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Owing to the use of large volumes of toxic solvents and reagents, green analytical methods have gained increasing importance in natural product research. Herein, a green approach is proposed using the natural deep eutectic solvents (NADES) for the extraction and separation of phenols from Teucrium chamaedrysby use of an ecofriendly high-performance thin-layer chromatography (HPTLC) method. Principal component analysis was used to classify NADES extracts based on HPTLC data. The method’s greenness was assessed using two different tools: the National Environmental Methods Index (NEMI) and the analytical eco-scale. This method can also find application in routine quality control analysis of the investigated medicinal herb with minimal harm to the environment or human health.

Purpose: Up to date, there has been a lack of software infrastructure to connect 3D Slicer to any augmented reality (AR) device. This work describes a novel connection approach using Microsoft HoloLens 2 and OpenIGTLink, with a demonstration in pedicle screw placement planning. Methods: We developed an AR application in Unity that is wirelessly rendered onto Microsoft HoloLens 2 using Holographic Remoting. Simultaneously, Unity connects to 3D Slicer using the OpenIGTLink communication protocol. Geometrical transform and image messages are transferred between both platforms in real time. Through the AR glasses, a user visualizes a patient’s computed tomography overlaid onto virtual 3D models showing anatomical structures. We technically evaluated the system by measuring message transference latency between the platforms. Its functionality was assessed in pedicle screw placement planning. Six volunteers planned pedicle screws' position and orientation with the AR system and on a 2D desktop planner. We compared the placement accuracy of each screw with both methods. Finally, we administered a questionnaire to all participants to assess their experience with the AR system. Results: The latency in message exchange is sufficiently low to enable real-time communication between the platforms. The AR method was non-inferior to the 2D desktop planner, with a mean error of 2.1 ± 1.4 mm. Moreover, 98% of the screw placements performed with the AR system were successful, according to the Gertzbein–Robbins scale. The average questionnaire outcomes were 4.5/5. Conclusions: Real-time communication between Microsoft HoloLens 2 and 3D Slicer is feasible and supports accurate planning for pedicle screw placement.

Background/AimMidwives play an important role in assisting women to cope with the initial trauma of perinatal loss, but their own coping and support needs can be overlooked. The purpose of the study was to explore the coping behaviours and support needs of midwives caring for women with perinatal loss.MethodsA qualitative, exploratory, descriptive design was used. Data were collected using semi-structured one-on-one interviews with 13 purposively sampled participants from the Nelson Mandela Bay Health District.ResultsThree themes emerged concerning midwives' coping mechanisms in relation to perinatal loss, their views on support from management and the need for psychological and emotional support.ConclusionsThe participants felt the need for unit-based psychological and emotional support. They called for the development of a protocol for midwives to manage perinatal loss events. They felt that the layout of the labour wards needed to be redesigned and that the problem of staff shortages needed to be urgently addressed.

We develop a sequential sampling procedure for a class of stochastic programs. We assume that a sequence of feasible solutions with an optimal limit point is given as input to [...]

The significant growth of the hedge funds industry in the past decade has been supplemented by increased allocations to alternative investments by high-net-worth individuals as well as endowments and foundations. [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jbankfin.2005.04.016 Byline: David P. Morton (a), Elmira Popova (a), Ivilina Popova (b) Keywords: Portfolio choice; Expected regret; Hedge funds; Fund of funds; Portfolio optimization; Monte Carlo simulation Abstract: We consider portfolio allocation in which the underlying investment instruments are hedge funds. We consider a family of utility functions involving the probability of outperforming a benchmark and expected regret relative to another benchmark. Non-normal return vectors with prescribed marginal distributions and correlation structure are modeled and simulated using the normal-to-anything method. A Monte Carlo procedure is used to obtain, and establish the quality of, a solution to the associated portfolio optimization model. Computational results are presented on a problem in which we construct a fund of 13 CSFB/Tremont hedge-fund indices. Author Affiliation: (a) Graduate Program in Operations Research and Industrial Engineering, The University of Texas at Austin, Austin, TX 78712, USA (b) Albers School of Business and Economics, Seattle University, Seattle, WA 98122, USA

We describe a large-scale linear programming model for optimizing strategic (intercontinental) airlift capability. The model routes cargo and passengers through a specified transportation network with a given fleet of aircraft [...]

