Running Genetic Algorithms in the Edge: A First Analysis

Nowadays, the volume of data produced by different kinds of devices is continuously growing, making even more difficult to solve the many optimization problems that impact directly on our living quality. For instance, Cisco projected that by 2019 the volume of data will reach 507.5 zettabytes per year, and the cloud traffic will quadruple. This is not sustainable in the long term, so it is a need to move part of the intelligence from the cloud to a highly decentralized computing model. Considering this, we propose a ubiquitous intelligent system which is composed by different kinds of endpoint devices such as smartphones, tablets, routers, wearables, and any other CPU powered device. We want to use this to solve tasks useful for smart cities. In this paper, we analyze if these devices are suitable for this purpose and how we have to adapt the optimization algorithms to be efficient using heterogeneous hardware. To do this, we perform a set of experiments in which we measure the speed, memory usage, and battery consumption of these devices for a set of binary and combinatorial problems. Our conclusions reveal the strong and weak features of each device to run future algorihms in the border of the cyber-physical system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This research has been partially funded by the Spanish MINECO and FEDER projects TIN2014-57341-R (http://moveon.lcc.uma.es), TIN2016-81766-REDT (http://cirti.es), TIN2017-88213-R (http://6city.lcc.uma.es), the Ministry of Education of Spain (FPU16/02595

A genetic programming based fuzzy regression approach to modelling manufacturing processes

Fuzzy regression has demonstrated its ability to model manufacturing processes in which the processes have fuzziness and the number of experimental data sets for modelling them is limited. However, previous studies only yield fuzzy linear regression based process models in which variables or higher order terms are not addressed. In fact, it is widely recognised that behaviours of manufacturing processes do often carry interactions among variables or higher order terms. In this paper, a genetic programming based fuzzy regression GP-FR, is proposed for modelling manufacturing processes. The proposed method uses the general outcome of GP to construct models the structure of which is based on a tree representation, which could carry interaction and higher order terms. Then, a fuzzy linear regression algorithm is used to estimate the contributions and the fuzziness of each branch of the tree, so as to determine the fuzzy parameters of the genetic programming based fuzzy regression model.To evaluate the effectiveness of the proposed method for process modelling, it was applied to the modelling of a solder paste dispensing process. Results were compared with those based on statistical regression and fuzzy linear regression. It was found that the proposed method can achieve better goodness-of-fitness than the other two methods. Also the prediction accuracy of the model developed based on GP-FR is better than those based on the other two methods

Hedgehog pathway mutations drive oncogenic transformation in high-risk T-cell acute lymphoblastic leukemia.

The role of Hedgehog signaling in normal and malignant T-cell development is controversial. Recently, Hedgehog pathway mutations have been described in T-ALL, but whether mutational activation of Hedgehog signaling drives T-cell transformation is unknown, hindering the rationale for therapeutic intervention. Here, we show that Hedgehog pathway mutations predict chemotherapy resistance in human T-ALL, and drive oncogenic transformation in a zebrafish model of the disease. We found Hedgehog pathway mutations in 16% of 109 childhood T-ALL cases, most commonly affecting its negative regulator PTCH1. Hedgehog mutations were associated with resistance to induction chemotherapy (P = 0.009). Transduction of wild-type PTCH1 into PTCH1-mutant T-ALL cells induced apoptosis (P = 0.005), a phenotype that was reversed by downstream Hedgehog pathway activation (P = 0.007). Transduction of most mutant PTCH1, SUFU, and GLI alleles into mammalian cells induced aberrant regulation of Hedgehog signaling, indicating that these mutations are pathogenic. Using a CRISPR/Cas9 system for lineage-restricted gene disruption in transgenic zebrafish, we found that ptch1 mutations accelerated the onset of notch1-induced T-ALL (P = 0.0001), and pharmacologic Hedgehog pathway inhibition had therapeutic activity. Thus, Hedgehog-activating mutations are driver oncogenic alterations in high-risk T-ALL, providing a molecular rationale for targeted therapy in this disease

Support and Assessment for Fall Emergency Referrals (SAFER 1) trial protocol. Computerised on-scene decision support for emergency ambulance staff to assess and plan care for older people who have fallen: evaluation of costs and benefits using a pragmatic cluster randomised trial

