Protein secondary structure prediction using three neural networks and a segmental semi Markov model

Prediction of protein secondary structure is an important step towards elucidating its three dimensional structure and its function. This is a challenging problem in bioinformatics. Segmental semi Markov models (SSMMs) are one of the best studied methods in this field. However, incorporating evolutionary information to these methods is somewhat difficult. On the other hand, the systems of multiple neural networks (NNs) are powerful tools for multi-class pattern classification which can easily be applied to take these sorts of information into account.To overcome the weakness of SSMMs in prediction, in this work we consider a SSMM as a decision function on outputs of three NNs that uses multiple sequence alignment profiles. We consider four types of observations for outputs of a neural network. Then profile table related to each sequence is reduced to a sequence of four observations. In order to predict secondary structure of each amino acid we need to consider a decision function. We use an SSMM on outputs of three neural networks. The proposed SSMM has discriminative power and weights over different dependency models for outputs of neural networks. The results show that the accuracy of our model in predictions, particularly for strands, is considerably increased.     

Enhancing Energy Storage Devices with Biomacromolecules in Hybrid Electrodes

The development of energy storage devices with higher energy and power outputs, and long cycling stability is urgently required in the pursuit of the expanding challenges of electrical energy storage. The utilization of biologically renewable redox compounds holds a great potential in designing sustainable energy storage systems and contributes in reducing the dependence on fossil fuels for energy materials. Quinones are the principal redox centers in natural organic materials and play a key role as charge storage electrode materials because of their abundance, multiple forms and integration into the materials flow through the biosphere. Electrical energy storage devices and systems can be significantly improved by the combination of scalable quinone‐based biomaterials with good electronic conductors. This review uses recent examples to show how biopolymers are providing new directions in the development of renewable biohybrid electrodes for energy storage devices.     

Photosynthetic reaction center-functionalized electrodes for photo-bioelectrochemical cells

During the last few years, intensive research efforts have been directed toward the application of several highly efficient light-harvesting photosynthetic proteins, including reaction centers (RCs), photosystem I (PSI), and photosystem II (PSII), as key components in the light-triggered generation of fuels or electrical power. This review highlights recent advances for the nano-engineering of photo-bioelectrochemical cells through the assembly of the photosynthetic proteins on electrode surfaces. Various strategies to immobilize the photosynthetic complexes on conductive surfaces and different methodologies to electrically wire them with the electrode supports are presented. The different photoelectrochemical systems exhibit a wide range of photocurrent intensities and power outputs that sharply depend on the nano-engineering strategy and the electroactive components. Such cells are promising candidates for a future production of biologically-driven solar power.     

Fly-like visuomotor responses of a robot using aVLSI motion-sensitive chips

 We explore the use of continuous-time analog very-large-scale-integrated (aVLSI) neuromorphic visual preprocessors together with a robotic platform in generating bio-inspired behaviors. Both the aVLSI motion sensors and the robot behaviors described in this work are inspired by the motion computation in the fly visual system and two different fly behaviors. In most robotic systems, the visual information comes from serially scanned imagers. This restricts the form of computation of the visual image and slows down the input rate to the controller system of the robot, hence increasing the reaction time of the robot. These aVLSI neuromorphic sensors reduce the computational load and power consumption of the robot, thus making it possible to explore continuous-time visuomotor control systems that react in real-time to the environment. The motion sensor provides two outputs: one for the preferred direction and the other for the null direction. These motion outputs are created from the aggregation of six elementary motion detectors that implement a variant of Reichardt's correlation algorithm. The four analog continuous-time outputs from the motion chips go to the control system on the robot which generates a mixture of two behaviors – course stabilization and fixation – from the outputs of these sensors. Since there are only four outputs, the amount of information transmitted to the controller is reduced (as compared to using a CCD sensor), and the reaction time of the robot is greatly decreased. In this work, the robot samples the motion sensors every 3.3 ms during the behavioral experiments. Received: 4 October 1999 / Accepted in revised form: 26 April 2001     

