Drug law enforcement : a review of the evaluation literature

This article describes the results of a systematic review of drug law enforcement evaluations. The authors describe the search procedures and document the results in five main categories: international/national interventions (e.g., interdiction and drug seizure), reactive/ directed interventions (e.g., crackdowns, raids, buy-busts, saturation patrol, etc.), proactive/ partnership interventions (e.g., third-party policing, problem-oriented policing, community policing, drug nuisance abatement, etc.), individualized interventions (e.g., arrest referral and diversion), or interventions that used a combination of reactive/directed and proactive/ partnership strategies. Results indicate that proactive interventions involving partnerships between the police and third parties and/or community entities appear to be more effective at reducing both drug and nondrug problems in drug problem places than are reactive/ directed approaches. But the general quality of research in drug law enforcement is poor, the range of interventions that have been evaluated is limited, and more high-quality research is needed across a greater variety of drug interventions.

Street-level drug law enforcement : a meta-analytical review

Our paper presents the results of a meta-analytical review of street level drug law enforcement. We conducted a series of meta-analyses to compare and contrast the effectiveness of four types of drug law enforcement approaches, including community-wide policing, problem-oriented/ partnership approaches that were geographically focused, hotspots policing and standard, unfocused law enforcement efforts. We examined the relative impact of these different crime control tactics on streetlevel drug problems as well as associated problems such as property crime, disorder and violent crime. The results of the meta-analyses, together with examination of forest plots, reveal that problem-oriented policing and geographically-focused interventions involving cooperative partnerships between police and third parties tend to be more effective at controlling drug problems than community-wide policing efforts that are unfocused and spread out across a community. But geographically focused and community-wide drug law enforcement interventions that leverage partnerships are more effective at dealing with drug problems than traditional, law enforcement-only interventions. Our results suggest that the key to successful drug law enforcement lies in the capacity of the police to forge productive partnerships with third parties rather than simply increasing police presence or intervention (e.g., arrests) at drug hotspots.

Mussel-inspired porous SiO2 scaffolds with improved mineralization and cytocompatibility for drug delivery and bone tissue engineering

Porous SiO2 scaffolds with mesopore structure (named as MS scaffolds) have been proposed as suitable for bone tissue engineering due to their excellent drug-delivery ability; however, the mineralization and cytocompatibility of MS scaffolds are far from optimal for bone tissue engineering, and it is also unclear how the delivery of drugs from MS scaffolds affects osteoblastic cells. The aims of the present study were to improve the mineralization and cytocompatibility of MS scaffolds by coating mussel-inspired polydopamine on the pore walls of scaffolds. The effects of polydopamine modification on MS scaffolds was investigated with respect to apatite mineralization and the attachment, proliferation and differentiation of bone marrow stromal cells (BMSCs), as was the release profile of the drug dexamethasone (DEX). Our results show that polydopamine can readily coat the pore walls of MS scaffolds and that polydopamine-modified MS scaffolds have a significantly improved apatite-mineralization ability as well as better attachment and proliferation of BMSCs in the scaffolds, compared to controls. Polydopamine modification did not alter the release profile of DEX from MS scaffolds but the sustained delivery of DEX significantly improved alkaline phosphatase (ALP) activity of BMSCs in the scaffolds. These results suggest that polydopamine modification is a viable option to enhance the bioactivity of bone tissue engineering scaffolds and, further, that DEX-loaded polydopamine MS scaffolds have potential uses as a release system to enhance the osteogenic properties of bone tissue engineering applications.

A Virtual Evaluation Track for Cross Language Link Discovery

The Wikipedia has become the most popular online source of encyclopedic information. The English Wikipedia collection, as well as some other languages collections, is extensively linked. However, as a multilingual collection the Wikipedia is only very weakly linked. There are few cross-language links or cross-dialect links (see, for example, Chinese dialects). In order to link the multilingual-Wikipedia as a single collection, automated cross language link discovery systems are needed – systems that identify anchor-texts in one language and targets in another. The evaluation of Link Discovery approaches within the English version of the Wikipedia has been examined in the INEX Link the-Wiki track since 2007, whilst both CLEF and NTCIR emphasized the investigation and the evaluation of cross-language information retrieval. In this position paper we propose a new virtual evaluation track: Cross Language Link Discovery (CLLD). The track will initially examine cross language linking of Wikipedia articles. This virtual track will not be tied to any one forum; instead we hope it can be connected to each of (at least): CLEF, NTCIR, and INEX as it will cover ground currently studied by each. The aim is to establish a virtual evaluation environment supporting continuous assessment and evaluation, and a forum for the exchange of research ideas. It will be free from the difficulties of scheduling and synchronizing groups of collaborating researchers and alleviate the necessity to travel across the globe in order to share knowledge. We aim to electronically publish peer-reviewed publications arising from CLLD in a similar fashion: online, with open access, and without fixed submission deadlines.

