bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stochasticity in host-parasitoid models informs mechanisms regulating population dynamics
Authors: Singh Abhyudai 
Published: August 2021

AbstractPopulation dynamics of host-parasitoid interactions have been traditionally studied using a discrete-time formalism starting from the classical work of Nicholson and Bailey. It is well known that differences in parasitism risk among individual hosts can stabilize the otherwise unstable equilibrium of the Nicholson-Bailey model. Here, we consider a stochastic formulation of these discrete-time models, where the host reproduction is a random variable that varies from year to year and drives fluctuations in population densities. Interestingly, our analysis reveals that there exists an optimal level of heterogeneity in parasitism risk that minimizes the extent of fluctuations in the host population density. Intuitively, low variation in parasitism risk drives large fluctuations in the host population density as the system is on the edge of stability. In contrast, high variation in parasitism risk makes the host equilibrium sensitive to the host reproduction rate, also leading to large fluctuations in the population density. Further results show that the correlation between the adult host and parasitoid densities is high for the same year, and gradually decays to zero as one considers cross-species correlations across different years. We next consider an alternative mechanism of stabilizing host-parasitoid population dynamics based on a Type III functional response, where the parasitoid attack rate accelerates with increasing host density. Intriguingly, this nonlinear functional response makes qualitatively different correlation signatures than those seen with heterogeneity in parasitism risk. In particular, a Type III functional response leads to uncorrelated adult and parasitoid densities in the same year, but high cross-species correlation across successive years. In summary, these results argue that the cross-correlation function between population densities contains signatures for uncovering mechanisms that stabilize consumer-resource population dynamics.
Modeling and prediction for diesel performance based on deep neural network combined with virtual sample
Authors: Zheng Hainan , Zhou Honggen , Kang Chao , Liu Zan , Dou Zhenhuan , Liu Jinfeng , Li Bingqiang , Chen Yu 
Published: August 2021

AbstractThe performance models are the critical step for condition monitoring and fault diagnosis of diesel engines, and are an important bridge to describe the link between input parameters and targets. Large-scale experimental methods with higher economic costs are often adopted to construct accurate performance models. To ensure the accuracy of the model and reduce the cost of the test, a novel method for modeling the performances of marine diesel engine is proposed based on deep neural network method coupled with virtual sample generation technology. Firstly, according to the practical experience, the four parameters including speed, power, lubricating oil temperature and pressure are selected as the input factors for establishing the performance models. Besides, brake specific fuel consumption, vibration and noise are adopted to assess the status of marine diesel engine. Secondly, small sample experiments for diesel engine are performed under multiple working conditions. Moreover, the experimental sample data are diffused for obtaining valid extended data based on virtual sample generation technology. Then, the performance models are established using the deep neural network method, in which the diffusion data set is adopted to reduce the cost of testing. Finally, the accuracy of the developed model is verified through experiment, and the parametric effects on performances are discussed. The results indicate that the overall prediction accuracy is more than 93%. Moreover, power is the key factor affecting brake specific fuel consumption with a weighting of 30% of the four input factors. While speed is the key factor affecting vibration and noise with a weighting of 30% and 30.5%, respectively.
External validation for sensitivity of the Ottawa subarachnoid hemorrhage rule in a Japanese tertiary teaching hospital
Authors: Suzuki Tomoharu , Itokazu David , Tokuda Yasuharu 
Published: August 2021

AbstractThe Ottawa subarachnoid hemorrhage (OSAH) rule is a validated clinical prediction rule for ruling out subarachnoid hemorrhage (SAH). Another SAH rule (Ottawa-like rule) was developed in Japan but was not well validated. We aimed to validate both rules by examining the sensitivity for ruling out SAH in Japanese patients diagnosed with SAH. We conducted a retrospective cohort study by reviewing the medical records of consecutive adult patients hospitalized with SAH at a tertiary-care teaching hospital in Japan who visited our emergency department between July 2009 and June 2019. Sensitivity and its 95% confidence interval (CI) were estimated for each rule for the diagnosis of SAH. In a total of 280 patients with SAH, 56 (20.0%) patients met the inclusion criteria and were analyzed for the OSAH rule, and a sensitivity of the OSAH rule was 56/56 (100%; 95% CI 93.6–100%). While, 126 (45%) patients met the inclusion criteria of the Ottawa-like rule, and the rule showed a sensitivity of 125/126 (99.2%; 95%CI 95.7–100%). The OSAH rule showed 100% sensitivity among our Japanese patients diagnosed with SAH. The implementation of the Ottawa-like rule should be cautious because the false-negative rate is up to 4%.
Performance optimisation of a segmented outer rotor flux switching permanent magnet motor for direct drive washing machine application
Authors: Saghin Sadegh Mollaei , Ghaheri Aghil , Shirzad Hossein , Afjei Ebrahim 
Published: August 2021

