bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on adaptive control strategy of virtual synchronous machine for optical storage inverter
Authors: Xia Min , Zhang Bin , Yang Yujin , Ke Qianwen , Li Sheng 
Published: February 2025

Abstract
With the wide application of renewable energy, the grid-connected stability of photovoltaic power generation systems has become increasingly prominent. To address the issues of power fluctuation and excessive frequency response caused by grid-connected photovoltaic power generation, this article introduces a flexible control approach for the Optical Storage Virtual Synchronous Generator (VSG). Through the construction of photovoltaic maximum power point tracking control (MPPT) and energy storage control strategy combined with basic circuit topology, the impact of rotational inertia and damping ratio on the dynamic behavior of VSG was examined. An adaptive control system was engineered to modify the control parameters dynamically. The simulation model was developed using the MATLAB/SIMULINK environment to verify the feasibility of the proposed control strategy. The simulation outcomes demonstrate that the adaptive control strategy is capable of effectively mitigating active power oscillations of the optical storage system, improving the rotor angular frequency overshoot, and enhancing the overall stability of the system.
Identification of transient unstable boundaries of distributed source loads considering the spatiotemporal distribution characteristics of virtual inertia
Authors: Sun Yifan , Zhong Weidong , Xu Jie , Chen Lei , Wang Yixiao 
Published: February 2025

Abstract
This paper proposes a research method for identifying transient unstable boundaries of distributed source loads considering the spatiotemporal distribution characteristics of virtual inertia. We establish a distributed source load system model and extract the spatiotemporal distribution characteristics of virtual inertia, including its variation patterns at different time scales, distribution differences at different spatial locations, and interaction mechanisms with other system parameters. A transient stability analysis model for power systems was established based on the dynamic model and control strategy of distributed power loads, identifying the transient instability boundaries of the system under different operating conditions. The experimental results show that this method can accurately identify the transient instability boundary of distributed power loads, improve the static voltage stability limit, suppress frequency and speed surges, increase power, and thus improve the transient voltage stability of the system.
Sensitivity analysis of closed and semi-closed heat pump drying systems
Authors: Zhang Weiqing , Fan Yi , Zhang Jingkui 
Published: February 2025

Abstract
Closed and semi-closed heat pump drying (CHPD and SCHPD) systems models were constructed. The system performance was found to be contingent upon the supply air temperature and the circulating air volume. The findings indicate that increasing the supply air temperature increases the Moisture Extraction Ratio (MER) of the CHPD and SCHPD systems but decreases the Coefficient of Performance (COP) of the CHPD and SCHPD systems. The energy efficiency and the Specific Moisture Extraction Ratio (SMER) of the SCHPD system are not as good as those of the CHPD system. The maximum difference in SMER between the CHPD and SCHPD systems is 3.31 kg/kWh, which occurs at a supply air temperature of 65°C. An increase in the circulating air volume has the effect of increasing the MER, SMER, and COP of the CHPD and SCHPD systems, reducing compressor power consumption but significantly decreasing supply air temperature.
An Extended Linearisation Approach to Nonlinear Control of Rover Lateral Dynamics
Authors: de Jesús Pablo-Sotelo Abraham , Ramírez-Luna Mauricio , Daniel Ávila-Gutiérrez Jesús , Olvera-Alvarado Abigail , Hernández Jorge 
Published: February 2025

Abstract
Space exploration in recent years has seen growth, with Mars being the preferred destination for major space agencies. Among the multiple problems faced by robotic exploration systems (commonly called rovers) is the control of their orientation. For this, complex and highly non-linear dynamic models are used as a starting point. Among the models used is the lateral dynamics model, which takes into consideration factors such as sideslip, yaw rate, and lateral forces generated in the rover. This work presents a non-linear control law based on extended linearisation capable of orienting the rover to a certain angle according to an inertial reference frame.
Failure analysis and lessons learned on crate and power supply equipment
Authors: Bobillier V. , Edvardsen J. , Mico S. , Pinzoni C. , Smaniotto B. 
Published: February 2025

