Critical quality indicators of high-performance polyetherimide(ULTEM)over the MEX 3D printing key generic control parameters:Prospects for personalized equipment in the defense industry

Additive Manufacturing(AM)can provide customized parts that conventional techniques fail to deliver.One important parameter in AM is the quality of the parts,as a result of the material extrusion 3D printing(3D-P)procedure.This can be very important in defense-related applications,where optimum performance needs to be guaranteed.The quality of the Polyetherimide 3D-P specimens was examined by considering six control parameters,namely,infill percentage,layer height,deposition angle,travel speed,nozzle,and bed temperature.The quality indicators were the root mean square(Rq)and average(Ra)roughness,porosity,and the actual to nominal dimensional deviation.The examination was performed with optical profilometry,optical microscopy,and micro-computed tomography scanning.The Taguchi design of experiments was applied,with twenty-five runs,five levels for each control parameter,on five replicas.Two additional confirmation runs were conducted,to ensure reliability.Prediction equations were constructed to express the quality indicators in terms of the control parameters.Three modeling approaches were applied to the experimental data,to compare their efficiency,i.e.,Linear Regression Model(LRM),Reduced Quadratic Regression Model,and Quadratic Regression Model(QRM).QRM was the most accurate one,still the differences were not high even considering the simpler LRM model.

Height-diameter models for King Boris fir(Abies borisii regis Mattf.) and Scots pine(Pinus sylvestris L.) in Olympus and Pieria Mountains, Greece

In forest science and practice, the total tree height is one of the basic morphometric attributes at the tree level and it has been closely linked with important stand attributes. In the current research, sixteen nonlinear functions for height prediction were tested in terms of their fitting ability against samples of Abies borisii regis and Pinus sylvestris trees from mountainous forests in central Greece. The fitting procedure was based on generalized nonlinear weighted regression. At the final stage, a five-quantile nonlinear height-diameter model was developed for both species through a quantile regression approach, to estimate the entire conditional distribution of tree height, enabling the evaluation of the diameter impact at various quantiles and providing a comprehensive understanding of the proposed relationship across the distribution. The results clearly showed that employing the diameter as the sole independent variable, the 3-parameter Hossfeld function and the 2-parameter N?slund function managed to explain approximately 84.0% and 81.7% of the total height variance in the case of King Boris fir and Scots pine species, respectively. Furthermore, the models exhibited low levels of error in both cases(2.310m for the fir and 3.004m for the pine), yielding unbiased predictions for both fir(-0.002m) and pine(-0.004m). Notably, all the required assumptions for homogeneity and normality of the associated residuals were achieved through the weighting procedure, while the quantile regression approach provided additional insights into the height-diameter allometry of the specific species. The proposed models can turn into valuable tools for operational forest management planning, particularly for wood production and conservation of mountainous forest ecosystems.

Physical and Mechanical Properties of Eco-Friendly Composites Made from Wood Dust and Recycled Polystyrene

The development of alternative wood composites based on the use of waste or recycled materials can be beneficial due to over exploitation of natural resources.Under this frame,an option for the successful utilization of waste polystyrene which avoids environmental problems that formaldehyde adhesives cause and also reduces waste dis-posal,is its potential application as a binder for the production of value-added environmentally friendly and low cost wood composites.Two types of panel were successfully made,consisting of wood dust and two recycled poly-styrene contents,namely,15%and 30%.Both physical properties,water absorption and thickness swelling,and mechanical properties,modulus of rupture,shear strength parallel in the plane of the board and glue line shear strength,were significantly improved as the recycled polystyrene content increased from 15%to 30%.Water absorption and thickness swelling after 24 h immersion in water were improved by 165%and 750%as the recycled polystyrene content increased from 15%to 30%.The magnitude of the improvement in mechanical properties however,was less pronounced than of the physical properties since modulus of rupture,shear strength parallel in the plane of the board and glue line shear strength were increased by 43.6%,50%and 61.5%,respec-tively.The low viscosity of the recycled polystyrene caused more mobility inside the panel matrix and therefore,an improved penetration took place into adequate depth of the compressed dust particles.It is concluded that boards can be successfully produced using these waste raw materials,wood dust and recycled polystyrene in organic solvent as a binder,and therefore it can reduce waste disposal and provide cleaner production for the development of wood-based boards.

