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The characterization of bacteria with hydrolytic potential significantly contributes to the industries. Six cellulose-degrading bacteria were isolated from mixture soil samples collected at Kingfisher Lake and the University of Manitoba campus by Congo red method using carboxymethyl cellulose agar medium and identified as Paenarthrobacter sp. MKAL1, Hymenobacter sp. MKAL2, Mycobacterium sp. MKAL3, Stenotrophomonas sp. MKAL4, Chryseobacterium sp. MKAL5, and Bacillus sp. MKAL6. Their cellulase production was optimized by controlling different environmental and nutritional factors such as pH, temperature, incubation period, substrate concentration, nitrogen, and carbon sources using the dinitrosalicylic acid and response surface methods. Except for Paenarthrobacter sp. MKAL1, all strains are motile. Only Bacillus sp. MKAL6 was non-salt-tolerant and showed gelatinase activity. Sucrose enhanced higher cellulase activity of 78.87 ± 4.71 to 190.30 ± 6.42 U/mL in these strains at their optimum pH (5-6) and temperature (35-40 °C). The molecular weights of these cellulases were about 25 kDa. These bacterial strains could be promising biocatalysts for converting cellulose into glucose for industrial purposes.

Soil bacteria participate in self-immobilization processes for survival, persistence and producing virulence factors in some niches or hosts through their capacities of autoaggregation, cell surface hydrophobicity, biofilm formation, and antibiotic and heavy metal resistance. This study investigated potential virulence, antibiotics and heavy metals resistance, solvent adhesion, and biofilm-forming capabilities of six cellulolytic bacteria isolated from soil samples: Paenarthrobacter sp. MKAL1, Hymenobacter sp. MKAL2, Mycobacterium sp. MKAL3, Stenotrophomonas sp. MKAL4, Chryseobacterium sp. MKAL5 and Bacillus sp. MKAL6. Strains were subjected to phenotypic methods, including heavy metal and antibiotic susceptibility and virulence factors (protease, lipase, capsule production, autoaggregation, hydrophobicity and biofilm formation). The effect of ciprofloxacin was also investigated on bacterial susceptibility over time, cell membrane and biofilm formation. Strains MKAL2, MKAL5 and MKAL6 exhibited protease and lipase activities, while only MKAL6 produced capsules. All strains were capable of aggregating, forming biofilm and adhering to solvents. Strains tolerated high amounts of chromium, lead, zinc, nickel and manganese and were resistant to lincomycin. Ciprofloxacin exhibited bactericidal activity against these strains. Although the phenotypic evaluation of virulence factors of bacteria can indicate their pathogenic nature, an in-depth genetic study of virulence, antibiotic and heavy metal resistance genes is required.

The cultural parameters of Streptomyces sp. for pectinase production were optimized using the Box-Behnken design. The maximum pectinase production was obtained after 58 hours at 35℃ and pH 7 upon submerged fermentation in yeast extract-containing media. The enzymes were partially purified with acetone precipitation and the analysis by SDS-PAGE and zymogram revealed that Streptomyces sp. produced two pectinases with molecular weights of about 25 and 75 kDa. The pectinase activity was detected in a wide range of temperatures (30℃ to 80℃) and pH (3 to 9) with maximum pectinase activities observed at 70℃ and pHs 5 and 9. The enzymes retained about 30 to 40% of their activities even after incubating the enzyme at different temperatures for 120 mins. The pectinase activities of Streptomyces sp. were enhanced in the media containing 1.5% pectin, 1% casein as a nitrogen source, 0.5 mM MgSO4, and 5 mM NaCl. Further, the addition of Tween-20, amino acids, and vitamins to the media also enhanced the pectinase activity. Moreover, the bacterium illustrated the ability to decolorize crystal violet dye efficiently. The decolorization rate ranged from 39.29 to 53.75% showing the highest bacterial decolorization in the media containing 2mg/mL crystal violet at 144 hours. Therefore, the bacterium has the potential in treating wastewater produced by industries like textile industries.

