Showing papers by "University of Patras published in 2023"

The Imprint of Exposome on the Development of Atopic Dermatitis across the Lifespan: A Narrative Review

Abstract: Atopic dermatitis (AD) is a chronic inflammatory skin condition that affects more than 200 million people worldwide, including up to 20% of children and 10% of the adult population. Although AD appears frequently in childhood and often continues into adulthood, about 1 in 4 adults develop the adult-onset disease. The prenatal period, early childhood, and adolescence are considered critical timepoints for the development of AD when the exposome results in long-lasting effects on the immune system. The exposome can be defined as the measure of all the exposures of an individual during their lifetime and how these exposures relate to well-being. While genetic factors could partially explain AD onset, multiple external environmental exposures (external exposome) in early life are implicated and are equally important for understanding AD manifestation. In this review, we describe the conceptual framework of the exposome and its relevance to AD from conception and across the lifespan. Through a spatiotemporal lens that focuses on the multi-level phenotyping of the environment, we highlight a framework that embraces the dynamic complex nature of exposome and recognizes the influence of additive and interactive environmental exposures. Moreover, we highlight the need to understand the developmental origins of AD from an age-related perspective when studying the effects of the exposome on AD, shifting the research paradigm away from the per se categorized exposome factors and beyond clinical contexts to explore the trajectory of age-related exposome risks and hence future preventive interventions.

Estimation of secondary organic aerosol formation parameters for the Volatility Basis Set combining thermodenuder, isothermal dilution and yield measurements

Abstract: Abstract. Secondary organic aerosol (SOA) is a major fraction of the total organic aerosol (OA) in the atmosphere. SOA is formed by the partitioning onto pre-existent particles of low vapor pressure products of the oxidation of volatile, intermediate volatility, and semivolatile organic compounds. Oxidation of the precursor molecules results in a myriad of organic products making the detailed analysis of smog chamber experiments difficult and the incorporation of the corresponding results into chemical transport models (CTMs) challenging. The volatility basis set (VBS) is a framework that has been designed to help bridge the gap between laboratory measurements and CTMs. The parametrization of SOA formation for the VBS has been traditionally based on fitting yield measurements of smog chamber experiments. To reduce the uncertainty of this approach we developed an algorithm to estimate the SOA product volatility distribution, effective vaporization enthalpy, and effective accommodation coefficient combining SOA yield measurements with thermograms (from thermodenuders) and areograms (from isothermal dilution chambers) from different experiments and laboratories. The algorithm is evaluated with “pseudo-data” produced from the simulation of the corresponding processes assuming SOA with known properties and introducing experimental error. One of the novel features of our approach is that the proposed algorithm estimates the uncertainty of the predicted yields for different atmospheric conditions (temperature, SOA concentration levels, etc.). The predicted yield uncertainty is significantly less than that of the estimated volatility distributions for all conditions tested.

Greek Topicalization: How do properties move?

Abstract: This paper argues that Greek topicalization is an A’-movement dependency which is headed by a property-denoting phrase (i.e., of type <e,t>), dislocated to a left peripheral topic position (spec,TopicP). Crucially, at the syntax-semantics interface, the dislocated topic phrase must undergo total reconstruction, which means that topicalization is obligatorily mapped to a logical form which only comprises the copy of the topic phrase in the thematic position. Through the study of Greek topicalization I examine the syntax-semantics mapping for movement chains that involve property-phrases (type <e,t>), showing that such a movement chain could not be mapped onto an individual variable or a property-denoting trace. More generally, the present paper provides novel empirical evidence for the claim that property denoting traces do not exist in natural languages (Poole 2017; 2022). As a result, topicalization resorts to total reconstruction as the only logical form which can be directly interpreted by the semantic component.

AM Applications

Abstract: In this chapter, a more holistic view of Additive Manufacturing (AM) will be presented, integrating all the previous modules in a practical way. Additionally, AM will be presented from a business perspective, focusing on the different phases of product development, encapsulating the entire supply chain of AM equipment, operation, and end-of-life toward a successful business plan. Furthermore, applications of AM in industrial cells and lines will be discussed. Also, specific AM case studies will be considered. Finally, Industry 4.0 capabilities and decentralized manufacturing applications will be presented.

