bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Therapeutic Potential of Chi Shao and Fu Zi in Acute-on-Chronic Liver Failure: Insights from Network Pharmacology and Animal Studies
Authors: Tian Xiaoling , Zhang Yu , Fu Qin , Chen Bin 
Published: July 2024

Abstract

Background & Aims
Acute-on-chronic liver failure (ACLF) has a high incidence and mortality rate, which has become an urgent clinical problem to be solved.Traditional Chinese medicine (TCM) has been widely applied in the clinical and experimental researches of ACLF. But its specific mechanism is not yet fully understood. This study attempted to identify the effective active ingredients, key targets, and biological mechanisms of Chinese herbal medicines Chi Shao (Paeoniae radix Rubra) and Fu Zi (Aconitum carmichaelii Debx) (CSFZ) for treating ACLF based on network pharmacology and animal experiments.
Methods & Results
Network pharmacology was performed to predicte the major components of CSFZ and potential signal pathways. Molecular docking method was applied to determine the binding affinity between the main components and the key targets. A rat model of ACLF was constructed. The liver injury were measured by histopathological methods. Biochemical indexes were used to evaluate liver function. ELISA was used to detect the IL-6, TNF-α, Caspase-3, BCL-2, ALB, and TB level. Also, PI3K/Akt signaling molecules were detected through RT-qPCR and WB. Immunofluorescence staining was used for PCNA and Cyclin B1. In the results we found that forty-nine potential active ingredients and 104 drug targets were screened from CSFZ, and 2730 genes were identified as ACLF targets, of which 72 overlapped with CSFZ targets. we identified ten key active ingredients of CSFZ. Moreover, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that CSFZ modulated ACLF may through numerous biological pathways, including antibacterial and anti-inflammatory mechanisms, cell proliferation, and apoptosis. Molecular docking verification shows that key components and core targets have good binding affinity. Also, through the vivo studies we found that CSFZ enhanced hepatic regeneration, improved hepatic structural damage, reduced hepatocyte apoptosis, and promoted the expression of PI3K and AKT.
Conclusions
Network pharmacology and in vivo experiments indicated that CSFZ may ameliorate hepatic injury by regulating the PI3k/Akt signaling pathway.
Bias compensation based recursive least squares identification algorithm for multivariable Hammerstein nonlinear systems
Authors: Lyu Bensheng , Wang Qiang , Xu Yanling , Zhang Huajun , Cai Chunbo 
Published: July 2024

Abstract

The multivariable Hammerstein nonlinear system contains the sum of bilinear parameters, which is not a regression form. By using the special properties of binary signals, we can transform the sum of bilinear parameter matrices into two different models, achieving the parameter separation for parallel nonlinear subsystems and a linear subsystem. In order to improve the accuracy of parameter identification, this paper uses a biased correction technique to compensate a biased recursive least squares estimates. Then, a bias compensation based recursive least squares algorithm is proposed to separately identify the parameters of a linear subsystem and parallel nonlinear systems. The numerical simulation indicate that the proposed algorithm has a higher accuracy than recursive least squares and over-parametrization based identification algorithms. The multivariate Hammerstein nonlinear system is implemented on a case study from the process industry namely the continuous stirred tank reactor. The accuracy of the prediction is improved by a biased correction term.
Efficient Crowd Density Estimation: Fusion of Faster CNN and Vision Transformer
Authors: Kushwaha Hemant , Gupta Sanjai Kumar 
Published: July 2024

