Influenced by the hydrogeological structure and other factors, the change in groundwater depth shows seasonal fluctuation characteristics. Human activities have disrupted the long-term stable pattern of groundwater change, which makes the short-term prediction of groundwater depth important. To cope with the emergence of short-term groundwater prediction scenarios, for the first time, a discrete grey seasonal model with fractional order accumulation is proposed in this paper (FDGSM(1,1)). First, the DGM(1,1) model, which has a relative advantage over fluctuating data, was chosen as the basis for the transformation of the proposed model. Then, the fractional order accumulation operator is used to reduce the seasonal fluctuations in the data series. Finally, grey seasonal variables are introduced to construct the time response function. The proposed model has the basic properties of the traditional grey forecasting model, which is proven to be stable and seasonal. Additionally, the prediction performance of the proposed model is verified in a real scenario of Handan groundwater. This paper expands the seasonal prediction field of the grey prediction model, enriches the research system of the grey system theory and fractional order, and has a positive influence on the short-term prediction of groundwater depth.
Self-centering structures have emerged as a promising seismic design solution, offering advantages in structural safety, rapid post-earthquake functionality recovery, and life-cycle economy. This paper introduces a self-centering beam–column joint that integrates superelastic shape memory alloys (SMAs) and prestressed steel tendons as restoring components. A numerical model was developed in OpenSees and validated against experimental results, with discrepancies in residual deformation within 10%. The validated model was used for parametric studies on strand area, prestress, and SMA configuration. The results show that the proposed joint sustains a maximum drift of 6% while maintaining nearly zero residual drift (less than 0.2%), and its hysteresis curve exhibits a stable flag-shaped pattern. The equivalent viscous damping ratio exceeds 0.1, confirming excellent deformation and energy dissipation capacities. These findings highlight the joint’s potential for application in seismic-resilient steel frames.
Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological drought from June 2002 to June 2017 based on the Standardized Precipitation Index (SPI) and Standardized Terrestrial Water Storage Index (STI) by employing wavelet coherence rather than a traditional correlation coefficient. The possible influencing factors on drought propagation in 28 regions across the world are examined. The results show that the number of drought months detected by the STI is higher than that detected by the SPI worldwide, especially for slight and moderate drought. Generally, TWS-derived hydrological drought is triggered by and occurs later than precipitation-based meteorological drought. The propagation characteristics between meteorological and hydrological droughts vary by region across the globe. Apparent intra-annual and interannual scales are detected by wavelet analysis in most regions, but not in the polar climate region. Drought propagation differs in phase lags in different regions. The phase lag between hydrological and meteorological drought ranges from 0.5 to 4 months on the intra-annual scale and from 1 to 16 months on the interannual scale. Drought propagation is influenced by multiple factors, among which the El Niño–Southern Oscillation, North Atlantic Oscillation, and potential evapotranspiration are the most influential when considering one, two, or three factors, respectively. The findings of this study improve scientific understanding of drought propagation mechanisms over a global scale and provide support for water management in different subregions.
Background. Cribriform morular thyroid carcinoma has been recently renamed in the 2022 WHO classification as a thyroid tumor of uncertain histogenesis. The epidemiologic, pathological, and pathophysiological characteristics distinguish it from papillary thyroid carcinoma (PTC). Preoperative genetic testing plays a role in facilitating the differential diagnosis. Methods. This report presents a confirmed case of cribriform morular thyroid carcinoma. Initially, fine-needle aspiration cytology suggested a diagnosis of PTC. However, a genetic analysis did not reveal the typical mutations associated with follicular-cell-derived neoplasms. Results. A 31-year-old woman was found to have a thyroid nodule at the left lobe measuring 11.8 × 10.2 × 12.4 mm. Ultrasonography indicated a hypoechoic, solid nodule with regular margins. Cytology revealed a papillary structure of tall cells, leading to a PTC diagnosis. Nevertheless, the genetic analysis failed to detect mutations such as BRAF V600E, NRAS Q61R, NRAS Q61K, HRAS Q61R, or HRAS Q61K mutation or the fusion of CCDC6-RET, NCOA4-RET, PAX8-PPARG, ETV6-NTRK3, TPM3-NTRK1, IRF2BP2-NTRK1, or SQSTM1-NTRK1 in the aspirated follicular cells. The patient subsequently underwent total thyroidectomy with central lymph node dissection. Pathological examination revealed a cribriform pattern of spindle-shaped cells with morular areas. Immunohistochemical staining showed positive results for β-catenin and TTF-1, except in the morular regions, and negative results for PAX8, thyroglobulin, and BRAF (clone VE1). The diagnosis was confirmed to be cribriform morular thyroid carcinoma. Conclusion. Significant cytological similarity exists between PTC and cribriform morular thyroid carcinoma. Preoperative genetic analysis is important to differentiate these two diseases. Cribriform morular thyroid carcinoma can be differentiated from common follicular-cell-derived tumors by the absence of typical mutations; the presence of nuclear and cytoplasmic expressions of β-catenin; the presence of TTF-1, except in morular areas; and the absence of thyroglobulin.
