bluuebunny/crossref_metadata_2025 huggingface dataset:
The thermal control system of NASA’s Curiosity rover: a case study
Authors: Quattrocchi Gaetano , Pittari Andrea , Vedova Matteo D.L. dalla , Maggiore Paolo
Published: February 2022

In any space mission, maintaining subsystems temperature within the allowed limits is a difficult challenge. Parts exposed to the Sun need to be cooled because temperatures rise extremely high, while parts not directly exposed to the Sun need to be heated, because temperatures can drop dramatically. The vacuum does not conduct heat, so the only way to transfer energy is through electromagnetic radiation, generated by the thermal motion of particles in matter. Operating on a planet surface allow convective dissipation and, to a lesser extent, conductive heat dissipation. Furthermore, Mars’ thin atmosphere mitigates the strong temperature gradients that would occur in a vacuum. Nevertheless, external parts of the rover are exposed to temperature ranging between – 123°C - +40°C. In this paper, the thermal control system of NASA’s Curiosity rover will be presented, analyzing the challenges of maintaining suitable operating conditions in Martian environment and the solutions adopted to allow safe operations.
Development of human-derived, three-dimensional respiratory epithelial tissue constructs with perfusable microvasculature on a high-throughput microfluidics screening platform
Authors: Jung Olive , Tung Yen-Ting , Sim Esther , Chen Yu-Chi , Lee Emily , Ferrer Marc , Song Min Jae
Published: February 2022

The COVID-19 pandemic has highlighted the need for human respiratory tract-based assay platforms for efficient discovery and development of antivirals and disease-modulating therapeutics. Physiologically relevant tissue models of the lower respiratory tract (LRT), including the respiratory bronchioles and the alveolar sacs, are of high interest because they are the primary site of severe SARS-CoV-2 infection and are most affected during the terminal stage of COVID-19. Current epithelial lung models used to study respiratory viral infections include lung epithelial cells at the air–liquid interface (ALI) with fibroblasts and endothelial cells, but such models do not have a perfusable microvascular network to investigate both viral infectivity and viral infection-induced thrombotic events. Using a high throughput, 64-chip microfluidic plate-based platform, we have developed two novel vascularized, LRT multi-chip models for the alveoli and the small airway. Both models include a perfusable microvascular network consisting of human primary microvascular endothelial cells, fibroblasts and pericytes. The established biofabrication protocols also enable the formation of differentiated lung epithelial layers at the ALI on top of the vascularized tissue bed. We validated the physiologically relevant cellular composition, architecture and perfusion of the vascularized lung tissue models using fluorescence microscopy, flow cytometry, and electrical resistance measurements. These vascularized, perfusable microfluidic lung tissue on high throughput assay platforms will enable the development of respiratory viral infection and disease models for research investigation and drug discovery.
−808 nm-activated Ca2+ doped up-conversion nanoparticles that release no inducing liver cancer cell (HepG2) apoptosis
Authors: Fa Xinmeng , Lin Shaowei , Yang Jianghua , Shen Chong , Liu Yuanli , Gong Yongyang , Qin Aimiao , Ou Jun , Resch-Genger Ute
Published: February 2022

A near-infrared (NIR) light-triggered release method for nitric oxide (NO) was developed utilizing core/shell NaYF4: Tm/Yb/Ca@NaGdF4: Nd/Yb up-conversion nanoparticles (UCNPs) bearing a mesoporous silica (mSiO2) shell loaded with the NO donor S-nitroso-N-acetyl-DL-penicillamine (SNAP). To avoid overheating in biological samples, Nd3+ was chosen as a sensitizer, Yb3+ ions as the bridging sensitizer, and Tm3+ ions as UV-emissive activator while co-doping with Ca2+ was done to enhance the luminescence of the activator Tm3+. NO release from SNAP was triggered by an NIR-UV up-conversion process, initiated by 808 nm light absorbed by the Nd3+ ions. NO release was confirmed by the Griess method. Under 808 nm irradiation, the viability of the liver cancer cell line HepG2 significantly decreased with increasing UCNPs@mSiO2-SNAP concentration. For a UCNPs@mSiO2-SNAP concentration of 200 μg ml−1, the cell survival probability was 47%. These results demonstrate that UCNPs@mSiO2-SNAP can induce the release of apoptosis-inducing NO by NIR irradiation.
Electrosynthesis of perchlorate using neodymium-doped PbO
2 electrode: application of experimental design methodology for optimization of the effective parameters
Authors: Cheraghveisi Meysam , Maddah Bozorgmehr , Najafi Mostafa
Published: February 2022

In recent decades, extensive research has been done on substrates (i.e., titanium and carbon) with lead dioxide coating to design a cheap anode in electrochemical systems instead of a platinized (Pt) electrode. Various factors can affect the structure and catalytic activity of lead dioxide coating. The most important of them are the type of substrate, how to prepare the substrate for the coating process and the types of lead dioxide additives. In this work, the effective factors in the preparation of the substrate were first investigated. Subsequently, the effect of neodymium as an additive on the catalytic activity of the electrode was studied. We prepared these electrodes and they were first evaluated by scanning electron microscopy (SEM), X-ray diffraction (XRD) spectrometer, voltammetry and electrochemical impedance spectrometer (EIS). The results showed that the potential of water oxidation on the modified