Abstract
For nearly 20 years, the Power Supply and Crate Service at CERN has been responsible for
the maintenance tracking of power supplies and crates used by the CERN experiments. With this
experience, and with the imminent introduction of a new generation of power supplies for the
HL-LHC, the timing is ideal to conduct a statistical analysis to draw lessons from the past and
make recommendations for the future. This study aims to analyze failures, expose
the most vulnerable components, identify the improvement solutions, and highlight
the benefits of preventive maintenance campaigns to ensure reliable long-term operation.
Application of physics-informed neural networks for thin liquid film flows
Authors: Han Qixun , Sun Xianhu , Zhang Fan , Shao Sujuan , Ma Chicheng 
Published: February 2025

Abstract
The flow of a film induced by gravity is not only widespread in nature but also has significant applications in various industrial technologies such as coating techniques, nanotechnology, microfluidic chips, and heat exchangers. The film exhibits various nonlinear dynamic phenomena due to the interactions between surface tension, gravity, and other forces, making the study of this type of flow of great importance. However, the theoretical derivation of thin film fluid dynamics is complex, with diverse working conditions, making numerical solutions difficult, time-consuming, and labor-intensive. Therefore, it is of significant importance to seek an approach that differs from theoretical derivation or numerical solutions for the study of thin film fluid dynamics. With the rapid development of deep learning, this paper employs physics-informed neural networks (PINNs) algorithm, in conjunction with the partial differential equation governing the fluid film thickness, to conduct research on forward prediction of the film thickness variation over time and space, and inverse problem solving to determine unknown parameters in the governing equation from data. The study investigates the governing equation for the thickness of a falling film along an inclined plane and applies the PINNs method to solve it. The research predicted the film thickness for three different characteristic waveforms and conducted a comparative analysis with solutions obtained using the commercial software COMSOL. Additionally, the unknown parameters in the governing equation were inversely solved using limited data, and the differences in prediction results with and without noisy data were compared.
Active Brownian particle under stochastic position and orientation resetting in a harmonic trap
Authors: Shee Amir 
Published: February 2025

Abstract
We present an exact analytical study of an active Brownian particle (ABP) subject to both position and orientation stochastic resetting in a two dimensional harmonic trap. Utilizing a Fokker-Planck-based renewal approach, we derive the system’s exact moments, including the mean parallel displacement, mean squared displacement (MSD), and the fourth order moment of displacement, and compare these with numerical simulations. To capture deviations from Gaussian behavior, we analyze the excess kurtosis, which reveals rich dynamical crossovers over time. These transitions span from Gaussian behavior (zero excess kurtosis) to two distinct non-Gaussian regimes: an activity-dominated regime (negative excess kurtosis) and a resetting-dominated regime (positive excess kurtosis). Furthermore, we quantify the steady state phase diagrams by varying three key control parameters: activity, resetting rate, and harmonic trap strength, using steady state excess kurtosis as the primary metric.
MBR membrane fouling diagnosis based on multi-dimensional network
Authors: Zeng Jingxiao , Wang Zhiwen , Shi Yaoke , Ling Guobi , Wang Haoxu , Dong Hongyu , Zhang Hailin 
Published: February 2025

Abstract
This paper presents a Multi-Dimensional Network model aimed at analyzing mutually coupled membrane fouling in membrane bioreactors (MBR), addressing the limitations of existing diagnostic methods. First, fouling data were processed through wavelet transformation, using time-domain information as the network input. Second, initial features were extracted via convolution, with an inception structure applied for multidimensional feature extraction. Third, horizontal dense blocks were utilized to reduce network complexity while preserving key information. An attention mechanism was then incorporated to enhance model expressiveness, generalization, and diagnostic stability. Comparative testing revealed strong overall performance in diagnosing membrane fouling in hollow fiber membrane systems, achieving an average accuracy of 99.44%, which increased to 99.72% under noisy conditions. This underscores the model’s effectiveness in filtering contaminants in complex environments while maintaining excellent noise resistance and stability. Ultimately, the model significantly reduces operational and maintenance costs of wastewater treatment, providing a valuable theoretical foundation for advancing membrane water treatment technologies.
A parameter adaptive sine cosine algorithm for global optimization problems
Authors: Cheng Jiatang , Song Peisen , Xiong Yan 
Published: February 2025