Asynchronous phenological dynamics in a deciduous plantation and their implications for the seasonal and annual carbon dynamics

Abstract: Forest phenological dynamics shape the underlying biogeophysical processes and impact the carbon balance from the seasonal to inter-annual time scales. Disentangling the phenological phases of the forest components (e.g., overstory and understory), could provide novel insights on ecosystem response to climate change. This quantitative description is particularly important not only for natural ecosystems but could also assist in the design of restoration and reclamation projects. Here, focusing on a deciduous plantation (black locust, Robinia pseudoacacia L.) in a degraded land of Northern Greece and combining multiyear field observations with detailed ecohydrological modeling, we assessed the ecosystem-level carbon dynamics and its individual components from seasonal to decadal time scales. Site-level long-term (>10 yr) biophysical processes were characterized with eddy covariance measurements together with detailed meteorological and soil data. In addition, ecosystem-level phenological dynamics were quantified with timelapse imagery available at the site and satellite remote sensing. These observations were used to parameterize and validate the ecohydrological model T&C which was then used for numerical experiments. Numerical simulations allowed us to disentangle the contribution of the overstory and understory to the overall carbon dynamics at the site, a separation hard to be done by field measurements alone. The phenological phases of the understory (perennial grass) and the canopy (black locust) were found to be asynchronous, with the former reaching its peak in late winter and the latter in late summer. Ground shading by black locust together with drying of the upper soil layer during the summer months lead to the observed mismatch, with grass activity only in winter and early spring. Yet, the asynchrony in the phenological phases of understory and canopy vegetation results in overall ecosystem-dynamics that are non-negligible over winter, despite the deciduous phenology of black locust. Quantitative description of the interplay between phenological cycles of the forest components enhances our process understanding including their interactions and intra- and inter-annual dynamics. Moreover, for species widely used in forest restoration projects, like the black locust, quantifying such interplays, where the forest is more than the tree, it is important for robust carbon balance estimations.

Towards a Transformative and Reflexive Curriculum

Abstract: The development of a diversity-sensitive curriculum remains the biggest challenge for inclusive quality education which seeks to enhance learners’ transformative learning and agency. Highly differentiated curricula embraced diversity, build on meaningful knowledge production processes, tackle challenging global issues, support reflexive learning, and aim at developing an intercultural growth mindset. Learners, when operate in inclusive and transformative learning environments, can become versatile and reflexive creators as well as responsive citizens holding a clear commitment to social justice. Thus, acquiring ethical entrepreneurialism and global citizenship skills is an important goal for curriculum differentiation (e.g., modifying content, pedagogical processes, learning products, and learning environment). This chapter focuses on differentiated curriculum intervention in seven Greek early childhood schools. Differentiated learning and informed decision-making were highly responsive to real-life conditions leading to novel pathways of meaning-making and experiencing. Scaffolded repertoires negotiated complex topics such as refugeeness, war effects, forced human mobility, and refugee integration. Curriculum content and multimodal materials are aligned to academic learning as well as learners’ lifeworlds, learning styles, and interests. Finally, participatory visual arts approach has proven a useful aid to sustain children’s active engagement throughout this intervention. At the end, a public visual arts exhibition allowed children to become public narrators and advocates, express their emotions, and try to be responsive to enhance refugee integration.

Explainable Feature Extraction and Prediction Framework for 3D Image Recognition Applied to Pneumonia Detection

