Reduced membrane fouling in a novel bio-entrapped membrane reactor for treatment of food and beverage processing wastewater

A novel Bio-Entrapped Membrane Reactor (BEMR) packed with bio-ball carriers was constructed and investigated for organics removal and membrane fouling by soluble microbial products (SMP). An objective was to evaluate the stability of the filtration process in membrane bioreactors through backwashing and chemical cleaning. The novel BEMR was compared to a conventional membrane bioreactor (CMBR) on performance, with both treating identical wastewater from a food and beverage processing plant. The new reactor has a longer sludge retention time (SRT) and lower mixed liquor suspended solids (MLSS) content than does the conventional. Three different hydraulic retention times (HRTs) of 6, 9, and 12 h were studied. The results show faster rise of the transmembrane pressure (TMP) with decreasing hydraulic retention time (HRT) in both reactors, where most significant membrane fouling was associated with high SMP (consisting of carbohydrate and protein) contents that were prevalent at the shortest HRT of 6 h. Membrane fouling was improved in the new reactor, which led to a longer membrane service period with the new reactor. Rapid membrane fouling was attributed to increased production of biomass and SMP, as in the conventional reactor. SMP of 10-100 kDa from both MBRs were predominant with more than 70% of the SMP <100 kDa. Protein was the major component of SMP rather than carbohydrate in both reactors. The new reactor sustained operation at constant permeate flux that required seven times less frequent chemical cleaning than did the conventional reactor. The new BEMR offers effective organics removal while reducing membrane fouling.     

Assembly of Fully Substituted 2H-Indazoles Catalyzed by Cu2O Rhombic Dodecahedra and Evaluation of Anticancer Activity

Simultaneous C−N, and N−N bond-forming methods for one-pot transformations are highly challenging in synthetic organic chemistry. In this study, the Cu₂O rhombic dodecahedra-catalyzed synthesis of 2H-indazoles is demonstrated with good to excellent yields from readily available chemicals. This one-pot procedure involves Cu₂O nanoparticle-catalyzed consecutive C−N, and N−N bond formation followed by cyclization to yield 2H-indazoles with broad substrate scope and high functional group tolerance. Various cell-based bioassay studies demonstrated that 2H-indazoles inhibit the growth of cancer cells, typically through induction of apoptosis in a dose-dependent manner. Moreover, 2H-indazoles tested in the MDA-MB-468 cell line were capable of inhibiting cancer cell migration and invasion. Thus, it is shown that 2H-indazoles have potent in vitro anticancer activity that warrant further investigation of this compound class.     

Controlling Plasmon‐Enhanced Fluorescence via Intersystem Crossing in Photoswitchable Molecules

By harnessing photoswitchable intersystem crossing (ISC) in spiropyran (SP) molecules, active control of plasmon‐enhanced fluorescence in the hybrid systems of SP molecules and plasmonic nanostructures is achieved. Specifically, SP‐derived merocyanine (MC) molecules formed by photochemical ring‐opening reaction display efficient ISC due to their zwitterionic character. In contrast, ISC in quinoidal MC molecules formed by thermal ring‐opening reaction is negligible. The high ISC rate can improve fluorescence quantum yield of the plasmon‐modified spontaneous emission, only when the plasmonic electromagnetic field enhancement is sufficiently high. Along this line, extensive photomodulation of fluorescence is demonstrated by switching the ISC in MC molecules at Au nanoparticle aggregates, where strongly enhanced plasmonic hot spots exist. The ISC‐mediated plasmon‐enhanced fluorescence represents a new approach toward controlling the spontaneous emission of fluorophores near plasmonic nanostructures, which expands the applications of active molecular plasmonics in information processing, biosensing, and bioimaging.     

Design and applications of lattice plasmon resonances

With their unique optical properties associated with the excitation of surface plasmons, metal nanoparticles (NPs) have been used in optical sensors and devices. The organization of these NPs into arrays can induce coupling effects to engineer new optical responses. In particular, lattice plasmon resonances (LPRs), which arise from coherent interactions and coupling among NPs in periodic arrays, have shown great promise for realizing narrow linewidths, angle-dependent dispersions, and high wavelength tunability of optical spectra. By engineering the materials, shapes, sizes, and spatial arrangements of NPs within arrays, one can tune the LPR-based spectral responses and electromagnetic field distributions to deliver a multitude of improvements, including a high figure-of-merit, superior light–matter interaction, and multiband operation. In this review, we discuss recent progress in designing and applying new metal nanostructures for LPR-based applications. We conclude this review with our perspective on the future opportunities and challenges of LPR-based devices.

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A learning theory approach to system identification and stochastic adaptive control

In this paper, we present an approach to system identification based on viewing identification as a problem in statistical learning theory. Apparently, this approach was first mooted in [E. Weyer, R.C. Williamson, I. Mareels, Sample complexity of least squares identification of FIR models, in: Proceedings of the 13th World Congress of IFAC, San Francisco, CA, July 1996, pp. 239–244]. The main motivation for initiating such a program is that traditionally system identification theory provide asymptotic results. In contrast, statistical learning theory is devoted to the derivation of finite-time estimates. If system identification is to be combined with robust control theory to develop a sound theory of indirect adaptive control, it is essential to have finite-time estimates of the sort provided by statistical learning theory. As an illustration of the approach, a result is derived showing that in the case of systems with fading memory, it is possible to combine standard results in statistical learning theory (suitably modified to the present situation) with some fading memory arguments to obtain finite-time estimates of the desired kind. It is also shown that the time series generated by a large class of BIBO stable nonlinear systems has a property known as β-mixing. As a result, earlier results of [E. Weyer, Finite sample properties of system identification of ARX models under mixing conditions, Automatica, 36 (9) (2000) 1291–1299] can be applied to many more situations than shown in that paper.     

On the Markov Chain Monte Carlo (MCMC) method

Markov Chain Monte Carlo (MCMC) is a popular method used to generate samples from arbitrary distributions, which may be specified indirectly. In this article, we give an introduction to this method along with some examples.     

Effects of mass retention of dissolved organic matter and membrane pore size on membrane fouling and flux decline

Ultrafiltration (UF) fouling has been attributed to concentration polarization, gel layer formation as well as outer and inner membrane pore clogging. It is believed that mass of humic materials either retained on membrane surface or associated with membrane inner pore surface is the primary cause for permeate flux decline and filtration resistance build-up in water supply industries. While biofilm/biofouling and inorganic matter could also be contributing factors for permeability decline in wastewater treatment practices. The present study relates UF fouling to mass of dissolved organic matter (DOM) retained on membrane and quantifies the effect of retained DOM mass on filtration flux decline. The results demonstrate that larger pore membranes exhibit significant flux decline in comparison with the smaller ones. During a 24-h period, dissolved organic carbon mass retained in 10 kDa membranes was about 1.0 g m⁻² and that in 100 kDa membranes was more than 3 times higher (3.6 g m⁻²). The accumulation of retained DOM mass significantly affects permeate flux. It is highly likely that some DOMs bind or aggregate together to form surface gel layer in the smaller 10 kDa UF system; those DOMs largely present in inner pore and serving as pore blockage on a loose membrane (100 kDa) are responsible for severe flux decline.