Protein Remote Homology Detection Based on an Ensemble Learning Approach

Protein remote homology detection is one of the central problems in bioinformatics. Although some computational methods have been proposed, the problem is still far from being solved. In this paper, an ensemble classifier for protein remote homology detection, called SVM-Ensemble, was proposed with a weighted voting strategy. SVM-Ensemble combined three basic classifiers based on different feature spaces, including Kmer, ACC, and SC-PseAAC. These features consider the characteristics of proteins from various perspectives, incorporating both the sequence composition and the sequence-order information along the protein sequences. Experimental results on a widely used benchmark dataset showed that the proposed SVM-Ensemble can obviously improve the predictive performance for the protein remote homology detection. Moreover, it achieved the best performance and outperformed other state-of-the-art methods

Haematology specimen acceptability: a national survey in Chinese laboratories

Introduction: Specimen adequacy is a crucial preanalytical factor affecting accuracy and usefulness of test result. The aim of this study was to determine the frequency and reasons for rejected haematology specimens, preanalytical variables which may affect specimen quality, and consequences of rejection, and provide suggestions on monitoring quality indicators as to obtain a quality improvement. Materials and methods: A cross-sectional survey was conducted and a questionnaire was sent to 1586 laboratories. Participants were asked to provide general information about institution and practices on specimen management and record rejections and reasons for rejection from 1st to 31st July. Results: A total survey response rate was 56% (890/1586). Of 10,181,036 tubes received during the data collection period, 11,447 (0.11%) were rejected, and the sigma (σ) was 4.6. The main reason for unacceptable specimens was clotted specimen (57%). Rejected specimens were related to source department, container type, container material type, transportation method and phlebotomy personnel. The recollection of 84% of the rejected specimens was required. The median specimen processing delay in inpatient, outpatient and emergency department were 81.0 minutes, 57.0 minutes and 43.3 minutes, respectively. Conclusions: Overall, rejection rate was a slightly lower than previously published data. In order to achieve a better quality in the preanalytical phase, haematology laboratories in China should pay more attention on training for phlebotomy and sample transportation, identify main reasons for clotted specimen and take effective measures. The platform in the study will be helpful for long-term monitoring, but simplification and modification should be introduced in the following investigation

Breastfeeding rates and growth charts—the Zhejiang infant feeding trial

A randomised control trial was undertaken in Hangzhou, China, to study the influence of the growth chart used on breastfeeding rates. Mothers with infants who were being fully breastfed at 6 weeks after birth (n = 1602) were invited to participate in the trial; 1415 agreed to participate and 1295 completed the study. Two growth charts were used, one that was heavier for the first six months of life (Chart A, n = 686) and a lighter growth chart (Chart B, n = 609). Mothers were interviewed and infants measured at 6 weeks and 3, 4, 5 and 6 months after delivery. At 6 months the full breastfeeding rates were 18.1% in the group using the heavier growth chart compared to 22.8% in the lighter growth chart group. After adjusting for potential confounders this difference remained significant (aOR 1.41, 95% confidence intervals 1.02, 1.93). These results suggest that breastfeeding rates may be influenced by the type of growth chart used. Mothers who perceive that their infants are not growing adequately (i.e., using the heavier charts) may introduce other foods to their infants earlier than mothers using the lighter chart. While a larger trial is required to confirm the results, in the interim it is suggested that if heavier growth charts are used, a lower percentile line could be used to assess adequacy of growth

