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The increased popularity of flipped classroom in higher education warrants more thorough investigation of the pedagogical format’s effects on student learning. This paper utilizes two iterations of a randomized field experiment to study the effects of flipped classroom on student learning specifically focusing on heterogeneous treatment effects across the important classroom-level factor of teachers. The empirical setting is an undergraduate macroeconomics course with 933 students and 11 teachers. Our findings show a positive yet insignificant average effect of flipped classroom on both pass rate and final exam grades. We further find substantial shifts in the ranking of the participating teachers’ effectiveness when comparing traditional and flipped classroom conditions, which suggests that the most successful teacher in a traditional teaching environment is not necessarily the most successful teacher in a flipped classroom environment.

A tryptophan-rich octapeptide, C8 (Ac-Trp-Glu-Asp-Trp-Val-Gly-Trp-Ile-NH(2)), modelled on the membrane-proximal external region of the feline immunodeficiency virus (FIV) gp36 glycoprotein ectodomain, exhibits potent antiviral activity against FIV. A mechanism has been proposed by which the peptide, being positioned on the surface of the cell membrane, inhibits its fusion with the virus. In the present work, peptide-lipid interactions of C8 with dimyristoyl phosphatidylcholine liposomes are investigated using electron spin resonance spectroscopy of spin-labelled lipids. Three other peptides, obtained from modifications of C8, have also been investigated, in an attempt to clarify the essential molecular features of the interactions involving the tryptophan residues. The results show that C8 adsorbs strongly on the bilayer surface. Membrane binding requires not only the presence of the Trp residues in the sequence, but also their common orientation on one side of the peptide that is engendered by the WX(2) WX(2) W motif. Membrane interaction correlates closely with peptide antiviral activity, indicating that the membrane is essential in stabilizing the peptide conformation that will be able to inhibit viral infection.

This paper presents the results of a bridge inspection task analysis conducted in collaboration with the Ministère des Transports du Québec (MTQ) in order to maximize the impact of the development of a technology aimed to assist bridge inspectors in performing their tasks. More specifically, we analyzed the inspection tasks for inspection of bridges made of concrete. Results include the set of requirements to become a MTQ’s bridge inspector and explain the various steps of a bridge inspection. Then we discuss ways to maximize the impact of technology to assist inspectors in doing their tasks. We conclude that for a use case of a drone inspection with a drone equipped with a common color image sensor for visible light, this technology is well suited to improve annual visual bridge inspections, as well as for the inspection of confined spaces., 20th International Conference, EPCE 2023, Held as Part of the 25th HCI International Conference, HCII 2023, July 23–28, 2023, Copenhagen, Denmark, Series: Lecture Notes in Computer Science

This paper reports on research being conducted under the National Research Council of Canada’s Aging in Place Program. The objective of this program is to evaluate and assist in the adaptation of assistive technologies for older adults living at home. The aims are to produce guidelines and prototypes needed to design safe, usable, and affordable aging in place technology solutions for virtual care. In preparation for this initiative, relevant findings are presented from a scoping review of the literature. Additionally, we present the framework for surveying older adults’ perspectives on their lived experiences with virtual care and digital technologies during the COVID-19 pandemic, which drove uptake of virtual care, particularly in critical areas such as cardiac rehabilitation. Here we discuss the target population for surveillance and describe the survey design, validation, and sampling approach that could achieve the widest range of perspectives; identify gaps, barriers, and challenges. Additionally, we explore remote usability assessment methods available for aging in place technology co-design and evaluation efforts., 9th International Conference, ITAP 2023, Held as Part of the 25th HCI International Conference, HCII 2023, July 23–28, 2023, Copenhagen, Denmark, Series: Lecture Notes in Computer Science

Computational models of learners have been recognized to play various roles in training and learning environments. While optimized tutoring strategies should be determined through empirical investigation, the adaptive instructional system design space is too large to fully validate empirically. Synthetic data generated by simulated learners could be one approach to explore the interaction between learner behaviours and adaptive instructional system strategies. The current paper reports on a computer simulation design and results for modelling the effects of learning and training strategies on the learning and performance of simulated learners. The application domain is marine navigation. The computer simulation included a fairly autonomous learning agent with self-assessment capabilities (reinforcement learning), and other means to acquire knowledge and skills including learning from instructions, and declarative memory base-level activation. Three instructional strategies were simulated: 1) a minimalist method leaving the simulated learner to proceed only by trial and error, 2) a discovery method where the simulated learners are left on their own but with an added capability to store a declarative representation of successful rules, and 3) a briefing then practice method, where all the declarative rules to execute tasks are in declarative memory prior to executing navigation tasks., 5th International Conference, AIS 2023, Held as Part of the 25th HCI International Conference, HCII 2023, July 23–28, 2023, Copenhagen, Denmark, Series: Lecture Notes in Computer Science

Nowadays, education is a fundamental element to provide people with independence and knowledge. All citizens have the right of access to education, including students with special educational needs. Education must be inclusive for these students at primary, secondary and university levels. Therefore, the aim is to analyse the conceptual, intellectual and social structure in the field of inclusive education in the university environment through bibliometric techniques. The sample consisted of 605 documents extracted from the Web of Science and analysed using the bibliometrix software designed in R. The results show that there are two journals that are fundamental in the field and that co-citation networks are generated around them. Furthermore, the most productive authors will occupy central positions. Nonetheless, the papers that initiated the field will receive more citations. Finally, since 2010, a greater diversity of topics within inclusive education can be observed, such as teacher training in inclusive education or considering the curriculum. Future lines of work include the possibility of using more databases and establishing an action protocol based on the results.

This paper provides necessary and sufficient optimality conditions for abstract-constrained mathematical programming problems in locally convex spaces under new qualification conditions. Our approach exploits the geometrical properties of certain mappings, in particular their structure as difference of convex functions, and uses techniques of generalized differentiation (subdifferential and coderivative). It turns out that these tools can be used fruitfully out of the scope of Asplund spaces. Applications to infinite, stochastic and semi-definite programming are developed in separate sections. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The first author was partially supported by ANID Grant Fondecyt Regular 1190110 and Centro de Modelamiento Matemático (CMM), ACE210010 and FB210005, BASAL funds for centers of excellence from ANID-Chile. The second author has been partially supported by Grants MTM2014-59179-C2-(1-2)-P from MINECO/MICINN, Spain, and FEDER, European Union, and by the Australian Research Council, Project DP180100602. The third author was partially supported by ANID Grants Fondecyt Regular 1190110 and Fondecyt Regular 1200283 and Centro de Modelamiento Matemático (CMM), ACE210010 and FB210005, BASAL funds for centers of excellence from ANID-Chile.

Around a third of the total population of Europe suffers from mental disorders. The use of electroencephalography (EEG) together with Machine Learning (ML) algorithms to diagnose mental disorders has recently been shown to be a prominent research area, as exposed by several reviews focused on the field. Nevertheless, previous to the application of ML algorithms, EEG data should be correctly preprocessed and prepared via Feature Engineering (FE). In fact, the choice of FE techniques can make the difference between an unusable ML model and a simple, effective model. In other words, it can be said that FE is crucial, especially when using complex, non-stationary data such as EEG. To this aim, in this paper we present a Systematic Mapping Study (SMS) focused on FE from EEG data used to identify mental disorders. Our SMS covers more than 900 papers, making it one of the most comprehensive to date, to the best of our knowledge. We gathered the mental disorder addressed, all the FE techniques used, and the Artificial Intelligence (AI) algorithm applied for classification from each paper. Our main contributions are: (i) we offer a starting point for new researchers on these topics, (ii) we extract the most used FE techniques to classify mental disorders, (iii) we show several graphical distributions of all used techniques, and (iv) we provide critical conclusions for detecting mental disorders. To provide a better overview of existing techniques, the FE process is divided into three parts: (i) signal transformation, (ii) feature extraction, and (iii) feature selection. Moreover, we classify and analyze the distribution of existing papers according to the mental disorder they treat, the FE processes used, and the ML techniques applied. As a result, we provide a valuable reference for the scientific community to identify which techniques have been proven and tested and where the gaps are located in the current state of the art. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work has been co-funded by the BALLADEER (PROMETEO/2021/088) project, a Big Data analytical platform for the diagnosis and treatment of Attention Deficit Hyperactivity Disorder (ADHD) featuring extended reality, funded by the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital (Generalitat Valenciana) and the AETHER-UA project (PID2020-112540RB-C43), a smart data holistic approach for context-aware data analytics: smarter machine learning for business modelling and analytics, funded by Spanish Ministry of Science and Innovation. Sandra García-Ponsoda holds a predoctoral contract granted by ValgrAI - Valencian Graduate School and Research Network of Artificial Intelligence and the Generalitat Valenciana, and co-funded by the European Union. Jorge García-Carrasco holds a predoctoral contract (CIACIF/2021/454) granted by the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital (Generalitat Valenciana).

