Origins of molecular neurobiology:The role of the physicists

The revolution in the foundations of physics at the beginning of the twentieth century suggested to several of its most prominent workers that biology was ripe for something similar. In consequence, a number of physicists moved into biology. They were highly influential in initiating a molecular biology in the 1950s. Two decades later it seemed to several of these migrants, and those they had influenced, that the major problems in molecular biology had been solved, and that it was time to move on to what seemed to them the final problem: the nervous system, consciousness, and the age-old mind-body problem. This paper reviews this "double migration" and shows how the hopes of the first generation of physicist-biologists were both realized and dashed. No new physical principles were discovered at work in the foundations of biology or neuroscience. On the other hand, the mind-set of those trained in physics proved immensely valuable in analyzing fundamental issues in both biology and neuroscience. It has been argued that the outcome of the molecular biology of the 1950s was a change in the concept of the gene from that of "a mysterious entity into that of a real molecular object" (Watson, 1965, p.6); the gates and channels which play such crucial roles in the functioning of nervous systems have been transformed in a similar way. Studies on highly simplified systems have also opened the prospect of finding the neural correlatives of numerous behaviors and neuropathologies. This increasing understanding at the molecular level is invaluable not only in devising rational therapies but also, by defining the material substrate of consciousness, in bringing the mind-body problem into sharper focus. Copyright © Taylor & Francis Inc.

The 'hard problem' and the quantum physicists. Part 1:the first generation

All four of the most important figures in the early twentieth-century development of quantum physics-Niels Bohr, Erwin Schroedinger, Werner Heisenberg and Wolfgang Pauli-had strong interests in the traditional mind-brain, or 'hard,' problem. This paper reviews their approach to this problem, showing the influence of Bohr's complementarity thesis, the significance of Schroedinger's small book, 'What is life?,' the updated Platonism of Heisenberg and, perhaps most interesting of all, the interaction of Carl Jung and Wolfgang Pauli in the latter's search for a unification of mind and matter. © 2005 Elsevier Inc. All rights reserved.

Lewy body and Alzheimer pathology in temporal lobe in dementia with Lewy bodies

The density of Lewy bodies (LB), senile plaques (SP), and neurofibrillary tangles (NFT) was studied in the temporal lobe in four patients diagnosed with ‘pure’ dementia with Lewy bodies (DLB) and eight patients diagnosed with DLB with associated Alzheimer’s disease (DLB/AD). In both patient groups, the density of LB was greatest in the lateral occipitotemporal gyrus (LOT) and least in areaas CA1 and CA4 of the hippocampus. In DLB/AD, the densities of SP and NFT were greatest in the cortical regions and in area CA1 of the hippocampus respectively. Mean LB densities in the temporal lobe were similar in ‘pure’ DLB and DLB/AD patients but mean SP and NFT densities were greater in DLB/AD. No significant correlations were observed between the densities of LB, SP and NFT in any brain region. The data suggest that in the temporal lobe LB and SP/NFT are distributed differently; SP and NFT in DLB/AD are distributed similarly to ‘pure’ AD and also that LB and AD pathologies appear to develop independently. Hence, the data support the hypothesis that some cases of DLB combine the features of DLB and AD.

The 'hard problem' and the quantum physicists. Part 2: modern times

This is the second part of a review of the work of quantum physicists on the ‘hard part’ of the problem of mind. After an introduction which sets the scene and a brief review of contemporary work on the neural correlates of consciousness (NCC) the work of four prominent modern investigators is examined: J.C. Eccles/Friedrich Beck; Henry Stapp; Stuart Hameroff/Roger Penrose; David Bohm. With the exception of David Bohm, all attempt to show where in the brain’s microstructure quantum affects could make themselves felt. It is reluctantly concluded that none have neurobiological plausibility. They are all instances, to paraphrase T.H. Huxley, of a beautiful hypothesis destroyed by ugly facts. David Bohm does not attempt to fit his new quantum physics to contemporary neurobiology but instead asks for a radical rethink of our conventional scientific paradigm. He suggests that we should look towards developing a ‘pan-experientialism’ or ‘dual-aspect monism’ where consciousness goes ‘all the way down’ and that the ‘hard problem’ is not soluble within the framework of ideas provided by ‘classical’ natural science.

