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Chronic obstructive pulmonary disease (COPD), a progressive inflammatory condition of the airways, emerges from the complex interplay between genetic predisposition and environmental factors. Notably, its incidence is on the rise, particularly among the elderly demographic. Current research increasingly highlights cellular senescence as a key driver in chronic lung pathologies. Despite this, the detailed mechanisms linking COPD with senescent genomic alterations remain elusive. To address this gap, there is a pressing need for comprehensive bioinformatics methodologies that can elucidate the molecular intricacies of this link. This approach is crucial for advancing our understanding of COPD and its association with cellular aging processes. Utilizing a spectrum of advanced bioinformatics techniques, this research delved into the potential mechanisms linking COPD with aging-related genes, identifying four key genes (EP300, MTOR, NFE2L1, TXN) through machine learning and weighted gene co-expression network analysis (WGCNA) analyses. Subsequently, a precise diagnostic model leveraging an artificial neural network was developed. The study further employed single-cell analysis and molecular docking to investigate senescence-related cell types in COPD tissues, particularly focusing on the interactions between COPD and NFE2L1, thereby enhancing the understanding of COPD's molecular underpinnings. Leveraging artificial neural networks, we developed a robust classification model centered on four genes—EP300, MTOR, NFE2L1, TXN—exhibiting significant predictive capability for COPD and offering novel avenues for its early diagnosis. Furthermore, employing various single-cell analysis techniques, the study intricately unraveled the characteristics of senescence-related cell types in COPD tissues, enriching our understanding of the disease's cellular landscape. This research anticipates offering novel biomarkers and therapeutic targets for early COPD intervention, potentially alleviating the disease's impact on individuals and healthcare systems, and contributing to a reduction in global COPD-related mortality. These findings carry significant clinical and public health ramifications, bolstering the foundation for future research and clinical strategies in managing and understanding COPD. [ABSTRACT FROM AUTHOR]

Multiple synchronous lung cancers (MSLCs) constitute a unique subtype of lung cancer. To explore the genomic and immune heterogeneity across different pathological stages of MSLCs, we analyse 16 MSLCs from 8 patients using single-cell RNA-seq, single-cell TCR sequencing, and bulk whole-exome sequencing. Our investigation indicates clonally independent tumours with convergent evolution driven by shared driver mutations. However, tumours from the same individual exhibit few shared mutations, indicating independent origins. During the transition from pre-invasive to invasive adenocarcinoma, we observe a shift in T cell phenotypes characterized by increased Treg cells and exhausted CD8+ T cells, accompanied by diminished cytotoxicity. Additionally, invasive adenocarcinomas exhibit greater neoantigen abundance and a more diverse TCR repertoire, indicating heightened heterogeneity. In summary, despite having a common genetic background and environmental exposure, our study emphasizes the individuality of MSLCs at different stages, highlighting their unique genomic and immune characteristics. Multiple synchronous lung cancers (MSLCs) are a subtype of lung cancer. Here the authors characterise MSLCs using single cell RNA sequencing, single cell TCR sequencing and bulk whole-exome sequencing to investigate the mutations that arise in and are associated with invasive adenocarcinoma development, and immune microenvironment changes in this process. [ABSTRACT FROM AUTHOR]

Anthropogenic activities have raised nitrogen (N) input worldwide with profound implications for soil carbon (C) cycling in ecosystems. The specific impacts of N input on soil organic matter (SOM) pools differing in microbial availability remain debatable. For the first time, we used a much‐improved approach by effectively combining the 13C natural abundance in SOM with 21 years of C3–C4 vegetation conversion and long‐term incubation. This allows to distinguish the impact of N input on SOM pools with various turnover times. We found that N input reduced the mineralization of all SOM pools, with labile pools having greater sensitivity to N than stable ones. The suppression in SOM mineralization was notably higher in the very labile pool (18%–52%) than the labile and stable (11%–47%) and the very stable pool (3%–21%) compared to that in the unfertilized control soil. The very labile C pool made a strong contribution (up to 60%) to total CO2 release and also contributed to 74%–96% of suppressed CO2 with N input. This suppression of SOM mineralization by N was initially attributed to the decreased microbial biomass and soil functions. Over the long‐term, the shift in bacterial community toward Proteobacteria and reduction in functional genes for labile C degradation were the primary drivers. In conclusion, the higher the availability of the SOM pools, the stronger the suppression of their mineralization by N input. Labile SOM pools are highly sensitive to N availability and may hold a greater potential for C sequestration under N input at global scale. [ABSTRACT FROM AUTHOR]

