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Many patients experience anxiety during MRI examinations. However, little attention has been focused on decreasing patient anxiety and minimizing on-site cancellations. Here, we aimed to investigate the effects of aromatherapy and music therapy on alleviating anxiety during MRI examinations.This single-center, double-blinded, randomized control trial was conducted between November 1, 2021, and January 10, 2022. Patients undergoing MRI examinations were assigned randomly into either the aromatherapy group (AG), music therapy group (MG), aromatherapy plus music therapy group (AMTG), or routine care group (RG) at a ratio of 1:1:1:1. Aromatherapy was conducted through inhalation of lavender oil. Music therapy was performed using Pachelbel's Canon in D major. The primary outcome was the change in anxiety before and after the MRI scan, assessed using both the State-Trait Anxiety Inventory form 1 (STAI-1) and Self-Rating Anxiety Scale (SAS). The second outcome was the participant's comfort, measured using Kolcaba's General Comfort Questionnaire (GCQ).A total of 200 participants (mean age: 48.3 ± 14.9 years; 126 [63.0%] females) were enrolled, with 50 per group. The mean anxiety scores of the AMTG showed greater reduction compared with the AG, MG, and RG (ΔSTAI-1: 6.5 vs 2.6 vs 2.7 vs 1.9, p0.001; ΔSAS: 4.0 vs 1.4 vs 1.7 vs 0.6, p0.001). The mean GCQ score of the AMTG was higher compared with the AG, MG, and RG (98.0 vs 92.6 vs 91.2 vs 89.2, respectively, p0.001).Aromatherapy combined with music therapy is effective for reducing patients' anxiety and improving their comfort level during MRI scans.• In this randomized control trial of 200 participants undergoing MRI scans, aromatherapy plus music therapy is effective in reducing STAI-1 and SAS, as well as improving GCQ scores. • Although there was a significant difference between the aromatherapy plus music therapy and the single-intervention modalities, no significant differences were observed between the aromatherapy and music therapy themselves for state anxiety and comfort score. • Aromatherapy plus music therapy is a safe, non-invasive, nonpharmacological, and inexpensive patient-centered intervention for reducing anxiety and improving comfort in adults undergoing MRI examinations.

We consider the consensus problem in a decentralized network, focusing on a compact submanifold that acts as a nonconvex constraint set. By leveraging the proximal smoothness of the compact submanifold, which encompasses the local singleton property and the local Lipschitz continuity of the projection operator on the manifold, and establishing the connection between the projection operator and general retraction, we show that the Riemannian gradient descent with a unit step size has locally linear convergence if the network has a satisfactory level of connectivity. Moreover, based on the geometry of the compact submanifold, we prove that a convexity-like regularity condition, referred to as the restricted secant inequality, always holds in an explicitly characterized neighborhood around the solution set of the nonconvex consensus problem. By leveraging this restricted secant inequality and imposing a weaker connectivity requirement on the decentralized network, we present a comprehensive analysis of the linear convergence of the Riemannian gradient descent, taking into consideration appropriate initialization and step size. Furthermore, if the network is well connected, we demonstrate that the local Lipschitz continuity endowed by proximal smoothness is a sufficient condition for the restricted secant inequality, thus contributing to the local error bound. We believe that our established results will find more application in the consensus problems over a more general proximally smooth set. Numerical experiments are conducted to validate our theoretical findings., 25 pages

Comparative analysis of primate genomes within a phylogenetic context is essential for understanding the evolution of human genetic architecture and primate diversity. We present such a study of 50 primate species spanning 38 genera and 14 families, including 27 genomes first reported here, with many from previously less well represented groups, the New World monkeys and the Strepsirrhini. Our analyses reveal heterogeneous rates of genomic rearrangement and gene evolution across primate lineages. Thousands of genes under positive selection in different lineages play roles in the nervous, skeletal, and digestive systems and may have contributed to primate innovations and adaptations. Our study reveals that many key genomic innovations occurred in the Simiiformes ancestral node and may have had an impact on the adaptive radiation of the Simiiformes and human evolution.

Global warming has led to environmental changes in the alpine Himalayan mountains, with significant glacier retreat, an increase in the area and number of glacial lakes, and an increase in the frequency and scale of glacial lake outburst debris flows, causing significant damage to people and facilities in downstream. In this study, we analyzed the spatial heterogeneity and variations of disaster-forming environments on the north and south areas of the Himalayan, identified the distribution patterns of glacial lake outburst debris flows, and predicted debris flows’ changing trends in the Himalayas. The results demonstrate that the distribution and variations of glaciers and glacial lakes in the Himalayan region have apparent spatial heterogeneity. The Central and South Himalayas are where glaciers and glacial lakes undergo the most dramatic changes. Glacial lakes are widely distributed in the Central Himalayas and southern slopes, with an increase in area and number from 1990-2015. New glacial lakes at higher elevations and alterations in moraine lakes dominate glacial lake variations across the region. Since the 20th century, there have been 249 outbursts of 113 glacial lakes in the Himalayan, Karakorum, and Southeast Tibetan regions, with the majority of outbreaks occurring in the Central and Eastern Himalayas along steep sections of main rivers. In the period 1901-2019, the inflection point for glacial lake outburst hazard is 1966+37/-31 years (median and 95% HDI), and the frequency of glacial lake outbursts proliferates before the inflection point and slowly increases after the break-point; the annual mean temperature changes have opposite trends before and after the inflection point, reflecting the lag effect of glacial lake outbursts on temperature changes. In addition, the measured data were calibrated and down-scaled the future simulated climate prediction data to reveal the spatial and temporal trends of glacial lake outburst debris flow disaster risk under the influence of future climate-causing factors. The annual mean temperature and precipitation in the Himalayas generally exhibited an upward trend in the 21st century, with higher increment speeds of warming and humidification on the northern slopes; Increasing very high and high glacial lake outburst debris flow hazard zones are a consequence of climate change, with a more concentrated distribution in the centre and northwest of the Himalayan Mountains.

