bluuebunny/crossref_metadata_2025 huggingface dataset:
Serotype-Specific Sugars Impact Structure but Not Functions of the Trimeric Autotransporter Adhesin EmaA of Aggregatibacter actinomycetemcomitans
Authors: Tang-Siegel Gaoyan G. , Radermacher Michael , Mintz Keith P. , Ruiz Teresa
Published: November 2022

The human oral pathogen
A. actinomycetemcomitans
is a causative agent of periodontal and several systemic diseases. EmaA is a trimeric autotransporter protein adhesin important for colonization by this pathobiont
in vivo
.
Utility of the Signal-to-Cutoff Ratio and Antigen Index from Fourth- and Fifth-Generation HIV-1/HIV-2 Antigen/Antibody Assays for the Diagnosis of Acute HIV Infection: Applicability for Real-Time Use for Immediate Initiation of Antiretroviral Therapy
Authors: Whitney Elena , Pitrak David , Beavis Kathleen G. , Moore Nicholas M. , Shankaran Shivanjali , Abeleda Ana Precy , Schmitt Jessica , Sha Beverly E.
Published: November 2022

Identification of individuals with acute HIV infection (AHI) and rapid initiation of antiretroviral therapy (ART) are priorities for HIV elimination efforts. Fourth- and fifth-generation HIV-1/HIV-2 antigen (Ag)/antibody (Ab) combination assays can quickly identify patients with AHI, but false-positive results can occur.
Structural Studies Reveal that Endosomal Cations Promote Formation of Infectious Coxsackievirus A9 A-Particles, Facilitating RNA and VP4 Release
Authors: Domanska Aušra , Plavec Zlatka , Ruokolainen Visa , Löflund Benita , Marjomäki Varpu , Butcher Sarah J.
Published: November 2022

Coxsackievirus A9 (CVA9) is a common cause of meningitis and neonatal sepsis. The triggers and mode of action of RNA release into the cell unusually do not require receptor interaction.
The BCL-2 Inhibitor Venetoclax Augments Immune Effector Function Mediated by Fas Ligand, TRAIL, and Perforin/Granzyme B, Resulting in Reduced Plasma Viremia and Decreased HIV Reservoir Size during Acute HIV Infection in a Humanized Mouse Model
Authors: Chandrasekar Aswath P. , Cummins Nathan W. , Natesampillai Sekar , Misra Anisha , Alto Alecia , Laird Greg , Badley Andrew D.
Published: November 2022

This study is the first to examine the applicability of BCL-2 inhibition in the setting of active HIV infectionin vivo. Furthermore, this study demonstrates that venetoclax significantly enhances target cell killing induced by Fas ligand, TRAIL, and perforin/granzyme B and synergistically enhances autologous NK and CD8 cells’ killing of target cells.
Epidemiological and Genomic Analysis of a Large SARS-CoV-2 Outbreak in a Long-Term Care Facility in Catalonia, Spain
Authors: Bordoy Antoni E. , Vallès Xavier , Not Anna , Chiner-Oms Álvaro , Saludes Verónica , Torres Cervós Judit , Roset Roig Anna , Juan-Andres Concha , Sureda Helena , Pardo-Amil Vanessa , García Irene , Guitart Rossell Gemma , Cambra Cibeira Laura , Casañ Cristina , Giménez Montserrat , Blanco Ignacio , Torres-Puente Manuela , Cancino-Muñoz Irving , González-Candelas Fernando , Comas Iñaki , Martró Elisa
Published: November 2022

The impact of COVID-19 on long-term care facilities (LTCFs) has been disproportionately large due to the high frailty of the residents. Here, we report epidemiological and genomic findings of a large outbreak that occurred at an LTCF, which ultimately affected almost all residents and nearly half of staff members.
Text mining and knowledge graph construction from geoscience literature legacy: A review
Authors: Wang* Chengbin , Li Yuanjun , Chen Jianguo
Published: November 2022

In the recent decade, knowledge graph has been a key technique under quick development in artificial intelligence. Due to its great potential for tackling big data and solving complex scientific questions in the geosciences, it has attracted the attention of both computer scientists and geoscientists. In this paper, we review concepts and technologies relevant to the knowledge graph, the workflow of geoscience knowledge graph construction, and state-of-the-art examples from several geoscience disciplines. There are two general strategies for constructing geoscience knowledge graphs: top-down and bottom-up. The detailed technologies include geoscience domain knowledge modeling, data collection, knowledge extraction, knowledge cleaning and fusion, knowledge storage, and knowledge service and discovery. A few recent studies have shown that knowledge graph is a useful tool for improving our understanding of the evolution of the Earth and can assist in data-intensive geoscience studies. At the end of the paper, we discuss the best practices from the studies reviewed and propose research topics for future work. Both knowledge and rules in existing human-curated databases and text mining from the literature should be leveraged in constructing geoscience knowledge graphs. Moreover, development of a higher level schema for existing ontology models and a comparable training corpus should be considered.
Supplemental Material: The role of surface processes in basin inversion and breakup unconformity
Authors: Mondy Luke , Rey Patrice F. , al. et
Published: November 2022