Sutha Paramasivam, Sathishkumar Chidambaram, Palanisamy Karumalaiyan
et al.
<b>Background:</b> Green synthesized nanoparticles (NPs) have gained increasing popularity in recent times due to their broad spectrum of antimicrobial properties. This study aimed to develop a phytofabrication approach for producing cuprous (Cu<sub>2</sub>O) and cupric oxide (CuO) NPs using a simple, non-hazardous process and to examine their antimicrobial properties. <b>Methods:</b> The synthesis employed <i>Bidens pilosa</i> plant extract as a natural reducing and stabilizing agent, alongside copper chloride dihydrate as the precursor. The biosynthesized NPs were characterized through various techniques, including X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier-transform infrared (FT-IR) spectroscopy, ultraviolet–visible (UV-Vis) spectroscopy, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS). <b>Results:</b> XRD analysis confirmed that the synthesized CuO and Cu<sub>2</sub>O NPs exhibited a high degree of crystallinity, with crystal structures corresponding to monoclinic and face-centered cubic systems. SEM images revealed that the NPs displayed distinct spherical and sponge-like morphologies. EDS analysis further validated the purity of the synthesized CuO NPs. The antimicrobial activity of the CuO and Cu<sub>2</sub>O NPs was tested against various pathogenic bacterial strains, including <i>Staphylococcus aureus</i>, <i>Pseudomonas aeruginosa</i>, <i>Escherichia coli</i>, and <i>Bacillus cereus</i>, with the minimum inhibitory concentration (MIC) used to gauge their effectiveness. <b>Conclusions:</b> The results showed that the phytosynthesized NPs had promising antibacterial properties, particularly the Cu<sub>2</sub>O NPs, which, with a larger crystal size of 68.19 nm, demonstrated significant inhibitory effects across all tested bacterial species. These findings suggest the potential of CuO and Cu<sub>2</sub>O NPs as effective antimicrobial agents produced via green synthesis.
Paris Kantaras, Niki Mourouti, Theodora Mouratidou
et al.
In total, 3274 adults (65.2% females) from six European countries were included in this cross-sectional analysis using data from the baseline assessment of the Feel4Diabetes study. Anthropometric, sociodemographic, dietary and behavioral data were assessed, and the existence of metabolic syndrome (MetS) was recorded. Beverage consumption patterns (BCPs) were derived via principal component analysis. Three BCPs were derived explaining 39.5% of the total variation. BCP1 was labeled as “Alcoholic beverage pattern”, which loaded heavily on high consumption of beer/cider, wine and other spirits; BCP2 was labeled as “High in sugars beverage pattern” that was mainly characterized by high consumption of soft drinks with sugar, juice containing sugar and low consumption of water; and BCP3 was labeled as “Healthy beverage pattern” that was mainly characterized by high consumption of water, tea, fruit juice freshly squeezed or prepacked without sugar and low consumption of soft drinks without sugar. After adjusting for various confounders, BCP2 was positively associated with elevated triglycerides (<i>p</i> = 0.001), elevated blood pressure (<i>p</i> = 0.001) elevated fasting glucose (<i>p</i> = 0.008) and the existence of MetS (<i>p</i> = 0.006), while BCP1 was inversely associated with reduced HDL-C (<i>p</i> = 0.005) and BCP3 was inversely associated with elevated blood pressure (<i>p</i> = 0.047). The establishment of policy actions as well as public health nutritional education can contribute to the promotion of a healthy beverage consumption.
