bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of point‐of‐care haemoglobin tests to diagnose childhood anaemia in low‐ and middle‐income countries: A systematic review
Authors: Brehm Rebecca , South Annabelle , George Elizabeth C.
Published: December 2023

Objectives

Anaemia is a major cause of mortality and transfusion in children in low‐ and middle‐income countries (LMICs); however, current diagnostics are slow, costly and frequently unavailable. Point‐of‐care haemoglobin tests (POC(Hb)Ts) could improve patient outcomes and use of resources by providing rapid and affordable results. We systematically reviewed the literature to investigate what, where and how POC(Hb)Ts are being used by health facilities in LMICs to diagnose childhood anaemia, and to explore challenges to their use.

Methods

We searched a total of nine databases and trial registries up to 10 June 2022 using the concepts: anaemia, POC(Hb)T, LMIC and clinical setting. Adults ≥21 years and literature published >15 years ago were excluded. A single reviewer conducted screening, data extraction and quality assessment (of diagnostic studies) using QUADAS‐2. Outcomes including POC(Hb)T used, location, setting, challenges and diagnostic accuracy were synthesised.

Results

Of 626 records screened, 41 studies were included. Evidence is available on the use of 15 POC(Hb)Ts in hospitals (n = 28, 68%), health centres (n = 9, 22%) and clinics/units (n = 10, 24%) across 16 LMICs. HemoCue (HemoCue AB, Ängelholm, Sweden) was the most used test (n = 31, 76%). Key challenges reported were overestimation of haemoglobin concentration, clinically unacceptable limits of agreement, errors/difficulty in sampling, environmental factors, cost, inter‐observer variability and supply of consumables. Five POC(Hb)Ts (33%) could not detect haemoglobin levels below 4.5 g/dL. Diagnostic accuracy varied, with sensitivity and specificity to detect anaemia ranging from 24.2% to 92.2% and 70% to 96.7%, respectively.

Conclusions

POC(Hb)Ts have been successfully utilised in health facilities in LMICs to diagnose childhood anaemia. However, limited evidence is available, and challenges exist that must be addressed before wider implementation. Further research is required to confirm accuracy, clinical benefits and cost‐effectiveness.
Plant nucleoside N‐ribohydrolases: riboside binding and role in nitrogen storage mobilization
Authors: Ľuptáková Eva , Vigouroux Armelle , Končitíková Radka , Kopečná Martina , Zalabák David , Novák Ondřej , Salcedo Sarmiento Sara , Ćavar Zeljković Sanja , Kopečný David Jaroslav , von Schwartzenberg Klaus , Strnad Miroslav , Spíchal Lukáš , De Diego Nuria , Kopečný David , Moréra Solange
Published: December 2023

Cells save their energy during nitrogen starvation by selective autophagy of ribosomes and degradation of RNA to ribonucleotides and nucleosides. Nucleosides are hydrolyzed by nucleoside N‐ribohydrolases (nucleosidases, NRHs). Subclass I of NRHs preferentially hydrolyzes the purine ribosides while subclass II is more active towards uridine and xanthosine. Here, we performed a crystallographic and kinetic study to shed light on nucleoside preferences among plant NRHs followed by in vivo metabolomic and phenotyping analyses to reveal the consequences of enhanced nucleoside breakdown. We report the crystal structure of Zea mays NRH2b (subclass II) and NRH3 (subclass I) in complexes with the substrate analog forodesine. Purine and pyrimidine catabolism are inseparable because nucleobase binding in the active site of ZmNRH is mediated via a water network and is thus unspecific. Dexamethasone‐inducible ZmNRH overexpressor lines of Arabidopsis thaliana, as well as double nrh knockout lines of moss Physcomitrium patents, reveal a fine control of adenosine in contrast to other ribosides. ZmNRH overexpressor lines display an accelerated early vegetative phase including faster root and rosette growth upon nitrogen starvation or osmotic stress. Moreover, the lines enter the bolting and flowering phase much earlier. We observe changes in the pathways related to nitrogen‐containing compounds such as β‐alanine and several polyamines, which allow plants to reprogram their metabolism to escape stress. Taken together, crop plant breeding targeting enhanced NRH‐mediated nitrogen recycling could therefore be a strategy to enhance plant growth tolerance and productivity under adverse growth conditions.
GARCH Models and Distributions Comparison for Nonlinear Time Series with Volatilities
Authors: Abdul Rahman Nur Haizum , Jia Goh Hui , Zulkafli Hani Syahida
Published: December 2023

The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is extensively used for handling volatilities. However, with numerous extensions to  the standard GARCH model, selecting the most suitable model for forecasting price volatilities becomes challenging. This study aims to examine the performance of different GARCH models in forecasting crude oil price volatilities using West Texas Intermediate (WTI) data. The models considered are the standard GARCH, Integrated GARCH (IGARCH), Exponential GARCH (EGARCH), and Golsten, Jagannathan, and Runkle GARCH (GJR-GARCH), each with normal distribution, Student’s t-distribution, and Generalized Error Distribution (GED). To evaluate the performance of each model, the Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) are used as the model selection criteria, along with forecast accuracy measures such as absolute error, root mean squared error (RMSE), and mean absolute error (MAE). Post-estimation tests, including the Autoregressive Conditional Heteroskedasticity Lagrange Multiplier (ARCH-LM) test and the Ljung-Box test, are conducted to ensure the adequacy of all models. The results reveal that all GARCH models are suitable for modeling the data, as indicated by statistically significant estimated parameters and satisfactory post-estimation outcomes. However, the EGARCH (1, 1) model, particularly with Student’s t-distribution, outperforms other models in both data fitting and accurate forecasting of nonlinear time series.
Influence of Enriched Urease Producing Bacteria from Leachate and Restaurant Wastewater on Heavy Metal Removal
Authors: Basri Hazlami Fikri , Omoregie Armstrong Ighodalo , Mokhter Mohd Akmali
Published: December 2023

