A New Blind Source Separation Algorithm Framework for Noisy Mixing Model Based on the Energy Concentration Characteristic in Signal Transform Domain

Blind source separation is a widely used technique to analyze multichannel data. In most real-world applications, noise is inevitable and will affect the quality of signal separation and even make signal separation failure. In this paper, a new signal processing framework is proposed to separate noisy mixing sources. It is composed of two different stages. The first step is to process the mixing signal by a certain signal transform method to make the expected signals have energy concentration characteristics in the transform domain. The second stage is formed by a certain BSS algorithm estimating the demixing matrix in the transform domain. In the energy concentration segment, the SNR can reach a high level so that the demixing matrix can be estimated accurately. The analysis process of the proposed algorithm framework is analyzed by taking the wavelet transform as an example. Numerical experiments demonstrate the efficiency of the proposed algorithm to estimate the mixing matrix in comparison with well-known algorithms.

A distinct growth physiology enhances bacterial growth under rapid nutrient fluctuations

It has long been known that bacteria coordinate their physiology with their nutrient environment, yet our current understanding offers little intuition for how bacteria respond to the second-to-minute scale fluctuations in nutrient concentration characteristic of many microbial habitats. To investigate the effects of rapid nutrient fluctuations on bacterial growth, we couple custom microfluidics with single-cell microscopy to quantify the growth rate of E. coli experiencing 30 s to 60 min nutrient fluctuations. Compared to steady environments of equal average concentration, fluctuating environments reduce growth rate by up to 50%. However, measured reductions in growth rate are only 38% of the growth loss predicted from single nutrient shifts. This enhancement derives from the distinct growth response of cells grown in environments that fluctuate rather than shift once. We report an unexpected physiology adapted for growth in nutrient fluctuations and implicate nutrient timescale as a critical environmental parameter beyond nutrient identity and concentration.

The Impact of Antimicrobial Substances on the Methanogenic Community during Methane Fermentation of Sewage Sludge and Cattle Slurry

This study showed the effect of amoxicillin (AMO), and oxytetracycline (OXY) at a concentration of 512 µg mL−1, and sulfamethoxazole (SMX), and metronidazole (MET) at a concentration of 1024 µg mL−1 on the efficiency of anaerobic digestion (AD) of sewage sludge (SS) and cattle slurry (CS). The production of biogas and methane (CH4) content, and the concentration of volatile fatty acids (VFAs) was analyzed in this study. Other determinations included the concentration of the mcrA gene, which catalyzes the methanogenesis, and analysis of MSC and MST gene concentration, characteristic of the families Methanosarcinaceae and Methanosaetaceae (Archaea). Both substrates differed in the composition of microbial communities, and in the sensitivity of these microorganisms to particular antimicrobial substances. Metronidazole inhibited SS fermentation to the greatest extent (sixfold decrease in biogas production and over 50% decrease in the content of CH4). The lowest concentrations of the mcrA gene (106 gD−1) were observed in CS and SS digestates with MET. A decline in the number of copies of the MSC and MST genes was noted in most of the digestate samples with antimicrobials supplementation. Due to selective pressure, antimicrobials led to a considerably lowered efficiency of the AD process and induced changes in the structure of methanogenic biodiversity.

A distinct growth physiology enhances bacterial growth under rapid nutrient fluctuations

It has been long known that bacteria coordinate their physiology with environmental nutrient, yet our current understanding offers little intuition for how bacteria respond to the second-to-minute scale fluctuations in nutrient concentration characteristic of many microbial habitats. To investigate the effects of rapid nutrient fluctuations on bacterial growth, we coupled custom microfluidics with single-cell microscopy to quantify the growth rate of E. coli experiencing 30 s to 60 min nutrient fluctuations. Compared to steady environments of equal average concentration, fluctuating environments reduced growth rate by up to 50%. However, measured reductions in growth rate were only 38% of the growth loss predicted from single nutrient shifts — an enhancement produced by the distinct growth response of cells grown in environments that fluctuate rather than shift once. We report an unexpected physiology adapted for growth in nutrient fluctuations and implicate nutrient timescale as a critical environmental parameter beyond nutrient concentration and source.

HEAVY METALS IN MILK INFANT FORMULAS

Baby food can contain harmful components that are very dangerous to little consumers. One of the most common harmful factors is heavy metals, in particular lead. It is known that introducing one extra microelement into the body changes not only the concentration of this element, but also the concentration of other elements. Disturbing the physiological balance of microelements leads to changes in complex enzymatic processes, which in turn violates the structure of tissue cells of individual organs. Studies by Russian scientists (T. Suldina and others) have determined, in milk for newborns, the maximum levels of lead (0.02 mg/kg), of cadmium (0.02 mg/kg), of arsenic (0.05 mg/kg). While studying certain samples of baby food, the method for determining the content of lead and other heavy metals was improved. Depending on the lead concentration, characteristic lines of both the ultraviolet and the visible spectral regions can be used. Monitoring heavy metals in infant milk has shown that lead, copper, and zinc are the main contaminants of the product. The concentration of toxic agents in baby milk depends on the type of raw materials and on the environmental conditions of their manufacture. To detect lead in products quickly and accurately, a method was used based on the emission spectral analysis. To this end, spectrographs ISP-28 and ISP-30 widely employed in industry and laboratory studies were taken, but the detection limits were lowered compared to those in the methods that had been used previously. Besides, the field-proven method for determining lead is applicable to detecting zinc and copper, too. An excess of lead by 0.08 mg/kg, copper by 0.07 mg/kg, zinc by 0.45 mg/kg was observed in the baby milk “Malyatko Premium 2.” In the milk “Bellakt 2,” the excessive amount of copper was 0.05 mg/kg, of zinc 0.20 mg/kg, of lead 0.05 mg/kg. In the baby milk “Nitricia Malyuk Istrynsky,” only zinc was found to exceed the normal level (by 0.1 mg/kg). The baby milks “Nutricia Milupa 2,” “Nestle Nestogen 2,” “HiPP Organic 2” do not contain excessive heavy metals, and thus, can be recommended as safe for consumption.

Light-Concentration Characteristic of Water Lens and its Application to Thermoelectric Generation

A water lens was used to concentrate sunlight on the surface of a thermoelectric (TE) module in order to heat it. The shape of this water lens could be flexibly adjusted to compensate for solar altitude changes. The light condensed by the water lens produced a large energy distribution on the top of the module. In this study, we simulated the power generation properties when the top of the module was heated by light with a certain condensing distribution. The simulation results revealed that the energy distribution had little effect on the TE generation if the solar light was effectively condensed on a plate with a condensing width of a few millimeters.

Study on Concentration Characteristics of TSP, PM10 and PM2.5 in Harbin

In order to investigate the concentration characteristic of atmospheric particles, TSP, PM10 and PM2.5 were collected in July 2008 to June 2010. This study investigates the mass concentration of atmospheric particles in each month. The results show the three particle concentrations reached the lowest value in July, while the peak in January. Compared with the national secondary standard, TSP and PM10 were exceeded in January, February, March, April, November, and December and PM2.5 concentrations is above 2 to 8 times of the EU standard (15 μg/m3). Fine particles (PM2.5) and coarse particles (PM2. 5-10) are major component of atmospheric particles. The mass concentration of atmospheric particles on day is higher than at night in major months and lower in May and June. However, it is not obvious in July, August and September.