P
b

O

2

electrodes by neodymium was 2 V. Here, we used an electrochemical method to prepare perchlorate. Since the anode potential for perchlorate oxidation is near that for water oxidation, conventional electrodes can’t be used in the perchlorate electrosynthesis. To achieve high production yield in the preparation of perchlorate from chlorate, various parameters including pH, time, and current density were optimized by the Box-Behnken design of the experiment method. The optimal values for this process were obtained at pH = 11, temperature 40 °C and current density of 0.5 mA cm−2. The results at the optimal condition showed that the perchlorate production yield by modified

P
b

O

2

electrodes was 80% in the 300 min. This value was only 60% for the unmodified

P
b

O

2

electrode.
Plasma processing of Fe-P/rGO powder for making robust wear resistance and anticorrosion coating over mild steel
Authors: Debasish Debidutta , Bajpai S , Gochhayat Snigdha , Dash Tapan , Pati Ankeet Rajan , Patra Pranay Kumar , Bhagat A N , Singh Saroj Kumar , Rout Tapan Kumar
Published: February 2022

Phosphating is a widely used metal pre-treatment process due to its ability to improvise pitting corrosion resistance, wear-resistance, and adherence properties. In the present investigation, we report the manufacturing of spray grade powder of Fe-P metal ingot by mechanical hammering, milling and sieving process. The Fe-P powder and its blending with reduced graphene oxide (rGO) (2 and 4 vol%) were successfully coated over mild steel by the thermal plasma spray method for thefirst time. Successful retention of rGO was observed even after thermal plasma spraying of Fe-P/rGO (2 vol% and 4 vol%), which was challenging and yet to be reported. The morphological investigation of the top-coat layer and cross-section was analysed using a field emission scanning electron microscope (FESEM). The presence of G, D and 2D bands at 1580 cm−1, 1350 cm−1, and 2700 cm−1,respectively in the Raman spectra were the straightforward demonstration of the retention of rGO. Hardness and air-jet erosion tests were performed to evaluate mechanical properties in view of exploring commercial applications of such coatings. We found that Fe-P-rGO composite coatings exhibited improved hardness, erosion, and corrosion resistance properties with increasing reduced graphene oxide content.
Conductive polypyrrole-coated electrospun chitosan nanoparticles/poly(D,L-lactide) fibrous mat: influence of drug delivery and Schwann cells proliferation
Authors: Li Siqi , Yu Xiaoling , Li Yuan , Zhang Tian
Published: February 2022

For nerve tissue engineering (NTE), scaffolds with the ability to release drugs under control and support the rapid proliferation of cells are very important for the repair of nerve defects. This study aimed to fabricate a conductive drug-loaded fiber mat by electrospinning and assess its potential as a scaffold for Schwann cells proliferation. The conductive polypyrrole (PPy) was coated on an electrospun poly (D, L-lactide) (PLA) fibrous mat, which was simultaneously embedded with protein-loaded chitosan nanoparticles and ibuprofen as a model small molecule drug. The fibrous mat shows suitable conductivity, mechanical properties, and hydrophilicity for NTE. For drug release and degradation studies, the fibrous mat can achieve sustained release of bovine serum albumin (BSA) and ibuprofen, and the PPy coating can increase the surface wettability and conductivity while slowing down the degradation of the fibrous mat. The application of electrical stimulation (ES) to the fibrous mat can accelerate the release of ibuprofen, but there was no significant effect on the release rate of the protein. The fibrous mat showed no cytotoxicity in vitro, and Schwann cells (SCs) can adhere, grow, and proliferate well on mats. At the 120th hour of culture in vitro, the relative growth rate of SCs on the conductive drug-loaded fibrous mat reached 198.22 ± 2.34%, which was an increase of 37.93% compared to the SCs on the drug-loaded fibrous mat with ES. The density and elongation of SCs on the conductive drug-loaded fibrous mat were greater than those on the PLA fibrous mat, indicating that the conductive polypyrrole-coated electrospun chitosan nanoparticles/PLA fibrous mat has good potential for application in nerve regeneration.
HyMM: hybrid method for disease-gene prediction by integrating multiscale module structure
Authors: Xiang Ju , Meng Xiangmao , Zhao Yichao , Wu Fang-Xiang , Li Min
Published: February 2022

Motivation

Identifying disease-related genes is an important issue in computational biology. Module structure widely exists in biomolecule networks, and complex diseases are usually thought to be caused by perturbations of local neighborhoods in the networks, which can provide useful insights for the study of disease-related genes. However, the mining and effective utilization of the module structure is still challenging in such issues as a disease gene prediction.