The escalation of heavy metal pollution in natural ecosystems due to industrialization presents a critical environmental concern, endangering the well-being of living organisms. Microbially Induced Carbonate Precipitation (MICP) technology, an emerging innovation, has gained attention from the scientific community for its potential in biocementation and bioremediation applications. However, a substantial gap in understanding exists regarding the utilization of ureolytic microbial strains from waste sources capable of effectively immobilizing high concentrations of heavy metals. This study endeavors to explore the latent potential of indigenous ureolytic bacteria derived from leachate and restaurant wastewater, possessing bioremediation capabilities for heavy metal immobilization. The investigation includes microbial screening, physiological characterization of ureolytic bacteria, assessment of their tolerance levels, and evaluation of heavy metal removal efficacy through Atomic Absorption Spectrophotometry (AAS) analysis. Notably, the results reveal that ureolytic bacteria from restaurant wastewater are more tolerant to Cd2+ concentrations compared to their leachate counterparts, manifesting optimum conductivity, pH, and optical density (OD). More so, AAS analysis demonstrates the restaurant wastewater-derived sample's remarkable proficiency in Cd2+ removal, achieving a substantial 95% removal rate, significantly outperforming the leachate wastewater sample's removal rate of 53%.
Application of Imputation Method for Compositional Data with Missing Values based on Adaptive LASSO Model: the Composition of Employment Industry in Taiyuan, China
Authors: Tian Ying , Majahar Ali Majid Khan , Pei Shan Fam , Wu Lili , Mohd Jamaludin Siti Zulaikha
Published: December 2023

The tripartite industry classification, which divides all economic activities into three parts, is a classification method to reflect the dynamic process of economic development and the historical trend of the change of resource allocation structure.The fact shows that the proportion of each industry has become an important symbol of the level of national economic development. The proportion of each industry is compositional data,which is a kind of complex multidimensional data used in many fields. All components in the compositional data are non-negative and carry only relative information. In practice, there could be missing values in compositional data. However, general statistical analysis methods cannot be firstly used for compositional data with missing values. The complexity of the missing value of compositional data makes traditional imputation methods no longer suitable. Thus, how to carry out effective statistical inference for compositional data with missing values attracts the attention of many scholars, recently. In this paper, we focus on the imputation problem in compositional data containing missing values, and propose an Adaptive Least Absolute Shrinkage and Selection Operator (ALASSO) imputation method to obtain a complete datasets through variable selection and parameter estimation. Then, the new method is simulated and empirically analyzed, and a comparative study with mean imputation, k-nearest neighbor imputation, and iterative regression imputation is conducted. The results show that the ALASSO imputation method has the highest accuracy for different missing rates, dimensions and correlation coefficients.
Molnupiravir maintains antiviral activity against SARS-CoV-2 variants and exhibits a high barrier to the development of resistance
Authors: Strizki Julie M. , Gaspar John M. , Howe John A. , Hutchins Beth , Mohri Hiroshi , Nair Manoj S. , Kinek Keith C. , McKenna Philip , Goh Shih Lin , Murgolo Nicholas
Published: December 2023

Molnupiravir, an oral prodrug of N-hydroxycytidine (NHC), previously demonstrated broad
in vitro
antiviral activity against multiple RNA viruses and has shown a high barrier to the development of resistance. Here, we present the antiviral activity of NHC against recent SARS-CoV-2 variants and the results of resistance selection studies to better understand the potential for viral resistance to NHC. NHC activity against SARS-CoV-2 variants omicron (BA.1, BA.1.1, BA.2, BA.4, BA.4.6, BA.5, BQ.1.1, XBB.1, and XBB.1.5), alpha (B.1.1.7), beta (B.1.351), gamma (P.1), delta (B.1.617.2), lambda (C.37), and mu (B.1.621) was evaluated in Vero E6 cells using cytopathic effect assays. Resistance selection studies were performed by passaging SARS-CoV-2 (WA1) in the presence of NHC or a 3C-like protease inhibitor (MRK-A) in Vero E6 cells. Supernatants from cultures exhibiting a cytopathic effect score of ≥2 were re-passaged, and IC
50
values were estimated. Whole-genome deep sequencing was performed on viral RNA isolated at each passage. NHC demonstrated similar potency against all SARS-CoV-2 variants evaluated. No evidence of SARS-CoV-2 phenotypic or genotypic resistance to NHC was observed following 30 passages. A random pattern of nucleotide changes was observed in NHC cultures, consistent with the drug’s mechanism of action. In contrast, resistance was readily selected in all three MRK-A control cultures with the selection of a T21I substitution in the 3C-like protease. In conclusion, molnupiravir maintains antiviral activity across all major SARS-CoV-2 variants. Furthermore, no evidence of viral resistance to NHC was observed, supporting previous reports that NHC has a high barrier to developing resistance.
Relative inhibitory activities of the broad-spectrum β-lactamase inhibitor taniborbactam against metallo-β-lactamases
Authors: Le Terrier Christophe , Viguier Clément , Nordmann Patrice , Vila Alejandro J. , Poirel Laurent
Published: December 2023

