Explore the vast range of titles available.

Air pollution has become a critical issue in human’s life. Predicting the changing trends of air pollutants would be of great help for public health and natural environments. Current methods focus on the prediction accuracy and retain the forecasting time span within 12 hours. Shorter time span decreases the practicability of these perditions, even with higher accuracy. This study proposes an attention and autoencoder (A&A) hybrid learning approach to obtain a longer period of air pollution changing trends while holding the same high accuracy. Since pollutant concentration forecast highly relates to time changing, quite different from normal prediction problems like autotranslation, we integrate “time decay factor” into the traditional attention mechanism. The time decay factor can alleviate the impact of the value observed from a longer time before while increasing the impact of the value from a closer time point. We also utilize the hidden states in the decoder to build connection between history values and current ones. Thus, the proposed model can extract the changing trend of a longer history time span while coping with abrupt changes within a shorter time span. A set of experiments demonstrate that the A&A learning approach can obtain the changing trend of air pollutants, like PM2.5, during a longer time span of 12, 24, or even 48 hours. The approach is also tested under different pollutant concentrations and different periods and the results validate its robustness and generality.

Carbonate rock is a critical reservoir for China’s onshore oil and gas exploration. Carbonate reservoirs in different regions significantly differ in sedimentary and diagenesis processes and factors affecting their petrophysical and seismic rock physics properties. Therefore, it is critical to analyze the corresponding properties of carbonate rocks in different regions. Based on systematic petrological, rock microstructure, physical property, and seismic elastic characteristic measurements of deep carbonate reservoir samples in the Tarim Basin, the variation laws and influencing factors of the samples’ physical and seismic elastic properties are analyzed. Based on these measurements, the variation patterns and influencing factors of petrophysical and seismic rock properties of rock samples are analyzed. The results show that the carbonate pore structure controls the overall variations of petrophysical and seismic rock physical properties of carbonate samples, and it is challenging to build a simple statistical model of porosity—permeability, porosity—velocity, and density—velocity. P- and S-velocities correlate well, and the P-and S-velocity ratio is a good index for rock typing. For tight carbonate samples, apparent velocity dispersion at a seismic exploration frequency band (5–200 Hz) can be observed, and the pore structure controls the velocity dispersion and attenuation features. Carbonate samples with crack-dissolution pores show moderately stronger velocity dispersion than samples with dissolution and microcrack pores. The pore aspect ratio and the frame flexibility factor (γ) calculated from the seismic rock physics model correlate well with pore structure parameters, such as the characteristic ratio surface. The pore aspect ratio and frame flexibility factor can be used to quantitatively characterize the changes in the pore structure of tight carbonate samples, reflecting the pore structure effects on the elastic wave velocity. This study’s results can provide a basis for rock-typing carbonate reservoirs, lithology, and hydrocarbon detection of relevant reservoirs.

The formation dip angle is an important characteristic parameter that reflects underground structures, and it is widely used in seismic exploration and geological interpretation. However, the routine dip angle calculation method suffers from the problems of artifact interference and insufficient accuracy, which restricts the development of fine exploration technology. More accurately obtaining the formation dip angle has become a general concern. To solve these problems, this paper proposes a method for calculating the formation dip angle using deep learning. The dip angle calculation is considered a regression problem. By establishing a database of synthetic seismic data and dip data tags, data-driven fitting of nonlinear functional relationships between the seismic data and dip angles are achieved, and intelligent dip calculations are realized. The method is verified using the synthetic sedimentary model and actual data and is compared with the mainstream dip angle calculation method in the industry. The results show that this method more realistically reflects the undulating characteristics of a structure with both high accuracy and anti-interference ability.

The Ordovician carbonate rocks of the Yingshan formation in the Tarim Basin have a complex pore structure owing to diagenetic and secondary structures. Seismic elastic parameters (e.g., wave velocity) depend on porosity and pore structure. We estimated the average specific surface, average pore-throat radius, pore roundness, and average aspect ratio of carbonate rocks from the Tazhong area. High P-wave velocity samples have small average specific surface, small average pore-throat radius, and large average aspect ratio. Differences in the pore structure of dense carbonate samples lead to fluid-related velocity variability. However, the relation between velocity dispersion and average specific surface, or the average aspect ratio, is not linear. For large or small average specific surface, the pore structure of the rock samples becomes uniform, which weakens squirt flow and minimizes the residuals of ultrasonic data and predictions with the Gassmann equation. When rigid dissolved (casting mold) pores coexist with less rigid microcracks, there are significant P-wave velocity differences between measurements and predictions.

