bluuebunny/crossref_metadata_2025 huggingface dataset:
A Deep Learning-Based Fault Diagnosis Approach for Power System Equipment via Infrared Image Sensing
Authors: Liu Hechao , Liu Wei
Published: November 2023

Automatic fault diagnosis for power system equipment has always been an essential concern in this industry. Conventionally, such works are conducted by manual patrol inspection, which consumes much human labor and expert knowledge. Fortunately, infrared images can present diagnosis areas inside the equipment via the thermal sensing function. In such context, this work utilizes deep neural network to construct a specific infrared image processing framework that can realize automatic fault diagnosis. Thus in this paper, a deep learning-based fault diagnosis approach for power system equipment via infrared image sensing is proposed. First, a pulse-coupled neural network structure is employed to enhance feature representation for infrared images of the equipment. Next, a fuzzy [Formula: see text]-means (FCM)-based segmentation method is developed to filter diagnosis areas from the infrared images. Finally, a convolution operation-based fault diagnosis operator is adopted to identify the diagnosis types. After that, some simulation experiments are conducted on real-world infrared images on the power system equipment, in order to make the performance evaluation of the proposed approach. The proposal realizes the end-to-end process of feature extraction and fault detection and identification, and avoids the problems of single feature. It is due to manual extraction of fault features, and the inability to detect and identify faults effectively in specific situations and scenarios.
Large deviations for Lévy diffusions in the small noise regime
Authors: Gomes André De Oliveira , Catuogno Pedro José
Published: November 2023

This paper concerns the large deviations regime and the consequent solution of the Kramers problem for a two-time scale stochastic system driven by a common jump noise signal perturbed in small intensity [Formula: see text] and with accelerated jumps by intensity [Formula: see text]. We establish Freidlin–Wentzell estimates for the slow process of the multiscale system in the small noise limit [Formula: see text] using the weak convergence approach to large deviations theory. The core of our proof is the reduction of the large deviations principle to the establishment of a stochastic averaging principle for auxiliary controlled processes. As consequence we solve the first exit time/exit locus problem from a bounded domain containing the stable state of the averaged dynamics for the family of the slow processes in the small noise limit.
How China Deals with COVID-19 Pandemic
Authors: Shi Yong , Qu Yi , Zhang Linzi
Published: November 2023

Currently, the whole world is still suffering from the COVID-19 (variants) pandemic that has been lasting for over three years and resulted in countless losses. Since its outbreak at the end of 2019, China has first suffered, but quickly gained the upper hand through strict epidemic control and emergency management. Despite several recurrences of regional epidemics in 2022, both economic growth and people’s livelihoods have been effectively safeguarded in China, with a regular prevention system established and social life recovery accomplished orderly. How does China deal with this pandemic? What practical measures taken and decisions made could be adopted and shared with other countries? In this paper, these issues are summarized and discussed as progressive lessons for the rest of the world. Though there’s a major shift of pandemic policy in late 2022 and early 2023 in China, this study still provides insightful and beneficial implications to support decision- and policy-makings in future fights against any possible COVID-19 variants until the end of the pandemic.
Analysis of regularized least squares ranking with centered reproducing kernel
Authors: He Fangchao , Zheng Lie
Published: November 2023

The existing results of the regularized least squares ranking (RLSR) algorithm are mainly related to the reproducing kernels. In this paper, we go beyond this limitation by investigating the convergence rates of ranking with centered reproducing kernel (CRK). We develop a new error analysis framework by means of CRK and integral operator. The result shows that the convergence rate of RLSR is still optimal as those in the traditional analysis framework.
The Impact of Social Media Marketing Adoption on Homemade Food Start-ups Performance
Authors: Harb Lana , Al Khasawneh Mohammad Hamdi
Published: November 2023

This study used TAM to achieve the objective of examining the impact of perceived ease of use (PEOU), perceived usefulness (PU), interactivity, perceived value (PV), and critical mass on business performance (BP) mediating buy social media marketing (SMM) adoption. An online survey was distributed to 174 participants in Jordanian homemade food start-ups. AMOS was used to evaluate a sample of 152 valid surveys. This study had seven hypotheses, all of which were supported. The results highlight that PEOU, PU, interactivity, PV, and critical mass have a significant positive impact on SMM adoption. Furthermore, this study found that SMM adoption has a significant impact on business performance. In addition, this study contributes to the existing knowledge related to SMM adoption and is valuable to enterprises.
On the dynamics of a test particle in the field of the de Broglie gravitational waves
Authors: D’Errico Luca , Benedetto Elmo , Feoli Antonio
Published: November 2023

The de Broglie gravitational waves are a solution of the linearized Einstein equations with properties that are absent in the standard gravity waves because they are also longitudinal waves and obey a dispersion relation that leads to an effective mass. Furthermore, they represent a classical realization of a form of dynamics, proposed for quantum particles by de Broglie in 1927. In this paper, we discuss the dynamics of a massive particle in presence of the de Broglie gravity wave. We will compute the analytical expression for the linear and angular momentum of the corpuscle. As an application, we will consider the case in which these oscillations of spacetime are associated to an electron travelling with a velocity equal to [Formula: see text] of the light speed and we will estimate the order of magnitude of the quantities involved. We will show that a nearby positron oscillates and radiates an energy of 1[Formula: see text]eV in [Formula: see text][Formula: see text]s, an effect that is, in principle, measurable.
Geometry of evolutoids and pedaloids for curves on timelike surfaces
Authors: Hua Yuefeng , Liu Haiming
Published: November 2023

