bluuebunny/crossref_metadata_2025_split huggingface dataset:
A healthcare data management system: Blockchain enabled IPFS providing algorithmic solution for increased privacy preserving scalability and interoperability
Authors: Tiwari Kajal , Kumar Sanjay 
Published: April 2024

Abstract
Finding a feasible and effective approach to sharing a large volume of healthcare data has been the focus of recent studies. Several techniques evolved over the years for healthcare data management can be categorized into three distinct categories. The first category mainly focused on deploying the centralized structure utilizing the cloud-based system, however, central system failure, the privacy of the data, and interoperability remain the major concerns of this approach. Later, in the second category, these limitations were addressed by implementing a decentralized system based on blockchain technology. The increased complexity of the healthcare data and the need for the inclusion of medical imaging restricted the scalability and storage efficiency of this decentralized method. Eventually, this led to the development of an integrated approach combining techniques such as InterPlanetary File System (IPFS) with blockchain. Even with the tremendous advancements, challenges like interoperability, scalability, and privacy still exist. This paper primarily focuses on increasing the privacy and security of healthcare data sharing by combining the authentication algorithm with the Elliptic Curve Cryptography (ECC) key exchange keeping the parameters such as interoperability, scalability, and storage efficiency intact. To evaluate the efficacy of the proposed system, performance monitoring along with a novel benchmarking technique was utilized. Also, the proposed system has been compared with the existing frameworks on different parameters such as access control, cryptographic algorithms, decentralized framework, scalability, performance evaluation, benchmarking, etc. The obtained results suggest that the proposed system provides an integrated solution for efficient healthcare data management that is secured, decentralized yet interoperable and scalable.
Perceived and expected quantity constraints in inventory dynamics
Authors: Ogawa Shogo 
Published: April 2024

Abstract

Inventory dynamics play a significant role in business cycles, as inventory tends to be more sensitive to excess demand fluctuations than it is to production. This study addresses the decision-making problem of firms and households under possible quantity-constrained trade using a simple model based on Keynesian unemployment in disequilib-rium economics. In the presented model, production and consumption are determined by the firm and household, respectively. In particular , they solve intertemporal optimizations under expected future constraints that depend on current states such as sales and income. Their independent decisions cause disequilibrium in goods: the gaps between production and sales and between planned and actual trade. While the former gap is buffered by inventory, we use United States data to show that the existence of inventory holdings cannot moderate the disequilibrium. Our simple model contributes to the body of knowledge on this topic as it endogenizes the firm’s objective value of the inventory–sales ratio in Metzlerian dynamics, reproduces the qualitative inventory dynamics, and reveals how stock disequilibrium affects flow disequilibrium dynamics.
JEL code:C60, E12, E32
Multi-PVO for Reversible Data Hiding Based onFull Homomorphic Encryption
Authors: Ge Bin , Shen Yaqing , Xia Chenxing , Sun Rui 
Published: April 2024

Abstract

To enhance the embedding performance of reversible data hiding algorithms and bolster the security of data transmission processes, a novel pixel value ordering method based on full homomorphic encryption is proposed in this paper. First, we propose a multi-PVO method to improve the fidelity of images with equal embedding capacity. In addition, we propose a double layer encryption method and achieve Paillier's fully homomorphic encryption. In practice, the sender encrypts the original image and then transmits the ciphertext to the embedding side. The embedding side performs a multi-PVO method and data hiding based on homomorphism to seamlessly embed the data into the ciphertext. This implementation offers dual functionality. On the one hand, users with no private keys can directly embed or extract the secret data without decryption keys. On the other hand, users with private keys can decrypt the marked ciphertext and help retrieve the marked plaintext. Finally, utilizing multi-PVO for extraction or recovery, additional data or original image can be retrieved from the marked image at receiver. With 20,000 bits embedded, the PSNR of the image Lena is as high as 59.60 dB, which demonstrates great image quality with the same embedding capability.
Intrinsic structural disorder on proteins is involved in the interactome evolution
Authors: Bustos Diego M , Moyano Luis G 
Published: April 2024