Background: Many emergency ambulance calls are for older people who have fallen. As half of them are left at home, a community-based response may often be more appropriate than hospital attendance. The SAFER 1 trial will assess the costs and benefits of a new healthcare technology - hand-held computers with computerised clinical decision support (CCDS) software - to help paramedics decide who needs hospital attendance, and who can be safely left at home with referral to community falls services. Methods/Design: Pragmatic cluster randomised trial with a qualitative component. We shall allocate 72 paramedics ('clusters') at random between receiving the intervention and a control group delivering care as usual, of whom we expect 60 to complete the trial. Patients are eligible if they are aged 65 or older, live in the study area but not in residential care, and are attended by a study paramedic following an emergency call for a fall. Seven to 10 days after the index fall we shall offer patients the opportunity to opt out of further follow up. Continuing participants will receive questionnaires after one and 6 months, and we shall monitor their routine clinical data for 6 months. We shall interview 20 of these patients in depth. We shall conduct focus groups or semi-structured interviews with paramedics and other stakeholders. The primary outcome is the interval to the first subsequent reported fall (or death). We shall analyse this and other measures of outcome, process and cost by 'intention to treat'. We shall analyse qualitative data thematically. Discussion: Since the SAFER 1 trial received funding in August 2006, implementation has come to terms with ambulance service reorganisation and a new national electronic patient record in England. In response to these hurdles the research team has adapted the research design, including aspects of the intervention, to meet the needs of the ambulance services. In conclusion this complex emergency care trial will provide rigorous evidence on the clinical and cost effectiveness of CCDS for paramedics in the care of older people who have fallen

Morphology and Nanomechanics of Sensory Neurons Growth Cones following Peripheral Nerve Injury

A prior peripheral nerve injury in vivo, promotes a rapid elongated mode of sensory neurons neurite regrowth in vitro. This in vitro model of conditioned axotomy allows analysis of the cellular and molecular mechanisms leading to an improved neurite re-growth. Our differential interference contrast microscopy and immunocytochemistry results show that conditioned axotomy, induced by sciatic nerve injury, did not increase somatic size of adult lumbar sensory neurons from mice dorsal root ganglia sensory neurons but promoted the appearance of larger neurites and growth cones. Using atomic force microscopy on live neurons, we investigated whether membrane mechanical properties of growth cones of axotomized neurons were modified following sciatic nerve injury. Our data revealed that neurons having a regenerative growth were characterized by softer growth cones, compared to control neurons. The increase of the growth cone membrane elasticity suggests a modification in the ratio and the inner framework of the main structural proteins

Methylmercury Exposure and Adverse Cardiovascular Effects in Faroese Whaling Men

Background: Methylmercury (MeHg), a worldwide contaminant found in fish and seafood, has been linked to an increased risk of cardiovascular mortality. Objective: We examined 42 Faroese whaling men (30–70 years of age) to assess possible adverse effects within a wide range of MeHg exposures from consumption of pilot whale meat. Methods: We assessed exposure levels from mercury analysis of toenails and whole blood (obtained at the time of clinical examination), and a hair sample collected 7 years previously. Outcome measures included heart rate variability (HRV), blood pressure (BP), common carotid intima-media thickness (IMT), and brainstem auditory evoked potentials (BAEP). We carried out multiple regression and structural equation model (SEM) analyses to determine the confounder-adjusted effect of mercury exposure. Taking into account correlations among related measures, we categorized exposure and outcomes in groups to derive latent exposure and response variables in SEMs. We used multiple regression analysis to compare the predictive validity of individual exposure biomarkers and the latent exposure variable on individual and latent outcomes. Results: The toenail mercury concentrations varied widely and had a geometric mean of 2.0 μg/g; hair concentrations averaged about 3-fold higher. Mercury exposure was significantly associated with increased BP and IMT. This effect was reflected by SEMs, but mercury in toenails tended to be the best effect predictor. Conclusions: The results support the notion that increased MeHg exposure promotes the development of cardiovascular disease

