Average sex ratio and population maintenance cost

The ratio of males to females in a population is a meaningful characteristic of sexual species. The reason for this biological property to be available to the observers of nature seems to be a question never asked. Introducing the notion of historically adapted populations as global minimizers of maintenance cost functions, we propose a theoretical explanation for the reported stability of this feature. This mathematical formulation suggests that sex ratio could be considered as an indirect result shaped by the antagonism between the size of the population and the finiteness of resources.Comment: 18 pages. A revised new version, where all the text was improved to become more clear for the reade

Exploring Constrained Type-2 fuzzy sets

Fuzzy logic has been widely used to model human reasoning thanks to its inherent capability of handling uncertainty. In particular, the introduction of Type-2 fuzzy sets added the possibility of expressing uncertainty even on the definition of the membership functions. Type-2 sets, however, don’t pose any restrictions on the continuity or convexity of their embedded sets while these properties may be desirable in certain contexts. To overcome this problem, Constrained Type-2 fuzzy sets have been proposed. In this paper, we focus on Interval Constrained Type-2 sets to see how their unique structure can be exploited to build a new inference process. This will set some ground work for future developments, such as the design of a new defuzzification process for Constrained Type-2 fuzzy systems

An epistatic mini-circuitry between the transcription factors Snail and HNF4a controls liver stem cell and hepatocyte features exhorting opposite regulation on stemness-inhibiting microRNAs

Preservation of the epithelial state involves the stable repression of EMT program while maintenance of the stem compartment requires the inhibition of differentiation processes. A simple and direct molecular mini-circuitry between master elements of these biological processes, may provide the best device to keep balanced such complex phenomena. In this work, we show that in hepatic stem cell Snail, a transcriptional repressor of the hepatocyte differentiation master gene HNF4, directly represses the expression of the epithelial microRNAs-200c and -34a, which in turn target several stem cell genes. Notably, in differentiated hepatocytes HNF4, previously identified as a transcriptional repressor of Snail, induces the microRNAs-34a and -200a, b, c that, when silenced, causes epithelial dedifferentiation and reacquisition of stem traits. Altogether these data unveiled Snail, HNF4 and microRNAs -200a, b, c and -34a as epistatic elements controlling hepatic stem cell maintenance/differentiation

Bacillus subtilis for the control of powdery mildew on cucumber and zucchini squash.

Application of concentrated metabolites of Bacillus subtilis - CMBS - (5,000 ug/mL) one and 24 h before or after inoculation of Sphaerotheca fuliginea (3 x 10 4 conidia/mL) reduced the number of lesions on cucumber leaves by 90-99%. The average number of lesions on control plants was 16.7 per leaf. A wettable powder product formulated with cells (10%) and metabolites (10%) of B. subtilis (WPBS), and CMBS sprayed on cucumber plants (1,000 ug/mL and 10,000 ug/mL) twice a week totally controlled powdery mildew. In the control treatment, 18 days after the first spray, the percent leaf surface covered by lesions was 99.0 and 46.7%, on the cotyledonary and expanded leaves, respectively. In the control treatment, 30 days after the first spray, the percent leaf surface with lesions was 26.1%, while leaves sprayed with CMBS presented no lesions. The fresh weight per plant was 4.3 g in the control treatment; 12.2 g, and 10.2 for plants sprayed with CMBS at the concentration of 1,000 and 10,000 ug/mL, respectively; and 9.7 g and 10.1 g for plants sprayed with WPBS 1,000 and 10,000 ug/mL, respectively. For zucchini squash, CMBS (5,000 ug/mL) sprayed every 2,4, and 6 days showed reductions in lesioned leaf surface of 100.0,98.3, and 94,7%, respectively

Best parameter choice of Stochastic Resonance to enhance fault signature in bearings

