bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Multi-Modal Fusion Model for Identification of Eight Different Particles in Urinary Sediment
Authors: Tuncer Seda Arslan , Çınar Ahmet , Erkuş Merve , Tuncer Taner 
Published: August 2024

Abstract
Urine sediment examination (USE) is an essential aspect in detecting urinary system diseases, and it is a prerequisite for diagnostic procedures. Urine images are complex, containing numerous particles, which makes a detailed analysis and interpretation challenging. It is crucial for both patients and medical professionals to conduct urine analysis automatically, quickly and inexpensively, without compromising reliability. In this paper, we present a deep multi-modal fusion system, commonly employed in artificial intelligence, capable of automatically distinguishing particles in urine sediment. To achieve this objective, we first created a new dataset comprising erythrocytes, leukocytes, yeast, epithelium, bacteria, crystals, cylinders, and other particles (such as sperm). The data were gathered from urinalysis requests made between July 2022 and September 2022 at the biochemistry laboratory of Fethi Sekin Medical Center Hospital. A dataset containing 8509 images was compiled using the Optika B293PLi microscope with trinocular brightfield. We propose a 5-step process for detecting particles in the dataset using a multi-modal fusion deep learning model: i) The obtained images were augmented by applying affine transformation. ii) To distinguish images, we opted for ResNet18 and ResNet50 models, which yielded high performance in medical data. iii) Feature vectors from both models were fused to generate more consistent, accurate, and useful particle features. iv) We employed ReliefF, Neighborhood Component Analysis (NCA), and Minimum-Redundancy Maximum-Relevancy (mRMR) feature selection methods, widely used to determine features that maximise particle discrimination success. v) In the final step, Support Vector Machine (SVM) was utilised to distinguish the particles. The results demonstrate that the highest accuracy value achieved is 98.54 % when employing the ReliefF algorithm. Contributions of the study include eliminating standardisation differences in manual microscopy, achieving high accuracy in particle discrimination, offering an artificial intelligence-based system applicable in laboratory environments, and providing the dataset as educational and practical material for biochemistry professionals.
Analysis of the Compressed Video with HEVC under Optical Link Transmission
Authors: Boukhatem Nadira , Messaoudi Kamel , Redjati Abdelghani , Brik Fatima , Nasri Amani 
Published: August 2024

Abstract
We study the feasibility of video transmission over optical fibre to optimise bandwidth with the implementation of HEVC codec features. We use simulation (Matlab and the OptiSystem software). Different values of the CRF are used to evaluate its impact on the visual quality and the size of the encoded file, as well as its influence on the video transmission performance. The simulation results show that by adjusting the CRF, the encoders can optimise the compression of the video data to reduce the file size while preserving an acceptable visual quality. This makes it possible to adapt the transmission to the bandwidth constraints of the optical fibre, by choosing higher CRF values to reduce the size of the files and save bandwidth, or lower values to maintain optimal quality when the bandwidth is sufficient. In addition, from the optical fibre point of view, the dispersion weakens and the eye opens, and it is observed that the length of the fibres is inversely proportional to the signal transmission quality. Thus, the judicious use of different CRF values can contribute to efficient and high-quality video transmission via optical fibre.
Deep Learning-Based Renal Stone Detection: A Comprehensive Study and Performance Analysis
Authors: Ravisankar Priyadharsini , Balaji Varsha , T Shahul Hameed 
Published: August 2024

Abstract
Early kidney stone detection is essential for the diagnosis and treatment of people who have kidney stones. The objective of this study is to employ deep learning algorithms for renal stone detection, addressing the critical need for early, accurate diagnosis, which can significantly improve patient outcomes and reduce healthcare costs. The paper thoroughly assesses a variety of models, including ResNet, DenseNet, and EfficientNet, for CT images. The limitations of manual identification procedures highlight the urgent need for a more effective automated approach, making this research necessary. Notably, the painstakingly improved DenseNet model achieves a peak accuracy of 0.86, demonstrating its potential superiority. These results convincingly demonstrate the revolutionary power of deep learning, which is poised to revolutionise the detection of renal stones. This fast, trustworthy, and non-invasive method has the potential to advance clinical procedures and significantly improve patient care.
Knowledge Elicitation Using the Delphi Technique in Developing Diagnosis Systems
Authors: Olayiwola Abisola , Afolabi Adekunle , Olayiwola Dare , Oyedeji Ajibola 
Published: August 2024

