparency from the end user’s point of view, who must blindly trust their outcomes compared to intelligible traditional manual approaches. In this research, manual and automatic methodologies for cf estimation were reviewed, taking into account their transparency limitations. This analysis led to the proposal of a new explainable ml solution for automatic cf calculations through bank transaction classification. Consideration should be given to the fact that no previous research has considered the explainability of bank transaction classification for this purpose. For classification, different ml models have been employed based on their promising performance in similar problems in the literature, such as Support Vector Machine, Random Forest, and Recursive Neural Networks. The results obtained were in the 90 % range for accuracy, precision, and recall evaluation metrics. From their decision paths, the proposed solution estimates the co2 emissions associated with bank transactions. The explainability methodology is based on an agnostic evaluation of the influence of the input terms extracted from the descriptions of transactions using locally interpretable models. The explainability terms were automatically validated using a similarity metric over the descriptions of the target categories. Conclusively, the explanation performance is satisfactory in terms of the proximity of the explanations to the associated activity sector descriptions, endorsing the trustworthiness of the process for a human operator and end users.Xunta de Galicia, Spain | Ref. ED481B-2021-118Xunta de Galicia, Spain | Ref. ED481B-2022-093Centro para el Desarrollo Tecnológico Industrial | Ref. EXP00146826/IDI-2022029

Stability of synchronous queued RFID networks

Queued Radio Frequency Identification (RFID) networks arise naturally in many applications, where tags are grouped into batches, and each batch must be processed before the next reading job starts. In these cases, the system must be able to handle all incoming jobs, keeping the queue backlogs bounded. This property is called stability. Besides, in RFID networks, it is common that some readers cannot operate at the same time, due to mutual interferences. This fact reduces the maximum traffic that readers can process since they have to share the channel. Synchronous networks share the channel using a TDMA approach. The goal of this work is to analytically determine whether a synchronous queued RFID network attains stable operation under a given incoming traffic. Stability depends on the service rate, which is characterized in this paper using an exact numerical method based on a recursive analytical approach, overcoming the limitations of previous works, which were based on simplifications. We also address different flow optimization problems, such as computing the maximum joint traffic that a network can process stably, selecting the minimal number of readers to process a given total load, or determining the optimal timeslot duration, which are novel in the RFID literature.Ministerio de Economía, Industria y Competitividad | Ref. TEC2016-76465-C2-1-

Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messages

Microblogging platforms, of which Twitter is a representative example, are valuable information sources for market screening and financial models. In them, users voluntarily provide relevant information, including educated knowledge on investments, reacting to the state of the stock markets in real-time and, often, influencing this state. We are interested in the user forecasts in financial, social media messages expressing opportunities and precautions about assets. We propose a novel Targeted Aspect-Based Emotion Analysis (tabea) system that can individually discern the financial emotions (positive and negative forecasts) on the different stock market assets in the same tweet (instead of making an overall guess about that whole tweet). It is based on Natural Language Processing (nlp) techniques and Machine Learning streaming algorithms. The system comprises a constituency parsing module for parsing the tweets and splitting them into simpler declarative clauses; an offline data processing module to engineer textual, numerical and categorical features and analyse and select them based on their relevance; and a stream classification module to continuously process tweets on-the-fly. Experimental results on a labelled data set endorse our solution. It achieves over 90% precision for the target emotions, financial opportunity, and precaution on Twitter. To the best of our knowledge, no prior work in the literature has addressed this problem despite its practical interest in decision-making, and we are not aware of any previous nlp nor online Machine Learning approaches to tabea.Xunta de Galicia | Ref. ED481B-2021-118Xunta de Galicia | Ref. ED481B-2022-093Financiado para publicación en acceso aberto: Universidade de Vigo/CISU

