ISCR28 is a fully functional and active member of the IS91-like family of insertion sequences. ISCR28 is 1,708-bp long and contains a 1,293-bp long putative open reading frame that codes a transposase. Sixty ISCR28-containing sequences from GenBank generated 27 non-repeat genetic contexts, all of which represented naturally occurring biological events that had occurred in a wide range of gram-negative organisms. Insertion of ISCR28 into target DNA preferred the presence of a 5\'-GXXT-3\' sequence at its terIS (replication terminator) end. Loss of the first 4 bp of its oriIS (origin of replication) likely caused ISCR28 to be trapped in ISApl1-based transposons or similar structures. Loss of terIS and fusion with a mobile element upstream likely promoted co-transfer of ISCR28 and the downstream resistance genes. ArmA and its downstream intact ISCR28 can be excised from recombinant pKD46 plasmids forming circular intermediates, further elucidating its activity as a transposase.

The rapid emergence of carbapenem-resistant Klebsiella pneumoniae (CRKP) and the comparatively limited development of new antibiotics pose a major threat to public health. Aminoglycosides are important options that can lower the mortality rate effectively in combination therapy with β-lactam agents. However, in this study, we observed two multidrug-resistant (MDR) K. pneumoniae named 1632 and 1864 that exhibited high-level resistance to both carbapenems and aminoglycosides. Through whole-genome sequencing (WGS), the unusual co-occurrence of rmtB, armA, and blaKPC-2 genes, associating with two key resistance plasmids, was observed in two isolates. Notably, we also found that the armA resistance gene and virulence factor iuc operon co-occurred on the same plasmid in K. pneumoniae 1864. Detailed comparative genetic analysis showed that all these plasmids were recognized as mobilizable plasmids, as they all carry the essential oriT site. Results of conjugation assay indicated that armA-positive plasmids in two isolates could self-transfer to Escherichia coli J53 effectively, especially, the p1864-1 plasmid, which could cotransfer hypervirulent and multidrug-resistant phenotypes to other isolates. Moreover, multiple insertion sequences (ISs) and transposons (Tns) were also found surrounding the vital resistant genes, which could even form a large antibiotic resistance island (ARI) and could stimulate mobilization of resistant determinants. Overall, we report the uncommon coexistence of armA plasmid, rmtB-blaKPC-2 plasmid, and even iuc virulence operon-encoding plasmid in K. pneumoniae isolates, which greatly increased the spread of these high-risk phenotypes and which are of great concern. IMPORTANCE Carbapenemase-producing Klebsiella pneumoniae have become a great challenge for antimicrobial chemotherapy, while aminoglycosides can lower the mortality rate effectively in combination therapy with them. Unfortunately, we isolated two K. pneumoniae from blood sample of patients that not only exhibited high-level resistance to carbapenems and aminoglycosides but also showed the unusual co-occurrence of the rmtB, armA, and blaKPC-2 genes. These elements were all located on mobile plasmids and flanked by polymorphic mobile genetic elements (MGEs). What\'s worse most, we also identified a conjugative virulent MDR plasmid, coharboring multiple resistant determinants, and iuc operon, which was confirmed could transfer such high-risk phenotype to other isolates. The emergence of such conjugative virulence plasmids may promote the rapid dissemination of virulence-encoding elements among Gram-negative pathogens. This uncommon coexistence of rmtB, armA, blaKPC-2, and iuc virulence operon-encoding plasmids in K. pneumoniae, presents a huge threat to clinical treatment. Future studies are necessary to evaluate the prevalence of such isolates.

The stock index is an important indicator to measure stock market fluctuation, with a guiding role for investors\' decision-making, thus being the object of much research. However, the stock market is affected by uncertainty and volatility, making accurate prediction a challenging task. We propose a new stock index forecasting model based on time series decomposition and a hybrid model. Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) decomposes the stock index into a series of Intrinsic Mode Functions (IMFs) with different feature scales and trend term. The Augmented Dickey Fuller (ADF) method judges the stability of each IMFs and trend term. The Autoregressive Moving Average (ARMA) model is used on stationary time series, and a Long Short-Term Memory (LSTM) model extracts abstract features of unstable time series. The predicted results of each time sequence are reconstructed to obtain the final predicted value. Experiments are conducted on four stock index time series, and the results show that the prediction of the proposed model is closer to the real value than that of seven reference models, and has a good quantitative investment reference value.

