Structured 3D linear space– time light bullets by nonlocal nanophotonics

We propose the generation of 3D linear light bullets propagating in free space using a single passive nonlocal optical surface. The nonlocal nanophotonics can g...     

Budgeting in Hierarchical Systems Under Uncertainty

This paper deals with budgeting procedures in a multi-division firm. The global objective function of the firm is composed of maximizing the present value and minimizing the risk of the accepted projects. A weight is assigned to each one of these objectives. Different budgeting procedures are developed for the cases where these weights are known or unknown and for centralized and decentralized settings. In the cases where these weights are known, mathematical programming methods are suggested. However, in the cases where the values of the weights are unspecified, the notion of Discrete Efficient Frontier (DEF) is developed to represent sets of efficient (not dominated) combinations of projects. A simple measure of performance is developed for evaluating the effectiveness of the various budgeting procedures. This measure is based on the total area beneath the DEF. Finally, an extensive simulation study is carried out to see the effectiveness of the centralized vs. the decentralized procedures suggested in this study.     

ESTABLISHING ZONES IN SINGLE-COMMAND CLASS-BASED RECTANGULAR AS/RS

In this paper, we develop procedures for dividing rectangular warehouses into classes. We describe three types of classes and develop their corresponding traveling time models. A solution procedure involving a one-dimensional (or at most two-dimensional) search is developed. We show that the one-dimensional search procedure is very effective in solving most practical problems. Additionally, we show that most of the savings obtained by a full-turnover policy can be obtained with a relatively few classes—a result similar to the one obtained for the square AS/RS.     

Relationship between intrinsic needs and women's persistence at work.

Attempted to predict Israeli females' persistence at work on the basis of the needs determining their occupational choice. Ss included 288 dentists, 31 registered nurses, 20 policewomen, 30 social workers, and 35 youth counselors. Ss rated a list of needs according to the effect they had on Ss' occupational choice. Persistence was measured by the length of time S worked during the critical period for her occupation (e.g., between ages 35-50 yr. for nurses). All correlations between job persistence and intrinsic needs were positive. Correlations between extrinsic needs and job persistence were either positive or negative. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Managing Demand to Optimize Production Costs

Manufacturing firms often have to deal with a demand pattern that is characterized by fluctuations. Demand fluctuations may be caused by factors such as seasonalities, the dynamics of a particular industrial sector or of the entire economy, change in demand levels over a short product life cycle, promotions carried out by marketing, or by contracts between an organization and its customers. Typically, a firm would be able to exercise a high degree of control over its choice of contracts and over marketing promotions and very little control over the remaining factors. This paper focuses on situations in which demand fluctuations are caused by "controllable" factors. The paper develops an analytic model to examine the impact of demand fluctuations (resulting from "controllable" factors) on the production system. The objective is to manage demand to ensure that production costs are minimized for a given amount of aggregate demand over the planning horizon. The paper examines the validity of the notion that demand fluctuations always have an adverse impact on manufacturing. The results indicate that optimal demand and production patterns tend to be well-behaved monotone series that are characterized by little, if any, fluctuation. These results thus support the notion that fluctuations are undesirable. It is shown, however, that a level demand pattern is not necessarily optimal.     

UV disinfection of wastewater effluents for unrestricted irrigation.

Wastewater reuse in arid regions is important for the production of a water resource to be utilised for non-potable purposes and to prevent the environmental transmission of disease-causing agents. This study was conducted to evaluate the effect of water quality on the comparative disinfection efficiency of viruses, bacteria and spores by UV irradiation. Furthermore, the microbial quality of effluent produced by coagulation, high rate filtration (HRF) and either UV irradiation or chlorination was determined. Using low pressure collimated beam, a UV dose of 80 mWs/cm2 was needed to achieve a 3-log10 inactivation of either rotavirus SA-11 or coliphage MS2, whereas over 5-log10 inactivation of E. coli was reached with a dose of only 20 mWs/cm2. B. subtilis inactivation was found to be linear up to a dose of 40 mWs/cm2 and then a tailing up to a UV dose of 120 mWs/cm2 was observed. It is worth noting that effluent turbidity of < 5 NTU did not influence the inactivation efficiency of UV irradiation. Operation of a pilot plant to treat secondary effluent by coagulation, HRF and UV disinfection at a UV dose of 80 mWs/cm2 resulted in the production of high quality effluent in compliance with the Israel standards for unrestricted irrigation (< 10 CFU/100 mL faecal coliform and turbidity of < 5 NTU). Sulphite reducing clostridia (SRC) were found to be more resistant than coliphages and F coliform for UV irradiation. The results of this study indicated that UV disinfection is suitable for the production of effluents for unrestricted irrigation of food crops.     

Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure

Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from findings in clinical trials, animal experiments, and molecular studies going back more than forty years. In this work we explore PSP chemical space and its relevance for the prediction of adverse drug reactions. Firstly, in silico (computational) Bayesian models for 70 PSP-related targets were built, which are able to detect 93% of the ligands binding at IC(50) < or = 10 microM at an overall correct classification rate of about 94%. Secondly, employing the World Drug Index (WDI), a model for adverse drug reactions was built directly based on normalized side-effect annotations in the WDI, which does not require any underlying functional knowledge. This is, to our knowledge, the first attempt to predict adverse drug reactions across hundreds of categories from chemical structure alone. On average 90% of the adverse drug reactions observed with known, clinically used compounds were detected, an overall correct classification rate of 92%. Drugs withdrawn from the market (Rapacuronium, Suprofen) were tested in the model and their predicted ADRs align well with known ADRs. The analysis was repeated for acetylsalicylic acid and Benperidol which are still on the market. Importantly, features of the models are interpretable and back-projectable to chemical structure, raising the possibility of rationally engineering out adverse effects. By combining PSP and ADR models new hypotheses linking targets and adverse effects can be proposed and examples for the opioid mu and the muscarinic M2 receptors, as well as for cyclooxygenase-1 are presented. It is hoped that the generation of predictive models for adverse drug reactions is able to help support early SAR to accelerate drug discovery and decrease late stage attrition in drug discovery projects. In addition, models such as the ones presented here can be used for compound profiling in all development stages.     

Cigarette smoking during pregnancy.

Maternal smoking during pregnancy is associated with several adverse developmental outcomes in the offspring. These include preterm delivery, spontaneous abortion, growth restriction, increased risk of sudden infant death syndrome (SIDS), as well as long-term behavioral and psychiatric disorders. However, the underlying physiological mechanisms for these ill-effects are not fully understood. The aim of this paper is to review the animal and human data to date, linking in utero smoke exposure to negative neurodevelopmental outcomes. It is known that nicotine from cigarette smoke exerts its effects by affecting placental vasculature, and also by nicotinic acetylcholine receptor binding in fetal membranes. Thus, subsequent consequences involve a cascade of events causing not only dysregulation of the nicotinic and muscarinic, but also catecholaminergic and serotonergic neurotransmitter systems. These observations provide some insight into how smoking can impair neurodevelopment, but the long-term neurotransmitter involvement in dysregulation of emotion and attention awaits further elucidation. It is important that pregnant women are warned of the detrimental effects of smoking, and encouraged to abstain for healthy fetal development.     

Internal Layout Design of a Warehouse

Two configurations of shelves, in a homogeneous or a zoned warehouse, are compared. Handling costs as well as costs associated with the warehouse area and perimeter are taken into consideration. From these, expressions for optimal design parameters are developed. It is shown that, depending on ratios between the relevant costs, some general preference rules for the two layouts examined can be laid down.