Identifying important habitats for waterbird conservation at a Greek Regional Nature Park

Background:Small coastal wetlands are vital sites for wintering waterbirds.Identifying important habitats is critical for managing waterbirds effectively.The Vourkari inlet is a small coastal wetland located near the capital Athens,within the most urbanized and industrialized area of Greece.We aimed at identifying the most important habitats for waterbirds at the Vourkari inlet during winter.Methods:Data about habitat use and availability were collected for 14 waterbird species and for seven habitat classes.Habitat selection(Manly’s selection ratio),overlap indices(Pianka’s niche overlap index)and null models were calculated.Results:All the studied waterbird species selected available habitats nonrandomly.Shallow waters(0–2 m),were used by 13 waterbirds and selected by five waterbirds.Pools and channels were used and selected by 10 species.Mud was used by nine species and selected by six species.Mud with rocky substrate was used by nine species and selected by eight species.Medium(2–4 m)and deep(4–6 m)open water habitats were used by seven species and selected by four species.Halophytic vegetation was used by six species and selected by two species.Several habitats were selected by nationally important populations:mudflat habitats(i.e.,mud,mud with rocky substrate and pools and channels)by Common Redshanks(Tringa totanus),halophytic vegetation by Little Egrets(Egretta garzetta),shallow waters by Common Shelducks(Tadorna tadorna)and medium and deep waters by Sandwich Terns(Thalasseus sandvicencis),whilst shallow waters and mudflat habitats were preferred by a possibly internationally important population of Mediterranean Gulls(Ichthyaetus melanocephalus).Although overlap in habitat use between species was generally low,null models indicated habitat sharing and a lack of competition.Conclusions:Waterbirds coexisted in the absence of competition for habitats at Vourkari,where they mostly used and preferred shallow water and mudflats.Small coastal wetlands are numerous,both in Greece and worldwide,therefore our findings would be useful as a basis for comparisons,both temporal at the inlet and spatial with other sites,that would help assess the importance of habitats and improve management strategies to benefit waterbirds,especially in areas with similar Mediterranean-type habitats and climate.

Review of New Data in Physiotherapeutic Approach to Patellofemoral Pain Syndrome (PFPS)

Patellofemoral pain syndrome (PFPS) is a common musculoskeletal condition, with a high incidence in young active adolescents, as well as in other age groups. The multifactorial etiology of the syndrome makes the clinical evaluation and synthesis of an effective treatment plan particularly demanding and difficult. The absence of a specific clinical trial for the diagnosis or rejection of PFPS leads to the diagnosis of the syndrome through the careful rejection of other conditions with similar symptoms. Physiotherapy is based on the management and immediate treatment of the patient’s pain, by combining active and passive means of treatment and address the fear of exercise and movement. Interventions for the treatment of patellofemoral pain present positive short-term but not as encouraging long-term results. Therefore we are posed with an interesting question: what is the most effective treatment plan for the management of PFPS? The purpose of the review is to present the necessary and most up-to-date data for the identification, clinical evaluation and etiology of the syndrome as well as to compose in the form of guidelines (Guidelines) the basis for building an effective treatment plan for the treatment of PFPS.

Diagnostic and clinical significance of antigen-specific pancreatic antibodies in inflammatory bowel diseases: A meta-analysis

