bluuebunny/crossref_metadata_2025_split huggingface dataset:
Current state of the ion exchange resin market (a review)
Authors: Павелкова А.М. , Спицов Д.В. 
Published: August 2023

Широкое распространение установок ионного обмена для подготовки природных вод и очистки промышленных сточных вод обусловлено применением разнообразных ионообменных смол. Это позволяет подобрать установку как для полного обессоливания воды, так и для селективной очистки под требования производства. Рассмотрены основные сферы применения ионного обмена. Проанализированы особенности выбора ионита в зависимости от типа регенерации фильтров, режима и скорости фильтрования. Отсутствие единой классификации ионообменных смол затрудняет их оптимальный выбор, поскольку само название не дает представления о их свойствах, что требует тщательного изучения характеристик. Проведен комплексный анализ рынка ионитов по классической классификации, их взаимозаменяемости, возможности импортозамещения. Оптимальный выбор ионообменной смолы с минимальной себестоимостью подготовленной воды происходит после комплексного анализа показателей качества обрабатываемой и исходной воды, режима фильтрования, типа установки.
Widespread use of ion exchange plants for both natural water and industrial wastewater treatment is driven by the use of various ion exchange resins. It provides for selecting a unit for both complete desalination of water and selective purification depending on the demands of work. The main fields of ion exchange application are considered. The specific features of ionite selection are analyzed depending on the type of filter regeneration, filtration mode and rate. The lack of a unified classification of ion exchange resins hampers their optimal choice since the very name gives no idea of their properties, which requires careful study of the characteristics. A comprehensive analysis of the current ionite market according to the classical classification, their interchangeability, possible import phaseout has been executed. The optimal choice of an ion exchange resin with the minimum cost of the treated water is made after a comprehensive analysis of the quality indicators of the treated and source water, filtration mode, type of the plant.
On possible combining the concepts of BIM and GIS while developing schematics of external water supply and sewer networks
Authors: Громов Г.Н. , Новиков К.А. 
Published: August 2023

На текущий момент в российском законодательстве закреплены понятия «схема водоснабжения и водоотведения населенного пункта» и «проектная документация». Исходя из мероприятий, предусмотренных в схеме, в дальнейшем разрабатывается проектная документация по каждому из них. При этом разработка электронной модели схемы водоснабжения и водоотведения, согласно Постановлению Правительства РФ от 5 сентября 2013 г. № 782, проводится с помощью программного обеспечения на основе геоинформационной системы (ГИС). А разработка проектной документации объекта капитального строительства должна проводиться на основе информационной модели в соответствии с Постановлением Правительства РФ № 331 от 5 марта 2021 г., формирование которой осуществляется с помощью программного обеспечения с использованием BIM-моделирования. Анализ показывает, что на сегодяшний день отсутствует программное обеспечение, которое бы полноценно объединяло эти две концепции – ГИС и BIM. Приведены промежуточные результаты внедрения программного комплекса в АО «Мосводоканал» с анализом возможности объединения концепций BIM и ГИС для получения более точной и полной информации о реализуемом объекте.
At the moment, the concepts of «scheme of water supply and wastewater disposal of a settlement» and «project documentation» are fixed in the Russian legislation. Based on the activities provided in the scheme, project documentation for each of them is further developed. At the same time, the development of an electronic model of the water supply and wastewater disposal scheme, in accordance with Decree of the Government of the Russian Federation of September 5, 2013 No. 782, is carried out using software based on a geographic information system (GIS); whereas the design documentation for a capital construction object should be developed on the basis of an information model in accordance with Decree of the Government of the Russian Federation No. 331 dated March 5, 2021. The information model is developed with the help of the software using BIM modeling. The analysis shows that for the moment the software that would fully combine these two concepts – GIS and BIM is not available. Interim results of the implementation of the software package in «Mosvodokanal» JSC are presented with the analysis of possible combining the concepts of BIM and GIS to obtain more accurate and complete information about the facility being implemented.
Ultrasound Concave 2D Ring Array for Retinal Stimulation
Authors: Lu Jian-yu , Lu Gengxi , Thomas Biju , Humayun Mark , Zhou Qifa 
Published: August 2023

