bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wi-Fi indoor 3D localization algorithm based on multi-classifier fusion
Authors: Wu Caixia , Zhang Wenjie , Yang Jingmin , Deng Shanghui 
Published: August 2022

Abstract
Indoor localization technology based on Received Signal Strength (RSS) fingerprint is widely used in life and industry. Compared with the traditional localization methods, the localization technology integrating multiple machine learning methods has better localization accuracy. However, in multi-floor localization, the existing fusion localization technology ignores the interaction between different floors in the localization process, resulting in low indoor localization accuracy. This paper proposes a Wi-Fi indoor 3D localization method based on multi-classifier fusion named FLMCF. Firstly, floor classification training is carried out to reduce the location deviation in the vertical direction. Secondly, for each floor, multiple classifiers are used for model training and training the optimal weight set by minimizing the average localization error. In this case, the advantages of each classifier can be fully integrated to improve the localization accuracy. Finally, the Reliability Fusion Weight Selection (RFWS) algorithm determines the weight and calculates the final location estimation. The experimental results indicate that FLMCF is nearly 14.1% better than DIFMIC in the 90th percentile of CDF.
Estimating residential hot water consumption from smart electricity meter data
Authors: Bongungu Joseph L , Francisco Paul W , Gloss Stacy L , Stillwell Ashlynn S 
Published: August 2022

Abstract
Residential water heating is among the most energy-intensive aspects of the water sector; however, residential hot water use is often poorly quantified. Estimating hot water consumption from smart electricity meter data can help advance the body of knowledge regarding the residential energy-water nexus by employing data to fill this knowledge gap, potentially promoting community resilience through energy and water resources efficiency. Using a non-intrusive load monitoring algorithm calibrated with fine-resolution data, we disaggregated electricity for water heating from half-hourly smart electricity meter data, demonstrated with data organized at the zip code level for areas in the city of Chicago. From these electricity for water heating signals, we estimated residential hot water consumption with quantified uncertainty. Results indicate that water heating accounted for 7%–20% of total electricity consumption in the analyzed single-family residential homes, representing an average of 1–8 kWh d−1 of electricity consumption and 7–55 gallons (26–208 l) of hot water per day. These results also demonstrated significant spatial variability, such that some areas of Chicago show higher per household hot water use. With the challenges of deploying advanced water metering infrastructure, using isolated water heating signals from smart electricity meters to develop a first-order estimate of domestic hot water use represents a valuable quantification of an energy-intense flow.
Anticipating water distribution service outages from increasing temperatures
Authors: Bondank Emily N , Chester Mikhail V , Michne Austin , Ahmad Nasir , Ruddell Benjamin L , Johnson Nathan G 
Published: August 2022

Abstract
With projected temperature increases and extreme events due to climate change for many regions of the world, characterizing the impacts of these emerging hazards on water distribution systems is necessary to identify and prioritize adaptation strategies for ensuring reliability. To aid decision-making, new insights are needed into how water distribution system reliability to climate-driven heat will change, and the proactive maintenance strategies available to combat failures. To this end, we present the model Perses, a framework that joins a water distribution network hydraulic solver with reliability models of physical assets or components to estimate temperature increase-driven failures and resulting service outages in the long term. A theoretical case study is developed using Phoenix, Arizona temperature profiles, a city with extreme temperatures and a rapidly expanding infrastructure. By end-of-century under hotter futures there are projected to be 1%–5% more pump failures, 2%–5% more PVC pipe failures, and 3%–7% more iron pipe failures (RCP 4.5–8.5) than a baseline historical temperature profile. Service outages, which constitute inadequate pressure for domestic and commercial use are projected to increase by 16%–26% above the baseline under maximum temperature conditions. The exceedance of baseline failures, when compounded across a large metro region, reveals potential challenges for budgeting, management, and maintenance. An exploration of the mitigation potential of adaptation strategies shows that expedited repair times are capable of offsetting the additional outages from climate change, but will come with a cost.
Transformative adaptation and implications for transdisciplinary climate change research
Authors: Hellin Jon , Amarnath Giriraj , Challinor Andrew , Fisher Eleanor , Girvetz Evan , Guo Zhe , Hodur Janet , Loboguerrero Ana Maria , Pacillo Grazia , Rose Sabrina , Schutz Tonya , Valencia Lina , You Liangzhi 
Published: August 2022

