bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dietary supplementation of phytoncide and soybean oil increases milk conjugated linoleic acid and depresses methane emissions in Holstein dairy cows
Authors: Kim TaeBin , Bae MunHee , Lee JaeSung , Ghassemi Nejad Jalil , Lee HongGu 
Published: March 2024

AbstractThe objective of this study was to determine whether adding phytoncide oil (PO) and soybean oil (SBO) to the dairy cow diet could increase milk conjugated linoleic acid (CLA) and depress methane (CH4) emissions in Holstein dairy cows. Rumen fermentation was conducted at four levels of SBO (0, 1, 2, and 4%, on DM basis) and two levels of PO (0 and 0.1%, on DM basis) with in vitro experiment. To evaluate blood parameters, fecal microbe population, milk yield and fatty acid compositions, and CH4 production, in vivo experiment was conducted using 38 Holstein dairy cows divided into two groups of control (fed TMR) and treatment (fed TMR with 0.1% PO and 2% SBO as DM basis). In the in vitro study (Experiment 1), PO or SBO did not affect rumen pH. However, SBO tended to decrease ruminal ammonia-N (p = 0.099). Additionally, PO or SBO significantly decreased total gas production (p = 0.041 and p = 0.034, respectively). Both PO and SBO significantly decreased CH4 production (p < 0.05). In addition, PO significantly increased both CLA isomers (c9, t11 and t10, c12 CLA) (p < 0.001). Collectively, 0.1% PO and 2% SBO were selected resulting in most effectively improved CLA and decreased CH4 production. In the in vivo study (Experiment 2), 0.1% PO with 2% SBO (PSO) did not affect complete blood count. However, it decreased blood urea nitrogen and magnesium levels in blood (p = 0.021 and p = 0.01, respectively). PSO treatment decreased pathogenic microbes (p < 0.05). It increased milk yield (p = 0.017) but decreased percentage of milk fat (p = 0.013) and MUN level (p < 0.01). In addition, PSO treatment increased both the concentration of CLA and PUFA in milk fat (p < 0.01). Finally, it decreased CH4 emissions from dairy cows. These results provide compelling evidence that a diet supplemented with PSO can simultaneously increase CLA concentration and decrease CH4 production with no influence on the amount of milk fat (kg/day) in Holstein dairy cows.
Occult endocrine disorders newly diagnosed in patients with post-COVID-19 symptoms
Authors: Nakano Yasuhiro , Sunada Naruhiko , Tokumasu Kazuki , Honda Hiroyuki , Otsuka Yuki , Sakurada Yasue , Matsuda Yui , Hasegawa Toru , Omura Daisuke , Ochi Kanako , Yasuda Miho , Hagiya Hideharu , Ueda Keigo , Otsuka Fumio 
Published: March 2024

AbstractDetermination of long COVID requires ruling out alternative diagnoses, but there has been no report on the features of alternative diagnoses. This study was a single-center retrospective study of outpatients who visited our clinic between February 2021 and June 2023 that was carried out to determine the characteristics of alternative diagnoses in patients with post-COVID-19 symptoms. In a total of 731 patients, 50 patients (6.8%) were newly diagnosed with 52 diseases requiring medical intervention, and 16 (32%) of those 50 patients (2.2% of the total) were considered to have priority for treatment of the newly diagnosed disorders over long COVID treatment. The proportion of patients with a new diagnosis increased with advance of age, with 15.7% of the patients aged 60 years or older having a new diagnosis. Endocrine and metabolic diseases and hematological and respiratory diseases were the most common, being detected in eight patients (16%) each. Although 35 of the 52 diseases (67%) were related to their symptoms, endocrine and metabolic diseases were the least associated with specific symptoms. Other disorders that require attention were found especially in elderly patients with symptomatic long COVID. Thus, appropriate assessment and differentiation from alternative diagnoses are necessary for managing long COVID.
Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems
Authors: Premkumar Manoharan , Sinha Garima , Ramasamy Manjula Devi , Sahu Santhoshini , Subramanyam Chithirala Bala , Sowmya Ravichandran , Abualigah Laith , Derebew Bizuwork 
Published: March 2024