In this paper, we focus on geometry of evolutoids and pedaloids for timelike curves and spacelike curves on timelike surfaces. First, by studying an example of a pseudo-circle, we get some properties of timelike curve on timelike surface. Then, we introduce a moving frame along curves and describe the corresponding evolutoids of curves as ruled surfaces. After that, we investigate relationships between pedal surfaces of evolutoids and pedaloids of curves. Moreover, we investigate the singularities of the evolutoids and the pedaloids.
Homological Dimensions of Extriangulated Categories and Recollements
Authors: Gu Weili , Ma Xin , Tan Lingling
Published: November 2023

Let [Formula: see text] be a recollement of extriangulated categories. In this paper we introduce the global dimension and extension dimension of extriangulated categories, and give some upper bounds of global dimensions and extension dimensions of the categories involved in [Formula: see text], which give a simultaneous generalization of some results in recollements of abelian categories and triangulated categories.
On w∞ -Warfield Cotorsion Modules and Krull Domains
Authors: Pu Yongyan , Zhao Wei , Tang Gaohua , Wang Fanggui , Xiao Xuelian
Published: November 2023

Let [Formula: see text] be a commutative domain with 1 and [Formula: see text] [Formula: see text] its field of quotients. In this note an [Formula: see text]-module [Formula: see text] is called [Formula: see text]-Warfield cotorsion if [Formula: see text], where [Formula: see text] denotes the class of all Warfield cotorsion [Formula: see text]-modules and [Formula: see text] the class of all [Formula: see text]-projective [Formula: see text]-modules. It is shown that [Formula: see text] is a PVMD if and only if all [Formula: see text]-cotorsion [Formula: see text]-modules are [Formula: see text]-Warfield cotorsion, and that [Formula: see text] is a Krull domain if and only if every [Formula: see text]-Matlis cotorsion strong [Formula: see text]-module over [Formula: see text] is a [Formula: see text]-Warfield cotorsion [Formula: see text]-module.
Taking into Account Sentient Non-Humans in AI Ambitious Value Learning: Sentientist Coherent Extrapolated Volition
Authors: Moret Adrià R.
Published: November 2023

Ambitious value learning proposals to solve the AI alignment problem and avoid catastrophic outcomes from a possible future misaligned Artificial Superintelligence (ASI), such as Coherent Extrapolated Volition (CEV), have focused on ensuring that an Artificial Superintelligence would try to do what humans would want it to do. However, present and future sentient non-humans, such as non-human animals and possible future digital minds, could also be affected by the ASI’s behavior in morally relevant ways. This paper puts forward Sentientist Coherent Extrapolated Volition, an alternative to CEV, that directly takes into account the interests of all sentient beings. This ambitious value learning proposal would significantly reduce the likelihood of risks of astronomical suffering from the ASI’s behavior, and thus we have very strong pro-tanto moral reasons in favor of implementing it instead of the CEV. This fact is crucial in conducting an adequate cost–benefit analysis between different ambitious value learning proposals.
C2Store: C2 Server Profiles at Your Fingertips
Authors: Jain Vivek , Alam S M Maksudul , Krishnamurthy Srikanth V. , Faloutsos Michalis
Published: November 2023

How can we build a definitive capability for tracking C2 servers? Having a large-scale continuously updating capability would be essential for understanding the spatiotemporal behaviors of C2 servers and, ultimately, for helping contain botnet activities. Unfortunately, existing information from threat intelligence feeds and previous works is often limited to a specific set of botnet families or short-term data collections. Responding to this need, we present C2Store, an initiative to provide the most comprehensive information on C2 servers. Our work makes the following contributions: (a) we develop techniques to collect, verify, and combine C2 server addresses from five types of sources, including uncommon platforms, such as GitHub and Twitter; (b) we create an open-access annotated database of 335,967 C2 servers across 133 malware families, which supports semantically-rich and smart queries; (c) we identify surprising behaviors of C2 servers with respect to their spatiotemporal patterns and behaviors. First, we successfully mine Twitter and GitHub and identify C2 servers with a precision of 97% and 94%, respectively. Furthermore, we find that the threat feeds identify only 24% of the servers in our database, with Twitter and GitHub providing 32%. A surprising observation is the identification of 250 IP addresses, each of which hosts more than 5 C2 servers for different botnet families at the same time. Overall, we envision C2Store as an ongoing effort that will facilitate research by providing timely, historical, and comprehensive C2 server information by critically combining multiple sources of information.
Data-driven Analysis of the Cost-Performance Trade-off of Reconfigurable Intelligent Surfaces in a Production Network
Authors: Rossanese Marco , Garcia-Saavedra Andres , Lutu Andra Elena , Costa Perez Xavier
Published: November 2023

This paper presents a comprehensive study on the deployment of Reconfigurable Intelligent Surfaces (RIS) in urban environments with poor radio coverage. We focus on the city of London, a large metropolis where radio network planning presents unique challenges due to diverse geographical and structural features. Using crowd-sourced datasets, we analyze the Reference Signal Received Power (RSRP) from end-user devices to understand the existing radio coverage landscape of a major Mobile Network Operator (MNO). Our study identifies areas with poor coverage and proposes the deployment of RIS to enhance signal strength and coverage. We selected a set of potential sites for RIS deployment and, combining data from the MNO, data extracted from a real RIS prototype, and a ray-tracing tool, we analyzed the gains of this novel technology with respect to deploying more conventional technologies in terms of RSRP, coverage, and cost-efficiency.

