bluuebunny/crossref_metadata_2025_split huggingface dataset:
Potential for spatial coexistence of a transboundary migratory species and wind energy development
Authors: Huang Ta-Ken , Feng Xiao , Derbridge Jonathan J. , Libby Kaitlin , Diffendorfer Jay E. , Thogmartin Wayne E. , McCracken Gary , Medellin Rodrigo , López-Hoffman Laura 
Published: July 2024

AbstractGlobal expansion in wind energy development is a notable achievement of the international community’s effort to reduce carbon emissions during energy production. However, the increasing number of wind turbines have unintended consequences for migratory birds and bats. Wind turbine curtailment and other mitigation strategies can reduce fatalities, but improved spatial and temporal data are needed to identify the most effective way for wind energy development and volant migratory species to coexist. Mexican free-tailed bats (Tadarida brasiliensis mexicana) account for a large proportion of known bat fatalities at wind facilities in the southwestern US. We examined the geographic concordance between existing wind energy generation facilities, areas of high wind potential amenable for future deployment of wind facilities, and seasonally suitable habitat for these bats. We used ecological niche modeling to determine species distribution during each of 4 seasons. We used a multi-criteria GIS-based approach to produce a wind turbine siting suitability map. We identified seasonal locations with highest and lowest potential for the species’ probability of occurrence, providing a potential explanation for the higher observed fatalities during fall migration. Thirty percent of 33,606 wind turbines within the southwestern US occurred in highly suitable areas for Mexican free-tailed bats, primarily in west Texas. There is also broad spatial overlap between areas of high wind potential and areas of suitable habitat for Mexican free-tailed bats. Because of this high degree of overlap, our results indicate that post-construction strategies, such as curtailing the timing of operations and deterrents, would be more effective for bat conservation than strategic siting of new wind energy installations.
Intergenerational effects of racism on amygdala and hippocampus resting state functional connectivity
Authors: Kral T. R. A. , Williams C. Y. , Wylie A. C. , McLaughlin K. , Stephens R. L. , Mills-Koonce W. R. , Birn R. M. , Propper C. B. , Short S. J. 
Published: July 2024

AbstractRacism is an insidious problem with far-reaching effects on the lives of Black, Indigenous, and People of Color (BIPOC). The pervasive negative impact of racism on mental health is well documented. However, less is known about the potential downstream impacts of maternal experiences of racism on offspring neurodevelopment. This study sought to examine evidence for a biological pathway of intergenerational transmission of racism-related trauma. This study examined the effects of self-reported maternal experiences of racism on resting state functional connectivity (rsFC) in n = 25 neonates (13 female, 12 male) birthed by BIPOC mothers. Amygdala and hippocampus are brain regions involved in fear, memory, and anxiety, and are central nodes in brain networks associated with trauma-related change. We used average scores on the Experiences of Racism Scale as a continuous, voxel-wise regressor in seed-based, whole-brain connectivity analysis of anatomically defined amygdala and hippocampus seed regions of interest. All analyses controlled for infant sex and gestational age at the 2-week scanning session. More maternal racism-related experiences were associated with (1) stronger right amygdala rsFC with visual cortex and thalamus; and (2) stronger hippocampus rsFC with visual cortex and a temporo-parietal network, in neonates. The results of this research have implications for understanding how maternal experiences of racism may alter neurodevelopment, and for related social policy.
Rapid differentiation of cystic fibrosis-related bacteria via reagentless atmospheric pressure photoionisation mass spectrometry
Authors: Haworth-Duff Adam , Smith Barry L. , Sham Tung-Ting , Boisdon Cedric , Loughnane Paul , Burnley Mark , Hawcutt Daniel B. , Raval Rasmita , Maher Simon 
Published: July 2024

