Miracle-dz/UniFAR-FTUs huggingface dataset:
Remote sensing for underwater archaeology: case stud-ies from Greece and Eastern Mediterranean

Τις τeλeυταίeς δύο δeκαeτίeς οι θαλάσσιeς γeωφυσικές μέθοδοι έχουν αναδeιχθeί σe eξαιρeτικά αποτeλeσματικό μέσο στη μeλέτη της παράκτιας παλαιογeωγραφίας καθώς eίναι eφικτό να eντοπί-ζουν και να αναγνωρίζουν καταβυθισμένeς παλαιοακτές και γeωμορφές σχeτιζόμeνeς μe αυτές. Η eπίκληση της θάλασσας και η eμφάνιση καταστροφικών φαινομένων (σeισμοί, παλιρροιακά κύματα) έχουν οδηγήσeι στην καταβύθιση αρχαίων πόλeων, οικισμών και λιμeνικών eγκαταστάσeων. Eπι-πλέον, αυτές χρησιμοποιούνται πλέον συστηματικά για τον eντοπισμό και τη μeλέτη κινητών μαρτυ-ριών (ναυάγια) της ανθρώπινης δραστηριότητας στον πυθμένα. Τα όργανα γeωφυσικής διασκόπη-σης του πυθμένα, που χρησιμοποιούνται για τις παραπάνω eφαρμογές eίναι : (i) το μονοδeσμι-κό/πολυδeσμικό βυθόμeτρο, (ii) o τομογράφος υποδομής πυθμένα υψηλής διακριτικής ικανότητας, (iii) ο ηχοβολιστής πλeυρικής σάρωσης, (iv) το θαλάσσιο μαγνητόμeτρο, eνώ τα αποτeλέσματα της γeωφυσικής διασκόπησης eπιβeβαιώνονται μe μeθόδους οπτικής παρατήρησης του πυθμένα (δύτeς, υποβρύχια οχήματα). Στην eργασία αυτή παρουσιάζονται παραδeίγματα eφαρμογής των μeθόδων θαλάσσιας γeωφυσικής διασκόπησης σe πeριοχές μe μeγάλο αρχαιολογικό eνδιαφέρον από τον Eλληνικό θαλάσσιο χώρο (νησίδα Δοκός, κόλπος Ναβαρίνου, αρχαίο λιμάνι Κυλλήνης) και την Ανα-τολική Μeσόγeιο Θάλασσα (Αλeξάνδρeια Αιγύπτου, ναυάγιο Μαζωτού Κύπρου).
Potential distribution of saltcedar in Prairie Canada

Abstract Saltcedar (Tamarix spp.) is an invasive plant that has only recently been detected in Canada. The goals of our research were to predict the potential geographical distribution of saltcedar in Prairie Canada (Alberta, Saskatchewan and Manitoba) and to enhance our invasive species models by incorporating expert knowledge. We used ecological niche modelling (ENM) to build our predictive models and a jackknife procedure to select the predictive variables. To test model predictivity, occurrence points were spatially partitioned into quadrants. We developed a questionnaire that was then used by four local weed experts to evaluate the performance of each model and then used the expert knowledge to refine the ENM. The resulting model indicated that the potential distribution of saltcedar extended well beyond the known distribution into areas of Alberta, Saskatchewan and Manitoba. Areas identified by our model as having potential distribution should be targeted by resource managers and decision makers for early detection surveys and efforts to prevent further spread of saltcedar.
Improved SLAM algorithm based on target detection in dynamic environments

For Simultaneous Localization and Mapping (SLAM) systems in static environments, the algorithms that have matured so far have obtained more accurate trajectories. Still, the optimization results of the back end in dynamic environments could be better due to the influence of various dynamic targets. Existing algorithms could perform better in dynamic environments with high illumination variation, low texture, and many dynamic targets. This paper uses a YOLOv5-based target detection module to screen potential dynamic targets in the front end and verify and reject dynamic feature points by subsequent polar line constraints. Experimental results show that such an approach can improve the system’s stability. The experimental results also show that the results are improved compared to ORB-SLAM2 for both indoor and outdoor dynamic environment datasets.
Perspectives of Mothers and Providers regarding Virtual Care Approaches during Pregnancy in High and Low-Income Countries: A Meta-Synthesis on Qualitative Studies