Additional detail concerning the numerical method, internal and boundary conditions, and numerical parameters, and access to outputs of the entire suite of the numerical experiments. 
Radical abdomino-pelvic surgery in the management of uterine carcinosarcoma with concomitant para-aortic lymphadenopathy metastasising from anal carcinoma
Authors: Cowdell Imogen , Smyth Sarah Louise , Eltawab Sally , Soleymani majd Hooman
Published: November 2022

Uterine carcinosarcomas are aggressive gynaecological cancers comprising less than 5% of uterine malignancies. We present the case of a woman in her 70s with a complicated history of advanced anal carcinoma treated with pelvic radiotherapy and multiple laparotomies, who was referred to gynae-oncology following MRI surveillance imaging showing evidence of endometrial carcinoma and para-aortic lymphadenopathy. Successful surgical excision required multidisciplinary teamwork between gynae-oncology, colorectal and urology surgeons. The patient underwent midline laparotomy, with adhesiolysis, ileum resection and side to side anastomosis, posterior exenteration, left kidney mobilisation and suspension, para-aortic lymph node debulking and left ureteric stent insertion. Significant challenge was posed by the extensive adhesions from previous laparotomies and the debulking of the para-aortic lymph nodes around the renal vessels. This case demonstrates the importance of a multidisciplinary approach in complex pelvic surgery and the vitality of good communication between colleagues in achieving effective patient care.
Protocol for a 30-day randomised, parallel-group, non-inferiority, controlled trial investigating the effects of discontinuing renin-angiotensin system inhibitors in patients with and without COVID-19: the RASCOVID-19 trial
Authors: Kliim-Hansen Vivian , Gasbjerg Lærke Smidt , Ellegaard Anne-Marie , Lorentsson Hans Johan Niklas , Lynggaard Mads Bank , Hagemann Christoffer Andersen , Legart Christian , Mathiesen David Siersbæk , Sivapalan Pradeesh , Jensen Jens-Ulrik Stæhr , Vilsbøll Tina , Christensen Mikkel Bring , Knop Filip Krag
Published: November 2022

Introduction

The COVID-19 pandemic caused by the virus SARS-CoV has spread rapidly and caused damage worldwide. Data suggest a major overrepresentation of hypertension and diabetes among patients experiencing severe courses of COVID-19 including COVID-19-related deaths. Many of these patients receive renin-angiotensin system (RAS) inhibiting therapy, and evidence suggests that treatment with angiotensin II receptor blockers (ARBs) could attenuate SARS-CoV-induced acute respiratory distress syndrome, and ACE inhibitors and ARBs have been suggested to alleviate COVID-19 pulmonary manifestations. This randomised clinical trial will address whether RAS inhibiting therapy should be continued or discontinued in hospitalised patients with COVID-19.

Methods and analysis

This trial is a 30-day randomised parallel-group non-inferiority clinical trial with an embedded mechanistic substudy. In the main trial, 215 patients treated with a RAS inhibitor will be included. The participants will be randomly assigned in a 1:1 ratio to either discontinue or continue their RAS inhibiting therapy in addition to standard care. The patients are included during hospitalisation and followed for a period of 30 days. The primary end point is number of days alive and out of hospital within 14 days after recruitment. In a mechanistic substudy, 40 patients treated with RAS inhibition, who are not in hospital and not infected with COVID-19 will be randomly assigned to discontinue or continue their RAS inhibiting therapy with the primary end point of serum ACE2 activity.

Ethics and dissemination

This trial has been approved by the Scientific-Ethical Committee of the Capital Region of Denmark (identification no. H-20026484), the Danish Medicines Agency (identification no. 2020040883) and by the Danish Data Protection Agency (P-2020-366). The results of this project will be compiled into one or more manuscripts for publication in international peer-reviewed scientific journals.

Trial registration number

2020-001544-26;NCT04351581.
Outcomes of a community-based antiretroviral therapy programme for key populations living with HIV in Benue State, Nigeria: protocol for a realist evaluation
Authors: Ibiloye Olujuwon , Decroo Tom , Masquillier Caroline , Jwanle Plang , Okonkwo Prosper , van Olmen Josefien , Lynen Lutgarde , Van Belle Sara
Published: November 2022

Introduction

Key populations (KP) living with HIV are underserved and often face social and health system barriers to HIV care. To optimise access to quality HIV services among KP, the WHO recommended community-based approaches to HIV service delivery for KP. However, to inform the successful rollout and scale-up of community-based antiretroviral therapy service delivery models for KP (KP-CBART), there is a need to study the programme implementation. This study aims to evaluate the outcomes of KP-CBART in Benue State Nigeria using a realist impact evaluation approach. Our evaluation question is: what are the mechanisms and context conditions that drive successful community-based implementation and how do these lead to better retention in care, treatment adherence and viral suppression among which categories of KP?

Methods and analysis

This study will be conducted in three phases, relying on a mixed-method design and following the realist evaluation cycle. The first phase is the development of the initial programme theory grounded in a scoping review, programme and policy document review and in-depth interviews with key stakeholders. In phase 2, findings from case studies of KP-CBART programme implementation in one Nigerian state are used to test the initial programme theory and to refine it. The quantitative part is a retrospective cohort study. All HIV-positive KP clients enrolled into the KP-CBART between 2016 and 2020 will be included in the study. While maximum variation and data saturation will inform sample size for the qualitative part, an estimated 90 purposively selected study participants will be interviewed. In phase 3, findings will be synthesised into a middle-range theory through cross-case analysis. The heuristic intervention, context, agents, mechanisms and outcomes (ICAMO) tool will be used to refine the initial programme theory.