Diseases of the endocrine glands. Clinical endocrinology
Quantum communication, and indeed quantum information in general, has changed the way we think about quantum physics. In 1984 and 1991, the first protocol for quantum cryptography and the first application of quantum non-locality, respectively, attracted a diverse field of researchers in theoretical and experimental physics, mathematics and computer science. Since then we have seen a fundamental shift in how we understand information when it is encoded in quantum systems. We review the current state of research and future directions in this new field of science with special emphasis on quantum key distribution and quantum networks.
With the trend of innovation-driven development and the deepening application of digital technology, the role of digital transformation in the relationship between industrial policies and enterprise innovation is becoming increasingly significant, but it has rarely been analyzed in previous studies. In order to fill this research gap, this study takes listed wind power enterprises in China from 2007 to 2021 as a sample, and it combines a large number of relevant policy documents issued by the State Council, the Ministry of Industry and Information Technology, the National Energy Administration, and other government departments to investigate the impact of digital transformation on the relationship between industrial policies and enterprise technological innovation performance. This study found that both demand-side policy and supply-side policy have significantly promoted the technological innovation performance of enterprises. There is a synergistic effect between demand-side policy and supply-side policy, and demand-side policy strengthens the promotional effect of supply-side policy on technological innovation performance. Moreover, digital transformation can promote the technological innovation performance of enterprises. Further research has found that digital transformation can strengthen the synergistic effect between demand-side policy and supply-side policy and strengthen the positive impact of demand-side policy on technological innovation performance, but that it has weakened the incentive role of supply-side policy.
Masaki Fujisawa, Yoshihiro Haga, Masahiro Sota
et al.
The International Commission on Radiological Protection has lowered the annual equivalent eye-lens dose to 20 mSv. Although occupational exposure can be high in nuclear medicine (NM) departments, few studies have been conducted regarding eye-lens exposure among NM staff. This study aimed to estimate the annual lens doses of staff in an NM department and identify factors contributing to lens exposure. Four nurses and six radiographers performing positron emission tomography (PET) examinations and four radiographers performing radioisotope (RI) examinations (excluding PET) were recruited for this study. A lens dosimeter was attached near the left eye to measure the 3-mm-dose equivalent; a personal dosimeter was attached to the left side of the neck to measure the 1-cm- and 70-µm-dose equivalents. Measurements were acquired over six months, and the cumulative lens dose was doubled to derive the annual dose. Correlations between the lens and personal-dosimeter doses, between the lens dose and the numbers of procedures, and between the lens dose and the amounts of PET drugs (radiopharmaceuticals) injected were examined. Wilcoxon’s signed-rank test was used to compare lens and personal-dosimeter doses. The estimated annual doses were 0.93 ± 0.13 mSv for PET nurses, 0.71 ± 0.41 mSv for PET radiographers, and 1.10 ± 0.53 mSv for RI radiographers. For PET nurses, but not for PET or RI radiographers, there was a positive correlation between the numbers of procedures and lens doses and between amounts injected and lens doses. There was a significant difference between the lens and personal-dosimeter doses of PET nurses. The use of protective measures, such as shielding, should prevent NM staff from receiving lens doses > 20 mSv/year. However, depending on the height of the protective shield, PET nurses may be unable to assess the lens dose accurately using personal dosimeters.