AbstractThis study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the conventional grey wolf optimizer in order to address the problem of data clustering. The process that groups similar items within a dataset into non-overlapping groups. Grey wolf hunting behaviour served as the model for grey wolf optimizer, however, it frequently lacks the exploration and exploitation capabilities that are essential for efficient data clustering. This work mainly focuses on enhancing the grey wolf optimizer using a new weight factor and the K-means algorithm concepts in order to increase variety and avoid premature convergence. Using a partitional clustering-inspired fitness function, the K-means clustering-based grey wolf optimizer was extensively evaluated on ten numerical functions and multiple real-world datasets with varying levels of complexity and dimensionality. The methodology is based on incorporating the K-means algorithm concept for the purpose of refining initial solutions and adding a weight factor to increase the diversity of solutions during the optimization phase. The results show that the K-means clustering-based grey wolf optimizer performs much better than the standard grey wolf optimizer in discovering optimal clustering solutions, indicating a higher capacity for effective exploration and exploitation of the solution space. The study found that the K-means clustering-based grey wolf optimizer was able to produce high-quality cluster centres in fewer iterations, demonstrating its efficacy and efficiency on various datasets. Finally, the study demonstrates the robustness and dependability of the K-means clustering-based grey wolf optimizer in resolving data clustering issues, which represents a significant advancement over conventional techniques. In addition to addressing the shortcomings of the initial algorithm, the incorporation of K-means and the innovative weight factor into the grey wolf optimizer establishes a new standard for further study in metaheuristic clustering algorithms. The performance of the K-means clustering-based grey wolf optimizer is around 34% better than the original grey wolf optimizer algorithm for both numerical test problems and data clustering problems.
Development of a distributed group control strategy for pumping well groups connected by multisource DC microgrids
Authors: Yue Jixiang , Sun Zhenhua , Li Haoguang , Zhu Wenyu , Li Fengming , Wang Zhenjie 
Published: March 2024

AbstractDue to the alternating loads on pumping units and the integration of new energy sources, multisource DC microgrid pumping unit well groups experience increased fluctuations in voltage and power as well as superimposed peak and valley values. This work presents a distributed control strategy for pumping unit well groups on a multisource DC microgrid based on the weighted moving average algorithm. A centralized control program is implanted in the RTU of the single-well controller of each pumping unit, and communication with each well is realized via SCADA and multicast communication, resulting in a distributed well group system. The real-time power values of the pumping well group are calculated by grouping the power values, and each group is weighted using the total power fluctuation threshold of the well group as the control target. Then, a weighted moving average algorithm is used to predict the next power value and form a table of predicted real-time power spectra. According to the power values in the community power spectrum table, the inverter frequency is proportionally adjusted downwards to reach the power peak before deceleration; after the power peak is crossed, the frequency is increased in the same way to reach the power valley before acceleration. Finally, the peak and valley power values of the bus system level off and further learn to reach the set impulse; ultimately, a stable impulse is formed. In laboratory testing and field application in the Shengli Oilfield XIN-11 block, the group control software module effectively suppressed the active power peak and valley values and voltage fluctuations of the bus system, the active power fluctuation rate range decreased by more than 70%, and the DC bus voltage fluctuation range decreased by more than 80%; moreover, the active power decreased by approximately 6% without additional hardware costs.
Research on the factors influencing the process of prefabricated fragments penetrating finite thickness concrete
Authors: Wang Zhenning , Li Qingxin , Yin Jianping , Wang Zhijun , Li Xudong , Yi Jianya 
Published: March 2024