Data availability statement: Data are available from the authors upon request. Code availability: The codes are in Fortran and are available from the authors upon request. Originally developed as CESifo Working Paper No. 10018, available at https://www.cesifo.org/DocDL/cesifo1_wp10018.pdf. Copyright © The Author(s) 2023. This paper analyses the stochastic properties of UK nominal and real wages over the period 1750–2015 using fractional integration techniques. Both the original series and logged ones are analysed. The results generally suggest that nominal wages exhibit a higher degree of persistence, which reflects relatively long lags between inflation and wage adjustments. Endogenous break tests are also carried out and various structural breaks are identified in both series. On the whole, the corresponding subsample estimates imply an increase over time in the degree of persistence of both series. MCIN/AEI Grant PID2020-113691RB-I00 10.13039/501100011033.

This paper reviews the state of the art in visual privacy protection techniques, with particular attention paid to techniques applicable to the field of Active and Assisted Living (AAL). A novel taxonomy with which state-of-the-art visual privacy protection methods can be classified is introduced. Perceptual obfuscation methods, a category in this taxonomy, is highlighted. These are a category of visual privacy preservation techniques, particularly relevant when considering scenarios that come under video-based AAL monitoring. Obfuscation against machine learning models is also explored. A high-level classification scheme of privacy by design, as defined by experts in privacy and data protection law, is connected to the proposed taxonomy of visual privacy preservation techniques. Finally, we note open questions that exist in the field and introduce the reader to some exciting avenues for future research in the area of visual privacy. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work is part of the visuAAL project on Privacy-Aware and Acceptable Video-Based Technologies and Services for Active and Assisted Living (https://www.visuaal-itn.eu/). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 861091. The authors would also like to acknowledge the contribution of COST Action CA19121 - GoodBrother, Network on Privacy-Aware Audio- and Video-Based Applications for Active and Assisted Living (https://goodbrother.eu/), supported by COST (European Cooperation in Science and Technology) (https://www.cost.eu/).

Accurate early warning systems for landslides are a reliable risk-reduction strategy that may significantly reduce fatalities and economic losses. Several machine learning methods have been examined for this purpose, underlying deep learning (DL) models’ remarkable prediction capabilities. The long short-term memory (LSTM) and gated recurrent unit (GRU) algorithms are the sole DL model studied in the extant comparisons. However, several other DL algorithms are suitable for time series forecasting tasks. In this paper, we assess, compare, and describe seven DL methods for forecasting future landslide displacement: multi-layer perception (MLP), LSTM, GRU, 1D convolutional neural network (1D CNN), 2xLSTM, bidirectional LSTM (bi-LSTM), and an architecture composed of 1D CNN and LSTM (Conv-LSTM). The investigation focuses on four landslides with different geographic locations, geological settings, time step dimensions, and measurement instruments. Two landslides are located in an artificial reservoir context, while the displacement of the other two is influenced just by rainfall. The results reveal that the MLP, GRU, and LSTM models can make reliable predictions in all four scenarios, while the Conv- LSTM model outperforms the others in the Baishuihe landslide, where the landslide is highly seasonal. No evident performance differences were found for landslides inside artificial reservoirs rather than outside. Furthermore, the research shows that MLP is better adapted to forecast the highest displacement peaks, while LSTM and GRU are better suited to model lower displacement peaks. We believe the findings of this research will serve as a precious aid when implementing a DL-based landslide early warning system (LEWS)., SUPPORTO SCIENTIFICO PER L’OTTIMIZZAZIONE, IMPLEMENTAZIONE E GESTIONE DEL SISTEMA DI MONITORAGGIO CON AGGIORNAMENTO DELLE SOGLIE DI ALLERTAMENTO DEL FENOMENO FRANOSO DI SANT’ANDREA – PERAROLO DI CADORE (BL)” and the Spanish Grant “SARAI, PID2020-116540RB-C21, MCIN/AEI/10.13039/501100011033” and “RISKCOAST, InSAR displacement data of the El Arrecife landslide, Geohazard Exploitation Platform (GEP) of the European Space Agency, NoR Projects Sponsorship (Project ID: 63737)

This work was jointly supported by the Spanish Ministry of Science and Innovation-State Research Agency through grants numbered PID2020-120217RB-I00 and PID2021-123737NB-I00, and the IMAG-Maria de Maeztu grant CEX2020-001105-/AEI/10.13039/501100011033; and by the Spanish Junta de Andalucia through grant number B-FQM-284-UGR20., In this paper we consider continuous-time hidden Markov processes (CTHMM). The model considered is a two-dimensional stochastic process (Xt, Yt) , with Xt an unobserved (hidden) Markov chain defined by its generating matrix and Yt an observed process whose distribution law depends on Xt and is called the emission function. In general, we allow the process Yt to take values in a subset of the q-dimensional real space, for some q. The coupled process (Xt, Yt) is a continuous-time Markov chain whose generator is constructed from the generating matrix of X and the emission distribution. We study the theoretical properties of this two-dimensional process using a formulation based on semi-Markov processes. Observations of the CTHMM are obtained by discretization considering two different scenarii. In the first case we consider that observations of the process Y are registered regularly in time, while in the second one, observations arrive at random. Maximum-likelihood estimators of the characteristics of the coupled process are obtained in both scenarii and the asymptotic properties of these estimators are shown, such as consistency and normality. To illustrate the model a real-data example and a simulation study are considered., Universidad de Granada/CBUA, IMAG-Maria de Maeztu CEX2020-001105-/AEI/10.13039/501100011033, Spanish Junta de Andalucia B-FQM-284-UGR20, Spanish Ministry of Science and Innovation-State Research Agency PID2020-120217RB-I00, PID2021-123737NB-I00

Funding for open access publishing: Universidad de Granada/CBUA. This article forms part of a larger project which has received funding from the European Commission under Grant Agreement No. 838444 (H2020 Marie Sklodowska-Curie Programme)., Common causes of wrongful conviction include eyewitness misidentification, improper forensics, or false confessions (Garrett in Convicting the innocent: where criminal prosecutions go wrong, Harvard University Press, Cambridge, 2011; Innocence Canada, https://www.innocencecanada.com/causes-of-wrongful-convictions/); whilst none of these factors are in question in this paper, the notion put forward is that a more implicit factor is also at play; that is, the newspaper coverage of a criminal case during the lead up to trial. According to Felton Rosulek (Text Talk 28:529–550, 2008), “[…] linguistic choices conspire together […] and create a specific interpretation of reality”. Thus, this paper explores how the accused and the (alleged) criminal events pertaining to a high-profile case of the 1980s in New York are discursively framed in a range of press coverage across the USA and further afield. The corpus comprises newspaper articles reporting on the Central Park Jogger case, which resulted in the wrongful conviction and lost freedom of five innocent young men. Using corpus-assisted critical discourse analysis (CADS) (Partington and Marchi, in: Biber, Reppen (eds) The Cambridge handbook of English corpus linguistics, Cambridge University Press, 2015; Stubbs in Text and corpus analysis. Computer-assisted studies of language and culture. Blackwell, Oxford, 1996), the Transitivity patterns (Halliday and Matthiessen in Halliday’s introduction to functional grammar, Routledge, London, 2014) present in the press coverage are examined to gain insights into whether the portrayal of (1) the accused and (2) the victim at the centre of this case may have contributed to securing a wrongful conviction. Furthermore, this paper strives to (1) draw awareness to wrongful convictions more generally and (2) contribute to studies on Transitivity, which serve to highlight societal injustice and the power of printed news when determining the innocence or guilt of an accused individual. To acquire both quantitative and qualitative results, the UAM Corpus Tool (O’Donnell in UAM Corpus Tool, http://www.corpustool.com/) was also employed here., Universidad de Granada/CBUA, H2020 Marie Sklodowska-Curie Programme, European Commission 838444 EC

Data availability: All data generated or analysed during this study are included in this article. Copyright © The Author(s) 2023. Energy consumption remains an open challenge in aerial systems such as CubeSats and therefore optimization of its allocation is a top priority for maximizing operational capacity. Our research review reveals a plethora of approaches for optimization of energy allocation and all achieving varying degrees of success and not without any compromises. In this paper, we exploit the use of serious gaming in a novel energy allocation algorithm that aims at minimizing energy consumption to maximize the utilities of both CubeSats and terrestrial sensors. To demonstrate this, we use Stackelberg for serious gaming and standalone topology for CubeSat configuration. The experimental results show that the use of a Stackelberg game approach for optimization has led to reduction in the required transmission energy in sensors, an improved link performance between the CubeSat and ground sensors, and an increase in network lifetime and performance without resorting into sensor power enhancements or other external power sources. The overall average operational capacity improvement predictions range between 22 to 27% across all performance indicators of energy efficiency across RF chains of link budgets.