Background. Various conflicting views have been presented between beneficiaries from different countries regarding the usage of virtual prenatal care. This review aimed to explain the perspectives of mothers and providers in high- and low-income countries regarding virtual approaches during pregnancy. Methods. This synthesis was conducted with an aggregative technique (which adopts a pragmatist epistemological framework) by searching the Web of Science, PubMed, Scopus, ProQuest, SID, Irandoc, Magiran databases, and Google Scholar search engine from January 2005 to February 2021 and completed until December 2022. Qualitative and mixed-method studies in English were included in this review. Extracted codes were set in three areas: participants, type of views (+ or −), and countries’ income levels. We used the JBI checklist for critical appraisal of the included studies. Results. Altogether, 1201 studies were retrieved, and finally, 16 articles were included in this review. We focused on the similarities of the extracted codes based on the stakeholders’ perspectives. These codes were organized into seven categories: positive or negative belief/sense, socio-cultural issues, economic save or cost, communication and information, technical issues, access and utilization, and management issues. At both income levels countries, the availability of services, lack of trust in virtual methods, cost of services or smartphones, and challenging interactions were shared codes between mothers. Also, raising engagements and extending workloads were shared items between providers. Overall, language barriers, saving time, and Internet disconnection or poor connectivity were three shared codes between the beneficiaries at two levels of countries regarding virtual care during pregnancy. Conclusion. Paying attention to virtual methods in maternal care is inevitable. Evidence illustrated that mothers and healthcare providers had different positive or negative views on this issue. The stakeholders’ perspectives should be considered in policies related to removing barriers and strengthening the benefits of virtual care during pregnancy.
Application of E-Healthcare Based on Machine Learning in an Internet of Things Ecosystem

Particularly in the biology and healthcare industries, advancements in technology have made it possible to collect enormous amounts of data. The obtained data is typically of an unstructured kind and can be presented in several ways, including visually, audibly, textually, etc. Technology breakthroughs, fitness bands, sensors, smart devices, even healthcare apps all have a significant impact on the healthcare industry. These innovations have brought medical care to a new level. As a result, everyone is worried about their current health and possible outcomes. Effective evaluation of clinical records and healthcare services is thus the most crucial component of the healthcare sector. By using machine learning, judgements can be made accurately and diseases can be identified earlier. Additionally, the quick and precise diagnosis of diseases is the main goal of this effort. The ischemic stroke dataset is examined in this work to enable quicker and more accurate diagnosis. There have been several ML algorithms documented from the literature, however reliability is the main issue, especially for healthcare datasets.
A GAN-Based Channel Estimation Method for MIMO OFDM Systems

Accurate channel estimation is crucial for communication systems. This paper proposes a Generative Adversarial Network (GAN) based method which can significantly improve the performance of channel estimation. Specifically, we first train two GANs to learn the receive and transmit correlation information, respectively. Through backpropagation, the parameters in the GANs are continuously updated until the distribution characteristics of the channels are learned. After that, we use these two trained GANs to perform online channel estimation separately. At this stage, GANs will search for latent vectors and complete the channel estimation with a very limited number of pilots. Finally, we linearly combine the outputs of two GANs to obtain the final channel estimates. According to the simulation results, the proposed method outperforms the channel estimation method without utilizing spatial correlation, since it fully utilizes channel correlation information.
ELEVATING INSIGHTS: PROGRESSIVE E-BOOKLET DEVELOPMENT IN TEMPERATURE AND HEAT

This study aims to evaluate the feasibility of an E-Booklet centered on temperature and heat materials. Employing the Research and Development (R&D) methodology, the research adheres to the Alessi and Trollip model, progressing through planning, design, and development stages. Validation instruments, encompassing validation sheets for both material and media, were employed. The validation process involved six material experts, including lecturers and teachers, along with three media experts. Results demonstrate the high feasibility of the developed E-Booklet for temperature and heat materials, attaining an average score of 95.58%, categorized as "very feasible. " Material expert validation from lecturers yielded an average score of 97.87%, categorized as "very decent," while validation from teachers resulted in an average score of 94.12%, also categorized as "very decent. " Media expert validation produced an average score of 94.75%, falling within the "very decent" category. In conclusion, the developed E-Booklet for temperature and heat materials proves highly suitable for integration into the learning process. Implications of the study highlight the importance of integrating innovative digital resources to enhance educational experiences. This research contributes to advancing educational practices through the creation of effective and engaging digital learning materials in the field of temperature and heat.
Efficient Federated Learning for Metaverse via Dynamic User Selection, Gradient Quantization and Resource Allocation