Results

We propose a hybrid disease-gene prediction method integrating multiscale module structure (HyMM), which can utilize multiscale information from local to global structure to more effectively predict disease-related genes. HyMM extracts module partitions from local to global scales by multiscale modularity optimization with exponential sampling, and estimates the disease relatedness of genes in partitions by the abundance of disease-related genes within modules. Then, a probabilistic model for integration of gene rankings is designed in order to integrate multiple predictions derived from multiscale module partitions and network propagation, and a parameter estimation strategy based on functional information is proposed to further enhance HyMM’s predictive power. By a series of experiments, we reveal the importance of module partitions at different scales, and verify the stable and good performance of HyMM compared with eight other state-of-the-arts and its further performance improvement derived from the parameter estimation.

Conclusions

The results confirm that HyMM is an effective framework for integrating multiscale module structure to enhance the ability to predict disease-related genes, which may provide useful insights for the study of the multiscale module structure and its application in such issues as a disease-gene prediction.
ACTIVA: realistic single-cell RNA-seq generation with automatic cell-type identification using introspective variational autoencoders
Authors: Heydari A Ali , Davalos Oscar A , Zhao Lihong , Hoyer Katrina K , Sindi Suzanne S
Published: February 2022

Motivation

Single-cell RNA sequencing (scRNAseq) technologies allow for measurements of gene expression at a single-cell resolution. This provides researchers with a tremendous advantage for detecting heterogeneity, delineating cellular maps or identifying rare subpopulations. However, a critical complication remains: the low number of single-cell observations due to limitations by rarity of subpopulation, tissue degradation or cost. This absence of sufficient data may cause inaccuracy or irreproducibility of downstream analysis. In this work, we present Automated Cell-Type-informed Introspective Variational Autoencoder (ACTIVA): a novel framework for generating realistic synthetic data using a single-stream adversarial variational autoencoder conditioned with cell-type information. Within a single framework, ACTIVA can enlarge existing datasets and generate specific subpopulations on demand, as opposed to two separate models [such as single-cell GAN (scGAN) and conditional scGAN (cscGAN)]. Data generation and augmentation with ACTIVA can enhance scRNAseq pipelines and analysis, such as benchmarking new algorithms, studying the accuracy of classifiers and detecting marker genes. ACTIVA will facilitate analysis of smaller datasets, potentially reducing the number of patients and animals necessary in initial studies.

Results

We train and evaluate models on multiple public scRNAseq datasets. In comparison to GAN-based models (scGAN and cscGAN), we demonstrate that ACTIVA generates cells that are more realistic and harder for classifiers to identify as synthetic which also have better pair-wise correlation between genes. Data augmentation with ACTIVA significantly improves classification of rare subtypes (more than 45% improvement compared with not augmenting and 4% better than cscGAN) all while reducing run-time by an order of magnitude in comparison to both models.

Availability and implementation

The codes and datasets are hosted on Zenodo (https://doi.org/10.5281/zenodo.5879639). Tutorials are available at https://github.com/SindiLab/ACTIVA.

Supplementary information

Supplementary data are available at Bioinformatics online.
CNGPLD: case–control copy-number analysis using Gaussian process latent difference
Authors: Shih David J H , Li Ruoxing , Müller Peter , Zheng W Jim , Do Kim-Anh , Lin Shiaw-Yih , Carter Scott L
Published: February 2022

Motivation

Cross-sectional analyses of primary cancer genomes have identified regions of recurrent somatic copy-number alteration, many of which result from positive selection during cancer formation and contain driver genes. However, no effective approach exists for identifying genomic loci under significantly different degrees of selection in cancers of different subtypes, anatomic sites or disease stages.

Results

CNGPLD is a new tool for performing case–control somatic copy-number analysis that facilitates the discovery of differentially amplified or deleted copy-number aberrations in a case group of cancer compared with a control group of cancer. This tool uses a Gaussian process statistical framework in order to account for the covariance structure of copy-number data along genomic coordinates and to control the false discovery rate at the region level.

Availability and implementation

CNGPLD is freely available at https://bitbucket.org/djhshih/cngpld as an R package.

Supplementary information

Supplementary data are available at Bioinformatics online.
Fast and accurate gene regulatory network inference by normalized least squares regression
Authors: Hillerton Thomas , Seçilmiş Deniz , Nelander Sven , Sonnhammer Erik L L
Published: February 2022

Motivation

Inferring an accurate gene regulatory network (GRN) has long been a key goal in the field of systems biology. To do this, it is important to find a suitable balance between the maximum number of true positive and the minimum number of false-positive interactions. Another key feature is that the inference method can handle the large size of modern experimental data, meaning the method needs to be both fast and accurate. The Least Squares Cut-Off (LSCO) method can fulfill both these criteria, however as it is based on least squares it is vulnerable to known issues of amplifying extreme values, small or large. In GRN this manifests itself with genes that are erroneously hyper-connected to a large fraction of all genes due to extremely low value fold changes.

Results

We developed a GRN inference method called Least Squares Cut-Off with Normalization (LSCON) that tackles this problem. LSCON extends the LSCO algorithm by regularization to avoid hyper-connected genes and thereby reduce false positives. The regularization used is based on normalization, which removes effects of extreme values on the fit. We benchmarked LSCON and compared it to Genie3, LASSO, LSCO and Ridge regression, in terms of accuracy, speed and tendency to predict hyper-connected genes. The results show that LSCON achieves better or equal accuracy compared to LASSO, the best existing method, especially for data with extreme values. Thanks to the speed of least squares regression, LSCON does this an order of magnitude faster than LASSO.

