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We propose identification robust statistics for testing hypotheses on the risk premia in dynamic affine term structure models. We do so using the moment equation specification proposed for these models in Adrian et al. (2013). We extend the subset (factor) Anderson-Rubin test from Guggenberger et al. (2012) to models with multiple dynamic factors and time-varying risk prices. Unlike projection-based tests, it provides a computationally tractable manner to conduct identification robust tests on a larger number of parameters. We analyze the potential identification issues arising in empirical studies. Statistical inference based on the three-stage estimator from Adrian et al. (2013) requires knowledge of the factors' quality and is misleading without full-rank beta's or with sampling errors of comparable size as the loadings. Empirical applications show that some factors, though potentially weak, may drive the time variation of risk prices, and weak identification issues are more prominent in multi-factor models.

Text summarization is essential for information aggregation and demands large amounts of training data. However, concerns about data privacy and security limit data collection and model training. To eliminate this concern, we propose a federated learning text summarization scheme, which allows users to share the global model in a cooperative learning manner without sharing raw data. Personalized federated learning (PFL) balances personalization and generalization in the process of optimizing the global model, to guide the training of local models. However, multiple local data have different distributions of semantics and context, which may cause the local model to learn deviated semantic and context information. In this paper, we propose FedSUMM, a dynamic gradient adapter to provide more appropriate local parameters for local model. Simultaneously, FedSUMM uses differential privacy to prevent parameter leakage during distributed training. Experimental evidence verifies FedSUMM can achieve faster model convergence on PFL algorithm for task-specific text summarization, and the method achieves superior performance for different optimization metrics for text summarization., Accepted by IJCNN2023. 2023 IEEE International Joint Conference on Neural Network (IJCNN2023)

In recent years, hypervirulent Klebsiella pneumoniae (hvKp) has received greater attention. It mainly infects diabetic patients and typically causes a hepatic abscess. Here, we report a case of hvKp that caused forearm muscle and soft tissue infection in addition to bacteremia, hepatic and pulmonary abscess, and hyperglycemia. The patient’s condition stabilized after comprehensive treatment. She eventually recovered and was discharged after several debridement and flap operations. At 9 months of follow-up, no signs of infectious recurrence were noted, and the hyperglycemia resolved. Here, we detail important clinical features of a severe hvKp case diagnosed in an otherwise healthy individual. This report underscores the potential of hvKp to cause deep tissue infection and present with clinical symptoms similar to gas gangrene. Symptom onset in the setting of hvKp infection is usually gradual and misdiagnosis is common. The diagnosis of hvKp should be routinely considered in the clinical setting, and be strongly suspected when presenting with characteristic epidemiological, clinical and laboratory features. Although diabetes is a predisposing factor to hvKp infection, hyperglycemia appeared to manifest as a consequence of hvKp infection in this patient.

Diquat is used in agricultural contexts to control the growth of broadleaf and grassy weeds in both terrestrial and aquatic areas. Diquat can be readily absorbed by the soil and can remain therein for extended periods of time, altering the local microenvironment. In this study, the Meyerozyma guilliermondii Wyslmt yeast strain, which has the capacity to degrade Diquat, was isolated from soil exposed to long-term Diquat treatment. Over a 7-day incubation period, this strain was able to remove 42.51% of available Diquat (100 mg/L). RNA-Seq was performed to assess changes in gene expression in this yeast strain over the course of Diquat degradation, revealing 63 and 151 upregulated and downregulated genes, respectively. KEGG pathway enrichment analysis revealed these genes to be most highly enriched in the carbohydrate metabolism pathway. Through functional annotation and gene expression analyses, we identified seven genes were predicted to be involved in Diquat biodegradation. Results of qRT-PCR assays indicated that the relative mRNA expression levels of these seven genes were significantly higher relative to the control group. Together these analyses led to the identification of DN676 as a candidate Diquat-degrading gene. When a pET-DN676 vector was expressed in E. coli BL21, this strain was able to remove 12.49% of provided Diquat (100 mg/L) over the course of a 7-day incubation. These results thus confirmed that the DN676 gene can promote Diquat degradation, with these studies having yielded an engineered BL21-pET-DN676 bacterial strain capable of degrading Diquat.

