Coupling Reduction and the Higgs Mass

Assuming the existence of a functional relation among the Standard Model (SM) couplings gauge $\alpha_1$ and quartic $\lambda$, we determine the mass of the Higgs particle. Similar considerations for the top and bottom Yukawa couplings in the minimal supersymmetric SM lead to the prediction of a narrow window for $\tan\beta$, one of the main parameters that determine the light Higgs mass.Comment: 17 pages, 16 figure

Turnover of grassland roots in mountain ecosystems revealed by their radiocarbon signature: role of temperature and management

Root turnover is an important carbon flux component in grassland ecosystems because it replenishes substantial parts of carbon lost from soil via heterotrophic respiration and leaching. Among the various methods to estimate root turnover, the root’s radiocarbon signature has rarely been applied to grassland soils previously, although the value of this approach is known from studies in forest soils. In this paper, we utilize the root’s radiocarbon signatures, at 25 plots, in mountain grasslands of the montane to alpine zone of Europe.We place the results in context of a global data base on root turnover and discuss driving factors. Root turnover rates were similar to those of a subsample of the global data, comprising a similar temperature range, but measured with different approaches, indicating that the radiocarbon method gives reliable, plausible and comparable results. Root turnover rates (0.06–1.0 y-1) scaled significantly and exponentially with mean annual temperatures. Root turnover rates indicated no trend with soil depth. The temperature sensitivity was significantly higher in mountain grassland, compared to the global data set, suggesting additional factors influencing root turnover. Information on management intensity from the 25 plots reveals that root turnover may be accelerated under intensive and moderate management compared to low intensity or semi-natural conditions. Because management intensity, in the studied ecosystems, co-varied with temperature, estimates on root turnover, based on mean annual temperature alone, may be biased. A greater recognition of management as a driver for root dynamics is warranted when effects of climatic change on belowground carbon dynamics are studied in mountain grasslands.KB received support from the Swiss National Science Foundation, project 200021-115891 (www.snf.ch). SM received support from the Swiss State Secretariat for Education and Research, project C07.0031 (www.sbfi.admin.ch). MTS received support from the Spanish Ministry of Science and Innovation, (project CAPAS, CGL2010-22378-C03- 01) (www.idi.mineco.gob.es)

CIRP: Cross-Item Relational Pre-training for Multimodal Product Bundling

Product bundling has been a prevailing marketing strategy that is beneficial in the online shopping scenario. Effective product bundling methods depend on high-quality item representations, which need to capture both the individual items' semantics and cross-item relations. However, previous item representation learning methods, either feature fusion or graph learning, suffer from inadequate cross-modal alignment and struggle to capture the cross-item relations for cold-start items. Multimodal pre-train models could be the potential solutions given their promising performance on various multimodal downstream tasks. However, the cross-item relations have been under-explored in the current multimodal pre-train models. To bridge this gap, we propose a novel and simple framework Cross-Item Relational Pre-training (CIRP) for item representation learning in product bundling. Specifically, we employ a multimodal encoder to generate image and text representations. Then we leverage both the cross-item contrastive loss (CIC) and individual item's image-text contrastive loss (ITC) as the pre-train objectives. Our method seeks to integrate cross-item relation modeling capability into the multimodal encoder, while preserving the in-depth aligned multimodal semantics. Therefore, even for cold-start items that have no relations, their representations are still relation-aware. Furthermore, to eliminate the potential noise and reduce the computational cost, we harness a relation pruning module to remove the noisy and redundant relations. We apply the item representations extracted by CIRP to the product bundling model ItemKNN, and experiments on three e-commerce datasets demonstrate that CIRP outperforms various leading representation learning methods.Comment: arXiv preprint, 10 pages, 4 figures, 6 table

Flexible constrained sampling with guarantees for pattern mining

Pattern sampling has been proposed as a potential solution to the infamous pattern explosion. Instead of enumerating all patterns that satisfy the constraints, individual patterns are sampled proportional to a given quality measure. Several sampling algorithms have been proposed, but each of them has its limitations when it comes to 1) flexibility in terms of quality measures and constraints that can be used, and/or 2) guarantees with respect to sampling accuracy. We therefore present Flexics, the first flexible pattern sampler that supports a broad class of quality measures and constraints, while providing strong guarantees regarding sampling accuracy. To achieve this, we leverage the perspective on pattern mining as a constraint satisfaction problem and build upon the latest advances in sampling solutions in SAT as well as existing pattern mining algorithms. Furthermore, the proposed algorithm is applicable to a variety of pattern languages, which allows us to introduce and tackle the novel task of sampling sets of patterns. We introduce and empirically evaluate two variants of Flexics: 1) a generic variant that addresses the well-known itemset sampling task and the novel pattern set sampling task as well as a wide range of expressive constraints within these tasks, and 2) a specialized variant that exploits existing frequent itemset techniques to achieve substantial speed-ups. Experiments show that Flexics is both accurate and efficient, making it a useful tool for pattern-based data exploration.Comment: Accepted for publication in Data Mining & Knowledge Discovery journal (ECML/PKDD 2017 journal track