Microfluidic technologies for studying synthetic circuits

Advances in synthetic biology have augmented the available toolkit of biomolecular modules, allowing engineering and manipulation of signaling in a variety of organisms, ranging in complexity from single bacteria and eukaryotic cells to multi-cellular systems. The richness of synthetic circuit outputs can be dramatically enhanced by sophisticated environmental control systems designed to precisely pattern spatial-temporally heterogeneous environmental stimuli controlling these circuits. Moreover, the performance of the synthetic modules and 'blocks' needed to assemble more complicated networks requires more complete characterization as a function of arbitrarily complex environmental inputs. Microfluidic technologies are poised to meet these needs through a variety of innovative designs capitalizing on the unique benefits of manipulating fluids on the micro-scales and nano-scales. This review discusses the utility of microfluidics for the study of synthetic circuits and highlights recent work in the area.     

Insect circadian clock outputs

Insects display an impressive variety of daily rhythms, which are most evident in their behaviour. Circadian timekeeping systems that generate these daily rhythms of physiology and behaviour all involve three interacting elements: the timekeeper itself (i.e. the clock), inputs to the clock through which it entrains and otherwise responds to environmental cues such as light and temperature, and outputs from the clock through which it imposes daily rhythms on various physiological and behavioural parameters. In insects, as in other animals, cellular clocks are embodied in clock neurons capable of sustained autonomous circadian rhythmicity, and those clock neurons are organized into clock circuits. Drosophila flies spend their entire lives in small areas near the ground, and use their circadian brain clock to regulate daily rhythms of rest and activity, so as to organize their behaviour appropriately to the daily rhythms of their local environment. Migratory locusts and butterflies, on the other hand, spend substantial portions of their lives high up in the air migrating long distances (sometimes thousands of miles) and use their circadian brain clocks to provide time-compensation to their sun-compass navigational systems. Interestingly, however, there appear to be substantial similarities in the cellular and network mechanisms that underlie circadian outputs in all insects.     

Predicting anaerobic capabilities in 11-13-year-old boys

Anaerobic exercise is involved in many recreational and competitive sport activities. This study first established regression equations to predict maximal anaerobic power and then cross-validated these prediction equations. Using stepwise multiple regression analysis prediction equations for relative (watts per kilogram of body mass) and absolute (watts) mean and peak anaerobic power using the 30-second Wingate Test as the power measure were determined for 40 boys (age, 11-13 years). Percentage of body fat, free-fat weight, midthigh circumference, and 30-m dash were the independent predictive variables with the generated regression equations subsequently cross-validated using 20 different boys (age, 11-13 years). Significant correlations (Pearson r) were found for the cross-validation subjects between the measured power outputs and predicted power outputs for relative mean power (r = 0.48, p < 0.05), absolute mean power (r = 0.77, p < 0.01), and absolute peak power (r = 0.76, p < 0.01). Using paired t-tests, no significant mean differences (p > 0.05) were found for the same subjects between actual and predicted power outputs for relative mean power, absolute mean power, and absolute peak power. Prediction of maximal anaerobic power from selected anthropometric measurements and 30-m dash appears tenable in 11-13-year-old boys and can be accomplished in a simple cost- and time-effective manner.     

A microprocessor-regulated constant voltage, current, wattage, and temperature electrophoresis power supply

The analog control circuitry typically found in commercial electrophoresis power supplies was replaced by a digital microcomputer. Analog to digital converters were used to monitor the voltage applied to and current passed through an electrophoresis cell. Microcomputer programming was employed to compare converter input values with preselected operating parameters and then calculate a required output voltage. Timing sequences were generated through programming utilizing clocks located on the interface boards. A digital to analog converter was employed to apply a control voltage to a constant voltage power supply. This process was completed at least 20 times each second. BASIC programming subroutines were written to maintain constant voltage, current, power (wattage), and temperature. To these operating procedures, other techniques such as automated endpoint detection of isoelectric focusing and pulsed waveform outputs were easily added. This power supply containing a microcomputer system as the feedback element was shown to have a greater stability and versatility than conventional supplies.     