Fish trophic niches reflect important ecological interactions and provide insight into the structure of mangrove food webs. Few studies have been conducted in mangrove fish predators to investigate interpopulation trophic niches and ontogenetic shifts. Using stable isotope analysis and two complementary approaches, the authors investigated trophic niche patterns within and between two ontogenetic groups (juveniles and sub-adults) of a generalist predator (Acentrogobius viridipunctatus) in four mangroves with heterogeneous environmental conditions (e.g., tidal regimes, salinity fluctuations and mangrove tree community). The authors hypothesized that the trophic niche between populations would vary regionally and trophic position would increase consistently from juvenile to sub-adult stages. The results revealed that both δ

Loess is widely deposited in arid and semi-arid areas and is characterized by low dry density, developed pore space, and loose structure, which is not commensurate with high structural strength and shear strength in the dry state. Many natural phenomena and experimental results show that intact loess is very sensitive to the change of water content, and a slight increase in water content can cause a rapid reduction in strength. Abundant information is available in the literature for the collapsibility of loess. However, research on the evolution of loess compressibility during wetting, which is very helpful in understanding loess collapsible deformation caused by long-term irrigation, remains minimal. To this end, in this article, the evolution of the compressibility of intact loess at different wetting stages is investigated by oedometer tests, and microstructure and pore size distribution (PSD) were characterized on intact loess specimens at different water contents before and after oedometer tests by scanning electron microscope (SEM) and mercury intrusion porosimetry (MIP) methods. The results show that the compression index (Cc) and secondary compression index (Cα) of intact loess depend on water content and vertical stress and change abruptly when vertical stress exceeds yield stress. Cα/Cc values of intact loess are not constant, which increases with vertical stress to a peak and then gradually decreases to 0.025. Wetting and loading can cause damage to the microstructure of intact loess; specifically, loading leads to the collapse of the overhead structure and the transformation from a bimodal PSD into a unimodal PSD, and wetting intensifies the collapse of the microstructure to form a compacted interlocking structure and promotes the transformation of medium pores into small pores.

Lingwei Kong,1,* Yu Wang,1,* Hairu Ji,2 Zhehong Li,1 Yupeng Sun,1 Yanchao Liu,1 Sheng Cao,1 Jingxin Zhao,1 Litao Shi,1 Yu Jin1 1Department of Orthopedics, The Affiliated Hospital of Chengde Medical College, Chengde, Hebei, 067000, People’s Republic of China; 2Pathology Teaching and Research Section, Chengde Medical College, Chengde, Hebei, 067000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yu Jin Tel +86 13832428328Email 358620793@qq.comAbstract: In recent years, hypervirulent Klebsiella pneumoniae (hvKp) has received greater attention. It mainly infects diabetic patients and typically causes a hepatic abscess. Here, we report a case of hvKp that caused forearm muscle and soft tissue infection in addition to bacteremia, hepatic and pulmonary abscess, and hyperglycemia. The patient’s condition stabilized after comprehensive treatment. She eventually recovered and was discharged after several debridement and flap operations. At 9 months of follow-up, no signs of infectious recurrence were noted, and the hyperglycemia resolved. Here, we detail important clinical features of a severe hvKp case diagnosed in an otherwise healthy individual. This report underscores the potential of hvKp to cause deep tissue infection and present with clinical symptoms similar to gas gangrene. Symptom onset in the setting of hvKp infection is usually gradual and misdiagnosis is common. The diagnosis of hvKp should be routinely considered in the clinical setting, and be strongly suspected when presenting with characteristic epidemiological, clinical and laboratory features. Although diabetes is a predisposing factor to hvKp infection, hyperglycemia appeared to manifest as a consequence of hvKp infection in this patient.Keywords: hypervirulent K. pneumoniae, hvKp, soft tissue infection, liver abscess, lung abscess, diabetes

Buddhism is an influential religion with a long-standing history and profound philosophy. Nowadays, more and more people worldwide aspire to learn the essence of Buddhism, attaching importance to Buddhism dissemination. However, Buddhist scriptures written in classical Chinese are obscure to most people and machine translation applications. For instance, general Chinese-English neural machine translation (NMT) fails in this domain. In this paper, we proposed a novel approach to building a practical NMT model for Buddhist scriptures. The performance of our translation pipeline acquired highly promising results in ablation experiments under three criteria., Comment: This paper is accepted by ICTAI 2022. The 34th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

