Language Education Policy Research in the United States: Review and Inspiration

Language education policy is a branch of language policy. The research on language education policy in academic circles has not been developed for a long time, but the research methods and research scope have undergone significant changes. The ethnic and cultural diversity of The United States is highly similar to the coexistence of multi-ethnic languages in China, especially the bilingual teaching research. Scholars began to study the language education policy in the United States in the 1960s. Up to now, it has experienced nearly 60 years of development, producing many valuable research methods and ideal research results. This paper summarizes and analyzes the studies on language education policy in the United States in the recent 60 years, so as to draw lessons from the methods and measures that can be referenced and absorbed in the formulation of language education policy research in China

Characteristics and distribution of geohazards since the middle miocene of the Xisha sea area, South China Sea

Geological hazards can cause significant harm to the construction and maintenance of reef infrastructure projects in the Xisha Sea area. This study uses high-resolution multichannel earthquake data, single-channel seismic profiles, and multi-beam survey data to identify and analyze the geological hazards in the Xisha Sea area since the Miocene. Based on the geophysical data interpretation, the destructive geological disaster factors that are active, such as active faults, shallow gas, diapers, landslides, multistage scarps (steps), scouring troughs, and canyons, as well as the restrictive geological disaster factors without activity ability, such as buried paleochannels, pockmarks, reefs, and undersea volcanoes, are identified and analyzed. This paper discusses the causes and hazards of geological hazards and, for the first time, draws a comprehensive plane layout of the geological hazards. The above analysis demonstrates that the scarps are mainly located around the atolls or platforms, and the slope of the southeast seabed topography is significantly higher than that of the northwest. There are seven medium and large landslides, mainly located around Yongxing Plateau and Yongle Plateau, caused by gravity and faulting. Shallow gas is mainly developed in the southern part of the North Reef and is indicated by diaper structures, faults, and gas chimneys. A series of shallow faults are developed in the study area, mainly steep normal faults. The scouring troughs are primarily distributed near the Yongxing Platform, Zhongjian North Platform, and Huaguang Platform. Submarine canyons are primarily located in the northern and southern parts of the Shidao Platform. Affected by multiple factors such as hydrodynamic conditions, the stability of sedimentary layers, and sediment supply, the scour degree varies, with the general depth ranging from several meters to several hundred meters. Underwater infrastructure in the study area should not be constructed in areas with active and destructive geological hazards. The results of this study can serve as a guide for further exploration in the Xisha area and disaster prevention and mitigation during construction activity in the area

MMOTU: A Multi-Modality Ovarian Tumor Ultrasound Image Dataset for Unsupervised Cross-Domain Semantic Segmentation

Ovarian cancer is one of the most harmful gynecological diseases. Detecting ovarian tumors in early stage with computer-aided techniques can efficiently decrease the mortality rate. With the improvement of medical treatment standard, ultrasound images are widely applied in clinical treatment. However, recent notable methods mainly focus on single-modality ultrasound ovarian tumor segmentation or recognition, which means there still lacks researches on exploring the representation capability of multi-modality ultrasound ovarian tumor images. To solve this problem, we propose a Multi-Modality Ovarian Tumor Ultrasound (MMOTU) image dataset containing 1469 2d ultrasound images and 170 contrast enhanced ultrasonography (CEUS) images with pixel-wise and global-wise annotations. Based on MMOTU, we mainly focus on unsupervised cross-domain semantic segmentation task. To solve the domain shift problem, we propose a feature alignment based architecture named Dual-Scheme Domain-Selected Network (DS2Net). Specifically, we first design source-encoder and target-encoder to extract two-style features of source and target images. Then, we propose Domain-Distinct Selected Module (DDSM) and Domain-Universal Selected Module (DUSM) to extract the distinct and universal features in two styles (source-style or target-style). Finally, we fuse these two kinds of features and feed them into the source-decoder and target-decoder to generate final predictions. Extensive comparison experiments and analysis on MMOTU image dataset show that DS2Net can boost the segmentation performance for bidirectional cross-domain adaptation of 2d ultrasound images and CEUS images. Our proposed dataset and code are all available at https://github.com/cv516Buaa/MMOTU_DS2Net.Comment: code: https://github.com/cv516Buaa/MMOTU_DS2Net paper:18 pages, 12 figures, 11 tables, 16 formula

Selection of suitable reference genes for abiotic stress-responsive gene expression studies in peanut by real-time quantitative PCR

