bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on the emergency capacity of coal mine enterprises in Longdong Area based on D-FAHP method
Authors: Yang Fengfeng , Zhang Jufeng , Jin Bangxin , Wang Siyang , Xi Caixia 
Published: May 2023

AbstractEmergency capability assessment is a complex system with multiple factors, variables and levels. Incomplete and uncertain assess information often occurs during assessment. Based on this, a method combining D-number theory and fuzzy analytic Hierarchy process (FAHP) is proposed to study the emergency capacity of coal enterprises in Longdong area. On the basis of analyzing the limitation of D-S evidence theory, the D-number theory was optimized and improved. According to the principles of systematicness, feasibility, scientificity and timeliness, a hierarchical structure model of enterprise emergency capability assessment was constructed from the perspective of pre-incident, mid-incident and post-incident, which consisted of 4 first-level indicators and 18 s-level indicators. The weight and importance of the assessment index of emergency response capability are calculated by organically integrating the D-number preference relation with the hierarchy structure. Combined with the assessment results of experts, a quantitative analysis and evaluation of the emergency response capacity of a coal enterprise was conducted by using FAHP. The comprehensive score of the enterprise's emergency response capability was 80.45, and the level of emergency response capacity was "good". The research results show that the D-FAHP method has high reliability in evaluating the emergency response capability of coal enterprises, avoiding the impact of uncertain and incomplete information on the assessment results. This can not only effectively identify the weak links in emergency management, but also meet the emergency decision-making needs of enterprises in the emergency state, which has important guiding significance to improve the ability and level of enterprise emergency management.
Percutaneous transluminal angioplasty and stenting vs aggressive medical management on stroke or intracranial atherosclerotic stenosis: a systematic review and meta-analysis
Authors: Lai Zhiyu , Peng Mingqiang , He Haoming , Li Yingbin , Bai Xiaoxin , Cai Jun 
Published: May 2023

AbstractThere are currently two main treatment strategies mainly for high-risk patients: percutaneous transluminal angioplasty and stenting (PTAS) and aggressive medical management (AMM). However, the choice between PTAS or AMM remains controversial for patients with stroke or intracranial atherosclerotic stenosis (ICAS). The investigators searched the PubMed, Web of Science, Embase, Scopus, and Cochrane library databases. Randomized controlled trial (RCT) comparing PTAS and AMM for patients with stroke or ICAS were selected. RevMan 5.3 was used to analyze the results and assess risk of bias. The primary endpoints are stroke and death within 30 days after enrollment, or ischemic stroke in the territory of the qualifying artery beyond 30 days, and entire follow-up endpoints. The secondary outcomes were the disabling or fatal stroke, and incidence of death within 3 years. Four studies, 989 patients were included in this article. The AMM group was superior in the entire follow-up endpoint (OR 0.56; 95% CI 0.40, 0.79). The AMM also better in primary endpoint within 30 days (OR 0.32; 95% CI 0.17, 0.61). There was no significant difference beyond 30 days (OR 1.08; 95% CI 0.63, 1.86). The remaining outcomes, such as stroke and death, were not significantly different (P > 0.05). This meta-analysis shows AMM is significantly more effective than PTAS in subjects with ICAS due to the high rate of periprocedural stroke (OR 0.32; 95% CI 0.17, 0.61) and stroke during the entire follow-up (OR 0.56; 95% CI 0.40, 0.79) associated with PTAS. Furthermore, PTAS offers no additional benefits over AMM beyond 30 days (OR 1.08; 95% CI 0.63, 1.86).
Comprehensive analysis of mitophagy in HPV-related head and neck squamous cell carcinoma
Authors: Yanan Li , Hui Liang , Zhuo Cheng , Longqing Ding , Ran Sun 
Published: May 2023