Abstract

New mathematical tools help understand cell functions, adaptability, and evolvability to discover hidden variables to predict phenotypes that could be tested in wet labs in the future. Different models have been successfully used to discover the properties of the protein-protein interaction networks or interactomes. We found that in the hyperbolic Popularity-Similarity model, cellular proteins with the highest contents of structural intrinsic disorder cluster together in many different eukaryotic interactomes and not the prokaryotic E. coli, where proteins with high levels of intrinsic disorder are very low. We also found that the normalized theta variable from the Popularity-Similarity model for a protein family correlate to the seniority of the organisms under analysis.
Statin Therapy in Non-ischemic Cardiomyopathy: evidence from a Population Based Cohort and Mendelian Randomization Analysis
Authors: zheng Xinpeng , Luo Dongling , Li Hezhi , Fei Hongwen , Zhang Caojin 
Published: April 2024

Abstract
Aims Statin therapy is widely used for atherosclerotic cardiovascular disease. However, evidence of benefits in patients with non-ischemic cardiomyopathy (NICM) remains controversial. Thus, this study aimed to examine the association between statin use and mortality risk in NICM patients and investigate the causal role of statin therapy on NICM.
Methods and Results We included NICM patients from a heart failure (HF) surveillance cohort abstracted from ARIC study. Kaplan-Meier estimates and logistic regression analysis were used to investigate the associated risk. In mendelian randomization (MR) analysis, summary-level GWAS data for statins SNPs were obtained through UK Biobank while data for NICM were obtained from FinnGen GWAS. Five MR methods were used to investigate the potential causality between statin therapy and NICM. 372 NICM patients were included in the population-based cohort, with 44% (164/372) reported as statin users. Overall, the 28-day and 1-year mortality rate were 5.11% (19/372) and 27.96% (104/372), respectively. In logistic regression analysis, statin use was associated with lower risk of 28-day (Odds Ratio [OR] 0.14, P=0.009) and 1-year mortality (OR 0.81, P=0.37) in the non-adjusted models. In MR analysis, estimates were concordant and similar in size in all MR methods, supporting a protective effect of statin use against NICM. The Cochran’s Q test suggested no evidence of heterogeneity in the instrumental variables while MR-Egger test showed no sign of directional pleiotropy.
ConclusionThis study provides evidence of a beneficial effect of statin use on NICM. This could have significant implications for current HF management in NICM patients.
Comparative in Vitro Dissolution Studies of Selected Generic Essential Medicines in Tanzania
Authors: Zihirwa Nampenda M , Nyondo Goodluck G. , Manyanga Vicky , Hipolite Danstan , Kaale Eliangiringa 
Published: April 2024

Abstract

BACKGROUND: The use of generic drugs is steadily increasing internationally because of economic pressure on drug budgets. When principles and practice of Health Technologies Assessments (HTA) are well applied, generic drugs provide the opportunity for major savings in healthcare expenditure since they are usually substantially lower in price than the innovator brands. However, physicians, pharmaceutical personnel and the community in general are apprehensive regarding the quality of generic drugs. There are concerns about their pharmaceutical equivalence and if they can interchange between one generic and the other without affecting therapeutic outcomes.
AIM:The objective of this study was to evaluate the biopharmaceutical equivalence of different brands of selected essential medicines by using comparative invitro dissolution profile technique.
METHOD: Dissolution testing using three different dissolution media at various pH (1.2, 4.5, and 6.8) was used by employing dissolution testing apparatus II. Samples were withdrawn at specified time intervals and analyzed for the released drug content by UV/VIS spectrophotometer. Drug released at each time interval were calculated and data obtained were used for comparison against a reference product.
RESULTS:
In this study five medicines (Ibuprofen, Ciprofloxacin, Erythromycin, Furosemide, Griseofulvin) _ were tested to determine their equivalence to the innovator brand. After conducting comparative dissolution testing and analyzed the similarity (f2) factor all brands of Ibuprofen, erythromycin, and ciprofloxacin were confirmed to be equivalent to their innovator brands. While one brand of Griseofulvin and all the brands of furosemide showed marked difference from innovator brands. Hence the findings revealed that of all the tested samples 70% showed similarity with innovator brand while 30% was not similar and cannot used interchangeably.
CONCLUSION:
The finding indicated that three is a need for continuous market surveillance to ensure that the quality of drug in the market always complies with specifications. But also, to sensitize manufactures to evaluate and improve the pharmaceutical characteristics of their formulation. There is need for careful evaluation of the various generics manufactured worldwide, to ensure the compliance to official standards.
Development of the methodology for the Detection and Quantification of Zinc Oxide Nanoparticles and dissolved Zinc by Single-Particle Inductively Coupled Plasma Mass Spectrometry
Authors: Santos Lisia Maria Gobbo dos , Barata-Silva Cristiane , Vicentini-Neto Santos Alves , Bazilio Fabio Silvestre , Silva André Luiz O. , Jacob Silvana Couto , Moreira Josino Costa 
Published: April 2024