Abstract
Knowledge elicitation is important in designing knowledge-based diagnosis systems. Various approaches such as interviews and questionnaires have been used to elicit knowledge from experts. These approaches elicit knowledge from individual experts separately. Medical practitioners have diverse knowledge and experience in the diagnosis and management of a particular disease. A major challenge is in producing a harmonised diagnosis from different practitioners, which will inform the level of agreement among them on the treatment of Sickle Cell Disease (SCD). Therefore, it is important to elicit and integrate knowledge from different medical practitioners in developing an effective diagnosis system. Thus, the Delphi technique was employed in this study to elicit domain knowledge in developing SCD diagnosis systems in African Traditional Medicine (ATM) since there is no gold standard for achieving diagnosis in ATM. A kappa value of 0.487 was achieved. This implies that the Herb sellers averagely agree in the ranking of the SCD symptoms. Therefore, to build an effective SCD diagnosis system, further work should be done by conducting more Delphi rounds to ensure that a high level of consensus is reached. The Delphi technique used in this study helped in the area of requirement elicitation of SCD diagnosis in ATM which could be used in the development of an SCD diagnosis system.
Customer Value and Sustainable Choice Behaviour in Social Commerce
Authors: Kanimozhi G. , Sengottuvel C. 
Published: August 2024

Abstract
The emergence of Social Commerce, facilitated by social media platforms such as Facebook, Snapchat, and Instagram, has revolutionized electronic commerce, reshaping consumer behavior and business dynamics. This study investigates the connection between customer value and sustainable choice behavior in Social Commerce, focusing on individuals aged 18 and above actively engaged with these platforms. Employing a convenience sampling method and a survey of 383 participants, a structural equation model was utilized to assess various hypotheses. The findings highlight the significant impact of word of mouth, intention, offers, and trust on purchase decisions within Social Commerce. These factors play pivotal roles in shaping customer perspectives, emphasizing the importance of integrating online brand communities into marketing and communication strategies. By leveraging social media, vendors can facilitate the discovery, sharing, recommendation, and transaction of goods and services, enhancing customer value and promoting sustainable choices. This study contributes to the understanding of consumer behavior in the context of Social Commerce, offering insights for businesses to adapt and thrive in an increasingly digital marketplace.
EU Concerns About Chinese Subsidies: What the Evidence Suggests
Authors: Bickenbach Frank , Dohse Dirk , Langhammer Rolf J. , Liu Wan-Hsin 
Published: August 2024

Abstract
China uses subsidies extensively to take a leading role in the global markets of green-tech products such as battery electric vehicles and wind turbines. Against the background of the current EU investigations into Chinese subsidies in these sectors, this article takes a careful look at the Chinese subsidy system and provides new data on direct government subsidies to leading Chinese producers of electric cars and wind turbines. Extensive government support has allowed Chinese companies to scale up rapidly, to dominate the Chinese market and to expand into foreign markets. The article concludes that the EU should use its strong bargaining power due to the single market to induce the Chinese government to abandon the most harmful subsidies.
Greening Central Bank Policies: Euro Area vs Non-Euro Area EU Member States
Authors: Vollmer Uwe 
Published: August 2024

Abstract
Climate change has become relevant for central banks worldwide, but they are adopting their instruments at different speeds. This article compares the reactions of the Eurosystem with those of the other EU central banks. Do these central banks differ in their efforts to make their own policies “greener”? The article argues that the options and constraints to react to climate change diverge between central banks.
Analysis of the unsaturated hydraulic properties of rocks using multiple laboratory methods
Authors: Zhuang Luwen , Hoerlle Fernanda O. , Chen Hao , Pontedeiro Elizabeth M. , van Genuchten Martinus Th. , Couto Paulo , Qin Chao-Zhong , Lin Kairong 
Published: August 2024