An FTO variant is associated with Type 2 diabetes in South Asian populations after accounting for body mass index and waist circumference

Aims - A common variant, rs9939609, in the FTO (fat mass and obesity) gene is associated with adiposity in Europeans, explaining its relationship with diabetes. However, data are inconsistent in South Asians. Our aim was to investigate the association of the FTO rs9939609 variant with obesity, obesity-related traits and Type 2 diabetes in South Asian individuals, and to use meta-analyses to attempt to clarify to what extent BMI influences the association of FTO variants with diabetes in South Asians. Methods - We analysed rs9939609 in two studies of Pakistani individuals: 1666 adults aged = 40 years from the Karachi population-based Control of Blood Pressure and Risk Attenuation (COBRA) study and 2745 individuals of Punjabi ancestry who were part of a Type 2 diabetes case–control study (UK Asian Diabetes Study/Diabetes Genetics in Pakistan; UKADS/DGP). The main outcomes were BMI, waist circumference and diabetes. Regression analyses were performed to determine associations between FTO alleles and outcomes. Summary estimates were combined in a meta-analysis of 8091 South Asian individuals (3919 patients with Type 2 diabetes and 4172 control subjects), including those from two previous studies. Results - In the 4411 Pakistani individuals from this study, the age-, sex- and diabetes-adjusted association of FTO variant rs9939609 with BMI was 0.45 (95% CI 0.24–0.67) kg/m2 per A-allele (P = 3.0 × 10-5) and with waist circumference was 0.88 (95% CI 0.36–1.41) cm per A-allele (P = 0.001). The A-allele (30% frequency) was also significantly associated with Type 2 diabetes [per A-allele odds ratio (95% CI) 1.18 (1.07–1.30); P = 0.0009]. A meta-analysis of four South Asian studies with 8091 subjects showed that the FTO A-allele predisposes to Type 2 diabetes [1.22 (95% CI 1.14–1.31); P = 1.07 × 10-8] even after adjusting for BMI [1.18 (95% CI 1.10–1.27); P = 1.02 × 10-5] or waist circumference [1.18 (95% CI 1.10–1.27); P = 3.97 × 10-5]. Conclusions - The strong association between FTO genotype and BMI and waist circumference in South Asians is similar to that observed in Europeans. In contrast, the strong association of FTO genotype with diabetes is only partly accounted for by BMI.

Paradoxical psychometric functions ("swan functions") are explained by dilution masking in four stimulus dimensions

The visual system dissects the retinal image into millions of local analyses along numerous visual dimensions. However, our perceptions of the world are not fragmentary, so further processes must be involved in stitching it all back together. Simply summing up the responses would not work because this would convey an increase in image contrast with an increase in the number of mechanisms stimulated. Here, we consider a generic model of signal combination and counter-suppression designed to address this problem. The model is derived and tested for simple stimulus pairings (e.g. A + B), but is readily extended over multiple analysers. The model can account for nonlinear contrast transduction, dilution masking, and signal combination at threshold and above. It also predicts nonmonotonic psychometric functions where sensitivity to signal A in the presence of pedestal B first declines with increasing signal strength (paradoxically dropping below 50% correct in two-interval forced choice), but then rises back up again, producing a contour that follows the wings and neck of a swan. We looked for and found these "swan" functions in four different stimulus dimensions (ocularity, space, orientation, and time), providing some support for our proposal.

Towards a web-based progressive handwriting recognition environment for mathematical problem solving

The emergence of pen-based mobile devices such as PDAs and tablet PCs provides a new way to input mathematical expressions to computer by using handwriting which is much more natural and efficient for entering mathematics. This paper proposes a web-based handwriting mathematics system, called WebMath, for supporting mathematical problem solving. The proposed WebMath system is based on client-server architecture. It comprises four major components: a standard web server, handwriting mathematical expression editor, computation engine and web browser with Ajax-based communicator. The handwriting mathematical expression editor adopts a progressive recognition approach for dynamic recognition of handwritten mathematical expressions. The computation engine supports mathematical functions such as algebraic simplification and factorization, and integration and differentiation. The web browser provides a user-friendly interface for accessing the system using advanced Ajax-based communication. In this paper, we describe the different components of the WebMath system and its performance analysis.