Abstract

Accurate crowd density estimation in densely populated areas is essential for applications such as urban planning, security, and event management. Traditional methods often fall short in terms of accuracy and efficiency, especially when handling large datasets and real-time demands. This study introduces an efficient approach to crowd density estimation by integrating a rapid Convolutional Neural Network (CNN) with a Vision Transformer (ViT) architecture.Our method capitalizes on the strengths of both models to achieve enhanced performance. The fast CNN effectively captures local features and spatial details, while the Vision Transformer excels at identifying long-range dependencies and global context. By fusing these models, we create a synergistic effect that significantly improves crowd density estimation accuracy.We validate our approach through experiments on several benchmark datasets, covering both indoor and outdoor scenes with varying crowd densities. The results indicate that our method surpasses existing techniques in terms of accuracy while also maintaining high computational efficiency. We further demonstrate the scalability of our approach by testing its performance on large-scale datasets, confirming its suitability for real-world applications. Additionally, we explore the interpretability of the fused model, showing how the combination of CNN and Vision Transformer features enhances crowd density estimation. In summary, our proposed fusion method offers a promising solution for efficient and accurate crowd density estimation, with broad implications for practical applications in crowd analysis and management.
Synthesis of novel 4-substituted isatin Schiff base derivatives as potential autophagy inducers and evaluation of their antitumour activity
Authors: Tan Huayuan , Zhang Guanglong , Xu Chenlu , Lei Xue , Chen Jiayi , Long Haitao , Qiu Xuemei , Wang Wenhang , Zhou Yue , Chen Danping , Li Chengpeng , Li Zhurui , Wang Zhenchao 
Published: July 2024

Abstract

Autophagy is a potential target in cancer therapy. In the present study, we designed and synthesized a series of isatin Schiff base derivatives containing thioether structures. After discovering the highly active target compound H13 (IC50 = 4.83 μM) based on in vitro antiproliferation, we also found it had a high safety against normal cells HEK293 with CC50 of 69.01 μM. In addition, to provide reference for subsequent studies, a model was successfully constructed by Sybyl software. Preliminary mechanistic studies suggested that H13-induced apoptosis may be closely related to ROS accumulation and mitochondrial dysfunction. Subsequent studies revealed that H13 inhibited cell proliferation by inducing cellular autophagy mainly through blocking signal of the PI3K/AKT/mTOR pathway. Altogether, these results suggested that H13 was potentially valuable as a lead compound.
A Contributing Factor and Characteristics of High 210Po Activity in Aerosols at Hanoi, Vietnam
Authors: Pham-Thi Thanh-Xuan , Trung Tien Chu , Hegedűs Miklós , Kovac Tibor , Ngo Thi Thuy Huong , Duong Van-Hao 
Published: July 2024

Abstract

Air pollution in crowded cities has become an urgent issue in recent years. The high toxic 210Po activity and trace heavy elements’ content in 24 aerosol samples in Hanoi, Vietnam were determined at roadside and residential areas. 210Po activity in the studied aerosol samples was observed with a wide range (from 92.2 to 3500 µBq.m− 3 and 1395 µBq.m− 3 on average) and relatively high activities in roadside samples in comparison with the worldwide reference value. The results showed the predominance of the earth's crustal and fuel-combusting elements relating to traffic activities, the lower elements concentration origin from other combusting sources, the large Ni excess, the strong relationship between 210Po and Ni, the high ratio of Ni/Pb and the far greater 210Po activities in the roadside in comparison with residential aerosol samples at the study area. A suggestion, the main primary sources and a factor contributing to high 210Po activity in Hanoi aerosol samples are human activity relating to fuel combustion, high traffic density, and local sources.
Odor prediction of whiskies based on their molecular composition
Authors: Singh* Satnam , Schicker* Doris , Haug Helen , Sauerwald Tilman , Grasskamp Andreas T. 
Published: July 2024

Abstract

Aroma compositions are usually complex mixtures of odor-active compounds exhibiting diverse molecular-structure. Due to the chemical interactions of the compounds in the olfactory system, assessing or even predicting the olfactory quality of such mixtures is a difficult problem, not only for statistical models, but even for trained assessors. Here, we combine fast automated analytical assessment tools with human sensory data of 11 trained panelists and machine learning algorithms. Using 16 previously analyzed whisky samples (American or Scotch origin), we use the linear classifier OWSum to distinguish the samples based on their detected molecules and to gain insights into the key molecular structure characteristics and odor descriptors for sample type. Moreover, we use OWSum and a Convolutional Neural Network (CNN) architecture to classify the five most relevant odor attributes of each sample and predict their sensory scores with promising accuracies (up to F1: 0.66, MCC: 0.65, ROCAUC: 0.76). The predictions outperform the panel and thus demonstrate previously impossible data-driven sensory assessment in mixtures.