Background: Improving meaning in life is beneficial for nursing students to provide better service for patients in the future. As a result, it is important to explore factors affecting meaning in life in nursing students. Objective: To investigate the mediating role of moral identity in the relationship between calling and meaning in life in nursing students. Design: This study was a cross-sectional design. Methods: A total of 10756 nursing students were recruited from November16 to January 17, 2023. The General Demographic Information Questionnaire, the Chinese Calling scale (CCS), the Moral Identity Measure (MIM), and the China Meaning Life Questionnaire (C-MLQ）were used to assess their socio-demographics, calling, moral identity, and meaning in life. Correlation analysis was used to examine the relationship between the three variables. The PROCESS macro was used to conduct mediation analysis. The study was compliant with the STROBE checklist. Results: The valid questionnaires were 10583 (effective response rate: 98.39%). Most of the participants were female(85.47%),unmarried(98.74%) and rural students(79.09%). High moral identity and high calling were associated with better meaning in life (all PConclusion: This study contributes to a broader understanding of the factors that influence nursing students' meaning in life. Calling may influence meaning in life, partly through moral identity. Educators can consider enhancing nursing students' meaning in life by increasing their moral identity and calling.

Background: One factor that influences nursing students' decision to pursue a nursing career is professional calling. It is important to comprehend nursing students' professional calling, which may have an impact on their career decisions and professional identities. Objectives: To investigate possible calling types and contributing variables among nursing students. Design: Cross-sectional descriptive study. Participants: A total of 10583 nursing students were enrolled in this survey. Methods: From November 16th, 2022, to January 17th, 2023, a cross-sectional study was carried out among nursing students using a convenient sampling. The subjects were given the Chinese Calling Scale and the General Demographic Information Questionnaire. Latent profile analysis (LPA) was used to separate nursing students' professional calling into a variety of subgroups. To find the variables connected to the prospective calling categories, we used ordinal and multinomial Logistic regression analysis. Results:We divided the respondents into three calling groups, low calling group (N=3204), moderate calling group (N=4492), and high calling group (N=2887), which accounted for 30.3%, 42.4%, and 27.3% of the total respondents, respectively, in accordance with the findings of the latent profile analysis. Across scale scores and dimensions for the three separate categories, three groups demonstrated statistically significant differences (both pConclusion: Three latent calling patterns were found, and there was calling variability across nursing students.Special care should be given to students with low calling. Nursing students must use professional education tools to help them develop their professional identities and stabilize the nursing team.

Background: Compassion is closely linked to psychological well-being, and several assessment tools have been developed and studied to assess the level of compassion in different populations and for more precise measurement. There is currently a scarcity of comprehensive knowledge about compassion-related assessment tools, and our research provides an overview of these tools. Aims: To collect exhaustively the tools used to assess compassion in order to serve as a resource for selecting tools for use in practice. Methods: Focusing on compassion assessment tools, the authors conducted a thorough search of 10 Chinese and English databases from their establishment until August 14, 2022. The extracted data comprised the author, the year, the nation, the target population, and the primary evaluation contents. Using the COSMIN checklist, the methodological quality and measurement properties of the included studies were appraised. This scoping review was registered with the Open Science Framework and followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. Results:There were 15965 papers searched, and 36 compassion-related measurement tools were considered in this study. None of the 36 studies provided possessed all nine psychometric properties, as outlined by the COSMIN criteria. On the basis of a systematic evaluation of quality, measurement qualities were ranked. The results for internal consistency and content validity were relatively favorable, whereas the results for structural validity were variable and the results for the remaining attributes were either uncertain or negative. A Venn diagram was used to illustrate the overlapping groups of compassion measurement tools based on the three-way flow of compassion. An overview of the reference instrument and theoretical basis for the included studies was provided, and half of them did not contain any theoretical or scale-based evidence. Conclusion: In this study, 36 compassion-related measuring instruments were identified, and the methodological quality and measurement properties of the included studies were acceptable. The included measurements in this study were found to be consistent with three-way compassion flows. Compassion measurement tools and compassion-related theories should be the focus of future research.

