Two-Species Harvesting System with Price and Biomass Dependent Demand Via Simulated Annealing

[[abstract]]Simulated Annealing (SA) algorithm has been developed and implemented for an inventory control system of living species whose demands are price and biomass dependent. Here, the species ameliorates with time and are of the type of prey – predator. Predator species do have some natural growth in addition to their growth depending on other species. The species are cultivated for one period only. For the first time, inventory model of ameliorating two species are formulated and SA algorithm for that model is developed and implemented to find the optimum values of initial stocks of the species and optimum time period. These are evaluated to have maximum possible profit out of the system. The system has been illustrated numerically and results for some particular cases are obtained

A fuzzy genetic algorithm with varying population size to solve an inventory model with credit-linked promotional demand in an imprecise planning horizon

A genetic algorithm (GA) with varying population size is developed where crossover probability is a function of parents' age-type (young, middle-aged, old, etc.) and is obtained using a fuzzy rule base and possibility theory. It is an improved GA where a subset of better children is included with the parent population for next generation and size of this subset is a percentage of the size of its parent set. This GA is used to make managerial decision for an inventory model of a newly launched product. It is assumed that lifetime of the product is finite and imprecise (fuzzy) in nature. Here wholesaler/producer offers a delay period of payment to its retailers to capture the market. Due to this facility retailer also offers a fixed credit-period to its customers for some cycles to boost the demand. During these cycles demand of the item increases with time at a decreasing rate depending upon the duration of customers' credit-period. Models are formulated for both the crisp and fuzzy inventory parameters to maximize the present value of total possible profit from the whole planning horizon under inflation and time value of money. Fuzzy models are transferred to deterministic ones following possibility/necessity measure on fuzzy goal and necessity measure on imprecise constraints. Finally optimal decision is made using above mentioned GA. Performance of the proposed GA on the model with respect to some other GAs are compared.Fuzzy genetic algorithm Fuzzy rule base Credit-linked demand Imprecise planning horizon

A novel hybrid algorithm for generalized traveling salesman problems in different environments

Abstract A swap sequence-based particle swarm optimization (SSPSO) technique and genetic algorithm (GA) are used in tandem to develop a hybrid algorithm to solve generalized traveling salesman problem. Local search algorithm K-Opt is occasionally used to move any stagnant solution. Here, SSPSO is used to find the sequence of groups of a solution in which a tour to be made and cities from different groups of the sequence are selected using GA. The K-Opt algorithm (for $$K=3$$ K=3 ) is used periodically for a predefined number of iterations to improve the quality of the solutions. The algorithm is capable of solving the problem in crisp as well as in imprecise environment. For this purpose, a general fitness evaluation rule for the solutions is proposed. The efficiency of the algorithm is tested in crisp environment using different size benchmark problems available in TSPLIB. In crisp environment, the algorithm gives 100% success rate for problems up to considerably large sizes. Imprecise problems are generated from crisp problems randomly using a rule and are solved using the proposed approach. The obtained results are discussed. Moreover it is observed that the proposed algorithm finds multiple optimal paths, when they exist, both for the crisp problems and their fuzzy variations

Inactivation of 9q22.3 tumor suppressor genes predict outcome for patients with head and neck squamous cell carcinoma

Aim: This study examined the prognostic significance of candidate tumor suppressor genes (TSGs) PHD finger protein-2 (PHF2), Fanconi anaemia complementation group C (FANCC) and human homologue of Drosophila patched gene (PTCH1), in head and neck squamous cell carcinoma (HNSCC) treated primarily with surgery, or surgery followed by adjuvant radiotherapy. Patients and Methods: Eighty-four patients with HNSCC were followed-up for recurrence/death for up to five years after diagnosis. Molecular alterations (deletion/methylation) of TSGs and human papilloma virus (HPV) status were determined in previous studies of our group. Statistical analyses of correlation of genetic alterations with treatment response and survival were carried out. Results: Alterations of FANCC and PTCH1 were significantly associated with locoregional recurrence/death. In the surgery with adjuvant radiotherapy-group (n=56), patients showing alterations in FANCC and in PTCH1 were seven- and six-times, respectively, more likely to have locoregional recurrence compared to those with no alterations. In addition, the presence of alterations of both FANCC and PTCH1 had remarkable prognostic significance. Conclusion: FANCC and PTCH1 alterations might be used as molecular markers for prognosis and to develop strategies for effective treatment planning

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Not AvailableBacterial blight (BB), caused by Xanthomonas oryzae pv. Oryzae (Xoo), is one of the most serious diseases of rice causing a significant yield loss mostly in Asia and parts of Africa and poses a threat to the breakdown of varietal resistance. Development of resistant varieties carrying major resistance (R) gene(s) has been the effective way for controlling BB. The type of R gene(s) to be deployed depends on the predominant Xoo pathotypes. Identification of the R genes present in rice germplasm is a vital exercise. In the present experiment, phenotyping for BB resistance was carried out in 210 rice germplasm comprised of released varieties and landraces from eastern and northeastern India. Based on disease scoring, 95 released varieties being categorized into 29 resistant, 42 moderately resistant and 24 susceptible, while, 115 rice landraces were grouped into eight resistant, 38 moderately resistant and 69 susceptible accessions. Molecular screening for the presence and frequency of 10 BB resistance genes was made from a sub set of 70 genotypes, comprising 35 resistant, 21 moderately resistant and 14 susceptible entries. The frequency of R genes varied from 0 to 5 per genotype. The most frequent gene was Xa1 followed by Xa7 > Xa4 > Xa10 > Xa11. A few entries such as Nua Kalajeera, Kalinga III, Naveen, CR Dhan 701, Swarna Sub1, Kalajeera, and ARC5791 possessed 3–5 genes. The findings indicated that Xa1, Xa7, and Xa11 had been frequently selected in breeding programmes, and the frequency of xa5, Xa8, xa13 and Xa21 should be increased in the released varieties in different combinations to achieve durable resistance. The resistant cultivars identified in the present study can be used directly as resistance donors in rice breeding as well as for identification of race-specific/broad spectrum sources of resistance against BB.Not Availabl

Conformational selection underpins recognition of multiple DNA sequences by proteins and consequent functional actions

Recognition of multiple functional DNA sequences by a DNA-binding protein occurs widely in nature. The physico-chemical basis of this phenomenon is not well-understood. The E. coli gal repressor, a gene regulatory protein, binds two homologous but non-identical sixteen basepair sequences in the gal operon and interacts by protein–protein interaction to regulate gene expression. The two sites have nearly equal affinities for the Gal repressor. Spectroscopic studies of the Gal repressor bound to these two different DNA sequences detected significant conformational differences between them. Comprehensive single base-substitution and binding measurements were carried out on the two sequences to understand the nature of the two protein–DNA interfaces. Magnitudes of basepair–protein interaction energy show significant variation between homologous positions of the two DNA sequences. Magnitudes of variation are such that when summed over the whole sequence they largely cancel each other out, thus producing nearly equal net affinity. Modeling suggests significant alterations in the protein–DNA interface in the two complexes, which are consistent with conformational adaptation of the protein to different DNA sequences. The functional role of the two sequences was studied by substitution of one site by the other and vice versa. In both cases, substitution reduces repression in vivo. This suggests that naturally occurring DNA sequence variations play functional roles beyond merely acting as high-affinity anchoring points. We propose that two different pre-existing conformations in the conformational ensemble of the free protein are selected by two different DNA sequences for efficient sequence read-out and the conformational difference of the bound proteins leads to different functional roles