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The vertical distribution of black carbon (BC), as well as its mixing state, is of great concern due to BC's strong regional climatic and environmental effects. In this study, vertical measurements were conducted through a moveable container based on a meteorological tower in the Beijing urban area during June and July. A total of 112 vertical profiles (0–240 m), including the concentrations of BC, O3, NOx and the optical properties of aerosols, were obtained. Based on BC concentration, the vertical profiles could be classified into four categories: uniform, gradual decrease, sharp decrease and sudden increase. The uniform type indicates strong vertical mixing with similar pollutant concentrations along the vertical direction. The gradual and sharp decrease types indicate stable vertical conditions with higher pollutant concentrations on the ground and lower concentrations at higher altitudes. Due to the strong radiation in summer, the vertical profiles exhibited a clear diurnal variation in which ∼ 80 % of profiles were uniform during the daytime and ∼ 40 %–90 % of profiles were of the gradual and sharp decrease types at night. O3 is an exception, and its concentration generally increases with height, even under strong vertical mixing conditions. The size distribution of the BC core varied slightly along the vertical direction, and the coating thickness, denoted by the diameter ratio between the BC-containing particle and BC core (Dp/Dc), of BC increased with height under stable conditions. Although the coating thickness could increase the absorption ability with an average absorption enhancement of 1.25 at 23:00 LT (local time: UTC+8), the vertical difference of Dp/Dc (2 %) was much lower than that of BC concentration (∼ 35 %). The vertical variation in absorption ability was mainly caused by the variation in BC concentration. In addition, O3 and Dp/Dc occasionally increased during 06:00–08:00 but remained stable during 08:00–10:00. Vertical mixing and transportation from upper heights, such as the residual layer, could significantly influence the pollutant properties on the surface during early mornings. This study exhibits a continuous vertical picture of BC and its mixing state in urban areas, which would be helpful for understanding BC's regional environmental effect.

Federated learning (FL) enables edge devices to collaboratively train machine learning models, with model communication replacing direct data uploading. While over-the-air model aggregation improves communication efficiency, uploading models to an edge server over wireless networks can pose privacy risks. Differential privacy (DP) is a widely used quantitative technique to measure statistical data privacy in FL. Previous research has focused on over-the-air FL with a single-antenna server, leveraging communication noise to enhance user-level DP. This approach achieves the so-called "free DP" by controlling transmit power rather than introducing additional DP-preserving mechanisms at devices, such as adding artificial noise. In this paper, we study differentially private over-the-air FL over a multiple-input multiple-output (MIMO) fading channel. We show that FL model communication with a multiple-antenna server amplifies privacy leakage as the multiple-antenna server employs separate receive combining for model aggregation and information inference. Consequently, relying solely on communication noise, as done in the multiple-input single-output system, cannot meet high privacy requirements, and a device-side privacy-preserving mechanism is necessary for optimal DP design. We analyze the learning convergence and privacy loss of the studied FL system and propose a transceiver design algorithm based on alternating optimization. Numerical results demonstrate that the proposed method achieves a better privacy-learning trade-off compared to prior work., This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

In close-range photogrammetry, circular-coded targets (CCTs) are a reliable method to solve the issue of image correspondence. Currently, the identification methods for CCTs are very mature, but complex illumination conditions are still a key factor restricting identification. This article proposes an adaptive homomorphic filtering (AHF) algorithm to solve this issue, utilizing homomorphic filtering (HF) to eliminate the influence of uneven illumination. However, HF parameters vary with different lighting types. We use a genetic algorithm (GA) to carry out global optimization and take the identification result as the objective function to realize automatic parameter adjustment. This is different from the optimization strategy of traditional adaptive image enhancement methods, so the most significant advantage of the proposed algorithm lies in its automation and universality, i.e., users only need to input photos without considering the type of lighting conditions. As a preprocessing algorithm, we conducted experiments combining advanced commercial photogrammetric software and traditional identification methods, respectively. We cast stripe- and lattice-structured light to create complex lighting conditions, including uneven lighting, dense shadow areas, and elliptical light spots. Experiments showed that our algorithm significantly improves the robustness and accuracy of CCT identification methods under complex lighting conditions. Given the perfect performance under stripe-structured light, this algorithm can provide a new idea for the fusion of close-range photogrammetry and structured light. This algorithm helps to improve the quality and accuracy of photogrammetry and even helps to improve the decision making and planning process of photogrammetry.

In recent decades, urbanization around the world has become an unavoidable trend. However, rapid urbanization has brought about a number of “urban diseases” which have considerable influence on sustainable urbanization. In order to diagnose urban problems, this study introduces a new perspective for the evaluation of urbanization sustainability named “urban health examination (UHE)” based on the urban lifeform theory which treats a city as a human body system. Then, an evaluation index system of UHE incorporating eight dimensions is constructed by referring to the existing authoritative indicator systems globally. Furthermore, a deviation maximization method and obstacle analysis method are integrated to evaluate urban development level and diagnose the urban diseases. Finally, in order to verify the feasibility of the UHE methodological framework, an empirical study was conducted in Wuhan, Central China. The results show that (1) the main urban diseases suffered by Wuhan City in 2010–2019 include traffic congestion, waterlogging, unsafe production, insufficient technological power, and excessive urban development; (2) the evolution mechanism of urban diseases in Wuhan has been explored. This study proposes a methodological framework of UHE which can successfully diagnose urban diseases, so that local urban managers adopt tailored strategies to prevent urban diseases and further achieve sustainable urban development goals.

In heavy quark limit, the lowest-lying charmed baryons with two light quarks can form an SU(3) triplet and sextet. The Ξc in the SU(3) triplet and Ξc′ in the sextet have the same JPC quantum number and can mix due to the finite charm quark mass and the fact the strange quark is heavier than the up/down quark. We explore the Ξc–Ξc′ mixing by calculating the two-point correlation functions of the Ξc and Ξc′ baryons from lattice QCD. Based on the lattice data, we adopt two independent methods to determine the mixing angle between Ξc and Ξc′. After making the chiral and continuum extrapolation, it is found that the mixing angle θ is 1.2∘±0.1∘, which seems insufficient to account for the large SU(3) symmetry breaking effects found in weak decays of charmed baryons.