Abstract
The severity of the climate challenge requires a change in the climate response, from an incremental to a more far-reaching and radical transformative one. There is also a need to avoid maladaptation whereby responses to climate risk inadvertently reinforce vulnerability, exposure and risk for some sections of society. Innovative technological interventions are critical but enabling social, institutional and governance factors are the actual drivers of the transformative process. Bringing about this transformation requires inter- and transdisciplinary approaches, and the embracing of social equity. In this Perspective, we unpack what this means for agricultural research and, based on our collective experience, we map out a research agenda that weaves different research components into a holistic and transformative one. We do not offer best practice, but rather reflections on how agricultural research can more readily contribute to transformative adaptation, along with the personal and practical challenges of designing and implementing such an agenda.
LRTCLS: low-rank tensor completion with Laplacian smoothing regularization for unveiling the post-transcriptional machinery of N6-methylation (m6A)-mediated diseases
Authors: Ma Jiani , Liu Hui , Mao Yumeng , Zhang Lin 
Published: August 2022

Abstract
Recently, N6-methylation (m6A) has recently become a hot topic due to its key role in disease pathogenesis. Identifying disease-related m6A sites aids in the understanding of the molecular mechanisms and biosynthetic pathways underlying m6A-mediated diseases. Existing methods treat it primarily as a binary classification issue, focusing solely on whether an m6A–disease association exists or not. Although they achieved good results, they all shared one common flaw: they ignored the post-transcriptional regulation events during disease pathogenesis, which makes biological interpretation unsatisfactory. Thus, accurate and explainable computational models are required to unveil the post-transcriptional regulation mechanisms of disease pathogenesis mediated by m6A modification, rather than simply inferring whether the m6A sites cause disease or not. Emerging laboratory experiments have revealed the interactions between m6A and other post-transcriptional regulation events, such as circular RNA (circRNA) targeting, microRNA (miRNA) targeting, RNA-binding protein binding and alternative splicing events, etc., present a diverse landscape during tumorigenesis. Based on these findings, we proposed a low-rank tensor completion-based method to infer disease-related m6A sites from a biological standpoint, which can further aid in specifying the post-transcriptional machinery of disease pathogenesis. It is so exciting that our biological analysis results show that Coronavirus disease 2019 may play a role in an m6A- and miRNA-dependent manner in inducing non-small cell lung cancer.
Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data
Authors: Sidorczuk Katarzyna , Gagat Przemysław , Pietluch Filip , Kała Jakub , Rafacz Dominik , Bąkała Laura , Słowik Jadwiga , Kolenda Rafał , Rödiger Stefan , Fingerhut Legana C H W , Cooke Ira R , Mackiewicz Paweł , Burdukiewicz Michał 
Published: August 2022

Abstract
Antimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target not only microorganisms but also viruses and cancer cells. Due to their lower selection for resistance compared with traditional antibiotics, AMPs have been attracting the ever-growing attention from researchers, including bioinformaticians. Machine learning represents the most cost-effective method for novel AMP discovery and consequently many computational tools for AMP prediction have been recently developed. In this article, we investigate the impact of negative data sampling on model performance and benchmarking. We generated 660 predictive models using 12 machine learning architectures, a single positive data set and 11 negative data sampling methods; the architectures and methods were defined on the basis of published AMP prediction software. Our results clearly indicate that similar training and benchmark data set, i.e. produced by the same or a similar negative data sampling method, positively affect model performance. Consequently, all the benchmark analyses that have been performed for AMP prediction models are significantly biased and, moreover, we do not know which model is the most accurate. To provide researchers with reliable information about the performance of AMP predictors, we also created a web server AMPBenchmark for fair model benchmarking. AMPBenchmark is available at http://BioGenies.info/AMPBenchmark.
Dynamic changes in the hormones of black-necked cranes during reproduction
Authors: Wang Yihua , Zhang Guogang , Jiang Hongxing , Liu Dongping , Hu Xingbo , Qian Fawen 
Published: August 2022

AbstractBlack-necked cranes (Grus nigricollis) are national first-level protected wild animals in China. Artificial breeding has been adopted by many zoos and reserves to achieve ex-situ conservation of black-necked cranes, but the breeding rate of the species in cages is low. This study used non-invasive methods combined with behavioural observations to investigate changes in sex hormones and glucocorticoid metabolites in the droppings of black-necked cranes during the breeding cycle, with the results showing that (i) levels of estradiol and testosterone in black-necked cranes increased significantly when they entered the breeding period, and these levels could be used as an important physiological indicator to effectively monitor the physiological status of females and males during the reproductive period, thus providing a theoretical basis for the timing of semen collection; (ii) the level of progesterone in the mid-reproduction stage was significantly higher than that in other stages in female black-necked cranes after successful mating, and this level could be an effective indicator of the mating status of female black-necked cranes; (iii) droppings’ glucocorticoid metabolites in the breeding period showed different dynamics between paired and singly caged black-necked cranes, indicating that the physiological phenomenon of reproduction could result in a certain amount of physiological burden on black-necked cranes. These results provide a theoretical basis for the selection of physiological parameters in the artificial breeding of black-necked cranes.
Cellular mechanisms of oligoclonal vascular smooth muscle cell expansion in cardiovascular disease
Authors: Worssam Matt D , Lambert Jordi , Oc Sebnem , Taylor James C K , Taylor Annabel L , Dobnikar Lina , Chappell Joel , Harman Jennifer L , Figg Nichola L , Finigan Alison , Foote Kirsty , Uryga Anna K , Bennett Martin R , Spivakov Mikhail , Jørgensen Helle F 
Published: August 2022