To the best of our knowledge, this is the first data-driven analysis of the cost-efficiency of RIS technology in the production of urban networks. Our findings provide compelling evidence about the potential of RIS as a cost-efficient solution for enhancing radio coverage in complex urban mobile networks. More specifically, our results indicate that large-scale RIS technology, when applied in real-world urban mobile network scenarios, can achieve 72% of the coverage gains attainable by deploying additional cells with only 22% of their Total Cost of Ownership (TCO) over a 5-year timespan. Consequently, RIS technology offers around 3x higher cost-efficiency than other more conventional coverage-enhancing technologies.
Modular Data Plane Verification for Compositional Networks
Authors: Liu Xu , Zhang Peng , Li Hao , Sun Wenbing
Published: November 2023

Modern networks are increasingly using layering and bridging to form a compositional architecture. Layering protocols like VXLAN create multiple overlay networks on top of a single underlay network infrastructure. This makes network configurations even more complex, and error-prone. To check the correctness of such compositional networks, one needs to model the dependency across multiple layers (underlay and overlay) and multiple domains (different VPNs/VPCs). Existing verifiers, which are optimized to scale in single-layer single-domain networks, exhibit scalability limitations when applied to compositional networks. This paper proposes MNV, a modular network verifier that scales to large compositional networks. At its core is a new verification method termed decompose-merge reasoning, which decomposes the network into self-contained modules, verifies each module independently, and merges the verification results. Our experiments show that for a typical data center network virtualized with VXLAN, to check reachability for more than 100 million pairs of subnets, MNV is at least 100x faster than state-of-the-art tools.
Practical Packet Deflection in Datacenters
Authors: Abdous Sepehr , Sharafzadeh Erfan , Ghorbani Soudeh
Published: November 2023

Bursts, sudden surges in network utilization, are a significant root cause of packet loss and high latency in datacenters. Packet deflection, re-routing packets that arrive at a local hotspot to neighboring switches, is shown to be a potent countermeasure against bursts. Unfortunately, existing deflection techniques cannot be implemented in today's datacenter switches. This is because, to minimize packet drops and remain effective under extreme load, existing deflection techniques rely on certain hardware primitives (e.g., extracting packets from arbitrary locations in the queue) that datacenter switches do not support. In this paper, we address the implementability hurdles of packet deflection. This paper proposes heuristics for approximating state-of-the-art deflection techniques in programmable switches. We introduce Simple Deflection which deflects excess traffic to randomly selected, non-congested ports and Preemptive Deflection (PD) in which switches identify the packets likely to be selected for deflection and preemptively deflect them before they are enqueued. We implement and evaluate our techniques on a testbed with Intel Tofino switches. Our testbed evaluations show that Simple and Preemptive Deflection improve the 99th percentile response times by 8× and 425×, respectively, compared to a baseline drop-tail queue under 90% load. Using large-scale network simulations, we show that the performance of our algorithms is close to the deflection techniques that they intend to approximate, e.g., PD achieves 4% lower 99th percentile query completion times (QCT) than Vertigo, a recent deflection technique that cannot be implemented in off-the-shelf switches, and 2.5× lower QCT than ECMP under 95% load.
A Survey on Graph Representation Learning Methods
Authors: Khoshraftar Shima , An Aijun
Published: November 2023

Graph representation learning has been a very active research area in recent years. The goal of graph representation learning is to generate graph representation vectors that capture the structure and features of large graphs accurately. This is especially important because the quality of the graph representation vectors will affect the performance of these vectors in downstream tasks such as node classification, link prediction and anomaly detection. Many techniques have been proposed for generating effective graph representation vectors, which generally fall into two categories: traditional graph embedding methods and graph neural network (GNN)–based methods. These methods can be applied to both static and dynamic graphs. A static graph is a single fixed graph, whereas a dynamic graph evolves over time and its nodes and edges can be added or deleted from the graph. In this survey, we review the graph-embedding methods in both traditional and GNN-based categories for both static and dynamic graphs and include the recent papers published until the time of submission. In addition, we summarize a number of limitations of GNNs and the proposed solutions to these limitations. Such a summary has not been provided in previous surveys. Finally, we explore some open and ongoing research directions for future work.
Environmental Control of Hypocotyl Elongation
Authors: Krahmer Johanna , Fankhauser Christian
Published: November 2023

The hypocotyl is the embryonic stem connecting the primary root to the cotyledons. Hypocotyl length varies tremendously depending on the conditions. This developmental plasticity and the simplicity of the organ explain its success as a model for growth regulation. Light and temperature are prominent growth-controlling cues, using shared signaling elements. Mechanisms controlling hypocotyl elongation in etiolated seedlings reaching the light differ from those in photoautotrophic seedlings. However, many common growth regulators intervene in both situations. Multiple photoreceptors including phytochromes, which also respond to temperature, control the activity of several transcription factors, thereby eliciting rapid transcriptional reprogramming. Hypocotyl growth often depends on sensing in green tissues and interorgan communication comprising auxin. Hypocotyl auxin, in conjunction with other hormones, determines epidermal cell elongation. Plants facing cues with opposite effects on growth control hypocotyl elongation through intricate mechanisms. We discuss the status of the field and end by highlighting open questions.
Seladelpar combined with complementary therapies improves fibrosis, inflammation, and liver injury in a mouse model of nonalcoholic steatohepatitis
Authors: Choi Yun-Jung , Johnson Jeff D. , Lee Jin-Ju , Song Jiangao , Matthews Marcy , Hellerstein Marc K. , McWherter Charles A.
Published: November 2023