BACKGROUND Non-invasive criteria are needed for Crohn’s disease(CD)diagnosis,with several biomarkers being tested.Results of individual diagnostic test accuracy studies assessing the diagnostic value of pancreatic autoantibodies-to-glycoprotein-2(anti-GP2)tests for the diagnosis of CD appear promising.AIM To systematically review and meta-analyze evidence on the diagnostic accuracy of anti-GP2 tests in patients with suspected/confirmed CD.METHODS An electronic search was conducted on PubMed,Cochrane-CENTRAL and grey literature(CRD42019125947).The structured research question in PICPTR format was“Population”including patients with symptoms akin to CD,the“Index test”being anti-GP2 testing,the“Comparator”involved standard CD diagnosis,the“Purpose of test”being diagnostic,“Target disorder”was CD,and the“Reference standard”included standard clinical,radiological,endoscopical,and histological CD diagnostic criteria.Quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool and hierarchical models were employed to synthesize the data.RESULTS Out of 722 studies retrieved,15 were meta-analyzed.Thirteen studies had industry-related conflicts-of-interest,and most included healthy donors as controls(spectrum bias).For the combination of IgA and/or IgG anti-GP2 test,the summary sensitivity was 20%(95%confidence interval:10%-29%)at a median specificity of 97%.If the test was applied in 10000 suspected patients,9669 would be true negatives and in 26,the diagnosis would be missed.In this hypothetical cohort,the anti-GP2 would fail to produce a diagnosis for 81.3%of the positive cases.Low summary points of sensitivity and high specificity were estimated for the IgG or IgA anti-GP2 test.Analogous results were observed when the analyses were restricted using specific cut-offs,or when ulcerative colitis patients were used as comparators.CONCLUSION Anti-GP2 tests demonstrate low sensitivity and high specificity.These results indicate that caution is required before relying on its diagnostic value.Additionally,the need for improving the methodology of diagnostic test accuracy studies is evident.

An advanced discrete‐time RNN for handling discrete time‐varying matrix inversion:Form model design to disturbance‐suppression analysis

Time‐varying matrix inversion is an important field of matrix research,and lots of research achievements have been obtained.In the process of solving time‐varying matrix inversion,disturbances inevitably exist,thus,a model that can suppress disturbance while solving the problem is required.In this paper,an advanced continuous‐time recurrent neural network(RNN)model based on a double integral RNN design formula is pro-posed for solving continuous time‐varying matrix inversion,which has incomparable disturbance‐suppression property.For digital hardware applications,the corresponding advanced discrete‐time RNN model is proposed based on the discretisation formulas.As a result of theoretical analysis,it is demonstrated that the advanced continuous‐time RNN model and the corresponding advanced discrete‐time RNN model have global and exponential convergence performance,and they are excellent for suppressing different disturbances.Finally,inspiring experiments,including two numerical experiments and a practical experiment,are presented to demonstrate the effectiveness and superiority of the advanced discrete‐time RNN model for solving discrete time‐varying matrix inversion with disturbance‐suppression.

Digital Communications and Networks

Guest editorial The emerging applications,suchas Augmented and Virtual Realities(AR/VR),InternetofThings(IoT),4K/8Kstreaming,raisestrongrequirementsto movecomputationfrom thecloudtotheedgestobecloser tousers.There are tremendous possibilities for the network edge,which may includeavariety ofentities,such as small datacenters,end devices,and resource-abundant network nodes.These together provide the network computation and intelligence to users.

Tourism Entropy as a Critical Factor for Destination Sustainability:Assessment of Carrying Capacity Through IoTs and Determination of Tourism Satisfaction

This paper introduces a novel methodology to address the issue of destination carrying capacity assessment and monitoring,while,to develop a new tool to enable effective and optimized policy making in tourism sector.Tourism fits together a chain value,where stakeholders are working as cogwheels targeting the sustainability.An inherent requirement towards the objectives of sustainability is the capacity of policy makers to sustain the available social,economic,and environmental resources.Given the facts that(i)carrying capacity is a complex,dynamic,multidimensional concept,apparently vague,as such it is quite difficult to assess and monitor and(ii)each destination has unique characteristics,varying the extent and intensity of tourism development,the research proposal refines and implements measures and establishes a state-of-the-art data collection network in order to monitor tourism development in terms of sustainability and to establish an integrated carrying capacity estimation framework.Since validity and reliability of input data is a critical issue,different kind of sensors for environmental data(IoTs)are used,as well as web mining methods and field surveys,statistical information and secondary research results.Also,specialized analysis methods are applied and integration of all sources is achieved,defining the characteristics of the tourism destination ecosystem from the perspective of entropy change,in order to provide planning,policy making,and decision support,as well as a set of intelligent tools.