Ethics and dissemination

The study protocol was approved by the Institutional Review Boards of APIN Public Health Initiatives (IRB022-FR), Institute of Tropical Medicine Antwerp (1503/21), and the Benue State Ministry of Health and Human Services (MOH/STA/204/VOL1/154). Written informed consent will be obtained from all study participants. Study results will be disseminated through stakeholders meeting, peer-reviewed journals and conferences.
Body weight and lifestyle changes under the COVID-19 pandemic in Japan: a cross-sectional study from NIPPON DATA2010
Authors: Taniguchi Hirokazu , Okuda Nagako , Arima Hisatomi , Satoh Atsushi , Abe Makiko , Nishi Nobuo , Higashiyama Aya , Suzuki Harumitsu , Ohkubo Takayoshi , Kadota Aya , Miura Katsuyuki , Ueshima Hirotsugu , Okayama Akira
Published: November 2022

Objectives

The COVID-19 pandemic has had an impact on people’s lifestyles such as causing body weight changes. This study examined associations among lifestyle changes and body weight during the COVID-19 pandemic among the Japanese population.

Design

A cross-sectional study.

Setting

A nationwide survey of the general Japanese population.

Participants

Total participants were 2244 men and women, of which 911 young/middle-aged (30–69 years old) and 899 older adults (70 years and older) were analysed separately.

Outcome

Changes in lifestyle (physical activity, dietary habits and alcohol intake) and body weight during the first wave of COVID-19 in spring 2020.

Results

Under the COVID-19 pandemic, 24.1% and 10.1% of Japanese respondents reported weight gain and reduction, respectively. Multivariable-adjusted stepwise logistic regression analyses revealed that the young/middle-aged respondents in the group increased body weight, weight gain was significantly associated with decrease in physical activity (OR 4.01, 95% CI 2.83 to 5.69) and both increase (OR 5.82, 95% CI 3.85 to 8.80) and decrease (OR 2.73, 95% CI 1.52 to 4.93) in eating between meals. In the group that decreased body weight, body weight reduction was significantly associated with increase in physical activity (OR 3.66, 95% CI 1.94 to 6.90), decrease in eating between meals (OR 5.97, 95% CI 3.11 to 11.48) and both increase and decrease in alcohol intake in the young/middle age. For the older adults, body weight gain was higher in women than in men, and significantly associated with higher quartile of regional COVID-19 infection, decrease in physical activity (OR 2.98, 95% CI 1.98 to 4.49), increase in home-cooked meals and increase in eating between meals (OR 4.22, 95% CI 2.55 to 6.99). On the other hand, body weight reduction was significantly associated with decreases in physical activity (OR 2.63, 95% CI 1.62 to 4.27), home-cooked meals and eating between meals (OR 1.95, 95% CI 1.05 to 3.61) in the older adults.

Conclusion

Changes in physical activity and eating between meals were associated with body weight change under the COVID-19 pandemic among Japanese.
Comorbidities in patients with migraine in Japan: a cross-sectional study using data from National Health and Wellness Survey
Authors: Kikui Shoji , Chen Yirong , Ikeda Ken , Hasebe Miki , Asao Keiko , Takeshima Takao
Published: November 2022

Objectives

This study aims to examine the association between migraine and various psychiatric and somatic comorbidities in Japan.

Design

Cross-sectional study using existing data of the 2017 Japan National Health and Wellness Survey (NHWS).

Setting

Nationally representative sample of persons (in terms of age and gender) living in the general community aged 18 years or older in Japan.

Participants

Out of a sample of 30 001 NHWS respondents, 378 respondents were identified as migraine patients and 25 209 were identified as non-migraine patients. After propensity score (PS) matching (1:4), 1512 matched non-migraine respondents were identified.

Primary and secondary outcome measures

Prevalence and PS-matched prevalence ORs (PORs) were assessed for each psychiatric and somatic comorbidity among migraine patients and matched non-migraine respondents (including migraine patients with less than 15 monthly headache days (MHDs) and migraine patients with more than 15 MHDs).

Results

Migraine patients were predominately female and had significantly higher prevalence than matched non-migraine respondents to have psychiatric and somatic comorbidities. Psychiatric comorbidities with >5% prevalence among migraine patients included depression, post-traumatic stress disorder and anxiety disorders, while gastrointestinal disorders were the most prevalent somatic comorbidity category. Other somatic comorbidities included allergies, insomnia, premenstrual syndrome and anaemia. Migraine patients with more than 15 MHDs tended to have higher point estimates for POR.

