A Formalization of the Theorem of Existence of First-Order Most General Unifiers

This work presents a formalization of the theorem of existence of most general unifiers in first-order signatures in the higher-order proof assistant PVS. The distinguishing feature of this formalization is that it remains close to the textbook proofs that are based on proving the correctness of the well-known Robinson's first-order unification algorithm. The formalization was applied inside a PVS development for term rewriting systems that provides a complete formalization of the Knuth-Bendix Critical Pair theorem, among other relevant theorems of the theory of rewriting. In addition, the formalization methodology has been proved of practical use in order to verify the correctness of unification algorithms in the style of the original Robinson's unification algorithm.Comment: In Proceedings LSFA 2011, arXiv:1203.542

Evaluation of stem rot in 339 Bornean tree species: implications of size, taxonomy, and soil-related variation for aboveground biomass estimates

Fungal decay of heart wood creates hollows and areas of reduced wood density within the stems of living trees known as stem rot. Although stem rot is acknowledged as a source of error in forest aboveground biomass (AGB) estimates, there are few data sets available to evaluate the controls over stem rot infection and severity in tropical forests. Using legacy and recent data from 3180 drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of stem rot in a total of 339 tree species, and related variation in stem rot with tree size, wood density, taxonomy, and species’ soil association, as well as edaphic conditions. Predicted stem rot frequency for a 50 cm tree was 53% of felled, 39% of drilled, and 28% of cored stems, demonstrating differences among methods in rot detection ability. The percent stem volume infected by rot, or stem rot severity, ranged widely among trees with stem rot infection (0.1–82.8 %) and averaged 9% across all trees felled. Tree taxonomy explained the greatest proportion of variance in both stem rot frequency and severity among the predictors evaluated in our models. Stem rot frequency, but not severity, increased sharply with tree diameter, ranging from 13% in trees 10–30 cm DBH to 54%in stems ≥ 50 cm DBH across all data sets. The frequency of stem rot increased significantly in soils with low pH and cation concentrations in topsoil, and stem rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the maximum percent of stem biomass lost to stem rot varied significantly with soil properties, and we estimate that stem rot reduces total forest AGB estimates by up to 7% relative to what would be predicted assuming all stems are composed strictly of intact wood. This study demonstrates not only that stem rot is likely to be a significant source of error in forest AGB estimation, but also that it strongly covaries with tree size, taxonomy, habitat association, and soil resources, underscoring the need to account for tree community composition and edaphic variation in estimating carbon storage in tropical forests

Does it bite? The role of stimuli characteristics on preschoolers’ interactions with robots, insects and a dog

While there is increasing interest in the impact of animal interactions upon children’s wellbeing and attitudes, there has been less attention paid to the specific characteristics of the animals which attract and engage children. We used a within-subjects design to explore how differences in animal features (such as their animacy, size, and texture) impacted upon pre-school children’s social and emotional responses. This study examined pre-schoolers’ interactions with two animal-like robots (Teksta and Scoozie), two insect types (stick insects and hissing cockroaches) and a dog (Teasel, a West Highland Terrier). Nineteen preschool participants aged 35-57 months were videoed while interacting with the experimenter, a peer and each stimulus (presented individually). We used both verbal and nonverbal behaviours to evaluate interactions and emotional responses to the stimuli and found that these two measures could be incongruent, highlighting the need for systematic approaches to evaluating children’s interactions with animals. We categorised the content of children’s dialogues in relation to psychological and biological attributes of each stimulus and their distinctions between living and non-living stimuli; the majority of comments were biological, with psychological terms largely reserved for the dog and mammal-like robot only. Comments relating to living qualities revealed ambiguity towards attributes that denote differences between living and non-living creatures. We used a range of nonverbal measures, including willingness to approach and touch stimuli, rates of self-touching, facial expressions of emotion, and touch to others. Insects (hissing cockroaches and stick insects) received the most negative verbal and nonverbal responses. The mammal-like robot (rounded, fluffy body shape, large eyes, and sympathetic sounds) was viewed much more positively than its metallic counterpart, as was the real dog. We propose that these interactions provide information on how children perceive animals and a platform for the examination of human socio-emotional and cognitive development more generally. The children engaged in social referencing to the adult experimenter rather than familiar peers when uncertain about the stimuli presented, suggesting that caregivers have a primary role in shaping children’s responses to animals