AbstractBreath analysis is an area of significant interest in medical research as it allows for non-invasive sampling with exceptional potential for disease monitoring and diagnosis. Volatile organic compounds (VOCs) found in breath can offer critical insight into a person’s lifestyle and/or disease/health state. To this end, the development of a rapid, sensitive, cost-effective and potentially portable method for the detection of key compounds in breath would mark a significant advancement. Herein, we have designed, built and tested a novel reagent-less atmospheric pressure photoionisation (APPI) source, coupled with mass spectrometry (MS), utilising a bespoke bias electrode within a custom 3D printed sampling chamber for direct analysis of VOCs. Optimal APPI-MS conditions were identified, including bias voltage, cone voltage and vaporisation temperature. Calibration curves were produced for ethanol, acetone, 2-butanone, ethyl acetate and eucalyptol, yielding R2 > 0.99 and limits of detection < 10 pg. As a pre-clinical proof of concept, this method was applied to bacterial headspace samples ofEscherichia coli(EC),Pseudomonas aeruginosa(PSA) andStaphylococcus aureus(SA) collected in 1 L Tedlar bags. In particular, PSA and SA are commonly associated with lung infection in cystic fibrosis patients. The headspace samples were classified using principal component analysis with 86.9% of the total variance across the first three components and yielding 100% classification in a blind-sample study. All experiments conducted with the novel APPI arrangement were carried out directly in real-time with low-resolution MS, which opens up exciting possibilities in the future for on-site (e.g., in the clinic) analysis with a portable system.
Reliable prediction of implant size and axial alignment in AI-based 3D preoperative planning for total knee arthroplasty
Authors: Lan Qing , Li Shulin , Zhang Jiahao , Guo Huiling , Yan Laipeng , Tang Faqiang 
Published: July 2024

AbstractThe size and axial alignment of prostheses, when planned during total knee replacement (TKA) are critical for recovery of knee function and improvement of knee pain symptoms. This research aims to study the effect of artificial intelligence (AI)-based preoperative three dimensional (3D) planning technology on prosthesis size and axial alignment planning in TKA, and to compare its advantages with two dimensional (2D) X-ray template measurement technology. A total of 60 patients with knee osteoarthritis (KOA) who underwent TKA for the first time were included in the AI (n = 30) and 2D (n = 30) groups. The preoperative and postoperative prosthesis size, femoral valgus correction angle (VCA) and hip-knee-ankle angle (HKA) were recorded and compared between the two groups. The results of the University of Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and the American Knee Association Score (AKS) were evaluated before surgery, 3 months, 6 months, and 12 months after surgery. The accuracy of prosthesis size, VCA and HKA prediction in AI group was significantly higher than that in 2D group (P < 0.05). The WOMAC and AKS scores in AI group at 3 months, 6 months and 12 months after surgery were better than those in 2D group (P < 0.05). Both groups showed significant improvement in WOMAC and AKS scores at 12 months follow-up. AI-based preoperative 3D planning technique has more reliable planning effect for prosthesis size and axial alignment in TKA.
Distribution and soil threshold of selenium in the cropland of southwest mountainous areas in China
Authors: Wang Sheng , Liu Qi , Liu Zhizong , Chen Wen , Zhao Xuanyue , Zhang Jilai , Bao Li , Zhang Naiming 
Published: July 2024

AbstractTo investigate the distribution characteristics of selenium (Se) in mountainous soil-crop systems and examine the threshold value of Se-rich soil, 275 soil samples and 153 associated crop samples (rice, maize, tea, nuts, konjac, mushrooms, buckwheat, and coffee) were collected in Ximeng County, a typical mountainous area in southwest China. The total Se, available Se, organic matter, pH, sampling point elevation, and crop Se content were analyzed to examine the distribution characteristics of soil Se and the ability of primary crops to enrich Se in Ximeng County. Random forest and multiple regression models were established to identify the factors influencing the available soil Se and the crop Se enrichment coefficient. Finally, the Se-rich soil threshold was examined based on the total Se, available Se, and Se content in primary crops (rice, maize, and tea). The results showed soil Se resource abundance in the study region, with high Se soil accounting for 64.72% of the entire area. The soil Se content displayed significant spatial autocorrelation. The average Se enrichment coefficient of the main cultivated crops included mushrooms > nuts > rice > coffee > tea > maize > buckwheat > konjac. The total Se content in the soil had the highest impact on the available Se content in the soil and the Se enrichment coefficient of crops. A Se-rich soil threshold of 0.3 mg·kg−1 was used for rice and maize, while that of tea was 0.4 mg·kg−1. This result provided a theoretical basis for developing and utilizing Se resources in mountainous soil in southwestern China and dividing the Se-rich soil threshold.
Exploring transcriptomic databases: unraveling circadian gene disruptions in lower grade glioma
Authors: Hou Weiyu , Hou Weiming , Zhao Xueming 
Published: July 2024

