Expression of keratin 13, 14 and 19 in oral squamous cell carcinomas from Sudanese snuff dippers: lack of association with human papillomavirus infection

In stratified squamous epithelia, altered expression of keratins (Ks) is one possible marker of malignant potential. In the epithelium of the uterine cervix, presence of human papillomaviruses (HPVs) is increasingly regarded as a marker of risk for cervical cancer. However, a similar role in oral cancer and precancer remains controversial. To address these questions, formalin-fixed, paraffin-embedded oral carcinomas from Sudanese snuff dippers (n=14) and oral carcinomas from Sudanese (n=14), Swedish (n=19) and Norwegian (n=41) non-snuff dippers were examined by immunohistochemistry for expression of K types 13, 14 and 19 using monoclonal antibodies. HPV infection was searched for in all the carcinomas by in situ hybridization (ISH) using the cocktail HPV OmniProbe and the ViraType probe. Carcinomas from Sudanese (snuff dippers/non-snuff dippers) were also examined for HPV infection by polymerase chain reaction (PCR) using the general HPV primers GP5+/GP6+. For the oral carcinomas from snuff dippers, moderate to intense expression of K13 (71%; 10/14), K14 (86%; 12/14) and K19 (93%; 13/14) was found. For the oral carcinomas from non-snuff dippers, weak to moderate expression of K13 (64%; 47/74), K14 (43%; 32/74) and K19 (45%; 33/74) was found. HPV DNA was not detected in any of the carcinomas from three countries when examined by ISH. The Sudanese (from snuff dippers/non-snuff dippers) oral carcinomas were also negative for HPV DNA with the PCR. The present study shows that (i) there is a high level of expression of K13, K14 and K19 in oral carcinomas from snuff dippers compared to those from non-snuff dippers, (ii) this high level of expression may arise from dysregulation of keratinocyte proliferation and maturation caused by damaging effects of snuff, (iii) the HPV genome is not found in Sudanese (snuff dippers/non-snuff dippers), Swedish or Norwegian oral carcinomas, and (iv) this may suggest that these viruses do not play a prominent role in the aetiology of oral carcinomas from these countries.     

Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data

Although hyperspectral remote sensing has been used to study many agricultural phenomena such as crop stress and diseases, the potential use of this technique for detecting Ganoderma disease infestations and damage to oil palms under field conditions has not been explored to date. This research was conducted to investigate the feasibility of using a portable hyperspectral remote-sensing instrument to identify spectral differences between oil-palm leaves with and without Ganoderma infections. Reflectance spectra of samples representative of three classes of disease severity were collected. The most significant bands for spectral discrimination were selected from reflectance spectra and first derivatives of reflectance spectra. The significant wavelengths were identified using one-way analysis of variance. Then, a Jeffries–Matusita (JM) distance measurement was used to determine spectral separability between the classes. A maximum likelihood classifier method was used to classify the three classes based on the most significant wavelength spectral responses, and an error matrix was finally used to assess the accuracy of the classification.     

Stemming Hausa text: using affix-stripping rules and reference look-up

Stemming is a process of reducing a derivational or inflectional word to its root or stem by stripping all its affixes. It is been used in applications such as information retrieval, machine translation, and text summarization, as their pre-processing step to increase efficiency. Currently, there are a few stemming algorithms which have been developed for languages such as English, Arabic, Turkish, Malay and Amharic. Unfortunately, no algorithm has been used to stem text in Hausa, a Chadic language spoken in West Africa. To address this need, we propose stemming Hausa text using affix-stripping rules and reference lookup. We stemmed Hausa text, using 78 affix stripping rules applied in 4 steps and a reference look-up consisting of 1500 Hausa root words. The over-stemming index, under-stemming index, stemmer weight, word stemmed factor, correctly stemmed words factor and average words conflation factor were calculated to determine the effect of reference look-up on the strength and accuracy of the stemmer. It was observed that reference look-up aided in reducing both over-stemming and under-stemming errors, increased accuracy and has a tendency to reduce the strength of an affix stripping stemmer. The rationality behind the approach used is discussed and directions for future research are identified.     

An artificial neural network-based mathematical model for the prediction of blast-induced ground vibrations

ABSTRACT

This paper presents an artificial neural network (ANN) based mathematical model for the prediction of blast-induced ground vibrations using the data obtained from the literature. A feed-forward back-propagation multi-layer perceptron (MLP) was adopted, and the Levenberg–Marquardt algorithm was used in training the network. The powder factor, the maximum charge per delay, and distance from blasting face to monitoring point are the input variables. The peak particle velocity (PPV) is the targeted output variable. The model was then formulated using the weights and biases output from the ANN simulation. Multilinear regression (MLR) analysis was also performed using the same number of datasets, as in the case of ANN. The quality of the proposed ANN-based model was also tested with another 14 datasets outside the one used in developing the models and compared with more classical models. The coefficient of the determination (R²) of the proposed ANN-based model was the highest.     