Abstract: Explainable machine learning is an emerging new domain fundamental for trustworthy real-world applications. A lack of trust and understanding are the main drawbacks of deep learning models when applied to real-world decision systems and prediction tasks. Such models are considered as black boxes because they are unable to explain the reasons for their predictions in human terms; thus, they cannot be universally trusted. In critical real-world applications, such as in medical, legal, and financial ones, an explanation of machine learning (ML) model decisions is considered crucially significant and mandatory in order to acquire trust and avoid fatal ML bugs, which could disturb human safety, rights, and health. Nevertheless, explainable models are more than often less accurate; thus, it is essential to invent new methodologies for creating interpretable predictors that are almost as accurate as black-box ones. In this work, we propose a novel explainable feature extraction and prediction framework applied to 3D image recognition. In particular, we propose a new set of explainable features based on mathematical and geometric concepts, such as lines, vertices, contours, and the area size of objects. These features are calculated based on the extracted contours of every 3D input image slice. In order to validate the efficiency of the proposed approach, we apply it to a critical real-world application: pneumonia detection based on CT 3D images. In our experimental results, the proposed white-box prediction framework manages to achieve a performance similar to or marginally better than state-of-the-art 3D-CNN black-box models. Considering the fact that the proposed approach is explainable, such a performance is particularly significant.

Α Behavior Trees-based architecture towards operation planning in hybrid manufacturing

Abstract: In modern manufacturing, the capability of process scheduling and task allocation is a major feature for the proper organization of complex production schedules. More particularly, the case of human-robot collaboration within assembly lines is considered as a quite challenging field, where an efficient process scheduling can reduce products’ delivery times, increasing in parallel its quality. The purpose of this paper is to propose an approach focusing on operation planning for Human-Robot Collaborative processes that consist of many tasks and multiple resources, such as the assembly of large-scale parts. The implementation of the Human-Robot Operation Planning (HROP) module is presented, which aim at the allocation of multiple operations between multiple and different types of resources. This development’s main pillar is a dynamic decision-making logic that combines both constraints, that exclude resources from the evaluation, as well as mathematical criteria, that provide finally a specific solution. The HROP particularity is that it is developed under the Behavior Trees (BT) architecture. For the validation of the proposed approach, a case study under a real industrial environment of the automotive industry is presented, based on the assembly of large-scale parts, such as buses, in a hybrid cell of both human operators and multi-type robots.

Sulfated Hyaluronan: A Novel Player in Cancer Therapeutic and Bioengineering Approaches

Abstract: Hyaluronan (HA) is a non-sulfated glycosaminoglycan ubiquitously distributed in cells and tissues. It plays a pivotal role in several cellular functions, such as proliferation and migration, with its binding to its receptors CD44 and RHAMM triggering various signaling cascades. HA modifications regulate cellular responses in a different manner compared to unmodified HA fragments. The modified fragments are synthesized through a variety of strategies and have several applications, including therapeutic strategies against cancer, enhancement of wound healing and osteogenesis, as well as preparation of innovative polymer matrices. Notably, sulfated HA (sHA) shows promising results in cancer treatment, exhibiting anti-cancer effects through different modes of action, while also interfering with the binding of matrix effectors controlling extracellular matrix remodeling. Additionally, sHA can be used in biomedical polymer matrices and different tissue-engineering applications to enhance bone formation when used for biomaterial coating. In this chapter we present the processes that sHA could contribute in for the development of future interventions and innovative bioengineering approaches.

Ultrafast Photophysics of Regioisomeric Triphenylamine Dyes Having Dipolar D‐π‐A‐A and Octupolar D‐(π‐A‐A) ₃ Character with a Benzothiazole Unit in Matched or Mismatched Orientation

Abstract: Benzothiazole is among prominent electron-withdrawing heteroarene moieties used in a variety of π-conjugated molecules. Its relative orientation with respect to the principal dipole vector(s) of chromophores derived thereof is crucial, affecting photophysical and nonlinear optical properties. Here we compare the photophysics and ultrafast dynamics of dipolar and octupolar molecules comprising a triphenylamine electron-donating core, ethynylene π-conjugated linker(s) and benzothiazole acceptor(s) having the matched or mismatched orientation (with respect to the direction of intramolecular charge transfer), while a carbaldehyde group is attached as an auxiliary acceptor. Among chromophores without the auxiliary acceptor, stronger fluorescence solvatochromism and faster excited state dynamics are exhibited for the derivatives with the mismatched geometry. On the contrary, introduction of the auxiliary acceptor to the benzothiazole unit enhances the intramolecular charge transfer ICT (featuring ultrafast dynamics of the excited state) for the matched geometry. The data confirm the crucial role of the relative orientation of asymmetric heteroaromatic unit (regioisomeric effect) in dipolar as well as in multipolar molecules in tuning linear and nonlinear optical properties as well as excited state dynamics.