Conclusion

Psychiatric and somatic conditions were more prevalent in migraine patients than matched non-migraine respondents, some being novel associations not previously reported in Japan. This study provided insights on comorbidities, which could complicate care, clinical practice and outcomes among migraine patients.
Sarcopenia as a predictor of outcome after transcatheter aortic valve implantation: protocol for systematic review and meta-analysis
Authors: Luo Kai , Yang Lei , Li Yu
Published: November 2022

Introduction

Sarcopenia represents a central biological substratum of frailty, which increases the incidence of adverse events and mortality after surgery for oesophageal cancer, gastrectomy and pancreatic surgery. Recently, sarcopenia has been suggested as a predictor of outcomes in patients undergoing transcatheter aortic valve implantation (TAVI). However, since relevant data were variable, we aimed to perform a systematic review and meta-analysis of the current literature to evaluate sarcopenia as a predictor of post-TAVI outcomes.

Methods and analysis

Two investigators will conduct independent searches in PubMed, EMBASE, Web of Science, MEDLINE and the Cochrane Library, from database inception to October 2022. The search will not be limited by language or region. Eligible studies will include reports investigating post-TAVI outcomes in patients with sarcopenia, who are aged >18 years and diagnosed using a CT scan. The primary outcome is short-term mortality (30-day mortality), while the secondary outcomes include long-term mortality (>30 days), length of intensive care unit (ICU) stay, need for ICU admission (the number of patients in the sarcopenia or non-sarcopenia group requiring ICU admission), length of hospital stay and overall complications. Included studies will be assessed for risk of bias according to the Quality in Prognosis Studies critical assessment tool and certainty of evidence using the Grading of Recommendations, Assessment, Development and Evaluation. The analysis will be done with Review Manager (V.5.4) software. If testing reveals little or no statistical heterogeneity, a fixed-effect model will be used for data synthesis; otherwise, a random-effect model may be employed. On encountering substantial heterogeneity, subgroup analysis and leave-one-out jackknife sensitivity analysis will be used to verify the robustness of the results. The obtained results will be presented as forest plots while Cochran’s Q test and I2test will be used to calculate the heterogeneity (>50% indicating strong heterogeneity).

Ethics and dissemination

No ethical approval is needed for this study since we will be using data from previously published studies. The results will be disseminated in a peer-reviewed journal.

PROSPERO registration number

CRD42022349525.
Kawasaki disease in children from Dubai, United Arab Emirates (2012–2020): a single-centre retrospective clinical case series
Authors: Sait Ruzaina , Azar Aida Joseph , Loney Tom , Hassan Sam
Published: November 2022

Kawasaki disease (KD) is most common among East Asian children. There is a lack of data from Middle Eastern countries. We conducted a retrospective study of 27 paediatric patients with KD in Dubai, United Arab Emirates, 2012–2020. The majority of the patients were male, Asian, aged 1–5 years and presented with typical (complete) KD. Timely high-dose intravenous immunoglobulins were administered to 18 patients. Twelve patients did not develop any cardiac complications, 12 had a coronary artery aneurysm and 2 patients developed serious cardiac complications . No patient experienced non-cardiac complications or died. Paediatric patients with KD in Dubai were similar to those from other countries.
Rechallenge of immune checkpoint inhibitors in a case with adverse events inducing myasthenia gravis
Authors: Gao Wen , Wu Lingxiang , Jin Shidai , Li Jun , Liu Xinyin , Xu Jiali , Zhang Wei , Gong Qixing , Sun Chunxiao , Wang Wei , Wang Zidun , Shao Yang W , Yin Jiani C , Shen Lu , Chen Liang , Wang Qianghu , Guo Renhua
Published: November 2022

The mechanism(s) of immune checkpoint inhibitor (ICI)-induced myasthenia gravis (MG), an immune-related adverse event (irAE) that is fatal and limits subsequent ICI use, remain unexplored. Here, through comparative genomic analysis, we identified a pathogenic p.S467C germline variant inSLC22A5in a thymoma case with ICI-induced MG, which was found to be associated with fatty acid oxidation through its regulation on L-carnitine levels. Remarkably, ICI rechallenge with L-carnitine pretreatment led to durable response without MG-related symptoms. Thus, we provide the first clinical evidence of genetic test-directed irAE management, which integrates individualized ICI treatment into the evolving paradigm of cancer management.
Quasinormal modes and thermodynamic properties of GUP-corrected Schwarzschild black hole surrounded by quintessence
Authors: Karmakar Ronit , Gogoi Dhruba Jyoti , Goswami Umananda Dev
Published: November 2022

We study the Quasinormal Modes (QNMs) of the Schwarzschild black hole surrounded by a quintessence field after implementing the quantum corrections to its solution as required by the Generalized Uncertainty Principle (GUP). We analyze the dependence of the QNMs on the deformation parameters of GUP as well as on the quintessence parameter. In most cases the QNMs show the appreciable dependency on these parameters. For a better idea of the accuracy of calculations of QNMs, we compare the results of the QNMs obtained via Mashhoon method with the sixth-order Wentzel–Kramers–Brillouin method. A good agreement between these two methods of QNM calculations is seen depending on the different factors. Further, we study the thermodynamic properties of the GUP-corrected Schwarzschild black hole and check for any dependence with the deformation parameters and the quintessence parameter. In particular, we compute the Hawking temperature, heat capacity and entropy for the black hole and analyze the results graphically to show the dependency of the thermodynamic properties on the said parameters. We have seen that the thermodynamic properties of black holes also depend noticeably on the model parameters in most cases. Black hole remnants have been studied and it is shown that the possible existence of remnant radius as well as remnant temperature depends on the deformations introduced. However, it is observed that the GUP-corrected black hole constructed here cannot become a remnant.
Bianchi type-I Barrow holographic dark energy model in symmetric teleparallel gravity
Authors: Koussour M. , Shekh S. H. , Bennai M.
Published: November 2022

