bluuebunny/crossref_metadata_2025_split huggingface dataset:
Technology Serving Justice
Authors: Lopes Ana Paula 
Published: November 2022

AbstractIn face-to-face interactions, people are constantly providing information through their body movements (Kendon in Body language communication: An international handbook on multimodality in human interaction, pp. 7–27, 2013). Berlin/Boston: De Gruyter Mouton.), in which gestures are included. These kinetic movements transmit two-thirds of what we communicate (Aghayeva in Khazar J Human Soc Sc 53–62, 2011), and ignoring them means disregarding the complexity of the human communication system (Jones and LeBaron in J Commun 52:499–521, 2002). When communicating, humans create signs, and “these signs are made with very many different means (…). They are the expression of the interest of socially formed individuals who, with these signs, realize (…) their meanings” (Kress in Multimodality: A social semiotic approach to contemporary communication. Routledge, p. 10 [2010]). And the way people understand what others mean to transmit can deeply vary. These different interpretations may originate from each person’s experience, prejudice, values, and expectations in life. Therefore, the probability of misunderstanding is vast. In the specific context of a forensic interaction, problems of communication misunderstandings can have serious consequences in a suspect’s or in a defendant’s life. Globally, body movements are not thoroughly considered when it comes to understanding what a suspect or a defendant really wants to declare. However, on some occasions, the correct interpretation of a kinetic movement could contribute to a fairer judicial decision. Through a consistent micro-analysis of interactions, it is possible to create meaning from body movements. The micro-analysis developed by the author showed that body movements can transmit information that had not been verbally uttered. That information has shown to be of great importance in the context of judicial process analysis.
Are ERDF Devoted to Boosting ICT in SMEs Inefficient? Insights Through Different DEA Models
Authors: Henriques Carla , Viseu Clara 
Published: November 2022

AbstractWe evaluated the execution of operational programs (OPs) targeted at increasing the adoption of information and communication technologies (ICT) in small and midsize enterprises (SMEs). As a result, we employed two different data envelopment analysis (DEA) models to evaluate 51 OPs from 16 countries, contemplating data provided to the European Union (EU). All in all, we observed that almost 20% of the OPs (10) achieved efficient procedural outcomes, with the slack-based method (SBM) and with the weighted Russel Directional Distance model (WRDDM), respectively. Two of the OPs most frequently viewed as benchmarks were in Spain (the country that uses “vouchers” simplifying processes), remaining robustly efficient for data perturbations of 5% and 10%. The ‘number of operations supported’ is the metric that necessitates more consideration according to both models. Overall, these findings show the robustness of results with both methods, highlighting a higher discriminatory power of the second method, particularly for inefficient OPs. Finally, the unsuccessful findings attained might be linked to bureaucratic procedures and SMEs’ incapacity to deal with the complicated processes involved in obtaining and implementing European Regional Development Fund (ERDF) proposals. As a result, it is critical to provide the extra help that reduces managerial requirements while also meeting the demands of SMEs.
Python Implementation of the Value-Based DEA Method
Authors: Trigo António , Gouveia Maria , Henriques Carla 
Published: November 2022

AbstractThis paper is aimed at presenting the Python implementation of the Value-Based Data Envelopment Analysis (VBDEA) method, which was designed to evaluate the efficiency of decision-making units (DMUs). This methodological framework explores the links between data envelopment analysis (DEA) and multi-criteria decision analysis (MCDA) and proposes a new perspective on the use of the additive DEA model using concepts from the multi-attribute value theory (MAVT). One of the major strengths of VBDEA over typical DEA methodologies is that it offers information on the main reasons behind DMUs’ (in)efficiency. Additionally, this approach allows straightforwardly ranking of efficient and inefficient DMUs, since it relies on a super-efficiency model. Because of the use of value functions, besides allowing the incorporation of the decision-maker (DM)’s preferences, this methodology easily handles negative or null data. In this context, we illustrate the Python implementation of the method by reproducing the main results obtained by (Gouveia et al., Or Spectrum 38:743–767, 2016), when these authors evaluated the performance of 12 health units in a Portuguese region incorporating management preferences given by real DMs.
Are ERDF Efficient in Strengthening the Switch to a Low-Carbon Economy? Some Insights with Value-Based Data Envelopment Analysis
Authors: Gouveia Maria , Henriques Carla , Amaro Ana 
Published: November 2022