Metaverse is envisioned to merge the actual world with a virtual world to bring users unprecedented immersive feelings. To ensure user experience, federated learning (FL) has been expected as a critical enabler to provide metaverse users with high-quality sensing, communicating, and rendering. However, considering the limitation of wireless communication resources and the stringent requirements of users, collaborating with massive metaverse users to realize FL still has tremendous challenges. Most pioneer works on improving the performance of FL assume that the system states are static, which is unsuitable in the metaverse. Because the FL in the metaverse is always a complicated long-term iteration process, where the fluctuations of channel status and available computing resources of users are inevitable, a changeless strategy may lead to poor results. Therefore, this paper proposes an efficient FL scheme relying on dynamic user selection, gradient quantization, and resource allocation. Specifically, we derive the convergence error bound to reveal the impact of user selection, wireless transmission error, and gradient quantization error of each iteration on FL’s convergence. Based on the theoretical analysis, we jointly and dynamically optimize the user selection, gradient quantization, and resource allocation to minimize the error bound with time and energy consumption budgets. Furthermore, to make the formulated sequential decision-making problem tractable, we transform it into a Markov decision process and design a soft actor-critic-based solution. Extensive experiments validate that our proposed scheme has superior performance compared to conventional schemes in dynamic-changing network environments.
A complex regulatory network governs the expression of symbiotic genes in Sinorhizobium fredii HH103

Introduction The establishment of the rhizobium-legume nitrogen-fixing symbiosis relies on the interchange of molecular signals between the two symbionts. We have previously studied by RNA-seq the effect of the symbiotic regulators NodD1, SyrM, and TtsI on the expression of the symbiotic genes (the nod regulon) of Sinorhizobium fredii HH103 upon treatment with the isoflavone genistein. In this work we have further investigated this regulatory network by incorporating new RNA-seq data of HH103 mutants in two other regulatory genes, nodD2 and nolR. Both genes code for global regulators with a predominant repressor effect on the nod regulon, although NodD2 acts as an activator of a small number of HH103 symbiotic genes. Methods By combining RNA-seq data, qPCR experiments, and b-galactosidase assays of HH103 mutants harbouring a lacZ gene inserted into a regulatory gene, we have analysed the regulatory relations between the nodD1, nodD2, nolR, syrM, and ttsI genes, confirming previous data and discovering previously unknown relations. Results and discussion Previously we showed that HH103 mutants in the nodD2, nolR, syrM, or ttsI genes gain effective nodulation with Lotus japonicus, a model legume, although with different symbiotic performances. Here we show that the combinations of mutations in these genes led, in most cases, to a decrease in symbiotic effectiveness, although all of them retained the ability to induce the formation of nitrogen-fixing nodules. In fact, the nodD2, nolR, and syrM single and double mutants share a set of Nod factors, either overproduced by them or not generated by the wild-type strain, that might be responsible for gaining effective nodulation with L. japonicus.
Wideband Antenna Pairs Consisting of E-/M-Coupling Frame Monopoles and M-/E-Coupling Back Cover Patches for Mobile Terminal Applications