The authors present new techniques for solving the problem of bounding the expected value of a stochastic linear program. Topics include the dual restricted-recourse bound and specifications for the model.

Most sampling-based stochastic based algorithms that perform repeated samples during the solution procedure for stochastic programs do not have stopping rules that can manage a priori the quality of the proposed solution. In this light, a study was conducted with the aim of formulating rules that can address this flaw for a specific type of sampling-based algorithms. The stopping rules developed have two components. One is a criteria for the termination of the algorithm and the other is a rule for the selection of the sample sizes. The stopping rules were found to ensure asymptotic validity of the targeted confidence interval statements as the interval width decreases and the sample sizes increase.

A study was conducted to characterize a stochastic network interdiction that attempts to destroy network components. The stochastic network interdiction problem was established with uncertain, binary interdiction successes to reduce achievable flow using a set of arcs. The minimization of the interdiction problem was represented with first-stage variables and random parameters. A number of variants were also establish to support nonnegative values, binary and uncertain arc capacities, and multiple uncertain interdictions on an arc. Results showed that the interdiction model reduces concave function based on the convex hull of the integer first-stage feasible region.

In the last 30 years, little experimental work has been reported on the critical properties of (halogenated hydrocarbon + hydrocarbon) mixtures. Furthermore, the overall amount of reported critical property data for these types of mixtures is quite small. This work aims to extended the existing data set and presents data on the critical temperatures of (i) 14 different chloroalkane (C3–C4) + hydrocarbon mixtures (C6–C7) as a function of mole fraction and (ii) 10 different aromatic halocarbons (chlorobenzene, fluorobenzene, 1,2-dichlorbenzene, or 1,3-dichlorobenzene) + alkanes (C8) as a function of mole fraction. All of the (gas + liquid) critical lines were continuous. Therefore, all mixtures displayed either Type I or Type II behavior.

Background:Job satisfaction among nurses often determines whether they choose to remain in the profession or in the facility where they work.Aim:The study sought to explore and describe the job satisfaction of registered nurses in South Africa through the lens of their nurse unit managers.Methods:A qualitative, exploratory, descriptive design was undertaken. Fourteen unit managers were interviewed and Tesch's method of data analysis was used.Findings:Four themes emerged: ‘staff shortages lead to nurses feeling overwhelmed and frustrated’, ‘nurses’ work performance is undermined by limited resources and poor infrastructure', ‘discontent among nurses with regard to poor top level and human resource management’ and ‘despite challenges, nurses experience rare moments of job satisfaction’.Conclusion:Unit managers need to find ways to enhance existing elements of job satisfaction by emphasising the nurse–patient relationship and teamwork among their staff in order to improve the overall job satisfaction of staff.

AbstractAromatherapy with essential oils (EOs) has been linked to improvement of cognitive function in patients with dementia. In order to act systemically, active EO components must be absorbed through the skin, enter the systemic circulation, and cross the blood brain barrier (BBB). Thus, the aim of this work was to develop quantitative structure activity relationships (QSARs), to predict skin and blood barrier penetrative abilities of 119 terpenoids from EOs used in aromatherapy. The first model was based on experimentally measured skin permeability for 162 molecules, and the second model on BBB permeability for 138 molecules. Each molecule was encoded with 63 calculated molecular descriptors and an artificial neural network was used to correlate molecular descriptors to permeabilities. Developed QSAR models confirm that EOs components penetrate through the skin and across the BBB. Some well-known descriptors, such as log P (lipophilicity), molecular size and shape, dominated the QSAR model for BBB permeability. Compounds with the highest predicted BBB penetration were hydrocarbon terpenes with the smallest molecular size and highest lipophilicity. Thus, molecular size is a limiting factor for penetration. Compounds with the highest skin permeability have slightly higher molecular size, high lipophilicity and low polarity. Our work shows that a major disadvantage of novel multitarget compounds developed for the treatment of Alzheimer’s disease is the size of molecules, which cause problems in their delivery to the brain. Therefore, there is a need for smaller compounds, which possess more desirable physicochemical properties and pharmacokinetics, in addition to targeted biological effects.Communicated by Ramaswamy H. Sarma

AbstractMultiple syringe exchange programs serve the Chicago metropolitan area, providing support for drug users to help prevent infectious diseases. Using data from one program over a ten-year period, we study the behavior of its clients, focusing on the temporal process governing their visits to service locations and on their demographics. We construct a phase-type distribution with an affine relationship between model parameters and features of an individual client. The phase-type distribution governs inter-arrival times between reoccurring visits of each client and is informed by characteristics of a client including age, gender, ethnicity, and more. The inter-arrival time model is a sub-model in a simulation that we construct for the larger system, which allows us to provide a personalized prediction regarding the client’s time-to-return to a service location so that better intervention decisions can be made with the help of simulation.

