bluuebunny/crossref_metadata_2025_split huggingface dataset:
Peran Internet Sebagai Inti Penting di Society 5.0
Authors: Nabil Hidayat Muhamad Farik , Wibawa Aji 
Published: July 2023

The development of digitalization that has occurred in almost all populations around the world has created an active and creative society in all fields. Society 5.0 encourages towards a previously unimaginable reality. In this era, it is possible to develop various sectors to support the formation of an intelligent society. This research results in the role of the internet in various fields to support a more comfortable world for the entire global population. The purpose of this research is to guide society as problem solvers in the evolution of the world in Society 5.0. In addition, there are methods and analysis techniques applied in this paper, so that the research produced is beneficial for society. Some findings in this research are that the internet is the core of Society 5.0 and that society plays an important role in utilizing technology to create an intelligent society and a comfortable world to live in. This research concludes that society must utilize the ability of the internet and media created in Society 5.0 because these three aspects are interconnected to create reality.
Perkembangan digitalisasi yang terjadi hampir semua populasi di seluruh dunia ini, menciptakan masyarakat yang aktif dan kreatif dalam semua bidang. Society 5.0 mendorong menuju realita yang sebelumnya bahkan tidak terpikirkan dapat direalisasikan. Di era ini memungkinkan pengembangan pada berbagai sektor untuk menunjang pembentukan masyarakat yang cerdas. Penelitian ini menghasilkan peran internet dalam berbagai bidang untuk menunjang dunia yang lebih nyaman bagi seluruh populasi dunia. Tujuan dari riset ini bermaksud untuk menuntun masyarakat sebagai pemecah masalah dalam evolusi dunia di society 5.0. Disamping itu, terdapat metode dan teknik analisis yang diterapkan dalam paper ini, agar paper yang dibuat peneliti bermanfaat bagi masyarakat. Beberapa temuan dalam riset ini adalah internet sebagai inti di society 5.0 dan masyarakat memiliki peran penting dalam pemanfaatan teknologi guna menciptakan masyarakat yang cerdas dan dunia yang nyaman untuk dihuni. Penelitian ini menghasilkan kesimpulan bahwa masyarakat harus memanfaatkan kemampuan dari internet serta media-media yang sudah tercipta di society 5.0 karena ketiga hal tersebut saling berhubungan agar terciptanya realitas.
Selected phenotypic and functional changes in ovarian cancer cells treated in vitro with combined therapy using cisplatin and hyperthermia
Authors: Zoń Aleksandra , Bednarek Ilona 
Published: July 2023

WstępTypową strategią leczenia raka jajnika jest operacja chirurgiczna oraz podawana po niej chemioterapia wykorzystująca leki cytostatyczne, w tym cisplatynę. Niestety u większości pacjentek dochodzi do nawrotu choroby, którego głównym powodem jest wykształcanie przez komórki nowotworowe oporności na cisplatynę. Z tego względu intensywnie poszukuje się nowych rozwiązań terapeutycznych, m.in. terapii skojarzonej, której przykładem jest jednoczesne traktowanie komórek lekiem cytostatycznym oraz hipertermią. Celem pracy była ocena zmian fenotypowych oraz funkcjonalnych w komórkach raka jajnika poddanych działaniu cisplatyny i/lub umiarkowanej hipertermii.Materiał i metodyLinie komórek raka jajnika SKOV-3 [ATCC: HTB-77] oraz TOV-21G [ATCC: CRL-11730] stymulowano do apoptozy z wykorzystaniem dichlorku cis-diamino platyny (II). Następnie komórki poddawano działaniu umiarkowanej hipertermii poprzez umieszczenie w temperaturach 39°C i 40°C oraz w temperaturze standardowej 37°C. Zmiany fenotypowe w obrębie badanych komórek weryfikowano z wykorzystaniem barwienia fluorescencyjnego z użyciem oranżu akrydyny, bromku etydyny oraz DAPI (4′,6-diamidyno-2-fenyloindol). Zmiany funkcjonalne odnoszące się do migracji in vitro komórek analizowano testem zarastania rany (<i>wound healing assay</i>).WynikiWykazano, że działanie na komórki cisplatyną indukowało śmierć komórek o charakterze apoptotycznym, przy czym zauważono efekt potencjalizacji działania cytostatyku na komórki poprzez zastosowanie umiarkowanej hipertermii (39°C oraz 40°C). Dodatkowo, w przypadku komórek linii SKOV-3 traktowanych wspomnianymi czynnikami, zaobserwowano istotny statystycznie spadek migracji komórek in vitro w odniesieniu do populacji komórek kontrolnych.WnioskiTraktowanie komórek raka jajnika cisplatyną oraz umiarkowaną hipertermią prowadzi do zmian fenotypowych, charakterystycznych dla procesów apoptozy. Dodatkowo zastosowanie obu tych czynników indukuje takie zmiany w komórkach, które zmniejszają migrację komórek, a tym samym wpływają na zmniejszenie potencjału metastatycznego komórek raka jajnika.
OBTAINING BULK PRODUCTS FROM CU-SIC METAL-MATRIX COMPOSITE FOR ENERGY-EFFICIENT HEAT-CONDUCTING SYSTEMS
Authors: Nikitin Dmitry S. , Shanenkov Ivan I. , Nassyrbayev Artur , Vympina Yuliya N. , Orlova Evgeniya G. , Ivashutenko Alexander S. , Sivkov Alexander A. 
Published: July 2023

