A new and sensitive reaction rate method for spectrophotometric determination of trace amounts of thiourea in different water samples based on an induction period

BACKGROUNDAgrilus bigutattus (Fabricius) is a forest pest of increasing importance in the United Kingdom. The larvae damage weakened native oaks and are thought to contribute to premature tree death. Suspected links with acute oak decline (AOD) are not yet confirmed, but AOD-predisposed trees appear to become more susceptible to A. biguttatus attack. Thus, management may be necessary for control of this insect. To explore the possibility of monitoring beetle populations by baited traps, the host tree volatiles regulating A. biguttatus-oak interactions were studied. RESULTSBiologically active volatile organic compounds in dynamic headspace extracts of oak foliage and bark were identified initially by coupled gas chromatography-electroantennography (GC-EAG) and GC-mass spectrometry (GC-MS), and the structures were confirmed by GC coinjection with authentic compounds. Of two synthetic blends of these compounds comprising the active leaf volatiles, the simpler one containing three components evoked strongly positive behavioural responses in four-arm olfactometer tests with virgin females and males, although fresh leaf material was more efficient than the blend. The other blend, comprising a five-component mixture made up of bark volatiles, proved to be as behaviourally active for gravid females as bark tissue. CONCLUSIONSThese initial results on A. biguttatus chemical ecology reveal aspects of the role of attractive tree volatiles in the host-finding of beetles and underpin the development of semiochemically based surveillance strategies for this forest insect. (c) 2015 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Risk of betel chewing for oesophageal cancer in Taiwan

Among 104 cases of squamous-cell oesophageal carcinoma patients and 277 controls in Taiwan, after adjusting for cigarette smoking, alcohol consumption, and other confounders, we found that subjects who chewed from 1 to 495 betel-year and more than 495 betel-years (about 20 betel quid per day for 20 years) had 3.6-fold (95% Cl = 1.3–10.1) and 9.2-fold risk (95% Cl = 1.8–46.7), respectively, of developing oesophageal cancer, compared to those who did not chew betel. © 2001 Cancer Research Campaign http://www.bjcancer.co

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at √s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into diferent pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at √ s = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, tt¯, and tb) or third-generation leptons (τν and τ τ ) are included in this kind of combination for the frst time. A simplifed model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confdence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Search for new phenomena with top-quark pairs and large missing transverse momentum using 140 fb−1 of pp collision data at \sqrt{s} = 13 TeV with the ATLAS detector

A search is conducted for new phenomena in events with a top quark pair and large missing transverse momentum, where the top quark pair is reconstructed in final states with one isolated electron or muon and multiple jets. The search is performed using the Large Hadron Collider proton-proton collision data sample at a centre-of-mass energy of \sqrt{s} = 13 TeV recorded by the ATLAS detector that corresponds to an integrated luminosity of 140 fb^{−1}. An analysis based on neural network classifiers is optimised to search for directly produced pairs of supersymmetric partners of the top quark (stop), and to search for spin-0 mediators, produced in association with a pair of top quarks, that decay into dark-matter particles. In the stop search, the analysis is designed to target models in which the mass difference between the stop and the neutralino from the stop decay is close to the top quark mass. This new search is combined with previously published searches in final states with different lepton multiplicities. No significant excess above the Standard Model background is observed, and limits at 95% confidence level are set. Models with neutralinos with masses up to 570 GeV are excluded, while for small neutralino masses models are excluded for stop masses up to 1230 GeV. Scalar (pseudoscalar) dark matter mediator masses as large as 350 (370) GeV are excluded when the coupling strengths of the mediator to Standard Model and dark-matter particles are both set to one. At lower mediator masses, models with production cross-sections as small as 0.15 (0.16) times the nominal predictions are excluded. Results of this search are also used to set constraints on effective four-fermion contact interactions between top quarks and neutrinos

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p

Combination of searches for resonant Higgs Boson pair production using pp collisions at √s = 13 TeV with the ATLAS detector

A combination of searches for a new resonance decaying into a Higgs boson pair is presented, using up to 139  fb−1 of pp collision data at √s = 13 TeV recorded with the ATLAS detector at the LHC. The combination includes searches performed in three decay channels: b ¯ b ⁢b ¯ b , b⁢ ¯ b ⁢τ+⁢τ−, and b⁢ ¯ bγγ ⁢. No excess above the expected Standard Model background is observed and upper limits are set at the 95% confidence level on the production cross section of Higgs boson pairs originating from the decay of a narrow scalar resonance with mass in the range 251 GeV–5 TeV. The observed (expected) limits are in the range 0.96–600 fb (1.2–390 fb). The limits are interpreted in the type-I two-Higgs-doublet model and the minimal supersymmetric standard model, and constrain parameter space not previously excluded by other searches

Search for light long-lived particles in pp collisions at √s = 13 TeV using displaced vertices in the ATLAS inner detector

A search for long-lived particles (LLPs) using 140 fb−1 of pp collision data with √s = 13 TeV recorded by the ATLAS experiment at the LHC is presented. The search targets LLPs with masses between 5 and 55 GeV that decay hadronically in the ATLAS inner detector. Benchmark models with LLP pair production from exotic decays of the Higgs boson and models featuring long-lived axionlike particles (ALPs) are considered. No significant excess above the expected background is observed. Upper limits are placed on the branching ratio of the Higgs boson to pairs of LLPs, the cross section for ALPs produced in association with a vector boson, and, for the first time, on the branching ratio of the top quark to an ALP and a u/c quark

High frequency AC-DC converter for high current applications

High amount of direct current is essential in many industrial processes. Conventional methods for obtaining high amount of direct current involve parallel operation of converters with interphase or five-legged rectifier transformer. The interphase transformer (IPT) and/or rectifier transformer employed in the system increase overall size of the system and also provide limited control over the operation. This paper presents simpler topology of high frequency AC-DC converter specially for low-voltage high-current industrial applications. In the proposed topology, rectifier module and low frequency L-C filter in the primary stage (required for conventional high frequency converters) are eliminated. The topology provides better control over the operation and helps in reducing size of the overall rectifier system. The topology is simulated for a practical application of 12 V, 5000 A rectifier system. The three-phase high frequency transformer present in the topology is designed and its estimated size is compared with the existing five-legged rectifier transformer for the conventional system