BackgroundMidwives play an important role as advocates and guides for women in labour regarding their choice of mode of birth. However, there is a paucity of research exploring midwives' perceptions of their role in how women make this choice.AimTo explore and describe how midwives perceive their role in facilitating the choice of mode of birth of women in labour at public sector birthing units.MethodA quantitative, exploratory-descriptive design was used. A questionnaire was used to collect data from 288 midwives in public birthing units in the Eastern Cape, South Africa.FindingsThe majority of the participants agreed that women in labour should be allowed to choose their preferred mode of birth. However, nearly half felt that care providers could overrule that decision depending on the health of the mother and the baby.ConclusionMidwives perceived themselves as the main role players in assisting women in labour to make an informed decision regarding the mode of birth that would best suit their circumstances.

Number of papers used nanosized aluminium oxides (NAOs) as adsorbents to remove pollutants. Sources: Google Scholar, Web of Science and Scopus; Period: 1997–2018.

The enhanced Commonwealth performance framework was introduced on 1 July 2015 under the Public Governance, Performance and Accountability Act 2013.It should allow the Australian Parliament and public to understand the proper use of public resources, whether the accountable authorities of Commonwealth entities and companies are achieving their purposes and who is benefitting from Commonwealth activity. Demonstrating the achievement of purposes amounts to demonstrating outcomes and impacts. It requires Commonwealth entities and companies to move past an over-reliance on input- and output-focused performance measures. There is a clear role for evaluators in helping entities make this important adjustment. The opportunities lie in helping a larger cross-section of the Commonwealth public service understand and use the evaluators’ toolbox – for example, program theory and qualitative analysis – to improve the quality of published performance information available to the Commonwealth’s stakeholders. The evaluation community has the opportunity to become a centre of key expertise, and to make a critical contribution to building the capability of ‘performance professionals’ across the public sector.

Antimicrobial resistance has emerged in recent years as a significant public health threat, which requires both an ethical and a scientific approach. In a recent Policy Delphi study, on-farm use of antimicrobials was a key concern identified by veterinary professionals in Ireland. In this case study (the second in a series of three resulting from a research workshop exploring the challenges facing the veterinary profession in Ireland; the other two case studies investigate clinical veterinary services and emergency/casualty slaughter certification) we aim to provide a value-based reflection on the constraints and possible opportunities for responsible use of veterinary antimicrobials in Ireland. Using a qualitative focus group approach, this study gathered evidence from relevant stakeholders, namely veterinarians working in public and private organisations, a representative from the veterinary regulatory body, a dairy farmer and a general medical practitioner. Three overarching constraints to prudent on-farm use of veterinary antimicrobials emerged from the thematic analysis: ‘Defective regulations’, ‘Lack of knowledge and values’ regarding farmers and vets and ‘Farm-centred concerns’, including economic and husbandry concerns. Conversely, three main themes which reflect possible opportunities to the barriers were identified: ‘Improved regulations’, ‘Education’ and ‘Herd health management’. Five main recommendations arose from this study based on the perspectives of the study participants including: a) the potential for regulatory change to facilitate an increase in the number of yearly visits of veterinarians to farms and to implement electronic prescribing and shorter validity of prescriptions; b) a ‘One Health’ education plan; c) improved professional guidance on responsible use of veterinary antimicrobials; d) improved on-farm herd health management practices; and e) the promotion of a ‘One Farm-One Vet’ policy. These findings may assist Veterinary Council of Ireland and other competent authorities when revising recommendations concerning the prudent use of veterinary antimicrobials in farmed animals.

