Analysis of the Earthʼs magnetic field variations on the basis of a wavelet-based approach

In the present paper we will discuss a new wavelet-based approach aimed at processing and analyzing different features of complex geomagnetic signals. This approach makes it possible to automatically extract different kinds of disturbances in the Earth?s magnetic field variations, which characterize solar activity and help to predict magnetic storms. In order to analyze geomagnetic signals wavelet packets are used in order to isolate local variations for quiet and perturbed periods and determine their intensity. Furthermore, a new automatic method of calculating the index of geomagnetic activity K is suggested on the basis of forming a quiet-day diurnal variation (Sq-curve). This method allows us to do calculations in the way that is closest to that developed by J. Bartels, who introduced the K-index in 1938. The results are compared with those obtained by INTERMAGNET and the original method of J. Bartels and the advantages of the suggested method are clearly demonstrated. For geomagnetic data collected in high-latitude regions of our planet it has become possible to reduce the error of estimating the K-index by 20% and unlike the technique used by INTERMAGNET here all the calculations can be done automatically. We will use geomagnetic signals that were kindly provided to us by the Institute of Cosmophysical Research and Radio Wave Propagation (Paratunka, Kamchatka region, Far East of Russia) for the period from January, 2002 till December, 2010.     

Comparison of an effect-model-law-based method versus traditional clinical practice guidelines for optimal treatment decision-making: application to statin treatment in the French population

Healthcare authorities make difficult decisions about how to spend limited budgets for interventions that guarantee the best cost-efficacy ratio. We propose a novel approach for treatment decision-making, OMES—in French: Objectif thérapeutique Modèle Effet Seuil (in English: Therapeutic Objective–Threshold–Effect Model; TOTEM). This approach takes into consideration results from clinical trials, adjusted for the patients'' characteristics in treatment decision-making. We compared OMES with the French clinical practice guidelines (CPGs) for the management of dyslipidemia with statin in a computer-generated realistic virtual population, representing the adult French population, in terms of the number of all-cause deaths avoided (number of avoided events: NAEs) under treatment and the individual absolute benefit. The total budget was fixed at the annual amount reimbursed by the French social security for statins. With the CPGs, the NAEs was 292 for an annual cost of 122.54 M€ compared with 443 with OMES. For a fixed NAEs, OMES reduced costs by 50% (60.53 M€ yr⁻¹). The results demonstrate that OMES is at least as good as, and even better than, the standard CPGs when applied to the same population. Hence the OMES approach is a practical, useful alternative which will help to overcome the limitations of treatment decision-making based uniquely on CPGs.     

Software features for the estimation of an operators’ group activity in man-machine system

Methods for the selection of candidates for operators of man-machine systems are analyzed. Vector mean estimates of group intelligence and estimates defining the group’s collective decision-making ability to obtain the unified solution to the selection problem and to retain the correct original solution to the problem, and estimates of solution quality and interoperability in correct decision-making are proposed. The properties of the suggested estimates are studied with a test example of five candidates. Amongst these properties are estimates of the group’s psychological traits, such as average estimates of professional competence, static components of the intelligence vector for tested candidates, components of the trainability vector for tested candidates, average intelligence estimates for tested candidates, average estimates for the basis of groups, average different-mindedness estimates of groups, variations in the trainability of operators, and arithmetic estimates of group intelligence variability such as levels of awareness, knowledge level, mean speed of knowledge variation, comprehension and motivation in operators’ reasoning.     

Synthesis,Enzymatic Evaluation,and Docking Studies of Fluorogenic Caspase 8 Tetrapeptide Substrates