Availability and implementation

Data: https://bitbucket.org/sonnhammergrni/lscon; Code: https://bitbucket.org/sonnhammergrni/genespider.

Supplementary information

Supplementary data are available at Bioinformatics online.
NeuCA web server: a neural network-based cell annotation tool with web-app and GUI
Authors: Duan Daoyu , He Sijia , Huang Emina , Li Ziyi , Feng Hao
Published: February 2022

Correctly annotating individual cell’s type is an important initial step in single-cell RNA sequencing (scRNA-seq) data analysis. Here, we present NeuCA web server, a neural network-based scRNA-seq cell annotation tool with web-app portal and graphical user interface, for automatically assigning cell labels. NeuCA algorithm is accurate and exhaustive, maximizing the usage of measured cells for downstream analysis. NeuCA web server provides over 20 ready-to-use pre-trained classifiers for commonly used tissue types. As the first web-app tool with neural-network infrastructure implemented, NeuCA web will facilitate the research community in analyzing and annotating scRNA-seq data.

Availability and implementation

NeuCA web server is implemented with R Shiny application online at https://statbioinfo.shinyapps.io/NeuCA/.

Supplementary information

Supplementary data are available at Bioinformatics online.
Neural decoding of emotional prosody in voice-sensitive auditory cortex predicts social communication abilities in children
Authors: Leipold Simon , Abrams Daniel A , Karraker Shelby , Menon Vinod
Published: February 2022

During social interactions, speakers signal information about their emotional state through their voice, which is known as emotional prosody. Little is known regarding the precise brain systems underlying emotional prosody decoding in children and whether accurate neural decoding of these vocal cues is linked to social skills. Here, we address critical gaps in the developmental literature by investigating neural representations of prosody and their links to behavior in children. Multivariate pattern analysis revealed that representations in the bilateral middle and posterior superior temporal sulcus (STS) divisions of voice-sensitive auditory cortex decode emotional prosody information in children. Crucially, emotional prosody decoding in middle STS was correlated with standardized measures of social communication abilities; more accurate decoding of prosody stimuli in the STS was predictive of greater social communication abilities in children. Moreover, social communication abilities were specifically related to decoding sadness, highlighting the importance of tuning in to negative emotional vocal cues for strengthening social responsiveness and functioning. Findings bridge an important theoretical gap by showing that the ability of the voice-sensitive cortex to detect emotional cues in speech is predictive of a child’s social skills, including the ability to relate and interact with others.
Characteristics of Persons Treated for Hepatitis C Using National Pharmacy Claims Data, United States, 2014–2020
Authors: Teshale Eyasu H , Roberts Henry , Gupta Neil , Jiles Ruth
Published: February 2022

Using national pharmacy claims data for 2014–2020, 843 329 persons were treated for hepatitis C at least once. The proportion treated increased annually among persons aged <40 years, insured by Medicaid, and treated by primary care providers. Monitoring hepatitis C treatment is essential to identify barriers to treatment access.
Evaluating the predictive accuracy of curated biological pathways in a public knowledgebase
Authors: Wright Adam J , Orlic-Milacic Marija , Rothfels Karen , Weiser Joel , Trinh Quang M , Jassal Bijay , Haw Robin A , Stein Lincoln D
Published: February 2022

Reactome is a database of human biological pathways manually curated from the primary literature and peer-reviewed by experts. To evaluate the utility of Reactome pathways for predicting functional consequences of genetic perturbations, we compared predictions of perturbation effects based on Reactome pathways against published empirical observations. Ten cancer-relevant Reactome pathways, representing diverse biological processes such as signal transduction, cell division, DNA repair and transcriptional regulation, were selected for testing. For each pathway, root input nodes and key pathway outputs were defined. We then used pathway-diagram-derived logic graphs to predict, either by inspection by biocurators or using a novel algorithm MP-BioPath, the effects of bidirectional perturbations (upregulation/activation or downregulation/inhibition) of single root inputs on the status of key outputs. These predictions were then compared to published empirical tests. In total, 4968 test cases were analyzed across 10 pathways, of which 847 were supported by published empirical findings. Out of the 847 test cases, curators’ predictions agreed with the experimental evidence in 670 and disagreed in 177 cases, resulting in ∼81% overall accuracy. MP-BioPath predictions agreed with experimental evidence for 625 and disagreed for 222 test cases, resulting in ∼75% overall accuracy. The expected accuracy of random guessing was 33%. Per-pathway accuracy did not correlate with the number of pathway edges nor the number of pathway nodes but varied across pathways, ranging from 56% (curator)/44% (MP-BioPath) for ‘Mitotic G1 phase and G1/S transition’ to 100% (curator)/94% (MP-BioPath) for ‘RAF/MAP kinase cascade’. This study highlights the potential of pathway databases such as Reactome in modeling genetic perturbations, promoting standardization of experimental pathway activity readout and supporting hypothesis-driven research by revealing relationships between pathway inputs and outputs that have not yet been directly experimentally tested.

