bluuebunny/crossref_metadata_2025 huggingface dataset:
Describing biodiversity in the genomics era: A new species of Nearctic Cynipidae gall wasp and its genome
Authors: Brandão‐Dias Pedro F. P. , Zhang Yuanmeng Miles , Pirro Stacy , Vinson Camila C. , Weinersmith Kelly L. , Ward Anna K. G. , Forbes Andrew A. , Egan Scott P.
Published: January 2022

Gall wasps (Hymenoptera: Cynipidae) specializing on live oaks in the genus Quercus (subsection Virentes) are a relatively diverse and well‐studied community with 14 species described to date, albeit with incomplete information on their biology, life history and genetic structure. Incorporating an integrative taxonomic approach, we combine morphology, phenology, behaviour, genetics and genomics to describe a new species, Neuroterus valhalla sp. nov. The alternating generations of this species induce galls on the catkins and stem nodes of Quercus virginiana and Quercus geminata in the southern United States. We describe both generations in the species' life cycle, and primarily use samples from a population in the centre of Houston, Texas, thus serving as an example of the undescribed biodiversity still present in well‐travelled urban centres. In parallel, we present a draft assembly of the N. valhalla genome providing a direct link between the type specimen and reference genome. The genome of N. valhalla is the smallest reported to date within the tribe Cynipini, providing an important comparative contrast to the otherwise large genome size of cynipids. While relatively small, the genome was found to be composed of >64% repetitive elements, including 43% unclassified repeats and 11% retrotransposons. A preliminary ab initio and homology‐based annotation revealed 32,005 genes, and a subsequent orthogroup analysis grouped 18,044 of these to 8186 orthogroups, with some evidence for high levels of gene duplications within Cynipidae. A mitochondrial barcode phylogeny linked each generation of the new species and a phylogenomic ultraconserved element (UCEs) phylogeny indicates that the new species groups with other Nearctic Neuroterus. However, both phylogenies present the genus Neuroterus in North America as polyphyletic.
A TASTE FOR THE INFINITE: WHAT PHILOSOPHY OF BIOLOGY CAN TELL US ABOUT RELIGIOUS BELIEF
Authors: De Cruz Helen
Published: January 2022

According to Friedrich Schleiermacher, religiosity is rooted in feeling (Gefühl). As a result of our engagement with the world, on which we depend and which we can influence, we have both a sense of dependence and of freedom. Schleiermacher speculated that a sense of absolute dependence in reflective beings with self‐consciousness (human beings) gave rise to religion. Using insights from contemporary philosophy of biology and cognitive science, I seek to naturalize Schleiermacher's ideas. I moreover show that this naturalization is in line with Schleiermacher's outlook on biology, as he already had evolutionary considerations in mind when he wrote the Christian Faith (1830). While Schleiermacher rejects natural theology in a narrow sense (proofs for the existence of God), his project is natural theological in a broader sense, as it roots religion in experiences that we can examine using naturalistic theories.
THE TERRITORIES OF THINKING AND FEELING: RETHINKING RELIGION, SCIENCE, AND REASON WITH ALISTER McGRATH
Authors: Schaefer Donovan O.
Published: January 2022

As Alister McGrath has argued across a lifetime of work, we need to approach the binaries that have been handed down to us—personal/academic, emotional/intellectual, secular/religious—with a healthy skepticism toward the integrity of their boundaries, attending instead to the contact zones between them. This article connects McGrath's body of work to what I call “cogency theory,” an approach that rejects the thinking/feeling binary itself. It begins with a survey of how McGrath understands rationality—not only as multiple, but as defined, in meaningful ways, by feeling. This is illustrated by reexamining McGrath's controversy with Richard Dawkins, analyzing their debate in terms of how the argument itself comes to feel. This new paradigm allows us to supersede petty antagonisms built into contemporary culture—like the presumed science–religion conflict—and refocus on overarching concerns like the climate crisis. The article concludes with a question about the extent to which beliefs and “worldviews” define how we—either as groups or individuals—can make or unmake ecological disaster.
Development of a Simplified Pressurized Water Reactor Fuel Assembly Nonlinear Model
Authors: Park Namgyu , Yoo Youngik , Kim Taesoon , Jeon Sangyoun
Published: January 2022

This paper proposes a computation technique to develop a simplified nonlinear model for a typical nuclear fuel assembly. Because more than a hundred fuel assemblies are packed in the reactor, simplistic model generation is critical to evaluate the motion during an anticipated event such as earthquake. Two straight beams are introduced to simplify the fuel assembly, and the beam properties are moderately defined to represent the skeleton structure and a bundle of slender fuel rods. Because nonlinearity is caused by the interaction between the rods and the spacer grids in the skeleton structure, the two beams are connected with multilinear joints that characterize the mechanical interaction between them. An equation of motion for the model is provided, and the degree of the freedom of the model can be reduced by using a few major modes of the beams. Significant mechanical parameters must be defined reasonably, so a method is proposed to identify unknown parameters through a deterministic calculation and an optimization process. All the information, including the identified parameters, are utilized to develop a nonlinear finite element model with a commercial code. The performance of the model is compared with the test results.
The Multisplit Ventilator System: Performance Testing of Respiratory Support Shared by Multiple Patients
Authors: Gaucher Donald J. , Trimble A. Zachary , Yamamoto Brennan E. , Seidi Ebrahim , Miller Scott F. , Vossler John D. , Mahoney Reid C. , Bellomy Ryan L. , Heilbron William R. , Johnson Sidney M. , Puapong Devin P. , Ahn Hyeong Jun , Woo Russell K.
Published: January 2022