Xianbao Lv,1,* Jingang Shen,1,* Zhen Guo,2,* Lingwei Kong,1 Guangchun Zhou,1 Hao Ning3 1Department of Urology, Chengwu People’s Hospital, Heze, Shandong, 274200, People’s Republic of China; 2Department of Urology, Central Hospital Affiliated Shandong First Medical University, Jinan, Shandong, 250033, People’s Republic of China; 3Department of Urology, Shandong Provincial Hospital, Jinan, Shandong, 250021, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hao NingDepartment of Urology Surgery, Shandong Provincial Hospital, No. 324, Jingwu Road, Jinan, Shandong 250021, People’s Republic of ChinaTel +86 531 68776310Email haotiecg4792@163.comPurpose: MicroRNAs have recently reported playing a vital role in the development of cancers. However, the role of miR-592 in renal cell carcinoma (RCC) has not been explored. In this study, the potential role of miR-592 was investigated in RCC.Patients and methods: The expression of miR-592 was evaluated in RCC tissues and cell lines using qRT-PCR assays. The Kaplan-Meier analysis and Cox proportional hazards model analysis was used to analyze the prognostic value of miR-592 in RCC. The effects of miR-592 on cell proliferation, migration, and invasion were determined by cell counting kit-8 (CCK-8) and Transwell assays in vitro.Results: The results showed that miR-592 was significantly increased both in RCC tissues and cell lines. Overexpression of miR-592 was significantly associated with lymph node metastasis, TNM stage, and poor overall survival. And functional studies in two RCC cell lines (786-O and Caki-1) have shown that overexpression of miR-592 promoted cell proliferation, migration, and invasion, while silence of miR-592 inhibited cell proliferation, migration, and invasion. SPRY2 was a direct target of miR-592.Conclusion: Overall, overexpression of miR-592 may be a prognostic biomarker and therapeutic strategy for patients with RCC, which is correlated with the progression of RCC.Keywords: miR-592, renal cell carcinoma, prognosis, proliferation, migration, invasion

By assembling mesocosms and utilizing high-throughput sequencing, we aim to characterize the shifts of the bacterial community in freshwaters driven by two contrasting submerged macrophyte species, Ceratophyllum demersum L. and Vallisneria spiralis L. Although the microbe in both the water column and sediment were largely modulated by the macrophyte, the effect varied considerably depending on bacterial locations and macrophyte species. Actinobacteria was the most abundant taxa in the water column of all the three treatments, but its abundances were significantly higher in the two planted treatments. Moreover, Alphaproteobacteria showed high abundance only in the unplanted control. For bacterial taxa in the sediment, C. demersum significantly increased the relative abundance of Anaerolineae but reduced the relative abundance of Betaproteobacteria and Gammaproteobacteria, while V. spiralis increased the relative abundance of Deltaproteobacteria and Gammaproteobacteria. Additionally, in the C. demersum treatment, the water column bacterial community increased more dramatically in richness, alpha diversity, and the relative abundance of the dominant taxa than those in the V. spiralis treatment. Taken together, the findings from this study reveal that the two species of submerged macrophyte modified the bacterial community in waters, despite the obvious interspecific performance differences.

Catalytic depolymerization proposed by our team was used on the thermal decomposition study of a typical perhydrous coal for improving the tar yield. The products from the coal catalytic depolymerization with or without a small amount of ZnCl2 or CoCl2 catalysts were investigated and compared. The composition of the tar and the structure of the coal char were characterized by a comprehensive two-dimensional gas chromatography coupled with mass spectrometric detection (GC × GC MS), thermogravimetric analysis (TGA), Raman spectrum and Elemental analysis, respectively. Compared with 8.21% of tar yield generated from the depolymerization of the raw coal, the tar yield increased to 9.19% and 10.02% when ZnCl2 and CoCl2 catalysts were added, respectively. The light fractions of tar also increased from 81.71% to 84.02% and 84.51%, respectively. Meanwhile, the yield of the aromatic ring components (> 3 fused benzene rings) and the ratio of aromatic rings with six or more fused benzene rings in the tar decreased. Further analysis reflected that the addition of catalysts in the catalytic depolymerization process could facilitate the cracking of more Cal-O bonds and precipitate the reaction start at lower temperature, which finally increases the volatiles released during the depolymerization stage.

There are mainly two views on the interpretation of high efficiency of Convolutional Neural Networks (CNNs) for the task of image classification: shape bias and texture bias. This is critical to the causality and reliability of CNN models in real applications. In this work, we try to explore the power of CNNs and reconcile the hypothesis contradiction of CNNs from a multi-view image representation. Firstly, we assume an image is generated from object shape representation, object texture representation, and background information. Secondly, we segment and recombine the object shape, texture and image background through two losses: image reconstructed loss and feature discrepancy loss. Finally, the classification loss is combined by shape, texture and background contributions weighted by multi-view features. Comprehensive experiments conducted on real-world datasets show that, first, CNNs generally do not have texture or shape bias, which change with the internal bias of data; second, CNNs are learning knowledge in a lazy way, i.e., high level knowledge is learned only if low level knowledge does not satisfy the task requirements. Our findings might benefit the interpretability of CNNs and provide insight of more robust design.