Abstract
Proper characterization of the unsaturated hydraulic properties in rocks is significant for predicting fluid flow in soil, hydrogeologic, and petroleum science and engineering problems. In this study, we contributed rigorous analysis of the unsaturated hydraulic properties of three reservoir rock samples (Berea Sandstone, Guelph Dolomite, and Indiana Limestone). An improved version of the standard evaporation method (HYPROP) was developed to cater specifically to rock samples. The improved HYPROP setup enables measurements of local water pressures within rock samples without disturbing the upper portion of the samples. The obtained results were compared with those obtained using the conventional pressure plate method and a state-of-the-art nuclear magnetic resonance (NMR) method. Observed data were analyzed in terms of four different unimodal and bimodal hydraulic functions. The HYPROP data were found to be relatively close to the pressure plate data of two carbonate rocks. The NMR-based data were reasonably consistent with the HYPROP data, with differences likely due in part to the fact that they were obtained using two different 5-cm long plugs taken from the same core. Heterogeneity along the rock cores from which the samples were taken could be a major reason for the observed differences, and hence should be considered in reservoir analyses.
A theoretical underpinning of the pesticide Groundwater Ubiquity Score (GUS)
Authors: Steenhuis Tammo S. , Brindt Naaran , Pacenka Steven , Richards Brian K. , Parlange J.-Yves , Hassanpour Bahareh 
Published: August 2024

Abstract
The Groundwater Ubiquity Score (GUS) is widely used to indicate the relative leachability of pesticides based on the soil half-life and the adsorption partition coefficient. In this manuscript, we derive mathematically the Theoretical Groundwater Ubiquity Score (TGUS) that, based on considerations of the preferential movement of pesticides to groundwater and a first-order pesticide degradation model, leads to a similar function as the GUS model. In the preferential flow model, movement to groundwater is fast, and the adsorption partition coefficient is thus not used for calculating the travel time to the groundwater (as it is in the advective-dispersive equation) but rather only determines the distribution of the pesticide between the water and soil phases. Both the GUS and TGUS models well predict the groundwater contamination of the originally studied pesticides for rainfall event(s) that caused pesticide leaching from 30 days after application. The theoretically derived Groundwater Ubiquity Score (TGUS) shows, in accordance with experimental evidence, that for leaching events shortly after spraying, the mass lost to (and resulting concentration in) groundwater is inversely related to the adsorption partition coefficient and not necessarily to the GUS index.
Empirical and physical modelling of soil erosion in agricultural hillslopes
Authors: Bueno-Hurtado Palmira , Seidou Ousmane 
Published: August 2024

Abstract
Soil erosion is a complex and highly heterogeneous process with a wide range of environmental and economic impacts. Its estimation is particularly challenging and modelling is typically used for erosion estimation over large areas. The aim of this study was to compare the two leading empirical and physical erosion estimation models, i.e. the Revised Universal Soil Loss Equation (RUSLE) and the Water Erosion Prediction Project (WEPP). The models were calibrated and validated using data collected from field experiments conducted in agricultural lands of Mexico. The simulated rainfall experiments involved measuring erosion from field plots subjected to four tillage systems (No crop, Conventional tillage, Conventional tillage + residues, and Handspike) under two antecedent soil moisture conditions (dry and wet). Different calibration approaches based on the factors K and C for RUSLE, and interrill erodibility and hydraulic conductivity in WEPP were tested. The best-performing methods in RUSLE involved measuring the K factor and adopting the recommended C factor by the National Forestry Commission of Mexico. In WEPP, the best results were obtained when interrill erodibility was estimated from experimental measurements. Overall, RUSLE outperformed WEPP in most of the treatments except for CT under WAMC.
Mapping Bucharest: Analyzing the Six Sectors Through Geospatial Data and Spatial Autocorrelation
Authors: Maricuț Alin-Cristian , Grădinaru Giani-Ionel , Marin Erika 
Published: August 2024

