Optimal auctions for multi-unit procurement with volume discount bids

Our attention, is focused on designing an optimal procurement mechanism which a buyer can use for procuring multiple units of a homogeneous item based on bids submitted by autonomous, rational, and intelligent suppliers. We design elegant optimal procurement mechanisms for two different situations. In the first situation, each supplier specifies the maximum quantity that can be supplied together with a per unit price. For this situation, we design an optimal mechanism S-OPT (Optimal with Simple bids). In the more generalized case, each supplier specifies discounts based on the volume of supply. In this case, we design an optimal mechanism VD-OPT (Optimal with Volume Discount, bids). The VD-OPT mechanism uses the S-OPT mechanism as a building block. The proposed mechanisms minimize the cost to the buyer, satisfying at the same time, (a) Bayesian, incentive compatibility and (b) interim individual rationality.

How Effective Is The Data On Co-Occurrence Of Domains In Multi-Domain Proteins In Prediction Of Protein-Protein Interactions?

We explore the fuse of information on co-occurrence of domains in multi-domain proteins in predicting protein-protein interactions. The basic premise of our work is the assumption that domains co-occurring in a polypeptide chain undergo either structural or functional interactions among themselves. In this study we use a template dataset of domains in multidomain proteins and predict protein-protein interactions in a target organism. We note that maximum number of correct predictions of interacting protein domain families (158) is made in S. cerevisiae when the dataset of closely related organisms is used as the template followed by the more diverse dataset of bacterial proteins (48) and a dataset of randomly chosen proteins (23). We conclude that use of multi-domain information from organisms closely-related to the target can aid prediction of interacting protein families.

Over-expression and purification strategies for recombinant multi-protein oligomers: A case study of Mycobacterium tuberculosis sigma/anti-sigma factor protein complexes

The function of a protein in a cell often involves coordinated interactions with one or several regulatory partners. It is thus imperative to characterize a protein both in isolation as well as in the context of its complex with an interacting partner. High resolution structural information determined by X-ray crystallography and Nuclear Magnetic Resonance offer the best route to characterize protein complexes. These techniques, however, require highly purified and homogenous protein samples at high concentration. This requirement often presents a major hurdle for structural studies. Here we present a strategy based on co-expression and co-purification to obtain recombinant multi-protein complexes in the quantity and concentration range that can enable hitherto intractable structural projects. The feasibility of this strategy was examined using the sigma factor/anti-sigma factor protein complexes from Mycobacterium tuberculosis. The approach was successful across a wide range of sigma factors and their cognate interacting partners. It thus appears likely that the analysis of these complexes based on variations in expression constructs and procedures for the purification and characterization of these recombinant protein samples would be widely applicable for other multi-protein systems. (C) 2010 Elsevier Inc. All rights reserved.

Improved lithium cyclability and storage in a multi-sized pore (''differential spacers'') mesoporous SnO2

A wide pore distribution mesoporous morphology stabilizes SnO2 structure during lithium insertion and removal and in the process remarkably enhances the lithium storage and cyclability.

Multi-Armed Bandit Mechanisms for Multi-Slot Sponsored Searth Auctions

In pay-per click sponsored search auctions which are currently extensively used by search engines, the auction for a keyword involves a certain number of advertisers (say k) competing for available slots (say m) to display their ads. This auction is typically conducted for a number of rounds (say T). There are click probabilities mu_ij associated with agent-slot pairs. The search engine's goal is to maximize social welfare, for example, the sum of values of the advertisers. The search engine does not know the true value of an advertiser for a click to her ad and also does not know the click probabilities mu_ij s. A key problem for the search engine therefore is to learn these during the T rounds of the auction and also to ensure that the auction mechanism is truthful. Mechanisms for addressing such learning and incentives issues have recently been introduced and would be referred to as multi-armed-bandit (MAB) mechanisms. When m = 1,characterizations for truthful MAB mechanisms are available in the literature and it has been shown that the regret for such mechanisms will be O(T^{2/3}). In this paper, we seek to derive a characterization in the realistic but nontrivial general case when m > 1 and obtain several interesting results.

Modulation of Catalytic Activity in Multi-Domain Protein Tyrosine Phosphatases

Signaling mechanisms involving protein tyrosine phosphatases govern several cellular and developmental processes. These enzymes are regulated by several mechanisms which include variation in the catalytic turnover rate based on redox stimuli, subcellular localization or protein-protein interactions. In the case of Receptor Protein Tyrosine Phosphatases (RPTPs) containing two PTP domains, phosphatase activity is localized in their membrane-proximal (D1) domains, while the membrane-distal (D2) domain is believed to play a modulatory role. Here we report our analysis of the influence of the D2 domain on the catalytic activity and substrate specificity of the D1 domain using two Drosophila melanogaster RPTPs as a model system. Biochemical studies reveal contrasting roles for the D2 domain of Drosophila Leukocyte antigen Related (DLAR) and Protein Tyrosine Phosphatase on Drosophila chromosome band 99A (PTP99A). While D2 lowers the catalytic activity of the D1 domain in DLAR, the D2 domain of PTP99A leads to an increase in the catalytic activity of its D1 domain. Substrate specificity, on the other hand, is cumulative, whereby the individual specificities of the D1 and D2 domains contribute to the substrate specificity of these two-domain enzymes. Molecular dynamics simulations on structural models of DLAR and PTP99A reveal a conformational rationale for the experimental observations. These studies reveal that concerted structural changes mediate inter-domain communication resulting in either inhibitory or activating effects of the membrane distal PTP domain on the catalytic activity of the membrane proximal PTP domain.