The effects of diabetes mellitus include long-term damages, dysfunctions, and failures of various organs. An important complication of diabetes is the disturbance in the male reproductive system. Glucose metabolism is an important event in spermatogenesis. Moreover, glucose metabolism is also important for maintaining basic cell activity, as well as specific functions, such as motility and fertilization ability in mature sperm. Diabetic disease and experimentally induced diabetes both demonstrated that either type 1 diabetes or type 2 diabetes could have detrimental effects on male fertility, especially on sperm quality, such as sperm motility, sperm DNA integrity, and ingredients of seminal plasma. Epigenetic modifications are essential during spermatogenesis. The epigenetic regulation represents chromatin modifications including DNA methylation, histone modifications, remodeling of nucleosomes and the higher-order chromatin reorganization and noncoding RNAs. If spermatogenesis is affected during the critical developmental window, embryonic gonadal development, and germline differentiation, environmentally-induced epigenetic modifications may become permanent in the germ line epigenome and have a potential impact on subsequent generations through epigenetic transgenerational inheritance. Diabetes may influence the epigenetic modification during sperm spermatogenesis and that these epigenetic dysregulation may be inherited through the male germ line and passed onto more than one generation, which in turn may increase the risk of diabetes in offspring.

Background： With the progress ofperinatal medicine and neonatal technology, more and more extremely low birth weight （ELBW） survived all over the world. This study was designed to investigate the short-term ontcomes of ELBW infants during their Neonatal Intensive Care Unit （NICU） stay in the mainland of China. Methods： All infants admitted to 26 NICUs with a birth weight （BW） 〈1000 g were included between January 1,2011 and December 31,2011. All the data were collected retrospectively from clinical records by a prospectively designed questionnaire. The data collected from each NICU transmitted to the main institution where the results were aggregated and analyzed. Categorical variables were performed with Pearson Chi-square test. Binary Logistic regression analysis was used to detect risk factors. Results： A total of 258 ELBW infants were admitted to 26 NICUs, of whom the mean gestational age （GA） was 28.1 ± 2.2 weeks, and the mean BW was 868 ± 97 g. The overall survival rate at discharge was 50.0%. Despite aggressive treatment 60 infants （23.3%） died and another 69 infants （26.7%） died after medical care withdrawal. Furthermore, the survival rate was significantly higher in coastal areas than inland areas （53.6% vs. 35.3%, P = 0.019）. BW 〈750 g and GA 〈28 weeks were the largest risk factors, and being small for gestational age was a protective factor related to mortality. Respiratory distress syndrome was the most common complication. The incidence of patent ductus arteriosus, intraventricular hemorrhage, periventricular leukomalacia, bronchopulmonary dysplasia, retinopathy of prematurity was 26.2%, 33.7%, 6.7%, 48.1%, and 41.4%, respectively. Ventilator associated pneumonia was the most common hospital acquired infection during hospitalization. Conclusions： Our study was the first survey that revealed the present status of ELBW infants in the mainland of China. The mortality and morbidity of ELBW infants remained high as compared to other developed countries.

The pursuit of discovering new high-temperature superconductors that diverge from the copper-based model 1 – 3 has profound implications for explaining mechanisms behind superconductivity and may also enable new applications 4 – 8 . Here our investigation shows that the application of pressure effectively suppresses the spin–charge order in trilayer nickelate La 4 Ni 3 O 10− δ single crystals, leading to the emergence of superconductivity with a maximum critical temperature ( T c ) of around 30 K at 69.0 GPa. The d.c. susceptibility measurements confirm a substantial diamagnetic response below T c , indicating the presence of bulk superconductivity with a volume fraction exceeding 80%. In the normal state, we observe a strange metal behaviour, characterized by a linear temperature-dependent resistance extending up to 300 K. Furthermore, the layer-dependent superconductivity observed hints at a unique interlayer coupling mechanism specific to nickelates, setting them apart from cuprates in this regard. Our findings provide crucial insights into the fundamental mechanisms underpinning superconductivity, while also introducing a new material platform to explore the intricate interplay between the spin–charge order, flat band structures, interlayer coupling, strange metal behaviour and high-temperature superconductivity. The application of pressure effectively suppresses the spin–charge order in trilayer nickelate La 4 Ni 3 O 10− δ single crystals, leading to the emergence of superconductivity.