AbstractHead and neck squamous cell carcinoma (HNSCC) is a common tumour type in otorhinolaryngology, and its occurrence is related to long-term exposure to tobacco and alcohol. Recently, HPV infection has become an increasingly important contributor to HNSCC, and HPV-associated HNSCC has a different clinical course and better prognosis than non-HPV-associated HNSCC. However, the exact molecular mechanism of HNSCC is unclear. Here, we obtained data from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) to analyse the mitophagy process and related influencing factors of HPV-associated HNSCC via the integration of bioinformatics analysis and experimental validation. We found that in HPV-associated HNSCC, process of mitophagy affects tumour development, immune cell infiltration and prognosis. In the mitophagy process of HPV-related HNSCC: NOS2, IL17REL, TMSB15A, TUBB4A and other hub genes showed significantly higher expression levels than in non-HPV-related HNSCC. Furthermore, this was also confirmed by quantitative real-time PCR (qRT‒PCR), which was used to detect the expression of differentially expressed genes in HNSCC tissues. Furthermore, we found that the unique immunological characteristics by expressing CD8+ T cell in a high level in HPV-related HNSCC, and the scores obtained from the score model affected the prognosis of patients. In conclusion, our study revealed the unique biomolecular signature of mitophagy in HPV-associated HNSCC, which may contribute to the development of precise treatment regimens for HPV-associated HNSCC patients.
A hybrid approach to full-scale reconstruction of renal arterial network
Authors: Xu Peidi , Holstein-Rathlou Niels-Henrik , Søgaard Stinne Byrholdt , Gundlach Carsten , Sørensen Charlotte Mehlin , Erleben Kenny , Sosnovtseva Olga , Darkner Sune 
Published: May 2023

AbstractThe renal vasculature, acting as a resource distribution network, plays an important role in both the physiology and pathophysiology of the kidney. However, no imaging techniques allow an assessment of the structure and function of the renal vasculature due to limited spatial and temporal resolution. To develop realistic computer simulations of renal function, and to develop new image-based diagnostic methods based on artificial intelligence, it is necessary to have a realistic full-scale model of the renal vasculature. We propose a hybrid framework to build subject-specific models of the renal vascular network by using semi-automated segmentation of large arteries and estimation of cortex area from a micro-CT scan as a starting point, and by adopting the Global Constructive Optimization algorithm for generating smaller vessels. Our results show a close agreement between the reconstructed vasculature and existing anatomical data obtained from a rat kidney with respect to morphometric and hemodynamic parameters.
Two legume fatty acid amide hydrolase isoforms with distinct preferences for microbial- and plant-derived acylamides
Authors: Arias-Gaguancela Omar , Herrell Emily , Aziz Mina , Chapman Kent D. 
Published: May 2023

AbstractFatty acid amide hydrolase (FAAH) is a widely conserved amidase in eukaryotes, perhaps best known for inactivating N-acylethanolamine lipid mediators. However, FAAH enzymes hydrolyze a wide range of acylamide substrates. Analysis of FAAHs from multiple angiosperm species revealed two conserved phylogenetic groups that differed in key conserved residues in the substrate binding pocket. While the foundation group of plant FAAHs, designated FAAH1, has been studied at the structural and functional level in Arabidopsis thaliana, nothing is known about FAAH2 members. Here, we combined computational and biochemical approaches to compare the structural and enzymatic properties of two FAAH isoforms in the legume Medicago truncatula designated MtFAAH1 and MtFAAH2a. Differences in structural and physicochemical properties of the substrate binding pockets, predicted from homology modeling, molecular docking, and molecular dynamic simulation experiments, suggested that these two FAAH isoforms would exhibit differences in their amidohydrolase activity profiles. Indeed, kinetic studies of purified, recombinant MtFAAHs indicated a reciprocal preference for acylamide substrates with MtFAAH1 more efficiently utilizing long-chain acylamides, and MtFAAH2a more efficiently hydrolyzing short-chain and aromatic acylamides. This first report of the enzymatic behavior of two phylogenetically distinct plant FAAHs will provide a foundation for further investigations regarding FAAH isoforms in legumes and other plant species.
Telemedicine and the environment: life cycle environmental emissions from in-person and virtual clinic visits
Authors: Thiel Cassandra L. , Mehta Natasha , Sejo Cory Sean , Qureshi Lubna , Moyer Meagan , Valentino Vincent , Saleh Jason 
Published: May 2023