Pleurochrysis genus algae are widely distributed in ocean waters. Pleurochrysis sp. algae are popularly known for its coccolithophores. Calcium carbonate (CaCO3) shells are major components of the coccolithophore, and they are key absorbers of carbondioxide. In this study, we have reported the effects of potassium nitrate (KNO3) concentration on calcium accumulation and total lipid, carbohydrate and protein contents of Pleurochrysis dentata. Results obtained from complexometric titration and scanning electron microscopy analysis showed higher rates of CaCO3 accumulation on Pleurochrysis dentata cell surface. We have also observed that overall cell size of Pleurochrysis dentata reached maximum when it was cultured at 0.75 mmol L-1 of KNO3. During 10 days of Pleurochrysis dentata culture total lipids and carbohydrate contents decreased, with slightly increased protein content. Results obtained from Fourier-Transform Infrared Spectroscopy (FTIR) also reported an increase in protein and decrease in lipids and carbohydrate contents, respectively. Similarly, Pleurochrysis dentata cultured at 1 mmol L-1 concentration of KNO3 exhibited the lowest carbohydrate (21.08%) and highest protein (32.87%) contents. Interestingly, Pleurochrysis dentata cultured without KNO3 exhibited 33.61% of total lipid content which reduced to a total lipid content of 13.67% when cultured at 1 mmol L-1 concentration of KNO3. Thus, culture medium containing higher than 1 mmol L-1 of KNO3 could inhibit the cell size of Pleurochrysis dentata and CaCO3 accumulation in shells but it could promote its cell growth. For the first time we have reported a relatively complete coccolith structure devoid of its protoplast. In this study, we have also described about the special planar structure of Pleurochrysis dentata CaCO3 shells present on its inner tube of the R unit and parallel to the outer tube of the V unit which we named it as "doornail structure". We believe that this doornail structure provides structural stability and support to the developing coccoliths in Pleurochrysis dentata. Also, we have discussed about the "double-disc" structure of coccoliths which are closely arranged and interlocked with each other. The double-disc structure ensures fixation of each coccolith and objecting its free horizontal movement and helps in attaining a complementary coccolith structure.

Peracetic-acid-based advanced oxidation processes (PAA-AOPs) on metal-free catalysts have emerged as charming strategies for water contaminant removal. However, the involved reactive species and their corresponding active sites are ambiguous. Herein, using carbon nanotube (CNT) as a model carbocatalyst, we demonstrated that, under neutral conditions, the CNT-PAA* complex was the dominant reactive species to oxidize phenolic compounds via electron-transfer process (ETP), whereas the surface-bound hydroxyl radicals (

The biological pretreatment for the enzymatic hydrolysis of lignocellulosic biomasses largely depends on an effective pretreatment process. A significant enhancement of enzymatic saccharification was obtained with corn stover using Bacillus sp. P3. The hemicellulose removal from corn stover by the strain Bacillus sp. P3 was evaluated for enhancing subsequent enzymatic hydrolysis. Therefore, our study revealed that an alkaline resistant xylanase produced by Bacillus sp. P3 in fermentation broth led to a substantially enhanced hemicellulose removal rate from corn stover within pH 9.36–9.68. However, after 20 d pretreatment of corn stover by the strain P3, the glucan content was increased by 51% and the xylan content was decreased by 35%. After 72 h of saccharification using 20 U g− 1 of commercial cellulase, the yield of reducing sugar released from 20 d pretreated corn stover was increased by 56% in comparison to the untreated corn stover. Therefore, the use of the strain P3 could be a promising approach to pretreat corn stover for enhancing the enzymatic hydrolysis process of industrial bioenergy productions.