Ventilator sharing has been proposed as a method of increasing ventilator capacity during instances of critical shortage. We sought to assess the ability of a regulated, shared ventilator system, the multisplit ventilator system, to individualize support to multiple simulated patients using one ventilator. We employed simulated patients of varying size, compliance, minute ventilation requirement, and positive end-expiratory pressure (PEEP) requirement. Performance tests were performed to assess the ability of the system, versus control, to achieve individualized respiratory goals to clinically disparate patients sharing a single ventilator following ARDSNet guidelines (Acute Respiratory Distress Syndrome). Resilience tests measured the effects of simulated adverse events occurring to one patient on another patient sharing a single ventilator. The multisplit ventilator system met individual oxygenation and ventilation requirements for multiple simulated patients with a tolerance similar to that of a single ventilator. Abrupt endotracheal tube occlusion or extubation occurring to one patient resulted in modest, clinically tolerable changes in ventilation parameters for the remaining patients. The proof-of-concept ventilator system presented in this paper is a regulated, shared ventilator system capable of individualizing ventilatory support to clinically dissimilar simulated patients. It is resilient to common adverse events and represents a feasible option to ventilate multiple patients during a severe ventilator shortage.
Ultrasound versus physical examination in predicting disease flare in children with juvenile idiopathic arthritis: a systematic literature review and qualitative synthesis
Authors: De Lucia Orazio , Giani Teresa , Caporali Roberto , Cimaz Rolando
Published: January 2022

In this systematic review we analyzed the published articles related to the predictive value for flare of subclinical synovitis assessed by ultrasound (US) in juvenile idiopathic arthritis (JIA). Medline, Embase and Cochrane databases were searched from 1990 to 2020 by two authors, using PICO methodology. The study is built and reported according to PRISMA guidelines. Searches identified four articles comprising a total of 187 JIA patients in clinical remission from at least 3 months. Two of the articles found US subclinical signs of synovitis to be predictive for flare, with a five times higher risk (with Power Doppler signal as an important feature), while in the other two baseline US abnormalities did not predict a clinical flare. The articles differed for protocols, definitions, and length of follow-up. US has an expanding role in pediatric rheumatology, with interest-ing applications especially during the follow-up, potentially identifying subclinical inflammatory signs predictive of flare. However, the few studies available do not allow definite conclusions at this time.
Investigación científica y promoción del desarrollo en los valles de Coina y Chuquizongo: un modelo de intervención interdisciplinaria en ámbitos rurales (distrito Usquil, provincia Otusco, departamento de la Libertad-Perú)
Authors:   Universidad Nacional de Trujillo, Escalante Gómez Heider Onú
Published: January 2022

Proponemos una alternativa de intervención de investigación científica y de promoción del desarrollo con participación interdisciplinaria en espacios territoriales locales de la sociedad rural, tomando como referencia la sub cuenca alta del río Chicama, en la comprensión de los afluentes Shugual, Huacamochal y Paranguarán, dentro de la concepción del desarrollo territorial y nueva ruralidad en la perspectiva del desarrollo humano sostenible de áreas donde existan asentamientos con influencia en un hinterland a los cuales puedan influir desde su propia dinamicidad. Los valles de Coina y Chuquizongo ubicados en el distrito de Usquil, provincia de Otusco del departamento de La Libertad-Perú, tienen las condiciones para potenciarse como ejes de desarrollo intermedio en la Cuenca Alta del río Chicama
Rapid preparation of amorphous Al2O3 on graphene surface by plasma electrolysis technology
Authors: Zhang Yongfu , Yang Yunjie , Wei Xiaolin , Ma Ben , Chen Weiwei , Cheng Huanwu , Wang Lu , Hou Tianyu , Li Maoyuan , Lu Lin
Published: January 2022

Difficult processing, easy agglomeration, and other issues make it difficult for graphene to be used in product design alone. Surface modification of graphene is the key to solving the problem. However, the disadvantage that graphene cannot be used as an electrode independently limits its study. Amorphous Al2O3-coated graphene was synthesized by plasma electrolysis in this study. The coating was composed of γ-Al2O3, Al2OC, and Al4C3 with a thickness of ∼7 nm. The unclear interface between the coating and the substrate demonstrated a good combination between the coating and the graphene. A weightlessness rate of only 1.9% before 600 °C, increasing five times while compared to the original sample, revealed excellent oxidation resistance of coating on the graphene. The mechanism of the coating onto the graphene was also studied for further investigation. We believe that the technique could optimize the application and development of graphene.
Alpha-Soluble NSF Attachment Protein Prevents the Cleavage of the SARS-CoV-2 Spike Protein by Functioning as an Interferon-Upregulated Furin Inhibitor
Authors: Wang Jinliang , Luo Jie , Wen Zhiyuan , Wang Xinxin , Shuai Lei , Zhong Gongxun , Wang Chong , Sun Ziruo , Chen Weiye , Ge Jinying , Liu Renqiang , Wang Xijun , Bu Zhigao
Published: January 2022