Abstract Numerous studies have proven the critical role of macrophages in the renal fibrosis process. Notably, G Protein-coupled Estrogen Receptor 1 (GPER1), a novel estrogen receptor, has been shown to play a ubiquitous role in regulating macrophage activities and proinflammatory pathways. However, the precise role of GPER1 in macrophage-mediated renal fibrosis is unknown. In this study, we aimed to investigate the function of macrophage GPER1 in the UUO-induced renal fibrosis model. Compared to vehicle-treated ovariectomized (OVX) female and male unilateral ureteral obstruction (UUO) models, we observed that G-1 (GPER1 agonist)-treated OVX female and male UUO mice had fewer renal fibrotic lesions and less M1 and M2 macrophage infiltration in the kidney tissues. Conversely, Gper1 deletion in male UUO mice accelerated renal fibrosis and increased inflammation. In vitro studies also revealed that GPER1 activation reduced M0 macrophage polarization towards M1 or M2 phenotypes. The RNA-sequencing analysis and immunoblotting indicated that GPER1 activation was primarily involved in downregulating immune pathways activation and inactivating MAPK pathways. Tubular epithelial cells co-cultured with G-1-pretreated M1 macrophages exhibited fewer injuries and immune activation. In addition, fibroblasts co-cultured with G-1-pretreated M2 macrophages showed downregulated extracellular matrix expression. Overall, this is the first study to demonstrate the effect of GPER1 on macrophage-mediated renal fibrosis via inhibition of M1 and M2 macrophage activation. These findings indicate that GPER1 may be a promising therapeutic target for treating renal fibrosis.
Hyung Joon Park, Hyo Lim Kang, Dae Gyun Ahn
et al.
Direct-drive permanent magnet generators are becoming an attractive option for highly efficient small-scale wind turbines due to their high-power density and size reduction capabilities. In this study, the optimal shape design of a direct-drive permanent magnet generator for 1 kW-class wind turbines was conducted while considering power generation and weight. Half of the geometry of a single stage in the generator was considered for a electromagnetic analysis under given electrical parameters. In order to construct a response surface model, a sensitivity analysis was conducted on seven design parameters of the proposed generator. The desirability function was used to minimize the weight of the generator while meeting a requirement of the target specification. The results indicated that the optimized design parameters for the generator met the target specification while maintaining the generator’s weight at the same level as the initial design model. From the comparisons with other research, the optimized generator exhibited a higher power generation/weight ratio than the generator with a rated capacity under 3 kW.
Samantha Hayward, Kevon Parmesar, Gavin I. Welsh
et al.
A small subset of people with nephrotic syndrome (NS) have genetically driven disease. However, the disease mechanisms for the remaining majority are unknown. Epigenetic marks are reversible but stable regulators of gene expression with utility as biomarkers and therapeutic targets. We aimed to identify and assess all published human studies of epigenetic mechanisms in NS. PubMed (MEDLINE) and Embase were searched for original research articles examining any epigenetic mechanism in samples collected from people with steroid resistant NS, steroid sensitive NS, focal segmental glomerulosclerosis or minimal change disease. Study quality was assessed by using the Joanna Briggs Institute critical appraisal tools. Forty-nine studies met our inclusion criteria. The majority of these examined micro-RNAs (<i>n</i> = 35, 71%). Study quality was low, with only 23 deemed higher quality, and most of these included fewer than 100 patients and failed to validate findings in a second cohort. However, there were some promising concordant results between the studies; higher levels of serum miR-191 and miR-30c, and urinary miR-23b-3p and miR-30a-5p were observed in NS compared to controls. We have identified that the epigenome, particularly DNA methylation and histone modifications, has been understudied in NS. Large clinical studies, which utilise the latest high-throughput technologies and analytical pipelines, should focus on addressing this critical gap in the literature.
China’s power industry is a major energy consumer, with the carbon dioxide (CO2) generated by coal consumption making the power industry one of the key emission sectors. Therefore, it is crucial to explore energy conservation and emissions reduction strategies suitable for China’s current situation. Taking a typical cogeneration enterprise in North China as an example, this paper aims to establish a generalized regression prediction model for carbon emissions of coal-fired power plants, which will provide a reference for China to seek strategies for carbon peaking and carbon neutralization in the future. Firstly, in terms of the selection of influencing factors, this paper uses objective index screening methods, simulation means, and the eXtreme Gradient Boosting algorithm (XG-Boost) to analyze the feature importance of various influencing factors. It is concluded that the relevant influencing factors of the boiler feed water system have a strong correlation and characteristic importance with the carbon emissions results of coal-fired power plants. Therefore, this paper proposes to introduce these factors into the regression prediction model as auxiliary variables to more scientifically reflect the carbon emissions results of coal-fired power plants. Secondly, in the aspect of regression prediction model establishment, inspired by the sparrow’s foraging behavior and anti-predation behavior, this paper selects the sparrow search algorithm (SSA) with strong optimization ability and fast convergence speed to optimize the super parameters of the long short-term memory network algorithm (LSTM). It is proposed to use the SSA-LSTM algorithm to establish the carbon emissions regression prediction model of coal-fired power plants. The advantage of the SSA-LSTM algorithm is that it can effectively simplify the super parameter selection process of the LSTM algorithm, effectively solve the global optimization problem, prevent the model from falling into overfitting and local optimization, and make the carbon emissions regression prediction model of coal-fired power plants achieve a better fitting effect. By comparing the performance indicators of the model before and after the improvement, it is found that the regression prediction effect of the SSA-LSTM coal-fired power plant carbon emissions regression prediction model, which introduces boiler feed water influencing factors, has been effectively improved. Therefore, the model proposed in this paper can be used to conduct a comprehensive impact factor analysis and regression prediction analysis on the carbon emissions intensity of China’s coal-fired power plants, formulate targeted carbon emissions reduction countermeasures, and provide a theoretical basis for energy conservation and emissions reduction of China’s coal-fired power plants.