NASH is a chronic, progressive, and increasingly problematic liver disease that has been resistant to treatment with individual therapeutics. In this study using a diet-induced mouse model of NASH, we found that the PPARδ agonist seladelpar reduced fibrosis and NASH pathology alone and in combinations with a GLP-1-R agonist (liraglutide) or an ASK1 inhibitor (selonsertib). Liver transcriptome analysis comparing each agent and coadministration suggests seladelpar should be effective in combination with a variety of therapeutics.
Palliative Extubation in Pediatric Patients in the Intensive Care Unit and at Home: A Scoping Review
Authors: Neto Joana , Casimiro Hugo Jorge , Reis-Pina Paulo
Published: November 2023

Aim. This scoping review is aimed at systematically mapping the evidence on palliative extubation in the pediatric intensive care unit. Methods. MEDLINE, EBSCO, and Cochrane databases were searched for articles published between January 2018 and December 2022, in English. Critical appraisal of sources of evidence was done using the Joanna Briggs Institute tools. PRISMA guidelines for scoping reviews were followed. Results. Six studies were included, with 366 patients, from the USA (

n
=
4

), Brazil (

n
=
1

), and Germany (

n
=
1

). Three were high-quality studies, two were moderate, and one was a low-quality study. Most studies were retrospective analysis; two were narrative approaches; two were evidence-based recommendation and quality improvement project; one study was a prospective intervention. Conclusion. Symptom control is crucial pre- and postextubation. A checklist (symptom management and family support) and a postdebriefing template improve team communication and staff support postextubation. Critical care transports from the hospital are feasible to provide extubation at home. A framework addressing common planning challenges and resource management is recommended for extubation at home. The provision of pediatric palliative extubation is necessary since futile measures and prolongation of suffering violate the principle of nonmaleficence. Future research on this subject will result in more benefits for patients, parents, and professionals.
Decline in the Incidence of Distant Recurrence of Breast Cancer: A Population-Based Health Record Linkage Study, Australia 2001–2016
Authors: Lord Sarah J. , Daniels Benjamin , O'Connell Dianne L. , Kiely Belinda E. , Beith Jane , Smith Andrea L. , Pearson Sallie-Anne , Chiew Kim-Lin , Bulsara Max K. , Houssami Nehmat
Published: November 2023

Background:

We investigated differences in cumulative incidence of first distant recurrence (DR) following non-metastatic breast cancer over a time period when new adjuvant therapies became available in Australia.

Methods:

We conducted a health record linkage study of females with localized (T1–3N0) or regional (T4 or N+) breast cancer in the New South Wales Cancer Registry in 2001 to 2002 and 2006 to 2007. We linked cancer registry records with administrative records from hospitals, dispensed medicines, radiotherapy services, and death registrations to estimate the 9-year cumulative incidence of DR and describe use of adjuvant treatment.

Results:

The study included 13,170 women (2001–2002 n = 6,338, 2006–2007 n = 6,832). The 9-year cumulative incidence of DR was 3.6% [95% confidence interval (CI), 2.3%–4.9%] lower for 2006–2007 diagnoses (15.0%) than 2001–2002 (18.6%). Differences in the annual hazard of DR between cohorts were largest in year two. DR incidence declined for localized and regional disease. Decline was largest for ages <40 years (absolute difference, 14.4%; 95% CI, 8.3%–20.6%), whereas their use of adjuvant chemotherapy (2001–2002 49%, 2006–2007 75%) and HER2-targeted therapy (2001–2002 0%, 2006–2007 16%) increased. DR did not decline for ages ≥70 years (absolute difference, 0.9%; 95% CI, −3.6%–1.8%) who had low use of adjuvant chemotherapy and HER2-targeted therapy.

Conclusions:

This whole-of-population study suggests that DR incidence declined over time. Decline was largest for younger ages, coinciding with changes to adjuvant breast cancer therapy.

Impact:

Study findings support the need for trials addressing questions relevant to older people and cancer registry surveillance of DR to inform cancer control programs.
Data from First-in-Human, Phase 1 Dose-Escalation Study of Biparatopic Anti-HER2 Antibody–Drug Conjugate MEDI4276 in Patients with HER2-positive Advanced Breast or Gastric Cancer
Authors: Pegram Mark D. , Hamilton Erika P. , Tan Antoinette R. , Storniolo Anna Maria , Balic Kemal , Rosenbaum Anton I. , Liang Meina , He Peng , Marshall Shannon , Scheuber Anita , Das Mayukh , Patel Manish R.
Published: November 2023