AbstractWe assessed the execution of European Regional Development Funds (ERDF) allocated to promote a Low-carbon economy (LCE) in 23 EU Member States (MS). Each MS is evaluated using the Value-Based Data Envelopment Analysis (VBDEA) method. In the first stage, the efficient MS were identified, and the major reasons that might affect the efficient performance of the ERDF. From the results obtained, 43% of the MS were deemed efficient in the application of ERDF committed to fostering an LCE, and these results were mostly justified by their financial spending rate. At the second stage of the analysis, the changes that needed to be done by inefficient MS to “try and replicate” their efficient counterparts were computed. Furthermore, from the robustness assessment conducted it was possible to show that with thresholds of δ = 5% and δ = 10%, 22% of the MS managed to attain a robust efficiency. While Spain is the leading country in terms of robustness efficiency, Romania (robustly inefficient for δ = 5%), Hungary, and the Czech Republic (the worst in the ranking of inefficient MS) could not apply these funds properly. Given this information, the EU should continue to push policies that secure financial opportunities from engaging in LCE, particularly for MS with limited financial capacities, while still supplying them with improved funding mechanisms and technical expertise.
Firm Competitiveness, Specialisation, and Employment Growth: Territorial Level Relationships
Authors: Fantechi Federico , Fratesi Ugo 
Published: November 2022

AbstractThe concept of competitiveness is today a central element for regional development, European cohesion policies and smart specialisation strategies. Despite being born for firm-level analyses, competitiveness is indeed commonly used at the territorial level, mainly at the regional or urban scale, normally measured with different composite structural indicators. However, since territorial competitiveness is unevenly distributed in space, territorial units smaller than a full NUTS-2 region might be differently competitive and hence suited to implement differentiated cohesion policies and smart specialisation strategies. To test the hypothesis that these firm-level indicators can characterize the intraregional differences in aggregate performance, the paper sets up a meta-analysis framework between these indicators and structural indicators (employment growth and specialisation index) measured at the NUTS-3 level. For the meta-analysis at this novel intraregional level, the paper exploits the Lombardy region as a case study. Lombardy is well suited for the aims of this paper, being a large and competitive European region, whose territory—as well as its labor market—is highly differentiated, from peripheral and mountainous areas to many medium and small cities, second-tier large cities and a large metropolitan area—the city of Milan. All these territories are characterized by different economic and social vocations, but all share the same regional administration. The results of the meta-analysis show that firm-level indicators correlate with the aggregate performance of regions and that the structural measures selected can characterize different territories in different conditions. Hence, the competitiveness of firms seems to translate into aggregate territorial performance at small spatial scales. This implies that territorial specificities are also relevant inside regions and should be considered in designing regional policy interventions, such as those of the Smart Specialisation Strategy (S3).
Smart and Sustainable Scheduling of Charging Events for Electric Buses
Authors: Jarvis Padraigh , Climent Laura , Arbelaez Alejandro 
Published: November 2022

AbstractThe Irish transportation sector currently accounts for more than 30% of the energy related CO2 emissions of the country. Therefore, in order to reach the sustainable goals, the Irish government is working on multiple incentives to promote Electric Vehicles (EV) and infrastructure to decarbonize the sector, e.g., free domestic charging points, tool reductions, and the implementation of electric Buses (eBuses) in the medium to long term. In particular, eBuses operate with rechargeable batteries with a capacity to store approximately 300 kWh (and up to 600 kWh), equivalent to around 29.9 L of diesel, while reaching approx. 200 km. In order to ensure a proper transition from regular diesel buses to eBuses, charging times must be coordinated to ensure each bus has adequate energy to complete their operational route. In this work, we present a framework for an efficient management of renewable energies to charge a fleet of eBuses without perturbing the quality of service. Our framework starts by building a deep learning model for wind power forecasting to predict clean energy time windows, i.e., periods of time when the production of clean energy exceeds the demand of the country. Then, the optimization phase schedules charging events to reduce the use of non-clean energy to recharge eBuses while passengers are embarking or disembarking. The proposed framework is capable of overcoming the unstable and chaotic nature of wind power generation to operate the fleet without perturbing the quality of service. As expected, the size of the batteries does have a positive impact on the percentage of clean energy required to operate large fleets of eBuses. Methods developed in this paper help to mitigate potentially inaccuracies derived the prediction models. Our extensive empirical validation with real instances from Ireland suggests that our solutions can significantly reduce non-clean energy consumed on large datasets.
SSOs’ Role in Facilitating IP Policy Measures
Authors: Bharadwaj Ashish , Devaiah Vishwas H. , Gupta Indranath 
Published: November 2022

AbstractGenerally speaking, standards are adopted to reduce transaction costs for several implementers and increase interoperability among devices and platforms. Standards make our lives as consumers easier. For instance, a Wi-Fi-enabled smartphone device will connect to a Wi-Fi connection regardless of the jurisdiction. It has happened because Wi-Fi is a standard, which has been unanimously adopted by all stakeholders. There are technical standards adopted through several standard setting organizations, and there are standards adopted through market demand, which have evolved with time. Standard setting organizations (SSOs) play a crucial role in operationalizing a standard. The stages through which a standard is operationalized are often fraught with uncertainty, and a lot depends on the internal structure of an SSO. The most significant contributor to the entire process is the IPR policies adopted by each of these SSOs. This chapter provides a glimpse of these IPR policies of SSOs in three different jurisdictions, i.e., Europe, the United States, and India. These policies show their diverse nature and often lead to complex end-results.
Catch-me-if-you-can: the overshoot problem and the weak/inflation hierarchy
Authors: Conlon Joseph P. , Revello Filippo 
Published: November 2022