AbstractConcern over climate change is growing in the healthcare space, and telemedicine has been rapidly expanding since the start of the COVID19 pandemic. Understanding the various sources of environmental emissions from clinic visits—both virtual and in-person—will help create a more sustainable healthcare system. This study uses a Life Cycle Assessment with retrospective clinical data from Stanford Health Care (SHC) in 2019–2021 to determine the environmental emissions associated with in-person and virtual clinic visits. SHC saw 13% increase in clinic visits, but due to the rise in telemedicine services, the Greenhouse Gas emissions (GHGs) from these visits decreased 36% between 2019 and 2021. Telemedicine (phone and video appointments) helped SHC avoid approximately 17,000 metric tons of GHGs in 2021. Some departments, such as psychiatry and cancer achieved greater GHG reductions, as they were able to perform more virtual visits. Telemedicine is an important component for the reduction of GHGs in healthcare systems; however, telemedicine cannot replace every clinic visit and proper triaging and tracking systems should be in place to avoid duplicative care.
Light-sheets and smart microscopy, an exciting future is dawning
Authors: Daetwyler Stephan , Fiolka Reto Paul 
Published: May 2023

AbstractLight-sheet fluorescence microscopy has transformed our ability to visualize and quantitatively measure biological processes rapidly and over long time periods. In this review, we discuss current and future developments in light-sheet fluorescence microscopy that we expect to further expand its capabilities. This includes smart and adaptive imaging schemes to overcome traditional imaging trade-offs, i.e., spatiotemporal resolution, field of view and sample health. In smart microscopy, a microscope will autonomously decide where, when, what and how to image. We further assess how image restoration techniques provide avenues to overcome these tradeoffs and how “open top” light-sheet microscopes may enable multi-modal imaging with high throughput. As such, we predict that light-sheet microscopy will fulfill an important role in biomedical and clinical imaging in the future.
Scale-free dynamics in the core-periphery topography and task alignment decline from conscious to unconscious states
Authors: Klar Philipp , Çatal Yasir , Langner Robert , Huang Zirui , Northoff Georg 
Published: May 2023

AbstractScale-free physiological processes are ubiquitous in the human organism. Resting-state functional MRI studies observed the loss of scale-free dynamics under anesthesia. In contrast, the modulation of scale-free dynamics during task-related activity remains an open question. We investigate scale-free dynamics in the cerebral cortex’s unimodal periphery and transmodal core topography in rest and task states during three conscious levels (awake, sedation, and anesthesia) complemented by computational modelling (Stuart-Landau model). The empirical findings demonstrate that the loss of the brain’s intrinsic scale-free dynamics in the core-periphery topography during anesthesia, where pink noise transforms into white noise, disrupts the brain’s neuronal alignment with the task’s temporal structure. The computational model shows that the stimuli’s scale-free dynamics, namely pink noise distinguishes from brown and white noise, also modulate task-related activity. Together, we provide evidence for two mechanisms of consciousness, temporo-spatial nestedness and alignment, suggested by the Temporo-Spatial Theory of Consciousness (TTC).
Non-thermal evolution of dense plasmas driven by intense x-ray fields
Authors: Ren Shenyuan , Shi Yuanfeng , van den Berg Quincy Y. , Kasim Muhammad F. , Chung Hyun-Kyung , Fernandez-Tello Elisa V. , Velarde Pedro , Wark Justin S. , Vinko Sam M. 
Published: May 2023

AbstractThe advent of x-ray free-electron lasers has enabled a range of new experimental investigations into the properties of matter driven to extreme conditions via intense x-ray-matter interactions. The femtosecond timescales of these interactions lead to the creation of transient high-energy-density plasmas, where both the electrons and the ions may be far from local thermodynamic equilibrium. Predictive modelling of such systems remains challenging because of the different timescales at which electrons and ions thermalize, and because of the vast number of atomic configurations required to describe highly-ionized plasmas. Here we present CCFLY, a code designed to model the time-dependent evolution of both electron distributions and ion states interacting with intense x-ray fields on ultra-short timescales, far from local thermodynamic equilibrium. We explore how the plasma relaxes to local thermodynamic equilibrium on femtosecond timescales in terms of the charge state distribution, electron density, and temperature.
Human metabolome variation along the upper intestinal tract
Authors: Folz Jacob , Culver Rebecca Neal , Morales Juan Montes , Grembi Jessica , Triadafilopoulos George , Relman David A. , Huang Kerwyn Casey , Shalon Dari , Fiehn Oliver 
Published: May 2023