Abstract
MEDI4276 is a biparatopic tetravalent antibody targeting two nonoverlapping epitopes in subdomains 2 and 4 of the HER2 ecto-domain, with site-specific conjugation to a tubulysin-based microtubule inhibitor payload. MEDI4276 demonstrates enhanced cellular internalization and cytolysis of HER2-positive tumor cells in vitro. This was a first-in-human, dose-escalation clinical trial in patients with HER2-positive advanced or metastatic breast cancer or gastric cancer. MEDI4276 doses escalated from 0.05 to 0.9 mg/kg (60- to 90-minute intravenous infusion every 3 weeks). Primary endpoints were safety and tolerability; secondary endpoints included antitumor activity (objective response, progression-free survival, and overall survival), pharmacokinetics, and immunogenicity. Forty-seven patients (median age 59 years; median of seven prior treatment regimens) were treated. The maximum tolerated dose was exceeded at 0.9 mg/kg with two patients experiencing dose-limiting toxicities (DLTs) of grade 3 liver function test (LFT) increases, one of whom also had grade 3 diarrhea, which resolved. Two additional patients reported DLTs of grade 3 LFT increases at lower doses (0.4 and 0.6 mg/kg). The most common (all grade) drug-related adverse events (AEs) were nausea (59.6%), fatigue (44.7%), aspartate aminotransferase (AST) increased (42.6%), and vomiting (38.3%). The most common grade 3/4 drug-related AE was AST increased (21.3%). Five patients had drug-related AEs leading to treatment discontinuation. In the as-treated population, there was one complete response (0.5 mg/kg; breast cancer), and two partial responses (0.6 and 0.75 mg/kg; breast cancer)—all had prior trastuzumab, pertuzumab, and ado-trastuzumab emtansine (T-DM1). MEDI4276 has demonstrable clinical activity but displays intolerable toxicity at doses >0.3 mg/kg.
Modeling Molecular Pathogenesis of Idiopathic Pulmonary Fibrosis-Associated Lung Cancer in Mice
Authors: Barravecchia Ivana , Lee Jennifer M. , Manassa Jason , Magnuson Brian , Ferris Sarah F. , Cavanaugh Sophia , Steele Nina G. , Espinoza Carlos E. , Galban Craig J. , Ramnath Nithya , Frankel Timothy L. , Pasca di Magliano Marina , Galban Stefanie
Published: November 2023

Idiopathic pulmonary fibrosis (IPF) is characterized by progressive, often fatal loss of lung function due to overactive collagen production and tissue scarring. Patients with IPF have a sevenfold-increased risk of developing lung cancer. The COVID-19 pandemic has increased the number of patients with lung diseases, and infection can worsen prognoses for those with chronic lung diseases and disease-associated cancer. Understanding the molecular pathogenesis of IPF-associated lung cancer is imperative for identifying diagnostic biomarkers and targeted therapies that will facilitate prevention of IPF and progression to lung cancer. To understand how IPF-associated fibroblast activation, matrix remodeling, epithelial-to-mesenchymal transition (EMT), and immune modulation influences lung cancer predisposition, we developed a mouse model to recapitulate the molecular pathogenesis of pulmonary fibrosis–associated lung cancer using the bleomycin and Lewis lung carcinoma models. We demonstrate that development of pulmonary fibrosis–associated lung cancer is likely linked to increased abundance of tumor-associated macrophages and a unique gene signature that supports an immune-suppressive microenvironment through secreted factors. Not surprisingly, preexisting fibrosis provides a pre-metastatic niche and results in augmented tumor growth, and tumors associated with bleomycin-induced fibrosis are characterized by a dramatic loss of cytokeratin expression, indicative of EMT.

Implications:

This characterization of tumors associated with lung diseases provides new therapeutic targets that may aid in the development of treatment paradigms for lung cancer patients with preexisting pulmonary diseases.
Endothelial Biomarkers in Critically Ill COVID-19 Patients: Potential Predictors of the Need for Dialysis
Authors: Zaranza Marza de Sousa , Meneses Gdayllon Cavalcante , Oriá Reinaldo Barreto , Martins Alice Maria Costa , Aragão Natalia Linhares Ponte , Aragão Nilcyeli Linhares , de Andrade Saskya Roberta Rodrigues , Lopes Nicole Coelho , de Araújo Letícia Machado , Santos Ranieri Sales de Souza , Guimarães Álvaro Rolim , Lázaro Ana Paula Pires , Beliero Andrea Mazza , Dantas Márcia Maria Pinheiro , Mota Sandra Mara Brasileiro , da Silva Júnior Geraldo Bezerra , Albuquerque Polianna Lemos Moura Moreira , Daher Elizabeth De Francesco
Published: November 2023

Introduction: The aim of this was to evaluate the function of vascular biomarkers to predict the need for hemodialysis in critically ill patients with COVID-19. Methods: This is a prospective study with 58 critically ill patients due to COVID-19 infection. Laboratory tests in general and vascular biomarkers, such as VCAM-1, syndecan-1, angiopoietin-1, and angiopoietin-2, were quantified on intensive care unit (ICU) admission. Results: There was a 40% death rate. VCAM and Ang-2/Ang-1 ratio on ICU admission were associated with the need for hemodialysis. Vascular biomarkers (VCAM-1, syndecan-1, angiopoietin-2/angiopoietin-1 ratio) were predictors of death and their cutoff values were useful to stratify patients with a worse prognosis. In the multivariate cox regression analysis with adjusted models, VCAM-1 (OR 1.13 [CI 95%: 1.01–1.27]; p = 0.034) and Ang-2/Ang-1 ratio (OR 4.87 [CI 95%: 1.732–13.719]; p = 0.003) were associated with the need for dialysis. Conclusion: Vascular biomarkers, mostly VCAM-1 and Ang-2/Ang-1 ratio, showed better efficiency to predict the need for hemodialysis in critically ill COVID-19 patients.
Performance of a Diagnostic Model for the Presence of Unruptured Intracranial Aneurysms in the General Population
Authors: Klieverik Vita M. , Roozenbeek Bob , Cras Tim Y. , Vernooij Meike W. , Geerlings Mirjam I. , Bos Daniel , Ruigrok Ynte M.
Published: November 2023