This work was supported by grant from the Ministry of Economy, Knowledge, Business and University, of the Andalusian Government, within the framework of the FEDER Andalusia 2014–2020 operational program. Specific objective 1.2.3. «Promotion and generation of frontier knowledge and knowledge oriented to the challenges of society, development of emerging technologies») within the framework of the reference research project (UPO-1380624). FEDER co-financing percentage 80%., School bullying is a growing concern in almost all developed economies, bringing negative and serious consequences for those students involved in the role of victims. In this paper, we propose to analyze this topic for the case of Spain, considering the data compiled in the Programme for International Student Assessment (PISA) report in 2018. The sample size consists of 12,549 15-old-year students (51.84% females and 48.16% males). With the help of structural equation models (SEM), we aim to detect the relationship between the risk of being a victim of bullying and several self-appreciations expressed by the students. We have considered variables that try to measure individual perceptions in several aspects, such as the self-image, the help provided by parents and teachers and how the school environment’s safety is perceived. A multigroup analysis was also performed to see the impact of the socioeconomic level of the families and the students’ academic performances on the proposed model. We conclude that several of those aspects are directly related with the risk of being bullied and this risk is higher in those students who present school failure and have a lower socioeconomic status. In this regard, the results would permit pointing out some aspects in which the decision-makers can focus their proposals to establish prevention measures., Departamento de Economía, Métodos Cuantitativos e Historia Económica. Universidad Pablo de Olavide

Recent advances in the area of the Internet of Things shows that devices are usually resource-constrained. To enable advanced applications on these devices, it is necessary to enhance their performance by leveraging external computing resources available in the network. This work presents a study of computational platforms to increase the performance of these devices based on the Mobile Cloud Computing (MCC) paradigm. The main contribution of this paper is to research the advantages and possibilities of architectures with multiple offloading options. To this end, a review of architectures that use a combination of the computing layers in the available infrastructure to perform this paradigm and outsource processing load is presented. In addition, a proof-of-concept application is introduced to demonstrate its realization along all the network layers. The results of the simulations confirm the high flexibility to offload numerous tasks using different layers and the ability to overcome unfavorable scenarios. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by the Spanish Research Agency (AEI) (DOI 10.13039/501100011033) under Project HPC4Industry PID2020-120213RB-I00.

This research was funded by the International Civil Aviation Organization (ICAO) under the Joint Finance Agreement with the Icelandic Meteorological Office, for working paper JS.212.WP.2054, The Icelandic Meteorological Office maintains a national network of webcams designed and built in house for environmental monitoring. During the 2021 Fagradalsfjall eruption these cameras, along with a temporary near-field network of commercial cameras installed by the Department of Civil Protection and Emergency Management, were used to estimate the height of the SO2 plume and lava fountain. Here we present the webcam designs, the techniques used to calibrate them, and the messaging system and web interface that allow near real time measurements to be made from the images. With this system we were able to make estimates of heights with an accuracy on the order of tens to a few hundreds of meters with a lag typically of five to ten minutes at up to ten minute intervals when weather conditions were favorable. The plume heights were then used to constrain the performance of the SO2 dispersion model used for air quality forecasts while fountain heights were used to delineate danger zones where visitors at the eruption site were in danger of being hit by ballistic clasts., Icelandic Meteorological Office, International Civil Aviation Organization

It is widely acknowledged that vaccinating at maximal effort in the face of an ongoing epidemic is the best strategy to minimise infections and deaths from the disease. Despite this, no one has proved that this is guaranteed to be true if the disease follows multi-group SIR (Susceptible-Infected-Recovered) dynamics. This paper provides a novel proof of this principle for the existing SIR framework, showing that the total number of deaths or infections from an epidemic is decreasing in vaccination effort. Furthermore, it presents a novel model for vaccination which assumes that vaccines assigned to a subgroup are distributed randomly to the unvaccinated population of that subgroup. It suggests, using COVID-19 data, that this more accurately captures vaccination dynamics than the model commonly found in the literature. However, as the novel model provides a strictly larger set of possible vaccination policies, the results presented in this paper hold for both models.

Acknowledgements The work reported here was supported by research project PID2019-106435GB-I00 of the Ministerio de Ciencia e Innovación of Spain. We thank Philippe Renard and the two anonymous reviewers who provided constructive comments that have allowed us to improve the final version of this paper., Transmissivity is a significant hydrogeological parameter that affects the reliability of groundwater flow and transport models. This study demonstrates the improvement in the estimated transmissivity field of an unconfined detritic aquifer that can be obtained by using geostatistical methods to combine three types of data: hard transmissivity data obtained from pumping tests, soft transmissivity data obtained from lithological information from boreholes, and water head data. The piezometric data can be related to transmissivity by solving the hydrogeology inverse problem, i.e., including the observed water head to determine the unknown model parameters (log transmissivities). The geostatistical combination of all the available information is achieved by using three different geostatistical methodologies: ordinary kriging, ordinary co-kriging and inverse problem universal co-kriging. In addition, there are eight methodological cases to be compared according to which log-transmissivity data are considered as the primary variable in co-kriging and whether two or three variables are used in inverse-problem universal co-kriging. The results are validated by using the performance statistics of the direct modelling of the unconfined groundwater flow and comparing observed water heads with the modelled ones. Although the results show that the two sets of log-transmissivity data are incompatible, the set of log-transmissivity data from the lithofacies provides a good log-transmissivity image that can be improved by inverse modelling. The map provided by inverse-problem universal co-kriging provides the best results. Using three variables, rather than two in the inverse problem, gives worse results because of the incompatibility of the log-transmissivity data sets., Project PID2019-106435GB-I00 of the Ministerio de Ciencia e Innovación of Spain, Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature

The anisotropic Kepler problem is a model of the motion of free electrons on an n-type semiconductor and is known to be a non-integrable Hamiltonian system. While many approximate periodic solutions have been found through numerical calculation (Sumiya et al. in Artif Life Robot 19:262–269, 2014), none have been rigorously proved to exist. In this paper, we first show that the action functional of the anisotropic Kepler problem has a minimizer under a fixed region condition with boundary conditions on a vertical half-line. Next, we identify the smallest collision trajectory that satisfies the same boundary conditions. By constructing an orbit with an action functional smaller than this collision orbit via local deformation, we show that the collision solution does not become the minimizer. This holds for any μ∈(0, 1). Reversibility allows the periodic orbit to be constructed from the minimizer obtained via the action functional.

Global efforts to upgrade water, drainage, and sanitation services are hampered by hydrometeorological data-scarcity plus uncertainty about climate change. Intensity–duration–frequency (IDF) tables are used routinely to design water infrastructure so offer an entry point for adapting engineering standards. This paper begins with a novel procedure for guiding downscaling predictor variable selection for heavy rainfall simulation using media reports of pluvial flooding. We then present a three-step workflow to: (1) spatially downscale daily rainfall from grid-to-point resolutions; (2) temporally scale from daily series to sub-daily extreme rainfalls and; (3) test methods of temporal scaling of extreme rainfalls within Regional Climate Model (RCM) simulations under changed climate conditions. Critically, we compare the methods of moments and of parameters for temporal scaling annual maximum series of daily rainfall into sub-daily extreme rainfalls, whilst accounting for rainfall intermittency. The methods are applied to Kampala, Uganda and Kisumu, Kenya using the Statistical Downscaling Model (SDSM), two RCM simulations covering East Africa (CP4 and P25), and in hybrid form (RCM-SDSM). We demonstrate that Gumbel parameters (and IDF tables) can be reliably scaled to durations of 3 h within observations and RCMs. Our hybrid RCM-SDSM scaling reduces errors in IDF estimates for the present climate when compared with direct RCM output. Credible parameter scaling relationships are also found within RCM simulations under changed climate conditions. We then discuss the practical aspects of applying such workflows to other city-regions.