Revisiting the determination of Mount Olympus Height(Greece)

The present study deals with the determination of Mount Olympus summit(Mytikas),exploiting modern observations such as Global Navigation Satellite Systems(GNSS)and existing geodetic information.The last official Olympus height determination goes back 102 years by the Swiss surveyor M.Kurz.Since then,only unofficial measurement campaigns have taken place.There is a variety of released heights,which range from 2917 to 2919 meters.In September and October of 2022,we conducted a GNSS campaign,focusing on the area of highest Olympus peaks.Employing precise GNSS measurements(accuracy of 1-3 cm),in conjunction with height information from Greece’s National Triangulation Network(5-10 cm accuracy)and an appropriate,recent geoid model(5-6 cm accuracy),we estimate through the so-called GNSS-levelling,the height of Olympus to 2917.727 m with respect to Greece’s officially accepted mean sea level and 2918.390 m with respect to the global vertical datum.Our estimation of Olympus highest peak shows remarkable consistency at the level of 12.8 cm to that of M.Kurz in 1921.

Neuroevolution Strategy for Time Series Prediction

Optimization is a concept, a process, and a method that all people use on a daily basis to solve their problems. The source of many optimization methods for many scientists has been the nature itself and the mechanisms that exist in it. Neural networks, inspired by the neurons of the human brain, have gained a great deal of recognition in recent years and provide solutions to everyday problems. Evolutionary algorithms are known for their efficiency and speed, in problems where the optimal solution is found in a huge number of possible solutions and they are also known for their simplicity, because their implementation does not require the use of complex mathematics. The combination of these two techniques is called neuroevolution. The purpose of the research is to combine and improve existing neuroevolution architectures, to solve time series problems. In this research, we propose a new improved strategy for such a system. As well as comparing the performance of our system with an already existing system, competing with it on five different datasets. Based on the final results and a combination of statistical results, we conclude that our system manages to perform much better than the existing system in all five datasets.

The Effect of Latinization on Reading Time and Understanding: Greeklish in Communication and Social Media

The increasing prevalence of technology in society has an impact on young people’s language use and development. Greeklish is the writing of Greek texts using the Latin instead of the Greek alphabet, a practice known as Latinization, also employed for many non-latin alphabet languages. The primary aim of this research is to evaluate the effect of Greeklish on reading time. A sample of 732 young Greeks were asked about their habits when communicating through e-mail and social media with their friends and they then participated in an experiment in which they were asked to read and understand two short texts, one written in Greek and the other in Greeklish. The findings of the research show that nearly one third of the participants use Greeklish. The results of the experiment conducted reveal that understanding is not affected by the alphabet used but reading Greeklish is significantly more time consuming than reading Greek independently of the sex and the familiarity of the participants with Greeklish. The findings suggest that amending social and communication media with software utilities related to Latinization such as language identifiers and converters may reduce reading time and thus facilitate written communication among the users.

Factors Influencing the Incidence of Heart Disease

Introduction:Understanding the causes of heart disease is a relatively new field in medicine.In fact,heart disease was relatively rare before the early 1900s.Aim:The aim of this review study is to investigate the risk factors associated with the development of heart disease and its prevention.Material Methodology:A scrutinized review of the Greek and international literature was carried out.The material of the study was manuscripts on the subject found in Greek and international electronic databases such as:Google Scholar,Mednet,PubMed and the Association of Hellenic Academic libraries(HEAL-Link).Results:The risk factors for the development of heart disease are metabolic factors,i.e.,hypertension,diabetes,cholesterol and obesity;environmental factors,i.e.,smoking,lack of physical activity or exercise,poor dietary patterns and alcohol consumption;and other factors such as age,gender,heredity,socioeconomic status and psychological factors.Conclusions:Heart diseases are multifactorial diseases and the only way to successfully treat them is to take into account all the risk factors for their development,and to treat them systematically.