Evaluation framework for focused link discovery

Information has no value unless it is accessible. Information must be connected together so a knowledge network can then be built. Such a knowledge base is a key resource for Internet users to interlink information from documents. Information retrieval, a key technology for knowledge management, guarantees access to large corpora of unstructured text. Collaborative knowledge management systems such as Wikipedia are becoming more popular than ever; however, their link creation function is not optimized for discovering possible links in the collection and the quality of automatically generated links has never been quantified. This research begins with an evaluation forum which is intended to cope with the experiments of focused link discovery in a collaborative way as well as with the investigation of the link discovery application. The research focus was on the evaluation strategy: the evaluation framework proposal, including rules, formats, pooling, validation, assessment and evaluation has proved to be efficient, reusable for further extension and efficient for conducting evaluation. The collection-split approach is used to re-construct the Wikipedia collection into a split collection comprising single passage files. This split collection is proved to be feasible for improving relevant passages discovery and is devoted to being a corpus for focused link discovery. Following these experiments, a mobile client-side prototype built on iPhone is developed to resolve the mobile Search issue by using focused link discovery technology. According to the interview survey, the proposed mobile interactive UI does improve the experience of mobile information seeking. Based on this evaluation framework, a novel cross-language link discovery proposal using multiple text collections is developed. A dynamic evaluation approach is proposed to enhance both the collaborative effort and the interacting experience between submission and evaluation. A realistic evaluation scheme has been implemented at NTCIR for cross-language link discovery tasks.

An ontology-based mining approach for user search intent discovery

Discovering proper search intents is a vi- tal process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this pa- per, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate con- cept levels for matching user search intents. An iter- ative mining algorithm is designed for evaluating po- tential intents level by level until meeting the best re- sult. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.

Relevance feature discovery for text analysis

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

Mobile applications of focused link discovery

Interaction with a mobile device remains difficult due to inherent physical limitations. This dif-ficulty is particularly evident for search, which re-quires typing. We extend the One-Search-Only search paradigm by adding a novel link-browsing scheme built on top of automatic link discovery. A prototype was built for iPhone and tested with 12 subjects. A post-use interview survey suggests that the extended paradigm improves the mobile information seeking experience.

Core-shell microspheres with surface grafted poly(vinyl alcohol) as drug carriers for the treatment of hepatocellular carcinoma

Core(polyvinyl neodecanoate-ethylene glycol dimethacrylate)-shell(polyvinyl alcohol) (core (P(VND-EGDMA))-shell(PVA)) microspheres were developed by seeded polymerization with the use of conventional free radical and RAFT/MADIX mediated polymerization. Poly(vinyl pivalate) PVPi was grafted onto microspheres prepared via suspension polymerization of vinylneodecanoate and ethylene glycol dimethacrylate. The amount of grafted polymer was found to be independent from the technique used with conventional free radical polymerization and MADIX polymerization resulting into similar shell thicknesses. Both systems—grafting via free radical polymerization or the MADIX process—were found to follow slightly different kinetics. While the free radical polymerization resulted in a weight gain linear with the monomer consumption in solution the growth in the MADIX controlled system experienced a delay. The core-shell microspheres were obtained by hydrolysis of the poly(vinyl pivalate) surface grafted brushes to form poly(vinyl alcohol). During hydrolysis the microspheres lost a significant amount of weight, consistent with the hydrolysis of 40–70% of all VPi units. Drug loading was found to be independent of the shell layer thickness, suggesting that the drug loading is governed by the amount of bulk material. The shell layer does not appear to represent an obstacle to the drug ingress. Cell testing using colorectal cancer cell lines HT 29 confirm the biocompatibility of the empty microspheres whereas the clofazimine loaded particles lead to 50% cell death, confirming the release of the drug.

Non-invasive, quantitative analysis of drug mixtures in containers using spatially offset Raman spectroscopy (SORS) and multivariate statistical analysis

In this paper, spatially offset Raman spectroscopy (SORS) is demonstrated for non-invasively investigating the composition of drug mixtures inside an opaque plastic container. The mixtures consisted of three components including a target drug (acetaminophen or phenylephrine hydrochloride) and two diluents (glucose and caffeine). The target drug concentrations ranged from 5% to 100%. After conducting SORS analysis to ascertain the Raman spectra of the concealed mixtures, principal component analysis (PCA) was performed on the SORS spectra to reveal trends within the data. Partial least squares (PLS) regression was used to construct models that predicted the concentration of each target drug, in the presence of the other two diluents. The PLS models were able to predict the concentration of acetaminophen in the validation samples with a root-mean-square error of prediction (RMSEP) of 3.8% and the concentration of phenylephrine hydrochloride with an RMSEP of 4.6%. This work demonstrates the potential of SORS, used in conjunction with multivariate statistical techniques, to perform non-invasive, quantitative analysis on mixtures inside opaque containers. This has applications for pharmaceutical analysis, such as monitoring the degradation of pharmaceutical products on the shelf, in forensic investigations of counterfeit drugs, and for the analysis of illicit drug mixtures which may contain multiple components.