bluuebunny/crossref_metadata_2025_split huggingface dataset:
SpiderLearner: An ensemble approach to Gaussian graphical model estimation
Authors: Shutta Katherine H. , Balzer Laura B. , Scholtens Denise M. , Balasubramanian Raji 
Published: April 2023

AbstractGaussian graphical models (GGMs) are a popular form of network model in which nodes represent features in multivariate normal data and edges reflect conditional dependencies between these features. GGM estimation is an active area of research. Currently available tools for GGM estimation require investigators to make several choices regarding algorithms, scoring criteria, and tuning parameters. An estimated GGM may be highly sensitive to these choices, and the accuracy of each method can vary based on structural characteristics of the network such as topology, degree distribution, and density. Because these characteristics area prioriunknown, it is not straightforward to establish universal guidelines for choosing a GGM estimation method. We address this problem by introducing SpiderLearner, an ensemble method that constructs a consensus network from multiple estimated GGMs. Given a set of candidate methods, SpiderLearner estimates the optimal convex combination of results from each method using a likelihood‐based loss function. ‐fold cross‐validation is applied in this process, reducing the risk of overfitting. In simulations, SpiderLearner performs better than or comparably to the best candidate methods according to a variety of metrics, including relative Frobenius norm and out‐of‐sample likelihood. We apply SpiderLearner to publicly available ovarian cancer gene expression data including 2013 participants from 13 diverse studies, demonstrating our tool's potential to identify biomarkers of complex disease. SpiderLearner is implemented as flexible, extensible, open‐source code in the R packageensembleGGMathttps://github.com/katehoffshutta/ensembleGGM.
Cross‐version defect prediction using threshold‐based active learning
Authors: Mei Yuanqing , Liu Xutong , Lu Zeyu , Yang Yibiao , Liu Huihui , Zhou Yuming 
Published: April 2023

AbstractBecause defects in software modules (e.g., classes) might lead to product failure and financial loss, software defect prediction enables us to better understand and control software quality. Software development is a dynamic evolutionary process that may result in data distributions (e.g., defect characteristics) varying from version to version. In this case, effective cross‐version defect prediction (CVDP) is not easy to achieve. In this paper, we aim to investigate whether the defect prediction method of the threshold‐based active learning (TAL) can tackle the problem of the different data distribution between successive versions. Our TAL method includes two stages. At the active learning stage, a committee of investigated metrics is constructed to vote on the unlabeled modules of the current version. We pick up the unlabeled module with the median of voting scores to domain experts. The domain experts test and label the selected unlabeled module. Then, we merge the selected labeled module and the remaining modules with pseudo‐labels from the current version into the labeled modules of the prior version to form enhanced training data. Based on the training data, we derive the metric thresholds used for the next iteration. At the defect prediction stage, the iterations stop when a predefined threshold is reached. Finally, we use the cutoff threshold of voting scores, that is, 50%, to predict the defect‐prone of the remaining unlabeled modules. We evaluate the TAL method on 31 versions of 10 projects with three prevalent performance indicators. The results show that TAL outperforms the baseline methods, including three variations methods, two common supervised methods, and the state‐of‐the‐art method Hybrid Active Learning and Kernel PCA (HALKP). The results indicate that TAL can effectively address the different data distribution between successive versions. Furthermore, to keep the cost of extensive testing low in practice, selecting 5% of candidate modules from the current version is sufficient for TAL to achieve a good performance of defect prediction.
Transillumination facilitates coccygeal arterial cannulation in anaesthetised small‐breed dogs
Authors: Kim Hyunseok , Park Kyoungsoo , Lee Junhyup , Shin Donghwi , Son Won‐Gyun , Lee Inhyung 
Published: April 2023