Veterinarians are faced with significant conflicts of interest when issuing certificates for the transport and slaughter of acutely injured and casualty livestock. In a recent Policy Delphi study, emergency and casualty slaughter certification was a key concern identified by veterinary professionals in Ireland. In this case study (the third in a series of three resulting from a research workshop exploring challenges facing the veterinary profession in Ireland; the other two case studies investigate clinical veterinary services and the on-farm use of veterinary antimicrobials), we aim to provide a value-based reflection on the constraints and opportunities for best practice in emergency and casualty slaughter certification in Ireland. Using a qualitative focus group approach, this study gathered evidence from relevant stakeholders, namely a representative from the regulatory body, local authority veterinarians with research experience in emergency slaughter, an animal welfare research scientist, official veterinarians from the competent authority, a private veterinary practitioner, and a member of a farming organisation. Results revealed a conflict between the responsibility of private veterinary practitioners (PVPs) to safeguard the welfare of acutely injured bovines on-farm and the client’s commercial concerns. As a consequence, some PVPs may feel under pressure to certify, for example, an acutely injured animal for casualty slaughter instead of recommending either on-farm emergency slaughter or disposal by the knackery service. Among Official Veterinarians, there are concerns about the pressure within processing plants to accept acutely injured livestock as casualty animals. Confusion pertaining to legislation and definition of fitness to travel also contribute to these dilemmas. Conflicts of interest arise due to the gap between governance and provision to facilitate on-farm emergency slaughter of livestock. Increased availability and acceptance of on-farm emergency slaughter by Food Business Operators (FBOs) would mitigate the need to certify acutely injured animals fit for transport and slaughter and thereby safeguard animal welfare. In the absence of nationwide availability and acceptance of on-farm emergency slaughter by FBOs, consideration should be given to methods to encourage all those involved in the food chain to prioritise animal welfare when in conflict with the commercial value of the animal. Training and guidelines for PVPs on the regulatory landscape and ethical decision-making should become available. The reintroduction of the fallen animal scheme should be considered to support farm animal welfare.

The provision of veterinary clinical services is known to elicit a range of challenges which require an ethical appraisal. In a recent Policy Delphi study, referrals/second opinions and 24 h emergency care were identified as matters of key concern by veterinary professionals in Ireland. In this case study (the first in a series of three resulting from a research workshop exploring challenges facing the veterinary profession in Ireland; the other two case studies investigate the on-farm use of veterinary antimicrobials and emergency/casualty slaughter certification) we aim to provide a value-based reflection on the constraints and possible opportunities for two prominent veterinary clinical services in Ireland: referrals/second opinions and 24 h emergency care. Using a qualitative focus group approach, this study gathered evidence from relevant stakeholders, namely referral and referring veterinarians, clients, animal charities, and the regulatory body. Six overarching, interrelated constraints emerged from the thematic analysis: the need to improve current guidance, managing clients’ expectations, concerns with veterinarian well-being, financial issues, timeliness of referral, and conflicts between veterinary practices. Possible solutions to improve veterinary referral and out-of-hours clinical services included clarifying the terms used in current norms and regulations (namely ‘referral’, ‘second opinion’, ‘24 h emergency care’ and ‘24 h cover’), improved communication (making the client aware of the different levels of veterinary care that are being offered, and transparent and full disclosure of clinical records), and the promotion of Continuing Veterinary Education in communication, business management and ethical decision-making. These findings may help inform the Veterinary Council of Ireland about future recommendations and regulatory measures.

Aim and Objective: This study investigates molecular structural requirements that are responsible for the antioxidant activity in phenolic compounds. Method: Antioxidant activity of compounds was determined with a 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical assay. Principal component analysis (PCA) was used to classify phenolic antioxidants according to the key molecular features that contribute to their antioxidant activity. Artificial neutral networks (ANNs) was used to develop a predictive QSAR model. Results: Both models agreed that structural characteristics of phenolic compounds responsible for the antioxidant activity include: (1) number and position of alcohol groups on the aromatic ring; (2) molecular size; (3) flexibility/bulkiness; and (4) water solubility. PCA has classified data into phenolic acids and flavonoids, suggesting two distinct mechanisms of action. ANN has confirmed different mechanisms of action for flavonoids and polyphenolic acids, i.e. breaking of free radical chain reactions by donation of a hydrogen atom to neutralise a free radical and the chelating ability of polyphenolic acids. Conclusion: Although two phenolic acids may have the same relative polarity, their different functional groups may drastically change the nature of their interactions with free radicals, and their antioxidant activity.