Introduction: The prevalence of unruptured intracranial aneurysms (UIAs) in the general population is 3%. Aneurysmal subarachnoid hemorrhage can be prevented by screening for UIAs followed by monitoring and, if needed, preventive neurosurgical or endovascular treatment of identified UIAs. Therefore, we developed a diagnostic model for the presence of UIAs in the general population to help identify persons at high risk of having UIAs. Methods: Between 2005 and 2015, participants from the population-based Rotterdam Study underwent brain magnetic resonance imaging at 1.5 T, on which the presence of incidental UIAs was evaluated. We developed a multivariable logistic regression model using candidate diagnostic markers that were selected based on the literature, including sex, age, hypertension, smoking, hypercholesterolemia, diabetes, alcohol, and their interactions. We corrected for overfitting using bootstrapping. Model performance was assessed with discrimination, calibration, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: 5,835 persons were included (55.0% women, mean age 64.9 ± 10.9 years) with a 2.2% UIA prevalence. Sex, age, hypertension, smoking, diabetes, and interactions of sex with age, hypertension, and smoking were independent diagnostic markers. The resulting model had a c-statistic of 0.65 (95% confidence interval [CI]: 0.60–0.68) and 56% sensitivity, 52% specificity, 98% PPV, and 3% NPV for UIA presence at a cutoff value of 4%. Because of interactions with sex, additional models for men and women separately were developed. The model for men had a c-statistic of 0.70 (95% CI: 0.62–0.78) with age, hypertension, and smoking as diagnostic markers and comparable additional performance values as for the full model. The model for women had a c-statistic of 0.58 (95% CI: 0.52–0.63) with smoking as the only diagnostic marker. Conclusion: Our diagnostic model had insufficient performance to help identify persons at high risk of having UIAs in the general population. Rather, it provides insight in risk factors contributing to UIA risk and shows that these may be in part sex-specific.
NT‐proBNP Mediates the Association Between FGF23 and All‐Cause Mortality in Individuals With Type 2 Diabetes
Authors: van der Vaart Amarens , Bakker Stephan J. L. , Laverman Gozewijn D. , van Dijk Peter R. , de Borst Martin H.
Published: November 2023

Background

FGF23 (fibroblast growth factor 23) is associated with a higher mortality risk in type 2 diabetes, but the mechanism is unclear. We aimed to study whether NT‐proBNP (N‐terminal pro‐brain natriuretic peptide) mediates the association between FGF23 and mortality.

Methods and Results

We analyzed C‐terminal FGF23 and NT‐proBNP levels in 399 patients with type 2 diabetes. Cox regression analyses were performed, followed by mediation analyses using Structural Equation Modeling. During follow‐up of 9.2 [7.6–11.3] years, 117 individuals died. FGF23 was associated with all‐cause mortality, independent of potential confounders (fully adjusted hazard ratio [HR], 2.32 [95% CI, 1.21–4.43],
P
=0.01). The association was lost upon further adjustment for NT‐proBNP (HR, 1.84; 95% CI, 0.91–3.73). NT‐proBNP accounted for 26% of the mediation effect between FGF23 and all‐cause mortality.

Conclusions

These findings suggest that a higher FGF23 level is associated with increased mortality in individuals with type 2 diabetes through an effect on volume homeostasis.
Le quasi-panpsychisme de Nishida Kitarō à la lumière de Gustav Theodor Fechner
Authors: Tremblay Jacynthe
Published: November 2023

Dans son livre Étude sur le bien (1911), Nishida s’inspira de William James, de Gustav Theodor Fechner et d’Ernst Mach pour développer son concept d’expérience pure. Or, il s’avère que ces trois scientifiques professaient ouvertement le panpsychisme, théorie selon laquelle les minéraux, les plantes et les animaux sont vivants et possèdent une nature psychique analogue à celle de l’être humain. Cet article s’attarde surtout aux relations entre Fechner et Nishida, de même qu’à leurs conséquences possibles sur le développement d’un panpsychisme explicite dans l’Étude sur le bien. Dans ses écrits subséquents, Nishida cessa d’accorder l’esprit aux minéraux et aux plantes. Par contraste, il maintint le panpsychisme dans le cas des animaux car, disait-il, l’esprit est la chose la plus répandue dans le règne du vivant. Nishida passa ainsi d’une conception panpsychiste du monde à une conception quasi-panpsychiste.
White Sugar and Dark Colonialism: Reflections on Girmitiyas and Coolies – Towards a new Paradigm of Reconciliation in Fiji
Authors: Ahluwalia Pal
Published: November 2023

