Integrative Analysis of Metabolomic,Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs

The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein “phosphoglycerate mutase 2” and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes.     

Effects of premixed diethyl ether (DEE) on combustion and exhaust emissions in a HCCI-DI diesel engine

In this study, the effects of premixed ratio of diethyl ether (DEE) on the combustion and exhaust emissions of a single-cylinder, HCCI-DI engine were investigated. The experiments were performed at the engine speed of 2200 rpm and 19 N m operating conditions. The amount of the premixed DEE was controlled by a programmable electronic control unit (ECU) and the DEE injection was conducted into the intake air charge using low pressure injector. The premixed fuel ratio (PFR) of DEE was changed from 0% to 40% and results were compared to neat diesel operation. The percentages of premixed fuel were calculated from the energy ratio of premixed DEE fuel to total energy rate of the fuels. The experimental results show that single stage ignition was found with the addition of premixed DEE fuel. Increasing and phasing in-cylinder pressure and heat release were observed in the premixed stage of the combustion. Lower diffusion combustion was also occurred. Cycle-to cycle variations were very small with diesel fuel and 10% DEE premixed fuel ratio. Audible knocking occurred with 40% DEE premixed fuel ratio. NO_x-soot trade-off characteristics were changed and improvements were found simultaneously. NO_x and soot emissions decreased up to 19.4% and 76.1%, respectively, while exhaust gas temperature decreased by 23.8%. On the other hand, CO and HC emissions increased.     

Hybrid anion exchanger for trace phosphate removal from water and wastewater

Throughout recent decades, the wastewater treatment industry has identified the discharge of nutrients, including phosphates and nitrates, into waterways as a risk to natural environments due to the serious effects of eutrophication. For this reason, new tertiary treatment processes have abounded; these processes generally utilize physico-chemical and biological methods to remove nutrients from secondary wastewaters. The disadvantages of such methods involve larger reactor volumes, operating costs, and waste sludge production; furthermore, complete nutrient removal is unattainable due to thermodynamic and kinetic limitations. The subject study presents the development and performance of a new phosphate-selective sorbent, referred to as hybrid anion exchanger or HAIX. HAIX combines durability and mechanical strength of polymeric anion exchange resins with high sorption affinity of hydrated ferric oxide (HFO) toward phosphate. HAIX is essentially a polymeric anion exchanger within which HFO nanoparticles have been dispersed irreversibly. Laboratory studies show that HAIX selectively removes phosphate from the background of much higher concentrations of competing sulfate, chloride and bicarbonate anions due to the combined presence of Coulombic and Lewis acid-base interactions. Experimental results demonstrate that HAIX's phosphate-sulfate separation factor is over two orders of magnitude greater than that of currently available commercial ion exchange resins. Additionally, optimal HAIX performance occurs at typical secondary wastewater pH conditions i.e., around 7.5. HAIX is amenable to efficient regeneration and reuse with no noticeable loss in capacity.     

An intelligent system for multivariate statistical process monitoring and diagnosis

A knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real-time KBS consists of a supervisory system using G2 KBS development software linked with external statistical modules for system identification and sensor fault diagnosis. The various statistical techniques were prototyped in MATLAB, converted to ANSI C code, and linked with the G2 Standard Interface. The KBS automatically performs all operations of data collection, identification, monitoring, and sensor fault diagnosis with little or no input from the user. Navigation throughout the KBS is via menu buttons on each user-accessible screen. Selected process variables are displayed on charts showing the history of the variables over a period of time. Multivariate statistical tests and contribution plots are also shown graphically. The KBS was evaluated using simulation studies with a polymerization reactor through a nonlinear dynamic model. Both normal operation conditions as well as conditions of process disturbances were observed to evaluate the KBS performance. Specific user-defined disturbances were added to the simulation, and the KBS correctly diagnosed both process and sensor faults when present.     

New classification techniques for electroencephalogram (EEG) signals and a real-time EEG control of a robot

This paper studies the state-of-the-art classification techniques for electroencephalogram (EEG) signals. Fuzzy Functions Support Vector Classifier, Improved Fuzzy Functions Support Vector Classifier and a novel technique that has been designed by utilizing Particle Swarm Optimization and Radial Basis Function Networks (PSO-RBFN) have been studied. The classification performances of the techniques are compared on standard EEG datasets that are publicly available and used by brain–computer interface (BCI) researchers. In addition to the standard EEG datasets, the proposed classifier is also tested on non-EEG datasets for thorough comparison. Within the scope of this study, several data clustering algorithms such as Fuzzy C-means, K-means and PSO clustering algorithms are studied and their clustering performances on the same datasets are compared. The results show that PSO-RBFN might reach the classification performance of state-of-the art classifiers and might be a better alternative technique in the classification of EEG signals for real-time application. This has been demonstrated by implementing the proposed classifier in a real-time BCI application for a mobile robot control.     