Database URL

www.reactome.org
Proximate larval epidermal cell layer generates forces for Pupal thorax closure in Drosophila
Authors: Athilingam Thamarailingam , Parihar Saurabh S , Bhattacharya Rachita , Rizvi Mohd S , Kumar Amit , Sinha Pradip
Published: February 2022

During tissue closures, such as embryonic dorsal closure in Drosophila melanogaster, a proximate extra-embryonic layer, amnioserosa, generates forces that drive migration of the flanking lateral embryonic epidermis, thereby zip-shutting the embryo. Arguably, this paradigm of tissue closure is also recapitulated in mammalian wound healing wherein proximate fibroblasts transform into contractile myofibroblasts, develop cell junctions, and form a tissue layer de novo: contraction of the latter then aids in wound closure. Given this parallelism between disparate exemplars, we posit a general principle of tissue closure via proximate cell layer-generated forces. Here, we have tested this hypothesis in pupal thorax closure wherein 2 halves of the presumptive adult thorax of Drosophila, the contralateral heminotal epithelia, migrate over an underlying larval epidermal cell layer. We show that the proximate larval epidermal cell layer promotes thorax closure by its active contraction, orchestrated by its elaborate actomyosin network-driven epithelial cell dynamics, cell delamination, and death—the latter being prefigured by the activation of caspases. Larval epidermal cell dynamics generate contraction forces, which when relayed to the flanking heminota—via their mutual integrin-based adhesions—mediate thorax closure. Compromising any of these contraction force-generating mechanisms in the larval epidermal cell layer slows down heminotal migration, while loss of its relay to the flanking heminota abrogates the thorax closure altogether. Mathematical modeling further reconciles the biophysical underpinning of this emergent mechanism of thorax closure. Revealing mechanism of thorax closure apart, these findings show conservation of an essential principle of a proximate cell layer-driven tissue closure.
A Fat-Promoting Botanical Extract From Artemisia scoparia Exerts Geroprotective Effects on Caenorhabditis elegans Life Span and Stress Resistance
Authors: Ghosh Bhaswati , Guidry Hayden J , Johnston Maxwell , Bohnert K Adam
Published: February 2022

Like other biological processes, aging is not random but subject to molecular control. Natural products that modify core metabolic parameters, including fat content, may provide entry points to extend animal life span and promote healthy aging. Here, we show that a botanical extract from Artemisia scoparia (SCO), which promotes fat storage and metabolic resiliency in mice, extends the life span of the nematode Caenorhabditis elegans by up to 40%. Notably, this life-span extension depends significantly on SCO’s effects on fat; SCO-treated worms exhibit heightened levels of unsaturated fat, and inhibition of Δ9 desaturases, which oversee biosynthesis of monounsaturated fatty acids, prevents SCO-dependent fat accumulation and life-span extension. At an upstream signaling level, SCO prompts changes to C. elegans fat regulation by stimulating nuclear translocation of transcription factor DAF-16/FOXO, an event that requires AMP-activated protein kinase under this condition. Importantly, animals treated with SCO are not only long-lived but also show improved stress resistance in late adulthood, suggesting that this fat-promoting intervention may enhance some aspects of physiological health in older age. These findings identify SCO as a natural product that can modify fat regulation for longevity benefit and add to growing evidence indicating that elevated fat can be prolongevity in some circumstances.
How is inclusiveness in health systems research priority-setting affected when community organizations lead the process?
Authors: Pratt Bridget , Srinivas Prashanth N , Seshadri Tanya
Published: February 2022

Community engagement is gaining prominence in health research. But communities rarely have a say in the agendas or conduct of the very health research projects that aim to help them. One way thought to achieve greater inclusion for communities throughout health research projects, including during priority-setting, is for researchers to partner with community organizations (COs). This paper provides initial empirical evidence as to the complexities such partnerships bring to priority-setting practice. Case study research was undertaken on a three-stage CO-led priority-setting process for health systems research. The CO was the Zilla Budakattu Girijana Abhivrudhhi Sangha, a district-level community development organization representing the Soliga people in Karnataka, India. Data on the priority-setting process were collected in 2018 and 2019 through in-depth interviews with researchers, Sangha leaders and field investigators from the Soliga community who collected data as part of the priority-setting process. Direct observation and document collection were also performed, and data from all three sources were thematically analysed. The case study demonstrates that, when COs lead health research priority-setting, their strengths and weaknesses in terms of representation and voice will affect inclusion at each stage of the priority-setting process. CO strengths can deepen inclusion by the CO and its wider community. CO weaknesses can create limitations for inclusion if not mitigated, exacerbating or reinforcing the very hierarchies that impede the achievement of improved health outcomes, e.g. exclusion of women in decision-making processes related to their health. Based on these findings, recommendations are made to support the achievement of inclusive CO-led health research priority-setting processes.
Fully discrete best-approximation-type estimates inL∞ (I;L2(Ω)d) for finite element discretizations of the transient Stokes equations
Authors: Behringer Niklas , Vexler Boris , Leykekhman Dmitriy
Published: February 2022