Abstract

The increasing production of zinc oxide nanoparticles and their use in products of sanitary interest make the analysis and characterization extremely important from the point of view of public health and environmental risk. This work aimed to validate the methodology using SP-ICP-MS to measure and quantify nanoparticles of ZnONPs and dissolved zinc -Zn(i). This study pointed out that the method was suitable for the purpose, presenting satisfactory results for the recovery and precision test for Zn (i) and size of NPs. The limits of detection size, dissolved zinc concentration, and particle concentration were 67 nm, 0.4 µg L-1, 1.08 × 105 particles mL-1, respectively. Thus, the results obtained demonstrate that the technique can be used to determine the size and concentration of Zn(i) in different products.
Hybrid Fragment-SMILES Tokenization for ADMET Prediction in Drug Discovery
Authors: Aksamit Nicholas , Tchagang Alain , Li Yifeng , Ombuki-Berman Beatrice 
Published: April 2024

Abstract

Background: Drug discovery and development is an extremely costly and time-consuming processing of identifying new molecules as therapeutics that can interact with a biomarker target to interrupt the disease pathway of interest. In addition to binding the target, a drug candidate needs to satisfy multiple properties affecting absorption, distribution, metabolism, excretion, and toxicity (ADMET). Computational and artificial intelligence approaches provide an opportunity to improve each step of the drug discovery and development process, in which the first question faced by us is how a molecule can be informatively represented such that the in-silico solutions are optimized.
Results: This study introduces a novel hybrid SMILES-fragment tokenization method, coupled with two pre-training strategies, utilizing a Transformer-based model. We investigate the efficacy of hybrid tokenization in improving the performance of ADMET prediction tasks. Our approach leverages MTL-BERT, an encoder-only Transformer model that achieves state-of-the-art ADMET predictions, and contrasts the standard SMILES tokenization with our hybrid method across a spectrum of fragment library cutoffs.
Conclusion: The findings reveal that while an excess of fragments can impede performance, using hybrid tokenization with high frequency fragments enhances results beyond the base SMILES tokenization. This advancement underscores the potential of integrating fragment- and character-level molecular features within the training of Transformer models for ADMET property prediction.
Seed priming with Parachlorella microalgae mitigates the effect of salt stress on soybean
Authors: Santos Cleberton Correia , Ozório João Pedro Assis , Martins Luiz Otávio Montera , Silva Obadias Alves da , de Alencar Davi Lucas Bertolino , Silva Otávio Augusto Sabino , Neto Kiichi Kodama , Ribeiro Dágon Manoel , Scalon Silvana de Paula Quintão 
Published: April 2024