Deep neural networks have revolutionized the field of machine learning by dramatically improving the state-of-the-art in various domains. The sizes of deep neural networks (DNNs) are rapidly outgrowing the capacity of hardware to fast store and train them. Over the past few decades, researches have explored the prospect of sparse DNNs before, during, and after training by pruning edges from the underlying topology. After the above operation, the generated neural network is known as a sparse neural network. More recent works have demonstrated the remarkable results that certain sparse DNNs can train to the same precision as dense DNNs at lower runtime and storage cost. Although existing methods ease the situation that high demand for computation resources severely hinders the deployment of large-scale DNNs in resource-constrained devices, DNNs can be trained at a faster speed and lower cost. In this work, we propose a Fine-tune Structured Sparsity Learning (FSSL) method to regularize the structures of DNNs and accelerate the training of DNNs. FSSL can: (1) learn a compact structure from large sparse DNN to reduce computation cost; (2) obtain a hardware-friendly to accelerate the DNNs evaluation efficiently. Experimental results of the training time and the compression rate show that superior performance and efficiency than the Matlab example code. These speedups are about twice speedups of non-structured sparsity.

Floating treatment wetlands (FTWs) and biofilm carriers are widely used in water purification. The objective of the present work was to explore whether and to what extent an FTW integrated with plants and biofilm carriers (FTW-I) could enhance the nutrient removal efficiency. Significantly higher removal rates of ammonia nitrogen (85.2 %), total phosphorus (82.7 %), and orthophosphate (82.5 %) were observed in the FTW-I treatment relative to the FTW with plants (FTW-P; 80.0, 78.5, and 77.6 %, respectively) and the FTW with biofilm carriers (FTW-B; 56.7, 12.9, and 13.4 %, respectively) (p

In this study, two types of artificial floating islands (AFIs), group A (consists of 1# and 2# traditional AFIs with plant and soil) and group B (consists of 4# and 5# new-type AFIs with plant, substrate, and with luffa sponge and corncob hanging at the bottom), were constructed, respectively. The removal effects and degradation mechanisms of luffa sponge and corncob in group B were compared and investigated. Plant height, root growth, and packing degradation of the two types of AFIs were studied. Temperature, dissolved oxygen (DO), and pH on the decontamination effects of AFI were discussed. The results showed that group A and group B AFIs showed great significant differences in removal of CODCr, TN, NO3−−N, NH4+−N, and TP (p

To investigate the effects of matrix metalloproteinase-1 (MMP-1) gene polymorphisms on the onset of osteomyelitis in Chinese Han population. In all, 80 osteomyelitis patients (case group) and 81 healthy people (control group) were recruited into this case-control study. Polymerase chain reaction-restriction fragment length polymorphism method was utilized to examine the genotypes of MMP-1 polymorphisms (−1607 2G/1G and −519A/G) in the 2 groups. Genotype and allele differences between the case and control groups were analyzed by chi-square test. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated to present the association strength between MMP-1 gene polymorphisms and osteomyelitis. Frequencies of −1607 2G/2G genotype between the case and control groups were statistically significant (P = .025). Compared with 1G/1G genotype carriers, the 2G/2G genotype carriers had 1.605 times risk of developing osteomyelitis (OR 2.605, 95% CI 1.116–6.082). Meanwhile, the 2G allele significantly associated with the risk of osteomyelitis (OR 1.735, 95% CI 1.115–2.701). In addition, frequency of −519GG genotype was obviously higher in case group than that in control group (P = .024), and GG genotype related to an increased risk of osteomyelitis (OR 2.792, 95% CI 1.127–6.917). Whereas, the −519G allele may be a susceptible factor for osteomyelitis (OR 1.622, 95% CI 1.038–2.536). The MMP-1 −1607 (2G/1G) and −519 (A/G) polymorphisms may contribute to the onset of osteomyelitis.

In this study, a new coupling process system of BFB (biological filter bed) and SFCW (subsurface-flow constructed wetland) based on the auto-ventilation network was proposed, and the comparative pollutant removal efficiency of the pilot test coupling system with different substrates configurations were investigated. The study found that: the influent concentration of the system fluctuated greatly and effluent concentration of the comparison system (b) was 20.22 ± 13.37 mg/L, 2.70 ± 2.49 mg/L, 4.40 ± 3.05 mg/L and 1.09 ± 0.62 mg/L, respectively. The comparison system (b) had better removal rates than that of the original system (a), which was 81.30 %, 90.28 %, 88.57 % and 75.36 % for CODcr, NH4 +-N, TN and TP, respectively. The removal of the above main water indexes of the comparison system (b) promoted to 4.20 %, 9.20 %, 7.66 % and 13.61 % respectively when compared to the original system (a), which showed that the optimized configuration of various kinds of substrates was significant and was more beneficial to the degradation and removal of pollutants. The adsorption and interception function of substrates in the constructed wetland was the main way of phosphorus removal. The function of auto-ventilation ensured the amount of DO in the coupling system, making the phosphorus removal was less affected comparing to structure of traditional wetland.