bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microgrid Fault Identification Based on VMD-MPE
Authors: Yu Zhenkai , Wang Bin , Xu Wanwan , Yan Yong 
Published: March 2023

Abstract
Due to complex operation of microgrid and the difficulty of extracting thin fault signal features, traditional relay protection will take misoperation to protect. This article proposes a fault detection method based on VMD-MPE to take accurate fault detection. This scheme processes the current signal through the VMD algorithm that decomposes it to different modes. Considering that MPE has the advantage of exploring the dynamic mutation within the faint signal, the MPE of the most significant mode is being computed, which can be selected to extract construct the fault signal feature and observe the difference of different phase, so as to characterize different fault types. Finally, a microgrid model system is built on the PSCAD simulation experiment platform for simulation analysis and algorithm experiments. The experimental results show that the method can achieve accurate fault detection in different operating states of microgrid, regardless of fault resistance and fault points, even maintain well accuracy in complex situations such as multiple disturbances and high impedance faults.
A Noise Rate Estimation Method for Image Classification with Label Noise
Authors: Chen Ziyun , Song Aibo , Wang Yudong , Huang Xinjian , Kong Yanru 
Published: March 2023

Abstract
In a dataset, the misidentified labels can be assumed as the true labels flipped with a probability. In this paper, we study a general situation in which sample labels are corrupted at random. We propose a noise rate estimation method and prove that by adopting importance reweighting, the accuracy of classification with label noise problem can rise approximately 10% through any surrogate loss function. The two classification methods we choose for robustness analysis are convolutional neural network and convolutional neural network with importance reweighting. The details of these two methods are fully illustrated in this paper. We discuss the label noise problems and solutions in the introduction part and explain how the importance reweighting method and the noise rate estimation method are combined to deal with this problem. Experiments on Fashion-MNIST0.5, Fashion-MNIST0.6, and CIFAR with noise verify our approach. In the end, we also provide the transition matrix of the flip rate for each dataset.
Design of Freight Transport Robot Based on roboRio Controller
Authors: Zuo Wenyan , Shi Qin 
Published: March 2023

Abstract
In order to reduce the labor intensity of the porters and improve the work efficiency, a freight robot with the functions of carrying goods steadily, climbing slopes, climbing stairs, and loading and unloading objects of different sizes and shapes is designed. The robot is composed of four parts: walking mechanism, climbing mechanism, gripper mechanism and lifting mechanism. On the basis of structural design, each mechanism of the freight robot is processed and assembled, the line is built, the program is debugged, the intelligent APP is made, and the prototype is completed. Through experimental testing, good results have been achieved.
A decentralized approach to model national and global food and land use systems
Authors: Mosnier Aline , Javalera-Rincon Valeria , Jones Sarah K , Andrew Robbie , Bai Zhaohai , Baker Justin , Basnet Shyam , Boer Rizaldi , Chavarro John , Costa Wanderson , Daloz Anne Sophie , DeClerck Fabrice A , Diaz Maria , Douzal Clara , Howe Fan Andrew Chiah , Fetzer Ingo , Frank Federico , Gonzalez-Abraham Charlotte E , Habiburrachman A H F , Immanuel Gito , Harrison Paula A , Imanirareba Dative , Jha Chandan , Jin Xinpeng , Ghosh Ranjan Kumar , Leach Nicholas , Lehtonen Heikki , Lotze-Campen Hermann , Low Wai Sern , Marcos-Martinez Raymundo , McCord Gordon Carlos , Molla Kiflu Gedefe , Monjeau Adrian , Navarro-Garcia Javier , Neubauer Rudolf , Obersteiner Michael , Olguín Marcela , Orduña-Cabrera Fernando , Pena Andres , Pérez-Guzmán Katya , Potashnikov Vladimir , Rämö Janne , Ramos Fernando M , Rasche Livia , Gallardo René Reyes , Schmidt-Traub Guido , Selomane Odirilwe , Singh Vartika , Smith Alison , Soterroni Aline C , Sperling Frank , Steinhauser Jan , Stevanovic Miodrag , Strokov Anton , Thomson Marcus , van Oort Bob , Vittis Yiorgos , Wade Chris , Winarni Nurul L , Woldeyes Firew Bekele , Wu Grace C , Zerriffi Hisham 
Published: March 2023

