diff --git a/fulltext/istex/tei/2FE1BB70A77D356A22B946D72169DC6938FEB254.training.fulltext.tei.xml b/fulltext/istex/tei/2FE1BB70A77D356A22B946D72169DC6938FEB254.training.fulltext.tei.xml index a9b530b..c64e273 100644 --- a/fulltext/istex/tei/2FE1BB70A77D356A22B946D72169DC6938FEB254.training.fulltext.tei.xml +++ b/fulltext/istex/tei/2FE1BB70A77D356A22B946D72169DC6938FEB254.training.fulltext.tei.xml @@ -299,16 +299,18 @@ 17 8 7 (42%) 10 6.2 4 19 2 10 (53%) 9 5.8 Total: 189 46 111 (59%) 78 Success rates for long-term pain relief are calculated as percentages of the number of patients achieving success - with trial stimulation. 3 Comparison of the Time Interval Between the First - Operation to the Body Part Experiencing Chronic Pain and SCS and the Subsequent - Response to SCS TIME BETWEEN FIRST OPERATION AND IMPLANT NUMBER - TRIAL STIMULATION PAIN RELIEF LONG-TERM PAIN RELIEF AVERAGE - FOLLOW-UP PERIOD (YEARS) SUCCESS FAILURE SUCCESS - FAILURE 0–3 years 15 14 1 13 (93%) 1 5.2 3–6 - years 34 28 6 23 (82%) 5 5.8 6–9 years 34 - 27 7 15 (56%) 12 6.3 9–12 years 29 28 1 11 - (39%) 17 5.9 12 years 32 23 9 2 (9%) 21 - 5.7 Total: 144 120 24 64 (53%) 56 + with trial stimulation. + +
3 Comparison of the Time Interval Between the First Operation to the Body Part + Experiencing Chronic Pain and SCS and the Subsequent Response to SCS TIME + BETWEEN FIRST OPERATION AND IMPLANT NUMBER TRIAL STIMULATION + PAIN RELIEF LONG-TERM PAIN RELIEF AVERAGE FOLLOW-UP PERIOD + (YEARS) SUCCESS FAILURE SUCCESS FAILURE 0–3 years 15 + 14 1 13 (93%) 1 5.2 3–6 years 34 28 6 23 + (82%) 5 5.8 6–9 years 34 27 7 15 (56%) 12 + 6.3 9–12 years 29 28 1 11 (39%) 17 5.9 12 + years 32 23 9 2 (9%) 21 5.7 Total: 144 + 120 24 64 (53%) 56
COMPLICATIONS diff --git a/fulltext/istex/tei/6927E50ECD751087F616E82E1E9CDB14F0321548.training.fulltext.tei.xml b/fulltext/istex/tei/6927E50ECD751087F616E82E1E9CDB14F0321548.training.fulltext.tei.xml index a57dcd3..9386a06 100644 --- a/fulltext/istex/tei/6927E50ECD751087F616E82E1E9CDB14F0321548.training.fulltext.tei.xml +++ b/fulltext/istex/tei/6927E50ECD751087F616E82E1E9CDB14F0321548.training.fulltext.tei.xml @@ -27,14 +27,15 @@ workers (e.g. GODWARD, 1934, 1937; WHITFORD, 1956; ODUM, 1957; BROWN, 1976; CATTANEO, 1978; CATTANEO and KALFF, 1978) have compared algal communities on artificial substrates and on macrophytes, with conflicting - results. Some studies (e.g. PROWSE, 1959; BOWNIK, 1970; - ALLANSON, 1973; SIVER, 1977; EMINSON and MOSS, 1980; ALLEN and OCEVSKI, 1981; - PIP and ROBINSON, 1982a; DELBECQUE, 1983; MI LLIE and LOWE, 1983) have - compared periphyton composition and/or productivity on different macrophytes, again - with various outcomes. However, these investigators have generally dealt with only - a few plant species, or with a mixture of submerged and emergent forms, which are - associated with different environmental situations, thus making interpretation of - any differences in community structure difficult.

