Scatteract: Automated extraction of data from scatter plots

Charts are an excellent way to convey patterns and trends in data, but they do not facilitate further modeling of the data or close inspection of individual data points. We present a fully automated system for extracting the numerical values of data points from images of scatter plots. We use deep learning techniques to identify the key components of the chart, and optical character recognition together with robust regression to map from pixels to the coordinate system of the chart. We focus on scatter plots with linear scales, which already have several interesting challenges. Previous work has done fully automatic extraction for other types of charts, but to our knowledge this is the first approach that is fully automatic for scatter plots. Our method performs well, achieving successful data extraction on 89% of the plots in our test set.Comment: Submitted to ECML PKDD 2017 proceedings, 16 page

Dopamine neurons learn relative chosen value from probabilistic rewards

Economic theories posit reward probability as one of the factors defining reward value. Individuals learn the value of cues that predict probabilistic rewards from experienced reward frequencies. Building on the notion that responses of dopamine neurons increase with reward probability and expected value, we asked how dopamine neurons in monkeys acquire this value signal that may represent an economic decision variable. We found in a Pavlovian learning task that reward probability-dependent value signals arose from experienced reward frequencies. We then assessed neuronal response acquisition during choices among probabilistic rewards. Here, dopamine responses became sensitive to the value of both chosen and unchosen options. Both experiments showed also the novelty responses of dopamine neurones that decreased as learning advanced. These results show that dopamine neurons acquire predictive value signals from the frequency of experienced rewards. This flexible and fast signal reflects a specific decision variable and could update neuronal decision mechanisms

Smarter than humans: rationality reflected in primate neuronal reward signals

Rational choice, in all its definitions by various disciplines, allows agents to maximize utility. Formal axioms and simple choice designs are suitable for assessing rationality in monkeys. Their economic preferences are complete and transitive; the dopamine signal follows transitivity. Dopamine signals also satisfy first-order stochastic dominance that unequivocally defines the better option. Neurons in orbitofrontal cortex (OFC) reflect the unchanged preferences when an irrelevant option is removed from the option set, thus satisfying Arrow’s Weak Axiom of Revealed Preference (WARP) concerning the Independence of Irrelevant Alternatives (IIA). While monkeys, with their reward neurons, may not be more rational than humans, the constraints of controlled experiments seem to allow them to behave rationally within their informational, cognitive and temporal bounds

Korelasi Lama Menjalani Hemodialisis dengan Indeks Massa Tubuh Pasien Gagal Ginjal Kronik di RSUD Arifin Achamad Provinsi Riau pada Bulan Mei Tahun 2014

Renal failure is a disesase causes a progresive and irreversible reduction of kidney's function to filtrate waste products from the blood. Indonesia's prevalence of chronic renal failure is about 0.2 %. Patient with chronic renal failure will achieved severe damage on kidney which will leads to emergency. This research was analytic study with consecutive sampling method to determined the correlation between hemodialysis duration with body mass index on chronic renal failure patients in General Hospital Arifin Achmad Riau Province on May 2014. Sample was taken by measuring patients' weight and height in Hemodialysis Unit General Hospital Arifin Achmad Riau Province on 2014, where have obtained as many as 58 people. The result showed that chronic renal failure patients most have underwent hemodialysis at age group 45-65 years old (72.4 %), commonest in women about 51.7 %, most hemodialisys frequency was twice a week for four hours(51.7 %). Most of patients had undergone hemodialisys duration about > 12 months (53.4 %). This research was processed by using statistic test correlation Lambda, results have shown a significant and moderate correlation between duration of hemodyalisis and body mass index (r=0.40;p<0,001), which was led to a conclusion: hemodyalisis duration will effect patients' body mass index

Effect of pancreatic and/or renal transplantation on diabetic autonomic neuropathy

Thirty-nine Type 1 (insulin-dependent) diabetic patients were studied prospectively after simultaneous pancreas and kidney (n=26) and kidney grafting alone (n=13) by measuring heart rate variation during various manoeuvers and answering a standardized questionnaire every 6 to 12 months post-transplant. While age, duration of diabetes, and serum creatinine (168.1±35.4 vs 132.7±17.7 mgrmol/l) were comparable, haemoglobin A1 levels were significantly lower (6.6±0.2 vs 8.5±0.3%; p<0.01) and the mean observation time longer (35±2 vs 25±3 months; p<0.05) in the pancreas recipients when compared with kidney transplanted patients. Heart rate variation during deep breathing, lying/standing and Valsalva manoeuver were very similar in both groups initially and did not improve during follow-up. However, there was a significant reduction in heart rate in the pancreas recipient group. Autonomic symptoms of the gastrointestinal and thermoregulatory system improved more in the pancreas grafted subjects, while hypoglycaemia unawareness deteriorated in the kidney recipients. This study suggests that long-term normoglycaemia by successful pancreatic grafting is able to halt the progression of autonomic dysfunction