The paper discusses a statistical problem related to testing for differences between two sparse networks with community structures. The community-wise edge probability matrices have entries of order $O(n^{-1}/\log n)$, where $n$ represents the size of the network. The authors propose a test statistic that combines a method proposed by Wu et al. \cite{WuTwoSampleSBM2022} and a resampling process. They derive the asymptotic null distribution of the test statistic and provide a guarantee of asymptotic power against the alternative hypothesis. To evaluate the performance of the proposed test statistic, the authors conduct simulations and provide real data examples. The results indicate that the proposed test statistic performs well in practice.

We focus on a class of non-smooth optimization problems over the Stiefel manifold in the decentralized setting, where a connected network of $n$ agents cooperatively minimize a finite-sum objective function with each component being weakly convex in the ambient Euclidean space. Such optimization problems, albeit frequently encountered in applications, are quite challenging due to their non-smoothness and non-convexity. To tackle them, we propose an iterative method called the decentralized Riemannian subgradient method (DRSM). The global convergence and an iteration complexity of $\mathcal{O}(\varepsilon^{-2} \log^2(\varepsilon^{-1}))$ for forcing a natural stationarity measure below $\varepsilon$ are established via the powerful tool of proximal smoothness from variational analysis, which could be of independent interest. Besides, we show the local linear convergence of the DRSM using geometrically diminishing stepsizes when the problem at hand further possesses a sharpness property. Numerical experiments are conducted to corroborate our theoretical findings., 27 pages, 6 figures, 1 table

The validation process for microprocessors is a very complex task that consumes substantial engineering time during the design process. Bugs that degrade overall system performance, without affecting its functional correctness, are particularly difficult to debug given the lack of a golden reference for bug-free performance. This work introduces two automated performance bug localization methodologies based on machine learning that aims to aid the debugging process. Our results show that, the evaluated microprocessor core performance bugs whose average IPC impact is greater than 1%, our best-performing technique is able to localize the exact microarchitectural unit of the bug $\sim$77\% of the time, while achieving a top-3 unit accuracy (out of 11 possible locations) of over 90% for bugs with the same average IPC impact. The proposed system in our simulation setup requires only a few seconds to perform a bug location inference, which leads to a reduced debugging time., 12 pages, 6 figures

Community detection in complex networks has attracted considerable attention, however, most existing methods need the number of communities to be specified beforehand. In this paper, a goodness-of-fit test based on the linear spectral statistic of the centered and rescaled adjacency matrix for the stochastic block model is proposed. We prove that the proposed test statistic converges in distribution to the standard Gaussian distribution under the null hypothesis. The proof uses some recent advances in generalized Wigner matrices. Simulations and real data examples show that our proposed test statistic performs well. This paper extends the work of Dong et al. [Information Science 512 (2020) 1360-1371].

This paper aims to develop a Newton-type method to solve a class of nonconvex composite programs. In particular, the nonsmooth part is possibly nonconvex. To tackle the nonconvexity, we develop a notion of strong prox-regularity which is related to the singleton property, Lipschitz continuity, and monotonicity of the associated proximal operator, and we verify it in various classes of functions, including weakly convex functions, indicator functions of proximally smooth sets, and two specific sphere-related nonconvex nonsmooth functions. In this case, the problem class we are concerned with covers smooth optimization problems on manifold and certain composite optimization problems on manifold. For the latter, the proposed algorithm is the first second-order type method. Combining with the semismoothness of the proximal operator, we design a projected semismooth Newton method to find a root of the natural residual induced by the proximal gradient method. Since the corresponding natural residual may not be globally monotone, an extra projection is added on the usual semismooth Newton step and new criteria are proposed for the switching between the projected semismooth Newton step and the proximal step. The global convergence is then established under the strong prox-regularity. Based on the BD regularity condition, we establish local superlinear convergence. Numerical experiments demonstrate the effectiveness of our proposed method compared with state-of-the-art ones., 26 pages

In this paper, we derive the analytical behavior of the limiting spectral distribution of non-central covariance matrices of the "general information-plus-noise" type, as studied in [14]. Through the equation defining its Stieltjes transform, it is shown that the limiting distribution has a continuous derivative away from zero, the derivative being analytic wherever it is positive, and we show the determination criterion for its support. We also extend the result in [14] to allow for all possible ratios of row to column of the underlying random matrix.

An important issue in many multivariate regression problems is to eliminate candidate predictors with null predictor vectors. In large-dimensional (LD) setting where the numbers of responses and predictors are large, model selection encounters the scalability challenge. Knock-one-out (KOO) statistics hold promise to meet this challenge. In this paper, the almost sure limits and the central limit theorem of the KOO statistics are derived under the LD setting and mild distributional assumptions (finite fourth moments) of the errors. These theoretical results guarantee the strong consistency of a subset selection rule based on the KOO statistics with a general threshold. For enhancing the robustness of the selection rule, we also propose a bootstrap threshold for the KOO approach. Simulation results support our conclusions and demonstrate the selection probabilities by the KOO approach with the bootstrap threshold outperform the methods using Akaike information threshold, Bayesian information threshold and Mallow's C$_p$ threshold. We compare the proposed KOO approach with those based on information threshold to a chemometrics dataset and a yeast cell-cycle dataset, which suggests our proposed method identifies useful models.

