Large‐Scale Roll‐to‐Roll Patterned Oxygen Indicators for Modified Atmosphere Packages

We demonstrate roll‐to‐roll fabrication of ultraviolet A light‐activated colorimetric oxygen indicators on paper and plastic substrates. Such large‐scale, cost‐effective and non‐toxic oxygen indicator and production method can find applications as a very low‐cost leakage indicator for modified atmosphere packages by printing the material directly or gluing the pre‐printed indicator label inside the lid. The introduction of leakage indicators onto all modified atmosphere packages could result in improved food safety and reduced food spoilage. Copyright © 2017 John Wiley & Sons, Ltd.     

Heat stress adaptation induces cross-protection against lethal acid stress conditions in Arcobacter butzleri but not in Campylobacter jejuni

The ability of many bacteria to adapt to stressful conditions may later protect them against the same type of stress (specific adaptive response) or different types of stresses (multiple adaptive response, also termed cross-protection). Arcobacter butzleri and Campylobacter jejuni are close phylogenetic relatives that occur in many foods of animal origin and have been linked with human illness (mainly diarrhoea). In the present study, sublethal stress adaptation temperatures (48 °C and 10 °C) and mild and lethal acid conditions (pH 5.0 and pH 4.0) were determined for A. butzleri and C. jejuni. In addition, it was evaluated whether these sublethal stress adaptations cause specific adaptive responses or cross-protection against subsequent mild or lethal acid stresses in these bacteria. The studies were conducted in broth adjusted to the different conditions and the results were determined by the dilution series plating method. It was shown that heat stress adapted A. butzleri (incubated for 2 h at 48 °C) were significantly more resistant to subsequent lethal acid stress (pH 4.0) than non-adapted cells at the 1 h time-point (p < 0.01 in Wilcoxon rank sum test). No specific adaptive responses against the stresses in A. butzleri or C. jejuni and no cross-protection in C. jejuni were found. The ability of heat stressed A. butzleri to tolerate later lethal acid conditions should be taken into account when designing new food decontamination and processing strategies.     

Does ice matter? Site fidelity and movements by Atlantic salmon (Salmo salar L.) parr during winter in a substrate enhanced river reach

In‐stream habitat enhancement is a common remedial action in rivers where degradation/lack of suitable fish habitat can be diagnosed. However, post‐project monitoring to assess the response of the biota to modification is rare particularly during winter. We conducted in situ monitoring during the winters of 2004–2006 in the regulated Dalåa River, central Norway, in order to determine if winter habitat requirements of Atlantic salmon (Salmo salar L.) parr were realized in an enhanced (substrate and mesohabitat modification) reach. In total, 140 parr were marked with passive integrated transponder (PIT) tags and the fish were followed by carrying out active tracking surveys under variable ice conditions throughout the winter. Highest emigration (44%) occurred before ice formation started. Emigration was reduced after ice formed and was largely offset by parr re‐entering the enhanced area. Dispersal into the non‐enhanced, small substrate control area was observed only when the study reach was ice covered, and no parr were subsequently encountered in the control section after ice had melted. In the enhanced area, declining water temperature and surface ice conditions did not affect the spatial distribution of the resident salmon parr at the studied scale. Areas with ‘solid’ anchor ice precluded access for salmon parr whilst areas with ‘patchy’ anchor were used throughout the winter. Our results indicate that surface ice creates conditions that allow salmon parr to use stream habitats that otherwise provide only a limited amount of in‐stream cover. Ice processes should be taken into consideration when habitat enhancement projects are carried out and subsequently assessed for effectiveness. Copyright © 2008 John Wiley & Sons, Ltd.     

An Introduction to Variational Methods for Graphical Models

This paper presents a tutorial introduction to the use of variational methods for inference and learning in graphical models (Bayesian networks and Markov random fields). We present a number of examples of graphical models, including the QMR-DT database, the sigmoid belief network, the Boltzmann machine, and several variants of hidden Markov models, in which it is infeasible to run exact inference algorithms. We then introduce variational methods, which exploit laws of large numbers to transform the original graphical model into a simplified graphical model in which inference is efficient. Inference in the simpified model provides bounds on probabilities of interest in the original model. We describe a general framework for generating variational transformations based on convex duality. Finally we return to the examples and demonstrate how variational algorithms can be formulated in each case.     

Occupational exposure to RF fields from base station antennas on rooftops

At specific situations, workers need to approach very close to the transmitting base station antennas. In this study, occupational exposure to RF fields from base station antennas was assessed at several rooftops. The measurements were carried out by mapping the power densities around the antennas. The results were compared with the ICNIRP guidelines. The results indicate that the reference levels for workers and the general public may be exceeded in front of the transmitting antenna at distances up to 1 and 2 m, respectively.     

Role of Brown and Beige Adipose Tissues in Seasonal Adaptation in the Raccoon Dog (Nyctereutes procyonoides)

Brown adipose tissue (BAT) expresses uncoupling protein-1 (UCP1), which enables energy to be exerted towards needed thermogenesis. Beige adipocytes are precursor cells interspersed among white adipose tissue (WAT) that possess similar UCP1 activity and capacity for thermogenesis. The raccoon dog (Nyctereutes procyonoides) is a canid species that utilizes seasonal obesity to survive periods of food shortage in climate zones with cold winters. The potential to recruit a part of the abundant WAT storages as beige adipocytes for UCP1-dependent thermogenesis was investigated in vitro by treating raccoon dog adipocytes with different browning inducing factors. In vivo positron emission tomography/computed tomography (PET/CT) imaging with the glucose analog ¹⁸F-FDG showed that BAT was not detected in the adult raccoon dog during the winter season. In addition, UCP1 expression was not changed in response to chronic treatments with browning inducing factors in adipocyte cultures. Our results demonstrated that most likely the raccoon dog endures cold weather without the induction of BAT or recruitment of beige adipocytes for heat production. Its thick fur coat, insulating fat, and muscle shivering seem to provide the adequate heat needed for surviving the winter.     

