br Conclusion Findings from interviews of officers from

Conclusion
Findings from interviews of officers from different council departments in South-East Queensland confirmed that planners and engineers differ from tree managers in their perspectives and principles for street tree planting and CA-074 Me selection (Roy et al., 2017). It would be interesting to study whether other officers, including planners, urban designers, infrastructure engineers and landscape architects involved in municipal street tree planting programs across Australia share preferences for street tree planting and species selection principles similar to that of tree managers. Future research identifying the species characteristics responsible for specific services/disservices might help Australian tree managers to select street tree species based on environmental principles to alleviate the negative impacts of rapid urbanisation (e.g., evergreen, broad canopy trees to reduce urban heat island effect) (Shashua-Bar and Hoffman, 2000, 2004; Tsiros, 2010). It will also help tree managers to align street tree species selection principles and parameters (e.g., species characteristics, management and maintenance factors) with street tree planting rationale (e.g., environmental benefits, visual and aesthetic benefits) in council documents.

Acknowledgements
The author acknowledges the generosity of time, experience and knowledge offered by tree managers from 129 city councils across Australia in identifying the issues that informed street tree planting principles and species selection rationales within the city councils. The author thanks Associate Professor Jason Byrne and Professor Catherine Pickering from Griffith University, Dr. Aidan Davison from University of Tasmania, Dr. Johan Östberg from Swedish University of Agricultural Sciences and the anonymous reviewers for providing valuable feedbacks that have helped to improve the manuscript. The map showing the geographical distribution of city councils across Australia was prepared by Spatial Science Officer Meghamala Roy Basu. CA-074 Me The funding for this research was made available by an Australian Postgraduate Award.

Introduction
Common ragweed, (Ambrosia artemisiifolia L.), hereafter referred to as ‘ragweed’, is a wind-pollinated annual plant that is native to North America. Ragweed pollen has been detected in Canadian interglacial deposits that are more than 60,000 years old (Bassett and Teresmae, 1962). The massive spread of ragweed in different parts of the world has coincided with major socio-economic transitions that increased disturbed land areas. In 18th and 19th century Canada, European settlement led to increased agricultural activity. Large-scale deforestation and soil disturbance resulted in a hundredfold increase of ragweed pollen in these regions (Bassett and Crompton, 1975).
Ragweed was introduced to Europe at the end of the 19th century. Since then, this species has spread and naturalised across Europe (Kiss and Béres, 2006). The key factor in the introduction of ragweed in Europe was anthropogenic (Chauvel et al., 2006). Commercial trade between North America and Europe, as well as American troops transporting food products and war equipment during the First World War, contributed to the spread of ragweed (Kiss and Béres, 2006). Smith et al. (2013) summarised most existing knowledge about ragweed ecology, its distribution and phenological characters of flowering and its environmental health risk. The authors demonstrated that invasive ragweed is an environmental health threat both in its native range and in the regions in which it has been introduced.
Ragweed was first recorded in Hungary in 1908 (Jávorka, 1910). Regular weed surveys since the 1950s have revealed an extension of the species’ distribution in Hungary. However, in the 1950s, ragweed was not a problematic weed; therefore, no attention was paid to its control. By 1997, under favourable environmental conditions and due to the excellent adaptation ability of this species, ragweed had become the dominant weed species, covering 4.7% of the arable crop area (Béres, 2004). In the most recent weed survey in 2007–2008, ragweed maintained its dominant position, covering 5.33% of Hungary\’s arable crop area (Novák et al., 2009).

br Acknowledgments This study was supported by funding from the

Acknowledgments
This study was supported by funding from the National Institute of Child Health & Human Development (HD 073977, HD 073952). The funder had no role in study design or collection, analysis and interpretation of data or in writing the manuscript.