Abstract
Connectivity at the level of basic services within a city is the basis for adopting an investment strategy, both at the level of public administration and in the private environment. In addition, based on the concept of connectivity to citizens' basic needs, individuals can make decisions about purchasing a home. Therefore, the paper aims to analyse Bucharest, at the level of the 6 administrative sectors, from the perspective of connectivity to basic services (health, education, culture, etc.). In order to achieve this objective, with the help of GIS technology, relevant data will be extracted on residential buildings, transport infrastructure, and variables characterizing basic services at city level, for all 6 sectors of the capital. At the level of the 6 sectors of the capital there are structural differences in terms of access to basic services, especially as a result of the expansionary residential trend in the peripheries of the 6 sectors of Bucharest.
Regionale Arbeitsmärkte unter Transformationsdruck –unterschiedliche Herausforderungen und Anpassungspotenziale
Authors: Haas Anette , Niebuhr Annekatrin , Vetterer Niklas 
Published: August 2024

Abstract
The transformation pressure caused by digitalisation, decarbonisation and demographic change differs between regional labour markets, as does the potential to adapt to these changes. For structurally weak (rural) regions, high transformation pressure due to digitalisation and/or decarbonisation is often accompanied by significant demographic problems. Policies should aim to increase innovation and further training in lagging regions, as these are of strategic importance for addressing the challenges of transformation.
Kapitalmärkte stärken: Deutschland braucht mehr institutionelle Anleger
Authors: Kogler Michael , Malmendier Ulrike , Nöh Lukas , Schaffranka Claudia 
Published: August 2024

Abstract
Too few institutional investors are prepared to invest in young and innovative companies. This hampers the long-term growth prospects of the German economy. Instead, institutional investors in Germany hold more conservative portfolios than their European counterparts, investing heavily in bonds. Building up supplementary funded pensions and removing barriers to investing in riskier but growth-enhancing activities can help mobilise more growth capital in the long term.
Steuersenkung als Investitionstreiber
Authors: Hentze Tobias , Kauder Björn , Obst Thomas 
Published: August 2024

Abstract
Germany has become a high-tax country for companies over the past 15 years. There is currently a lot of discussion in politics about how the tax burden for companies can be lowered in order to enhance private investments. Compared to challenges in the areas of infrastructure or bureaucracy, the disadvantage of a high tax burden can be easily remedied by political decisions. According to simulations, a tax cut would lead to a noticeable upswing in private investments and could also act as a signal in international location competition that should not be underestimated.
Inflationsberechnung: Replik und Erwiderung
Authors: Rupprecht Manuel 
Published: August 2024

Abstract
In the March 2024 issue, Wirtschaftsdienst published an article entitled “Inflation calculation: ECB Interest Rate Policy is Not Statistically Recognised as a Driver of Inflation” by Johannes Schwanitz. Manuel Rupprecht takes a different view in a reply; Schwanitz then explains his position in a rejoinder.
PENGGUNAAN GAYA BAHASA DALAM AKUN INSTAGRAM @NAJWASHIHAB
Authors: Nur'asih Ela Sri , Herdiana Herdiana , Mulyani Sri 
Published: August 2024