With a computationally efficient approximation of the second-order information, natural gradient methods have been successful in solving large-scale structured optimization problems. We study the natural gradient methods for the large-scale decentralized optimization problems on Riemannian manifolds, where the local objective function defined by the local dataset is of a log-probability type. By utilizing the structure of the Riemannian Fisher information matrix (RFIM), we present an efficient decentralized Riemannian natural gradient descent (DRNGD) method. To overcome the communication issue of the high-dimension RFIM, we consider a class of structured problems for which the RFIM can be approximated by a Kronecker product of two low-dimension matrices. By performing the communications over the Kronecker factors, a high-quality approximation of the RFIM can be obtained in a low cost. We prove that DRNGD converges to a stationary point with the best-known rate of $\mathcal{O}(1/K)$. Numerical experiments demonstrate the efficiency of our proposed method compared with the state-of-the-art ones. To the best of our knowledge, this is the first Riemannian second-order method for solving decentralized manifold optimization problems., Comment: 17 pages

We consider the problem of decentralized nonconvex optimization over a compact submanifold, where each local agent's objective function defined by the local dataset is smooth. Leveraging the powerful tool of proximal smoothness, we establish local linear convergence of the projected gradient descent method with unit step size for solving the consensus problem over the compact manifold. This serves as the basis for analyzing decentralized algorithms on manifolds. Then, we propose two decentralized methods, namely the decentralized projected Riemannian gradient descent (DPRGD) and the decentralized projected Riemannian gradient tracking (DPRGT) methods. We establish their convergence rates of $\mathcal{O}(1/\sqrt{K})$ and $\mathcal{O}(1/K)$, respectively, to reach a stationary point. To the best of our knowledge, DPRGT is the first decentralized algorithm to achieve exact convergence for solving decentralized optimization over a compact manifold. The key ingredients in the proof are the Lipschitz-type inequalities of the projection operator on the compact manifold and smooth functions on the manifold, which could be of independent interest. Finally, we demonstrate the effectiveness of our proposed methods compared to state-of-the-art ones through numerical experiments on eigenvalue problems and low-rank matrix completion., Comment: 32 pages

Family caregivers of dementia patients face high levels of interpersonal stress, which frequently leads to increased anxiety and depression, as well as negative effects on interpersonal relationships. Mentalizing Imagery Therapy (MIT) was created to incorporate balanced attention to mentalizing into a series of structured mindfulness and guided imagery practices. There is currently a scarcity of comprehensive knowledge about the application of mentalizing imagery therapy for family dementia caregivers. The purpose of this study is to compile evidence for the use of mentalizing imagery therapy for family dementia caregivers.

Let $ \bbB_n =\frac{1}{n}(\bbR_n + \bbT^{1/2}_n \bbX_n)(\bbR_n + \bbT^{1/2}_n \bbX_n)^* $, where $ \bbX_n $ is a $ p \times n $ matrix with independent standardized random variables, $ \bbR_n $ is a $ p \times n $ non-random matrix and $ \bbT_{n} $ is a $ p \times p $ non-random, nonnegative definite Hermitian matrix. The matrix $\bbB_n$ is referred to as the information-plus-noise type matrix, where $\bbR_n$ contains the information and $\bbT^{1/2}_n \bbX_n$ is the noise matrix with the covariance matrix $\bbT_{n} $. It is known that, as $ n \to \infty $, if $ p/n $ converges to a positive number, the empirical spectral distribution of $ \bbB_n $ converges almost surely to a nonrandom limit, under some mild conditions. In this paper, we prove that, under certain conditions on the eigenvalues of $ \bbR_n $ and $ \bbT_n $, for any closed interval outside the support of the limit spectral distribution, with probability one there will be no eigenvalues falling in this interval for all $ n $ sufficiently large., Comment: 26 pages

The various benefits of multi-tenanting, such as higher device utilization and increased profit margin, intrigue the cloud field-programmable gate array (FPGA) servers to include multi-tenanting in their infrastructure. However, this property makes these servers vulnerable to power side-channel (PSC) attacks. Logic designs such as ring oscillator (RO) and time-to-digital converter (TDC) are used to measure the power consumed by security critical circuits, such as advanced encryption standard (AES). Firstly, the existing works require higher minimum traces for disclosure (MTD). Hence, in this work, we improve the sensitivity of the TDC-based sensors by manually placing the FPGA primitives inferring these sensors. This enhancement helps to determine the 128-bit AES key using 3.8K traces. Secondly, the existing defenses use ROs to defend against PSC attacks. However, cloud servers such as Amazon Web Services (AWS) block design with combinatorial loops. Hence, we propose a placement-based defense. We study the impact of (i) primitive-level placement on the AES design and (ii) additional logic that resides along with the AES on the correlation power analysis (CPA) attack results. Our results showcase that the AES along with filters and/or processors are sufficient to provide the same level or better security than the existing defenses.