In this work, we have discussed a spatially homogeneous and anisotropic Bianchi type-I space–time in the presence of Barrow holographic dark energy (infrared cut-off is the Hubble’s horizon) proposed by Barrow recently [J. D. Barrow, Phys. Lett. B 808, 135643 (2020).] and matter in the framework of [Formula: see text] gravity where the nonmetricity [Formula: see text] is responsible for the gravitational interaction for the specific choice of [Formula: see text] (where [Formula: see text] is a constant). To find the exact solutions to the field equations, we consider the deceleration parameter [Formula: see text], which is a function of the Hubble’s parameter [Formula: see text] i.e. [Formula: see text] (where [Formula: see text] and [Formula: see text] are constants). We have studied the physical behavior of important cosmological parameters such as the EoS parameter, BHDE and matter density, skewness parameter, squared sound speed and [Formula: see text] plane. Also, we constrain the values of the model parameters [Formula: see text] and [Formula: see text] using 57 Hubble’s parameter measurements.
Bulk-edge correspondence for Floquet topological phases in honeycomb nanoribbon
Authors: Kang Chol Jun , So Yong U , Kim Un Sok
Published: November 2022

Possibility of having different topological phases by time-periodic external field encourages people who wish to manipulate the properties of the materials as their will for the various kinds of systems including a honeycomb nanoribbon. We study bulk-edge correspondence by looking at the change in the value of the first Chern number of a specific band, which reflects the bulk properties, together with the change of associated edge states in quasienergy spectrum when the honeycomb nanoribbon is exposed to circularly polarized laser field. Various topological phase transitions are observed as the intensity of the laser field is raised up and we classify them in two categories. In the first category, when the frequency is sufficiently high, the system undergoes simple transition from trivial phase to topological one, reflected by the sudden jump in the value of Chern number from 0 to 1 and the appearance of two crossing edge states in the spectrum. Whereas, in the second category where the frequency is low enough, anomalous transitions are drawn, having several nonzero values of Chern number, and band folding prevails, often disappearing depending on the laser intensities. The results confirm the bulk-edge correspondence in periodically driven systems and will contribute to future material designs.
Analysis and modeling of fractal evolutionary dynamics of industrial systems
Authors: Yang Yang , Nian Fuzhong , Cui Yuanlin
Published: November 2022

The industry is the key to economic development. This paper proposed a fractal evolutionary dynamic model of industry based on the propagation dynamics theory from the perspective of fractal theory. The model quantitatively portrays the evolutionary trend of industries and provides reasonable solutions to the problems faced by industrial structure optimization. First, the fractal characteristics of the industrial system are analyzed, and the proposed model is used to study the evolution of industry and enterprise impact values at different granularities. Subsequently, the impact of micro firms on the macro industrial development was further investigated. Finally, the correctness of the model simulation results was verified by real data. The results showed that the evolution of industries under different granularities shows self-similarity and that micro industries with small and medium-sized enterprises (SMEs) were more influential in the development of industries. Finally, the proposed fractal evolutionary dynamics model of the industry has proven to be reasonable and effective through empirical comparison. This study provided new insights for solving industrial development problems with high theoreticality and reliability.
Holographic Ricci DE as running vacuum with nonlinear interaction
Authors: George Paxy
Published: November 2022

The holographic Ricci dark energy (HRDE) can be treated as a running vacuum due to its analogy in the energy density, which is a combination of H and [Formula: see text], the model can predict either eternal acceleration or eternal deceleration. In the earlier works, we have shown that the presence of additive constant in the energy density or by considering possible interaction between dark sectors through a phenomenological term, the model can predict a transition from a prior decelerated to a late accelerated epoch. This paper analyzes the cosmic evolution of HRDE as running vacuum with a nonlinear interaction (NLI) between dark sectors in a flat Friedmann-Lemaitre-Robertson-Walker (FLRW) universe. We consider three possible NLI forms which give analytically feasible solutions. We have constrained the model using the Type1a Supernova(Pantheon) + CMB(Planck 2018) + BAO(SDSS) data and evaluated the best estimated values of all the model parameters. We have analyzed the evolution of the Hubble parameter and deceleration parameter of all three cases. We perform state finder analysis of the model, which implies the quintessence nature of the model and found that it is distinguishably different from the standard [Formula: see text]CDM model. The dynamical system analysis of all three cases confirms the evolution of the universe from an unstable prior matter-dominated era to a stable end de Sitter phase.
EXPERIMENTAL DETERMINATION OF BIOFILM AND MECHANICAL PROPERTIES OF SURFACES OBTAINED BY CO2 LASER GAS-ASSISTED NITRIDING OF Ti–6Al–4V ALLOY
Authors: URTEKIN LEVENT , AYDIN ŞEYHMUS , SEVIM ALI , GÖK KADIR , USLAN İBRAHIM
Published: November 2022