The healthy properties of functional food are associated with the presence of a wide range of phenolic antioxidants. Thus, the aim of this study was to develop a simple, rapid, and reproducible high-performance thin-layer chromatographic (HPTLC) method combined with a direct 2,2′-diphenyl-1-picrylhydrazyl (DPPH) assay, to compare antioxidant activity in terms of free radical scavenging activity in functional food. We wanted to quantify caffeic acid, chlorogenic, and gallic acid, three natural phenolic antioxidants commonly found in functional food, and determine their contribution to the total free radical scavenging activity. Antioxidant activities of organic cacao, green coffee, chia seeds, goji berries, spirulina, and chlorella were evaluated and compared. The most potent free radical scavenger was found to be chlorogenic acid. Free radical scavenging activity in the functional foods tested was mostly affected by the presence of chlorogenic and caffeic acid, while gallic acid, although present in higher amounts, was a less potent free radical scavenger.

The article discusses integration of systems leading to inter-dependency where in infrastructure of the U.S.and the world is interconnected and poses a security challenge and states it can be solved through restoring urban infrastructure, preventing nuclear terror, and securing cyberspace.

In this study a carrier-free dry powder inhalation (DPI) containing L-arginine (ARG) was developed. As such, it is proposed that ARG could be used for adjunctive treatment of cystic fibrosis and/or tuberculosis. Various processing methods were used to manufacture high-dose formulation batches consisting various amounts of ARG and excipients. The formulations were evaluated using several analytical methods to assess suitability for further investigation. Several batches had enhanced in vitroaerolization properties. Significant future challenges include the highly hygroscopic nature of unformulated ARG powder and identifying the scale of dose of ARG required to achieve the response in lungs.

Tablets represent the preferred and most commonly dispensed pharmaceutical dosage form for administering active pharmaceutical ingredients (APIs). Minimizing the cost of goods and improving manufacturing output efficiency has motivated companies to use direct compression as a preferred method of tablet manufacturing. Excipients dictate the success of direct compression, notably by optimizing powder formulation compactability and flow, thus there has been a surge in creating excipients specifically designed to meet these needs for direct compression. Greater scientific understanding of tablet manufacturing coupled with effective application of the principles of material science and particle engineering has resulted in a number of improved direct compression excipients. Despite this, significant practical disadvantages of direct compression remain relative to granulation, and this is partly due to the limitations of direct compression excipients. For instance, in formulating high-dose APIs, a much higher level of excipient is required relative to wet or dry granulation and so tablets are much bigger. Creating excipients to enable direct compression of high-dose APIs requires the knowledge of the relationship between fundamental material properties and excipient functionalities. In this paper, we review the current understanding of the relationship between fundamental material properties and excipient functionality for direct compression.

Cohesive powders are problematic in the manufacturing of pharmaceutical solid dosage forms because they exhibit poor flowability, fluidization and aerosolization. These undesirable bulk properties of cohesive powders represent a fundamental challenge in the design of efficient pharmaceutical manufacturing processes. Recently, mechanical dry coating has attracted increasing attention as it can improve the bulk properties of cohesive powders in a cheaper, simpler, safer and more environment-friendly way than the existing solvent-based counterparts. In this review, mechanical dry coating techniques are outlined and their potential applications in formulation and manufacturing of pharmaceutical solid dosage forms are discussed. Reported data from the literature have shown that mechanical dry coating holds promise for the design of superior pharmaceutical solid formulations or manufacturing processes by engineering the interfaces of cohesive powders in an efficient and economical way.

The flow of powders can often play a critical role in the manufacturing of pharmaceutical products. Many of these processes require good, consistent and predictable flow of powders to ensure continuous production of pharmaceutical dosages and to ensure their quality. Therefore, the flow of powders is of paramount importance to the pharmaceutical industry and thus the measuring and evaluating of powder flow is of utmost importance. At present, there are numerous methods in which the flow of powders can be measured. However, due to the complex and environment-dependant nature of powders, no one method exists that is capable of providing a complete picture of the behaviour of powders under dynamic conditions. Some of the most commonly applied methods to measure the flow of powders include: density indices, such as the Carr index and Hausner ratio, powder avalanching, the angle of repose (AOR), flow through an orifice, powder rheometry and shear cell testing.