Current challenges in healthcare urge the need for more productive and efficient healthcare. Healthcare technologies are expected to address these challenges as part of the Society 5.0 (S5.0) vision. Earlier research revealed a variety of digital architectures under S5.0. However, most research is based on single case studies and no cross-case analysis has been conducted in healthcare. Therefore, this paper aims to identify and analyze health-related applications that are developed and evaluated in case studies under S5.0. More specific, this paper focuses on alignment between the research and development work of the Open Healthcare Platform 2023 (OHP2023) consortium and the S5.0 reference architecture using the Adaptive Integrated Digital Architecture Framework (AIDAF). The PRISMA2020 guidelines were used to conduct a Systematic Literature Review (SLR) regarding healthcare applications and evaluations in case studies under S5.0. The initial search included 94 documents of which 23 documents were selected for this SLR. The SLR extracted 18 applications and six case studies. Based on the SLR, the use of the AIDAF by the OHP2030 consortium is visualized and described for the development of applications under S5.0 and alignment with the S5.0 reference architecture. The main limitation of the SLR is the limited depth of the cross-case analysis. In spite of this limitation, this study contributes to creating a common ground for the OHP2030 consortium, interested healthcare scholars, and professionals, to develop applications under S5.0 and align with the S5.0 reference architecture. Future research may contribute to developing a case study protocol for in-depth and cross-case analysis.

The world is becoming increasingly dependant in computing intensive applications. The appearance of new paradigms, such as Internet of Things (IoT), and advances in technologies such as Computer Vision (CV) and Artificial Intelligence (AI) are creating a demand for high-performance applications. In this regard, Graphics Processing Units (GPUs) have the ability to provide better performance by allowing a high degree of data parallelism. These devices are also beneficial in specialized fields of manufacturing industry such as CAD/CAM. For all these applications, there is a recent tendency to offload these computations to the Cloud, using a computing offloading Cloud architecture. However, the use of GPUs in the Cloud presents some inefficiencies, where GPU virtualization is still not fully resolved, as our research on what main Cloud providers currently offer in terms of GPU Cloud instances shows. To address these problems, this paper first makes a review of current GPU technologies and programming techniques that increase concurrency, to then propose a Cloud computing outsourcing architecture to make more efficient use of these devices in the Cloud. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by the Spanish Research Agency (AEI) under project HPC4Industry PID2020-120213RB-I00.

In a special run of the LHC with β⋆=2.5 km, proton–proton elastic-scattering events were recorded at s√=13 TeV with an integrated luminosity of 340 μb−1 using the ALFA subdetector of ATLAS in 2016. The elastic cross section was measured differentially in the Mandelstam t variable in the range from −t=2.5⋅10−4 GeV2 to −t=0.46 GeV2 using 6.9 million elastic-scattering candidates. This paper presents measurements of the total cross section σtot, parameters of the nuclear slope, and the ρ-parameter defined as the ratio of the real part to the imaginary part of the elastic-scattering amplitude in the limit t→0. These parameters are determined from a fit to the differential elastic cross section using the optical theorem and different parameterizations of the t-dependence. The results for σtot and ρ are σtot(pp→X)=104.7±1.1 mb ,ρ=0.098±0.011. The uncertainty in σtot is dominated by the luminosity measurement, and in ρ by imperfect knowledge of the detector alignment and by modelling of the nuclear amplitude., CEA-DRF, DNSRC IN2P3-CNRS, EU-ESF, GenT Programmes Generalitat Valenciana, Spain, La Caixa Banking Foundation, PROMETEO, UNCE SCI/013, CRC Health Group 21/SCI/017 CRC, H2020 Marie Skłodowska-Curie Actions MSCA, CERN, European Research Council ERC, European Cooperation in Science and Technology COST, Generalitat de Catalunya, Agencia Nacional de Promoción Científica y Tecnológica ANPCyT, Ministerio de Ciencia e Innovación MICINN, Horizon 2020, European Regional Development Fund ERDF, Agencia Nacional de Investigación y Desarrollo ANID

The recognition of patterns that have a time dependency is common in areas like speech recognition or natural language processing. The equivalent situation in image analysis is present in tasks like text or video recognition. Recently, Convolutional Recurrent Neural Networks (CRNN) have been broadly applied to solve these tasks in an end-to-end fashion with successful performance. However, its application to Optical Music Recognition (OMR) is not so straightforward due to the presence of different elements sharing the same horizontal position, disrupting the linear flow of the timeline. In this paper, we study the ability of the state-of-the-art CRNN approach to learn codes that represent this disruption in homophonic scores. In our experiments, we study the lower bounds in the recognition task of real scores when the models are trained with synthetic data. Two relevant conclusions are drawn: (1) Our serialized ways of encoding the music content are appropriate for CRNN-based OMR; (2) the learning process is possible with synthetic data, but there exists a glass ceiling when recognizing real sheet music. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This paper is part of the I+D+i PID2020-118447RA-I00 (MultiScore) project, funded by MCIN/AEI/10.13039/501100011033. The first author is supported by grant FPU19/04957 from the Spanish Ministerio de Universidades.

This paper presents a conceptual framework that accurately represents the current and future perspectives of data-driven companies in tourism by means of an analysis of the data sources used in the data-driven tourism research literature, as well as the research topics to which they are applied. For this purpose, a bibliometric analysis of data-driven tourism research is carried out. The framework of the study is all tourism-related publications whose research was based on data sources during the period 1982–2020. The results show some of the basic bibliometric performance indicators and the maps of science. The main themes of research interest are identified, and the conceptual evolution is obtained based on these maps. Three major thematic areas are identified: tourism research topics, information sources, and data analysis techniques. Based on these three thematic areas, the conceptual model of data architecture and processes of a data-driven organization in the tourism sector are obtained. An additional qualitative analysis of the three thematic areas is performed, CRUE-CSIC agreement with Springer Nature

Health institutions recommend that young infants be exclusively breastfed on demand, and it is widely held that parents who can breastfeed have an obligation to do so. This has been challenged in recent philosophical work, especially by Fiona Woollard. Woollard’s work critically engages with two distinct views of parental obligation that might ground such an obligation—based on maximal benefit and avoidance of significant harm—to reject an obligation to breastfeed. While agreeing with Woollard’s substantive conclusion, this paper (drawing on philosophical discussion of the ‘right to rear’) argues that there are several more moderate views of parental obligation which might also be thought to ground parental obligation. We first show that an obligation to breastfeed might result not from a general obligation to maximally benefit one’s child, but from what we call ‘choice-specific’ obligations to maximise benefit within particular activities. We then develop this idea through two views of parental obligation—the Dual Interest view, and the Best Custodian view—to ground an obligation to exclusively breastfeed on demand, before showing how both these more moderate views fail. Finally, we argue that not only is there no general obligation to breastfeed children, but that it is often morally right not to do so. Since much advice from health institutions on this issue implies that exclusive breastfeeding on demand is the best option for all families, our argument drives the feeding debate forward by showing that this advice often misrepresents parents’ moral obligations in potentially harmful ways.

Knowledge about the interactions between dietary and biomedical factors is scattered throughout uncountable research articles in an unstructured form (e.g., text, images, etc.) and requires automatic structuring so that it can be provided to medical professionals in a suitable format. Various biomedical knowledge graphs exist, however, they require further extension with relations between food and biomedical entities. In this study, we evaluate the performance of three state-of-the-art relation-mining pipelines (FooDis, FoodChem and ChemDis) which extract relations between food, chemical and disease entities from textual data. We perform two case studies, where relations were automatically extracted by the pipelines and validated by domain experts. The results show that the pipelines can extract relations with an average precision around 70%, making new discoveries available to domain experts with reduced human effort, since the domain experts should only evaluate the results, instead of finding, and reading all new scientific papers.

End-to-end solutions have brought about significant advances in the field of Optical Music Recognition. These approaches directly provide the symbolic representation of a given image of a musical score. Despite this, several documents, such as pianoform musical scores, cannot yet benefit from these solutions since their structural complexity does not allow their effective transcription. This paper presents a neural method whose objective is to transcribe these musical scores in an end-to-end fashion. We also introduce the GrandStaff dataset, which contains 53,882 single-system piano scores in common western modern notation. The sources are encoded in both a standard digital music representation and its adaptation for current transcription technologies. The method proposed in this paper is trained and evaluated using this dataset. The results show that the approach presented is, for the first time, able to effectively transcribe pianoform notation in an end-to-end manner. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This paper is part of the MultiScore project (PID2020-118447RA-I00), funded by MCIN/AEI/10.13039/501100011033. The first author is supported by Grant ACIF/2021/356 from the “Programa I+D+i de la Generalitat Valenciana.”