Abstract
We study the overshoot problem in the context of post-inflationary string cosmology (in particular LVS). LVS cosmology features a long kination epoch as the volume modulus rolls down the exponential slope towards the final minimum, with an energy density that scales as $$ {m}_s^4 $$

m
s
4

. It is a known fact that such a roll admits attractor tracker solutions, and if these are located the overshoot problem is solved. We show that, provided a sufficiently large hierarchy exists between the inflationary scale and the weak scale, this will always occur in LVS as initial seed radiation grows into the tracker solution. The consistency requirement of ending in a stable vacuum containing the weak hierarchy therefore gives a preference for high inflationary scales — an anthropic argument, if one likes, for a large inflation/weak hierarchy. We discuss various origins, both universal and model-dependent, of the initial seed radiation (or matter). One particularly interesting case is that of a fundamental string network arising from brane inflation — this may lead to an early epoch in which the universe energy density principally consists of gravitational waves, while an LVS fundamental string network survives into the present universe.
FGFR2b signalling restricts lineage-flexible alveolar progenitors during mouse lung development and converges in mature alveolar type 2 cells
Authors: Jones Matthew R. , Lingampally Arun , Ahmadvand Negah , Chong Lei , Wu Jin , Wilhem Jochen , Vazquez-Armendariz Ana Ivonne , Ansari Meshal , Herold Susanne , Ornitz David M. , Schiller Herbert B. , Chao Cho-Ming , Zhang Jin-San , Carraro Gianni , Bellusci Saverio 
Published: November 2022

AbstractThe specification, characterization, and fate of alveolar type 1 and type 2 (AT1 and AT2) progenitors during embryonic lung development are poorly defined. Current models of distal epithelial lineage formation fail to capture the heterogeneity and dynamic contribution of progenitor pools present during early development. Furthermore, few studies explore the pathways involved in alveolar progenitor specification and fate. In this paper, we build upon our previously published work on the regulation of airway epithelial progenitors by fibroblast growth factor receptor 2b (FGFR2b) signalling during early (E12.5) and mid (E14.5) pseudoglandular stage lung development. Our results suggest that a significant proportion of AT2 and AT1 progenitors are lineage-flexible during late pseudoglandular stage development, and that lineage commitment is regulated in part by FGFR2b signalling. We have characterized a set of direct FGFR2b targets at E16.5 which are likely involved in alveolar lineage formation. These signature genes converge on a subpopulation of AT2 cells later in development and are downregulated in AT2 cells transitioning to the AT1 lineage during repair after injury in adults. Our findings highlight the extensive heterogeneity of pneumocytes by elucidating the role of FGFR2b signalling in these cells during early airway epithelial lineage formation, as well as during repair after injury.
Sturm-Liouville Boundary Value Problem for a Sea-Breeze Flow
Authors: Marynets Kateryna 
Published: November 2022

AbstractWe present recent results in study of a mathematical model of the Sea-Breeze flow, arising from a general model of the ‘morning glory’ phenomena. Based on analysis of the Dirichlet spectrum of a corresponding Sturm-Liouville problem and application of the Fredholm alternative, we establish conditions of existence/uniqueness of solutions to the given problem.
An integrated data- and capability-driven approach to the reconfiguration of agent-based production systems
Authors: Scrimieri Daniele , Adalat Omar , Afazov Shukri , Ratchev Svetan 
Published: November 2022

AbstractIndustry 4.0 promotes highly automated mechanisms for setting up and operating flexible manufacturing systems, using distributed control and data-driven machine intelligence. This paper presents an approach to reconfiguring distributed production systems based on complex product requirements, combining the capabilities of the available production resources. A method for both checking the “realisability” of a product by matching required operations and capabilities, and adapting resources is introduced. The reconfiguration is handled by a multi-agent system, which reflects the distributed nature of the production system and provides an intelligent interface to the user. This is all integrated with a self-adaptation technique for learning how to improve the performance of the production system as part of a reconfiguration. This technique is based on a machine learning algorithm that generalises from past experience on adjustments. The mechanisms of the proposed approach have been evaluated on a distributed robotic manufacturing system, demonstrating their efficacy. Nevertheless, the approach is general and it can be applied to other scenarios.
The battle of opinion: dynamic information revelation by ideological senders
Authors: Polanski Arnold , Le Quement Mark 
Published: November 2022