AbstractElectrical machines are widely used in home appliances, the performance of which is mostly related to the quality function of the electrical machines. What has been used so far in home appliances brought with themselves a wide assortment of advantages and disadvantages. With the aim to overcome the drawbacks of the previously implemented electrical motors in washing machines, a new configuration of flux switching permanent magnet motor (FSPM) with the segmented outer rotor (SOR‐FSPM) is proposed benefitting from a direct driven drum. To reduce the cogging torque as well as torque ripple and to improve the total harmonic distortion, cutting the stator in a way to lower overlapping between the rotor and stator pole, inserting notches into the poles of the rotor to modify the air gap between the stator teeth and the rotor segments are proposed. The Taguchi method and sensitivity analysis are further applied to find the best combination set of changes in such a way to smoothen the chart showing reluctance between stator and rotor and fix the zero‐point crossing of the flux linkages in different rotor positions. Finally, the proposed SOR‐FSPM is prototyped, and experimental results along with the finite element method results are discussed and compared in order to verify the design process.
COVID-19 Mass Vaccination Resource Calculator
Authors: Pryor Grace E. , Marble Kelsea , Velasco Ferdinand T. , Lehmann Christoph U. , Basit Mujeeb A. 
Published: August 2021

Abstract
Background Despite the recent emergency use authorization of two vaccines for the prevention of the 2019 novel coronavirus (COVID-19) disease, vaccination rates are lower than expected. Vaccination efforts may be hampered by supply, delivery, storage, patient prioritization, administration infrastructure or logistics problems. To address the last issue, our institution is sharing publically a calculator to optimize the management of staffing and facility resources in an outpatient mass vaccination effort.
Objective By sharing our calculator locally and through this paper, we aim to help health organizations administering vaccines optimize resource allocation while maximizing efficiency.
Methods Our calculator determines the maximum number of vaccinations that can be administered per hour, the number of check-in staff (clerks) needed, the number of vaccination staff (nurses) needed, and the required room capacity needed for the vaccination and the mandatory 15-minute observation period after inoculation.
Results We provide a functional version of the calculator, allowing users to replicate the calculation for their own vaccine events.
Conclusion An efficient and organized vaccination program is critical to halting the spread of COVID-19. By sharing this calculator, it is our hope that other organizations may use it to facilitate rapid and efficient vaccination.
Holistic Management of Pollinators and Pests: Integrating Semiochemicals With On-Farm Pesticides
Authors: Okosun Olabimpe O , Reddy Gadi V P 
Published: August 2021

Abstract
Insect pollinators and insect herbivores affect plant reproduction and fitness. Floral displays are used to attract and manipulate pollinators’ behavior to support plant sexual reproduction while rewarding the visitors with access to nectar and pollen. The plant–pollinator interactions use various semiochemicals as important communication channels for successful species interaction networks. Floral display and scents can also attract insect herbivores (in which case they act as kairomones). Consequently, semiochemical-color-based traps used for monitoring pest insects in crop fields often accidentally capture pollinators, and these interactions simultaneously affect pest monitoring, pollinator assemblages, and crop production in agroecosystems. An integrated interdisciplinary approach that would use inter- and intraspecific signals employed by foraging insects for predator’s avoidance with the goal of deterring pollinators and beneficial insects from entering pesticide-treated fields is proposed. Specifically, it should be possible to reduce the bycatch of pollinators by pest monitoring traps if these trap lures also include the alarm pheromones of insect pollinators such as bees. In addition, other tactics for pollinator protection could include first the application of nonlethal repellants to fields that have recently been treated with synthetic chemical pesticides to deter pollinators’ visitation. A second action would be to incorporate the results of comparative risk evaluations (pollinators vs pests) for botanical pesticides, as well as for synthetic pesticides. Finally, we urge that wild pollinator species be included in pesticide risk assessments, especially for new classes of insecticides. Collectively, these actions should integrate pest and pollinator management strategies.
ScCAEs: deep clustering of single-cell RNA-seq via convolutional autoencoder embedding and soft K-means
Authors: Hu Hang , Li Zhong , Li Xiangjie , Yu Minzhe , Pan Xiutao 
Published: August 2021