AbstractBackgroundArterial access in small‐breed dogs is challenging, but arterial visualisation may facilitate the procedure, as evidenced in human medicine. This prospective, randomised study investigated the result of using transillumination to guide coccygeal artery cannulation in small‐breed dogs.MethodsCoccygeal artery cannulation was attempted in dogs anaesthetised with butorphanol, midazolam, propofol and sevoflurane. In 70 dogs (standard technique group [STECHNIQUE group]), arterial cannulation was performed using pulse palpation. In 71 dogs (transilluminating‐standard technique group [TSTECHNIQUE group]), a transilluminating device was utilised. The device was placed on the dorsal tail, and the cannula was advanced towards the dark line visible against the bright background. If the artery was not well visualised due to pigmentation, pulse palpation was used. The success rate of arterial cannulation was compared between the groups using the chi‐squared test.ResultsArterial cannulation was significantly more successful (p < 0.001) in the TSTECHNIQUE group (63/71 [88.7%]) than in the STECHNIQUE group (43/70 [61.4%]).LimitationsThe number of punctures attempted and the time to cannulation were not assessed, and the procedure was only performed by veterinarians experienced in arterial cannulation.ConclusionsThe transillumination allows for a more accurate approach to the coccygeal artery, improving the success of arterial cannulation when combined with pulse palpation.
Unanticipated hyperkalaemia and associated perioperative complications in three captive grey wolves (Canis lupus) undergoing general anaesthesia
Authors: Mattaliano Giorgio , Heberlein Marianne , Cruz Benedetti Inga‐Catalina 
Published: April 2023

AbstractIntraoperative hyperkalaemia has been described in dogs, cats, non‐domestic felids and in a calf. This case series reports the occurrence and associated complications in three captive‐held grey wolves anaesthetised for root canal treatment. Severe bradyarrhythmia associated with hypotension was detected in two cases before hyperkalaemia was confirmed. These also presented with signs compatible with malignant hyperthermia and rhabdomyolysis. In the third wolf, regular arterial blood gas analysis revealed a progressive increase in plasma potassium exceeding reference values 240 min after premedication. Hyperkalaemia was treated symptomatically with standard protocols, and the recovery was uneventful in all three wolves. The cause of hyperkalaemia in the described cases remains unknown and is most likely multifactorial. Prolonged recumbency, long anaesthetic duration and the administration of α2‐adrenoceptor agonists are potential influencing factors. Additionally, malignant hyperthermia, rhabdomyolysis, acidaemia and drug effects are discussed for their potential of causing the described intraoperative hyperkalaemia.
Autologous blood patch pleurodesis for management of persistent pneumothorax in a dog with metastatic osteosarcoma
Authors: Moses Amber A. , Robinson Christopher J. , Rincon Angie A. , Wurlod Virginie A. , Withers Sita S. 
Published: April 2023

AbstractA 10‐year‐old, neutered, male Pitbull was presented to the oncology service with dyspnoea, approximately 16 months after treatment with amputation and chemotherapy for appendicular osteosarcoma, and 4 months after development of diffuse pulmonary metastatic disease. Thoracic radiographs diagnosed bilateral pneumothorax, presumed secondary to metastatic osteosarcoma. The pneumothorax was refractory to conservative management, and two autologous blood patch pleurodesis procedures were performed 48 hours apart, according to a previously published protocol. Marked radiographic improvement was evident within 24 hours of the autologous blood patch pleurodesis procedures, and the dog was discharged 6 days after initial presentation. Approximately 13 weeks later, the dog was humanely euthanased due to progressive clinical signs. This report describes the development of spontaneous persistent pneumothorax secondary to osteosarcoma metastatic disease in a dog, and its palliation with autologous blood patch pleurodesis. This case demonstrates that autologous blood patch pleurodesis can be considered as a treatment option for pneumothorax secondary to metastatic disease in dogs.
A retrospective study on the immobilisation of captive chimpanzees (Pan troglodytes) at UWEC, Uganda
Authors: Watuwa James , Mbabazi Racheal , Sente Celsus , Musinguzi James , Laubscher Liesel 
Published: April 2023

AbstractThe study used the records of 188 chimpanzees that were immobilised with medetomidine and ketamine for annual health checks from 1998 to 2020. The initial dose for each animal was estimated as 5 mg/kg ketamine plus 0.05 mg/kg medetomidine administered intramuscularly. When necessary, additional intramuscular top‐ups of 5 mg/kg ketamine plus 0.05 mg/kg medetomidine were given. Monitoring started from the moment the animals were on the examination table until they were placed back in their enclosure. All animals were positioned in dorsal recumbency. Physiologic parameters including heart rate (beats per minute), respiration rate (breaths per minute), peripheral oxygen saturation (SpO2, %) and rectal temperature (°C) were measured. Atipamezole was administered at five times the dose of medetomidine. Time to first sign of sedation, time to recumbency, time from darting to reversal, time to first sign of recovery, time to head up and sternal, and time to standing were also measured.
Machine learning for design and optimization of organic Rankine cycle plants: A review of current status and future perspectives
Authors: Oyekale Joseph , Oreko Benjamin 
Published: April 2023

