With the ever increasing size of the web, relevant information extraction on the Internet with a query formed by a few keywords has become a big challenge. Query Expansion (QE) plays a crucial role in improving searches on the Internet. Here, the user's initial query is reformulated by adding additional meaningful terms with similar significance. QE -as part of information retrieval (IR) -has long attracted researchers' attention. It has become very influential in the field of personalized social document, question answering, cross-language IR, information filtering and multimedia IR. Research in QE has gained further prominence because of IR dedicated conferences such as TREC (Text Information Retrieval Conference) and CLEF (Conference and Labs of the Evaluation Forum). This paper surveys QE techniques in IR from 1960 to 2017 with respect to core techniques, data sources used, weighting and ranking methodologies, user participation and applications -bringing out similarities and differences.There is a huge amount of data available on the Internet, and it is growing exponentially. This unconstrained information-growth has not been accompanied by a corresponding technical advancement in the approaches for extracting relevant information [191]. Often, a web-search does not yield relevant results. There are multiple reasons for this. First, the keywords submitted by the user can be related to multiple topics; as a result, the search results are not focused on the topic of interest. Second, the query can be too short to capture appropriately what the user is looking for. This can happen just as a matter of habit (e.g., the average size of a web search is 2.4 words [257,255]). Third, the user is often not sure about what he is looking for until he sees the results. Even if the user knows what he is searching for, he does not know how to formulate an appropriate query (navigational queries are exceptions to this [51]). QE plays an important part in fetching relevant results in the above cases. Most web queries fall under the following three fundamental categories [51, 139] :-Informational Queries: Queries that cover a broad topic (e.g., India or journals) for which there may be thousands of relevant results. -Navigational Queries: Queries that are looking for specific website or URL (e.g., ISRO).-Transactional Queries: Queries that demonstrate the user's intent to execute a specific activity (e.g., downloading papers or buying books).2 Hiteshwar Kumar Azad, Akshay DeepakCurrently, user-queries are mostly processed using indexes and ontologies, which work on exact matches and are hidden from the users. This leads to the problem of term mismatch: user queries and search index are not based on the same set of terms. This is also known as the vocabulary problem [99]; it results from a combination of synonymy and polysemy. Synonymy refers to multiple words with common meaning, e.g., "buy" and "purchase". Polysemy refers to words with multiple meanings, e.g., "mouse" (a computer device or an animal). Synonymous and polysemou...

Chronic pulmonary diseases encompass different persistent and lethal diseases, including chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), cystic fibrosis (CF), asthma, and lung cancers that affect millions of people globally. Traditional pharmacotherapeutic treatment approaches (i.e., bronchodilators, corticosteroids, chemotherapeutics, peptide-based agents, etc.) are not satisfactory to cure or impede diseases. With the advent of nanotechnology, drug delivery to an intended site is still difficult, but the nanoparticle’s physicochemical properties can accomplish targeted therapeutic delivery. Based on their surface, size, density, and physical-chemical properties, nanoparticles have demonstrated enhanced pharmacokinetics of actives, achieving the spotlight in the drug delivery research field. In this review, the authors have highlighted different nanoparticle-based therapeutic delivery approaches to treat chronic pulmonary diseases along with the preparation techniques. The authors have remarked the nanosuspension delivery via nebulization and dry powder carrier is further effective in the lung delivery system since the particles released from these systems are innumerable to composite nanoparticles. The authors have also outlined the inhaled particle’s toxicity, patented nanoparticle-based pulmonary formulations, and commercial pulmonary drug delivery devices (PDD) in other sections. Recently advanced formulations employing nanoparticles as therapeutic carriers for the efficient treatment of chronic pulmonary diseases are also canvassed.