Some key mutations of SARS-CoV-2 spike protein, such as D614G and P681R mutations, increase the transmission or pathogenicity by enhancing the cleavage efficacy of spike protein by furin. Loss of the furin cleavage motif of SARS-CoV-2 spike protein reduces the virulence and transmission, suggesting that furin is an attractive antiviral drug target.
A Goldilocks Principle for the Gut Microbiome: Taxonomic Resolution Matters for Microbiome-Based Classification of Colorectal Cancer
Authors: Armour Courtney R. , Topçuoğlu Begüm D. , Garretto Andrea , Schloss Patrick D.
Published: January 2022

Despite being highly preventable, colorectal cancer remains a leading cause of cancer-related death in the United States. Low-cost, noninvasive detection methods could greatly improve our ability to identify and treat early stages of disease.
Genome-Scale Metabolic Modelling of Lifestyle Changes in Rhizobium leguminosarum
Authors: Schulte Carolin C. M. , Ramachandran Vinoy K. , Papachristodoulou Antonis , Poole Philip S.
Published: January 2022

Rhizobia are soil bacteria that induce nodule formation on plant roots and differentiate into nitrogen-fixing bacteroids. A detailed understanding of this complex symbiosis is essential for advancing ongoing efforts to engineer novel symbioses with cereal crops for sustainable agriculture.
Supplemental Material: Rifting of the Indian passive continental margin: Insights from the Langjiexue basalts in the central Tethyan Himalaya, southern Tibet
Authors: Wang Chao , al. et
Published: January 2022

Text S1: Analytical methods. Figure S1: Zr versus selected element variation diagrams to highlight the effects of alteration and metamorphism for the basalts from Langjiexue area. Figure S2: (A) Ti/Y vs. TiO2, and (B) Ti/Y vs. MgO diagrams for the basalt samples from the Langjiexue in Tethyan Himalaya. Table S1: Representative Permian-Triassic magmatic events along the Tethyan Himalaya. Table S2: Zircon LA-ICP-MS U-Pb in-situ analyzing results for zircons from the Langjiexue basalts. Table S3: Whole-rock major, trace element and Sr-Nd isotope data of Langjiexue basalts.
Bedside formulation of a personalized multi-neoantigen vaccine against mammary carcinoma
Authors: Mohsen Mona O , Speiser Daniel E , Michaux Justine , Pak HuiSong , Stevenson Brian J , Vogel Monique , Inchakalody Varghese Philipose , de Brot Simone , Dermime Said , Coukos Georges , Bassani-Sternberg Michal , Bachmann Martin F
Published: January 2022

Background

Harnessing the immune system to purposely recognize and destroy tumors represents a significant breakthrough in clinical oncology. Non-synonymous mutations (neoantigenic peptides) were identified as powerful cancer targets. This knowledge can be exploited for further improvements of active immunotherapies, including cancer vaccines, as T cells specific for neoantigens are not attenuated by immune tolerance mechanism and do not harm healthy tissues. The current study aimed at developing an optimized multitarget vaccine using short or long neoantigenic peptides utilizing virus-like particles (VLPs) as an efficient vaccine platform.

Methods

Mutations of murine mammary carcinoma cells were identified by integrating mass spectrometry-based immunopeptidomics and whole exome sequencing. Neoantigenic peptides were synthesized and covalently linked to virus-like nanoparticles using a Cu-free click chemistry method for easy preparation of vaccines against mouse mammary carcinoma.

Results

As compared with short peptides, vaccination with long peptides was superior in the generation of neoantigen-specific CD4+and CD8+T cells, which readily produced interferon gamma (IFN-γ) and tumor-necrosis factor α (TNF-α). The resulting anti-tumor effect was associated with favorable immune re-polarization in the tumor microenvironment through reduction of myeloid-derived suppressor cells. Vaccination with long neoantigenic peptides also decreased post-surgical tumor recurrence and metastases, and prolonged mouse survival, despite the tumor’s low mutational burden.

Conclusion

Integrating mass spectrometry-based immunopeptidomics and whole exome sequencing is an efficient approach for identifying neoantigenic peptides. Our multitarget VLP-based vaccine shows a promising anti-tumor effect in an aggressive murine mammary carcinoma model. Future clinical application using this strategy is readily feasible and practical, as click chemistry coupling of personalized synthetic peptides to the nanoparticles can be done at the bedside directly before injection.
B cells imprint adoptively transferred CD8+T cells with enhanced tumor immunity
Authors: Smith Aubrey S , Knochelmann Hannah M , Wyatt Megan M , Rangel Rivera Guillermo O , Rivera-Reyes Amalia M , Dwyer Connor J , Ware Michael B , Cole Anna C , Neskey David M , Rubinstein Mark P , Liu Bei , Thaxton Jessica E , Bartee Eric , Paulos Chrystal M
Published: January 2022

Background

Adoptive T cell transfer (ACT) therapy improves outcomes in patients with advanced malignancies, yet many individuals relapse due to the infusion of T cells with poor function or persistence. Toll-like receptor (TLR) agonists can invigorate antitumor T cell responses when administered directly to patients, but these responses often coincide with toxicities. We posited that TLR agonists could be repurposed ex vivo to condition T cells with remarkable potency in vivo, circumventing TLR-related toxicity.