In this article, we obtain an optimal best-approximation-type result for fully discrete approximations of the transient Stokes problem. For the time discretization, we use the discontinuous Galerkin method and for the spatial discretization we use standard finite elements for the Stokes problem satisfying the discrete inf-sup condition. The analysis uses the technique of discrete maximal parabolic regularity. The results require only natural assumptions on the data and do not assume any additional smoothness of the solutions.
Ivermectin for the prevention of COVID-19: addressing potential bias and medical fraud
Authors: Hill Andrew , Mirchandani Manya , Ellis Leah , Pilkington Victoria
Published: February 2022

Background

Ivermectin is an antiparasitic drug being investigated in clinical trials for the prevention of COVID-19. However, there are concerns about the quality of some of these trials.

Objectives

To conduct a meta-analysis with randomized controlled trials of ivermectin for the prevention of COVID-19, while controlling for the quality of data. The primary outcome was RT–PCR-confirmed COVID-19 infection. The secondary outcome was rate of symptomatic COVID-19 infection.

Methods

We conducted a subgroup analysis based on the quality of randomized controlled trials evaluating ivermectin for the prevention of COVID-19. Quality was assessed using the Cochrane risk of bias measures (RoB 2) and additional checks on raw data, where possible.

Results

Four studies were included in the meta-analysis. One was rated as being potentially fraudulent, two as having a high risk of bias and one as having some concerns for bias. Ivermectin did not have a significant effect on preventing RT–PCR-confirmed COVID-19 infection. Ivermectin had a significant effect on preventing symptomatic COVID-19 infection in one trial with some concerns of bias, but this result was based on post hoc analysis of a multi-arm study.

Conclusions

In this meta-analysis, the use of ivermectin was not associated with the prevention of RT–PCR-confirmed or symptomatic COVID-19. The currently available randomized trials evaluating ivermectin for the prevention of COVID-19 are insufficient and of poor quality.
Working With Fire Departments to Adapt and Implement Evidence-Based Programs That Increase Uptake of Smoke Alarms: A Case-Series Report
Authors: Omaki Elise , Shields Wendy , Buhs Sarah , Curtis Michael , Kulak Dawn , Luna Joe , Frattaroli Shannon
Published: February 2022

We describe a partnership between an academic injury center and three U.S. fire departments to adapt and implement strategies for promoting smoke alarm programs. Each fire department identified the aims and parameters for a new promotion campaign for their smoke alarm programs. Promotion was directed toward residents in each department’s catchment area who were eligible for the smoke alarm program. All three departments independently elected to use an automated telephone message to promote their smoke alarm programs. Uptake of smoke alarm installation services ranged between 0.02% and 2% of the calls placed. In Rochester, automated calls were sent to all residential landlines via the city’s nonemergency call center; requests for smoke alarms increased by a factor of 7.5 in the month following the campaign. In Grand Rapids, automated calls were sent to 6% of the households served due to the telecommunications infrastructure; because of the limited reach, the overall number of requests remained unchanged, and the number of callers citing the automated calls was less than the number of requests callers reported were motivated by Grand Rapids’ existing promotion strategies. In Cloquet, the automated calls were broadcast on a rolling basis to geographic clusters of households; although the number of requests remained unchanged, fire district officials were pleased to reduce driving time between appointments which allowed volunteers to offer more home visit appointments. Automated telephone calls can be a valuable tool for promoting smoke alarm programs, but fire departments should carefully identify how dissemination strategies can best complement existing program efforts.
Term Structure, Forecast Revision, and the Signaling Channel of Monetary Policy
Authors: Zhang Donghai
Published: February 2022

Monetary policy shocks affect interest rates at long horizons (10 years or more). Furthermore, the private sectorâs real GDP forecasts are revised upward in response to a monetary tightening. These facts challenge the prevailing theories in academic and policy circles. In this paper, I propose a micro-founded model to rationalize those facts, based on the signaling channel of monetary policy. I consider a framework where the central bank has private information about future economic conditions. Agents update their beliefs according to Bayes’ theorem. Policy actions play a signaling role, and may therefore rationalize the above empirical findings.
Iran’s Arbitrary Detention of Foreign and Dual Nationals as Hostage-taking and Crimes Against Humanity
Authors: Ferstman Carla , Sharpe Marina
Published: February 2022

This article examines, within the frame of international criminal law, Iran’s arbitrary detention of foreign and dual nationals for leverage over the detainee’s (other) country of nationality. It provides an overview of Iran’s pattern of conduct since 2010, involving at least 66 victims, and analyses this in terms of hostage-taking and crimes against humanity. First, we argue that Iran’s pattern of conduct constitutes hostage-taking within the meaning of the International Convention Against the Taking of Hostages. This gives rise to Iran’s international responsibility for the breaches concerned and has important implications for victims’ and their loved ones’ perceptions of their experiences. Second, we assess the context elements of the definition of crimes against humanity as well as the gravity threshold and the compatibility of the pattern of conduct with the requisite elements of the relevant underlying offences: imprisonment or other severe deprivation of physical liberty, torture, and persecution. We conclude that the actions of certain Iranian officials reasonably satisfy the requirements for crimes against humanity. This is legally important for the application of crimes against humanity jurisprudence to this new context. It also opens avenues of accountability, given the aut dedere aut judicare provisions for crimes against humanity enacted by many states and the growth of sanctions legislation in several states. It should be difficult for responsible officials to travel outside Iran for fear of arrest and sanction.
Filtering non-balanced data using an evolutionary approach
Authors: Carballido Jessica A , Ponzoni Ignacio , Cecchini Rocío L
Published: February 2022