Stability of synchronous queued RFID networks

Queued Radio Frequency Identification (RFID) networks arise naturally in many applications, where tags are grouped into batches, and each batch must be processed before the next reading job starts. In these cases, the system must be able to handle all incoming jobs, keeping the queue backlogs bounded. This property is called stability. Besides, in RFID networks, it is common that some readers cannot operate at the same time, due to mutual interferences. This fact reduces the maximum traffic that readers can process since they have to share the channel. Synchronous networks share the channel using a TDMA approach. The goal of this work is to analytically determine whether a synchronous queued RFID network attains stable operation under a given incoming traffic. Stability depends on the service rate, which is characterized in this paper using an exact numerical method based on a recursive analytical approach, overcoming the limitations of previous works, which were based on simplifications. We also address different flow optimization problems, such as computing the maximum joint traffic that a network can process stably, selecting the minimal number of readers to process a given total load, or determining the optimal timeslot duration, which are novel in the RFID literature.This work was supported by the Project AIM, (AEI/FEDER, EU) under Grant TEC2016-76465-C2-1-R

Knockout packet loss probability analysis of SCWP optical packet switching wavelength distributed knockout architecture

The deployment of Optical Packet Switching (OPS) in Dense Wavelength Division Multiplexing (DWDM) backbone networks is perceived as a medium term promising alternative. Scalability restrictions imply that conventional switching architectures are unfeasible in this large-scale scenario. In a previous paper, the wavelength-distributed knockout architecture was proposed as a cost-effective scaling strategy for OPS switching fabrics. In this paper, this growable architecture is applied to OPS switching fabrics able to emulate output buffering. We also propose an scheduling algorithm which provides optimum performance if knockout packet losses are made negligible. The mathematical analysis to evaluate the knockout packet loss probability of this architecture is obtained, under uniform and non-uniform traffic patterns. To complement the switch dimensioning process, an upper bound assuring 0-knockout packet losses is compared with the exact analytical results.This research has been funded by Spanish MCyT grants TEC2004-05622-C04-01/TCM (CAPITAL) and TEC2004-05622-C04-02/TCM (ARPaq) and Xunta de Galicia grant PGIDIT04TIC322003PR

Is the edge really necessary for drone computing offloading? An experimental assessment in carrier‐grade 5G operator networks

In this article, we evaluate the first experience of computation offloading from drones to real fifth-generation (5G) operator systems, including commercial and private carrier-grade 5G networks. A follow-me drone service was implemented as a representative testbed of remote video analytics. In this application, an image of a person from a drone camera is processed at the edge, and image tracking displacements are translated into positioning commands that are sent back to the drone, so that the drone keeps the camera focused on the person at all times. The application is characterised to identify the processing and communication contributions to service delay. Then, we evaluate the latency of the application in a real non standalone 5G operator network, a standalone carrier-grade 5G private network, and, to compare these results with previous research, a Wi-Fi wireless local area network. We considered both multi-access edge computing (MEC) and cloud offloading scenarios. Onboard computing was also evaluated to assess the trade-offs with task offloading. The results determine the network configurations that are feasible for the follow-me application use case depending on the mobility of the end user, and to what extent MEC is advantageous over a state-of-the-art cloud service.Ministerio de Ciencia e Innovación | Ref. PDC2021‐121335‐C21Ministerio de Ciencia e Innovación | Ref. PRE2021‐098290Agencia Estatal de Investigación | Ref. PID2020-116329GB-C2

Demographic market segmentation on short banking movement descriptions applying Natural Language Processing

Xunta de Galicia | Ref. GRC2018/05

A software-defined networking solution for interconnecting network functions in service-based architectures

Mobile core networks handle critical control functions for delivering services in modern cellular networks. Traditional point-to-point architectures, where network functions are directly connected through standardized interfaces, are being substituted by service-based architectures (SBAs), where core functionalities are finer-grained microservices decoupled from the underlying infrastructure. In this way, network functions and services can be distributed, with scaling and fail-over mechanisms, and can be dynamically deployed, updated, or removed to support slicing. A myriad of network functions can be deployed or removed according to traffic flows, thereby increasing the complexity of connection management. In this context, 3GPP Release 16 defines the service communication proxy (SCP) as a unified communication interface for a set of network functions. In this paper, we propose a novel software-defined networking (SDN)-based solution with the same role for a service mesh architecture where network functions can be deployed anywhere in the infrastructure. We demonstrated its efficiency in comparison with alternative architectures.La Caixa Foundation | Ref. LCF/BQ/ES18/11670020Agencia Estatal de Investigación | Ref. PID2020-116329GB-C21Agencia Estatal de Investigación | Ref. PDC2021-121335-C2