Taniborbactam (TAN) is a novel broad-spectrum β-lactamase inhibitor with significant activity against subclass B1 metallo-β-lactamases (MBLs). Here, we showed that TAN exhibited an overall excellent activity against B1 MBLs including most NDM- and VIM-like as well as SPM-1, GIM-1, and DIM-1 enzymes, but not against SIM-1. Noteworthy, VIM-1-like enzymes (particularly VIM-83) were less inhibited by TAN than VIM-2-like. Like NDM-9, NDM-30 (also differing from NDM-1 by a single amino acid substitution) was resistant to TAN.
Identification of four neutralizing antigenic sites on the enterovirus D68 capsid
Authors: Dai Wenlong , Li Xue , Liu Zeyu , Zhang Chao
Published: December 2023

Enterovirus D68 (EV-D68) is an emerging human pathogen associated with respiratory diseases and/or acute flaccid myelitis. Neutralizing antigenic sites of EV-D68 have not yet been comprehensively studied. In this study, we generated multiple neutralizing monoclonal antibodies (MAbs) directed against EV-D68 prototype or clinical strains. All these antibodies can inhibit EV-D68 attachment. The antibody epitopes were identified by selection and sequence analysis of prototype or clinical strain-derived neutralization-resistant mutants. The epitopes were then grouped into four distinct neutralizing antigenic sites (I to IV) by cross-neutralization analysis of the mutants with the MAbs and by spatial considerations. Site I, including residues 81, 85, and 87 of VP1 protein, is located in the VP1 BC loop, near the fivefold axis, and at the north rim of the canyon (the receptor binding site). Site II, involving residues 137, 139, and 142 of VP2, is situated in the VP2 EF loop and at the south rim of the canyon. Site III is composed of VP1 C-terminal residues 285 and 293 and resides on the south side of the canyon of neighboring asymmetric unit. Site IV contains residue 70 (βB strand) of VP2 from an asymmetric unit and residues 74 and 79 (BC loop) of VP3 from an adjacent unit and is located around the threefold axis. The four antigenic sites show various degrees of sequence variation. The identification of the four neutralizing antigenic sites on EV-D68 capsid provides a better understanding of the recognition of EV-D68 by neutralizing antibodies and viral evolution and immune escape.

IMPORTANCE

Enterovirus D68 (EV-D68) is an emerging respiratory pathogen associated with acute flaccid myelitis. Currently, no approved vaccines or antiviral drugs are available. Here, we report four functionally independent neutralizing antigenic sites (I to IV) by analyses of neutralizing monoclonal antibody (MAb)-resistant mutants. Site I is located in the VP1 BC loop near the fivefold axis. Site II resides in the VP2 EF loop, and site III is situated in VP1 C-terminus; both sites are located at the south rim of the canyon. Site IV is composed of residue in VP2 βB strand and residues in the VP3 BC loop and resides around the threefold axis. The developed MAbs targeting the antigenic sites can inhibit viral binding to cells. These findings advance the understanding of the recognition of EV-D68 by neutralizing antibodies and viral evolution and immune escape and also have important implications for the development of novel EV-D68 vaccines.
Aminoglycoside uptake, stress, and potentiation in Gram-negative bacteria: new therapies with old molecules
Authors: Lang Manon , Carvalho André , Baharoglu Zeynep , Mazel Didier
Published: December 2023

Aminoglycosides (AGs) are long-known molecules successfully used against Gram-negative pathogens. While their use declined with the discovery of new antibiotics, they are now classified as critically important molecules because of their effectiveness against multidrug-resistant bacteria. While they can efficiently cross the Gram-negative envelope, the mechanism of AG entry is still incompletely understood, although this comprehension is essential for the development of new therapies in the face of the alarming increase in antibiotic resistance. Increasing antibiotic uptake in bacteria is one strategy to enhance effective treatments. This review aims, first, to consolidate old and recent knowledge about AG uptake; second, to explore the connection between AG-dependent bacterial stress and drug uptake; and finally, to present new strategies of potentiation of AG uptake for more efficient antibiotic therapies. In particular, we emphasize on the connection between sugar transport and AG potentiation.
Microbiology of the built environment: harnessing human-associated built environment research to inform the study and design of animal nests and enclosures
Authors: Hill Megan S. , Gilbert Jack A.
Published: December 2023

Over the past decade, hundreds of studies have characterized the microbial communities found in human-associated built environments (BEs). These have focused primarily on how the design and use of our built spaces have shaped human-microbe interactions and how the differential selection of certain taxa or genetic traits has influenced health outcomes. It is now known that the more removed humans are from the natural environment, the greater the risk for the development of autoimmune and allergic diseases, and that indoor spaces can be harsh, selective environments that can increase the emergence of antimicrobial-resistant and virulent phenotypes in surface-bound communities. However, despite the abundance of research that now points to the importance of BEs in determining human-microbe interactions, only a fraction of non-human animal structures have been comparatively explored. It is here, in the context of human-associated BE research, that we consider the microbial ecology of animal-built natural nests and burrows, as well as artificial enclosures, and point to areas of primary interest for future research.
Complete genome sequence of Japanese encephalitis virus strain SDWF-2021 isolated from a
Culex
mosquito pool from a duck farm
Authors: Li Chenxi , Zhao Wen
Published: December 2023

