bluuebunny/crossref_metadata_2025_split huggingface dataset:
ВПЛИВ ВИКОРИСТАННЯ РОЗКЛАДУ ЗАНЯТЬ ДЛЯ ПРОГРАМУВАННЯ ТЕРМОСТАТІВ НА ЕНЕРГОСПОЖИВАННЯ БУДІВЛІ ШКІЛЬНОГО ЗАКЛАДУ
Authors: ДЕШКО В. І. , ГОЛУБЕНКО О. О. 
Published: March 2024

Вступ. Варіації пониження температури в періоди невикористання будівлі показало свою ефективність, як захід з енергозбереження. Проте, в заходах пов’язаних з терморегулювання зберігається потенціал енергозбереження, пов’язаний з більш детальними графіками опалення. Дослідження переваг та недоліків детальних графіків опалення для програмування термостатів стає важливим напрямком в розвитку сучасних систем опалення та кондиціонування.
Мета. Метою даного дослідження є дослідження переваг та недоліків впровадження терморегулювання системи опалення на базі шкільного розкладу уроків.
Методика. Дослідження виконуються на базі енергетичного моделювання у програмному середовищі DesiqnBuilder.
Результати. За результатами енергетичного моделювання будівлі було дослідження вплив впровадження графіку опалення на основі розкладу шкільних занять для будівель з різним рівнем теплового захисту. Графік опалення оснований на розкладі занять показав ряд переваг перед простішим графіком з провалами в неробочі години, а саме, вищу на понад 3% енергоефективність і зниження пікового навантаження на систему опалення на 3,3–3,7%.
Наукова новизна. Дослідження впливу впровадження графіку опалення основаного на розкладі занять на енергоефективність в будівлі школи та комфортність перебування людей в приміщеннях.
Практична значимість. Врахування кліматичних та будівельних особливостей, а також нівелювання впливу людського фактору, шляхом впровадження програмованих термостатів, може сприяти розробці ефективних стратегій управління опаленням, що в свою чергу призведе до значної економії енергоресурсів.
Microstructural Evolution in a Ni- Based Superalloy for Power Plant Applications as a Consequence of High Temperature Degradation and Rejuvenation Heat Treatments
Authors: Yao Z. , Jepson M. A. E. , Thomson R. C. , Degnan C. C. 
Published: March 2024

Abstract
The microstructural evolution of the Ni-based superalloy CMSX-4 including the change in gamma prime size and distribution and the degree of rafting has been examined in detail using field emission gun scanning electron microscopy (FEGSEM) and transmission electron microscopy (TEM) after high temperature degradation and rejuvenation heat treatments. The relationship between the microstructure, mechanical properties and the applied heat treatment procedures has been investigated. It is shown that there are significant differences in the rafting behaviour, the size of the ‘channels’ between the gamma prime particles, the degree of rafting and the size of the tertiary gamma prime particles in each of the different microstructural conditions studied. Chemical segregation investigations were carried out to establish the cause of reduced mechanical properties of the rejuvenated sample after high temperature degradation compared to an as-received sample after the same degradation procedure. The results indicate that although the microstructure of as-received and rejuvenated samples were similar, the chemical segregation was more pronounced in the rejuvenated samples, suggesting that chemical segregation from partitioning of the elements during rejuvenation was not completely eliminated. The aim of this research is to provide greater understanding of the suitability of rejuvenation heat treatments and their role in the extension of component life in power plant applications.
The Figure of Jan Czochralski as an Example of a Scientist, Teacher and Patriot for the Youth of Today to Imitate (1885 – 1953)
Authors: Yankovych Oleksandra , Verbets Vladyslav 
Published: March 2024