It is well known that most of the existing theoretical results in statistics are based on the assumption that the sample is generated with replacement from an infinite population. However, in practice, available samples are almost always collected without replacement. If the population is a finite set of real numbers, whether we can still safely use the results from samples drawn without replacement becomes an important problem. In this paper, we focus on the eigenvalues of high-dimensional sample covariance matrices generated without replacement from finite populations. Specifically, we derive the Tracy-Widom laws for their largest eigenvalues and apply these results to parallel analysis. We provide new insight into the permutation methods proposed by Buja and Eyuboglu in [Multivar Behav Res. 27(4) (1992) 509--540]. Simulation and real data studies are conducted to demonstrate our results., Comment: Accepted by Bernoulli

The classical chroma subsampling involves downsampling chrominance components (U and V) while maintaining the luminance component (Y). Recently, a study has attempted to change Y for the chroma-subsampling process, and improved results in the reconstructed image quality are obtained. However, computational complexity remains an issue because the study examines all the candidates in the determined range for minimal pixel distortion for the modified Y; the complexity can be high if the range is large. In this study, we reduced the candidate number to seven at most, which is mathematically optimized. Boundary points for in-the-range red, green, and blue (RGB) values are first decided, followed by the determination of the intervals that concatenate the entire curve (at most seven intervals). Each interval belongs to one of the seven sub-cases of different linear combinations of individual curves. The optimal solution (modified Y) for each sub-case is derived, which is in highly efficient form. Compared with the existing method, the proposed fast method ensures that the image quality is preserved, while the number of search candidates is reduced by 61.30%–69.19% on average, and the computational time of the process is reduced by 31.39%–58.97%, thereby demonstrating an efficient performance.

Microbial ammonia oxidation is vital to the nitrogen cycle. A biological process, called Dirammox (direct ammonia oxidation, NH

Abstract Low-porosity, extra-low-permeability tight sandstone oil and gas reservoirs have become an important research area for hydraulic fracturing. Sand-mud interlayer is often developed in this type of reservoir in the longitudinal direction. The heterogeneous distribution of oil layers and mud shale barrier layers in the longitudinal direction will lead to restrict propagation of hydraulic fractures in the fracture height direction, which affects the effective stimulated reservoir volume significantly. In this paper, a finite element model of hydraulic fracture propagation in sand-mud interlayer was established based on the real characteristics of the target block formation to study the hydraulic fracture penetrating propagation feasibility under different combinations of fracturing parameters in the tight sandstone reservoir in the target block, and the model verification was completed with the field data. A total of three types of variable orthogonal combinations of 7 kinds of viscosities of fracturing fluid, 5 kinds of injection rate and 8 kinds of thicknesses of barrier layer were carried out to explore the penetration feasibility of hydraulic fracture under the commonly used combination of low injection flow rate and high viscosity in offshore and high injection flow rate and low viscosity in onshore shale gas reservoirs. And the feasibility evaluation plate of the hydraulic fracture penetration propagation in sand-mud interlayer is established. The method for evaluating the feasibility of hydraulic fracture penetrating propagation in sand-mud Interlayer under different combinations of fracturing parameters can be well applied to the tight sandstone reservoir in this paper. And it will provide theoretical guidance for hydraulic fracture design and fracturing parameter optimization. In addition, the method can also be applied to the fracturing development of shale reservoirs with sand-mud interlayers.

Although Siraitia grosvenorii (abbreviated as S.g.) is frequently used to prevent and cure diabetes problems, the precise mechanism underlying its ability to do so remains unknown. Through network pharmacology and molecular docking techniques, we studied the early molecular mechanisms of S.g in the treating of proliferative diabetic retinopathy (PDR) in this study. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to screen the active compounds and related targets of S.g. Oral bioavailability (OB) 30% and drug likeness (DL) 0.18 were used as screening criteria. The active compounds without knowledge of a probable target were excluded. The Uniprot database included converted symbols for the associated targets. GEO2R was used to explore several genes related to PDR. Using jvenn web service to intersect targets of S.g and PDR. The Xiantao Academic Online website was used to examine the expression patterns of intersect targets in PDR samples. The STRING database was used to create a protein-protein interaction (PPI) network of intersecting targets. Cytoscape software was used to show the PPI network, MCODE software was used to evaluate the network’s core proteins, and CytoHubba software was used to extract the important networks of the top three targets. Omicshare platform carried a functional analysis using the Gene Ontology (GO) and pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Pymol, AutoDock Vina software, Schrödinger Software were used to conduct molecular docking experiments or pockets search on the top three targets. The results showed that 85 targets were matched to six active compounds of S.g. 18 intersect targets were found. Seven DEGs were up-regulated and eleven genes were down-regulated when these targets were divided into two groups. TNF, PTGS2, and CASP3 were the main targets, according to the PPI network. The intersect targets were mostly related to angiogenesis, cell proliferation, oxidative stress, inflammatory response, and metabolism. It was discovered that the core targets TNF, PTGS2, and CASP3 had various levels of affinity for their respective compounds. Interestingly, multiple good drug-forming pockets for CASP3 and PTGS2 targets were identified through Schrödinger software. In particular, six compounds bind to the top three core targets to inhibit IL-17 signaling pathway, AGE-RAGE signaling pathway in diabetic complications, Pathways in cancer and 14 other signaling pathways to inhibit inflammation, apoptosis, oxidative stress, arachidonic acid metabolism, and angiogenesis to prevent and treat PDR. The study’s findings, which served as a guide for the widespread use of S.g in PDR clinical practise, included multi-substances and targets of S.g to prevent and cure PDR.