Methods

In this study we investigated how tumor-specific murine CD8+T cells and human tumor infiltrating lymphocytes (TILs) are impacted when expanded ex vivo with the TLR9 agonist CpG.

Results

Herein we reveal a new way to reverse the tolerant state of adoptively transferred CD8+T cells against tumors using TLR-activated B cells. We repurposed the TLR9 agonist, CpG, commonly used in the clinic, to bolster T cell—B cell interactions during expansion for ACT. T cells expanded ex vivo from a CpG-treated culture demonstrated potent antitumor efficacy and prolonged persistence in vivo. This antitumor efficacy was accomplished without in vivo administration of TLR agonists or other adjuvants of high-dose interleukin (IL)-2 or vaccination, which are classically required for effective ACT therapy. CpG-conditioned CD8+T cells acquired a unique proteomic signature hallmarked by an IL-2RαhighICOShighCD39lowphenotype and an altered metabolic profile, all reliant on B cells transiently present in the culture. Likewise, human TILs benefitted from expansion with CpG ex vivo, as they also possessed the IL-2RαhighICOShighCD39lowphenotype. CpG fostered the expansion of potent CD8+T cells with the signature phenotype and antitumor ability via empowering a direct B–T cell interaction. Isolated B cells also imparted T cells with the CpG-associated phenotype and improved tumor immunity without the aid of additional antigen-presenting cells or other immune cells in the culture.

Conclusions

Our results demonstrate a novel way to use TLR agonists to improve immunotherapy and reveal a vital role for B cells in the generation of potent CD8+T cell-based therapies. Our findings have immediate implications in the clinical treatment of advanced solid tumors.
Systemic high-dose dexamethasone treatment may modulate the efficacy of intratumoral viral oncolytic immunotherapy in glioblastoma models
Authors: Koch Marilin S , Zdioruk Mykola , Nowicki Michal O , Griffith Alec M , Aguilar Estuardo , Aguilar Laura K , Guzik Brian W , Barone Francesca , Tak Paul P , Tabatabai Ghazaleh , Lederer James A , Chiocca E Antonio , Lawler Sean
Published: January 2022

Background

Intratumoral viral oncolytic immunotherapy is a promising new approach for the treatment of a variety of solid cancers. CAN-2409 is a replication-deficient adenovirus that delivers herpes simplex virus thymidine kinase to cancer cells, resulting in local conversion of ganciclovir or valacyclovir into a toxic metabolite. This leads to highly immunogenic cell death, followed by a local immune response against a variety of cancer neoantigens and, next, a systemic immune response against the injected tumor and uninjected distant metastases. CAN-2409 treatment has shown promising results in clinical studies in glioblastoma (GBM). Patients with GBM are usually given the corticosteroid dexamethasone to manage edema. Previous work has suggested that concurrent dexamethasone therapy may have a negative effect in patients treated with immune checkpoint inhibitors in patients with GBM. However, the effects of dexamethasone on the efficacy of CAN-2409 treatment have not been explored.

Methods

In vitro experiments included cell viability and neurosphere T-cell killing assays. Effects of dexamethasone on CAN-2409 in vivo were examined using a syngeneic murine GBM model; survival was assessed according to Kaplan-Meier; analyses of tumor-infiltrating lymphocytes were performed with mass cytometry (CyTOF - cytometry by time-of-flight). Data were analyzed using a general linear model, with one-way analysis of variance followed by Dunnett’s multiple comparison test, Kruskal-Wallis test, Dunn’s multiple comparison test or statistical significance analysis of microarrays.

Results

In a mouse model of GBM, we found that high doses of dexamethasone combined with CAN-2409 led to significantly reduced median survival (29.0 days) compared with CAN-2409 treatment alone (39.5 days). CyTOF analyses of tumor-infiltrating immune cells demonstrated potent immune stimulation induced by CAN-2409 treatment. These effects were diminished when high-dose dexamethasone was used. Functional immune cell characterization suggested increased immune cell exhaustion and tumor promoting profiles after dexamethasone treatment.

Conclusion

Our data suggest that concurrent high-dose dexamethasone treatment may impair the efficacy of oncolytic viral immunotherapy of GBM, supporting the notion that dexamethasone use should be balanced between symptom control and impact on the therapeutic outcome.
Fc-null anti-PD-1 monoclonal antibodies deliver optimal checkpoint blockade in diverse immune environments
Authors: Moreno-Vicente Julia , Willoughby Jane E , Taylor Martin C , Booth Steven G , English Vikki L , Williams Emily L , Penfold Christine A , Mockridge C Ian , Inzhelevskaya Tatyana , Kim Jinny , Chan H T Claude , Cragg Mark S , Gray Juliet C , Beers Stephen A
Published: January 2022

Background

Despite extensive clinical use, the mechanisms that lead to therapeutic resistance to anti-programmed cell-death (PD)-1 monoclonal antibodies (mAbs) remain elusive. Here, we sought to determine how interactions between the Fc region of anti-PD-1 mAbs and Fcγ receptors (FcγRs) affect therapeutic activity and how these are impacted by the immune environment.