The article analyses the life path and activities of the world-recognized Polish scientist, inventor, metallurgist, patron and philanthropist, writer, professor of the Warsaw Polytechnic Jan Czochralski (1885 - 1953). He is considered one of the four most famous and most cited Polish scientists who influenced the development of civilization. In terms of the greatness and significance of his scientific achievements, he is placed in the same row as the world-famous Poles M. Copernicus, M. Skłodowska-Curie, I. Łukasiewicz, who not only glorified Poland, but also changed the world. The purpose of the article is to study and analyze the main milestones of J. Czochralski's creative activity and the role of his scientific achievements. Research methods. Theoretical methods were used as synthesis analysis, systematization, comparison, classification, generalization. The results. The life path, the main stages of Jan Czochralski's activity against the background of historical events of the end of the 19th and the first half of the 20th centuries are revealed. The trials that the scientist underwent, unjust accusations of helping the Third Reich, and the reasons for his persecution are shown (he was fully rehabilitated only in 2011). Patriotism, hard work, perseverance, humanism, which contributed to successful teaching activities are emphasized as the personal qualities of Jan Czochralski. The most important achievements of the outstanding Polish scientist are analysed: the method of growing silicon single crystals, which are used in modern electronic and digital technology, in solar energy, and in jewellery; the discovery of alloys for railway bearings (known as B-metal); the invention of the radio microscope as the predecessor of the modern atomic force microscope, the enrichment of research tools. Jan Czochralski is a scientist, inventor, metallurgist, and philanthropist. He started processes that we now interpret as technology transfer. He is an author of poetry collections and manuals, a university professor who created a new image of a teacher, an entrepreneur and a person who believed in family values. He was a comprehensively developed personality who combined intellectual achievements and aesthetics, spiritual and moral qualities and hard work. Conclusions. The expediency of wider popularization of the figure of J. Czochralski in modern educational institutions as a comprehensively developed personality, as a model for younger generations to follow is shown.
Deep learning approaches for breast cancer detection in histopathology images: A review
Authors: Priya C V Lakshmi , V G Biju , B R Vinod , Ramachandran Sivakumar 
Published: March 2024

BACKGROUND: Breast cancer is one of the leading causes of death in women worldwide. Histopathology analysis of breast tissue is an essential tool for diagnosing and staging breast cancer. In recent years, there has been a significant increase in research exploring the use of deep-learning approaches for breast cancer detection from histopathology images. OBJECTIVE: To provide an overview of the current state-of-the-art technologies in automated breast cancer detection in histopathology images using deep learning techniques. METHODS: This review focuses on the use of deep learning algorithms for the detection and classification of breast cancer from histopathology images. We provide an overview of publicly available histopathology image datasets for breast cancer detection. We also highlight the strengths and weaknesses of these architectures and their performance on different histopathology image datasets. Finally, we discuss the challenges associated with using deep learning techniques for breast cancer detection, including the need for large and diverse datasets and the interpretability of deep learning models. RESULTS: Deep learning techniques have shown great promise in accurately detecting and classifying breast cancer from histopathology images. Although the accuracy levels vary depending on the specific data set, image pre-processing techniques, and deep learning architecture used, these results highlight the potential of deep learning algorithms in improving the accuracy and efficiency of breast cancer detection from histopathology images. CONCLUSION: This review has presented a thorough account of the current state-of-the-art techniques for detecting breast cancer using histopathology images. The integration of machine learning and deep learning algorithms has demonstrated promising results in accurately identifying breast cancer from histopathology images. The insights gathered from this review can act as a valuable reference for researchers in this field who are developing diagnostic strategies using histopathology images. Overall, the objective of this review is to spark interest among scholars in this complex field and acquaint them with cutting-edge technologies in breast cancer detection using histopathology images.
Automated license plate authentication framework using multi-view vehicle images
Authors: Ganesh M.A. , Saravana Perumaal S. , Gomathi Sankar S.M. 
Published: March 2024