Abstract

Aims
Quiescent, differentiated adult vascular smooth muscle cells (VSMCs) can be induced to proliferate and switch phenotype. Such plasticity underlies blood vessel homeostasis and contributes to vascular disease development. Oligoclonal VSMC contribution is a hallmark of end-stage vascular disease. Here, we aim to understand cellular mechanisms underpinning generation of this VSMC oligoclonality.

Methods and results
We investigate the dynamics of VSMC clone formation using confocal microscopy and single-cell transcriptomics in VSMC-lineage-traced animal models. We find that activation of medial VSMC proliferation occurs at low frequency after vascular injury and that only a subset of expanding clones migrate, which together drives formation of oligoclonal neointimal lesions. VSMC contribution in small atherosclerotic lesions is typically from one or two clones, similar to observations in mature lesions. Low frequency (&lt;0.1%) of clonal VSMC proliferation is also observed in vitro. Single-cell RNA-sequencing revealed progressive cell state changes across a contiguous VSMC population at onset of injury-induced proliferation. Proliferating VSMCs mapped selectively to one of two distinct trajectories and were associated with cells showing extensive phenotypic switching. A proliferation-associated transitory state shared pronounced similarities with atypical SCA1+ VSMCs from uninjured mouse arteries and VSMCs in healthy human aorta. We show functionally that clonal expansion of SCA1+ VSMCs from healthy arteries occurs at higher rate and frequency compared with SCA1− cells.

Conclusion
Our data suggest that activation of proliferation at low frequency is a general, cell-intrinsic feature of VSMCs. We show that rare VSMCs in healthy arteries display VSMC phenotypic switching akin to that observed in pathological vessel remodelling and that this is a conserved feature of mouse and human healthy arteries. The increased proliferation of modulated VSMCs from healthy arteries suggests that these cells respond more readily to disease-inducing cues and could drive oligoclonal VSMC expansion.
Relapsing low-flow alarms due to suboptimal alignment of the left ventricular assist device inflow cannula
Authors: Zijderhand Casper F , Knol Wiebe G , Budde Ricardo P J , van der Heiden Cornelis W , Veen Kevin M , Sjatskig Jelena , Manintveld Olivier C , Constantinescu Alina A , Birim Ozcan , Bekkers Jos A , Bogers Ad J J C , Caliskan Kadir 
Published: August 2022

AbstractOBJECTIVESThis retrospective study investigated the correlation between the angular position of the left ventricular assist device (LVAD) inflow cannula and relapsing low-flow alarms.METHODSMedical charts were reviewed of all patients with HeartMate 3 LVAD support for relapsing low-flow alarms. A standardized protocol was created to measure the angular position with a contrast-enhanced computed tomography scan. Statistics were done using a gamma frailty model with a constant rate function.RESULTSFor this analysis, 48 LVAD-supported patients were included. The majority of the patients were male (79%) with a median age of 57 years and a median follow-up of 30 months (interquartile range: 19–41). Low-flow alarm(s) were experienced in 30 (63%) patients. Angulation towards the septal–lateral plane showed a significant increase in low-flow alarms over time with a constant rate function of 0.031 increase in low-flow alarms per month of follow-up per increasing degree of angulation (P = 0.048). When dividing this group using an optimal cut-off point, a significant increase in low-flow alarms was observed when the septal–lateral angulation was 28° or more (P = 0.001). Anterior–posterior and maximal inflow cannula angulation did not show a significant difference.CONCLUSIONSThis study showed an increasing number of low-flow alarms when the degrees of LVAD inflow cannula expand towards the septal–lateral plane. This emphasizes the importance of the LVAD inflow cannula angular position to prevent relapsing low-flow alarms with the risk of diminished quality of life and morbidity.
Repolarization indicates electrical instability in ventricular arrhythmia originating from papillary muscle
Authors: Münkler Paula , Klatt Niklas , Scherschel Katharina , Kuklik Pawel , Jungen Christiane , Cavus Ersin , Eickholt Christian , Christoph Jan , Lemoine Marc D , Christ Torsten , Willems Stephan , Riedel René , Kirchhof Paulus , Meyer Christian 
Published: August 2022