Confluence and Convergence in Probabilistically Terminating Reduction Systems

Convergence of an abstract reduction system (ARS) is the property that any derivation from an initial state will end in the same final state, a.k.a. normal form. We generalize this for probabilistic ARS as almost-sure convergence, meaning that the normal form is reached with probability one, even if diverging derivations may exist. We show and exemplify properties that can be used for proving almost-sure convergence of probabilistic ARS, generalizing known results from ARS.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854

Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lowerstratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system¿s climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere.This work uses S2S Project data. S2S is a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP). This work was initiated by the Stratospheric Network for the Assessment of Predictability (SNAP), a joint activity of SPARC (WCRP) and the S2S Project (WWRP–WCRP). The work of Rachel W.-Y. Wu is funded through ETH grant ETH-05 19-1. Support from the Swiss National Science Foundation through projects PP00P2_170523 and PP00P2_198896 to Daniela I. V. Domeisen is gratefully acknowledged. Chaim I. Garfinkel and Chen Schwartz are supported by the ISF–NSFC joint research program (grant no. 3259/19). The work of Marisol Osman was supported by UBACyT20020170100428BA and PICT-2018-03046 projects. The work of Alvaro de la Cámara is funded by the Spanish Ministry of Science and Innovation through project PID2019-109107GB-I00. Blanca Ayarzagüena and Natalia Calvo acknowledge the support of the Spanish Ministry of Science and Innovation through the JeDiS (RTI2018-096402-B-I00) project. Froila M. Palmeiro and Javier García-Serrano have been partially supported by the Spanish ATLANTE project (PID2019-110234RB-C21) and Ramón y Cajal program (RYC-2016-21181), respectively. Neil P. Hindley and Corwin J. Wright are supported by UK Natural Environment Research Council (NERC), grant number NE/S00985X/1. Corwin J. Wright is also supported by a Royal Society University Research Fellowship UF160545. Seok-Woo Son and Hera Kim are supported by the Basic Science Research Program through the National Research Foundation of Korea (2017R1E1A1A01074889). This material is based upon work supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling program under award no. DE-SC0022070 and National Science Foundation (NSF) IA 1947282. This work was also supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF under cooperative agreement no. 1852977. Pu Lin is supported by award NA18OAR4320123 from the National Oceanic and Atmospheric Administration (NOAA), U.S. Department of Commerce. Zachary D. Lawrence was partially supported under NOAA award NA20NWS4680051; Zachary D. Lawrence and Judith Perlwitz also acknowledge support from US federally appropriated funds

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Detection of unsafety in families with parental and/or child developmental problems at the start of family support

Background Risk assessment is crucial in preventing child maltreatment as it can identify high-risk cases in need of child protection intervention. Despite this importance, there have been no validated risk assessment instruments available in the Netherlands for assessing the risk of child maltreatment. Therefore, the predictive validity of the California Family Risk Assessment (CFRA) was examined in Dutch families who received family support. In addition, the added value of a number of experimental items was examined. Finally, it was examined whether the predictive value of the instrument could be improved by modifying the scoring procedure. Methods Dutch families who experienced parenting and/or child developmental problems and were referred by the Centres for Youth and Family for family support between July 2009 and March 2011 were included. This led to a sample of 491 families. The predictive validity of the CFRA and the added value of the experimental items were examined by calculating AUC values. A CHAID analysis was performed to examine whether the scoring procedure could be improved. Results About half of the individual CFRA items were not related to future reports of child maltreatment. The predictive validity of the CFRA in predicting future reports of child maltreatment was found to be modest (AUC = .693). The addition of some of the experimental items and the modification of the scoring procedure by including only items that were significantly associated with future maltreatment reports resulted in a ‘high’ predictive validity (AUC = .795). Conclusions This new set of items might be a valuable instrument that also saves time because only variables that uniquely contribute to the prediction of future reports of child maltreatment are included. Furthermore, items that are perceived as difficult to assess by professionals, such as parental mental health problems or parents’ history of abuse/neglect, could be omitted without compromising predictive validity. However, it is important to examine the psychometric properties of this new set of items in a new dataset

Regulation of cellular proliferation, differentiation and cell death by activated Raf

The protein kinases Raf-1, A-Raf and B-Raf connect receptor stimulation with intracellular signaling pathways and function as a central intermediate in many signaling pathways. Gain-of-function experiments shed light on the pleiotropic biological activities of these enzymes. Expression experiments involving constitutively active Raf revealed the essential functions of Raf in controlling proliferation, differentiation and cell death in a cell-type specific manner