Heavy metals in cow’s milk and cheese produced in areas irrigated with waste water in Puebla,Mexico

The aim of this work was to determine Ni, Cr, Cu, Zn, Pb, and As levels in raw milk and Oaxaca and ranchero type cheeses, produced in areas irrigated with waste water from Puebla in Mexico. Milk results showed a mean Pb level of 0.03 mg kg^?1, which is above the maximum limit as set by Codex Alimentarius and the European Commission standards. For As a mean value of 0.12 mg kg^?1 in milk was obtained. Mean As and Pb levels in milk were below the Mexican standard. Milk whey and ranchero cheese had mean Pb levels of 0.07 and 0.11 mg kg^?1, respectively. As was higher in Oaxaca and ranchero cheese at 0.17 and 0.16 mg kg^?1, respectively. It was concluded that cheeses made from cow’s milk from areas irrigated with waste water are contaminated with Pb and As, which may represent a health risk.     

Study of keyhole TIG welding by comparative analysis of two high-productivity torches for joining medium-thickness carbon steel plates

In the usual reference works, welding by the keyhole technique has always been associated with welding processes with high energy concentration, such as the laser process or the plasma process. Recent advances in TIG torches are changing how the TIG welding process should be viewed. An example of these recent advances is the torch with the trade name Infocus, the main feature of which, according to its manufacturers, is the capacity for concentration of energy at the electrode tip, by increasing the cooling power of the electrode, which differentiates the Infocus torch from a conventional TIG torch. This concentration of energy allows the Infocus torch to operate by the keyhole technique. Therefore, the aim of the present work is to study the feasibility of employing the keyhole technique with a conventional TIG torch, with the same working conditions as the torch known commercially as Infocus. The tests confirmed that the TIG process can operate by the keyhole technique, without the need for a torch with special characteristics. However, the electrode of the Infocus torch has a longer life, in comparison with a conventional electrode of the same composition, increasing process productivity.     

The study of a novel crystal SiGeC far infrared sensor with thermal isolated by MEMS technology

In this study, we report the design, fabrication and performance of a novel crystal SiGeC infrared sensor with thermal isolation structure. The developed sensor was prepared using the technology of micro-electromechanical systems (MEMS) to achieve a better thermal isolation structure. The operation principle of the sensor is based on the change of thermistor’s resistance under the irradiation FIR light. The thermistor in the IR detector is made of Si_0.68Ge_0.31C_0.01 thin films for its large activation energy 0.21 eV and the temperature coefficient (TCR) of ?2.74%, respectively. Finite element method (FEM) package ANSYS has been employed for the analysis of the thermal isolation and stress distribution in the IR detector. The major FIR-sensing part on the micro-bridge with dimensions of 2,000 × 2,000 × 25 μm³ is fabricated by anisotropic wet etching. Responsivity, thermal conductance, thermal time constant were investigated and found that the thermal isolation improved structure possesses a much superior performance.     

Boron-doped carbon powders formed at 1000 °C and one atmosphere

Boron-doped amorphous carbon powders were produced at 1000 °C and under one atmosphere of pressure using a simple tube furnace. Doping was monitored using XRD and Raman spectroscopy, and boron content was confirmed by XPS. The XPS data showed a peak at 188 eV which coincides with the B1s energy when bound to carbon. XRD data showed a decreasing d₀₀₂-spacing, indicating increased graphitization upon doping. The full width at half maximum of this peak decreased, probably due to an increase in grain size upon boron doping. Raman spectroscopy showed a decrease in the height of the G-band, due to the boron substitution. The intensity ratio of the G- to D-bands increased, indicating larger grain sizes in the powders.     

NMR investigation on the occurrence of Na species in porous carbons prepared by NaOH activation

A detailed investigation was conducted about the process of alkali activation of charred rice hulls using NaOH. A carbon-rich precursor was initially prepared from the pyrolysis of rice hulls under N₂ atmosphere, part of it being leached with HF to remove silica. The precursor was then mixed with NaOH, heat-treated at activation temperatures from 600 to 800 °C, and part of the product was finally washed with distilled water. Thermogravimetric curves under O₂ flux showed a strong reduction in the ash content of the activated samples, indicating the consumption of silica during the activation process. From X-ray diffractometry, ²⁹Si, and ²³Na NMR spectroscopy, it was possible to identify the formation of sodium carbonate and silicates in the non-washed samples. After washing, all these compounds were removed and specific surface area measurements indicated a substantial porosity development, with larger surface area values obtained for the samples prepared from the HF-leached precursor. The use of ²³Na NMR spectroscopy indicated the retention of sodium in the washed samples, in a chemical environment distinct from carbonates and silicates. The shapes and positions of the observed resonance lines pointed to a disordered environment, associated with oxygenated surface groups within the porous structure of the activated carbons.     