Background: Because of its strong specificity and high accuracy, real-time quantitative PCR (RT-qPCR) has been a widely used method to study the expression of genes responsive to stress. It is crucial to have a suitable set of reference genes to normalize target gene expression in peanut under different conditions using RT-qPCR. In this study, 11 candidate reference genes were selected and examined under abiotic stresses (drought, salt, heavy metal, and low temperature) and hormone (SA and ABA) conditions as well as across different organ types. Three statistical algorithms (geNorm, NormFinder and BestKeeper) were used to evaluate the expression stabilities of reference genes, and the comprehensive rankings of gene stability were generated. Results: The results indicated that ELF1B and YLS8 were the most stable reference genes under PEG-simulated drought treatment. For high-salt treatment using NaCl, YLS8 and GAPDH were the most stable genes. Under CdCl2 treatment, UBI1 and YLS8 were suitable as stable reference genes. UBI1, ADH3, and ACTIN11 were sufficient for gene expression normalization in low-temperature experiment. All the 11 candidate reference genes showed relatively high stability under hormone treatments. For organs subset, UBI1, GAPDH, and ELF1B showed the maximum stability. UBI1 and ADH3 were the top two genes that could be used reliably in all the stress conditions assessed. Furthermore, the necessity of the reference genes screened was further confirmed by the expression pattern of AnnAhs. Conclusions: The results perfect the selection of stable reference genes for future gene expression studies in peanut and provide a list of reference genes that may be used in the future

In-Vessel Co-Composting of Food Waste Employing Enriched Bacterial Consortium

Svrha je ovoga rada bila pripremiti odgovarajuću smjesu za kompostiranje s pomoću kulture bakterija i 2 % vapna za učinkovitu obradu otpada od hrane u posudi zapremnine 60 litara. U pokusu, koji je trajao 42 dana, otpaci su od hrane prvo pomiješani s piljevinom i 2 % (suhe tvari) vapna, zatim je u jedan reaktor dodana obogaćena kultura bakterija, dok se u drugom reaktoru nalazio kontrolni uzorak. Rezultati pokazuju da se inokuliranjem smjese za kompostiranje bakterijskom kulturom može uspješno riješiti problem zasićenosti uljem te poboljšati mineralizacija. Osim toga, parametri kao što su: emisija ugljičnog dioksida od (0,81±0,2) g/(kg·dan), indeks klijanja od (105±3) %, maseni udjel ekstraktibilnog amonijaka od 305,78 mg/kg, omjer ugljika i dušika od 16,18, pH=7,6 i električna vodljivost od 3,12 mS/cm potvrđuju zrelost komposta, koji je zadovoljio standarde kompostiranja. U kontrolnom je uzorku opaženo kašnjenje termofilne faze, pa kompost nije sazrio ni nakon 42 dana. Stoga je zaključeno da su dobro pripremljena smjesa za kompostiranje i bakterijska kultura s odgovarajućim svojstvima za razgradnju ulja nužni za uspješan sustav kompostiranja otpada od hrane.The aim of the present study is to develop a good initial composting mix using a bacterial consortium and 2 % lime for effective co-composting of food waste in a 60-litre in-vessel composter. In the experiment that lasted for 42 days, the food waste was first mixed with sawdust and 2 % lime (by dry mass), then one of the reactors was inoculated with an enriched bacterial consortium, while the other served as control. The results show that inoculation of the enriched natural bacterial consortium effectively overcame the oil-laden co-composting mass in the composter and increased the rate of mineralization. In addition, CO2 evolution rate of (0.81±0.2) g/(kg·day), seed germination index of (105±3) %, extractable ammonium mass fraction of 305.78 mg/kg, C/N ratio of 16.18, pH=7.6 and electrical conductivity of 3.12 mS/cm clearly indicate that the compost was well matured and met the composting standard requirements. In contrast, control treatment exhibited a delayed thermophilic phase and did not mature after 42 days, as evidenced by the maturity parameters. Therefore, a good composting mix and potential bacterial inoculum to degrade the oil are essential for food waste co-composting systems

Molecular epidemiology and antimicrobial resistance patterns of carbapenem-resistant Acinetobacter baumannii isolates from patients admitted at ICUs of a teaching hospital in Zunyi, China

BackgroundCarbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as a predominant strain of healthcare-associated infections worldwide, particularly in intensive care units (ICUs). Therefore, it is imperative to study the molecular epidemiology of CRAB in the ICUs using multiple molecular typing methods to lay the foundation for the development of infection prevention and control strategies. This study aimed to determine the antimicrobial susceptibility profile, the molecular epidemiology and conduct homology analysis on CRAB strains isolated from ICUs.MethodsThe sensitivity to various antimicrobials was determined using the minimum inhibitory concentration (MIC) method, Kirby-Bauer disk diffusion (KBDD), and E-test assays. Resistance genes were identified by polymerase chain reaction (PCR). Molecular typing was performed using multilocus sequence typing (MLST) and multiple-locus variable-number tandem repeat analysis (MLVA).ResultsAmong the 79 isolates collected, they exhibited high resistance to various antimicrobials but showed low resistance to levofloxacin, trimethoprim-sulfamethoxazole, and tetracyclines. Notably, all isolates of A. baumannii were identified as multidrug-resistant A. baumannii (MDR-AB). The blaOXA-51-like, adeJ, and adeG genes were all detected, while the detection rates of blaOXA-23-like (97.5%), adeB (93.67%), blaADC (93.67%), qacEΔ1-sul1 (84.81%) were higher; most of the Ambler class A and class B genes were not detected. MLST analysis on the 79 isolates identified five sequence types (STs), which belonged to group 3 clonal complexes 369. ST1145Ox was the most frequently observed ST with a count of 56 out of 79 isolates (70.89%). MLST analysis for non-sensitive tigecycline isolates, which were revealed ST1145Ox and ST1417Ox as well. By using the MLVA assay, the 79 isolates could be grouped into a total of 64 distinct MTs with eleven clusters identified in them. Minimum spanning tree analysis defined seven different MLVA complexes (MCs) labeled MC1 to MC6 along with twenty singletons. The locus MLVA-AB_2396 demonstrated the highest Simpson’s diversity index value at 0.829 among all loci tested in this study while also having one of the highest variety of tandem repeat species.ConclusionThe molecular diversity and clonal affinities within the genomes of the CRAB strains were clearly evident, with the identification of ST1144Ox, ST1658Ox, and ST1646Oxqaq representing novel findings