AbstractThe organic Rankine cycle (ORC) is widely acknowledged as a sustainable power cycle. However, the traditional approach commonly adopted for its optimal design involves sequential consideration of working fluid selection, plant configuration, and component types, before the optimization of state parameters. This way, the design process fails to achieve an optimal design in most cases, since the process relies heavily on empirical judgments. To improve the design process, researchers have been exploring lately the suitability of machine learning techniques. It is however not clear yet if data‐driven designs of ORC plants are practically viable and accurate. To bridge this gap, this article reviews literature studies in the field. Overviews were first presented on the ORC technology and machine learning modeling approaches. Next, studies that applied machine‐learning methods for the design and performance prediction of ORC plants were discussed. Furthermore, studies that focused on ORC machine learning optimizations were discussed. The artificial neural network (ANN) approach was observed as the technique most frequently applied for ORC design and optimization. Additionally, researchers agree in general that machine‐learning methods can achieve accurate results, with significant reductions of computational time and cost. However, there is the risk of using inadequate data size in the machine learning design approach, or insufficient data set training time, all of which can affect accuracy. It is hoped that this effort would spur the practical implementation of machine learning techniques in the future design and optimization of ORC plants, toward the achievement of more sustainable energy technology.This article is categorized under:
Sustainable Energy > Energy Efficiency
Sustainable Energy > Other Renewables
Biomonitoring of heavy metals using Contracaecum quadripapillatum (Nematoda) in comparison to its fish host, Lates niloticus, from the Nile River, Egypt
Authors: Thabit Hasnaa 
Published: April 2023

AbstractRecently, fish parasites have been used as a biomonitoring tool to indicate the health status of ecosystems. Therefore, this research aimed to evaluate the potential capacity of Contracaecum quadripapillatum larvae as accumulation indicators for metal pollution and compare metal concentrations in host tissues of non-infected and infected fish: Lates niloticus from the Nile River. Accumulations of Cd, Cu, Fe, Mn, Ni, Pb, and Zn in larval nematodes and tissues of the liver, kidney, and muscles of both infected and non-infected fish were determined. All metal concentrations exhibit a significantly higher increase in larval nematodes than the muscles of infected fish and vice versa except Cd in the kidney. On the other hand, only Cd, Mn, Pb, and Zn concentrations were significantly higher in the parasite than in the host liver. Therefore, bioaccumulation factors were most obvious and effective in the muscles of infected fish than in the liver and kidney. Contracaecum larvae accumulate Cd and Pb more than other metals. The infrapopulation size of C. quadripapillatum correlated with metal concentrations in different host tissues, especially the kidney, while the correlations between metal levels in the tissues of both parasite and fish organs exhibit different patterns in each organ. The current work revealed that C. quadripapillatum larvae represent environmental monitors for metal pollution in the freshwater ecosystem.
Structural, Optical and Antibacterial Activity Studies on CMC/PVA Blend Filled with Three Different Types of Green Synthesized ZnO Nanoparticles
Authors: Yassin A. Y. , Abdelghany A. M. , Salama Reda S. , Tarabiah A. E. 
Published: April 2023

