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

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

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

Magnetoelectric Effect in Hydrogen Harvesting: Magnetic Field as a Trigger of Catalytic Reactions (Adv. Mater. 19/2022)

Magnetic fields have been regarded as an additional stimulus for electro- and photocatalytic reactions, but not as a direct trigger for catalytic processes. Multiferroic/magnetoelectric materials, whose electrical polarization and surface charges can be magnetically altered, are especially suitable for triggering and control of catalytic reactions solely with magnetic fields. Here, we demonstrate that magnetic fields can be employed as an independent input energy source for hydrogen harvesting by means of the magnetoelectric effect. Composite multiferroic CoFe2O4-BiFeO3 core-shell nanoparticles act as catalysts for the hydrogen evolution reaction (HER) that is triggered when an alternating magnetic field is applied to an aqueous dispersion of the magnetoelectric nanocatalysts. Based on density functional calculations, we propose that the hydrogen evolution is driven by changes in the ferroelectric polarization direction of BiFeO3 caused by the magnetoelectric coupling. We believe our findings will open new avenues towards magnetically induced renewable energy harvesting

Data mining to identify risk factors associated with university students dropout

. This paper presents the identification of university students dropout patterns by means of data mining techniques. The database consists of a series of questionnaires and interviews to students from several universities in Colombia. The information was processed by the Weka software following the Knowledge Extraction Process methodology with the purpose of facilitating the interpretation of results and finding useful knowledge about the students. The partial results of data mining processing on the information about the generations of students of Industrial Engineering from 2016 to 2018 are analyzed and discussed, finding relationships between family, economic, and academic issues that indicate a probable desertion risk in students with common behaviors. These relationships provide enough and appropriate information for the decision-making process in the treatment of university dropout.Universidad Peruana de Ciencias Aplicadas, Universidad de la Costa, Universidad Libre Seccional Barranquilla, Corporación Universitaria Latinoamericana

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

Dropout-permanence analysis of university students using data mining

Dropout is a rejection method present in every educational system, related to the various selection processes, academic performance, and the efficiency of the system in general, that is, the result of the combination and effect of different variables. In this sense, the dropout of university students related to their academic performance is a matter of concern since several years ago. Academic information is analyzed in order to identify factors that influence students´ dropout at the University of Mumbai, India, by using a data mining technique. The data source contains information provided to the entrance (personal and educational background) and that is generated during the study period. The data selection and cleansing are made using different criteria of representation and implementation of classification algorithms such as decision trees, Bayesian networks, and rules. the following factors are identified as influential variables in the desertion: approved courses, quantity and results of attended courses, origin and age of entry of the student. Through this process, it was possible to identify the attributes that characterize the dropout cases and their relationship with the academic performance, especially in the first year of the career

Intelligent and Distributed Data Warehouse for Student’s Academic Performance Analysis

In the academic world, a large amount of data is handled each day, ranging from student’s assessments to their socio-economic data. In order to analyze this historical information, an interesting alternative is to implement a Data Warehouse. However, Data Warehouses are not able to perform predictive analysis by themselves, so machine intelligence techniques can be used for sorting, grouping, and predicting based on historical information to improve the analysis quality. This work describes a Data Warehouse architecture to carry out an academic performance analysis of students

Cost-Effectiveness of Treating Multidrug-Resistant Tuberculosis

BACKGROUND: Despite the existence of effective drug treatments, tuberculosis (TB) causes 2 million deaths annually worldwide. Effective treatment is complicated by multidrug-resistant TB (MDR TB) strains that respond only to second-line drugs. We projected the health benefits and cost-effectiveness of using drug susceptibility testing and second-line drugs in a lower-middle-income setting with high levels of MDR TB. METHODS AND FINDINGS: We developed a dynamic state-transition model of TB. In a base case analysis, the model was calibrated to approximate the TB epidemic in Peru, a setting with a smear-positive TB incidence of 120 per 100,000 and 4.5% MDR TB among prevalent cases. Secondary analyses considered other settings. The following strategies were evaluated: first-line drugs administered under directly observed therapy (DOTS), locally standardized second-line drugs for previously treated cases (STR1), locally standardized second-line drugs for previously treated cases with test-confirmed MDR TB (STR2), comprehensive drug susceptibility testing and individualized treatment for previously treated cases (ITR1), and comprehensive drug susceptibility testing and individualized treatment for all cases (ITR2). Outcomes were costs per TB death averted and costs per quality-adjusted life year (QALY) gained. We found that strategies incorporating the use of second-line drug regimens following first-line treatment failure were highly cost-effective compared to strategies using first-line drugs only. In our base case, standardized second-line treatment for confirmed MDR TB cases (STR2) had an incremental cost-effectiveness ratio of $720 per QALY ($8,700 per averted death) compared to DOTS. Individualized second-line drug treatment for MDR TB following first-line failure (ITR1) provided more benefit at an incremental cost of $990 per QALY ($12,000 per averted death) compared to STR2. A more aggressive version of the individualized treatment strategy (ITR2), in which both new and previously treated cases are tested for MDR TB, had an incremental cost-effectiveness ratio of $11,000 per QALY ($160,000 per averted death) compared to ITR1. The STR2 and ITR1 strategies remained cost-effective under a wide range of alternative assumptions about treatment costs, effectiveness, MDR TB prevalence, and transmission. CONCLUSIONS: Treatment of MDR TB using second-line drugs is highly cost-effective in Peru. In other settings, the attractiveness of strategies using second-line drugs will depend on TB incidence, MDR burden, and the available budget, but simulation results suggest that individualized regimens would be cost-effective in a wide range of situations