This paper examines the corporate governance mechanisms in Sri Lanka, a country that only a little more than a decade ago emerged from a 30-year long civil war. We focus on the evolution of Sri Lanka’s corporate governance from historical, sociocultural, and institutional perspectives. Taking Sri Lanka as a case where inclusiveness and reconciliation at the board level is important, we aim to diagnose the key corporate governance issues which we then broaden towards other South Asia developing countries and provide a research agenda. Many Sri Lankan firms suffer from typical Asian-style agency problems; conflicts of interest between (i) minority and majority shareholders, (ii) shareholders and debtholders, and (iii) shareholders and stakeholders. The most prevalent agency problem is the expropriation of minority shareholders’ rights through ownership pyramids, cross-holdings, or intermediate private firms. Although creditor protection laws limit the expropriation of debtholders’ rights, firms’ widespread use of political connections forces banks to grant cheap credit at favorable terms. Poor stakeholder management creates agency problems following window dressing of ESG disclosures, corporate opacity, and ethnicity-and gender-based discrimination in the workplace. This study shows that social norms and ethical values play a non-negligible role in the functioning of the corporate governance regulation and in corporate culture in Sri Lanka.

This paper examines the corporate governance mechanisms in Sri Lanka, a country that only a little more than a decade ago emerged from a 30-year long civil war. We focus on the evolution of Sri Lanka’s corporate governance from historical, sociocultural, and institutional perspectives. Taking Sri Lanka as a case where inclusiveness and reconciliation at the board level is important, we aim to diagnose the key corporate governance issues which we then broaden towards other South Asia developing countries and provide a research agenda. Many Sri Lankan firms suffer from typical Asian-style agency problems; conflicts of interest between (i) minority and majority shareholders, (ii) shareholders and debtholders, and (iii) shareholders and stakeholders. The most prevalent agency problem is the expropriation of minority shareholders’ rights through ownership pyramids, cross-holdings, or intermediate private firms. Although creditor protection laws limit the expropriation of debtholders’ rights, firms’ widespread use of political connections forces banks to grant cheap credit at favorable terms. Poor stakeholder management creates agency problems following window dressing of ESG disclosures, corporate opacity, and ethnicity-and gender-based discrimination in the workplace. This study shows that social norms and ethical values play a non-negligible role in the functioning of the corporate governance regulation and in corporate culture in Sri Lanka.

This paper sets two questions. (a) What changes has the pandemic engendered? (b) How should the government connect these changes to efficient administration?.Three changes can be delineated. (a) The Special Law established a prefecturalcentered management. (b) Substantial power was assigned to the governors. (c) The effectiveness of inter-prefectural cooperation is reflected. The governments face the challenges: (a) demand for strengthening public health administration, (b) difficult complex financial management, and (c) regional disparities. The governments are trying to overcome these challenges. This paper focuses on (a) the enrichment of medical welfare personnel and (b) living shift and local revitalization.

The authors acknowledge the financial support of the funding agencies: Agence Nationale de la Recherche (contract ANR-15-CE31-0020), Centre National de la Recherche Scientifique (CNRS), Commission Européenne (FEDER fund and Marie Curie Program), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Paris Île-de-France Region, France; The General Secretariat of Research and Innovation (GSRI), Greece Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell’Università e della Ricerca (MIUR), PRIN 2017 program (Grant NAT-NET 2017W4HA7S) Italy; Ministry of Higher Education, Scientific Research and Innovation, Morocco, and the Arab Fund for Economic and Social Development, Kuwait; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; The National Science Centre, Poland (2021/41/N/ST2/01177); National Authority for Scientific Research (ANCS), Romania; Grants PID2021-124591NB-C41, -C42, -C43 funded by MCIN/AEI/ 10.13039/501100011033 and, as appropriate, by “ERDF A way of making Europe”, by the “European Union” or by the “European Union NextGenerationEU/PRTR”, Programa de Planes Complementarios I+D+I (refs. ASFAE/2022/023, ASFAE/2022/014), Programa Prometeo (PROMETEO/2020/019) and GenT (refs. CIDEGENT/2018/034, /2019/043, /2020/049. /2021/23) of the Generalitat Valenciana, Junta de Andalucía (ref. SOMM17/6104/UGR, P18-FR-5057), EU: MSC program (ref. 101025085), Programa María Zambrano (Spanish Ministry of Universities, funded by the European Union, NextGenerationEU), Spain., In the era of precision measurements of the neutrino oscillation parameters, upcoming neutrino experiments will also be sensitive to physics beyond the Standard Model. KM3NeT/ORCA is a neutrino detector optimised for measuring atmospheric neutrinos from a few GeV to around 100 GeV. In this paper, the sensitivity of the KM3NeT/ORCA detector to neutrino decay has been explored. A three-flavour neutrino oscillation scenario, where the third neutrino mass state v3 decays into an invisible state, e.g. a sterile neutrino, is considered. We find that KM3NeT/ORCA would be sensitive to invisible neutrino decays with 1/alpha 3 = T3/m3 < 180 ps/eV at 90% confidence level, assuming true normal ordering. Finally, the impact of neutrino decay on the precision of KM3NeT/ORCA measurements for theta(23), Delta m(31)(2) and mass ordering have been studied. No significant effect of neutrino decay on the sensitivity to these measurements has been found., Commission Européenne FEDER fund, Commission Européenn Marie Curie Program, MCIN/AEI/ 10.13039/501100011033, ID2021-124591NB-C41, -C42, -C43, ERDF, European Union, European Union NextGenerationEU/PRTR, Planes Complementarios I+D+I, ASFAE/2022/023, ASFAE/2022/014, PROMETEO/2020/019, Generalitat Valenciana, GenT, CIDEGENT/2018/034, /2019/043, /2020/049, /2021/23, Junta de Andalucía SOMM17/6104/UGR, P18-FR-5057, EU: MSC program 101025085, European Union, NextGenerationEU, Programa María Zambrano

Funding for open access publishing: Universidad de Granada/CBUA, The first part of this paper concern with the study of the Lorentz force equation [GRAPHICS] in the relevant physical configuration where the electric field (E) over right arrow has a singularity in zero. By using Szulkin's critical point theory, we prove the existence of T-periodic solutions provided that T and the electric and magnetic fields interact properly. In the last part, we employ both a variational and a topological argument to prove that the scalar relativistic pendulum-type equation [GRAPHICS] admits at least a periodic solution when h is an element of L-1(0, T) and G is singular at zero., Universidad de Granada/CBUA, Spanish Government PGC2018-096422-B-I00, PID2021-122122NB-I00, Junta de Andalucia FQM-116, Ministry of Education, Universities and Research (MIUR) 2017JPCAPN_005

The Winograd Schema Challenge (WSC) of pronoun disambiguation is a Natural Language Processing (NLP) task designed to test to what extent the reading comprehension capabilities of language models (LMs) can be compared to those of human subjects. It is generally assumed across the NLP literature that human subjects are capable of resolving this task because of their acquired commonsense knowledge, thus setting a commonsense benchmark for LMs, one which has even been proposed as an alternative to the Turing test. In the context of complex natural language communications, Shannon and Weaver observed that the act of semantic interpretation is subject to semantic noise (Shannon and Weaver, 1964 (1949)). Semantic noise is a constraint that ensues from terms exhibiting variable interpretations across contexts, presenting a challenge to the resolution of tasks such as the WSC. However, the main argument of this paper is that rather than seeing semantic noise as a challenge to otherwise unambiguous communication, it can also be understood as a functional quality of natural language, given that it results in the conceptual negotiation of terms. Failing to theoretically attend to this linguistic matter of fact leads to unintended problems in instances where NLP applications are offered as unbiased or objectively applicable solutions. To address this, this article offers a renewed and original analysis of a series of Winograd Schemas, in order to demonstrate how they are not as straightforwardly solvable by human subjects as is commonly claimed across the NLP literature. The methodology employed is that of historical contextualisation in information theory, and qualitative cultural analysis drawing on examples from a wide variety of recent NLP literature.