Clear cell renal cell carcinoma (ccRCC), a prevalent kidney cancer form characterised by its invasiveness and heterogeneity, presents challenges in late‐stage prognosis and treatment outcomes. Programmed cell death mechanisms, crucial in eliminating cancer cells, offer substantial insights into malignant tumour diagnosis, treatment and prognosis. This study aims to provide a model based on 15 types of Programmed Cell Death‐Related Genes (PCDRGs) for evaluating immune microenvironment and prognosis in ccRCC patients. ccRCC patients from the TCGA and arrayexpress cohorts were grouped based on PCDRGs. A combination model using Lasso and SuperPC was constructed to identify prognostic gene features. The arrayexpress cohort validated the model, confirming its robustness. Immune microenvironment analysis, facilitated by PCDRGs, employed various methods, including CIBERSORT. Drug sensitivity analysis guided clinical treatment decisions. Single‐cell data enabled Programmed Cell Death‐Related scoring, subsequent pseudo‐temporal and cell–cell communication analyses. A PCDRGs signature was established using TCGA‐KIRC data. External validation in the arrayexpress cohort underscored the model's superiority over traditional clinical features. Furthermore, our single‐cell analysis unveiled the roles of PCDRG‐based single‐cell subgroups in ccRCC, both in pseudo‐temporal progression and intercellular communication. Finally, we performed CCK‐8 assay and other experiments to investigate csf2. In conclusion, these findings reveal that csf2 inhibit the growth, infiltration and movement of cells associated with renal clear cell carcinoma. This study introduces a PCDRGs prognostic model benefiting ccRCC patients while shedding light on the pivotal role of programmed cell death genes in shaping the immune microenvironment of ccRCC patients. [ABSTRACT FROM AUTHOR]

Kidney renal clear cell carcinoma (KIRC) pathogenesis intricately involves immune system dynamics, particularly the role of T cells within the tumour microenvironment. Through a multifaceted approach encompassing single‐cell RNA sequencing, spatial transcriptome analysis and bulk transcriptome profiling, we systematically explored the contribution of infiltrating T cells to KIRC heterogeneity. Employing high‐density weighted gene co‐expression network analysis (hdWGCNA), module scoring and machine learning, we identified a distinct signature of infiltrating T cell‐associated genes (ITSGs). Spatial transcriptomic data were analysed using robust cell type decomposition (RCTD) to uncover spatial interactions. Further analyses included enrichment assessments, immune infiltration evaluations and drug susceptibility predictions. Experimental validation involved PCR experiments, CCK‐8 assays, plate cloning assays, wound‐healing assays and Transwell assays. Six subpopulations of infiltrating and proliferating T cells were identified in KIRC, with notable dynamics observed in mid‐ to late‐stage disease progression. Spatial analysis revealed significant correlations between T cells and epithelial cells across varying distances within the tumour microenvironment. The ITSG‐based prognostic model demonstrated robust predictive capabilities, implicating these genes in immune modulation and metabolic pathways and offering prognostic insights into drug sensitivity for 12 KIRC treatment agents. Experimental validation underscored the functional relevance of PPIB in KIRC cell proliferation, invasion and migration. Our study comprehensively characterizes infiltrating T‐cell heterogeneity in KIRC using single‐cell RNA sequencing and spatial transcriptome data. The stable prognostic model based on ITSGs unveils infiltrating T cells' prognostic potential, shedding light on the immune microenvironment and offering avenues for personalized treatment and immunotherapy. [ABSTRACT FROM AUTHOR]