Methods

Mouse and human anti-PD-1 mAbs with different Fc binding profiles were generated and characterized in vitro. The ability of these mAbs to elicit T-cell responses in vivo was first assessed in a vaccination setting using the model antigen ovalbumin. The antitumor activity of anti-PD-1 mAbs was investigated in the context of immune ‘hot’ MC38 versus ‘cold’ neuroblastoma tumor models, and flow cytometry performed to assess immune infiltration.

Results

Engagement of activating FcγRs by anti-PD-1 mAbs led to depletion of activated CD8 T cells in vitro and in vivo, abrogating therapeutic activity. Importantly, the extent of this Fc-mediated modulation was determined by the surrounding immune environment. Low FcγR-engaging mouse anti-PD-1 isotypes, which are frequently used as surrogates for human mAbs, were unable to expand ovalbumin-reactive CD8 T cells, in contrast to Fc-null mAbs. These results were recapitulated in mice expressing human FcγRs, in which clinically relevant hIgG4 anti-PD-1 led to reduced endogenous expansion of CD8 T cells compared with its engineered Fc-null counterpart. In the context of an immunologically ‘hot’ tumor however, both low-engaging and Fc-null mAbs induced long-term antitumor immunity in MC38-bearing mice. Finally, a similar anti-PD-1 isotype hierarchy was demonstrated in the less responsive ‘cold’ 9464D neuroblastoma model, where the most effective mAbs were able to delay tumor growth but could not induce long-term protection.

Conclusions

Our data collectively support a critical role for Fc:FcγR interactions in inhibiting immune responses to both mouse and human anti-PD-1 mAbs, and highlight the context-dependent effect that anti-PD-1 mAb isotypes can have on T-cell responses. We propose that engineering of Fc-null anti-PD-1 mAbs would prevent FcγR-mediated resistance in vivo and allow maximal T-cell stimulation independent of the immunological environment.
Theoretical investigation of the mechanism of DMAP-promoted [4 + 2]-annulation of prop-2-ynylsulfonium with isatoic anhydride
Authors: Lu Nan , Liang Hui , Miao Chengxia , Lan Xiaozheng , Qian Ping
Published: January 2022

The mechanism for DMAP-promoted [4 + 2]-annulation of prop-2-ynylsulfonium with isatoic anhydride is investigated using the M06-2X functional. The reaction comprises isomerization of prop-2-ynylsulfonium in stage 1. Stage 2 includes DMAP-promoted deprotonation, nucleophilic addition, ring opening, and decarboxylation. Three steps of intramolecular cycloaddition, DMAP-promoted protonation, and dealkylation occur in stage 3, generating methylated DMAP and neutral thioether, which undergo double-bond isomerization to yield 3-methylthio-4-quinolone. The ability of DMAP to promote the reaction lies in the barrier decrease for alkyne isomerization, deprotonation/protonation of allenes, and dealkylation as effective bases for transferring protons and methyl groups. The roles of prop-2-ynylsulfonium and isatoic anhydride were demonstrated to be C2 and C4 synthons via Multiwfn analysis on the frontier molecular orbital. An alternative path was also confirmed by the Mayer bond order of the vital transition states.
Numerical framework for unsteady bioconvection flow of third-grade nanofluid over a porous Riga surface with convective Nield approach
Authors: Ahmad Iftikhar , Ali Nasir , Aziz Samaira , Khan Sami Ullah
Published: January 2022

The ultra-high significances of thermal radiation, magnetic field and activation energy in thermal enhancement processes allow significant applications in chemical and mechanical engineering, modern technology and various thermal engineering eras. The improvement in energy resources and production became one of the major challenges for researchers and scientists for sustained development in industrial growths. Beside this, the bioconvection assessment in nanomaterials conveys prestigious applications in biotechnology like bio-sensors, enzymes, petroleum industry, bio-fuels and many more. In view of such renewable applications, present exploration discloses unsteady two-dimensional flow of third-grade nanomaterial accommodating gyrotactic microorganisms induced by unsteady stretched Riga sheet in porous medium. The formulated flow problem is further scrutinized by utilizing the chemical reaction, activation energy, thermal radiation and magnetic aspects. The convective Nield constraints are further subjected in the current investigation. Apposite transformations are used to condense the nonlinear developed problem into dimensionless ordinary form. The numerical solution of such similar flow problem is presented via shooting technique. The detailed graphical illustrations of the dimensionless temperature, nanoparticles concentration, velocity and motile microorganisms for physical significance of diverse relevant parameters are deliberated. Furthermore, numerical data of local Sherwood, Nusselt and motile density numbers is designated in tabular form. Study accentuated that velocity increases for higher modified Hartmann and material constants, while the effects of buoyancy ratio and bioconvected Rayleigh numbers are rather opposite. The temperature, microorganism and concentration distributions were enhanced for unsteady parameter. It is also acknowledged that the concentration distribution is enhanced for activating the energy number. Moreover, the microorganism distribution enhances for concentration difference and magneto-porous constants, while bioconvected Lewis and Peclet numbers show conflicting trend.
Integration of fuzzy logic in the SEIRD compartmental model for the analysis of intervention and transmission heterogeneity on SARS-CoV-2 transmission dynamics
Authors: Siam Zakaria Shams , Hasan Rubyat Tasnuva , Ahamed Hossain , Youme Samiya Kabir , Anik Soumik Sarker , Alita Sumaia Islam , Rahman Rashedur M.
Published: January 2022