We report here the complete genome sequence of Japanese encephalitis virus (JEV) strain SDWF-2021, isolated from a
Culex
mosquito pool in a duck farm located in Shandong, China. The isolated JEV genetically belong to genotype I, which is the dominant genotype circulation in China.
Complete genome sequence of
Limnobacter thiooxidans
CS-K2
T
, isolated from freshwater lake sediments in Bavaria, Germany
Authors: Naruki Miu , Watanabe Aoi , Warashina Tomoro , Morita Teppei , Arakawa Kazuharu
Published: December 2023

Limnobacter thiooxidans
CS-K2
T
is a Gram-negative bacterium first isolated from the sediment of the littoral zone of a freshwater lake in Germany. We here present the complete annotated genome sequence of this thiosulfate-oxidizing bacterium, spanning 3.54 Mb and encoding 3,192 protein-coding sequences.
Lake characteristics drive concordant trophic responses across ecosystems in three top predator fish species
Authors: Thelen Mary A. , Gallagher David J. , Johnson Payton E. , Kangas Sara M. , McNulty Dylan J. , Morrison Alexandra L. , Herwig Brian R. , Staples David F. , Zimmer Kyle D.
Published: December 2023

Understanding similarities in trophic ecology of top predators is crucial given their influences on food webs. We sampled walleye ( Sander vitreus), northern pike ( Esox lucius), and muskellunge ( Esox masquinongy) from 17 Minnesota (USA) lakes and used δ13C and δ15N to estimate littoral carbon use, trophic position, and isotopic niche size of each species. All three species showed large inter-lake variability yet had concordant trophic responses across lakes, as littoral carbon use, trophic position, variability in littoral carbon and trophic position, and niche size were all positively related among species across lakes. Concordant responses were driven by a few key lake variables, with trophic position positively related to proportion littoral area and depth of hypoxic water, littoral carbon positively related to depth of hypoxic water and presence of zebra mussels ( Dreissena polymorpha), and niche size inversely related to lake area. Our results indicate that lake characteristics may influence food webs via consistent effects on multiple top predators. They also show that the amount of suitable habitat can be important for the ecosystem size hypothesis for trophic position.
Tillage effects on growing season nitrous oxide emissions in Canadian cropland soils
Authors: Pelster David E. , Matteau Jean-Pascal , Farrell Richard , Hernandez Ramirez Guillermo
Published: December 2023

Minimizing tillage has been promoted as an agricultural practice that may mitigate greenhouse gas emissions through carbon sequestration. However, there is some ambiguity regarding the effect of minimum tillage (MT) on emissions of other greenhouse gases, in particular soil nitrous oxide (N2O) emissions. To determine how effective MT could be in helping Canada mitigate greenhouse gas emissions, we used a meta-analysis to compare growing season N2O emissions from MT versus conventional tillage (CT). Overall, MT had 12% lower N2O emissions compared to CT ( P = 0.03). However, there was high variability due to soil texture and growing season precipitation (GSP), with MT tending to emit more N2O than CT in climates where GSP exceeded 600 mm, particularly for soils with sand content less than 60%. Therefore, unless long-term tillage trials, which are urgently needed in eastern Canada, show a reduction in N2O emissions over time, MT should be used as a greenhouse gas mitigation measure only in dry climates or on sandy soils.
Enhancement of electronic and magnetic properties in Cr2O3 monolayer honeycomb-kagome by hydrogenation and oxygenation
Authors: Mohamed Nehal , Moaied Mohammed
Published: December 2023

This study investigates the structural, electronic, and magnetic properties of pristine, hydrogenated, and oxygenated Cr2O3 monolayer honeycomb-kagome (HK) surface using first-principles calculations based on density functional theory (DFT). Molecular dynamics and phonon dispersion calculations demonstrate the thermal and dynamic stability of these systems, implying their feasibility for laboratory synthesis. The results revealed that the adsorption of hydrogen and oxygen atoms on the Cr2O3 monolayer surface exhibited negative adsorption energies, indicating that these structures are energetically favorable. Specifically, the adsorption of oxygen atoms transforms the initial half-metallic nature of the monolayer into semiconducting behavior. Moreover, the introduction of hydrogen and oxygen atoms considerably enhances the Curie temperature of the surface. These findings offer a practical approach for enhancing the electronic and magnetic properties of Cr2O3 monolayer HK surface, thereby facilitating their prospective application in spintronics.
Global Robust Newsvendor Operation Strategy for a Two-Market Stochastic Inventory System
Authors: Yan Xiaoli , Yu Hui
Published: December 2023

Global markets increase sales and profitability opportunities for enterprises, but more environmental uncertainty poses new challenges for operational planning. This paper attempts to introduce the idea of distributionally robust optimization into the global operation problem of a two-market stochastic inventory system, providing theoretical guidance and reference decision-making for enterprises to optimize and configure in a global market with non-overlapping geographic locations and sales seasons. We find that the demand correlation and the lack of demand information will not substantially affect the operation strategy, and the enterprise’s industrial chain and supply chain remain stable. However, reducing inter-market tariffs or logistics costs will lead to a change in strategy, and the existence of the secondary market will lead to more capacity planning in the primary market. In addition, we find that enterprises’ transshipment strategies rely significantly on exchange rate volatility. Numerical experiments were conducted to demonstrate our theoretical results.
Hybrid Optimized Deep Learning-Based Bacilli Segmentation and Infection-Level Identification of Tuberculosis Using Sputum Images
Authors: Sathish P. , Preethi D , Dominic Clara Shanthi , Kadiravan G.
Published: December 2023