<p>This paper developed an ultrasound concave 2D ring array transducer for retinal visual stimulation of the brain to restore vision in blind people. Theory, simulation, and experiment were presented. </p>
Traffic-Aware Optimal Multi-Beam Resource Allocation in 5G Networks Impaired by Rain and Foliage
Authors: Bose Tushar , Chatur Nilesh , Mukherjee Mithun , Verma Sandeep , Adhya Aneek 
Published: August 2023

<p>In this work, we investigate a novel framework for a traffic-aware multi-beam optimal resource allocation to serve fixed home users distributed over a geographical area in the presence of rain and foliage. The fixed home users in the geographical area of interest are served by small-cell next-generation node B (gNB) via multiple beams generated simultaneously by the uniform planar array (UPA) installed at the gNB. In this regard, we present a framework to compute the optimal coverage radius of the gNB to satisfy the desired quality of service (QoS) requirements of the users. We also derive the closed-form expression for the optimum coverage radius of the gNB, considering free space and foliage attenuation scenarios. We propose a graphical methodology to compute the optimal radius of gNB in free space propagation, rain, and foliage attenuation. Further, based on the location information of the users, we determine the optimal location of the gNB by leveraging the unsupervised machine learning (ML) framework. Finally, we investigate a non-linear programming (NLP)-based technique for allocating optimal power and bandwidth to each beam, constrained by total power and bandwidth availability at the gNB. The optimal beam resource allocation (power and bandwidth) strategy ensures that the requested data rate (traffic demand) is satisfied for each user served by each beam. The simulation results demonstrate the effectiveness of our proposed methodology to ensure high QoS for a larger number of users in the presence of rain and foliage as compared to genetic algorithm and surrogate optimization </p>
Traffic-Aware Optimal Multi-Beam Resource Allocation in 5G Networks Impaired by Rain and Foliage
Authors: Bose Tushar , Chatur Nilesh , Verma Sandeep , Adhya Aneek 
Published: August 2023

<p> In this work, we investigate a novel framework for a traffic-aware multi-beam optimal resource allocation to serve fixed home users distributed over a geographical area in the presence of rain and foliage. The fixed home users in the geographical area of interest are served by small-cell next-generation node B (gNB) via multiple beams generated simultaneously by the uniform planar array (UPA) installed at the gNB. In this regard, we present a framework to compute the optimal coverage radius of the gNB to satisfy the desired quality of service (QoS) requirements of the users. We also derive the closed-form expression for the optimum coverage radius of the gNB, considering free space and foliage attenuation scenarios. We propose a graphical methodology to compute the optimal radius of gNB in free space propagation, rain, and foliage attenuation. Further, based on the location information of the users, we determine the optimal location of the gNB by leveraging the unsupervised machine learning (ML) framework. Finally, we investigate a non-linear programming (NLP)-based technique for allocating optimal power and bandwidth to each beam, constrained by total power and bandwidth availability at the gNB. The optimal beam resource allocation (power and bandwidth) strategy ensures that the requested data rate (traffic demand) is satisfied for each user served by each beam. The simulation results demonstrate the effectiveness of our proposed methodology to ensure high QoS for a larger number of users in the presence of rain and foliage as compared to genetic algorithm and surrogate optimization </p>
SSIVD-Net: A Novel Salient Super Image Classification & Detection Technique for Weaponized Violence
Authors: Aremu Toluwani 
Published: August 2023

<p> Detection of violence and weaponized violence in closed-circuit television (CCTV) footage requires a comprehensive approach. In this work, we introduce the \emph{Smart-City CCTV Violence Detection (SCVD)} dataset, specifically designed to facilitate the learning of weapon distribution in surveillance videos. To tackle the complexities of analyzing 3D surveillance video for violence recognition tasks, we propose a novel technique called, \emph{SSIVD-Net} (\textbf{S}alient-\textbf{S}uper-\textbf{I}mage for \textbf{V}iolence \textbf{D}etection). Our method reduces 3D video data complexity, dimensionality, and information loss while improving inference, performance, and explainability through the use of Salient-Super-Image representations. Considering the scalability and sustainability requirements of futuristic smart cities, the authors introduce the \emph{Salient-Classifier}, a novel architecture combining a kernelized approach with a residual learning strategy. We evaluate variations of SSIVD-Net and Salient Classifier on our SCVD dataset and benchmark against state-of-the-art (SOTA) models commonly employed in violence detection. Our approach exhibits significant improvements in detecting both weaponized and non-weaponized violence instances. By advancing the SOTA in violence detection, our work offers a practical and scalable solution suitable for real-world applications. The proposed methodology not only addresses the challenges of violence detection in CCTV footage but also contributes to the understanding of weapon distribution in smart surveillance. Ultimately, our research findings should enable smarter and more secure cities, as well as enhance public safety measures.</p>
Underwater Acoustic Target Recognition Using Spectrogram ROI Approximation And Mobilenet One-Dimensional And Two-Dimensional Networks
Authors: Akbarian Hassan , Sedaaghi Mohammad Hossein 
Published: August 2023