Abstract
Sine cosine algorithm (SCA) is a random search technique for global numerical optimization. However, SCA still exhibits low efficiency for some complex problems. In this paper, we develop a novel SCA variant (PASCA) by introducing a parameter adaptive mechanism. Specifically, the control parameter is produced based on a Cauchy distribution rather than the original linear decreasing scheme. After that, at the end of each generation, the successful historical information is utilized to dynamically update the control parameter, which helps to strengthen the search ability and reduce dependence on the problem to be solved. To verify the effectiveness of PASCA algorithm, comparison experiments are conducted on 43 benchmark functions including 13 classic problems and CEC 2017 test suite as well as a time series prediction problem. Simulation results demonstrate that PASCA is an efficient and promising optimization method compared with the classic SCA and its four recent strong variants.
LSTM-based estimation of energy consumption in energy-intensive facilities
Authors: Uzun Ecem , Karabinaoğlu Murat Salim , Ayaz Murat 
Published: February 2025

Abstract
With rising energy demand, it is crucial to diversify energy sources and enhance energy efficiency. This urgency is particularly evident in energy-intensive facilities, where efficient energy production and consumption management play a pivotal role in optimizing energy utilization. In this study, a long- short-term memory (LSTM) based energy consumption estimation model was developed for a steel production plant as a representative energy-intensive facility. LSTM models excel in handling time-series data because of their ability to store sequential data in memory using memory blocks. The proposed model was subjected to a performance comparison with a traditional back-propagation neural network (BPNN) and regression-based models. Utilizing three-year production and consumption data, along with heating and cooling degree day information specific to the plant, the models were developed and tested. We validated and analyzed the models using 8640 data entries from the fourth year, which were not included in the training data. The evaluation based on the root mean squared error parameter yielded error values of 0.0586, 0.0608, and 0.0879 for the LSTM, BPNN, and regression models, respectively. Notably, the LSTM model achieved approximately 3.6% and 33.3% lower error rates in predicting the fourth year’s energy consumption compared to the BPNN and regression methods, utilizing data from the previous three years in an energy-intensive facility. In conclusion, the LSTM model introduced in this study offers a systematic approach to energy consumption forecasting, proving its effectiveness for energy-intensive facilities due to its flexible structure and ability to model nonlinear relationships.
Early Sedation with Dexmedetomidine in Patients with Acute Myocardial Infarction Requiring Mechanical Ventilation
Authors: Banna Soumya , Schenck Christopher , Singh Avinainder , Safiriyu Israel , Jimenez Jose Victor , Franko Ashley , Thomas Alexander , Heck Cory , Ludmir Jonathan , Gage Ann , Ali Tariq , Katz Jason N , Dudzinski David M , Ross Joseph S , Miller P Elliott 
Published: February 2025

Abstract

Background and Aims
Patients with acute myocardial infarction (AMI) who require invasive mechanical ventilation (IMV) represent a critically ill population with limited data on optimal sedative and analgesic use. Clinical trials assessing dexmedetomidine use exclude or poorly represent patients with AMI. This study aimed to compare the use of early sedation with dexmedetomidine to usual-care sedation in patients with AMI requiring IMV.

Methods
We utilized the Vizient® Clinical Data Base to identify patients aged ≥18 years admitted between 2015 and 2019 with a primary diagnosis of AMI who required IMV. Patients receiving dexmedetomidine on the first day of IMV were included in the early dexmedetomidine group while the remaining patients were assigned to the usual care group. Inverse probability of treatment weighting (IPTW) was used to estimate adjusted risk differences between groups.