The fluctuation of the carbon price and its related components can effectively reflect the overall economy. This paper explores the fluctuation of the carbon price and its influencing factors. First, the ensemble empirical mode decomposition (EEMD) method is used to decompose the carbon price series of eight pilot projects at multiple timescales. Second, according to the historical trading records in the eight pilot projects, this paper constructs a national carbon price under a variety of scenarios. Finally, based on the average of the eight pilot market daily trading datasets, the national carbon price is constructed, and a short-term prediction is made. The results show that: (1) the pilot projects in Beijing and Hubei are susceptible to short-term external factors, and Beijing\'s pilot internal market mechanism has a large impact on the carbon price; (2) in most scenarios, the national price fluctuates, with the highest carbon price approaching 70 CNY/tCO2 and the lowest falling below 10 CNY/tCO2; and (3) China\'s carbon price is still has ample room to rise in the future. This paper provides a theoretical basis and practical guidance for the prediction of carbon prices in China.

In this paper, we propose a novel hybrid model that extends prior work involving ensemble empirical mode decomposition (EEMD) by using fuzzy entropy and extreme learning machine (ELM) methods. We demonstrate this 3-stage model by applying it to forecast carbon futures prices which are characterized by chaos and complexity. First, we employ the EEMD method to decompose carbon futures prices into a couple of intrinsic mode functions (IMFs) and one residue. Second, the fuzzy entropy and K-means clustering methods are used to reconstruct the IMFs and the residue to obtain three reconstructed components, specifically a high frequency series, a low frequency series, and a trend series. Third, the ARMA model is implemented for the stationary high and low frequency series, while the extreme learning machine (ELM) model is utilized for the non-stationary trend series. Finally, all the component forecasts are aggregated to form final forecasts of the carbon price for each model. The empirical results show that the proposed reconstruction algorithm can bring more than 40% improvement in prediction accuracy compared to the traditional fine-to-coarse reconstruction algorithm under the same forecasting framework. The hybrid forecasting model proposed in this paper also well captures the direction of the price changes, with strong and robust forecasting ability, which is significantly better than the single forecasting models and the other hybrid forecasting models.

BACKGROUND: Accurate and timely prediction of regional winter wheat maturity date can provide essential information to improve the management of agriculture and avoid declines in the yield and quality of crops. In this paper, we propose the use of an autoregressive moving-average model to predict vegetation indices on 1, 9, and 17 May each year, and applied them to the methods of evaluating crop maturity based on vegetation indices. Growing degree days and a widely applied local empirical method were selected to explore and compare the feasibility of several methods. We analyzed winter wheat harvested from the Guanzhong Plain during 2003-2013 and used leave-one-out cross-validation to compare and verify the performance of the maturity prediction methods.
RESULTS: The results demonstrated that (i) the vegetation index methods and growing degree days methods predicted maturity with higher accuracy than did the widely applied local empirical method, and (ii) the two-step filtering method based on future meteorological data from The Observing System Research and Predictability Experiment Interactive Grand Global Ensemble exhibited the highest prediction accuracy on 1 May and had the lowest error fluctuation range on 17 May.
CONCLUSIONS: These results provide new insights for predicting regional crop maturity, deploying agricultural harvesting equipment in various regions, and avoiding decreases in crop yields caused by adverse weather.

With the development of human motion capture (MoCap) equipment and motion analysis technologies, MoCap systems have been widely applied in many fields, including biomedicine, computer vision, virtual reality, etc. With the rapid increase in MoCap data collection in different scenarios and applications, effective segmentation of MoCap data is becoming a crucial issue for further human motion posture and behavior analysis, which requires both robustness and computation efficiency in the algorithm design. In this paper, we propose an unsupervised segmentation algorithm based on limb-bone partition angle body structural representation and autoregressive moving average (ARMA) model fitting. The collected MoCap data were converted into the angle sequence formed by the human limb-bone partition segment and the central spine segment. The limb angle sequences are matched by the ARMA model, and the segmentation points of the limb angle sequences are distinguished by analyzing the good of fitness of the ARMA model. A medial filtering algorithm is proposed to ensemble the segmentation results from individual limb motion sequences. A set of MoCap measurements were also conducted to evaluate the algorithm including typical body motions collected from subjects of different heights, and were labeled by manual segmentation. The proposed algorithm is compared with the principle component analysis (PCA), K-means clustering algorithm (K-means), and back propagation (BP) neural-network-based segmentation algorithms, which shows higher segmentation accuracy due to a more semantic description of human motions by limb-bone partition angles. The results highlight the efficiency and performance of the proposed algorithm, and reveals the potentials of this segmentation model on analyzing inter- and intra-motion sequence distinguishing.