Comparison of power output by rice (Oryza sativa) and an associated weed (Echinochloa glabrescens) in vascular plant bio-photovoltaic (VP-BPV) systems

Vascular plant bio-photovoltaics (VP-BPV) is a recently developed technology that uses higher plants to harvest solar energy and the metabolic activity of heterotrophic microorganisms in the plant rhizosphere to generate electrical power. In the present study, electrical output and maximum power output variations were investigated in a novel VP-BPV configuration using the crop plant rice (Oryza sativa L.) or an associated weed, Echinochloa glabrescens (Munro ex Hook. f.). In order to compare directly the physiological performances of these two species in VP-BPV systems, plants were grown in the same soil and glasshouse conditions, while the bio-electrochemical systems were operated in the absence of additional energy inputs (e.g. bias potential, injection of organic substrate and/or bacterial pre-inoculum). Diurnal oscillations were clearly observed in the electrical outputs of VP-BPV systems containing the two species over an 8-day growth period. During this 8-day period, O. sativa generated charge ～6 times faster than E. glabrescens. This greater electrogenic activity generated a total charge accumulation of 6.75?±?0.87 Coulombs for O. sativa compared to 1.12?±?0.16 for E. glabrescens. The average power output observed over a period of about 30 days for O. sativa was significantly higher (0.980?±?0.059 GJ?ha^?1?year^?1) than for E. glabrescens (0.088?±?0.008 GJ?ha^?1?year^?1). This work indicates that electrical power can be generated in both VP-BPV systems (O. sativa and E. glabrescens) when bacterial populations are self-forming. Possible reasons for the differences in power outputs between the two plant species are discussed.     

Sprint performance-duration relationships are set by the fractional duration of external force application

We hypothesized that the maximum mechanical power outputs that can be maintained during all-out sprint cycling efforts lasting from a few seconds to several minutes can be accurately estimated from a single exponential time constant (k(cycle)) and two measurements on individual cyclists: the peak 3-s power output (P(mech max)) and the maximum mechanical power output that can be supported aerobically (P(aer)). Tests were conducted on seven subjects, four males and three females, on a stationary cycle ergometer at a pedal frequency of 100 rpm. Peak mechanical power output (P(mech max)) was the highest mean power output attained during a 3-s burst; the maximum power output supported aerobically (P(aer)) was determined from rates of oxygen uptake measured during a progressive, discontinuous cycling test to failure. Individual power output-duration relationships were determined from 13 to 16 all-out constant load sprints lasting from 5 to 350 s. In accordance with the above hypothesis, the power outputs measured during all-out sprinting efforts were estimated to within an average of 34 W or 6.6% from P(mech max), P(aer), and a single exponential constant (k(cycle) = 0.026 s(-1)) across a sixfold range of power outputs and a 70-fold range of sprint trial durations (R2 = 0.96 vs. identity, n = 105; range: 180 to 1,136 W). Duration-dependent decrements in sprint cycling power outputs were two times greater than those previously identified for sprint running speed (k(run) = 0.013 s(-1)). When related to the respective times of pedal and ground force application rather than total sprint time, decrements in sprint cycling and running performance followed the same time course (k = 0.054 s(-1)). We conclude that the duration-dependent decrements in sprinting performance are set by the fractional duration of the relevant muscular contractions.     

A Water‐Proof Triboelectric–Electromagnetic Hybrid Generator for Energy Harvesting in Harsh Environments

Packaging is a critical aspect of triboelectric nanogenerators (TENG) toward practical applications, since the performance of TENG is greatly affected by environmental conditions such as humidity. A waterproof triboelectric–electromagnetic hybrid generator (WPHG) for harvesting mechanical energy in harsh environments is reported. Since the mechanical transmission from the external mechanical source to the TENG is through a noncontact force between the paired magnets, a fully isolated packaging of TENG part can be easily achieved. At the same time, combining with metal coils, these magnets can be fabricated to be electromagnetic generators (EMG). The characteristics and advantages of outputs from both TENG and EMG are systematically studied and compared to each other. By using transformers and full‐wave rectifiers, 2.3 mA for total short‐circuit current and 5 V for open‐circuit voltage are obtained for WPHG under a rotation speed of 1600 rpm, and it can charge a supercapacitor (20 mF) to 1 V in 22s. Finally, the WPHG is demonstrated to harvest wind energy in the rainy condition and water‐flow energy under water. The reported WPHG renders an effective and sustainable technology for ambient mechanical energy harvesting in harsh environments. Solid progress in both the packaging of TENG and the practical applications of the hybrid generator toward practical power source and self‐powered systems is presented.     