Transitions between use/land cover classes and burnt areas in Europe

Abstract: Wildfires play a fundamental role in Land Use/Land Cover (LULC) change dynamics by burning vegetation in forested and rural areas and by affecting human infrastructures. Conversely, LULC can disturb fire regime by altering vegetation cover, conditioning subsequent transitions, and acting on fuel loads and continuity. Though there is an evident mutual influence between wildfires and LULC changes, a rigorous quantification of their reciprocal effects in Europe has never been performed before. To fill this gap, in the present study we developed a methodology allowing the evaluation of different indicators for the quantitative assessment and a better understanding of the transitions among LULC classes and Burnt Areas (BA) that occurred in Europe within the last two decades (2000 – 2020).Our analyses revealed that the two LULC classes which had experienced major changes were Forests (44%), and Scrubs and/or herbaceous vegetation associations (32%). As a general trend, within the five European Mediterranean Countries more prone to wildfires (Portugal, Spain, France, Italy, and Greece) we found a decrease in the classes Forests and Arable land, and an increase in Scrubs and/or herbaceous vegetation associations, suggesting the impact of wildfires in shaping the natural and rural landscape. This assumption was better evaluated and confirmed by the following analyses, performed at both the European and national levels. Results showed that most of the BA have occurred in Forests (42% for the entire Europe), with a predominance in Coniferous forests; the subsequent transitions from BA were generally to Transitional woodland/shrub or again to BA. This last indicates a high frequency of wildfires in a given area, while the first transition can be partially due to the regeneration/recolonization of the vegetation after a wildfire event. Outcomes for the single countries followed almost the same trend.Overall, our results confirm the existence of a strong relationship between wildfires and LULC changes in Europe, which have been quantified in the present study. These findings are in line with previous research and provide a deep insight into the process at the global and local levels, paving the way for further analyses on fire intensity and frequency with coupled environmental elements of land cover and climate changes.

Energy Release Rate and Mode Partitioning of Moment-Loaded Fracture Tests on Layered Beams with Bending–Extension Coupling and Hygrothermal Stresses

Abstract: In the present chapter, the analyticalAnalytical framework proposed in Chap. 2 is enriched, and the study of the fracture toughnessFracture toughness of the titanium-to-CFRPTitanium-to-Carbon Fiber-Reinforced Polymer (CFRP) joint presented in Chaps. 3 and 4 is extended. New closed-formClosed-form expressions are derived for the ERREnergy release rate (ERR) and MMMode Mixity (MM) of interfacialInterfacial fracture tests on layered beamsBeam with BEC and RHTSResidual (Hygro)Thermal Stresses (R[H]TS), loaded with unevenUneven bending momentsMoment. The analyticalAnalytical model uses Timoshenko beamTimoshenko (beam) kinematics, a semi-rigidSemi-rigid interfaceInterface model, and the crack closure integral for mode partitioningMode partitioning. The proposed expressions are validated via the finite element method in two typical examples of metal-to-compositeMetal-to-composite joints. In addition, experiments employing the DCBDouble cantilever beam (DCB)-UBM test setup are performed in a titanium-to-CFRPTitanium-to-Carbon Fiber-Reinforced Polymer (CFRP) adhesive jointAdhesive joint, and the new analyticalAnalytical expressions are used to achieve data reductionData reduction. We demonstrate that the effect of RTS on the ERREnergy release rate (ERR) and MMMode Mixity (MM) of the metalMetal/compositeComposite interfacesInterface can be non-negligible and, thus, should be considered in the design and analysis of such structures. The proposed formulae serve as a DRS to determine fracture toughnessFracture toughness and MMMode Mixity (MM) of momentMoment-loaded tests on arbitrarily layered beamsBeam with BECBending–Extension Coupling (BEC) and hygrothermalHygrothermal stresses.

