A Resource-Constrained Optimal Control Model for Crackdown on Illicit Drug Markets

In this paper we present a budget-constrained optimal control model aimed at finding the optimal enforcement profile for a street-level, illicit drug crackdown operation. The objective is defined as minimizing the number of dealers dealing at the end of the crackdown operation, using this as a surrogate measure of residual criminal activity. Analytical results show that optimal enforcement policy will invariably use the budget resources completely. Numerical analysis using realistic estimates of parameters shows that crackdowns normally lead to significant results within a matter of a week, and if they do not, it is likely that they will be offering very limited success even if pursued for a much longer duration. We also show that a ramp-up enforcement policy will be most effective in collapsing a drug market if the drug dealers are risk-seeking, and the policy of using maximum enforcement as early as possible is usually optimal in the case when the dealers are risk averse or risk neutral. The work then goes on to argue that the underlying model has some general characteristics that are both reasonable and intuitive, allowing possible applications in focussed, local enforcement operations on other similar illegal activities.crackdown enforcement;illicit drug markets;optimal control

On k-Column Sparse Packing Programs

We consider the class of packing integer programs (PIPs) that are column sparse, i.e. there is a specified upper bound k on the number of constraints that each variable appears in. We give an (ek+o(k))-approximation algorithm for k-column sparse PIPs, improving on recent results of $k^2\cdot 2^k$ and $O(k^2)$. We also show that the integrality gap of our linear programming relaxation is at least 2k-1; it is known that k-column sparse PIPs are $\Omega(k/ \log k)$-hard to approximate. We also extend our result (at the loss of a small constant factor) to the more general case of maximizing a submodular objective over k-column sparse packing constraints.Comment: 19 pages, v3: additional detail

Sustaining Sustainability in Marine Terminals: A Strategic Framework

Sustainability initiatives in maritime industry, despite their global need and relevance, are often riddled with strategic and implementation issues. Here we examine “green” initiatives of top-five global marine terminal operators. We classify their initiatives as technology-centric, process-centric and relationship-centric, and develop a core-competency-driven framework for these initiatives. Our findings indicate that technological initiatives are easy to adopt and yield quicker impact in reducing emissions and increasing ROI. On the other hand, process-centric and relationship-centric initiatives are more difficult to deploy, take longer to yield benefits, but are difficult to imitate. We argue that terminal operators should recognize the value of long-term initiatives that are difficult to replicate, to build competency

Improved Bounds in Stochastic Matching and Optimization

We consider two fundamental problems in stochastic optimization: approximation algorithms for stochastic matching, and sampling bounds in the black-box model. For the former, we improve the current-best bound of 3.709 due to Adamczyk et al. (2015), to 3.224; we also present improvements on Bansal et al. (2012) for hypergraph matching and for relaxed versions of the problem. In the context of stochastic optimization, we improve upon the sampling bounds of Charikar et al. (2005)

Green Symbiotic Cloud Communications: Virtualized Transport Layer and Cognitive Decision Function

The evolution of the concept of cloud communications has posed a growing emphasis on virtual and abstract environments for the flow of information, structuring it in similitude to a natural cloud. The Green Symbiotic Cloud Communications (GSCC) paradigm created on this concept facilitates the use of multiple communication mediums concomitantly creating a first of its kind communication cloud. This paper specifically corroborates a virtualized transport layer and network ports and an abstracted Internet protocol scheme in defining the GSCC architecture. We further address the issue of formulating a cognitive decision function based on utility theory, which allows users with GSCC enabled devices to intelligently distribute its bandwidth requirement amongst the available communication mediums. Considering the multiple criteria associated with different networks we formulate an optimization problem to find the solution for this resource allocation problem for single user. We further address the multi-user scenario and formulate and solve the multi-objective optimization problem using goal attainment technique. Results in single and multiple user scenarios, demonstrate that by utilizing multiple mediums as per GSCC paradigm coupled with our proposed decision function improves the functionality of the communication cloud. The proposed architecture is dynamic and evolving, embedding greenness by efficiently utilizing the available resources as and when required. The multiple virtual links equate a linearly increasing relationship with the throughput achieved. Experimental results for both real time and static data through the proposed schematic are documented. The augmented paradigm enhances the quality of service, linearly increases throughput and increases the overall security in communications

Susceptibility of Multi-Drug-Resistant Organisms (MDROs), Isolated from Cases of Urinary Tract Infection to Fosfomycin (The New Antibiotic) vis-a-vis Other Antimicrobial Agents

Introduction: Urinary tract infection (UTI) is one of the commonest infections encountered in the hospital. Most of the hospital UTIs are caused by MDROs. There is scarcity of available drugs to treat MDR infections. In this scenario, reevaluation of the old antimicrobial agents is being done. Fosfomycin is one such old molecule. The studies suggest that Fosfomycin may provide a useful option for the treatment of patients with the MDR/XDR difficult-to-treat infections.Materials and Methods: Urine samples (including catheter samples) were collected in sterile containers; cultured on CHROME agar, using calibrated loop; colony count was done in positive cultures; identification and antimicrobial susceptibility of the organism was done by VITEK2 compact system. Susceptibility pattern of antimicrobial agents used for treatment of UTI including Fosfomycin was analyzed.Results: Of the 502 urinary MDRO isolates, 74.9% were ESBLs and 29.49% were CROs. MDRO susceptibility was 88% to Fosfomycin, 70.52% to Ertapenem, 53.98% to Nitrofurantoin, 37.05% to Trimethoprim-Sulfamethoxazole, 22.31% to Norfloxacin, 20.91% to Ciprofloxacin, and 10.96% to Ampicillin respectively.Discussion: Gupta et al.10 reported 52.6% E. coli urinary isolates to be ESBLs and all were susceptible to Fosfomycin. In the present study, 76.8% Escherichia coli isolates were ESBLs and 98.5% only were susceptible to Fosfomycin