Abstract
Clustering and cell type classification are a vital step of analyzing scRNA-seq data to reveal the complexity of the tissue (e.g. the number of cell types and the transcription characteristics of the respective cell type). Recently, deep learning-based single-cell clustering algorithms become popular since they integrate the dimensionality reduction with clustering. But these methods still have unstable clustering effects for the scRNA-seq datasets with high dropouts or noise. In this study, a novel single-cell RNA-seq deep embedding clustering via convolutional autoencoder embedding and soft K-means (scCAEs) is proposed by simultaneously learning the feature representation and clustering. It integrates the deep learning with convolutional autoencoder to characterize scRNA-seq data and proposes a regularized soft K-means algorithm to cluster cell populations in a learned latent space. Next, a novel constraint is introduced to the clustering objective function to iteratively optimize the clustering results, and more importantly, it is theoretically proved that this objective function optimization ensures the convergence. Moreover, it adds the reconstruction loss to the objective function combining the dimensionality reduction with clustering to find a more suitable embedding space for clustering. The proposed method is validated on a variety of datasets, in which the number of clusters in the mentioned datasets ranges from 4 to 46, and the number of cells ranges from 90 to 30 302. The experimental results show that scCAEs is superior to other state-of-the-art methods on the mentioned datasets, and it also keeps the satisfying compatibility and robustness. In addition, for single-cell datasets with the batch effects, scCAEs can ensure the cell separation while removing batch effects.
A span-based joint model for extracting entities and relations of bacteria biotopes
Authors: Zuo Mei , Zhang Yang 
Published: August 2021

Abstract

Motivation
Information about bacteria biotopes (BB) is important for fundamental research and applications in microbiology. BB task at BioNLP-OST 2019 focuses on the extraction of locations and phenotypes of microorganisms from PubMed abstracts and full-text excerpts. The subtask BB-rel+ner aims to recognize relevant entities and extract interrelationships about BBs. The corresponding corpus owns some distinctive features (e.g. nested entities) which are challenging to deal with. Therefore, previous methods achieved low performance on entity and relation extraction and limited the mutual effect between named entity recognition and relation extraction. There is still much room for improvement.

Results
We propose a span-based model to extract entities and relations jointly from biomedical text regarding the BBs. For alleviating the problem of annotated data deficiency in domain-specific task, we employ a BERT (Bidirectional Encoder Representations from Transformers) model pre-trained on the domain-specific corpus to encode sentences. Our model considers all spans in a sentence as potential entity mentions and computes relation scores between the most confident entity spans based on representations of spans and contexts between spans. Experiments on the BB-rel+ner 2019 corpus demonstrate that our model achieves significantly better performance than the state-of-the-art method, with a reduction of 21.6% slot error rate (SER) for extracting relations. Our model is also effective in recognizing nested entities. Furthermore, the model can be applied to the CHEMPROT corpus for joint extraction of chemical–protein entities and relations, achieving state-of-the-art performance.

Availability and implementation
Our source code is available at https://github.com/zmmzGitHub/SpanMB_BERT.

