Available evidence does not support serosorting as an HIV risk reduction strategy

Recent data highlighted the association between penetration of antiretrovirals in the central nervous system (CNS) and neurocognitive impairment in HIVpositive patients. Existing antiretrovirals have been ranked according to a score of neuropenetration, which was shown to be a predictor of anti-HIVactivity in the CNS and improvement of neurocognitive disorders [1]. Main factors affecting drug penetration are known to be protein binding, lipophilicity and molecular weight [2]. Moreover, active translation by membrane transporters (such as p-glycoprotein) could be a key mechanism of passage [3]. The use of raltegravir (RGV), a novel antiretroviral drug targeted to inhibit the HIV preintegrase complex, is increasing worldwide due to its efficacy and tolerability. However, penetration of RGV in the CNS has not been yet elucidated. In fact, prediction of RGV neuropenetration according to molecular characteristics is controversial. Intermediate protein binding (83%) and large volume of distribution (273 l) could suggest a high distribution beyond extracellular spaces [4]. On the contrary, low lipophilicity (oil/water partition coefficient at pH 7.4 of 2.80) and intermediate molecular weight (482.51 Da) suggest a limited diffusion. Furthermore, in-vitro studies suggest that RGV is substrate of p-glycoprotein, although this efflux pump has not been identified to significantly affect plasma pharmacokinetics [5]. In any case, no data concerning RGV passage into cerebrospinal fluid of animals or humans have yet been published.

Sectional analysis of stormwater treatment performance of a constructed wetland

Constructed wetlands are among the most common Water Sensitive Urban Design (WSUD) measures for stormwater treatment. These systems have been extensively studied to understand their performance and influential treatment processes. Unfortunately, most past studies have been undertaken considering a wetland system as a lumped system with a primary focus on the reduction of the event mean concentration (EMC) values of specific pollutant species or total pollutant load removal. This research study adopted an innovative approach by partitioning the inflow runoff hydrograph and then investigating treatment performance in each partition and their relationships with a range of hydraulic factors. The study outcomes confirmed that influenced by rainfall characteristics, the constructed wetland displays different treatment characteristics for the initial and later sectors of the runoff hydrograph. The treatment of small rainfall events (<15 mm) is comparatively better at the beginning of runoff events while the trends in pollutant load reductions for large rainfall events (>15 mm) are generally lower at the beginning and gradually increase towards the end of rainfall events. This highlights the importance of ensuring that the inflow into a constructed wetland has low turbulence in order to achieve consistent treatment performance for both, small and large rainfall events.

Open problem: Shifting experts on easy data

A number of online algorithms have been developed that have small additional loss (regret) compared to the best “shifting expert”. In this model, there is a set of experts and the comparator is the best partition of the trial sequence into a small number of segments, where the expert of smallest loss is chosen in each segment. The regret is typically defined for worst-case data / loss sequences. There has been a recent surge of interest in online algorithms that combine good worst-case guarantees with much improved performance on easy data. A practically relevant class of easy data is the case when the loss of each expert is iid and the best and second best experts have a gap between their mean loss. In the full information setting, the FlipFlop algorithm by De Rooij et al. (2014) combines the best of the iid optimal Follow-The-Leader (FL) and the worst-case-safe Hedge algorithms, whereas in the bandit information case SAO by Bubeck and Slivkins (2012) competes with the iid optimal UCB and the worst-case-safe EXP3. We ask the same question for the shifting expert problem. First, we ask what are the simple and efficient algorithms for the shifting experts problem when the loss sequence in each segment is iid with respect to a fixed but unknown distribution. Second, we ask how to efficiently unite the performance of such algorithms on easy data with worst-case robustness. A particular intriguing open problem is the case when the comparator shifts within a small subset of experts from a large set under the assumption that the losses in each segment are iid.

Experimental and theoretical characterization of 5,10- diminoporphodimethenes: Dearomatized porphyrinoids from palladium-catalyzed hydrazinations of 5,10-diarylporphyrins

A new dearomatized porphyrinoid, 5,10-diiminoporphodimethene (5,10-DIPD), has been prepared by palladium-catalyzed hydrazination of 5,10-dibromo-15,20-bis(3,5-di-tert-butylphenyl)porphyrin and its nickel(II) complex, by using ethyl and 4-methoxybenzyl carbazates. The oxidative dearomatization of the porphyrin ring occurs in high yield. Further oxidation with 2,3-dichloro-5,6-dicyanobenzoquinone forms the corresponding 5,10-bis(azocarboxylates), thereby restoring the porphyrin aromaticity. The UV/visible spectra of the NiII DIPDs exhibit remarkable redshifts of the lowest-energy bands to 780 nm, and differential pulse voltammetry reveals a contracted electrochemical HOMO–LUMO gap of 1.44 V. Density functional theory (DFT) was used to calculate the optimized geometries and frontier molecular orbitals of model 5,10-DIPD Ni7c and 5,10-bis(azocarboxylate) Ni8c. The conformations of the carbamate groups and the configurations of the CNZ unit were considered in conjunction with the NOESY spectra, to generate the global minimum geometry and two other structures with slightly higher energies. In the absence of solution data regarding conformations, ten possible local minimum conformations were considered for Ni8c. Partition of the porphyrin macrocycle into tri- and monopyrrole fragments in Ni7c and the inclusion of terminal conjugating functional groups generate unique frontier molecular orbital distributions and a HOMO–LUMO transition with a strong element of charge transfer from the monopyrrole ring. Time-dependent DFT calculations were performed for the three lowest-energy structures of Ni7c and Ni8c, and weighting according to their energies allowed the prediction of the electronic spectra. The calculations reproduce the lower-energy regions of the spectra and the overall forms of the spectra with high accuracy, but agreement is not as good in the Soret region below 450 nm.