+ results. Some studies (e.g. + PROWSE, 1959; BOWNIK, 1970; ALLANSON, 1973; SIVER, 1977; EMINSON + and MOSS, 1980; ALLEN and OCEVSKI, 1981; PIP and ROBINSON, 1982a; + DELBECQUE, 1983; MI LLIE and LOWE, 1983) have compared periphyton + composition and/or productivity on different macrophytes, again with various + outcomes. However, these investigators have generally dealt with only a few plant + species, or with a mixture of submerged and emergent forms, which are associated + with different environmental situations, thus making interpretation of any + differences in community structure difficult.

In the present study eleven species of submerged macrophytes were collected at a constant depth in a nitrogen and phosphorus rich lake. These were compared with @@ -329,7 +330,7 @@ the periphyton composition of a site. Although CASTENHOLZ (1960) found similar communities on glass plates and on natural surfaces, and GODWARD (1934, 1937), WHITFORD - (1956) and ODUM (1957) found reasonable + (1956) and ODUM (1957) found reasonable similarity between communities on aquatic plants and on artificial substrates, FOERSTER and SCHLICHTING (1965), TIPPETT (1970), BROWN (1976) and n ¼ ðL=L p Þ d0 ; -

with d 0 the capacity (fractal) dimension of the flocs. Solving equation (3) for L - and substituting it throughout equation (1), with the differential dL = ðL p n 1=d - 0 À1 =d 0 Þ dn, we can equivalently re-write equation (1) in terms of n as

+

with d 0 the capacity (fractal) dimension of the flocs. Solving equation (3) for L and substituting it throughout equation (1), with the differential dL = ðL p n 1=d 0 À1 =d 0 Þ dn, + we can equivalently re-write equation (1) in terms of n + as

dn dt ¼ d 0 G L d0À3 p ck a n 3 d 0 À G 1 2 k b n d 0 þ1 d 0 L p n 1 d 0 À 1 3Àd0 @@ -218,12 +220,12 @@

[17] Finding the probability p n (t) in equation (10) solves the stochastic modeling problem as much as finding the solution n(t) in equation (6) solves the deterministic prob-lem. However, - the analytical solution to equation (10) can be difficult to find when the rates f - a (n) and f b (n) are functions of the floc state n. Alternatively, a - numerical approach that mirrors the assumptions made to write the forward - Kolmogorov differential equation can be used. To accomplish this, we must define - the inter-event time Dt, the probability p m a (t), and the probability p - m b (t).

+ the analytical solution to equation (10) can be difficult + to find when the rates f a (n) and f b (n) are functions of the floc state n. + Alternatively, a numerical approach that mirrors the assumptions made to write + the forward Kolmogorov differential equation can be used. To accomplish this, + we must define the inter-event time Dt, the probability p m a (t), and the + probability p m b (t).

2.2. Inter-event Time @@ -380,8 +382,8 @@ column tests at various turbulence shear rates G, and for mass concentration c = 0.5 kg m À3 . Values of m were determined via equation (3) by measuring the size L of individual flocs and estimating their capacity dimension d 0 from optical - recordings [Maggi and Winterwerp, 2004]. The sediment used - was kaolinite with L p % 5 mm and density r s = 2650 kg m À3 . + recordings [Maggi and Winterwerp, 2004]. The sediment used was kaolinite with L p % + 5 mm and density r s = 2650 kg m À3 .
Table 1. Statistical Parameters of the Floc Distributions of Figure 1 Expressed in Terms of Primary-Particle Number and Floc Size a G [ s À1 @@ -469,9 +471,10 @@ To integrate their effect into p m (t), we elaborated further on the parameter m(1) as follows. The median m 50 = e m(1) of the steady state lognormal floc distribution p m (1) can be written in terms of L 50 as m 50 ¼ ðL 50 =L p Þ d 0 ¼ e - mð1Þ by using the fractal scaling in equation (3). Next, having at our disposal the - solution of L* ' L 50 from the deterministic model for any c and G in - equation (2), we can obtain m(1) as