<p>In this paper, we proposed a new model for underwater acoustic target recognition, which is based on the deep learning methods (CNN, VGG19, and MobileNet) with modified mechanisms at the end of the network in the ShipsEar dataset. we show that the automatic target recognition of ship-radiated noise with deep learning methods has a relatively more appropriate and reliable performance. This is significant because This research has intensively tried to achieve a proper balance between the accuracy and speed of the networks, so that with the relative improvement of the classification accuracy,they have noticeably reduced the number of parameters and the amount of calculations. The proposed models presented in this paper will run on portable devices and mobile phones. The proposed method aided in the Sonar system's acoustic target classification and recognition. </p>
Letramento acadêmico de estudantes ingressantes em uma instituição de ensino superior do meio norte do Brasil
Authors: Fernandes da Silva Edison , Costa de Sousa Gilcyvan , Letícia Oliveira Silva Amanda , Maria de Sousa Lima Fabrícia 
Published: August 2023

O iletramento acadêmico de ingressantes das Instituições de Ensino Superior e tem sido um limitante à conclusão do curso mais forte do que aspectos financeiros e de outra natureza. Nesse estudo, verificou-se a capacidade de leitura, de interpretação de texto e de produção textual de estudantes ingressantes em uma Instituição Federal de Ensino Superior IFES do Estado do Maranhão, e implementou-se medidas mitigadoras que fomententram a leitura interpretativa e a produção textual. As atividades foram desenvolvidas em duas etapas: (I leitura e intepretação textual; II produção textual) e foram todas aplicadas online através da plataforma Google Classroom. A adesão ao projeto foi baixa e a maior parte da turma foi composta por estudantes do curso de Licenciatura em Biologia. A leitura continuada na etapa I afetou positivamente a produção textual da etapa II. O desempenho dos estudantes na etapa II foi maior do que na etapa I. Os estudantes recém egressos do ensino médio, que participam de projetos de pesquisa, de projetos de ensino, que são bolsistas de iniciação científica e que são oriundos de escolas privadas, apresentaram os níveis mais altos de desempenho em leitura, interpretação de textos e produção textual.
Formulasi dan uji sifat fisik lulur krim ekstrak etanol bunga kecombrang (Etlingera eliator (Jack) R.M. Smith)
Authors: Kurniaty Rina , Ainun Asri , Farida Mutia , Azhari Saiful , Salman Salman , Mahmudi Mahmudi 
Published: August 2023

Tanaman kecombrang (Etlingera eliator (Jack) R.M. Smith), memiliki senyawa bioaktif polifenol, alkaloid, flavonoid, steroid, saponin dan minyak atsiri. Tujuan penelitian ini, untuk membuat formulasi lulur krim dari ekstrak etanol bunga kecombrang yang sesuai standar serta manfaat pada kulit. Metode penelitian ini, dengan memvariasikan konsentrasi dari ekstrak etanol bunga kecombrang 5% dan 10% dengan formulasi modifikasi penambahan amylum oryzae sebagai scrub dan tanpa penambahan amyulum oryzae. Hasil penelitian selama 28 hari berdasarkan parameter, pada uji organoleptis memiliki bentuk, bau, dan warna yang stabil, pada uji homogenitas menunjukan sediaan homogen, uji pH memiliki nilai stabil 7, uji daya sebar nilai rata-rata 5 cm, hasil stabil dalam penyimpanan suhu kamar atau rendah (2-8oC). Hasil uji hedonik dengan parameter, aroma, tekstur, warna, dan efektifitas yaitu formulasi I 10% dengan nilai skala rata- rata 5, yang berarti sangat suka merupakan formulasi dengan penambahan amylum oryzae sebagai scrub. Hasil Formulasi dengan penambahan amylum oryzae berpengaruh pada sediaan formulasi yang abrasive. Hasil uji efektifitas kulit, pada uji kelembapan menggunakan skin analyzer dengan nilai rata- rata kulit sukarelawan lembab pada minggu ke 4, dan warna kulit sukarelawan sedikit lebih cerah. Kesimpulan formulasi lulur krim memiliki formulasi yang baik, ekstrak bunga kecombrang memiliki efek mencerahkan kulit dan melembabkan kulit.
Ações de assistência odontológica hospitalar em pacientes pediátricos do instituto de saúde da criança do Amazonas
Authors: Lamêgo de Oliveira Luanna Gabrielly , Ribeiro Eliane de Oliveira Aranha , Sousa Soares Keuly , Prestes Gimol Benchimol Resende 
Published: August 2023

