Comprehensive Analysis Of Changes Research Articles

Comprehensive analysis of changes in expression of lncRNA, microRNA and mRNA in liver tissues of chickens with high or low abdominal fat deposition.

1. The liver of chickens is a dominant lipid biosynthetic tissue and plays a vital role in fat deposition, particularly in the abdomen. To determine the molecular mechanisms involved in its lipid metabolism, the livers of chickens with high (H) or low (L) abdominal fat content were sampled and sequencing on long non-coding RNA (lncRNA), messenger RNA (mRNA) and small RNA (microRNA) was performed.2. In total, 351 expressed protein-coding genes for long non-coding RNA (DEL; 201 upregulated and 150 downregulated), 400 differentially expressed genes (DEG; 223 upregulated and 177 downregulated) and 10 differentially expressed miRNA (DEM; four upregulated and six downregulated) were identified between the two groups. Multiple potential signalling pathways related to lipogenesis and lipid metabolism were identified via pathway enrichment analysis. In addition, 173 lncRNA - miRNA - mRNA interaction regulatory networks were identified, including 30 lncRNA, 27 mRNA and seven miRNA.3. These networks may help regulate lipid metabolism and fat deposition. Five promising candidate genes and two lncRNA may play important roles in the regulation of adipogenesis and lipid metabolism in chickens.

The integration of metabolic and proteomic data uncovers an augmentation of the sphingolipid biosynthesis pathway during T-cell differentiation

Recent studies have highlighted the significance of cellular metabolism in the initiation of clonal expansion and effector differentiation of T cells. Upon exposure to antigens, naïve CD4+ T cells undergo metabolic reprogramming to meet their metabolic requirements. However, only few studies have simultaneously evaluated the changes in protein and metabolite levels during T cell differentiation. Our research seeks to fill the gap by conducting a comprehensive analysis of changes in levels of metabolites, including sugars, amino acids, intermediates of the TCA cycle, fatty acids, and lipids. By integrating metabolomics and proteomics data, we discovered that the quantity and composition of cellular lipids underwent significant changes in different effector Th cell subsets. Especially, we found that the sphingolipid biosynthesis pathway was commonly activated in Th1, Th2, Th17, and iTreg cells and that inhibition of this pathway led to the suppression of Th17 and iTreg cells differentiation. Additionally, we discovered that Th17 and iTreg cells enhance glycosphingolipid metabolism, and inhibition of this pathway also results in the suppression of Th17 and iTreg cell generation. These findings demonstrate that the utility of our combined metabolomics and proteomics analysis in furthering the understanding of metabolic transition during Th cell differentiation.

High Level of CD8+PD-1+ Cells in Patients with Chronic Myeloid Leukemia Who Experienced Loss of MMR after Imatinib Discontinuation.

Treatment-free remission (TFR) is achieved in approximately half of chronic myeloid leukemia (CML) patients treated with tyrosine kinase inhibitors. The mechanisms responsible for TFR maintenance remain elusive. This study aimed to identify immune markers responsible for the control of residual CML cells early in the TFR (at 3 months), which may be the key to achieving long-term TFR and relapse-free survival (RFS) after discontinuation of imatinib. Our study included 63 CML patients after imatinib discontinuation, in whom comprehensive analysis of changes in the immune system was performed by flow cytometry, and changes in the BCR::ABL1 transcript levels were assessed by RQ-PCR and ddPCR. We demonstrated a significant increase in the percentage of CD8+PD-1+ cells in patients losing TFR. The level of CD8+PD-1+ cells is inversely related to the duration of treatment and incidence of deep molecular response (DMR) before discontinuation. Analysis of the ROC curve showed that the percentage of CD8+PD-1+ cells may be a significant factor in early molecular recurrence. Interestingly, at 3 months of TFR, patients with the e13a2 transcript had a significantly higher proportion of the PD-1-expressing immune cells compared to patients with the e14a2. Our results suggest the important involvement of CD8+PD-1+ cells in the success of TFR and may help in identifying a group of patients who could successfully discontinue imatinib.