+ mð1Þ by using the fractal scaling in equation (3). Next, + having at our disposal the solution of L* ' L 50 from the deterministic model + for any c and G in equation (2), we can obtain m(1) + as

mð1Þ ¼ d 0 ln 1 þ k a c k b L p G 1=2 ! : diff --git a/fulltext/istex/tei/75E64DC1152F1C53894B27B14C76E9F0BAFAD509.training.fulltext.tei.xml b/fulltext/istex/tei/75E64DC1152F1C53894B27B14C76E9F0BAFAD509.training.fulltext.tei.xml index 698d039..d0bd68f 100644 --- a/fulltext/istex/tei/75E64DC1152F1C53894B27B14C76E9F0BAFAD509.training.fulltext.tei.xml +++ b/fulltext/istex/tei/75E64DC1152F1C53894B27B14C76E9F0BAFAD509.training.fulltext.tei.xml @@ -194,12 +194,12 @@ decisions regarding patient eligibility were made before code breaking.

-

Baseline demographic and clinical measures were compara-ble in both groups ( table - 1). Mean age and average duration of the current episode, however, were higher in - the hypericum group. The baseline total depression scores ranged from 22 - (minimum required) to 34 in both groups. In each group more than half of the - patients had a total score ≥ 25 and were thus severely depressed. 20

+

Baseline demographic and clinical measures were compara-ble in both groups ( table 1). Mean age and average duration of the current + episode, however, were higher in the hypericum group. The baseline total depression + scores ranged from 22 (minimum required) to 34 in both groups. In each group + more than half of the patients had a total score ≥ 25 and were thus severely + depressed. 20

Investigational treatment @@ -237,19 +237,20 @@ compliance (n=10) Per protocol (n=91) Fig 1 Flow of patients and datasets for analysis
-
Table 1 Demographic and clinical characteristics at baseline (intention to - treat analysis; figures are means (SD); medians unless stated otherwise) Hypericum - (n=122) Paroxetine (n=122) No (%) of women 85 (70) 83 (68) Age - (years) 49.0 (11.0); 51.5 45.5 (11.5); 48.0 No (%) with recurrent - depression 50 (41) 49 (40) Duration of current episode (days) - 160 (109); 148 127 (81); 106 HAMD total score* 25.5 (2.7); 25.0 25.5 - (2.9); 25.0 No (%) with HAMD total score ≥25 69 (57) 67 (55) - MADRS total score † 29.9 (5.0); 29.0 29.4 (4.9); 29.0 Beck depression - inventory ‡ 26.3 (8.5); 26.0 25.6 (8.0); 24.5 No (%) markedly or - severely ill § 87 (71) 84 (69) HAMD=Hamilton depression scale; - MADRS=Montgomery-Åsberg depression rating scale. *Theoretical range 0–52. - †Theoretical range 0–60. ‡Theoretical range 0–63; 119 in hypericum group, 120 in - paroxetine group. §According to clinical global impressions score.
+
Table 1 Demographic and clinical characteristics at baseline (intention + to treat analysis; figures are means (SD); medians unless stated otherwise) + Hypericum (n=122) Paroxetine (n=122) No (%) of women 85 (70) 83 + (68) Age (years) 49.0 (11.0); 51.5 45.5 (11.5); 48.0 No (%) with + recurrent depression 50 (41) 49 (40) Duration of current + episode (days) 160 (109); 148 127 (81); 106 HAMD total score* + 25.5 (2.7); 25.0 25.5 (2.9); 25.0 No (%) with HAMD total score ≥25 + 69 (57) 67 (55) MADRS total score † 29.9 (5.0); 29.0 29.4 (4.9); + 29.0 Beck depression inventory ‡ 26.3 (8.5); 26.0 25.6 (8.0); 24.5 + No (%) markedly or severely ill § 87 (71) 84 (69) HAMD=Hamilton + depression scale; MADRS=Montgomery-Åsberg depression rating scale. *Theoretical + range 0–52. †Theoretical range 0–60. ‡Theoretical range 0–63; 119 in hypericum + group, 120 in paroxetine group. §According to clinical global impressions + score.