Link for citation: Nikitin D.S., Shanenkov I.I., Nassyrbayev A., Vympina Yu. N., Orlova E.G., Ivashutenko A.S., Sivkov A.A. Obtaining bulk products from Cu-SiC metal-matrix composite for energy-efficient heat-conducting systems. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 7, рр. 93-101. In Rus.
The relevance of the research is associated with the rapid development of modern high-performance computing systems, superneurocomputers and artificial intelligence devices. Today such development is held back largely due to the lack of an effective cooling system for high-power elements of their structures. Composite materials Cu-SiC with improved physical, mechanical and thermophysical characteristics can be used to solve problems of heat removal intensification. The main aim of the research is to obtain bulk products from metal-matrix composite Cu-10% SiC with improved physical, mechanical and thermal characteristics by spark plasma sintering. Objects of the research are bulk products from metal-matrix composite Cu-10%SiC. The samples were obtained by spark plasma sintering at temperatures of 700, 750, 800, 850 °C and a pressure of 60 MPa. Methods: spark plasma sintering, X-ray diffractometry (X-ray phase analysis), scanning electron microscopy, indentation, laser flash method. Results. Experimental studies have been carried out to obtain bulk metal-matrix composites with a copper matrix and the addition of reinforcing superhard particles of silicon carbide Cu-10%SiC. The compaction of dispersed composite materials was carried out by spark plasma sintering at various temperatures of 700, 750, 800, and 850 °C. The microstructure and composition of initial dispersed materials and final bulk products have been studied. It is shown that the spark plasma sintering method has advantages for obtaining relatively dense materials with high physical, mechanical and thermal properties. Analysis of the obtained samples showed the formation of a dense (up to ~88 %) homogeneous fine-grained composite structure. The greatest densification of the material is achieved at the highest sintering temperature of 850 °C, which causes this sample to demonstrate the maximum hardness (H=3,63 GPa) and Young's modulus (E=159,63 GPa), as well as the thermal conductivity at room temperature (λ=223 W/m K). The obtained composite materials can be used as structural and functional materials for energy-efficient heat-conducting systems.
Toward Sustainable Economic Growth: Aligning Macroeconomic Policies and Trade with SDG12
Authors: Turkmen Nermin Ceren 
Published: July 2023