The presence of Indians fundamentally altered the political, social and economic landscape of sugar producing nations. In most cases, race, which was used as an important signifier of difference by the colonising power, left these states with a colonial legacy of division and derision which they continue to endure and navigate in such diverse locations as the Caribbean, the West Indies, Fiji, Mauritius and parts of Africa. In the quest for recognition, equality and political status that allows the girmitiyas to celebrate their past, embrace their present and imagine a future where they are enmeshed in the fabric of a new Fiji entail understanding why the declaration of girmit day on May 15th is such a powerful symbolic gesture on the part of the new coalition government.
La communauté méditerranéenne comme utopie du dépassement de l’anthropocène ?
Authors: Quenot Sébastien
Published: November 2023

En tant que hotspot de la diversité culturelle et du réchauffement climatique, la Méditerranée apparait particulièrement exposée aux chocs provoqués par l’anthropocène. Sur cette île de la Méditerranée occidentale, l’analyse d’échantillons de discours relatifs à l’imaginaire corse et de mobilisations sociales et d’innovations juridiques relatives à l’écologie peut-elle nous informer quant à l’avènement d’une communauté méditerranéenne susceptible de transformer le rapport des Méditerranéens à la nature et aux vivants humains ou non-humains ? Ce travail s’appuie notamment sur les travaux d’Achille Mbembé, Philippe Descola et Bruno Latour.
Synergistic Effect of Warming in the Tropical Indian Ocean and North Tropical Atlantic on the Central-Pacific Type of La Niña Based on Observations and CMIP5
Authors: Yang Guang , Zhao Xia , Yuan Dongliang , Zhang Yazhou , Liu Lin , Peng Shiqiu
Published: November 2023

Previous studies have indicated that boreal winter-to-spring sea surface temperature anomalies (SSTA) over the tropical Atlantic or Indian Ocean can trigger the central-Pacific (CP) type of ENSO in the following winter due to winds over the western Pacific. Here, with the aid of observational data and CMIP5 model simulations, we demonstrate that the ability of the winter-to-spring north tropical Atlantic (NTA) SSTA or Indian Ocean Basin (IOB) mode to initiate CP ENSO events in the following winter may strongly depend on each other. Most warming events of the IOB and NTA, which are followed by CP La Niña events, are concomitant. The synergistic effect of the IOB and NTA SSTA may produce greater CP ENSO events in the subsequent winter via Walker circulation adjustments. The impacts between warming and cooling events of the IOB and NTA SSTA are asymmetric. IOB and NTA warmings appear to contribute to the subsequent CP La Niña development, which is much greater than IOB and NTA cooling contributing to CP El Niño. Overall, a combination of the IOB and NTA SSTA precursors may improve predictions of La Niña events.

Significance Statement

Although boreal winter-to-spring sea surface temperature anomalies over the tropical Atlantic or Indian Ocean can trigger central-Pacific (CP) ENSO in the following winter, it is not yet clear whether the effects of these two basins are independent. The purpose of this study is to better understand the joint effect of these two basins on CP ENSO events. We demonstrate that the ability of the north tropical Atlantic (NTA) SSTA to initiate CP ENSO events in the following winter may strongly depend on the state of the Indian Ocean Basin mode (IOB). The synergistic impact of these two basins may produce stronger CP ENSO events. These results highlight the role of three-ocean interactions in ENSO diversity and prediction.
A Global Overview of Missed Nursing Care During the COVID-19 Pandemic: A Systematic Review
Authors: Labrague Leodoro J. , T. Kostovich Carol
Published: November 2023

The coronavirus disease 2019 (COVID-19) pandemic has placed unparalleled pressure on many countries’ healthcare systems, impacting the delivery of health and nursing care services. Despite the growing number of missed care studies during the pandemic, a broader perspective is essential when designing theory-driven strategies to improve nursing care delivery. This review aimed to synthesize evidence of missed nursing care during the COVID-19 pandemic in acute care settings through a systematic review and narrative synthesis. An electronic search of articles published since the emergence of the pandemic was conducted using 5 databases (Scopus, PubMed, Web of Science, CINAHL, and PsycINFO). A total of 470 articles were identified during the initial search, and 10 articles were included in the review. The sample sizes of the studies ranged from 37 to 536 nurses. Results of the content analysis were grouped into 5 categories: (1) prevalence of missed care, (2) frequency of missed care, (3) reasons for missed care, (4) nurses’ and organizational variables contributing to missed care, and (5) work environment elements contributing to missed care. The review’s findings revealed a shift in the nature of missed nursing care during the pandemic, with an emphasis on nursing care tasks vital for the recovery of patients with COVID-19. Despite the unique circumstances brought about by the pandemic, an inadequate nursing workforce continued to be identified as the primary reason for missed care, consistent with the pre-pandemic period.
Undercutting Transit? Exploring Potential Competition Between Automated Vehicles and Public Transportation in the United States
Authors: Kaplan Leah , Helveston John Paul
Published: November 2023