confidence limit adjusted for the interim analysis 18 for the differ-ence hypericum–paroxetine was 1.5 points). In the per protocol analysis diff --git a/fulltext/istex/tei/B3490B8637ABC221C150475D7C06AE3BF92D6CEB.fulltext.original.training.fulltext.tei.xml b/fulltext/istex/tei/B3490B8637ABC221C150475D7C06AE3BF92D6CEB.fulltext.original.training.fulltext.tei.xml index 7a1a98a..df3d576 100644 --- a/fulltext/istex/tei/B3490B8637ABC221C150475D7C06AE3BF92D6CEB.fulltext.original.training.fulltext.tei.xml +++ b/fulltext/istex/tei/B3490B8637ABC221C150475D7C06AE3BF92D6CEB.fulltext.original.training.fulltext.tei.xml @@ -101,11 +101,12 @@ reserves on the western slopes and plains by wide roadside areas, often following the valley floor along creeks and rivers (NSW RLPB 2001). Some of the highland TSRs contain significant subalpine - grasslands (Eddy 2000), whilst others contain significant riparian wood-land - or foothill forest communities. On the lower slopes, the dominant vegetation - in most TSRs is grassy woodland, except TSRs located along riparian areas such - as the Murray River or Billabong Creek, which support River Red Gum forest - (Webster 1997; 1999a; 1999b; 2000a; 2000b).

+ grasslands (Eddy 2000), whilst others contain significant + riparian wood-land or foothill forest communities. On the lower slopes, the + dominant vegetation in most TSRs is grassy woodland, except TSRs located along + riparian areas such as the Murray River or Billabong Creek, which support + River Red Gum forest (Webster 1997; 1999a; 1999b; 2000a; + 2000b).

The current dilemma for Rural Land Protection Board (RLPB) managers is that TSRs were originally intended for grazing purposes, however, they often @@ -588,22 +589,22 @@ we're starting to change the management, it's quite amazing what is starting to come back very, very quickly. A lot of the lilies, they come back pretty quickly; Chocolate Lily, Vanilla Lily and Onion Orchid are probably the main ones - that I see (Fig. 5). Today I saw an area of fern I hadn't - seen before – then there are the everlasting daisies and the burr daisies. On sites - where we're getting some of the White Box regeneration, we are finding little - saltbushes, orchids and things that you would not imagine could have survived - considering the use the sites have had over the time. I think lack of cultivation is the - secret. If the land has never been cultivated, I think there's a good chance - of getting it back, but once it's cultivated, its chances are much reduced. - Michael Mullins from the Riverina board cites the annual forbs as being the plant group - that is probably the most resilient, without intervention, along with the wallaby - grasses and some of the stipas. But we have not had any good seasons, due to - drought, since I began this approach here. Also, I know that some species such as - the saltbushes are hard to get back in, probably because there's no seed source - there to bring them back. So seed sources can be a probem. To counter this, - we're looking at trialling how to improve some of our isolated patches of - Kangaroo Grass, north of Moama. We're considering scalping weedy areas and placing - seed bearing Kangaroo Grass hay on them. + that I see (Fig. 5). Today I saw an area of fern I hadn't seen before – then + there are the everlasting daisies and the burr daisies. On sites where we're + getting some of the White Box regeneration, we are finding little saltbushes, + orchids and things that you would not imagine could have survived considering the + use the sites have had over the time. I think lack of cultivation is the secret. If the + land has never been cultivated, I think there's a good chance of getting it + back, but once it's cultivated, its chances are much reduced. Michael Mullins + from the Riverina board cites the annual forbs as being the plant group that is probably + the most resilient, without intervention, along with the wallaby grasses and some + of the stipas. But we have not had any good seasons, due to drought, since I began + this approach here. Also, I know that some species such as the saltbushes are hard + to get back in, probably because there's no seed source there to bring them back. + So seed sources can be a probem. To counter this, we're looking at trialling + how to improve some of our isolated patches of Kangaroo Grass, north of Moama. + We're considering scalping weedy areas and placing seed bearing Kangaroo Grass + hay on them.

Figure 5. [Orchid in grassland – to be inserted in Box 5 ] Leek Orchid (Prasophyllum sp.) at Bundure travelling stock reserve (TSR), an extensive