Salmonella is the primary cause of community-acquired foodborne infections, so its resistance to antimicrobials, such as aminoglycosides, is a public health issue. Of concern, aminoglycoside resistance in Salmonella is increasing rapidly. Here, we performed a retrospective study evaluating the prevalence of Salmonella harboring armA-mediated aminoglycoside resistance in community-acquired infections and in food or environmental sources. The prevalence rates of armA-harboring Salmonella strains were 1.1/1,000 (13/12,095) and 8.7/1,000 (32/3,687) in outpatient and food/environmental isolates, respectively. All the armA-harboring Salmonella strains were resistant to multiple drugs, including fluoroquinolone and/or extended-spectrum cephalosporins, and most (34/45) belonged to serovar Indiana. The armA gene of these strains were all carried on plasmids, which spanned five replicon types with IncHI2 being the dominant plasmid type. All the armA-carrying plasmids were transferable into Escherichia coli and Acinetobacter baumannii recipients. The conjugation experiment results revealed that the armA-harboring S. Indiana strains had a relatively higher ability to acquire armA-carrying plasmids. The low similarity of their pulsed field gel electrophoresis patterns indicates that the armA-harboring Salmonella strains were unlikely to have originated from a single epidemic clone, suggesting broad armA spread. Furthermore, the genetic backgrounds of armA-harboring Salmonella strains isolated from outpatients exhibited higher similarity to those isolated from poultry than to those isolated from swine, suggesting that poultry consumption maybe an infection source. These findings highlight an urgent need to monitor the prevalence and transmission of armA-harboring Salmonella, especially S. Indiana, to better understand the potential public health threat and prevent the further spread of these strains.

Aminoglycosides are important options for treating life-threatening infections. However, high levels of aminoglycoside resistance (HLAR) among Klebsiella pneumoniae isolates have been observed to be increasing frequently. In this study, a total of 292 isolates of the K. pneumoniae complex from a teaching hospital in China were analyzed. Among these isolates, the percentage of HLAR strains was 13.7% (40/292), and 15 aminoglycoside resistance genes were identified among the HLAR strains, with rmtB being the most dominant resistance gene (70%, 28/40). We also described an armA-carrying Klebsiella variicola strain KP2757 that exhibited a high-level resistance to all aminoglycosides tested. Whole-genome sequencing of KP2757 demonstrated that the strain contained one chromosome and three plasmids, with all the aminoglycoside resistance genes (including two copies of armA and six AME genes) being located on a conjugative plasmid, p2757-346, belonging to type IncHI5. Comparative genomic analysis of eight IncHI5 plasmids showed that six of them carried two copies of the intact armA gene in the complete or truncated Tn1548 transposon. To the best of our knowledge, for the first time, we observed that two copies of armA together with six AME genes coexisted on the same plasmid in a strain of K. variicola with HLAR. Comparative genomic analysis of eight armA-carrying IncHI5 plasmids isolated from humans and sediment was performed, suggesting the potential for dissemination of these plasmids among bacteria from different sources. These results demonstrated the necessity of monitoring the prevalence of IncHI5 plasmids to restrict their worldwide dissemination.

UNASSIGNED: The aminoglycosides are widely used for the therapeutic management of infections caused by gram-negative bacteria, including the Acinetobacter baumannii strains. However, the resistance to the members of the aminoglycoside family, such as amikacin, gentamicin, and tobramycin, is increasingly being common among the clinical isolates.
UNASSIGNED: This study aimed to investigate the presence of 16SrRNA methylases and aminoglycoside modifying enzymes (AMEs) genes among aminoglycoside resistant A. baumannii isolates and to study the genetic diversity of the clinical population of A. baumannii in local hospitals.
UNASSIGNED: The 143 A. baumannii clinical strains were analyzed for antimicrobial susceptibility, genetic screening for enzymes conferring aminoglycosides resistance followed by the multilocus sequence typing.
UNASSIGNED: The 133/143 (93%) isolates were non-susceptible to at least one of the tested aminoglycosides, including amikacin, gentamicin, and tobramycin. The MIC distribution has shown that 87.486.7% strains were resistant to amikacin and gentamicin, respectively. The aphA6, aadB, aacC1, and aphA1 were found in 74.1%, 59.4%, 16.1%, and 11.2% isolates, respectively, whereas the armA was found in 28% of the strains having a higher MIC value (MIC; ≥256µg/mL). The MLST data have shown that the ST589 and ST2 were the most common STs and corresponded to 51 (35.7%) and 38 (26.6%) isolates, respectively, and few of the isolates corresponding to these STs were found to harbor the armA gene with a variable genotypic profile for AMEs.
UNASSIGNED: The study has reported the incidence of various enzymes conferring aminoglycoside resistance among the A. baumannii clones for the first time from Pakistan. The findings suggest the possibility of transmission of aminoglycoside resistance determinants through the lateral gene transfer as well as clonal dissemination.