Presently, one of the foremost health issues and an extremely transferrable disease is Tuberculosis which is spreading worldwide. Tuberculosis is generally produced by mycobacterium tuberculosis and can cause death if it is not detected at premature stages. Therefore, a precise and efficient approach is essential for the identification of tuberculosis. The physical analysis of sputum smears through fluorescence microscopy for the detection process and also the treatment process is a subjective and difficult task. Thus, the hybrid optimization-driven deep learning approach is designed in this paper for infection-level identification of severity prediction of tuberculosis. Here, a sputum image is considered for performing tuberculosis detection and it is acquired from a database. For executing bacilli segmentation, the Deep Contour Aware Network (DCAN) model is used. In addition, DCAN is trained by the introduced Fractional Artificial Hummingbird Algorithm (FAHA). Additionally, the LeNet scheme is applied to detect the infection level and severity detection. The LeNet is also trained using Coot-FAHA thereby; the system performance is highly increased. The devised optimization-enabled deep learning method achieved improved performance with precision, F1-score, and recall of 0.9326, 0.9386, and 0.9163, respectively.
Research on Lightweight Network Segmentation of Lung Parenchyma CT Image Based on FPGA Platform
Authors: Dou Yumin , Zhao Xuezhuan
Published: December 2023

Image segmentation algorithms for medical embedded vision devices usually require a light and low latency model. In this study, a novel lightweight DepthWise U-shape network (DWU-net) is proposed to address this issue, which implements the task of lung parenchyma image segmentation. In the contracting path and expanding path of segmentation network, we introduce a separable convolution unit to replace standard convolution for image feature extraction, which can learn the unique features of each layer of the image from multiple perspectives, and has more advantages in feature expression. Our algorithm has better flexibility, comparing to the original model, the model parameters’ number has been greatly reduced and the time efficiency is fully improved. The proposed architecture achieves good performance in FPGA implementation.
A Low-Cost and Fault-Tolerant Stochastic Architecture for the Bernsen Algorithm Using Bitstream Correlation
Authors: Wang Shaowei , Xie Guangjun , Xu Wenbing , Zhang Yongqiang , Han Jie
Published: December 2023

Many algorithms for image processing do not require particularly high precision, but they rely on complicated arithmetic operations for every pixel in an image. The Bernsen algorithm is a typical local thresholding algorithm for solving the problem of uneven lighting. However, this algorithm requires a significant computing overhead and is extremely sensitive to noise. In this work, two stochastic computing architectures are proposed for implementing the Bernsen algorithm by using, respectively, uncorrelated and correlated input bitstreams. Experimental results show that both designs, especially the one using correlated bitstreams, present high fault tolerance of soft errors and low hardware cost in comparison with its conventional binary implementation. However, SC logic with uncorrelated inputs is not always superior to its corresponding binary circuit in energy consumption, especially the circuit that needs long input bitstreams. That means that a reasonable use of correlation can further optimize the SC circuit design.
Three-qubit Deutsch–Jozsa in measurement-based quantum computing
Authors: Schwetz M. , Noack R. M.
Published: December 2023

Measurement-based quantum computing (MBQC), an alternate paradigm for formulating quantum algorithms, can lead to potentially more flexible and efficient implementations as well as to theoretical insights on the role of entanglement in a quantum algorithm. Using the graph-theoretical ZX-calculus, we describe and apply a general scheme for reformulating quantum circuits as MBQC implementations. After illustrating the method using the two-qubit Deutsch–Jozsa algorithm, we derive a ZX graph-diagram that encodes a general MBQC implementation for the three-qubit Deutsch–Jozsa algorithm. This graph describes an 11-qubit cluster state on which single-qubit measurements are used to execute the algorithm. Particular sets of choices of the axes for the measurements can be used to implement any realization of the oracle. In addition, we derive an equivalent lattice cluster state for the algorithm.
A Multi-Scale Computer Model of Mechanical Ventilation for COVID-19 Patients
Authors: Middleton Shea , Dimbath Elizabeth , Maddipati Veeranna , Peach M. Sean , Ju Andrew W. , George Stephanie , Vadati Alex
Published: December 2023

There is a need for more individualized treatment of critically ill patients receiving mechanical ventilation (MV). Therefore, this research aims to create a preliminary multi-scale computational modeling framework for MV in critically ill COVID-19 patients as a step toward studying region-specific and overall lung dynamics in these patients. This goal was accomplished by developing proof-of-concept image-based computer models providing insight into airflow redistribution and volume and pressure gradients on a lobe-specific basis. Our in silico multi-scale MV models simulated redistribution of ventilation for up to 20% of air volume from severely damaged lung lobes to the lobes less affected by COVID-19, hence potentially revealing a risk factor of MV-induced volutrauma due to heterogeneity of lung damage distribution in COVID-19. This study lays the foundation for future COVID-19 patient-specific lung models for individualized simulation of MV.
Damage Spectra of SDOF Structures Under Tsunami Actions Considering the Nonlinear Dynamic Analysis Method
Authors: Pan Xiaolan , Lin Zhongyao , Zhang Lianpeng , Zheng Zhi
Published: December 2023