Background: Globally, breast cancer, with diverse subtypes and prognoses, necessitates tailored therapies for enhanced survival rates. A key focus is glutamine metabolism, governed by select genes. This study explored genes associated with T cells and linked them to glutamine metabolism to construct a prognostic staging index for breast cancer patients for more precise medical treatment. Methods: Two frameworks, T‐cell related genes (TRG) and glutamine metabolism (GM), stratified breast cancer patients. TRG analysis identified key genes via hdWGCNA and machine learning. T‐cell communication and spatial transcriptomics emphasized TRG's clinical value. GM was defined using Cox analyses and the Lasso algorithm. Scores categorized patients as TRG_high+GM_high (HH), TRG_high+GM_low (HL), TRG_low+GM_high (LH), or TRG_low+GM_low (LL). Similarities between HL and LH birthed a "Mixed" class and the TRG_GM classifier. This classifier illuminated gene variations, immune profiles, mutations, and drug responses. Results: Utilizing a composite of two distinct criteria, we devised a typification index termed TRG_GM classifier, which exhibited robust prognostic potential for breast cancer patients. Our analysis elucidated distinct immunological attributes across the classifiers. Moreover, by scrutinizing the genetic variations across groups, we illuminated their unique genetic profiles. Insights into drug sensitivity further underscored avenues for tailored therapeutic interventions. Conclusion: Utilizing TRG and GM, a robust TRG_GM classifier was developed, integrating clinical indicators to create an accurate predictive diagnostic map. Analysis of enrichment disparities, immune responses, and mutation patterns across different subtypes yields crucial subtype‐specific characteristics essential for prognostic assessment, clinical decision‐making, and personalized therapies. Further exploration is warranted into multiple fusions between metrics to uncover prognostic presentations across various dimensions. [ABSTRACT FROM AUTHOR]

[Objective] Winter wheat in Northern China is often rotated with other crops which are expected to have a legacy effect. This paper aims to study the effect of different tillage and preceding crops on soil nutrients, yield and water use efficiency of the winter wheat. [Method] The field experiment consisted of a rotary tillage (RT) and a no-tillage (NT). The preceding crops for each tillage were corn (MW) or soybean (SW). During the experiment, we measured the changes in soil nutrients, soil water content, water and fertilizer use efficiency, and yield of the wheat. [Result] For the same preceding crop, non-tillage increased soil water content compared to rotary tillage; under the same tillage, soil water content with maize as the preceding crop was higher than that with soybean as the preceding crop. In all treatments, soil nutrients decreased with soil depth. In the 0-50 cm soil layer, NTSW increased soil organic carbon, soil total nitrogen and nitrate nitrogen by 4.14%-13.54%, 35.51%-54.44% and 55.75%-112%, respectively, compared to the RTMW. RTMW had the highest available phosphorus and potassium in the 10-50 cm soil layer. The RTSW had the highest ammonium nitrogen in the 0-50 cm soil layer, 13.39%-20.64% more than that in the RTMW. The winter wheat in NTSW had the highest spike numbers, spikelet numbers, thousand-grain weight; and its grain yield was 16.62% higher than that of RTMW. The NTSW had the highest water use efficiency, 8.67% more than that of RTMW. The NTSW had the highest nitrogen, phosphorus and potassium use efficiency. [Conclusion] The NTSW facilitated nutrient accumulation in the winter wheat field. It had the highest water and fertilizer use efficiency and increased grain yields the most as a result. [ABSTRACT FROM AUTHOR]

Subsoiling tillage breaks up the shallow plow layer and thickened plow pan resulting from prolonged crop rotation, thus enhancing the soil tillage layer environment and fostering crop growth. However, these changes in tillage practices are not accompanied by corresponding advancements in irrigation technology. Therefore, this study compared drip irrigation (DI) and micro-sprinkler irrigation (MS) with three watering levels (H, M, L) based on soil water content (70%, 60%, 50% of field capacity) against traditional surface irrigation (CK, 70%FC) to find the most suitable irrigation approach for subsoiling wheat fields. This study found that adjusting irrigation methods and regimes significantly impacted wheat growth and yield. Drip irrigation boosts winter wheat grain yield, harvest index, biomass transfer amount, biomass transfer rate, nitrogen accumulation, nitrogen use efficiency, and nitrogen harvest index significantly compared to surface and micro-sprinkler methods. Drip irrigation, notably the DI-M treatment, significantly enhances winter wheat grain yield by 28.7% compared to CK. Drip irrigation produced optimal results when soil water levels decreased to 60% of the field capacity. This suggests adopting a combination of DI, with irrigation initiated at 60% of field capacity, for enhanced wheat production and resource efficiency. [ABSTRACT FROM AUTHOR]