AbstractThe study explored the role of circadian rhythm genes (CRGs) in lower grade glioma (LGG) development and found that certain genes, such as CRY1, NPAS2, and RORB, were associated with increased or decreased risk of LGG. The study also investigated the correlation between CRGs and immune cell infiltration, revealing a negative association with macrophage infiltration and a positive correlation with B cell and CD8 + T cell infiltration. Additionally, the study identified major mutated CRGs, including PER2, BMAL1, CLOCK, and BMAL2, and their potential interaction with other CNS-associated genes. The study suggests that CRGs play a crucial role in immune response and tumorigenesis in LGG patients and warrants further investigation.
Analysis of Rutherford backscattering spectra with CNN-GRU mixture density network
Authors: Muzakka Khoirul Faiq , Möller Sören , Kesselheim Stefan , Ebert Jan , Bazarova Alina , Hoffmann Helene , Starke Sebastian , Finsterbusch Martin 
Published: July 2024

AbstractIon Beam Analysis (IBA) utilizing MeV ion beams provides valuable insights into surface elemental composition across the entire periodic table. While ion beam measurements have advanced towards high throughput for mapping applications, data analysis has lagged behind due to the challenges posed by large volumes of data and multiple detectors providing diverse analytical information. Traditional physics-based fitting algorithms for these spectra can be time-consuming and prone to local minima traps, often taking days or weeks to complete. This study presents an approach employing a Mixture Density Network (MDN) to model the posterior distribution of Elemental Depth Profiles (EDP) from input spectra. Our MDN architecture includes an encoder module (EM), leveraging a Convolutional Neural Network-Gated Recurrent Unit (CNN-GRU), and a Mixture Density Head (MDH) employing a Multi-Layer Perceptron (MLP). Validation across three datasets with varying complexities demonstrates that for simple and intermediate cases, the MDN performs comparably to the conventional automatic fitting method (Autofit). However, for more complex datasets, Autofit still outperforms the MDN. Additionally, our integrated approach, combining MDN with the automatic fit method, significantly enhances accuracy while still reducing computational time, offering a promising avenue for improved analysis in IBA.
Racial/ethnic disparities in the distribution of heatwave frequency and expected economic losses in the US
Authors: Chakraborty Jayajit 
Published: July 2024

AbstractPrevious research on social disparities in heat exposure has not examined heatwave frequency or economic damage at the local or neighborhood level. Additionally, most US studies have focused on specific cities or regions, and few national-scale studies encompassing both urban and rural areas have been conducted. These gaps are addressed here by analyzing racial/ethnic disparities in the distribution of annual heatwave frequency and expected economic losses from heatwave occurrence in the contiguous US. Census tract-level data on annualized heatwave frequency and expected loss from the FEMA’s National Risk Index are linked to relevant variables from the American Community Survey. Results indicate that all racial/ethnic minority groups except non-Hispanic Black are significantly overrepresented in neighborhoods with greater annual heatwave frequency (top 10% nationally), and all minority groups are overrepresented in neighborhoods with greater total expected annual loss from heatwaves, compared to non-Hispanic Whites. Multivariable models that control for spatial clustering, climate zone, and relevant socio-demographic factors reveal similar racial/ethnic disparities, and suggest significantly greater heatwave frequency and economic losses in neighborhoods with higher percentages of Hispanics and American Indians. These findings represent an important starting point for more detailed investigations on the adverse impacts of heatwaves for US minority populations and formulating appropriate policy interventions.
Note-taking fosters distance video learning: smartphones as risk and intellectual values as protective factors
Authors: Hefter Markus H. 
Published: July 2024

