Optimal Prime-Time Television Network Scheduling

This paper introduces SPOT (Scheduling of Programs Optimally for Television), an analytical model for optimal prime-time TV program scheduling. Due in part to the advent of new cable TV channels. the competition for viewer ratings has intensified substantially in recent years, and the revenues of the major networks have not kept pace with the costs of the programs. As profit margins decrease, the networks seek to improve their viewer ratings with innovative scheduling strategies. Our SPOT models for scheduling network programs combine predicted ratings for different combinations of prime-time schedules with 3 novel, mixed-integer, generalized network flow, mathematical programming model, which, when solved, provides an optimal schedule. In addition to historical performance, subjective inputs from actual network managers were used as input to the network flow optimization model. The optimization model is flexible. It can utilize the managers' input and maximize profit (instead of ratings) by considering not only the revenue potential but also the costs of the shows. Moreover, SPOT can describe the scheduling problem over any time period (e.g.. day, week month, season), and designate certain shows to, and restrict them from, given time slots. The methodology of SPOT is illustrated using data obtained from a cable network during the first quarter of 1990. The optimization model produces solutions which would have generated an increase of approximately 2 percent in overall profitability, representing over $12 million annually for a typical network with an average Nielsen rating of 18. SPOT not only produces more profitable TV schedules for this network, but also provides valuable general insights into the development of mixed programming strategies for improving future schedules

Rematuration of Spent Macrobrachium rosenbergii Female Broodstock through Dietary Manipulation and Eyestalk Ablation

The single or combined effects of artificial feed and eyestalk ablation on gonadal maturation of spent Macrobrachium rosenbergii female brooders was studied in 48 females. Significant differ- ences in percent weight gain, food conversion ratio, specific growth rate, gonado-somatic index, number of molts, molting interval, and ovarian development stages were observed. The highest numbers of molts and shortest molting intervals were found in eyestalk-ablated groups while higher percent weight gains were obtained in non-ablated groups. Groups fed formulated feed registered lower percent weight gains and higher FCRs than groups fed natural feed (clam and squid meat). Females in immature stages were found only in non-ablated groups while the only ovigerous females were found in the ablated group fed formulated feed. In short, unilateral eye- stalk ablation together with properly formulated feed (46.1% crude protein) could induce gonad maturation of spent female Macrobrachium rosenbergii brooders during the non-monsoon sea- son

Control and analysis of crucial parameters for an automatic boiler unit in a chemical industry

A boiler plays a significant role in a processing industry, particularly in chemical industry. It requires proper adoption of control techniques for supplying accurate temperature, pressure, steam, and water flow to produce chemicals. An uncontrolled boiler can shut down the whole process. Therefore it requires a continuous monitoring system for avoiding such shutdown. In the past few decades, relay logic, embedded or process card systems were used for controlling the boiler system. In the conventional system, the controlling scheme was also complex for troubleshooting because process cards are used only once. In order to overcome this type of problem Supervisory Control and Data Acquisition (SCADA) and Programmable Logic Controller (PLC) system helps to collect data and information about the flow of boiler from various sensors. In this paper, SCADA and PLC assist in controlling crucial parameters using Proportional Integral Derivative (PID) control. PID controller used in this paper is programmed according to the boiler operation's need, and the data can be stored and analyzed using the SCADA system. The results in this paper help the industrial personnel for boiler automation, allowing the plant operator to observe the crucial parameters for increasing boiler efficiency and reducing the financial losses.&nbsp

directional genome walking using pcr

We describe here a PCR-based "directional genome walking" protocol. The basic procedure for the amplification consists of two rounds of PCR. A primary PCR was performed, on the genomic DNA using a ..

Aldo-keto reductase-1 (AKR1) protect cellular enzymes from salt stress by detoxifying reactive cytotoxic compounds

Cytotoxic compounds like reactive carbonyl compounds such as methylglyoxal (MG), melandialdehyde (MDA), besides the ROS accumulate significantly at higher levels under salinity stress conditions and affect lipids and proteins that inhibit plant growth and productivity. The detoxification of these cytotoxic compounds by overexpression of NADPH-dependent Aldo-ketoreductase (AKR1) enzyme enhances the salinity stress tolerance in tobacco. The PsAKR1 overexpression plants showed higher survival and chlorophyll content and reduced MDA, H2O2, and MG levels under NaCl stress. The transgenic plants showed reduced levels of Na+ levels in both root and shoot due to reduced reactive carbonyl compounds (RCCs) and showed enhanced membrane stability resulted in higher root growth and biomass. The increased levels of antioxidant glutathione and enhanced activity of superoxide dismutase (SOD), ascorbate peroxidase (APX) and glutathione reductase (GR) suggest AKR1 could protect these enzymes from the RCC induced protein carbonylation by detoxification process. The transgenics also showed higher activity of delta 1-pyrroline-5- carboxylate synthase (P5CS) enzyme resulted in increasedproline levels to maintain osmotic homeostasis. The results demonstrates that the AKR1 protects proteins or enzymes that are involved in scavenging of cytotoxic compounds by detoxifying RCCs generated under salinity stress. © 2017 Elsevier Masson SA

