bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Two-stage Humidification-dehumidification Heat Pump Desalination System
Authors: Wang Bingdong , Shen Jiubing , Jiang Lele , Wei Wenbin 
Published: April 2023

Abstract
For the humidification-dehumidification desalination unit to perform more efficiently, a two-stage humidification-dehumidification heat pump desalination system was proposed. So as to improve the heat and mass transfer effect between seawater and moist air, the two-stage humidifier was employed to recover the waste heat of seawater discharged from the first stage humidifier. The models of a one-stage and two-stage humidification heat pump seawater desalination system were built using Aspen Plus simulation software. Multi-condition simulation studies were carried out for different inlet seawater temperatures, liquid-gas mass ratios, and refrigerant flow rates of the heat pump. According to the comparative examination of the simulation’s outcomes, it is concluded that: with the increase in inlet seawater temperature and liquid-gas flow ratio, the two-stage humidifier system’s recovery rate and gain output ratio are superior to those of the first-stage humidifier system, and the inlet seawater temperature and circulating airflow needed for the two-stage humidifier system to perform at its best are less demanding than those for the first-stage humidifier system., indicating that the two-stage humidifier dehumidification desalination technology of the heat pump has great performance improvement and a broad application prospect.
Numerical study on the flow field in a supercritical fluid radial inflow turbine volute
Authors: Duan Siyu , Wang Zhongwei , Niu Yaobin , Miao Heyang 
Published: April 2023

Abstract
Due to the axial asymmetry of the volute structure, the circumferential inhomogeneity of the flow at the volute outlet exists, leading to the deviation of the flow in the nozzle and impeller from the ideal state. In this paper, a numerical study of a SCO2-radial inflow turbine is carried out to simulate the flow inside the turbine with the asymmetric and symmetric volute respectively. The results show that the use of a pear-shaped symmetric cross-section volute can effectively reduce the circumferential inhomogeneity of the flow, simplify the vortex structure inside the volute, reduce the flow losses and improve the efficiency of the turbine.
Pretreatment of Mulberry Twig using Nonionic Surfactant-assisted Ionic Liquid for Zymolysis and Subsequent Bioethanol Production
Authors: Ji Gengsheng , Li Qiang , Zhang Jianping 
Published: April 2023

Abstract
A natural cellulosic biomass pretreatment process was established to use ionic liquid (IL) for efficient zymolysis and subsequent bioethanol production, the IL 1, 3-Dimethylimidazolium dimethyl phosphate/Tween-80 ([Mmim][DMP]/T80) was selected in view of its high pretreatment function. The productivity of reducing sugars from mulberry twigs pretreated with the IL at 130°C for 0.33 h reached 74.72% after zymolysis for 48 h, while only a 14.62% conversion rate for the sample pretreated by water. The fermentability character of the hydrolyzate, witdrawn from zymolysis, was fermented into bioethanol using Saccharomyces cerevisiae. This kind of microbe could efficiently utilize glucose to produce ethanol with the yield of 0.382 g/g glucose in 30 h fermentation. In conclusion, the ionic liquid pretreatment at low temperatures shows promise as a pretreatment reagent for natural lignocellulosic biomass.
Reactive Power Optimization of Distribution Network with Distributed Power Based on MOPSO Algorithm
Authors: Xu Qianhui , Lan Ying 
Published: April 2023

Abstract
Wind turbine, photovoltaic and other power supply connected to the grid operation brings new critical problems to traditional reactive power optimization. Considering the safety and stability of operation, a reactive power optimization model with two objectives of minimum voltage offset and minimum network loss is established. In MATLAB, the reactive power optimization simulation analysis of the IEEE33 system connected with a wind turbine and photovoltaic is carried out, and the MOPSO algorithm is used to solve the reactive power optimization model. The multi-objective MOPSO algorithm is optimized to improve the stability of power grid operation and reduce the fluctuation of power flow. The network loss is reduced, and the effectiveness of the strategy is verified.
Wind Power Output Fluctuation Analysis Using Improved Motifs Method
Authors: Li Nan , Li Fang , Ma Xue , Qi Mengxue 
Published: April 2023