Purpose Although surgery has been considered as the first choice treatment for patients diagnosed with tracheal cancer, the prediction of overall survival (OS) for those who undergo surgical intervention is poor. To address this issue, we developed a nomogram that combines a risk classification system to estimate OS of tracheal cancer patients who have undergone surgical intervention. Methods The 525 qualified patients were identified from the SEER database between 1975 and 2018 and randomly divided into training cohort(TC) and validation cohort(VC). The parameters were detemined by Cox regression analyses for predicting OS and to form nomogram and risk classification. The nomogram predictive ability was tested by calibration curves and ROC curves. Kaplan-Meier curves were drawn and compared using the log-rank test for different risk classification groups. Results The results indicated that age, stage, histology, and tumor size were independent prognostic factors (PFs) and were included in the predictive model. The calibration plots demonstrated that the 24- and 36-month OS rates generated by the nomograms were in good agreement with the actual observed value of the 24- and 36-month OS rates. The ROC curves suggested that the predictive model had good discrimination ability. Furthermore, in the total cohort, TC and VC, the low-risk group had a better prognosis than the high-risk group. Conclusions A novel nomogram system to predict OS and identify independent PFs for tracheal cancer patients who have undergone surgical intervention was established in this study. This model performance has the potential to assist doctors in making decisions about treatment options.

As a physical method for starch modification, dry heating treatment (DHT) at high temperatures (150 and 180°C, respectively) was applied to blue highland barley (BH) starch with different durations (2 and 4 h). The effects on its multi-structures, physicochemical properties, and in vitro digestibility were investigated. The results showed that DHT had changed the morphology of BH starch, and the diffraction pattern remained an “A”-type crystalline structure. However, with an extension of DHT temperature and time, the amylose content, gelatinization temperature, enthalpy value, swelling power, and pasting viscosity of modified starches decreased, while the light transmittance, solubility, and water and oil absorption capacities increased. Additionally, compared with native starch, the content of rapidly digestible starch in modified samples increased after DHT, whereas those of slowly digestible starch and RS decreased. Based on these results, the conclusion could be drawn that DHT is an effective and green way to transform multi-structures, physicochemical properties, and in vitro digestibility of BH starch. This fundamental information might be meaningful to enrich the theoretical basis of physical modification on BH starch and extend the applications of BH in the food industry.

Inspired by the recent anomalies on the lepton flavor universalities, we present a investigation of baryonic form factors induced by heavy-to-light tensor currents. With the light-front quark model, we calculate the tensor form factors and the momentum-distributions are accessed with two parametrization forms. Numerical results for the form factors at $q^2=0$ are derived and parameters in $q^2$ distributions are obtained through extrapolation. Our results are helpful for the analysis of new physics contributions in the heavy-to-light transition., 9 pages, 2 figures, 3 tables

In this study, we investigate the nonleptonic decays of heavy baryons \Xi^0_c induced by the c\to u (d \bar{d})/ (s \bar{s}) transition. Utilizing the factorization assumption, hadronic form factors are calculated within the light-front quark model. We employ helicity amplitudes to analyze the nonleptonic decay modes of heavy baryons and derive benchmark results for partial decay widths and branching fractions. Our calculations suggest that the branching fractions for some of these rare nonleptonic decays are at the order of 10^ {-5} or 10^ {-6}, which are likely to be detectable at experiments such as LHCb or Belle-II. The potential data accumulated in the future may help to further our understanding of the decay mechanism in the presence of heavy quarks., Comment: 8 pages,3 figures

Rechargeable Li-I2 battery has attracted considerable attentions due to its high theoretical capacity, low cost and environment-friendliness. Dissolution of polyiodides are required to facilitate the electrochemical redox reaction of the I2 cathode, which would lead to a harmful shuttle effect. All-solid-state Li-I2 battery totally avoids the polyiodides shuttle in a liquid system. However, the insoluble discharge product at the conventional solid interface results in a sluggish electrochemical reaction and poor rechargeability. In this work, by adopting a well-designed hybrid electrolyte composed of a dispersion layer and a blocking layer, we successfully promote a new polyiodides chemistry and localize the polyiodides dissolution within a limited space near the cathode. Owing to this confined dissolution strategy, a rechargeable and highly reversible all-solid-state Li-I2 battery is demonstrated and shows a long-term life of over 9000 cycles at 1C with a capacity retention of 84.1%., Rechargeable Li-I2 battery system is interesting due to high theoretical capacities but the insoluble discharge product at the conventional solid interface leads to poor performances. Here, by using a confined dissolution strategy the authors demonstrate a rechargeable all-solid-state Li-I2 battery with extended cycle life.

In heavy quark limit, the lowest-lying charmed baryons with two light quarks can form an SU(3) triplet and sextet. The $\Xi_c$ in the SU(3) triplet and $\Xi_c'$ in the sextet have the same $J^{PC}$ quantum number and can mix due to the finite charm quark mass and the fact the strange quark is heavier than the up/down quark. We explore the $\Xi_c$-$\Xi_c'$ mixing by calculating the two-point correlation functions of the $\Xi_c$ and $\Xi_c'$ baryons from lattice QCD. Based on the lattice data, we adopt two independent methods to determine the mixing angle between $\Xi_c$ and $\Xi_c'$. After making the chiral and continuum extrapolation, it is found that the mixing angle $\theta$ is $1.2^{\circ}\pm0.1^{\circ}$, which seems insufficient to account for the large SU(3) symmetry breaking effects found in weak decays of charmed baryons.