*Satnam Singh and Doris Schicker contributed equally to the work and are shared first authors.
Gas-Fueled Non-Equilibrium Co-Assembly via C1 Catalytic Feedback for Gas-Encoded 4D Information Encryption
Authors: YAN Qiang , Zhang Yulian , Yang Cuiqin , Liang Xin , Xiang Jun 
Published: July 2024

Abstract

Dissipative self-assembly, which exploits energy inputs of chemical fuels to maintain the functional states far from equilibrium, is essential to the living systems. Among a variety of fuels, carbon dioxide (CO2) gas, as one of the most ubiquitous but original forms of fuel on which life depends, has yet been introduced in artificial dissipative materials. Here we describe a CO2-fueled non-equilibrium co-assembly system that couples with a C1 catalytic feedback path to drive fuel dissipation and function output. Using common frustrated Lewis pair (FLP) as precursors, CO2 can dynamically bridge between them to constitute metastable amphiphiles, which not only highly activate CO2 but also enable their co-assembly with substrates into a transient fibrillar gel. In turn, the feedback process is realized by cooperative C1 catalytic insertion owing to the proximity of substrate and activated CO2 species in the assembled state. This can boost the depletion of gas fuel and facilitate disassembly to sol. Moreover, tailoring the intrinsic substrate/FLP chemistries, as well as external cues, to shift the catalytic activity is accessible to regulate the period and lifetime of sol-gel-sol transition over a wide range. Based on the tunability in phase transition on a time scale, we develop time-dependent information encryption materials using the transient FLP array loaded gas-encoded substrates, and the correct information can be read only at a specified time window. This study provides inspiration on a new fuel paradigm for dissipative system and their intelligent material applications.
Management of Pneumonia
Authors: Rankoussi Dima , Naser Noor , Bardan Housam 
Published: July 2024

Abstract

Background: The primary treatment for pneumonia is timely administration of antibiotics, so it is important to highlight the treatments used in Damascus Hospital in order to improve survival, morbidity, duration of hospitalization, and bacterial resistance.
Methods and materials: A prospective, retrospective study in which 100 patients with a primary diagnosis of community or hospital-acquired pneumonia, aged over 18 years, were studied during the period 1/22/2023 to 1/22/2024. The data were analyzed using the SPSS-26 program.
Results: The average age of the patients was 56.75±19.175 years, the most common age group was 60-74 years, males were 56%, and females were 44%. We found that community-acquired pneumonia was more common than nosocomial pneumonia, and the most common comorbid condition was type 2 diabetes, 7%. The most common symptoms and signs observed are respiratory depression 87%, cough 84%, general symptoms 83%, phlegm 73%, fever 56%, the most common radiological manifestation is multi-lobular density 45%, diffuse bilateral infiltrates 40%, and unilateral density 37%. The most common therapeutic protocols for all patients (intravenous ceftriaxone plus and oral levofloxacin), 41%, followed by oral levofloxacin, oral clindamycin, and intravenous ceftriaxone, 17%, and oral levofloxacin and intravenous vancomycin, 16%. Additional treatments included mucolytics, antipyretics, anticoagulants, and steroids.
Conclusion: Regarding empiric antibiotic therapy for pneumonia, the use of ceftriaxone could be reduced, broad-spectrum antibiotics could be administered more carefully to prevent resistance, and potential indications for systemic corticosteroid administration in patients with pneumonia should be documented more carefully.
The socio-technical short-term implications of drinking water hoarding on supply reliability
Authors: Satish Rahul , Oberascher Martin , Ender Monica , Lampalzer Thomas , Rief Silvia , Sitzenfrei Robert 
Published: July 2024