Study on the effect and regularity of plating parts cleaning wastewater by enhanced aerobic process with high-density bacterial flora

In this research, we established an enhanced aerobic biological method utilizing a high-density bacterial flora for the treatment of low-biochemical plating parts washing wastewater. The elucidation of pollutant removal mechanisms was achieved through a comprehensive analysis of changes in sludge characteristics and bacterial community structure. The results demonstrated that throughout the operational period, the organic load remained stable within the range of 0.01–0.02 kgCOD/kgMLSS·d, the BOD5/COD ratio increased from 0.004 mg/L to 0.33 mg/L, and the average removal rates for key pollutants, including COD, NH4+-N, and TN, reached 98.13%, 99.86%, and 98.09%. MLSS concentration remained at 7627 mg/L, indicating a high-density flora. Notably, Proteobacteria, Bacteroidota, and Acidobacteriota, which have the ability to degrade large organic molecules, had been found in the system. This study affirms the efficacy of the intensive aerobic biological method for treating low-biochemical plating washing wastewater while ensuring system stability.

Metabolic profiling of aortic stenosis and hypertrophic cardiomyopathy identifies mechanistic contrasts in substrate utilization.

Aortic stenosis (AS) and hypertrophic cardiomyopathy (HCM) are distinct disorders leading to left ventricular hypertrophy (LVH), but whether cardiac metabolism substantially differs between these in humans remains to be elucidated. We undertook an invasive (aortic root, coronary sinus) metabolic profiling in patients with severe AS and HCM in comparison with non-LVH controls to investigate cardiac fuel selection and metabolic remodeling. These patients were assessed under different physiological states (at rest, during stress induced by pacing). The identified changes in the metabolome were further validated by metabolomic and orthogonal transcriptomic analysis, in separately recruited patient cohorts. We identified a highly discriminant metabolomic signature in severe AS in all samples, regardless of sampling site, characterized by striking accumulation of long-chain acylcarnitines, intermediates of fatty acid transport across the inner mitochondrial membrane, and validated this in a separate cohort. Mechanistically, we identify a downregulation in the PPAR-α transcriptional network, including expression of genes regulating fatty acid oxidation (FAO). In silico modeling of β-oxidation demonstrated that flux could be inhibited by both the accumulation of fatty acids as a substrate for mitochondria and the accumulation of medium-chain carnitines which induce competitive inhibition of the acyl-CoA dehydrogenases. We present a comprehensive analysis of changes in the metabolic pathways (transcriptome to metabolome) in severe AS, and its comparison to HCM. Our results demonstrate a progressive impairment of β-oxidation from HCM to AS, particularly for FAO of long-chain fatty acids, and that the PPAR-α signaling network may be a specific metabolic therapeutic target in AS.

Revolutionizing core muscle analysis in female sexual dysfunction based on machine learning

The purpose of this study is to investigate the role of core muscles in female sexual dysfunction (FSD) and develop comprehensive rehabilitation programs to address this issue. We aim to answer the following research questions: what are the roles of core muscles in FSD, and how can machine and deep learning models accurately predict changes in core muscles during FSD? FSD is a common condition that affects women of all ages, characterized by symptoms such as decreased libido, difficulty achieving orgasm, and pain during intercourse. We conducted a comprehensive analysis of changes in core muscles during FSD using machine and deep learning. We evaluated the performance of multiple models, including multi-layer perceptron (MLP), long short-term memory (LSTM), convolutional neural network (CNN), recurrent neural network (RNN), ElasticNetCV, random forest regressor, SVR, and Bagging regressor. The models were evaluated based on mean squared error (MSE), mean absolute error (MAE), and R-squared (R2) score. Our results show that CNN and random forest regressor are the most accurate models for predicting changes in core muscles during FSD. CNN achieved the lowest MSE (0.002) and the highest R2 score (0.988), while random forest regressor also performed well with an MSE of 0.0021 and an R2 score of 0.9905. Our study demonstrates that machine and deep learning models can accurately predict changes in core muscles during FSD. The neglected core muscles play a significant role in FSD, highlighting the need for comprehensive rehabilitation programs that address these muscles. By developing these programs, we can improve the quality of life for women with FSD and help them achieve optimal sexual health.