The current framework for detecting Fake License Plates (FLP) in real-time is not robust enough for patrol teams. The objective of this paper is to develop a robust license plate authentication framework, based on the Vehicle Make and Model Recognition (VMMR) and the License Plate Recognition (LPR) algorithms that is implementable at the edge devices. The contributions of this paper are (i) Development of license plate database for 547 Indian cars, (ii) Development of an image dataset with 3173 images of 547 Indian cars in 8 classes, (iii) Development of an ensemble model to recognize vehicle make and model from frontal, rear, and side images, and (iv) Development of a framework to authenticate the license plates with frontal, rear, and side images. The proposed ensemble model is compared with the state-of-the-art networks from the literature. Among the implemented networks for VMMR, the Ensembling model with a size of 303.2 MB achieves the best accuracy of 89% . Due to the limited memory size, Easy OCR is chosen to recognize license plate. The total size of the authentication framework is 308 MB. The performance of the proposed framework is compared with the literature. According to the results, the proposed framework enhances FLP recognition due to the recognition of vehicles from side images. The dataset is made public at https://www.kaggle.com/ganeshmailecture/datasets.
smart-KG: Partition-Based Linked Data Fragments for querying knowledge graphs
Authors: Azzam Amr , Polleres Axel , D. Fernández Javier , Acosta Maribel 
Published: March 2024

RDF and SPARQL provide a uniform way to publish and query billions of triples in open knowledge graphs (KGs) on the Web. Yet, provisioning of a fast, reliable, and responsive live querying solution for open KGs is still hardly possible through SPARQL endpoints alone: while such endpoints provide a remarkable performance for single queries, they typically can not cope with highly concurrent query workloads by multiple clients. To mitigate this, the Linked Data Fragments (LDF) framework sparked the design of different alternative low-cost interfaces such as Triple Pattern Fragments (TPF), that partially offload the query processing workload to the client side. On the downside, such interfaces still come with the expense of unnecessarily high network load due to the necessary transfer of intermediate results to the client, leading to query performance degradation compared with endpoints. To address this problem, in the present work, we investigate alternative interfaces, refining and extending the original TPF idea, which also aims at reducing server-resource consumption, by shipping query-relevant partitions of KGs from the server to the client. To this end, first, we align formal definitions and notations of the original LDF framework to uniformly present existing LDF implements and such “partition-based” LDF approaches. These novel LDF interfaces retrieve, instead of the exact triples matching a particular query pattern, a subset of pre-materialized, compressed, partitions of the original graph, containing all answers to a query pattern, to be further evaluated on the client side. As a concrete representative of partition-based LDF, we present smart-KG+, extending and refining our prior work (In WWW ’20: The Web Conference 2020 (2020) 984–994 ACM / IW3C2) in several respects. Our proposed approach is a step forward towards a better-balanced share of the query processing load between clients and servers by shipping graph partitions driven by the structure of RDF graphs to group entities described with the same sets of properties and classes, resulting in significant data transfer reduction. Our experiments demonstrate that the smart-KG+ significantly outperforms existing Web SPARQL interfaces on both pre-existing benchmarks for highly concurrent query execution as well as an accustomed query workload inspired by query logs of existing SPARQL endpoints.
Research on the use of sensor networks in underwater technologies
Authors: Delembovskyi Maksym , Korniychuk Boris , Klymenko Mykola , Diachenko Oleksandr 
Published: March 2024

This study focuses on the application of sensor networks in the field of underwater technologies, opening new possibilities for monitoring and researching the marine environment. Main attention is given to the development and implementation of sensor systems capable of withstanding high pressure and corrosion in the underwater environment, as well as providing accurate and reliable data.
The work covers the theoretical aspects of sensor networks, including their design, functional capabilities, and challenges associated with their use in the underwater environment. Particular attention is paid to data transmission methods and energy conservation in conditions of limited access to energy.
The next component of the work is the analysis of the practical aspects of implementing sensor networks, particularly considering their application for monitoring water resources, studying marine fauna and flora, and in underwater archaeological research. The work emphasizes the importance of these technologies for collecting data about the seabed, its relief, and ecosystem.
This scientific work considers the prospects for the development of sensor networks in underwater research, including integration with other technologies, such as autonomous underwater vehicles, and the development of new materials and technologies to enhance the efficiency and durability of sensor systems.
Analysis of the state of development of the issue of protection of critical infrastructure facilities using engineered munitions
Authors: Lenkov Serhii , Kryvtsun Volodymyr , Miroshnichenko Oleg , Golushko Serhii , Ruslan Koltsov 
Published: March 2024