To find a multifunctional lignocellulolytic enzyme-producing strain, ten bacterial isolates from paper mill wastewater were tested for their carboxymethyl cellulose (CMC) hydrolytic ability. Bacillus sp. TPF-1, which exhibits the highest hydrolytic ability, was selected to produce lignocellulolytic enzymes using various biomass types as carbon sources. The highest CMCase (9.12 U/mL) and xylanase (102.55 U/mL) activities were obtained by green algae, and the maximum laccase activity (7037.28 U/L) was induced by Sargassum fusiforme. CMCase and xylanase showed the highest activities at 55 and 50 °C, respectively, with the same optimum pH of 5.4. The laccase exhibited optimum temperature of 40 °C and retained 60% more activity at 80 °C in extreme acid conditions (pH 2.2). To explore the multiple applications of these enzymes, crude enzymes induced by green algae were used to saccharify untreated algae. The reducing sugar produced by crude enzymes and commercial cellulase was 23 and 14% higher than that of the control, respectively, and it was 48% higher using crude enzymes with commercial cellulase (72 h). Additionally, the laccase induced by S. fusiforme was tested to decolorize two chemical dyes under an acidic condition (pH 2.2). The highest decolorization rates were 56.13 and 62.14% for Coomassie brilliant blue R-250 and Congo Red, respectively, in the presence of hydroxybenzotriazole monohydrate.

Summary Biomass recalcitrance is still a main challenge for the production of biofuels and high‐value products. Here, an alternative Miscanthus pretreatment method by using lignin‐degrading bacteria was developed. Six efficient Miscanthus‐degrading bacteria were first cultured to produce laccase by using 0.5% Miscanthus biomass as carbon source. After 1–5 days of incubation, the maximum laccase activities induced by Miscanthus in the six strains were ranged from 103 to 8091 U l−1. Then, the crude enzymes were directly diluted by equal volumes of citrate buffer and added Miscanthus biomass to a solid concentration at 4% (w/v). The results showed that all bacterial pretreatments significantly decreased the lignin content, especially in the presence of two laccase mediators (ABTS and HBT). The lignin removal directly correlated with increases in total sugar and glucose yields after enzymatic hydrolysis. When ABTS was used as a mediator, the best lignin‐degrading bacteria (Pseudomonas sp. AS1) can remove up to 50.1% lignin of Miscanthus by obtaining 2.2‐fold glucose yield, compared with that of untreated biomass. Therefore, this study provided an effective Miscanthus pretreatment method by using lignin‐degrading bacteria, which may be potentially used in improving enzymatic hydrolysability of biomass.

With the rapid urbanization, the transportation system, especially the bus system, plays an increasingly prominent role in city planning. However, the current bus evaluation model usually focuses on just one aspect either spatial or temporal. Inspired by “Pulsation Analysis”, this study presents a new approach for evaluating Service Level of Bus as well as Demand for Public Transport based on both spatial and temporal aspects of the bus trips, called “Public Transit Pulsation Analysis”. The transport pulsation assessment model which assesses the supply side and the demand of community for bus model which calculates the demand side, are combined to optimize the bus frequency settings in this approach. The proposed method is tested on a real case study in Tianjin, China, which implies its usefulness in evaluating the service level and improving the service quality of the bus system by 17.6%. As well as developing a bus frequency optimization model, this study also demonstrates its real-world application of “Pulsation Analysis” for decision-making in city planning.

Human Action Recognition is becoming more and more important in many fields, especially in sports. However, conventional algorithm are almost camera-based methods, which make it cumbersome and expensive. As the wearable inertial sensor has developed a lot, in this paper, we present a novel human action classification algorithm using in basketball, based on a single inertial sensor, which is a application of multi-label classification. We performed experiment on real world datasets. The AUPRC, AUROC and confusion matrix of our results demonstrated that our novel basketball motion recognizer have a great performance.

A reliable and robust zero velocity points (ZVPs) detection approach is important to restrain the accumulative error in the pedestrian inertial navigation systems. A novel recursive zero-velocity detection (RZVD) approach for smartphone based pedestrian dead reckoning systems is proposed in this paper. It combined the adaptive threshold and context information of the vertical velocity to verify the correctness of ZVP detection and fixed the incorrect ZVPs recursively. The test results show that the performance of the proposed approach is better than original method. It indicates that the proposed approach is helpful to eliminate the serious estimation error caused by false detection of ZVPs.