Background Although people of all ages are susceptible to the novel coronavirus infection, which is presently named “Coronavirus Disease 2019” (COVID-19), there has been relatively few cases reported among children. Therefore, it is necessary to understand the clinical characteristics of COVID-19 in children and the differences from adults. Case presentation We report one pediatric case of COVID-19. A 14-month-old boy was admitted to the hospital with a symptom of fever, and was diagnosed with a mild form of COVID-19. The child’s mother and grandmother also tested positive for SARS-CoV-2 RNA. However, the lymphocyte counts were normal. The chest computed tomography (CT) revealed scattered ground glass opacities in the right lower lobe close to the pleura and resorption after the treatment. The patient continued to test positive for SARS-CoV-2 RNA in the nasopharyngeal swabs and stool at 17 days after the disappearance of symptoms. Conclusion The present pediatric case of COVID-19 was acquired through household transmission, and the symptoms were mild. Lymphocyte counts did not significantly decrease. The RNA of SARS-CoV-2 in stool and nasopharyngeal swabs remained positive for an extended period of time after the disappearance of symptoms. This suggests that attention should be given to the potential contagiousness of pediatric COVID-19 cases after clinical recovery.

We investigated 14 antibiotic residues in 8 marketed freshwater fish species from southeast China and estimated the associated health risks to local consumers. The antibiotic residues were determined by UPLC-MS/MS. Our findings revealed widespread distribution of quinolones (QNs), tetracyclines (TCs), and chloramphenicols (CAPs) in the freshwater fish. Notably, the average concentrations of enrofloxacin and ciprofloxacin reached levels as high as 62.5 μg/kg wet weight (ww) and 11.7 μg/kg ww, respectively, and detection frequencies were 68.7% for enrofloxacin and 31.6% for ciprofloxacin. Additionally, we detected chloramphenicol, a prohibited antibiotic, in samples with a detection frequency of 0.76%. Among the fish species, the mean concentration of total antibiotic residues was highest in bluntnose black bream (263.3 μg/kg), followed by English perch (52.4 μg/kg), crucian carp (46.3 μg/kg), black carp (28.6 μg/kg), yellowcheek carp (21.0 μg/kg), grass carp (15.3 μg/kg), bighead carp (3.78 μg/kg), and mandarin fish (3.69 μg/kg). We estimated the daily intake values of these antibiotic residues which were lower than the acceptable daily intake values and hazard indexes were much less than 1. It indicates that there is very low direct health risk to consumers. Despite that, investigation on the chronic impact, such as antibiotic-resistant bacteria, gut microbiota disruption, and allergic reactions, is urgently needed.

Long noncoding RNAs (lncRNAs) have been reported to exert important roles in tumors, including clear cell renal cell carcinoma (ccRCC). PVT1 is an important oncogenic lncRNA which has critical effects on onset and development of various cancers, however, the underlying mechanism of PVT1 functioning in ccRCC remains largely unknown. VHL deficiency-induced HIF2α accumulation is one of the major factors for ccRCC. Here, we identified the potential molecular mechanism of PVT1 in promoting ccRCC development by stabilizing HIF2α. PVT1 was significantly upregulated in ccRCC tissues and high PVT1 expression was associated with poor prognosis of ccRCC patients. Both gain-of-function and loss-of function experiments revealed that PVT1 enhanced ccRCC cells proliferation, migration, and invasion and induced tumor angiogenesis in vitro and in vivo. Mechanistically, PVT1 interacted with HIF2α protein and enhanced its stability by protecting it from ubiquitination-dependent degradation, thereby exerting its biological significance. Meanwhile, HIF2α bound to the enhancer of PVT1 to transactivate its expression. Furthermore, HIF2α specific inhibitor could repress PVT1 expression and its oncogenic functions. Therefore, our study demonstrates that the PVT1/ HIF2α positive feedback loop involves in tumorigenesis and progression of ccRCC, which may be exploited for anticancer therapy.