Generalized Pareto distribution (GPD), an asymmetrical distribution, primarily models exceedances over a high threshold in many applications. Within the peaks-over-threshold (POT) framework, we consider a new GPD parameter estimation method to estimate a common tail risk measure, the value at risk (VaR). The proposed method is more suitable for the POT framework and makes full use of data information. Specifically, our estimation method builds upon the generalized probability weighted moments method and integrates it with the nonlinear weighted least squares method. We use exceedances for the GPD, minimizing the sum of squared differences between the sample and population moments of a function of GPD random variables. At the same time, the proposed estimator uses three iterations and assigns weight to further improving the estimated performance. Under Monte Carlo simulations and with a real heavy-tailed dataset, the simulation results show the advantage of the newly proposed estimator, particularly when VaRs are at high confidence levels. In addition, by simulating other heavy-tailed distributions, our method still exhibits good performance in estimating misjudgment distributions. [ABSTRACT FROM AUTHOR]

This letter to the editor commends a study titled "The impact of health care on outcomes of suspected testicular torsion: results from the GRAND study." The study provides valuable insights into surgical exploration for suspected testicular torsion and its perioperative outcomes. The authors used national data from the German National Inpatient Dataset (GRAND) to analyze the factors influencing exploration results. The study found that almost half of the patients who underwent surgical exploration did not have intraoperative confirmation of testicular torsion. However, there are limitations to the study, including its retrospective nature, reliance on administrative data, and the inability to assess long-term complications. Despite these limitations, the research contributes to our understanding of the treatment of suspected testicular torsion and can guide clinical practice. [Extracted from the article]

In this paper, we propose a least-squares estimator based on Logistic transformation of order statistics (LLSE) and grouped LLSE for the generalized Logistic distribution. Some asymptotic results are provided. Two simulations are undertaken to assess the performance of the proposed method and to compare them with other methods suggested in this paper. The simulation results indicate that LLSE performs better than some other methods and grouped LLSE performs fairly well in small sample size. Finally, LLSE is applied to a real dataset. [ABSTRACT FROM AUTHOR]

Summer maize crop development, yield, and water use characteristics under water deficit conditions at different growth stages were investigated in this study using different irrigation regime treatments at the seedling (S), jointing (J), tasseling (T), and grain filling stages (F) in 2018 and 2019 in China. Ten different irrigation treatments were set, including three-irrigation application intervals (JTFi, STFi, SJFi, SJTi), two-irrigation applications (STi, JTi, JFi), and single-irrigation applications (Ti, Ji). These were compared to the control treatment (CK), which had sufficient irrigation provided at four intervals (SJTFi). The results showed that compared to CK, a water deficit at the seedling and jointing stages had a greater effect on plant height, whereas a water deficit at the tasseling and filling stages had a greater effect on the leaf area index, and a continuous water deficit had an effect on the stem diameter of summer maize. Limitations in terms of the growth and development of summer maize increased with less frequent irrigation. As irrigation decreased, the grain yield decreased, and the water use efficiency increased, and a water deficit at the tasseling stage had the greatest effect on the yield and water use efficiency. The JTFi treatment was the optimal irrigation regime with a yield decline, and its water consumption was reduced by 16.9% (p < 0.05) on average. However, compared to CK, the water use efficiency of the JTFi treatment increased by 17.3% (p < 0.05). Moreover, the JTFi treatment had the smallest maize yield response factor value (Ky) of 0.16, and its comprehensive score was the second highest after CK. [ABSTRACT FROM AUTHOR]

Livestock sheds are local and regional hotspots of greenhouse gases (GHG) emissions, but only very few studies analyse the intensities of GHG emissions from this source. The objective of this study was to quantify annual CH4, CO2 and N2O emissions from inside and outside of sheepfolds and summer cattle sheds in a typical agro‐pastoral ecotone using static chamber technique. Both sheepfolds and cattle shed functioned as huge net sources of CH4 and N2O at annual scale. Animal presence increased CH4, CO2 and N2O effluxes for up to 1100 times compared to the animal sheds without animals. N2O emissions boosted for 160%–280% during and after rainfall and spring‐thaw events. The CH4 and CO2 fluxes increased exponentially with faeces temperature for the outside sheepfold and summer cattle shed. The annual GHG emissions from both sheepfolds and summer cattle shed were 56 t CO2 equivalents ha−1, of which N2O contributed to 94%. Sheepfold dominated the total GHG emissions from animal sheds and accounted for 83% of the annual GHG flux. Annual emission on a per animal basis was 15, 0.2 and 28 kg CO2 eq year−1 sheep−1 and 26, 10 and 140 kg CO2 eq year−1 cattle−1 for N2O, CH4 and CO2, respectively. The annual N2O emissions from animal sheds were 70–250 times larger than nearby grassland soils, which were also net sink for atmospheric CH4. Concluding, animal sheds are very intensive local hotspots of GHG emissions, which should be considered at the local and regional scales. [ABSTRACT FROM AUTHOR]