Performance Evaluation of Standard and Modified OLSR Protocols for Uncoordinated UAV Ad-Hoc Networks in Search and Rescue Environments

Abstract: Widespread usage of unmanned aerial vehicles (UAVs) in new and emerging applications needs dynamic and adaptive networking. The development of routing protocols for UAV ad hoc networks faces numerous issues because of the unique characteristics of UAVs, such as rapid mobility, frequent changes in network topology, and limited energy consumption. The Optimized Link State Routing (OLSR) protocol seems to be a promising solution as it offers improved delay performance. It is expected that OLSR will satisfy the strict demands of real-time UAV applications such as “search and rescue” (SAR) missions as it involves the most recent update of routing information. The classical OLSR routing protocol and its enhanced versions, D-OLSR, ML-OLSR, and P-OLSR, use different techniques to make an appropriate decision for routing packets. These routing techniques consider the quality of a wireless link, type of antenna, load, and mobility-aware mechanism to select the best UAV to send the message to the destination. This study evaluates and examines the performance of the original and modified OLSR routing protocols in UAV ad hoc networks for three SAR scenarios: (1) increasing mobility, (2) increasing scalability, and (3) increasing the allowed space of UAVs. It analyzes and validates the performance of the four OLSR-based routing protocols. It determines the best OSLR routing protocol by taking into account the packet delivery ratio, latency, energy consumption, and throughput. The four routing protocols and the SAR scenarios were simulated using NS-3.32. Based on the simulation results, ML-OLSR outperforms OLSR, D-OLSR, and P-OLSR in the considered measures.

Antimicrobial Proteins and Peptides as a Promising Weapon to Promote Food Safety Under the One Health Approach

Abstract: In the One Health approach there is a necessity for safer foods with an extended shelf life. The scientific community is underway developing novel, low cost, efficient, and environmental-friendly antimicrobials that will be better suited for human and animal consumption. In this book chapter, we focus on the application of antimicrobial proteins and peptides (APPs) to combat spoilage and pathogenic microorganisms in foods. APPs may constitute an extended toolbox of natural biopreservatives for the food industry. Herein we present the different schemes of APPs classification, along with examples of proof-of-concept studies demonstrating their efficiency in different food models of animal and plant origin.

Synergy of accelerometer, GNSS, InSAR and TLS measurements in the light of PROION Project

Abstract: As infrastructure faces the consequences of climate change there is an urgent need for monitoring methodologies that can provide accurate and timely information to the stakeholders and decision makers in order to mitigate the risk and ensure the safety. According to the World Meteorological Organization the last decade has been recorded as the warmest period in human history. As a consequence, particularly high temperatures and frequent weather extremes (drought, floods, etc.) jeopardize the infrastructure safety. At the same time, the need for reliable, cost-efficient and globally applied infrastructure monitoring methodologies is even more crucial in areas with high seismicity and or volcanic activity.In this framework the current project, named “PROION”, focuses on the infrastructure monitoring in the “Enceladus” Hellenic supersite. Τhis very active tectonic and seismic area includes geographically:the urban centers of Athens, Corinth and Patras (> 50% of the country's population), some of the most important archaeological monuments (Ancient Olympia and Mycenae) and some very important infrastructures such as Mornos and Evinos dams, Rio-Antirrio Bridge etc. The Enceladus Supersite area presents the highest seismicity in Europe, the highest recorded ground acceleration in Greece(0.77g) and a very high frequency of landslides.The aim of the project is the development of a platform for the continuous monitoring of high importance infrastructures such as public buildings and dams. The methodology combines instrumental and remote sensing measurements along with fuzzy logic networks methods and machine learning algorithms. Specifically, measurements obtained by three-axis accelerometers, low cost GNSS receivers and Persistent Scatterer Interferometry are fused and validated with high-precision 3D reference data derived from TLS surveys and UAV campaigns. The processing is based on soft computing algorithms while very accurate deformation maps are utilized for making decision about the current and the future state of each infrastructure. “PROION” project is financially supported by the European Union and the Hellenic government. «Acknowledgment:  This research has been co‐financed  by the European Union and Greek  national funds  through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call  RESEARCH – CREATE – INNOVATE (project code: T2EΔK-02396 Μultiparametric monitoring platform with micro-sensors of eNceladus hellenIc supersite)».