This paper examines the complex relationship between macroeconomic policies, international trade practices, and sustainable development within the context of Sustainable Development Goal 12 (SDG12) - promoting sustainable consumption and production. The objective is to explore a path towards sustainable economic growth that balances economic progress and ecological sustainability. A comprehensive analysis of the challenges and opportunities in aligning macroeconomic and trade policies with SDG12 is conducted, complemented by a meticulous review of literature, academic discourse, empirical evidence, and case studies from different countries.
The methodology entails a systematic review of relevant literature, theoretical foundations, and empirical validations, including insightful case studies illustrating successful strategies employed by nations. Practical results demonstrate the potential for successful reconciliation between economic growth and environmental sustainability, offering replicable blueprints for other countries. The paper identifies areas of conflict and symbiosis between macroeconomic and trade policies concerning SDG12.
In conclusion, achieving sustainable economic growth requires cohesive policy formulation, aligning macroeconomic and trade strategies with SDG12. The study proposes specific, implementable policy recommendations to guide countries towards a sustainable trajectory of economic growth while preserving the environment. Emphasizing the significance of coherent policy frameworks, the paper highlights the potential for building a robust, sustainable global economy that addresses growth and environmental conservation simultaneously, contributing to the promotion of sustainable consumption and production worldwide.
Plasma branched-chain amino acid concentrations in individuals without cardiovascular diseases versus patients diagnosed with hypertension and coronary artery disease
Authors: Kozhevnikova M. V. , Korobkova E. O. , Krivova A. V. , Kukharenko A. V. , Moskaleva N. E. , Shestakova K. M. , Mesonzhnik N. V. , Ageev A. A. , Boldin A. A. , Brito A. , Appolonova S. А. , Privalova E. V. , Belenkov Y. N. 
Published: July 2023

Aim. Branched-chain amino acids (BCAAs) have been postulated as potential indicators of cardiovascular risk. The objective of this study was to explore the relationship between plasma BCAAs and different stages of cardiovascular disorders.Material and methods. In our cross-sectional study, plasma BCAAs (valine, leucine and isoleucine) in individuals without cardiovascular diseases (CVDs) (nonCVD group, total n=27, with n=16 healthy, but with metabolic disorders) were compared to patients diagnosed with CVDs [CVD group, total n=109, being n=61 hypertension (n=31 with signs of beginning of myocardial remodeling) and n=48 patients with coronary artery disease (CAD)].Results. The plasma concentration of BCAAs was significantly higher in the group of patients with cardiovascular disease compared with the healthy group (p<0.05 for all amino acids tested): valine concentration was 238.7 [219.6; 267.0] μM in the non-CVD group and 261.2 [233.8; 298.7] μM in the CVD group; leucine concentration was 134.8 [122.4; 153.2] μM and 146.8 [129.0; 166.6] μM, respectively; and isoleucine 72.7 [65.3; 84.4] μM and 81.7 [68.0; 96.2] μM, respectively. Leucine and isoleucine concentration levels were minimal in the healthy participant subgroup and maximal in the IBS patient subgroup. No statistically significant differences in BCAAs concentrations were found in the subgroups without CAD. Significant increases in concentrations were observed in the subgroups of patients with CAD as follows: valine concentration was 256.3 [219.0; 297.9] μM in hypertension group and 261.7 [236.5; 307.5] μM in CAD group; leucine concentration was 141.8 [123.5; 166.6] μM and 154.1 [134.7; 172.7] μM, respectively, and isoleucine 72.8 [65.7; 94.0] μM and 85.7 [74.9; 101.7] μM, respectively. BCAAs profiles in all participants with metabolic disorders had “good” diagnostic accuracy with area under the receiver operating characteristics curve being 0.72, 0.70 and 0.70 for valine, leucine and isoleucine, respectively.Conclusion. BCAAs concentrations are elevated with higher severity of the cardiovascular disorder and exhibit potential as early independent indicators of coronary artery disease.
Evaluation of Asphalt Film Thickness and Metallic Material Leaching of Oxidizing Slag used as Aggregates in Dense-Graded Asphalt Concrete
Authors: Chang Jia-Ruey , Chien Hsiao-Tsun 
Published: July 2023

Abstract
Electric-arc-furnace steelmaking uses scrap iron and steel as raw materials. However, scrap iron and steel have complicated sources and contain heavy metal components, which may be released into the environment after long-term wear and tear. Oxidizing slag is a by-product of the electric-arc-furnace steelmaking process and approximately 1.2 million metric tons of oxidizing slag are produced every year in Taiwan. Substituting oxidizing slag in place of fine aggregates in dense-graded asphalt concrete, the main aims of this study are to evaluate the water resistance and asphalt film thickness, to explore the performance of oxidizing slag as paving material, to examine current regulations for using the dissolved amount and total amount of heavy metals, and to assess the environmental compatibility. The results show that, owing to the complicated sources of oxidizing slag, the basic properties should be checked for each batch and trial mixing should be carried out before producing dense-graded asphalt concrete in order to confirm the mixing time to achieve uniformity. The results also show that using oxidizing slag in dense-graded asphalt concrete yields good performance. In addition, the results of the toxicity characteristic leaching procedure (TCLP) meet the regulation requirements. However, the amounts of heavy metal elements obtained through microwave-assisted aqua-regia digestion exceed the monitoring standards for food crops. Considering environmental compatibility, it is recommended that controlling the total amount of heavy metals in oxidizing slag should be included in regulatory requirements.
FedRCD: A Federated Learning Algorithm Leveraging Distribution Extraction and Community Detection for Enhanced Clustering
Authors: Wang Ruicong , Bian Naizheng , Wu Yingjun 
Published: July 2023