Leveraging Machine Learning based Ensemble Time Series Prediction Model for Rainfall Using SVM, KNN and Advanced ARIMA+ E-GARCH

Today's precipitation is growing increasingly variable, making forecasting increasingly difficult. The Indian Meteorological Department (IMD) currently employs Composite and Stochastic approaches to forecast spring storm precipitation in Asia. As a corollary, planners are unlikely to predict the macroeconomic effects of disasters (due to excessive precipitation) or famine (less precipitation). The amount of precipitation that drops dependent on a variety of factors, including the temperature of the atmosphere, humidity, velocity, mobility, and weather conditions. This paper would then employ the Hybrid time-series predictive ARIMA+ E-GARCH (Exponential Generalized Auto-Regressive Conditional Heteroskedasticity) to predict precise runoff by taking into account different climatic considerations such as maritime tension, water content, relative dampness, min-max heat, heavy ice, geostrophic tallness, breeze patterns, soil dampness, and barometric force. In perspective of RMSE, MAE, and MSE, the proposed hybrid ARIMA+E-GARCH paradigm outperformed single simulations and latest hybrid techniques

Interplay of magnetic order and Jahn-Teller distortion in a model with strongly correlated electron system

The Hubbard model has been employed successfully to understand many aspects of correlation driven physical properties, in particular, the magnetic order in itenerant electron systems. In some systems such as Heusler alloys, manganites etc., it is known that, in addition to magnetic order, distortion induced by Jahn-Teller(J-T) effect also exists. In this paper, based on two-fold degenerate Hubbard model, the influence of magnetic order on J-T distortion is investigated. The electron correlation is treated using a spectral density approach and J-T interaction is added to the model. We find that magnetic order and structural distortion coexist at low temperature $T$ for a certain range of electron correlation strength $U$, J-T coupling strength $G$ and band occupation $n$. At T=0, for a given $n$ and $U$, magnetic order is present but distortion appears only for a $G$ larger than a critical value. We also studied the temperature dependence of lattice strain and magnetization choosing a $G$ close to the critical value.Comment: 12 pages, 5 Figures. Physica- B 405 1701-1705 (2010

Rabies Virus Infection in Domestic Buffaloes and Wild Animals in India

Rabies is one of the most significant diseases in India with severe health implication to humans, domestic and wild animals. In the present study, four concomitant incidents of rabies related deaths were recorded in the western province of India, Gujarat during 2012 - 2014. Brain samples were collected from two buffaloes, nilgai, and mongoose during these incidents and rabies virus was identified from these samples. Further genetic relationship of these isolates was determined and the rabies virus transmission among the wild and domestic mammals was established. Molecular epidemiology based on the glycoprotein ecto-domain and complete nucleoprotein gene showed that all the four isolates belonged to Arctic-like 1 lineage which is predominant in India. Phylogenetic analysis and time scaled evolutionary tree analysis indicated that the wild animals are playing an important role in the maintenance and also transmission of the rabies virus in India

Fitting the curve in Excel®:Systematic curve fitting of laboratory and remotely sensed planetary spectra

Spectroscopy in planetary science often provides the only information regarding the compositional and mineralogical make up of planetary surfaces. The methods employed when curve fitting and modelling spectra can be confusing and difficult to visualize and comprehend. Researchers who are new to working with spectra may find inadequate help or documentation in the scientific literature or in the software packages available for curve fitting. This problem also extends to the parameterization of spectra and the dissemination of derived metrics. Often, when derived metrics are reported, such as band centres, the discussion of exactly how the metrics were derived, or if there was any systematic curve fitting performed, is not included. Herein we provide both recommendations and methods for curve fitting and explanations of the terms and methods used. Techniques to curve fit spectral data of various types are demonstrated using simple-to-understand mathematics and equations written to be used in Microsoft Excel® software, free of macros, in a cut-and-paste fashion that allows one to curve fit spectra in a reasonably user-friendly manner. The procedures use empirical curve fitting, include visualizations, and ameliorates many of the unknowns one may encounter when using black-box commercial software. The provided framework is a comprehensive record of the curve fitting parameters used, the derived metrics, and is intended to be an example of a format for dissemination when curve fitting data