Compressive sampling is a promising solution to reduce required sampling rates for signal reconstruction. In many scenarios, such as cognitive radio and modulation recognition, there are only expecting to acquire useful features rather than original signals. To reconstruct these features from compressive measurements, Compressive Sensing (CS) requires features to be sparse and have a one-dimensional relationship with those measurements. Since most of features are nonlinearly transformed from signals, selecting one with high sparsity and then building a linear mapping between it and measurements become the main challenges. This work proposed a new method to find sparsity representations for signals based on their intra-structure. With this method, two common features, autocorrelation function and fourth order time-varying moment are respectively expressed as another two sparse representations called structure-based sparsity representations. Simulation shows that these representations can work effectively in reducing reconstruction iterations, computing consumption, and memory cost for sensing matrices.

In this study an effective bacterial pretreatment method was developed to improve digestibility of Miscanthus. Seven new bacterial isolates, which showed excellent xylanase production ability using Miscanthus as carbon source, were used to perform the pretreatment experiments. After pretreatment, the hemicellulose content and crystallinity index of Miscanthus were decreased, while the reducing sugars released from Miscanthus were significantly increased by 30.8-87.8% after enzymatic hydrolysis. Bacillus sp. G0 was selected to optimize the pretreatment parameters via response surface methodology due to its high reducing sugars released from Miscanthus. According to the optimal model, the pretreatment parameters were set as citrate buffer/G0 fermentation broth ratio at 0.34, pretreatment time at 100h and Tween-20 concentration at 1.73%. The reducing sugars released from Miscanthus pretreated by optimal parameters were 305mgg-1 dry biomass. The results suggested our bacterial pretreatment approaches have great potential to increase digestibility of bioenergy crops.

Compressive sensing can be applied to reconstruct the signal with far fewer measurements than what is usually considered necessary. While in many scenarios, such as spectrum detection and modulation recognition, we only expect to acquire useful characteristics rather than the original signals. In this paper, we propose an effective method of digital communication signal detection based on the sub-Nyquist cyclic feature without the introduction of the reconstruction algorithm. By analyzing the difference between matrixes of cyclic autocorrelation for the two sceneries, it can be determined whether there exists signal or not. The simulation results show that the method performs well even at a low signal-to-noise ratio such as −10 dB, and complexity of both time and space is lowered considerably.

Compressive Sensing (CS) enables us to take few measurements of a signal than that Shannon-Nyquist sampling requires if it has a spare representation in a certain basis. However if the signal is contaminated with noise and interference, the reconstruction performance may be poor due to the existence of noise and interference. In this paper, using prior statistical character, we construct a linear operator H which can filter out the noise in compressed domain, then use the filtered signal for reconstruction. Simulation results demonstrate this modified method still holds sufficient information on the desirable signal and it can achieve better recovery performance than the method which first reconstructs the signal and then processes the recovered signal with prior information.

In recent years,to meet the challenge of spectrum sensing with ultra wide band and big data in cooperative and cognitive radio networks,the theory of compressed sensing is introduced in,which can solve the problem of high sampling rate requirement due to Shannon-Nyquist sampling theory. In this paper,considering the property of signals’ cyclostationarity, we innovatively propose a method in OFDM signal detection using sub-Nyquist samples. By doing sparsity analysis combined with detection necessities,we present a partial-scale reconstruction method to reduce the recovery iteration and lower the algorithm complexity. Furthermore,we find out an equivalent cyclic cumulant calculation method for OFDM signals to simplify the calculation and lower the high memory consumption during signal processing. From the simulations we can see the optimized method introduced in effectively eliminates the constraints for compressed detection of OFDM signals and possesses a far-reaching significance in further researches and applications.