Abstract
Wind power has been widely utilized to support a considerable proportion of the power supply. However, wind power output is affected by weather and geographic factors to a large extent and therefore has the characteristics of being intermittent and random. To conduct subsequent studies on wind power output forecasting, a proper assessment of wind power output is required. We modified the traditional concept of three-vertex connected motifs from the perspective of magnitude, inspired by complex network and motif theory, and realized the wind power output fluctuation analysis. To testify to the effectiveness of the proposed method, an experiment based on the real-world wind power output of a wind farm was conducted. The network motifs’ distribution of the experimental results was consistent with the real-world wind power output fluctuation, which verified the accuracy of the proposed method.
Health Status Prediction of Lithium Battery Based on LSTM Model with Optimization Algorithms
Authors: Yang Jie , Zou Lin , Wei Yiying , Yuan Pengju , Zhou Chen 
Published: April 2023

Abstract
Consider the current status of health (SOH) of lithium batteries, which presents challenging existing issues of accurately predicting and calculating. In this paper, an LSTM model and multi-optimization algorithm were used to estimate the battery health state. Taking advantage of the fast convergence speed and wide global optimization range of the optimization algorithm, optimized the number of layers and neurons in the LSTM model so the LSTM model was established, used to predict the health status of lithium batteries, and compared with the LSTM model prediction method without optimization. The results showed that the error of the battery health prediction model based on the proposed prediction model was less than 3%, the prediction accuracy was higher than the LSTM model without optimization, and the model had better accuracy and stability.
INFIERI 2021: Hands-on Lab – LiDAR
Authors: Unno Y. 
Published: April 2023

Abstract
LiDAR is an acronym of “Light Detection and Ranging”, which is to measure the
distance to an object (“Ranging”) by detecting the light being reflected (“Light
Detection”).
The "hands-on" lab is made of two sections: (1) overviewing the technology, the
application, and the key devices of LiDAR, and (2) a laboratory where we operate
a LiDAR setup, do calibration, and look into signals in the electronics.
In the section (1), we learn the “basics” of the LiDAR.
In the section (2), we learn “real stuff” by using a LiDAR setup.
We use a simple desktop LiDAR setup developed by Hamamatsu photonics K.K. (HPK),
adapted for the hands-on lab in collaboration with the author.
The LiDAR setup, which is using “cutting-edge” solid-state devices, is a direct
time-of-flight LiDAR equipped with a 905 nm laser diode and a 16-ch MPPC photon
counting image sensor.
The light emitter is a pulsed solid-state laser (PLD) of 905 nm infra-red light.
The light receiver (a photon counting image sensor (PCI)) is a linear-array of
16 channel MPPC (a solid-state photomultiplier) with a readout ASIC.
The setup is also equipped with a visible-light camera, with which we correlate
the visual image with the feature of the LiDAR setup.
In the LiDAR laboratory, we do “aiming” (i.e., calibrate) by
detecting the infra-red laser light, and
correlating visual imaging and LiDAR “ranging”.
We get insight into the LiDAR setup by monitoring time-of-flight (TOF) and
energy (pulse height with time-over-threshold technology (TOT)) signals in the
electronics with an oscilloscope.
Through the process, we learn the real stuff of LiDAR and the issues associated.
Southwest US winter precipitation variability: reviewing the role of oceanic teleconnections
Authors: Karanja J , Svoma B M , Walter J , Georgescu M 
Published: April 2023