Microstructure and densification of ZrB2–SiC composites prepared by spark plasma sintering

ZrB₂–SiC composites were prepared by spark plasma sintering (SPS) at temperatures of 1800–2100 °C for 180–300 s under a pressure of 20 MPa and at higher temperatures of above 2100 °C without a holding time under 10 MPa. Densification, microstructure and mechanical properties of ZrB₂–SiC composites were investigated. Fully dense ZrB₂–SiC composites containing 20–60 mass% SiC with a relative density of more than 99% were obtained at 2000 and 2100 °C for 180 s. Below 2120 °C, microstructures consisted of equiaxed ZrB₂ grains with a size of 2–5 μm and α-SiC grains with a size of 2–4 μm. Morphological change from equiaxed to elongated α-SiC grains was observed at higher temperatures. Vickers hardness of ZrB₂–SiC composites increased with increasing sintering temperature and SiC content up to 60 mass%, and ZrB₂–SiC composite containing 60 mass% SiC sintered at 2100 °C for 180 s had the highest value of 26.8 GPa. The highest fracture toughness was observed for ZrB₂–SiC composites containing 50 mass% SiC independent of sintering temperatures.     

Rock salt dilatancy boundary from combined acoustic emission and triaxial compression tests

This paper presents an experimental investigation of rock salt dilatancy boundary based on combined acoustic emission and triaxial compression tests carried out on the rock salt samples from the Asse Salt Mine, Germany. The experimental results were evaluated to determine the dilatancy boundary under specified stress, stress loading rate and pore pressure. Pore volume changes caused by deviatoric stresses were measured during triaxial compression tests. The dilatancy boundary was then determined from the maximum compression on a stress–strain curve which separates the compression and dilatancy regions. Variations in acoustic emissions that occur during microcrack development under triaxial compression were recorded with ten sensors mounted on the outer surface of the cylindrical samples. A spontaneous increase observed in the cumulative number of acoustic events is consistent with the dilatancy boundary determined from the minimum pore volume. It is confirmed that the dilatancy boundary depends on both stress loading rate and pore pressure. The dilatancy boundary slightly decreases with increasing the loading rate, but increases with increasing the minor normal stress. High pore pressures accelerate the dilatancy. A Biot coefficient of 0.25 for Asse rock salt was determined from the dilatancy boundary. An analysis of two-dimensional (2D) fractal dimensions determined for several samples shows that the samples with smaller dimensions have slightly higher dilatancy boundaries. The dilatancy boundary values of Asse rock salt are lower than those reported for crystalline rocks, although both rock types show similar dilatancy behaviour.     

DYNAMIC BEHAVIOR OF PERIODIC FEEDBACK CONTROL SYSTEMS

Periodic feedback is a control strategy implemented by fast zero-average oscillations in the parameters of the control law. It is well known that time invariant feedback control offers no means for zeros relocation. Periodic feedback allows zeros relocation in an asymptotic sense, resulting in improved closed loop characteristics, such as increased gain margins.     

Association of PPARGC1A and CAPNS1 gene polymorphisms and expression with meat quality traits in pigs

This study aimed to investigate the genes PPARGC1A (peroxisome proliferator-activated receptor gamma-coactivator 1A) and CAPNS1 (calpain small subunit 1) as candidate genes affecting meat quality traits in pigs. Four polymorphisms were identified in PPARCG1A and three in CAPNS1. The PPARGC1A polymorphism c.1288T>A was associated with pH and cooking loss in a F2 Duroc×Pietrain experimental cross (DuPi, n=313) and with pH values in Italian Large White (ILW, n=380) and Italian Landrace (ILA, n=158) populations (P<0.05). The CAPNS1 polymorphism c.429A>C was associated with pH and conductivity in DuPi and with meat color in ILA (P<0.05). PPARGC1A mRNA expression associated with drip loss (P<0.01) and the same tendency was found for CAPNS1 (P=0.06). The promoter methylation profiling suggested that methylation is not involved in CAPNS1 expression regulation. In conclusion, porcine PPARGC1A and CAPNS1 genes may affect meat quality traits, with breed-specific differences, and they could be used as markers for the improvement of meat quality in pigs.