Bandit Models of Human Behavior: Reward Processing in Mental Disorders

Drawing an inspiration from behavioral studies of human decision making, we propose here a general parametric framework for multi-armed bandit problem, which extends the standard Thompson Sampling approach to incorporate reward processing biases associated with several neurological and psychiatric conditions, including Parkinson's and Alzheimer's diseases, attention-deficit/hyperactivity disorder (ADHD), addiction, and chronic pain. We demonstrate empirically that the proposed parametric approach can often outperform the baseline Thompson Sampling on a variety of datasets. Moreover, from the behavioral modeling perspective, our parametric framework can be viewed as a first step towards a unifying computational model capturing reward processing abnormalities across multiple mental conditions.Comment: Conference on Artificial General Intelligence, AGI-1

A conserved role for kinesin-5 in plant mitosis

The mitotic spindle of vascular plants is assembled and maintained by processes that remain poorly explored at a molecular level. Here, we report that AtKRP125c, one of four kinesin-5 motor proteins in arabidopsis, decorates microtubules throughout the cell cycle and appears to function in both interphase and mitosis. In a temperature-sensitive mutant, interphase cortical microtubules are disorganized at the restrictive temperature and mitotic spindles are massively disrupted, consistent with a defect in the stabilization of anti-parallel microtubules in the spindle midzone, as previously described in kinesin-5 mutants from animals and yeast. AtKRP125c introduced into mammalian epithelial cells by transfection decorates microtubules throughout the cell cycle but is unable to complement the loss of the endogenous kinesin-5 motor (Eg5). These results are among the first reports of any motor with a major role in anastral spindle structure in plants and demonstrate that the conservation of kinesin-5 motor function throughout eukaryotes extends to vascular plants

Long-term trends in diatom diversity and palaeoproductivity: a 16 000-year multidecadal record from Lake Baikal, southern Siberia

Biological diversity is inextricably linked to community stability and ecosystem functioning, but our understanding of these relationships in freshwater ecosystems is largely based on short-term observational, experimental, and modelling approaches. Using a multidecadal diatom record for the past ca. 16 000 years from Lake Baikal, we investigate how diversity and palaeoproductivity have responded to climate change during periods of both rapid climate fluctuation and relative climate stability. We show dynamic changes in diatom communities during the past 16 000 years, with decadal shifts in species dominance punctuating millennial-scale seasonal trends. We describe for the first time in Lake Baikal a gradual shift from spring to autumnal diatom communities that started during the Younger Dryas and peaked during the Late Holocene, which likely represents orbitally driven ecosystem responses to long-term changes in seasonality. Using a multivariate classification tree, we show that trends in planktonic and tychoplanktonic diatoms broadly reflect both long-term climatic changes associated with the demise of Northern Hemisphere ice sheets and abrupt climatic changes associated with, for example, the Younger Dryas stadial. Indeed, diatom communities are most different before and after the boundary between the Early and Middle Holocene periods of ca. 8.2 cal kyr BP, associated with the presence and demise of Northern Hemisphere ice sheets respectively. Diatom richness and diversity, estimated using Hill's species numbers, are also shown to be very responsive to periods characterized by abrupt climate change, and using knowledge of diatom autecologies in Lake Baikal, diversity trends are interpreted in terms of resource availability. Using diatom biovolume accumulation rates (BVARs; µm3 cm−2 yr−1), we show that spring diatom crops dominate palaeoproductivity for nearly all of our record, apart from a short period during the Late Holocene, when autumnal productivity dominated between 1.8–1.4 cal kyr BP. Palaeoproductivity was especially unstable during the Younger Dryas, reaching peak rates of 18.3 × 103 µm3 cm−2 yr−1 at ca. 12.3 cal kyr BP. Generalized additive models (GAMs), which explore productivity–diversity relationships (PDRs) during pre-defined climate periods, reveal complex relationships. The strongest statistical evidence for GAMs were found during the Younger Dryas, the Early Holocene, and the Late Holocene, i.e. periods of rapid climate change. We account for these differences in terms of climate-mediated resource availability, and the ability of endemic diatom species in Lake Baikal to adapt to extreme forms of living in this unique ecosystem. Our analyses offer insight into how productivity–diversity relationships may develop in the future under a warming climate