Stability of domain structures in multi-domain proteins

Multi-domain proteins have many advantages with respect to stability and folding inside cells. Here we attempt to understand the intricate relationship between the domain-domain interactions and the stability of domains in isolation. We provide quantitative treatment and proof for prevailing intuitive ideas on the strategies employed by nature to stabilize otherwise unstable domains. We find that domains incapable of independent stability are stabilized by favourable interactions with tethered domains in the multi-domain context. Stability of such folds to exist independently is optimized by evolution. Specific residue mutations in the sites equivalent to inter-domain interface enhance the overall solvation, thereby stabilizing these domain folds independently. A few naturally occurring variants at these sites alter communication between domains and affect stability leading to disease manifestation. Our analysis provides safe guidelines for mutagenesis which have attractive applications in obtaining stable fragments and domain constructs essential for structural studies by crystallography and NMR.

Truthful multi-armed bandit mechanisms for multi-slot sponsored search auctions

In pay-per-click sponsored search auctions which are currently extensively used by search engines, the auction for a keyword involves a certain number of advertisers (say k) competing for available slots (say m) to display their advertisements (ads for short). A sponsored search auction for a keyword is typically conducted for a number of rounds (say T). There are click probabilities mu(ij) associated with each agent slot pair (agent i and slot j). The search engine would like to maximize the social welfare of the advertisers, that is, the sum of values of the advertisers for the keyword. However, the search engine does not know the true values advertisers have for a click to their respective advertisements and also does not know the click probabilities. A key problem for the search engine therefore is to learn these click probabilities during the initial rounds of the auction and also to ensure that the auction mechanism is truthful. Mechanisms for addressing such learning and incentives issues have recently been introduced. These mechanisms, due to their connection to the multi-armed bandit problem, are aptly referred to as multi-armed bandit (MAB) mechanisms. When m = 1, exact characterizations for truthful MAB mechanisms are available in the literature. Recent work has focused on the more realistic but non-trivial general case when m > 1 and a few promising results have started appearing. In this article, we consider this general case when m > 1 and prove several interesting results. Our contributions include: (1) When, mu(ij)s are unconstrained, we prove that any truthful mechanism must satisfy strong pointwise monotonicity and show that the regret will be Theta T7) for such mechanisms. (2) When the clicks on the ads follow a certain click precedence property, we show that weak pointwise monotonicity is necessary for MAB mechanisms to be truthful. (3) If the search engine has a certain coarse pre-estimate of mu(ij) values and wishes to update them during the course of the T rounds, we show that weak pointwise monotonicity and type-I separatedness are necessary while weak pointwise monotonicity and type-II separatedness are sufficient conditions for the MAB mechanisms to be truthful. (4) If the click probabilities are separable into agent-specific and slot-specific terms, we provide a characterization of MAB mechanisms that are truthful in expectation.

Tethering preferences of domain families co-occurring in multi-domain proteins

Genomic data of several organisms have revealed the presence of a vast repertoire of multi-domain proteins. The role played by individual domains in a multi-domain protein has a profound influence on the overall function of the protein. In the present analysis an attempt has been made to better understand the tethering preferences of domain families that occur in multi-domain proteins. The analysis has been carried out on an exhaustive dataset of 2 961 898 sequences of proteins from 930 organisms, where 741 274 proteins are comprised of at least two domain families. For every domain family, the number of other domain families with which it co-occurs within a protein in this dataset has been enumerated and is referred to as the tethering number of the domain family. It was found that, in the general dataset, the AAA ATPase family and the family of Ser/Thr kinases have the highest tethering numbers of 450 and 444 respectively. Further analysis reveals significant correlation between the number of members in a family and its tethering number. Positive correlation was also observed for the extent of a sequence and functional diversity within a family and the tethering numbers of domain families. Domain families that are present ubiquitously in diverse organisms tend to have large tethering numbers, while organism/kingdom-specific families have low tethering numbers. Thus, the analysis uncovers how domain families recombine and evolve to give rise to multi-domain proteins.

