Resonant sequential scattering in two-frequency-pumping superradiance from a Bose-Einstein condensate

We study sequential scattering in superradiance from a Bose-Einstein condensate pumped by a two-frequency laser beam. We find that the distribution of atomic side modes presents highly different patterns for various frequency difference between the two pump components. A novel distribution is observed, with a frequency difference of eight times the recoil frequency. These observations reveal that the frequency overlap between the end-fire modes related to different side modes plays an essential role in the dynamics of sequential superradiant scattering. The numerical results from a semiclassical model qualitatively agree with our observations.Comment: Submitted to PR

Solution Path Algorithm for Twin Multi-class Support Vector Machine

The twin support vector machine and its extensions have made great achievements in dealing with binary classification problems, however, which is faced with some difficulties such as model selection and solving multi-classification problems quickly. This paper is devoted to the fast regularization parameter tuning algorithm for the twin multi-class support vector machine. A new sample dataset division method is adopted and the Lagrangian multipliers are proved to be piecewise linear with respect to the regularization parameters by combining the linear equations and block matrix theory. Eight kinds of events are defined to seek for the starting event and then the solution path algorithm is designed, which greatly reduces the computational cost. In addition, only few points are combined to complete the initialization and Lagrangian multipliers are proved to be 1 as the regularization parameter tends to infinity. Simulation results based on UCI datasets show that the proposed method can achieve good classification performance with reducing the computational cost of grid search method from exponential level to the constant level

Effect of quercetin on bone metabolism and serum osteocalcin in osteoporotic rats

Purpose: To determine the effect of quercetin on bone metabolism and serum osteocalcin in osteoporotic rats. Methods: Sixty specific pathogen-free rats were randomly divided into control group, model group; high, medium and low dose quercetin groups, and diethylstilbestrol group, with 10 rats in each group. The high, middle and low dose quercetin groups were given quercetin suspension at doses of 200, 100, 50 mg/kg/day, respectively; the ethylene estradiol group was given ethylene estradiol (1.0 mg/kg/week), while control rats received ethylene estradiol at doses of 200, 100, 50 mg/kg/day. Rats in the model group were given saline. Samples were taken after 6 weeks of administration. The levels of serum bone-derived alkaline phosphatase (BALP), estradiol (E2) and serum osteocalcin (BGP) in femur tissue were measured using ELISA kits. Bone mineral density (BMD) was determined using BMD tester. Results: Relative to normal rats, BALP and BGP levels in the model rats were markedly increased, while E2 was significantly lower (p < 0.5). Quercetin treatment led to significant increases in BALP and E2 levels in the middle and high dose groups, relative to the model group, while BGP levels in all quercetin treatment groups decreased significantly, when compared to model rats (p < 0.05). There were higher BMD values in quercetin and diethylstilbestrol groups than in model (p < 0.05). Conclusion: Quercetin enhances bone formation and BMD, but decreases osteocalcin levels and maintains bone biomechanics in ovariectomized rats. Thus, it may find therapeutic application in maintaining bone health. Keywords: Quercetin, Osteoporosis, Bone metabolism, Osteocalci

Unraveling fish diversity and assembly patterns in a temperate river: evidence from environmental DNA metabarcoding and morphological data

The loss of freshwater biodiversity has drawn greater attention to fish diversity and community assembly patterns. However, traditional survey methods, such as ground cages and electrofishing, may cause damage to fish communities and have become increasingly unsuitable for frequent and large-scale fish diversity surveys. In this study, environmental DNA (eDNA) metabarcoding and morphological data were both used to investigate the distribution and diversity of fish communities in the Taizi River basin, a temperate river in Northeast China, and the fish diversity and assembly patterns were investigated by using the null model. The results showed that a total of 7 orders, 17 families, 49 genera and 56 species were detected by the eDNA metabarcoding (6 orders, 15 families, 40 genera and 45 species) and morphological method (6 orders, 10 families, 31 genera and 34 species), and the eDNA method had a higher detection probability. Cypriniformes was detected most frequently, followed by Perciformes. Principal coordinate analysis revealed that fish communities in the Taizi River exhibited different spatial structures between the upper and lower reaches, with fish sensitive to environmental changes mostly found in the upper reaches and higher fish richness in the same area. The beta diversity in the upper reaches was higher than that in the lower reaches. The null model results showed the main factor that affected the distribution of fish in the Taizi River is the stochastic processes. Among the deterministic processes, the main environmental filter factors affecting fish community structure include total phosphorus, biochemical oxygen demand and temperature. We also confirm that eDNA metabarcoding has a higher detection rate compared to traditional survey methods, so it is feasible for freshwater ecosystem and fish resource monitoring. Therefore, the utilization of eDNA metabarcoding can effectively enhance monitoring efficiency and minimize interference with water bodies

AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation

Diffusion models have gained significant attention in the realm of image generation due to their exceptional performance. Their success has been recently expanded to text generation via generating all tokens within a sequence concurrently. However, natural language exhibits a far more pronounced sequential dependency in comparison to images, and the majority of existing language models are trained with a left-to-right auto-regressive approach. To account for the inherent sequential characteristic of natural language, we introduce Auto-Regressive Diffusion (AR-Diffusion). AR-Diffusion ensures that the generation of tokens on the right depends on the generated ones on the left, a mechanism achieved through employing a dynamic number of denoising steps that vary based on token position. This results in tokens on the left undergoing fewer denoising steps than those on the right, thereby enabling them to generate earlier and subsequently influence the generation of tokens on the right. In a series of experiments on various text generation tasks, including text summarization, machine translation, and common sense generation, AR-Diffusion clearly demonstrated its superiority over existing diffusion language models and that it can be $100\times\sim600\times$ faster when achieving comparable results. Our code is available at https://github.com/microsoft/ProphetNet/tree/master/AR-diffusion.Comment: Accept By NIPS 202

Derivation of aquatic life criteria for four phthalate esters and their ecological risk assessment in Liao River

As a critical family of endocrine disruptors, phthalate esters (PAEs) attracted considerable attentions due to increasingly detected worldwide. Aquatic life criteria (ALC) for PAEs are crucial for their accurate ecological risk assessment (ERA) and have seldom been derived before. Given this concern, the purpose of the present study is to optimize the ALCs of four priority PAEs to estimate their ecological risks in Liao River. Reproductive endpoint was found to be more sensitive than other endpoints. Thus, reproduction related toxicity data were screened to derive ALCs applying species sensitivity distribution (SSD) method. ALCs of DEHP, DBP, BBP and DEP were calculated to be 0.04, 0.62, 4.71 and 41.9 μg L−1, which indicated decreased toxicity in sequence. Then, the derived ALCs of the four PAEs were applied to estimate their ecological risks in Liao River. A total of 27 sampling sites were selected to detect and analyze the exposure concentrations of PAEs. ERA using the hazard quotient (HQ) method was conducted. The results demonstrated that DEHP exhibited higher risks at 92.6% of sampling sites, and risks posed by DBP were moderate at 63.0% sampling sites. However, risks posed by BBP were low at 70.4% of sampling sites, and there were no risks posed by DEP at 96.3% of sampling sites. The results of probabilistic ecological risk assessment (PERA) indicated that probabilities of exceeding effects thresholds on 5% of species were 60.41%, 0%, 0.12%, 14.28% for DEHP, DEP, BBP and DBP, respectively. The work provides useful information to protect aquatic species in Liao River

Prognostic Analysis of Duodenal Gastrointestinal Stromal Tumors

Aim. This study aims to analyze factors possibly related to the prognosis of duodenal gastrointestinal stromal tumors (DGISTs). Methods. We collected and retrospectively analyzed clinical and pathological data of 62 patients with primary DGISTs. All the patients were hospitalized and received complete surgical resection at Shanghai Ruijin Hospital from September 2003 to April 2015. We followed up the patients to determine survival outcomes. We also analyzed the effect of clinical and pathological factors on disease-free survival (DFS) and overall survival (OS) of the patients. Results. Kaplan-Meier univariate survival analysis demonstrated that tumor size, mitotic index, Ki-67 index, and pathological risk were correlated with the DFS and OS of the patients (DFS P=0.039, 0.001, <0.001, and 0.005, resp.; OS P=0.027, 0.007, <0.001, and 0.012, resp.). Cox multivariate regression analysis revealed that Ki-67 index was an independent prognostic factor affecting DFS and OS (P=0.007 and 0.028, resp.). Moreover, Kaplan-Meier survival analysis showed that imatinib treatment for patients with recurrence was correlated with prolonged OS (P=0.002). Conclusion. Prognosis for DGIST treated by R0 resection is favorable. High level of Ki-67 can be an independent risk factor of DGIST prognosis. Adjuvant imatinib therapy for patients with tumor recurrence could probably lead to prolonged survival

The potential impacts of climate change factors on freshwater eutrophication: Implications for research and countermeasures of water management in China

Water eutrophication has become one of the most serious aquatic environmental problems around the world. More and more research has indicated climate change as a major natural factor that will lead to the acceleration of eutrophication in rivers and lakes. However, understanding the mechanism of climate change's effect on water eutrophication is difficult due to the uncertainties caused by its complex, non-linear process. There is considerable uncertainty about the magnitude of future temperature changes, and how these will drive eutrophication in water bodies at regional scales under the effect of human activities. This review collects the existing international and domestic literature from the last 10 years, discussing the most sensitive factors of climate change (i.e., temperature, precipitation, wind, and solar radiation) and analyzing their interaction with water eutrophication. Case studies of serious eutrophication and algal bloom problems in China are discussed to further demonstrate the conclusion. Finally, adaptation countermeasures and related implications are proposed in order to foster the development of sustainability strategies for water management in China