Chitosan, a naturally abundant cationic polymer, is chemically composed of cellulose-based biopolymers derived by deacetylating chitin. It offers several attractive characteristics such as renewability, hydrophilicity, biodegradability, biocompatibility, non-toxicity, and a broad spectrum of antimicrobial activity towards gram-positive and gram-negative bacteria as well as fungi, etc., because of which it is receiving immense attention as a biopolymer for a plethora of applications including drug delivery, protective coating materials, food packaging films, wastewater treatment, and so on. Additionally, its structure carries reactive functional groups that enable several reactions and electrochemical interactions at the biomolecular level and improves the chitosan’s physicochemical properties and functionality. This review article highlights the extensive research about the properties, extraction techniques, and recent developments of chitosan-based composites for drug, gene, protein, and vaccine delivery applications. Its versatile applications in tissue engineering and wound healing are also discussed. Finally, the challenges and future perspectives for chitosan in biomedical applications are elucidated.

A prominent research topic in contemporary advanced functional materials science is the production of smart materials based on polymers that may independently adjust their physical and/or chemical characteristics when subjected to external stimuli. Smart hydrogels based on poly(N-isopropylacrylamide) (PNIPAM) demonstrate distinct thermoresponsive features close to a lower critical solution temperature (LCST) that enhance their capability in various biomedical applications such as drug delivery, tissue engineering, and wound dressings. Nevertheless, they have intrinsic shortcomings such as poor mechanical properties, limited loading capacity of actives, and poor biodegradability. Formulation of PNIPAM with diverse functional constituents to develop hydrogel composites is an efficient scheme to overcome these defects, which can significantly help for practicable application. This review reports on the latest developments in functional PNIPAM-based smart hydrogels for various biomedical applications. The first section describes the properties of PNIPAM-based hydrogels, followed by potential applications in diverse fields. Ultimately, this review summarizes the challenges and opportunities in this emerging area of research and development concerning this fascinating polymer-based system deep-rooted in chemistry and material science.

Query expansion (QE) is a well-known technique used to enhance the effectiveness of information retrieval. QE reformulates the initial query by adding similar terms that help in retrieving more relevant results. Several approaches have been proposed in literature producing quite favorable results, but they are not evenly favorable for all types of queries (individual and phrase queries). One of the main reasons for this is the use of the same kind of data sources and weighting scheme while expanding both the individual and the phrase query terms. As a result, the holistic relationship among the query terms is not well captured or scored. To address this issue, we have presented a new approach for QE using Wikipedia and WordNet as data sources. Specifically, Wikipedia gives rich expansion terms for phrase terms, while WordNet does the same for individual terms.We have also proposed novel weighting schemes for expansion terms: in-link score (for terms extracted from Wikipedia) and a tf-idf based scheme (for terms extracted from WordNet). In the proposed Wikipedia-WordNet-based QE technique (WWQE), we weigh the expansion terms twice: first, they are scored by the weighting scheme individually, and then, the weighting scheme scores the selected expansion terms concerning the entire query using correlation score. The proposed approach gains improvements of 24% on the MAP score and 48% on the GMAP score over unexpanded queries on the FIRE dataset. Experimental results achieve a significant improvement over individual expansion and other related state-of-the-art approaches. We also analyzed the effect on retrieval effectiveness of the proposed technique by varying the number of expansion terms. makes information processing a big challenge and creates a vocabulary gap between user queries and indexed documents. It is common for a user's query Q and its set of relevant documents D to use different vocabulary and language styles while referring to the same concept. For example, terms 'buy' and 'purchase' have the same meaning; however, only one of these can be present in the documents' index while the other one can be the user's query term. This makes it difficult to retrieve the information actually wanted by the user [21,28]. An effective strategy to fill this gap is to use the Query Expansion (QE) technique, which enhances the retrieval effectiveness by adding expansion terms to the initial query. Selection of the expansion terms plays a crucial role in QE because only a small subset of the expanded terms are actually relevant to the query [26].In this sense, the approach for selection of expansion terms is equally important in comparison to what we do further with the expanded terms in order to retrieve the desired information. QE has a long research history in information retrieval (IR) [31,39]. It has the potential to enhance IR's effectiveness by adding relevant terms that can help to discriminate the relevant documents from irrelevant ones. The source of expansion terms plays a significant role in QE. A variety of ...