This paper studies the damage spectra of single-degree-of-freedom (SDOF) systems for tsunami loading. The 2011 Tohoku tsunami wave traces are computed and obtained by adopting the Cornell Multi-grid Coupled Tsunami (COMCOT) model and are further verified by the Tohoku Tsunami Joint Survey (TTJS) data. The tsunami response analyses of SDOF systems are conducted taking into account the dynamic analysis method. The classical ductility damage is considered as the damage performance. The damage spectra are computed for five force reduction factors and 791 tsunami loadings. The effects of inundation depths, hysteretic model, post-yield stiffness ratio, [Formula: see text], viscous damping ratio, [Formula: see text], are explored and interpreted scientifically and statistically. The results demonstrate that the effect of the hysteretic model, force reduction factor, R, post-yield stiffness ratio, [Formula: see text], viscous damping ratio, [Formula: see text], on the damage of the structure is evident. Comparison with the static method and influence analysis of structural damping indicate the necessity for the application of the dynamic method. A simplified predictive formulation is developed for the evaluation of structural damage for tsunami loadings.
Modeling and analyzing COVID-19 infections in South Africa
Authors: Song Tianqi , Wang Yishi , Wang Chuncheng , An Qi
Published: December 2023

In this paper, we present a mathematical model that incorporates seasonal variations in COVID-19 transmission within South Africa. By fitting the model to real-world data, we estimate its parameters and demonstrate its enhanced accuracy in describing the local infection dynamics. We analyze the basic reproduction number and establish threshold dynamics through theoretical analysis, alongside investigating its numerical relationship with specific parameters. Furthermore, we conduct an optimal control analysis to evaluate the impact of intervention strategies, including quarantine, vaccination and medical treatment, on COVID-19 spread. Our findings emphasize the effectiveness of combining all three interventions in reducing the number of exposed and infected individuals. We identify that implementing these interventions when the infected population is at its lowest yields optimal results.
Scenario-specific verification of system requirements consistency via time modeling
Authors: Shi Jingkai , Zheng Liwei
Published: December 2023

Traditional requirement verification methods often fail to fully consider the modeling of time-dependent behaviors during system execution, which may lead to inconsistent system requirements, thereby compromise software reliability and correctness. To address this limitation, this paper proposes the Scenario-Specific Verification Method for System Requirements Consistency via Time Modeling. The Scenario-Specific Verification Method converts use case descriptions and problem graphs into Clock Constraint Specification Language (CCSL) constraints, transformed into clock graphs for verifying requirement consistency. The resulting constraints are solved with the Z3 solver to validate correctness, thereby enhancing system reliability. The novel time modeling approach provides techniques for verifying temporal dependencies in requirements. A case study demonstrates the efficiency and accuracy of the Scenario-Specific Verification Method in detecting inconsistencies. The main contributions include that a technique is demonstrated to formalize use case descriptions as CCSL constraints, improving on natural language and a method is presented utilizing CCSL time modeling and clock graphs to analyze requirements for consistency. Overall, an innovative solution for requirement verification using time modeling is offered by this paper, contributing to the enhancement of system development process reliability and correctness.
“Sometimes It’s Like Putting the Track in Front of the Rushing Train”: Having to Be ‘On Call’ for Work Limits the Temporal Flexibility of Crowdworkers
Authors: Lascău Laura , Brumby Duncan P. , Gould Sandy J. J. , Cox Anna L.
Published: December 2023

Research suggests that the temporal flexibility advertised to crowdworkers by crowdsourcing platforms is limited by both client-imposed constraints (e.g., strict completion times) and crowdworkers’ tooling practices (e.g., multitasking). In this article, we explore an additional contributor to workers’ limited temporal flexibility: the design of crowdsourcing platforms, namely requiring crowdworkers to be ‘on call’ for work. We conducted two studies to investigate the impact of having to be ‘on call’ on workers’ schedule control and job control. We find that being ‘on call’ impacted (1) participants’ ability to schedule their time and stick to planned work hours, and (2) the pace at which participants worked and took breaks. The results of the two studies suggest that the ‘on-demand’ nature of crowdsourcing platforms can limit workers’ temporal flexibility by reducing schedule control and job control. We conclude the article by discussing the implications of the results for (a) crowdworkers, (b) crowdsourcing platforms, and (c) the wider platform economy.
Learning Hierarchical Task Structures for Few-shot Graph Classification
Authors: Wang Song , Dong Yushun , Huang Xiao , Chen Chen , Li Jundong
Published: December 2023

The problem of few-shot graph classification targets at assigning class labels for graph samples, where only limited labeled graphs are provided for each class. To solve the problem brought by label scarcity, recent studies have proposed to adopt the prevalent few-shot learning framework to achieve fast adaptations to graph classes with limited labeled graphs. In particular, these studies typically propose to accumulate meta-knowledge across a large number of meta-training tasks, and then generalize such meta-knowledge to meta-test tasks sampled from a disjoint class set. Nevertheless, existing studies generally ignore the crucial task correlations among meta-training tasks and treat them independently. In fact, such task correlations can help promote the model generalization to meta-test tasks and result in better classification performance. On the other hand, it remains challenging to capture and utilize task correlations due to the complex components and interactions in meta-training tasks. To deal with this, we propose a novel few-shot graph classification framework FAITH to capture task correlations via learning a hierarchical task structure at different granularities. We further propose a task-specific classifier to incorporate the learned task correlations into the few-shot graph classification process. Moreover, we derive FAITH+, a variant of FAITH that can improve the sampling process for the hierarchical task structure. The extensive experiments on four prevalent graph datasets further demonstrate the superiority of FAITH and FAITH+ over other state-of-the-art baselines.
Auxiliary Information Guided Self-attention for Image Quality Assessment
Authors: Yang Jifan , Wang Zhongyuan , Wang Guangcheng , Huang Baojin , Yang Yuhong , Tu Weiping
Published: December 2023