Regional temperature extremes and vulnerability under net zero CO2 emissions

Signatories to the Paris Agreement have pledged to keep global warming to well below 2 °C above pre-industrial levels and preferably below 1.5 °C above pre-industrial levels. Beyond over-shooting Paris Agreement warming levels followed by net negative emissions, achieving a state of net zero carbon dioxide emissions is required to satisfy Paris Agreement warming goals. Research on climate changes under net zero CO2 emissions is very limited to date with no comprehensive analysis of changes in extremes. In this study, we use results from Earth System Models in the zero emissions commitment model intercomparison project to understand regional mean-state climate change patterns during a 100 year period following carbon dioxide emissions cessation. We also perform an initial study of the evolution of hot and cold monthly temperature extremes after net zero CO2 emissions, including an assessment of how the change in frequency of temperature extremes affects areas of different levels of socioeconomic development based on regional Human Development Index (HDI). The results show that most land regions experience a fast and continuous cooling response following emissions cessation, with large areas of significant model agreement. In contrast, the Southern Ocean continues warming over the century after emissions cessation. The frequency of land-based local monthly high temperature extremes generally stays constant or decreases during the century after emissions cessation, however, decreases in heat extreme frequencies are generally less for locations with lower modern HDI than areas with higher HDI which suggests that inequality of climate change will remain an issue even after net zero CO2 emissions. There is an evident emergence of local monthly cold extremes following emissions cessation with most significant impact over high HDI mid- and high-latitude land regions.

Depth Evaluation of Tiny Defects on or near Surface Based on Convolutional Neural Network

This paper proposes a method for the detection and depth assessment of tiny defects in or near surfaces by combining laser ultrasonics with convolutional neural networks (CNNs). The innovation in this study lies in several key aspects. Firstly, a comprehensive analysis of changes in ultrasonic signal characteristics caused by variations in defect depth is conducted in both the time and frequency domains, based on discrete frequency spectra and original A—scan signals. Continuous wavelet transform (CWT) is employed to obtain wavelet time–frequency maps, demonstrating the consistent characteristics of this image with crack depth variations. A crucial innovation in this research involves the targeted design and optimization of the model based on the characteristics of ultrasonic signals and dataset size. This includes aspects such as data preparation, CNN architecture construction, and hyperparameter selection. The model is tested using a random validation set, which effectively demonstrates the CNN model’s validity and high precision. The proposed method enables the recognition and depth assessment of tiny defects on or near surfaces.

Changes in various lignocellulose biomasses structure after microwave-assisted hydrotropic pretreatment

Effective pretreatment of lignocellulosic biomass combined with delignification is a condition for effective enzymatic hydrolysis of cellulose, which is of key significance for the efficiency of the process of production of cellulosic ethanol. Becoming aware of the full range of changes in the structure of lignocellulose as a result of biomass pretreatment is important in view of the necessity to optimise the process of technological production of bioethanol. Our research was aimed at a comprehensive analysis of changes in structure of pine chip (softwood), beech chip (hardwood) and wheat straw (non-wood) biomasses resulting from a newly developed pretreatment method combining the use of hydrotrope in the form of sodium cumene sulfonate and microwave radiation. The performed analyses of the biomass composition indicate a high effectiveness of the proposed pretreatment method in the area of biomass delignification and hemicellulose removal. An effective removal of amorphous substances, i.e. lignin and hemicellulose, led to an increase in the crystallinity of pine chip biomass to 55%, and beech chips and wheat straw biomasses to 61%.

Temporal and spatial transcriptional regulation of phytohormone metabolism during seed development in barley (Hordeum vulgare L.).