With advances in technology in recent years and the use of modern techniques for generating and evaluating digital images, high-performance thin-layer chromatography (HPTLC) has become a powerful analytical method to analyze complex herbal samples, providing both qualitative and quantitative data. One of the major concerns with the use of HPTLC is the accuracy of quantitation. In this study, a number of marker compounds in Calendula officinalisplant extracts were analyzed using HPTLC with the aim to investigate and assess the quantitative errors observed. Accuracy of the sample applicator at different sample volumes, the use of a gradient mobile phase, and plate post-chromatographic derivatization all contribute to uncertainties of the HPTLC method and need to be carefully selected in order to minimize error.

A non-linear quantitative structure activity relationship (QSAR) model based on 350 drug molecules was developed as a predictive tool for drug protein binding, by correlating experimentally measured protein binding values with ten calculated molecular descriptors using a radial basis function (RBF) neural network. The developed model has a statistically significant overall correlation value (r > 0.73), a high efficiency ratio (0.986), and a good predictive squared correlation coefficient (q2) of 0.532, which is regarded as producing a robust and high quality QSAR model. The developed model may be used for the screening of drug candidate molecules that have high protein binding data, filtering out compounds that are unlikely to be protein bound, and may assist in the dose adjustment for drugs that are highly protein bound. The advantage of using such a model is that the percentage of a potential drug candidate that is protein bound (PB (%)) can be simply predicted from its molecular structure.

Human activities have introduced tens of thousands of chemicals into water systems around the world which has significantly impacted water quality and aquatic ecosystems. The aim of this study was to develop an in silico QSAR model, capable of predicting the aquatic toxicity of pesticides in terms of a lethal dose (LD50) for fish without requiring the use of in vivo testing. A large data set of 230 diverse pesticides, including fungicides, herbicides and insecticides, with experimentally measured LD50 values was used to develop a predictive QSAR model. Each pesticide molecule was described using 62 calculated molecular descriptors. These descriptors were then related to the LD50 values via an Artificial Neural Network. Sensitivity analysis was used to select descriptors that best describe the model. The developed model included 13 molecular descriptors related to lipophilicity, hydrogen binding and polarity. Note the value of the predictive squared correlation coefficient (q2) for the final model was 0.748, demonstrating the model’s predictability. In the domain of QSAR studies, a q2 value above 0.5 renders a model to be predictive. The model could therefore be used to accurately screen a wide range of compounds without the need for actual compound synthesis and to prioritize potentially toxic compounds for further testing.

The UK housing market has, over the recent 5 years, experienced considerable economic pressures both from the market place and the construction sector. The need for an economic and mass produced housing type that specifically targets the market to achieve the balance for the need of affordability and the benefits of mass customisation is a key focus for delivery. This study sought to deliver a mass produced housing system that could also deliver a high level of customisation. Historically housing that has been mass produced to ensure affordability, has removed a high level of customisation to ensure that the final costs were controlled. This paper also examines the design factors that are integral to the process of delivery of affordable housing. In addition, it will observe the gaps between affordability and mass customisation of a modern method of construction delivered project and the move away from traditional methods of delivery, mapping the shift in the procurement of the design for such housing typologies.

Discounted, discrete-time, discrete state-space, discrete action-space Markov decision processes (MDPs) form a classical topic in control, game theory, and learning, and as a result are widely applied, increasingly, in very large-scale applications. Many algorithms have been developed to solve large-scale MDPs. Algorithms based on value iteration are particularly popular, as they are more efficient than the generic linear programming approach, by an order of magnitude in the number of states of the MDP. Yet in the case of budget constrained MDPs, no more efficient algorithm than linear programming is known. The theoretically slower running times of linear programming may limit the scalability of constrained MDPs piratically; while, theoretically, it invites the question of whether the increase is somehow intrinsic. In this technical note we show that it is not, and provide two algorithms for budget-constrained MDPs that are as efficient as value iteration. Denoting the running time of value iteration by VI, and the magnitude of the input by U, for an MDP with m expected budget constraints our first algorithm runs in time O(poly(m,\log U)\cdotVI). Given a pre-specified degree of precision, \eta, for satisfying the budget constraints, our second algorithm runs in time O(\log m\cdotpoly(\log U)\cdot(1/\eta^2)\cdotVI), but may produce solutions that overutilize each of the $m$ budgets by a multiplicative factor of $1+\eta$. In fact, one can substitute value iteration with any algorithm, possibly specially designed for a specific MDP, that solves the MDP quickly to achieve similar theoretical guarantees. Both algorithms restrict attention to constrained infinite-horizon MDPs under discounted costs. [ABSTRACT FROM PUBLISHER]

