bluuebunny/crossref_metadata_2025_split huggingface dataset:
Contention-aware Greedy Heuristic Method and Learning based Method for Load Balancing through Scheduling for Containers in Cloud Computing Environments
Authors: Gogineni Neelima , S Saravanan. M. 
Published: April 2024

Abstract

Containerization became indispensable in distributed environments for packaging software and dependencies in a lightweight executable container. In the era of big data and availability of cloud infrastructure, it is more so as distributed applications are more resource and data-intensive. Such High Performance Computing (HPC) applications are deployed in containerized services. However, data-intensive nature of those applications lead to poor performance unless scheduler considers it. In this paper, not only load balancing of containers but also performance of underlying applications is considered. Towards this end, a scheduling algorithm with unified optimization considering load balancing and also application performance is proposed. This algorithm, named Contention-aware Greedy Heuristic Scheduling and Load Balancing for Containers (CGHSLBC), helps in improving performance of containerization in distributed environments. Problems associated with containerization in terms of balancing load and also application performance are NP-hard. CGHSLBC has heuristics to deal with such issues. Empirical study has revealed that CGHSLBC better application performance besides balancing load of containerized services in cloud infrastructure. We also proposed a learning based methodology to schedule and balance load for containers. It is based on Deep Reinforcement Learning (DRL) where state change is continuously monitored while making well informed scheduling decisions. An algorithm named Reinforcement Learning based Dynamic Scheduling (RLbDS) is proposed and empirical study has revealed that it shows better performance over state of the art methods.
Mesenchymal stem cell derived proteome can target multiple signalling pathways to ameliorate rheumatoid arthritis: network pharmacology and molecular docking based approach
Authors: Tariq Muhammad Hamza , Farid Nouran , Kohli Nupur 
Published: April 2024

Abstract

Rheumatoid arthritis (RA) is an autoimmune chronic inflammatory disease with a global prevalence of approximately 1%. Mesenchymal stem cells (MSCs) have been thoroughly investigated for the treatment of RA; however, their clinical use is limited due to issues related to cell engraftment. It is now well established that MSCs exert their regenerative effect through the paracrine mechanism of their secreted factors (called the secretome); however, the mechanism by which secretome proteins target diseases is still unclear. This study aimed to investigate the potential of the proteome of the MSC secretome in targeting the key molecular signatures of RA. Secretome from primary human bone marrow MSCs was collected, and proteomic analysis was performed using label-free tandem mass spectrometry. A network pharmacology approach was used to identify the target genes of the MSC proteome as well as therapeutic targets of RA. Proteomic analysis of the MSC secretome confirmed the presence of 187 unique proteins, with 136 direct human gene targets. 52 of the identified genes were common with the 1922 identified targets of RA. Functional annotations of the 52 genes revealed their involvement in multiple RA-related KEGG pathways, such as ECM-receptor interaction, focal adhesion, the PI3K-AKT SIGNALLING pathway, the phagosome, and the p53 pathway. Molecular docking of the top 10 hub proteins with the PI3K-AKT pathway revealed a strong binding affinity forall the hub proteins, indicating the potential mechanism by which the MSC proteome can be used as a therapeutic cocktail to ameliorate RA.
Water and Seawater Splitting with MgB2 Plasmonic Metal-Based Photocatalyst
Authors: Kravets Vasyl , Grigorenko Alexander 
Published: April 2024