The synthesis, enzymatic evaluation, and molecular modeling studies of new fluorogenic tetrapeptide‐based substrates selective for caspase 8, having the general structure Ac‐IETD–AXX, are described. Various fluorescent reporter groups (AXX), i.e., 3‐ and 4‐substituted coumarins and quinolin‐2(1H)‐ones were synthesized by von Pechmann condensation. They were subsequently coupled with the caspase‐8‐selective tetrapeptide Ac‐IETD‐OH under newly developed synthetic conditions to give the desired substrates in good yields and in high enantiomeric purity. Based on K_M and V_max values, the new compounds proved to be excellent substrates for recombinant human caspase 8. In contrast, the K_M values for the same compounds as substrates for human caspase 3 were approximately 10–20‐fold higher. Molecular modeling studies based on the X‐ray crystal structures of both human caspases 3 and 8 revealed that there is sufficient room within both active sites to accommodate substrates with moderately bulky substituents in the 3‐ and 4‐positions of the fluorogenic coumarins and quinolin‐2(1H)‐ones. Automated docking of the substrates into the active sites of both human caspases 3 and 8 with the program AutoDock 3 gave structures similar to the published crystallographic structures for the same tetrapeptide bound to caspase 8 in the form of an irreversible inhibitor. The calculated binding energies for the new substrates to either caspase 3 or 8 showed little difference between the substrates, consistent with the K_M data. In addition, the calculated binding energies (ΔG) to caspase 8 were considerably more negative than those to caspase 3, also consistent with the K_M data. A possible molecular interaction that might explain the selectivity of the IETD tetrapeptide motif for caspase 8 over caspase 3 is discussed.     

Effects of Speeds,Materials, and Tool Rake Angles on Metallic Particle Emission During Orthogonal Cutting

Dry high speed machining has been proposed as a viable and cost-effective process in metal cutting industries. However, it produces fine and ultra-fine metallic particles, also referred to as dust, which can be harmful to the machine-tool operator. The risk associated with exposure to metallic particles increases as the particle size decreases. For machining processes, little data exist on the size and distribution of dust generated during the shaping of materials. In order to reduce or eliminate the generation of these particles, it is necessary to understand how and under which conditions they are formed, as well as to be able to make predictions. In this study, the effects exerted by tool geometry, material, and machining parameters on dust emission were studied experimentally in order to understand the mechanisms of dust generation and to develop a predictive model. The particle sizes studied include the PM2.5 (particles with aerodynamique diameter below 2.5 μm) and a distribution of nanoparticles varying in size from 10 nm to 10 μm. Using dry machining and reducing the amount of dust generated should improve the air quality in machine shops in addition to helping protect the environment.     

Modeling of Particle Emission During Dry Orthogonal Cutting

Because of the risks associated with exposure to metallic particles, efforts are being put into controlling and reducing them during the metal working process. Recent studies by the authors involved in this project have presented the effects of cutting speeds, workpiece material, and tool geometry on particle emission during dry machining; the authors have also proposed a new parameter, named the dust unit (D _u), for use in evaluating the quantity of particle emissions relative to the quantity of chips produced during a machining operation. In this study, a model for predicting the particle emission (dust unit) during orthogonal turning is proposed. This model, which is based on the energy approach combined with the microfriction and the plastic deformation of the material, takes into account the tool geometry, the properties of the worked material, the cutting conditions, and the chip segmentation. The model is validated using experimental results obtained during the orthogonal turning of 6061-T6 aluminum alloy, AISI 1018, AISI 4140 steels, and grey cast iron. A good agreement was found with experimental results. This model can help in designing strategies for reducing particle emission during machining processes, at the source.     

Biotechnical measurement and software system controlled features for determining the level of psycho-emotional tension on man-machine systems by fuzzy measures

A new software technique for determining emotional tension on humans is developed by means of psychological tests connected with the psycho-emotional sphere and on indicators characterizing the state of a subject’s visual attention. Each of these two areas determines several factors for psycho-emotional tension. The level of tension is determined as an aggregate of these two components with the rules of fuzzy logic. The membership functions and solving rules for the psychological tests, and for the state of visual attention, are constructed using fuzzy logic theory. It is shown that the resulting method can be used as an informative feature for prediction of many properties, such as the situational awareness (training and experience) of an operator and the operator’s individual capacity to function (mental-physiological limits). The second group of indicators characterize properties such as switchable attention (the ability to switch attention) (SWA), concentration (ability to concentrate) (CNA), stability of visual attention (STA) and parameters determining the state of memory. One of the most important issues for man-machine systems is to evaluate the performance of operators under abnormal conditions such as stress or tension.     