Polycarbonate/silica nanocomposite membranes: Fabrication,characterization, and performance evaluation

Polycarbonate/silica nanocomposite membranes at low silica loading were fabricated by solution blending and solvent evaporation technique. The functionalized silica nanoparticles used were synthesized by co‐condensing hydrolyzed tetraethylorthosilicate with 3‐aminopropyl trimethoxysilane in the sol–gel process. The membranes morphology, composition, surface, structure, thermal and mechanical properties were analyzed by the standard characterization techniques. The gas permeation tests were conducted in four‐channel permeation cells. Field emission scanning electron microscopy results reveal that membranes above 3 wt % silica content formed distinguishable voids and agglomerates. Fair distribution of silica nanoparticles and absence of residual solvents were observed by energy dispersive X‐ray and thermogravimetric analysis. Fourier transform infrared spectroscopy spectra confirmed the presence of new functional groups (N? H) and (O? H) bonds. The X‐ray diffraction pattern revealed the polymer‐particle interactions, the formation of rigidified polymer chain, and nanostructured silicon crystals. Further, the thermogravimetric analysis results revealed thermal stability enhancement while differential scanning calorimetry results of increased glass transition temperatures confirmed the presence of rigidified polymer chain. Furthermore, enhancements in mechanical strength of the membranes were observed. Moreover, at all feed pressures, increased CO₂, N₂, and CH₄ gas permeation was observed. At 6 bar feed pressure, the CO₂/N₂ and CO₂/CH₄ ideal selectivities of PC membranes with 3 wt % silica loading have increased from 19.2 to 38.0 and 29.2, respectively. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134 , 45310.     

Effects of silica aerogel particle sizes on the thermal–mechanical properties of silica aerogel – unsaturated polyester composites

Silica aerogels with a surface area as high as 773?m²?g^?1 and a density of 0.077?g?cm^?3 were produced from rice husk via sol–gel process and ambient pressure drying. A particulate composite material was prepared by adding silica aerogel particles of three different particle sizes (powder, granules and bead) to unsaturated polyester resin with a fixed volume fraction of 30%. Thermogravimetric and thermal conductivity studies revealed that silica aerogel composites were having higher thermal stability and thermal insulation than the neat resin. It was suggested that the preservation of aerogel pores from resin intrusion is important for better thermal properties. Larger silica aerogel particles have more porous area (unwetted region) which results in a lower degradation rate and lower thermal conductivity of the base polymer. However, the addition of silica aerogel into resin has reduced the tensile modulus of the polymer matrix where smaller particle size displayed higher toughness than those with bigger particle size.     

Engineering of Lanthanide‐Doped Upconversion Nanoparticles for Optical Encoding

Lanthanide‐doped upconversion nanoparticles (UCNPs) are an emerging class of luminescent materials that emit UV or visible light under near infra‐red (NIR) excitations, thereby possessing a large anti‐Stokes shift property. Due to their sharp excitation and emission bands, excellent photo‐ and chemical stability, low autofluorescence, and high tissue penetration depth of the NIR light used for excitation, UCNPs have surpassed conventional fluorophores in many bioapplications. A better understanding of the mechanism of upconversion, as well as the development of better approaches to preparing UCNPs, have provided more opportunities to explore their use for optical encoding, which has the potential for applications in multiplex detection and imaging. With the current ability to precisely control the microstructure and properties of UCNPs to produce particles of tunable emission, excitation, luminescence lifetime, and size, various strategies for optical encoding based on UCNPs can now be developed. These optical properties of UCNPs (such as emission and excitation wavelengths, ratiometric intensity, luminescence lifetime, and multicolor patterns), and the strategies employed to engineer these properties for optical encoding of UCNPs through homogeneous ion doping, heterogeneous structure fabrication and microbead encapsulation are reviewed. The challenges and potential solutions faced by UCNP optical encoding are also discussed.     

COSUM: Text summarization based on clustering and optimization

Text summarization is a process of extracting salient information from a source text and presenting that information to the user in a condensed form while preserving its main content. In the text summarization, most of the difficult problems are providing wide topic coverage and diversity in a summary. Research based on clustering, optimization, and evolutionary algorithm for text summarization has recently shown good results, making this a promising area. In this paper, for a text summarization, a two‐stage sentences selection model based on clustering and optimization techniques, called COSUM, is proposed. At the first stage, to discover all topics in a text, the sentences set is clustered by using k‐means method. At the second stage, for selection of salient sentences from clusters, an optimization model is proposed. This model optimizes an objective function that expressed as a harmonic mean of the objective functions enforcing the coverage and diversity of the selected sentences in the summary. To provide readability of a summary, this model also controls length of sentences selected in the candidate summary. For solving the optimization problem, an adaptive differential evolution algorithm with novel mutation strategy is developed. The method COSUM was compared with the 14 state‐of‐the‐art methods: DPSO‐EDASum; LexRank; CollabSum; UnifiedRank; 0–1 non‐linear; query, cluster, summarize; support vector machine; fuzzy evolutionary optimization model; conditional random fields; MA‐SingleDocSum; NetSum; manifold ranking; ESDS‐GHS‐GLO; and differential evolution, using ROUGE tool kit on the DUC2001 and DUC2002 data sets. Experimental results demonstrated that COSUM outperforms the state‐of‐the‐art methods in terms of ROUGE‐1 and ROUGE‐2 measures.     

Performance evaluation of shortenings based on palm oil and butterfat in yellow cake

Shortenings based on palm oil (PO), combinations of PO and butter fat (BF) at a ratio of PO:BF = 3:2 and PO:BF = 2:3 and 100% BF were evaluated. In the case of PO shortening, 0.2% diacetyl flavour was added during processing. Baking tests indicated that combination of PO with BF produced higher specific batter volume and specific cake volume compared with PO shortening or 100% BF. The addition of BF to PO resulted in softer cake texture as indicated by instrumental measurement. Sensory evaluation indicated that cakes made with PO shortening with added diacetyl flavour (at 0.2%) resulted in significantly (p<0.05) higher scores in terms of grain size, softness and flavour compared to cakes made with 100% BF. However, there was no significant difference in the sensory scores of the cakes made with PO, PO:BF = 3:2 and PO:BF = 2:3 shortenings. Thus PO helped to improve performance of BF in production of yellow cake.