AbstractThe damage to the back of the target plate is a phenomenon that occurs when concrete is subjected to high-speed impact. In order to study the motion parameters of prefabricated spherical fragments penetrating finite thickness concrete targets at high speeds and the occurrence rules of concrete damage, as well as the impact of target back damage on the motion of fragments, experiments were conducted on 100 mm finite thickness concrete targets with prefabricated spherical fragments. The concrete model parameters in LS-DYNA were modified based on the residual velocity of fragments, and numerical simulations were conducted on the penetration of prefabricated fragments with different impact velocities and concrete target plates with different thicknesses. By analyzing the location of concrete target plate damage, the relationship between concrete thickness and concrete damage was obtained; Combining the motion parameters of fragment penetration process, the phenomenon of concrete collapse was linked to fragment motion, and the influence of concrete thickness on fragment motion parameters was analyzed. The results indicate that the thickness of the finite thickness concrete target plate and the penetration speed of fragments have a significant impact on the damage state of the target back, and further affect the motion change response stage during the penetration process of prefabricated fragments.
Reconfiguration of low-voltage distributed power sources within electric power's distribution network based on improved particle swarm-fish swarm fusibility algorithm
Authors: Xu Xiaowei , Nie Ding , Xu Wenhua , Xiang Enxin , Chen Shan , Nie Yongjie , Fu Xiao , Xu Wan , Han Yiming 
Published: March 2024

AbstractWith the development of distributed power sources in the distribution network, the algorithm of distribution network reconfiguration is gaining attention from experts and scholars. Its goal is to reduce the power loss during power transmission, so as to reduce the power grid loss during power transmission. And weaken the electric heating effect in the process of electric energy transmission, thus maintaining the safety of the surrounding residents. Due to the wire impedance effect, a lot of electric energy of the circuit is lost to electric heating, which is easy to cause local overheating and lead to fire. This will not only cause power loss, but also endanger the safety of surrounding residents. To address the issue, experiments on distribution grid reconstruction are performed using the enhanced particle swarm-fish swarm algorithm with the Elecgrid self-constructed dataset. Initially, low-voltage distributed power sources in parallel are connected to the circuit, thereby decreasing internal resistance and electrical heat. Then, by controlling the circuit in the system, the double separation relay adjusts the inductance and capacitance of the conductor, thus reducing the reactance length. Additionally, particle swarm particles are mutated to enable them to jump out of the local optimum, and elite fish approach is used to expand the search area. Finally, the proposed fusion algorithm is applied to the self-built data set of Elecgrid and compared with the other three algorithms. The fusion algorithm serves as the standard test system for this comparison. The active power loss of the hybrid algorithm is 63 kW at an operating voltage of 0.74 V. The loss work of the other three algorithms is 74 kW, 97 kW and 109 kW respectively. The mixed algorithm has the lowest loss among the four algorithms. The experiments are repeated for six times, and the linear fitting degrees of the four algorithms are 0.9804, 0.9527, 0.9612 and 0.9503, respectively. The experimental results show that the application of this algorithm can effectively reduce the active loss in the process of distribution network reconfiguration, thus reducing energy consumption; At the same time, it can reduce the electric heating in the process of electric energy transmission, and then prevent the occurrence of fire. There are three main contributions of this study. Firstly, the resistance in the transmission path is reduced by using this algorithm, so that the power transmission efficiency can be analyzed more accurately. Secondly, the new algorithm enriches the power safety maintenance method; Finally, the fire caused by local overheating of the line is reduced by fusion algorithm.
Transcriptomic screening of novel targets of sericin in human hepatocellular carcinoma cells
Authors: Jantaravinid Jiraporn , Tirawanchai Napatara , Ampawong Sumate , Kengkoom Kanchana , Somkasetrin Anchaleekorn , Nakhonsri Vorthunju , Aramwit Pornanong 
Published: March 2024