A Odontologia Hospitalar (OH), é uma habilitação da Odontologia em que o Dentista é responsável pelo tratamento de pacientes internados que apresentam problemas dentários ou infecções bucais durante o período de hospitalização. O objetivo deste estudo foi analisar e quantificar as ações de assistência odontológica hospitalar em um hospital pediátrico. Foi realizado um estudo observacional, descritivo e transversal a partir dos procedimentos provenientes dos atendimentos realizados e coletados das fichas odontológicas idealizadas para este estudo. Os resultados mostraram a realização de 106 procedimentos odontológicos heterogêneos, onde os pareceres odontológicos totalizaram 47%, exodontias com 38%, restaurações 10% e tratamento periodontal 3%. Assim conclui-se que tratamentos odontológicos podem ser realizados em pacientes hospitalizados, quer seja em enfermarias, UTIs ou centro cirúrgico, permitindo uma melhoria do estado de saúde geral do paciente pediátrico internado.
Movilización social, racismo y discriminaciones en los medios de comunicación masiva colombianos durante la pandemia
Authors: Guerrero-Rivera Javier 
Published: August 2023

En este artículo de investigación se analiza un caso de racismo y discriminación contra los indígenas por parte de un medio de comunicación, representante de la élite mediática y de la derecha de Colombia. El hecho acontece en el marco del paro nacional durante el primer semestre de 2021, en plena pandemia ocasionada por el Covid-19, a través de una entrevista radial al gobernador Misak con ocasión del derribamiento de la estatua del colonizador Sebastián de Belalcázar en Cali. Desde la perspectiva de los Estudios Críticos del Discurso se demuestra que, mediante la estrategia discursiva de los binarismos y la victimización empleada por el periodista que conduce la entrevista, se violenta y discrimina a los indígenas. Se concluye que este racismo de élite los denigra como violadores de los derechos humanos de la mayoría del país, guerreristas, odiadores, incivilizados y torpes, lo cual se argumenta desde una ideología colonial, binarista y reduccionista. Con esto, se legitima y reproduce el racismo estructural que atenta contra la dignidad humana, situando a los indígenas (los otros) como cultura inferior destructora de los “valores occidentales” y “decentes” de las élites (nosotros) y, en general, los demás ciudadanos o “la gente de bien”. No obstante, el gobernador Misak construye un contradiscurso que confronta el abuso de poder del periodista y posiciona una imagen positiva del movimiento social indígena frente al reduccionismo de los binarismos del discurso de élite.
Challenges and Benefits of 7 ways Artificial Intelligence in Education Sector
Authors: Tambuskar Sonali 
Published: August 2023