In feature weighted fuzzy c-means algorithms, there exist two challenges when the feature weighting techniques are used to improve their performances. On one hand, if the values of feature weights are learnt in advance, and then fixed in the process of clustering, the learnt weights might be lack of flexibility and might not fully reflect their relevance. On the other hand, if the feature weights are adaptively adjusted during the clustering process, the algorithms maybe suffer from bad initialization and lead to incorrect feature weight assignment, thus the performance of the algorithms may degrade the in some conditions. In order to ease these problems, a novel weighted fuzzy c-means based on feature weight learning (FWL-FWCM) is proposed. It is a hybrid of fuzzy weighted c-means (FWCM) algorithm with Improved FWCM (IFWCM) algorithm. FWL-FWCM algorithm first learns feature weights as priori knowledge from the data in advance by minimizing the feature evaluation function using the gradient descent technique, then iteratively optimizes the clustering objective function which integrates the within weighted cluster dispersion with a term of the discrepancy between the weights and the priori knowledge. Experiments conducted on an artificial dataset and real datasets demonstrate the proposed approach outperforms the-state-of-the-art feature weight clustering methods. The convergence property of FWL-FWCM is also presented. [ABSTRACT FROM AUTHOR]

Objectives: To assess the association between common-used serum tumor markers and recurrence of lung adenocarcinoma and squamous cell carcinoma separately and determine the prognostic value of serum tumor markers in lung adenocarcinoma featured as ground glass opacities. Methods: A total of 2,654 non-small cell lung cancer patients undergoing surgical resection between January 2008 and September 2014 were analyzed. The serum levels of carcinoma embryonic antigen (CEA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153) and carbohydrate antigen 199 (CA199) were tested preoperatively. Survival analyses were performed with COX proportional hazard regression. Results: Among patients with lung adenocarcinoma, elevated preoperative serum CEA(HR=1.246, 95%CI:1.043-1.488, P=0.015), CYFRA21-1(HR=1.209, 95%CI:1.015-1.441, P=0.034) and CA125(HR=1.361, 95%CI:1.053-1.757, P=0.018) were significantly associated with poorer recurrence free survival (RFS). Elevated preoperative serum CA199 predicted worse RFS in patients diagnosed with lung squamous cell carcinoma (HR=1.833, 95%CI: 1.216-2.762, P=0.004). Preoperative serum CYFRA21-1(HR=1.256, 95%CI:1.044-1.512, P=0.016) and CA125(HR=1.373, 95%CI: 1.050-1.795, P=0.020) were independent prognostic factors for patients with adenocarcinoma presenting as solid nodules while serum CEA (HR=2.160,95%CI:1.311-3.558, P=0.003) and CA125(HR=2.475,95%CI:1.163-5.266, P=0.019) were independent prognostic factors for patients with adenocarcinoma featured as ground glass opacities. Conclusions: The prognostic significances of preoperative serum tumor markers in non-small cell lung cancer were associated with radiological features and histological types. [ABSTRACT FROM AUTHOR]

Ankyrin 1 (ANK1) gene has been demonstrated to be a functional candidate gene for meat quality that helps to constitute and maintain the structure of the cell skeleton. In this study, three contiguous ANK1 regions from yak were analyzed using polymerase chain reaction-single-stranded conformational polymorphism (PCR–SSCP). As a result, nine single-nucleotide polymorphisms (SNPs) were identified, four of them in the coding region and three (c.179 C/A, c.250 G/C, and c.313 C/T) putatively resulting in amino acid changes (p. Ala 60 Glu, p. Asp 84 His, and p. Pro 105 Ser). Some SNPs in promoter region were located within or nearby the putative transcription factor binding sites, such as Sp1 and GATA, which might have an impact on the expression of the yak ANK1 gene. The presence of C1–D3 and C1–A3 were associated with an increased hot carcass weight (p = 0.0045) and a decreased drip loss rate (p = 0.0046). The presence of B1–B3, C1–A3 and C1–D3 had decreased Warner–Bratzler shear force (p = 0.0066, p = 0.0343 and p = 0.0004). The presence of one and two copies of B1–B3 and C1–A3 had decreased Warner–Bratzler shear force (p = 0.0005 and p = 0.0443), and C1–A3 had also decreased drip loss rate (p = 0.0164). These findings indicated that genetic variations of the ANK1 gene would be a preferable biomarker for the improvement of yak meat quality. [ABSTRACT FROM AUTHOR]

