Effect of Residual Surface Stress on the Strenght Distribution of Brittle Materials

The introduction of residual surface stresses into a material can change the strength distribution simply due to variability in the stress intensity factor of surface cracks. This variability arises from the distribution in surface (critical) crack lengths. A fracture mechanics approach was used to determine the influence of surface compression on the average strength and the standard deviation of the strength distribution. The strengths of the stress-free samples were assumed to fit a twoparameter Weibull distribution, and the increases in strength resulting from the surface compression were determined using fracture mechanics. It was determined from the analysis that the standard deviation/average strength ratio (coefficient of variation) initially increases, passes through a maximum, and ultimately reaches a plateau value below the initial value, as one increases the depth of surface compression. The maximum increase in the strength scatter occurs when the depth of the surface compression is approximately equal to the characteristic crack size. These changes were found to be dependent on the magnitude of the surface stress, as well as the characteristic strength, Weibull modulus, and fracture toughness of the stress-free material.     

Interactive sonification to assist children with autism during motor therapeutic interventions

Personal and Ubiquitous Computing - Interactive sonification is an effective tool used to guide individuals when practicing movements. Little research has shown the use of interactive sonification...     

Spatio‐temporal trends of nutrients and physico‐chemical parameters on lake ecosystem and fisheries prior to onset of cage farming and re‐opening of the Mbita passage in the Nyanza Gulf of Lake Victoria

Many large lake ecosystems are experiencing increasing eutrophication and persistent cyanobacteria‐dominated algal blooms affecting their water quality and ecosystem productivity because of widespread non‐point and point nutrient sources. Accordingly, the present study utilized data of July 2003 and January–February 2004, as well as previous measurements of nutrients and physico‐chemical variables (electrical conductivity, dissolved oxygen, temperature, pH, turbidity and chlorophyll‐a), to characterize the spatial and temporal trends, as a means of better understanding the factors influencing lake environmental conditions, as support tools for long‐term ecosystem management and for better understanding the long‐term trends and effects. Inshore gulf areas were found to represent zones of maximum nutrient concentrations, compared to the deep main lake zones, with significant inter‐parameter correlations. Phosphorus, silicon and chlorophyll‐a concentrations were significantly correlated. Water electrical conductivity was also significantly and positively correlated with soluble reactive silicon (SRSi), alkalinity hardness DO, while exhibiting a negative association with water transparency. Water turbidity and transparency, electrical conductivity, and SRSi concentrations clearly describe a gradient from the gulf into the main lake. For such a shallow gulf, these findings suggest primary productivity is influenced mainly by the availability of nutrients, light transparency and the extent of availability of resuspended nutrients. The increasing eutrophic state of Lake Victoria is a serious concern since it contributes to an increased potential of more frequent occurrences of cyanobacterial blooms, a potential public health risk to both humans and wildlife. Improved understanding of influences from previous fish species introductions and concomitant changes in indigenous fish species, increased lake basin population and anthropogenic activities, water hyacinth resurgences, sustainability of biodiversity, and current interests in cage farming, are among the major concerns and challenges facing the contemporary Lake Victoria. The trends regarding nutrients and physico‐chemical characteristics are intended to support better monitoring efforts and data to promote the lake's ecosystem services and the sustainable management of the lake ecosystem.     

Prediction of jominy hardness profiles of steels using artificial neural networks

Jominy hardness profiles of steels were predicted from chemical composition and austenitizing temperature using an artificial neural network. The neural network was trained using some 4000 examples, covering a wide range of steel compositions. The performance of the neural network is examined as a function of the network architecture, the number of alloying elements, and the number of data sets used for training. A well-trained network predicts the Jominy hardness profile with an average error of about 2 HRC. Special attention was devoted to the effect of boron on hardenability. A network trained using data only from boron steels produced results similar to those of a network trained using all data available. The accuracy of the predictions of the model is compared with that of an analytical model for hardenability and with that of a partial least- squares model using the same set of data.     

Multilingual resources for NLP in the lexical markup framework (LMF)

Optimizing the production, maintenance and extension of lexical resources is one the crucial aspects impacting natural language processing (NLP). A second aspect involves optimizing the process leading to their integration in applications. With this respect, we believe that a consensual specification on monolingual, bilingual and multilingual lexicons can be a useful aid for the various NLP actors. Within ISO, one purpose of Lexical Markup Framework (LMF, ISO-24613) is to define a standard for lexicons that covers multilingual lexical data.

