Assessing Human Error Against a Benchmark of Perfection

An increasing number of domains are providing us with detailed trace data on human decisions in settings where we can evaluate the quality of these decisions via an algorithm. Motivated by this development, an emerging line of work has begun to consider whether we can characterize and predict the kinds of decisions where people are likely to make errors. To investigate what a general framework for human error prediction might look like, we focus on a model system with a rich history in the behavioral sciences: the decisions made by chess players as they select moves in a game. We carry out our analysis at a large scale, employing datasets with several million recorded games, and using chess tablebases to acquire a form of ground truth for a subset of chess positions that have been completely solved by computers but remain challenging even for the best players in the world. We organize our analysis around three categories of features that we argue are present in most settings where the analysis of human error is applicable: the skill of the decision-maker, the time available to make the decision, and the inherent difficulty of the decision. We identify rich structure in all three of these categories of features, and find strong evidence that in our domain, features describing the inherent difficulty of an instance are significantly more powerful than features based on skill or time.Comment: KDD 2016; 10 page

A Match in Time Saves Nine: Deterministic Online Matching With Delays

We consider the problem of online Min-cost Perfect Matching with Delays (MPMD) introduced by Emek et al. (STOC 2016). In this problem, an even number of requests appear in a metric space at different times and the goal of an online algorithm is to match them in pairs. In contrast to traditional online matching problems, in MPMD all requests appear online and an algorithm can match any pair of requests, but such decision may be delayed (e.g., to find a better match). The cost is the sum of matching distances and the introduced delays. We present the first deterministic online algorithm for this problem. Its competitive ratio is $O(m^{\log_2 5.5})$ $= O(m^{2.46})$, where $2 m$ is the number of requests. This is polynomial in the number of metric space points if all requests are given at different points. In particular, the bound does not depend on other parameters of the metric, such as its aspect ratio. Unlike previous (randomized) solutions for the MPMD problem, our algorithm does not need to know the metric space in advance

An empirical cognitive model of the development of shared understanding of requirements

It is well documented that customers and software development teams need to share and refine understanding of the requirements throughout the software development lifecycle. The development of this shared understand- ing is complex and error-prone however. Techniques and tools to support the development of a shared understanding of requirements (SUR) should be based on a clear conceptualization of the phenomenon, with a basis on relevant theory and analysis of observed practice. This study contributes to this with a detailed conceptualization of SUR development as sequence of group-level state transi- tions based on specializing the Team Mental Model construct. Furthermore it proposes a novel group-level cognitive model as the main result of an analysis of data collected from the observation of an Agile software development team over a period of several months. The initial high-level application of the model shows it has promise for providing new insights into supporting SUR development

Three independently deleted regions at chromosome arm 16q in human prostate cancer: allelic loss at 16q24.1–q24.2 is associated with aggressive behaviour of the disease, recurrent growth, poor differentiation of the tumour and poor prognosis for the patient

Loss of heterozygosity at chromosome arm 16q is a frequent event in human prostate cancer. In this study, loss of heterozygosity at 16q was studied in 44 prostate cancer patients exhibiting various clinical features. Fifteen polymorphic polymerase chain reaction (PCR) markers were used to identify the separately deleted areas and the findings were compared with clinicopathological variables and 5-year survival of the patients. The results indicated that there are at least three independently deleted regions at 16q. Allelic losses at the central and distal areas were associated significantly with aggressive behaviour of the disease (16q24.1–q24.2, P< 0.01, and 16q24.3–qter, P< 0.05), and the central area of deletion was further significantly associated with poorly differentiated tumour cells (P< 0.05) and with recurrent (P< 0.01) growth of the tumour. During the follow-up period, 28% of the patients initially with M0 disease developed distant metastases. Of the patients showing allelic loss at 16q24.1–q24.2, distant metastasis were found in 45% during the 5-year follow-up period, and 31% of the patients showing loss at 16q21.1 also developed distant metastases. After the 5-year follow-up period, 14 (32%) of the patients remained alive, whereas 19 (43%) had died because of their prostate cancer. The overall survival rate of the patients showing allelic loss at 16q21.1 or 16q24.1–q24.2 was significantly lower than that of the patients with retained heterozygosity. © 1999 Cancer Research Campaig

Boltzmann and Fokker-Planck equations modelling the Elo rating system with learning effects

In this paper we propose and study a new kinetic rating model for a large number of players, which is motivated by the well-known Elo rating system. Each player is characterised by an intrinsic strength and a rating, which are both updated after each game. We state and analyse the respective Boltzmann type equation and derive the corresponding nonlinear, nonlocal Fokker-Planck equation. We investigate the existence of solutions to the Fokker-Planck equation and discuss their behaviour in the long time limit. Furthermore, we illustrate the dynamics of the Boltzmann and Fokker-Planck equation with various numerical experiments

Spirometry Abnormalities and Its Associated Factors Among Primary School Children in a Nigerian City.