Abstract
The achievement of several sustainable development goals and the Paris Climate Agreement depends on rapid progress towards sustainable food and land systems in all countries. We have built a flexible, collaborative modeling framework to foster the development of national pathways by local research teams and their integration up to global scale. Local researchers independently customize national models to explore mid-century pathways of the food and land use system transformation in collaboration with stakeholders. An online platform connects the national models, iteratively balances global exports and imports, and aggregates results to the global level. Our results show that actions toward greater sustainability in countries could sum up to 1 Mha net forest gain per year, 950 Mha net gain in the land where natural processes predominate, and an increased CO2 sink of 3.7 GtCO2e yr−1 over the period 2020–2050 compared to current trends, while average food consumption per capita remains above the adequate food requirements in all countries. We show examples of how the global linkage impacts national results and how different assumptions in national pathways impact global results. This modeling setup acknowledges the broad heterogeneity of socio-ecological contexts and the fact that people who live in these different contexts should be empowered to design the future they want. But it also demonstrates to local decision-makers the interconnectedness of our food and land use system and the urgent need for more collaboration to converge local and global priorities.
The evolution of UK sea-level projections
Authors: Weeks Jennifer H , Fung Fai , Harrison Benjamin J , Palmer Matthew D 
Published: March 2023

Abstract
The methods used to generate process-based global and local mean sea-level projections have evolved substantially over the last fifteen years, including improved process understanding, advances in ice-sheet modelling, the use of emulators and further development of high-end scenarios. During this time, two sets of UK national sea-level projections have been generated as part of the UK Climate Projections in 2009 (UKCP09; Lowe et al 2009) and in 2018 (UKCP18; Palmer et al 2018b). UKCP18 presented local mean sea-level projections for the UK coastline for the 21st century rooted in Coupled Model Intercomparison Project Phase 5 (CMIP5) models and in methods used in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), with an emulator-based methodology to provide extended projections to 2300 (Palmer et al 2018a; 2020). We compare UKCP18 global and local mean sea-level projections with those presented in the IPCC Sixth Assessment Report (AR6, IPCC 2021a). We find the likely range projections (characterising the central two-thirds of the distribution) are broadly similar at 2150 to within 0.1 m, except at Edinburgh, where the maximum difference is 0.22 m under medium emissions. Differences arise due to higher contributions from sterodynamic processes and the Antarctic ice sheet, and higher or lower vertical land movement, in AR6 compared to UKCP18. We also compare high-end sea-level rise estimates, presented in AR6 and UKCP09, finding reasonable global and UK local agreement over the 21st century. We explore future paths for UK sea-level science considering both user needs for information and developments in modelling capability. Future UK sea-level projections would benefit from updated high-end sea-level rise scenarios which extend beyond 2100 and continued efforts to build understanding of observed sea-level change drivers. Alongside close collaboration with user groups this would enhance the utility of local sea-level projections by UK coastal practitioners and decision-makers.
Improvements in Hypertension Control in the Rural Longitudinal HAALSI Cohort of South African Adults Aged 40 and Older, From 2014 to 2019
Authors: Abrahams-Gessel Shafika , Gómez-Olivé F Xavier , Tollman Stephen , Wade Alisha N , Du Toit Jacques D , Ferro Enrico G , Kabudula Chodziwadziwa W , Gaziano Thomas A 
Published: March 2023

Abstract

Background
Over half of the South African adults aged 45 years and older have hypertension but its effective management along the treatment cascade (awareness, treatment, and control) remains poorly understood.