AbstractAimsCardiac arrhythmia originating from the papillary muscle (PM) can trigger ventricular fibrillation (VF) and cause sudden cardiac death even in the absence of structural heart disease. Most premature ventricular contractions, however, are benign and hitherto difficult to distinguish from a potentially fatal arrhythmia. Altered repolarization characteristics are associated with electrical instability, but electrophysiological changes which precede degeneration into VF are still not fully understood.Methods and resultsVentricular arrhythmia (VA) was induced by aconitine injection into PMs of healthy sheep. To investigate mechanisms of degeneration of stable VA into VF in structurally healthy hearts, endocardial high-density and epicardial mapping was performed during sinus rhythm (SR) and VA. The electrical restitution curve, modelling the relation of diastolic interval and activation recovery interval (a surrogate parameter for action potential duration), is steeper in VA than in non-arrhythmia (ventricular pacing and SR). Steeper restitution curves reflect electrical instability and propensity to degenerate into VF. Importantly, we find the parameter repolarization time in relation to cycle length (RT/CL) to differentiate self-limiting from degenerating arrhythmia with high specificity and sensitivity.ConclusionRT/CL may serve as a simple index to aid differentiation between self-limiting and electrically instable arrhythmia with the propensity to degenerate to VF. RT/CL is independent of cycle length and could easily be measured to identify electrical instability in patients.
Expanding the neutral sites for integrated gene expression in Saccharomyces cerevisiae
Authors: Kong Sijia , Yu Wei , Gao Ning , Zhai Xiaoxin , Zhou Yongjin J 
Published: August 2022

ABSTRACT
Construction of efficient microbial cell factories always requires assembling biosynthetic pathways and rewiring cellular metabolism with overexpression of multiple genes. Genomic integration is considered to be helpful for stable gene expression in compared with the episomal plasmids. However, the limited availability of suitable loci hinders the extensive metabolic engineering. We here characterized 30 neutral sites in Saccharomyces cerevisiae genome that did not affect cellular fitness by using expression cassettes of green fluorescent protein (eGFP) and fatty acyl-CoA reductase (MaFAR1) with the aid of efficient CRISPR-Cas9 technique. We found that integration of gene expression cassettes to different genome loci resulted a varied GFP signal and fatty alcohol production, which showed that genomic loci could be used for tuning gene expression. The characterized set of neutral sites should be helpful for extensively metabolic engineering of S. cerevisiae for chemical production and other purposes.
Beyond the safe and censored: outcomes from student experiences within a pedagogy of discomfort
Authors: McIver Shane , Murphy Berni 
Published: August 2022

Summary
Educators continue to seek teaching and learning strategies to augment student self-empowerment, agency and professional skills. This qualitative study analysed students’ own evolving perspectives when Boler’s pedagogy of discomfort was used to redevelop curriculum. Changes over time were examined regarding personal and professional development in public health and health promotion, including those most significant to the students themselves. Participants were final-year Australian undergraduate health students (n = 91) who applied a thematic analysis to their regular online ‘blogs’, articulating their thoughts and opinions about what they observed regarding unit content and tasks throughout the trimester. The researchers then conducted their own analysis to identify patterns and trends within the depth and breadth of student perceptions. Findings revealed that the personal and professional growth educators seek to instil arose spontaneously from students’ increasing self-awareness, rather than classroom prompting or instruction and occurred in specific ways. This study chartered the course of how students challenged their own typical values and limiting beliefs, becoming more aligned and reflective of health promotion competencies. Other positive self-transformation was also identified, such as cultivating an open mind, shifts from victim-blaming to increasing compassion and empathy, through to the importance of finding their own voice. Future comparable studies including postgraduate students and diverse student groups are encouraged.
Inference of putative cell-type-specific imprinted regulatory elements and genes during human neuronal differentiation
Authors: Liang Dan , Aygün Nil , Matoba Nana , Ideraabdullah Folami Y , Love Michael I , Stein Jason L 
Published: August 2022

AbstractGenomic imprinting results in gene expression bias caused by parental chromosome of origin and occurs in genes with important roles during human brain development. However, the cell-type and temporal specificity of imprinting during human neurogenesis is generally unknown. By detecting within-donor allelic biases in chromatin accessibility and gene expression that are unrelated to cross-donor genotype, we inferred imprinting in both primary human neural progenitor cells and their differentiated neuronal progeny from up to 85 donors. We identified 43/20 putatively imprinted regulatory elements (IREs) in neurons/progenitors, and 133/79 putatively imprinted genes in neurons/progenitors. Although 10 IREs and 42 genes were shared between neurons and progenitors, most putative imprinting was only detected within specific cell types. In addition to well-known imprinted genes and their promoters, we inferred novel putative IREs and imprinted genes. Consistent with both DNA methylation-based and H3K27me3-based regulation of imprinted expression, some putative IREs also overlapped with differentially methylated or histone-marked regions. Finally, we identified a progenitor-specific putatively imprinted gene overlapping with copy number variation that is associated with uniparental disomy-like phenotypes. Our results can therefore be useful in interpreting the function of variants identified in future parent-of-origin association studies.