Image quality assessment (IQA) is an important problem in computer vision with many applications. We propose a transformer-based multi-task learning framework for the IQA task. Two subtasks: constructing an auxiliary information error map and completing image quality prediction, are jointly optimized using a shared feature extractor. We use visual transformers (ViT) as a feature extractor for feature extraction and guide ViT to focus on image quality-related features by building auxiliary information error map subtask. In particular, we propose a fusion network that includes a channel focus module. Unlike the fusion methods commonly used in previous IQA methods, we use the fusion network, including the channel attention module, to fuse the auxiliary information error map features with the image features, which facilitates the model to mine the image quality features for more accurate image quality assessment. And by jointly optimizing the two subtasks, ViT focuses more on extracting image quality features and building a more precise mapping from feature representation to quality score. With slight adjustments to the model, our approach can be used in both no-reference (NR) and full-reference (FR) IQA environments. We evaluate the proposed method in multiple IQA databases, showing better performance than state-of-the-art FR and NR IQA methods.
Trajectory-User Linking via Hierarchical Spatio-Temporal Attention Networks
Authors: Chen Wei , Huang Chao , Yu Yanwei , Jiang Yongguo , Dong Junyu
Published: December 2023

Trajectory-User Linking (TUL) is crucial for human mobility modeling by linking different trajectories to users with the exploration of complex mobility patterns. Existing works mainly rely on the recurrent neural framework to encode the temporal dependencies in trajectories, have fall short in capturing spatial-temporal global context for TUL prediction. To fill this gap, this work presents a new hierarchical spatio-temporal attention neural network, calledAttnTUL, to jointly encode the local trajectory transitional patterns and global spatial dependencies for TUL. Specifically, our first model component is built over the graph neural architecture to preserve the local and global context and enhance the representation paradigm of geographical regions and user trajectories. Additionally, a hierarchically structured attention network is designed to simultaneously encode the intra-trajectory and inter-trajectory dependencies, with the integration of the temporal attention mechanism and global elastic attentional encoder. Extensive experiments demonstrate the superiority of our AttnTUL method as compared to state-of-the-art baselines on various trajectory datasets. The source code of our model is available athttps://github.com/Onedean/AttnTUL.
Report on the 6th International Workshop on Narrative Extraction from Texts (Text2Story 2023) at ECIR 2023
Authors: Campos Ricardo , Jorge Alípio M. , Jatowt Adam , Bhatia Sumit , Litvak Marina , Cordeiro João Paulo , Rocha Conceição , Sousa Hugo , Mansouri Behrooz
Published: December 2023

The Sixth International Workshop on Narrative Extraction from Texts (Text2Story'23) was held on April 2

nd

, 2023, in conjunction with the 45

th

European Conference on Information Retrieval (ECIR 2023) in Dublin, Ireland. Continuing the tradition of past years, the workshop was held as a hybrid event. Online participation was allowed using the Zoom platform. During the course of the day, more than 50 attendees had the opportunity to follow up and discuss the recent advances in topics related to representation, extraction, and generation of narratives. The workshop program included two invited keynotes and nineteen paper presentations. The proceedings of the workshop are available online
1
.

Date:
2 April 2023.

Website:
https://text2story23.inesctec.pt/.
Not just fibrotic: endothelial-derived TGFβ maintains contractile function and lymphatic muscle phenotype during homeostasis
Authors: Carrillo Diaz de Leon Miriam , Keane Keith , Roizes Simon , Liao Shan , von der Weid Pierre-Yves , Stephens Matthew
Published: December 2023

The growth factor TGFβ is commonly associated with its pathological overproduction during tissue fibrosis rather than its homeostatic functions. We expose the lymphatic endothelium as a source of endogenous TGFβ, the impact of its production on the maintenance of surrounding lymphatic muscle cell phenotype, and internally regulated mechanisms of its production. Overall, these results highlight the intricate balance of TGFβ-signaling as an essential component of maintaining lymphatic contractile function.
Following the cellular itinerary of renal aquaporin-2 shuttling with 4.5x expansion microscopy
Authors: Login Frédéric H. , Dam Vibeke S. , Nejsum Lene N.
Published: December 2023

Renal aquaporin-2 (AQP2) imaged by expansion microscopy provides unprecedented 3-D information regarding the AQP2 itinerary in response to changes in cellular cAMP.
The paracrine isthmin1 transcriptionally regulated by C/EBPβ exacerbates pulmonary vascular leakage in murine sepsis
Authors: Li Junxia , Tan Miaomiao , Yang Tian , Huang Qingyuan , Shan Fabo
Published: December 2023