Different epidemiological compartmental models have been presented to predict the transmission dynamics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we have proposed a fuzzy rule-based Susceptible-Exposed-Infectious-Recovered-Death ([Formula: see text]) compartmental model considering a new dynamic transmission possibility variable as a function of time and three different fuzzy linguistic intervention variables to delineate the intervention and transmission heterogeneity on SARS-CoV-2 viral infection. We have analyzed the datasets of active cases and total death cases of China and Bangladesh. Using our model, we have predicted active cases and total death cases for China and Bangladesh. We further presented the correspondence of different intervention measures in relaxing the transmission possibility. The proposed model delineates the correspondence between the intervention measures as fuzzy subsets and the predicted active cases and total death cases. The prediction made by our system fitted the collected dataset very well while considering different fuzzy intervention measures. The integration of fuzzy logic in the classical compartmental model also produces more realistic results as it generates a dynamic transmission possibility variable. The proposed model could be used to control the transmission of SARS-CoV-2 as it deals with the intervention and transmission heterogeneity on SARS-CoV-2 transmission dynamics.
The role of engineering geology in delivering the United Nations Sustainable Development Goals
Authors: Lagesse Richard H. , Hambling Jennifer , Gill Joel C. , Dobbs Marcus , Lim Cheryl , Ingvorsen Peter
Published: January 2022

Engineering geology has an important role to play in sustainable development. This is due to the unique perspective that engineering geologists have of the interfaces between: science and engineering; the natural and built environments; the past, present and future. This paper examines the role of engineering geology in delivering the United Nations Sustainable Development Goals (SDGs) and demonstrates that there is a strong link between the knowledge, skills and activities of engineering geologists and the delivery of all 17 goals. The study includes a detailed evaluation of all 169 SDG targets and highlights the key impact areas where engineering geologists already contribute to sustainable development, as well as identifying opportunities for contributions to be strengthened. It is hoped that this paper will empower engineering geologists to confidently communicate the value of their role, act responsibly and exert their influence to drive positive outcomes in terms of sustainable development in everything that they do.

Supplementary material
:
Mapping exercise of typical engineering geology knowledge, skills and activities against all 169 SDG targets and related indicators is available at
https://doi.org/10.6084/m9.figshare.c.5778817

Thematic collection:
This article is part of the Sustainability in Engineering Geology & Hydrogeology collection available at:
https://www.lyellcollection.org/cc/sustainability-in-engineering-geology-and-hydrogeology
GECCO 2021
Authors: Liefooghe Arnaud , Veerapen Nadarajen
Published: January 2022

The 2021 Genetic and Evolutionary Computation Conference (GECCO 2021 @ Lille, https://gecco-2021.sigevo.org/) was organized as an online-only conference on July 10-14. After 2020, this is the second time that GECCO is going online. This report describes the virtual environments used for the conference and provides statistics about the GECCO virtualization.
When Tiny Goes Big
Authors: Kumar Rakesh
Published: January 2022

I believe that the Internet of Tiny Things (IoTT) will be the next big driver of the computing and semiconductor industry - imagine applications such as smart city, home sensors, wearables, implantables, single-use electronic tags for pharmaceuticals and produce, and more. Trillions of tiny devices may be needed every year to enable these applications, while meeting extreme requirements in terms of cost (sometimes only a few cents), power (often self-powered), and trust (often physically accessible and producing sensitive data). Our research over last few years has been focused on enabling an internet of these tiny things by addressing the unique cost, power, and trust challenges of these devices.
AuraRing
Authors: Salemi Parizi Farshid , Whitmire Eric , Patel Shwetak N.
Published: January 2022

Wearable computing platforms, such as smartwatches and head-mounted mixed reality displays, demand new input devices for high-fidelity interaction. We present AuraRing, a wearable magnetic tracking system designed for tracking fine-grained finger movement. The hardware consists of a ring with an embedded electromagnetic transmitter coil and a wristband with multiple sensor coils. By measuring the magnetic fields at different points around the wrist, AuraRing estimates the five degree-of-freedom pose of the ring. AuraRing is trained only on simulated data and requires no runtime supervised training, ensuring user and session independence. It has a resolution of 0.1 mm and a dynamic accuracy of 4.4 mm, as measured through a user evaluation with optical ground truth. The ring is completely self-contained and consumes just 2.3 mW of power.
Wireless Network Access and Emotion Recognition of Online English Translation Teaching System from the Perspective of Artificial Intelligence
Authors: Li Yonglan , Shu Wen
Published: January 2022

The research is aimed at verifying the application effect of the online automatic evaluation system in English translation teaching and at understanding the satisfaction of students with different feedback methods. The research uses three classes of human resource management majors in Xi’an Technological University as the research object and uses questionnaire survey and comparative experiment methods to compare and analyse the three feedback methods: teacher feedback, online automatic feedback, and teacher feedback combined with online automatic feedback. The research answers the following three questions: (1) will the three feedback methods affect students’ English translation performance? (2) Which of the three feedback methods will improve students’ English performance better? (3) What about students’ satisfaction with current feedback methods? The research results show that the significance value between the control group (CG) and the experimental group 1 (EG1) is 0.029, that between CG and the experimental group 2 (EG2) is 0.432, and that between EG1 and EG2 is 0.001. There are obvious differences in the posttest scores of the three groups of students. EG2 has the largest average posttest score, which is 9.8182; there is no obvious difference in posttest translation scores between CG and EG2. It indicates that “teacher feedback + online automatic feedback” and teacher feedback have the equivalent effect on improving students’ translation. The results of the questionnaire survey show that students have the highest degree of recognition of “teacher feedback + online automatic feedback.” The research is helpful for teachers to better understand the shortcomings in the translation teaching process, so that they can take effective measures against these problems in the follow-up teaching process to improve their teaching effect.
A Case Study in Process Improvement to Minimize Delays from Obtaining Blood for Red Cell Exchange for a Patient with Sickle Cell Disease and Multiple Red Blood Cell Alloantibodies
Authors: Narayanan Damodaran , Hogan Noreen B. , Schaser Karen A. , Ruegsegger Patricia , Rose William Nicholas
Published: January 2022