Anammox in IFAS reactor for reject water treatment

The aim of this study was to evaluate the performance of the integrated fixed-film activated sludge (IFAS) reactor achieving partial nitritation/anammox process to treat reject water after dewatering of digested sludge. During the study period, dissolved oxygen setpoint, aeration mode and inflow loading were changed to evaluate their influence on the process performance and efficiency in the reactor. Four different values for dissolved oxygen setpoint were tested: 2.0 mg/L, 1.8 mg/L, 1.5mg/L and 1.3 mg/L. Three different aeration modes in a one-hour cycle were tested: 30 min, 35 min, 40 min. And two different inflow loadings were tested: 2 g N/m2∙d and 1.6 g N/m2∙d. Discussion and evaluation were based on laboratory analyses and online sensors. The highest achieved total inorganic nitrogen removal efficiency was 85.6%, at 40 min aeration per hour, 2.0 mg/L dissolved oxygen and with 2 g N/m2∙day inflow NH4-N loading. Specific anammox activity (SAA) tests were also done for the anaerobic ammonia oxidizing bacteria in biofilm attached to the carriers in the IFAS reactor, and the results showed that the bacteria could achieve a higher nitrogen removal rate than in the pilot-scale IFAS reactor

Anammox in IFAS reactor for reject water treatment

The aim of this study was to evaluate the performance of the integrated fixed-film activated sludge (IFAS) reactor achieving partial nitritation/anammox process to treat reject water after dewatering of digested sludge. During the study period, dissolved oxygen setpoint, aeration mode and inflow loading were changed to evaluate their influence on the process performance and efficiency in the reactor. Four different values for dissolved oxygen setpoint were tested: 2.0 mg/L, 1.8 mg/L, 1.5mg/L and 1.3 mg/L. Three different aeration modes in a one-hour cycle were tested: 30 min, 35 min, 40 min. And two different inflow loadings were tested: 2 g N/m2∙d and 1.6 g N/m2∙d. Discussion and evaluation were based on laboratory analyses and online sensors. The highest achieved total inorganic nitrogen removal efficiency was 85.6%, at 40 min aeration per hour, 2.0 mg/L dissolved oxygen and with 2 g N/m2∙day inflow NH4-N loading. Specific anammox activity (SAA) tests were also done for the anaerobic ammonia oxidizing bacteria in biofilm attached to the carriers in the IFAS reactor, and the results showed that the bacteria could achieve a higher nitrogen removal rate than in the pilot-scale IFAS reactor

Anammox in IFAS reactor for reject water treatment

The aim of this study was to evaluate the performance of the integrated fixed-film activated sludge (IFAS) reactor achieving partial nitritation/anammox process to treat reject water after dewatering of digested sludge. During the study period, dissolved oxygen setpoint, aeration mode and inflow loading were changed to evaluate their influence on the process performance and efficiency in the reactor. Four different values for dissolved oxygen setpoint were tested: 2.0 mg/L, 1.8 mg/L, 1.5mg/L and 1.3 mg/L. Three different aeration modes in a one-hour cycle were tested: 30 min, 35 min, 40 min. And two different inflow loadings were tested: 2 g N/m2∙d and 1.6 g N/m2∙d. Discussion and evaluation were based on laboratory analyses and online sensors. The highest achieved total inorganic nitrogen removal efficiency was 85.6%, at 40 min aeration per hour, 2.0 mg/L dissolved oxygen and with 2 g N/m2∙day inflow NH4-N loading. Specific anammox activity (SAA) tests were also done for the anaerobic ammonia oxidizing bacteria in biofilm attached to the carriers in the IFAS reactor, and the results showed that the bacteria could achieve a higher nitrogen removal rate than in the pilot-scale IFAS reactor

Protein Remote Homology Detection Based on an Ensemble Learning Approach

Protein remote homology detection is one of the central problems in bioinformatics. Although some computational methods have been proposed, the problem is still far from being solved. In this paper, an ensemble classifier for protein remote homology detection, called SVM-Ensemble, was proposed with a weighted voting strategy. SVM-Ensemble combined three basic classifiers based on different feature spaces, including Kmer, ACC, and SC-PseAAC. These features consider the characteristics of proteins from various perspectives, incorporating both the sequence composition and the sequence-order information along the protein sequences. Experimental results on a widely used benchmark dataset showed that the proposed SVM-Ensemble can obviously improve the predictive performance for the protein remote homology detection. Moreover, it achieved the best performance and outperformed other state-of-the-art methods