Abstract
The current drought plaguing the Southwest US (SWUS) underscores the need for long-term precipitation predictability to inform sustainable planning of future ecological and economic systems. Precipitation predictability requires understanding the teleconnections and intercorrelations of a suite of climate indices that are known to impact the SWUS. However, decision criteria about the selection of El Niño and southern oscillation (ENSO) and non-ENSO indices, definition of winter months, geographical extent, temporal scale, computation of what constitutes a long-term mean, and determination of the study period, have not been systematically examined, yet have important consequences on the appropriate characterization of SWUS winter precipitation predictability. Here, we used Pearson’s correlations, Mann–Kendall tests, descriptive statistics, and principal component analyses to explore the statistical relationships between natural modes of climate variability and observed SWUS precipitation. We found no statistically significant persistent changes in the patterns of precipitation for a suite of SWUS geographical designations. Our results show that the choice of the temporal scale has an important impact on the determination of the strength of the climate signal. We show that ENSO indices were the primary determinants of SWUS precipitation, although inconsistencies persisted depending on the choice of ENSO index, the selection of SWUS geographical designation, and the chosen winter month combination. Non-ENSO indices in isolation were found inadequate to explain SWUS precipitation outcomes. Our analysis also indicates the predictability of SWUS precipitation must consider neutral ENSO events when non-ENSO modes are found to play an important role. We recommend the undertaking of a coordinated multi-decadal suite of numerical modeling experiments that systematically account for the individual and total impacts of this critical set of climate indices to improve understanding of past precipitation outcomes and by extension, improve predictability for a future for which tens of millions of people will require advanced planning.
Decoding Connectivity Map-based drug repurposing for oncotherapy
Authors: Zhao Yuanchun , Chen Xingqi , Chen Jiajia , Qi Xin 
Published: April 2023

AbstractThe rising global burden of cancer has driven considerable efforts into the research and development of effective anti-cancer agents. Fortunately, with impressive advances in transcriptome profiling technology, the Connectivity Map (CMap) database has emerged as a promising and powerful drug repurposing approach. It provides an important platform for systematically discovering of the associations among genes, small-molecule compounds and diseases, and elucidating the mechanism of action of drug, contributing toward efficient anti-cancer pharmacotherapy. Moreover, CMap-based computational drug repurposing is gaining attention because of its potential to overcome the bottleneck constraints faced by traditional drug discovery in terms of cost, time and risk. Herein, we provide a comprehensive review of the applications of drug repurposing for anti-cancer drug discovery and summarize approaches for computational drug repurposing. We focus on the principle of the CMap database and novel CMap-based software/algorithms as well as their progress achieved for drug repurposing in the field of oncotherapy. This article is expected to illuminate the emerging potential of CMap in discovering effective anti-cancer drugs, thereby promoting efficient healthcare for cancer patients.
Multivariate genome-wide association analysis by iterative hard thresholding
Authors: Chu Benjamin B , Ko Seyoon , Zhou Jin J , Jensen Aubrey , Zhou Hua , Sinsheimer Janet S , Lange Kenneth 
Published: April 2023

Abstract

Motivation
In a genome-wide association study, analyzing multiple correlated traits simultaneously is potentially superior to analyzing the traits one by one. Standard methods for multivariate genome-wide association study operate marker-by-marker and are computationally intensive.

Results
We present a sparsity constrained regression algorithm for multivariate genome-wide association study based on iterative hard thresholding and implement it in a convenient Julia package MendelIHT.jl. In simulation studies with up to 100 quantitative traits, iterative hard thresholding exhibits similar true positive rates, smaller false positive rates, and faster execution times than GEMMA’s linear mixed models and mv-PLINK’s canonical correlation analysis. On UK Biobank data with 470 228 variants, MendelIHT completed a three-trait joint analysis (n=185 656) in 20 h and an 18-trait joint analysis (n=104 264) in 53 h with an 80 GB memory footprint. In short, MendelIHT enables geneticists to fit a single regression model that simultaneously considers the effect of all SNPs and dozens of traits.