The process of procuring several units of red blood cells for red cell exchange can sometimes take several hours to days, especially for patients with multiple clinically significant red cell alloantibodies. This can introduce delays, inconveniences, and even health challenges for the patient. For most planned exchanges, these delays are preventable with some foresight and process modifications that are relatively minor yet high leverage. We report a case study of process improvement whereby the apheresis nurse sends an e-mail to the blood bank when the nurse makes the patient’s next red cell exchange appointment as the signal to order blood about 6–8 weeks before the exchange.
Experimental Study of Prevention and Control of Rock Burst in Steeply Inclined Coal Seams by Mining Sequence and Filling
Authors: Zhang Zhihui , Liu Yangyi , Zhu Wenwen , Liu Jian , Ma Tian , Xie Chunxue
Published: January 2022

The control and prevention of rock burst in a steeply inclined coal seam are essential. In order to figure out the effects of filling and mining sequence on rock burst in the steeply inclined coal seam, B3+6 and B1+2 coal seams in Wudong coal mine are chosen as the research objects, and an in-house experiment system of similarity simulation is established in this study. Combined with numerical simulation, the characteristics of collapse, stress distribution, and displacement variations can be measured, which provide useful information to study the effects of the filling body and mining sequence on rock burst. Experimental results show that the key reason for rock burst in a steeply inclined coal seam is the stress concentration of the rock pillar between B3+6 and B1+2 coal seams instead of the stress-lever-effect of a deeper rock pillar. The filling body can support the middle rock pillar, share the geological structure stress in the horizontal and vertical direction, eliminate the stress concentration zone largely, and prevent the occurrence of rock burst. When multiple working faces are working, the opposite side of the coal seam should be mined first to release the energy in the rock in advance, thus preventing the rock burst effectively. The research results provide fundamental information for better understanding the reason for rock burst and preventing rock burst in the steeply inclined coal seam.
An Arc-Consistent Viscous-Spring Artificial Boundary for Numerical Analysis of Seismic Response of Underground Structures
Authors: Ye Dan , Yin Shangzhi , Wang Yihong , Zuo Taian
Published: January 2022

A new arc-consistent viscous-spring artificial boundary (ACVAB) was proposed by changing a traditional flat artificial boundary based on the theory of viscous-spring artificial boundaries. Through examples, the concept underpinning the establishment and specific setting of the boundary in the finite element software were described. Through comparison with other commonly used artificial boundaries in an example for near-field wave analysis using the two-dimensional (2D) half-space model, the reliability of the ACVAB was verified. Furthermore, the ACVAB was used in the numerical analysis of the effects of an earthquake on underground structures. The results were compared with the shaking table test results on underground structures. On this basis, the applicability of the ACVAB to a numerical model of seismic response of underground structures was evaluated. The results show that the boundary is superior to common viscous-spring boundaries in terms of accuracy and stability, and therefore, it can be used to evaluate radiation damping effects of seismic response of underground structures and is easier to use.
Improvement of AHMES Using AI Algorithms
Authors: Chen Le , Song JeongYoung
Published: January 2022

This research aims to improve the rationality and intelligence of AUTOMATICALLY HIGHER MATHEMATICALLY EXAM SYSTEM (AHMES) through some AI algorithms. AHMES is an intelligent and high-quality higher math examination solution for the Department of Computer Engineering at Pai Chai University. This research redesigned the difficulty system of AHMES and used some AI algorithms for initialization and continuous adjustment. This paper describes the multiple linear regression algorithm involved in this research and the AHMES learning (AL) algorithm improved by the Q-learning algorithm. The simulation test results of the upgraded AHMES show the effectiveness of these algorithms.
A Fast Density Peak Clustering Method with Autoselect Cluster Centers
Authors: Wang Zhihe , Li Yongbiao , Du Hui , Wei Xiaofen
Published: January 2022

Aiming at density peaks clustering needs to manually select cluster centers, this paper proposes a fast new clustering method with auto-select cluster centers. Firstly, our method groups the data and marks each group as core or boundary groups according to its density. Secondly, it determines clusters by iteratively merging two core groups whose distance is less than the threshold and selects the cluster centers at the densest position in each cluster. Finally, it assigns boundary groups to the cluster corresponding to the nearest cluster center. Our method eliminates the need for the manual selection of cluster centers and improves clustering efficiency with the experimental results.
A Novel High-Capacity Information Hiding Scheme Based on Improved U-Net
Authors: Liu Lianshan , Meng Lingzhuang , Zheng Weimin , Peng Yanjun , Wang Xiaoli
Published: January 2022