The development of a lysosome-targeting fluorescent probe to visualize endogenous and exogenous methylglyoxal (MGO) in live cells has important implications for associated diseases. Herein, a lysosome-targeting fluorescent probe MGO-Naph-A was designed and synthesized to detect MGO with high selectivity. The probe contained naphthalimide as the fluorescent group

In alpine and gorge regions, surficial failure of granular slopes has seriously affected infrastructure construction and the safe operation of transportation networks. This research focuses on dry granular slopes confined by retaining walls. Repeated surficial failure of granular slopes has been explored through indoor physical model tests. The results show that surficial failure presents low frequency and large scale for granular slopes dominated by coarse particles. The mass of debris that crosses retaining walls indicates activity level of granular slopes. When this mass for each surficial failure gradually decreases, it is highly likely that large-scale surficial failure will occur. As the amount of debris deposited on the slope increases, it is probable that the debris mass falling during a massive sliding event will be many times that of the previous sliding event. In engineering practice, it is necessary during road cleaning processes to record the volume of debris accumulated on the road. A continuous increase in the slope angle indicates a high probability of large-scale surficial failure. For each granular slope with a unique particle composition, there is a critical change rate for early warning of surficial failure, which can be determined by long-term monitoring.

Hillslope processes and mass movement are key issues in the analysis and evaluation of geological disasters in mountainous regions. A rockfall-dominated talus slope exhibits a typical outcrop–talus slope system as the product of detached boulders and rock fragments. The Zongling rockfall zone is one of the most active outcrop–talus slope systems in southwest China, and it provides a representative case study on the assessment of rockfall hazards at the base of talus slopes. In this article, the formation mechanism and failure mode of this rock-talus system were studied using field investigation, remote sensing image analysis, and numerical simulation. The findings reveal that the lithology and rock mass structure of the study site are controlling factors for outcrop retreat and the progressive development of talus deposits. This process is intensified by rainfall and mining activities. Boulder accumulation on the platform at the middle section of the talus slope serves as top loading for the slope mechanical system. During the boulder–ground interaction, the rockfall impact acts as toe cutting to change the geometry and mechanical balance of the talus slope. It was found that toe cutting significantly influenced the slope stability, which led to a decrease in the antisliding force of the slope. The slope failure induced by rockfalls occurred with the combined effect of top loading and toe cutting on this talus slope. During rockfall prevention and mitigation in this region, the government and residents should consider the geodisaster chain, as this relates to the impact of rockfall on talus slopes, in addition to the risk of damage due to the rockfall trajectory.

Background and purposeNo research currently exists on the role of the accessory parotid gland (APG) in nasopharyngeal carcinoma (NPC). We thereby aimed to assess the effects of APG on the dosimetry of the parotid glands (PGs) during NPC radiotherapy and evaluate its predictive value for late xerostomia.Material and methodsThe clinical data of 32 NPC patients with radiological evidence of the APG treated at Sun Yat-sen Memorial Hospital between November 2020 and February 2021 were retrospectively reviewed. Clinically approved treatment plans consisted of only the PGs as an organ at risk (OAR) (Plan1), while Plan2 was designed by considering the APG as a single organ at risk (OAR). The APG on Plan1 was delineated, and dose–volume parameters of the PGs alone (PG-only) and of the combined structure (PG+APG) were analyzed in both plans. The association of such dosimetric parameters in Plan1 with xerostomia at 6–9 months post-radiotherapy was further explored.ResultsFifty APGs were found, with a mean volume of 3.3 ± 0.2 ml. Significant differences were found in all dosimetric parameters between Plan1 and Plan2. The mean dose and percentage of OAR volumes receiving more than 30 Gy significantly reduced in Plan1 itself (PG-only vs. PG+APG, 39.55 ± 0.83 Gy vs. 37.71 ± 0.75 Gy, and 62.00 ± 2.00% vs. 57.41 ± 1.56%, respectively; p < 001) and reduced further in Plan2 (PG+APG, 36.40 ± 0.74 Gy, and 55.54 ± 1.61%, respectively; p < 0.001). Three additional patients met the dose constraint in Plan1, which increased to seven in Plan2. With APG included, the predictive power of the dosimetric parameters for xerostomia tended to improve, although no significant differences were observed.ConclusionAPG is anatomically similar to the PGs. Our findings suggest the potential benefits of treating the APG and PGs as a single OAR during radiotherapy (RT) of NPC by improving PG sparing.

AIM: To evaluate the global trends in and explore hotspots of high myopia (HM) research. METHODS: This bibliometric analysis was used to reveal the publication trends in HM research field based on the Web of Science Core Collection (WoSCC). VOSviewer version 1.6.13 software was used to analyze the data and construct a knowledge map including the yearly publication number, journals, countries, international collaborations, authors, research hotspots, and intellectual base in HM. RESULTS: The search engine found 3544 peer-reviewed publications on HM between 2010 and 2019, and the yearly research output substantially elevated over the past decade. China is the top publishing country, and Sun Yat-sen University was the most active academic institution. Jonas JB is the top publishing scientist, and Investigative Ophthalmology and Visual Science (IOVS) was the most productive journal. The highest cited references mainly focused on epidemiology and management. The keywords formed 6 clusters: 1) refractive surgery; 2) etiology and clinical characteristics; 3) the mechanism of eye growth; 4) management for myopic maculopathy; 5) vitrectomy surgical treatment; 6) myopia-associated glaucoma-like optic neuropathy. CONCLUSION: The evaluation of development trends based on the data extracted from WoSCC can provide valuable information and guidance for ophthalmologists and public health researchers to improve management procedures in HM field.