Human mimic color perception for segmentation of color images using a three-layered self-organizing map previously trained to classify color chromaticity

Most of the works addressing segmentation of color images use clustering-based methods; the drawback with such methods is that they require a priori knowledge of the amount of clusters, so the number of clusters is set depending on the nature of the scene so as not to lose color features of the scene. Other works that employ different unsupervised learning-based methods use the colors of the given image, but the classifying method employed is retrained again when a new image is given. Humans have the nature capability to: (1) recognize colors by using their previous knowledge, that is, they do not need to learn to identify colors every time they observe a new image and, (2) within a scene, humans can recognize regions or objects by their chromaticity features. Hence, in this paper we propose to emulate the human color perception for color image segmentation. We train a three-layered self-organizing map with chromaticity samples so that the neural network is able to segment color images by their chromaticity features. When training is finished, we use the same neural network to process several images, without training it again and without specifying, to some extent, the number of colors the image have. The hue component of colors is extracted by mapping the input image from the RGB space to the HSV space. We test our proposal using the Berkeley segmentation database and compare quantitatively our results with related works; according to the results comparison, we claim that our approach is competitive.

     

Exploiting label semantic relatedness for unsupervised image annotation with large free vocabularies

Automatic Image Annotation (AIA) is the task of assigning keywords to images, with the aim to describe their visual content. Recently, an unsupervised approach has been used to tackle this task. Unsupervised AIA (UAIA) methods use reference collections that consist of the textual documents containing images. The aim of the UAIA methods is to extract words from the reference collection to be assigned to images. In this regard, by using an unsupervised approach it is possible to include large vocabularies because any word could be extracted from the reference collection. However, having a greater diversity of words for labeling entails to deal with a larger number of wrong annotations, due to the increasing difficulty for assigning a correct relevance to the labels. With this problem in mind, this paper presents a general strategy for UAIA methods that reranks assigned labels. The proposed method exploits the semantic-relatedness information among labels in order to assign them an appropriate relevance for describing images. Experimental results in different benchmark datasets show the flexibility of our method to deal with assignments from free-vocabularies, and its effectiveness to improve the initial annotation performance for different UAIA methods. Moreover, we found that (1) when considering the semantic-relatedness information among the assigned labels, the initial ranking provided by a UAIA method is improved in most of the cases; and (2) the robustness of the proposed method to be applied on different UAIA methods, will allow extending capabilities of state-of-the-art UAIA methods.

     

Study on characterization of pyrolysis and hydrolysis products of poly(vinyl chloride) waste

Poly(vinyl chloride) PVC pyrolysis and hydrolysis are conducted in a fixed bed reactor and in an autoclave, respectively, under different operating conditions such as the temperature and time. The product distribution is studied. For the PVC pyrolysis process, the main gas product is HCl (55% at 340°C), there is 9% hydrocarbon gas (C₁–C₅), the liquid product fraction is about 5% (at 340°C), and the solid residue fraction is about 31% (at 340°C). For the hydrolysis process, the main gas product is HCl (55.8% at 240°C) and the solid residue is about 49.6% (at 240°C). The pyrolysis liquid product is analyzed by using gas chromatography with magic‐angle spinning. Aromatic hydrocarbons are the main class (90%), of which the major part is benzene (33%). The residue produced through pyrolysis and hydrolysis is investigated by high‐resolution solid‐state ¹³C‐NMR. These details revealed by the high‐field NMR spectra provide importmant information about the chemical changes in the PVC pyrolysis and hydrolysis process. The mechanism of PVC hydrolysis dechlorination is also discussed. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 90: 3252–3259, 2003     

Stimuli‐sensitive nanostructured poly(sodium 4‐styrene sulfonate): Synthesis,characterization, and study of metal ion retention properties

Stimuli‐sensitive polymers are a type of smart polymers having the capability to change their configuration or properties under adequate stimuli as heat, pH, magnetic field, mechanical strength, among other. The aim of this work was to synthesize nanostructured polymers with antibacterial properties capable to change their retention properties of divalent metal ions by external stimuli (pH and ionic strength). For that, a polymerizable nanostructured crosslinker (PNC) based on silver nanoparticles (AgNPs) and acrylic acid was synthesized. Later, NPSS was synthesized by free‐radical polymerization, characterized by different analytical techniques and its retention properties of divalent ions (Cu²⁺, Fe²⁺, Mn²⁺, and Zn²⁺) were studied at different pHs and ionic strengths (5.0, 7.0, and 9.0; and 0.0, 0.5, and 1.5% NaCl, respectively). It was evidenced that AgNPs can be synthesized using acrylic acid as stabilizing agent, and later, be used for synthesis of NPSS by free‐radical polymerization. For NPSS, metal ion retention decreases as pH is increased; in addition, results suggest that the electrostatic interaction is not the only determining factor in the retention of ions. Other possible factors which would be affecting the retention are: water flow by swelling capacity and water flow by osmotic stress resulting of high salt concentration. NPSS showed antimicrobial activity against Escherichia coli and Staphylococcus aureus which was enhanced by incorporation of PNC based on AgNPs. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46001.