Supplementary information
Supplementary data are available at Bioinformatics online.
‘She Was Just Like A Lassie’: Analysing The Views of Cis-Women In Custody About Their Experiences of Living With Transgender Women In The Scottish Prison Estate
Authors: Maycock Matthew 
Published: August 2021

Abstract
The subject of transgender rights has recently come under increasing scrutiny in many parts of the world. Despite this, there has been no research that analyses this issue from the perspective of cis-women living alongside transwomen in prison settings. This paper addresses this omission by analysing the views of fifteen cis-women in prison in Scotland, living on halls of four prisons that also housed transgender women. Findings are analysed across a range of areas incorporating the acceptance, support and solidarity as well rejection, feelings of vulnerability relating to transgender people in custody. Responses analysed highlight a diversity of views, reflective of wider societal perspectives about transgender people. This paper has relevance for prisons systems housing transgender people, and provides unique insights into the complexity of performances of gender within the contemporary prison settings.
JAK/STAT of all trades: linking inflammation with cancer development, tumor progression and therapy resistance
Authors: Sabaawy Hatem E , Ryan Bríd M , Khiabanian Hossein , Pine Sharon R 
Published: August 2021

AbstractInflammation is at the forefront of carcinogenesis, tumor progression and resistance to therapy. The Janus kinase (JAK)/signal transducer and activator of transcription (STAT) signaling axis is a central pathway that mediates the cellular response to inflammation and contributes to carcinogenesis. The JAK/STAT pathway coordinates intercellular communication between tumor cells and their immune microenvironment, and JAK/STAT activation leads to the expression of a variety of proteins involved in cell proliferation, cell survival, stemness, self-renewal, evasion of immunosurveillance mechanisms and overall tumor progression. Activation of JAK/STAT signaling also mediates resistance to radiation therapy or cytotoxic agents and modulates tumor cell responses to molecularly targeted and immune modulating drugs. Despite extensive research focused on understanding its signaling mechanisms and downstream phenotypic and functional consequences in hematological disorders, the importance of JAK/STAT signaling in solid tumor initiation and progression has been underappreciated. We highlight the role of chronic inflammation in cancer, the epidemiological evidence for contribution of JAK/STAT to carcinogenesis, the current cancer prevention measures involving JAK/STAT inhibition and the impact of JAK/STAT signaling activity on cancer development, progression and treatment resistance. We also discuss recent therapeutic advances in targeting key factors within the JAK/STAT pathway with single agents and the use of these agents in combination with other targeted therapies and immune checkpoint inhibitors.
Maine’s Bumble Bee (Hymenoptera: Apidae) Assemblage—Part 1: Composition, Seasonal and Regional Distribution, and Resource Use
Authors: Butler Ronald G , Lage Christopher , Dobrin Scott E , Staples Joseph K , Venturini Eric , Frank Jereme , Drummond Francis A 
Published: August 2021

AbstractGlobal declines of bumble bees place natural and agricultural ecosystems at risk. Given bumble bees importance to Maine’s major agricultural crops, we conducted a statewide, quantitative survey of bumble bee species seasonal and ecoregional abundance, richness, diversity, and floral resource use. We recorded 11 Bombus species at 40 survey sites across Maine’s three ecoregions, with Bombus ternarius Cresson, 1863 and Bombus impatiens Cresson, 1863 being the most common and Bombus citrinus Smith, 1854 the least commonly encountered. Bumble bee species richness did not differ as a function of ecoregion, but did decline over the season, while species diversity differed by ecoregion and also declined over the season. Multiple response permutation procedure (MRPP) indicated ecoregional differences in species composition of bumble bee assemblages and nonmetric multidimensional scaling produced a stable ordination suggesting assemblage differences were associated with survey site variables including forage plant cover, forage plant richness, elevation, development, and deciduous forest cover. Both MRPP and correspondence analysis also revealed differences in the floral resources utilized by bumble bee species in each ecoregion. Low connectance and nestedness levels indicated low stability pollinator networks in each ecoregion, suggesting Maine bumble bee assemblages may be at risk of decline in response to additional external perturbations.
A rapidly growing cardiac calcified amorphous tumour diagnosed after coronary artery bypass graft surgery: a case report
Authors: Suzue Takashi , Sawayama Yuichi , Suzuki Tomoaki , Nakagawa Yoshihisa 
Published: August 2021

Abstract

Background
A cardiac calcified amorphous tumour (CAT) is a non-neoplastic intracavitary cardiac mass. The most serious complication is systemic embolism. Cardiac CATs tend to be surgically resected immediately after detection; therefore, its progress of growth is rarely reported.