Probabilistic modelling of water distribution networks and resilient reduction of leakages: Large scale application to the city of Patras in western Greece

Abstract: Modeling of leakages in Water Distribution Networks (WDNs) is a vital task for all water related professionals and experts towards the development of management practices and strategies, which aim at the reduction of water losses (leakages) and the associated financial cost and environmental footprint. In the current work we develop an integrated, theoretically founded, and easily applicable probabilistic framework for resilient reduction of leakages in WDNs, which combines: a) a set of conceptually and methodologically different probabilistic approaches for minimum night flow (MNF) estimation in WDNs based on statistical metrics (Serafeim et al., 2021 and 2022a), and b) a combination of statistical clustering and hydraulic modeling techniques for the rigorous and user unbiased partitioning of WDNs into pressure management areas (PMAs) or district metered areas (DMAs), which seeks for minimization of leakages while maintaining an acceptable level of the network’s hydraulic resilience (Serafeim et al., 2022b). The efficiency of the introduced framework is tested via a large-scale real-world application to the water distribution network of the City of Patras, the largest smart water network (SWN) in Greece, which covers an area of approximately 27 km2 and serves more than 213000 consumers (based on data from the Hellenic Statistical Authority and the Municipality of Patras), with more than 700 km of pipeline grid (mainly HDPE and PVC pipes).AcknowledgementsThe research work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (Project Number: 1162).ReferencesSerafeim, A.V., Kokosalakis, G., Deidda, R., Karathanasi I. and Langousis A (2021) Probabilistic estimation of minimum night flow in water distribution networks: large-scale application to the city of Patras in western Greece, Stoch. Environ. Res. Risk. Assess., https://doi.org/10.1007/s00477-021-02042-9.Serafeim, A.V., G. Kokosalakis, R. Deidda, I. Karathanasi and A. Langousis (2022) Probabilistic Minimum Night Flow Estimation in Water Distribution Networks and Comparison with the Water Balance Approach: Large-Scale Application to the City Center of Patras in Western Greece, Water, 14, 98, https://doi.org/10.3390/w14010098.Serafeim, A.V., G. Kokosalakis, R. Deidda, N. Th. Fourniotis and A. Langousis (2022) Combining statistical clustering with hydraulic modeling for resilient reduction of water loses in water distribution networks: Large scale application to the city of Patras in Western Greece, Water, 14(21), 3493. https://doi.org/10.3390/w14213493. 

Response to Referee #1

Abstract: Abstract. The off-line Aerosol Mass Spectrometry (AMS) technique is a useful tool for the source apportionment of organic aerosol (OA) in areas and periods during which an AMS is not available. However, the technique is based on the extraction of aerosol samples in water, while several atmospheric OA components are partially or fully insoluble in water. In this work an improved off-line technique was developed and evaluated in an effort to capture most of the partially soluble and insoluble organic aerosol material, reducing significantly the uncertainty of the corresponding source apportionment. A major advantage of the proposed approach is that no corrections are needed for the off-line analysis to account for the limited water solubility of some OA components. The improved off-line AMS analysis was tested in three campaigns: two during winter and one during summer. Collocated on-line AMS measurements were performed for the evaluation of the off-line method. Source apportionment analysis was performed separately for the on-line and the off-line measurements using Positive Matrix Factorization (PMF). The PMF results showed that the fractional contribution of each factor to the total OA differed between the on-line and the off-line PMF results by less than 15 %. The differences in the AMS spectra of the factors of the two approaches could be significant suggesting that the use of factor profiles from the literature in the off-line analysis may lead to complications. Part of the good agreement between the on-line and the off-line PMF results is due to the ability of the improved off-line AMS technique to capture a bigger part of the OA, including insoluble organic material. This was evident by the significant fraction of submicrometer suspended insoluble particles present in the water extract, and by the reduced insoluble material on the filters after the extraction process. More than half of the elemental carbon (EC) was on average missing from the filters after the water extraction. Significant EC concentrations were measured in the produced aerosol that was used as input to the AMS during the off-line analysis.