Background: Nonsynonymous tumor mutation burden (NSTMB) could affect the prognosis of esophageal cancer (EC) patients, but differentially expressed genes between EC patients with different NSTMB have not been explored. Our study aimed to compare differentially expressed genes between EC patients with different NSTMB (high vs. low). Methods: RNA‐seq data for EC patients were downloaded from The Cancer Genome Atlas (TCGA). The edgeR package was used to identify differentially expressed genes between patients with different NSTMB. Cell type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) software was employed to underscore immune cell differences between patients with different NSTMB. Results: In total, we discovered 2215 differentially expressed genes between patients with different NSTMB, among which 842 genes were upregulated and 1373 downregulated in patients with high NSTMB. The differentially expressed genes were enriched in pathways such as heme binding and structural molecule activity. We built a logistic model that may be used to predict patients' NSTMB. We found that tumors with high NSTMB had a significantly higher percentage of resting natural killer (NK) cells than those with low NSTMB (P = 0.028). The percentages of regulatory T (Treg) and CD8+ T cells were also higher in those with high NSTMB, although it was not statistically significant (P = 0.064 for Treg cells and P = 0.12 for CD8+ T cells). Conclusions: NSTMB may cause changes in gene expression and immune cell infiltration in EC patients, and affect the overall survival of EC patients. Key points: Significant findings of the studyThis study found differentially expressed genes and differences in infiltration of immune cells between esophageal cancer (EC) with different NSTMB. What this study addsThis study highlights differences between EC patients with different NSTMB. [ABSTRACT FROM AUTHOR]

Climate warming and anthropogenic nitrogen (N) loads are two major global change components interactively affecting carbon cycling. However, the effects of N forms and amounts on temperature sensitivity (Q10) of soil organic matter (SOM) mineralization remain incomplete. With this goal, soil was sampled after 23 years of mineral and (or) organic N fertilization, and then incubated for one year at 10, 20, and 30°C. For the first time, we compared four approaches (Equal time, Equal C, 1‐C pool, and 2‐C pool model) to evaluate the Q10 of SOM mineralization. All approaches showed that the Q10 decreased by more than one third with N fertilization compared to unfertilized control at low temperatures. The '1‐C pool model' was not adequate for Q10 estimation with various C availability. The Q10 estimated by '2‐C pool model' was strongly depended on incubation duration. The 'Equal C' approach was more powerful for separating SOM pools and it revealed the decreased Q10 of the recalcitrant pool at high N rates. The impact of N fertilization on Q10 was more evident at high N than at low N. Notably, the Q10 decreased more by mineral N compared to organic fertilizers (~60% vs. ~40% decreased in Q10) at 10–20oC. The added benefit of N fertilization in protecting SOM under climate warming was demonstrated by decreased Q10. Such one‐third reduction of temperature sensitivity by N fertilization is large enough to be considered in predictions of global SOM stocks under warming and anthropogenic N loads. [ABSTRACT FROM AUTHOR]

In this paper, we propose a modified estimators based on percentiles (MPCE) to improve the estimators performance based on percentiles for the generalized Logistic distribution. Simulation results indicate that MPCE outperforms other existing methods in terms of MSE. Finally, the proposed method is applied to a real data set. [ABSTRACT FROM AUTHOR]

Classification experiments using the spherical carbonyl iron (SCI) with particle size ranged from 1 to 7 µm were conducted by an air classifier. The electromagnetic properties of the SCI with different particle size were investigated in the frequency range of 2–18 GHz. The effects of particle size on the microwave absorption properties of the SCI were discussed on the results of scanning electronic microscopy, vibrating sample magnetometer, and frequency dependence of complex permittivity and permeability. The results show that the larger particle size leads to higher permittivity and lower permeability. The dielectric loss is attributed to the Debye dipolar polarization, while the magnetic loss arises from natural resonance and blocking resonance between superparamagnetism and ferromagnetism. The SCI with average particle size of 1.49 µm exhibits the optimal microwave absorption performance. A minimum reflection loss (RL) of − 50.8 dB is achieved at 15.6 GHz with a thickness of 1.27 mm, along with the corresponding bandwidth of RL less than − 10 dB (90% absorption) covering 7.04 GHz. Notably, the SCI with smaller particle size (about 1–3 µm) show superior microwave absorption properties at higher frequency range and thinner thickness than the corresponding larger ones (about 5 µm), which is mainly attributed to the improved impedance matching. [ABSTRACT FROM AUTHOR]