Introduction
Chronic, soft tissue wounds in the lower limbs, defined as ulcers persisting longer than 3 mo and demanding specialized care (Werdin et al. 2008), have a prevalence of 1% in the adult population, including 3.6% in people older than 65 y, in developed countries (London and Donnelly 2000).
The most common etiology is multifactorial and includes local (e.g., venous or arterial insufficiency, infection and local pressure) and systemic (e.g., diabetes and nutritional status) factors; another common cause is represented by traumatic injuries or surgery (Ferriera et al. 2006). The primary goal in the treatment of chronic soft tissue wounds is to obtain wound closure. Their management includes medical and nutritional optimization, mechanical or surgical debridement, compression, treatment of ischemia, treatment of infection, appropriate wound bed preparation and topical therapies ranging from conservative to advanced (Frykberg and Banks 2015). When chronic wounds do not respond sufficiently to standard care, new wound care therapies are encouraged (Snyder et al. 2010). Among these, the most known are negative pressure wound therapy (Armstrong et al. 2004), hyperbaric oxygen therapy (Zamboni et al. 2003), biological and bio-engineered therapies (Frykberg et al. 2010), biophysical therapies such as electrical stimulation (Baker et al. 1997), pulsed radio frequency CA-074 Me (Frykberg et al. 2011) and extracorporeal shock wave therapy (ESWT) (Schaden et al. 2007). However, for most of these treatments there is neither a high level of evidence, nor randomized prospective studies assessing their efficacy.
The use of ESWT for clinical applications was introduced more than three decades ago for the treatment of urolithiasis (Demling et al. 1982). ESWT was then used to treat several musculoskeletal conditions (Seil et al. 2006). Schaden et al. (2001) observed that the application of ESWT resulted in bony consolidation and soft tissue healing in patients with non-unions and delayed bone fracture healing. Starting from these observations, different studies (Haupt and Chvapil 1990; Kuo et al. 2009a) have reported that ESWT acts to accelerate wound healing through the recruitment of skin fibroblasts and release of endogenous angiogenic factors from endothelial cells and fibroblasts. Other studies have found that ESWT is also responsible for reducing pain in the short term after exposure to ESWT by an as yet incompletely clarified mechanism (Abed et al. 2007; Mariotto et al. 2005, 2009; Ochiai et al. 2007; Ohtori et al. 2001; Takahashi et al. 2003).
Focused ESWT is defined as a sequence of sonic pulses characterized by high peak pressure >100 MPa, rapid pressure rise and short life cycle (Wang 2003). Defocused ESWT is characterized by lower energy values delivered into the soft tissues with a superficial and quite large (3–5 cm2) zone of impact (Mittermayr et al. 2012). Consequently, defocused is more useful than focused ESWT to treat superficial, wide wounds such as ulcers. However, both focused ESWT (Moretti et al. 2009; Omar et al. 2014; Saggini et al. 2008; Wang et al. 2009) and defocused ESWT (Larking et al. 2010; Schaden et al. 2007; Wang et al. 2011; Wolff et al. 2011) have recently been reported to be effective in the treatment of chronic wounds.

Methods

Results
The patients\’ demographic and clinical data are summarized in Table 1. There were four men and six women. Median patient age was 65 (range: 35–81). Median body mass index was 35 (range: 24.9–36.4). Comorbidities were diabetes mellitus type 2 and arterial hypertension in three patients, arterial hypertension (alone) in five patients, venous insufficiency in seven patients and arterial insufficiency in one patient. Four patients were smokers. Wound etiology was mixed (diabetic plus venous in two patients, post-surgical dehiscence plus venous in two patients), venous (three patients) and post-surgical dehiscence, diabetic and arterial (one patient each).

br Method efficacy Three datasets were selected for comparison Fig

Method efficacy
Three datasets were selected for comparison (Fig. 3), with the datasets names were chosen based upon their perceived complexity for automatic identification. An “easy”, “medium” and “hard” case given in Table 1 (PF: Pulse Fraction, TD: target detection rate). Each dataset was acquired from the same LEAP 3000× HR. All datasets masses were randomly shuffled prior to analysis, to eliminate spatial markers that some participants might use to aid their analysis.
The easy case contains no major ambiguities in ranging, but does have an Al/Fe overlap at position 27Da. Decomposition showed a 1.1:0.75 ratio of Fe:Al in this position (~60% total Fe). Manual and automated ranging attempts (intra-participant) ranged this as Fe. For the medium case, the signal-to-noise level was much lower than the easy case, and many molecular species were present (eg MoO) though no major overlaps were present. For the hard case, many overlaps were present, and participants were free to select the CA-074 Me range bounds. For the reported results, decomposition of overlaps is not considered when computing compositions – only the participant label is used.