There is a large chemical variability between commercially available Echinaceafor both research and consumption impacts on the quality and efficacy of these products. Globally, herbal industries are largely unregulated, leaving manufacturers responsible for quality control. Several recent efforts to improve regulation have created a need for rapid, accurate, and reliable assays suitable for a quality control setting. Thus, the aim of this study was to develop and validate a high-performance thin-layer chromatographic (HPTLC) method for the quantitative analysis of commercial Echinaceaproducts. HPTLC and high-resolution plate imaging were used to separate and quantify the amounts of three phenyl-propanoid compounds which were used then as markers in product quality assessment. The developed method was validated according to the current International Conference on Harmonization (ICH) guidelines in terms of accuracy, precision, linearity, specificity, limits of quantification and detection, and robustness and was used to quantify these markers in three commercial Echinaceaformulations. The method achieved better limits of detection than previous assays, despite exhibiting lower repeatability, particularly when quantifying cichoric acid. This work has demonstrated that high-resolution plate imaging can be used as a reliable method for the quantitative analysis of commercial Echinaceaproducts.

Most drugs are carried from the site of absorption to their intended site of action (target site) by the bloodstream, either dissolved in the serum or bound to plasma proteins. Binding to plasma proteins influences (i.e. limits or favours), drug distribution through the body. Usually it is the unbound drug concentration that determines its pharmacological and toxicological properties. Our ability to design suitable drug candidates depends on our ability to understand the molecular characteristics of drug-protein binding and ideally be able to predict the extent of binding in vivo. Here we review the different approaches that have been used to model and predict the binding of drugs and drug like molecules to plasma proteins in the body.

The aim of this study was to develop an in silico Quantitative Structure Activity Relationship (QSAR) model capable of predicting partitioning of pesticides into breast milk from their respective chemical structures. A large data set of 190 diverse compounds, including drugs and their active metabolites (87), and pesticides (13) with experimentally derived milk/plasma (M/P) ratios taken from the literature, was used to train, test and validate a predictive model. Each compound was encoded with 65 calculated chemical structure descriptors. Sensitivity analysis was then used to select a subset of the descriptors that best describe the transfer of pesticides into breast milk and Artificial neural networks modeling was applied to correlate selected descriptors (inputs) with the M/P ratio (output) in order to develop a predictive QSAR. The developed QSAR model included 26 molecular descriptors related to the molecular size, polarity and hydrogen binding capacity. Together with aromatic rings, these descriptors account for molecules size and hydrophobic interaction capabilities. The average correlation for the final model (incorporating training, testing, and validation) was 0.85. The developed model provides a useful method for predicting the M/P ratios of pesticides from just a sketch of their respective molecular structures. However, these predictions should only be used to assist in the evaluation of risk in conjunction with an assessment of the infants response to a given drug/pesticide.

Building Information Modeling (BIM) has made a considerable impact on the construction industry and the way in which building design information can be accessed and interrogated. This impact is now being seen in the Schools of Architecture in the UK. Academia is beginning to see the feasibility and benefits of converting to such a new technology; will this inevitably start to filter into teaching BIM to architecture students? The concern by many in academia is that design will become secondary to pedagogy of building design. This viewpoint is based on the impact of CAD, where the art of hand drawing was feared lost forever. The use of computers in schools of architecture has become the norm, and the creative moving of a pen across paper has been replaced, to a degree, by the cursor across the CAD screen. As academia moved to respond to this change, the need to teach CAD became increasingly important. Therefore, will the paradigm shift of BIM require the inevitable move to a new approach in the design and construction of buildings? There are many misconceptions of BIM and the dilemma is that those teaching within the schools need to understand how BIM can readily interface with the design process and allow interrogation of the design are far earlier stages of the concept. Will academia ensure that BIM is used to enhance the creative process not hinder it?