AbstractSericin, a natural protein derived from Bombyx mori, is known to ameliorate liver tissue damage; however, its molecular mechanism remains unclear. Herein, we aimed to identify the possible novel targets of sericin in hepatocytes and related cellular pathways. RNA sequencing analysis indicated that a low dose of sericin resulted in 18 differentially expressed genes (DEGs) being upregulated and 68 DEGs being downregulated, while 61 DEGs were upregulated and 265 DEGs were downregulated in response to a high dose of sericin (FDR ≤ 0.05, fold change > 1.50). Functional analysis revealed that a low dose of sericin regulated pathways associated with the complement and coagulation cascade, metallothionine, and histone demethylate (HDMs), whereas a high dose of sericin was associated with pathways involved in lipid metabolism, mitogen-activated protein kinase (MAPK) signaling and autophagy. The gene network analysis highlighted twelve genes, A2M, SERPINA5, MT2A, MT1G, MT1E, ARID5B, POU2F1, APOB, TRAF6, HSPA8, FGFR1, and OGT, as novel targets of sericin. Network analysis of transcription factor activity revealed that sericin affects NFE2L2, TFAP2C, STAT1, GATA3, CREB1 and CEBPA. Additionally, the protective effects of sericin depended on the counterregulation of APOB, POU2F1, OGT, TRAF6, and HSPA5. These findings suggest that sericin exerts hepatoprotective effects through diverse pathways at different doses, providing novel potential targets for the treatment of liver diseases.
Comparable outcomes of outpatient remdesivir and sotrovimab among high-risk patients with mild to moderate COVID-19 during the omicron BA.1 surge
Authors: Chesdachai Supavit , Rivera Christina G. , Cole Kristin C. , Teaford Hilary R. , Gonzalez Suarez Maria L. , Larsen Jennifer J. , Ganesh Ravindra , Tulledge-Scheitel Sidna , Razonable Raymund R. 
Published: March 2024

AbstractStudies conducted prior to SARS-CoV-2 Omicron demonstrated that sotrovimab and remdesivir reduced hospitalization among high-risk outpatients with mild to moderate COVID-19. However, their effectiveness has not been directly compared. This study examined all high-risk outpatients with mild to moderate COVID-19 who received either remdesivir or sotrovimab at Mayo Clinic during the Omicron BA.1 surge from January to March 2022. COVID-19-related hospitalization or death within 28 days were compared between the two treatment groups. Among 3257 patients, 2158 received sotrovimab and 1099 received remdesivir. Patients treated with sotrovimab were younger and had lower comorbidity but were more likely to be immunocompromised than remdesivir-treated patients. The majority (89%) had received at least one dose of COVID-19 vaccine. COVID-19-related hospitalization (1.5% and 1.0% in remdesivir and sotrovimab, respectively, p = .15) and mortality within 28 days (0.4% in both groups, p = .82) were similarly low. A propensity score weighted analysis demonstrated no significant difference in the outcomes between the two groups. We demonstrated favorable outcomes that were not significantly different between patients treated with remdesivir or sotrovimab.
Do galaxy mergers prefer under-dense environments?
Authors: Sureshkumar U. , Durkalec A. , Pollo A. , Pearson W. J. , Farrow D. J. , Narayanan A. , Loveday J. , Taylor E. N. , Suelves L. E. 
Published: March 2024

Context. Galaxy mergers play a crucial role in galaxy evolution. However, the correlation between mergers and the local environment of galaxies is not fully understood.
Aims. We aim to address the question of whether galaxy mergers prefer denser or less dense environments by quantifying the spatial clustering of mergers and non-mergers. We use two different indicators to classify mergers and non-mergers – classification based on a deep learning technique (f) and non-parametric measures of galaxy morphology, Gini-M20 (g).
Methods. We used a set of galaxy samples in the redshift range 0.1 < z < 0.15 from the Galaxy and Mass Assembly (GAMA) survey with a stellar mass cut of log(M⋆/M⊙) > 9.5. We measured and compared the two-point correlation function (2pCF) of the mergers and non-mergers classified using the two merger indicators f and g. We measured the marked correlation function (MCF), in which the galaxies were weighted by f to probe the environmental dependence of galaxy mergers.
Results. We do not observe a statistically significant difference between the clustering strengths of mergers and non-mergers obtained using 2pCF. However, using the MCF measurements with f as a mark, we observe an anti-correlation between the likelihood of a galaxy being a merger and its environment. Our results emphasise the advantage of MCF over 2pCF in probing the environmental correlations.
Conclusions. Based on the MCF measurements, we conclude that the galaxy mergers prefer to occur in the under-dense environments on scales > 50 h−1 kpc of the large-scale structure (LSS). We attribute this observation to the high relative velocities of galaxies in the densest environments that prevent them from merging.
Dynamically cold disks in the early Universe: Myth or reality?
Authors: Kohandel M. , Pallottini A. , Ferrara A. , Zanella A. , Rizzo F. , Carniani S. 
Published: March 2024