Abstract

Plasmonic nanostructures can help to drive chemical photocatalytic reactions powered by sunlight. These reactions involve excitation of plasmon resonances and subsequent charge transfer to molecular orbitals under study. Here we engineered photoactive plasmonic nanostructures with enhanced photocatalytic performance using non-noble metallic MgB2 high-temperature superconductor which represents a new family of photocatalysts. Ellipsometric study of fabricated MgB2 nanostructures demonstrates that this covalent binary metal with layered graphite-like structure could effectively absorb visible and infrared light by excitation of multi-wavelengths surface plasmon resonances. We show that a MgB2 plasmonic metal-based photocatalyst exhibit fundamentally different behaviour compared to that of a semiconductor photocatalyst and provides several advantages in photovoltaics applications. Excitation of localised surface plasmon resonances in MgB2 nanostructures allows one to overcome the limiting factors of photocatalytic efficiency observed in semiconductors with a wide energy bandgap due to the usage of a broader spectrum range of solar radiation for water splitting catalytic reactions conditioned by enhanced local electromagnetic fields of localised plasmons. Excitation of localised surface plasmon resonances induced by absorption of light in MgB2 nanosheets could help to achieve near full-solar spectrum harvesting in this photocatalytic system. We demonstrate a conversion efficiency of ~5% at bias voltage of Vbias = 0.3 V for magnesium diboride working as a catalyst for the case of plasmon-photoinduced seawater splitting. Our work could result in inexpensive and stable photocatalysts that can be produced in large quantities using a mechanical rolling mill procedure.
Biomineralized bacterial outer membrane vesicles exert pleiotropic immunoferroptotic effects on immune-deserted liver cancer
Authors: Luo Ying , Xu Zhongsheng , Du Qianying , Xu Lian , Wang Yi , Xu Jie , Wang Junrui , Chen Sijin , Zhang Wenli , Liu Bo , Liu Jia , Guo Dajing , Liu Yun 
Published: April 2024

Abstract

The immune landscape of late-stage liver cancer is featured by severe immunosuppression that is characterized by poor immunogenicity, T-cell exhaustion, and infiltration of a large number of immunosuppressive cells, leading to compromised therapeutic efficacy of mainstream immunotherapies. Herein, we developed a pleiotropic immunoferroptotic mobilization strategy to treat intractable advanced liver cancer. In this study, immunogenic bacteria-derived outer membrane vesicles (OMVs) were exploited as a vector to deposit Cu and Mn with mixed valence states via one-step biomineralization, followed by platelet membrane camouflage to enhance the circulation time and reduce systemic side effects of the metal biomineralized OMVs, which are denoted as OPCM. Mechanistically, the metal-deposited OPCM possesses POD, CAT, and GPX-like activities, thereby stimulating immunogenic ferroptosis, cGAS-STING activation, and tumor hypoxia alleviation, ultimately leading to pleiotropic immunoferroptotic mobilization to combat tumor growth, recurrence, and metastasis. Notably, the combination with typical αPD-L1 augmented the tumor suppression effect, since the administration of αPD-L1 not only rescued exhausted T cells, but also amplified the intensity of ferroptosis due to IFN-γ secretion by activated T cells. Overall, the metal biomineralized OPCMs in combination with αPD-L1 formed a closed-loop therapy that cycles from immunotherapy and ferroptosis therapy, providing new insights for treating immunosuppressive liver cancer.
Insight Into the Relationship Between Motor and Cognitive Symptoms in Essential Tremor
Authors: Paparella Giulia , Angelini Luca , Margiotta Roberta , Passaretti Massimiliano , Birreci Daniele , Costa Davide , Cannavacciuolo Antonio , De Riggi Martina , Fegatelli Danilo Alunni , Bologna Matteo 
Published: April 2024

Abstract

Introduction:Essential tremor (ET) is a heterogeneous disorder characterized by bilateral upper limbs action tremor and, possibly, neurological signs of uncertain significance, including voluntary movement abnormalities and cognitive disturbances, i.e., the so-called ‘soft’ signs configuring ET-plus definition. While motor and cognitive disturbances often coexist in ET, their interrelationship remains largely unexplored. Here we aim to further investigate the relationship between motor symptoms, objectively assessed through kinematic analysis, and cognitive dysfunctions in ET.Methods:70 ET patients underwent clinical examination, as well as kinematic recordings of tremor and finger tapping and a thorough cognitive assessment. We then tested clinic-demographic and kinematic differences between patients with and without cognitive abnormalities, i.e., with mild cognitive impairment (MCI). Correlation analysis served to explore potential associations between kinematic and cognitive data.Results:43 ET patients (61.42%) had MCI. ET-MCI patients exhibited reduced movement velocity during finger tapping compared to those with normal cognition (p<0.001). Lower movement velocity during finger tapping was associated with poorer cognitive performance. Namely, we observed a correlation between movement velocity and performance on the Babcock Story Immediate and Delayed Recall Test (r=0.52 and r=0.45, both p<0.001), as well as the interference memory task at 10 and 30 seconds (r=0.3, p=0.008 and r=0.2, p=0.03).Conclusions:In this study, we have provided data for a better pathophysiological interpretation of motor and cognitive signs in ET, including the role played by the cerebellum or extra-cerebellar areas, which possibly underpin both signs.
An applied noise model for scintillation-based CCD detectors in transmission electron microscopy
Authors: Zietlow Christian , Lindner Jörg K. N. 
Published: April 2024