Plant hormones play important roles in seed development; however, transcriptional regulation of their metabolism and levels of the respective bioactive forms during barley seed development is poorly understood. To this end, this study performed a comprehensive analysis of changes in the expression patterns phytohormone metabolism genes and levels of the respective bioactive forms in the embryo and endosperm tissues. Our study showed the presence of elevated levels of abscisic acid (ABA), bioactive forms of gibberellins (GAs), jasmonate (JA) and cytokinins (CKs), auxin and salicylic acid (SA) in the endosperm and embryo tissues at early stage of seed filling (SF). The levels of all hormones in both tissues, except that of ABA, decreased to low levels during SF. In contrast, embryonic ABA level increased during SF and peaked at physiological maturity (PM) while the endospermic ABA was maintained at a similar level observed during SF. Although its level decreased high amount of ABA was still present in the embryo during post-PM. We detected low levels of ABA in the endosperm and all the other hormones in both tissues during post-PM phase except the relatively higher levels of jasmonoyl-isoleucine and SA detected at late stage of post-PM. Our data also showed that spatiotemporal changes in the levels of plant hormones during barley seed development are mediated by the expression of specific genes involved in their respective metabolic pathways. These results indicate that seed development in barley is mediated by spatiotemporal modulation in the metabolism and levels of plant hormones.

Identifying of chemical composition changes during the carburizing process of carbon steel under tension

Carburizing is a commonly employed technique used to improve carbon steel’s surface characteristics, specifically its hardness and ability to resist wear. The introduction of tension during the carburizing process adds complexities that affect the distribution of elements in the material. The research methodology includes subjecting carbon steel samples to carburizing temperatures and applying tensile stress. This approach allows for analyzing the effects of carburization and stress on the carbon steel samples. The focus of the investigation was to analyze the use of the pack carburizing technique at lower temperatures, specifically 700 °C and 750 °C, while also applying proportional-voltage tensile stresses. The study focuses on conducting a comprehensive analysis of changes in the chemical composition throughout the cross-section of the material. Advanced analytical techniques perform mapping and elemental spectrum analysis, such as scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). These techniques enable a thorough investigation of the distribution and composition of elements such as carbon, iron, silicon, magnesium, and phosphorus. According to the research findings, carbon elements were added within the temperature range of 700 °C to 750 °C during the carburization process. The carbon content in the material increased from 0.15 % in its unprocessed state to 0.73 % at a temperature of 700 °C, followed by a further increase to 1.26 % at a temperature of 750 °C. According to the study, it was found that applying tensile loads and reducing carburizing temperatures can enhance the carburizing process and result in higher carbon steel content. This can bring about cost savings and improve overall industrial efficiency

Quantitative proteomics profiling of plasma from children with asthma.

A lack of validated blood diagnostic markers presents an obstacle to asthma control. The present study sought to profile the plasma proteins of children with asthma and to determine potential biomarkers. Plasma samples from children in acute exacerbation (n=4), in clinical remission (n=4), and from healthy children (n=4, control) were analyzed using a tandem mass tag (TMT)-labeling quantitative proteomics and the candidate biomarkers were validated using liquid chromatography-parallel reaction monitoring (PRM)/mass spectrometry (MS) with enzyme-linked immunosorbent assay (ELISA). We identified 347 proteins with differential expression between groups: 125 (50 upregulated, 75 downregulated) between acute exacerbation and control, 142 (72 upregulated, 70 downregulated) between clinical remission and control, and 55 (22 upregulated, 33 downregulated) between acute and remission groups (all between-group fold changes>1.2; P<0.05 by Student's t-test). Gene ontology analysis implicated differentially expressed proteins among children with asthma in immune response, the extracellular region, and protein binding. Further, KEGG pathway analysis of differentially expressed proteins identified complement and coagulation cascades and Staphylococcus aureus infection pathways as having the highest protein aggregation. Our analyses of protein interactions identified important node proteins, particularly KRT10. Among 11 differentially expressed proteins, seven proteins (IgHD, IgHG4, AACT, IgHA1, SAA, HBB, and HBA1) were verified through PRM/MS. Protein levels of AACT, IgA, SAA, and HBB were verified through ELISA and may be useful as biomarkers to identify individuals with asthma. In conclusion, our study presents a novel comprehensive analysis of changes in plasma proteins in children with asthma and identifies a panel for accessory diagnosis of pediatric asthma.