Abstract

Salinity can be stressful and impair water relations and the germination of soybean seeds, making it necessary to establish sustainable solutions to overcome this situation. We hypothesized that seed priming (SP) with Parachlorella sp. microalgae can reduce the stressful effects of salinity and contribute to seed germination and seedling growth, inducing tolerance. We aimed to evaluate the constituents of Parachlorella sp. biomass and potential of SP in soybean to mitigate the effect of salinity on germination and vigor. Seeds were subjected to the following priming: i) without priming, ii) priming with 5 mL, and iii) 10 mL kg seed-1. Then, seeds were subjected to four osmotic potentials: 0.0 (control), –0.4, –0.8 and –1.2 MPa, induced by KCl. Parachlorella sp. biomass contained several metabolites such amino acids, carnitines, lipids, and phytohormones. The maximum percentage of normal seedlings was in –0.79 MPa. Seed without and with 5 and 10 mL of Parachlorella sp. showed higher root protrusion at –0.71, –0.37 and –0.30 MPa, respectively. Priming with 5 and 10 mL of Parachlorella sp. resulted in greater root protrusion in seeds not exposed to salinity. Seedlings from seed that received Parachlorella sp. showed greater growth even under salt stress. Priming with 10 mL of Parachlorella sp. resulted in seedlings with greater biomass accumulation at –1.2 MPa. Priming contributed to the lower electrolyte leakage in –1.2 MPa. Although soybean is sensitive to –1.2 MPa, SP with 10 mL of Parachlorella sp. microalgae demonstrated to be a sustainable and efficient alternative to mitigate the stressful effect of salinity on seedling vigor.
AI-Infused Cloud Storage Management: Structured, Secure, Interactive and Efficient Retrieval System
Authors: Swathika P. , Buvaneshkumaar A. , Vimal P. 
Published: April 2024

Abstract

Explores the symbiotic relationship between cloud computing and AI-based chat models in revolutionizing document management. Emphasizing scalability, flexibility, and accessibility, the cloud enables streamlined operations and innovation across industries. Leveraging standardized formats and structured data organization enhances document management efficiency within cloud environments. Digital signature techniques and AI-driven verification algorithms ensure document authenticity, while access control strategies, employing encryption with private keys managed through AI authentication mechanisms,security. The integration of AI-based chat models enriches user experience by enabling dynamic document organization, retrieval, and content creation. Together, these technologies redefine document management, promising unprecedented efficiency, security, and user-centric functionalities.
Spatial-temporal variation and source analysis of heavy metal in urban and peri-urban soils：The case study of Beilun District (Ningbo, China) from 2015 to 2022
Authors: Zhang Pengwei , Hu Lanfang , Gao Bo , Gao Feng , Zhu Xuchu , Li Yaying , Yao Huaiying 
Published: April 2024

Abstract
The soil environment plays an important role in urban ecosystems. To study the heavy metal contamination of soil in Beilun District, Ningbo, we collected soil samples from 60 points in urban and peri-urban areas of Beilun District and analyzed the spatiotemporal variation and sources of heavy metal pollution in various land-use types. The contents of heavy metals in green belts and woodland in 2022 were higher than those in 2015, while there was no significant change in agricultural land. The heavy metal contents in both years were mainly in the order green belts > agricultural land > woodland. The spatiotemporal analysis showed that heavy metal pollution in Beilun District was concentrated in five industrial areas, and there was a trend toward the disappearance of highly polluted points. The single-factor pollution index, pollution load index (PLI), and geoaccumulation index (Igeo) indicated that there was no significant heavy metal pollution in Beilun District, and individual elements at specific points showed slight pollution. The source analysis results showed that the main source of Hg is chemical, As is mainly derived from agricultural, Cr, Ni and Cu are mainly derived from natural, the main sources of Zn and Cd are electroplating and machinery activities, and the main source of Pb is traffic. This results specify a reference for future investigation on urban soil heavy metals, and the source apportionment results provide a scientific foundation for subsequent soil heavy metal pollution treatment.
High performance multifunction integrated optic circuits base on thin- film lithium niobate
Authors: GuoHongjie Guo , Haifeng Liu , zhiguo Yu , Wenbin Chen , Yongkang Yang , Baiang Qu , Manqing Tan , Wentao Guo 
Published: April 2024

Abstract

This paper introduces a revolutionary Multifunction Integrated Optic Circuit (MIOC) design utilizing thin-film lithium niobate, surpassing traditional bulk waveguide-based MIOCs in terms of size, half-wave voltage requirements, and integration capabilities. By implementing a sub-wavelength grating structure, we achieve a Polarization Extinction Ratio (PER) exceeding 29 dB. Furthermore, our electrode design facilitates a voltage-length product (VπL) below 2 V·cm, while a double-tapered coupling structure significantly reduces insertion loss. This advancement provides a pivotal direction for the miniaturization and integration of optical gyroscopes, marking a substantial contribution to the field
Identification of key industries of provincial carbon emissions in China based on inter-layer association of multi-layer network
Authors: xu lipeng , Wang wenping 
Published: April 2024