The influence of desiccation cracks on the performance of upstream anti-seepage systems subjected to abrupt flood was investigated using centrifuge experiments of scaled-down embankment dam models. Desiccation cracks were introduced in the sloping core and the upstream blanket by simulating solar radiation. Both intact and cracked models were subject to 100×g centrifuge acceleration. Pore water pressure was monitored using pore pressure transducers placed at preselected locations within the model, and the opening width and length of the dominant cracks were manually measured. The crack number was lower on the blanket surface than on the sloping core, but the crack opening width and length developed rapidly. The intact anti-seepage system, which lowered the infiltration surface and effectively dissipated the pore water pressure, showed good performance, whereas the cracked anti-seepage system suffered seepage failure owing to high pore water pressure at the crack tip under the abrupt flood condition. The results indicate that desiccation cracks on the blanket surface provide the essential material condition for hydraulic fracturing, and abrupt flood provides the favorable mechanical condition. Desiccation cracks on upstream anti-seepage systems pose a major hidden danger and should be excavated and backfilled in a timely manner to prevent dam accidents.

Background The modern lifestyle trend of pet ownership is undoubtedly beneficial for both physical and mental health. Research has shown a connection between pet ownership and staff self-compassion. However, there has not been any evidence linking pet ownership to self-compassion in the nurse population. Aims To investigate the current status of pet ownership among nurses and explore the influence of pet ownership on self-compassion among nurses. Methods An online survey was conducted in July 2022 with 1,308 nurses in China. Data were collected using a general information questionnaire and a self-compassion scale. To compare categorical variables, the independent t test, one-way ANOVA, and multiple linear regression analysis were utilized. SPSS software was used for the statistical analysis. Results We found that 16.9% of nurses owned at least one pet, and dogs and cats were the primary pets. The t test for independent samples showed that pet owners and non-pet owners scored differently on self-compassion (t = 3.286, p = 0.001), self-kindness (t = 3.378, p = 0.001), common humanity (t = 2.419, p = 0.016), and mindfulness (t = 2.246, p = 0.025). One-way ANOVA revealed that the highest degree was an influencing factor of self-compassion (χ2 = 1.386, p = 0.019). Multiple linear regression showed that average monthly income, pet ownership, and highest degree were the factors that influenced self-compassion most significantly (F = 8.335, p Conclusion The results revealed that nurses actually own pets as part of their modern lifestyle, which provides them with social support and potentially enhances their self-compassion. More efforts should be focused on the impact of pet ownership on nurses’ physical and mental health, and pet-based interventions should also be developed.

Dynamic point clouds (DPC) are new media storage formats that allow end-users to watch objects/scenes in a three-dimensional (3D) sense. It can be displayed from different angles throughout time. However, the raw size of a point cloud is huge because there can be millions of points (each containing color triplet and location triplet information) in a point cloud, and there can be multiple point clouds in a DPC. Video-based point cloud compression (V-PCC) is developed to project a 3D point cloud to 2D images: attribute, geometry, and occupancy images. After padding, the 2D images are compressed using the well-established high-efficiency video coding (HEVC). In this study, we first employ an occupancy image to propose a blocky occupancy flag (BOF), to denote the occupancy information on “a block basis”. For coding attribute and geometry images, we use a BOF to develop a fast coding unit (CU) algorithm for early termination of the CU search recursion. We also utilize the geometry images to calculate the 2D and 3D information of each pixel, for 2D/3D spatial homogeneity of the pixels to design fast CU decision. In addition, we proposed a modified rate-distortion optimization for different color components considering the picture order count (POC) structure in HEVC/V-PCC. Finally, we propose an HEVC input pixel modification method based on a BOF to reduce the unnecessary information to be coded for attribute images. Compared with the state-of-the-art fast V-PCC encoding method, the proposed work outperforms by up to 2.31% in Bjøntegaard delta bit rates (BDBR) (with very slight loss by only up to 0.38%), and improves the time saving performances by up to 7.84% for two different testing datasets.