Environmental State of a Harbor in Terms of Waters Renewal. A Case Study for a Fishery Harbor in Thessaloniki Gulf

The waters renewal of the fishery harbor of Nea Krini is presented here. The harbor is located at the east Thessaloniki Gulf (NE Thermaikos Gulf, Greece). The main research point is focused on the environmental state of the harbor which is under construction. Under that point of view, the description of a two-dimensional, depth average, hydrodynamic model follows, in order to simulate the wind generated circulation of waters, initially on the greater area of Thermaikos Gulf and then on the coastal basin of the fishing harbor. The renewal of waters in the harbor’s basin is subsequently studied. Tidal effects on the waters’ renewal are also studied. The calculation of the concentration of Biochemically Oxygen Demand (BOD) in the fishing harbor for the average time of waters’ renewal is then examined for three different cases, concerning the existence and operation of openings on the body of the groins. Finally, the analysis of the results shows a good environmental state of the harbor. It is obvious that the use of numerical models for different scenarios of engineering and design approaches can lead to the prognosis of hydrodynamic and environmental sate of a harbor’s basin so that the best possible technical design can be adopted.

The Religious Tourism as a Competitive Advantage of the Prefecture of Pieria,Greece

The scope of the present paper is the research of whether the prefecture of Pieria comprises an attractive destination for religious tourism and pilgrimage.For this reason,the use of questionnaires takes place which aims to realizing if and to what extend this form of tourism comprises a comparative and competitive advantage for the prefecture of Pieria.The research method of this paper is the qualitative research and more specifically the use of questionnaires with 13 questions in total.The scope was to research whether the prefecture of Pieria is a religious-pilgrimage destination.The sample is comprised of 102 participants,being Greek residents originating from other Greek counties,the European Union,and Third World Countries.The requirement was for the participant to have visited the prefecture of Pieria.The independency test(x2)was used for checking the interconnections between the different factors,while at the same time an allocation of frequencies was conducted based on the study and presentation of frequency as much as relevant frequency.Due to the fact that,no other similar former researches have been conducted regarding religious tourism in Pieria,this research will be able to give some useful conclusions.These conclusions will lead us to more specialized knowledge on the tourism of the under study prefecture.

Polyamide nylon 6 microplastics enhance nitrification activity in two agricultural soils

Dear Editor,Microplastics are plastic debris with a maximum size of5 mm,and their presence in terrestrial and aquatic ecosystems may affect environmental quality,living organisms,and human health(Zhou et al.,2020).Due to their physical and chemical properties,microplastics in soils may interact with naturally occurring inorganic and organic compounds(Zhou et al.,2020)for longer periods,affecting soil microorganisms and their activities,such as nitrogen(N)cycling(Qian et al.,2018).

Enhancing the functionality of augmented reality using deep learning,semantic web and knowledge graphs:A review

The growth rates of today’s societies and the rapid advances in technology have led to the need for access to dynamic,adaptive and personalized information in real time.Augmented reality provides prompt access to rapidly flowing information which becomes meaningful and‘‘alive’’as it is embedded in the appropriate spatial and time framework.Augmented reality provides new ways for users to interact with both the physical and digital world in real time.Furthermore,the digitization of everyday life has led to an exponential increase of data volume and consequently,not only have new requirements and challenges been created but also new opportunities and potentials have arisen.Knowledge graphs and semantic web technologies exploit the data increase and web content representation to provide semantically interconnected and interrelated information,while deep learning technology offers novel solutions and applications in various domains.The aim of this study is to present how augmented reality functions and services can be enhanced when integrating deep learning,semantic web and knowledge graphs and to showcase the potentials their combination can provide in developing contemporary,user-friendly and user-centered intelligent applications.Particularly,we briefly describe the concept of augmented reality and mixed reality and present deep learning,semantic web and knowledge graphs technologies.Moreover,based on our literature review,we present and analyze related studies regarding the development of augmented reality applications and systems that utilize these technologies.Finally,after discussing how the integration of deep learning,semantic web and knowledge graphs into augmented reality enhances the quality of experience and quality of service of augmented reality applications to facilitate and improve users’everyday life,conclusions and suggestions for future research and studies are given.