Matrices that cannot be handled using conventional clustering, regression or classification methods are often found in every big data research area. In particular, datasets with thousands or millions of rows and less than a hundred columns regularly appear in biological so-called omic problems. The effectiveness of conventional data analysis approaches is hampered by this matrix structure, which necessitates some means of reduction. An evolutionary method called PreCLAS is presented in this article. Its main objective is to find a submatrix with fewer rows that exhibits some group structure. Three stages of experiments were performed. First, a benchmark dataset was used to assess the correct functionality of the method for clustering purposes. Then, a microarray gene expression data matrix was used to analyze the method’s performance in a simple classification scenario, where differential expression was carried out. Finally, several classification methods were compared in terms of classification accuracy using an RNA-seq gene expression dataset. Experiments showed that the new evolutionary technique significantly reduces the number of rows in the matrix and intelligently performs unsupervised row selection, improving classification and clustering methods.
Design and implementation of parallel self-adaptive differential evolution for global optimization
Authors: Fister Iztok , Iglesias Andres , Galvez Akemi , Fister DuŠan , Fister Iztok
Published: February 2022

The results of evolutionary algorithms depend on population diversity that normally decreases by increasing the selection pressure from generation to generation. Usually, this can lead the evolution process to get stuck in local optima. This study is focused on mechanisms to avoid this undesired phenomenon by introducing parallel self-adapted differential evolution that decomposes a monolithic population into more variable-sized sub-populations and combining this with the characteristics of evolutionary multi-agent systems into a hybrid algorithm. The proposed hybrid algorithm operates with individuals having some characteristics of agents, e.g. they act autonomously by selecting actions, with which they affect the state of the environment. Additionally, this algorithm incorporates two additional mechanisms: ageing and adaptive population growth, which help the individuals by decision-making. The proposed parallel differential evolution was applied to the CEC’18 benchmark function suite, while the produced results were compared with some traditional stochastic nature-inspired population-based and state-of-the-art algorithms.
Reforming the countermeasures injury compensation program for COVID-19 and beyond: An economic perspective
Authors: Zhao Junying , Demir Firat , Ghosh Pallab K , Earley Austin , Kim Myongjin
Published: February 2022

As of Aug. 2, 2021, 1693 injury claims associated with COVID-19 medical countermeasures have been filed in the Countermeasures Injury Compensation Program (CICP), of which 686 claims were related to COVID-19 vaccines and urgently needed compensation decisions. However, from an economic and public policy perspective, we find that the CICP design has unintended consequences: locating CICP in the executive agency DHHS potentially creates a conflict of interest, and not permitting judicial review generates a lack of checks and balances, both of which could jeopardize justice. These fundamental problems would subsequently weaken four key performance indicators of CICP compared with its judicial counterpart in the Court of Federal Claims. CICP lacks accountability, transparency, and cost-effectiveness efficiency, with 94% of its total costs spent on administration rather than compensation. CICP’s ability to compensate is also questionable. If COVID-19 claims were compensated at its historical rate, CICP would face around $21.16 million in compensation outlays and $317.94 million in total outlays, 72.1 times its current balance. To ensure just compensation for injured petitioners during COVID-19 and future public health emergencies, we recommend Congress (1) initiate a major reform by relocating CICP from DHHS to the Claims Court or (2) keep CICP within DHHS and make incremental changes by permitting judicial review of DHHS administrative adjudication of CICP claims. We further recommend Congress audit and adjust budgets for CICP and DHHS promptly propose an injury table for COVID-19 claims. This is the first study that contributes an economic perspective to the limited literature on CICP and also provides unique and rich economic data.
Cancer-Related Care Costs and Employment Disruption: Recommendations to Reduce Patient Economic Burden as Part of Cancer Care Delivery
Authors: de Moor Janet S , Williams Courtney P , Blinder Victoria S
Published: February 2022