Background: Both hospital-acquired infection (HAI) and cancer represents major health concerns worldwide, but there is a paucity of data describing HAI in Chinese cancer patients. The objective of this study is to demonstrate the prevalence, causative agents, antimicrobial use and risk factors for HAI in a cancer hospital in Southwestern China. Methods: We use the criteria of the Ministry of Health of the People's Republic of China to define hospital-acquired infections. One-day cross-sectional surveys were annually conducted from 2014 to 2018. Trained staff collected hospital-acquired infections, antimicrobial use and clinical characteristics data of inpatients. Multivariate logistic regression was used to determine the potential risk factors associated with HAIs. Results: Of the 6717 patients surveyed, there were 140 patients (2.1%, 95% confidence interval, 1.7–2.4%) with 144 distinct HAIs. Lower respiratory tract infections (47, 32.6%) and surgical-site infections (29, 20.1%) were the most common HAIs. Escherichia coli was the most common pathogen (29.6%). Risk factors for HAI included younger age (65 years), hospitalization in the intensive care unit, presence of central catheter and undergoing surgery in the previous 30 days. The overall prevalence of patients receiving antimicrobial agents was 15.2%. Conclusion: To control hospital-acquired infections in cancer patients, surveillance and prevention strategies to infections associated with central catheters or related to surgery should be augmented.

In this paper, we establish the central limit theorem (CLT) for linear spectral statistics (LSS) of large-dimensional sample covariance matrix when the population covariance matrices are not uniformly bounded, which is a nontrivial extension of the Bai-Silverstein theorem (BST) (2004). The latter has strongly stimulated the development of high-dimensional statistics, especially the application of random matrix theory to statistics. However, the assumption of uniform boundedness of the population covariance matrices is found strongly limited to the applications of BST. The aim of this paper is to remove the blockages to the applications of BST. The new CLT, allows the spiked eigenvalues to exist and tend to infinity. It is interesting to note that the roles of either spiked eigenvalues or the bulk eigenvalues or both of the two are dominating in the CLT. Moreover, the results are checked by simulation studies with various population settings. The CLT for LSS is then applied for testing the hypothesis that a covariance matrix $ \bSi $ is equal to an identity matrix. For this, the asymptotic distributions for the corrected likelihood ratio test (LRT) and Nagao's trace test (NT) under alternative are derived, and we also propose the asymptotic power of LRT and NT under certain alternatives.

Depressive disorder is the leading cause of disability worldwide, yet the mechanisms underlying depression are not fully understood. Vesicle release is essential for synaptic neurotransmission, the abnormalities of vesicle release and synaptic plasticity are associated with various neuropsychiatric disorders. Neural circuits are ensembles of interconnected neurons that collectively perform specific functions. To some extent, depression may be caused by a disruption in the structural and functional connections of the neural circuits underlying emotion regulation. In this review, we summarized the role of abnormalities of vesicle release and synaptic transmission, as well as the related regulatory molecules and signal pathways in the regulation of depression.

Adipogenesis is a complex process controlled by intrinsic and extrinsic factors that regulate preadipocyte proliferation, adipogenic capacity and maturation of metabolic function. Here we show that insulin and IGF-1 receptors are essential for mature adipocyte survival and that deletion of both IR and IGF1R specifically in fat using a tamoxifen inducible-AdipoQ-Cre (Ai-DKO) leads to rapid and severe loss of adipocytes in all depots, associated with a metabolic syndrome characterized by hypertriglyceridemia, hyperglycemia, hyperinsulinemia, fatty liver, and pancreatic beta cell proliferation. In this model, this pathological phenotype reverses over a few weeks, in large part, due to preadipocyte proliferation and adipose tissue regeneration. Incubation of preadipocytes with serum from the Ai-DKO mice in vitro stimulates cell proliferation, and this effect can be mimicked by conditioned media from liver slices of Ai-DKO mice, but not by media of cultured Ai-DKO adipocytes, indicating a hepatic origin of the growth factor. Proteomic analysis of serum reveals apolipoprotein C3 (APOC3), a protein secreted by liver, as one of the most upregulated proteins in the Ai-DKO mice. In vitro, purified and delipidated APOC3 stimulates preadipocyte proliferation, however, knockdown of hepatic APOC3 in vivo in Ai-DKO mice is not sufficient to block adipose regeneration. Thus, lipodystrophy is associated with presence of increased preadipocyte-stimulating growth factors in serum. Our study indicates that APOC3 is one contributing factor to preadipocyte proliferation, however, other still-unidentified circulating growth factors are also likely present in Ai-DKO mice. Identification of these factors may provide a new approach to regulation of adipose mass in health and disease.

The images obtained by the camera sensors are stored in the format of CFA, Color Filter Array, which only contains limited information about the R, G, and B signals of images. The images in CFA are upsampled into RGB 444 format by demosaicking algorithms, converted into YCbCr 444, then chroma-downsampled into YCrCb 420 format for image/video compression. In this paper, a novel chroma-downsampling method is developed to improve a state-of-the-art method. The optimization problem for the proposed method considers more factors and provides a better closed-form solution for the optimally sampled chroma values. Reversely in the decoder, a chroma-upsampling method is required for the image reconstruction. In the proposed chroma-upsampling method, the neighboring chroma pixels and their distances to the recovered pixel are considered; the procedure is to produce weightings to redistribute the total pixel values in the original estimates. Combining the proposed chroma-downsampling and the proposed chroma-upsampling works, the proposed method outperforms the state-of-the-art method by BDPSNR (Bjontegaard Delta peak signal-to-noise ratio) 0.3161 for H.264/AVC, 0.3845 for HEVC (High Efficiency Video Compression) and 0.3739 for VVC (Versatile Video Coding), averaged over all tested videos and all 7 different considered CFA formats.