Linear regression models, especially the extended STIRPAT model, are routinely-applied for analyzing carbon emissions data. However, since the relationship between carbon emissions and the influencing factors is complex, fitting a simple parametric model may not be an ideal solution. This paper investigated various nonparametric approaches in statistics and machine learning (ML) for modeling carbon emissions data, including kernel regression, random forest and neural network. We selected data from ten Chinese cities from 2005 to 2019 for modeling studies. We found that neural network had the best performance in both fitting and prediction accuracy, which implies its capability of expressing the complex relationships between carbon emissions and the influencing factors. This study provides a new means for quantitative modeling of carbon emissions research that helps to understand how to characterize urban carbon emissions and to propose policy recommendations for "carbon reduction". In addition, we used the carbon emissions data of Wuhu city as an example to illustrate how to use this new approach.

This paper is written for a Festschrift in honour of Professor Marc Hallin and it proposes some developments on quantile regression. We connect our investigation to Marc's scientific production and we present some theoretical and methodological advances for quantiles estimation in non standard settings. We split our contributions in two parts. The first part is about conditional quantiles estimation for nonstationary time series: our approach combines local stationarity for Markov processes with quantile regression. The second part is about conditional quantiles estimation for the analysis of multivariate independent data in the presence of possibly large dimensional covariates: our procedure combines optimal transport theory with quantile regression forests. Monte Carlo studies illustrate numerically the performance of our methods and compare them to extant methods. The codes needed to replicate our results are available on our $\mathtt{GitHub}$ pages.

Artemisinin, derived from Artemisia annua, is currently used as the first-line treatment for malaria. However, wild-type plants have a low artemisinin biosynthesis rate. Although yeast engineering and plant synthetic biology have shown promising results, plant genetic engineering is considered the most feasible strategy, but it is also constrained by the stability of progeny development. Here we constructed three independent unique overexpressing vectors harboring three mainstream artemisinin biosynthesis enzymes HMGR, FPS, and DBR2, as well as two trichomes-specific transcription factors AaHD1 and AaORA. The simultaneous co-transformation of these vectors by Agrobacterium resulted in the successful increase of the artemisinin content in T0 transgenic lines by up to 3.2-fold (2.72%) leaf dry weight compared to the control plants. We also investigated the stability of transformation in progeny T1 lines. The results indicated that the transgenic genes were successfully integrated, maintained, and overexpressed in some of the T1 progeny plants’ genomes, potentially increasing the artemisinin content by up to 2.2-fold (2.51%) leaf dry weight. These results indicated that the co-overexpression of multiple enzymatic genes and transcription factors via the constructed vectors provided promising results, which could be used to achieve the ultimate goal of a steady supply of artemisinin at affordable prices around the world.

Optimal transport (OT) theory and the related $p$-Wasserstein distance ($W_p$, $p\geq 1$) are popular tools in statistics and machine learning. Recent studies have been remarking that inference based on OT and on $W_p$ is sensitive to outliers. To cope with this issue, we work on a robust version of the primal OT problem (ROBOT) and show that it defines a robust version of $W_1$, called robust Wasserstein distance, which is able to downweight the impact of outliers. We study properties of this novel distance and use it to define minimum distance estimators. Our novel estimators do not impose any moment restrictions: this allows us to extend the use of OT methods to inference on heavy-tailed distributions. We also provide statistical guarantees of the proposed estimators. Moreover, we derive the dual form of the ROBOT and illustrate its applicability to machine learning. Numerical exercises (see also the supplementary material) provide evidence of the benefits yielded by our methods., 55 pages, 11 Figures

Ionospheric scintillationadversely degrades the accuracy and reliability of satellite operation, communications, and navigation. At present, extensive ionospheric surveys and climatological statistics addressing GNSS scintillation have been conductedusing mainly global positioning system(GPS) observations. Nevertheless, the current investigationaboutionospheric scintillationin terms of the signals from the newly-developed BeiDou navigation satellite system (BDS) is limited, especially its multifrequency signals, which have significantly affected the BDS high-precision ionospheric research and applications.In this report, we focus on investigatingthe effects of ionospheric scintillation onmulti-frequencyBDSsignalsbased on ionospheric scintillation monitor receivers (ISMR) data at different geomagnetic latitudes in the Brazilian territory. The result illustratesthat the S4(B2) and S4(B3) linearly increase with S4(B1) for S4(B1)≤0.6, which is consistent with weak scattering theories.Meanwhile, the probability of the ionospheric scintillation events on B2 and B3 signals is approximately twice (S4≥0.7) as B1 signals in the equatorial ionization anomaly (EIA) regions. Additionally, we evaluated the inter-frequencyrelationship of two scintillation spectral characteristic parameters among three BDS frequencies (the strength at 1 Hz T andslope p) widely applied in GNSS positioning solutions.In terms of pand T, the performances among B1, B2, and B3 frequencies have a higher correlation respectively, and their values for B2 and B3 signals are more susceptible to be impacted by ionospheric scintillation. It is expected that the inter-frequencyrelation of these scintillation parameters among the BDS signals could support the robustness of GNSS receiver design and subsequent high-precision positioning applications under ionospheric scintillation conditions., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

In this paper, we investigate some characteristics of phantom Reissner-Nordström-de Sitter (RN-dS) black holes. The peculiar feature of phantom field renders this kind of black holes quite different from their counterparts. We can only find at most two horizons in this spacetime, i.e. event horizon and cosmological horizon. For the black hole charge parameter, we find that it is not bounded from below. We calculate quasinormal modes (QNMs) frequencies of massless neutral scalar field perturbation in this black hole spacetime, and some properties related to the large charge parameter are disclosed.