The nitriding process is a surface treatment that improves the surface properties of titanium alloys and increases wear/corrosion resistance. This study investigates the structural and mechanical property changes in titanium alloy after nitriding. Micro-hardness differences between the nitrided and non-nitrided surface and morphological changes on the surface were determined. In addition to evaluating the effect of vanadium and aluminum ions on the nonnitrided surface, the impact of nitrided and non-nitrided surfaces on biofilm layer formation was investigated. It was determined that the TiN layer formed on the nitrided surface showed superior properties to its non-nitrided surface in the biofilm tests performed for 6 h. As a result of the tensile tests, it can be said that the nitriding process increases the elasticity module of the Ti–6Al–4V alloy and provides the material to have a more rigid structure. It was also analyzed using finite element analysis (FEA) of mechanical behaviors of the test sample under the tension loads.
A Text Mining Approach to Covid-19 Literature
Authors: Liu Fangyao , Ergu Daji , Li Biao , Deng Wei , Chen Zhengxin , Lu Guoqing , Shi Yong
Published: November 2022

The novel coronavirus disease — COVID-19 is a historic catastrophe that has caused many devastating impacts on human life and wellness. Researchers in academia and industry strive to understand the causes of this pandemic disease and find new therapeutics combating it. Consequently, the number of COVID-19 related publications increases rapidly, and it is too difficult for medical researchers and practitioners to keep up with the latest research and development. Literature filtering and categorization, and knowledge discovery can use text mining as a powerful tool. In this paper, we propose a text mining method to explore the categories of COVID-19 related themes and identify the standard methodologies that have been used. We discuss the potential limitations of this preliminary study and present future perspectives related to COVID-19 research. This paper provides an quantitative and qualitative mixed analysis example of using some research papers by data mining method to dig out several hidden information and set up a foundation for data scientists to develop more effective algorithms to deal with COVID-19 related problems.
The Optimum Inertial Amplifier Tuned Mass Dampers for Nonlinear Dynamic Systems
Authors: Chowdhury Sudip , Banerjee Arnab , Adhikari Sondipon
Published: November 2022

The optimum inertial amplifier tuned mass dampers (IATMD) for vibration reduction of linear and nonlinear dynamic systems are introduced in this paper. [Formula: see text] and [Formula: see text] optimization methods are applied to derive the exact closed-form expressions for optimal design parameters such as frequency and viscous damping ratios in simplified form mathematically for IATMD. From the parametric study, using these optimal closed-form solutions, a higher damper mass ratio, a higher amplifier mass ratio, and a lower inertial angle are recommended to design optimum IATMD to achieve robust dynamic response reduction capacity having moderate viscous damping and lower frequency ratios at an affordable range. The optimum IATMD systems are installed on top of linear and nonlinear single-degree-of-freedom systems to mitigate their dynamic responses of them. The linear dynamic responses are determined through transfer matrix formations, and nonlinear dynamic responses are derived using the harmonic balance (HB) method. [Formula: see text] optimized IATMD is significantly [Formula: see text] and [Formula: see text] superior to the [Formula: see text] optimized conventional tuned mass damper one (CTMD1) and conventional tuned mass damper two (CTMD2). Furthermore, [Formula: see text] optimized IATMD is significantly [Formula: see text] superior to the [Formula: see text] optimized conventional tuned mass damper (CTMD). According to the nonlinear dynamic analysis, [Formula: see text] optimized IATMD systems are significantly [Formula: see text], [Formula: see text], and [Formula: see text] superior to the [Formula: see text] optimized CTMD. Furthermore, [Formula: see text] optimized IATMD systems are significantly [Formula: see text], [Formula: see text], and [Formula: see text] superior to the [Formula: see text] optimized CTMD. The results of this study are mathematically accurate and feasible for practical applications.
Functional equation of Mordell–Tornheim multiple zeta function
Authors: Sahoo Dilip K. , Viswanadham G. K.
Published: November 2022

We give an alternative and relatively simple proof of the functional equation (Funct. Approx. Comment. Math. 55(2) (2016) 227–241) of Mordell–Tornheim multiple zeta function.
Limit shapes for unimodal sequences
Authors: Bridges Walter
Published: November 2022

In this paper, we prove asymptotic 0–1 laws satisfied by diagrams of unimodal sequences of positive integers. These diagrams consist of columns of squares in the plane, and the upper boundary is called the shape. For various types, we show that, as the number of squares tends to infinity, 100% of shapes are near a certain curve — that is, there is a single limit shape. Similar phenomena have been well studied for integer partitions, so this work is a natural extension. One notable corollary is a transferred limit shape for overpartitions.
A study on anabelian geometry of higher local fields
Authors: Murotani Takahiro
Published: November 2022

Anabelian geometry has been developed over a much wider class of fields than Grothendieck, who is the originator of anabelian geometry, conjectured. So, it is natural to ask the following question: What kinds of fields are suitable for the base fields of anabelian geometry?