Abstract Simple, portable, and low-cost paper-based sensors are alternative devices that have the potential to replace high-cost sensing technologies. The compatibility of the paper base biosensors for both chemical and biochemical accentuates its feasibility for application in clinical diagnosis, environmental monitoring, and food quality monitoring. High concentration of copper in blood serum and urine is associated with diseases like liver diseases, carcinomas, acute and chronic infections, rheumatoid arthritis, etc. Detection of copper concentration can give an early sign of Alzheimer disease. Apart from that genetic Wilson's disease can be detected by evaluating the concentration of copper in the urine. In view of the above advantages, a novel and the highly sensitive paper-based sensor has been designed for the selective detection of Cu2+ ions. The fast and highly sensitive chemiresistive multi-dye system sensor can detect Cu2+ ions selectively in as low as 2.23 ppm concentration. Least interference has been observed for counter ion in the detection of Cu2+. Copper chloride, nitrate, and acetate were used to validate the detection process. This assay provides a very high selectivity of Cu2+ ion over other metal cations such as Na+, Mg2+, Ca2+, etc. The easy preparation and high stability of dye solutions, easy functionalization of the paper-based sensors, high selectivity over other cations, low interference of counter anion, and significantly low detection limit of 2.23 ppm make it an effective Cu2+ ion sensor for real-time application in near future. Graphical Abstract

Genomics; Perivascular space Genòmica; Espai perivascular Genómica; Espacio perivascular Perivascular space (PVS) burden is an emerging, poorly understood, magnetic resonance imaging marker of cerebral small vessel disease, a leading cause of stroke and dementia. Genome-wide association studies in up to 40,095 participants (18 population-based cohorts, 66.3 ± 8.6 yr, 96.9% European ancestry) revealed 24 genome-wide significant PVS risk loci, mainly in the white matter. These were associated with white matter PVS already in young adults (N = 1,748; 22.1 ± 2.3 yr) and were enriched in early-onset leukodystrophy genes and genes expressed in fetal brain endothelial cells, suggesting early-life mechanisms. In total, 53% of white matter PVS risk loci showed nominally significant associations (27% after multiple-testing correction) in a Japanese population-based cohort (N = 2,862; 68.3 ± 5.3 yr). Mendelian randomization supported causal associations of high blood pressure with basal ganglia and hippocampal PVS, and of basal ganglia PVS and hippocampal PVS with stroke, accounting for blood pressure. Our findings provide insight into the biology of PVS and cerebral small vessel disease, pointing to pathways involving extracellular matrix, membrane transport and developmental processes, and the potential for genetically informed prioritization of drug targets. Austrian Stroke Prevention Study (ASPS)/Austrian Stroke Prevention Family Study (ASPS-Fam) (E.H., P.G.G., H.S. and R.S.): We thank the staff and the participants for their valuable contributions. We thank B. Reinhart for her long-term administrative commitment, E. Hofer for the technical assistance in creating the DNA bank, J. Semmler and A. Harb for DNA sequencing and DNA analyses by TaqMan assays, and I. Poelzl for supervising the quality management processes after ISO9001 in the biobanking and DNA analyses. The Medical University of Graz and the Steiermärkische Krankenanstaltengesellschaft support the databank of the ASPS/ASPS-Fam. The research reported in this article was funded by the Austrian Science Fund (FWF) (grant nos. PI904, P20545-P05 and P13180) and supported by the Austrian National Bank Anniversary Fund (grant no. P15435) and the Austrian Ministry of Science under the aegis of the EU Joint Programme–Neurodegenerative Disease Research (JPND): www.jpnd.eu. Epidemiology of Dementia in Singapore (EDIS) (S.H., C.Chen, C.-Y.C., T.Y.W. and W.Z.): The EDIS study is supported by the National Medical Research Council (NMRC), Singapore (NMRC/CG/NUHS/2010 (grant no. R-184-006-184-511), NMRC/CSA/038/2013) and a Ministry of Education Tier 1 grant (no. A-0006106-00-00). Framingham Heart Study (FHS) (J.R.R., A.B., J.J.H., S.L., P.P., C.L.S., Q.Y. and S.Seshadri): This work was supported by the National Heart, Lung and Blood Institute’s FHS Contract (no. N01-HC-25195, no. HHSN268201500001I and no. 75N92019D00031). This study was also supported by grants from the National Institute of Aging (R01 grant nos. AG031287, AG054076, AG049607, AG059421, AG059725; U01 grant nos. AG049505, AG052409) and the National Institute of Neurological Disorders and Stroke (R01 grant no. NS017950). Funding for SHARe Affymetrix genotyping was provided by NHLBI Contract no. N02-HL64278. The computational work reported in this paper was performed on the Shared Computing Cluster which is administered by Boston University’s Research Computing Services. We also thank all the FHS study participants. Internet-based Students’ Health Research Enterprise (i-Share) study (C.B., J.Z., M.M., Q.LG., S. Schilling, Y.-C.Z., A.Tsuchida, M.-G.D., B.M., S.D. and C.T.): The i-Share study is conducted by the Universities of Bordeaux and Versailles Saint-Quentin-en-Yvelines (France). The i-Share study has received funding by the French National Agency (Agence Nationale de la Recherche, ANR), via the Investment for the Future program (grant nos. ANR-10-COHO-05 and ANR-18-RHUS-0002) and from the University of Bordeaux Initiative of Exellence (IdEX). This project has also received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program under grant agreement no. 640643 and from the Fondation pour la Recherche Médicale (grant no. DIC202161236446). Q.L.G. was supported by the Digital Public Health Graduate Program (DPH), a PhD program supported by the French Investment for the Future Program (grant no. 17-EURE-0019). Investigating Silent Strokes in Hypertensives: a Magnetic Resonance Imaging Study (ISSYS) (P.D., C.C. and I.F.-C.): This research was funded by the Instituto de Salud Carlos III (grant nos. PI10/0705, PI14/01535, PI17/02222), cofinanced by the European Regional Development Fund. Lothian Birth Cohort 1936 (LBC1936) (M.L., M.E.B., I.J.D., Z.M., S.M.M., M.C.V.H. and J.M.W.): We thank the LBC1936 cohort members and research staff involved in data collection, processing and preparation. The LBC1936 is supported by Age UK (Disconnected Mind program grant). The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (grant no. MR/K026992/1). The brain imaging was performed in the Brain Research Imaging Centre (www.bric.ed.ac.uk), a center in the SINAPSE Collaboration (www.sinapse.ac.uk) supported by the Scottish Funding Council and Chief Scientist Office. Funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC), the UK Medical Research Council (MRC), the Row Fogo Charitable Trust (M.C.V.H.) and the UK Dementia Research Institute, which receives its funding from the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK (J.M.W.), is gratefully acknowledged. Genotyping was supported by a grant from the BBSRC (no. BB/F019394/1). The Nagahama Study (T.K., S.M., M.O., K.S., Y.T., K.Y., A.Tsuchida, P.B., B.M., M.J., M.-G.D. and F.M.): We are grateful to the Nagahama City Office and nonprofit organization Zeroji Club for their help in conducting the study. This project is supported by operational funds of Kyoto University and the Top Global University Project of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan. We also received a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science, research grants from the Japan Agency for Medical Research and Development for the Practical Research Project for Rare/Intractable Diseases, and the Comprehensive Research on Aging and Health Science for Dementia R&D. We thank C. Galmiche for rating PVS in the validation dataset for the artificial intelligence-based method. The Northern Manhattan Study (NOMAS) (N.D.D., T.J. and R.L.S.): We gratefully acknowledge and thank the NOMAS participants. Funding was awarded through grants from the National Institute of Neurological Disorders and Stroke (R01 grant no. NS 29993) and the Evelyn F. McKnight Brain Institute. Rotterdam Study (M.J.K., F.D., M.W.V., M.A.I. and H.H.H.A.): The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, the Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study (RS I, RS II, RS III) were executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands. The GWAS datasets are supported by the Netherlands Organisation for Scientific Research (NWO) Investments (no. 175.010.2005.011, 911-03-012), the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, the Research Institute for Diseases in the Elderly (grant no. 014-93-015; RIDE2), the Netherlands Genomics Initiative/NWO, the Netherlands Consortium for Healthy Aging, project no. 050-060-810. We thank P. Arp, M. Jhamai, M. Verkerk, L. Herrera, M. Peters and C. Medina-Gomez for their help in creating the GWAS database; and K. Estrada, Y. Aulchenko and C. Medina-Gomez for the creation and analysis of imputed data. H.H.H.A. is supported by ZonMW grant no. 916.19.151. Study of Health in Pomerania (SHIP) (S.F., R.B., A.T., K.W., H.J.G. and U.V.): SHIP is part of the Community Medicine Research net (CMR) (http://www.medizin.uni-greifswald.de/icm) of the University Medicine Greifswald, which is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant no. 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. This study was further supported by the EU-JPND Funding for BRIDGET (grant no. FKZ:01ED1615). H.J.G. has received travel grants and speakers’ honoraria from Fresenius Medical Care, Servier, Neuraxpharm and Janssen Cilag, as well as research funding from Fresenius Medical Care. Sydney Memory and Ageing Study (MAS) & Older Australian Twins Study (OATS) (R.M.T., N.J.A., H.B., J.J., M.P., A.T., J.N.T., P.S.S., W.W., K.A.M. and M.J.W.): Sydney MAS: The Sydney MAS has been funded by three National Health & Medical Research Council (NHMRC) Program Grants (grant nos. ID350833, ID568969 and APP1093083). Collection of WGS data was supported by the NHMRC National Institute for Dementia Research Grants no. APP1115575 and no. APP1115462. MRI scans were processed with the support of NHMRC Project Grants (grant nos. 510175 and 1025243) and an Australian Research Council (ARC) Discovery Project Grant (no. DP0774213) and the John Holden Family Foundation. We also thank the MRI Facility at NeuRA. We thank the participants and their informants for their time and generosity in contributing to this research. We also acknowledge the MAS research team: https://cheba.unsw.edu.au/research-projects/sydney-memory-and-ageing-study. OATS: The OATS study has been funded by an NHMRC and ARC Strategic Award Grant of the Ageing Well, Ageing Productively Program (grant no. 401162); NHMRC Project (seed) Grants (grant nos. 1024224 and 1025243); NHMRC Project Grants (grant nos. 1045325 and 1085606); and NHMRC Program Grants (grant nos. 568969 and 1093083). Collection of WGS data was supported by the NHMRC National Institute for Dementia Research Grants no. APP1115575 and no. APP1115462. This research was facilitated through access to Twins Research Australia, a national resource supported by a Centre of Research Excellence Grant (no. 1079102) from the National Health and Medical Research Council. We thank the participants for their time and generosity in contributing to this research. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/project/older-australian-twins-study) to this study. Three-City Dijon Study (3C-Dijon) (S.D., M.-G.D., S. Schilling, C.T., B.M. and A.M.): This project is supported by a grant overseen by the French National Research Agency (ANR) as part of the ‘Investment for the Future Program’ no. ANR-18-RHUS-0002. It is also supported by a JPND project through the following funding organizations under the aegis of JPND: www.jpnd.eu: Australia, National Health and Medical Research Council; Austria, Federal Ministry of Science, Research and Economy; Canada, Canadian Institutes of Health Research; France, French National Research Agency; Germany, Federal Ministry of Education and Research; the Netherlands, the Netherlands Organisation for Health Research and Development; United Kingdom, Medical Research Council. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement nos. 643417, 640643, 667375 and 754517. The project also received funding from the French National Research Agency (ANR) through the VASCOGENE and SHIVA projects, and from the Initiative of Excellence of the University of Bordeaux (C-SMART project). Computations were performed on the Bordeaux Bioinformatics Center (CBiB) computer resources, University of Bordeaux. Funding support for additional computer resources at the CREDIM (Centre de Recherche et Développement en Informatique Médicale, University of Bordeaux) has been provided to S.D. by the Fondation Claude Pompidou. The Three-City (3C) Study: The 3C Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France and Ministry of Research–INSERM program ‘Cohortes et collections de données biologiques.’ C.T. and S.D. have received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. M.-G.D. received a grant from the ‘Fondation Bettencourt Schueller’. We thank P. Amouyel, U1167 Institut Pasteur de Lille - University of Lille - Inserm, for supporting funding of genome-wide genotyping of the 3C Study. This work was supported by the National Foundation for Alzheimer’s disease and related disorders, the Institut Pasteur de Lille, the labex DISTALZ and the Centre National de Génotypage. We thank A. Boland (CNG) for her technical help in preparing the DNA samples for analyses. UK Biobank (UKB) (M.J.K., F.D., M.W.V., M.A.I., H.H.H.A., A.M. and T.E.): This research has been conducted using the UK Resource under application no. 23509. McGill Genome Center (M.B., P.M., G.B. and M.Lathrop): Work done at the Canadian Center for Computational Genomics was supported by Genome Canada. Data analyses were enabled by computing and storage resources provided by Compute Canada and Calcul Québec. G.B. is supported by the Fonds de Recherche Santé Québec and the Canada Research Chair program. We thank all the participating cohorts for contributing to this study. We thank H. Jacqmin-Gadda, Bordeaux Population Health research center, University of Bordeaux/Inserm U1219 for statistical advice. We thank J. Thomas-Crusells, Bordeaux Population Health Research Center, University of Bordeaux/Inserm U1219, for editorial assistance. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