AbstractIn this work, zinc oxide (ZnO) was produced using extracts of Thymus (Z), Hibiscus rosa-sinensis (K), and Daucus carota (G). Furthermore, sodium carboxymethyl cellulose (CMC) and polyvinyl alcohol (PVA) were combined with ZnO to form three novel nanocomposites. X-ray diffraction (XRD) was used for the structural analysis, where the semicrystalline nature of the (CMC/PVA)/ZnO nanocomposites was confirmed. The characteristics functional groups that arose inside the prepared samples were identified by Fourier transform infrared spectroscopy (FTIR). Evidence for the successful preparation of the pure ZnO particles and their nanocomposites was carried out using a transmission electron microscope (TEM). The ZnO nanoparticles are mostly spherical, irregularly distributed, and have radii ranging from 10 to 40 nm. Their anti-bacterial activity was studied against B. subtilis, E. coli, and Candida albicans. The inhibition zones of all the prepared samples against E. coli were 0, 19, 31, and 23 mm for PVA/CMC blend, PVA/CMC/ZnO (Z) (PCZ-Z), PVA/CMC/ZnO (K) (PCZ-K), and PVA/CMC/ZnO (G) (PCZ-G), respectively, compared to the streptomycin control Gram-positive standard with inhibition zone (34 mm). On the other hand, the inhibition zones of the prepared samples against B. subtilis were equal to 0, 26, 33, and 28 mm for CMC/PVA, PCZ-Z, PCZ-K, and PCZ-G, respectively. Based on these results, the PCZ-K sample is the most effective at resisting E. coli (91.17%) and B. subtilis (94.28%). These nanocomposites do not have harmful chemicals, making them strong candidates for use in biological applications.
The Relationship Between African Easterly Waves and Tropical Cyclones in Historical and Future Climates in the HighResMIP‐PRIMAVERA Simulations
Authors: Bercos‐Hickey Emily , Patricola Christina M. , Loring Burlen , Collins William D. 
Published: April 2023

AbstractThe deadly and destructive nature of tropical cyclones (TCs) makes understanding their response to future climate change of the utmost importance. TC genesis hinges on multiple factors, including an initial disturbance. African easterly waves (AEWs) have been shown to serve as such disturbances for TCs developing in the North Atlantic. It is therefore crucial to understand the relationship between AEWs and TCs and how this relationship may be affected by climate change. In this study, we examine the AEW‐TC relationship in historical and future climates using three models from the HighResMIP PRIMAVERA simulations. The AEWs and TCs were tracked in the model data using objective tracking algorithms, and AEW and TC tracks were then matched together if they were close to each other in space and time. The strength of the AEWs was measured using the eddy kinetic energy and the curvature vorticity of the waves. TC strength and intensity were measured using potential intensity and lifetime maximum 10 m windspeed. We found that future changes in the frequency of AEWs are not a good indicator of future TC activity. However, AEW strength, as well as environmental conditions conducive to strong TCs, are good indicators of AEWs that develop into TCs in both historical and future climates.
Dissimilarity of Turbulent Transport of Momentum and Heat Under Unstable Conditions Linked to Convective Circulations
Authors: Zhang Lu , Zhang Hongsheng , Zhang Xiaoye , Li Qianhui , Wu Bingui , Cai Xuhui , Song Yu , Zhu Tong 
Published: April 2023

AbstractThe dissimilarity between the turbulent transport of momentum and heat under unstable conditions and its physical mechanisms are investigated in this study, based on the multiple‐level turbulence observation from the Tianjin 255‐m meteorological tower. The transport dissimilarity is observed from the surface layer to the lower part of mixed layer as atmospheric instability increases. Although the transport dissimilarity is accompanied by the development of plumes and thermals under unstable conditions, plumes and thermals can produce intense transport both of momentum and heat simultaneously. It is convective circulations induced by vigorous thermals that cause transport dissimilarity. The horizontal divergence generated by convective circulations imposes a dominant large‐scale reduction in the along‐wind velocity component near the surface, which is related to increased counter gradient transport of momentum, while the temporal variations in temperature mainly reflect the role of plumes and thermals and thus the transport of heat is predominantly down‐gradient. This difference in respective physical processes subsequently leads to dissimilar transport between momentum and heat under unstable conditions. Therefore, it is of great interest to represent the influence of convective circulations on the momentum‐flux estimation in future investigations, aiming to improve the boundary‐layer parameterization schemes for mesoscale numerical weather models.
Acceptance and willingness-to-pay for oocyte cryopreservation in medical versus age-related fertility preservation scenarios among Swedish female university students
Authors: Gambadauro Pietro , Bränn Emma , Hadlaczky Gergö 
Published: April 2023