A dialectometric approach to inner Asia Minor Greek: Comparisons and associations between linguistic levels

Abstract: Abstract Even though dialectometric approaches have significantly contributed to the development of dialectology in the last few decades, no relevant analyses have ever been performed on Modern Greek dialects. This article attempts to fill this gap by using dialectometric techniques to measure the degrees of association between aggregate morphological, phonological, and syntactic differences in nineteen varieties of inner Asia Minor Greek (i.e. of Cappadocian, Pharasiot, and Silliot). Our methods include correlations (between pairs of linguistic levels and between linguistic levels and geography) as well as multidimensional scaling and cluster analysis (of the whole dataset as well as of the linguistic levels), which allow us, on the one hand, to draw conclusions about the associations of linguistic levels and the distributions of dialects and, on the other hand, to directly compare our results to those coming from previous dialectometric studies and Greek dialectology. Results show that, although the complete dataset, phonology, and morphology yield—in some instances—similar patterns (i.e. high correlations between them as well as with geography, high agreement of dialect classifications), the level of syntax deviates the most, which is interpreted as a tendency to form larger dialect areas. Our findings are consistent with patterns found in earlier large-scale studies in dialectometry, but they only partially confirm the classifications of Greek dialectology.

A comparative study of SMAP and ASCAT satellite soil moisture products with cosmic-ray neutron sensing and in-situ data in a Mediterranean setting

Abstract: Obtaining Soil Moisture Content (SMC) over large scales is of key importance in several environmental and agricultural applications especially in the context of climate change and transition to digital farming. Remote sensing (RS) has a demonstrated capability in retrieving SMC over large areas with several operational products already available at different spatiotemporal resolutions. At the same time, cosmic-ray neutron sensing is a recently emerged approach in retrieving high temporal resolution SMC at intermediate spatial scales. The present study conducts an intercomparison between different RS-based soil moisture products, daily SMC retrievals from a cosmic-ray neutron sensor (CRNS) station and a network of in situ SoilNet wireless sensors installed at the Pinios Hydrologic Observatory ILTER site in central Greece for a time period of 2018-2019. The RS-based soil moisture products included herein are from NASA’s Soil Moisture Active Passive (SMAP) and Metop-A/B Advanced Scatterometer (ASCAT) satellite missions. The methodological workflow adopted includes standardized validation procedures employing a series of statistical measures to quantify the agreement between the different RS-based soil moisture products, CRNS-based SMC and the SoilNet ground truth data. Our study results contribute towards global efforts aiming at exploiting CRNS data in the context of soil moisture retrievals and their potential synergies with RS-based products. Furthermore, our findings provide valuable insights into assessing the capability of CRNS at retrieving more accurate SMC estimates at arid and semi-arid environments such as those found in the Mediterranean basin, while supporting also ongoing global validation efforts.Keywords: Cosmic Ray Neutron Sensors; SMAP; ASCAT; SoilNet; Soil Moisture Content

Non-dynamic and multiphase CT protocols for parathyroid glands imaging: a review of technical parameters, radiation dose and diagnostic accuracy

Abstract: INTRODUCTION: Our purpose was to review the scientific literature and collect information regarding clinical and technical parameters of different single- or multiphase CT protocols, their diagnostic performance and patient dose during parathyroid imaging.EVIDENCE ACQUISITION: PubMed and Scopus databases were searched for studies investigating the diagnostic performance of CT in detecting parathyroid lesions and the corresponding patients’ dose. The following information was retrieved for each article: CT system, number, combination and time interval between phases, scanning length, sensitivity, specificity, accuracy, positive and negative predictive values, contrast enhancement in Hounsfield Units (HUs), technical and exposure parameters, and dose indices. Fifty studies published during the last sixteen years (2005-2021) were reviewed.EVIDENCE SYNTHESIS: A large discrepancy in the number and combination of phases, as well as clinical and technical parameters of the CT protocols was indicated. The variations in patients’ doses are mainly due to scanners’ technology, number and combination of phases, the extent of scanning length, technical parameters (tube voltage, tube current modulation, pitch, reconstruction algorithms), and patient-related parameters. Technical parameters are not always adjusted appropriately to the clinical question or patient size. These variations indicate a large potential to optimize dose during parathyroid imaging without compromising diagnostic performance. The potential is to decrease the number of phases or use low tube voltage protocols, tube current modulation, iterative reconstruction, and reduce the scanning length during some phases.CONCLUSIONS: The reporting results could inform researchers about the current status of CT parathyroid imaging and guide their future efforts to optimize both patients’ dose and corresponding image quality.