Abstract
Clustering clients and performing federated learning within clusters is an effective method for overcoming the constraint of traditional federated learning algorithms in non-IID data scenarios. However, existing methods often rely on iterative processes and model parameters to represent and cluster clients, resulting in significant computational overhead and unsatisfactory clustering outcomes. To overcome these limitations, we propose a novel one-shot clustering federated learning algorithm called FedRCD. This algorithm extracts distribution information from clients’ datasets in a single step to represent them, reducing the reliance on model parameters. It further organizes clients into a graph and constructs clustering relationships using the Louvain algorithm, removing the need for pre-specifying the number of clusters. Experiments show that FedRCD significantly enhances the training effectiveness of neural networks compared to other federated learning algorithms in various non-IID data scenarios. Notably, on the CIFAR10 dataset, FedRCD achieves an impressive 37.08% accuracy improvement over the classical FedAvg and a 1.89% improvement over the recently released FeSEM, while demonstrating superior fairness performance.
Taxonomic and phylogenetic evidence reveal two new Russula species (Russulaceae, Russulales) from northern Thailand
Authors: Paloi Soumitra , Kumla Jaturong , Karunarathna Samantha , Lumyong Saisamorn , Suwannarach Nakarin 
Published: July 2023

Abstract

Russula is the most diverse genus within the family Russulaceae and has an ectomycorrhizal association with many host trees. During the monsoon season of 2022, five Russula specimens were collected in northern Thailand. After morphological and molecular analyses, the five specimens were determined to belong to Russula subgenus Heterophyllidia. A single specimen belonged to R. bellissima. Four other collected specimens were distinct from all other known species. We have identified these specimens as two new species, namely R. pseudomodesta and R. sribuabanensis. Russula pseudomodesta belongs to the subsection Modestinae, while R. sribuabanensis belongs to the subsection Virescentinae. The phylogenetic placement of two new species within Russula has been confirmed based on sequences of the nuclear internal transcribed spacer (nrITS) region and a large subunit (nrLSU) of the nuclear ribosomal RNA (nrRNA). Comprehensive morphological descriptions, field photographs, and comparisons of two new species with other morphologically and phylogenetically closely related species have been provided.
3D finite element analysis of stress distribution in dental tissues and materials as a result of oblique and horizontal forces after regenerative endodontic treatment Part II: Comparison of Material Thickness
Authors: Demircan Beril , Demir Pınar 
Published: July 2023

Abstract
Aim
This study aimed to evaluate the stress distribution caused by secondary trauma forces after regenerative endodontic treatment (RET) using different thicknesses of coronary barrier material, with three-dimensional finite element analysis(FEA).
Method
A control model was created using the tomography image of the immature maxillary central tooth with computer software. Study models were created with the modulus of elasticity and Poisson’s ratio of the materials used in RET.Enamel, dentin, cementum, periodontal ligament, cortical, and cancellous bone were modeled. Coronary barrier materials were applied in 3mm and 5mm thicknesses(Model 1:control model, model 2:3mm/Calcium Enriched Mixture(CEM), model 3:3mm/Mineral Trioxide Aggregate(MTA), model 4:3mm/Biodentin, model 5:5mm/CEM, model 6:5mm/MTA, model 7:5mm/Biodentin). Forthe trauma force simulation, 300N force in the horizontal direction was applied to the buccal surface of the tooth in the first scenario. For the second scenario, maximum bite force simulation, a force of 240N in the oblique direction was applied to the palatal surface of the tooth. FEA was performed with Algor Fempro. The resulting stresses were recorded as Von Mises, maximum and minimum principal stresses.
Results
Lower stress values were obtained in 5mm models compared to 3mmmodels. However, the difference between them was insignificant. Lower stress values were obtained in all RET models compared to the control model. The lowest stress values in dental tissues and bone tissue were obtained inthe CEM models.
Conclusion
This is the first study in which the stress caused by different thicknesses of CEM on dental tissues was evaluated with FEA. RET strengthens immature teeth biomechanically CEM andBiodentin are more successful materials in stress distribution than MTA. Considering the cost of treatment, 3 mm material thickness is ideal for RET since there is no significant difference between the stress values resulting from the use of 5mm and 3mm coronary barrier material.
Trajectories of Dental Caries From Childhood to Young Adulthood: Unsupervised Machine Learning Approach
Authors: Ogwo Chukwuebuka , Levy Steven , Warren John , Caplan Daniel , Brown Grant 
Published: July 2023