AbstractTwo informed and interested parties (senders) repeatedly send messages to an uninformed party (public). Senders face a trade-off between propagating their favoured opinions, possibly by lying, and maintaining a high audience (or market share), as the state is occasionally revealed and lies cause audiences to switch to the competitor. We fully characterize a focal Markov perfect equilibrium of this game and discuss the impact of exogenous parameters on the truthfulness of equilibrium reporting. In particular, we find that senders’ lying propensities are strategic complements so that increasing one sender’s bias decreases both senders’ truthfulness. We also analyse the role of polarization across senders.
An International Continence Society (ICS)/ International Urogynecological Association (IUGA) joint report on the terminology for the assessment and management of obstetric pelvic floor disorders
Authors: Doumouchtsis Stergios K. , de Tayrac Renaud , Lee Joseph , Daly Oliver , Melendez-Munoz Joan , Lindo Fiona M. , Cross Angela , White Amanda , Cichowski Sara , Falconi Gabriele , Haylen Bernard 
Published: November 2022

Abstract
Aims
The terminology of obstetric pelvic floor disorders should be defined and reported as part of a wider clinically oriented consensus.

Methods
This Report combines the input of members of two International Organizations, the International Continence Society (ICS) and the International Urogynecological Association (IUGA). The process was supported by external referees. Appropriate clinical categories and a sub-classification were developed to give coding to definitions. An extensive process of 12 main rounds of internal and 2 rounds of external review was involved to exhaustively examine each definition, with decision-making by consensus.

Results
A terminology report for obstetric pelvic floor disorders, encompassing 357 separate definitions, has been developed. It is clinically-based with the most common diagnoses defined. Clarity and user-friendliness have been key aims to make it usable by different specialty groups and disciplines involved in the study and management of pregnancy, childbirth and female pelvic floor disorders. Clinical assessment, investigations, diagnosis, conservative and surgical treatments are major components. Illustrations have been included to supplement and clarify the text. Emerging concepts, in use in the literature and offering further research potential but requiring further validation, have been included as an Appendix. As with similar reports, interval (5–10 year) review is anticipated to maintain relevance of the document and ensure it remains as widely applicable as possible.

Conclusion
A consensus-based Terminology Report for obstetric pelvic floor disorders has been produced to support clinical practice and research.
Modelling optimal lockdowns with waning immunity
Authors: Goenka Aditya , Liu Lin , Nguyen Manh-Hung 
Published: November 2022

AbstractThis paper studies continuing optimal lockdowns (can also be interpreted as quarantines or self-isolation) in the long run if a disease (Covid-19) is endemic and immunity can fail, that is, the disease has SIRS dynamics. We model how disease related mortality affects the optimal choices in a dynamic general equilibrium neoclassical growth framework. An extended welfare function that incorporates loss from mortality is used. In a disease endemic steady state, without this welfare loss even if there is continuing mortality, it is not optimal to impose even a partial lockdown. We characterize how the optimal restriction and equilibrium outcomes vary with the effectiveness of the lockdown, the productivity of working from home, the rate of mortality from the disease, and failure of immunity. We provide the sufficiency conditions for economic models with SIRS dynamics with disease related mortality–a class of models which are non-convex and have endogenous discounting so that no existing results are applicable.
AChE-based electrochemical biosensor for pesticide detection in vegetable oils: matrix effects and synergistic inhibition of the immobilized enzyme
Authors: Tsounidi Dimitra , Soulis Dionysios , Manoli Fotini , Klinakis Apostolos , Tsekenis George 
Published: November 2022

AbstractEnzyme-based electrochemical biosensors have been widely deployed for the detection of a range of contaminants in different food products due to their significant advantages over other (bio)sensing techniques. Nevertheless, their performance is greatly affected by the sample matrix itself or by the matrix they are presented with in pretreated samples, both of which can impact the accuracy as well as the sensitivity of the measurements. Therefore, and in order to acquire reliable and accurate measurements, matrix effects and their influence on sensor performance should be taken into consideration. Herein, acetylcholinesterase (AChE)-modified electrochemical sensors were employed for the detection of pesticides in vegetable oils. Sensor interrogation with pretreated oil samples, spiked with carbofuran, revealed the inhibitory potential of the extracted matrix varies between different types of vegetable oil and their fatty acid content. In addition, synergies between the extracted matrix from different types of vegetable oils and the carbamate pesticide, carbofuran, were observed, which led to significant deviations of the sensor’s performance from its anticipated behavior in buffered solution. Taking the aforementioned into consideration, appropriate calibration curves for each type of vegetable oil were drafted, which allowed for the highly reproducible determination of different pesticide concentrations in pretreated real samples. Collectively, a better understanding of AChE inhibition by single or multiple contaminants present in vegetable oils was gained, which can find many applications in numerous fields, ranging from sensor development to the design of new pesticides and medicinal products.