The Russian-Ukrainian war at the stage of full-scale invasion has shown that one of the most difficult tasks of ensuring the survivability of troops and the functioning of critical infrastructure is to protect them from high-precision weapons, namely cruise and ballistic missiles and unmanned aerial vehicles.
The experience of warfare shows that the existing domestic air defense systems do not fully defeat air targets, while highly effective foreign-made air defense systems are supplied in insufficient quantities, and the created mobile fire groups to destroy air targets are not always effective. In these circumstances, it is advisable to consider new integrated approaches to the use of various types of weapons in the active defense of troops and critical infrastructure against air attack.
The complex construction of a system of active defense of troops and critical infrastructure against air attack is possible with the use of several types of weapons. Based on the analysis of the enemy's use of missiles of various classes and Shahed-type attack unmanned aerial vehicles, the paper proposes the use of engineered munitions as one of the means of defeating moving air targets that fly low at low speed. The use of special engineered ammunition will make it possible to increase the range of low-flying air targets and increase the likelihood of their defeat. This will improve the effectiveness of the existing system of protecting troops and critical infrastructure from air attack.
The paper analyzes the use of air attack weapons of the Russian Federation against troops and critical infrastructure facilities of Ukraine, substantiates proposals on the expediency of using engineered ammunition as an element of building a system of active protection of troops and critical infrastructure facilities from air attack, and presents their principle of operation and possible applications.
Pengaruh Terpaan Informasi Stunting di Media Sosial dan Intensitas Penyuluhan Terhadap Perilaku Pencegahan Stunting Pada Ibu Yang Memiliki Balita di Kabupaten Deli Serdang Provinsi Sumatera Utara, Indonesia
Authors: Nurhasanah Pratiwi  , Kurniawati Dewi , Nurbani  
Published: March 2024

ABSTRAKPenelitian ini bertujuan untuk menganalisis seberapa besar pengaruh terpaan informasi stunting di media sosial dan intensitas penyuluhan terhadap perilaku pencegahan stunting serta seberapa besar pengaruhnya jika dimoderasi tingkat pendidikan. Teori yang digunakan dalam penelitian adalah teori pembelajaran sosial. Penelitian ini menggunakan pendekatan kuantitatif dengan metode korelasional. Penelitian dilakukan di Kecamatan Percut Sei Tuan dengan total responden sebanyak 388 orang melalui penentuan sampel menggunakan purposive sampling dengan kriteria ibu yang memiliki balita, pernah mendengar informasi terkait stunting, menggunakan media sosial, serta pernah mengikuti kegiatan penyuluhan. Teknik pengumpulan sampel menggunakan teknik proportional random sampling dimana jumlah sampel pada masing-masing strata memiliki jumlah yang bervariasi atau dalam hal ini dibagi ke dalam tiap-tiap kelurahan sebanyak 20 kelurahan di kecamatan Percut Sei Tuan. Data yang sudah terkumpul kemudian di analisis dan di uji menggunakan teknik analisis data yaitu analisis regresi linear berganda dan uji interaksi moderated regression analysis (MRA). Hasil penelitian ini menunjukkan terpaan informasi stunting melalui media sosial dan intensitas penyuluhan berpengaruh secara simultan dan signifikan terhadap perilaku pencegahan stunting dengan besaran pengaruh yang muncul sebesar 9,6% dan setelah dimoderasi pengaruhnya menjadi sebesar 12,3 % terhadap perilaku pencegahan stunting.
ABSTRACTThis study aims to analyze how much influence stunting information exposure has on social media and the intensity of counseling on stunting prevention behavior and how big the effect is if it is moderated by the level of education. The theory used in this research is social learning theory. This study uses a quantitative approach with correlational methods. The research was conducted in Percut Sei Tuan Sub-District with a total of 388 respondents by determining the sample using purposive sampling with the criteria of mothers who have toddlers, have heard of information related to stunting, used social media, and have participated in counseling activities. The sample collection technique used a proportional random sampling technique in which the number of samples in each stratum varied, or in this case it was divided into 20 villages in Percut Sei Tuan sub-district. The data that has been collected is then analyzed and tested using data analysis techniques, namely multiple linear regression analysis and moderated regression analysis (MRA) interaction test. The results of this study indicate that exposure to stunting information through social media and the intensity of counseling have a simultaneous and significant effect on stunting prevention behavior with a magnitude of 9.6% and after being moderated the effect becomes 12.3% on stunting prevention behavior.
comercio minorista ante 2024
Authors: Gradolph Cadierno Juan Enrique 
Published: March 2024

