Tolerance,Adaptation, and Cell Response Elicited by Micromonospora sp. Facing Tellurite Toxicity: A Biological and Physical-Chemical Characterization

The intense use of tellurium (Te) in industrial applications, along with the improper disposal of Te-derivatives, is causing their accumulation in the environment, where oxyanion tellurite (TeO₃²⁻) is the most soluble, bioavailable, and toxic Te-species. On the other hand, tellurium is a rare metalloid element whose natural supply will end shortly with possible economic and technological effects. Thus, Te-containing waste represents the source from which Te should be recycled and recovered. Among the explored strategies, the microbial TeO₃²⁻ biotransformation into less toxic Te-species is the most appropriate concerning the circular economy. Actinomycetes are ideal candidates in environmental biotechnology. However, their exploration in TeO₃²⁻ biotransformation is scarce due to limited knowledge regarding oxyanion microbial processing. Here, this gap was filled by investigating the cell tolerance, adaptation, and response to TeO₃²⁻ of a Micromonospora strain isolated from a metal(loid)-rich environment. To this aim, an integrated biological, physical-chemical, and statistical approach combining physiological and biochemical assays with confocal or scanning electron (SEM) microscopy and Fourier-transform infrared spectroscopy in attenuated total reflectance mode (ATR-FTIR) was designed. Micromonospora cells exposed to TeO₃²⁻ under different physiological states revealed a series of striking cell responses, such as cell morphology changes, extracellular polymeric substance production, cell membrane damages and modifications, oxidative stress burst, protein aggregation and phosphorylation, and superoxide dismutase induction. These results highlight this Micromonospora strain as an asset for biotechnological purposes.     

An unsupervised approach for fault diagnosis of power transformers

Electrical utilities apply condition monitoring on power transformers (PTs) to prevent unplanned outages and detect incipient faults. This monitoring is often done using dissolved gas analysis (DGA) coupled with engineering methods to interpret the data, however the obtained results lack accuracy and reproducibility. In order to improve accuracy, various advanced analytical methods have been proposed in the literature. Nonetheless, these methods are often hard to interpret by the decision-maker and require a substantial amount of failure records to be trained. In the context of the PTs, failure data quality is recurrently questionable, and failure records are scarce when compared to nonfailure records. This work tackles these challenges by proposing a novel unsupervised methodology for diagnosing PT condition. Differently from the supervised approaches in the literature, our method does not require the labeling of DGA records and incorporates a visual representation of the results in a 2D scatter plot to assist in interpretation. A modified clustering technique is used to classify the condition of different PTs using historical DGA data. Finally, well-known engineering methods are applied to interpret each of the obtained clusters. The approach was validated using data from two different real-world data sets provided by a generation company and a distribution system operator. The results highlight the advantages of the proposed approach and outperformed engineering methods (from IEC and IEEE standards) and companies legacy method. The approach was also validated on the public IEC TC10 database, showing the capability to achieve comparable accuracy with supervised learning methods from the literature. As a result of the methodology performance, both companies are currently using it in their daily DGA diagnosis.     

OPERATING REGIME DECOMPOSITION USING NEURAL NETWORKS

This article addresses the problem of identification of a nonlinear process operating over a wide range of conditions. The global space is divided into multiple local regimes, a nonlinear model is developed for each regime, and a quadratic programming-based algorithm is used to ensure smooth transition between the regimes on-line. The use of nonlinear models as opposed to linear models reduces the number of local regimes needed. Neural networks are used to model these regimes because of their strong ability to capture nonlinearity, and their combination with the switching algorithm improves transient performance. The performance of the method is demonstrated on an exothermic CSTR and a pH neutralization process.     

Bridging a Culture: The Design of Museo Soumaya

Fernando Romero and Armando Ramos of Fernando Romero EnterprisE (FREE) describe how the firm's design for an iconic museum in Mexico City, which adopted complex computational techniques, required them to develop an integrated and highly collaborative approach to design; with a central digital 3-D model being applied throughout the construction phase.     