In this paper, we propose estimating equations estimators (EEE) based on the order statistics for the generalized Logistic distribution. Some asymptotic results are provided. Two simulation studies are undertaken to assess the performance of the proposed method and to compare them with other methods suggested in this paper. The simulation results indicate that EEE performs better than some other methods in terms of MSE. Finally, the proposed method is applied to two real data sets. [ABSTRACT FROM AUTHOR]

Generalized Pareto distribution (GPD) has been widely used to model exceedances over thresholds. In this article we propose a new method called weighted nonlinear least squares (WNLS) to estimate the parameters of the GPD. The WNLS estimators always exist and are simple to compute. Some asymptotic results of the proposed method are provided. The simulation results indicate that the proposed method performs well compared to existing methods in terms of mean squared error and bias. Its advantages are further illustrated through the analysis of two real data sets. [ABSTRACT FROM AUTHOR]

In order to avoid wrong conclusions in any further analysis, it is of importance to conduct a formal comparison for characteristic quantities of the distributions. These characteristic quantities we are familiar with include mean, quantity and reliability function, and so on. In this paper, we consider two tests aiming at the comparisons for function of parameters in Pareto distribution based on record values. They are generalized p-value-based test and parametric bootstrap-based test, respectively. The resulting procedures are easy to compute and are applicable to small samples. A simulation study is conducted to investigate and compare the performance of the proposed tests. A phenomenon we note is that generalized p-value-based test almost uniformly outperforms the parametric bootstrap-based test. [ABSTRACT FROM AUTHOR]

Generalized Pareto distribution (GPD) is widely used to model exceedances over thresholds. In this paper, we propose a new method, called weighted non linear least squares (WNLS), to estimate the parameters of the three-parameter GPD. Some asymptotic results of the proposed method are provided. An extensive simulation is carried out to evaluate the finite sample behaviour of the proposed method and to compare the behaviour with other methods suggested in the literature. The simulation results show that WNLS outperforms other methods in general situations. Finally, the WNLS is applied to analysis the real-life data. [ABSTRACT FROM AUTHOR]

The generalized Pareto distribution (GPD) has been widely used to model exceedances over a threshold. This article generalizes the method of generalized probability weighted moments, and applies this method to estimate the parameters of GPD. The estimator is computationally easy. Some asymptotic results of this method are provided. Two simulations are carried out to investigate the behavior of this method and to compare them with other methods suggested in the literature. The simulation results show that the performance of the proposed method is better than some other methods. Finally, this method is applied to analyze a real-life data. [ABSTRACT FROM AUTHOR]

High pressure processing (HPP) is an emerging non-thermal technology that is growing exponentially in use worldwide for the pasteurization of commercial foodstuffs. At combinations of elevated pressures and temperatures, HPP inactivates bacterial spores, but HPP has not yet been implemented commercially for food sterilization. Studies of the mechanisms of bacterial spore inactivation by HPP using primarily spores of Bacillus species have shown that spore germination precedes inactivation, with the release of dipicolinic acid from the spore core as the rate-determining step. Investigations probing spore resistance to and germination by HPP using Bacillus subtilis, a number of selected B. subtilis mutants, Bacillus amyloliquefaciens, and Clostridium difficile spores have compiled a wealth of detailed mechanistic information, while also accumulating abundant germination kinetics data that has not previously been analyzed by predictive models. Presently, we devise a 'quasi-chemical' model for bacterial spore germination dynamics by HPP. This quasi-chemical germination model (QCGM) hypothesizes a three-step mechanism and derives a set of ordinary differential equations to model the observed germination dynamics. The results with this model are viewed in the context of historical studies of spore activation, germination, and inactivation, with an eye toward potentially integrating differential equation models for germination and inactivation into a single, comprehensive model for spore dynamics by HPP. With the increasing use of high hydrostatic pressure to investigate mechanisms of bacterial spore resistance and physiology, the QCGM results help promote the efficient control of bacterial spores, whether for the inactivation of Clostridium botulinum spores in low-acid foods or aerosolized Bacillus anthracis spores on textiles used in protective clothing, tents, or shelters. [ABSTRACT FROM AUTHOR]