To address the contradiction between numerous antennas and tight space within a modern mobile terminal, wire-type co-frequency antenna pairs on the frame and planar-type patch antennas on the back cover have been research hotspots in recent years. To the best of the authors’ knowledge, there is no work to study the relationship between wire-type frame monopoles and planar-type back cover patches. This article first proposes antenna pairs consisting of frame monopoles and back cover patches for mobile terminals. Monopole and half-mode patch act as the basic radiating elements, and their operation bandwidths are enhanced by using the electric-/magnetic-coupling (E-/M-coupling). The first antenna pair consists of the M-coupling monopole and E-coupling patch, while the second antenna pair consists of the E-coupling monopole and M-coupling patch. Both antenna pairs are with wideband performance. Ground booster effect is adopted in the second pair to achieve patch size reduction. Antenna isolation and irrelevance within each pair can be guaranteed attributing to the mode orthogonality of the E-/M-coupling antennas. Two antenna pairs operating at the 5G Wi-Fi band (5.15–5.85 GHz) are designed and the measured results demonstrate the feasibility. The proposed antenna pairs make full use of the limited space of the mobile terminal, are easy to constitute the $4\times4$ MIMO, and are suitable for two mainstream smartphones.
EFFECTS OF NONCONSUMPTIVE RECREATION ON WILDLIFE: A REVIEW1

Interest and participation in nonconsumptive outdoor recreation have increased rapidly during the past 20 years (U.S. Dep. Inter. 1982, Diamond et al. 1983). Recreational demands and the nature and behavior of participants have been reviewed elsewhere (Potter et al. 1973, More 1979, U.S. Dep. Inter. 1979, 1982). Approximately 145 million Americans (72% of the U.S. population) engaged in nonconsumptive outdoor recreation in 1980 (Diamond et al. 1983), and substantial increases in numbers of participants are expected in the next 2 decades (U.S. Dep. Inter. 1979). By some analyses, nonconsumptive recreational values of wildlife may outweigh direct consumptive values (Shaw and King 1980, Lyons 1982). Governmental agencies are interested in developing a sound basis for management of nonconsumptive outdoor recreation (Diamond et al. 1983). Agency planners and managers must not only assess and provide for recreational demands, but also assess effects of recreational activities on natural resources, including wildlife and wildlife habitat. This paper evaluates available information on the effects of nonconsumptive outdoor recreation on wildlife in order to bring attention to, and provide a better understanding of, the relationship between recreationists and wildlife.
A community resource for integrated predictive microbial modelling (PMM-Lab)

The prediction of growth and inactivation of microorganisms in food matrices is a field of intensive research with increasing relevance to food safety professionals and public authorities. Today, large quantities of experimental and quality control data are available in comprehensive public or proprietary databases. In parallel the mathematical foundation for the generation of predictive microbial models has been developed and is available. Nevertheless, there is a gap in easy-to-use and transparent software solutions that enable e.g. food safety professionals to apply state-of-the art mathematical modelling concepts to their proprietary data that provide additionally an integrated data and model management solution. The software PMM-Lab has been specifically designed to address this gap. It is outlined right from the beginning as community resource to allow broad application and joint development. PMM-Lab already provides many valuable data analysis and modelling features including modules to create, visualize, analyze, save, import, export and deploy predictive microbial models based on experimental data. Moreover, it allows consistent data management for the analyzed experimental data and generated models due to the integrated database. Technically, PMM-Lab is an extension to the open-source data integration and analysis platform KNIME (www.knime.org) from which it inherits highly beneficial properties like modularity, flexibility, scalability and extensibility. PMM-Lab is designed to be used by laboratory scientists, food safety specialists or even modelling experts who wish to distribute their methods to a broad community. Also users trying to answer fundamental research questions based on experimental data collections or looking for structure in their growing data and model collection will find value in this software. Possible application areas are numerous including
Characteristics of tin droplet target system for EUV source research

Droplet-based laser-produced plasma source shows enormous significance in extreme ultraviolet lithography, which places high demands on the stability of tin droplets. This paper presents a tin droplet target system including the tin droplet generator (DG), droplet diagnosis, and spatiotemporal synchronization of tin droplets and laser. Shadowgraph technology is used to determine the stability of tin droplets. The characteristics of the DG were analyzed, and the operation parameter maps are provided. By varying operating frequencies from 18.4 kHz to 49.3 kHz, the diameter and spacing of droplets can be adjusted in the ranges of 120–200 μm and 200–1100 μm respectively. Both theoretical calculations and experimental results show that tin droplets keep high stability when the operation parameters locate at the optimal range. The long-term lateral stability is also proven under a high degree of vacuum. Additionally, the application feasibility of the DG system is verified by the experiments of laser impact tin droplets.
Estimation of connector insertion state based on phase spectrum of waves transmitted between robot fingers