El comercio minorista mantuvo durante 2023 una senda expansiva y presenta buenas perspectivas para el año 2024. El crecimiento de la actividad y la contribución a la generación de empleo son generalizados en los distintos formatos comerciales y más intensos en aquellos en los que hay mayor presencia de empresas de gran tamaño.
El sector avanza hacia la transformación de su estructura empresarial, la mejora de su competitividad y la transición hacia un modelo de omnicanalidad que aproveche las ventajas del comercio electrónico. Las acciones públicas puestas en marcha en el marco del Plan de Recuperación, Transformación y Resiliencia son claves para que pueda afrontar estos desafíos y reforzar su contribución a la cohesión social y territorial.
External validation of a minimal-resource model to predict reduced estimated glomerular filtration rate in people with type 2 diabetes without diagnosis of chronic kidney disease in Mexico: a comparison between country-level and regional performance
Authors: Sammut-Powell Camilla , Sisk Rose , Silva-Tinoco Ruben , de la Pena Gustavo , Almeda-Valdes Paloma , Juarez Comboni Sonia Citlali , Goncalves Susana , Cameron Rory 
Published: March 2024

BackgroundPatients with type 2 diabetes are at an increased risk of chronic kidney disease (CKD) hence it is recommended that they receive annual CKD screening. The huge burden of diabetes in Mexico and limited screening resource mean that CKD screening is underperformed. Consequently, patients often have a late diagnosis of CKD. A regional minimal-resource model to support risk-tailored CKD screening in patients with type 2 diabetes has been developed and globally validated. However, population heath and care services between countries within a region are expected to differ. The aim of this study was to evaluate the performance of the model within Mexico and compare this with the performance demonstrated within the Americas in the global validation.MethodsWe performed a retrospective observational study with data from primary care (Clinic Specialized in Diabetes Management in Mexico City), tertiary care (Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán) and the Mexican national survey of health and nutrition (ENSANUT-MC 2016). We applied the minimal-resource model across the datasets and evaluated model performance metrics, with the primary interest in the sensitivity and increase in the positive predictive value (PPV) compared to a screen-everyone approach.ResultsThe model was evaluated on 2510 patients from Mexico (primary care: 1358, tertiary care: 735, ENSANUT-MC: 417). Across the Mexico data, the sensitivity was 0.730 (95% CI: 0.689 – 0.779) and the relative increase in PPV was 61.0% (95% CI: 52.1% - 70.8%). These were not statistically different to the regional performance metrics for the Americas (sensitivity: p=0.964; relative improvement: p=0.132), however considerable variability was observed across the data sources.ConclusionThe minimal-resource model performs consistently in a representative Mexican population sample compared with the Americas regional performance. In primary care settings where screening is underperformed and access to laboratory testing is limited, the model can act as a risk-tailored CKD screening solution, directing screening resources to patients who are at highest risk.