Availability and implementation
Software, documentation, and scripts to reproduce our results are available from https://github.com/OpenMendel/MendelIHT.jl.
Lem2 is essential for cardiac development by maintaining nuclear integrity
Authors: Ross Jacob A , Arcos-Villacis Nathaly , Battey Edmund , Boogerd Cornelis , Orellana Constanza Avalos , Marhuenda Emilie , Swiatlowska Pamela , Hodzic Didier , Prin Fabrice , Mohun Tim , Catibog Norman , Tapia Olga , Gerace Larry , Iskratsch Thomas , Shah Ajay M , Stroud Matthew J 
Published: April 2023

Abstract

Aims
Nuclear envelope integrity is essential for the compartmentalization of the nucleus and cytoplasm. Importantly, mutations in genes encoding nuclear envelope (NE) and associated proteins are the second highest cause of familial dilated cardiomyopathy. One such NE protein that causes cardiomyopathy in humans and affects mouse heart development is Lem2. However, its role in the heart remains poorly understood.

Methods and results
We generated mice in which Lem2 was specifically ablated either in embryonic cardiomyocytes (Lem2 cKO) or in adult cardiomyocytes (Lem2 iCKO) and carried out detailed physiological, tissue, and cellular analyses. High-resolution episcopic microscopy was used for three-dimensional reconstructions and detailed morphological analyses. RNA-sequencing and immunofluorescence identified altered pathways and cellular phenotypes, and cardiomyocytes were isolated to interrogate nuclear integrity in more detail. In addition, echocardiography provided a physiological assessment of Lem2 iCKO adult mice. We found that Lem2 was essential for cardiac development, and hearts from Lem2 cKO mice were morphologically and transcriptionally underdeveloped. Lem2 cKO hearts displayed high levels of DNA damage, nuclear rupture, and apoptosis. Crucially, we found that these defects were driven by muscle contraction as they were ameliorated by inhibiting myosin contraction and L-type calcium channels. Conversely, reducing Lem2 levels to ∼45% in adult cardiomyocytes did not lead to overt cardiac dysfunction up to 18 months of age.

Conclusions
Our data suggest that Lem2 is critical for integrity at the nascent NE in foetal hearts, and protects the nucleus from the mechanical forces of muscle contraction. In contrast, the adult heart is not detectably affected by partial Lem2 depletion, perhaps owing to a more established NE and increased adaptation to mechanical stress. Taken together, these data provide insights into mechanisms underlying cardiomyopathy in patients with mutations in Lem2 and cardio-laminopathies in general.
Nurse-led care after ablation of atrial fibrillation: a randomized controlled trial
Authors: Vanharen Yaël , Abugattas de Torres Juan Pablo , Adriaenssens Bert , Convens Carl , Schwagten Bruno , Tijskens Maxime , Wolf Michael , Goossens Eva , Van Bogaert Peter , de Greef Yves 
Published: April 2023

Abstract

Aims
The added value of advanced practitioner nurse (APN) care after ablation of atrial fibrillation (AF) is unknown. The present study investigates the impact of APN-led care on AF recurrence, patient knowledge, lifestyle, and patient satisfaction.

Methods and results
Sixty-five patients undergoing AF ablation were prospectively randomized to usual care (N = 33) or intervention (N = 32) group. In addition to usual care, the intervention consisted of an educational session, three consultations spread over 6 months and telephone accessibility coordinated by the APN. Primary outcome was the AF recurrence rate at 6-month follow-up. Secondary outcomes were lifestyle factors (alcohol intake, exercise, BMI, smoking), patient satisfaction and AF knowledge measured at 1 and 6 months between groups and within each group. Study demographics at 1 month were similar, except AF knowledge was higher in the intervention group (8.6 vs. 7, P = 0.001). At 6 months, AF recurrence was significantly lower in the intervention group (13.5 vs. 39.4%, P = 0.014). Between groups, patient satisfaction and AF knowledge were significantly higher in the intervention group, respectively, 9.4 vs. 8.7 (P &lt; 0.001) and 8.6 vs. 7.0 out of 10 (P &lt; 0.001). Within the intervention group, alcohol intake decreased from 3.9 to 2.6 units per week (P = 0.031) and physical activity increased from 224.4 ± 210.7 to 283.8 ± 169.3 (P = 0.048). No changes occurred within the usual care group. Assignment to the intervention group was the only protective factor for AF recurrence [Exp(B) 0.299, P = 0.04] in multivariable-adjusted analysis.