ABSTRAKPenelitian ini berdasar dari masalah yang dikaji dirumuskan dalam bentuk rumusan masalah berikut,1) Bagaimana penggunaan gaya bahasa dalam akun Instagram Najwa Shihab? 2)Bagaimana alternatif pengembangan bahan ajar yang berkaitan dengan gaya bahasa dalam pembelajaran puisi dalam K.D 3.17 Menganalisis unsur pembangun puisi? Penelitian ini bertujuan untuk mendeksripsikan penggunaan gaya bahasa pada postingan akun Instagram @najwashihab dan mendeksripsikan pengembangan bahan ajar atau alternatif bahan ajar yang berkaitan dengan penggunaan gaya bahasa pada teks Puisi. Metode penelitian yang digunakan adalah deksriptif kualitatif. Data yang digunakan berupa kata, kalimat, ungkapan dan istilah yang dapat dirumuskan sebagai gaya bahasa yang diambil dari postingan akun Instagram @najwashihab. Berdasarkan analisis data dan pembahasan secara merinci dapat diperoleh penggunaan gaya bahasa ada 4, yaitu: gaya bahasa perbandingan meliputi metafora untuk perbandingan implisit tanpa kata seperti atau sebagai antara dua hal yang berbeda,antitesis untuk perbandingan antara dua antonim yaitu kata-kata yang mengandung ciri-ciri semantik yang bertentangan, gaya bahasa pertentangan meliputi litotes untuk pernyataan yang dikurangi dari kenyataan yang sebenarnya, paradoks pertentangan yang nyata dengan fakta-fakta yang ada, klimaks untuk urutan-urutan pikiran yang setiap kali semakin meningkat kepentingan dari gagasan-gagasan sebelumnya, gaya bahasa pertautan meliputi sinekdoke untuk mengatakan sebagian pengganti keseluruhan dan gaya bahasa perulangan meliputi tautotes untuk perulangan atau repetisi atau sebuah kata berulang-ulang dalam sebuah konstruksi. Gaya bahasa perbandingan metafora dominan digunakan oleh akun Instagram @najwashihab dalam penyampaian berita yang terdapat didalamnya. Hasil analisis penelitian ini membuktikan bahwa gaya bahasa yang digunakan oleh pemilik akun Instagram @najwashihab dapat dijadikan sebagai alternatif bahan ajar khususnya jenjang Sekolah Menengah Atas kelas X/2 dalam mempelajari teks puisi. Hasil penelitian sesuai dengan prinsip pengembangan bahan ajar, yakni tepat guna, daya guna dan bervariasi. Maka penyajian bahan ajar berisi contoh-contoh jelas mengenai penggunaan gaya bahasa. Kesesuaian dengan prinsip tepat guna ialah yakni memudahkan pemahaman siswa karena gaya bahasa kerap kali digunakan oleh siswa dalam kehidupan sehari-hari atau pada lingkunganya. Dapat dikatakan berdaya guna karena dapat memudahkan siswa untuk memahami pembelajaran dan memudahkan untuk mencapai tujuan pembelajaran dan dapat dikatakan bervariatif karena menyesuaikan dengan tingkat pengetahuan dan minat siswa dalam bermedia sosial.
Principais causas relacionadas à mortalidade materna no Brasil nos últimos 10 anos
Authors: Sousa Maria Vitória Santos de , Miyoshi Caroline Midore , Silva Ana Maria Nunes da , Santos Ediálida Costa 
Published: August 2024

Objetivo: Investigar as causas recorrentes de óbitos maternos ocorridos nos últimos dez anos no Brasil. Métodos: Revisão Integrativa da Literatura, que abrange os anos de 2012 a 2022, estando compreendido neste período o surgimento da pandemia de COVID-19. O levantamento bibliográfico foi realizado na primeira quinzena do mês de abril de 2023 através da Biblioteca Virtual de Saúde (BVS), especificamente, nas bases de dados LILACS, BDENF e MEDLINE respeitando como critérios de inclusão o idioma português brasileiro, últimos 10 anos, texto completo e excluindo-se teses e dissertações. Resultados: A análise compreendeu 12 artigos. As principais causas da mortalidade materna foram: causas obstétricas diretas (hipertensão, infecções puerperais e aborto), seguidas pelas causas obstétricas indiretas (complicações no puerpério, hipertensão preexistente, HIV/AIDS). A não especificação da causa do óbito materno também foi constatada por alguns estudos. Considerações finais: A identificação e especificação das causas de mortalidade materna permitem conhecer a real magnitude do problema. As causas em sua maioria são evitáveis e se detectadas precocemente e tratadas de forma adequada podem reduzir os óbitos maternos.