MathSAT: Tight Integration of SAT and Mathematical Decision Procedures

Recent improvements in propositional satisfiability techniques (SAT) made it possible to tackle successfully some hard real-world problems (e.g., model-checking, circuit testing, propositional planning) by encoding into SAT. However, a purely Boolean representation is not expressive enough for many other real-world applications, including the verification of timed and hybrid systems, of proof obligations in software, and of circuit design at RTL level. These problems can be naturally modeled as satisfiability in linear arithmetic logic (LAL), that is, the Boolean combination of propositional variables and linear constraints over numerical variables. In this paper we present MathSAT, a new, SAT-based decision procedure for LAL, based on the (known approach) of integrating a state-of-the-art SAT solver with a dedicated mathematical solver for LAL. We improve MathSAT in two different directions. First, the top‐level line procedure is enhanced and now features a tighter integration between the Boolean search and the mathematical solver. In particular, we allow for theory-driven backjumping and learning, and theory-driven deduction; we use static learning in order to reduce the number of Boolean models that are mathematically inconsistent; we exploit problem clustering in order to partition mathematical reasoning; and we define a stack-based interface that allows us to implement mathematical reasoning in an incremental and backtrackable way. Second, the mathematical solver is based on layering; that is, the consistency of (partial) assignments is checked in theories of increasing strength (equality and uninterpreted functions, linear arithmetic over the reals, linear arithmetic over the integers). For each of these layers, a dedicated (sub)solver is used. Cheaper solvers are called first, and detection of inconsistency makes call of the subsequent solvers superfluous. We provide a through experimental evaluation of our approach, by taking into account a large set of previously proposed benchmarks. We first investigate the relative benefits and drawbacks of each proposed technique by comparison with respect to a reference option setting. We then demonstrate the global effectiveness of our approach by a comparison with several state-of-the-art decision procedures. We show that the behavior of MathSAT is often superior to its competitors, both on LAL and in the subclass of difference logic. This work has been partly supported by ISAAC, a European-sponsored project, contract no. AST3-CT-2003-501848; by ORCHID, a project sponsored by Provincia Autonoma di Trento; and by a grant from Intel Corporation. The work of T. Junttila has also been supported by the Academy of Finland, project 53695. S. Schulz has also been supported by a grant of the Italian Ministero dell'Istruzione, dell'Università e della Ricerca and the University of Verona.     

Unrestricted vs restricted cut in a tableau method for Boolean circuits

This paper studies the relative efficiency of variations of a tableau method for Boolean circuit satisfiability checking. The considered method is a nonclausal generalisation of the Davis–Putnam–Logemann–Loveland (DPLL) procedure to Boolean circuits. The variations are obtained by restricting the use of the cut (splitting) rule in several natural ways. It is shown that the more restricted variations cannot polynomially simulate the less restricted ones. For each pair of methods T, T′, an infinite family of circuits is devised for which T has polynomial size proofs while in T′ the minimal proofs are of exponential size w.r.t. n, implying exponential separation of T and T′ w.r.t. n. The results also apply to DPLL for formulas in conjunctive normal form obtained from Boolean circuits by using Tseitin’s translation. Thus DPLL with the considered cut restrictions, such as allowing splitting only on the variables corresponding to the input gates, cannot polynomially simulate DPLL with unrestricted splitting.AMS subject classification 03B70, 03F20, 68T15, 68T20The financial support from Academy of Finland (project #53695) is gratefully acknowledged.Tommi Junttila: This work was partially done while visiting ITC-IRST (Trento, Italy), and has been sponsored by the CALCULEMUS! IHP-RTN EC project, contract code HPRN-CT-2000-00102.     

Economic Geography of Knowledge-Intensive Technology Clusters: Lessons from the Helsinki Metropolitan Area

This paper analyzes industrial clusters in the Helsinki Metropolitan Area (HMA) in Finland. The HMA is the largest and most powerful concentration of population and economic activity in Finland. The paper analyzes knowledge-intensive industrial clusters and their structures. Clusters are identified according to a statistical analysis that provides a systematic perspective on the knowledge-intensive economic geography of the HMA. There are two main questions: how diverse are the identified clusters in terms of their internal structure; and, are there spatial irregularities identifiable in these structures? Knowledge-intensive clusters are strongly localized close to the infrastructural nodes: their physical localization is closely linked to road- and rail-structures and terminals. In general, clusters become smaller as their distance to the center of Helsinki increases: distance decay is evidently present. Our findings indicate that clusters are plural entities and their diversities do not follow a clearly identifiable pre-determined logic. Knowledge-based industries focusing on immaterial products tend to have closer central proximity than other industries but variations are extensive. This cluster diversity indicates that the HMA has a threshold for manifesting agglomeration gains that generate and extend industrial diversities within key clusters. The most diverse clusters tend to be located in the urban core, whereas the more narrowly focused clusters may be found in relatively peripheral locations.