This paper aims to craft adversarial queries for image retrieval, which uses image features for similarity measurement. Many commonly used methods are developed in the context of image classification. However, these methods, which attack prediction probabilities, only exert an indirect influence on the image features and are thus found less effective when being applied to the retrieval problem. In designing an attack method specifically for image retrieval, we introduce opposite-direction feature attack (ODFA), a white-box attack approach that directly attacks query image features to generate adversarial queries. As the name implies, the main idea underpinning ODFA is to impel the original image feature to the opposite direction, similar to a U-turn. This simple idea is experimentally evaluated on five retrieval datasets. We show that the adversarial queries generated by ODFA cause true matches no longer to be seen at the top ranks, and the attack success rate is consistently higher than classifier attack methods. In addition, our method of creating adversarial queries can be extended for multi-scale query inputs and is generalizable to other retrieval models without foreknowing their weights, i.e., the black-box setting.

Computation offloading is the solution for IoT devices of limited resources and high-cost processing requirements. However, the network related issues such as latency and bandwidth consumption need to be considered. Data transmission reduction is one of the solutions aiming to solve network related problems by reducing the amount of data transmitted. In this paper, we propose a generalized formal data transmission reduction model independent of the system and the data type. This formalization is based on two main ideas: 1) Not sending data until a significant change occurs, 2) Sending a lighter size entity permitting the cloud to deduct the data captured by the IoT device without actually receiving it. This paper includes the mathematical representation of the model, general evaluation metrics formulas as well as detailed projections on real world use cases. This work is supported by the Spanish Research Agency (AEI) (https://doi.org/10.13039/501100011033) under project HPC4Industry PID2020-120213RB-I00.

Aesthetic image analysis is essential for improving the performance of multimedia image retrieval systems, especially from a repository of social media and multimedia content stored on mobile devices. This paper presents a novel method for classifying aesthetic natural scene images by studying the naturalness of image content using statistical features, and reading text in the images using semantic features. Unlike existing methods that focus only on image quality with human information, the proposed approach focuses on image features as well as text-based semantic features without human intervention to reduce the gap between subjectivity and objectivity in the classification. The aesthetic classes considered in this work are (i) Very Pleasant, (ii) Pleasant, (iii) Normal and (iv) Unpleasant. The naturalness is represented by features of focus, defocus, perceived brightness, perceived contrast, blurriness and noisiness, while semantics are represented by text recognition, description of the images and labels of images, profile pictures, and banner images. Furthermore, a deep learning model is proposed in a novel way to fuse statistical and semantic features for the classification of aesthetic natural scene images. Experiments on our own dataset and the standard datasets demonstrate that the proposed approach achieves 92.74%, 88.67% and 83.22% average classification rates on our own dataset, AVA dataset and CUHKPQ dataset, respectively. Furthermore, a comparative study of the proposed model with the existing methods shows that the proposed method is effective for the classification of aesthetic social media images.

In this paper, we examine stable exact relaxations for classes of parametric robust convex polynomial optimization problems under affinely parameterized data uncertainty in the constraints. We first show that a parametric robust convex polynomial problem with convex compact uncertainty sets enjoys stable exact conic relaxations under the validation of a characteristic cone constraint qualification. We then show that such stable exact conic relaxations become stable exact semidefinite programming relaxations for a parametric robust SOS-convex polynomial problem, where the uncertainty sets are assumed to be bounded spectrahedra. In addition, under the corresponding constraint qualification, we derive stable exact second-order cone programming relaxations for some classes of parametric robust convex quadratic programs under ellipsoidal uncertainty sets. Chuong was supported by the National Foundation for Science and Technology Development of Vietnam (NAFOSTED) under grant number 101.01−2020.09. Research of J. Vicente-Pérez was partially supported by the Ministry of Science, Innovation and Universities of Spain and the European Regional Development Fund (ERDF) of the European Commission, Grant PGC2018-097960-B-C22, and by the Generalitat Valenciana, Grant AICO/2021/165.