Patients with end-stage renal disease (ESRD) especially those undergoing dialysis have a high prevalence of hyperkalemia, which must be detected and treated immediately. But the initial symptoms of hyperkalemia are insidious, and traditional laboratory serum potassium concentration testing takes time. Therefore, rapid and real-time measurement of serum potassium is urgently needed. In this study, different machine learning methods were used to make rapid predictions of different degrees of hyperkalemia by analyzing the ECG. A total of 1024 datasets of ECG and serum potassium concentrations were analyzed from December 2020 to December 2021. The data were scaled into training and test sets. Different machine learning models (LR, SVM, CNN, XGB, Adaboost) were built for dichotomous prediction of hyperkalemia by analyzing 48 features of chest leads V2-V5. The performance of the models was also evaluated and compared using sensitivity, specificity, accuracy, accuracy, F1 score and AUC. We constructed different machine models to predict hyperkalemia using LR and four other common machine-learning methods. The AUCs of the different models ranged from 0.740 (0.661, 0.810) to 0.931 (0.912,0.953) when different serum potassium concentrations were used as the diagnostic threshold for hyperkalemia, respectively. As the diagnostic threshold of hyperkalemia was raised, the sensitivity, specificity, accuracy and precision of the model decreased to various degrees. And AUC also performed less well than when predicting mild hyperkalemia. Noninvasive and rapid prediction of hyperkalemia can be achieved by analyzing specific waveforms on the ECG by machine learning methods. But overall, XGB had a higher AUC in mild hyperkalemia, but SVM performed better in predicting more severe hyperkalemia.

Classical graph matching aims to find a node correspondence between two unlabeled graphs of known topologies. This problem has a wide range of applications, from matching identities in social networks to identifying similar biological network functions across species. However, when the underlying graphs are unknown, the use of conventional graph matching methods requires inferring the graph topologies first, a process that is highly sensitive to observation errors. In this paper, we tackle the blind graph matching problem with unknown underlying graphs directly using observations of graph signals, which are generated from graph filters applied to graph signal excitations. We propose to construct sample covariance matrices from the observed signals and match the nodes based on the selected sample eigenvectors. Our analysis shows that the blind matching outcome converges to the result obtained with known graph topologies when the signal sampling size is large and the signal noise is small. Numerical results showcase the performance improvement of the proposed algorithm compared to matching two estimated underlying graphs learned from the graph signals., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

In heavy quark limit, the lowest-lying charmed baryons with two light quarks can form an SU(3) triplet and sextet. The $Ξ_c$ in the SU(3) triplet and $Ξ_c'$ in the sextet have the same $J^{PC}$ quantum number and can mix due to the finite charm quark mass and the fact the strange quark is heavier than the up/down quark. We explore the $Ξ_c$-$Ξ_c'$ mixing by calculating the two-point correlation functions of the $Ξ_c$ and $Ξ_c'$ baryons from lattice QCD. Based on the lattice data, we adopt two independent methods to determine the mixing angle between $Ξ_c$ and $Ξ_c'$. After making the chiral and continuum extrapolation, it is found that the mixing angle $θ$ is $1.2^{\circ}\pm0.1^{\circ}$, which seems insufficient to account for the large SU(3) symmetry breaking effects found in weak decays of charmed baryons.

Nearest neighbor (NN) search is inherently computationally expensive in high-dimensional spaces due to the curse of dimensionality. As a well-known solution, locality-sensitive hashing (LSH) is able to answer c-approximate NN (c-ANN) queries in sublinear time with constant probability. Existing LSH methods focus mainly on building hash bucket-based indexing such that the candidate points can be retrieved quickly. However, existing coarse-grained structures fail to offer accurate distance estimation for candidate points, which translates into additional computational overhead when having to examine unnecessary points. This in turn reduces the performance of query processing. In contrast, we propose a fast and accurate in-memory LSH framework, called PM-LSH, that aims to compute the c-ANN query on large-scale, high-dimensional datasets. First, we adopt a simple yet effective PM-tree to index the data points. Second, we develop a tunable confidence interval to achieve accurate distance estimation and guarantee high result quality. Third, we propose an efficient algorithm on top of the PM-tree to improve the performance of computing c-ANN queries. In addition, we extend PM-LSH to support closest pair (CP) search in high-dimensional spaces. Here, we again adopt the PM-tree to organize the points in a low-dimensional space, and we propose a branch and bound algorithm together with a radius pruning technique to improve the performance of computing c-approximate closest pair (c-ACP) queries. Extensive experiments with real-world data offer evidence that PM-LSH is capable of outperforming existing proposals with respect to both efficiency and accuracy for both NN and CP search.

We explore the semileptonic and nonleptonic decays of doubly heavy baryons $(\Omega_{cc}^ {(*) +}, \Omega_{bb}^ {(*)0}, \Omega_{bc}^ {(*) -}, \Omega_{bc}^ {\prime 0}) $ induced by the $s\to u$ transition. Hadronic form factors are parametrized by transition matrix elements and are calculated in the light front quark model. With the form factors, we make use of helicity amplitudes and analyze semileptonic and nonleptonic decay modes of doubly heavy baryons. Benchmark results for partial decay widths, branching fractions, forward-backward asymmetries and other phenomenological observables are derived. We find that typical branching fractions for semileptonic decays into $\ell\bar\nu$ are at the order $10^ {-7}-10^ {-8} $ and the ones for nonleptonic decays are at the order $10^ {-5} $, which are likely detectable such as in LHCb experiment. With the potential data accumulated in future, our results may help to shape our understanding of the decay mechanism in the presence of two heavy quarks., Comment: 18 pages,8 figures