Using genetic programming and decision trees for generating structural descriptions of four bar mechanisms

Four bar mechanisms are basic components of many important mechanical devices. The kinematic synthesis of four bar mechanisms is a difficult design problem. A novel method that combines the genetic programming and decision tree learning methods is presented. We give a structural description for the class of mechanisms that produce desired coupler curves. Constructive induction is used to find and characterize feasible regions of the design space. Decision trees constitute the learning engine, and the new features are created by genetic programming.

Investigating the role of capacitive coupling between the operating table and the return electrode of an electrosurgery unit in the modification of the current density distribution within the patients’ body

Background: Electrosurgery units are widely employed in modern surgery. Advances in technology have enhanced the safety of these devices, nevertheless, accidental burns are still regularly reported. This study focuses on possible causes of sacral burns as complication of the use of electrosurgery. Burns are caused by local densifications of the current, but the actual pathway of current within patient's body is unknown. Numerical electromagnetic analysis can help in understanding the issue. Methods: To this aim, an accurate heterogeneous model of human body (including seventy-seven different tissues), electrosurgery electrodes, operating table and mattress was build to resemble a typical surgery condition. The patient lays supine on the mattress with the active electrode placed onto the thorax and the return electrode on his back. Common operating frequencies of electrosurgery units were considered. Finite Difference Time Domain electromagnetic analysis was carried out to compute the spatial distribution of current density within the patient's body. A differential analysis by changing the electrical properties of the operating table from a conductor to an insulator was also performed. Results: Results revealed that distributed capacitive coupling between patient body and the conductive operating table offers an alternative path to the electrosurgery current. The patient's anatomy, the positioning and the different electromagnetic properties of tissues promote a densification of the current at the head and sacral region. In particular, high values of current density were located behind the sacral bone and beneath the skin. This did not occur in the case of non-conductive operating table. Conclusion: Results of the simulation highlight the role played from capacitive couplings between the return electrode and the conductive operating table. The concentration of current density may result in an undesired rise in temperature, originating burns in body region far from the electrodes. This outcome is concordant with the type of surgery-related sacral burns reported in literature. Such burns cannot be immediately detected after surgery, but appear later and can be confused with bedsores. In addition, the dosimetric analysis suggests that reducing the capacity coupling between the return electrode and the operating table can decrease or avoid this problem. © 2013 Bifulco et al.; licensee BioMed Central Ltd.

Catalytic supercritical water gasification of plastics with supported RuO2:a potential solution to hydrocarbons-water pollution problem

Here we report on a potential catalytic process for efficient clean-up of plastic pollution in waters, such as the Great Pacific Garbage Patch (CPGP). Detailed catalytic mechanisms of RuO2 during supercritical water gasification of common polyolefin plastics including low-density polyethylene (LDPE), high-density polyethylene (HDPE), polypropylene (PP) and polystyrene (PP), have been investigated in a batch reactor at 450 °C, 60 min. All four plastics gave very high carbon gasification efficiencies (CGE) and hydrogen gasification efficiencies (HGE). Methane was the highest gas component, with a yield of up to 37 mol kg−1LDPE using the 20 wt% RuO2 catalyst. Evaluation of the gas yields, CGE and HGE revealed that the conversion of PS involved thermal degradation, steam reforming and methanation; whereas hydrogenolysis was a possible additional mechanism during the conversion of aliphatic plastics. The process has the benefits of producing a clean-pressurized methane-rich fuel gas as well as cleaning up hydrocarbons-polluted waters.

Parallel Problem Solving from Nature – PPSN XIV:14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.

Collaborative filtering and deep learning based hybrid recommendation for cold start problem

Recommender systems (RS) are used by many social networking applications and online e-commercial services. Collaborative filtering (CF) is one of the most popular approaches used for RS. However traditional CF approach suffers from sparsity and cold start problems. In this paper, we propose a hybrid recommendation model to address the cold start problem, which explores the item content features learned from a deep learning neural network and applies them to the timeSVD++ CF model. Extensive experiments are run on a large Netflix rating dataset for movies. Experiment results show that the proposed hybrid recommendation model provides a good prediction for cold start items, and performs better than four existing recommendation models for rating of non-cold start items.