HDTQ: Managing RDF Datasets in Compressed Space

HDT (Header-Dictionary-Triples) is a compressed representation of RDF data that supports retrieval features without prior decompression. Yet, RDF datasets often contain additional graph information, such as the origin, version or validity time of a triple. Traditional HDT is not capable of handling this additional parameter(s). This work introduces HDTQ (HDT Quads), an extension of HDT that is able to represent quadruples (or quads) while still being highly compact and queryable. Two HDTQ-based approaches are introduced: Annotated Triples and Annotated Graphs, and their performance is compared to the leading open-source RDF stores on the market. Results show that HDTQ achieves the best compression rates and is a competitive alternative to well-established systems

Constraints on Finite Soft Supersymmetry-Breaking Terms

Requiring the soft supersymmetry-breaking (SSB) parameters in finite gauge-Yukawa unified models to be finite up to and including two-loop order, we derive a two-loop sum rule for the soft scalar-masses. It is shown that this sum rule coincides with that of a certain class of string models in which the massive string states are organized into N=4 supermultiplets. We investigate the SSB sector of two finite SU(5) models. Using the sum rule which allows the non-universality of the SSB terms and requiring that the lightest superparticle particleis neutral, we constrain the parameter space of the SSB sector in each model.Comment: 34 page

Evolution of Cooperation and Coordination in a Dynamically Networked Society

Situations of conflict giving rise to social dilemmas are widespread in society and game theory is one major way in which they can be investigated. Starting from the observation that individuals in society interact through networks of acquaintances, we model the co-evolution of the agents' strategies and of the social network itself using two prototypical games, the Prisoner's Dilemma and the Stag Hunt. Allowing agents to dismiss ties and establish new ones, we find that cooperation and coordination can be achieved through the self-organization of the social network, a result that is non-trivial, especially in the Prisoner's Dilemma case. The evolution and stability of cooperation implies the condensation of agents exploiting particular game strategies into strong and stable clusters which are more densely connected, even in the more difficult case of the Prisoner's Dilemma.Comment: 18 pages, 14 figures. to appea

Finite SU(N)^k Unification

We consider N=1 supersymmetric gauge theories based on the group SU(N)_1 x SU(N)_2 x ... x SU(N)_k with matter content (N,N*,1,...,1) + (1,N,N*,...,1) + >... + (N*,1,1,...,N) as candidates for the unification symmetry of all particles. In particular we examine to which extent such theories can become finite and we find that a necessary condition is that there should be exactly three families. We discuss further some phenomenological issues related to the cases (N,k) = (3,3), (3,4), and (4,3), in an attempt to choose those theories that can become also realistic. Thus we are naturally led to consider the SU(3)^3 model which we first promote to an all-loop finite theory and then we study its additional predictions concerning the top quark mass, Higgs mass and supersymmetric spectrum.Comment: 15 page

Continuous infusion of physostigmine in patients with perioperative septic shock: A pharmacokinetic/pharmacodynamic study with population pharmacokinetic modeling

Background In the context of the cholinergic anti-inflammatory pathway, the clinical trial Anticholium® per Se (EudraCT Number: 2012-001650-26, ClinicalTrials.gov NCT03013322) addressed the possibility of taking adjunctive physostigmine salicylate treatment in septic shock from bench to bedside. Pharmacokinetics (PK) are likely altered in critically ill patients; data on physostigmine PK and target concentrations are sparse, particularly for continuous infusion. Our objective was to build a population PK (popPK) model for physostigmine, and further evaluate pharmacodynamics (PD) and concentration-response relationship in this setting. Methods In the randomized, double-blind, placebo-controlled trial, 20 patients with perioperative septic shock either received an initial dose of 0.04 mg/kg physostigmine salicylate, followed by continuous infusion of 1 mg/h for up to 120 h, or equivalent volumes of 0.9% sodium chloride (placebo group). Physostigmine plasma concentrations and acetylcholinesterase (AChE) activity were measured; concentration-response associations were evaluated, and popPK and PD modeling was performed with NONMEM. Results Steady state physostigmine plasma concentrations reached 7.60 ± 2.81 ng/mL (mean ± standard deviation [SD]). PK was best described by a two-compartment model with linear clearance. Significant covariate effects were detected for body weight and age on clearance, as well as a high inter-individual variability of the central volume of distribution. AChE activity was significantly reduced to 30.5%–50.6% of baseline activity during physostigmine salicylate infusion. A sigmoidal direct effect PD model best described enzyme inhibition by physostigmine, with an estimated half maximal effective concentration (EC50) of 5.99 ng/mL. Conclusions PK of physostigmine in patients with septic shock displayed substantial inter-individual variability with body weight and age influencing the clearance. Physostigmine inhibited AChE activity with a sigmoidal concentration-response effect