Conclusion
Adding APN-led care after ablation of AF improves short-term clinical outcome, patient satisfaction and physical activity and decreases alcohol intake.
Generating synthetic laser scanning data of forests by combining forest inventory information, a tree point cloud database and an open-source laser scanning simulator
Authors: Schäfer Jannika , Weiser Hannah , Winiwarter Lukas , Höfle Bernhard , Schmidtlein Sebastian , Fassnacht Fabian Ewald 
Published: April 2023

Abstract
Airborne laser scanning (ALS) data are routinely used to estimate and map structure-related forest inventory variables. The further development, refinement and evaluation of methods to derive forest inventory variables from ALS data require extensive datasets of forest stand information on an individual tree-level and corresponding ALS data. A cost-efficient method to obtain such datasets is the combination of virtual forest stands with a laser scanning simulator. We present an approach to simulate ALS data of forest stands by combining forest inventory information, a tree point cloud database and the laser scanning simulation framework HELIOS++. ALS data of six 1-ha plots were simulated and compared to real ALS data of these plots. The synthetic 3D representations of the forest stands were composed of real laser scanning point clouds of individual trees that were acquired by an uncrewed aerial vehicle (UAV), and, for comparison, simplified tree models with cylindrical stems and spheroidal crowns. The simulated ALS point clouds of the six plots were compared with the real point clouds based on canopy cover, height distribution of returns and several other point cloud metrics. In addition, the performance of biomass models trained using these synthetic data was evaluated. The comparison revealed that, in general, both the real tree models and the simplified tree models can be used to generate synthetic data. The results differed for the different study sites and depending on whether all returns or only first returns were considered. The measure of canopy cover was better represented by the data of the simplified tree models, whereas the height distribution of the returns was – for most of the study sites – better represented by the real tree model data. Training biomass models with metrics derived from the real tree model data led to an overestimation of biomass, while using metrics of the simplified tree model data resulted in an underestimation of biomass. Still, the accuracy of models trained with simulated data was only slightly lower compared to models trained with real ALS data. Our results suggest that the presented approach can be used to generate ALS data that are sufficiently realistic for many applications. The synthetic data may be used to develop new or refine existing ALS-based forest inventory methods, to systematically investigate the relationship between point cloud metrics and forest inventory variables and to analyse how this relationship is affected by laser scanning acquisition settings and field reference data characteristics.
Adaptive Regulation of Stopover Refueling during Bird Migration: Insights from Whole Blood Transcriptomics
Authors: Bounas Anastasios , Komini Chrysoula , Talioura Artemis , Toli Elisavet-Aspasia , Sotiropoulos Konstantinos , Barboutis Christos 
Published: April 2023

Abstract
Migration is one of the most energy-demanding tasks in avian life cycle. Many birds might not have sufficient fuel stores to cover long distances, so they must stop to rest and refuel at stopover sites, especially after the crossing of large ecological barriers. There, birds undergo several behavioral, morphological, and physiological trait adjustments to recover from and prepare for their journey; however, regulation of such processes at the molecular level remains largely unknown. In this study, we used transcriptomic information from the whole blood of migrating garden warblers (Sylvia borin) to identify key regulatory pathways related to adaptations for migration. Birds were temporarily caged during spring migration stopover and then sampled twice at different refueling states (lean vs. fat), reflecting different migratory stages (stopover arrival vs. departure) after the crossing of an extended ecological barrier. Our results show that top expressed genes during migration are involved in important pathways regarding adaptations to migration at high altitudes such as increase of aerobic capacity and angiogenesis. Gene expression profiles largely reflected the two experimental conditions with several enzymes involved in different aspects of metabolic activity being differentially expressed between states providing several candidate genes for future functional studies. Additionally, we identified several hub genes, upregulated in lean birds that could be involved in the extraordinary phenotypic flexibility in organ mass displayed by avian migrants. Finally, our approach provides novel evidence that regulation of water homeostasis may represent a significant adaptive mechanism, allowing birds to conserve water during long-distance flight, mainly through protein catabolism.