The phase diagram of random threshold networks

Threshold networks are used as models for neural or gene regulatory networks. They show a rich dynamical behaviour with a transition between a frozen and a chaotic phase. We investigate the phase diagram of randomly connected threshold networks with real-valued thresholds h and a fixed number of inputs per node. The nodes are updated according to the same rules as in a model of the cell-cycle network of Saccharomyces cereviseae [PNAS 101, 4781 (2004)]. Using the annealed approximation, we derive expressions for the time evolution of the proportion of nodes in the "on" and "off" state, and for the sensitivity $\lambda$. The results are compared with simulations of quenched networks. We find that for integer values of h the simulations show marked deviations from the annealed approximation even for large networks. This can be attributed to the particular choice of the updating rule.Comment: 8 pages, 6 figure

Strategies for the evolution of sex

We find that the hypothesis made by Jan, Stauffer and Moseley [Theory in Biosc., 119, 166 (2000)] for the evolution of sex, namely a strategy devised to escape extinction due to too many deleterious mutations, is sufficient but not necessary for the successful evolution of a steady state population of sexual individuals within a finite population. Simply allowing for a finite probability for conversion to sex in each generation also gives rise to a stable sexual population, in the presence of an upper limit on the number of deleterious mutations per individual. For large values of this probability, we find a phase transition to an intermittent, multi-stable regime. On the other hand, in the limit of extremely slow drive, another transition takes place to a different steady state distribution, with fewer deleterious mutations within the asexual population.Comment: RevTeX, 11 pages, multicolumn, including 12 figure

Effects of occupational health and safety law on forestry employees

Forest covering 28.6% of Turkey is an important area of employment. In this study, the awareness of the employees of Erzurum Forest Nursery Directorate has been attempted to be investigated by applying the Law No. 6331 on occupational health and safety. In the study, a questionnaire consisting of 36 independent questions, 8 independent and 28 dependent variables were prepared. The data obtained from the questionnaires was evaluated in the SPSS 20.0 program, and frequency distributions were determined. In addition, Chiropractic Analysis was performed to see if there is a statistical relation between dependent and independent variables in the questionnaires. According to the results; the ratio of General Occupational Health and Safety Education is 82.3%. However, the percantage of those using Personel Protective Equipment was lower 70.5%. Nearly all of those who stated that they had health problems in the institution were married women over the age of 40. If these groups are generally considered to be physically active and do not have job descriptions, the measures to be taken are: To ensure that dangerous situations affecting the health of employees are identified and removed from the scene by means of the risk assessment team established in accordance with Law No. 6331 on occupational health and safet

Self-optimization, community stability, and fluctuations in two individual-based models of biological coevolution

We compare and contrast the long-time dynamical properties of two individual-based models of biological coevolution. Selection occurs via multispecies, stochastic population dynamics with reproduction probabilities that depend nonlinearly on the population densities of all species resident in the community. New species are introduced through mutation. Both models are amenable to exact linear stability analysis, and we compare the analytic results with large-scale kinetic Monte Carlo simulations, obtaining the population size as a function of an average interspecies interaction strength. Over time, the models self-optimize through mutation and selection to approximately maximize a community fitness function, subject only to constraints internal to the particular model. If the interspecies interactions are randomly distributed on an interval including positive values, the system evolves toward self-sustaining, mutualistic communities. In contrast, for the predator-prey case the matrix of interactions is antisymmetric, and a nonzero population size must be sustained by an external resource. Time series of the diversity and population size for both models show approximate 1/f noise and power-law distributions for the lifetimes of communities and species. For the mutualistic model, these two lifetime distributions have the same exponent, while their exponents are different for the predator-prey model. The difference is probably due to greater resilience toward mass extinctions in the food-web like communities produced by the predator-prey model.Comment: 26 pages, 12 figures. Discussion of early-time dynamics added. J. Math. Biol., in pres

Headspace volatiles of Allium subhirsutum L. growing in Turkey

WOS: 000456212300027Allium subhirsutum L. (Amaryllidaceae family) is a plant species, widely spread around the Mediterranean region from Spain and the Canary Islands to Turkey and Palestine. The A. subhirsutum is called in the regional name 'Tuylu kormen, Koremen' or called 'Yabani sarymsak'. Allium is represented by a single species in Turkey, is a Mediterranean elements. We collected the plant material needed for this study from Marmaris: Yemeler district of Mugla Province. A. subhirsutum sample using headspace - SPME procedure the fibres used in this study were coated with polydimethylsiloxane (PDMS, 100 mu m) (supplied by Supelco Bellefonte, USA), was used with a sampling time of 30 min. Thermal desorption at 250 degrees C during 10 min for the GC/MS analysis. The GC/MS analysis was carried out with an Agilent 5975 GC-MSD system. Innowax FSC column (60 m x 0.25 mm, 0.25 mm film thickness) was used with He as carrier gas. GC oven temperature was kept at 60 degrees C for 10 min and programmed to 220 degrees C at a rate of 4 degrees C/min, and kept constant at 220 degrees C for 10 min and then programmed to 240 degrees C at a rate of 1 degrees C/min, at splitless mode. MS were taken at 70 eV. Mass range was from m/z 35 to 450. Headspace volatiles of crushed bulbs of A. subhirsutum were analyzed by gas chromatography/mass spectrometry. The volatiles were trapped by SPME in a dynamic headspace set up. Volatiles of crushed bulbs of A. subhirsutum were trapped on an HS-SPME (Red fiber). Main components were found to be allyl methyl disulfide (41.0%), diallyl disulfide (20.7%) and dimethyl sulfide (15.3%)