In this paper, we consider this problem for higher local fields. First, to consider “anabelianness” of higher local fields themselves, we give mono-anabelian reconstruction algorithms of various invariants of higher local fields from their absolute Galois groups. As a result, the isomorphism classes of certain types of higher local fields are completely determined by their absolute Galois groups. Next, we prove that mixed-characteristic higher local fields are Kummer-faithful. This result affirms the above question for these higher local fields to a certain extent.
A polynomial method for proving congruences of pω(n,m) and pν(n,m)
Authors: Xia Ernest X. W. , Zhao Xiang
Published: November 2022

Recently, two partition functions [Formula: see text] and [Formula: see text] were introduced by Andrews et al. The partition function [Formula: see text] denotes the number of partitions of [Formula: see text] in which each odd part is less than twice the smallest part, and [Formula: see text] counts the number of partitions of [Formula: see text] into distinct non-negative parts such that all odd parts are less than twice the smallest part. Very recently, Silva et al. studied congruence properties of the restricted partition functions [Formula: see text] and [Formula: see text] which denote the number of partitions enumerated by [Formula: see text] and [Formula: see text], respectively, into exactly [Formula: see text] parts. In this paper, we give a polynomial method for discovering congruences for [Formula: see text] and [Formula: see text] by checking a finite number of initial values. Employing the polynomial method, we proved new and existing congruences for [Formula: see text] and [Formula: see text] based on a bounded number of calculations. For example, in order to prove that [Formula: see text] holds for all [Formula: see text], it suffices to show that the congruence holds when [Formula: see text].
An explicit lifting construction of CAP forms on O(1,5)
Authors: Narita Hiro-aki , Pitale Ameya , Wagh Siddhesh
Published: November 2022

In this paper, we explicitly construct nontempered cusp forms on the orthogonal group O(1,5) of signature [Formula: see text]. Given a definite quaternion algebra [Formula: see text] over [Formula: see text], the orthogonal group is attached to the indefinite quadratic space of rank 6 with the anisotropic part defined by the reduced norm of [Formula: see text]. Our construction can be viewed as a generalization of the previous work by the first two authors joint with Masanori Muto to the case of any definite quaternion algebras, for which we note that the work just mentioned takes up the case where the discriminant of [Formula: see text] is two. Unlike the previous work the method of the construction is to consider the theta lifting from Maass cusp forms to O(1,5), following the formulation by Borcherds. The cuspidal representations generated by our cusp forms are studied in detail. We determine all local components of the cuspidal representations and show that our cusp forms are CAP forms.
Distributional Effects of Fourth Industrial Revolution Technology on Productivity: Evidence from Korean Firm-level Data
Authors: Rhyu Minji , Lee Sungwon
Published: November 2022

We consider the impacts of a new information and communications technology, referred to as the Fourth Industrial Revolution (4IR) technology, on firm productivity by using a Korean dataset. We estimate the total factor productivity (TFP) of each firm using the control function approach for estimating the production functions, and then estimate the impacts of 4IR technology on TFP. We consider quantile regression models to account for the potential heterogeneity in the effects across TFP distribution. Overall, 4IR technology is beneficial to firms with a high level of productivity, suggesting that there is substantial heterogeneity in the effects that cannot be captured by the conditional mean regression. Our results contribute to the literature by investigating the distributional effects (quantile treatment effects) of the use of new technology on productivity, and these findings are expected to have rich implications for policies regarding support on the use of 4IR technology and R&D.
SHRED
Authors: Jones R. Kenny , Habib Aalia , Ritchie Daniel
Published: November 2022

We present SHRED, a method for 3D SHape REgion Decomposition. SHRED takes a 3D point cloud as input and uses learned local operations to produce a segmentation that approximates fine-grained part instances. We endow SHRED with three decomposition operations: splitting regions, fixing the boundaries between regions, and merging regions together. Modules are trained independently and locally, allowing SHRED to generate high-quality segmentations for categories not seen during training. We train and evaluate SHRED with fine-grained segmentations from PartNet; using its merge-threshold hyperparameter, we show that SHRED produces segmentations that better respect ground-truth annotations compared with baseline methods, at any desired decomposition granularity. Finally, we demonstrate that SHRED is useful for downstream applications, out-performing all baselines on zero-shot fine-grained part instance segmentation and few-shot finegrained semantic segmentation when combined with methods that learn to label shape regions.
A Monte Carlo Method for Fluid Simulation
Authors: Rioux-Lavoie Damien , Sugimoto Ryusuke , Özdemir Tümay , Shimada Naoharu H. , Batty Christopher , Nowrouzezahrai Derek , Hachisuka Toshiya
Published: November 2022

We present a novel Monte Carlo-based fluid simulation approach capable of pointwise and stochastic estimation of fluid motion. Drawing on the Feynman-Kac representation of the vorticity transport equation, we propose a recursive Monte Carlo estimator of the Biot-Savart law and extend it with a stream function formulation that allows us to treat free-slip boundary conditions using a Walk-on-Spheres algorithm. Inspired by the Monte Carlo literature in rendering, we design and compare variance reduction schemes suited to a fluid simulation context for the first time, show its applicability to complex boundary settings, and detail a simple and practical implementation with temporal grid caching. We validate the correctness of our approach via quantitative and qualitative evaluations - across a range of settings and domain geometries - and thoroughly explore its parameters' design space. Finally, we provide an in-depth discussion of several axes of future work building on this new numerical simulation modality.
A Neural Galerkin Solver for Accurate Surface Reconstruction
Authors: Huang Jiahui , Chen Hao-Xiang , Hu Shi-Min
Published: November 2022