Post-Traumatic Stress as a Psychological Effect of Mild Head Injuries in Children

Abstract: Background: Head trauma is one of the most common pediatric emergencies. While the psychological effects of severe head injuries are well studied, the psychological consequences of mild head injuries often go overlooked. Head injuries with a Glasgow Coma Scale score of 13–15, with symptoms such as headache, vomiting, brief loss of consciousness, transient amnesia, and absence of focal neurological signs, are defined as mild. The aim of this study is to evaluate the stress of children with mild head injuries and their parents’ relevant perception during the early post-traumatic period. Methods: This is a prospective cross-sectional study on a cohort of children with mild head injuries and their parents. Two questionnaires were implemented, the Child Trauma Screening Questionnaire (CTSQ) which was compiled by the children, and the Children’s Revised Impact of Event Scale (CRIES-13), compiled by their parents. Both questionnaires are widely used and reliable. The first presents an excellent predictive ability in children with a risk of post-traumatic stress disorder, while the second is a weighted self-completed detecting instrument for the measurement of post-traumatic stress in children and adolescents, with a detailed evaluation of their reactions to the traumatic incident. The participants responded one week and one month after the traumatic event. Results: A total of 175 children aged 6–14 years and 174 parents participated in the study. Stress was diagnosed in 33.7% of children after one week, and in 9.9% after one month. Parental responses suggesting stress presence in their children were 19.0% and 3.9%, respectively. These outcomes showed that mild head injuries are not so innocent. They are often underestimated by their parents and may generate a psychological burden to the children during the early post-traumatic period. Conclusions: Mild head injuries may affect the emotional welfare of children. Healthcare providers should understand the importance of the psychological effect of this overlooked type of injury. They should be trained in the psychological effect of trauma and be aware of this probability, promptly notify the parents accordingly, and provide psychological assistance beyond medical treatment. Follow-up and support are needed to avoid the possibility of future post-traumatic stress disorder. More extensive research is needed as the outcomes of this study regarded a limited population in numbers, age, and survey period. Furthermore, many children with mild head injuries do not ever visit the emergency department and stay at home unrecorded. Community-based research on the topic should therefore be considered.

Management of patients with idiopathic pulmonary fibrosis and lung cancer: challenges in clinical practice

Abstract: Idiopathic pulmonary fibrosis (IPF) is the nonmalignant, chronic lung disease with the worst prognosis. Prevalent comorbidities including lung cancer exert a negative impact on patients' survival. However, there is considerable lack of knowledge on the diagnostic and therapeutic management of patients diagnosed with both clinical entities. This review article presents the main challenges in the management of patients with IPF and lung cancer and highlights future perspectives.Recent registries for patients with IPF demonstrated that approximately 10% of patients developed lung cancer. Importantly, incidence of lung cancer was increasing remarkably over time in patients with IPF. Patients with IPF and otherwise technically operable lung cancer who underwent surgical resection had improved survival compared with those who did not undergo surgery. However, specific precautions perioperatively are crucial. Finally, the first randomized-controlled, phase 3 trial (J-SONIC trial) showed no significant difference in exacerbation-free survival for chemotherapy-naive patients with IPF and advanced nonsmall cell lung cancer that were allocated to receive carboplatin and nab-paclitaxel every 3 weeks with or without nintedanib.Lung cancer is prevalent in IPF. Management of patients with IPF and lung cancer is challenging. A consensus statement aiming to attenuate confusion is greatly anticipated.