Effects of perinatal stress on the metabolites and lipids in plasma of dairy goats

Dairy goats experience metabolic stress during the peripartal period, and their ability to navigate this stage of lactation is related to the occurrence and development of metabolic diseases. Unlike dairy cows, there is a lack of comprehensive analysis of changes in the plasma profiles of peripartal dairy goats, particularly using high-throughput techniques. A subset of 9 clinically-healthy dairy goats were used from a cohort of 96 primiparous Guanzhong dairy goats (BCS, 2.75 ± 0.15). Blood samples were collected at seven time points around parturition (d 21, 14, 7 before parturition, the day of kidding, and d 7, 14, 21 postpartum), were analyzed using untargeted metabolomics and targeted lipidomics. The orthogonal partial least squares discriminant analysis model revealed a total of 31 differential metabolites including p-cresol sulfate, pyruvic acid, cholic acid, and oxoglutaric acid. The pathway enrichment analysis identified phenylalanine metabolism, aminoacyl-tRNA biosynthesis, and citrate cycle as the top three significantly-altered pathways. The Limma package identified a total of 123 differentially expressed lipids. Phosphatidylserine (PS), free fatty acids (FFA), and acylcarnitines (ACs) were significantly increased on the day of kidding, while diacylglycerols (DAG) and triacylglycerols (TAG) decreased. Ceramides (Cer) and lyso-phosphatidylinositols (LPI) were significantly increased during postpartum period, while PS, FFA, and ACs decreased postpartum and gradually returned to antepartum levels. Individual species of FFA and phosphatidylcholines (PC) were segregated based on the differences in the saturation and length of the carbon chain. Overall, this work generated the largest repository of the plasma lipidome and metabolome in dairy goats across the peripartal period, which contributed to our understanding of the multifaceted adaptations of transition dairy goats.

Clinical analysis of eye movement-based data in the medical diagnosis of amblyopia

Amblyopia is an abnormal visual processing-induced developmental disorder of the central nervous system that affects static and dynamic vision, as well as binocular visual function. Currently, changes in static vision in one eye are the gold standard for amblyopia diagnosis. However, there have been few comprehensive analyses of changes in dynamic vision, especially eye movement, among children with amblyopia. Here, we proposed an optimization scheme involving a video eye tracker combined with an "artificial eye" for comprehensive examination of eye movement in children with amblyopia; we sought to improve the diagnostic criteria for amblyopia and provide theoretical support for practical treatment. The resulting eye movement data were used to construct a deep learning approach for diagnostic and predictive applications. Through efforts to manage the uncooperativeness of children with strabismus who could not complete the eye movement assessment, this study quantitatively and objectively assessed the clinical implications of eye movement characteristics in children with amblyopia. Our results indicated that an amblyopic eye is always in a state of adjustment, and thus is not "lazy." Additionally, we found that the eye movement parameters of amblyopic eyes and eyes with normal vision are significantly different. Finally, we identified eye movement parameters that can be used to supplement and optimize the diagnostic criteria for amblyopia, providing a diagnostic basis for evaluation of binocular visual function.

Modeling changes in ice dynamics and subsurface thermal structure in Lake Michigan-Huron between 1979 and 2021

The world’s largest lakes, including the Laurentian Great Lakes, have experienced significant surface warming and loss of ice cover over the last several decades. Although changing surface conditions have received substantial research interest, changes below the surface remain largely unexplored, despite their importance for turbulent mixing, nutrient cycling, and primary production. In this study, we investigate changes in subsurface thermal structure and timing in Lake Michigan-Huron related to ongoing climate warming. This work utilizes atmospheric reanalysis data to drive the Great Lakes Finite Volume Community Ocean Model (GL-FVCOM), providing three-dimensional hydrodynamic and ice simulations between 1979 and 2021. Results are used to analyze trends in ice and temperature dynamics, revealing significant changes in annually averaged ice cover (− 2.1– − 5.2%/decade), ice thickness (− 0.68 – − 2.0 cm/decade), surface temperature (+ 0.47– + 0.51 ^circ{rm C}/decade), and bottom temperature (+ 0.26– + 0.29 ^circ{rm C}/decade) over the last 40 years, especially in ecologically important bays (e.g., Green Bay, Saginaw Bay). Significant warming was observed at all depth layers (0–270 m), with warming trends in the epilimnion and hypolimnion that agreed well with recent analysis of observational data in Lake Michigan. Shifting stratification dynamics led to dramatic changes in modelled overturning behavior, and earlier spring turnover dates (− 2.2– − 7.5 days/decade) and later fall turnover dates (+ 2.5– + 6.3 days/decade) led to a net lengthening of the stratified period. This study presents one of the most comprehensive analyses of changes in Great Lakes subsurface temperatures to date, providing important context for future climate modelling and coastal management efforts in the region.