AbstractDistance video learning, especially with how-to videos, has become extremely popular. Whereas previous studies revealed note-taking as a prominent and promising support measure for video learning in the lab, we focus on note-taking while learning from a how-to video in a distance learning setting. Meanwhile, learners’ digital distraction and smartphone usage have become widespread and excessive, potentially harming learning. We thus also aimed to analyze potential risk and protective factors associated with learning with how-to videos, such as smartphone usage time and intellectual values. We conducted an online field experiment involving 59 psychology students, who learned with a short how-to video on plumbing. We found that note-takers outperformed non-note-takers in a posttest about the video content. Furthermore, this note-taking effect on learning outcomes was mediated by learning engagement. Besides note-taking and intellectual values as contributing positively to learning outcomes, we also identified the mean daily smartphone usage time as a risk factor to learning. Overall, our results show how beneficial it is for students to take notes while learning with how-to videos in a distance learning setting. Conversely, learners should avoid digital distractions, in particular through smartphones.
Biomarker-guided acute kidney injury risk assessment under liberal versus restrictive fluid therapy - the prospective-randomized MAYDAY-trial
Authors: Anker Alexandra M. , Ruewe Marc , Prantl Lukas , Baringer Magnus , Pawlik Michael T. , Zeman Florian , Goecze Ivan , Klein Silvan M. 
Published: July 2024

AbstractAcute kidney injury (AKI) prevalence in surgical patients is high, emphasizing the need for preventative measures. This study addresses the insufficient evidence on nephroprotective intraoperative fluid resuscitation and highlights the drawbacks of relying solely on serum creatinine/urine output to monitor kidney function. This study assessed the impact of intraoperative fluid management on AKI in female breast cancer patients undergoing autologous breast reconstruction, utilizing novel urinary biomarkers (TIMP-2 and IGFBP-7). In a monocentric prospective randomized controlled trial involving 40 patients, liberal (LFA) and restrictive (FRV) fluid management strategies were compared. TIMP-2 and IGFBP-7 biomarker levels were assessed using the NephroCheck (bioMerieux, France) test kit at preoperative, immediate postoperative, and 24-h postoperative stages. FRV showed significantly higher immediate postoperative biomarker levels, indicating renal tubular stress. FRV patients had 21% (4/19) experiencing AKI compared to 13% (2/15) in the LFA group according to KDIGO criteria (p = 0.385). Restrictive fluid resuscitation increases the risk of AKI in surgical patients significantly, emphasizing the necessity for individualized hemodynamic management. The findings underscore the importance of urinary biomarkers in early AKI detection.
BCL-2 and BOK regulate apoptosis by interaction of their C-terminal transmembrane domains
Authors: Beigl Tobias B , Paul Alexander , Fellmeth Thomas P , Nguyen Dang , Barber Lynn , Weller Sandra , Schäfer Benjamin , Gillissen Bernhard F , Aulitzky Walter E , Kopp Hans-Georg , Rehm Markus , Andrews David W , Pluhackova Kristyna , Essmann Frank 
Published: July 2024

AbstractThe Bcl-2 family controls apoptosis by direct interactions of pro- and anti-apoptotic proteins. The principle mechanism is binding of the BH3 domain of pro-apoptotic proteins to the hydrophobic groove of anti-apoptotic siblings, which is therapeutically exploited by approved BH3-mimetic anti-cancer drugs. Evidence suggests that also the transmembrane domain (TMD) of Bcl-2 proteins can mediate Bcl-2 interactions. We developed a highly-specific split luciferase assay enabling the analysis of TMD interactions of pore-forming apoptosis effectors BAX, BAK, and BOK with anti-apoptotic Bcl-2 proteins in living cells. We confirm homotypic interaction of the BAX-TMD, but also newly identify interaction of the TMD of anti-apoptotic BCL-2 with the TMD of BOK, a peculiar pro-apoptotic Bcl-2 protein. BOK-TMD and BCL-2-TMD interact at the endoplasmic reticulum. Molecular dynamics simulations confirm dynamic BOK-TMD and BCL-2-TMD dimers and stable heterotetramers. Mutation of BCL-2-TMD at predicted key residues abolishes interaction with BOK-TMD. Also, inhibition of BOK-induced apoptosis by BCL-2 depends specifically on their TMDs. Thus, TMDs of Bcl-2 proteins are a relevant interaction interface for apoptosis regulation and provide a novel potential drug target.
Derating factor determination of the three‐phase induction motor under unbalanced voltage using pumping system
Authors: Majeed Samar Hameed , Seifossadat Seyed Ghodratolah , Saniei Mohsen , Moosapour Seyyed Sajjad 
Published: July 2024