Results
We identified 15,928 patients, of which 1,620 (10.2%) received early dexmedetomidine. Patients who received early dexmedetomidine were more likely to present with cardiogenic shock (52.0% vs. 47.7%, P=0.001). In unadjusted analyses, patients receiving early dexmedetomidine had lower in-hospital mortality (33.0% vs 42.1%) and more ventilator-free days (13.6 vs 12.1) compared to usual care (both, P&lt;0.05). After IPTW, patients receiving early dexmedetomidine had a 11.0% (95% confidence interval [CI]: 8.6% to 13.5%) lower mortality and more ventilator-free days (mean difference: +2.2 days, 95% CI: 1.6-2.8 days).

Conclusion
Early sedation with dexmedetomidine was associated with lower mortality compared to usual care in patients with AMI requiring IMV. A randomized controlled trial of sedative agents in this population is warranted
Genome-wide SNP-based relationships improve genetic parameter estimates and genomic prediction of growth traits in a large operational breeding trials of Pinus taeda L.
Authors: Tambarussi Evandro Vagner , Shalizi Mohammad Nasir , Grattapaglia Dario , Hodge Gary , Isik Fikret , Paludeto João Gabriel Zanon , Biernaski Fabricio A , Acosta Juan Jose 
Published: February 2025

Abstract
High-precision estimation of genetic parameters of growth traits is a fundamental requisite for effective selection of individuals to advance breeding cycles and support continued genetic gain in tree improvement. Due to the lack of efficient large-scale cloning techniques of adult trees, plantation forestry of Pinus taeda relies mostly on genetically improved families deployed by seed or clonally propagated from juvenile tissue. The accuracy of genetic parameter estimation is a direct function of the precision by which the genetic relatedness of individuals is measured. To this end, modern tree breeding has increasingly used high-density DNA markers to capture the realized genetic relatedness among individuals into a genomic relationship matrix (GRM) instead of the standard pedigrees. This study aimed to assess the impact of GRM in improving parameter estimation in an operational P. taeda network of progeny trials in southern Brazil. A total of 35 820 individuals from 332 open-pollinated families were measured for growth traits at age five, and 917 of them were genotyped with the Pita50K SNP array. Pedigree-best linear unbiased prediction (ABLUP) and single-step genomic BLUP (ssGBLUP) models were compared for parameter estimates and predictions of individual tree and family genetic values. Estimates of narrow-sense heritability (${h}_i^2$) were moderate to high, varying between 0.46 for height and 0.68 for diameter at breast height using both ABLUP and ssGBLUP models. Additive genetic correlations among trials indicated low magnitude genotype by environment interaction across trials. Preliminary estimates of genomic predictive ability ranged from 0.34 for height to 0.46 for volume using an RRBLUP model applied exclusively to the genotyped trees. Genotyping a relatively small portion of progeny individuals provides improved accuracies in selecting individuals and families opening the possibility of clonally propagating them from juvenile tissue for large-scale deployment of P. taeda clonal plantations.
Trajectories of Burden or Benefits of Caregiving Among Informal Caregivers of Older Adults: A Systematic Review
Authors: Ping Yongjing , Lim-Soh Jeremy , Østbye Truls , A'Azman Shamirah D/O , Ting Yong , Malhotra Rahul 
Published: February 2025

Abstract

Background and Objectives
Informal caregiving for older adults can be both burdensome and beneficial. Given that the informal caregiving situation may evolve over time, and care needs of older adults can result from diverse health conditions, it is valuable to understand the trajectories of burden or benefits of caregiving and how these trajectories vary across health conditions common among older care-recipients. This review is the first to summarize the literature on trajectories of burden or benefits of caregiving, including caregiver and care-recipient characteristics associated with the trajectories.

Research Design and Methods
We reviewed longitudinal observational quantitative studies, from five bibliographic databases, that assessed burden or benefits of caregiving at three or more time points among informal caregivers of older adults (60 years or above).