Context. Theoretical models struggle to reproduce dynamically cold disks with significant rotation-to-dispersion support (Vrot/σ) observed in star-forming galaxies in the early Universe at redshift z > 4.
Aims. We aim to explore the possible emergence of dynamically cold disks in cosmological simulations and to understand whether different kinematic tracers can help reconcile the tension between theory and observations.
Methods. We used 3218 galaxies from the SERRA suite of zoom-in simulations, with 8 ≤ log(M⋆/M⊙) ≤ 10.3 and star formation rates SFR ≤ 128 M⊙/yr, within the 4 ≤ z ≤ 9 range. We generated hyperspectral data cubes for 2 × 3218 synthetic observations of Hα and [CII].
Results. We find that the choice of kinematic tracer strongly influences gas velocity dispersion (σ) estimates. In Hα ([C II]) synthetic observations, we observe a strong (mild) correlation between σ and M⋆. This difference mostly arises for M⋆ > 109 M⊙ galaxies, for which σHα > 2σ[CII] for a significant fraction of the sample. Regardless of the tracer, our predictions suggest the existence of massive (M⋆ > 1010 M⊙) galaxies with Vrot/σ > 10 at z > 4, maintaining cold disks for > 10 orbital periods (∼ 200 Myr). Furthermore, we find no significant redshift dependence for the Vrot/σ ratio in our sample.
Conclusions. Our simulations predict the existence of dynamically cold disks in the early Universe. However, different tracers are sensitive to different kinematic properties. While [C II] effectively traces the thin gaseous disk of galaxies, Hα includes the contribution from ionized gas beyond the disk region, characterized by prevalent vertical or radial motions that may be associated with outflows. We show that Hα halos could be a signature of these galactic outflows. This result emphasizes the importance of combining ALMA and JWST/NIRspec studies of high-z galaxies.
The steady state of intermediate-mass black holes near a supermassive black hole
Authors: Hochart E. , Portegies Zwart S. 
Published: March 2024

Aims. Our aim is to investigate the properties of a cluster of intermediate-mass black holes (IMBHs) surrounding a supermassive black hole (SMBH).
Methods. We simulated clusters of equal-mass IMBHs (mIMBH = 103 M⊙) initialised in a shell between 0.15 ≤ r [pc] ≤ 0.25 centred about a SMBH. We explored the influence of the cluster population and SMBH on the merger rate, the ejection rate, and the escape velocity. For MSMBH = 4 × 106 M⊙, we used both a Newtonian and post-Newtonian formalism, going up to the 2.5th order and including cross terms. We ran 40 and 60 simulations per cluster population for either formalism, respectively. For the other two SMBH masses (MSMBH = 4 × 105 M⊙ and MSMBH = 4 × 107 M⊙), we modelled the system only taking into account relativistic effects. In the case of MSMBH = 4 × 105 M⊙, 30 simulations were run per population. For MSMBH = 4 × 107 M⊙ we ran ten simulations per population. The simulations ended once a black hole escaped the cluster, a merger occured, or the system evolved until 100 Myr.
Results. The post-Newtonian formalism accelerates the loss rate of IMBHs compared to the Newtonian formalism. Ejections occur more often for lighter SMBHs while more massive ones increase the rate of mergers. Although relativistic effects allow for circularisation, all merging binaries have e ≳ 0.97 when measured 1 − 2 kyr before the merging event. The strongest gravitational wave signals are often sourced by IMBH-SMBH binaries that eventually merge. Strong signals were suppressed during our Newtonian calculations since, here, the IMBH typically stalls in the vicinity of the SMBH, before being generally ejected via the slingshot mechanism or experiencing a head-on collision. Weaker and more frequent signals are expected from gravitational wave radiation emitted in a flyby. In our post-Newtonian calculations, 30/406 (7.4%) of the gravitational wave events capable of being observed with LISA and μAres were detected as gravitational wave capture binaries with the remaining being in-cluster mergers. Throughout our investigation, no IMBH-IMBH binaries were detected.