Intra-operator variance
Using the “easy” dataset from Table 1, the author undertook six separate ranging attempts, each attempt separated by at least ten minutes. This was used to generate a composition for the overall dataset, after excluding the first “Test” ranging. The significant figure precision, which estimates the number of “accurate” leading digits in the reported composition value, is shown in Fig. 4 – computed as D=−log10(2σ/) of the composition (σ – std. deviation). As an example, if the composition was reported to be 12.345%, and D=2, then the composition is 12±0.5% assuming a Gaussian error distribution and a 2σ error threshold. As a further example, if the composition is 10±5%, then D=0, as the leading digit is “inaccurate”. Intra-participant composition was computed using IVAS 3.6.6, including background subtraction. Subsequently variation in measurement is purely single-participant precision, as the mass spectrum has not been altered.
As can be seen from Fig. 4, there is a participant variance between each attempt. In the manual case the trend of single-participant precision is such that more dilute species have a lower precision, roughly linearly on a log–log scaling. H when using an automatically suggested rangefile as the starting point for ranging, the reported error has been reduced for H, Si, Mn and Cr; with Cr and H markedly reduced as during ranging, and this is ascribed to peaks being considered to be sufficiently well-labelled that they were minimally altered by the participant, thus providing a smaller quantity of scatter.
The mean time required for ranging was 8.0min in the manual case, and 7.0min in the assisted case, implying a slightly faster evaluation of datasets even without a customised user interface.
It is suggested that inter-operator variance will be higher when performing manual ranging. The results from Fig. 4 show that there is little alteration in the intra-participant variance between the two cases, unless the participant chooses not to alter the peak at all. As a highly rough approximation for the achievable intra-operator variance E(x), during the ranging procedure the following equation is suggested based upon the logarithmic guide for the unaided case, where x is in atomic fraction, and E(x) in significant figures of precision at 2σ confidence. This equation is valid for this dataset, and is unclear how applicable this is to dissimilar systems.
As an example, using this equation, at 100ppm, intra-operator precision is reduced to 1.2 significant figures. If this procedure were fully automated to an operator-acceptable level, the inter-operator error source could, in theory, be eliminated.

Inter-operator variance
To minimise concerns about the effect of a-priori knowledge on the comparisons, the sequence (automated then manual, or vice-versa) was assigned randomly per participant, per dataset. For the purposes of the test, participants were explicitly instructed to range H and H-containing peaks as such, and to label multi-isotopes using their multiple form. No direction was given as to how peaks should be ranged. The authors were not included as participants in the study, and all participants had experience with APT in their own work, and self-declared as proficient with using the IVAS software package.

br Method efficacy Three datasets were selected for comparison Fig

Method efficacy
Three datasets were selected for comparison (Fig. 3), with the datasets names were chosen based upon their perceived complexity for automatic identification. An “easy”, “medium” and “hard” case given in Table 1 (PF: Pulse Fraction, TD: target detection rate). Each dataset was acquired from the same LEAP 3000× HR. All datasets masses were randomly shuffled prior to analysis, to eliminate spatial markers that some participants might use to aid their analysis.
The easy case contains no major ambiguities in ranging, but does have an Al/Fe overlap at position 27Da. Decomposition showed a 1.1:0.75 ratio of Fe:Al in this position (~60% total Fe). Manual and automated ranging attempts (intra-participant) ranged this as Fe. For the medium case, the signal-to-noise level was much lower than the easy case, and many molecular species were present (eg MoO) though no major overlaps were present. For the hard case, many overlaps were present, and participants were free to select the CA-074 Me range bounds. For the reported results, decomposition of overlaps is not considered when computing compositions – only the participant label is used.

Intra-operator variance
Using the “easy” dataset from Table 1, the author undertook six separate ranging attempts, each attempt separated by at least ten minutes. This was used to generate a composition for the overall dataset, after excluding the first “Test” ranging. The significant figure precision, which estimates the number of “accurate” leading digits in the reported composition value, is shown in Fig. 4 – computed as D=−log10(2σ/) of the composition (σ – std. deviation). As an example, if the composition was reported to be 12.345%, and D=2, then the composition is 12±0.5% assuming a Gaussian error distribution and a 2σ error threshold. As a further example, if the composition is 10±5%, then D=0, as the leading digit is “inaccurate”. Intra-participant composition was computed using IVAS 3.6.6, including background subtraction. Subsequently variation in measurement is purely single-participant precision, as the mass spectrum has not been altered.
As can be seen from Fig. 4, there is a participant variance between each attempt. In the manual case the trend of single-participant precision is such that more dilute species have a lower precision, roughly linearly on a log–log scaling. H when using an automatically suggested rangefile as the starting point for ranging, the reported error has been reduced for H, Si, Mn and Cr; with Cr and H markedly reduced as during ranging, and this is ascribed to peaks being considered to be sufficiently well-labelled that they were minimally altered by the participant, thus providing a smaller quantity of scatter.
The mean time required for ranging was 8.0min in the manual case, and 7.0min in the assisted case, implying a slightly faster evaluation of datasets even without a customised user interface.
It is suggested that inter-operator variance will be higher when performing manual ranging. The results from Fig. 4 show that there is little alteration in the intra-participant variance between the two cases, unless the participant chooses not to alter the peak at all. As a highly rough approximation for the achievable intra-operator variance E(x), during the ranging procedure the following equation is suggested based upon the logarithmic guide for the unaided case, where x is in atomic fraction, and E(x) in significant figures of precision at 2σ confidence. This equation is valid for this dataset, and is unclear how applicable this is to dissimilar systems.
As an example, using this equation, at 100ppm, intra-operator precision is reduced to 1.2 significant figures. If this procedure were fully automated to an operator-acceptable level, the inter-operator error source could, in theory, be eliminated.