Cheng-Shyuan Rau1 *, Pao-Jen Kuo2 *, Hui-Ping Lin,2 Chia-Jung Wu,2 Yi-Chan Wu,2 Peng-Chen Chien,2 Ting-Min Hsieh,3 Hang-Tsung Liu,3 Chun-Ying Huang,3 Ching-Hua Hsieh2 1Department of Neurosurgery, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan; 2Department of Plastic Surgery, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan; 3Department of Trauma Surgery, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan*These authors contributed equally to this workCorrespondence: Ching-Hua Hsieh, Department of Plastic Surgery, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, No. 123, Ta-Pei Road, Niao-Song District, Kaohsiung City, 833, Taiwan, Tel +886-7-7327476, Fax +886-7-3450431, Email m93chinghua@gmail.comPurpose: Following major trauma, genes involved in adaptive immunity are downregulated, which accompanies the upregulation of genes involved in systemic inflammatory responses. This study investigated microRNA (miRNA)-mRNA interactome dysregulation in circulating T cells of patients with major trauma.Patients and Methods: This study included adult trauma patients who had an injury severity score ≥ 16 and required ventilator support for more than 48 h in the intensive care unit. Next-generation sequencing was used to profile the miRNAs and mRNAs expressed in CD3+ T cells isolated from patient blood samples collected during the injury and recovery stages.Results: In the 26 studied patients, 9 miRNAs (hsa-miR-16-2-3p, hsa-miR-16-5p, hsa-miR-185-5p, hsa-miR-192-5p, hsa-miR-197-3p, hsa-miR-23a-3p, hsa-miR-26b-5p, hsa-miR-223-3p, and hsa-miR-485-5p) were significantly upregulated, while 58 mRNAs were significantly downregulated in T cells following major trauma. A network consisting of 8 miRNAs and 22 mRNAs interactions was revealed by miRWalk, with three miRNAs (hsa-miR-185-5p, hsa-miR-197-3p, and hsa-miR-485-5p) acting as hub genes that regulate the network. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis suggested that “chemokine signaling pathway” was the predominant pathway.Conclusion: The study revealed a miRNA-mRNA interactome consisting of 8 miRNAs and 22 mRNAs that are predominantly involved in chemokine signaling in circulating T cells of patients following major trauma.Keywords: miRNA, next-generation sequencing, T cells, adaptive immunity, major trauma, critical illness

Here we report a study exploring how performance on visual short-term memory (VSTM) varies as a function of the availability of three-dimensional depth information and spatial features of objects.

Phonons as bosons are different from electrons as fermions. Unlike interatomic electron hopping that can be either positive or negative and further tuned by spin-orbit coupling, interatomic spring constant is positive, or the structure of atomic lattices would be dynamically unstable. Surprisingly, we found that topological phonon flat bands (FBs) can manifest either a positive or negative interatomic spring constant that couples the FB-modes of opposite chirality, as exemplified by first-principles calculations of a 2D material of Kagome-BN. To reveal its physical origin, we first establish a fundamental correspondence between a collective lattice-coupling (CLC) variable of two quasi-particle states (e.g., electronic states or phonon modes) of opposite parity in a periodic lattice with band topology. Topological semimetals arise with zero CLC at special k-points protected by symmetry; while positive and negative CLC at these k-points gives rise to normal and topological insulators, respectively. Then, we show topological FB has a special form of CLC that vanishes at all k-points as characterized by its real-space wave function, and multi-atom FB phonon mode can manifest effectively a negative interatomic spring constant. Our findings shed new light on our fundamental understanding of topology and provide a practical design principle for creating artificial bosonic topological states.

Veterinary antibiotics in agricultural soil are a growing concern, as they pose risks to soil quality and food safety. An analysis approach that covers a broad spectrum of target substances and has low detection limits is required for a comprehensive risk assessment. In this study, we developed a method for simultaneously analyzing 34 antibiotics (tetracyclines, sulfonamides, macrolides, and quinolones) in agricultural soil. The soil was extracted using an organic solution of acetonitrile and methanol (v:v, 1:1) with 0.2% formic acid followed by the addition of Na2EDTA-McIlvaine buffer. Dispersive and solid-phase extractions (SPE) were compared for cleanup. Ultra-performance liquid chromatography-tandem mass spectrometry with matrix-matched calibration was used for quantification. The results of this study showed that SPE was more appropriate for determining multi-class antibiotics. The SPE approach proved better recoveries (56–98%) than dispersive SPE (d-SPE) (28–121%). The matrix effects obtained by SPE (46–299%) were more reasonable than that by d-SPE (3–4036%). The method detection limits by SPE were in the range of 0.007–1.400 μg/kg with relative standard deviations

Objective: To conduct a preliminary assessment of intense pulsed light (IPL) treatment for allergic keratoconjunctivitis (AKC)-associated ocular itch. Background: Current control measures for AKC rely primarily on drugs. IPL is effective for dry eye disease (DED). Furthermore, phototherapy is effective for managing skin inflammation and pruritus, suggesting that eye itching could decrease in some patients having AKC complicated with DED following IPL treatment to control dry eye symptoms. Methods: Thirty-five patients having DED complicated with mid-to-severe AKC were administered three IPL treatments to the periorbital skin. The eye scores of subjective symptoms and signs of AKC and tear film breakup time (TBUT) were retrospectively assessed before and after each treatment. Results: The scores for AKC-related symptoms and signs were determined four times: on Day 1 (time 0), Day 15 (time 1), Day 45 (time 2), and Day 75 (time 3) before each treatment. The average symptom score significantly decreased with treatments (time 0: 30.97, time 1: 15.03, time 3: 10). The average sign score for both eyes decreased after the first IPL treatment (left eye: 7.97 vs. 11.38; right eye: 8.1 vs. 11.1). There were no further improvements in the signs after the last treatment. The TBUT value in the right eye increased from times 0 to 3 (2.31 vs. 4.66 vs. 7.71 vs. 7.74). The TBUT value in the left eye increased from times 0 to 3 (2.50 vs. 6.97 vs. 7.57 vs. 8.24). Conclusions: Symptoms and signs improved after IPL treatment in patients with AKC. Eye itching was gradually controlled and rarely recurred. IPL may be effective for AKC treatment.

The genus Alcea, a member of Malvaceae family consists of approximately 75 species worldwide distributing mainly in South-West Asia. Among these, 33 species grow in Iran. Plants of the Alcea (or Althaea) are among important medicinal plants in Iranian traditional medicine. They have long been used in the treatment of health problems and diseases. Alcea aucheri (Boiss.) Alef. species are distributed in different habitats of Iran. There is no information on its population genetic structure, genetic diversity, and morphological variability in Iran. Therefore, due to the importance of these plant species, we performed a combination of morphological and molecular data for this species. For this study, we used 118 randomly collected plants from 10 geographical populations in 5 provinces. AMOVA test revealed significant genetic difference among the studied populations and also revealed that, 74% of total genetic variability was due to within population diversity while, 26% was due to among population genetic differentiation. Mantel test showed positive significant correlation between genetic distance and geographical distance of the studied populations. Networking, STRUCTURE analyses revealed some degree of gene flow among these populations.