Measurement of the hadronic photon structure function F_{2}^{γ} at LEP2

The hadronic structure function of the photon F_{2}^{γ} (x, Q²) is measured as a function of Bjorken x and of the photon virtuality Q² using deep-inelastic scattering data taken by the OPAL detector at LEP at e⁺e⁻ centre-of-mass energies from 183 to 209 GeV. Previous OPAL measurements of the x dependence of F_{2}^{γ} are extended to an average Q² of 〈Q²〉=780 GeV² using data in the kinematic range 0.15<x<0.98. The Q² evolution of F_{2}^{γ} is studied for 12.1<〈Q²〉<780 GeV² using three ranges of x. As predicted by QCD, the data show positive scaling violations in F_{2}^{γ} with F_{2}^{γ} (Q²)/α = (0.08±0.02⁺⁰·⁰⁵_₀.₀₃) + (0.13±0.01⁺⁰·⁰¹_₀.₀₁) lnQ², where Q² is in GeV², for the central x region 0.10–0.60. Several parameterisations of F_{2}^{γ} are in qualitative agreement with the measurements whereas the quark-parton model prediction fails to describe the data

Creatinine clearance versus serum creatinine as a risk factor in cardiac surgery

BACKGROUND: Renal impairment is one of the predictors of mortality in cardiac surgery. Usually a binarized value of serum creatinine is used to assess the renal function in risk models. Creatinine clearance can be easily estimated by the Cockcroft and Gault equation from serum creatinine, gender, age and body weight. In this work we examine whether this estimation of the glomerular filtration rate can advantageously replace the serum creatinine in the EuroSCORE preoperative risk assessment. METHODS: In a group of 8138 patients out of a total of 11878 patients, who underwent cardiac surgery in our hospital between January 1996 and July 2002, the 18 standard EuroSCORE parameters could retrospectively be determined and logistic regression analysis performed. In all patients scored, creatinine clearance was calculated according to Cockcroft and Gault. The relationship between the predicted and observed 30-days mortality was evaluated in systematically selected intervals of creatinine clearance and significance values computed by employing Monte Carlo methods. Afterwards, risk scoring was performed using a continuous or a categorical value of creatinine clearance instead of serum creatinine. The predictive ability of several risk score models and the individual contribution of their predictor variables were studied using ROC curve analysis. RESULTS: The comparison between the expected and observed 30-days mortalities, which were determined in different intervals of creatinine clearance, revealed the best threshold value of 55 ml/min. A significantly higher 30-days mortality was observed below this threshold and vice versa (both with p < 0.001). The local adaptation of the EuroSCORE is better than the standard EuroSCORE and was further improved by replacing serum creatinine (SC) by creatinine clearance (CC). Differential ROC analysis revealed that CC is superior to SC in providing predictive power within the logistic regression. Variable rank comparison identified CC as the best single variable predictor, even better than the variable age, former number 1, and SC, previously number 9 in the standard set of EuroSCORE variables. CONCLUSION: The renal function is an important determinant of mortality in heart surgery. This risk factor is not well captured in the standard EuroSCORE risk evaluation system. Our study shows that creatinine clearance, calculated according to the Cockcroft and Gault equation, should be applied to estimate the preoperative renal function instead of serum creatinine. This predictor variable replacement gains a significant improvement in the predictive accuracy of the scoring model

Measurement of the charm structure function F_{2,c)^{γ} of the photon at LEP

The production of charm quarks is studied in deep-inelastic electron–photon scattering using data recorded by the OPAL detector at LEP at nominal e⁺e⁻ centre-of-mass energies from 183 to 209 GeV. The charm quarks have been identified by full reconstruction of charged D* mesons using their decays into D⁰π with the D⁰ observed in two decay modes with charged particle final states, Kπ and Kπππ. The cross-section σ^{D*} for production of charged D* in the reaction e⁺e⁻→e⁺e⁻D*Χ is measured in a restricted kinematical region using two bins in Bjorken x, 0.00140.1 the perturbative QCD calculation at next-to-leading order agrees perfectly with the measured cross-section. For x<0.1 the measured cross-section is 43.8±14.3±6.3±2.8 pb with a next-to-leading order prediction of 17.0⁺²·⁹_₂.₃ pb