Automated vehicles (AVs) have the potential to dramatically disrupt current transportation patterns and practices. One particular area of concern is AVs’ impacts on public transit systems. If vehicle automation enables significant price decreases or performance improvements for ride-hailing services, some fear that it could undercut public transit, which could have significant implications for the environment and transportation equity. The extent to which individuals adopt automated transportation modes will drive many system-level outcomes, and research on public preferences for AVs is immature and inconclusive. In this study, we used responses from an online choice-based conjoint survey fielded in the Washington, D.C. metropolitan region (N = 1,694) in October 2021 to estimate discrete choice models of public preferences for different automated (ride-hailing, shared ride-hailing, bus) and nonautomated (ride-hailing, shared ride-hailing, bus, rail) modes. We used the estimated models to simulate future marketplace competition across a range of trip scenarios. Respondents on average were only willing to pay a premium for automated modes when a vehicle attendant was also present, limiting the potential cost-savings that AV operators might achieve by removing the driver. Scenario analysis additionally revealed that for trips where good transit options were available, transit remained competitive with automated ride-hailing modes. These results suggest that fears of a mass transition away from transit to AVs may be limited by people’s willingness to use AVs, at least in the short term. Future AV operators should also recognize the presence of an AV attendant as a critical feature for early AV adoption.
Crosswalk Detection from Satellite Imagery for Pedestrian Network Completion
Authors: Verma Rajat , Ukkusuri Satish V.
Published: November 2023

Pedestrian network creation and completion for various tasks in transportation planning engineering generally requires laborious manual labeling of sidewalks and crosswalks. In this study, we employed the deep learning-based object detection model YOLO v5 for detecting crosswalks using Google Maps satellite imagery data of four North American cities. We also tested for two additional scenarios involving two image-processing techniques to exploit the special properties of crosswalks. Observations showed that the original images performed better than with binary thresholding and nearly the same even when noisy regions outside the right-of-way were removed. We proposed an algorithm to assign the detected crosswalks to intersection legs. We demonstrated the effectiveness of this technique for Washington, D.C. and Los Angeles, CA, showing classification accuracy rates of 71% and 89%, respectively. We also showed the influence of increasing distance threshold, a tolerance radius of prediction accuracy, in degrading the classification performance. This method, when combined with existing methods for sidewalk detection from aerial and street view images, could be reasonably used to help complete urban pedestrian networks in cities where high-resolution satellite images are available.
Simulation of Signalized Intersection with Non-Lane-Based Heterogeneous Traffic Conditions Using Cellular Automata
Authors: Singh Mohit Kumar , Ramachandra Rao K.
Published: November 2023

Intersections affect the maneuvering and driving behavior of vehicles. The present study attempts to simulate an isolated signalized intersection with the dimensions obtained through the influence zone of intersections. This model includes several unexplored traffic characteristics observed at the intersection, such as non-lane-based heterogeneity and seepage behavior. The model was calibrated and validated with the field data collected in New Delhi, India. Several measures of performance, such as GEH statistics, Theil’s coefficient, root mean square error, and so forth, were used to validate and benchmark the simulation model. After calibration and validation, the model was used to find delays. The delays obtained from the model, several manuals, and the field were compared and found to be close to the field delays. Further, delays obtained from Indonesian and Canadian manuals were comparatively closer to the delays obtained from the field, whereas delays obtained from the Indian Highway Capacity Manual (2017) and U.S. Highway Capacity Manual (2010) are overestimated. The model presented can be used to benchmark the performance of signalized intersections under a variety of traffic and environmental conditions.
The role of citizen journalism in society: An analysis based on foreign theory and Kazakhstani experience
Authors: Togtarbay Beibit , Zhaksylyk Aibarsha , Mukasheva Manchuk T. , Turzhan Onaigul , Omashev Namazaly O.
Published: November 2023

This study investigates the impact of citizen journalism in Kazakhstan, utilizing quantitative and logical methods, drawing on both foreign and local insights. Findings reveal trust in mainstream media, concerns about bias and recognition of citizen journalism’s value for diverse perspectives. Media professionals acknowledge its significance and express varied opinions on credibility and future development.
Future leaders in a learning health system: Exploring the Health System Impact Fellowship
Authors: Petrie Samuel , Cheng Ivy , McMahon Meghan , Lavis John N.
Published: November 2023

The Canadian health system is reeling following the COVID-19 pandemic. Strains have become growing cracks, with long emergency department wait times, shortage of human health resources, and growing dissatisfaction from both clinicians and patients. To address long-needed health system reform in Canada, a modernization of training is required for the next generation health leaders. The Canadian Institutes of Health Research Health System Impact Fellowship (HSIF) is an example of a well-funded and connected training program which prioritizes embedded research and embedding technically trained scholars with health system partners. The program has been successful in the scope and impact of its training outcomes as well as providing health system partners with a pool of connected and capable scholars. Looking forward, integrating aspects of evidence synthesis from both domestic and international sources and adapting a general contractor approach to implementation within the HSIF could help catalyze learning health system reform in Canada.
What is an Animal? A Philosophical Reflection on the Possibility of a Moral Relationship with Animals
Authors: Zwart Hub
Published: November 2023

Contemporary ethical discourse on animals is influenced partly by a scientific and partly by an anthropomorphic understanding of them. Apparently, we have deprived ourselves of the possibility of a more profound acquaintance with them. In this contribution it is claimed that all ethical theories or statements regarding the moral significance of animals are grounded in an ontological assessment of the animal's way of being. In the course of history, several answers have been put forward to the question of what animals really and basically are. Three of them (namely the animal as a machine, an organism and a being that dwells in an – apparently – restricted world) are discussed. It is argued that the latter (Heideggerian) answer contains a valuable starting point for an ethical reflection on recent changes in the moral relationship between humans and animals.