The Origin of Photoplasticity in ZnS

ZnS is a brittle material but shows extraordinary plasticity during mechanical tests performed in complete darkness. This phenomenon is known as the photoplastic effect, whose underlying mechanisms have long been unclear. We study the impact of light, via photoexcited charge carriers, on the dislocation core structure and mobility using first-principles calculations. We calculate the core structure and the charge-dependent Peierls barriers of the glide set of Shockley partial dislocations in ZnS. Our findings reveal that locally charged dislocations capture excess carriers in the system, leading to core reconstructions that alter the Peierls barrier, resulting in higher barriers and lower mobility for these dislocations. This altered and asymmetric mobility, depending on dislocation character (edge or mixed) and local stoichiometry (Zn or S rich), is responsible for the brittle behavior of ZnS under light exposure and will be reversed in complete darkness

VIBRATION ANALYSES OF RAILWAY SYSTEMS USING PROPOSED NEURAL PREDICTORS

Due to travelling on railway systems; there are many gaps and problems in cross areas. Therefore; it is necessary and very important to establish intelligent crossing systems in such areas. On the other hand, it is not possible for trains to stop or brake immediately against an obstacle due to their high speed and inertia. For this reason, it is necessary to work on the safety/warning of the other main fac-tors and necessities (pedestrians and vehicles) in level crossings. This experimental investigation is carried out by using an experimental real-time train and crossing systems. The main vibration parameters are analysed by using neural networks. First, the dynamics of the train-rail system related to level crossings are examined, and the vibrations created by the train on rails are measured at different speeds. Then three types of proposed neural networks predictors, Levenberg-Marquardt backpropagation (LMBP), scaled conjugate gradient backpropagation (SCGB) and BFGS quasi-Newton backpropagation (BFGS) are used to predict the vibration of the train-rail system. From the results, it is seen that the proposed LMBP is more suitable for analysing and predicting the vibration of the train-rail system. It is clear that the speeds of the trains approaching the level crossing can be estimated from the vibration of the trains on the rails

DESIGN OF NEURAL PREDICTORS FOR PREDICTING AND ANALYSING COVID-19 CASES IN DIFFERENT REGIONS

Nowadays, some unexpected viruses are affecting people with many troubles. COVID-19 virus is spread in the world very rapidly. However, it seems that predicting cases and death fatalities is not easy. Artificial neural networks are employed in many areas for predicting the system's parameters in simulation or real-time approaches. This paper presents the design of neural predictors for analysing the cases of COVID-19 in three countries. Three countries were selected because of their different regions. Especially, these major countries' cases were selected for predicting future effects. Furthermore, three types of neural network predictors were employed to analyse COVID-19 cases. NAR-NN is one of the pro-posed neural networks that have three layers with one input layer neurons, hidden layer neurons and an output layer with fifteen neurons. Each neuron consisted of the activation functions of the tan-sigmoid. The other proposed neural network, ANFIS, consists of five layers with two inputs and one output and ARIMA uses four iterative steps to predict. The proposed neural network types have been selected from many other types of neural network types. These neural network structures are feed-forward types rather than recurrent neural networks. Learning time is better and faster than other types of networks. Finally, three types of neural pre-dictors were used to predict the cases. The R2 and MSE results improved that three types of neural networks have good performance to predict and analyse three region cases of countries

Electrostatic Catalysis of a Click Reaction in a Microfluidic Cell

Electric fields have been highlighted as a smart reagent in nature's enzymatic machinery, as they can directly trigger or accelerate redox and/or non-redox chemical processes with stereo- and regio-specificity. In natural catalysis, controlled mass transport of chemical species in confined spaces is also key in facilitating the transport of reactants into the active reaction site. Despite the opportunities the above offers in developing strategies for a new, clean electrostatic catalysis exploiting oriented electric fields, research in this area has been mostly limited to theoretical and experimental studies at the level of single molecules or small molecular ensembles, where both the control over mass transport and scalability cannot be tested. Here, we quantify the electrostatic catalysis of a prototypical Huisgen cycloaddition in a large-area electrode surface and directly compare its performance to the traditional Cu(I)-catalyzed method of the same reaction. Mass diffusion control is achieved in a custom-built microfluidic cell, which enhances reagent transport towards the electrified reactive interface while avoiding both turbulent flow conditions and poor control of the convective mass transport. This unprecedented electrostatic continuous-flow microfluidic reactor is an example of an electric-field driven platform where clean large-scale electrostatic catalytic processes can be efficiently implemented and regulated.Comment: Main Manuscript part includes 12 pages, 4 figures, 1 table and Supporting Information part includes 20 pages, 8 figures, 1 tabl

Measuring paw preferences in dogs, cats and rats: Design requirements and innovations in methodology

Studying behavioural lateralization in animals holds great potential for answering important questions in laterality research and clinical neuroscience. However, comparative research encounters challenges in reliability and validity, requiring new approaches and innovative designs to overcome. Although validated tests exist for some species, there is yet no standard test to compare lateralized manual behaviours between individuals, populations, and animal species. One of the main reasons is that different fine-motor abilities and postures must be considered for each species. Given that pawedness/handedness is a universal marker for behavioural lateralization across species, this article focuses on three commonly investigated species in laterality research: dogs, cats, and rats. We will present six apparatuses (two for dogs, three for cats, and one for rats) that enable an accurate assessment of paw preference. Design requirements and specifications such as zoometric fit for different body sizes and ages, reliability, robustness of the material, maintenance during and after testing, and animal welfare are extremely important when designing a new apparatus. Given that the study of behavioural lateralization yields crucial insights into animal welfare, laterality research, and clinical neuroscience, we aim to provide a solution to these challenges by presenting design requirements and innovations in methodology across species