Sedimentary DNA and pigments show increasing abundance and toxicity of cyanoHABs during the Anthropocene

Abstract Cyanobacterial harmful algal blooms (cyanoHABs) are assumed to be increasing in abundance and toxicity, but comprehensive analysis of change through time is limited, in part, because some key taxa (e.g., Microcystis) leave ambiguous evidence of historical abundance and toxicity. Sedimentary DNA (sedDNA) can allow the reconstruction of the cyanobacteria community as well as the frequency of genes specific to cyanotoxin production, enabling us to determine which taxa are present and their potential for toxin‐production. Using a combination of droplet digital polymerase chain reaction (ddPCR) and high‐throughput sequencing (HTS), we quantified the abundance of cyanobacterial genes of known function and changes in cyanobacteria taxa from sedDNA over the last century in nine lakes along a gradient of lake size, depth and trophic state in Minnesota, U.S.A. Using ddPCR, we quantified genes associated with microcystin toxin‐producing potential (mcyE), total cyanobacteria (CYA, 16S rRNA) and the genus Microcystis (MICR, 16S rRNA). Using HTS on a subset of lakes, we investigated how the abundance of this toxin‐producing gene covaried with the cyanobacteria community composition. We also compared ddPCR and HTS data to fossil pigments, a well‐established palaeolimnological method used to track changes in primary producers over time. Our results showed a significant correlation between MICR and the quantity of mcyE gene and cyanobacterial taxa with known toxin‐production potential. The abundance of both genes likewise increased concomitantly through time. Community analyses of HTS data showed significant change in cyanobacterial communities commencing c. 1950 when major land‐use change in this region led to increased lake productivity, and c. 1990 when Dolichospermum and Microcystis genera increased in abundance, and the subtropical exotic cyanobacteria Raphidiopsis raciborskii and Sphaerospermopsis aphanizomenoides became abundant. Cyanobacteria pigment data reflected these changes only in deeper lakes, suggesting issues related to benthic production or biomarker preservation in shallower systems. This study provides evidence for historical development of increasingly toxic cyanoHABs across a diverse set of lakes and illustrates how sedDNA may help link changes in the cyanobacteria community to the expression of potentially toxic genes.

Increased angiotensin II coupled with decreased Adra1a expression enhances cardiac hypertrophy in pregnancy-associated hypertensive mice

Cardiac hypertrophy is a crucial risk factor for hypertensive disorders during pregnancy, but its progression during pregnancy remains unclear. We previously showed cardiac hypertrophy in a pregnancy-associated hypertensive (PAH) mouse model, in which an increase in angiotensin II (Ang II) levels was induced by human renin and human angiotensinogen, depending on pregnancy conditions. Here, to elucidate the factors involved in the progression of cardiac hypertrophy, we performed a comprehensive analysis of changes in gene expression in the hearts of PAH mice and compared them with those in control mice. We found that alpha-1A adrenergic receptor (Adra1a) mRNA levels in the heart were significantly reduced under PAH conditions, whereas the renin-angiotensin system was upregulated. Furthermore, we found that Adra1a-deficient PAH mice exhibited more severe cardiac hypertrophy than PAH mice. Our study suggests that Adra1a levels are regulated by renin-angiotensin system and that changes in Adra1a expression are involved in progressive cardiac hypertrophy in PAH mice.