Methods
We compared the prevalence of all stages of the hypertension treatment cascade in the rural HAALSI cohort of older adults at baseline and after four years of follow-up using household surveys and blood pressure data. Hypertension was a mean systolic blood pressure &gt;140 mm Hg or diastolic pressure &gt;90 mm Hg, or current use of anti-hypertension medication. Control was a mean blood pressure &lt;140/90 mm Hg. The effects of sex and age on the treatment cascade at follow-up were assessed. Multivariate Poisson regression models were used to estimate prevalence ratios along the treatment cascade at follow-up.

Results
Prevalence along the treatment cascade increased from baseline (B) to follow-up (F): awareness (64.4% vs. 83.6%), treatment (49.7% vs. 73.9%), and control (22.8% vs. 41.3%). At both time points, women had higher levels of awareness (B: 70.5% vs. 56.3%; F: 88.1% vs. 76.7%), treatment (B: 55.9% vs. 41.55; F: 79.9% vs. 64.7%), and control (B: 26.5% vs. 17.9%; F: 44.8% vs. 35.7%). Prevalence along the cascade increased linearly with age for everyone. Predictors of awareness included being female, elderly, or visiting a primary health clinic three times in the previous 3 months, and the latter two also predicted hypertension control.

Conclusions
There were significant improvements in awareness, treatment, and control of hypertension from baseline to follow-up and women fared better at all stages, at both time points.
Coercion promotes alloparental care in cooperative breeders
Authors: Zöttl Markus , Schreier Tanja , Taborsky Michael 
Published: March 2023

Abstract
Members of social groups may negotiate among each other about the exchange of goods and services. If this involves asymmetries between interacting partners, for instance in condition, power, or expected payoffs, coercion may be involved in the bargain. Cooperative breeders are excellent models to study such interactions, because asymmetries are inherent in the relationship between dominant breeders and subordinate helpers. Currently it is unclear whether punishment is used to enforce costly cooperation in such systems. Here we investigated experimentally in the cooperatively breeding cichlid Neolamprologus pulcher whether alloparental brood care provided by subordinates is contingent on enforcement by dominant breeders. We manipulated first the brood care behavior of a subordinate group member and then the possibility of the dominant breeders to punish idle helpers. When subordinates were prevented from providing brood care, breeders increased their attacks on them, which triggered increased alloparental brood care by helpers as soon as this was again possible. In contrast, when the possibility to punish helpers was prevented, energetically costly alloparental brood care did not increase. Our results confirm predictions of the pay-to-stay mechanism causing alloparental care in this species and they suggest more generally that coercion can play an important role in the control of cooperation.
Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
Authors: Wertenbroek Rick , Xenarios Ioannis , Thoma Yann , Delaneau Olivier 
Published: March 2023

AbstractSummaryThe positional Burrows–Wheeler transform (PBWT) data structure allows for efficient haplotype data matching and compression. Its performance makes it a powerful tool for bioinformatics. However, existing algorithms do not exploit parallelism due to inner dependencies. We introduce a new method to break the dependencies and show how to fully exploit modern multi-core processors.Availability and implementationSource code and applications are available at https://github.com/rwk-unil/parallel_pbwt.Supplementary informationSupplementary data are available at Bioinformatics Advances online.
GEOfetch: a command-line tool for downloading data and standardized metadata from GEO and SRA
Authors: Khoroshevskyi Oleksandr , LeRoy Nathan , Reuter Vincent P , Sheffield Nathan C 
Published: March 2023

AbstractMotivationThe Gene Expression Omnibus has become an important source of biological data for secondary analysis. However, there is no simple, programmatic way to download data and metadata from Gene Expression Omnibus (GEO) in a standardized annotation format.ResultsTo address this, we present GEOfetch—a command-line tool that downloads and organizes data and metadata from GEO and SRA. GEOfetch formats the downloaded metadata as a Portable Encapsulated Project, providing universal format for the reanalysis of public data.Availability and implementationGEOfetch is available on Bioconda and the Python Package Index (PyPI).
kb_DRAM: annotation and metabolic profiling of genomes with DRAM in KBase
Authors: Shaffer Michael , Borton Mikayla A , Bolduc Ben , Faria José P , Flynn Rory M , Ghadermazi Parsa , Edirisinghe Janaka N , Wood-Charlson Elisha M , Miller Christopher S , Chan Siu Hung Joshua , Sullivan Matthew B , Henry Christopher S , Wrighton Kelly C 
Published: March 2023