This paper proposes a method for estimating the insertion state of a connector based on the measurement of vibration waves transmitted between robot fingers through the grasped connector. The change in the phase spectrum derived from generated and detected vibration waves between the fingers of a parallel two-fingered robot hand is used for the estimation. Experimental results verify that the connector insertion state can be estimated from the change in the phase spectrum derived from detected vibration waves by applying the fast Fourier transform. In the proposed method, the normal grasping motion serves as the sensing motion. The results will be useful for expanding the application range of assembly work by a robot hand-arm system.
Optical properties of YSAG : Yb : Er ceramics with Sc3+ cations in the dodecahedral and octahedral positions of the garnet crystal lattice

Optical ceramics based on YSAG : Yb : Er with the compositions {Y1.86Yb0. 45Er0.09Sc0. 6}[Al1.6Sc0. 4]Al3O12 and {Y2.26Yb0. 45Er0.09Sc0. 2}[Al1.0Sc1. 0]Al3O12 were fabricated by vacuum sintering from pre-synthesized nanocrystalline powders. A comparative analysis of these samples with optical ceramics of the compositions {Y2.34Yb0. 45Er0.09Sc0. 12}[Al1.92Sc0. 08]Al3O12 and {Y0.96Yb0. 45Er0.09Sc1. 50}[Al1.8Sc0. 2]Al3O12 was carried out. The influence of scandium cations in the dodecahedral and octahedral positions of the garnet crystal lattice on the refractive index of YSAG : Yb : Er, as well as the values of absorption coefficients, integral luminescent intensities, and lifetimes of excited states of Yb3+ (2F7/2 and 2F5/2) and Er3+ (4I15/2, 4I13/2, 4F9/2, and 4S3/2) cations was revealed in the wavelength ranges 520–700 nm and 890–1690 nm. It has been shown that by changing the concentrations of scandium cations in the dodecahedral and octahedral positions of the crystal lattice of YSAG : Yb : Er solid solutions, it is possible to purposefully change the efficiency of energy transfer from ytterbium cations to erbium cations.
Problèmes de désignation, de localisation et d'accès dans les systèmes répartis à objets

L'introduction de la repartition dans les Systemes d'exploitation a donne lieu a deux types de systemes, les systemes repartis a gestion de fichiers et les systemes repartis a espace d'objets. Dans ces derniers, l'objet est utilise comme unite de conservation, de designation, de partage et de protection de l'information. Ces systemes doivent donc fournir les mecanismes permettant de designer et de localiser les objets sachant qu'ils peuvent etre deplaces; ils doivent permettre le partage des objets entre des processus s'executant sur des machines differentes tout en assurant une certaine isolation entre ces processus et ces objets; ils doivent enfin fournir des mecanismes d'acces efficaces. Apres une presentation de ces problemes, nous passons en revue et evaluons dans cet article les solutions actuellement adoptees ou explorees.
Handwritten Bangla character recognition to braille pattern conversion using image processing and machine learning

There has been significant development in the recent Education System with the rapid development of technology however there are very few facilities that can help those people with disabilities such people without sight. Braille has been one such method however it has not yet been digitized or has not been incorporated in the education system. On the other hand, many papers and works have been conducted on English Character Recognition with satisfactory outcomes with considerably good accuracy however such cannot be said about Bengali Characters. Some works have been done with considerable accuracy however its frequency is still low. This paper introduces the development of a prototype system which takes an image of a handwritten Bangla Character and applies the concepts of Image Processing using OpenCV and ​Machine Learning to capture and process an image then recognize the character and finally with the help of a device present the recognized character in a Braille pattern. Furthermore, this paper will also look into the different machine learning modules and assess the reliability and accuracy. For the machine learning part ​Deep Neural Network was applied on the image and then ​VGG-16​, ​Resnet-50 and DenseNet-121 which are modules of Convoluted Neural Networks where used. Then the outcome is passed into a device which will engrave the corresponding character into its respective Braille Pattern. The device will consist of ​Atmega2560 chipset (Arduino Mega)​ , Servo Motor and LCD which will process the data and finally present it in Braille pattern using servo motor and will show the corresponding character on the LCD monitor.