Objective: This article aims to investigate the integration of artificial intelligence (AI) into the education sector and explore its impact on teaching and learning in the digital era. By synthesizing existing literature, the study seeks to provide insights into the benefits and challenges associated with AI's incorporation in education.
Method: A comprehensive review of the literature was conducted using a narrative synthesis approach. Peer-reviewed articles explicitly defining AI within an educational context, published in English and subjected to peer review, were included. Five independent reviewers evaluated research quality, extracted relevant data, and analyzed search results to ensure a comprehensive overview of the field.
Results: The study reveals the significant influence of AI on education. Its implementation is identified as a pivotal and strategic element of educational advancement. The growing role of AI as a digital assistant is particularly noteworthy, facilitating personalized learning experiences for students by tailoring educational resources to individual preferences and subject-specific needs. AI technologies are also instrumental in supporting both teachers and students across various aspects of education.
Conclusions: The integration of AI in education marks a transformative phase for the industry. While AI offers substantial benefits in terms of enhanced learning experiences and increased teacher efficiency, potential drawbacks and concerns are also evident. Privacy, security, and safety issues arising from AI development underscore the need for thoughtful implementation. Thus, AI's impact on education is multifaceted, presenting both positive and negative implications. This study serves as a foundation for stakeholders in education to navigate the evolving landscape, making informed decisions that harness the potential of AI while mitigating its risks. By comprehensively assessing AI's current and future role in education, this research contributes to shaping a balanced and effective utilization of AI technologies in the pursuit of educational excellence.
Astrometry and Photometry for ≈1000 L, T, and Y Dwarfs from the UKIRT Hemisphere Survey
Authors: Schneider Adam C. , Munn Jeffrey A. , Vrba Frederick J. , Bruursema Justice , Dahm Scott E. , Williams Stephen J. , Liu Michael C. , Dorland Bryan N. 
Published: August 2023

Abstract
We present the positions, proper motions, and near-infrared photometry for 966 known objects with spectral types later than M that were observed as part of the the UKIRT Hemisphere Survey (UHS). We augment the photometry and astrometry from UHS with information from Gaia DR3, Pan-STARRS DR2, and CatWISE 2020 to produce a database of homogeneous photometry and astrometry for this sample. The multi-epoch survey strategy of UHS allows us to determine the proper motions for most sources, with a median proper motion uncertainty of ∼3.6 mas yr−1. Our UHS proper motion measurements are generally in good agreement with those from Gaia DR3, Pan-STARRS, and CatWISE 2020, with UHS proper motions typically more precise than those from CatWISE 2020 and Pan-STARRS but not Gaia DR3. We critically analyze the publicly available spectra for 406 members of this sample and provide updated near-infrared spectral types for ∼100 objects. We determine typical colors as a function of spectral type and provide absolute magnitude versus spectral type relations for UHS J- and K-band photometry. Using newly determined proper motions, we highlight several objects of interest, such as objects with large tangential velocities, widely separated co-moving companions, and potential members of young nearby associations.
Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey
Authors: Ghosh অরিত্র Aritra  ঘোষ , Urry C. Megan , Mishra Aayush , Perreault-Levasseur Laurence , Natarajan Priyamvada , Sanders David B. , Nagai Daisuke , Tian 田 Chuan 川 , Cappelluti Nico , Kartaltepe Jeyhan S. , Powell Meredith C. , Rau Amrit , Treister Ezequiel 
Published: August 2023

Abstract
We use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for ∼8 million galaxies in the Hyper Suprime-Cam Wide survey with z ≤ 0.75 and m ≤ 23. GaMPEN is a machine-learning framework that estimates Bayesian posteriors for a galaxy’s bulge-to-total light ratio (L

B
/L

T
), effective radius (R

e
), and flux (F). By first training on simulations of galaxies and then applying transfer learning using real data, we trained GaMPEN with <1% of our data set. This two-step process will be critical for applying machine-learning algorithms to future large imaging surveys, such as the Rubin-Legacy Survey of Space and Time, the Nancy Grace Roman Space Telescope, and Euclid. By comparing our results to those obtained using light profile fitting, we demonstrate that GaMPEN’s predicted posterior distributions are well calibrated (≲5% deviation) and accurate. This represents a significant improvement over light profile fitting algorithms, which underestimate uncertainties by as much as ∼60%. For an overlapping subsample, we also compare the derived morphological parameters with values in two external catalogs and find that the results agree within the limits of uncertainties predicted by GaMPEN. This step also permits us to define an empirical relationship between the Sérsic index and L

B
/L

T
that can be used to convert between these two parameters. The catalog presented here represents a significant improvement in size (∼10×), depth (∼4 mag), and uncertainty quantification over previous state-of-the-art bulge+disk decomposition catalogs. With this work, we also release GaMPEN’s source code and trained models, which can be adapted to other data sets.