Abstract

It is crucial for China to achieve the dual-carbon goal by precisely identifying key industries of carbon emissions and achieving orderly and coordinated synergistic emission reduction across provinces. Unlike the existing research and practice on key industries of carbon emissions, which ignore provincial differences, this paper takes into account the flow characteristics of products and services in industries within provinces as well as the differential characteristics in the level of economic development and social factors among provinces and constructs a multi-layer network model of carbon emissions based on the provincial-level input-output data of China in 2012, 2015 and 2017. Moreover, we improve the PageRank algorithm to rank the importance of nodes in the multi-layer network. The empirical results indicate that China’s top-ranking industries of carbon emission include high-carbon industries such as metal smelting and chemical industry, which are mainly distributed in provinces such as Hebei and Liaoning. Meanwhile, the production and supply industries of electric power and heat has gradually evolved into key industries of carbon emissions in most provinces of China due to its distinctions in fundamentals, livelihood, and high technology content. In addition, unlike provinces with relatively lower carbon emission intensity, such as Beijing and Shanghai, provinces with comparatively higher carbon emission intensity, such as Ningxia and Inner Mongolia, have key industries of carbon emissions such as electronics, machinery manufacturing industry and transportation. The conclusions of this research provide theoretical support for precise synergistic emission reduction strategies in various Chinese provinces.
Novel Comparative Analysis of Fuzzy C-Mean and Region Growing in Spine Image Segmentation
Authors: Waykule J. M. , Udupi V. R. 
Published: April 2024

Abstract

Medical image segmentation plays a crucial role in various clinical applications, including disease diagnosis and treatment planning. In the context of spine imaging, accurate segmentation is essential for precise analysis and intervention. This study presents a comparative analysis of two prominent segmentation algorithms: fuzzy c-means (FCM) and region growing, applied to spine image segmentation. The dataset consists of spine images obtained from medical imaging modalities, preprocessed to enhance clarity and remove noise. Both FCM and region-growing algorithms are implemented with appropriate parameter settings and evaluated using quantitative metrics such as the Dice similarity coefficient, sensitivity, and specificity. Additionally, qualitative assessments are conducted through visual inspection of segmented images. The results reveal distinct performance characteristics of each algorithm, highlighting their respective strengths and weaknesses in spine image segmentation tasks. Through comprehensive analysis and discussion, this study provides valuable insights into the effectiveness of FCM and region-growing algorithms, aiding clinicians and researchers in selecting suitable segmentation approaches for spine imaging applications.
The Effect of the Beech Wood Steaming Condensate on Curing Behaviour of Urea-formaldehyde Adhesive
Authors: Rančić Milica , Popović Mlađan , Milić Goran , Todorović Nebojša , Veizović Marko , Gavrilović-Grmuša Ivana 
Published: April 2024

Abstract

This study explores the potential of using condensate generated during beech wood steaming (BSC) as an eco-friendly additive in urea-formaldehyde (UF) adhesives for wood-based panel (WBP) production. The research aimed to assess the hardening behavior of pure commercial UF resin and UF with added condensate (UFC), investigating the potential catalytic effect of BSC on the hardening characteristics of UF adhesives. Changes in chemical structure after the curing process were observed with Fourier transform infrared spectroscopy (FTIR). The curing kinetics was studied by differential scanning calorimetry (DSC) under a dynamic scanning regime with heating rates of 5, 10, and 20°C/min. Obtained data were analyzed using Kissinger-Akahira-Sunose (KAS) and Friedman (FR) kinetic iso-conversional methods to estimate the activation energy (Ea) of the curing reaction in the investigated UF adhesive systems. The results of DSC analysis imply that BSC lowers the temperature of the curing reaction of UF adhesive along with the prolongation of the curing reaction. The obtained kinetic data supported by FTIR and chemical analysis suggest that phenolic compounds present in BSC interfere with the main curing reactions leading to lower peak temperatures but higher activation energy. Тhis suggests that BSC increased the number of active sites involved in the reaction and, consequently, the number of collisions. BSC, as wastewater of the wood processing industry, can be efficiently utilized as an environmentally friendly, inexpensive substitute for deionized water in UF adhesive formulations for WBP manufacturing.