With the gradual introduction of deep learning into the field of information hiding, the capacity of information hiding has been greatly improved. Therefore, a solution with a higher capacity and a good visual effect had become the current research goal. A novel high-capacity information hiding scheme based on improved U-Net was proposed in this paper, which combined improved U-Net network and multiscale image analysis to carry out high-capacity information hiding. The proposed improved U-Net structure had a smaller network scale and could be used in both information hiding and information extraction. In the information hiding network, the secret image was decomposed into wavelet components through wavelet transform, and the wavelet components were hidden into image. In the extraction network, the features of the hidden image were extracted into four components, and the extracted secret image was obtained. Both the hiding network and the extraction network of this scheme used the improved U-Net structure, which preserved the details of the carrier image and the secret image to the greatest extent. The simulation experiment had shown that the capacity of this scheme was greatly improved than that of the traditional scheme, and the visual effect was good. And compared with the existing similar solution, the network size has been reduced by nearly 60%, and the processing speed has been increased by 20%. The image effect after hiding the information was improved, and the PSNR between the secret image and the extracted image was improved by 6.3 dB.
Network Embedding-Based Approach for Detecting Collusive Spamming Groups on E-Commerce Platforms
Authors: Chao Jinbo , Zhao Chunhui , Zhang Fuzhi
Published: January 2022

Information security is one of the key issues in e-commerce Internet of Things (IoT) platform research. The collusive spamming groups on e-commerce platforms can write a large number of fake reviews over a period of time for the evaluated products, which seriously affect the purchase decision behaviors of consumers and destroy the fair competition environment among merchants. To address this problem, we propose a network embedding based approach to detect collusive spamming groups. First, we use the idea of a meta-graph to construct a heterogeneous information network based on the user review dataset. Second, we exploit the modified DeepWalk algorithm to learn the low-dimensional vector representations of user nodes in the heterogeneous information network and employ the clustering methods to obtain candidate spamming groups. Finally, we leverage an indicator weighting strategy to calculate the spamming score of each candidate group, and the top-k groups with high spamming scores are considered to be the collusive spamming groups. The experimental results on two real-world review datasets show that the overall detection performance of the proposed approach is much better than that of baseline methods.
The Screening of Rubella Virus, Cytomegalovirus, Hepatitis B Virus, and Toxoplasma gondii Antibodies in Prepregnancy and Reproductive-Age Women in Tabriz, Iran
Authors: Nabizadeh Edris , Ghotaslou Anahita , Salahi Behnaz , Ghotaslou Reza
Published: January 2022

Objectives. The organisms of Toxoplasma gondii, Rubella virus, Cytomegalovirus, and Herpes simplex virus as an acronym of TORCH are major pathogens in prepregnancy and reproductive-age women. These microorganisms are considered a serious problem and cause 2-3% of all birth defects in the fetus. Our study was aimed at screening the seroprevalence of TORCH antibodies among prepregnancy and reproductive-age women in Tabriz, Iran. Design and Setting. This study was carried out in 2726 prepregnancy and reproductive-age women, who were referred to the laboratory for prenatal TORCH screening. To detect the presence of IgG, IgM antibodies and Hepatitis B surface antigen against these microorganisms were carried out using a chemiluminescence immunoassay analyzer (CLIA). Results. In the current study, the rates of anti-Toxoplasma gondii IgG, anti-Rubella virus IgG, and anti-Cytomegalovirus IgG were found in 722 cases (26.5%), 2579 cases (94.6%0), and 2718 cases (99.7%), respectively. Moreover, the rates of anti-Toxoplasma gondii IgM, anti-Rubella virus IgM, and anti-Cytomegalovirus IgM were discovered in 10 cases (0.4%), 13 cases (0.5%), and 16 cases (0.6%), respectively. The Hepatitis B surface antigen was found in 32 cases (1.2%). The dissemination of positive TORCH in various ages was different (

P
<
0.05

). Conclusions. In our study, the seroprevalence of acute TORCH infections was relatively low. Due to the probability of vertical transmission to the fetus during pregnancy and the unpleasant complication of these pathogens, it is essential to be screened for detection of specific IgG and IgM antibodies in reproductive ages.
A Novel Generative Method for Machine Fault Diagnosis
Authors: Dong Zhipeng , Liu Yucheng , Kang Jianshe , Zhang Shaohui
Published: January 2022

Deep learning is widely used in fault diagnosis of mechanical equipment and has achieved good results. However, these deep learning models require a large number of labeled samples for training, which is difficult to obtain enough labeled samples in the actual production process. However, it is easier to obtain unlabeled samples in the industrial environment. To overcome this problem, this paper proposes a novel method to generative enough label samples for training deep learning models. Unlike the generative adversarial networks, which required complex computing time, the calculation of the proposed novel generative method is simple and effective. First, we calculate the Euclidean distance between the training sample and the test sample; then, the weight coefficient between the training sample and the test sample is settled to generate pseudosamples; finally, combine with the pseudosamples, the deep learning method is training for machine fault diagnosis. In order to verify the effectiveness of the proposed method, two experiment datasets with planetary gearboxes and wind gearboxes are carried out with different activation functions. Experimental results show that the proposed method is effective for most activation function models.