Spatio‐temporal changes in the mean and extreme temperature indices for Serbia

AbstractThis study provides a comprehensive analysis of changes in mean and extreme temperature indices for Serbia using a high‐resolution daily gridded temperature data set during the period of 1951–2020. The annual and seasonal trends of the indices in the gridded fields were computed and tested for statistical significance using the nonparametric Mann–Kendall test and the Sen's slope estimator. The t‐test was applied to check the stability of means of temperature indices between two standard periods (1961–1990 and 1991–2020). A correlation analysis was used in order to investigate the connections of the large‐scale circulation patterns and the mean and extreme temperature indices. Results showed that a warming trend dominated for the last 70 years, with slightly more intense changes for the mean maximum temperatures (TXM) than for the mean minimum temperatures (TNM). An increase was recorded for indices based on the maximum temperature (TXM, hottest days, warm days, summer days) and minimum temperature (TNM, coldest nights, warm nights, tropical nights). The highest increase was observed for warm nights (7 days⋅decade−1) during the summer season. The negative change in cool days (−1.5 days⋅decade−1) and cool nights (−2 days⋅decade−1) was recorded in almost all seasons, being significant for the both annual and summer values. The correlation between the temperature indices and large‐scale circulation patterns revealed that the East Atlantic (EA) pattern had a highly positive correlation with warm temperature indices (hottest days, warm days, warm nights, summer days, and tropical nights) and a negative correlation with cold indices (coldest nights, cool days, cool nights, frost days, and ice days). The North Atlantic Oscillation, the most important teleconnection pattern during the winter months in Europe, had weaker influence on temperature indices in Serbia than the EA pattern, but stronger than the EA/Western Russia pattern.

Surface modification of coatings based on Ni-Cr-Al by pulsed plasma treatment

&lt;abstract&gt; &lt;p&gt;To protect materials from abrasion-corrosion, various thermal spraying methods can be used to apply coatings, such as gas-flame powder spraying, plasma spraying, high velocity oxygen-fuel spraying and detonation cannon. Thermal spraying is one of the most effective methods of protecting the material from wear and corrosion, thereby increasing the service life of the material used. We present the surface modification of coatings based on Ni-Cr-Al by a pulsed plasma treatment using a plasma generator. The coatings were obtained by detonation spraying followed by pulsed plasma treatment. The changes to the structural properties of the coatings under the influence of plasma flow were studied using scanning electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction. The mechanical and tribological properties were analyzed by surface roughness characterization, microhardness testing and tribological tests for a comprehensive analysis of changes in the characteristics of the Ni-Cr-Al coatings following pulsed plasma treatment. It was found that modification of the coating by pulsed plasma treatment causes an increase in the microhardness of the surface layer, as well as a reduction in the surface roughness and friction coefficient. According to the results of X-ray phase analysis, these improvements in the mechanical and tribomechanical properties of the obtained surfaces is associated with an increase in the content of CrNi&lt;sub&gt;3&lt;/sub&gt;, NiAl and NiCr phases in the coatings.&lt;/p&gt; &lt;/abstract&gt;

Urbanization of grasslands in the Denver area affects streamflow responses to rainfall events

A thorough understanding of how urbanization affects stream hydrology is crucial for effective and sustainable water management, particularly in rapidly urbanizing regions. This study presents a comprehensive analysis of changes in streamflow response to rainfall events across a rural to urban gradient in the semi-arid area of Denver, Colorado. We used 8 years of April to October instantaneous streamflow data in 21 watersheds ranging in size from 0.8 to 90 km2 and with impervious areas ranging from 1% to 47%. With these data, we applied a semi-automated method to identify a total of 2877 streamflow responses, which were analysed for event-based metrics of peak flow, runoff depth, runoff to rainfall ratio, time to peak, duration and number of streamflow responses to rainfall events. We also determined whether streamflow responses could be predicted by a precipitation threshold. Watersheds with >10% impervious cover had a precipitation threshold of 1–2 mm/hr needed to produce a streamflow response, compared to thresholds of 4–36 mm/hr for watersheds with less than 10% impervious surface cover. This lower precipitation threshold in more impervious watersheds led to more frequent streamflow responses. On average, streamflow responses had shorter duration and higher peak flows in watersheds with more impervious surface cover. In contrast to other regions, runoff depth, runoff to rainfall ratio and time to peak either gave mixed results or did not vary significantly with imperviousness. These alterations in streamflow response to rainfall events indicate the specific ways that urban development changes how streams respond to rain events in a semi-arid setting. This work points to the need for local adaptation of stormwater management to mitigate the effects of streamflow changes with urbanization.