Polygonum is a generalized genus of the Polygonaceae family that includes various herbaceous plants. In order to provide aid in understanding the evolutionary and phylogenetic relationship in Polygonum at the chloroplast (cp) genome-scale level, we sequenced and annotated the complete chloroplast genomes of four Polygonum species using next-generation sequencing technology and CpGAVAS. Then, repeat sequences, IR contractions, and expansion and transformation sites of chloroplast genomes of four Polygonum species were studied, and a phylogenetic tree was built using the chloroplast genomes of Polygonum. The results indicated that the chloroplast genome construction of Polygonum also displayed characteristic four types of results, comparable to the published chloroplast genome of recorded angiosperms. The chloroplast genomes of the four Polygonum plants are highly consistent in genome size (159,015 bp–163,461 bp), number of genes (112 genes, including 78 protein-coding genes, 30 tRNA genes, and 4 rRNA genes), gene types, gene order, codon usage, and repeat sequence distribution, which identifies the high preservation among the Polygonum chloroplast genomes. The Polygonum phylogenetic tree was recreated by a full sequence of the chloroplast genome, which illustrates that the P. bistorta, P. orientale, and P. perfoliatum are divided into the same branch, and P. aviculare belongs to Fallopia. The precise system site of lots base parts requires further verification, but the study would provide a basis for developing the available genetic resources and evolutionary relationships of Polygonum.
Dinny Fitriani, Anisa Rarasati, Suhadi Wido Saputro
et al.
A set <em>W</em> is called a local resolving set of <em>G</em> if the distance of <em>u</em> and <em>v</em> to some elements of <em>W</em> are distinct for every two adjacent vertices <em>u</em> and <em>v</em> in <em>G</em>. The local metric dimension of <em>G</em> is the minimum cardinality of a local resolving set of <em>G</em>. A connected graph <em>G</em> is called a split graph if <em>V</em>(<em>G</em>) can be partitioned into two subsets <em>V</em><sub>1</sub> and <em>V</em><sub>2</sub> where an induced subgraph of G by <em>V</em><sub>1</sub> and <em>V</em><sub>2</sub> is a complete graph and an independent set, respectively. We also consider a graph, namely the unicyclic graph which is a connected graph containing exactly one cycle. In this paper, we provide a general sharp bounds of local metric dimension of split graph. We also determine an exact value of local metric dimension of any unicyclic graphs.
Abstract Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such protein language models by jointly learning protein properties from strongly-correlated protein tasks. Here we elaborately designed a multi-task learning (MTL) architecture, aiming to decipher implicit structural and evolutionary information from three sequence-level classification tasks for protein family, superfamily and fold. Considering the co-existing contextual relevance between human words and protein language, we employed BERT, pre-trained on a large natural language corpus, as our backbone to handle protein sequences. More importantly, the encoded knowledge obtained in the MTL stage can be well transferred to more fine-grained downstream tasks of TAPE. Experiments on structure- or evolution-related applications demonstrate that our approach outperforms many state-of-the-art Transformer-based protein models, especially in remote homology detection.
Computer applications to medicine. Medical informatics, Biology (General)