Half‐Sandwich Scorpionate Vanadium,Iron and Copper Complexes: Synthesis and Application in the Catalytic Peroxidative Oxidation of Cyclohexane under Mild Conditions

The new half‐sandwich scorpionate complexes [hydridotris(1‐pyrazolyl)methane]vanadium trichloride, ([VCl₃{HC(pz)₃}] 1 (pz=pyrazolyl), [tris(1‐pyrazolyl)methanesulfonate]vanadium trichloride, [VCl₃{SO₃C(pz)₃}] 2 , [hydrido(1‐pyrazolyl)methane]iron dichloride, [FeCl₂{HC(pz)₃}] 3 , lithium [tris(1‐pyrazolyl)methanesulfonate]dichloroferrate, Li[FeCl₂{SO₃C(pz)₃}] 4 , and [tris(1‐pyrazolyl)methanesulfonate]copper chloride, [CuCl{SO₃C(pz)₃}] 5 were synthesized, characterized and shown to act, as well as the related (tripyrazolylmethane)copper dichloride, [CuCl₂{HC(pz)₃}] 6 , as selective catalysts (or catalyst precursors) for the peroxidative oxidation (with hydrogen peroxide) of cyclohexane to cyclohexanol and cyclohexanone, under mild conditions (at room temperature and using an aqueous solution of H₂O₂). The iron complexes are the most active ones (reaching TON values up to ca. 690), the effects of a variety of factors are reported and the reaction is shown to proceed via both C‐ and O‐centred radical mechanisms, conceivably involving a metal‐based oxidant.     

Effect of waste milk pasteurization on fecal shedding of Salmonella in preweaned calves

The objective of the current research was to determine if pasteurization of nonsaleable waste milk influences fecal Salmonella concentrations and prevalence, or antimicrobial susceptibility and serotype of the cultured isolates. Holstein dairy calves (n = 211) were housed on a single commercial dairy in the southwestern United States and randomly allotted to be fed either pasteurized (PWM; n = 128 calves) or nonpasteurized waste milk (NPWM; n = 83 calves). Fecal samples were collected via rectal palpation or from freshly voided, undisturbed fecal pats, weekly during the first 4 wk of the animal's life and then again at weaning. Eight total collections were made and 1,117 fecal samples cultured for Salmonella. One isolate from each culture-positive fecal sample was preserved for antimicrobial susceptibility screening and serotyping. Sixty-nine percent of the fecal samples were culture positive for Salmonella with no difference due to treatment (67.7 and 69% Salmonella positive for PWM and NPWM treatments, respectively). Few fecal samples (178/1,117; 15.9%) contained Salmonella concentrations above the limit of detection (～1 cfu/g of feces) with concentrations ranging from 1.0 to 6.46 cfu (log₁₀)/g of feces. Concentration was not affected by treatment. Seventeen different serotypes were identified, the majority of which were Montevideo and Anatum. A greater percentage of Typhimurium (87 vs. 13%), Muenchen (88 vs. 12%), and Derby (91 vs. 9%) were recovered from calves fed PWM compared with NPWM-fed calves. Conversely, Newport (12.5 vs. 86%), Bredeney (22.2 vs. 77.8%), and Muenster (12.5 vs. 87.5%) were lower in PWM compared with NPWM treatments. The majority (66.7%) of isolates were susceptible to all of the antibiotics examined. Results from this one commercial dairy suggest that milkborne Salmonella is not an important vector of transmission in dairy neonates, nor does pasteurization of waste milk influence fecal shedding of this pathogen. Caution should be used, however, when extrapolating results to other farms as Salmonella contamination of milk on farm is well documented. The potential benefits of pasteurization in disease prevention outweigh the potential risks of feeding a nonpasteurized product and warrants incorporation into any calf-rearing program using nonsaleable waste milk for feeding young dairy neonates.     

Performance of several Cr and Yb analytical techniques applied to samples of different biological origin (digesta or faeces)

This paper compares the performance, in terms of Cr (liquid phase marker) and Yb (solid phase marker) recovery from spiked samples, of five mineralization procedures applied to faeces, whole duodenal digesta, particulate and liquid phases of duodenal digesta, whole ruminal digesta and ruminal fluid from cattle. Two Holstein–Friesian heifers, fitted with permanent ruminal and duodenal cannulae, and fed twice daily on barley straw and a concentrate (15:85), were used as sample donors. Cr and Yb were added to the samples at 5, 25, 125 and 625 µg g^?1 dry matter, and analyzed by atomic absorption spectrometry. There were differences in marker recovery (p = 0.0481) depending on the mineralization procedure utilized but their performance was not affected by marker type (p = 0.6143). The interaction between type of sample and digestion procedure was statistically significant (p = 0.0290) and the results showed that homogeneous samples (whole duodenal digesta, the particulate phase of duodenal digesta and faeces) allowed the more even distribution of the marker and an easier and more complete mineralization. In contrast, heterogeneous samples (whole rumen digesta and rumen fluid) resulted in either a lesser attachment of markers to the particles and/or incomplete mineralization of the samples, which resulted in a higher variability between procedures. The interaction between type of sample and marker was also significant (p = 0.0426), with Cr recovery being more affected by type of sample than Yb. Copyright © 2004 Society of Chemical Industry