Demystifying global climate models for use in the life sciences

For each assessment cycle of the Intergovernmental Panel on Climate Change (IPCC), researchers in the life sciences are called upon to provide evidence to policymakers planning for a changing future. This research increasingly relies on highly technical and complex outputs from climate models. The strengths and weaknesses of these data may not be fully appreciated beyond the climate modelling community; therefore, uninformed use of raw or preprocessed climate data could lead to overconfident or spurious conclusions. We provide an accessible introduction to climate model outputs that is intended to empower the life science community to robustly address questions about human and natural systems in a changing world.     

Muscle metabolism, blood lactate and oxygen uptake in steady state exercise at aerobic and anaerobic thresholds

Muscle metabolites and blood lactate concentration were studied in five male subjects during five constant-load cycling exercises. The power outputs were below, equal to and above aerobic (AerT) and anaerobic (AnT) threshold as determined during an incremental leg cycling test. At AerT, muscle lactate had increased significantly (p less than 0.05) from the rest value of 2.31 to 5.56 mmol X kg-1 wet wt. This was accompanied by a significant reduction in CP by 28% (p less than 0.05), whereas only a minor change (9%) was observed for ATP. At AnT muscle lactate had further increased and CP decreased although not significantly as compared with values at AerT. At the highest power outputs (greater than AnT) muscle lactate had increased (p less than 0.01) and CP decreased (p less than 0.01) significantly from the values observed at AnT. Furthermore, a significant reduction (p less than 0.05) in ATP over resting values was recorded. Blood lactate decreased significantly (p less than 0.01) during the last half of the lowest 5 min exercise, remained unchanged at AerT and increased significantly (p less than 0.05-0.01) at power outputs greater than or equal to AnT. It is concluded that anaerobic muscle metabolism is increased above resting values at AerT: at low power outputs (less than or equal to AerT) this could be related to the transient oxygen deficit during the onset of exercise or the increase in power output. At high power outputs (greater than AnT) anaerobic energy production is accelerated and it is suggested that AnT represents the upper limit of power output where lactate production and removal may attain equilibrium during constant load exercise.     

Positive-feedback loops in cell cycle progression

A positive-feedback loop is a simple motif that is ubiquitous to the modules and networks that comprise cellular signaling systems. Signaling behaviors that are synonymous with positive feedback include amplification and rapid switching, maintenance, and the coherence of outputs. Recent advances have been made towards understanding how positive-feedback loops function, as well as their mechanistic basis in controlling eukaryotic cell cycle progression. Some of these advances will be reviewed here, including: how cyclin controls passage through Start and maintains coherence of G1/S regulon expression in yeast; how Polo-like kinase 1 activation is driven by Bora and Aurora A, and its expression is stimulated by Forkhead Box M1 in mammalian cells; and how some of the various dynamic behaviors of spindle assembly and anaphase onset can be produced.     

Total power output generated during dynamic knee extensor exercise at different contraction frequencies.

A novel approach has been developed for the quantification of total mechanical power output produced by an isolated, well-defined muscle group during dynamic exercise in humans at different contraction frequencies. The calculation of total power output comprises the external power delivered to the ergometer (i.e., the external power output setting of the ergometer) and the "internal" power generated to overcome inertial and gravitational forces related to movement of the lower limb. Total power output was determined at contraction frequencies of 60 and 100 rpm. At 60 rpm, the internal power was 18+/- 1 W (range: 16-19 W) at external power outputs that ranged between 0 and 50 W. This was less (P<0.05) than the internal power of 33+/-2 W (27-38 W) at 100 rpm at 0-50 W. Moreover, at 100 rpm, internal power was lower (P<0.05) at the higher external power outputs. Pulmonary oxygen uptake was observed to be greater (P<0.05) at 100 than at 60 rpm at comparable total power outputs, suggesting that mechanical efficiency is lower at 100 rpm. Thus a method was developed that allowed accurate determination of the total power output during exercise generated by an isolated muscle group at different contraction frequencies.     