BACKGROUND: There is paucity of data on objectively measured lung function abnormalities in Nigerian children using diagnostic testing methods such as spirometry. Such assessments could prompt early diagnosis and therapeutic interventions. METHODS: This was a cross sectional study among children aged 6 to 12 years in South-Eastern Nigeria. We selected participants from one school using a multistage stratified random sampling technique. A structured respiratory questionnaire was administered to obtain necessary data. The lung functions of the children were measured by spirometry. We used Lower Limits of Normal (LLN) based on GLI reference equations for African-American and mixed ethnicities to define abnormal spirometry. We studied the association between the exposures and lung function using logistic regression/chi-squared tests. RESULTS: A total of 145 children performed acceptable and repeatable tests. There were 73 males (50.3%), mean age of 9.13 years (+1.5) and age range 6 to 12 years. Frequency of respiratory symptoms was cough- 64 (44.1%) and wheeze in 19 (13.1%). Using GLI for African-Americans, fifty-five (37.9%) children had abnormal spirometryobstructive pattern in 40 (27.6%) and restrictive pattern in 15 (10.3%). The two references showed significant differences in interpretation of abnormality (χ2 = 72.86; P < .001). Respiratory symptom-wheeze was an independent determinant of abnormal lung function in this population.(OR = 0.31; 95%CI: 0.10-0.94; P = .04). CONCLUSION: There is a high burden of respiratory symptoms and abnormal spirometry among these children. The need for objective evaluation of lung function especially for children with respiratory symptoms is evident

Biodiversity of 52 chicken populations assessed by microsatellite typing of DNA pools

In a project on the biodiversity of chickens funded by the European Commission (EC), eight laboratories collaborated to assess the genetic variation within and between 52 populations from a wide range of chicken types. Twenty-two di-nucleotide microsatellite markers were used to genotype DNA pools of 50 birds from each population. The polymorphism measures for the average, the least polymorphic population (inbred C line) and the most polymorphic population (Gallus gallus spadiceus) were, respectively, as follows: number of alleles per locus, per population: 3.5, 1.3 and 5.2; average gene diversity across markers: 0.47, 0.05 and 0.64; and proportion of polymorphic markers: 0.91, 0.25 and 1.0. These were in good agreement with the breeding history of the populations. For instance, unselected populations were found to be more polymorphic than selected breeds such as layers. Thus DNA pools are effective in the preliminary assessment of genetic variation of populations and markers. Mean genetic distance indicates the extent to which a given population shares its genetic diversity with that of the whole tested gene pool and is a useful criterion for conservation of diversity. The distribution of population-specific (private) alleles and the amount of genetic variation shared among populations supports the hypothesis that the red jungle fowl is the main progenitor of the domesticated chicken

Transcriptional regulatory framework for vascular cambium development in Arabidopsis roots

Vascular cambium, a lateral plant meristem is a central producer of woody biomass. Although a few transcription factors (TFs) have been shown to regulate cambial activity1, the phenotypes of the corresponding loss-of-function mutants are relatively modest, highlighting our limited understanding of the underlying transcriptional regulation. Here, we utilize cambium cell-specific transcript profiling followed by a combination of TF network and genetic analyses to identify 62 novel TF genotypes displaying an array of cambial phenotypes. This approach culminated in virtual loss of cambial activity when both WUSCHEL-RELATED HOMEOBOX 4 (WOX4) and KNOTTED-like from Arabidopsis thaliana 1 (KNAT1; also known as BREVIPEDICELLUS (BP) were mutated, thereby unlocking the genetic redundancy in the regulation of cambium development. We also identified TFs with dual functions in cambial cell proliferation and xylem differentiation, including WOX4, SHORT VEGETATIVE PHASE (SVP) and PETAL LOSS (PTL). Using the TF network information, we combined overexpression of the cambial activator WOX4 and removal of the putative inhibitor PTL to engineer Arabidopsis for enhanced radial growth. This line also showed ectopic cambial activity, thus further highlighting the central roles of WOX4 and PTL in cambium development.This work was supported by Finnish Centre of Excellence in Molecular Biology of Primary Producers (Academy of Finland CoE program 2014-2019) decision #271832, the Gatsby Foundation (GAT3395/PR3)), the University of Helsinki (award 799992091) and the European Research Council Advanced Investigator Grant SYMDEV (No. 323052) to Y.H.; Academy of Finland (grants #132376, #266431, #271832), University of Helsinki HiLIFE fellowship to A.P.M.; National Research Foundation of Korea (2018R1A5A1023599 and 2016R1A2B2015258) to J-Y. L

Uncertainty in humanities network visualization

Network visualization is one of the most widely used tools in digital humanities research. The idea of uncertain or “fuzzy” data is also a core notion in digital humanities research. Yet network visualizations in digital humanities do not always prominently represent uncertainty. In this article, we present a mathematical and logical model of uncertainty as a range of values which can be used in network visualizations. We review some of the principles for visualizing uncertainty of different kinds, visual variables that can be used for representing uncertainty, and how these variables have been used to represent different data types in visualizations drawn from a range of non-humanities fields like climate science and bioinformatics. We then provide examples of two diagrams: one in which the variables displaying degrees of uncertainty are integrated/pinto the graph and one in which glyphs are added to represent data certainty and uncertainty. Finally, we discuss how probabilistic data and what-if scenarios could be used to expand the representation of uncertainty in humanities network visualizations