Stochastic Resonance (SR) is a phenomenon studied and exploited for telecommunication, which permits the detection and amplification of weak signals by the assistance of noise. The first papers on this topic date back to the early 80s and were developed to explain some periodic natural phenomena. Other applications are in neuroscience, biology, medicine and, obviously, mechanics. Recently, a few researchers have tried to apply this technique for detecting faults in mechanical systems and also bearings. In this paper we discuss the best way to select the parameters to augment the performance of the algorithm. This is probably the main drawback of SR, since in system identification the procedure should be as blind as possible to be efficient and widely applicable. The classical bi-stable potential form is adopted in our study, with three parameters to be selected. Based on numerical tests, a characteristic trend of the amplification factor has been found with respect to the parameters variation, so that a general rule is consequently determined which gives the best performances in terms of detection and amplification. The SR algorithm is tested on both simulated and experimental data showing a good capacity of increasing the signal to noise ratio

Control of cucumber damping-off caused by Pythium ultimum, with organic matter

The effectiveness of several media soil-sand-pertile (1:1:1 v/v); soil-sand-pertile-manure (1:1:1:3); soil-sand-perlite-compost (1:1:1:3); soil-sand-perlite-peat (1:1:1:3); soil-sand-perlite-straw (1:1:1:3), and sand-perlite-peat-compost-mamure-wheat straw (2:2:1:3:3:1) as suppressers of the cucumber (Cucumis sativus) damping-off causal agent, Pythium ultimum, was evaluated. The media were infested with 12 g/l of Pythium inoculum (broken corn-sand medium), fifteen days before sowing ten cucumber seeds (mezzolungo Marketer) 1 cm deep in pots containing approximately 500 ml of medium. Plants were grown at a constant temperature of 25oC simbolo 177\\ f "Symbol" \\s 12 2 with 12 hours of illumination per day. The percentage of emerged seedlings, post- and pre-emerg ent damping-off and disease severity were determined at fifteen days after planting. This procedure was repeated on the same substrates, without reinoculation, ten days after harvesting this first trial. The manure medium was the most suppressive to the disease, with percent of emergence, percent of pre-and post-emergence damping-off and disease severity values of 84.5%, 12.0%, 0% and 1.35, respectively, for the first bioassay. The replanting experiment results were 98.5%, 0%, 0% and 1,0, respectively. However, plants grown in this medium in both bioassays were shorter than ones grown in the other media. Peat medium and the mixture sand-peat-manure-compost-wheat straw medium were more conducive to the disease than wheat straw medium, resulting in higher occurrence and severity of attack by Pythium

Machine vibration monitoring for diagnostics through hypothesis testing

Nowadays, the subject of machine diagnostics is gathering growing interest in the research field as switching from a programmed to a preventive maintenance regime based on the real health conditions (i.e., condition-based maintenance) can lead to great advantages both in terms of safety and costs. Nondestructive tests monitoring the state of health are fundamental for this purpose. An effective form of condition monitoring is that based on vibration (vibration monitoring), which exploits inexpensive accelerometers to perform machine diagnostics. In this work, statistics and hypothesis testing will be used to build a solid foundation for damage detection by recognition of patterns in a multivariate dataset which collects simple time features extracted from accelerometric measurements. In this regard, data from high-speed aeronautical bearings were analyzed. These were acquired on a test rig built by the Dynamic and Identification Research Group (DIRG) of the Department of Mechanical and Aerospace Engineering at Politecnico di Torino. The proposed strategy was to reduce the multivariate dataset to a single index which the health conditions can be determined. This dimensionality reduction was initially performed using Principal Component Analysis, which proved to be a lossy compression. Improvement was obtained via Fisher’s Linear Discriminant Analysis, which finds the direction with maximum distance between the damaged and healthy indices. This method is still ineffective in highlighting phenomena that develop in directions orthogonal to the discriminant. Finally, a lossless compression was achieved using the Mahalanobis distance-based Novelty Indices, which was also able to compensate for possible latent confounding factors. Further, considerations about the confidence, the sensitivity, the curse of dimensionality, and the minimum number of samples were also tackled for ensuring statistical significance. The results obtained here were very good not only in terms of reduced amounts of missed and false alarms, but also considering the speed of the algorithms, their simplicity, and the full independence from human interaction, which make them suitable for real time implementation and integration in condition-based maintenance (CBM) regimes