Mixed crop-livestock systems: an economic and environmental-friendly way of farming?

Intensification and specialisation of agriculture in developed countries enabled productivity to be improved but had detrimental impacts on the environment and threatened the economic viability of a huge number of farms. The combination of livestock and crops, which was very common in the past, is assumed to be a viable alternative to specialised livestock or cropping systems. Mixed crop-livestock systems can improve nutrient cycling while reducing chemical inputs and generate economies of scope at farm level. Most assumptions underlying these views are based on theoretical and experimental evidence. Very few assessments of their environmental and economic advantages have nevertheless been undertaken in real-world farming conditions. In this paper, we present a comparative assessment of the environmental and economic performances of mixed crop-livestock farms v. specialised farms among the farm population of the French ‘Coteaux de Gascogne’. In this hilly region, half of the farms currently use a mixed crop-livestock system including beef cattle and cash crops, the remaining farms being specialised in either crops or cattle. Data were collected through an exhaustive survey of farms located in our study area. The economic performances of farming systems were assessed on 48 farms on the basis of (i) overall gross margin, (ii) production costs and (iii) analysis of the sensitivity of gross margins to fluctuations in the price of inputs and outputs. The environmental dimension was analysed through (i) characterisation of farmers’ crop management practices, (ii) analysis of farm land use diversity and (iii) nitrogen farm-gate balance. Local mixed crop-livestock farms did not have significantly higher overall gross margins than specialised farms but were less sensitive than dairy and crop farms to fluctuations in the price of inputs and outputs considered. Mixed crop-livestock farms had lower costs than crop farms, while beef farms had the lowest costs as they are grass-based systems. Concerning crop management practices, our results revealed an intensification gradient from low to high input farming systems. Beyond some general trends, a wide range of management practices and levels of intensification were observed among farms with a similar production system. Mixed crop-livestock farms were very heterogeneous with respect to the use of inputs. Nevertheless, our study revealed a lower potential for nitrogen pollution in mixed crop-livestock and beef production systems than in dairy and crop farming systems. Even if a wide variability exists within system, mixed crop-livestock systems appear to be a way for an environmental and economical sustainable agriculture.     

Power series expansion and structural analysis for life cycle assessment

Goal, Scope and Background The usefulness of power series expansion for an LCA system has often been doubted, as those systems may not possess the unique properties that enable power series expansion and analyses based on the power series. This paper surveys the existing literature on power series expansion of monetary input-output system and discusses how the power series expansion can be utilized for more general systems including the LCA model. Methods The inherent properties of matrices that are capable of producing power series forms for their inverse and, further, can utilize structural path analysis are analyzed. Using these analyses, the way how a matrix that is not eligible for structural analyses is converted into an eligible form is investigated. A numerical example is presented to demonstrate the findings. Results The necessary and sufficient condition for an indecomposable, real square technology matrix can be expressed using power series was identified. Two additional conditions for a technology matrix to be utilized for structural analyses using power series expansion are discussed as well. It was also shown that an LCA system that fulfills the Hawkins-Simon condition can be easily converted into the form that is eligible for structural analysis by rescaling the columns and rows. Discussion As a numerical example, an application of accumulative structural path analysis for an LCA system is shown. The implications of the results are discussed in a more plain language as well. Conclusions The survey presented in this paper provides not only the conditions under which a linear system is expressed using a power series form but also the way to appropriately convert a system to utilize the rich analytical tools using power series expansion for structural analyses. Recommendations and Perspectives Widely used LCA databases and software tools have employed the linear systems approach as the basis. Much of these developments in the domain of LCA have been made, however, in isolation of the rich findings of IOA. There will be much to benefit LCA through an active dialogue between the two disciplines. There are rich analytical tools available through the use of power series expansion. The current survey will help software developers and LCA practitioners to apply such tools in LCA.     