ABSTRACT
Panic buying during crises, like the initial hoarding of toilet paper amid COVID-19 restrictions, is mainly driven by social and emotional factors influenced by risk perception and social media content. Similarly, unreasonable drinking water hoarding, i.e., simultaneous withdrawal of water by a large number of customers, can influence the performance of water supply systems (WSS). Decreasing performance (e.g., more friction losses and therefore a smaller outflow rate at faucets) can cause a negative feedback loop that might trigger further water hoarding behaviours. This research explores the socio-technical implications of water hoarding in crisis situations within a WSS. An analysis of an Alpine WSS in Austria reveals that up to 40% of households, with a filling rate of 0.1 L/s (bathtub filling), can hoard without performance drop and negative feedback. Beyond this threshold, impacts become noticeable, leading to inadequate water supply for some households, causing disruptions and negative feedback loops. This emphasizes the need for information campaigns to counter false information, preventing emotional triggers. In conclusion, the research highlights the interplay between technical and social factors in crisis water demand management, stressing the importance of informed interventions to mitigate hoarding behaviour and maintain efficient WSS operation.
Forecasting of time-dependent scour depth based on bagging and boosting machine learning approaches
Authors: Kumar Sanjit , Oliveto Giuseppe , Deshpande Vishal , Agarwal Mayank , Rathnayake Upaka 
Published: July 2024

ABSTRACT
Forecasting the time-dependent scour depth (dst) is very important for the protection of bridge structures. Since scour is the result of a complicated interaction between structure, sediment, and flow velocity, empirical equations cannot guarantee an advanced accuracy, although they would preserve the merit of being straightforward and physically inspiring. In this article, we propose three ensemble machine learning methods to forecast the time-dependent scour depth at piers: extreme gradient boosting regressor (XGBR), random forest regressor (RFR), and extra trees regressor (ETR). These models predict the scour depth at a given time, dst, based on the following main variables: the median grain size, d50, the sediment gradation, σg, the approach flow velocity, U, the approach flow depth y, the pier diameter Dp, and the time t. A total of 555 data points from different studies have been taken for this research work. The results indicate that all the proposed models precisely estimate the time-dependent scour depth. However, the XGBR method performs better than the other methods with R = 0.97, NSE = 0.93, AI = 0.98, and CRMSE = 0.09 at the testing stage. Sensitivity analysis exhibits that the time-dependent scour depth is highly influenced by the time scale.
Research on the coupling effect of water security and socio-economy in five economic zones of Sichuan Province, China
Authors: He Zuli , Liu Bin , Liu Jian , Xia Xinyu , Han Suyue , Pan Ke , Li Jiajia , Tang Long 
Published: July 2024

ABSTRACT

The uneven distribution, scarcity, and pollution of water resources can significantly hinder socioeconomic development. A conceptual framework of Water Resources Endowment-Efficiency-Pressure-Response-Structure-Cycle (2EPRSC) was proposed, and 16 indicators were selected to establish the evaluation index system. Taking the five economic zones in the Sichuan Province of China as the research area, the genetic algorithm optimized entropy weighting method-cloud model was applied to determine the water security grades. Subsequently, the coupling coordination degree (CCD) model was established based on water security system (WSS)-SES to analyze the CCD. The results showed that (1) temperature and investment were the two indicators with more significant impacts on water security in Sichuan Province. (2) From 2012 to 2022, water security in Sichuan Province as a whole presented a decreasing and then increasing trend. (3) From 2012 to 2022, CCDs of the WSS-SES in Sichuan Province's economic zones were mostly at moderate imbalance, with the Chengdu Plain economic zone showing the highest CCD. Overall, the CCD scores across the economic zones were on an ascending trajectory. The study, grounded in the state of water security and CCD in Sichuan, can forge a scientific foundation for the sustainable development of WSS-SES.
Contribution of water, sanitation, hygiene and basic education to reduce under-five mortality in Sudan
Authors: Mohamed Elwasila Saeed Elamin 
Published: July 2024