Understanding stakeholder preferences for managing red foxes in different situations

Background:Red foxes(Vulpes vulpes)have historically been interacting with human societies,thus being an important component of socio-ecological systems.In Greece,farmers and hunters have been increasingly complaining about predation of red foxes on livestock and game,and the recurrence of rabies incidents has raised concerns about human and animal health.Understanding public preferences about management is necessary for successful wildlife management.This study aimed at investigating the preferences of north Greece residents for managing the negative impacts of red foxes and also at understanding variation between stakeholder groups:farmers,hunters,farmers-hunters,and the general public.Data were collected from on-site face-to-face surveys(n=746),between March and May 2017.Respondents were asked to rate their acceptability of management strategies under three impact scenarios:red foxes attack livestock,reduce game,and carry rabies.Results:Stakeholders preferred nonlethal management strategies,with generally high consensus,both between and within groups.Fencing and compensation were the most acceptable strategies for protecting livestock and vaccination and the removal of sick animals for eliminating rabies.Acceptability and consensus for lethal strategies were lower,with hunting being the most acceptable lethal strategy for hunters,especially when foxes threatened game or carried rabies.Doing nothing was becoming more unacceptable and lethal control more acceptable with increasing severity of the impacts,i.e.,livestock and game predation versus rabies transmission.Conclusions:Variation in the acceptability of and consensus for management strategies was considerable among scenarios,and both between and within stakeholder groups.Research implications could be used as a guide for reaching consensus for proper management strategies during the conservation conflict management process in the study area.As similar studies are scarce,findings might also prove useful elsewhere,especially in the northern hemisphere where native populations do occur.Findings about managing rabid red foxes would be particularly useful for countries where rabies has not been eliminated,particularly for neighboring Balkan and Asia Minor countries.Findings about managing red fox impacts on livestock and game would be most useful for European countries and especially Mediterranean countries with social and ecological conditions similar to Greece.

Scientific scripting in Java with JShellLab and application to deep learning using DeepLearning4j

JShellLab is an easy to use MATLAB-like environment for the Java Virtual Machine(JVM).It implements scientific scripting based on the JShell Application Programming Interface(API)of modern Java.The paper illustrates that JShellLab can significantly facilitate and simplify the development of complex computational demanding scientific software at the JVM.The novelty at the JShellLab is that it completely hides the complexity and the intricate dependencies of optimized scientific software.As an example,the demanded field of deep learning is exploited.Specifically,the implementation of effective practical deep learning-based systems using the JShellLab environment and the Deeplearning4j Java library is considered.

Recurring heavy rainfall resulting in degraded-upgraded phases in soil microbial networks that are reflected insoil functioning

Biological soil crusts(BSCs)are an important multi-trophic component of arid ecosystems in the Mediterranean region.In a mesocosm experiment,the authors investigated how the network of interactions among the members of the soil microbial communities in four types of soil sample responded when soils were exposed to two simulated extreme rain events.The four types of soil samples were:covered by Cladonia rangiformis and previously hydrated(+BSC+H),covered by C.rangiformis and dried(+BSC-H),uncovered and hydrated(-BSC+H),uncovered and dried(-BSC-H).Network analysis was based on the co-occurrence patterns of microbes;microbes were assessed by the phospholipid fatty acids analysis.The authors further explored the relations between networks’metrics and soil functions denoted by enzymatic activity and soil chemical variables.All networks exhibited Small world properties,moderate values of clustering coefficient and eigen centrality,indicating the lack of hub nodes.The networks in-BSC-H soils appeared coherent during the pre-rain phases and they became modular after rains,while those in+BSC-H soils kept their connectivity till the second rain but this then collapsed.The network metrics that were indicative of cohesive networks tended to be related to enzyme activity while those that characterized the loose networks were related to Ca,K,Mg,NH_(4)^(+) and organic N.In all mesocosms except for+BSC-H,networks’fragmentation after the second heavy rain was milder than after the first one,supporting the idea of community acclimatization.The response of microbial networks to heavy rains was characterized by the tendency to exhibit degradation-reconstruction phases.The network collapse in the crusted only mesocosms showed that the communities beneath crusts in arid areas were extremely vulnerable to recurring heavy rain events.