Cancer survivors are frequently unprepared to manage the out-of-pocket (OOP) costs associated with undergoing cancer treatment and the potential for employment disruption. This commentary outlines a set of research recommendations stemming from the National Cancer Institute’s Future of Health Economics Research Conference to better understand and reduce patient economic burden as part of cancer care delivery. Currently, there are a lack of detailed metrics and measures of survivors’ OOP costs and employment disruption, and data on these costs are rarely available at the point of care to guide patient-centered treatment and survivorship care planning. Future research should improve the collection of data about survivors’ OOP costs for medical care, other cancer-related expenses, and experiences of employment disruption. Methods such as microcosting and the prospective collection of patient-reported outcomes in cancer care are needed to understand the true sum of cancer-related costs taken on by survivors and caregivers. Better metrics and measures of survivors’ costs must be coupled with interventions to incorporate that information into cancer care delivery and inform meaningful communication about OOP costs and employment disruption that is tailored to different clinical situations. Informing survivors about the anticipated costs of their cancer care supports informed decision making and proactive planning to mitigate financial hardship. Additionally, system-level infrastructure should be developed and tested to facilitate screening to identify survivors at risk for financial hardship, improve communication about OOP costs and employment disruption between survivors and their health-care providers, and support the delivery of appropriate financial navigation services.
Identifying importation points of the SARS-CoV-2 Omicron variant into the USA and potential locations of early domestic spread and impact
Authors: Au Natalie H , Thomas-Bachli Andrea , Forsyth Jack , Demarsh P Alex , Huber Carmen , Bogoch Isaac I , Khan Kamran
Published: February 2022

Highlight: We identified the US airports and metropolitan areas, particularly New York City, Miami and Los Angeles, that were the most likely locations of importation and domestic spread of Omicron from South Africa. Vaccination coverage suggested that several cities in GA, TX and UT were particularly vulnerable to public health impacts.
Data from public and governmental databases show that a large proportion of the regional animal species pool occur in cities in Germany
Authors: Sweet Fabio S T , Apfelbeck Beate , Hanusch Maximilian , Garland Monteagudo Cynthia , Weisser Wolfgang W
Published: February 2022

Cities have been shown to be biodiverse, but it is unclear what fraction of a regional species pool can live within city borders and how this differs between taxa. Among animals, most research has focused on a few well-studied taxa, such as birds or butterflies. For other species, progress is limited by the paucity of data. We used species occurrence data for 11 taxa and 23 German cities from the Global Biodiversity Information Facility (GBIF) and the different German states, in a 50-km buffer around the city centre, to investigate what proportion of species of the regional species pools also occur in cities. While data could be obtained for all cities from GBIF, state databases only provided data for a subset of cities. Sample coverage of data from GBIF was higher across all taxa than of the state databases. For each database and taxon, we analysed (i) all cities where the number of occurrences of a taxon was >50 and (ii) only those cities where additionally sample coverage was >0.85. Across all taxa studied on average, 44.9 ± 7.2% (GBIF) and 40.8 ± 9.6% (German states) of the species of the regional species pool were also found in cities. When all cities were considered together, more than 76% of all species occurred within city borders. Our results show that German cities harbour a large part of the regional diversity of different taxa when city borders rather than the city centre is considered. This opens up ample opportunities for conservation and for fostering human–nature relationships.
The role of migration in enhancing resilience to climate change
Authors: Entzinger Han , Scholten Peter
Published: February 2022

Migration out of areas affected by climate change has long been considered a common adaptation strategy. More recent studies, however, claim that migration should not exclusively be seen as an escape from areas under threat, but that it can also be understood as a powerful strategy towards change and innovation in those areas. This article examines the relationship between environmental stress and migration in the Vietnamese Mekong River Delta, one of the global hotspots of climate change. Based on an extensive survey among households and interviews with key actors, our study shows that indeed environmental stress is an important factor—though not the only one—behind the development of migration corridors, particularly to Ho Chi Minh City. Low-income households are more likely to have experienced migration than high-income ones. Low-income households also account for the largest group of recipients of financial remittances, which are mainly spent on basic household needs and health care, and not on longer-term investments. Our research also shows the important role of non-financial remittances in supporting climate resilience among vulnerable (low-income) households. Actually, in the Mekong Delta case, the transfer of knowledge and skills proves to be more prominent than the sending of cash. Such skills are brought along by returning migrants, and then passed on to others, leading to a diversification of local economies so that these become more resilient to environmental degradation.
Verification of atomic data for solar oxygen abundance models
Authors: Nahar Sultana N
Published: February 2022

Recently, Bergemann et al. reported a re-analysis of O i lines, 777 and 630 nm, using their new atomic models of O and Ni, and presented solar photospheric oxygen abundance differing from others. We discuss the accuracy of atomic data employed in their models, and demonstrate that the photoionization cross-sections (σPI) of the two levels ${\rm1s^22s^22p^33s (^5S^o_2)}$ and 1s22s22p33p(5P1), which they present as illustrations of their data in the non-local-thermodynamic-equilibrium (NLTE) model, are incorrect by large factors. For example, their σPI at the threshold of level ${\rm ^5S^o_2}$ is larger by a factor of 1000 than that of Nahar and the Opacity Project data base, TOPbase, and has an incorrect energy behaviour. They included a blending of the 630 nm line with N i for which they computed σPI in the hydrogenic approximation. The approximation does not include electron–electron interaction and hence is not valid for Ni i. They noted that the use of oscillator strengths of O i by Hibbert et al., which agree very well with TOPbase and Nahar, gave an abundance close to the existing values, but reported using averaged values of two sources. Therefore, their oxygen abundance from the new atomic models is likely to be in question.