AbstractMost processing of the human diet occurs in the small intestine. Metabolites in the small intestine originate from host secretions, plus the ingested exposome1and microbial transformations. Here we probe the spatiotemporal variation of upper intestinal luminal contents during routine daily digestion in 15 healthy male and female participants. For this, we use a non-invasive, ingestible sampling device to collect and analyse 274 intestinal samples and 60 corresponding stool homogenates by combining five mass spectrometry assays2,3and 16S rRNA sequencing. We identify 1,909 metabolites, including sulfonolipids and fatty acid esters of hydroxy fatty acids (FAHFA) lipids. We observe that stool and intestinal metabolomes differ dramatically. Food metabolites display trends in dietary biomarkers, unexpected increases in dicarboxylic acids along the intestinal tract and a positive association between luminal keto acids and fruit intake. Diet-derived and microbially linked metabolites account for the largest inter-individual differences. Notably, two individuals who had taken antibiotics within 6 months before sampling show large variation in levels of bioactive FAHFAs and sulfonolipids and other microbially related metabolites. From inter-individual variation, we identifyBlautiaspecies as a candidate to be involved in FAHFA metabolism. In conclusion, non-invasive, in vivo sampling of the human small intestine and ascending colon under physiological conditions reveals links between diet, host and microbial metabolism.
Strong and tough magnesium-MAX phase composites with nacre-like lamellar and brick-and-mortar architectures
Authors: Liu Yanyan , Xie Xi , Liu Zengqian , Yu Qin , Wang Xuegang , Wang Shaogang , Jia Qing , Zhang Zhefeng , Yang Rui , Ritchie Robert O. 
Published: May 2023

AbstractBioinspired nacre-like structures are effective in toughening materials, yet are difficult to construct in magnesium-ceramic systems. Here, a set of magnesium-MAX phase composites with nacre-like lamellar and brick-and-mortar architectures are fabricated by pressureless infiltration of the magnesium melt into ice-templated Ti3AlC2 ceramic scaffolds. The structure and mechanical properties of the composites are elucidated with a special focus on the effects of the types of architectures (lamellar or brick-and-mortar) and matrices (pure magnesium or AZ91D alloy) on the toughening mechanisms. The nacre-like architectures are found to play a role in blunting the cracks via plastic deformation and microcracking, and shielding the cracks from applied stress by promoting crack deflection and uncracked-ligament bridging mechanisms. These composites achieve a good combination of specific strength and fracture toughness, which are superior to many other reported magnesium-ceramic and nacre-like metal-ceramic composite materials.
Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson’s disease
Authors: Hadisurya Marco , Li Li , Kuwaranancharoen Kananart , Wu Xiaofeng , Lee Zheng-Chi , Alcalay Roy N. , Padmanabhan Shalini , Tao W. Andy , Iliuk Anton 
Published: May 2023

Abstract
Background
Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been recognized as genetic risk factors for Parkinson’s disease (PD). However, compared to cancer, fewer genetic mutations contribute to the cause of PD, propelling the search for protein biomarkers for early detection of the disease.

Methods
Utilizing 138 urine samples from four groups, healthy individuals (control), healthy individuals with G2019S mutation in the LRRK2 gene (non-manifesting carrier/NMC), PD individuals without G2019S mutation (idiopathic PD/iPD), and PD individuals with G2019S mutation (LRRK2 PD), we applied a proteomics strategy to determine potential diagnostic biomarkers for PD from urinary extracellular vesicles (EVs).

Results
After efficient isolation of urinary EVs through chemical affinity followed by mass spectrometric analyses of EV peptides and enriched phosphopeptides, we identify and quantify 4476 unique proteins and 2680 unique phosphoproteins. We detect multiple proteins and phosphoproteins elevated in PD EVs that are known to be involved in important PD pathways, in particular the autophagy pathway, as well as neuronal cell death, neuroinflammation, and formation of amyloid fibrils. We establish a panel of proteins and phosphoproteins as novel candidates for disease biomarkers and substantiate the biomarkers using machine learning, ROC, clinical correlation, and in-depth network analysis. Several putative disease biomarkers are further partially validated in patients with PD using parallel reaction monitoring (PRM) and immunoassay for targeted quantitation.