Efficacy of biogenic silver nanoparticles against clinical isolates of fungi causing mycotic keratitis in humans

Mycotic keratitis is mainly responsible for vision loss caused by various fungi. Sometimes, proper treatment of such infection is not possible due to unavailability of effective antifungal agents and development of resistance of such fungi to antimycotic drugs. Hence, it is necessary to search for potential antifungal agents, which can effectively eradicate fungal infection of eyes. Nanoparticles‐based antifungal drugs overcome this problem by increasing permeability and properties of drug molecules. In the present study, silver nanoparticles were synthesised by using Helminthosporium sp. and Chaetomium sp. following sequential reduction technique. The synthesised silver nanoparticles were detected primarily by UV‐visible spectrophotometer showing absorption spectra at 424 and 433 nm, respectively. Nanoparticles tracking analysis confirmed the mean particle size of silver nanoparticles as 45 and 55 nm. The synthesised AgNPs showed significant antifungal activity against fungi causing mycotic keratitis, when used alone and in combination with ketoconazole and amphotericin B in the range of 30–70 microgram per millilitre of minimum inhibitory concentration. Thus, the synthesised AgNPs can be used to enhance the activities of ketoconazole and amphotericin B.Inspec keywords: silver, nanoparticles, nanomedicine, antibacterial activity, diseases, permeability, ultraviolet spectra, visible spectra, particle sizeOther keywords: biogenic silver nanoparticles, fungi, mycotitic keratitis, vision loss, infection, antifungal agents, antimycotic drugs, antifungal drugs, permeability, Helminthosporium sp, Chaetomium sp, sequential reduction technique, UV‐visible spectrophotometer, mean particle size, ketoconazole, amphotericin B, wavelength 424 nm, wavelength 433 nm, size 45 nm, size 55 nm, Ag     

Cell-protection mechanism through autophagy in HGFs/<Emphasis Type="Italic">S. mitis</Emphasis> co-culture treated with Chitlac-nAg

Silver-based products have been proven to be effective in retarding and preventing bacterial growth since ancient times. In the field of restorative dentistry, the use of silver ions/nanoparticles has been explored to counteract bacterial infections, as silver can destroy bacterial cell walls by reacting with membrane proteins. However, it is also cytotoxic towards eukaryotic cells, which are capable of internalizing nanoparticles. In this work, we investigated the biological effects of Chitlac-nAg, a colloidal system based on a modified chitosan (Chitlac), administered for 24–48?h to a co-culture of primary human gingival fibroblasts and Streptococcus mitis in the presence of saliva, developed to mimic the microenvironment of the oral cavity. We sought to determine its efficiency to combat oral hygiene-related diseases without affecting eukaryotic cells. Cytotoxicity, reactive oxygen species production, apoptosis induction, nanoparticles uptake, and lysosome and autophagosome metabolism were evaluated. In vitro results show that Chitlac-nAg does not exert cytotoxic effects on human gingival fibroblasts, which seem to survive through a homoeostasis mechanism involving autophagy. That suggests that the novel biomaterial Chitlac-nAg could be a promising tool in the field of dentistry.     

Process optimization in the self-reacting friction stir welding of aluminum 6061-T6

Self-reacting friction stir welding (SR-FSW), also called bobbin-tool friction stir welding (BT-FSW), is a solid state welding process similar to friction stir welding (FSW) except that the tool has two opposing shoulders instead of the shoulder and a backing plate found in FSW. The tool configuration results in greater heat input and a symmetrical weld macrostructure. A significant amount of information has been published in the literature concerning traditional FSW while little has been published about SR-FSW. An optimization experiment was performed using a factorial design to evaluate the effect of process parameters on the weld temperature, surface and internal quality, and mechanical properties of self-reacting friction stir welded aluminum alloy 6061-T6 butt joints. The parameters evaluated were tool rotational speed, traverse speed, and tool plunge force. A correlation between weld temperature, defect formation (specifically galling and void formation), and mechanical properties was found. Optimum parameters were determined for the welding of 8-mm-thick 6061-T6 plate.     

Nanocrystalline Nd–Fe–B Anisotropic Magnets by Flash Spark Plasma Sintering

Flash spark plasma sintering (flash SPS) is an attractive method to obtain Nd–Fe–B magnets with anisotropic magnetic properties when starting from melt-spun powders. Compared to the benchmark processing route via hot pressing with subsequent die upsetting, flash SPS promises electroplasticity as an additional deformation mechanism and reduced tool wear, while maximizing magnetic properties by tailoring the microstructure—fully dense and high texture. A detailed parameter study is conducted to understand the influence of Flash SPS parameters on the densification and magnetic properties of commercial MQU-F powder. It is revealed that the presintering conditions and preheating temperature before applying the power pulse play a major role for tailoring grain size and texture in the case of hot deformation via Flash SPS. Detailed microstructure and magnetic domain evaluation disclose the texture enhancement with increasing flash SPS temperature at the expense of coercivity. The best compromise between remanence and coercivity (1.37 T and 1195 kA m⁻¹, respectively) is achieved through a combination of presintering at 500 °C for 120 s and preheating temperature of 600 °C, resulting in a magnet with energy product (BH)_max of 350 kJm⁻³. These findings show the potential of flash SPS to obtain fully dense anisotropic nanocrystalline magnets with high magnetic performance.