Phytochemical and biological investigation of <Emphasis Type="Italic">Stevia rebaudiana</Emphasis> Bertoni; 1-labdane-type diterpene

Five labdane diterpenoids, austroinulin, iso-austroinulin, sterebin E, sterebin E acetate, and sterebin A acetate, along with hydrocarbons, aliphatic alcohols, β-amyrin, β-sitosterol and stigmasterol were isolated from the chloroform soluble fraction of the methanol extract of Stevia rebaudiana leaves. Chlorogenic and caffeic acids were isolated from the EtOAc fraction. All the isolated compounds were identified using spectral tools. The chloroform and methanol extracts proved significant anti-inflammatory effect and caused marked inhibition of carrageenan-induced paw oedema in rats.     

National surveillance of poultry diseases in Lebanon

From 1992 to mid-1996, a national survey of poultry diseases in Lebanon was conducted. This surveillance included meat breeder, layer breeder, commercial layer and chicken broiler flocks. The history, signs, lesions and laboratory tests of poultry were used in the diagnosis of prevalent poultry diseases. Culture techniques were used to screen for bacterial diseases; serological techniques and, to a lesser extent, culture techniques were used to diagnose viral diseases; and both serological and culture techniques were used to diagnose Mycoplasma infections. The outbreaks of diseases detected in broiler breeder flocks and the number of such flocks experiencing these diseases were as follows: femoral head necrosis (6), egg-drop syndrome (3), reovirus-associated malabsorption syndrome (3), synovitis (Mycoplasma synoviae infection) (7), swollen head syndrome (SHS) (3), tenosynovitis (viral arthritis) (1), lymphoid leukosis (3), avian encephalomyelitis (1), fowl pox (1) and aortic rupture (1). The disease outbreaks detected in layer breeders were as follows: SHS (2), bumble foot (2), egg-drop syndrome (3) and avian infectious bronchitis (IB) (1). The disease outbreaks detected in commercial layer flocks were as follows: egg-drop syndrome (5), avian infectious laryngotracheitis (2), avian IB (nephrogenic strain) (1), malabsorption (1), avian tuberculosis (Mycobacterium avium) (1), Marek's disease (1), fowl pox (1), Salmonella enterica subsp. enterica Enteritidis infection (1), salpingitis (1) and Heterakis gallinae infestation (1). The disease outbreaks detected in broiler flocks were as follows: colibacillosis (40), infectious bursal disease (Gumboro disease) (15), malabsorption syndrome (8), avian infectious laryngotracheitis (8), paratyphoids (salmonellosis) (7), femoral head necrosis (8), SHS (6), avian mycoplasmosis (Mycoplasma gallisepticum infection) (6), synovitis (7), avian IB (6), botulism (1), avian encephalomyelitis (1) and gangrenous dermatitis (1). Diseases which occurred and which were reported for the first time in Lebanon were as follows: bumble foot, femoral head necrosis, avian IB (nephrogenic strain), malabsorption syndrome and SHS. This surveillance helped to establish baseline data concerning the predominant poultry diseases in Lebanon. Such information is a prerequisite for future regional and international collaboration to identify the source of the aetiological agents and to control their spread to neighbouring countries.     

Explosive chemistry: Simulating the chemistry of energetic materials at extreme conditions

In this article, we review recent atomistic computational techniques to study the electronic structure aspects and chemistry of energetic materials at high-pressure and/or high temperature. While several mechanisms have been proposed for the initial events of energetic materials at high-pressure, we explore the validity of a proposed shear-induced local metallization via molecular bond bending in the insensitive explosive TATB. We study the effect of high-stress (both uniform and uniaxial) on the electronic energy band-gap and the first chemical event of a prototypical energetic material, that of nitromethane. We also determine chemical reactions rate laws and decomposition mechanisms from a quantum-based molecular dynamics simulation of HMX, a widely used explosive material, at conditions of high density and temperature similar to that encounter under detonation. Finally, we review a new multi-scale computational tool recently developed to model the shock-induced chemistry of energetic materials at the atomistic level, and report its applicability to shocked solid nitromethane. This revised version was published online in June 2006 with corrections to the Cover Date.