Results
The narrative synthesis included 41 studies, with only seven (17%) considering trajectories of benefits. A stable average trajectory of burden or benefits of caregiving was the most common pattern over time across various care-recipient health conditions. However, increasing burden over time was primarily observed among caregivers of persons with dementia, and decreasing burden among caregivers of persons discharged from a hospital after an acute health event. Only six (10%) studies, which reported heterogeneity in the progression of burden or benefits separately or jointly, identified distinctive trajectories within the same set of caregivers. Risk factors consistently identified to be associated with trajectories indicating persistently higher burden or persistently lower benefits included more care-recipient functional limitations and behavioral problems, being a non-spousal caregiver, being a solo caregiver, and perceiving less self-efficacy or competence.

Discussion and Implications
Future studies should focus on the trajectories of benefits of caregiving, untangle heterogeneity in trajectories of burden or benefits of caregiving, and consider both burden and benefits concurrently to identify factors that both enhance benefits and alleviate burden over time.
Poplar plantations enhance biomass and soil organic carbon stocks in a Yangtze River-connected floodplain wetland, China
Authors: Zhong Jiashun , Li Youzhi , Yu Dongzheng , Xie Yonghong , Hou Zhiyong , Chen Xinsheng 
Published: February 2025

Abstract
Floodplain wetlands have a significant capacity for carbon sequestration but are vulnerable to land use changes. Poplars are extensively planted in wetlands due to the increasing demand for wood products and bioenergy. Although the large biomass of poplar may increase the carbon stock in wetlands, a high transpiration rate may reduce soil moisture, thereby improving the aeration of wetland soils and facilitating the oxidation of organic materials. Therefore, the impact of poplars on wetland carbon stocks is undetermined and remains unexplored. Here, we investigated the effects of poplar plantations on biomass carbon stocks (BCS) and soil organic carbon (SOC) stocks in Dongting Lake wetlands, China, using native Miscanthus lutarioriparius vegetation as a control. Our results indicated that the BCS of middle-aged and near-mature poplar plantations (36.47–81.34 t ha−1) was higher than that of M. lutarioriparius (8.31 t ha−1), and it increased with stand age. The SOC stocks within the 0–60 cm depth in young, middle-aged, and near-mature poplar plantations (130.32–152.58 t ha−1) were higher than those in M. lutarioriparius (70.48 t ha−1), but it did not increase with stand age. The BCS was positively associated with soil bulk density, and the SOC stocks were negatively associated with soil sand content. Overall, our findings indicate that poplar plantations increase carbon stocks in the Dongting Lake wetlands. Nevertheless, the long-term effect of poplar plantation on carbon sequestration in floodplain wetlands should be further investigated.
Correlation between formaldehyde and methanol in prestellar cores
Authors: Punanova A F , Borshcheva K , Fedoseev G S , Caselli P , Wiebe D S , Vasyunin A I 
Published: February 2025

ABSTRACT
Formaldehyde is a key precursor in the formation routes of many complex organic molecules (COMs) in space. It is also an intermediate step in CO hydrogenation sequence that leads to methanol formation on the surface of interstellar grains in cold dense prestellar cores where pristine ices are formed. Various chemical models successfully reproduce the COMs abundances in cold cores, however, they consistently overpredict the abundance of formaldehyde by an order of magnitude. This results in an inverse H$_2$CO:CH$_3$OH abundance ratio obtained in the astrochemical simulations as compared to the observed values. In this work, we present a homogeneous data set of formaldehyde observational maps obtained towards seven dense cores in the L1495 filament with the IRAM 30-m telescope. Resolving the spatial distribution of the molecules is essential to test the chemical models. We carefully estimate the formaldehyde column densities and abundances to put reliable observational constraints on the chemical models of cold cores. Through numerous tests, we aim to constrain the updated chemical model monaco to better align with the observed formaldehyde abundance and its ratio to methanol. In particular, we elaborate on the branching ratio of the CH$_3$ + O reaction at low temperatures. The revised monaco model reproduces abundances of both methanol and formaldehyde within an order of magnitude. However, the model tends to overproduce formaldehyde and underproduce methanol. Consequently, the model systematically overestimates the H$_2$CO:CH$_3$OH ratio, although it remains within an order of magnitude of the values derived from observations.