AbstractA novel method is presented for determining the derating factors of a three‐phase induction motor under the condition of the unbalanced supply voltages. In this method, a mechanical system is used which consist of the a centrifugal pump, two valves, a DC motor, which are connected to the shaft of the three‐phase induction motor. A sliding mode control system is used for position control of the DC motor for adjusting the valve angle for derating the induction motor. The authors present the results of an experiment in which a three‐phase induction motor was subjected to various unbalanced voltage conditions. The results of simulations were used to look into what happened when there were different levels of imbalanced voltage. This was done to determine how these situations changed an induction motor's speed, torque, and efficiency. For this system, the stator current would be greater than the rated current if there was an imbalance in the supply voltage. Therefore, to reduce the amount of power that the three‐phase induction motor can produce, the control system uses a DC motor to reduce the angle of one of the two valves. This decreasing angle continues until the root mean square value of the stator current returns to the rated current. At this point, the derating factor may be calculated by dividing the output power of the three‐phase induction motor in the unbalanced condition by the output power when there are ideal sinusoidal. The MATLAB SIMULINK environment is utilised to perform simulations of the proposed system.
Frequency control using fuzzy active disturbance rejection control and machine learning in a two‐area microgrid under cyberattacks
Authors: Rahnamayian Jelodar Soheil , Heidary Jalal , Rahmani Reza , Vahidi Behrooz , Askarian‐Abyaneh Hossein 
Published: July 2024

AbstractThere is a change in the traditional power system structure as a result of the increased incorporation of microgrids (MGs) into the grid. Multi‐area MGs will emerge as a result, and issues related to them will need to be addressed. Load frequency control (LFC) is a challenge in such structures, which are more complicated due to variations in demand and the stochastic characteristics of renewable energy sources. This paper presents a cascade fuzzy active disturbance rejection control technique to deal with the LFC problem. In order to tune different parameters of controllers, a newly developed heuristic algorithm called the Gazelle optimization algorithm (GOA) is also employed. Moreover, due to the fact that multi‐area MGs are regarded as cyber‐physical systems (CPSs), a relatively new concern for LFC problems is their resilience to cyberattacks such as false data injection (FDI) and denial of service (DoS) attacks. Therefore, this research also presents a novel machine learning approach called parallel attack resilience detection system (PARDS) to deal with the LFC problem in the presence of cyberattacks. The efficiency of the proposed strategy is investigated under different scenarios, such as non‐linearities in the power system or server cyberattacks.
An optimizated additional damping control for suppressing ultra‐low frequency oscillation suppression based on SVC
Authors: Shi Huabo , Fan Chengwei , Zeng Xueyang , Chen Gang , Chen Baorui , Chen Zhen 
Published: July 2024

AbstractThe ultra‐low frequency oscillation (ULFO) imposes an emerging stability challenge to the high proportion of hydropower grids. To suppress ULFO without reducing the primary frequency regulation of the hydro governor, a novel idea to exploit the voltage regulation effect of load is implemented. First, the additional damping controller is designed and configured in static var compensator (SVC), and the frequency analysis model considering the configuration of SVC as well as damping controller is established. Based on the model, the specific influence of SVC and controller on ULFO is analysed through eigenvalue calculation. In addition, the influence of various load models and SVC location on the damping level are further studied. Consequently, a parameter optimization design method for SVC additional damping control is proposed, it is modelled as the optimization problem of damping ratio in ULFO mode under multi‐operation conditions, which is solved by a particle swarm optimization algorithm. Finally, the effectiveness of the designed SVC additional damping controller is verified in the improved four‐machine two‐area power system and the actual power grid in China.