Inter-operator variance
To minimise concerns about the effect of a-priori knowledge on the comparisons, the sequence (automated then manual, or vice-versa) was assigned randomly per participant, per dataset. For the purposes of the test, participants were explicitly instructed to range H and H-containing peaks as such, and to label multi-isotopes using their multiple form. No direction was given as to how peaks should be ranged. The authors were not included as participants in the study, and all participants had experience with APT in their own work, and self-declared as proficient with using the IVAS software package.

br Materials and methods br

Materials and methods

Snakes

Twenty one adult South American rattlesnakes (Crotalus durissus terrificus Laurenti 1768), 11 males and 10 females, were obtained from Butantan Institute in São Paulo, Brazil and transported to UNESP Rio Claro where they were maintained in vivaria at natural temperatures and light regimes. Their mean body mass (±SD) was 615 ± 179 g (range, 400–1067 g) and mean body length was 98 ± 16 cm (range, 92–115 cm). The snakes were deemed healthy on the basis of a cursory clinical examination and subsequent post-mortem examinations, which were unremarkable except for intestinal nematodiasis in some individuals. The snakes were fasted for 3 weeks prior to experiments to avoid postprandial changes in acid-base status and CA-074 Me (Arvedsen et al. 2005). All experiments were approved by the Institutional Animal Care and Use Committee (Comissão de Ética na Experimentação Animal, UNESP 03/08-CEEA) at UNESP, Brazil.

Study design and procedure

The study was conducted as a prospective experimental trial. Snakes were removed from their enclosure using a snake hook, and manually restrained by firmly but carefully compressing their bodies under a flexible rubber pad. Anesthesia was induced by administering propofol (15 mg kg−1; 20 mg mL−1, Braun AG, Melsungen, Germany) into the tail vein using a 25 gauge needle. Following induction, the trachea was intubated with an appropriately sized un-cuffed tube. The snakes were randomly assigned to one of four ventilation regimens: 1) spontaneous ventilation (n = 5); 2) mechanical ventilation at a tidal volume (VT) of 30 mL kg−1 and 1 breath every 90 seconds (n = 6); 3) mechanical ventilation at the same VT and 5 breaths minute−1 (n = 5); and 4) mechanical ventilation at the same VT and 15 breaths minute−1 (n = 5). Positive pressure ventilation was initiated immediately after tracheal intubation using a small animal ventilator (SAR 830/AP; CWE Inc., PA, USA) connected directly to the endotracheal tube, and continued for 60 minutes. All animals breathed 100% oxygen and inspiratory time was 3 seconds.

Following local infiltration with lidocaine (0.5 mL, 20 mg mL−1; Xylocaine; AstraZeneca, Denmark) subcutaneously for a right-sided access immediately cranial to the heart, an indwelling occlusive catheter made from polyethylene (Fine Bore Polyethylene Tubing, 0.58 mm internal diameter, 0.96 mm outside diameter; Smiths Medical International Ltd, Horsholm, Denmark) was placed in the vertebral artery to enable arterial blood sampling and measurements of arterial blood pressure (Skals et al. 2005). The catheter was externalized and sutured to the skin dorsally, and the incision closed with interrupted sutures. The procedure lasted approximately 20 minutes. Mechanical ventilation was discontinued 60 minutes after induction of anesthesia and the endotracheal tube was removed when the snake resumed spontaneous movement. The snakes were then transferred to a perforated plastic container (35 × 25 × 10 cm) for the remainder of the experiment, the arterial extension tubing exiting the container through a hole. During surgery, and for the remainder of the experiment, the room temperature was maintained within 26–28 °C. It was only occasionally necessary to cool animals by means of a wet cloth.

Blood gas analysis

Arterial blood (0.5 mL) was obtained from the catheter into a heparinized 1 mL syringe at 30, 40, 60 minutes and 2, 6 and 24 hours after induction of anesthesia. The analyzer uses approximately 100 μL of blood and blood not used by the machine was returned to the snake within 1 minute to alleviate reductions in blood volume. The blood samples were analyzed immediately for pH, partial pressures of oxygen (PaO2) and carbon dioxide (PaCO2), sodium, potassium, calcium, lactate and glucose concentrations as well as hematocrit using an integrated analyzer (GEM Premier 3500; Instrumentation Laboratory, MA, USA) that corrected for individual body temperature. Recent data has verified that the temperature correction of PaCO2 and pH performed by this blood-gas analyzer is adequate for arterial blood from snakes, whereas the temperature correction for PaO2 may be less reliable (Malte et al. in Press).