ABSTRACT

Until 2015, the under-five mortality rate (U5MR) in Sudan was 65.9 per 1,000 livebirths, higher than the MDG4 target, and it has to be reduced by 5.04% per year from its 2020 level to achieve the SDG3.2 by 2030. This target cannot be achieved without improvements in access to safe drinking water (ASW), sanitation and hygiene (ISF) (WASH) and basic education. An estimated autoregressive distributed lag bounds test model confirms a long-run equilibrium relationship between U5MR, WASH, basic education, economic growth and health care. In the short run, U5MR decelerates itself with a coefficient of 0.56. Sanitation and basic education significantly reduce U5MR. Collectively, health care and economic growth affect U5MR adversely. In the long run, declines of U5MR are driven respectively by access to sanitation, hygiene and basic education (a factor of 1.79), economic growth (a factor of 0.21), and health care (a factor of 0.18). The study recommends promotion of access to safe drinking water with investments in sanitation and hygiene of 32 million $US annually between 2020 and 2030, in order to meet the SDG3.2 in Sudan. Skilled physicians and full vaccination of children can be more effective in reducing U5MR, dependent on progress in safe WASH.
Experimental study of methylene blue adsorption from aqueous solutions onto natural Algerian goethite
Authors: Larakeb Manal , Remmache Mohammed Ridha , Senoussi Mohammed Mourad , Ziar Aissaoui , Hadjeris Lazhar 
Published: July 2024

ABSTRACT

The objective of this work is to study and model the methylene blue (MB) sorption, from aqueous solutions by goethite. The equilibrium time was reached during 10 min of agitation with 26.21 ℅ efficiency. MB removal efficiency is improved with an increased absorbent dose (0.5–08 g/L) for an initial 10 mg/L concentration. Treatment efficiency decreases with the increase of initial MB concentration (2–100 mg/L). The best adsorption yields were obtained in basic media. MB sorption kinetics via goethite leads to several results as to mechanisms that govern kinetics and isotherms equilibrium: Blanchard's model provides a better fit of the experimental results compared to Lagergren's model. Thus, the MB sorption kinetics is described by the pseudo-second order. Particle diffusion is involved in the MB removal mechanism, but it is not the only limiting step and the Boyd model application confirms that diffusion in the pores is the limiting step of the MB sorption process. The Elovich model is well verified and translated probably the existence of chemical-type interactions between MB and goethite. The study of MB adsorption isotherms showed that Freundlich, Temkin, and Elovich models are the best adapted than the Langmuir model. Finally, we can assess that goethite can be an interesting natural adsorbent for MB elimination from polluted waters in basic environments.
Accessible Ecosystem for Clinical Research (Federated Learning for Everyone): Development and Usability Study
Authors: Pirmani Ashkan , Oldenhof Martijn , Peeters Liesbet M , De Brouwer Edward , Moreau Yves 
Published: July 2024

Background
The integrity and reliability of clinical research outcomes rely heavily on access to vast amounts of data. However, the fragmented distribution of these data across multiple institutions, along with ethical and regulatory barriers, presents significant challenges to accessing relevant data. While federated learning offers a promising solution to leverage insights from fragmented data sets, its adoption faces hurdles due to implementation complexities, scalability issues, and inclusivity challenges.

Objective
This paper introduces Federated Learning for Everyone (FL4E), an accessible framework facilitating multistakeholder collaboration in clinical research. It focuses on simplifying federated learning through an innovative ecosystem-based approach.

Methods
The “degree of federation” is a fundamental concept of FL4E, allowing for flexible integration of federated and centralized learning models. This feature provides a customizable solution by enabling users to choose the level of data decentralization based on specific health care settings or project needs, making federated learning more adaptable and efficient. By using an ecosystem-based collaborative learning strategy, FL4E encourages a comprehensive platform for managing real-world data, enhancing collaboration and knowledge sharing among its stakeholders.

Results
Evaluating FL4E’s effectiveness using real-world health care data sets has highlighted its ecosystem-oriented and inclusive design. By applying hybrid models to 2 distinct analytical tasks—classification and survival analysis—within real-world settings, we have effectively measured the “degree of federation” across various contexts. These evaluations show that FL4E’s hybrid models not only match the performance of fully federated models but also avoid the substantial overhead usually linked with these models. Achieving this balance greatly enhances collaborative initiatives and broadens the scope of analytical possibilities within the ecosystem.

Conclusions
FL4E represents a significant step forward in collaborative clinical research by merging the benefits of centralized and federated learning. Its modular ecosystem-based design and the “degree of federation” feature make it an inclusive, customizable framework suitable for a wide array of clinical research scenarios, promising to revolutionize the field through improved collaboration and data use. Detailed implementation and analyses are available on the associated GitHub repository.