To reconstruct meshes from the widely-available 3D point cloud data, implicit shape representation is among the primary choices as an intermediate form due to its superior representation power and robustness in topological optimizations. Although different parameterizations of the implicit fields have been explored to model the underlying geometry, there is no explicit mechanism to ensure the fitting tightness of the surface to the input. We present in response, NeuralGalerkin, a neural Galerkin-method-based solver designed for reconstructing highly-accurate surfaces from the input point clouds. NeuralGalerkin internally discretizes the target implicit field as a linear combination of a set of spatially-varying basis functions inferred by an adaptive sparse convolution neural network. It then solves differentiably for a variational problem that incorporates both positional and normal constraints from the data in closed form within a single forward pass, highly respecting the raw input points. The reconstructed surface extracted from the implicit interpolants is hence very accurate and incorporates useful inductive biases benefiting from the training data. Extensive evaluations on various datasets demonstrate our method's promising reconstruction performance and scalability.
Learning-Based Bending Stiffness Parameter Estimation by a Drape Tester
Authors: Feng Xudong , Huang Wenchao , Xu Weiwei , Wang Huamin
Published: November 2022

Real-world fabrics often possess complicated nonlinear, anisotropic bending stiffness properties. Measuring the physical parameters of such properties for physics-based simulation is difficult yet unnecessary, due to the persistent existence of numerical errors in simulation technology. In this work, we propose to adopt a simulation-in-the-loop strategy: instead of measuring the physical parameters, we estimate the simulation parameters to minimize the discrepancy between reality and simulation. This strategy offers good flexibility in test setups, but the associated optimization problem is computationally expensive to solve by numerical methods. Our solution is to train a regression-based neural network for inferring bending stiffness parameters, directly from drape features captured in the real world. Specifically, we choose the Cusick drape test method and treat multiple-view depth images as the feature vector. To effectively and efficiently train our network, we develop a highly expressive and physically validated bending stiffness model, and we use the traditional cantilever test to collect the parameters of this model for 618 real-world fabrics. Given the whole parameter data set, we then construct a parameter subspace, generate new samples within the sub-space, and finally simulate and augment synthetic data for training purposes. The experiment shows that our trained system can replace cantilever tests for quick, reliable and effective estimation of simulation-ready parameters. Thanks to the use of the system, our simulator can now faithfully simulate bending effects comparable to those in the real world.
Computing Medial Axis Transform with Feature Preservation via Restricted Power Diagram
Authors: Wang Ningna , Wang Bin , Wang Wenping , Guo Xiaohu
Published: November 2022

We propose a novel framework for computing the medial axis transform of 3D shapes while preserving their
medial features
via
restricted power diagram
(RPD). Medial features, including
external features
such as the sharp edges and corners of the input mesh surface and
internal features
such as the seams and junctions of medial axis, are important shape descriptors both topologically and geometrically. However, existing medial axis approximation methods fail to capture and preserve them due to the fundamentally under-sampling in the vicinity of medial features, and the difficulty to build their correct connections. In this paper we use the RPD of medial spheres and its affiliated structures to help solve these challenges. The dual structure of RPD provides the connectivity of medial spheres. The surfacic
restricted power cell
(RPC) of each medial sphere provides the tangential surface regions that these spheres have contact with. The connected components (CC) of surfacic RPC give us the classification of each sphere, to be on a medial sheet, a seam, or a junction. They allow us to detect insufficient sphere sampling around medial features and develop necessary conditions to preserve them. Using this RPD-based framework, we are able to construct high quality medial meshes with features preserved. Compared with existing sampling-based or voxel-based methods, our method is the first one that can preserve not only external features but also internal features of medial axes.
NeuralMarker
Authors: Huang Zhaoyang , Pan Xiaokun , Pan Weihong , Bian Weikang , Xu Yan , Cheung Ka Chun , Zhang Guofeng , Li Hongsheng
Published: November 2022

We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker. Conventionally, this problem is addressed by fitting a homography model based on sparse feature matching. However, they are only able to handle plane-like markers and the sparse features do not sufficiently utilize appearance information. In this paper, we propose a novel framework NeuralMarker, training a neural network estimating dense marker correspondences under various challenging conditions, such as marker deformation, harsh lighting, etc. Deep learning has presented an excellent performance in correspondence learning once provided with sufficient training data. However, annotating pixel-wise dense correspondence for training marker correspondence is too expensive. We observe that the challenges of marker correspondence estimation come from two individual aspects: geometry variation and appearance variation. We, therefore, design two components addressing these two challenges in NeuralMarker. First, we create a synthetic dataset FlyingMarkers containing marker-image pairs with ground truth dense correspondences. By training with FlyingMarkers, the neural network is encouraged to capture various marker motions. Second, we propose the novel Symmetric Epipolar Distance (SED) loss, which enables learning dense correspondence from posed images. Learning with the SED loss and the cross-lighting posed images collected by Structure-from-Motion (SfM), NeuralMarker is remarkably robust in harsh lighting environments and avoids synthetic image bias. Besides, we also propose a novel marker correspondence evaluation method circumstancing annotations on real marker-image pairs and create a new benchmark. We show that NeuralMarker significantly outperforms previous methods and enables new interesting applications, including Augmented Reality (AR) and video editing.