No-reference quality assessment aims at designing objective assessment criteria consistent to subjective perceived quality without any knowledge about reference image. This paper proposes a no-reference quality assessment algorithm specific to JPEG images. Blocking artifact in JPEG images is caused by the block based quantization of frequency coefficients, which is equivalent to applying low pass filtering in each block. In view of this idea, the algorithm in this paper was used to realize the quality assessment of JPEG images by quantizing the difference of power spectrum distribution between inner-block and inter-block. The assessment method proposed in this paper owns low algorithm complexity, clear physical meanings, free from learning and training and other advantages. Compared with most presented algorithms, the assessment results of proposed algorithm demonstrate a higher correlation to the subjective perceived quality. [ABSTRACT FROM AUTHOR]

Field measurements of net ecosystem CO exchange (NEE) with high temporal resolution are essential to construct a meaningful ecosystem C balance. The objectives of this study were to monitor NEE in high temporal resolution in cropland and grassland between middle August and middle November (2006) at Kleinhohenheim, Germany and to evaluate NEE in autumn. A fully automated temperature controlled closed chamber system with an infrared CO analyzer was used to measure NEE. The measured NEE varied between the two ecosystems depending on changes in above-ground vegetation and environmental factors. The diurnal NEE pattern of daytime CO uptake and night time CO release was evident in the grassland, but not in the cropland as the crops were harvested at the beginning of the measurement period. The grassland generally showed higher night time NEE, but lower daytime NEE than the cropland. Night time NEE showed exponential dependence on air and soil temperature, resulting in Q of 1.8 and 1.9 (for air temperature), 2.3 and 2.4 (for soil temperature) in the grassland and cropland, respectively. The average daily NEE was 2.77 and 1.86 g CO-C m day in the cropland and grassland, respectively. Both ecosystems were sources of CO, during 3 months in autumn, but the grassland emitted less CO by 87.9 g CO-C m than the cropland. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) and its labile fractions are strong determinants of chemical, physical, and biological properties, and soil quality. Thus, a 15-year experiment was established to assess how diverse soil fertility management treatments for winter wheat ( Triticum aestivum L.) and summer maize ( Zea mays L.) cropping system affect SOC and total N (TN) concentrations in the North China Plain. The field experiment included three treatments: (1) unfertilized control (CK); (2) inorganic fertilizers (INF); and (3) farmyard manure (FYM). Concentrations of SOC, TN, and different labile SOC fractions were evaluated to 1-m depth. In comparison with INF and CK, FYM significantly increased SOC and TN concentrations in the 0-30 cm depth, and also those of dissolved organic C (DOC), microbial biomass C (MBC), hot-water extractable C (HWC), permanganate oxidizable C (KMnO-C), and particulate organic C (POC) in the 0-20 cm depth. Despite the higher crop yields over CK, application of INF neither increased the SOC nor the labile C fractions, suggesting that by itself INF is not a significant factor affecting SOC sequestration. Yet, POC (18.0-45.8% of SOC) and HWC (2.0-2.8%) were the most sensitive fractions affected by applications of FYM. Significantly positive correlations were observed between SOC and labile organic C fractions in the 0-20 cm depth. The data support the conclusion that, wherever feasible and practical, application of FYM is important to soil C sequestration and improving soil quality under a wheat/maize system in the North China Plain. [ABSTRACT FROM AUTHOR]

We propose a scanning imaging measurement method using two linear array charge coupled devices (CCD) to evaluate the transmission performance of the linear laser beam of 90° × 2°. The two linear array CCDs are placed at two positions in the far field separated by a definite angle. The beam divergence angles in the view direction are measured by linear fitting because the beam width conforms to the linear relationship in the far field. This method has the ability for real-time testing and is appropriate for the complicated beam shapes with a wide measurement range. [ABSTRACT FROM AUTHOR]

Internal patch prior (e.g. self-similarity) has achieved a great success in image denoising. However, it is a challenging task to utilize clean external natural patches for denoising. Natural image patch comes from very complex distributions which are hard to learn without supervision. In this paper, we use an autoencoder to discover and utilize these underlying distributions to learn a compact representation that is more robust to realistic noises. By exploiting learned external prior and internal self-similarity jointly, we develop an efficient patch sparse coding scheme for real-world image denoising. Numerical experiments demonstrate that the proposed method outperforms many state-of-the-art denoising methods, especially on removing realistic noise. [ABSTRACT FROM AUTHOR]