Abstract

Microbial genome annotation is the process of identifying structural and functional elements in DNA sequences and subsequently attaching biological information to those elements. DRAM is a tool developed to annotate bacterial, archaeal, and viral genomes derived from pure cultures or metagenomes. DRAM goes beyond traditional annotation tools by distilling multiple gene annotations to genome level summaries of functional potential. Despite these benefits, a downside of DRAM is the requirement of large computational resources, which limits its accessibility. Further, it did not integrate with downstream metabolic modeling tools that require genome annotation. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated with the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point-and-click interface, as well as generate genome-scale metabolic models from DRAM annotations.

Availability and implementation
For kb_DRAM users, the kb_DRAM apps on KBase can be found in the catalog at https://narrative.kbase.us/#catalog/modules/kb_DRAM. For kb_DRAM users, a tutorial workflow with all documentation is available at https://narrative.kbase.us/narrative/129480. For kb_DRAM developers, software is available at https://github.com/shafferm/kb_DRAM.
Interpretable meta-learning of multi-omics data for survival analysis and pathway enrichment
Authors: Cho Hyun Jae , Shu Mia , Bekiranov Stefan , Zang Chongzhi , Zhang Aidong 
Published: March 2023

AbstractMotivationDespite the success of recent machine learning algorithms’ applications to survival analysis, their black-box nature hinders interpretability, which is arguably the most important aspect. Similarly, multi-omics data integration for survival analysis is often constrained by the underlying relationships and correlations that are rarely well understood. The goal of this work is to alleviate the interpretability problem in machine learning approaches for survival analysis and also demonstrate how multi-omics data integration improves survival analysis and pathway enrichment. We use meta-learning, a machine-learning algorithm that is trained on a variety of related datasets and allows quick adaptations to new tasks, to perform survival analysis and pathway enrichment on pan-cancer datasets. In recent machine learning research, meta-learning has been effectively used for knowledge transfer among multiple related datasets.ResultsWe use meta-learning with Cox hazard loss to show that the integration of TCGA pan-cancer data increases the performance of survival analysis. We also apply advanced model interpretability method called DeepLIFT (Deep Learning Important FeaTures) to show different sets of enriched pathways for multi-omics and transcriptomics data. Our results show that multi-omics cancer survival analysis enhances performance compared with using transcriptomics or clinical data alone. Additionally, we show a correlation between variable importance assignment from DeepLIFT and gene coenrichment, suggesting that genes with higher and similar contribution scores are more likely to be enriched together in the same enrichment sets.Availability and implementationhttps://github.com/berkuva/TCGA-omics-integration.
Targeting tumor heterogeneity: multiplex-detection-based multiple instance learning for whole slide image classification
Authors: Wang Zhikang , Bi Yue , Pan Tong , Wang Xiaoyu , Bain Chris , Bassed Richard , Imoto Seiya , Yao Jianhua , Daly Roger J , Song Jiangning 
Published: March 2023