Economic shocks create insolvency law-making space, generating opportunities for legal reform that may be absent in good times. Policymakers may suddenly acquire a mandate to resource institutions or drive through a change in the law where in good times such reforms were likely to be foiled by interest group capture, or simply unlikely to get sufficient political traction. A crisis, then, is an opportunity for the well-prepared insolvency policymaker. Insolvency rule-making in crisis conditions is, however, plainly also risky. Making best use of the opportunity implies making more than temporary changes to the regime. But design choices made mid-crisis will almost inevitably be influenced by the features of the crisis itself, generating a risk that the result of the reform effort will be distorted law, ill-suited to the achievement of the lawmaker’s objectives in the long run. This paper considers the permanent restructuring law reforms enacted in the UK during the first wave of the Covid-19 pandemic. At first glance, these reforms appear to exemplify the case of the well-prepared policymaker, poised to drive through carefully planned changes to the law when the opportunity arises. On closer inspection, however, a different picture emerges. The permanent measures, which were enacted in a fast-track legislative process, departed from the Government’s pre-pandemic plan in material and undesirable ways. In some cases, these deviations mean that the original objective has not been achieved at all; in others, the objective has been at least partially achieved, but at unnecessary cost. Overall, the UK experience appears to better exemplify the risks of attempting insolvency law reform in a crisis, than the opportunities that a crisis affords to an insolvency policymaker.

Background The prevalence of diabetes is increasing rapidly worldwide. Nurses work collaboratively with multidisciplinary teams to improve diabetes management. Yet, little is known about nurses’ role in nutritional management of diabetes. This study aimed to evaluate nurses’ knowledge, attitudes, and practice (KAP) toward nutritional management of diabetes. Methods This cross-sectional study was conducted with 160 nurses, who were recruited between July 4 and July 18, 2021 from two referral tertiary teaching hospitals in Iran. A validated paper-based self-reported questionnaire was used to assess nurses’ KAP. Data were analyzed using descriptive statistics and multiple linear regression analysis. Results The mean knowledge score of nurses about nutritional management of diabetes was 12.16 ± 2.83, and 61.2% showing a moderate knowledge level on nutritional management of diabetes. The mean attitudes score was 60.68 ± 6.11, with 86.92% of participants demonstrating positive attitudes. The mean practice score of study participants was 44.74 ± 7.81, with 51.9% having a moderate level of practice. Higher knowledge scores were observed among male nurses (B = -7.55, p = 0.009) and those with blended learning as a preferred learning method (B = 7.28, p = 0.029). Having an opportunity to provide education to patients with diabetes during shifts affected nurses’ attitudes positively (B = -7.59, p = 0.017). Practice scores were higher among nurses who perceived themselves competent in the nutritional management of diabetes (B = -18.05, p = 0.008). Conclusion Nurses’ knowledge and practice in the nutritional management of diabetes should be increased to help improve the quality of the dietary care and patient education they provide these patients. Further studies are needed to confirm the results of this study both in Iran and internationally.

The telecare medicine information systems (TMIS) offer a networking channel across public networks to access remote medical services and enable health care professionals and medical staff to make the best clinical decisions and treatments quickly. The verified-based three-party authentication protocol in TMIS for data exchange, authorizations only two patients/users to accumulation their verifiers in the record of authentication server calculated exhausting own password. The authentication scheme will then verify the verifiers of the patients/users and allow them to exchange electronic medical records securely and easily. In this paper, we provide an effective, provably secure, verified-based three-party authentication protocol for data exchange in TMIS utilising fractional chaotic maps. The authentication protocol provided does not use any public server keys and does not require the number of additional messages and rounds for key validation. The projected protocol is appropriate for TMIS because it has stronger security and cheaper communication costs than the corresponding verified-based approach. The development of smart cities can be accelerated with the proposed protocol. Post-print / Final draft

Optimal power flow (OPF) is a complex, highly nonlinear, NP-hard optimization problem, in which the goal is to determine the optimal operational parameters of a power-related system (in many cases a type of smart or micro grid) which guarantee an economic and effective power dispatch. In recent years, a number of approaches based on metaheuristics algorithms have been proposed to solve OPF problems. In this paper, we propose the use of the Cross-Entropy (CE) method as a first step depth search operator to assist population-based evolutionary methods in the framework of an OPF problem. Specifically, a new variant of the Coral Reefs Optimization with Substrate Layers algorithm boosted with CE method (CE+CRO-SL) is presented in this work. We have adopted the IEEE 57-Bus System as a test scenario which, by default, has seven thermal generators for power production for the grid. We have modified this system by replacing three thermal generators with renewable source generators, in order to consider a smart grid approach with renewable energy production. The performance of CE+CRO-SL in this particular case study scenario has been compared with that of well-known techniques such as population?s methods CMA-ES and EPSO (both boosted with CE). The results obtained indicate that CE+CRO-SL showed a superior performance than the alternative techniques in terms of efficiency and accuracy. This is justified by its greater exploration capacity, since it has internally operations coming from different heuristics, thus surpassing the performance of classic methods. Moreover, in a projection analysis, the CE+CRO-SL provides a profit of millions of dollars per month in all cases tested considering the modified version of the IEEE 57-Bus smart grid system., European Commission

Safety-critical infrastructures must operate in a safe and reliable way. Fault tree analysis is a widespread method used for risk assessment of these systems: fault trees (FTs) are required by, e.g., the Federal Aviation Administration and the Nuclear Regulatory Commission. In spite of their popularity, little work has been done on formulating structural queries about and analyzing these, e.g., when evaluating potential scenarios, and to give practitioners instruments to formulate queries on in an understandable yet powerful way. In this paper, we aim to fill this gap by extending [37], a logic that reasons about Boolean. To do so, we introduce a Probabilistic Fault tree Logic is a simple, yet expressive logic that supports easier formulation of complex scenarios and specification of FT properties that comprise probabilities. Alongside, we present, a domain specific language to further ease property specification. We showcase and by applying them to a COVID-19 related FT and to a FT for an oil/gas pipeline. Finally, we present theory and model checking algorithms based on binary decision diagrams (BDDs).

This paper aims to explore the experiences of female leaders considering the interplay of gender, religion, and culture. Drawing on an inductive-qualitative study, the paper examines perceptions regarding the role of religion and cultural norms in women’s ascension into leadership positions in Jordan. The results indicated that Jordanian women leaders adopted an Islamic feminist worldview and did not embrace a liberal nor a socialist/Marxist feminist worldview. Women leaders seemed wanting to claim their religion back from those forces that are reportedly holding their aspirations hostage to monolithic interpretations of religious texts. By constantly referring to their religion, female leaders wanted to be granted spaces of trust and responsibility in leadership positions that they did not see contradictory to the way they understood their faith. The paper provides insights into how women leaders understand prejudicial stereotypes and discrimination in their society, explaining how those are linked to patriarchal socio-cultural traditions emphasizing male control.Other Information Published in: Journal of Business Ethics License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s10551-022-05041-0

Artificial intelligence and mechanical engineering are two mature fields of science that intersect more and more often. Computer-aided mechanical analysis tools, often multibody system software, are very versatile and have revolutionalized many industries. However, as shown by the literature presented in this review, combining the advantages of multibody system dynamics and machine learning creates new and exciting possibilities. For example, the multibody method can assist machine learning by providing synthetic data, while machine learning can provide fast and accurate subsystem models. The intersection of both approaches results in surrogate and hybrid modeling techniques, advanced control algorithms, and optimal design applications. A notable example is the development of autonomous systems for vehicles, robots, and mobile machinery. In our review we have found nontrivial, innovative, and even surprising applications of machine learning and multibody dynamics. This review focuses on applying neural networks, mainly deep learning, in connection with the multibody system method. Over one hundred and fifty papers are covered, and three main research areas are identified and introduced: data-driven modeling, model-based control and estimation, and data-driven control. The paper starts with a primer on machine learning and concludes with future research directions. The main goal is to provide a comprehensive and up-to-date review of existing literature to inspire further research. Post-print / Final draft

Digital solutions have the potential to drastically transform manufacturing operations, but smaller manufacturing businesses (SMEs) have been reluctant to adopt digital solutions due to perceived investment and upskilling costs. The Digital Manufacturing on a Shoestring project was thus established to facilitate the process of digital solution adoption in manufacturing SMEs. To this end, a solution development approach was proposed including a graphical environment to support the design of affordable digital solutions. This paper discusses the concepts and methods underlying this graphical design environment, including its early implementation. A preliminary evaluation is also presented involving industrial user studies with SMEs

This paper examines the design of low-cost digital solutions for manufactur-ing. A set of criteria are established that take into account the limited design-er experience and limited time budget that accompany a low-cost project. Al-ternatives are assessed and a design approach is proposed that addresses these criteria using a set of identified features. Development of the proposed approach is not yet complete, however it already provides a simple, accessi-ble, and streamlined method for implementing low-cost digital solutions.