Effect of water management practice on pesticide behavior in paddy water

The fate and transport of three herbicides commonly used in rice production in Japan were compared using two water management practices. The herbicides were simetryn, thiobencarb and mefenacet. The first management practice was an intermittent irrigation scheme using an automatic irrigation system (AI) with a high drainage gate and the second one was a continuous irrigation and overflow drainage scheme (CI) in experimental paddy fields. Dissipation of the herbicides appeared to follow first order kinetics with the half-lives (DT₅₀) of 1.6-3.4 days and the DT₉₀ (90% dissipation) of 7.4-9.8 days. The AI scheme had little drainage even during large rainfall events thus resulting in losses of less than 4% of each applied herbicide through runoff. Meanwhile the CI scheme resulted in losses of about 37%, 12% and 35% of the applied masses of simetryn, thiobencarb and mefenacet, respectively. The intermittent irrigation scheme using an automatic irrigation system with a high drainage gate saved irrigation water and prevented herbicide runoff whereas the continuous irrigation and overflow scheme resulted in significant losses of water as well as the herbicides. Maintaining the excess water storage is important for preventing paddy water runoff during significant rainfall events. The organic carbon partition coefficient K_oc seems to be a strong indicator of the aquatic fate of the herbicide as compared to the water solubility (S_W). However, further investigations are required to understand the relation between K_oc and the agricultural practices upon the pesticide fate and transport. An extension of the water holding period up to 10 days after herbicide application based on the DT₉₀ from the currently specified period of 3-4 days in Japan is recommended to be a good agricultural practice for controlling the herbicide runoff from paddy fields. Also, the best water management practice, which can be recommended for use during the water holding period, is the intermittent irrigation scheme using an automatic irrigation system with a high drainage gate. © 2006 Elsevier B.V. All rights reserved.

ESR measurements of the partitioning of some new spin probes in n-octanol-water

The stable free radical 1,1,3,3-tetramethylisoindolin-2-yloxyl (TMIO) has proved to be very suitable for use as a spin probe for a number of applications. Because it is soluble mainly in non-polar liquids, there is a need for new derivatives that can be used in a variety of environments. This has been done by introducing substituents in the 5-position of the aromatic ring, namely carboxyl (CTMIO), trimethylamino (TMTMIOI) and sodium sulphonate (NaTMIOS). An accurate ESR method was developed for the measurement of partition coefficients in n-octanol–water. For comparison purposes the method was also applied to some Tempo derivatives. The effect of temperature on the rotational correlation times and the nitrogen-14 hyperfine coupling constant of some of the spin probes was investigated. There is evidence for dimerization of CTMIO to form a biradical

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

Australia’s first Pharmacists Immunisation Pilot – about the service

Background: The first phase of the Queensland Pharmacist Immunisation Pilot (QPIP) ran between April and August 2014, to pilot pharmacists administering influenza vaccinations for the flu season for the first time in Australia. Aim: An aim was to investigate factors facilitating implementation of a pharmacist vaccination service in the community pharmacy setting. Method: The QPIP pharmacies were divided into two arms; the South East Queensland arm consisting of 51 Terry White Chemists (TWCs), and 29 pharmacies in the North Queensland (NQ) arm. The TWCs featured pharmacies which previously provided a vaccination service and that were experienced with using an online booking system, providing an opportunity to capture booking data. Results: The TWCs delivered 9902 (90%) of the influenza vaccinations in QPIP. Of these, 48.5% of the vaccines were delivered via appointments made using the online booking system, while 13.3% were in-store bookings. Over one-third (38.2%) of the vaccinations delivered in were “walk-ins” where the vaccination was delivered ‘on the spot’ as spontaneous or opportunistic vaccinations. The absence of a booking system meant all vaccinations delivered in the NQ arm were “walk-ins”. The online-booking data showed 10:00 am and Tuesday being the most popular time and day for vaccinations. Patients preferred having their vaccinations in private consultation rooms, over areas which used a screen to partition off a private area. Discussion: The presence of an online booking system appeared to increase the efficiency and penetration of the of vaccine service delivery. Also, as the level of privacy afforded to patients increased, the number of patients vaccinated also increased. Conclusions: As pharmacist-delivered vaccination services start to progressively roll out across Australia; these findings pave the way for more efficient and effective implementation of the service.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.