The relationship between classification of multi-domain proteins using an alignment-free approach and their functions: a case study with immunoglobulins

Establishing functional relationships between multi-domain protein sequences is a non-trivial task. Traditionally, delineating functional assignment and relationships of proteins requires domain assignments as a prerequisite. This process is sensitive to alignment quality and domain definitions. In multi-domain proteins due to multiple reasons, the quality of alignments is poor. We report the correspondence between the classification of proteins represented as full-length gene products and their functions. Our approach differs fundamentally from traditional methods in not performing the classification at the level of domains. Our method is based on an alignment free local matching scores (LMS) computation at the amino-acid sequence level followed by hierarchical clustering. As there are no gold standards for full-length protein sequence classification, we resorted to Gene Ontology and domain-architecture based similarity measures to assess our classification. The final clusters obtained using LMS show high functional and domain architectural similarities. Comparison of the current method with alignment based approaches at both domain and full-length protein showed superiority of the LMS scores. Using this method we have recreated objective relationships among different protein kinase sub-families and also classified immunoglobulin containing proteins where sub-family definitions do not exist currently. This method can be applied to any set of protein sequences and hence will be instrumental in analysis of large numbers of full-length protein sequences.

CLAP: A web-server for automatic classification of proteins with special reference to multi-domain proteins

Background: The function of a protein can be deciphered with higher accuracy from its structure than from its amino acid sequence. Due to the huge gap in the available protein sequence and structural space, tools that can generate functionally homogeneous clusters using only the sequence information, hold great importance. For this, traditional alignment-based tools work well in most cases and clustering is performed on the basis of sequence similarity. But, in the case of multi-domain proteins, the alignment quality might be poor due to varied lengths of the proteins, domain shuffling or circular permutations. Multi-domain proteins are ubiquitous in nature, hence alignment-free tools, which overcome the shortcomings of alignment-based protein comparison methods, are required. Further, existing tools classify proteins using only domain-level information and hence miss out on the information encoded in the tethered regions or accessory domains. Our method, on the other hand, takes into account the full-length sequence of a protein, consolidating the complete sequence information to understand a given protein better. Results: Our web-server, CLAP (Classification of Proteins), is one such alignment-free software for automatic classification of protein sequences. It utilizes a pattern-matching algorithm that assigns local matching scores (LMS) to residues that are a part of the matched patterns between two sequences being compared. CLAP works on full-length sequences and does not require prior domain definitions. Pilot studies undertaken previously on protein kinases and immunoglobulins have shown that CLAP yields clusters, which have high functional and domain architectural similarity. Moreover, parsing at a statistically determined cut-off resulted in clusters that corroborated with the sub-family level classification of that particular domain family. Conclusions: CLAP is a useful protein-clustering tool, independent of domain assignment, domain order, sequence length and domain diversity. Our method can be used for any set of protein sequences, yielding functionally relevant clusters with high domain architectural homogeneity. The CLAP web server is freely available for academic use at http://nslab.mbu.iisc.ernet.in/clap/.

A queuing approach for inventory planning with batch ordering in multi-echelon supply chains

This paper presents stylized models for conducting performance analysis of the manufacturing supply chain network (SCN) in a stochastic setting for batch ordering. We use queueing models to capture the behavior of SCN. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies . In the first case, we model one manufacturer with one warehouse, which supplies to various retailers. We determine the optimal inventory level at the warehouse that minimizes total expected cost of carrying inventory, back order cost associated with serving orders in the backlog queue, and ordering cost. In the second model we impose service level constraint in terms of fill rate (probability an order is filled from stock at warehouse), assuming that customers do not balk from the system. We present several numerical examples to illustrate the model and to illustrate its various features. In the third case, we extend the model to a three-echelon inventory model which explicitly considers the logistics process.

Design of multi-frequency microstrip antennas using multiple rings

An electromagnetically coupled feed arrangement is proposed for simultaneously exciting multiple concentric ring antennas for multi-frequency operation. This has a multi-layer dielectric configuration in which a transmission line is embedded below the layer containing radiating rings. Energy coupled to these rings from the line beneath is optimised by suitably adjusting the location and dimensions of stubs on the line. It has been shown that the resonant frequencies of these rings do not change as several of these single-frequency antennas are combined to form a multi-resonant antenna. Furthermore, all radiators are forced to operate at their primary mode and some harmonics of the lower resonant frequency rings appearing within the frequency range are suppressed when combined. The experimental prototype antenna has three resonant frequencies at which it has good radiation characteristics.

Flow behavior of long chain plasticizing liquids: Segment size calculations in carboxylate esters

This is the first comprehensive report on the calculation of segment size, which signifies the asic unit of flow in long chain plasticizing liquids, by a novel multi-pronged approach. Unlike,low molecular weight liquids and high polymer melts these complex long chain liquids encompasses the least understood domain of the liquid state. In the present work the flow behaviour of carboxylate ester (300-900 Da) has been explained through segmental motion taking into account the independence of molecular weight region. The segment size have been calculated by various methods based on satistical thermodynamics, molecular dynamics and group additivity nd their merits analysed.