Abstract
Objective To determine the dental caries trajectories over the life course (from age 9 to 23) using an unsupervised machine learning approach.Methods This is a longitudinal study of caries trajectories over a life course using data from 1,382 individuals from the Iowa Fluoride Study birth cohort. The trajectory analysis of caries in the permanent dentition at ages 9, 13, 17 and 23 was performed using the unsupervised machine learning algorithm known as K-means for Longitudinal Data (KmL), a k-means based clustering algorithm implemented in R specifically designed for analyzing longitudinal data. The trajectory grouping was performed by assessing the distances of the individual trajectories from the centroid and the prediction of the “best” partition was performed based on the Calinsky & Harabatz criterion. The number of cluster partitions assessed was 2 to 6. The number of re-runs with different starting conditions for each number of clusters was 20.Results The trajectory analysis identified three trajectory groups with 70.5%, 21.1%, and 8.4% of participants in the low, medium, and high caries trajectory groups, respectively. The mean D2+MFS counts of the low caries trajectory groups at ages 9, 13, 17, and 23 were 0.23, 0.37, 1.10, and 1.56, respectively. The mean D2+MFS counts of the medium caries trajectory groups at ages 9, 13, 17, and 23 were 0.92, 2.09, 6.24, and 9.55, respectively. The mean D2+MFS counts of the high caries trajectory groups at ages 9, 13, 17, and 23 were 1.49, 4.80, 12.91, and 22.52, respectively. There were steeper increases in the D2+MFS scores of the three trajectory groups between age 13 and 17, with less steep but also strongly positive slopes from age 17 to 23, suggesting that the period from age 13 to 17 is the highest risk period.Conclusion There was an increase in the trajectory slopes after age 13 which might be due to changes in risk factors. The next step in this study will be to identify those factors that predict trajectory group membership by modeling their relationships using supervised machine learning techniques.
Uncovering Drone Intentions using Control Physics Informed Machine Learning
Authors: Perrusquia Adolfo , Guo Weisi , Fraser Benjamin , Wei Zhuangkun 
Published: July 2023

Abstract
Fully autonomous aerial platforms or drones are increasingly used across diverse application areas. Uncooperative drones do not announce their identity nor file flight plans and can pose a potential risk to a variety of critical infrastructures. Understanding an uncooperative drone's intention is important to assigning risk and executing countermeasures. Drones have rapidly changing design, flexible capabilities, and diverse underpinning algorithms. This makes distinguishing malicious from naive intentions across platforms difficult. Intentions are often intangible and unobservable, and a variety of tangible intention classes are often inferred as a proxy. However, inference of drone intention classes (e.g., via inverse learning) using observational data alone is inherently unreliable due to observational and learning bias.

Here we develop a novel control-physics informed machine learning (CPhy-ML) that can robustly infer across intention classes, out performing over expert-defined anomaly detection and inverse learning approaches. Our CPhy-ML complementary learning couples the representation power of deep learning with the conservation laws of aerospace control models, reducing bias and instability. The results in simulation and experimentation demonstrate that we can find common intention patterns across the inferred intention classes, ranging from trajectory to reward goals. We believe that this framework can provide deeper insight into the complex nature of intention and a firm step towards to its smooth integration in current counter drone technologies. The techniques developed here can aid the enforcement of drone incursions in a time where geo-fencing is no-longer efficiently enforceable. As transport and operational autonomy is increasingly used, enforcement algorithms can also inform the design of better criminal justice system and safer autonomous systems themselves.