The article explains the science and action in plyometrics or an exercise training that aims to produce fast, powerful movements and improve nervous system functions. The amount of time between muscles stretching and initiation of the powerful contraction is reduced by plyometric training. The phases of a plyometric movement include the Pre-Stretch phase and the Concentric phase. The need to establish adequate strength in legs prior to the addition of plyo drills in the training regime is cited.

Nifedipine is a dihydropyridine calcium channel antagonist effective in the clinical management of cardiovascular disease. Due to nifedipines poor water solubility and erratic bioavailability, complexation with selected cyclodextrins was studied in order to overcome these limitations. The aim was to develop a quantitative structure property relationship (QSPR) to identify cyclodextrin molecular properties important in complex formation and provide a predictive tool which would be valuable during preformulation studies. The QSPR developed indicates that the major driving forces for nifedipine complexation, in addition to cyclodextrin concentration, are hydrophobicity and Van der Waals interactions (3D solubility parameters, hydrophilic surface area and differential connectivity index).

The ability to detect changes in oxygen concentration in the environment is critical to the survival of all animals. This requires cells to express a molecular oxygen sensor that can detect shifts in oxygen levels and transmit a signal that leads to the appropriate cellular response. Recent biochemical, genetic and behavioral studies have shown that the atypical soluble guanylyl cyclases function as oxygen detectors in Drosophila larvae triggering a behavioral escape response when exposed to hypoxia. These studies also identified the sensory neurons that innervate the terminal sensory cones as likely chemosensors that mediate this response. Here I summarize the data that led to these conclusions and also highlight evidence that suggests additional, as yet unidentified, proteins are also required for detecting increases and decreases in oxygen concentrations.

Evidence suggests that environmental exposure to estrogen-like compounds can cause adverse effects in humans and wildlife. The Endocrine Disruptor Screening and Testing Advisory Committee (EDSTAC) has advised screening of 87,000 compounds in the interest of human safety. This may best be accomplished by pre-screening using quantitative structure-activity relationship (QSAR) modelling. The present study aimed to develop in silico QSARs based on natural, semi-synthetic, synthetic, and phytoestrogens, to predict the potential estrogenic toxicity of pesticides. A diverse set of 170 compounds including steroidal-, synthetic- and phytoestrogens, as well as pesticides was used to construct the QSAR models using artificial neural networks (ANNs). Mean correlation coefficients between experimentally measured and predicted binding affinities were all greater than 0.7 and models had few false negative results, an important consideration for screening tools. This study demonstrated the utility of ANNs as QSAR models for pre-screening of potential endocrine disruptors.

The article offers nutrition tips for runners. For salads, it recommends replacing lettuce with spinach since it will increase one's athletic performance. To prepare a sandwich for lunch, it notes that darker whole grain bread is better than low GI white bread because it will provide the most fiber and the benefits of whole grain. A basmati rice is also recommended when a runner is not training but needs energy. Other recommended foods are salsa, parmesan, flaxseed oil, and kale.

Dopamine and its receptors play a critical role in diseases such as Parkinsons disease and schizophrenia. A problem with developing specific drugs for such diseases is that there are five subtypes of dopamine receptors that can be categorized as either D1 like or D2 like. Since the binding sites are quite similar, it is difficult to design the subtype specific agonists and antagonists required for therapy with minimal side effects. Thus, the aim of this study was to identify the molecular characteristics important to the selective binding of dopamine D1 like and D2 like receptors using quantitative structure activity relationships (QSARs). Datasets of 29 and 69 molecules capable of binding to cloned human D1 and D2 receptors were used to build QSAR models. The dissociation constants (Ki) for these molecules were taken from the literature. The optimized 3D structure of each molecule was encoded with 62 theoretical molecular descriptors. The QSAR, using hybrid neural network modeling, was built using categorical and continuous molecular descriptors as inputs, with dissociation constants (Ki) as outputs. Categorically assigned molecular descriptors improved performance in both models. Secondary amines and other nitrogen-containing moieties were shown to be important for the D1 like receptor selectivity, whereas molecular size, volume and tertiary and quaternary carbons were found to be of significant importance for the D2 like receptor selectivity.