This article addresses the role of the alveolar epithelial-secreted protein isthmin1 on the exacerbation of pulmonary vascular permeability in sepsis and identified nuclear factor CCAAT/enhancer binding protein (C/EBP)β as a new regulator of isthmin1 gene transcription. Targeting the C/EBPβ-isthmin1 regulatory axis on the alveolar side would be of great value in the treatment of pulmonary vascular leakage and lung injury induced by sepsis.
RTA 408 ameliorates diabetic cardiomyopathy by activating Nrf2 to regulate mitochondrial fission and fusion and inhibiting NF-κB-mediated inflammation
Authors: Hao Jinjin , Zhou Jiedong , Hu Songqing , Zhang Peipei , Wu Haowei , Yang Juntao , Zhao Bingjie , Liu Hanxuan , Lin Hui , Chi Jufang , Lou Dajun
Published: December 2023

We demonstrated first that the nuclear factor erythroid 2-related factor 2 (Nrf2) activator RTA 408 has a protective effect against diabetic cardiomyopathy. We found that RTA 408 could stimulate the nuclear entry of Nrf2 protein, regulate the mitochondrial fission-fusion balance, and redistribute p65, which significantly alleviated the oxidative stress level in cardiomyocytes, thereby reducing apoptosis and inflammation, and protecting the systolic and diastolic functions of the heart.
Intermittent normobaric hypoxia alters substrate partitioning and muscle oxygenation in individuals with obesity: implications for fat burning
Authors: Costalat Guillaume , Lemaitre Frederic , Ramos Sandra , Renshaw Gillian M. C.
Published: December 2023

This single-blind, crossover study aimed to measure and evaluate the short-term metabolic responses to continuous and intermittent hypoxic patterns in individuals with obesity. Indirect calorimetry was used to quantify changes in resting metabolic rate (RMR), carbohydrate (CHOox, %CHO), and fat oxidation (FATox, %FAT) in nine individuals with obesity pre and post: 1) breathing normoxic air [normoxic sham control (NS-control)], 2) breathing continuous hypoxia (CH), or 3) breathing intermittent hypoxia (IH). A mean peripheral oxygen saturation ([Formula: see text]) of 80–85% was achieved over a total of 45 min of hypoxia. Throughout each intervention, pulmonary gas exchanges, oxygen consumption (V̇o2) carbon dioxide production (V̇co2), and deoxyhemoglobin concentration (Δ[HHb]) in the vastus lateralis were measured. Both RMR and CHOox measured pre- and postinterventions were unchanged following each treatment: NS-control, CH, or IH (all P > 0.05). Conversely, a significant increase in FATox was evident between pre- and post-IH (+44%, P = 0.048). Although the mean Δ[HHb] values significantly increased during both IH and CH ( P < 0.05), the greatest zenith of Δ[HHb] was achieved in IH compared with CH ( P = 0.002). Furthermore, there was a positive correlation between Δ[HHb] and the shift in FATox measured pre- and postintervention. It is suggested that during IH, the increased bouts of muscle hypoxia, revealed by elevated Δ[HHb], coupled with cyclic periods of excess posthypoxia oxygen consumption (EPHOC, inherent to the intermittent pattern) played a significant role in driving the increase in FATox post-IH.
Senescent hearts from male Ts65Dn mice exhibit preserved function but altered size and nicotinamide adenine dinucleotide pathway signaling
Authors: Brandauer Josef , Receno Candace N. , Anyaoku Cynthia , Cooke Lauren E. , Schwarzer Hannalyn M. , DeRuisseau Keith C. , Cunningham Caitlin M. , DeRuisseau Lara R.
Published: December 2023

Down syndrome (DS) is associated with congenital heart defects at birth, but cardiac function has not been assessed at older ages. We used the Ts65Dn mouse, a model of DS, to quantify heart structure and function with echocardiography in 18-mo male Ts65Dn and wild-type (WT) mice. Heart weight, nicotinamide adenine dinucleotide (NAD) signaling, and mitochondrial (citrate synthase) activity were investigated, as these pathways may be implicated in the cardiac pathology of DS. The left ventricle was smaller in Ts65Dn versus WT, as well as the anterior wall thickness of the left ventricle during both diastole (LVAW_d; mm) and systole (LVAW_s; mm) as assessed by echocardiography. Other functional metrics were similar between groups including left ventricular area end systole (mm2), left ventricular area end diastole (mm2), left ventricular diameter end systole (mm), left ventricular diameter end diastole (mm), isovolumetric relaxation time (ms), mitral valve atrial peak velocity (mm/s), mitral valve early peak velocity (mm/s), ratio of atrial and early peak velocities (E/A), heart rate (beats/min), ejection fraction (%), and fractional shortening (%). Nicotinamide phosphoribosyltransferase (NAMPT) protein expression, NAD concentration, and tissue weight were lower in the left ventricle of Ts65Dn versus WT mice. Sirtuin 3 (SIRT3) protein expression and citrate synthase activity were not different between groups. Although cardiac function was generally preserved in male Ts65Dn, the altered heart size and bioenergetic disturbances may contribute to differences in aging for DS.
Input-size dependence of the baroreflex neural arc transfer characteristics during Gaussian white noise inputs
Authors: Kawada Toru , Miyamoto Tadayoshi , Fukumitsu Masafumi , Saku Keita
Published: December 2023

We examined the input-size dependence of the baroreflex neural arc transfer characteristics during Gaussian white noise inputs. A linear dynamic-static nonlinear model yielded higher R2 values compared with a linear model and captured the well-known sigmoidal nonlinearity of the neural arc, indicating that the nonlinear dynamics contributed to determining sympathetic nerve activity. Ignoring such nonlinear dynamics might reduce our ability to explain underlying physiology and significantly limit the interpretation of experimental data.