AbstractOocytes can be effectively cryopreserved and stored for future use in in-vitro fertilisation. Oocyte cryopreservation (OC) can therefore mitigate different threats to female fertility, but attitudes and policies often seem more favourable in medical rather than age-related fertility preservation scenarios. The value of OC for potential candidates may be perceived differently depending on the indications, although relevant empirical data are lacking. An adequately powered sample of Swedish female university students (n = 270; median age 25; range 19–35) were randomly delivered a medical (n = 130) or age-related (n = 140) fertility preservation scenario within an online survey. Sociodemographic factors, reproductive experiences, and awareness about OC were not significantly different between the groups. Differences in four outcomes were studied: proportions of respondents (1) positive to the use of OC, (2) positive to public funding for OC, or (3) open to considering OC; and (4) willingness-to-pay (WTP) for OC, measured in thousand Swedish krona (K SEK) through contingent valuation. There were no significant differences in the proportions of respondents positive to the use of OC (medical: 96%; age-related: 93%) or open to consider it (medical: 90%; age-related: 88%) in each scenario. However, public funding had significantly greater support in the medical scenario (85%) than in the age-related one (64%). The median WTP (45 K SEK ≈ 4.15 K EUR) approximated the current Swedish market price for a single elective cycle and was not significantly different between the scenarios (Cliff’s delta − 0.009; 95%CI − 0.146, 0.128). These findings suggest that it may be inappropriate to justify counselling and priority policies only on the assumption that fertility preservation with OC for medical indications is more beneficial to women than when the same technique is used for age-related reasons. However, it would be interesting to investigate further why public funding appears more debatable than the treatment itself.
mlf-core: a framework for deterministic machine learning
Authors: Heumos Lukas , Ehmele Philipp , Kuhn Cuellar Luis , Menden Kevin , Miller Edmund , Lemke Steffen , Gabernet Gisela , Nahnsen Sven 
Published: April 2023

AbstractMotivationMachine learning has shown extensive growth in recent years and is now routinely applied to sensitive areas. To allow appropriate verification of predictive models before deployment, models must be deterministic. Solely fixing all random seeds is not sufficient for deterministic machine learning, as major machine learning libraries default to the usage of nondeterministic algorithms based on atomic operations.ResultsVarious machine learning libraries released deterministic counterparts to the nondeterministic algorithms. We evaluated the effect of these algorithms on determinism and runtime. Based on these results, we formulated a set of requirements for deterministic machine learning and developed a new software solution, the mlf-core ecosystem, which aids machine learning projects to meet and keep these requirements. We applied mlf-core to develop deterministic models in various biomedical fields including a single-cell autoencoder with TensorFlow, a PyTorch-based U-Net model for liver-tumor segmentation in computed tomography scans, and a liver cancer classifier based on gene expression profiles with XGBoost.Availability and implementationThe complete data together with the implementations of the mlf-core ecosystem and use case models are available at https://github.com/mlf-core.
STGRNS: an interpretable transformer-based method for inferring gene regulatory networks from single-cell transcriptomic data
Authors: Xu Jing , Zhang Aidi , Liu Fang , Zhang Xiujun 
Published: April 2023

AbstractMotivationSingle-cell RNA-sequencing (scRNA-seq) technologies provide an opportunity to infer cell-specific gene regulatory networks (GRNs), which is an important challenge in systems biology. Although numerous methods have been developed for inferring GRNs from scRNA-seq data, it is still a challenge to deal with cellular heterogeneity.ResultsTo address this challenge, we developed an interpretable transformer-based method namely STGRNS for inferring GRNs from scRNA-seq data. In this algorithm, gene expression motif technique was proposed to convert gene pairs into contiguous sub-vectors, which can be used as input for the transformer encoder. By avoiding missing phase-specific regulations in a network, gene expression motif can improve the accuracy of GRN inference for different types of scRNA-seq data. To assess the performance of STGRNS, we implemented the comparative experiments with some popular methods on extensive benchmark datasets including 21 static and 27 time-series scRNA-seq dataset. All the results show that STGRNS is superior to other comparative methods. In addition, STGRNS was also proved to be more interpretable than “black box” deep learning methods, which are well-known for the difficulty to explain the predictions clearly.Availability and implementationThe source code and data are available at https://github.com/zhanglab-wbgcas/STGRNS.