'Non-destructive' biocomputing security system based on gas-controlled biofuel cell and potentially used for intelligent medical diagnostics

MOTIVATION: Biofuel cells (BFCs) based on enzymes and microbes are the promising future alternative sources of sustainable electrical energy under mild conditions (i.e. ambient temperature and neutral pH). By combining the adaptive behavior of BFCs self-regulating energy release with the versatility of biocomputing, we construct a novel gas-controlled biocomputing security system, which could be used as the potential implantable self-powered and 'smart' medical system with the logic diagnosis aim. RESULTS: We have demonstrated a biocomputing security system based on BFCs. Due to the unique 'RESET' reagent of N(2) applied in this work, the prepared biocomputing security system can be reset and cycled for a large number of times with no 'RESET' reagent-based 'waste'. This would be advantageous for the potential practical applications of such keypad lock as well as the development of biocomputing security devices. In order to validate the universality of the system and also to harvest energy directly from biofuels with enhanced power output, we replace the glucose with orange juice as the biofuel to operate BFCs-based biocomputing system, which also possesses the function of keypad lock. In addition, by introducing BFCs into the biocomputing security system, the adaptive behavior of the BFCs self-regulating the power release would be an immense advantage of such security keypad lock devices in potential self-powered implantable medical systems. The designed sequence gives the maximum power output and discriminate itself from the rest of the sequences. From this, we find that maximizing the dimensionless ratio of gap versus SD of the power output spectrum (a funnel in power outputs) gives the quantitative optimal design criterion. Therefore, our construction here may also provide a practical example and microscopic structural basis for mimicking the real biological network systems and bridge the gaps between the theoretical concepts and experiments important for biomolecular systems and synthetic biology.     

The theoretical limits to the power output of a muscle-tendon complex with inertial and gravitational loads

When a muscle delivers power to an inertial load through a spring, the peak power can exceed the maximum that the muscle alone could produce. Using normalized differential equations relating dimensionless quantities we show, by solving the equations either analytically or numerically, that one dimensionless constant (Xi), representing the inertial load, is sufficient to specify the behaviour during shortening of a muscle-tendon complex with linear force-velocity and force-extension properties. In the presence of gravity, an additional constant (Gamma), representing the gravitational acceleration, is required. Nonlinear force-velocity and force-extension relationships each introduce an additional constant, representing their curvature. In the absence of gravity the power output delivered to an inertial load is limited to approximately 1.4 times the maximum power of the muscle alone, and when gravity is present the power delivered is limited to approximately twice the power of muscle alone. These limits are found for the purely inertial load at Xi ca. 1 and with gravity acting at XiGamma = 0.5 with Xi arbitrarily small. The effects of nonlinear muscle and tendon properties tend to cancel each other out and do not produce large deviations from these optima. A lever system of constant ratio between muscle and load does not alter these limits. Cams and catches are required to exceed these limits and attain the high power outputs sometimes observed during explosive animal movement.     

Minimal models of multidimensional computations

The multidimensional computations performed by many biological systems are often characterized with limited information about the correlations between inputs and outputs. Given this limitation, our approach is to construct the maximum noise entropy response function of the system, leading to a closed-form and minimally biased model consistent with a given set of constraints on the input/output moments; the result is equivalent to conditional random field models from machine learning. For systems with binary outputs, such as neurons encoding sensory stimuli, the maximum noise entropy models are logistic functions whose arguments depend on the constraints. A constraint on the average output turns the binary maximum noise entropy models into minimum mutual information models, allowing for the calculation of the information content of the constraints and an information theoretic characterization of the system's computations. We use this approach to analyze the nonlinear input/output functions in macaque retina and thalamus; although these systems have been previously shown to be responsive to two input dimensions, the functional form of the response function in this reduced space had not been unambiguously identified. A second order model based on the logistic function is found to be both necessary and sufficient to accurately describe the neural responses to naturalistic stimuli, accounting for an average of 93% of the mutual information with a small number of parameters. Thus, despite the fact that the stimulus is highly non-Gaussian, the vast majority of the information in the neural responses is related to first and second order correlations. Our results suggest a principled and unbiased way to model multidimensional computations and determine the statistics of the inputs that are being encoded in the outputs.