Abstract

Measurements in general are limited in accuracy by the presence of noise. This also holds true for highly sophisticated scintillation-based CCD cameras, as they are used in medical applications, astronomy or transmission electron microscopy (TEM). Further, signals measured with pixelated detectors are convolved with the inherent detector point spread function (PSF). The Poisson noise, arising from the quantized nature of the beam electrons, gets correlated by this convolution, which allows to reconstruct the detector PSF based on the Wiener–Khinchin theorem and the Pearson correlation coefficients under homogeneous illumination conditions. However, correlation also has a strong impact on the noise statistics of basic operations like the binning of signals, as it is usually done in electron energy-loss spectroscopy (EELS). Thus, this paper aims to give an insight into the different noise contributions occurring on such detectors, into their underlying statistics and their correlation. Detectors usually suffer from gain non-linearities and quantum efficiency deviations, which must be corrected for optimal results. All these operations influence the noise and are influenced by it, vice versa. In this work, we mathematically describe all these changes and show them experimentally. Methods on how to measure individual noise and correlation parameters are described allowing readers to implement routines for finding them. Sufficient knowledge on the noise of a measurement is not only crucial for classifying its quality and meaningfulness, but also allows for better post-processing operations like deconvolution, which is a common practice in spectroscopy to enhance signals.
A pH-Triggered self-releaseing humic acids hydrogels loaded with porcine interferon α/γ achieves anti-PRV effects by oral administration
Authors: Sun Mao-Yuan , Shi Yong-li , Lei Bai-Shi , Zhang Wu-Chao , Feng Jing-Jing , Ge Sheng-Hu , Yuan Wan-Zhe , Zhao Kuan 
Published: April 2024

Abstract

Interferon α (IFNα) and interferon γ (IFNγ) are cytokines that mediate important biological functions, including antiviral activity and immune regulation. However, the function of monomer IFN was limited and the administration route completely depends on injection. To solve this problem, recombinant porcine IFN-α and IFN-γ fusion protein (rPoIFNα/γ) was expressed, purified, and used to develop an effective oral rPoIFNα/γ humic acid hydrogel delivery system triggered by pH to protect the IFNα/γ from gastric acid destruction. Neither the humic acid hydrogel nor rPoIFNα/γ showed cytotoxicity in vitro for porcine kidney-15 (PK-15) cells. rPoIFNα/γ inhibited the replication of vesicular stomatitis virus (VSV) and pseudorabies virus (PRV), with an antiviral activity of approximately 104 U/mL. Scanning electron microscopy revealed that the humic acid (HA) hydrogel had a loose and porous honeycomb structure. rPoIFNα/γ was adsorbed by the hydrogel (IFNα/γ@PAMgel) and measured using Fourier transform infrared spectroscopy, and the results indicated a good IFN-loading effect. In vitro experiments showed that IFNα/γ@PAMgel swelled and released the IFNα/γ rapidly at pH 7.4 but not at pH 1.2. Mice oral administered IFNα/γ@PAMgel had enhanced proliferation and differentiation of CD4+ and CD8+ cells, whereas mice infected with PRV and treated with IFNα/γ@PAMgel had increased interferon stimulating genes (ISGs) transcription levels in the serum, lower mortality, lower viral loads in different tissues, and lower levels of organ damage. Conclusively, this study demonstrates that oral administered IFNα/γ@PAMgel has antiviral and immunomodulatory effects and is a potential antiviral agent for PRV infection.
Research on the Impact and Mechanism of Digital Empowerment on Agricultural Carbon Emissions: Evidence from China
Authors: Song Jianfeng , Ma mingguo , Li Jiafen 
Published: April 2024