5-Hydroxymethylcytosine (5hmC), one of the most important RNA modifications, plays an important role in many biological processes. Accurately identifying RNA modification sites helps understand the function of RNA modification. In this work, we propose a computational method for identifying 5hmC-modified regions using machine learning algorithms. We applied a sequence feature embedding method based on the dna2vec algorithm to represent the RNA sequence. The results showed that the performance of our model is better that of than state-of-art methods. All dataset and source codes used in this study are available at: https://github.com/liu-h-y/5hmC_model.

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In recent years, the consensus control has become a research hotspot in microgrid cooperative control. However, when the VSG control is applied, the system has higher order, more parameters and more complex dynamic response. And there are few studies on the dynamic characteristics of parallel VSGs with the consensus control. Aiming at this problem, the small signal state space model of parallel VSG with consensus based secondary control is established in this paper firstly. Then the influences of damping, inertia, secondary control parameters on dynamic response are analyzed, and the design criterion of secondary control parameters is proposed. Finally, the simulation results verify the accuracy of model and correctness of conclusions.

As representative varieties of the four phases of the super rice breeding project in China, Lianyoupei 9 (LYP9), Y Liangyou 1 (YLY1), Y Liangyou 2 (YLY2), and Y Liangyou 900 (YLY900) achieved higher yield under optimal cultivation techniques. However, the impact of these high-yield rice varieties on greenhouse gas (GHG) emissions under high-yield cultivation management practices remains poorly understood. In this study, we conducted field experiments to investigate CH4 and N2O emissions from paddies containing four elite rice varieties, managed with field drying at the ineffective tillering stage and alternate wet/dry irrigation at the grain-filling stage. The plants were fertilised with nitrogen (N) at three different rates. The results showed that CH4 emission was highest at the tillering stage. N2O emission flux was dramatically increased by field drying at the ineffective tillering stage, and with the rate of N application. Rice variety was among the most important factors affecting CH4 emission and global warming potential (GWP). N2O emission was mainly related to N application rate rather than rice variety. YLY2 achieved higher yield than LYP9, YLY1, and YLY900, and lower GHG emission than YLY900. Our results indicate that rice variety should be considered as a key factor to reduce GHG emissions from rice paddies under high-yield cultivation practices. Based on its high yield and low GHG emission at the study site, YLY2 may be an optimal rice variety.

Yu Tang, Hang Liu, Jinxin Zhao, Miao Yi, Yaling Yuan, Yun Xia Department of Clinical Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of ChinaCorrespondence: Yun XiaDepartment of Clinical Laboratory, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing 400016, People’s Republic of ChinaTel +86-23-89012742Fax +86-23-89012513Email xiayun12cn@aliyun.comPurpose: Hypervirulent klebsiella pneumoniae (hvKP) is responsible for various invasive diseases and associated with high mortality. However, the clinical and microbiological factors of hvKP infection that influence prognosis have not been well studied. The purpose of this study was to evaluate the prognostic factors for in-hospital mortality of patients with hvKP infections, mainly focusing on clinical and microbiological characteristics.Methods: A retrospective study was conducted in hvKP strains which positive for iucA and string test. According to the clinical outcomes during hospitalization, hvKP-infected patients were divided into non-survivor and survivor groups. The clinical characteristics, capsule types, multi-locus sequence types (MLST), virulence genes and antimicrobial susceptibility were compared between those of the two groups.Results: A total of 135 patients were demonstrated to be with hvKP infections, with a prevalence rate of 22% among all the klebsiella pneumoniae infected cases. Sixteen of these patients died during hospitalization, with an in-hospital mortality rate of 11.9%. Univariate analysis confirmed that admission to the intensive care unit (ICU) (p=0.008), antimicrobial resistance of hvKP to ampicillin/sulbactam (p=0.028), cefepime (p=0.033), aztreonam (p=0.049) and harboring iroN gene (p=0.023) were associated with in-hospital mortality. On the contrary, the rmpA gene showed an inverse association with in-hospital mortality (p=0.017). Multivariate logistic regression analysis revealed that ICU admission (odds ratio [OR]=3.452, 95% confidence interval [CI]=1.052– 11.329; P=0.041) and iroN carriage (OR=9.278, 95% CI=1.654– 52.035; P=0.011) were independent prognostic factors for the in-hospital mortality of patients with hvKP infections.Conclusion: Emerging hvKP infection may lead to relatively high in-hospital mortality. ICU admission and iroN carriage were independent prognostic factors for the in-hospital mortality of patients with hvKP infections.Keywords: hypervirulent Klebsiella pneumoniae, prognostic factors, iucA, iroN, in-hospital mortality

In this study, the fate of carbon and nutrient elements; nitrogen, phosphorus, and potassium was investigated during the HTC of three model solutions with different nutrient concentrations to mimic...

Objective To evaluate the performance of modified carbapenem inactivation method (mCIM) and EDTA carbapenem inactivation method (eCIM) in detection of carbapenemase in Enterobacteriaceae Bateremia. Methods Polymerase chain reaction (PCR) was used to detect carbapenemase gene in 136 strains of carbapenem-resistant and -sensitive Enterobacteriaceae clinically isolated from 16 county-level hospital during January 2017 and September 2018. Meanwhile, the phenotype of obtained carbapenemase gene was screened by mCIM and eCIM. The results of gene detection and phenotypic screening test were analyzed and evaluated. Results Seventy-nine strains out of 85 carbapenem-resistant Enterobacteriaceae strains (CRE) were positive to carbapenemase gene by PCR, and 8 strains expressed class A and B carbapenemase gene, accounting for 10.13% (8/79). Seventy-eight strains of 85 CRE strains were positive detected by mCIM, and 44 strains were identified to be positive by eCIM among them. The carbapenem-resistant genes were not detected in the 51 carbapenem-sensitive strains by mCIM results. Screening the carbapenemase by mCIM had the sensitivity of 98.7% (95%CI: 92.2~99.9), the specificity of 100.0% (95%CI: 92.1~100.0), and the Kappa value of 0.985. When eCIM screened metallo-β-lactamase, the sensitivity was 85.7% (95%CI: 72.1~93.6), the specificity was 94.4%(95%CI: 80.0~99.0), and the Kappa value was 0.787. Screening serine carbapenemase, the sensitivity of eCIM was 89.5%(95%CI: 74.3~96.6), the specificity was 100.0%(95%CI: 90.6~100.0), and the Kappa value was 0.904. Conclusion Combination of mCIM and eCIM can screen carbapenemase-producing Enterobacteriaceae effectively. However, the sensitivity of the combined detection to screen metallo-β-lactamase will be reduced with the emergence of a large number of co-expressed class A and B carbapenemase-producing Enterobacteriaceae.