Case summary
An 83-year-old Japanese woman received on-pump beating coronary artery bypass graft surgery (CABG) for angina pectoris. Transthoracic echocardiography (TTE) performed preoperatively and 1 month postoperatively revealed the presence of mitral annular calcification, with no other abnormal findings. However, follow-up TTE performed 5 months after CABG revealed a mobile nodular mass (5.0 × 8.2 mm) in the left ventricular outflow tract. At 1 month after detection, the mass had enlarged to 5.0 × 13.0 mm. Transoesophageal echocardiography revealed that the pedunculated high-echoic mass was adhered to the posterior commissure of the mitral valve and was dynamically swinging towards the non-coronary cusp in the systolic phase. As the mass had grown rapidly in less than 6 months, it was surgically resected to prevent systemic embolism. The histological specimen consisted mainly of fibrin, including calcification and hemosiderin deposition, which lead to a diagnosis of cardiac CAT. The patient had an uneventful postoperative course during her hospital stay and had no evidence of recurrence for 1 year after discharge.

Discussion
This was a rare case in which a rapidly growing cardiac CAT was detected following on-pump CABG. Cardiac CATs may grow very rapidly and therefore early surgery should be considered after initial diagnosis.
Thrombosed sinus of Valsalva aneurysm masquer ading as a cardiac tumour: a case report
Authors: Sato Wakana , Seki Katsuhito , Yamamoto Hiroshi , Watanabe Hiroyuki 
Published: August 2021

Abstract

Background
An aortic sinus of Valsalva aneurysm (SVA) often remains undiagnosed until it ruptures. An SVA filled with thrombus can be challenging to diagnose accurately.

Case summary
A 70-year-old man was admitted with a clinical diagnosis of well-tolerated complete atrioventricular block (AVB). Transthoracic echocardiography revealed a spherical mass (43 × 49 mm) at the interatrial septum. Enhanced computed tomography (CT) showed a well-defined, hollow, and non-enhanced mass suggesting a cardiac tumour. However, 18F-fluorodeoxyglucose positron emission tomography/CT (18F-FDG PET/CT) showed no uptake in the mass. After implantation of a permanent pacemaker, anticoagulant therapy was started for paroxysmal atrial fibrillation. Two months later, follow-up evaluation by echocardiography and enhanced CT revealed an increase in size of the hollow interior cavity, suggesting thrombolysis by the anticoagulant. We diagnosed a non-coronary SVA filled with thrombus, which masqueraded as a cardiac tumour and may have caused complete AVB.

Conclusions
We describe a rare case of a giant thrombosed SVA masquerading as a cardiac tumour. Initial 18F-FDG PET/CT and serial imaging studies were helpful in distinguishing it from a cardiac tumour.
Acute coronary syndrome of the left main coronary artery caused by a huge floating thrombus in the ascending aorta: a case report of intravascular ultrasound effectiveness
Authors: Takafuji Hiroya , Nakama Tatsuya , Asano Kazuhiro , Obunai Kotaro 
Published: August 2021

Abstract

Background
Left main coronary artery (LMCA)–acute coronary syndrome (ACS) is a rare complication of a floating thrombus in the ascending aorta. However, diagnosing the aetiology of LMCA–ACS during an emergency situation is challenging. We present a rare case of LMCA–ACS caused by a large thrombus in the ascending aorta, confirmed by intravascular ultrasound (IVUS).

Case summary
A 90-year-old woman presented to the emergency department complaining of chest pain and syncope. On admission, her electrocardiogram showed normal sinus rhythm and a complete right bundle branch block with significant ST depression in the V3–V6 leads; hence, ACS was suspected. The first emergency angiogram of the left coronary artery showed filling defect in the proximal ascending aorta. IVUS revealed a large thrombus in the ascending aorta. The thrombus extended from the ascending aorta to the proximal left anterior descending coronary artery. IVUS confirmed that there was no dissection of the coronary artery or the proximal ascending aorta. Based on the IVUS findings, this case was diagnosed as ACS of the LMCA caused by a floating thrombus in the ascending aorta.

Discussion
This rare case of LMCA–ACS caused by a thrombus in the ascending aorta was confirmed by IVUS, which can be a useful imaging tool for diagnosing morphological abnormalities during emergencies.