Abstract

Whether digital empowerment can promote the dual-carbon process in agriculture and how its specific mechanisms of action work is a significant proposition that deserves in-depth research. Based on panel data from 30 provincial-level regions in China from 2012 to 2021, this paper calculates the level of digital empowerment in regional agriculture using the input-output method. Based on clarifying the theoretical mechanism of the impact of digital empowerment development on agricultural carbon emissions, it employs methods such as the two-way fixed effect model, dynamic panel model, mediation effect model, and spatial econometric model to multidimensionally empirically explore the impact of digital empowerment development on agricultural carbon emissions and its mechanisms. The study finds that: (1) From 2012 to 2021, the level of digital empowerment in Chinese agriculture has been on an upward trend, but only in economically developed regions is this upward momentum apparent. At the same time, China's agricultural carbon emissions from 2012 to 2021 show a clear trend of initially increasing and then decreasing. (2) The development of digital empowerment has a significant inverted U-shaped non-linear impact on agricultural carbon emissions, and at present, the level of agricultural digital empowerment in most provinces in China has not yet crossed the inflection point of inhibiting agricultural carbon emissions, which still holds after endogeneity tests and robustness tests. (3) The mechanism analysis results show that digital empowerment reduces agricultural carbon emissions by optimizing carbon-intensive factor inputs and improving factor allocation efficiency. (4) Heterogeneity analysis results indicate that digital empowerment has a significant inverted U-shaped impact on agricultural carbon emissions in economically developed areas, while its impact on moderately developed and less developed economic areas is not significant; in non-grain main producing areas, the inhibitory effect of digital empowerment is more pronounced. (5) Further discussion reveals that digital empowerment has an inverted U-shaped spatial spillover effect on agricultural carbon emissions in neighboring areas. The aforementioned research results provide substantial empirical evidence for policymakers on how to better promote the development of digital empowerment and enhance the coordination of China's digital infrastructure in regional environmental governance.
Comparative analysis of meteorological drought based on the SPI and SPEI Indices in Benin
Authors: BOUKO Abdoul-Aziz BIO SIDI D , Gao Bing , Mutelo Admire M. , El-Saadani Zozo , Abubakar Jabir , Dehah LEKOUEIRY 
Published: April 2024

Abstract

In Benin, drought refers to a meteorological disaster that causes insufficient soil moisture and has adverse consequences on agriculture, the environment, and food security. However, to better understand the evolution of drought, the Mann–Kendall trend test, and comparative statistical evaluation of drought indices were applied in this paper. To achieve this objective, firstly, this article used daily precipitation, temperature, and relative humidity data from the National Meteorological Agency of Benin (NMAB) to calculate the standardized precipitation index (SPI), the standardized evapotranspiration of precipitation (SPEI), and used the Mann-Kendall trend test to quantify the importance of characteristic drought trends in the three (03) zones of Benin at different time scales. Then, we performed a statistical and comparative evaluation of SPI and SPEI based on Pearson's correlation coefficient, and cross-wavelet transform, to identify the strengths of SPI and SPEI. The results showed that (1) as the time scale increased, the temporal variations of the SPI and SPEI were increasingly consistent across all 3 areas of Benin; but there remains a difference between SPI and SPEI; (2) the drought trends identified by the SPI and the SPEI in certain areas of Benin were quite different. In Zone 2 (Central Benin), SPI showed an insignificant decreasing trend (P > 0.05), while SPEI showed a significant decreasing trend (P < 0.05) on all time scales. In Zone 3 (northern Benin), SPI showed a significantly increasing trend (P < 0.05) except for SPI-1, while SPEI showed a significantly decreasing trend except for SPEI-12. (3) the two indices (SPI/SPEI) show a strong correlation with each other; (4) Compared to the drought index (SPI/SPEI) and the standard relative humidity indices (SRHI), the SRHI-3 and SPEI-3 gave the largest correlation coefficient (r = 0.5), The SPEI could be more appropriate than SPI for monitoring drought in Benin. It should be noted that the adaptability of SPI and SPEI may be different across periods and regions.
Evaluating Satellite-based multilinear regression and gauge- based spatial interpolation techniques for Köppen-Geiger classification in a national scale
Authors: Tayebi Asieh , Mokhtari Mohammad Hossein , Deilami Kaveh 
Published: April 2024