Ground-based differential interferometry synthetic aperture radar (GB-DInSAR) is a promising deformation measurement technology developed in the last 20 years. The GBDInSAR system is capable of sensing millimeter-scale deformations in the range of tens of meters to several kilometers from the target area in a continuous, all-weather environment. This article introduces in detail the basic principles of GB-DInSAR imaging, conventional signal models, deformationinversion algorithms, system working mode, existing typical systems, and application examples of high-precision deformation measurement in different scenarios. Moreover, this article systematically summarizes the latest research progress of GB-DInSAR technology and its future direction of development.

An Improved Sinusoidal Pulse Width Modulation (ISPWM) technique carried out to obtain pure sine waves for voltage and current signals in Quasi Z-Sourc Inverters (QZSIs) in the load side is given in this study. This switching method can be examined to two and multi-phase approaches simply through the addition of the same controller structure to per phase. This is the main advantage of the proposed converter to obtain higher voltage gains at the output ends of this inverter. The idea is to generate a positive rectified voltage at the output point of the QZSI and positive and negative rectified voltages at the output terminals of the QZSI in two-phase approaches to improve the quality of the output voltage of the F-Bridge Inverter (FBI). These rectified voltages are applied to the Full-Bridge Inverter (FBI) block and pure sine waves to obtain the load current and voltages. 1.34% of the Total Harmonic Distortion (THD) for the output voltage has been reported in the one-phase system while 0.88% of THD has been obtained in the two-phase approach. Besides, the reliability of the QZSI was tested through the Mean Time to Failure (MTTF) analysis with the values of the proposed components. The calculations show a very good result for the long-life of the converter. All experimental and simulations steps have been obtained for the same values of the components to support and confirm the accuracy and correctness of the proposed IMSPW. For the states of single-phase and two-phase converters, a 50 Hz sine-wave with 220 V and 440 V peak to peak amplitude has been acquired. Evaluations of the quality of the voltage and current waveforms related to different active (Resistive, P) and reactive (combination of Resistance and Inductance, QL) loads have been carried out. Experimental results show confirmation for all simulation and mathematical results.

Layered SnSe2 flakes and SnSe2/SnO2 heterojunction-based chemiresistive-type sensors demonstrate good gas sensing properties at low temperatures. The pure SnSe2-based chemiresistive-type sensor exhibited good response and recovery to both NO2 and NH3 while also showing a moderate response to hydrogen, CO, C3H6 and several typical volatile organic vapors, such as methanol, ethanol, acetone and formaldehyde, near room temperature, indicating that it possesses poor selectivity. However, compared to pristine SnSe2, a SnSe2/SnO2 heterojunction-based chemiresistive-type sensor prepared by the thermal oxidation method showed greatly improved sensitivity and superior selectivity toward NO2 at 120 °C. Such impressive improvements in the sensing performance can be attributed to the formation of SnSe2/SnO2 heterojunctions. The density functional theory (DFT) calculations revealed that there was a lower adsorption energy and greater Bader charge value between the adsorbed NO2 and SnSe2/SnO2 heterojunction materials.

Recently the second author and Qin numerically verified some Mahler measure identities of genus 2 and 3 polynomial families. In this paper, we use the elliptic regulator to prove an identity invoving shifted Mahler measure for Boyd's family.

The stochastic block model is widely used for detecting community structures in network data. However, the research interest of much literature focuses on the study of one sample of stochastic block models. How to detect the difference of the community structures is a less studied issue for stochastic block models. In this article, we propose a novel test statistic based on the largest singular value of a residual matrix obtained by subtracting the geometric mean of two estimated block mean effects from the sum of two observed adjacency matrices. We prove that the null distribution of the proposed test statistic converges in distribution to the Tracy-Widom distribution with index 1, and we show the difference between the two samples for stochastic block models can be tested via the proposed method. Further, we show that the proposed test has asymptotic power guarantee against alternative models. Both simulation studies and real-world data examples indicate that the proposed method works well.

Non-Euclidean data is currently prevalent in many fields, necessitating the development of novel concepts such as distribution functions, quantiles, rankings, and signs for these data in order to conduct nonparametric statistical inference. This study provides new thoughts on quantiles, both locally and globally, in metric spaces. This is realized by expanding upon metric distribution function proposed by Wang et al. (2021). Rank and sign are defined at both the local and global levels as a natural consequence of the center-outward ordering of metric spaces brought about by the local and global quantiles. The theoretical properties are established, such as the root-$n$ consistency and uniform consistency of the local and global empirical quantiles and the distribution-freeness of ranks and signs. The empirical metric median, which is defined here as the 0th empirical global metric quantile, is proven to be resistant to contaminations by means of both theoretical and numerical approaches. Quantiles have been shown valuable through extensive simulations in a number of metric spaces. Moreover, we introduce a family of fast rank-based independence tests for a generic metric space. Monte Carlo experiments show good finite-sample performance of the test. Quantiles are demonstrated in a real-world setting by analysing hippocampal data., Comment: 55 pages

This paper proposes various nonparametric tools based on measure transportation for directional data. We use optimal transports to define new notions of distribution and quantile functions on the hypersphere, with meaningful quantile contours and regions yielding closed-form formulas under the classical assumption of rotational symmetry. The empirical versions of our distribution functions enjoy the expected Glivenko-Cantelli property of traditional distribution functions. They provide fully distribution-free concepts of ranks and signs and define data-driven systems of (curvilinear) parallels and (hyper)meridians. Based on this, we also construct a universally consistent test of uniformity and a class of fully distribution-free tests for directional MANOVA which, in simulations, outperform all their existing competitors. Two real-data examples involving the analysis of sunspots and the structure of proteins conclude the paper.