Conclusions
These findings demonstrate a general strategy of utilizing biofluid EV proteome/phosphoproteome as an outstanding and non-invasive source for a wide range of disease exploration.
Detecting smart meter false data attacks using hierarchical feature clustering and incentive weighted anomaly detection
Authors: Higgins Martin , Stephen Bruce , Wallom David 
Published: May 2023

AbstractSpot pricing is often suggested as a method of increasing demand‐side flexibility in electrical power load. However, few works have considered the vulnerability of spot pricing to financial fraud via false data injection (FDI) style attacks. The authors consider attacks which aim to alter the consumer load profile to exploit intraday price dips. The authors examine an anomaly detection protocol for cyber‐attacks that seek to leverage spot prices for financial gain. In this way the authors outline a methodology for detecting attacks on industrial load smart meters. The authors first create a feature clustering model of the underlying business, segregated by business type. The authors then use these clusters to create an incentive‐weighted anomaly detection protocol for false data attacks against load profiles. This clustering‐based methodology incorporates both the load profile and spot pricing considerations for the detection of injected load profiles. To reduce false positives, the authors model incentive‐based detection, which includes knowledge of spot prices, into the anomaly tracking, enabling the methodology to account for changes in the load profile which are unlikely to be attacks.
Attack‐resilient event‐triggered distributed control strategy of microgrid based on multi‐objective optimization
Authors: Liu Jinglu , Wang Chen , Liu Jingshu , Xie Pengfei 
Published: May 2023

AbstractAs an important form of renewable energy utilization, microgrid (MG) is considered to be the main bearing form of distributed generation in the future. One of the most concerning issues in the operation of MG is how to realize its economic dispatch (ED). Nowadays, distributed algorithms have been increasingly used to solve the economic dispatch problem of MG. However, the MG based on the distributed optimization architecture must bear higher cyber‐attack risks. To address this issue, this paper investigates the distributed robust ED problem of MG. Firstly, a multi‐objective dispatch model of MG using a linear weighted sum (LWS) algorithm is developed, which considers the environmental and economic costs. On this basis, an event‐triggered fully distributed algorithm is proposed, which can effectively reduce communication times. Furthermore, an attack resilient strategy against false data injection (FDI) attacks is implemented in the proposed fully distributed algorithm, which has strong robustness against various colluding attacks and non‐colluding attacks, and can eliminate incorrect measurement of incremental cost and power generation data. Finally, the effectiveness of the proposed distributed control strategy is demonstrated through case studies in this paper.
Adaptive model predictive control for grid‐forming converters to achieve smooth transition from islanded to grid‐connected mode
Authors: Meng Jianhui , Zhang Zhiyi , Zhang Gengmin , Ye Tairan , Zhao Pengfei , Wang Yi , Yang Jian , Yu Jie 
Published: May 2023

AbstractOne of the main capabilities of grid‐forming converters is the ability to operate in both islanded and grid‐connected modes. The grid‐forming converters work autonomously and behave as an AC voltage source when they are isolated from the bulk power system. In a grid‐connected mode, it is necessary for them to offer a set of grid‐forming capabilities for enhancing system inertia and strength. A grid‐forming converter may experience significant fluctuations in voltage, current, and frequency when the transition occurs. This paper investigates an improved adaptive model predictive control (AMPC) method for grid‐forming converters to achieve a smooth transition from islanded to grid‐connected mode and balance the contradiction between frequency stability and response speed. The AMPC method uses the angular frequency and phase angle as the performance indicators and introduces the angular frequency variations to adaptively adjust its weight coefficient in the objective function. The implementations and effects of the proposed AMPC method on the grid‐forming converter are theoretically evaluated. Compared to the conventional control, the proposed control scheme can not only suppress voltage, current, and frequency fluctuations, but also achieve a smooth transition. Additionally, the frequency control strategy in the islanded mode is improved for better independent operation. Finally, experiment tests on a controller‐level hardware‐in‐the‐loop simulation platform are carried out to validate the proposed control strategy for achieving a smooth transition.