Abstract

Empirical climate classification is a process that makes environmental conditions understandable to humans by using climatic elements. Köppen-Geiger (KG) is a popular climate classification method that uses long-term precipitation and temperature data to classify climate into five primary groups. However, long-term continuous meteorological data is heavily exposed to data scarcity, particularly in a national scale. This research study addresses this challenge by leveraging satellite imageries, multilinear regression models and spatial interpolation within the context of entire country of Iran between 2016 and 2019. Accordingly, this study examined statistical relationship between 14 explanatory variables under four main categories of MODIS-LST, MODIS-NDVI, MODIS-TVDI, GPM-precipitation and SRTM-DEM against ground-based precipitation and temperature data (dependent variables). The spatial interpolation model (i.e. Krigging and CO-krigging) was directly developed from weather observation station datasets. A total of 332 synoptic stations were selected, 67% of which were used in modeling and the remaining 33% in testing. Accuracy assessment was performed with Kappa statistics. Overall, this research study developed three KG classification maps. These include a map per precipitation and temperature from regression model and spatial interpolation and a point-based maps from unused climate data in modelling. This study identified three KG main climate groups of arid, warm temperate and snow and eight KG sub-groups of hot desert, cold steppe, cold desert, hot steppe, warm temperate climate with dry hot summer, Snow climate with dry hot summer, Warm temperate climate with dry warm summer and Snow climate with dry warm summer. A comparison between those maps (kappa = 0.75) showed the higher accuracy of regression-based KG maps against spatial interpolation maps. This study contributes to a more detailed monitor of climate change across countries and regions with sparse distribution of weather observation data.
Anatomical factor associated with thoracic procedural difficulty in robot-assisted minimally invasive esophagectomy
Authors: Kuriyama Kengo , Okamura Akihiko , Kanamori Jun , Imamura Yu , Tamura Masahiro , Takahashi Naoki , Terayama Masayoshi , Kanie Yasukazu , Maruyama Suguru , Watanabe Masayuki 
Published: April 2024

Abstract

Background: Robotic surgical systems with full articulation of instruments, tremor filtering, and motion scaling can potentially overcome the procedural difficulties in endoscopic surgeries. However, whether robot-assisted minimally invasive esophagectomy (RAMIE) can overcome anatomical difficulties during thoracoscopic esophagectomy remains unclear. This study aimed to clarify the anatomical and clinical factors that influence the difficulty of RAMIE in the thoracic region.
Methods: Forty-five patients who underwent curative-intent RAMIE with upper mediastinal lymph node dissection for esophageal cancer were included. Using preoperative computed tomography images, we calculated previously reported anatomical indices to assess the upper mediastinal narrowness and vertebral body projections in the middle thoracic region. The factors influencing thoracic operative time were then investigated.
Results: During the thoracic procedure, the median operative time was 215 (124–367) min and the median blood loss was 20 (5–190) mL. Postoperatively, pneumonia, anastomotic leakage, and recurrent laryngeal nerve palsy occurred in 17.8%, 2.2%, and 6.7% of the patients, respectively. The multiple linear regression model revealed that a narrow upper mediastinum and greater blood loss during the thoracic procedure were significant factors associated with a prolonged thoracic operative time (P = 0.025 and P < 0.001, respectively). Upper mediastinal narrowing was not associated with postoperative complications.
Conclusions: A narrow upper mediastinum was significantly associated with a prolonged thoracic operative time in patients with RAMIE.