Critical Roles of STAT3 in β-Adrenergic Functions in the Heart

BACKGROUND: β-Adrenergic receptors (βARs) play paradoxical roles in the heart. On one hand, βARs augment cardiac performance to fulfill the physiological demands, but on the other hand, prolonged activations of βARs exert deleterious effects that result in heart failure. The signal transducer and activator of transcription 3 (STAT3) plays a dynamic role in integrating multiple cytokine signaling pathways in a number of tissues. Altered activation of STAT3 has been observed in failing hearts in both human patients and animal models. Our objective is to determine the potential regulatory roles of STAT3 in cardiac βAR-mediated signaling and function. METHODS AND RESULTS: We observed that STAT3 can be directly activated in cardiomyocytes by β-adrenergic agonists. To follow up this finding, we analyzed βAR function in cardiomyocyte-restricted STAT3 knockouts and discovered that the conditional loss of STAT3 in cardiomyocytes markedly reduced the cardiac contractile response to acute βAR stimulation, and caused disengagement of calcium coupling and muscle contraction. Under chronic β-adrenergic stimulation, Stat3cKO hearts exhibited pronounced cardiomyocyte hypertrophy, cell death, and subsequent cardiac fibrosis. Biochemical and genetic data supported that Gαs and Src kinases are required for βAR-mediated activation of STAT3. Finally, we demonstrated that STAT3 transcriptionally regulates several key components of βAR pathway, including β1AR, protein kinase A, and T-type Ca(2+) channels. CONCLUSIONS: Our data demonstrate for the first time that STAT3 has a fundamental role in βAR signaling and functions in the heart. STAT3 serves as a critical transcriptional regulator for βAR-mediated cardiac stress adaption, pathological remodeling, and heart failure

Adaptive position calibration technique for an optical micro-scanning thermal microscope imaging system

In order to improve the spatial resolution of an optical micro-scanning thermal microscope system, the micro-scanning position must be accurately calibrated. An adaptive calibration method based on image registration and plane coordinate system is proposed. The meaning of calibration is given, and the principle and method of point calibration are introduced in detail and experiments using the real system were done. Different reconstruction methods were applied to reconstruct the visible light image and the real thermal microscope image, and the evaluation scores are given. Results of simulation and real thermal imaging processing show that the method can successfully calibrate the micro-scanning position. The method can significantly improve the oversampled reconstructed image quality, thus enhancing the spatial resolution of the system. This method can also be used in other electro-optical imaging systems

HIV and Stigma in Liuzhou, China

To describe emergent stigma-related themes from individual descriptions of living with HIV in Liuzhou, China

One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction

Magnetic resonance imaging (MRI) is a principal radiological modality that provides radiation-free, abundant, and diverse information about the whole human body for medical diagnosis, but suffers from prolonged scan time. The scan time can be significantly reduced through k-space undersampling but the introduced artifacts need to be removed in image reconstruction. Although deep learning (DL) has emerged as a powerful tool for image reconstruction in fast MRI, its potential in multiple imaging scenarios remains largely untapped. This is because not only collecting large-scale and diverse realistic training data is generally costly and privacy-restricted, but also existing DL methods are hard to handle the practically inevitable mismatch between training and target data. Here, we present a Physics-Informed Synthetic data learning framework for Fast MRI, called PISF, which is the first to enable generalizable DL for multi-scenario MRI reconstruction using solely one trained model. For a 2D image, the reconstruction is separated into many 1D basic problems and starts with the 1D data synthesis, to facilitate generalization. We demonstrate that training DL models on synthetic data, integrated with enhanced learning techniques, can achieve comparable or even better in vivo MRI reconstruction compared to models trained on a matched realistic dataset, reducing the demand for real-world MRI data by up to 96%. Moreover, our PISF shows impressive generalizability in multi-vendor multi-center imaging. Its excellent adaptability to patients has been verified through 10 experienced doctors' evaluations. PISF provides a feasible and cost-effective way to markedly boost the widespread usage of DL in various fast MRI applications, while freeing from the intractable ethical and practical considerations of in vivo human data acquisitions.Comment: 22 pages, 9 figures, 1 tabl