AbstractMotivationMultiple instance learning (MIL) is a powerful technique to classify whole slide images (WSIs) for diagnostic pathology. The key challenge of MIL on WSI classification is to discover the critical instances that trigger the bag label. However, tumor heterogeneity significantly hinders the algorithm’s performance.ResultsHere, we propose a novel multiplex-detection-based multiple instance learning (MDMIL) which targets tumor heterogeneity by multiplex detection strategy and feature constraints among samples. Specifically, the internal query generated after the probability distribution analysis and the variational query optimized throughout the training process are utilized to detect potential instances in the form of internal and external assistance, respectively. The multiplex detection strategy significantly improves the instance-mining capacity of the deep neural network. Meanwhile, a memory-based contrastive loss is proposed to reach consistency on various phenotypes in the feature space. The novel network and loss function jointly achieve high robustness towards tumor heterogeneity. We conduct experiments on three computational pathology datasets, e.g. CAMELYON16, TCGA-NSCLC, and TCGA-RCC. Benchmarking experiments on the three datasets illustrate that our proposed MDMIL approach achieves superior performance over several existing state-of-the-art methods.Availability and implementationMDMIL is available for academic purposes at https://github.com/ZacharyWang-007/MDMIL.
More than a Bit of Fun: The Multiple Outcomes of a Bioblitz
Authors: Meeus Sofie , Silva-Rocha Iolanda , Adriaens Tim , Brown Peter M J , Chartosia Niki , Claramunt-López Bernat , Martinou Angeliki F , Pocock Michael J O , Preda Cristina , Roy Helen E , Tricarico Elena , Groom Quentin J 
Published: March 2023

AbstractBioblitzes are a popular approach to engage people and collect biodiversity data. Despite this, few studies have actually evaluated the multiple outcomes of bioblitz activities. We used a systematic review, an analysis of data from more than 1000 bioblitzes, and a detailed analysis of one specific bioblitz to inform our inquiry. We evaluated five possible bioblitz outcomes, which were creating a species inventory, engaging people in biological recording, enhancing learning about nature, discovering a species new to an area, and promoting an organization. We conclude that bioblitzes are diverse but overall effective at their aims and have advantages over unstructured biodiversity recording. We demonstrate for the first time that bioblitzes increase the recording activity of the participants for several months after the event. In addition, we provide evidence that bioblitzes are effective at bringing people and organizations together to build communities of professionals and amateurs, critical for conserving and protecting biodiversity.
Systematic evaluation of high-level visual deficits and lesions in posterior cerebral artery stroke
Authors: Robotham Ro Julia , Rice Grace E , Leff Alex P , Lambon Ralph Matthew A , Starrfelt Randi 
Published: March 2023

AbstractKnowledge about the consequences of stroke on high-level vision comes primarily from single case studies of patients selected based on their behavioural profiles, typically patients with specific stroke syndromes like pure alexia or prosopagnosia. There are, however, no systematic, detailed, large-scale evaluations of the more typical clinical behavioural and lesion profiles of impairments in high-level vision after posterior cerebral artery stroke. We present behavioural and lesion data from the Back of the Brain project, to date the largest (N = 64) and most detailed examination of patients with cortical posterior cerebral artery strokes selected based on lesion location. The aim of the current study was to relate behavioural performance with faces, objects and written words to lesion data through two complementary analyses: (i) a multivariate multiple regression analysis to establish the relationships between lesion volume, lesion laterality and the presence of a bilateral lesion with performance and (ii) a voxel-based correlational methodology analysis to establish whether there are distinct or separate regions within the posterior cerebral artery territory that underpin the visual processing of words, faces and objects. Behaviourally, most patients showed more general deficits in high-level vision (n = 22) or no deficits at all (n = 21). Category-selective deficits were rare (n = 6) and were only found for words. Overall, total lesion volume was most strongly related to performance across all three domains. While behavioural impairments in all domains were observed following unilateral left and right as well as bilateral lesions, the regions most strongly related to performance mainly confirmed the pattern reported in more selective cases. For words, these included a left hemisphere cluster extending from the occipital pole along the fusiform and lingual gyri; for objects, bilateral clusters which overlapped with the word cluster in the left occipital lobe. Face performance mainly correlated with a right hemisphere cluster within the white matter, partly overlapping with the object cluster. While the findings provide partial support for the relative laterality of posterior brain regions supporting reading and face processing, the results also suggest that both hemispheres are involved in the visual processing of faces, words and objects.