The pseudo-Gaussian portmanteau tests of Chitturi, Hosking, and Li and McLeod for VARMA models are revisited from a Le Cam perspective, providing a precise and more rigorous description of the asymptotic behavior of the multivariate portmanteau test statistic, which depends on the dimension $d$ of the observations, the number $m$ of lags involved, and the length $n$ of the observation period. Then, based on the concepts of center-outward ranks and signs recently developed (Hallin, del Barrio, Cuesta-Albertos, and Matr\' an, {\it Annals of Statistics} 49, 1139--1165, 2021), a class of multivariate rank- and sign-based portmanteau test statistics is proposed which, under the null hypothesis and under a broad family of innovation densities, can be approximated by an asymptotically chi-square variable. The asymptotic properties of these tests are derived; simulations demonstrate their advantages over their classical pseudo-Gaussian counterpart., Comment: 46 pages, 7 figures

The massive consumption of fossil fuels has led to a significant accumulation of carbon dioxide in the atmosphere, and a CO2 concentration unprecedented over the past 3 million years. Capturing CO2 and further converting it into valuable chemicals or fuels could contribute to solving this dilemma. In recent years, electrochemical CO2 reduction technology has attracted increasing attention in research and development due to the tremendous advances in green and renewable electricity. This doctoral thesis provides a comprehensive summary of the progress in electrochemical CO2 reduction, especially for the formation of formic acid/formate, due to its advantages in meeting techno-economic requirements. Furthermore, in terms of the catalyst selection, we opt for metal-organic framework (MOF) based materials as our target catalysts, which have received much attention in recent years due to their unique structures. Firstly, considering the poor conductivity of most MOFs, electrocatalysts based on 2D-MOFs (also known as metal-organic layers, MOLs) would be a promising option. Based on the synthesis strategy and stability requirement, we decided to synthesize MOLs with a 2D-kgd lattice, consisting of Zr6-oxo clusters as metal nodes and tridentate linkers. Zr6-oxo-based MOFs, such as UiO-66, are usually found to exhibit good chemical stability. Furthermore, the addition of acetic acid as a capping agent can inhibit the stacking of the MOL layers and enable the direct synthesis of free-standing MOLs. As a result, Zr-TATB MOL was successfully constructed by a facile solvothermal process, using for the first time TATB (4,4’,4’’-s-triazine-2,4,6-triyl-tribenzoate) as a linker. Furthermore, multiple characterizations verified and validated its exact structure, which was in agreement with the expected MOL structure. Secondly, Zr-TATB MOL with multiple anchoring sites on its surface shows a great potential of immobilizing different catalytic sites by post-modification strategies to form MOL composites. As a representative, uniformly dispersed Bi2O3 nanowires were grown on the Zr-TATB MOL, denoted as Bi2O3/MOL. The structure of Bi2O3/MOL was exactly determined by advanced electron microscopy techniques. The post-modification process of Zr-TATB MOL was followed by ex-situ electron microscopy in order to determine the growth process from atomic level dispersion to Bi nanowires. The monolayer morphology of MOL facilitates the characterization of the structures, which provides a good basis for the rational design of MOF composites. Thirdly, electrocatalytic CO2 reduction (ECR) tests were conducted in a conventional H-type cell using carbon paper as a backing electrode. Bi2O3/MOL exhibited excellent ECR performance with Faradaic efficiencies of over 85% to formate at a wide potential window (~0.4 V), and the best partial current density reached an impressive value of 2.3 A·mgBi-1. This performance far exceeded that of Bi2O3/UiO (a typical 3D-MOF-based composite) and Bi2O3/AB (a conductive carbon based composite), highlighting the superiority of 2D-MOF composites. The Bi2O3/MOL also exhibited good structural stability, verified by multiple characterizations. In addition, further ECR tests were conducted using gas diffusion electrodes (GDEs), achieving industrially relevant current densities towards formate of over 300 mA·cm-2. Among all MOFs reported for ECR reactions, Bi2O3/MOL exhibited excellent formate generation activity, whether using carbon paper in H-cells or GDEs. Finally, we verified the universality of the post-modification strategy for the design of MOL-based composites. We were able to obtain a series of MOL composites bearing different metal species by tuning the reaction conditions, all of which exhibited good ECR activity. This research demonstrates the great potential of MOL-based composites as electrocatalysts and encourages further exploration of highly tunable MOLs for catalytic studies.

Additional file 3: Fig. S1. DNA transfection induced immunoreaction and its suppression with treatment with immune inhibitors in ST cells. Fig. S2. Assessment of the immunoreaction (DMSO) and treatment effect of immune inhibitors after DNA is transfected into cells. Fig. S3. Distribution of fragment sizes in the STARR-seq libraries. Fig. S4. Genome coverage of STARR-seq libraries in pig non-repetitive regions. Fig. S5. GC-content analysis for the STARR-seq libraries. Fig. S6. Reproducibility of STARR-seq. Fig. S7. Correlation analysis of enhancers strength in two biological replicates of ST cells. Fig. S8. Venn diagram showing the overlap of enhancers between our STARR-seq approach and other published studies. Fig. S9. GO analysis of genes in proximity to enhancers. Fig. S10. ATAC-seq and STARR-seq enhancers integrated analysis. Fig. S11. Snapshots of signals at three types of chromatin state for the STARR-seq enhancer regions. Fig. S12. The enhancer (Sscrofa11.1, 8:119,324,324-119,325,095) and PPP3CA gene interacted by a TAD region in pig muscle tissues. Fig. S13. The enhancer (Sscrofa11.1, 1:4,548,557-4,549,774) and QKI gene interacted by a TAD region in pig liver tissues.